Miracle-dz/UniFAR-FTUs huggingface dataset:
VPRNet: Voxel-based Efficient and Partial-to-Partial Point Cloud Registration on Mobile Devices

With the popularity of embedded devices such as LIDAR sensors and depth cameras, the resulting point clouds become the main data format for representing the 3D world and spawn various smart mobile applications. A key technology for enabling these applications to furnish high-quality services is real-time point cloud registration on mobile devices, which synthesizes a complete model or a large-scale scene from multiple partial scans. It aims to deliver increasing sensing range, faster 3D reconstruction and more robust robot navigation. Unfortunately, the performance of these applications is limited by the scale and partial loss of raw point cloud frame. The existing solutions for point cloud registration are difficult to deploy on mobile devices due to their complex models and assumptions about point cloud pairs with large overlap, which cause significant delay and inaccuracy. This paper proposes VPRNet - the first voxel-based registration solution that can achieve real-time partial-to-partial registration with competitive registration quality while being more advantageous for large-scale point clouds on mobile devices. We conduct real-world experiments and extensive simulations cross various datasets and platforms to validate the efficacy of VPRNet and further compare the performance with state-of-the-art approaches.
Toward a Fundamental Understanding of SQL Education

Relational databases are ubiquitous in industry and have been for several decades. As such, almost all Computer Science bachelor degrees include one or more courses that teach about databases and their corresponding query language called Structured Query Language (SQL). However, many learners struggle with learning the language, making many mistakes and finding the problems hard to solve. In this paper, we explore the research done to identify learners’ issues as well as showcase some research that can support these learners.
Managing across diverse cultures in East Asia : issues and challenges in a changing globalized world

Part 1: Introduction 1. Managing Across Diverse Cultures in East Asia: Introduction Malcolm Warner Part 2: Themes 2. East Asian Economy: An Overview Dilip X. Das 3. East Asian Culture: An Overview Mischo Minkov 4. East Asian Management: An Overview Keith Jackson Part 3: Societal Case-Studies 5. The Changing Nature of Management and Culture in China Shuming Zhao and Juan Du 6. The Changing Nature of Management and Culture in Hong Kong, Macau and Taiwan Olivia Ip and Sek-Hong Ng 7. The Changing Nature of Management and Culture in Japan John Benson and Philippe Debroux 8. The Changing Nature of Management and Culture South Korea Chris Rowley Part 4: Issues and Challenges in East Asian Management 9. Gender and Management in East Asia Fang Lee Cooke 10. Continuity and Change in Guanxi Networks in East Asia Jane Nolan 11. East Asian Business Systems in Transition Michael A. Witt 12. SMEs in Selected Economies in East Asia Li Xue Cunningham 13. HRM Strategies, Informality and Re-regulation in East Asian Employment Relations Sarosh Kuruvilla and Sun-wook Chung 14. Management and Culture in East, South East and South Asia Shaista Khilji 15. Management Education and Training in East Asia: China, Japan and South Korea Malcolm Warner Part 5: The Future and Conclusions 16. The Future of East Asian Management Rosalie L. Tung 17. Managing Across Diverse Cultures in East Asia: Conclusions Malcolm Warner
Dirichlet Laplacian in a thin twisted strip

Let [Formula: see text] be a two-dimensional, infinite and twisted strip in [Formula: see text]. Consider [Formula: see text] the Dirichlet Laplacian operator in [Formula: see text]. At first, we find the effective operator when the transversal sections of [Formula: see text] tend to zero. Then, assuming that [Formula: see text] is thin enough, we show some situations where the discrete spectrum [Formula: see text] is nonempty; an asymptotic behavior for the eigenvalues is also found. In particular, we study the case where the twisted effect “grows” at infinity.
Rasgos Morfológicos Dentales Coronales en dentición temporal y permanente: Distancia biológica entre tres grupos indígenas del Amazonas Colombiano

Objetivos: Determinar la frecuencia y variabilidad de doce rasgos morfológicos dentales coronales (Winging, incisivos centrales y laterales en pala, doble pala, cúspide de Carabelli, patrón cuspídeo, número de cúspides, cresta distal del trigónido, pliegue acodado, protostílido, cúspide 6 y cúspide 7), en dientes temporales (ui1/ui2/um2/lm2) y permanentes (UI1/UI2/ UM1/LM1), para comprender la influencia étnica y la distancia biológica de tres grupos indígenas del Amazonas Colombiano. Material y métodos: Se realizó un estudio descriptivo cuantitativo para observar la frecuencia y variabilidad de doce rasgos morfológicos dentales coronales mediante los sistemas Hanihara, Dahlberg, Sciulli, Grine y ASUDAS en 96 modelos de niños de ambos sexos, en dentición mixta y pertenecientes a los grupos Ticuna, Huitoto y Cocama. Resultados: Fueron observadas altas frecuencias de winging, incisivos centrales y laterales en pala, de las formas surco y fosa de la cúspide de Carabelli, patrón cuspídeo Y6 o Y7, pliegue acodado, protostílido y cúspide 6, típicas de la morfología dental del complejo dental Mongoloide - subdivisión Sinodonte. Se apreciaron frecuencias significativas del patrón cuspídeo +6 y +7, y de la cúspide, 7 lo cual sugiere mestizaje. Existe afinidad biológica entre las tres etnias, y fue demostrada la simetría bilateral y ausencia de dimorfismo sexual.
Systematic Literature Review on Adoption of E-government among Employees in the Public Sector

Government worldwide has adopted e-government into their organizations to improve the efficiency and effectiveness of service delivery to citizens. However, the non-adoption behavior among public-sector employees is hampering the digitalization effort. This issue has attracted several researchers to conduct a study on e-government adoption among employees in the public sector. Although numerous studies are being conducted on e-government adoption among employees, the effort made to review this topic is still scarce and limited. Nevertheless, only scant researchers have made an effort to review this topic systematically. Therefore, this study aims to conduct a systematic literature review concerning the adoption of an e-government system among employees in the public sector. PRISMA guided the review process. This SLR consists of the following methodological steps: formulating research questions, systematic searching strategies based on identification, screening, and eligibility on established databases (Scopus), then data extraction and analysis. Three main themes were identified through thematic analysis, namely (1) human factors, (2) technical factors, and (3) organizational factors. This review aims to provide reliable knowledge and ideas for academics and practitioners to implement e-government strategies in governmental agencies effectively. Although this study was only restricted to the review, it would provide a valuable basis for empirical research in the future.
Effects of Urgency and Cognitive Load on Interaction in Highly Automated Vehicles

In highly automated vehicles, passengers can engage in non-driving-related activities. Additionally, the technical advancement allows for novel interaction possibilities such as voice, gesture, gaze, touch, or multimodal interaction, both to refer to in-vehicle and outside objects (e.g., thermostat or restaurant). This interaction can be characterized by levels of urgency (e.g., based on late detection of objects) and cognitive load (e.g., because of watching a movie or working). Therefore, we implemented a Virtual Reality simulation and conducted a within-subjects study with N=11 participants evaluating the effects of urgency and cognitive load on modality usage in automated vehicles. We found that while all modalities were possible to use, participants relied on touch the most. This was followed by gaze, especially for external referencing. This work helps to further understand multimodal interaction and the requirements this poses on natural interaction in (automated) vehicles.
DAG-Aware Optimization for Geo-Distributed Data Analytics

Geo-distributed data analytics has been proposed to analyze geographically distributed data. Existing studies have achieved significant reductions in execution time and data transfer cost ($) of data analytics jobs by optimizing task placement. Given a directed acyclic graph (DAG)-style job, however, they mainly optimize each stage independently, and they tend to distribute tasks and intermediate data across all locations, potentially inflating execution time and data transfer cost of descendent stages and the whole job. In this paper, we propose a DAG-aware approach to minimize job data transfer costs while guaranteeing job execution time. Specifically, we design a two-phase static/runtime algorithm that is both lightweight and adaptive to dynamics. The static phase estimates the optimal placement of all stages in the job, minimizing the job data transfer cost. Then for each stage ready to be executed, the runtime phase re-optimizes its task placement based on the static task placement of child stages and runtime information. It minimizes the stage data transfer cost while incorporating the stage execution time with a simple control knob. Overall, our approach properly aggregates early-stage tasks to fewer data centers, thereby reducing subsequent stages and whole job data transfer cost and execution time. We implement our approach in Spark and evaluate it across geo-distributed datacenters. Our approach reduces application data transfer cost by up to 91% without increasing job execution time compared to existing baselines.
Adapting Visual Complexity Based on Electrodermal Activity Improves Working Memory Performance in Virtual Reality

Biocybernetic loops encompass users' state detection and system adaptation based on physiological signals. Current adaptive systems limit the adaptation to task features such as task difficulty or multitasking demands. However, virtual reality allows the manipulation of task-irrelevant elements in the environment. We present a physiologically adaptive system that adjusts the virtual environment based on physiological arousal, i.e., electrodermal activity. We conducted a user study with our adaptive system in social virtual reality to verify improved performance. Here, participants completed an n-back task, and we adapted the visual complexity of the environment by changing the number of non-player characters. Our results show that an adaptive virtual reality can control users' comfort, performance, and workload by adapting the visual complexity based on physiological arousal. Thus, our physiologically adaptive system improves task performance and perceived workload. Finally, we embed our findings in physiological computing and discuss applications in various scenarios.
A Minimalistic Approach to Predict and Understand the Relation of App Usage with Students' Academic Performance

Due to usage of self-reported data which may contain biasness, the existing studies may not unveil the exact relation between academic grades and app categories such as Video. Additionally, the existing systems' requirement for data of prolonged period to predict grades may not facilitate early intervention to improve it. Thus, we presented an app that retrieves past 7 days' actual app usage data within a second (Mean=0.31s, SD=1.1s). Our analysis on 124 Bangladeshi students' real-time data demonstrates app usage sessions have a significant (p<0.05) negative association with CGPA. However, the Productivity and Books categories have a significant positive association whereas Video has a significant negative association. Moreover, the high and low CGPA holders have significantly different app usage behavior. Leveraging only the instantly accessed data, our machine learning model predicts CGPA within ±0.36 of the actual CGPA. We discuss the design implications that can be potential for students to improve grades.
Probing hippocampal stimulation in experimental temporal lobe epilepsy with functional MRI

Background Electrical neurostimulation is a potentially effective therapy in epilepsy but the optimal approach is not yet clear. The parameter space is wide and the effects of different stimulations are not immediately obvious. Functional MRI (fMRI) can reveal which brain areas are affected by stimulation and help understand the induced effects. However, simultaneous deep brain stimulation (DBS)-fMRI examinations in patients are rare and the possibility to investigate multiple stimulation protocols is limited. Preclinical stimulation-fMRI studies can provide predictive value and help identify optimal neurostimulation parameters. Objective To systematically investigate the brain-wide responses to hippocampal electrical stimulations in a mouse model of mesial temporal lobe epilepsy (mTLE) using fMRI. Methods We applied electrical stimulation in the intrahippocampal kainate mouse model of mTLE and assessed the effect of different stimulation amplitudes (80-230 µA) and frequencies (1-100 Hz). In addition, the effect of prolonged 1 Hz stimulation was explored. Saline-injected mice served as controls. Results Varying the stimulation amplitudes had little effect on the resulting activation patterns. Low frequency stimulation led to a local response at the stimulation site only, whereas high frequency resulted in a spread of activation from the hippocampal formation into cortical and frontal areas. Prolonged low frequency stimulation reduced excitability. Conclusions While the amplitude parameter offers little opportunity to vary the outcome, the frequency represented the key parameter and determined whether the induced activation remained local or spread across the brain. This is in line with the few DBS-fMRI results obtained in epilepsy patients demonstrating the translational value of fMRI.
Sound elicits stereotyped facial movements that provide a sensitive index of hearing abilities

Sound elicits rapid movements of muscles in the face, ears, and eyes that protect the body from injury and trigger brain-wide internal state changes. Here, we performed quantitative facial videography from mice resting atop a piezoelectric force plate and observed that broadband sounds elicit rapid, small, and highly stereotyped movements of a facial region near the vibrissae array. Facial motion energy (FME) analysis revealed sensitivity to far lower sound levels than the acoustic startle reflex and greater reliability across trials and mice than sound-evoked pupil dilations or movement of other facial and body regions. FME tracked the low-frequency envelope of sounds and could even decode speech phonemes in varying levels of background noise with high accuracy. FME growth slopes were disproportionately steep in mice with autism risk gene mutations and noise-induced sensorineural hearing loss, providing an objective behavioral measure of sensory hyper-responsivity. Increased FME after noise-induced cochlear injury was closely associated with the emergence of excess gain in later waves of the auditory brainstem response, suggesting a midbrain contribution. Deep layer auditory cortex units were entrained to spontaneous facial movements but optogenetic suppression of cortical activity facilitated – not suppressed – sound-evoked FME, suggesting the auditory cortex is a modulator rather than a mediator of sound-evoked facial movements. These findings highlight a simple involuntary behavior that is more sensitive and integrative than other auditory reflex pathways and captures higher-order changes in sound processing from mice with inherited and acquired hearing disorders.
Partial Face Visibility and Facial Cognition: An Electroencephalography and Eye-Tracking Investigation

Face masks became a part of everyday life in the SARS-CoV-2 pandemic. Previous studies showed that the face cognition mechanism involves holistic face processing, and the absence of face features could lower cognition ability. This is opposed to the experience during the pandemic, when people were able to correctly recognize faces, although the mask covered a part of the face. This paper shows a strong correlation in face cognition based on the EEG and eye-tracking data between the full and partial faces. We observed two event-related potentials, P3a in the frontal lobe and P3b in the parietal lobe, as subcomponents of P300. Both P3a and P3b were lowered when the eyes were invisible, and P3a evoked by the nose covered was larger than the full face. The eye-tracking data showed that 16 out of 18 participants focused on the eyes associated with the EEG results. Our results demonstrate that the eyes are the most crucial feature of facial cognition. Moreover, the face with the nose covered might enhance cognition ability due to the visual working memory capacity. Our experiment shows the possibility of people recognizing faces using both holistic face processing and structural face processing. Furthermore, people can recognize the masked face as well as the full face in similar cognition patterns due to the high correlation in the cognition mechanism.
Targeting YAP mechanosignaling to ameliorate stiffness-induced Schlemm’s canal cell pathobiology

Pathologic alterations in the biomechanical properties of the Schlemm’s canal (SC) inner wall endothelium and its immediate vicinity are strongly associated with ocular hypertension in glaucoma due to decreased outflow facility. Specifically, the underlying trabecular meshwork is substantially stiffer in glaucomatous eyes compared to that from normal eyes. This raises the possibility of a critical involvement of mechanotransduction processes in driving SC cell dysfunction. Yes-associated protein (YAP) has emerged as a key contributor to glaucoma pathogenesis. However, the molecular underpinnings of SC cell YAP mechanosignaling in response to glaucomatous extracellular matrix (ECM) stiffening are not well understood. Using a novel biopolymer hydrogel that facilitates dynamic and reversible stiffness tuning, we investigated how ECM stiffening modulates YAP activity in primary human SC cells, and whether disruption of YAP mechanosignaling attenuates SC cell pathobiology and increases ex vivo outflow facility. We demonstrated that ECM stiffening drives pathologic YAP activation and cytoskeletal reorganization in SC cells, which was fully reversible by matrix softening in a distinct time-dependent manner. Furthermore, we showed that pharmacologic or genetic disruption of YAP mechanosignaling abrogates stiffness-induced SC cell dysfunction involving altered cytoskeletal and ECM remodeling. Lastly, we found that perfusion of the clinically-used, small molecule YAP inhibitor verteporfin (without light activation) increases ex vivo outflow facility in normal mouse eyes. Collectively, our data provide new evidence for a pathologic role of aberrant YAP mechanosignaling in SC cell dysfunction and suggest that YAP inhibition has therapeutic value for treating ocular hypertension in glaucoma.
Nigerian Universities’ Sexual Harassment Policies: Palliative or Provocative?

ABSTRACT Sexual violence and sexual harassment have been perennial topics in higher education across the continent and beyond. In response to stories and scandals, including the 2019 “Sex for Grades: Undercover in West African Universities” documentary by the BBC’s Africa Eye series, Nigerian universities have instituted sexual harassment policies. This article draws on a feminist textual analysis of the BBC documentary and three Nigerian higher institutions’ sexual harassment policies, complemented by specialized literature on gender, history, and sexuality, to examine the value of the policies and their limitations. I argue that the fundamental limitation of most of the policies is the persistence of how coloniality shapes gender in education. The gendered influences on education date back to colonialism and need to be challenged and questioned. I argue that, while policies are vital for driving transformative education, inclusive learning and a safe environment, it is crucial to consider how colonialism shaped gender in Nigeria, and to reflect on the structural and cultural logics that perpetuate gender norms.
The Impact of the COVID-19 Pandemic on Social Work Instructors: The Case of Israel

ABSTRACT The COVID-19 pandemic’s impact on people’s professional and personal lives is ongoing. The transition to remote teaching has particularly affected social work education due to its experiential methods incorporating a direct experience whereby students “learn by doing. ” This study examined the impact of the global pandemic and the transition to remote teaching on the emotional and cognitive experiences of 144 social work instructors in Israel. The results indicated that they quickly adapted to remote teaching. Furthermore, the instructors reported a mixed effect of the transition to remote teaching on their work – life balance. This study suggests that institutions should provide their instructors with sufficient time and tools to design remote classes in order to better engage their students in the learning process. The findings provide the foundation for understanding the complexity of remote teaching in the social work profession and offer opportunities to learn from experience. This study suggests that institutions should provide their instructors with sufficient time and tools to design their remote classes in order to better engage their students in the learning process.
An Auction Algorithm for Market Equilibrium with Weak Gross Substitute Demands

We consider the Arrow–Debreu exchange market model under the assumption that the agents’ demands satisfy the weak gross substitutes (WGS) property. We present a simple auction algorithm that obtains an approximate market equilibrium for WGS demands assuming the availability of a price update oracle. We exhibit specific implementations of such an oracle for WGS demands with bounded price elasticities and for Gale demand systems.
Xylazine is an agonist at kappa opioid receptors and exhibits sex-specific responses to naloxone administration

Xylazine has been found in the unregulated drug supply at increasing rates, usually in combination with fentanyl. It has become critical to understand its basic pharmacology, how it impacts behavior, and how it interacts with fentanyl in rodent models of opioid administration. Despite commentary from scientists, politicians, and public health officials, it is not known if xylazine impacts the efficacy of naloxone, the opioid receptor antagonist used to reverse opioid induced respiratory depression. Furthermore, few studies have examined the effects of xylazine alone, without co-administration of ketamine. Here, we examine the impact of xylazine alone and in combination with fentanyl on several key behaviors in male and female mice. We demonstrate differential locomotor responses by dose and sex to xylazine. Surprisingly, our results further indicate that naloxone precipitates withdrawal from xylazine and a fentanyl/xylazine combination, in both sexes, with enhanced sensitivity in females. Further, we show that xylazine is a full agonist at the kappa opioid receptor, a potential mechanism for its naloxone sensitivity. One-Sentence Summary We present surprising new insights into xylazine and fentanyl pharmacology with immediate implications for clinical practice and frontline public health.