The developing health IT infrastructure, with its host of new applications, is ushering in the most intensely competitive era in the healthcare industry's history, by sharply accelerating the industry's clockspeed. Charles H. Fine of MIT's Sloan School of Management used the term to describe the pace of business evolution within industries. He found that industries with faster clockspeeds, such as computers and entertainment, had higher levels of market experimentation, more competition, and increasingly frequent waves of innovation. This will be challenging for the healthcare industry, and for insurers in particular, who are used to a much slower pace of change. To succeed, they'll need to look outside their sector for effective business models, and build new capabilities that support rapid product development, a consumer product mind-set, and expansion into adjacent markets.
The leading healthcare insurers will find that IT modernization will either expand their role as information aggregators — making them the primary engine for higher-quality, more cost-effective care — or enable new competitors to supplant them. Historically, insurers have not needed a strategy for responding in a fast-paced environment. Repeated waves of consolidation (which oriented insurers toward scale rather than innovation), complex regulatory requirements that varied by market, the competing incentives and targets of multiple stakeholders, and the slow adoption of information standards have created speed bumps that impeded innovation. The ambiguity in healthcare reform's implementation may seem yet another reason for insurers to assume that the historical pace of the industry will continue.
However, as health IT becomes more connected, precise, and prevalent, many companies will have to race to realize its potential. Insurers' products have already begun to be seen as commodities in the more consumer-driven post-reform marketplace, where health-insurance exchanges, bundled offerings, greater transparency, easy comparison of features, and lower switching costs will soon be commonplace. Add in the conditions typical in fast-clockspeed industries, and incumbents and even first movers could suffer competitive erosion, especially when new players and fast followers with deeper capabilities and more flexibility enter their markets.
For instance, greater granularity in claims data and significant investments in electronic health records (EHRs) will provide the raw material for improved analytics and will presumably lead to better medical outcomes. And these data sources are only part of the picture: More sophisticated medical devices and the ubiquity of social media and smartphones will enable faster, more comprehensive data collection and more effective interventions. Existing competitors and new entrants will create real-time decision support tools to help providers and patients better manage care. Microsoft, for example, is exploring virtual care delivery, and medical device manufacturer Medtronic has developed Wi-Fi-enabled cardiac devices that allow doctors to remotely monitor and assist patients. Insurers, who currently control claims data and the valuable insights contained therein, will face a crucial point of reinvention as these advances and the companies that field them engage consumers, influence medical utilization, and seek a proportional share of the healthcare dollar.
Health insurers looking for guidance on how to compete in a fast-paced environment won't find many examples within their own industry. But they can look to industries where the clockspeed has long been fast and furious, such as online retailing. One excellent model for them to study is Amazon.com Inc.
Amazon has built a full-service, seamless vertical approach — including order fulfillment, recommendations, and customer service — around its core retail business over the past decade. Simultaneously, it has staked out beachheads in key horizontal platforms, becoming a partner to other vendors through Amazon Marketplace, e-commerce hosting, and Web services (home of its much-ballyhooed cloud computing business). These businesses generate additional revenues that are funneled back into R&D for Amazon's core business.
This kind of approach could translate very well for healthcare insurers today, but to make it work, they will have to establish the proper balance between vertical and horizontal integration, and between control and speed. They will need a vertically integrated approach that keeps critical components under proprietary control to create differentiation. At the same time, they will need strong horizontal capabilities that can be deployed in fast and flexible ways to help master accelerating product cycles.
For example, insurers that decide to help physicians use EHR data will need swift application-development capabilities. That robust expertise could be deployed in multiple vehicles (such as cloud-based computing to the physician's desktop or to handheld devices) and for multiple purposes (for example, health analysis or prevention campaigns). New businesses like these could enable insurers to strengthen physician relationships and create future revenue streams. Amazon's example also suggests that the most successful insurers will be those that continually engage their customers through product design and nimbly capitalize on emerging capabilities.
To compete effectively in a faster environment, insurers will need to develop capabilities that enable them to achieve the following outcomes.
1.	Business systems designed for rapid product development. Insurers often serve several customer segments in different regions and provider networks. This emphasis on breadth has contributed to an abundance of uncoordinated technology strategies and a scattershot approach to value chain design. Furthermore, speed-to-market has often been achieved via custom development rather than via an architecture designed for rapid product cycles. Over the long term, this hampers insurers' efforts to be truly nimble.
Insurers need a coherent infrastructure that can deliver over successive product cycles. This suggests that they should adopt a business architecture that can be broken into simpler subsystems, that uses modular and off-the-shelf components, that assumes technological obsolescence, and that preserves future flexibility.
2.	A consumer product design mind-set. Insurers have traditionally maintained market share by locking in networks of customers and providers, and in many markets by relying on strong brand names. But they may be ill-equipped to compete on product features in an environment with low switching costs and intense competition.
To succeed in this emerging environment, successful health plans will develop robust product ideation and iteration capabilities. They will use these capabilities to better align demand with care utilization, creating new products (such as one-price care bundles) and designing incentives that shift care to less-expensive channels (such as non-acute care facilities and preventive health programs). In addition, to capture the expected growth in individual and small group markets, insurers will need to sell directly to these groups, manage their experience, and encourage healthy behaviors. This will require new retail capabilities in customer engagement, including the support and provision of enhanced interventions and self-care, as well as new service channels.
3.	Expertise in entering adjacent markets. Although some insurers may decide to stick to their traditional strengths in core administrative services to insulate them from the faster pace, they are likely to discover that competing on transactions alone has drawbacks. The large-scale system migrations required to significantly improve transaction speeds are both costly and risky. Only a few insurers will achieve the necessary economies of scale, and they will most likely become outsourcing partners for the rest of the industry.
Instead, most insurers should be looking for areas where there is headroom for growth, such as adjacent markets for care delivery. Because clinical care delivery accounts for almost 80 cents of every healthcare dollar spent in the U.S., products and services aimed at delivering more effective outcomes at lower costs, solving ambiguous clinical problems, and promoting virtual care delivery are rich areas of new opportunity for health plans. Successful plans will consolidate a broad range of platforms, including smartphones, cloud-based computing, and videoconferencing, to launch care products that deliver greater value. They will also master the art of relationship building and creative collaboration to overcome adversarial provider relationships and consumer mistrust.
Insurers will succeed either by meeting multiple needs within their chosen markets or by realizing the full breadth of capabilities in their horizontal niches; over time, they may do both. In any of these scenarios, however, health insurers will have to design value chains that can deliver successive waves of innovation. They must be prepared to quickly generate and launch new products and services, learn, adapt, and repeat the process, if they hope to profitably retain fickle customers who traditionally have not taken a great deal of responsibility for or control over their own care. Clearly, existing players won't be able to depend on their hard-won brand equity. In other industries, established brand names have meant little when the pace of innovation has accelerated (think of Encyclopedia Britannica, displaced by Wikipedia's open source model). As Charles Fine's work on clockspeed ultimately concluded, the only enduring competitive advantage is the ability to continuously assess and build value chains that exploit current opportunities and anticipate future ones.
Carl Dumont is a partner in Booz & Company's global healthcare practice based in New York.
Ashish Kaura is a partner in Booz & Company's global healthcare practice based in Chicago.
Sundar Subramanian is a principal in Booz & Company's global healthcare and operations practices based in New York.


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Lifestyle / Entertainment
Thomas the Tank Engine to get more female and multicultural friends
01/09/2018, 12:02 am Updated: 01/09/2018, 9:24 am
Thomas and Friends is to introduce gender-balanced and multicultural characters (Thomas And Friends)
Children's programme Thomas And Friends is to introduce an "inclusive" gender-balanced, multicultural set of characters as part of a revamp.
The new series of the animated show about Thomas the Tank Engine and his Steam Team will see the beloved locomotive leave his home in Sodor to travel the world for the first time.
Now called Thomas And Friends: Big World! Big Adventures!, the new series also marks the first collaboration between a children's TV programme and the United Nations to promote the Sustainable Development Goals.
New Thomas And Friends character Noor Jehan (Thomas And Friends)
The changes to Thomas And Friends, the biggest relaunch the brand has had in its 73-year history with the aim of appealing to a wider global audience, were unveiled at a premiere at Bafta's headquarters in London.
There will also be a new theme tune for the show, a faster-paced format, increased humour and music and fantasy elements and dream sequences.
For the first time in the series' history, Thomas will discover new countries and cultures by travelling to China, India and Australia.
YongBao is joining the train ranks (Mattel Inc/Mark Collins PR/PA)
The Steam Team, the core group of trains on the fictional island of Sodor, will now comprise three male and three female characters.
Long-running favourites Percy, Gordon, James and Emily will be joined by additions Nia and Rebecca, along with Thomas.
The changes were made to represent the female viewership of the series, which is thought to be more than 40%, and send a strong message of gender equality to the young audience.
In addition to these, the series will feature new characters from around the world, including Ashima from India, Yong Bao from China and Shane from Australia.
Shane is an Australian train (Mattel Inc/Mark Collins PR/PA)
New female characters, described by show bosses as "strong girl characters", include Isla, an Australian flying doctor plane, Noor Jehan, a royal express engine from India, Hong-Mei, a number one blue tank engine from China, and female railway controller Charubala, from India.
Another first for the show will see Thomas talk directly to the audience to narrate it himself.
The programme's redevelopment included a collaboration with the UN Department of Public Information's Creative Community Outreach Initiative to develop content inspired by the Sustainable Development Goals appropriate for a pre-school audience while in keeping with the Thomas And Friends brand.
Ian McCue, senior producer at Thomas And Friends, said: "The show has undergone an evolution to remain relevant for the next generation of parents and children by opening up the world of Thomas And Friends so children can discover the world around them while being entertained.
Isla, a Flying Doctors' plane will be one of the new 'strong girl' characters (Mattel Inc/Mark Collins PR/PA)
"The changes and new additions of characters and geographies will make the show more entertaining, inclusive and global – whilst ensuring all the favourite characters and storylines that fans around the world love remain at the heart of the action."
Thomas the Tank Engine was created more than 70 years ago by Reverend Wilbert Awdry as part of his Railway Series of books, which have become a global brand including TV programmes, films, toys and live attractions.
Awdry's granddaughter, Claire Chambers, welcomed the changes to the franchise, saying she thinks he would be "very happy" with them.
"If the gender-balanced Steam Team encourages more girls to maintain an interest then that can only be a good thing," she said.
Thomas And Friends will air daily from September 3 at 7am on Channel 5's Milkshake.

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Updated Apr 25, 2018 - Technology
Meet the scooter winning the "scooter wars"
Kia Kokalitcheva
The Xiaomi Mi scooter. Photo: Xiaomi.
The "scooter wars" are raging in San Francisco (and other cities), but one scooter is emerging victorious: the Xiaomi Mi electric scooter, used by several of the startups.
Why it matters: For now, these scooter companies have found a reliable vehicle in the Xiaomi product — but as this war heats up, they may find that designing and manufacturing their own scooters will help differentiate them.
Though it sports the Xiaomi brand, the Mi electric scooter is actually designed by Ninebot, which was founded in 2012 in Beijing by Wang Ye and Lufeng Gao.
The Segway connection: In 2015, the same year Ninebot raised $80 million from investors like Sequoia China and Xiaomi, among others, it also merged with Segway—yes, that Segway company. Which means Segway just might become part of the future of transportation after all.
The prior year, Ninebot was one of the companies Segway sued for patent infringement. Since then, the two companies have kept their individual brands while also sharing resources. Ninebot has also worked closely with Xiaomi on certain projects, including the Mi scooter.
Ye was inspired by the popularity of electric scooters he observed in Southern Europe in 2011, according to a Xiaomi blog post.
The Xiaomi Mi scooter was created for personal use, but it's quickly become the model of choice for a number of electric scooter-sharing startups.
The list of companies using the Mi includes Spin, Blue Ducks and Bird. (Although Bird won't confirm its use of the Xiaomi scooter, sources outside the company have identified the vehicle.) All these companies have customized their scooters, adding GPS-enabled tracking devices and integrating their own mobile apps, among other tweaks. LimeBike has designed its own scooter, while Waybots uses a scooter by Minimotors.
"The fact that scooter-sharing companies consider it ideal for their use case and have purchased it for that purpose is testament to the quality of Mi Electric Scooter," a Xiaomi spokesperson told Axios.
"We wanted to make sure we had the best possible riding machine," Spin co-founder and president Euwyn Poon said in a statement to Axios. "Xiaomi is one of the best manufacturers in the world and they've spent over a decade developing electric mobility devices, so we knew they'd be a good partner for us."
The scooter was first unveiled in late 2016, and the company has released at least one other version in addition to the classic Mi model.
The Mi weighs 27 lbs., can go about 18.6 miles on a single battery charge, and supports up to 220 lbs. payload. It can also be tracked via Bluetooth using Xiaomi's Mi app.
In the U.S., Amazon is the official seller of the Xiaomi Mi scooter, and it retails for $499.
Bottom line: Some of these startups are considering designing and manufacturing their own hardware, but for the time being, Xiaomi's Mi scooter is helping them get in the game fast.


text:
Home > Legislation > 109th Congress > S.Con.Res.36
S.Con.Res.36 - Reinforce the Nuclear Non-Proliferation Treaty Act of 2005109th Congress (2005-2006)
Sen. Feinstein, Dianne [D-CA] (Introduced 05/23/2005)
Senate - Foreign Relations
Senate - 05/23/2005 Referred to the Committee on Foreign Relations. (All Actions)
Summary: S.Con.Res.36 — 109th Congress (2005-2006)All Information (Except Text)
There is one summary for S.Con.Res.36. Bill summaries are authored by CRS.
Reinforce the Nuclear Nonproliferation Treaty Act of 2005 - Reaffirms congressional support for the objectives of the Nuclear Nonproliferation Treaty (NPT) and expresses support for appropriate measures to strengthen the NPT.
Calls on all parties participating in the Seventh Review Conference on the Treaty on the Nonproliferation of Nuclear Weapons to make good faith efforts to: (1) comply with NPT nonproliferation obligations; (2) establish more effective controls on sensitive technologies that can be used to produce nuclear weapons material; (3) expand the International Atomic Energy Agency's (IAEA) inspection and monitoring ability; (4) demonstrate the international community's opposition to the Iranian nuclear weapons program; (5) support U.S. diplomatic efforts in the context of the six-party talks to dismantle North Korea's nuclear weapons programs; (6) pursue diplomacy to address regional security problems in Northeast Asia, South Asia, and the Middle East, which would facilitate nonproliferation and disarmament efforts in those regions; (7) accelerate programs to safeguard and eliminate nuclear weapons-usable material; (8) halt the use of highly enriched uranium in civilian reactors; (9) strengthen national and international export controls and relevant security measures; (10) agree that no state may withdraw from the NPT and escape responsibility for prior Treaty violations or retain access to controlled materials and equipment acquired for "peaceful" purposes; (11) accelerate efforts to reduce stockpiles of nuclear weapons and weapons-grade fissile material; and (12) strengthen Proliferation Security Initiative support.


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4478 Бланко (4478 Blanco) — астероїд головного поясу, відкритий 23 квітня 1984 року.

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text:
Trump unveils new strategy to prolong military presence in Afghanistan
Tue Aug 22, 2017 1:32AM
US President Donald Trump has unveiled his administration's new strategy in Afghanistan, saying he would prolong the military intervention in the South Asian country, which he once described as a "complete waste."
"My original instinct was to pull out, and historically I like following my instincts, but all of my life I heard that decisions are much different when you sit behind the desk in the Oval Office," Trump said in a nationally televised speech Monday night before a military audience at Fort Myer.
The US president described his decision to continue the US military intervention, albeit with conditions.
"Our commitment is not unlimited, and our support is not a blank check. The American people expect to see real reforms and real results."
Trump, however, did not provide details about an exact number of troops or the exact cost of his decision. The White House has given the Pentagon authority to deploy another 4,000 more troops on top of the 8,400 already in the country.
Trump's willingness to further commit to the war in Afghanistan, rather than withdraw, represents a significant shift in his approach since taking office. As a candidate, Trump denounced the US military intervention there as a "total disaster" which drained resources at a time of more pressing needs at home.
Elsewhere in his remarks, the president said Washington can no longer remain silent towards Pakistan's "safe havens for terrorists."
He was referring to the Taliban and other groups posing a threat to the region and beyond during a prime time address to the nation on Monday, in which he elaborated on a new US strategy towards Afghanistan.
"We can no longer be silent about Pakistan's safe havens for terrorist organizations," Trump declared. "Pakistan has much to gain from partnering with our effort in Afghanistan. It has much to lose by continuing to harbor criminals and terrorists."
The commander in chief tacitly threatened Islamabad to cut the "billions and billions of dollars" the US pays Pakistan in aid.
"We have been paying Pakistan billions and billions of dollars at the same time they are housing the very terrorists that we are fighting," he said. "That will have to change and that will change immediately… It is time for Pakistan to dedicate to civilization and order and peace."
US support no 'blank check'
Trump also indicated that Washington could stop supporting the Afghan government if it does not show "determination" in its efforts.
"America will work with the Afghan government as long as we see determination and progress," Trump said. "However, our commitment is not unlimited, and our support is not a blank check. The American people expect to see real reforms and real results."
Victory in Afghanistan would mean "attacking our enemies," and "obliterating" the Daesh Takfiri group. He also vowed to crush al-Qaeda, prevent the Taliban from taking over the country.
The United States -- under Republican George W. Bush's presidency -- and its allies invaded Afghanistan on October 7, 2001 as part of Washington's so-called war on terror.
Trump who had previously called for withdrawal of American troops from Afghanistan argued that his "original instinct was to pull out," but that he was convinced by his national security team to take on the Taliban militants.


text:
\section{Introduction}
\label{sec:intro}

\IEEEPARstart{M}{etasurfaces}, defined as artificial structures with subwavelength thickness, have enabled the realization of novel compact devices with unprecedented electromagnetic control. Frequency selectivity, absorption, anomalous reflection/transmission, polarization conversion, and focusing are among the many electromagnetic functionalities that can be achieved through the careful design of the metasurfaces \cite{Chen2016, Glybovski2016}. With such unprecedented control of the response to the impinging wave, metasurfaces have led to important breakthroughs in electromagnetic cloaking, imaging, as well as in the creation of ultra-efficient, miniaturized antennas for sensors and implantable communication devices \cite{Chen2011, ChenXZ2012, Li2017b, Vellucci2017, Tasolamprou2017, Tsilipakos2018a}.

A metasurface is generally defined as a planar array of periodic or quasi-periodic subwavelength elements, whose structure and coupling determine the electromagnetic function. As long as the elements remain subwavelength in size, the working principle of metasurfaces can be applied from microwaves to the visible range \cite{Glybovski2016}. Between these two extremes
lies the terahertz (THz) band, for which designs have been reported to manipulate the phase, amplitude or polarization of the waves reflected or transmitted by the metasurface \cite{Qu2015, Zhang2016a, Liu2016a, Qu2017}.

The main issue of conventional metasurfaces are the lack of adaptivity and reconfigurability as, in most designs, the electromagnetic function and its scope are fixed once the unit cell is designed. In order to avoid re-designing and re-fabricating metasurfaces each time a change in frequency or functionality is required, one can introduce tunable or switchable elements in the design of unit cells \cite{Oliveri2015}. The resulting reconfigurable metasurfaces can be globally or locally tunable depending on the specific design, and better yet through appropriate control means, they can become programmable \cite{Liu2018ISCAS, Liu2018}.

Coding metamaterials, sometimes also referred to as \emph{digital} metamaterials, are a particular type of programmable metamaterials that discretize the number of states of a unit cell \cite{liu2017concepts, Liang2015a, DellaGiovampaola2014, Cui2014}. Each state is represented by a number of bits that are used to make the actual metasurface. A desired global response is achieved through a medium profile that is not necessarily periodical. Such structure, when built using locally switchable elements, can be elegantly described as a bit or state matrix and digitally controlled through reconfigurable devices such as Field-Programmable Gate Arrays (FPGAs) \cite{Cui2014}. Several examples implementing polarization control, focusing control, or beam manipulation in the GHz range can be found in the literature \cite{Cui2014, Yang2016, Huang2017}.

Graphene, with its outstanding optoelectrical properties, has been recently introduced as a key enabler of a myriad of applications in countless domains \cite{Novoselov2012, Wu2012, Low2014, Hosseininejad2017}. It is well known that graphene naturally supports Surface Plasmon Polaritons (SPP) in the terahertz band, and therefore, becomes an excellent option for the implementation of terahertz sources \cite{Jornet2014TRANSCEIVER} and antennas \cite{Correas2017}, among others. The plasmonic nature of graphene at terahertz frequencies leads to miniaturized devices \cite{LlatserComparison}, whereas its inherent tunability has been leveraged in frequency-agile or reconfigurable concepts \cite{tamagnone2012reconfigurable,  Hosseininejad2016, Hosseininejad2018EuCAP}. Some of such designs are array-based, and similar to programmable metasurfaces, they achieve reconfigurability by switching the state of its elements, i.e. \emph{tuning them in or out} \cite{Huang2012ARRAY, Xu2014MIMO, Hosseininejad2018WCNC}.

\begin{figure*}[!ht]
\centering
{\includegraphics[width=1\textwidth]{./figures/Figure1.png}
\vspace{-0.3cm}
\caption{Sketch of the programmable graphene-based digital metasurface for THz beam steering and its design flow: from the unit cell to the global controller.\label{fig:summary}}
\vspace{-0.3cm}
\end{figure*}

The above-mentioned properties turn graphene into a unique material for the implementation of terahertz reconfigurable metasurfaces. First explorations in this regard considered graphene reflectarrays and studied their amplitude-phase responses when tuning the chemical potential of the graphene \cite{Carrasco2013a}. By means of local tuning of the graphene elements through electrostatic biasing, the scattering profile of the reflectarray can be modified to achieve beam steering \cite{Orazbayev2017}, focusing \cite{Hosseininejad2019}, diffusive scattering \cite{Rouhi2017a}, cloaking \cite{Biswas2018} or wave vorticity control \cite{Chang2016}. \hl{These functionalities have been achieved in the microwave regime thanks to the use of} phase change materials (PCMs) \cite{Chen2015SR}, semiconductor diodes \cite{Perruisseau2010}, \hl{or microelectromechanical systems (MEMS)} \cite{Ma2014light}. \hl{However, as we approach to terahertz frequencies, diodes and MEMS become lossy and too large to be integrated within individual unit cells. On the other hand, PCMs offer limited reconfigurability as they generally switch among two states only}. \hl{With graphene}, the design can be greatly simplified and the device can be reconfigured much faster.

Although the natural switchability of graphene in the terahertz band matches perfectly with the coding metamaterial paradigm, which has been explored in \cite{Wang2015} for the first time, the lack of literature to present a clear methodology for the unit cell design based on graphene and the coding of the metasurface seems evident. To bridge this gap, this paper presents a comprehensive methodology for the design of programmable metasurfaces from the unit cell to the metasurface controller (Figure \ref{fig:summary}). The proposed methodology is then applied to develop a metasurface for fine-grained beam steering at terahertz frequencies. The metasurface acts as a reflectarray that forms dynamically reconfigurable phase gradients in the X and Y directions, through which the reflected beam can be driven to any desired direction. The unit cells of the reflectarray are based on a graphene-insulator-graphene stack that achieves wide phase tuning via electrostatic biasing of the graphene patches. With two bits per unit cell and the appropriate controller, the proposed metasurface achieves a very wide steering range with low beam width.

The proposed metasurface is particularly suitable for wireless communication applications. In this context, the use of the lower part of the THz spectrum (our design operates at $f=2$ THz) becomes extremely attractive due to the abundance of bandwidth that allows to satisfy the extreme data rate demands of 5G networks and beyond \cite{Akyildiz2014a}. Communication in the THz band, however, requires overcoming high path losses mainly through directive antennas with very narrow beams and through the use of smart programmable reflectors \cite{Akyildiz2018, Akyildiz2016, Tan2018, Liaskos2018a, Hosseininejad2018WCNC}. It is thus fundamental that these devices be capable of steering the THz beam with high precision to track the users and avoid interrupting communication.

In summary, the main contributions of this paper are:
\begin{itemize}
\item The development of a comprehensive methodology for the design of graphene-based programmable terahertz metasurfaces for beam steering, from the unit cell up to the global controller.
\item The use of the proposed methodology to design and evaluate a 2-bit coding metasurface for beam steering. Wide steering range with a sharp reflected beam and low overheads are demonstrated. The chosen frequency of operation is $f=2$ THz, within the range expected for THz wireless communication applications.
\item A scalability analysis illustrating the relation between the different design parameters and performance metrics, and uncovering several co-design opportunities.
\end{itemize}

The rest of this paper is organized as shown schematically in Fig. \ref{fig:summary}. Section \ref{sec:geometry} presents a design space exploration of graphene-based unit cells from the perspectives of size, chemical potential, and number of states. Section \ref{sec:coding} formulates a design flow for beam steering coding metasurfaces, which is then tested by showing the effective steering of the antenna beam in several directions. Section \ref{sec:antenna} discusses and evaluates the implementation of the scheme that actually controls and (re)programs of the metasurface. Finally, Section \ref{sec:disc} outlines the main scalability trends and co-design opportunities of the proposed design. Section \ref{sec:conclusion} concludes the paper.

\begin{figure*}[!ht]
\centering
\subfigure[Full layer unit cell (\textsc{1L}).\label{fig:1G}]{\includegraphics[width=1\columnwidth]{./figures/2a.PNG}}
\subfigure[Single patch unit cell (\textsc{1G}).\label{fig:1G-patch}]{\includegraphics[width=1\columnwidth]{./figures/2b.png}}
\subfigure[Dual patch unit cell (\textsc{2G}).\label{fig:2G-patch}]{\includegraphics[width=1\columnwidth]{./figures/2c.png}}
\vspace{-0.2cm}
\caption{A schematic representation of the graphene unit cells with their respective equivalent circuit models.}
\label{fig:unit cells}
\vspace{-0.3cm}
\end{figure*}

\section{Graphene-based unit cell}
\label{sec:geometry}
The design of any metasurface starts with its most basic building block, namely, the unit cell. For beam manipulation, we need to provide a unit cell with the ability of controlling the phase response over a wide range of values \cite{Qu2017}. Moreover, since the proposed device acts as a reflectarray, the unit cell needs to yield a high reflection amplitude at all times. To enable dynamic reconfigurability, it is necessary that both objectives can be met without physically changing any geometry. In this paper, reconfigurability is achieved at THz frequencies by means of the electrostatic tuning of graphene.

\subsection{Graphene Modeling}
We analyze different unit cells that leverage the tunability of graphene to achieve the desired phase variation with reasonable losses and without the need of changing any geometry. To drive the design and to perform an accurate evaluation of different proposals, we model graphene as an infinitesimally thin sheet with surface impedance $Z = 1/\sigma(\omega)$, where $\sigma(\omega)$ is the frequency-dependent conductivity of graphene. The complex conductivity is given by
\begin{equation}
\sigma\left(\omega\right)=\frac{2e^{2}}{\pi\hbar}\frac{k_{B}T}{\hbar}\ln\left[2\cosh\left[\frac{\mu_{c}}{2k_{B}T}\right]\right]\frac{i}{\omega+i\tau^{-1}},\label{eq:sigma_graphene}
\end{equation}
where $e$, $\hbar$ and $k_{B}$ are constants corresponding to the charge of an electron, the reduced Planck constant and the Boltzmann constant, respectively \cite{Hanson2008}. Variables $T$, $\tau$ and $\mu_{c}$ correspond to the temperature, the relaxation time and the chemical potential of the graphene layer. Note that this expression neglects the edge effects of the graphene and considers that the Drude-like intraband contribution dominates, which are experimentally validated assumptions at the sizes and frequencies considered in this work \cite{AbadalTCOM}.

On the one hand, the phase control in graphene metasurface is achieved via changes in its complex conductivity when biased -- the effect that can be modeled through the chemical potential value $\mu_{c}$. The chemical potential can be controlled through electrostatic biasing, and therefore, we can meet the phase change requirement. On the other hand, the amplitude response depends on the losses within graphene, which are mostly influenced by the relaxation time value $\tau$. Note that the relaxation time is proportional to the carrier mobility, which depends on the quality of the material. For the purpose of this work, losses will be affordable as long as the carrier mobility of the graphene sheets is on the order of 10,000 cm\textsuperscript{2}V\textsuperscript{-1}s\textsuperscript{-1}, which is achievable with current fabrication and encapsulation techniques \cite{Banszerus2015}. Thus, the amplitude requirement can be met as well.

\subsection{Unit Cell Design}
Figure \ref{fig:unit cells} shows a schematic representation of the proposed unit cells together with their approximate equivalent circuit models. We numerically simulate different designs in CST Microwave Studio \cite{CST} to obtain the amplitude and phase responses. Then, through the equivalent circuit models, we verify the results of the numerical approach, and reason about the behavior of different unit cells. In all cases, we assume a lateral size of $d_{u} = 20\,\upmu$m. This value is around $\lambda_{0}/8$ for the targeted frequency of operation (2 THz), enough to provide the subwavelength behavior required in the metasurface. The relaxation time of graphene is assumed to be $\tau = 0.6$ ps, which is compatible with the carrier mobility requirements mentioned above.

The first unit cell (Fig. \ref{fig:1G}) consists of a fully covered layer of graphene on top of a silicon substrate with refractive index $n_{Si} = 3.45$ and thickness $d_{Si} = 10 \upmu$m along with a metallic ground plane on the backside. In such a unit cell, graphene is a lossy medium that can be modeled through an $RL$ circuit. Fig. \ref{fig:results1G} plots the amplitude and phase responses of reflection coefficient for such unit cell versus frequency and the chemical potential. It is observed that the amplitude response is within an acceptable range, whereas the phase range is not wide enough --around 135\textsuperscript{o} at 2 THz assuming a maximum chemical potential range of 1 eV. A very good agreement is also obtained between the numerical results and the equivalent circuit model.

\begin{figure*}[!ht]
\centering
\label{fig:1G1}{\includegraphics[width=2\columnwidth]{./figures/Figure3.png}}
\vspace{-0.2cm}
\caption{a) Amplitude and b) phase responses of reflection coefficient for the \textsc{1L} unit cell. Effect of chemical potential variation in c) amplitude and d) phase for various frequency. Unless noted, $E_{F} = 0.7$ eV, $\tau = 0.6$ ps, and $f = 2$ THz. \label{fig:results1G}}
\vspace{-0.1cm}
\end{figure*}

\begin{figure*}[!ht]
\centering
\label{fig:1Gpatch1}{\includegraphics[width=2\columnwidth]{./figures/Figure4.png}}
\vspace{-0.2cm}
\caption{a) Amplitude and b) phase responses of reflection coefficient for the \textsc{1G} unit cell. Unless noted, $E_{F} = 0.2$ eV, $\tau = 0.6$ ps, $d_{G} = 16 \upmu$m, and $f = 2$ THz. Effect of chemical potential and patch size variation in c) amplitude and d) phase for a constant frequency $f = 2$ THz.\label{fig:results1Gp}}
\vspace{-0.1cm}
\end{figure*}

\begin{figure*}[!ht]
\centering
\label{fig:2Gpatch1}{\includegraphics[width=2\columnwidth]{./figures/Figure5.png}}
\vspace{-0.2cm}
\caption{a) Amplitude and b) phase responses of reflection coefficient for the \textsc{2G} unit cell. In the frequency response figures, $E_{F} = 0.2$ eV, $\tau = 0.6$ ps, $d_{G} = 16 \upmu$m. Effect of top and bottom layers chemical potential in c) amplitude and d) phase for a constant frequency (the four chosen coding states used in the simulation are marked by different signs). In these figures, $\tau = 0.6$ ps, $d_{G} = 12 \upmu$m and $f = 2$ THz. \label{fig:results2Gp}}
\vspace{-0.2cm}
\end{figure*}

The second unit cell (Fig. \ref{fig:1G-patch}) consists of a graphene patch that partially covers the unit cell. The substrate and ground plane remain unchanged. In this case, a capacitance is introduced to model the coupling effects generated between the edges of adjacent graphene patches. As shown in Fig. \ref{fig:results1Gp}, the size of the graphene patch provides an extra degree of freedom to deliver the target amplitude and phase responses. Exploring the \{chemical potential, patch size\} design space, we observe that there is a tradeoff between the amplitude and phase variation. For a patch size of 6 $\upmu$m, the phase range covers almost 360\textsuperscript{o} with less than 0.8 eV chemical potential variation. However, the amplitude response also has a very large variation, which discourages the choice of such design point. A patch size of 8 $\upmu$m or larger provides a better amplitude response with a reasonable phase change variation.

The third unit cell (Fig. \ref{fig:2G-patch}) is composed of a graphene-insulator-graphene stack placed over the substrate along with a ground plane on the backside. High-density polyethylene (HDPE) is chosen as the insulator due to its particularly low losses in the terahertz band \cite{Zhou2014a}. The refractive index of the insulator is $n_{HDPE} = 1.54$ and its thickness is $d_{HDPE} = 4 \upmu$m. The equivalent circuit model of this structure consists of two parallel $RLC$ cells representing each of the graphene sheets. As shown in Fig. \ref{fig:results2Gp}, this unit cell achieves a much wider phase variation, and by addressing each graphene patch independently, provides an extra degree of freedom to choose the states of the metasurface.

\hl{According to the formulation presented in [], the initial values for RLC model parameters are estimated. For the dual patch unit cell, due to the coupling effect between two graphene layers, small changes can occur in the RLC parameters which are optimized by genetic algoritm. The parameters for three unit cell are calculated respectively as....}

Regarding fabrication feasibility of the proposed low-profile structure (10 $\upmu$m substrate), there are advanced Silicon substrate thinning techniques that can be used to achieve an ultra-thinning down to 4 $\upmu$m without damage occurred due to thinning processes \cite{kim2014ultra}.

\subsection{Unit Cell Discrete States}
\label{sec:states}
The results above show the response of the metasurface for a continuous range of chemical potentials. However, in order to design a bit-programmable metasurface, we need to discretize the potentials to obtain a finite set of addressable states.

The first decision concerns the number of target states, and thus, the number of bits required to address a unit cell. Here, the number of states will determine the phase difference between consecutive unit cell states. For the application at hand, there is a relation between the phase difference and the steering resolution, i.e., the angle difference between consecutive achievable beam directions (see Sec. \ref{sec:disc} for details). Therefore, the number of bits must be chosen carefully.

Let us now exemplify this process by deriving the states required for the metasurface to work at 2 THz. We start by addressing the  \textsc{1G} unit cell with a single bit. From the design space exploration shown in Fig. \ref{fig:results1Gp}, we choose design points that have high amplitude and a phase difference of approximately 180\textsuperscript{o}. A good choice is  $d_{G} = 8 \upmu$m with $\mu_{c} = \{0.6, 1.28\}$ eV corresponding to a bit combination of $B=\{0,1\}$. The resulting amplitude and phase responses, illustrated in Fig. \ref{fig:1code}, provide a constant reflection coefficient of around 0.7 and deliver the targeted 180\textsuperscript{o} phase shift.

Two-bit coding leads to a phase shift resolution of 90\textsuperscript{o} and would improve the beam steering accuracy substantially. The  \textsc{1G} unit cell, however, barely meets the amplitude and phase shift requirements with a 90\textsuperscript{o} resolution. With $d_{G} = 8 \upmu$m, there is no combination of chemical potentials capable of avoiding the region of low amplitude around 0.9 eV. For larger patch sizes, the phase response is not wide enough to accommodate two bits. For three or more bits, this unit cell would not be suitable for beam steering, at least for the relaxation time values and geometry considered in this work.

\begin{figure}[!t]
\centering
\label{fig:1code1}{\includegraphics[width=0.7\columnwidth]{./figures/Figure6.png}}
\vspace{-0.2cm}
\caption{a) Amplitude and b) phase of reflection coefficient for 1-bit digital metasurface by \textsc{1G} unit cell. \label{fig:1code}}
\vspace{-0.2cm}
\end{figure}

Alternatively, the \textsc{2G} unit cell offers much more freedom and is capable of accommodating two or more bits. Addressing the \textsc{2G} unit cell with two bits, one can find suitable design points with $d_{G}=12 \upmu$m. Using the design space exploration from Fig. \ref{fig:results2Gp}, good performance is obtained for the following up-layer and down-layer chemical potentials, respectively: $\mu_{c,1} = \{0.6, 1.3, 0.1, 0.4\}$ eV and $\mu_{c,2} = \{0, 0.6, 0.1, 0.1\}$ eV corresponding to the bit combinations $B = \{00, 01, 10, 11\}$. It is observed in Fig. \ref{fig:2code} that these states consistently achieve a reflection coefficient around 0.7 and a phase difference of 90\textsuperscript{o} covering the whole phase space. In Section \ref{sec:antenna}, we discuss how to electronically achieve these states.

\begin{figure}[!t]
\centering
\label{fig:2code1}{\includegraphics[width=0.7 \columnwidth]{./figures/Figure7.png}}
\vspace{-0.2cm}
\caption{a) Amplitude and b) phase of reflection coefficient for 2-bit digital metasurface in \textsc{2G} unit cell. \label{fig:2code}}
\vspace{-0.2cm}
\end{figure}

\section{Coding Metasurface Terahertz Antenna}
\label{sec:coding}
To illustrate the design approach of a terahertz metasurface for beam steering application, a metasurface including $M\times N$ controllable unit cells is considered. Our design allows one to introduce a phase gradient by smartly changing the chemical potential $\mu_{c}$ of the graphene sheets from one unit cell to another. In this case, we need to use the generalized reflection law to evaluate the response of the metasurface \cite{yu2011light}.

In the following, we first derive the conditions required to achieve beam steering to a desired direction $\{\theta_{r}, \phi_{r}\}$ in Section \ref{sec:formula}. Then, we define the design and configuration flow to achieve such the desired direction by our proposed design in Section \ref{sec:flow}. Finally, we evaluate the performance of the proposed metasurface in Section \ref{sec:evaluation}.

\subsection{Generalized Reflection Law Formulation}
\label{sec:formula}
Consider a reflective metasurface under illumination of an incident plane wave at elevation angle $\theta_{i}$ and azimuth angle $\phi_{i}$ according to the coordinate system shown in Fig. \ref{fig:coor}. The incident wave vector $k_{i}$ can be written as
\begin{equation}
k_{i} = k_{ix} \hat{x} + k_{iy} \hat{y} + k_{iz} \hat{z}
\end{equation}
where $\{k_{ix}, k_{iy}, k_{iy}\}$ are the wave vector coordinates, \hl{given} by
\begin{equation}
\begin{array}{l} \label{eq:ki}
k_{ix} = k_{i} \sin{\theta_{i}}\cos{\phi_{i}} = k_{0} n_{i} \sin{\theta_{i}}\cos{\phi_{i}} \\
k_{iy} = k_{i} \sin{\theta_{i}}\sin{\phi_{i}} = k_{0} n_{i} \sin{\theta_{i}}\sin{\phi_{i}} \\
k_{iz} = k_{i} \cos{\theta_{i}} = k_{0} n_{i} \cos{\theta_{i}}
\end{array}
\end{equation}
The same formulation can be applied to the reflected wave vector $k_{r}$ given the elevation angle $\theta_{r}$ and azimuth angle $\phi_{r}$ of the reflected wave.

Assuming that the metasurface imposes the phase profile $\Phi(x,y)$, we assign it the virtual wave vector $k_{\Phi}$ so that
\begin{equation}
\label{eq:kphi}
k_{\Phi} = k_{\Phi x} \hat{x} + k_{\Phi y} \hat{y} = \frac{d\Phi}{dx}\hat{x} + \frac{d\Phi}{dy}\hat{y} = \nabla \Phi_{x} \hat{x} + \nabla \Phi_{y} \hat{y}
\end{equation}
where $\nabla_{x} \Phi = \tfrac{d\Phi}{dx}$ and $\nabla_{y} \Phi = \tfrac{d\Phi}{dy}$ are the phase gradients along the $x$ and $y$ directions, respectively.

Applying the boundary conditions of the tangential components of the electromagnetic fields, the momentum conservation law for wave vectors can be expressed as
\begin{equation}\label{eq:BC}
\begin{array}{l}
k_{ix} + k_{\Phi x} = k_{rx} \\
k_{iy} + k_{\Phi y} = k_{ry}
\end{array}
\end{equation}
and substituting \eqref{eq:ki} and \eqref{eq:kphi} in \eqref{eq:BC} yields
\begin{equation}\label{eq:dphi}
\begin{array}{l}
k_{i} \sin{\theta_{i}}\cos{\phi_{i}} + \frac{d\Phi}{dx} = k_{r} \sin{\theta_{r}}\cos{\phi_{r}} \\
k_{i} \sin{\theta_{i}}\sin{\phi_{i}} + \frac{d\Phi}{dy} = k_{r} \sin{\theta_{r}}\sin{\phi_{r}}
\end{array}
\end{equation}

\begin{figure}[!t]
\centering
{\includegraphics[width=1\columnwidth]{./figures/coordinateSystem.pdf}}
\vspace{-0.3cm}
\caption{Coordinate system used in the formulations of generalized reflection law.\label{fig:coor}}
\vspace{-0.1cm}
\end{figure}

By mathematically simplifying the above equations as shown in the Appendix, the reflected elevation angle $\theta_{r}$ and azimuth angle $\phi_{r}$ are obtained as
\begin{equation}
\label{eq:simp}
\begin{array}{l}
\theta_{r} = \arcsin{\frac{\sqrt{(k_{i} \sin{\theta_{i}}\cos{\phi_{i}} + \frac{d\Phi}{dx})^{2} + (k_{i} \sin{\theta_{i}}\sin{\phi_{i}} + \frac{d\Phi}{dy})^{2}}}{k_{r}}} \\
\phi_{r} = \arctan{\frac{k_{i} \sin{\theta_{i}}\sin{\phi_{i}} + \frac{d\Phi}{dy}}{k_{i} \sin{\theta_{i}}\cos{\phi_{i}} + \frac{d\Phi}{dx}}}
\end{array}
\end{equation}

When the metasurface is illuminated by a normally incident wave ($\theta_{i}=\phi_{i}=0$), and assuming air as the medium of the incident and reflected wave, we can simplify the formulas as
\begin{equation}
\label{eq:reflected}
\begin{array}{l}
\theta_{r} = \arcsin{\frac{\sqrt{(\nabla_{x}\Phi)^{2}+(\nabla_{y}\Phi)^{2}}}{k_{0}}} \\
\phi_{r} = \arctan{\frac{\nabla_{y}\Phi}{\nabla_{x}\Phi}},
\end{array}
\end{equation}
which relates the phase gradient in the metasurface to the direction of the reflected wave.

\subsection{Design Flow}
\label{sec:flow}
Using \eqref{eq:reflected}, the reflected angles for all phase profiles of the metasurface can be calculated. The design of the metasurface can be then thought as an inversion process. We need to estimate the necessary phase profile to achieve the desired elevation and azimuth angles of the reflected wave. To this end, and again assuming a normal incident plane wave and air as the medium, we can rearrange \eqref{eq:dphi} as
\begin{equation}
\label{eq:dphi2}
\begin{array}{l}
dx = \frac{\lambda_{0} d\Phi}{2\pi\cos{\phi_{r}}\sin{\theta_{r}}} \\
dy = \frac{\lambda_{0} d\Phi}{2\pi\sin{\phi_{r}}\sin{\theta_{r}}}
\end{array}
\end{equation}
where $d\Phi$ describes the phase difference between adjacent unit cell states. Starting from here, the design methodology requires the knowledge of the unit cell dimensions and the number of states. The design flow is as follows,

\vspace{0.1cm}
\noindent
\textbf{1. Obtaining the cluster size (in $\upmu$m):} Assume that the coding metasurface can choose among $2^{n}$ states for each unit cell (referred to as $n$-bit coding). In this case, the granularity of the gradient is $d\Phi = \pi/2^{n-1}$. Therefore, the lateral dimensions of the required cluster of unit cells ($d_{cx}$ and $d_{cy}$), as shown in Fig. \ref{fig:summary}, are obtained by substituting $d\Phi$ in Eq. \eqref{eq:dphi2},
\begin{equation}
\label{eq:dphi3}
\begin{array}{l}
d_{cx} =
\frac{\lambda_{0}}{2^{n}\cos{\phi_{r}}\sin{\theta_{r}}} \\
d_{cy} =
\frac{\lambda_{0}}{2^{n}\sin{\phi_{r}}\sin{\theta_{r}}}.
\end{array}
\end{equation}
It is worth noting that the results in \eqref{eq:dphi2} can be negative if $d\Phi$ becomes negative, which implies that the gradient needs to be reversed at the coding stage. We will later see that the algorithm for metasurface coding already takes the direction of the gradient into consideration. Also, the value of $\phi_{r}$ determines the difference between $d_{cx}$ and $d_{cy}$, which impacts on the shape of the reflected beam. The larger difference results in the more elliptical shape of the reflected beam.

\vspace{0.1cm}
\noindent
\textbf{2. Obtaining the cluster size (in number of unit cells):} The nature of a metasurface, consisting an array of unit cells, dictates the discretization of  space. Therefore, the values of $d_{cx}$ and $d_{cy}$ needs to be approximated in an integer number of unit cells. For this purpose, we consider that the number of unit cells in the $x$ and $y$ directions, designated by $c_{x} \in \mathbb{Z}$ and $c_{y} \in \mathbb{Z}$, respectively, are rounded as
\begin{equation}
\label{eq:cluster}
c_{x} = \lfloor \frac{d_{cx}}{d_{u}} \rceil \,\, ,\,\, c_{x} = \lfloor \frac{d_{cy}}{d_{u}} \rceil.
\end{equation}

Figure \ref{fig:cx} shows the absolute value of $c_{x}$ as a function of the target direction for a normally incident plane wave. It is observed that $c_{x}$ becomes arbitrarily large as the reflected angle approaches $\theta_{r} = 0$ (white areas of the figure). This is consistent with the fact that such direction implies specular reflection, which can only be realized with a homogeneous surface, i.e. zero gradient. For directions approaching $\phi=\pi/2,~3\pi/2$, $c_{x}$ also becomes large because the gradient is only needed in the $y$ axis. On the contrary, $c_{x}$ approaches zero in the co-planar directions, where an infinite gradient would be required. The black area in Fig. \ref{fig:cx} denotes $c_{x} < 1$, which is unfeasible.

\begin{figure}[!t]
\centering
{\includegraphics[width=0.8\columnwidth]{./figures/cx2.png}}
\vspace{-0.4cm}
\caption{Absolute value of $c_{x}$ as a function of the desired direction of reflection.
\label{fig:cx}}
\vspace{-0.1cm}
\end{figure}

\vspace{0.1cm}
\noindent
\textbf{3. Obtaining the size of the super unit cell:} To calculate the size of the super unit cell, designated by $s_{x} \in \mathbb{Z}$ and $s_{y} \in \mathbb{Z}$, in number of unit cells, one needs to apply
\begin{equation}
\label{eq:dphi4}
s_{x} = 2^{n}c_{x} \,\, ,\,\, s_{y} = 2^{n}c_{y}.
\end{equation}

\subsection{Evaluation}
\label{sec:evaluation}
In this section, we evaluate the proposed metasurface both numerically and analytically. We numerically model the four states of the $2G$ unit cell in CST \cite{CST}, and apply the formulation developed above to assign the states to different unit cells of an $M\times N$ metasurface. Then, we obtain the response of the metasurface in the form of the far field pattern produced by a normally incident plane wave. We assume that the beam covers the whole metasurface.

\begin{figure*}[!t]
\centering
\label{fig:Meta1N}{\includegraphics[width=1.8\columnwidth]{./figures/Figure10.png}}
\vspace{-0.2cm}
\caption{Radiation pattern of the metasurface structure at 2 THz with the main reflected beam pointed at $\{\phi_{r}=30^{o},\theta_{r}=45^{o}\}$  by a) numerical approach and b) analytical approach. The incident wave is normal to the metasurface.
\label{fig:Meta1}}
\vspace{-0.2cm}
\end{figure*}

\begin{figure*}[!t]
\centering
\label{fig:Meta22}{\includegraphics[width=1\textwidth]{./figures/Figure11.png}}
\vspace{-0.5cm}
\caption{Radiation pattern of the metasurface structure at 2 THz with the main reflected beam pointed at the directions (numerical approach): a) $\{\phi_{r}=130^{o},\theta_{r}=30^{o}\}$, b) $\{\phi_{r}=230^{o},\theta_{r}=20^{o}\}$, and c) $\{\phi_{r}=340^{o},\theta_{r}=60^{o}\}$. The incident wave is normal to the metasurface.
\label{fig:Meta2}}
\vspace{-0.2cm}
\end{figure*}

\begin{table*}[!t]
\caption{Design and Performance Results.}
\vspace{-0.2cm}
\label{tab:performance}
\footnotesize
\centering
\begin{tabular}{|c||cc|cc|cc|cc|}
\hline
Direction & $d_{cx}$ & $d_{cy}$ & $c_{x}$ & $c_{y}$ & $\phi_{3dB}$ & $\theta_{3dB}$ & $Err_{\phi}$ & $Err_{\theta}$  \\
$\{\phi_{r}, \theta_{r}\}$ & \multicolumn{2}{c|}{($\upmu$m)} & \multicolumn{2}{c|}{(cells)} & \multicolumn{2}{c|}{(\textsuperscript{o})} & \multicolumn{2}{c|}{(\%)} \\ \hline
\{30\textsuperscript{o}, 45\textsuperscript{o}\} &  61.24  & 106.07 &  3 & 5 & 5 & 5.25  & 2.5  & 3.3 \\
\{130\textsuperscript{o}, 30\textsuperscript{o}\} &  116.68 & 97.91  & 6 & 5 & 8.25 & 4.75 & 0.58 & 4.16  \\
\{230\textsuperscript{o}, 20\textsuperscript{o}\} &  170.57 & 143.13 & 8 & 7 & 10.5 & 4 & 0.11 & 6.25 \\
\{340\textsuperscript{o}, 60\textsuperscript{o}\} &  46.08  &  126.6 & 2 & 6 & 4.5 & 8.25 & 0.15 & 3.75 \\
\hline
\end{tabular}
\vspace{-0.3cm}
\end{table*}

In the analytical approach that is used to verify the numerical results, the reflection phase $\Phi(p,q)$ of each unit cell of size $d_{u}$ is assumed to be exactly either 0, $\pi/2$, $\pi$, or $3\pi/2$. Assuming a designed phase distribution assigned to the unit cells, we can express the far-field scattering pattern $F(\theta,\phi)$ as
\begin{equation}
F(\theta,\phi) = f_{E}(\theta,\phi)\times f_{A}(\theta,\phi)
\end{equation}
where $\theta$ and $\phi$ are the elevation and azimuth angles of an arbitrary direction, respectively, and $f_{E}(\theta,\phi)$ and $f_{A}(\theta,\phi)$ are the element factor (pattern function of unit cell) and array factor (pattern function of unit cell arrangement), respectively. Here, the unit cells are assumed to be isotropic, and therefore the scattering pattern depends only on the array factor
\begin{equation}
\begin{array}{l}
F(\theta,\phi) = \sum_{p=1}^{M}\sum_{q=1}^{N}exp\{-j[\Phi(p,q)+ \\
+\, kd_{u}(p-1/2)\sin{\theta}\cos{\phi}\, + \\
+\, kd_{u}(q-1/2)\sin{\theta}\sin{\phi}]\}.
\end{array}
\end{equation}

We first evaluate the metasurface when configured to steer the beam at $\{\phi_{r}=30^{o},\theta_{r}=45^{o}\}$ with $M=N=100$. Following the design flow from Section \ref{sec:flow} and assuming 20-$\upmu$m unit cells and 2-bit coding, we obtain that $d_{cx} = 61.24 \,\upmu$m and $d_{cy} = 106.07 \,\upmu$m, which leads to a cluster of $3\times 5$. The super unit cell thus extends for $12\times 20$ unit cells. Figure \ref{fig:Meta1} shows the far field pattern of the resulting metasurface, which confirms that there is a good agreement between the numerical and analytical solutions. The reason for the small differences between the numerical and theoretical results in sidelobe levels could be the marginal unit cells in the clusters, super unit cells, and the whole structure. We obtain the amplitude and phase of the reflection coefficient of the proposed unit cells while taking into consideration mutual coupling between the same adjacent unit \hl{cells} by assuming a periodic boundary condition. While in the real metasurface structure for beam steering, there are some marginal unit cells which their adjoining unit cells are not similar with them. Consequently, the peridicity condition is broken. In the simulation of full structure, the correct coupling of marginal unit cells is considered while in the theoretical analysis of entire metasurface structure, it is ignored perforce. It is seen that the reflected beam indeed points to the target direction. The steering error, evaluated as the difference between the target and achieved angles, is 2.5\% and 3.3\% in $\phi$ and $\theta$, respectively. The 3-dB width of the beam is approximately 5\textsuperscript{o} in both cases.

To further verify the validity of the approach, we reconfigure the metasurface to operate at three different steering directions. Figure \ref{fig:Meta2} shows how the proposed metasurface design is capable of achieving the desired responses and Table \ref{tab:performance} summarizes the characteristics and performance of the resulting configurations. A wide range of reflected angles is achieved with clusters of 2--8 unit cells, achieving in all cases beam widths below 11\textsuperscript{o} (minimum 4\textsuperscript{o}) with steering error below 7\% (minimum 0.11\%). Note that the error and beam width generally increase when approaching \emph{forbidden areas} in the design space, where the gradient tends to zero or infinity. Also, the reflected beam for the cases \{30\textsuperscript{o}, 45\textsuperscript{o}\} and \{340\textsuperscript{o}, 60\textsuperscript{o}\} especially the latter) tend to be elliptical due to the larger difference between $d_{cx}$ and $d_{cy}$, as hinted in Section \ref{sec:flow}. In addition, to achieve a continuous beam scanning ability of coding metasurface with minimum angle variation, the convolution approach can be leveraged to steer the far-field pattern to a predetermined direction \cite{liu2016convolution}. Regarding the Fourier relation between the field distribution on the coding metasurface and the resultant scattering pattern in the far-field, one can shift the reflected pencil beam by adding the two calculated phase gradient coding \hl{patterns} so that the total phase gradient deflection angle is equal to the desired angle.

\section{Programmability and Implementation Issues}
\label{sec:antenna}
The final steps in the design of our beam steering device relate to the elements that control and excite the metasurface. More precisely, we need to conceive a setup that takes the target reflected angle as input and modifies the metasurface accordingly. To this end, in Sec. \ref{sec:controller} we propose a controller that automatically converts the target reflected angle into a bit matrix defining the states of each unit cell. Then, in Sec. \ref{sec:biasing} we discuss the biasing scheme required to address each unit cell with the appropriate voltage (chemical potential). Finally, we review source considerations in Sec. \ref{sec:source}.

\subsection{Controller Design}
\label{sec:controller}
To achieve programmability, it is necessary to attach the metasurface to a digital device capable of translating the beam steering requirements into the global metasurface state. Algorithm \ref{alg1} shows a pseudocode that exemplifies this function. The process starts by calculating the size of the unit cell clusters $c_{x}\times c_{y}$ as a function of the bit number per cell $n$, and the dimension of the unit cell $d_{u}$. Then, the gradient can be built easily by assigning consecutive states to adjacent clusters of unit cells. As already mentioned in Section \ref{sec:flow}, \eqref{eq:dphi3} and \eqref{eq:cluster} can produce negative values, in which case the order of states is reversed.

Algorithm \ref{alg1} assumes that all unit cells are addressed by a centralized device, probably an FPGA. However, since the metasurface implements a discretized gradient, it would be relatively straightforward to come up with an algorithm that can calculate the required state in a distributed way, only relying on the state of the immediate neighbour. Such simplified scheme would be suitable for the rising Software-Defined Metamaterial (SDM) paradigm \cite{Liaskos2015, AbadalACCESS}, which aims to provide programmable metamaterials that can be reconfigured via an integrated network of controllers that drive unit cells individually. In that case, an external entity called gateway would receive the command of changing the direction of the beam. The gateway would compute $c_{x}$ and $c_{y}$, then rely them to the first controller together with $n$. The first controller would be initialized and pass its state along with $c_{x}$, $c_{y}$, and $n$ to their neighbours, which would repeat the process until the whole metasurface is programmed.

\subsection{Actuator Design}
\label{sec:biasing}
The actuator is a circuit that translates the state matrix $[B]$ provided by the controller into the matrix of appropriate voltages $[V_{G}]$ that, in turn, leads to the required chemical potentials in each graphene patch of the metasurface. As shown in Fig. \ref{fig:actuator}, a set of voltage level shifters and a matrix of multiplexers would be enough for this purpose. Note that several independent sets of multiplexers (two in our case) may be required to drive the graphene patches of individual unit cells. It is also worth noting that only five distinct voltages are needed in our case, because several states share the same target chemical potentials according to the calculations made in Section \ref{sec:states}.

\begin{algorithm}[!t]
\caption{Algorithm for clustered gradient formation.}
\label{alg1}
\begin{algorithmic}
\small
\STATE Inputs: du, phiR, thetaR, n, f
\STATE
\STATE /* CALCULATION OF THE CLUSTER SIZES */
\STATE lambda = 3e8/f;
\STATE dcx = lambda/(2\^{}n*cos(phiR)*sin(thetaR));
\STATE dcy = lambda/(2\^{}n*sin(phiR)*sin(thetaR));
\STATE cx = round(dcx/du); // MAY BE NEGATIVE
\STATE cy = round(dcy/du); // MAY BE NEGATIVE
\STATE
\STATE /* CALCULATION OF THE STATE MATRIX */
\STATE for(i=1; i$<$M; i++) \{
\STATE $\,\,\,\,$for(j=1; j$<$N; j++) \{
\STATE $\,\,\,\,\,\,\,\,$B(i,j) = (round(i/cx) + round(j/cy)) mod(2\^{}n);
\STATE $\,\,\,\,$\}
\STATE \}
\end{algorithmic}
\end{algorithm}

The actual voltages required at the output of the level shifters mainly depend on the graphene biasing structure and the required chemical potential \cite{Huang2012ARRAY, Gomez2015}. The configuration assumed in this paper is similar to that used in \cite{Huang2012ARRAY}, which couples graphene capacitively with a back gate through a thin Al$_{2}$O$_{3}$ layer. Essentially, this scheme shifts the operation of graphene between the Dirac point, where the chemical potential is minimum, and a point where the potential reaches the maximum desired point. The resulting chemical potential $\mu_{c}$ relates to the change of voltage $\Delta v_{g}$ as
\begin{equation}
\label{eq:SLG}
\Delta v_{g} = \frac{e \mu_{c}^2 t}{\pi \hbar^2 v_{F}^2 \varepsilon_{0} \varepsilon_{r}},
\end{equation}
where $e$ is the elementary charge, $\hbar$ is the reduced Planck constant, $v_{F} \approx 10^{6} $ m/s is the Fermi velocity, $\varepsilon_{0}$ is the vacuum permittivity, whereas $\varepsilon_{d}$ and $t$ are the permittivity and thickness of the material below graphene \cite{Yu2009Chemical}.

Figure \ref{fig:voltage} illustrates the voltage ranges required to achieve a certain target chemical potential range. As directly implied by \eqref{eq:SLG}, the voltage requirements increase quadratically with the target chemical potential range. To limit the requirements, one can either minimize the space between the gate and the graphene layer or use materials with high dielectric constant. However, the former is determined by technological constraints, and the latter needs to take into consideration the cost and other characteristics of the material.

The chemical potential range required by our metasurface can be obtained easily once the unit cell states are defined. In the present design, $\Delta\mu_{c} = 1.3$ eV. Assuming a Al$_{2}$O$_{3}$ layer ($\varepsilon_{r} = 9.1$) with thickness $t = 10$ nm, achievable with current technologies \cite{Huang2012ARRAY}, the resulting voltage range is 24.9 V.

\begin{figure}[!t]
\centering
{\includegraphics[width=0.7\columnwidth]{./figures/actuator.pdf}}
\vspace{-0.3cm}
\caption{Sample implementation of the actuator for the metasurface based on the $2G$ unit cell and 2-bit coding.\label{fig:actuator}}
\vspace{-0.3cm}
\end{figure}

\begin{figure*}[!ht]
\centering
\subfigure[Voltage as a function of the dielectric thickness.\label{fig:voltT}]{\includegraphics[width=1\columnwidth]{./figures/voltage_t.pdf}}
\subfigure[Voltage as a function of the dielectric constant.\label{fig:voltE}]{\includegraphics[width=1\columnwidth]{./figures/voltage_er.pdf}}
\vspace{-0.1cm}
\caption{Voltage range required at the level shifting stage to achieve a given target chemical potential range.\label{fig:voltage}}
\vspace{-0.3cm}
\end{figure*}

\subsection{Towards an Experimental Setup}
\label{sec:source}
Figure \ref{fig:setup} illustrates a possible measurement setup for the experimental \hl{validation} of the metasurface. \hl{The testbed would mainly consist of a fiber-coupled time domain spectroscopy (THz-TDS) system with a fixed source (generally harder to calibrate) and a movable receiver placed on a rotatory platform. The source is based on a photoconductive antenna coupled to a focusing or collimating lens that minimizes spreading losses. Additional optics such as parabolic reflectors can be incorporated to meet the receiver sensitivity as well as the source--metasurface--receiver distance requirements. It is worth noting that such a scheme has been used successfully in other works proving anomalous reflection in the THz band} \cite{Liu2016a, Liang2015a}\hl{. A very similar system has been built in} \cite{Kokkoniemi2016} \hl{for the measurement of the reflection coefficient of surfaces in the terahertz band entirely with commercial solutions.}

\begin{figure}[!ht]
\centering
{\includegraphics[width=0.8\columnwidth]{./figures/setup.pdf}}
\vspace{-0.3cm}
\caption{\hl{Sketch of a potential measurement setup for the proposed device.}\label{fig:setup}}
\vspace{-0.3cm}
\end{figure}

\section{Discussion}
\label{sec:disc}
In this section, we qualitatively discuss several cross-cutting issues related to the design of the metasurface.

\vspace{0.1cm}
\noindent
\textbf{Scalability analysis:} To accommodate the proposed design flow to different beam steering specifications, it is crucial to understand which are the key design parameters and what performance metrics do they affect. Here, we highlight some:

\begin{itemize}
\item The size of the unit cell presents an interesting tradeoff. While it may be difficult to achieve a wide phase range if the unit cell is too small with respect to the wavelength (see Figs. \ref{fig:results1G} and \ref{fig:results1Gp}), reducing its dimensions leads to a raise in the maximum achievable phase gradient. This is useful to achieve better control at the end-fire directions ($\theta_{r}\to 90$\textsuperscript{o}) of the metasurface, as exemplified by Fig. \ref{fig:rangeDX}. For instance, we can achieve beam steering at $\theta_{r} > 70$\textsuperscript{o} only for $d_{u} < 5 \upmu$m. For angles even closer to $\theta_{r}=90$\textsuperscript{o}, a design converting the incident wave into a surface wave may be required \cite{Tcvetkova2017}. In any case, note that such fine-grained control at THz frequencies can only be achieved with graphene, thanks to its support of plasmonic slow-wave propagation in this frequency band.

\item Increasing the number of bits provides better control on the phase as it allows to draw the phase gradient more accurately, with more clusters and less unit cells per cluster. This is of special importance in directions close to the boresight ($\theta_{r}\to 0$\textsuperscript{o}), where a subtle gradient is required. Fig. \ref{fig:resDX} exemplifies this for a design targeting $\theta_{r} = 5.37$\textsuperscript{o} with fixed size, but increasing number of bits. The 3-bit instance greatly reduces the side lobes and has its maximum at $\theta_{r} = 5.26$\textsuperscript{o}, whereas the beam moves away from the desired direction for the 2-bit and 1-bit cases (4.92\textsuperscript{o} and 4.22\textsuperscript{o}, respectively). Note, however, that the gain in accuracy comes at the cost of a substantially higher complexity at the controller and the actuator.
\item In arrays, adding more antennas allows to reduce the beam width. The same principle should apply in our design, as exemplified in Section \ref{sec:evaluation} with the array factor formulation. We verified such hypothesis by fixing the gradient and doubling the number of supercells once and twice (from $M=N=40$ to $M=N=160$). The resulting far field patterns, shown in Fig. \ref{fig:sizeDX}, clearly demonstrate that the beam is sharpened without significantly changing the direction of maximum energy. In fact, the beam width is reduced by a factor proportional to the increase in metasurface size, i.e. from 50\textsuperscript{o} and 5\textsuperscript{o} to 12\textsuperscript{o} and 1.3\textsuperscript{o} in the $\theta$ and $\phi$ angles, respectively.
\end{itemize}

\begin{figure*}[!ht]
\centering
\subfigure[Achieved $\theta_{r}$ for different values $d_{u}$.\label{fig:rangeDX}]{\includegraphics[width=0.68\columnwidth]{./figures/range_dx.pdf}}
\subfigure[Far field patterns for different number of bits (top) and metasurface sizes (bottom).\label{fig:resDX}
\label{fig:sizeDX}]{\includegraphics[width=1.3\columnwidth]{./figures/res+size_dx.png}}
\vspace{-0.1cm}
\caption{Performance scalability analysis of the metasurface from the unit cell, coding, and complete device perspectives.}
\vspace{-0.3cm}
\end{figure*}

\vspace{0.1cm}
\noindent
\textbf{Co-design opportunities:} Understanding the design flow from the point of view of the unit cell, the metasurface, or the device as a whole helps to identify possible co-design opportunities. For instance, the unit cell configuration and the coding determine the complexity in terms of number of required voltage levels, as well as the quantity and size of the multiplexers. For an $n$-bit coding with $g$ independently biased graphene patches, we may require up to $g\cdot 2^{n}$ levels and $g$ multiplexers with $2^{n}$ inputs. However, advanced design exploration techniques may allow to find design points that reduce the voltage range, the number of required levels, and the multiplexer inputs while gracefully degrading the performance of the system. For instance, in our 2-bit implementation with the $2G$ unit cell, we could take $\mu_{c,1} = \mu_{c,2} = \{0.1, 0.6\}$ and still achieve reasonable performance, but with a $4\times$ reduction of voltage range and number of levels and greatly simplfying the multiplexing circuits.

\vspace{0.1cm}
\noindent
\textbf{Adaptive clusterization:} The strength of the proposed design flow is its simplicity. By fixing the cluster size first and then statically building the super cells, the state matrix can be calculated easily. However, the rounding operation used in the number of unit cells per cluster (Equation \eqref{eq:cluster}) introduces an error, specially for large unit cells, that is later amplified by the static building of super cells. Both issues can be alleviated by simply inverting the design flow, i.e. obtaining the size of the super cell first, and then breaking it down into unequal clusters. For instance, a super cell composed by 18 unit cells can be coded with 4, 5, 4, and 5 unit cells per state; otherwise, the super cell would be statically coded to either 4 or 5 unit cells per state, leading to a significant error. In a similar approach, the coding algorithm could dynamically adapt the number of states, using fewer bits in those directions that require a very large gradient.

\section{Conclusion}
\label{sec:conclusion}
This paper has presented the complete design, from the unit cell up to the programming algorithm, of a reconfigurable digital metamaterial for beam steering in the terahertz band. The tunability of graphene is exploited at the unit cell level to provide a phase range close to $2\pi$, whereas the generalized Snell's law of reflection has been used to derive the phase gradients required to target the beam to the desired direction. The results confirm the validity of the approach, which for normal incidence achieves a very broad reflection range with angle-dependent beam widths and steering errors. Considering normal incidence, the analytical formulation also models forbidden (and unreasonable) reflection directions effectively as infinite gradients. Finally, the scalability analysis confirms that the beam width depends on the size of the metasurface, the reflection range depends on the size of the unit cells, and the steering error and side lobe levels depend on the number of phases that the graphene-based unit cells can implement. Future works could leverage the comprehensive methodology developed herein to optimize the unit cell design and phase gradient formation to reduce the overhead of the solution and further improve the beam steering performance.

\section*{Acknowledgment}
This work has been partially funded by Iran's National Elites Foundation (INEF), the Spanish Ministry of \emph{Econom\'ia y Competitividad} under grant PCIN-2015-012, and by ICREA under the ICREA Academia programme. Also, the authors would like to thank Christoph S{\"u}{\ss}meier and the anonymous reviewers for their invaluable feedback

\section*{Appendix}
To extract $\phi_{r}$ from \eqref{eq:dphi}, we divide both expressions and apply basic trigometry to obtain
\begin{equation}
\tan{\phi_{r}} = \frac{k_{i} \sin{\theta_{i}}\sin{\phi_{i}} + \frac{d\Phi}{dy}}{k_{i} \sin{\theta_{i}}\cos{\phi_{i}} + \frac{d\Phi}{dx}}
\end{equation}
which yields
\begin{equation}
\phi_{r} = \arctan{\frac{k_{i} \sin{\theta_{i}}\sin{\phi_{i}} + \frac{d\Phi}{dy}}{k_{i} \sin{\theta_{i}}\cos{\phi_{i}} + \frac{d\Phi}{dx}}}
\end{equation}

To extract $\theta_{r}$ from \eqref{eq:dphi}, we square and sum both expressions:
\begin{equation}
\begin{array}{l}
k_{r}^{2} \sin{\theta_{r}}^{2}\cos{\phi_{r}}^{2} + k_{r}^{2} \sin{\theta_{r}}^{2}\sin{\phi_{r}}^{2} = \\
= (k_{i} \sin{\theta_{i}}\cos{\phi_{i}} + \frac{d\Phi}{dx})^{2} + (k_{i} \sin{\theta_{i}}\sin{\phi_{i}} + \frac{d\Phi}{dy})^{2}
\end{array}
\end{equation}
which, after applying basic trigonometry, becomes
\begin{equation}
\begin{array}{l}
k_{r}^{2} \sin{\theta_{r}}^{2} = \\
= (k_{i} \sin{\theta_{i}}\cos{\phi_{i}} + \frac{d\Phi}{dx})^{2} + (k_{i} \sin{\theta_{i}}\sin{\phi_{i}} + \frac{d\Phi}{dy})^{2}
\end{array}
\end{equation}

Isolating, we obtain
\begin{equation}
\begin{array}{l}
k_{r} = \arcsin{ \frac{\sqrt{(k_{i} \sin{\theta_{i}}\cos{\phi_{i}} + \frac{d\Phi}{dx})^{2} + (k_{i} \sin{\theta_{i}}\sin{\phi_{i}} + \frac{d\Phi}{dy})^{2} }}{k_{r}} }
\end{array}
\end{equation}

redpajama_set_name: RedPajamaArXiv


text:
E-cigarette Misinformation Imperils Public Health
by Marc Hyden | Aug 14, 2018 | The Forum | 0 comments
Misinformation regarding e-cigarettes is alarmingly ubiquitous. For example, days ago, the Saporta Report published an article discussing juveniles' supposed rampant e-cigarette usage. Georgia State University recently released a dubious study claiming that vaping doesn't help people quit smoking. Meanwhile, other institutions have allegedly exposed vaping's dire health risks.
These are misleading and, at times, false claims. Unfortunately, they are widespread and have already been the impetus for proposed statutory changes intended to limit access to e-cigarettes in Georgia and around the country. The simple truth, however, is that vaping's benefits far outweigh combustible cigarette's risks. As such, state and local governments should do more to promote e-cigarettes as a safer alternative for adults.
Efforts to restrict e-cigarette usage have been primarily based on the assumption that they are like traditional cigarettes. This is not only incredibly damaging, it's also far from the truth. Indeed, Public Health England – the UK's version of the Department of Health and Human Services – has found that e-cigarettes are 95 percent safer than combustible ones. The American Cancer Society itself has admitted that vaping presents a reduced risk. In fact, even the Office of the Surgeon General has stated that the effects of e-cigarettes on the body are similar to those of nicotine gum, patches and lozenges.
The reason for their increased safety is largely because e-cigarettes don't use the traditional cigarette combustion process that releases over 7,000 chemicals. Rather, they rely on much less harmful vaporization.
Regardless of their reduced risks, however, a recent Georgia State University study concluded that e-cigarettes do not help individuals quit smoking, and news of this report has been making waves in the media. However, the study's authors freely admit that their examination has limitations, including the fact that the sample size may be insufficient to draw any conclusions. The report has a far more serious flaw that makes its findings highly questionable: Individuals who already quit smoking traditional cigarettes by using e-cigarettes weren't counted as recent ex-smokers in the study. Put simply, this means that the research misidentified the very population of respondents that had already successfully accomplished the very thing for which they were testing.
Despite GSU's conclusions, e-cigarettes are quickly becoming the most popular quit tool in the United States and they have contributed to tens of thousands of individuals ceasing to smoke in England. Based on these findings, there's reason to believe that e-cigarettes are having the same effect in Georgia. In turn, they may even be limiting the broader risks associated with secondhand smoke by reducing the number of people using traditional cigarettes.
While there are many positives related to vaping, it is still important to discourage juveniles from using nicotine altogether. To date, it is already illegal for youths to purchase these products, and campaigns to educate adolescents on tobacco have been ongoing.
Nevertheless, safeguarding juveniles has spurred lawmakers into seeking further preventative measures. In doing so, however, they often rely on misleading numbers that present youth usage as a worsening epidemic. For example, most analyses identify any juvenile who has taken a single puff from a vaping device in the past 30 days as a current user. This definition simply doesn't comport with the general understanding of what a current or regular nicotine user really is. It's also particularly misleading when more reliable research is ignored that demonstrates that traditional cigarette usage is the lowest it's ever been among youths.
The bottom line is that roughly 480,000 people die annually in the United States from smoking-related illnesses. Yet, e-cigarettes are quite clearly less hazardous than combustible ones and have the potential to aid those attempting to quit smoking. Given that around 18 percent of Georgians are current traditional cigarette smokers, vaping can help thousands in the Peach State reduce these otherwise certain health risks. Rather than attempting to over-regulate and restrict a product that can benefit so many people, pragmatic policymakers should be encouraging its use as an alternative.
Marc Hyden is the Southeast region director with the R Street Institute, and he is a long-time Georgia resident. You can follow him on Twitter at @marc_hyden.


text:
// MS compatible compilers support #pragma once
#if defined(_MSC_VER)
# pragma once
#endif

/////////1/////////2/////////3/////////4/////////5/////////6/////////7/////////8
// text_wiarchive.hpp

// (C) Copyright 2002 Robert Ramey - http://www.rrsd.com .
// Use, modification and distribution is subject to the Boost Software
// License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)

//  See http://www.boost.org for updates, documentation, and revision history.

#include <boost/config.hpp>
#ifdef BOOST_NO_STD_WSTREAMBUF
#error "wide char i/o not supported on this platform"
#else

#include <istream>

#include <boost/archive/detail/auto_link_warchive.hpp>
#include <boost/archive/basic_text_iprimitive.hpp>
#include <boost/archive/basic_text_iarchive.hpp>
#include <boost/archive/detail/register_archive.hpp>
#include <boost/serialization/item_version_type.hpp>

#include <boost/archive/detail/abi_prefix.hpp> // must be the last header

#ifdef BOOST_MSVC
#  pragma warning(push)
#  pragma warning(disable : 4511 4512)
#endif

namespace boost {
namespace archive {

namespace detail {
    template<class Archive> class interface_iarchive;
} // namespace detail

template<class Archive>
class BOOST_SYMBOL_VISIBLE text_wiarchive_impl :
    public basic_text_iprimitive<std::wistream>,
    public basic_text_iarchive<Archive>
{
#ifdef BOOST_NO_MEMBER_TEMPLATE_FRIENDS
public:
#else
protected:
    #if BOOST_WORKAROUND(BOOST_MSVC, < 1500)
        // for some inexplicable reason insertion of "class" generates compile erro
        // on msvc 7.1
        friend detail::interface_iarchive<Archive>;
        friend load_access;
    #else
        friend class detail::interface_iarchive<Archive>;
        friend class load_access;
    #endif
#endif
    template<class T>
    void load(T & t){
        basic_text_iprimitive<std::wistream>::load(t);
    }
    void load(version_type & t){
        unsigned int v;
        load(v);
        t = version_type(v);
    }
    void load(boost::serialization::item_version_type & t){
        unsigned int v;
        load(v);
        t = boost::serialization::item_version_type(v);
    }
    BOOST_WARCHIVE_DECL void
    load(char * t);
    #ifndef BOOST_NO_INTRINSIC_WCHAR_T
    BOOST_WARCHIVE_DECL void
    load(wchar_t * t);
    #endif
    BOOST_WARCHIVE_DECL void
    load(std::string &s);
    #ifndef BOOST_NO_STD_WSTRING
    BOOST_WARCHIVE_DECL void
    load(std::wstring &ws);
    #endif
    template<class T>
    void load_override(T & t){
        basic_text_iarchive<Archive>::load_override(t);
    }
    BOOST_WARCHIVE_DECL
    text_wiarchive_impl(std::wistream & is, unsigned int flags);
    ~text_wiarchive_impl(){};
};

} // namespace archive
} // namespace boost

#ifdef BOOST_MSVC
#pragma warning(pop)
#endif

#include <boost/archive/detail/abi_suffix.hpp> // pops abi_suffix.hpp pragmas

#ifdef BOOST_MSVC
#  pragma warning(push)
#  pragma warning(disable : 4511 4512)
#endif

namespace boost {
namespace archive {

class BOOST_SYMBOL_VISIBLE text_wiarchive :
    public text_wiarchive_impl<text_wiarchive>{
public:
    text_wiarchive(std::wistream & is, unsigned int flags = 0) :
        text_wiarchive_impl<text_wiarchive>(is, flags)
    {}
    ~text_wiarchive(){}
};

} // namespace archive
} // namespace boost

// required by export
BOOST_SERIALIZATION_REGISTER_ARCHIVE(boost::archive::text_wiarchive)

#ifdef BOOST_MSVC
#pragma warning(pop)
#endif

#endif // BOOST_NO_STD_WSTREAMBUF
#endif // BOOST_ARCHIVE_TEXT_WIARCHIVE_HPP

redpajama_set_name: RedPajamaGithub


text:
<?php

namespace HiPay\Fullservice\Gateway\Model;

use HiPay\Fullservice\Model\AbstractModel;

/**
 * Security Settings Model
 *
 * @package HiPay\Fullservice
 * @author Etienne Landais <elandais@hipay.com>
 * @copyright Copyright (c) 2018 - HiPay
 * @license http://www.apache.org/licenses/LICENSE-2.0 Apache 2.0 License
 * @link https://github.com/hipay/hipay-fullservice-sdk-php
 * @api
 */
class SecuritySettings extends AbstractModel
{
    /**
     * @var string hash algorithm used for signature
     */
    protected $hashingAlgorithm;

    /**
     * SecuritySettings constructor.
     * @param string $hashingAlgorithm
     */
    public function __construct($hashingAlgorithm)
    {
        $this->hashingAlgorithm = $hashingAlgorithm;
    }

    /**
     * @return string
     */
    public function getHashingAlgorithm()
    {
        return $this->hashingAlgorithm;
    }

    /**
     * @param string $hashingAlgorithm
     * @return void
     */
    public function setHashingAlgorithm($hashingAlgorithm)
    {
        $this->hashingAlgorithm = $hashingAlgorithm;
    }
}


text:
const fs = require('fs');

function getBootstraprcCustomLocation() {
    return process.env.BOOTSTRAPRC_LOCATION;
}

const bootstraprcCustomLocation = getBootstraprcCustomLocation();

let defaultBootstraprcFileExists;

try {
    fs.statSync('./.bootstraprc');
    defaultBootstraprcFileExists = true;
} catch ( e ) {
    defaultBootstraprcFileExists = false;
}

if ( !bootstraprcCustomLocation && !defaultBootstraprcFileExists ) {
    /* eslint no-console: 0 */
    console.log('You did not specify a \'bootstraprc-location\' ' +
        'arg or a ./.boostraprc file in the root.');
    console.log('Using the bootstrap-loader default configuration.');
}

let bootstrapProdEntryPoint;
if ( bootstraprcCustomLocation ) {
    bootstrapProdEntryPoint = 'bootstrap-loader/lib/bootstrap.loader?extractStyles' +
        `&configFilePath=${__dirname}/${bootstraprcCustomLocation}` +
        '!bootstrap-loader/no-op.js';
} else {
    bootstrapProdEntryPoint = 'bootstrap-loader/extractStyles';
}

module.exports = bootstrapProdEntryPoint;