The Impact of HVDC Links on Transmission System Collapse

Modern power systems are continually being expanded, are required to carry more power and are being increasingly interconnected. All of these increase the risk of wide area blackout.In 2003 the North America Blackout demonstrated that a HVDC link provides a ‘firewall’ against the system collapse propagating through a network. The HVDC link between Quebec and New York ensured that the system collapse did not progress beyond the HVDC interconnection interface. The objectives of this paper are to investigate contributions that integrate HVDC interconnections into AC networks. The simulation studies were performed using MATLAB

Simulation Combined Approach to Police Patrol Services Staffing

Motivated by the squeeze on public service expenditure, staffing is an important issue for service systems, which are required to maintain or even improve their service levels in order to meet general public demand. This paper considers Police Patrol Service Systems (PPSSs) where staffing issues are extremely serious and important because they have an impact on service costs, quality and public-safety. Police patrol service systems are of particularly interest because the demand for service exhibits large time-varying characteristics. In this case, incidents with different urgent grades have different targets of patrol officers’ immediate attendances. A new method is proposed which aims to determine appropriate staffing levels. This method starts at a refinement of the Square Root Staffing (SRS) algorithm which introduces the possibility of a delay in responding to a priority incident. Simulation of queueing systems will then be implemented to indicate modifications in shift schedules. The proposed method is proved to be effective on a test instance generated from real patrol activity records in a local police force

Body Knowledge and Uncertainty Modeling for Monocular 3D Human Body Reconstruction

While 3D body reconstruction methods have made remarkable progress recently, it remains difficult to acquire the sufficiently accurate and numerous 3D supervisions required for training. In this paper, we propose \textbf{KNOWN}, a framework that effectively utilizes body \textbf{KNOW}ledge and u\textbf{N}certainty modeling to compensate for insufficient 3D supervisions. KNOWN exploits a comprehensive set of generic body constraints derived from well-established body knowledge. These generic constraints precisely and explicitly characterize the reconstruction plausibility and enable 3D reconstruction models to be trained without any 3D data. Moreover, existing methods typically use images from multiple datasets during training, which can result in data noise (\textit{e.g.}, inconsistent joint annotation) and data imbalance (\textit{e.g.}, minority images representing unusual poses or captured from challenging camera views). KNOWN solves these problems through a novel probabilistic framework that models both aleatoric and epistemic uncertainty. Aleatoric uncertainty is encoded in a robust Negative Log-Likelihood (NLL) training loss, while epistemic uncertainty is used to guide model refinement. Experiments demonstrate that KNOWN's body reconstruction outperforms prior weakly-supervised approaches, particularly on the challenging minority images.Comment: ICCV 202

[(3R,4S)-4-(4-Fluoro­phen­yl)-1-methyl­piperidin-3-yl]methyl 4-methyl­benzene­sulfonate

In the title compound, C20H24FNO3S, the piperidine ring adopts a chair conformation. The dihedral angle between the aromatic rings is 47.01 (17)°

WMFormer++: Nested Transformer for Visible Watermark Removal via Implict Joint Learning

Watermarking serves as a widely adopted approach to safeguard media copyright. In parallel, the research focus has extended to watermark removal techniques, offering an adversarial means to enhance watermark robustness and foster advancements in the watermarking field. Existing watermark removal methods mainly rely on UNet with task-specific decoder branches--one for watermark localization and the other for background image restoration. However, watermark localization and background restoration are not isolated tasks; precise watermark localization inherently implies regions necessitating restoration, and the background restoration process contributes to more accurate watermark localization. To holistically integrate information from both branches, we introduce an implicit joint learning paradigm. This empowers the network to autonomously navigate the flow of information between implicit branches through a gate mechanism. Furthermore, we employ cross-channel attention to facilitate local detail restoration and holistic structural comprehension, while harnessing nested structures to integrate multi-scale information. Extensive experiments are conducted on various challenging benchmarks to validate the effectiveness of our proposed method. The results demonstrate our approach's remarkable superiority, surpassing existing state-of-the-art methods by a large margin

A simulation of a police patrol service system with multi-grade time-varying incident arrivals

Due to the squeeze on public expenditure, the funding cuts imposed on the police provide a great impetus to find an efficient incident response sequence with limited resources. This is especially the case for police response systems which exhibit the characteristics of time-varying volume of demand. In this paper, we investigate two types of priority queues in the patrol service system. Both the incident arrival rate and the scheduled staff level change with time. For such a system, there is no analytical model available to give close-form performance, so simulation is used for the study. Although dynamic priority queues which enable more flexibility in setting the sequence of service requests are widely applied in many service systems, such as the NHS service system, the simulation model results show that in police patrol service systems static priority queue performs better

Influencing operational policing strategy by predictive service analytics

Everyday there are growing pressures to ensure that services are delivered efficiently, with high levels of quality and with acceptability of regulatory standards. For the Police Force, their service requirement is to the public, with the police officer presence being the most visible product of this criminal justice provision. Using historical data from over 10 years of operation, this research demonstrates the benefits of using data mining methods for knowledge discovery in regards to the crime and incident related elements which impact on the Police Force service provision. In the UK, a Force operates over a designated region (macro-level), which is further subdivided into Beats (micro-level). This research also demonstrates differences between the outputs of micro-level and macro-level analytics, where the lower level analysis enables adaptation of the operational Policing strategy. The evidence base provided through the analysis supports decisions regarding further investigations into the capability of flexible neighbourhood policing practices; alongside wider operations i.e. optimal officer training times

Reward Imputation with Sketching for Contextual Batched Bandits

Contextual batched bandit (CBB) is a setting where a batch of rewards is observed from the environment at the end of each episode, but the rewards of the non-executed actions are unobserved, resulting in partial-information feedback. Existing approaches for CBB often ignore the rewards of the non-executed actions, leading to underutilization of feedback information. In this paper, we propose an efficient approach called Sketched Policy Updating with Imputed Rewards (SPUIR) that completes the unobserved rewards using sketching, which approximates the full-information feedbacks. We formulate reward imputation as an imputation regularized ridge regression problem that captures the feedback mechanisms of both executed and non-executed actions. To reduce time complexity, we solve the regression problem using randomized sketching. We prove that our approach achieves an instantaneous regret with controllable bias and smaller variance than approaches without reward imputation. Furthermore, our approach enjoys a sublinear regret bound against the optimal policy. We also present two extensions, a rate-scheduled version and a version for nonlinear rewards, making our approach more practical. Experimental results show that SPUIR outperforms state-of-the-art baselines on synthetic, public benchmark, and real-world datasets.Comment: Accepted by NeurIPS 202

FGF-23 and PTH levels in patients with acute kidney injury: A cross-sectional case series study

BackgroundFibroblast growth factor-23 (FGF-23), a novel regulator of mineral metabolism, is markedly elevated in chronic kidney disease and has been associated with poor long-term outcomes. However, whether FGF-23 has an analogous role in acute kidney injury is unknown. The goal of this study was to measure FGF-23 levels in critically ill patients with acute kidney injury to determine whether FGF-23 levels were elevated, as in chronic kidney disease.MethodsPlasma FGF-23 and intact parathyroid hormone (PTH) levels were measured in 12 patients with acute kidney injury and 8 control subjects.ResultsFGF-23 levels were significantly higher in acute kidney injury cases than in critically ill subjects without acute kidney injury, with a median FGF-23 level of 1948 RU/mL (interquartile range (IQR), 437-4369) in cases compared with 252 RU/mL (IQR, 65-533) in controls (p = 0.01). No correlations were observed between FGF-23 and severity of acute kidney injury (defined by the Acute Kidney Injury Network criteria); among patients with acute kidney injury, FGF-23 levels were higher in nonsurvivors than survivors (median levels of 4446 RU/mL (IQR, 3455-5443) versus 544 RU/mL (IQR, 390-1948; p = 0.02). Severe hyperparathyroidism (defined as intact PTH >250 mg/dL) was present in 3 of 12 (25%) of the acute kidney injury subjects versus none of the subjects without acute kidney injury, although this result did not meet statistical significance.ConclusionsWe provide novel data that demonstrate that FGF-23 levels are elevated in acute kidney injury, suggesting that FGF-23 dysregulation occurs in acute kidney injury as well as chronic kidney disease. Further studies are needed to define the short- and long-term clinical effects of dysregulated mineral metabolism in acute kidney injury patients