Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling and Simulation of Exit Selection Behavior in Pedestrian Evacuation Based on Information Perception and Transmission

This paper aims to present an improved evacuation model, which is capable of simulating individual exit selection behavior based on the acquisition and processing of information, especially in dangerous and unfamiliar environments. Firstly, an evacuation model was improved by the introduction of a floor field of gas concentration and an exit selection model, considering the congestion avoidance and danger avoidance behavior. Secondly, the process of information perception and transmission was studied and introduced into the model with a set of rules. Finally, real experiments in a simple double-exit room were conducted for model validation and parameter setting, and simulation experiments in scenarios with an unknown hazard or unknown exits were conducted to confirm the necessity and rationality of introducing information perception and transmission. The simulation results show that, with the increase in perception distance or trust extent, the pedestrian safety increases. The critical values of perception distance or trust extent, below which some people cannot acquire any new information, vary depending on the pedestrian density. When the density is high, the influence of perception distance or trust extent reduces, and the probability of reselecting an exit increases, which causes the safety of pedestrians to decrease.
Climate Change and Livestock Management Drove Extensive Vegetation Recovery in the Qinghai-Tibet Plateau

The vegetation of the Qinghai-Tibet Plateau (QTP), China, is diverse and sensitive to climate change. Because of extensive grassland degradation in the QTP, several ecological restoration projects, which affect the livestock population, have been implemented in the QTP. Although many studies have reported the impacts of climate change on vegetation in the QTP, our knowledge on the impacts of both climate change and livestock on vegetation remains very limited. Here, we investigated the impacts of climate change and livestock population on vegetation growth by using the annual maximum normalized difference vegetation index (NDVImax) and growing-season climate data from 1981 to 2019. We analyzed the relationship between NDVImax and climate and livestock population using the modified Mann-Kendall trend Test and Pearson correlation analysis. For the entire QTP, NDVImax had a two-phase trend, with a slow rise during 1981–2000 and a rapid rise during 2000–2019. Overall, NDVImax in the QTP increased and decreased in 63.7% and 6.7% of the area in 2000–2019. In areas with significant changes in NDVImax, it was strongly correlated with relative humidity and vapor pressure. The small positive trend in NDVImax during 1981–2000 was influenced by warmer and wetter climate, and the overgrazing by a large population of livestock slowed down the rate of increase in NDVImax. Livestock population for Qinghai and Tibet in recent years has been lower than in the 1980s.The warmer and wetter climate and substantial drops in the livestock population contributed to large recovery in vegetation during 2001–2019. Vegetation degradation in Qinghai during 1981–2000 and central-northern Tibet during 2000–2019 was driven mainly by drier and hotter climatic. Although 63.7% of the area in the QTP became greener, the vegetation degradation in central-northern Tibet should not be ignored and more measures should be taken to alleviate the impact of warming and drying climate. Our findings provide a better understanding of the factors that drove changes in vegetation in the QTP.
Synthesis and Preliminary Anticancer Activity Assessment of N-Glycosides of 2-Amino-1,3,4-thiadiazoles

The addition of 2-amino-1,3,4-thiadiazole derivatives with parallel iodination of differently protected glycals has been achieved using a double molar excess of molecular iodine under mild conditions. The corresponding thiadiazole derivatives of N-glycosides were obtained in good yields and anomeric selectivity. The usage of iodine as a catalyst makes this method easy, inexpensive, and successfully useable in reactions with sugars. Thiadiazole derivatives were tested in a panel of three tumor cell lines, MCF-7, HCT116, and HeLa. These compounds initiated biological response in investigated tumor models in a different rate. The MCF-7 is resistant to the tested compounds, and the cytometry assay indicated low increase in cell numbers in the sub- G1 phase. The most sensitive are HCT-116 and HeLa cells. The thiadiazole derivatives have a pro-apoptotic effect on HCT-116 cells. In the case of the HeLa cells, an increase in the number of cells in the sub-G1- phase and the induction of apoptosis was observed.
Optimization Problems in Supply Chain Management

textabstractMaria Dolores Romero Morales was born on Augustus 5th, 1971, in Sevilla (Spain). She studied Mathematics at University of Sevilla from 1989 to 1994 and specialized in Statistics and Operations Research. She wrote her Master's thesis on Global Optimization in Location Theory under the supervision of Dr. Emilio Carrizosa Priego and Dr. Eduardo Conde S? nchez. During the academic year 1995-1996 she was assistant professor at the department of Mathematics of the Business School, University of C? diz, Spain. From September 1996 to July 2000, she has been research assistant at the department of Decision and Information Sciences of the Faculty of Business Administration, Erasmus University, The Netherlands. During the second semester of the academic year 1997-1998, she was assistant professor at the department of Statistics and Operations Research of the Faculty of Mathematics, University of Sevilla, Spain.
chopper stabilization in Analog Multipliers

Analog multiplication is widely used in systems today ranging from analog building blocks to phase-alignment systems. As with any system, analog multipliers are plagued by DC offset. The Gilbert multiplier cell in Figure1 shows common mismatches in resistor sizes, transistor W/L’s, and threshold variations that contribute to the offset. We can model this offset by three quantities-δx, δy, and δz--as shown in the block diagram in Figure 2. These offsets can lead to inaccurate results in critical calculations. For example, in a phase-alignment system integrated with Cartesian Feedback, any significant errors in the sum of products IQ-QI’, which is critical to the phase alignment, can lead to instability in the loop [1]. Chopper stabilization is a well known technique for removing DC offset from amplifiers. We propose a new application of chopper stabilization to analog multipliers for improved DC performance. In order to apply this method, two necessary modifications must be made, as Figure 2 shows: the first is to chop the two inputs in quadrature, and the second is to perform the down chopping operation at twice the inputchopping frequency. The result is, effectively, to separate the offset terms from the desired output. Our goal is to produce an in-depth analysis of the performance and to examine the limitations of this new technique when applied to analog multiplication.
Linking Pedigree Information to the Gene Expression Phenotype to Understand Differential Family Survival Mechanisms in Highly Fecund Fish: A Case Study in the Larviculture of Pacific Bluefin Tuna

Mass spawning in fish culture often brings about a marked variance in family size, which can cause a reduction in effective population sizes in seed production for stock enhancement. This study reports an example of combined pedigree information and gene expression phenotypes to understand differential family survival mechanisms in early stages of Pacific bluefin tuna, Thunnus orientalis, in a mass culture tank. Initially, parentage was determined using the partial mitochondrial DNA control region sequence and 11 microsatellite loci at 1, 10, 15, and 40 days post-hatch (DPH). A dramatic proportional change in the families was observed at around 15 DPH; therefore, transcriptome analysis was conducted for the 15 DPH larvae using a previously developed oligonucleotide microarray. This analysis successfully addressed the family-specific gene expression phenotypes with 5739 differentially expressed genes and highlighted the importance of expression levels of gastric-function-related genes at the developmental stage for subsequent survival. This strategy demonstrated herein can be broadly applicable to species of interest in aquaculture to comprehend the molecular mechanism of parental effects on offspring survival, which will contribute to the optimization of breeding technologies.
Towards a transformative space for conversations about sexualised violence? Obstacles, strategies and precarious moments

ABSTRACT Drawing from an ethnographic evaluation of the American violence prevention program Mentors in Violence Prevention (MVP), the present paper aims to explore 1) The participating girls’ views of classroom culture and sense of safety, and; 2) Strategies for and obstacles to creating a transformative space for conversations about sexualized violence in three schools with young people aged 12–18 in Sweden. The material analysed in this paper consists of transcripts from video observations and field notes from all sessions in three classes and from group and individual interviews with participants. The paper contributes to critical research on violence in a broad sense, including its prevention, and on anti-oppressive education. In conclusion, we stress the importance of competence, commitment and preparing for precarity, when involving young people. Addressing boys and men as allies in violence prevention must be balanced with a critical feminist understanding of the realities of violence, including sensitivity both to the needs of the group and of individual possibly victimized participants.
Investigation of the networking performance of remote real-time computing farms for ATLAS trigger DAQ

To test the feasibility of using remote farms to perform real-time event selection in the trigger/data acquisition system for the ATLAS experiment at CERN, a proof of concept was set up during 2004. The behaviour of the request-response protocol to move application data has been measured for remote farms connected with different wide area networks including a dedicated lightpath, a virtual private network, and the standard production network. The dynamics and effect of using TCP/IP as the transport protocol has also been investigated for this realtime application. These data are compared with conventional bulk data transfers and used to validate the observed performance of the online farms and estimate the effect of this traffic pattern on the wide area network
Current Readiness Status of Electric Vehicles in Indonesia: Multistakeholder Perceptions

As a net oil importer since 2004, Indonesia’s success in developing fuel economy and infrastructure for electric vehicles would be vital to ensuring energy security and decarbonization from the transport sector. Following the Presidential Regulation on the Acceleration Program for battery-based EV for Road Transportation in 2019, the Indonesian government provides incentives for the domestic production of EVs. However, as EV technology is relatively new for the domestic automotive industry in Indonesia, it needs to go through stages of development to achieve full readiness in society. This study analyses the key stakeholders’ perceptions of EV industries using the Japanese technology readiness assessment (J-TRA) to better understand the current readiness level of EVs in Indonesia. Primary data are collected through interviews with an EV start-up company, experts in the EV field, government officials in charge of the national EV projects, and EV end-users. Extensive literature related to success stories of EV adoption in other countries was conducted as the basis for this study. The results showed that key stakeholders agree that EV technology has reached a high readiness level in technology development. Most of the stakeholders voted that the readiness bottleneck is commercialization, safety, and integration parameters. Furthermore, an elaborate policy recommendation gathered from both literature reviews and interviews with related stakeholders is presented.
3D Simulation of Heavy-Ion Induced Charge Collection in Sub-100nm MOS-FETs Using Strained Silicon-Germanium

Single event transient of a PMOS using strained Silicon-Germanium in a sub-100nm bulk process is studied by 3D TCAD simulation. The impact of bias voltage, temperature, LET, and struck position on SET is considered. Our simulation results demonstrate that bias voltage in the range 0.8 to 1.2V greatly influence the amplitude of SET current. Temperature has a stronger influence on a SiGe channel PMOS than a Si-channel PMOS. Both SET current duration and total collection charge increase as LET increases, and SET current duration and total collection of a SiGe channel PMOS are larger than that of Si channel PMOS. These simulation results are beneficial to the space application of SiGe circuits.
A Mathematical Model for Numerical Simulation of Weft Insertion on an Air-Jet Weaving Machine

In air-jet weft insertion, the weft yarn is moved by the frictional drag between the air stream and the yarn surface. This paper reports the computer simulation of this process in order to determine the motion of the yarn during weft insertion. Forces acting on the weft . depend on time as well as the varying position of the weft during insertion. The mathematical model of the system is implemented with a worksheet, and the results are shown using a graphics package. These theoretical results are compared with those experimentally obtained for the weft yarn. Weft positions in the reed channel in relation to machine timing in terms of shaft degrees are measured by the stroboscope of the machine for several picks, and the average value is taken for each position. Weft speed is calculated based on this measurement.
Sound Biting Conspiracy: From India with “Love Jihad”

Since 2013, India has seen a remarkable growth of a conspiracy theory known as “love jihad”, which holds that Muslim men conspire to lure Hindu women for marriage to alter India’s religious demography as part of a political takeover strategy. While earlier scholarship on “love jihad” emphasizes the Hindu nationalist propagation of this conspiracy theory, this article pays equal attention to its appeal among conservative Hindus. Making its point of departure in the generative effects of speech, it argues that the “love jihad” neologism performs two logical operations simultaneously. Firstly, it fuses the long-standing Hindu anxiety about daughters marrying against their parents’ will, with the equally long-standing anxiety about unfavorable religious demographic trends. Secondly, it attributes a sinister political takeover intent to every Muslim man who casts his eyes on a young Hindu woman. To bring out these points, this article pays equal empirical attention to marriage and kinship practices as to the genealogy of, and forerunners to, the “love jihad” neologism, and develops the concept of “sound biting” to bring out its meaning-making effect.
Application of Deep Learning Architectures for Satellite Image Time Series Prediction: A Review

Satellite image time series (SITS) is a sequence of satellite images that record a given area at several consecutive times. The aim of such sequences is to use not only spatial information but also the temporal dimension of the data, which is used for multiple real-world applications, such as classification, segmentation, anomaly detection, and prediction. Several traditional machine learning algorithms have been developed and successfully applied to time series for predictions. However, these methods have limitations in some situations, thus deep learning (DL) techniques have been introduced to achieve the best performance. Reviews of machine learning and DL methods for time series prediction problems have been conducted in previous studies. However, to the best of our knowledge, none of these surveys have addressed the specific case of works using DL techniques and satellite images as datasets for predictions. Therefore, this paper concentrates on the DL applications for SITS prediction, giving an overview of the main elements used to design and evaluate the predictive models, namely the architectures, data, optimization functions, and evaluation metrics. The reviewed DL-based models are divided into three categories, namely recurrent neural network-based models, hybrid models, and feed-forward-based models (convolutional neural networks and multi-layer perceptron). The main characteristics of satellite images and the major existing applications in the field of SITS prediction are also presented in this article. These applications include weather forecasting, precipitation nowcasting, spatio-temporal analysis, and missing data reconstruction. Finally, current limitations and proposed workable solutions related to the use of DL for SITS prediction are also highlighted.
A review of automatic contingency selection algorithms for online security analysis

An essential aspect of modern power system security assessment is the consideration of any contingencies which may arise due, for example, to planned or unplanned outages of lines, and which may cause system overloads. For power systems comprising of several hundred lines, it is impractical to examine all possible contingencies. Therefore, the system engineer makes a judgement, based on intuition and experience, and ranks contingencies in order of importance. An automatic contingency selection algorithm can assist this process of security assessment by providing an objective criterion to select the most critical contingencies in a given system state and to limit the number of contingencies included in this assessment. The author presents a critical assessment of automatic contingency selection methods as reported in the literature, and identifies the general requirements of automatic contingency selection algorithms in the real-time monitoring and control of power systems. < >
Multiplex Gene Tagging with CRISPR-Cas9 for Live-Cell Microscopy and Application to Study the Role of SARS-CoV-2 Proteins in Autophagy, Mitochondrial Dynamics, and Cell Growth

The lack of efficient tools to label multiple endogenous targets in cell lines without staining or fixation has limited our ability to track physiological and pathological changes in cells over time via live-cell studies. Here, we outline the FAST-HDR vector system to be used in combination with CRISPR-Cas9 to allow visual live-cell studies of up to three endogenous proteins within the same cell line. Our approach utilizes a novel set of advanced donor plasmids for homology-directed repair and a streamlined workflow optimized for microscopy-based cell screening to create genetically modified cell lines that do not require staining or fixation to accommodate microscopy-based studies. We validated this new methodology by developing two advanced cell lines with three fluorescent-labeled endogenous proteins that support high-content imaging without using antibodies or exogenous staining. We applied this technology to study seven severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/COVID-19) viral proteins to understand better their effects on autophagy, mitochondrial dynamics, and cell growth. Using these two cell lines, we were able to identify the protein ORF3a successfully as a potent inhibitor of autophagy, inducer of mitochondrial relocalization, and a growth inhibitor, which highlights the effectiveness of live-cell studies using this technology.
Assessment of Collaboration-Based and Non-Collaboration-Based Logistics Risks with Plithogenic SWARA Method

Background: Uncertainty is the major source of hazards, and it is present in a wide range of business activities. Due to the high level of unpredictability in logistics operations, the logistics sector has traditionally operated in a high-risk environment. These risks have become considerably more complicated as the corporate environment has changed in recent years, such through globalization, environmental concerns, and changes in demand. As a result, in order for a logistics firm to thrive, it is necessary to evaluate and assess the risks associated with logistics. Methods: The Plithogenic Stepwise Weight Assessment Ratio Analysis (SWARA) has been used in this study to assess the logistics risks. The logistics risk considered in this study are transportation-related risks, purchasing-related risks, inventory-related risks, information-related risks, packaging-related risks, operational-related risks, geographical location-related risks, natural disaster-related risks, and organization-related risks. Results: The most significant logistics risks are found to be Inventory-Related Risks, while the least significant are Geographical Location-Related Risks. When compared to the standard SWARA approach, the Plithogenic SWARA method may be employed in group decision-making issues without losing information. Conclusions: The proposed technique will help logistics professionals make informed decisions and manage and analyze risks more efficiently. This study will also contribute to the literature as it is the first time that logistical risks have been addressed by utilizing the Plithogenic SWARA technique.
Designing infrastructures using a complex systems perspective

Networked infrastructures are complex socio-technical systems. Their complexity shows in the physical networks, in the actor networks, and the combination thereof. This paper addresses the question, 'how should the design of these systems be undertaken? ' Both for physical networks and for actor networks, design processes exist that can be applied separately. For integrated networks, however, an integrated approach is proposed. Three case studies are discussed concerning the design of a district heating system, a gas network and a seaport development, respectively. It is concluded that the integrated socio-technical complex system design process proposed has merit for networked infrastructures.
Research on the Algorithm for Off-line Rectification of Welding Seam Based on Improved ICP

In order to improve the low registration efficiency and poor accuracy caused by the size error and initial position's major difference of the workpiece in the registration process of off-line welding rectification, this paper adopts a coarse registration first and then fine registration's process strategy. On the basis of quaternion algorithm to achieve coarse registration, an iterative closest point (ICP) registration algorithm based on K-D tree nearest neighbor search method is proposed. In the precise registration algorithm, the K-D tree nearest neighbor search method is first used to improve the search speed of corresponding point pairs, and then the bidirectional search method is used to improve the registration accuracy. In order to verify the feasibility and effectiveness of the algorithm, the registration experiments are carried out on the point cloud data of circular weld, square weld and complex weld. The results show that the accuracy of the proposed method is 90% higher than the PCA algorithm when the time is similar, and compared with the traditional ICP algorithm, the registration accuracy and time of this method are improved by 35% and 55%. Therefore, the method presented in this paper has good efficiency, accuracy and stability in solving the problem of weld track point cloud data registration.