Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal cutoff scores of the Chinese version of 15-item negative symptom assessment that indicate prominent negative symptoms of schizophrenia

Objective The Chinese version of 15-item negative symptom assessment (NSA-15) is an instrument with a three-factor structure specifically validated for assessing negative symptoms of schizophrenia. To provide a reference for future practical applications in the recognition of schizophrenia patients with negative symptoms, this study aimed to determine an appropriate NSA-15 cutoff score regarding negative symptoms to identify prominent negative symptoms (PNS). Methods A total of 199 participants with schizophrenia were recruited and divided into the PNS group (n = 79) and non-PNS group (n = 120) according to scale for assessment of negative symptoms (SANS) scores. Receiver-operating characteristic (ROC) curve analysis was used to determine the optimal NSA-15 cutoff score for identifying PNS. Results The optimal cutoff NSA-15 score for identifying PNS was 40. Communication, emotion and motivation factors in the NSA-15 had cutoffs of 13, 6, and 16, respectively. The communication factor score had slightly better discrimination than scores on the other two factors. The discriminant ability of the global rating of the NSA-15 was not as good as that of the NSA-15 total score (area under the curve (AUC): 0.873 vs. 0.944). Conclusion The optimal NSA-15 cutoff scores for identifying PNS in schizophrenia were determined in this study. The NSA-15 provides a convenient and easy-to-use assessment for identifying patients with PNS in Chinese clinical situations. The communication factor of the NSA-15 also has excellent discrimination.
Development, predictors, and effects of trainees’ organizational identification during their first year of vocational education and training

The vocational identity of trainees is one component of their professional competence and is considered to be a central goal of vocational education and training (VET) programs. From the numerous identity constructs and conceptualizations, this study focuses on the organizational identification of trainees, that is, the extent to which trainees internalize the values and goals of their training company and perceive themselves as part of this company. We are specifically interested in the development, predictors, and effects of trainees’ organizational identification, as well as the interrelations between organizational identification and social integration. We use longitudinal data of n = 250 trainees in dual VET programs in Germany at the very beginning of their VET program (t1), after 3 months (t2), and after 9 months (t3). A structural equation model was used to analyze the development, predictors, and effects of organizational identification for the first 9 months of training and the cross-lagged effects between organizational identification and social integration. The results showed a high stability of trainees’ organizational identification over the first 9 months. Regarding the predictors, the results indicated positive direct and indirect effects of the formal socialization tactics implemented by the training company, as well as of support by the trainer at the beginning of the training. However, collegial support at the beginning of the training did not seem to play a significant role in organizational identification. Moreover, organizational identification positively affected trainees’ emotional engagement and self-perceived competence while negatively predicting dropout intentions after 9 months of training. Finally, the cross-lagged effects between organizational identification and social integration were not significant, and only at t3 were these constructs positively correlated. However, regarding the development, predictors, and effects, very similar results were found for organizational identification and social integration. The results underline the positive significance of organizational identification for the individual, the company, and society, even at this early stage of training. The results are discussed regarding both their scientific and practical implications.
Optimization of surgical tourniquet usage to improve patient outcomes: Translational cross-disciplinary implications of a surgical practice survey

Tourniquet use is common practice in many millions of orthopaedic procedures annually. Recent reviews of risks and benefits of surgical tourniquet use have primarily involved meta-analyses, many of which have forgone a comprehensive risk-benefit analysis to simply question whether “tourniquet or no tourniquet” use produces improved patient outcomes, often leading to limited, inconclusive, or conflicting results. To investigate further, a pilot survey was undertaken to determine current practices, opinions, and understandings among orthopaedic surgeons in Canada regarding use of surgical tourniquets in total knee arthroplasties (TKAs). Results of the pilot survey showed a wide range of understanding and practice associated with tourniquet use in TKAs, especially regarding tourniquet pressures and tourniquet times, two key factors known from basic research and clinical studies to impact the safety and efficacy of tourniquet use. The wide variation of use indicated by the survey results reveals important implications for surgeons, researchers, educators, and biomedical engineers, to better understand the association between key tourniquet parameters and outcomes assessed in research, which may be factors leading to their often limited, inconclusive, and conflicting results. Lastly, we provide an overview of the overly simplified assessments of tourniquet use in meta-analyses, whose conclusions may not provide an understanding of how or whether key tourniquet parameters might be optimized to retain the benefits of tourniquet use while mitigating the associated real or perceived risks.
Temporal attention

Attention, that is, the ability to focus processing resources on a specific part of sensory input, is often thought of as being mainly allocated in space, toward specific objects or modalities. However, attention can also be allocated within time. Temporal attention can be induced implicitly, that is, through learning of temporal regularities between at least two events, or explicitly, by the active instruction to attend to a specific time point. Moreover, temporal attention can be induced via external rhythmic stimulation. Many studies throughout the last 120 years have shown that, irrespective of the way temporal attention is induced, it facilitates processing of upcoming events. Based on early findings measuring reaction time, researchers initially assumed that temporal attention primarily accelerates motor processing. Within the last 20 years, however, more and more evidence has emerged supporting the view that temporal attention facilitates perceptual processing. Moreover, temporal attention may even interact with other attentional domains such as spatial attention or feature-based attention. In the present article, we summarize classical as well as current findings and theoretical accounts on how temporal attention affects perceptual processing. Furthermore, we sketch current challenges and open questions in research on temporal attention.
The contribution and interactive relationship of tourism industry development and technological innovation to the informatization level: Based on the context of low-carbon development

Research background: Informatization is a new economic form arising from a new round of technological and industrial changes. Information technology has been used to promote the integrated development of the tourism industry and propel technological innovation, which will help accelerate the achievement of the strategic goals of carbon emission peaking and carbon neutrality. China’s informatization level has improved to a certain extent due to the concentration of capital and technological innovation brought about by the government-led model, and also owing to the consumer dynamics released by the industry-side reform. Research contents and methods: This study constructs a panel vector auto-regression model to investigate the impact of tourism industry development and technological innovation on informatization based on Chinese provincial statistics from 2010 to 2019. This study adopts the entropy method, Monte Carlo simulation, variance decomposition, and pulse response to investigate the impact, characteristics, and trends of their interactions. Results: First, tourism industry development, technological innovation, and informatization all experience inertia development and have self-reinforcing mechanisms during the research period. Second, tourism industry development and technological innovation have a significantly positive impact on the enhancement of informatization, and their influence presents a trend, from upward to downward. Third, tourism industry development has a positive impact on technological innovation, and the response trend presents a curve approximately inverted U-shape. Fourth, from the results of variance decomposition, the contribution of technological innovation to the improvement of informatization level increases rapidly and reaches 18.5% and then levels off. The contribution rate of tourism industry development to the improvement of informatization level gradually rises and reaches 5.1%, finally tending to be stable. Contribution: This study reveals that tourism industry development and technological innovation will exert different pulling effects on informatization at different development stages in China and their advantages and provides theoretical contributions to tourism industry development and technological innovation on the advancement of informatization level. The research results provide a reference basis for the government and related industrial sectors in how to effectively facilitate the development of informatization in the context of the low-carbon economy.
Salinity stress endurance of the plants with the aid of bacterial genes

The application of plant growth-promoting bacteria (PGPB) is vital for sustainable agriculture with continuous world population growth and an increase in soil salinity. Salinity is one of the severe abiotic stresses which lessens the productivity of agricultural lands. Plant growth-promoting bacteria are key players in solving this problem and can mitigate salinity stress. The highest of reported halotolerant Plant growth-promoting bacteria belonged to Firmicutes (approximately 50%), Proteobacteria (40%), and Actinobacteria (10%), respectively. The most dominant genera of halotolerant plant growth-promoting bacteria are Bacillus and Pseudomonas. Currently, the identification of new plant growth-promoting bacteria with special beneficial properties is increasingly needed. Moreover, for the effective use of plant growth-promoting bacteria in agriculture, the unknown molecular aspects of their function and interaction with plants must be defined. Omics and meta-omics studies can unreveal these unknown genes and pathways. However, more accurate omics studies need a detailed understanding of so far known molecular mechanisms of plant stress protection by plant growth-promoting bacteria. In this review, the molecular basis of salinity stress mitigation by plant growth-promoting bacteria is presented, the identified genes in the genomes of 20 halotolerant plant growth-promoting bacteria are assessed, and the prevalence of their involved genes is highlighted. The genes related to the synthesis of indole acetic acid (IAA) (70%), siderophores (60%), osmoprotectants (80%), chaperons (40%), 1-aminocyclopropane-1-carboxylate (ACC) deaminase (50%), and antioxidants (50%), phosphate solubilization (60%), and ion homeostasis (80%) were the most common detected genes in the genomes of evaluated halotolerant plant growth-promoting and salinity stress-alleviating bacteria. The most prevalent genes can be applied as candidates for designing molecular markers for screening of new halotolerant plant growth-promoting bacteria.
Editorial: Perception, cognition, and working memory: interactions, technology, and applied research

COPYRIGHT © 2023 Xu and Burns. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Perception, cognition, and working memory: interactions, technology, and applied research
Knowledge-based engineering and computer vision for configuration-based substation design

Introduction: As the increase in electrification poses new demands on power delivery, the quality of the distribution system is paramount. Substations are a critical part of power grids that allow for control and service of the electrical distribution system. Substations are currently developed in a project-based and manually intensive manner, with a high degree of manual work and lengthy lead times. Substations are primarily sold through tenders that are accompanied by an inherent need for engineering-to-order activities. Although necessary, these activities present a paradox as tender processes must be agile and fast. To remedy this shortcoming, this article outlines a knowledge capture and reuse methodology to standardize and automate the product development processes of substation design. Methods: A novel framework for substation design is presented that implements knowledge-based engineering (KBE) and artificial intelligence methods in computer vision to capture knowledge. In addition, a product configuration system is presented, utilizing high-level CAD templates. The development has followed the KBE methodology MOKA. Results: The proposed framework has been implemented on several company cases where three (simplified) are presented in this paper. The framework decreased the time to create a 3D model from a basic electric single line diagram by performing the identification and design tasks in an automated fashion. Discussion: Ultimately, the framework will allow substation design companies to increase competitiveness through automation and knowledge management and enable more tenders to be answered without losing engineering quality.
Convergence analysis of stochastic gradient descent on strongly convex objective functions

Recently, (3) posed an open problem on whether the Stochastic Gradient Descent (SGD) algorithm, without averaging, could achieve the optimal O( 1 ) error convergence rate on strongly convex (possibly non-smooth) functions. Our work gives an armative answer to this question for a subclass of functions. In high dimension, challenges arise in uniting the analyses of dierent optimality conditions for general strongly convex functions. We provide a subclassication scheme for these functions, using a rened denition of strong convexity and a relaxed denition of strong smoothness. We show how each denition captures the class of strongly convex functions and how we can describe the lower and upper bound on the norm of the subgradients of the function, which characterizes the diculty of optimizing it. Our
EM Field Enhancement for Array Antenna byUsing the Array of EBG Cells

In this paper the mutual coupling in array antennas where the mutual coupling resulting poor radiation efficiency is minimized with the help of a single line of EBG structure. In general each element in the array antenna produce their respective radiation and the final pattern will be the superimposition of all these individual patterns, in this process some of the components in the space wave vector of one element may cancel the neighbour element components this implies the loss of energy. Now in the current paper the problem is rectified by introducing a single line of EBG structure and the comparative analysis is illustrated in this paper.
Adaptive SLIC superpixel segmentation based on images of UAV forward-view

Although the original Simple Linear Iterative Clustering (SLIC) superpixel segmentation algorithm is simple and efficient, the segmentation effect has a strong dependence on the number of initial clusters, so it is not free of human-computer interaction when dealing with real images. Aiming at the problem of low automation above, this paper introduces the Gray-level Cooccurrence Matrix (GLCM) and give the formula for calculating the number of initial clustering centers by evaluating the image complexity. An adaptive SLIC algorithm is designed for the characteristics of forward-view images in UAV low-altitude flight scenes, combined with the trade-off of image segmentation accuracy and speed under obstacle avoidance requirements. The experiments show that the method can quantify the image complexity effectively, having a great performance on both classical BSDS500 dataset and the forward-view images in the UAV low-altitude flight scenes.
Recent progress in flexible micro-pressure sensors for wearable health monitoring

In recent years, flexible micro-pressure sensors have been used widely in wearable health monitoring applications due to their excellent flexibility, stretchability, non-invasiveness, comfort wearing and real-time detection. According to the working mechanism of the flexible micro-pressure sensor, it can be classified as piezoresistive, piezoelectric, capacitive and triboelectric types. Herein, an overview of flexible micro-pressure sensors for wearable health monitoring is presented. The physiological signaling and body motions contain a lot of health status information. Thus, this review focuses on the applications of flexible micro-pressure sensors in these fields. Additionally, the contents of sensing mechanism, sensing materials and performance of flexible micro-pressure sensors are introduced in detail. Finally, we predict the future research directions of the flexible micro-pressure sensors, and discuss the challenges in practical applications.
Online Interactive Flipped Classroom Teaching in Pediatrics for Medical Undergraduates

Objectives: To introduce online flipped classroom teaching for medical undergraduates in Pediatrics and to assess students' engagement and satisfaction with the students and faculty with the flipped classroom teaching method. Methods: An interventional education study was conducted on online flipped classrooms for final-year medical undergraduates. The core team of faculty members was identified, students and faculty were sensitized, and pre-reading material and feedback forms were validated. Students were engaged using the Socrative app, and feedback from students and faculty was collected using Google Forms. Results: One hundred sixty students and six faculty members participated in the study. During the scheduled class, 91.9% of students were engaged. The majority of the students strongly agreed that the flipped classroom was interesting (87.2%) and interactive (87%) and developed an interest in the subject of Pediatrics (86%). Faculty were also motivated to adopt this method. Conclusion: The present study revealed that introducing flipped classroom strategy in an online model improved students' engagement and increased their interest in the subject.
Strong uniform consistency of nonparametric estimation of the censored conditional mode function

Let (T n ) n≥1 be a sequence of independent and identically distributed of interest random variables and (X n ) n≥1 be a sequence of covariates. In the censorship model, the random variable T is subject to random censoring by another random variable C. Let Θ(x) be the conditional mode function of T given X = x. In this article, we define a new kernel estimator Θ n (x) of Θ(x) and we establish the uniform strong consistency with a rate of convergence.
A New Method for the Image Texture Representation

Texture is an important element to human vision, and it has been found to provide cues to scene depth and surface orientation. The pity is that it is hard to adequately model texture so far, and most research on texture is carried out on the Brodatz texture collection. However, the appearance of texture in unconstrained imagery is substantially different from that represented in Brodatz set, and textures in these real-world images are distorted by artifacts such as those resulting from non-uniform lighting, shading and warping in the 3-D space. This makes the problem of texture region extraction even more difficult. In view of above reasons, we adopt previous research experience on which texture is useful for decoding shapes and perspective projections, to present the overall process of representing texture using texture histograms, and new representations of texture is based upon histograms of texture elements. The texture elements are defined from the transformation and quantization of QMG (a quadrature mirror filter) wavelet transform energies. Several experimental evaluations of the wavelet texture feature sets that demonstrate excellent performance in classifying Brodatz textures are presented, and several transformations that allow for approximate rotation or scale invariance are also investigated. The texture histogram representation satisfies the objectives of (1) providing a representation for image or regional texture that is compatible with color histograms, (2) being compatible with compressed-domain texture extraction techniques. By using the histogram and binary set representations of texture we efficiently and effectively represent texture information in images and regions. These visual dimensions are extremely useful for image search and retrieval. Finally, we introduce the process of generating the texture histogram and binary texture set-based feature spaces that are symmetric to those for color histograms. The objectives of obtaining these representations of texture are for measuring the similarity of textures and extracting texture regions from images.
Radiated and reflected Doppler effects

Till now was known only one Doppler effect. In the article, we have named it classical. By the exact solution of correct mathematical problems with initial and boundary conditions which in mathematics are named as Cauchy’s problems adequate to physical processes which are described by Maxwell’s equations forming system of the partial differential equations of hyperbolic type of the problems of mathematical physics, existence of two Doppler effect was discovered. They differ from each other quantitatively and on physical sense. Classical Doppler effect, according to its physical sense, we have named radiated Doppler effect. Other effect, earlier completely unknown, according to physical sense, we have named reflected Doppler effect. The second new physical phenomenon derived as a result of research in this article, we have named deviation of radiated (classical) Doppler effect. The sense of opening is that the quantitative value of radiated Doppler effect measured by the receiver depends on an angle between the direction of a radiator movement and the direction from a radiator to the receiver. Existence of this effect is known to physics long ago. However, strictly reasonable mathematical model is offered for the first time.