Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Morals and Ethicals Issues in VR Games - A Case Study of Religious Worship Video Game

With intense and fearsome emotions from horror games, video game players resonate with the video game or the character, adding depth and immersion to the gaming experience. However, these emotions sometimes lead to psychological distress and lingering effects even after the game ends. A female gamer, Jordan Belamire, described the feeling of being abused and afraid of sexual harassment in virtual reality (VR) games as being violated in real life. The morals and ethics in video games have been rarely discussed though players often struggle with guilt or remorse after engaging in morally ambiguous actions within a game. Most players do not see video games as a judgment-free zone, yet the minority develops moral disengagement tendencies, leading to deviant behaviors. With the advancement of electronic devices, VR systems provide players with a heightened sense of realism compared to traditional PC screen games, allowing them to immerse themselves in virtual worlds that mimic reality. However, as the gaming experience becomes more realistic, players become aware of the moral and ethical issues and intensified emotional experiences evoked within the games. Therefore, we researched morals and ethics in games, specifically centered around religious worship using the Positive and Negative Affect Schedule (PANAS) emotion scale as a measurement tool. A 3D game scenario with intense emotional experiences related to “religious worship” was created and presented to participants on PC screens and VR headset gaming platforms. Differences among participants in cognitive recognition and reaction times in observing and interacting were observed with positive and negative emotional experiences of in-game morals and ethics after gameplay.
The management of fisheries and marine ecosystems

The global marine fish catch is approaching its upper limit. The number of overfished populations, as well as the indirect effects of fisheries on marine ecosystems, indicate that management has failed to achieve a principal goal, sustainability. This failure is primarily due to continually increasing harvest rates in response to incessant sociopolitical pressure for greater harvests and the intrinsic uncertainty in predicting the harvest that will cause population collapse. A more holistic approach incorporating interspecific interactions and physical environmental influences would contribute to greater sustainability by reducing the uncertainty in predictions. However, transforming the management process to reduce the influence of pressure for greater harvest holds more immediate promise.
Violent Activity Detection on Public Transportation using Surveillance Footage

The increasing challenges in public management, safety, and security have made it imperative to develop an automated violence detection system. However, current AI-based techniques often face generalization problems, making violence detection difficult. Additionally, traditional training methods make it challenging for models to recognize all diverse sets of violent activities. To address this, we propose a unique approach to training models called Data Categorization. This approach involves categorizing violent actions into individual actions and training a model separately on each action subset with different learning parameters. The pre-trained models are consolidated as a network and built as a multi-model approach using ResNet 3D as the base model. The proposed method is tested in four experiments, and the results demonstrate a 2-3% improvement in accuracy compared to other state-of-the-art approaches. This study proposes a novel training method that can be applied to various data science problems and contributes to the advancement of automatic violence detection.
Evaluation of Dynamic Resource Allocation for Multi-Core ASICs

the demand for multiplied performance in included circuits has led to the significant adoption of multi-center processors in cutting-edge digital devices. To fully use the potential of those multi-core architectures, green and dynamic useful resource allocation is vital. This technical abstract info the assessment of dynamic useful resource allocation techniques for multi-middle application-precise incorporated circuits (ASICs). In particular, the point of interest is at the exchange-off between performance and energy performance in such structures. The assessment is carried out by implementing a bendy and configurable simulation framework, which permits the easy evaluation of different resource allocation techniques. Essential procedures are considered worldwide highest quality resource allocation static partitioning, deterministic dynamic aid allocation, and probabilistic dynamic resource allocation. These techniques' overall performance and strength efficiency are evaluated across various benchmark programs. The effects display that dynamic aid allocation techniques, particularly the probabilistic approach, can considerably enhance performance and decrease energy intake in multi-middle ASICs compared to traditional static partitioning.
Speed Control of Doubly-Fed Induction Generator Based on a Improved Reaching Law Integral Sliding Mode Structure

As a nonlinear system with various uncertainties, doubly-fed induction generator(DFIG) is very sensitive to external disturbances and internal parameter variations. In order to suppress the external disturbances and system uncertainties and improve the dynamic quality of the motor speed control system, an improved integral sliding mode control is proposed, which based on a improved variable exponential reaching law. The reaching law introduces a variable speed reaching term on the basis of the conventional exponential reaching law and combines it with the integral sliding mode surface, which overcomes the shortcomings of the conventional exponential reaching law, improves the speed of the sliding mode reaching, and effectively suppresses the inherent chatter of the sliding mode control. The stability of the improved exponential reaching law is analyzed by Lyapunov function, and applied to the design of sliding mode controller for DFIG control system, and compared with some other classical methods to prove its effectiveness. The simulation results show that the designed sliding mode controller has better load disturbance resistance and robustness, effectively mitigating external disturbances and system uncertainties.
Heparin binding protein is increased in chronic leg ulcer fluid and released from granulocytes by secreted products of Pseudomonas aeruginosa

Summary Recently it was demonstrated by Gautam, et al. that release of neutrophil-borne heparin-binding protein (HBP), also known as CAP37/azurocidin, induced endothelial hyperpermeability and neutrophil efflux. Here, we show that chronic leg ulcer fluid, in contrast to wound fluid from acute wounds, contains highly increased levels of HBP. Immunohistochemistry demonstrated the presence of HBP in chronic ulcer tissues. Furthermore, secreted products of Pseudomonas aeruginosa were found to induce release of HBP from human neutrophils. Our data suggest a possible link between bacterial presence and HBPrelease in chronic ulcers.Thus, targeting HBP offers an interesting option for reduction of endothelial barrier dysfunction in chronic ulcers.
Quebec and Canada at the Crossroads: A Nation within a Nation

I argue first that there are many different concepts of the nation, and advocate a certain conceptual pluralism. I also argue that a population as a whole cannot constitute a nation unless it has a certain national consciousness. I then show that we must adopt a fundamental principle of tolerance. I also try to attend to the complexities of the relations between Quebec and Canada, and argue that different populations represent themselves as nations in different ways and with different concepts. 1 show that Quebec constitutes a nation within a nation. I then wonder what it would mean for Canadians to accept a Quebec nation. Finally, I try to explain why a very large proportion of the population of Quebec has increasingly been favourable to sovereignty, and favourable to making a partnership proposal to Canada.
Sediment Characteristics and Methane Ebullition in Three Subarctic Lakes

Ebullition (bubbling) from climate‐sensitive northern lakes remains an unconstrained source of atmospheric methane (CH4). Although the focus of many recent studies, ebullition is rarely linked to the physical characteristics of lakes. In this study we analyze the sediments of subarctic postglacial lakes and investigate how sediment properties relate to the large spatial variation in CH4 bubble flux, quantified over multiple years using bubble traps. The results show that the sediments from our lakes are rich in total organic carbon, containing 37 kg/m3 on average. This number is roughly 40% higher than the average for yedoma deposits, which have been identified as high CH4 emitters. However, the quantity of total organic carbon is not a useful indicator of high emissions from the study lakes. Neither is the amount of CH4 in the sediment a reliable measure of ebullition potential. Instead, our data point to coarse detritus, partly from buried submerged aquatic vegetation and redeposited peat as spatial controls on fluxes, often in combination with previously established effects of incoming solar radiation and water depth. The results once again highlight the climate sensitivity of northern lakes, indicating that biological responses to warmer waters and increased energy input and heating of organic sediments during longer ice‐free seasons can substantially alter future CH4 emissions.
Dynamic Pricing Strategies for Multi-Product Revenue Management Problems

This article reviews multiproduct dynamic pricing models for a revenue maximizing monopolist firm. The baseline model studied in this article is of a seller that owns a fixed capacity of a resource that is consumed in the production or delivery of some type of product. The seller selects a dynamic pricing strategy for the offered product so as to maximize its total expected revenues over a finite time horizon. We then review how this model can be extended to settings where the firm is selling multiple products that consume this firm's capacity, and finally highlight a connection between these dynamic pricing models and the closely related model where prices are fixed, and the seller dynamically controls how to allocate capacity to requests for the different products. Methodologically, this article reviews the dynamic programming formulations of the above problems, as well as their associated deterministic (fluid) analogues. It highlights some of the key insights and pricing heuristics that are known for these problems, and briefly mentions possible extensions and areas of current interest. Keywords: revenue management; dynamic pricing; fluid approximations; multiproduct; capacity controls
A Wideband Quasi-Isotropic Antenna Based on U-Shaped Quarter-Wavelength Radiator

In this paper, a wideband quasi-isotropic antenna based on a U-shaped quarter-wavelength radiator structure is designed. By introducing a stepped structure into the conventional U-shaped quarter-wavelength radiator, the antenna bandwidth is increased while ensuring quasi-isotropic radiation characteristics. The proposed antenna consists of two symmetrical stepped metal arms and a side metal patch, which can be equivalent to electric and magnetic dipoles, the combination of the two dipoles leads to a quasi-isotropic radiation pattern. The operating bandwidth of the antenna is 2.35-2.73GHz, corresponding to a fractional bandwidth of 15.1%, and the gain deviation does not exceed 7dB in the operating bandwidth.
Cloud Renaissance: Thriving in the Post-Pandemic Digital Landscape

The research work seeks to understand the need of organizations to shift their business to a Cloud Environment specifically in the post pandemic situation, and suggests a set of best practices for cloud migration considering the security concerns in different industries. This is a primary qualitative research based on a semi-structured in-depth interview of 19 technology experts from various industries. Initially 27 experts were approached, 19 responses were received and they were then engaged into a detailed in-depth interview. The qualitative thematic analysis of the data led to a few major findings. The research indicates the cloud adoption for carrying out the business virtually could be a game changer for any medium or large-scale organization in the post pandemic phase. Various organizations can use this study to reduce their capex and opex in the pandemic situation by carrying out their business virtually using the suggested set of best practices for cloud migration.
Tolerance of control-flow testing criteria

Effectiveness of testing criteria is the ability to detect failure in a software program. We consider not only effectiveness of some testing criterion in itself but a variance of effectiveness of different test sets satisfied the same testing criterion. We name this property "tolerance" of a testing criterion and show that, for practical using a criterion, a high tolerance is as well important as high effectiveness. The results of empirical evaluation of tolerance for different criteria, types of faults and decisions are presented. As well as quite simple and well-known control-flow criteria, we study more complicated criteria: full predicate coverage, modified condition/decision coverage and reinforced condition/decision coverage criteria.
Breast Cancer Prediction Using Artificial Intelligence Technology

The aim of the project is to compare the performance of four different machine learning algorithms for breast cancer prediction such as decision tree, logistic regression, XG boost, and CAT boost. We used a dataset of patient medical records containing various clinical factors to train and test the algorithms. Accurate diagnosis and early detection are essential for enhancing patient outcomes. Data mining is a prominent tool in the healthcare industry for processing massive amounts of data. To examine massive amounts of complicated medical data, researchers use a variety of data mining and machine learning approaches. The use of these strategies can help medical practitioners forecast the onset of breast cancer.
Secular changes in the tropical stratospheric water vapour entry induced by the Indo-Paciﬁc warm pool warming

A decreasing trend in the tropical (30 ° S˜30 ° N) stratospheric water vapour (SWV) entry in recent four decades (from 1984 to 2020) is detected based on the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) measurements and the ERA5 reanalysis dataset using linear regression and Ensemble Empirical Mode Decomposition (EEMD) analysis. With the concurrent warming of the SST, the Indo-Paciﬁc warm pool (IPWP) appears to be the most signiﬁcant region among the tropical oceans based on correlation analysis. More than 43% of the decreasing tropical lower SWV trend is likely to be related to the IPWP sea surface temperature (SST) warming. To validate this relationship, two groups of idealized runs are carried out with version 4 of the Whole Atmosphere Community Climate Model (WACCM4) and version 5 of the Community Atmosphere Model (CAM5). Both simulations agree with the observational-based linkage. The IPWP-SST-warming forced simulations show that the temperature in the tropical tropopause has decreased at the rate of around 0.318 K per decade in the coldest point region, as the tropical convection over the IPWP has become more vigorous and excited stronger equatorial waves to produce adiabatic cooling around tropopause. This cooling tropical tropopause leads to a dehydrating tropical lower stratosphere at the rate of 0.025 ppmv per decade, as expected by the freeze-drying mechanism. These results imply the substantial warming trend of IPWP is an important factor for the long-term trend of the tropical SWV entry under climate change, and a better representation of this relationship in the model is critical for the SWV projection under future climate scenarios.
A Web Service Architecture for Tracking and Analyzing Data from Distributed E-Learning Environments

Modern e-learning systems offer students many interactive learning elements such as videos or quiz questions. For the optimization of the teaching, the learning elements themselves and the prediction of student performance, it is important for educators to figure out how student interactions can be tracked and how the tracked data can be used. Modern learning courses can consist of different Software-as-a-Service products by third-party providers. These learning elements and the associated learning environments can be both heterogeneous and distributed. This requires advanced tracking methods. For these reasons, a tracking architecture that is capable of tracking and integrating the data of different learning environments is needed. Based on the xAPI specification, we provide such an architecture in this paper.
Shepherding Behaviors with Multiple Shepherds

Shepherding behaviors are a type of group be haviors in which one group (the shepherds) tries to control the motion of another group (the flock). Shepherding behaviors can be found in many forms in nature and have various important robotic applications. In this paper we extend our previous work of shepherding behaviors with a single shepherd to multiple shepherds. More specifically, we study how a group of shepherds can work cooperatively without communication to efficiently control the flock.
How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approach

Context and objectives: Although urbanization is a major driver of biodiversity erosion, it does not aﬀect all species equally. The neutral genetic structure of populations in a given species is aﬀected by both genetic drift and gene ﬂow processes. In cities, the size of animal populations determines drift and can depend on multiple processes, whereas gene ﬂow essentially depends on the ability of species to disperse across urban areas. Considering this, we tested whether variations in dispersal constraints alone could explain the variability of neutral genetic patterns commonly observed in urban areas. Besides, we assessed how the spatial distribution of urban green spaces (UGS) and peri-urban forests acts on these patterns. Methods: We simulated multi-generational genetic processes in virtual populations of animal species occupying either UGS or
Analysis of Adjacent Channel Interference from IMT-A System to Broadcasting System in China

Due to the scarcity of the frequency spectrum, coexistence of two systems in adjacent channels is possible if reasonable measures are taken in the network plan and spectrum plan. According to the Chinese and international business applications, mobile and broadcasting services will coexist at ultra high frequency band which means that harmful interference may be transpired. In this paper, the interference from the International Mobile Telecommunication-Advanced system at 698-806 MHz to the broadcasting system below 698 MHz is analyzed using Monte Carlo simulations. A simplified simulation flow is proposed and the results are presented to provide the necessary technical support for the spectrum plan and interference coordination.
Inﬂuences on Cash Dividends Paid

This study examines the influences on regular cash dividend paid in Nigeria. The study makes the null hypothesises that revenues, return on assets, firm size, independent auditors, and leverage have no influence on cash dividend paid. We analysed 744 firm-year observations which were obtained from e-annual financial statements of 2012 to 2021. Correlation and multivariate regressions were used to draw conclusion on the tests of our hypotheses. The results reject the null hypotheses on revenues, return on assets, firm size and independent auditors whereas it accepts the null hypothesis on leverage. Our results found that industrial sector and time fixed effects negatively influence cash dividend paid. Except for the result on returns on assets, which is insignificant in the robust standard errors estimation model, these results are robust to our alternative multivariate techniques. It is therefore recommend that listed Nigerian non-financial firms should continue to improve on their revenues and total assets; and engage more Big-4 auditors to audit their financial statements.
Positive topological entropy for Reeb ﬂows on 3-dimensional Anosov contact manifolds

Abstract. Let ( M, ξ ) be a compact contact 3-manifold and assume that there exists a contact form α 0 on ( M, ξ ) whose Reeb ﬂow is Anosov. We show this implies that every Reeb ﬂow on ( M, ξ ) has positive topological entropy, giving a positive answer to a question raised in [1]. Our argument builds on previous work of the author [1] and recent work of Barthelm´e and Fenley [4]. This result combined with the work of Foulon and Hasselblatt [14] is then used to obtain the ﬁrst examples of hyperbolic contact 3-manifolds on which every Reeb ﬂow has positive topological entropy.
Structure-based design and characterization of Parkin activating mutations

Human autosomal recessive mutations in the Parkin gene are causal for Parkinson’s disease (PD). Parkin encodes a ubiquitin E3 ligase that functions together with the PD associated kinase, PINK1, in a mitochondrial quality control pathway. Structural studies reveal that Parkin exists in an inactive conformation mediated by multiple autoinhibitory domain interfaces. Here we have performed comprehensive mutational analysis of both human and rat Parkin to unbiasedly determine Parkin activating mutations across all major autoinhibitory interfaces. Out of 31 mutations tested, we identify 11 activating mutations clustered near the RING0:RING2 or REP:RING1 interfaces, which reduce the thermal stability of Parkin. Of these, we demonstrate that three mutations, V393D, A401D, and W403A located at the REP:RING1 interface were able to completely rescue a Parkin S65A mutant, defective in mitophagy, in cell-based studies. Overall our data extends previous analysis of Parkin activation mutants and suggests that small molecules that mimic REP:RING1 destabilisation offer therapeutic potential for PD patients harbouring select Parkin mutations. Summary blurb Parkin, an E3 ubiquitin ligase involved in Parkinson’s disease, is inactive in the basal state and is activated by PINK1 to mediate mitophagy. Here we characterized 31 mutations and discovered three that activate Parkin and rescue loss of PINK1 phosphorylation.
Partial Differential Equations/Numerical Analysis Long time behavior of splitting methods applied to the linear Schrödinger equation

We consider the linear Schrödinger equation on a one-dimensional torus and its time-discretization by splitting methods. Assuming a non-resonance condition on the stepsize and a small analytical size of the potential, we show the conservation over exponentially long time of the energies associated with the double eigenvalues of the Laplace operator for asymptotically large modes. The result relies on a normal form theorem whose proof uses standard techniques of classical perturbations theory, extended here to an inﬁnite dimensional context. To cite this article: G. Dujardin, E. Faou, C. R. Acad. Sci. Paris, Ser. I 344 (2007). © 2006 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved. Résumé
Minimal Generalized Answer-Sets and their Applications

When intelligent agents get new knowledge and this knowledge must be added or updated to their knowledge base, then it is important to avoid inconsistencies. In this paper, we propose a semantics for update sequences of programs. The semantics is proposed as an application of an extension of the notion of generalized answer sets. This extension is also introduced in this work.