### Apache Airflow version

2.5.1

### What happened

I'd expect the `scheduler.tasks.running` metric to represent the number of running tasks, but it is always zero. It appears that #10956 broke this when it removed [the line that increments `num_tasks_in_executor`](https://github.com/apache/airflow/pull/10956/files#diff-bde85feb359b12bdd358aed4106ef4fccbd8fa9915e16b9abb7502912a1c1ab3L1363). Right now that variable is set to 0, never incremented, and the emitted as a gauge.

### What you think should happen instead

`scheduler.tasks.running` should either represent the number of tasks running or be removed altogether.

### How to reproduce

_No response_

### Operating System

Ubuntu 18.04

### Versions of Apache Airflow Providers

_No response_

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

from airflow.models.pool import Pool
        pools = Pool.slots_stats(session=session)
        for pool_name, slot_stats in pools.items():
            Stats.gauge(f"pool.open_slots.{pool_name}", slot_stats["open"])
            Stats.gauge(f"pool.queued_slots.{pool_name}", slot_stats["queued"])
            Stats.gauge(f"pool.running_slots.{pool_name}", slot_stats["running"])
            
            Stats.gauge("pool.open_slots", slot_stats["open"], tags={"pool_name": pool_name})
            Stats.gauge("pool.queued_slots", slot_stats["queued"], tags={"pool_name": pool_name})
            Stats.gauge("pool.running_slots", slot_stats["running"], tags={"pool_name": pool_name})
    @provide_session
    def adopt_or_reset_orphaned_tasks(self, session: Session = NEW_SESSION) -> int:
        """
        Reset any TaskInstance still in QUEUED or SCHEDULED states that were
        enqueued by a SchedulerJob that is no longer running.
        :return: the number of TIs reset
        """
        self.log.info("Resetting orphaned tasks for active dag runs")
        timeout = conf.getint("scheduler", "scheduler_health_check_threshold")
        for attempt in run_with_db_retries(logger=self.log):
            with attempt:
                self.log.debug(
                    "Running SchedulerJob.adopt_or_reset_orphaned_tasks with retries. Try %d of %d",
                    attempt.retry_state.attempt_number,
                    MAX_DB_RETRIES,
                )
                self.log.debug("Calling SchedulerJob.adopt_or_reset_orphaned_tasks method")