Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on the Characteristics of Small-Molecule Kinase Inhibitors-Related Drug-Induced Liver Injury

Background and Aim: More than half of the small-molecule kinase inhibitors (KIs) induced liver injury clinically. Meanwhile, studies have shown a close relationship between mitochondrial damage and drug-induced liver injury (DILI). We aimed to study KIs and the binding between drugs and mitochondrial proteins to find factors related to DILI occurrence. Methods: A total of 1,223 oral FDA-approved drugs were collected and analyzed, including 44 KIs. Fisher’s exact test was used to analyze DILI potential and risk of different factors. A total of 187 human mitochondrial proteins were further collected, and high-throughput molecular docking was performed between human mitochondrial proteins and drugs in the data set. The molecular dynamics simulation was used to optimize and evaluate the dynamic binding behavior of the selected mitochondrial protein/KI complexes. Results: The possibility of KIs to produce DILI is much higher than that of other types (OR = 46.89, p = 9.28E-13). A few DILI risk factors were identified, including molecular weight (MW) between 400 and 600, the defined daily dose (DDD) ≥ 100 mg/day, the octanol–water partition coefficient (LogP) ≥ 3, and the degree of liver metabolism (LM) more than 50%. Drugs that met this combination of rules were found to have a higher DILI risk than controls (OR = 8.28, p = 4.82E-05) and were more likely to cause severe DILI (OR = 8.26, p = 5.06E-04). The docking results showed that KIs had a significant higher affinity with human mitochondrial proteins (p = 4.19E-11) than other drug types. Furthermore, the five proteins with the lowest docking score were selected for molecular dynamics simulation, and the smallest fluctuation of the backbone RMSD curve was found in the protein 5FS8/KI complexes, which indicated the best stability of the protein 5FS8 bound to KIs. Conclusions: KIs were found to have the highest odds ratio of causing DILI. MW was significantly related to the production of DILI, and the average docking scores of KI drugs were found to be significantly different from other classes. Further analysis identified the top binding mitochondrial proteins for KIs, and specific binding sites were analyzed. The optimization of molecular docking results by molecular dynamics simulation may contribute to further studying the mechanism of DILI.
The Effect and Mechanism of Cultural Capital on Chinese Residents’ Participation in Physical Activities

Background Using Bourdieu’s cultural capital theory, this paper discusses the inequality of Chinese urban residents’ participation in physical activities caused by cultural capital and explores the relationship and role of residents’ income and self-rated health in cultural capital and physical activity participation. Methods Using Chinese social survey data (2017), the proposed assumptions were tested and analyzed by using a linear regression model. Results Cultural capital can promote the participation of Chinese urban residents in physical activities, and personal income and health self-assessment play an intermediary role in promoting residents’ participation in physical activities. Conclusion Promoting Chinese residents’ participation in physical activities can be realized not only through traditional publicity and sports venue construction but also by increasing residents’ educational level, art appreciation level and health awareness.
Advances in Our Clinical Understanding of Autonomic Regulation Therapy Using Vagal Nerve Stimulation in Patients Living With Heart Failure

The ANTHEM-HF, INOVATE-HF, and NECTAR-HF clinical studies of autonomic regulation therapy (ART) using vagus nerve stimulation (VNS) systems have collectively provided dose-ranging information enabling the development of several working hypotheses on how stimulation frequency can be utilized during VNS for tolerability and improving cardiovascular outcomes in patients living with heart failure (HF) and reduced ejection fraction (HFrEF). Changes in heart rate dynamics, comprising reduced heart rate (HR) and increased HR variability, are a biomarker of autonomic nerve system engagement and cardiac control, and appear to be sensitive to VNS that is delivered using a stimulation frequency that is similar to the natural operating frequency of the vagus nerve. Among prior studies, the ANTHEM-HF Pilot Study has provided the clearest evidence of autonomic engagement with VNS that was delivered using a stimulation frequency that was within the operating range of the vagus nerve. Achieving autonomic engagement was accompanied by improvement from baseline in six-minute walk duration (6MWD), health-related quality of life, and left ventricular EF (LVEF), over and above those achieved by concomitant guideline-directed medical therapy (GDMT) administered to counteract harmful neurohormonal activation, with relative freedom from deleterious effects. Autonomic engagement and positive directional changes have persisted over time, and an exploratory analysis suggests that improvement in autonomic tone, symptoms, and physical capacity may be independent of baseline NT-proBNP values. Based upon these encouraging observations, prospective, randomized controlled trials examining the effects on symptoms and cardiac function as well as natural history have been warranted. A multi-national, large-scale, randomized, controlled trial is well underway to determine the outcomes associated with ART using autonomic nervous system engagement as a guide for VNS delivery.
Role of Efficient Human Resource Management in Managing Diversified Organizations

As the world has turned into a global village, it has created many challenges for human resource departments regarding the management of a diverse workforce in satisfying the employees and creating a diverse yet safe environment for them that does not make them uncomfortable. The current study has investigated the effect of human resource practices on the diversity climate with the mediation of job satisfaction. The data has been collected from human resource personnel of multinationals in China with the help of 316 participants. The study deployed SEM analysis to analyze and measure the effect of training and development along with performance appraisal on the diversity climate. The findings of the study revealed that training and growth or development do not have an impact on the diversity climate, however, performance appraisal has a strong positive impact. Similarly, the mediating role of job satisfaction has been found to ensure the relationship of training and development and performance appraisal with the diversity climate. This study has provided certain implications for the HR managers of multinationals to ensure a secure diversity climate for a diverse workforce.
Benchmarking and Analysing the NIST PQC Finalist Lattice-Based Signature Schemes on the ARM Cortex M7

This paper presents benchmarking and profiling of the two lattice-based signature scheme finalists, Dilithium and Falcon, on the ARM Cortex M7 using the STM32F767ZI NUCLEO-144 development board. This research is motivated by the Cortex M7 device being the only processor in the Cortex-M family to offer a double precision (i.e., 64-bit) floating-point unit, making Falcon’s implementations, requiring 53 bits of precision, able to fully run native floating-point operations without any emulation. Falcon shows significant speed-ups between 6.2-8.3x in clock cycles, 6.2-11.8x in runtime, but Dilithium does not show much improvement other than those gained by the slightly faster processor. We then present profiling results of the two schemes on the Cortex M7 to show their respective bottlenecks and operations where the improvements are and can be made, which show some operations in Falcon’s procedures observe speed-ups by an order of magnitude. Finally, we test the native FPU instructions on the Cortex M7, used in Falcon’s FPR instructions, for constant runtime and find irregularities on four different STM32 boards, as well as on the Raspberry Pi 3, used in previous benchmarking results for Falcon.
Simulating Olfactory Cocktail Party Effect in VR: A Multi-odor Display Approach Based on Attention

Odor display has been a popular approach in virtual reality (VR) to enhance users’ multi-sensory experience. The existing multi-odor presentation methods in VR are mostly based on spatiality of scent sources to produce mixed scents, which will possibly compromise users’ olfactory experience because humans normally have poor ability to analyze distinct odorant components from a mixture. To tackle this problem, we present a VR multi-odor display approach that dynamically changes the intensity combinations of different scent sources in the virtual environment according to the user’s attention, hence simulating a virtual cocktail party effect of smell. We acquire the user’s gaze information as attention from the eye-tracking sensors embedded in the head mounted display (HMD), and increase the display intensity of the scent that the user is focusing on to simulate the cocktail party effect of smell, enabling the user to distinguish their desired scent source. We conducted a user study to validate the perception and experience of 2 ways of intensity settings in response to the user’s attention shift, which were a strong level of focused scent mixed with weak levels of non-focused scents and strong focused scent only. The results showed that both of the two intensity settings were able to improve olfactory experience in VR compared to the non-dynamic odor display method. Meanwhile, only the method of presenting strengthened focused scent while maintaining the weaker mixture of background scents showed significant improvement on simulating the olfactory cocktail party effect by giving the users an enhanced sense of their own olfactory sensitivity.
Analysis of Google Play Store's Sentiment Review on Indonesia's P2P Fintech Platform

Nowadays there are so many mobile phone-based investment applications, ranging from mutual funds, stocks, and P2P lending. While these investment applications are gaining huge attraction among the general masses, sometimes selecting the right platform still becomes a hot issue. This research aimed to analyze the sentiment on P2P lending applications and to determine the user's response due to the increase in the number of funds distribution during the COVID-19 pandemic. By doing so, this research could give some insight into the new and existing user. Data was obtained through assessment reviews on the Play store platform for the P2P A, P2P B, and P2P C applications. Assessment reviews were classified by using a data mining approach, TF-IDF feature extraction, and Naïve-Bayes classification method. This research showed that P2P A got 77% positive sentiment and 23% negative sentiment, P2P B got 36% positive sentiment and 64% negative sentiment, and P2P C got 68% positive sentiment and 32% negative sentiment. From the results of the study, it was found that P2P A got better results than both P2P B and P2P C. those were 77% positive sentiment with 23% negative sentiment in finance topic, 56% positive sentiment with 44 % negative sentiment in account verification topic, 79% positive sentiment with 21% negative sentiment in apps review, and 99% positive sentiment with 1% negative sentiment in referral topic.
Anomaly Detection for Web Log based Data: A Survey

Web Log data contains crucial information such as User Name, IP Address, Access Request, Time Stamp, Result Status, number of Bytes Transferred, Use Agent and URL that Referred. In post-error investigations, log files are useful as you can use log files to figure out what's causing an error or a security breach. This is because the log files record data at the same time as the information system's activity. Regularly reviewing logs may aid in the detection of harmful assaults on the system. This review aims to layout a comprehensive outline of the various research methods related to anomaly detection in system logs, and to evaluate their effectiveness. We have discussed the various advantages and drawbacks of different types of anomaly detection techniques. We also talk about the computational complexity of these techniques in real applications.
FDI-linked Spillovers and the Indian Economic Growth: The role of Country's Absorptive Capacity

The study's aim is to frame and analyze the influence of foreign direct investment (FDI) on a nation's economic growth. Inflows of FDI effect economic growth by causing an influx of physical capital and a technological spillover. Depending on the characteristics of the host nation, technology spillover will play a bigger role in stimulating economic growth. The study examines the influence of FDI on India's economic growth by adopting OLS regression to assess time series data of a variety of macroeconomic variables. The study found that the human capital has a critical role in regulating the economic growth of the host country by directly complementing FDI.
Asymmetric Lateral Field-of-View Restriction to Mitigate Cybersickness During Virtual Turns

Field-of-view (FOV) restriction is a common technique to reduce cybersickness in commercial virtual reality (VR) applications. However, the majority of existing FOV restriction techniques are implemented as symmetric imagery, which occludes users’ views during virtual rotation. In this paper, we proposed and evaluated a novel variant of FOV restriction, referred to as a side restrictor. Side restriction uses an asymmetric mask to obscure only one side region of the periphery during virtual rotation and laterally shifts the center of restriction towards the direction of the turn. We conducted a study using a between-subjects design that compared the side restrictor, a traditional symmetric restrictor, and a control condition without FOV restriction. Participants were required to navigate through a complex maze-like environment using a controller using one of three restrictors. Compared to the control condition, the side restrictor was effective in mitigating cybersickness, reducing discomfort, improving subjective visibility, and enabling users to remain immersed for a longer period of time. Additionally, we found no empirical evidence of negative drawbacks when compared to the symmetric restrictor, which suggests that side restriction is an effective cybersickness mitigation technique for virtual environments with frequent turns.
A Replication Study to Measure the Perceived Three-Dimensional Location of Virtual Objects in Optical See Through Augmented Reality

An important research question in optical see-through (OST) augmented reality (AR) is, how accurately and precisely can a virtual object's real world location be perceived? Previously, a method was developed to measure the perceived three-dimensional location of virtual objects in OST AR. In this research, a replication study is reported, which examined whether the perceived location of virtual objects are biased in the direction of the dominant eye. The successful replication analysis suggests that perceptual accuracy is not biased in the direction of the dominant eye. Compared to the previous study's findings, overall perceptual accuracy increased, and precision was similar.
Experimental study of headform–PVB laminated windshield impact

Abstract To determine the pedestrian's head injury criteria in a vehicle–pedestrian accident and the crack propagation and distribution laws for use in accident reconstruction, headform–polyvinyl butyral (PVB) laminated windshield upright impact tests were conducted at different impact speeds with a newly designed dropping impact hammer. A real vehicle was used considering the buffer performance of the entire vehicle. The crack propagation and distribution characteristics of the PVB laminated glass were explained by wave propagation. The resultant acceleration–time curves of headform were obtained, while a high-speed camera captured headform movement and glass crack propagation. The results showed that head injuries occur primarily in the initial collision stage. The crack propagation and distribution characteristics are related to the internal random defects of glass and the frequency, strength, and angle of impact. These results will help to better understand a pedestrian's head movement and injury criteria, and provide the foundation for simulation analysis.
Effects of Field of View on Dynamic Out-of-View Target Search in Virtual Reality

We present a study of the effects of field of view (FOV), target movement, and number of targets on visual search performance in virtual reality. We compared visual search tasks in two FOVs (~65°, ~32.5°) under two target movement speeds (static, dynamic) while varying the visible target count, with targets potentially out of the user’s view. We examined the expected linear relationship between search time and number of items, to explore how moving and/or out-of-view targets affected this relationship. Overall, search performance increased with a wide FOV, but decreased when targets were moving and with more visible targets. FOV more strongly influenced search performance than target movement. Neither FOV nor target movement meaningfully altered the linear relationship between visual search time and number of items. Participants also rated perceived workload for each condition; FOV and target movement both negatively affected the perceived workload, with target movement being a more significant factor.
Evaluating Perceptional Tasks for Medicine: A Comparative User Study Between a Virtual Reality and a Desktop Application

Since for most consumers the Virtual Reality (VR) experience exceeds that of desktop applications, an increasing number of applications is being transferred from desktop to VR. Industrial and entertainment applications primarily expect for a richer consumer experience, while others, such as surgical applications, seek for improved precision over their desktop counterparts. One way to improve the performance of precision-based VR applications is to provide suitable visualizations. Today, these "suitable" visualizations are mostly transferred from desktop to VR without considering their spatial and temporal performance might change in VR. This may not lead to an optimal solution, which can be crucial for precision-based tasks. Misinterpretation of shape or distance in a surgical or pre-operative simulation can affect the chosen treatment and thus directly impact the outcome. Therefore, we evaluate the performance differences of multiple visualizations for 3D surfaces based on their shape and distance estimation for desktop and VR applications. We conducted a quantitative user study with 56 participants evaluating seven visualizations (Phong, Toon, Fresnel, Pseudo-Chromadepth, Heatmap, Isolines, and Arrow Glyphs). Our results show that the performance of each visualization varies depending on the task, system, and surface type, with VR generally providing improved results. While Isolines are able to improve distance estimation, Phong and Heatmaps are beneficial for shape estimation.
An Optimal Thresholds for Segmenting Medical Images Using Improved Swarm Algorithm

The key to threshold segmentation is selecting the thresholds that will determine the segmentation’s outcome—as the number of thresholds increases, the calculation complexity increases, posing issues for traditional methods. This paper presents an improved swarm algorithm method (ISA) for determining the best image segmentation thresholds. The objective function is modeled to be the global optimization issue of the segmentation function based on its entropy. The ISA works well with picture segmentation, resulting in remarkable computing in terms of global convergence and resilience and preventing local optimization trapping. It is incredibly well adapted to solving complex functions with multiple peaks and large dimensions. According to thorough theoretical study and simulation ﬁndings, in multi-image and multi-thresholds segmentation, the ISA has more eﬃcacy, eﬃciency, stability of the range of thresholds, and quality than the swarm algorithm (PSO) and diﬀerential evolution (DE)
A Comparison of Spatial Augmented Reality Predictive Cues and their Effects on Sleep Deprived Users

Spatial Augmented Reality (SAR) is a useful tool for procedural tasks as virtual instructions can be co-located with the physical task. Predictive cue annotations have been utilized to further enhance user performance through SAR. These predictive cues have only been measured under ordinary circumstances. This paper aims to investigate predictive cues under a sub-optimal scenario by depriving users of sleep. Sleep deprivation is a common form of fatigue, which is known to have serious detriments on user performance. Based upon existing sleep literature, we expected predictive cue performance to degrade over time with sharp declines during the early hours of the morning. Despite these drops in performance, we hypothesized that having a predictive cue would benefit user performance in comparison to no cue. Results from a 62-hour sleep deprivation experiment indicated that providing SAR predictive cues was beneficial throughout sleep deprivation. Furthermore, having no predictive cue caused accuracy to decline earlier in the sleep deprivation period. From the predictive cues outlined in this paper, the line cue maintained the fastest response time and was least impacted by early morning performance declines.
Modeling and Evaluation of a Data Center Sovereignty

Technology Sovereignty aims at protecting the interests of the consumers belonging to a sovereign state. The new laws on network sovereignty monitor and govern networks inside a state. They protect the constitutional rights of citizens and ensure data security. However, they do not focus on the infrastructure and hardware associated with these networks. Ensuring a robust end-to-end network fuels the need for reliable hardware manufacturers and an appropriate network architecture that can handle multiple failures efficiently. To understand technological sovereignty in communication networks, the Data Center Network (DCN) is targeted as it is a critical part of the digital society. Data centers are dedicated physical facilities that act as storage houses for large amounts of data. Though several fault-tolerance studies have been performed in DCNs, none have studied the role of hardware manufacturers in DCN Sovereignty. The unavailability of components from a manufacturer can lead to multiple failures. So, it is necessary to build a sovereign DCN without creating a dependency on the manufacturer(s). In this work, to evaluate the sovereignty of a DCN, (i) Multiple failure scenarios depending on manufacturer reliability are evaluated, and (ii) Design guidelines on how to choose the number of hardware manufacturers and how to arrange them in the DCN topology are presented.