Miracle-dz/UniFAR-FTUs huggingface dataset:
RMHP_A_325074 4537..4544

1Nursing Department, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia; 2King Faisal Medical Complex, Ministry of Health, Taif, Saudi Arabia Introduction: Nurses in Saudi Arabia face several challenges in all phases of disaster nursing, such as the infancy of the specialty and a lack of education, preparedness, research, and expertise in both the clinical field and in academics. Overcoming these challenges will help both nurses and the development of the specialty itself in aspects such as policies and procedures, education, and research. Thus, the aim of this study was to explore strategies for improving disaster nursing in Saudi Arabia. Methods: A cross-sectional study with a principal component analysis (PCA) was conducted to identify the factors affecting disaster nursing in Saudi Arabia. The sample of the study was Saudi Arabian nurses, as they are first-line responders in disasters and pandemics. Results: From 800 distributed questionnaires, 569 completed questionnaires were returned, for a response rate of 71%. The findings of the PCA revealed two components that can be extracted from the data. The first is preparedness, which involves 13 items related to the actions that must be taken before a disaster occurs, with a loading range of 0.82 to 0.70. The second factor is the action taken after a disaster occurs, and there are seven items with a loading range of 0.83 to 0.73. Conclusion: For improved disaster nursing, it is essential to develop evaluation tools, create specific nursing legislation for disaster situations, provide personal protective equipment to nurses to minimize the risk of infection, and encourage nurses by appreciating their efforts to minimize their stress level during a disaster. It is also important to make sufficient supplies and equipment available to nurses during a disaster and provide them with psychological support while acknowledging the importance of contact with their families and friends.
Vivo Inhibition of Effector Cell Proliferation Regulatory T Cells: Evidence for In + CD25 + Promotion of Allograft Survival by CD4

Regulatory T cells preserve tolerance to peripheral self-Ags and may control the response to allogeneic tissues to promote transplantation tolerance. Although prior studies have demonstrated prolonged allograft survival in the presence of regulatory T cells (T-reg), data documenting the capacity of these cells to promote tolerance in immunocompetent transplant models are lacking, and the mechanism of suppression in vivo remains unclear. We used a TCR transgenic model of allograft rejection to characterize the in vivo activity of CD4 (cid:1) CD25 (cid:1) T-reg. We demonstrate that graft Ag-speciﬁc T-reg effectively intercede in the rejection response of naive T cells to established skin allografts. Furthermore, CFSE labeling demonstrates impaired proliferation of naive graft Ag-speciﬁc T cells in the draining lymph node in the presence of T-reg. These results conﬁrm the efﬁcacy of T-reg in promoting graft survival and suggest that their suppressive action is accomplished in part through inhibition of proliferation. The Journal of Immunology, 2004, 172: 6539–6544.
The Chromatin-associated Protein PWO1 Interacts with Plant Nuclear 3 Lamin-like Components to Regulate Nuclear Size 4

Spatial organization of chromatin contributes to gene regulation of many cellular processes and 31 includes a connection of chromatin with the nuclear lamina (NL). The NL is a protein mesh 32 that resides underneath the inner nuclear membrane (INM) and consists of lamins and lamina- 33 associated proteins. Chromatin regions associated with lamins in animals are characterized 34 mostly by constitutive heterochromatin, but association with facultative PWO1 protein interactors. We conducted co-immunoprecipitation experiments coupled with mass spectrometry using the PWO1:PWO1-GFP Arabidopsis transgenic line. The protein abundance was scored via label- free quantification (LFQ) analysis and a comparison to background sample (Col-0, wild type) was used to identify significantly enriched proteins in the PWO1:PWO1-GFP line. As a result, we obtained a list of 99 putative PWO1 interactors.
(2013) 300 Faces in-the-Wild Challenge: the first facial landmark localization challenge. In: 2013 IEEE International

Automatic facial point detection plays arguably the most important role in face analysis. Several methods have been proposed which reported their results on databases of both constrained and unconstrained conditions. Most of these databases provide annotations with different mark-ups and in some cases the are problems related to the accuracy of the ﬁducial points. The aforementioned issues as well as the lack of a evaluation protocol makes it difﬁcult to compare performance between different systems. In this paper, we present the 300 Faces in-the-Wild Challenge: The ﬁrst facial landmark localization Challenge which is held in conjunction with the International Conference on Computer Vision 2013, Sydney, Australia. The main goal of this challenge is to compare the performance of different methods on a new-collected dataset using the same evaluation protocol and the same mark-up and hence to develop the ﬁrst standardized benchmark for facial landmark localization.
Fractional Schr¨odinger equation in optics

In quantum mechanics, the space-fractional Schro¨dinger equation provides a natural extension of the standard Schro¨dinger equation when the Brownian trajectories in Feynman path integrals are replaced by Levy ﬂights. Here an optical realization of the fractional Schro¨dinger equation, based on transverse light dynamics in aspherical optical cavities, is proposed. As an example a laser implementation of the fractional quantum harmonic oscillator is presented, in which dual Airy beams can be selectively generated under oﬀ-axis longitudinal pumping.
The HP0165-HP0166 Two-Component System (ArsRS) Regulates Acid-Induced Expression of HP1186 (cid:2) -Carbonic Anhydrase in Helicobacter pylori by Activating the pH-Dependent Promoter (cid:1)

The periplasmic (cid:1) -carbonic anhydrase of Helicobacter pylori is essential for buffering the periplasm at acidic pH. This enzyme is an integral component of the acid acclimation response that allows this neutralophile to colonize the stomach. Transcription of the HP1186 (cid:1) -carbonic anhydrase gene is upregulated in response to low environmental pH. A binding site for the HP0166 response regulator (ArsR) has been identiﬁed in the promoter region of the HP1186 gene. To investigate the mechanism that regulates the expression of HP1186 in response to low pH and the role of the HP0165-HP0166 two-component system (ArsRS) in this acid- inducible regulation, Northern blot analysis was performed with RNAs isolated from two different wild-type H. pylori strains (26695 and 43504) and mutants with HP0165 histidine kinase ( ArsS ) deletions, after exposure to either neutral pH or low pH (pH 4.5). ArsS-dependent upregulation of HP1186 (cid:1) -carbonic anhydrase in response to low pH was found in both strains. Western blot analysis of H. pylori membrane proteins conﬁrmed the regulatory role of ArsS in HP1186 expression in response to low pH. Analysis of the HP1186 promoter region revealed two possible transcription start points (TSP 1 and TSP 2 ) located 43 and 11 bp 5 (cid:1) of the ATG start codon, respectively, suggesting that there are two promoters transcribing the HP1186 gene. Quantitative primer extension analysis showed that the promoter from TSP 1 (43 bp 5 (cid:1) of the ATG start codon) is a pH-dependent promoter and is regulated by ArsRS in combating environmental acidity, whereas the promoter from TSP 2 may be responsible for control of the basal transcription of HP1186 (cid:1) -carbonic anhydrase. that
EarthCube Data Capabilities: Collaborative Proposal: Jupyter meets the Earth: Enabling discovery in geoscience through interactive computing at scale

Our project seeks to advance interactive computing capabilities on the cloud and high performance computing (HPC) centers to better serve the needs of geoscience researchers. The proposed work will: (a) improve access to data sources and data catalogs by exposing them to users in the same interface where they conduct their computational work, (b) empower researchers to seamlessly utilize and combine cloud and HPC resources, (c) accelerate research by simplifying the process for scientists to create and deploy custom, interactive applications for their research question, and (d) facilitate dissemination of research ﬁndings to decision-makers, stakeholders, and the general public. We will achieve these goals by extending the current capabilities of Jupyter technologies for interactive computing.
Beyond valence in customer dissatisfaction

Dissatisfied customers may express their dissatisfaction behaviorally. These behavioral responses may impact the firms’ profitability. How do we model the impact of emotions on satisfaction and subsequent customer behaviors? There are essentially two approaches: the valence-based approach and the specific emotions approach. The authors indicate theoretically and show empirically that it matters to distinguish these approaches in services research. Dissatisfaction and the specific emotions disappointment and regret were assessed and their influence on customers’ behavioral responses (complaining, switching, word-of-mouth, and customer inertia) was examined, using a sample of over 900 customers. It was found that emotions have a direct impact on behavior, over and above the effects of dissatisfaction. Hence, the authors argue against incorporating emotions such as regret and disappointment into a general (dis)satisfaction measure (i.e., the valence-based approach), and in favor of a specific emotions approach to customer dissatisfaction. Implications for services marketing practice and theory are discussed. D 2002 Elsevier Inc. All rights reserved.
Indole-3-acetic Acid Synthesis in Tumorous and Nontumorous Species of Nicotiana1

The synthesis of indole-3-acetic acid (IAA) in the enzyme extracts of Nicotiana glauca, Nicotiana langsdorfti, their Fl hybrid, their amphidiploid hybrid, and the nontumorous mutant of the hybrid was investigated. Tryptamine, a possible precursor of IAA biosynthesis in Nicotana tabacum, was not found in the callus tissue of N. glauca, N. langsdorffli, and their Fl hybrid. In petiole slices, the synthesis of IAA progressively increased during 5 hours of incubation in 114Cltryptophan. The rate of synthesis was about equal in the hybrid and N. IangsdorMf but lower in N. glauca on either a cell or fresh weight basis. It was also found that tryptophan was about 25 times more efficient than tryptamine in promoting synthesis of IAA in petiole slices. then, 500 1l of NaHCO3 phase was counted with an Intertechnique SL-30 liquid scintillation counter. The external standard channel ratio method was used and background counts were subtracted. A mixture of toluene (Eastman Kodak, scintillation grade)-Omnifluor (New England Nuclear)-Triton X-100 (Rohm and Haas) (3.75 liters-15 g-1.87 liters) was used as scintillation fluid. It was found that the recoveries were 91% for IAA and less than 1% for tryptophan and tryptamine and hence the latter two compounds did not interfere with the assay of IAA.
Rock failure analysis based on a coupled elastoplastic-logarithmic damage model

The rock materials surrounding the underground excavations typically demonstrate nonlinear mechanical response and irreversible behavior in particular under high in-situ stress states. The dominant causes of irreversible behavior are plastic flow and damage process. The plastic flow is controlled by the presence of local shear stresses which cause the frictional sliding. During this process, the net number of bonds remains unchanged practically. The overall macroscopic consequence of plastic flow is that the elastic properties (e.g. the stiffness of the material) are insensitive to this type of irreversible change. The main cause of irreversible changes in quasi-brittle materials such as rock is the damage process occurring within the material. From a microscopic viewpoint, damage initiates with the nucleation and growth of microcracks. When the microcracks length reaches a critical value, the coalescence of them occurs and finally, the localized meso-cracks appear. The macroscopic and phenomenological consequence of damage process is stiffness degradation, dilatation and softening response. In this paper, a coupled elastoplastic-logarithmic damage model was used to simulate the irreversible deformations and stiffness degradation of rock materials under loading. In this model, damage evolution & plastic flow rules were formulated in the framework of irreversible thermodynamics principles. To take into account the stiffness degradation and softening on post-peak region, logarithmic damage variable was implemented. Also, a plastic model with Drucker-Prager yield function was used to model plastic strains. Then, an algorithm was proposed to calculate the numerical steps based on the proposed coupled plastic and damage constitutive model. The developed model has been programmed in VC++ environment. Then, it was used as a separate and new constitutive model in DEM code (UDEC). Finally, the experimental Oolitic limestone rock behavior was simulated based on the developed model. The irreversible strains, softening and stiffness degradation were reproduced in the numerical results. Furthermore, the confinement pressure dependency of rock behavior was simulated in according to experimental observations.
Control, implementation, and analysis of a dual two-level photovoltaic inverter based on modified proportional–resonant controller

This study presents a modified proportional-resonant (M-PR) control topology for single-stage photovoltaic (PV) system, operating both in grid-connected and stand-alone modes. Dual two-level voltage source inverter fed three-phase open-end winding transformer is used to supply the load in this scheme. The M-PR controller is developed for the inner current control loop of the system. The M-PR controller has the ability to track ac current with zero steady-state error. The outer dc-link voltage control loop is developed through the indirect vector control method at synchronously rotating reference frame. The control scheme ensures improved performance of the system at variable solar irradiance and load disturbances. The performance analysis of the dual two-level PV inverter is carried out for different operating conditions. The control scheme is implemented in MATLAB-SIMULINK environment. The theoretical results are verified through experiments in a laboratory prototype. The experimental results show close match with their theoretical counterparts.
The Discourse Particle Wal in Yucatec Maya: Uncertainty and Negativity across Sentence Types

The morpheme wal in Yucatec Maya is regarded informally as an epistemic modal, often translated with words like English ‘might’ or ‘maybe’. In this paper, we consider the use of wal across a broader range of environments, arguing for a complex picture of wal as a discourse particle as well as its interactions with other factors. First, we show that the semantic effect of wal differs systematically depending on its intonational realization. Second, we show that both intonational variants of wal are felicitous across a wide variety of sentence types, not just declaratives. Overall, we present an analysis in which stressed and unstressed variants of wal interact with different sentence types in principled ways to produce a range of apparent effects. Beyond furthering our understanding of these various elements in Yucatec Maya, the resulting picture contributes to our growing cross-linguistic understanding of discourse particles and their interactions with intonation.
Détection d’anomalies textuelles à base de l’ingénierie d’invite (Prompt Engineering-Based Text Anomaly Detection )

La détection d’anomalies textuelles est une tâche importante de la fouille de textes. Plusieurs approches générales, visant l’identification de points de données aberrants, ont été appliqués dans ce domaine. Néanmoins, ces approches exploitent peu les nouvelles avancées du traitement automatique des langues naturelles (TALN). L’avènement des modèles de langage pré-entraînés comme BERT et GPT-2 a donné naissance à un nouveau paradigme de l’apprentissage automatique appelé ingénierie d’invite (prompt engineering) qui a montré de bonnes performances sur plusieurs tâches du TALN. Cet article présente un travail exploratoire visant à examiner la possibilité de détecter des anomalies textuelles à l’aide de l’ingénierie d’invite. Dans nos expérimentations, nous avons examiné la performance de différents modèles d’invite. Les résultats ont montré que l’ingénierie d’invite est une méthode prometteuse pour la détection d’anomalies textuelles.
Region normalization for image inpainting based on dual-channel generative adversarial network

In order to solve the problem of artifact or image distortion when repairing the image with complex background as well as large and irregular damage, a region normalization image inpainting algorithm based on dual channel generative adversarial network is proposed. Firstly, the images to be repaired are fed into the parallel channel generative adversarial network where the damaged areas and the non-damaged areas are separately normalized through the basic region normalization (RN-B) to solve the deviation of mean and variance. Thereafter, a residual block containing hybrid dilated convolution and learnable region normalization (RN-L) is performed to capture multi-scale and multi-receptive field image information and automatically detect potentially damaged and undamaged regions for separate rate normalization. Subsequently, global radiological transformation is performed to enhance the fusion of damaged and undamaged regions. And the result is inputted to the decoding layer for decoding after the self-attention module. Finally, the results are sent to the Patch-GAN discriminator for discriminant optimization. Simulation experiments are carried out on the public datasets CelebA-HQ and Paris-street. Experimental results show that the proposed algorithm can enhance the accuracy of texture detail and effectively avoid image distortion, and is superior to state-of-the-art inpainting algorithms in terms of visual effect, PSNR, SSIM and L1 loss.
What do Students’ Interactions with Online Lecture Videos Reveal about their Learning?

Video viewing is an important component of online learning, yet little is known about what information about learning outcomes can be derived from students’ video control actions. We investigate the extent to which information on student learning is contained in their video-watching clickstreams (e.g. pausing, playing) immediately after watching a video. We analyzed data from 10,492 students who used an online learning platform for their Algebra 1 course. Our experiments encode students’ video-control clickstreams into sequences in several ways (e.g. aggregate actions, shuffle actions, and merge action types), and train Long Short-term Memory (LSTM) neural network models to predict after-video quiz scores (N = 32,482) from the sequences in a student-independent fashion. The results suggest that the action sequences contain a limited amount of information about student learning (r = 0.108 between model-predicted- and actual- quiz scores), with most of the information in simple counts of actions (r = 0.081) rather than the temporal ordering of actions. Combining information from video action sequences and traditional knowledge estimates from item-response theory (IRT) outperformed (r = 0.224) either approach independently. Implications for student modeling and adaptive learning support for viewing lecture videos are discussed.
ReStyle-MusicVAE: Enhancing User Control of Deep Generative Music Models with Expert Labeled Anchors

Deep generative models have emerged as one of the most actively researched topics in artificial intelligence. An area that draws increasing attention is the automatic generation of music, with various applications including systems that support and inspire the process of music composition. For these assistive systems, in order to be successful and accepted by users, it is imperative to give the user agency and express their personal style in the process of composition. In this paper, we demonstrate ReStyle-MusicVAE, a system for human-AI co-creation in music composition. More specifically, ReStyle-MusicVAE combines the automatic melody generation and variation approach of MusicVAE and adds semantic control dimensions to further steer the process. To this end, expert-annotated melody lines created for music production are used to define stylistic anchors, which serve as semantic references for interpolation. We present an easy-to-use web app built on top of the Magenta.js JavaScript library and pre-trained MusicVAE checkpoints.
Following the Trail of Fake News Spreaders in Social Media: A Deep Learning Model

Even though the Internet and social media are usually safe and enjoyable, communication through social media also bears risks. For more than ten years, there have been concerns regarding the manipulation of public opinion through the social Web. In particular, misinformation spreading has proven effective in influencing people, their beliefs and behaviors, from swaying opinions on elections to having direct consequences on health during the COVID-19 pandemic. Most techniques in the literature focus on identifying the individual pieces of misinformation or fake news based on a set of stylistic, content-derived features, user profiles or sharing statistics. Recently, those methods have been extended to identify spreaders. However, they are not enough to effectively detect either fake content or the users spreading it. In this context, this paper presents an initial proof of concept of a deep learning model for identifying fake news spreaders in social media, focusing not only on the characteristics of the shared content but also on user interactions and the resulting content propagation tree structures. Although preliminary, an experimental evaluation over COVID-related data showed promising results, significantly outperforming other alternatives in the literature.
The Impact of Digital Nudging Techniques on the Formation of Self-Assembled Crowd Project Teams

Self-assembling team formation systems, where online users can select their teammates, are gaining research and industry interest. Still, the benefits of diversity remain frequently untapped for these teams, as people tend to choose others similar to them. In this study, we examine whether making users aware of the team’s diversity can impact their selections. In a study involving 120 crowd participants, working on the scenario of a crowdsourced innovation project, we tested the effects of two choice architecture and nudging techniques. The first technique displayed explicit personalized diversity information in the form of the current team diversity score and diversity recommendations. The second technique used diversity priming, in the form of counter-stereotypes and all-inclusive multiculturalism. Our results indicate that, while priming deterred participants from picking teammates of different regions, displaying diversity information was the only factor to positively enhance diverse choices. These results were not moderated by the users’ ’‘need to belong” levels, an intrinsic motivation justifying one’s need to form social ties. Other factors which we also find to predict selection behavior were the participants’ region of origin, participants’ gender, teammates’ functional backgrounds, and teammates’ order of appearance. In light of these findings, we suggest that nudging techniques need to be cautiously applied to online team formation as the different techniques differ in their ability to evoke diversity among intrinsically diverse crowds, and that personalised displaying of diversity information seems most promising.