Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Level of Service of Toll Lane Allocation of Hong Kong-Zhuhai-Macao Bridge

Hong Kong-Zhuhai-Macao Bridge is a world-class sea channel, and this research analyzed the level of service and capacity of the toll plaza of this bridge. The delay and queue length under two different charging methods, namely, Manual Toll Collection (MTC) and Electronic Toll Collection (ETC), in different volume forecast years were analyzed with a traffic simulation method. Based on the operation indicators, the levels of service in different traffic demands of the toll plaza were evaluated. Furthermore, the capacities of the toll lane combinations of MTC and ETC were calculated using theoretical formulas, and toll lane allocation under different traffic demands was recommended. This research can provide a useful reference to management for decision making.
Modeling Structure and Country-specific Heterogeneity in Misclassification Matrices of Verbal Autopsy-based Cause of Death Classifiers

Verbal autopsy (VA) algorithms are routinely used to determine individual-level causes of death (COD) in many low-and-middle-income countries, which are then aggregated to derive population-level cause-specific mortality fractions (CSMF), essential to informing public health policies. However, VA algorithms frequently misclassify COD and introduce bias in CSMF estimates. A recent method, VA-calibration, can correct for this bias using a VA misclassification matrix estimated from paired data on COD from both VA and minimally invasive tissue sampling (MITS) from the Child Health and Mortality Prevention Surveillance (CHAMPS) Network. Due to the limited sample size, CHAMPS data are pooled across all countries, implicitly assuming that the misclassification rates are homogeneous. In this research, we show that the VA misclassification matrices are substantially heterogeneous across countries, thereby biasing the VA-calibration. We develop a coherent framework for modeling country-specific misclassification matrices in data-scarce settings. We first introduce a novel base model based on two latent mechanisms: intrinsic accuracy and systematic preference to parsimoniously characterize misclassifications. We prove that they are identifiable from the data and manifest as a form of invariance in certain misclassification odds, a pattern evident in the CHAMPS data. Then we expand from this base model, adding higher complexity and country-specific heterogeneity via interpretable effect sizes. Shrinkage priors balance the bias-variance tradeoff by adaptively favoring simpler models. We publish uncertainty-quantified estimates of VA misclassification rates for 6 countries. This effort broadens VA-calibration's future applicability and strengthens ongoing efforts of using VA for mortality surveillance.
China's quantitative expansion phase: exponential growth but low impact

It is shown that although China’s publication share in the world has been increasing exponentially, its impact defined as the number of citations per publication lags far behind. This state of affairs is expressed as a ‘quantitative expansion phase’. China’s science needs to move from the ‘quantitative expansion’ phase in which it is nowadays to a ‘rising quality’ phase. Correspondingly scientists’ motivation for publishing papers must shift from ‘driven by benefit’ to ‘driven by excellence and timeliness’. Currently, China’s science although blending into the world, is not yet a full player in its major league. Yet, all growth-related graphs show an exponential increase. Moreover, doubling times calculated in this article are clear indications that, despite obvious problems and short-comings, the quality of Chinese research as a whole is increasing very quickly. We conclude that, if the necessary measures are taken and the observed exponentially increasing trend continues, the impact of Chinese research results will soon catch up with that of other major countries.
An Extended Generalized Super-Twisting Algorithm for Estimating Key Biochemical Variables in Bioprocesses

In order to improve the behavior of any bioprocess, it is required to know some of its key biochemical variables, such as the reaction rates and the influent feeding rates. However, these variables are hard to measure, challenging to describe mathematically, or can be the source of unknown disturbances. Moreover, even though many unknown input observers were designed for their estimation, their convergence cannot be modified. In this work, an extended generalized super-twisting algorithm is designed to simultaneously estimate reaction rates and influent feeding rates in finite time. For this task, a change of variables is used, valid if the dilution rate is strictly positive. The proposed algorithm is applied on an alcoholic fermentation process, and simulated results show a good performance from the design observer.
Energy Efficient Bio-Inspired Clustering in Flying Ad-Hoc Network

The Flying Ad hoc NETworks (FANETs) have evolved from the interaction of multiple unmanned aerial vehicles (UAV s) in ad hoc fashion to provide a versatility of applications and services in civilian and military domains. As it ensures cooperation and collaboration between these UAVs, Communication is one of the most crucial issues in the design of FANETs systems. However, the limited resources, in terms of energy, bandwidth utilization, and the mobility patterns of the flying UAVs should be considered when ensuring the information's reliability. This research aims to investigate the routing issue in FANET systems while considering the constraining features presented by these latter. Here, we proposed a new clustering and mobility management strategy for robust data routing in FANETs relying on combining k-means and black-hole algorithms. The simulation of the proposed protocol conducted using Network Simulator 3 (NS3) has yielded convincing results in terms of energy consumption and data communication, outperforming those exhibited by the referred protocols.
Viscous rebound of a quasi-2D cylinder on a solid wall

The purpose of the present study is to extend the simple concept of apparent coefficient of restitution, widely approached in the literature for the case of a single-contact-point between a sphere and a wall, to the case of bouncing whose complexity is increased due to the shape of the contacting object. Experiments are carried out with a finite-length cylinder, freely falling in a liquid at rest. Complex 3D motions of the cylinder with respect to the wall occur during bouncing, including multi-contact-points between the cylinder and the bottom as well as cavitation. We investigate numerical modelling of an idealized situation (2D infinite cylinder falling parallel to the wall) with 2D simulations where the fluid equations of motion were coupled to the particle equation of motion through an Immersed Boundary Method. The particle equation of motion is coupled to an elastic force to model bouncing, requiring a parameterization of the cut-off length (interpreted as a roughness) and the contact time (associated with the contact elasticity) used here to capture the experimental observations. The simulations confirmed that i) the departure of the coefficient of restitution from 0 is strictly dependent on the apparent roughness and ii) the coefficient of restitution depends on the contact time. Finally, we model the coefficient of restitution as the product of two contributions to the mechanical loss of energy: the collision-to-terminal velocity ratio ($V_c/V_t$) of the approach-phase and the rebound-to-collision velocity ratio ($-V_r/V_c$) of the contact-phase. This leads to a reasonably good prediction of the coefficient of restitution in the intermediate regime in $St$. This suggests the relevance of lumping the complex details of physical phenomena involved during contact into a simple concept based on the contact apparent roughness and elasticity.
High-definition transcranial direct current stimulation for upper extremity rehabilitation in moderate-to-severe ischemic stroke: a pilot study

Introduction Previous studies found that post-stroke motor impairments are associated with damage to the lesioned corticospinal tract (CST) and hyperexcitability of the contralesional cortico-reticulospinal tract (CRST). This proof-of-concept study aims to develop a non-invasive brain stimulation protocol that facilitates the lesioned CST and inhibits the contralesional CRST to improve upper extremity rehabilitation in individuals with moderate-to-severe motor impairments post-stroke. Methods Fourteen individuals (minimum 3 months post ischemic stroke) consented. Physician decision of the participants baseline assessment qualified eight to continue in a randomized, double-blind cross-over pilot trial (ClinicalTrials.gov Identifier: NCT05174949) with: (1) anodal high-definition transcranial direct stimulation (HD-tDCS) over the ipsilesional primary motor cortex (M1), (2) cathodal HD-tDCS over contralesional dorsal premotor cortex (PMd), (3) sham stimulation, with a two-week washout period in-between. Subject-specific MR images and computer simulation were used to guide HD-tDCS and verified by Transcranial Magnetic Stimulation (TMS) induced Motor Evoked Potential (MEP). The motor behavior outcome was evaluated by an Fugl-Meyer Upper Extremity score (primary outcome measure) and the excitability of the ipslesoinal CST and contralesional CRST was determined by the change of MEP latencies and amplitude (secondary outcome measures). Results The baseline ipsilesional M1 MEP latency and amplitude were correlated with FM-UE. FM-UE scores were improved post HD-tDCS, in comparison to sham stimulation. Both anodal and cathodal HD-tDCS reduced the latency of the ipsilesional M1 MEP. The contralesional PMd MEP disappeared/delayed after HD-tDCS. Discussion These results suggest that HD-tDCS could improve the function of the lesioned corticospinal tract and reduce the excitability of the contralesional cortico-reticulospinal tract, thus, improving motor function of the upper extremity in more severely impaired individuals.
The Ableist and White Supremacist Origins of U.S. Policing and Connections to Involuntary Hospitalization

Abstract This paper discusses the impact of White supremacy, ableism, and U.S. policing on both the history and current state of psychology and sheds light on ways that psychologists can acknowledge and divest from carceral White supremacist practices in mental healthcare. Because of how oppression and intersectionality function within a White supremacist society, not all Black lives have been equally valued by non-Black Americans. Similarly, White supremacy and ableism have had lasting impacts on the public perception of disabled people. Connecting the historical origins of the U.S. policing system to the current practices of the U.S. police system, this paper argues that the police have always been about controlling “disorder. ” Similarly, psychology and the larger mental health field have a troubled history of controlling Black, Brown, and disabled bodies. Recommendations for ways therapists can unlearn therapy practices stemming from White supremacy cultural practices (e.g., carceral therapeutic practices and biased mental health care) are provided along with action items for mental health practitioners to maintain a commitment to undoing the harm from these historic and systemic issues.
Transient Characteristics of Negative Sequence Suppression in Offshore Wind Power Integrated via VSC-HVDC

The offshore AC system is a passive system without any synchronous power supply. The offshore converter station provides a stable voltage and frequency source for the system. Both ends of the system are power electronic converters with different negative-sequence suppression (NSS) strategies, which significantly influence the transient response characteristics at the point of common coupling and the convergence bus of wind farms. Thus, the fault characteristics and fault ride-through characteristics of the offshore AC system are determined by the control modes and negative-sequence suppressions. A real-time-digital-simulation platform of offshore wind power integrated via VSC-HVDC system is constructed according to the actual topology and parameters of Rudong project. Based on the platform, the configuration program and control objectives of existing NSS strategies are explicated. The influences of NSS on fault characteristics and fault ride-through characteristics are revealed.
Reconfigurable-Intelligent-Surface-Aided Space-Shift Keying With Imperfect CSI

In this article, we investigate the performance of reconfigurable intelligent surface (RIS)-aided spatial shift keying (SSK) wireless communication systems with imperfect channel state information (CSI). Specifically, we study the average bit error probability (ABEP) of two RIS-SSK systems based on intelligent reflection and blind reflection modes. For the intelligent RIS-SSK scheme, we first derive the conditional pairwise error probability of the composite channel through maximum-likelihood (ML) detection. Subsequently, we derive the probability density function of the combined channel. Due to the intricacies of the composite channel formulation, an exact closed-form ABEP expression is unattainable through direct derivation. To this end, we resort to employing the Gaussian–Chebyshev quadrature method to estimate the results. Additionally, we employ $Q$ -function approximation to derive the nonexact closed-form expression in the presence of channel estimation errors. For the blind RIS-SSK scheme, we derive both closed-form ABEP expression and asymptotic ABEP expression with imperfect CSI by adopting the ML detector. To offer deeper insights, we explore the impact of discrete reflection phase shifts on the performance of the RIS-SSK system. Finally, we extensively validate all the analytical derivations via Monte Carlo simulations.
How Are Spring Snow Conditions in Central Canada Related to Early Warm-Season Precipitation?

AbstractThe response of the warm-season atmosphere to antecedent snow anomalies has long been an area of study. This paper explores how the spring snow depth relates to subsequent precipitation in central Canada using ground observations, reanalysis datasets, and offline land surface model estimates. After removal of low-frequency ocean influences, April snow depth is found to correlate negatively with early warm-season (May–June) precipitation across a large portion of the study area. A chain of mechanisms is hypothesized to account for this observed negative relation: 1) a snow depth anomaly leads to a soil moisture anomaly, 2) the subsequent soil moisture anomaly affects ground turbulent fluxes, and 3) the atmospheric vertical structure allows dry soil to promote local convection. A detailed analysis supports this chain of mechanisms for those portions of the domain manifesting a statistically significant negative snow–precipitation correlation. For a portion of the study area, large-scale atmospheric .
Finger-Vein Recognition Using ResNet with Elastic Margin Loss

As technology evolves, people are starting to value the safety of their personal information more than ever. However, traditional keys and passwords as security features are subject to vulnerabilities, prompting a flux of new methods of biometric recognition with deep learning (DL). We proposed the RestNet model and elastic margin loss to perform a finger-vein recognition system. Experimental results indicated that the proposed DL architecture showed that precision, recall, F1-score, and accuracy metrics were higher than 99% in the FV-USM dataset.
A 1-5GHz Inverter-Based Phase Interpolator with All Digital Control for Spin-Wave Detection Circuit

This paper represents a wide-band inverter-based phase interpolator (PI) designed for spin-wave detection circuit with all digital control. The proposed PI consists of a phase selector for selecting two input phases, a band selector to control the slew rate for good linearity in wide operating frequency range, and a phase mixer for output phase tuning. The circuit is implemented in 65nm CMOS technology and operates from 1GHz to 5GHz, with 1V supply. The power consumption of the proposed PI core is 2.78mW at 5GHz. The measured differential non-linearity and integral non-linearity are 3.2 LSB and -10.4 LSB respectively at the worst case.
Enhancing Auditory Immersion in Interactive Virtual Reality Environments

The realm of sound remains relatively underexplored in comparison to its visual counterpart within the context of interactive virtual reality (IVR). It is a well-known practice to create a digital representation of the user’s human body in the virtual space, thereby enhancing human-computer interaction and facilitating navigation amid fellow users and objects within these environments, commonly referred to as avatars. Human sensory feedback is predominantly oriented towards visual stimuli. The sonic design, presence and interactions of avatars are often neglected in research. However, a more accurate representation of the virtual body, both visual and sonic, can increase immersion and the overall effectiveness of the user experience.By studying how users react to their own sonic environments and to the sounds created by themselves/their avatars, developers could create more personalized scenarios for IVR applications. To the best of my knowledge, there is still a lot to explore in this field.The goal of this research is to investigate the effects of sonic interactions between humans and computers in VR, where the users have six degrees of freedom to interact with their environment. This doctoral research aims to find the answers to the following questions: How can auditory immersion be enhanced in IVR? How do interactive sounds affect body ownership in a virtual environment? How do procedurally generated sounds affect the agency of the user in IVR? The focus of this study will be on finding ways to enhance the plausibility illusion experienced by the users, which allows them to believe that the given scenario is truly happening, even though they know it is not real. Both sample-based, and procedural audio productions will be explored to create a more effective user experience. Advancements in this field of study could be applied for both entertainment, serious games, health, and other IVR applications, to increase their desired impact.
Breaking barriers in antibody discovery: harnessing divergent species for accessing difficult and conserved drug targets

ABSTRACT To exploit highly conserved and difficult drug targets, including multipass membrane proteins, monoclonal antibody discovery efforts increasingly rely on the advantages offered by divergent species such as rabbits, camelids, and chickens. Here, we provide an overview of antibody discovery technologies, analyze gaps in therapeutic antibodies that stem from the historic use of mice, and examine opportunities to exploit previously inaccessible targets through discovery now possible in alternate species. We summarize the clinical development of antibodies raised from divergent species, discussing how these animals enable robust immune responses against highly conserved binding sites and yield antibodies capable of penetrating functional pockets via long HCDR3 regions. We also discuss the value of pan-reactive molecules often produced by these hosts, and how these antibodies can be tested in accessible animal models, offering a faster path to clinical development.
PH-shape: an adaptive persistent homology-based approach for building outline extraction from ALS point cloud data

Building outline extraction from segmented point clouds is a critical step of building footprint generation. Existing methods for this task are often based on the convex hull and α-shape algorithm. There are also some methods using grids and Delaunay triangulation. The common challenge of these methods is the determination of proper parameters. While deep learning-based methods have shown promise in reducing the impact and dependence on parameter selection, their reliance on datasets with ground truth information limits the generalization of these methods. In this study, a novel unsupervised approach, called PH-shape, is proposed to address the aforementioned challenge. The methods of Persistence Homology (PH) and Fourier descriptor are introduced into the task of building outline extraction. The PH from the theory of topological data analysis supports the automatic and adaptive determination of proper buffer radius, thus enabling the parameter-adaptive extraction of building outlines through buffering and “inverse” buffering. The quantitative and qualitative experiment results on two datasets with different point densities demonstrate the effectiveness of the proposed approach in the face of various building types, interior boundaries, and the density variation in the point cloud data of one building. The PH-supported parameter adaptivity helps the proposed approach overcome the challenge of parameter determination and data variations and achieve reliable extraction of building outlines.
The statistical analysis of compositional data

The simplex plays an important role as sample space in many practical situations where compositionaldata, in the form ofproportions ofsome whole,require interpretation. It is argued that the statistical analysisofsuch data has proved difficult becauseofa lack both ofconcepts of independenceand of rich enough parametric classesofdistributions in the simplex. A variety of independence hypotheses are introduced and interrelated, and new classesoftransformed-normal distributions in the simplexare provided as models within whichthe independencehypothesescan be tested through standard theory of parametric hypothesis testing. The new concepts and statistical methodology are illustrated by a number of applications. marginal tests indicate evidence of departure from additive logistic normality the other tests show no such evidence. Secondly, zero components in 14 of the samples were replaced by proportions 0,0005, half the lowest recorded value, before analysis. We shall return to this problem of zeros in Section 7.4.
Point & Portal: A New Action at a Distance Technique For Virtual Reality

This paper introduces Point & Portal, a novel Virtual Reality (VR) interaction technique, inspired by Point & Teleport. This new technique enables users to configure portals using pointing actions, and supports seamless action at a distance and navigation without requiring line of sight. By supporting multiple portals, Point & Portalenables users to create dynamic portal configurations to manage multiple remote tasks. Additionally, this paper introduces Relative Portal Positioning for reliable portal interactions, and the concept of maintaining Level Portals. In a comparative user study, Point & Portal demonstrated significant advantages over the traditional Point & Teleport technique to bring interaction devices within-arm’s reach. In the presence of obstacles, Point & Portal exhibited faster speed, lower cognitive load and was preferred by participants. Overall, participants required less physical movement, pointing actions, and reported higher involvement and “good” usability.