A potential third-generation gravitational-wave detector based on autocorrelative weak-value amplification

Reducing noises and enhancing signal-to-noise ratios (SNRs) have become critical for designing third-generation gravitational-wave (GW) detectors with a GW strain of less than $10^{-23}$/$\rm \sqrt{Hz}$. In this paper, we propose a potential third-generation GW detector based on autocorrelative weak-value amplification (AWVA) for GW detection with a strain of $h_g =$ $4 \times 10^{-25}$/$\rm \sqrt{Hz}$. In our scheme, a GW event induces a phase difference $\Delta \phi$ by passing through an 11-bounce delay line, 10-km arm-length, zero-area Sagnac interferometer illuminated with a 1064-nm laser. Subsequently, $\Delta \phi$ is amplified as the parameter of post-selection by choosing the appropriate pre-selected state and coupling strength in AWVA. In particular, we theoretically investigate the AWVA measurements for GW detection within the frequency band of 200 Hz $\leq$ $f_g$ $\leq$ 800 Hz, considering Gaussian noises with negative-decibel SNRs. The peak response of the AWVA sensitivity $\kappa(f_g)$ occurs at frequency $f_{g, max}$ = 500 Hz, which falls within the frequency band of interest of the current third-generation GW detectors. Our simulation results indicate that AWVA can demonstrate a measurable sensitivity of $\Theta(f_g)$ within the frequency band of interest. Moreover, the robustness of WVA shows promising potential in mitigating the effects of Gaussian noises.Comment: 21 pages, 6 figure

Data-Driven Distributionally Robust Electric Vehicle Balancing for Autonomous Mobility-on-Demand Systems under Demand and Supply Uncertainties

Electric vehicles (EVs) are being rapidly adopted due to their economic and societal benefits. Autonomous mobility-on-demand (AMoD) systems also embrace this trend. However, the long charging time and high recharging frequency of EVs pose challenges to efficiently managing EV AMoD systems. The complicated dynamic charging and mobility process of EV AMoD systems makes the demand and supply uncertainties significant when designing vehicle balancing algorithms. In this work, we design a data-driven distributionally robust optimization (DRO) approach to balance EVs for both the mobility service and the charging process. The optimization goal is to minimize the worst-case expected cost under both passenger mobility demand uncertainties and EV supply uncertainties. We then propose a novel distributional uncertainty sets construction algorithm that guarantees the produced parameters are contained in desired confidence regions with a given probability. To solve the proposed DRO AMoD EV balancing problem, we derive an equivalent computationally tractable convex optimization problem. Based on real-world EV data of a taxi system, we show that with our solution the average total balancing cost is reduced by 14.49%, and the average mobility fairness and charging fairness are improved by 15.78% and 34.51%, respectively, compared to solutions that do not consider uncertainties.Comment: 16 page

Auto-correlative weak-value amplification under strong noise background

In the general optical metro-logical protocols based on the weak-value amplification(WVA) approach, it is beneficial to choose the pre-selected state and the post-selected one to be nearly orthogonal for improving the sensitivity. However, the orthogonality of the post-selection decreases the probability of detecting photons and makes the weak measurement difficult, especially when there is strong noise background and the pointer is drowned in noise. In this article, we investigate a modified weak measurement protocol with a temporal pointer, namely, the auto-correlative weak-value amplification (AWVA) approach. We find it can significantly improve the precision of optical metrology under Gaussian white noise, especially with a negative signal-to-noise ratio. With the AWVA approach, a small longitudinal time delay (tiny phase shift) $\tau$ of a Gaussian pulse is measured by implementing two auto-correlative weak measurements. The small quantities are obtained by measuring the auto-correlation coefficient of the pulses instead of fitting the shift of the mean value of the probe. Simulation results show that the AWVA approach outperforms the standard WVA technique in the time domain, remarkably increasing the precision of weak measurement under strong noise background.Comment: 15 pages, 10 figure

Effects of Voluntary Wheel-Running Types on Hippocampal Neurogenesis and Spatial Cognition in Middle-Aged Mice

While increasing evidence demonstrated that voluntary wheel running promotes cognitive function, little is known on how different types of voluntary wheel running affect cognitive function in elderly populations. We investigated the effects of various voluntary wheel-running types on adult hippocampal neurogenesis and spatial cognition in middle-aged mice. Male C57BL6 and Thy1-green fluorescent protein (GFP) transgenic mice (13 months) were equally assigned to one of the following groups: (1) T1: no voluntary wheel running; (2) T2: intermittent voluntary wheel running; and (3) T3: continuous voluntary wheel running. The Thy1-GFP transgenic mice were used to specifically label granule cells, since Thy-1 is a promoter for neuronal expression. Behavioral evaluations suggested that intermittent voluntary wheel running improved Morris water maze performance in middle-aged mice. The number of BrdU-positive cells was significantly higher in both intermittent and continuous voluntary wheel running compared with no voluntary wheel running. However, only intermittent voluntary wheel running facilitated the newborn cells to differentiate into granule cells, while newborn cells tended to differentiate into astrocytes and repopulation of microglia was also enhanced in the continuous voluntary wheel-running group. These results indicated that intermittent voluntary exercise may be more beneficial for enhancing spatial memory. Effective improvement of hippocampal neurogenesis was also caused by intermittent voluntary wheel running in middle-aged mice

Ketogenic Diet as a Treatment for Super-Refractory Status Epilepticus in Febrile Infection-Related Epilepsy Syndrome

Background: Febrile infection-related epilepsy syndrome (FIRES) is a fatal epileptic encephalopathy associated with super-refractory status epilepticus (SRSE). Several treatment strategies have been proposed for this condition although the clinical outcomes are poor. Huge efforts from neurointensivists have been focused on identifying the characteristics of FIRES and treatment to reduce the mortality associated with this condition. However, the role of ketogenic diet (KD) in FIRES is not fully understood.Methods: We performed a retrospective review of patients who met the diagnostic criteria of FIRES, SRSE, and were treated with KD between 2015 and 2018 at the Department of Pediatrics, Xiangya Hospital of Central South University. The following data were recorded: demographic features, clinical presentation, anticonvulsant treatment, timing and duration of KD and follow-up information. Electroencephalography recordings were reviewed and analyzed.Results: Seven patients with FIRES were put on KD (5 via enteral route, and 2 via intravenous line) for SRSE in the PICU. The median age was 8. Four patients were male and 3 were female. Although patients underwent treatment with a median of 4 antiepileptic drugs and 2 anesthetic agents, the status epilepticus (SE) persisted for 7–31 days before KD initiation. After KD initiation, all patients achieved ketosis and SE disappeared within an average of 5 days (IQR 3.5), although there were minor side effects. In 6 patients, a unique pattern was identified in the EEG recording at the peak period. After initiation of KD, the number of seizures reduced, the duration of seizure shortened, the background recovered and sleep architecture normalized in the EEG recordings. The early initiation of KD (at the onset of SE) in the acute phase of patients decreased the mRS score in the subsequent period (p = 0.012, r = 0.866).Conclusions: The characteristic EEG pattern in the acute phase promoted timely diagnosis of FIRES. Our data suggest that KD may be a safe and promising therapy for FIRES with SRSE, and that early initiation of KD produces a favorable prognosis. Therefore, KD should be applied earlier in the course of FIRES. Intravenous KD can be an effective alternative route of administration for patients who may not take KD enterally

Synaptopathology Involved in Autism Spectrum Disorder

Autism spectrum disorder (ASD) encompasses a group of multifactorial neurodevelopmental disorders characterized by impaired social communication, social interaction and repetitive behaviors. ASD affects 1 in 59 children, and is about 4 times more common among boys than among girls. Strong genetic components, together with environmental factors in the early stage of development, contribute to the pathogenesis of ASD. Multiple studies have revealed that mutations in genes like NRXN, NLGN, SHANK, TSC1/2, FMR1, and MECP2 converge on common cellular pathways that intersect at synapses. These genes encode cell adhesion molecules, scaffolding proteins and proteins involved in synaptic transcription, protein synthesis and degradation, affecting various aspects of synapses including synapse formation and elimination, synaptic transmission and plasticity. This suggests that the pathogenesis of ASD may, at least in part, be attributed to synaptic dysfunction. In this article, we will review major genes and signaling pathways implicated in synaptic abnormalities underlying ASD, and discuss molecular, cellular and functional studies of ASD experimental models