Miracle-dz/UniFAR-FTUs huggingface dataset:
Embrace the leadership challenge: The role of Gay men's internalized sexual stigma on the evaluation of others' leadership and one's own.

Grounded in the framework of the gay glass ceiling, the current research investigated the effect of gay men's internalized sexual stigma (ISS) on both the perceived effectiveness of other gay men's leadership and on their self-perceived leadership effectiveness and their intention to apply to a leadership position. In three studies (N = 402), we manipulated either the leader's sexual orientation (SO) (study 1), or his adherence to traditional gender roles (TGR) (study 2), or participants' fictitious masculinity score (study 3). Our hypotheses were as follows: the leader's SO and TGR would moderate the association of gay participants' ISS with their positive attitudes towards the leader and with his leadership effectiveness; and gay participants' masculinity threat would moderate the association of their ISS with their intention to apply to a leadership position, and with their self-perceived effectiveness as potential leaders. Moderated regression analyses showed that: participants reported a more positive attitude towards a gay man (vs. heterosexual) as leader only when they had low - and not high - ISS; participants with high (vs. low) ISS perceived the masculine gay leader as more effective than the feminine gay leader; under masculinity threat, participants with high (vs. low) ISS showed less intention to apply to a leadership position. These studies provide both confirmation and novel insights into the key role of internalized sexual stigma and traditional gender roles. Indeed, these factors can strengthen and perpetuate the gay glass ceiling effect.
Sb2Te3 Nanoparticles with Enhanced Seebeck Coefficient and Low Thermal Conductivity

Nanostructured thermoelectric semiconductors represent a promising new direction that can further increase energy conversion efficiency, which requires the realization of thermoelectric nanocrystals with size comparable to their de Broglie wavelength while maintaining a high electrical conductivity. Here, we demonstrate a new facile process to grow self-assembled Sb2Te3 nanoparticles with controlled particle size and enhanced thermoelectric properties by using a catalyst-free vapor transport growth technique. The samples show much more enhanced Seebeck coefficients than that of bulk Sb2Te3 with similar charge carrier concentration. Meanwhile, the thermal conductivity measurements with pulse photothermal reflectance suggest that the these Sb2Te3 nanoparticle films show much reduced thermal conductivity as compared to that of bulk Sb2Te3. The discussed approach is promising for realizing new types of highly efficient thermoelectric semiconductors.
Effects of 5-Week Foam Rolling Intervention on Range of Motion and Muscle Stiffness

Abstract Kiyono, R, Onuma, R, Yasaka, K, Sato, S, Yahata, K, and Nakamura, M. Effects of 5-week foam rolling intervention on range of motion and muscle stiffness. J Strength Cond Res 36(7): 1890–1895, 2022—In clinical and sports settings, foam rolling (FR) intervention is widely used to increase the range of motion (ROM). However, the chronic effects of FR on ROM and muscle stiffness are unclear. The aim of this study was to investigate the effects of 5-week FR intervention on dorsiflexion ROM (DFROM) and shear elastic modulus of the medial gastrocnemius (MG) muscle. Accordingly, 30 healthy young adults were enrolled and randomly assigned to either the FR or control group with the former receiving 90 seconds of FR thrice per week over 5 weeks. Thereafter, DFROM, passive torque at DFROM, and shear elastic modulus of the MG during passive ankle dorsiflexion were assessed using a dynamometer and ultrasonography before and after 5 weeks. Our results showed that the FR group exhibited a significant increase in DFROM (Δ = 11.7%, p < 0.05, effect size = 0.39), but no changes in passive torque at DFROM, and shear elastic modulus at 0° and 10° dorsiflexion. Moreover, significant correlations were observed between change in DFROM and change in passive torque at DFROM in the FR group (rs = 0.607, p = 0.016). These results suggested that FR was an effective method to increase DFROM given its ability to change passive torque at DFROM (stretch tolerance) without altering muscle stiffness.
Effects of forehead cooling and supportive care on menopause-related sleep difficulties, hot flashes and menopausal symptoms: a pilot study

ABSTRACT Objective/Background This pilot study explored the efficacy of a novel forehead cooling device for perceived sleep difficulties and hot flashes in menopausal-age women. Participants 20 women (55.1 ± 4.2 years; 19 post-menopausal) with insomnia symptoms and self-reported two or more hot flashes per day. Methods Participants completed daily assessments of sleep and hot flashes (via diaries) across 1 baseline week and 4 weeks of open-label, in-home, nightly treatment with a forehead cooling device (15–18°C) along with sleep hygiene instructions. They also completed ratings of insomnia and menopausal symptoms using standardized questionnaires. Results Women reported reductions in sleep onset latency (SOL), wakefulness after sleep onset (WASO), and nocturnal hot flash severity during the first week of treatment (SOL: 25.7 ± 18.4 min; WASO: 36.3 ± 27.3 min; hot flash severity: 3.0 ± 2.8) compared with baseline (SOL: 38 ± 26.3 min; WASO: 52.2 ± 35.6 min; hot flash severity: 6.8 ± 3.7), with further improvements after 2–4 weeks of use (p < .001). There were also clinically meaningful reductions in insomnia severity and hot flash-related daily interference and lower psychological and physical symptom scores on the Greene climacteric scale after treatment (all p’s<0.001). Conclusions This exploratory, naturalistic, pilot study shows that nightly use of a forehead cooling device produces improvements in self-reported sleep and reductions in insomnia, hot flash, and other menopausal, symptoms. Controlled studies are warranted to determine the role of this therapy in the management of sleep difficulties and menopausal symptoms in women. Further mechanistic studies are needed to understand the physiological impact of forehead cooling on sleep and menopausal symptoms.
Sexual activity and contraceptive use during social distancing and self-isolation in the COVID-19 pandemic

Abstract Objectives The aims of the study were to investigate the effects of social distancing during the COVID-19 pandemic on the use of hormonal contraceptives, their discontinuation and the risk of unplanned pregnancy. Methods The study enrolled 317 women listed in the database of the Department of General Surgery and Medical-Surgical Specialties, University of Catania, Italy, family planning clinic who were known to be using hormonal contraceptives. The women were contacted by telephone and asked whether they would like to participate in the study. If they agreed, they were then emailed a questionnaire about their social behaviour and sexual activity during the pandemic, according to their cohabiting status, i.e., whether they were continuing to use their hormonal contraception and whether they had had an unplanned pregnancy. Results The questionnaire was completed by 175 (81.8%) women who were using short-acting reversible contraception (SARC) and by 90 (87.4%) women who were using long-acting reversible contraception (LARC). All married and cohabiting women were continuing to use their contraceptive method. None had had an unplanned pregnancy. On the other hand, 51 (50.5%) non-cohabiting or single women had discontinued their SARC method while social distancing, for non-method-related reasons; however, 47 (46.5%) non-cohabiting or single women had continued their sexual activity, infringing social distancing rules, and 14.9% had had an unplanned pregnancy, for which they had sought a termination. Conclusion Several non-cohabiting women using SARC had discontinued their contraceptive method during the pandemic but had continued to engage in sexual activity and had had an unplanned pregnancy. Clinicians should counsel women about what they should do in regard to contraception in the event of new, future social distancing measures.
Radiomics Approaches for Predicting Liver Fibrosis With Nonenhanced T1‐Weighted Imaging: Comparison of Different Radiomics Models

Liver fibrosis is a common process resulting from various etiologies. Sustained progression of liver fibrosis leads to cirrhosis, even hepatocellular carcinoma. Thus, noninvasive staging of liver fibrosis is of clinical importance. Radiomics is an emerging approach for staging liver fibrosis. However, the feature selection methods and classifier models are complicated, and may result in a discrepancy of diagnostic performance owing to different radiomics models.
An Undergraduate Student‐Led Neuroscience Outreach Program Shows Promise in Shifting Teen Attitudes About Drugs

ABSTRACT Drug Outreach, Promoting Awareness (DOPA) is an undergraduate outreach program for local high school students designed to convey the neurobiological basis, risks, and addictive potential of commonly abused drugs. Here we describe DOPA and evaluate the program, including its impact on high school student attitudes about drug harm risk and addiction. Undergraduate neuroscience students versed in the neurobiology, physiology, and policy of drugs are trained in active learning methods, enabling them to create engaging and interactive classroom‐based educational materials. Survey results showed that participation in DOPA increased high school student perceptions of the addictive potential and harm risk of drugs, which studies have shown to be inversely correlated with drug‐taking. High school students also responded positively to the interactive nature of the program. These findings demonstrate how extensively trained undergraduates who are close peers to high school students can effectively lead science outreach initiatives and shift adolescent attitudes about drugs.
RESISTANCE TO DIEBACK DISEASE CAUSED BY FUSARIUM AND LASIODIPLODIA SPECIES IN CACAO (THEOBROMA CACAO L.) GENOTYPES

SUMMARY Fusarium and Lasiodiplodia species invade feeding lesions caused by mirid bugs (Distantiella theobroma [Dist.] and Sahlbergella singularis Hagl.) and inflict serious damage and yield loss to susceptible cacao (Theobroma cacao L.) varieties in West Africa. As it is the fungal invasion rather than the physical feeding injury by mirids that cause dieback and tree death in cacao, a dieback resistance strategy in cacao crop must take into account resistance to these causal agents. Twenty-nine and 15 cacao genotypes were screened in the laboratory and the greenhouse, respectively, for resistance to isolates of Fusarium decemcellulare and Lasiodiplodia theobromae at Imperial College London's Biological Sciences Campus, UK. Resistance was assessed as the size of necrotic lesions, distance of fungal colonisation in the stem and the proportion of seedlings with dieback symptoms. Genotypic differences were found in both laboratory and greenhouse tests among various cacao genotypes, and the clones showed a wide range of disease reactions from highly resistant to very susceptible. The pathogenicity of F. decemcellulare and L. theobromae were similar in this study, which suggests that a breeding programme for controlling one of the pathogens can have benefit against the other. Direct significant correlations (r = 0.7) were obtained between visual dieback assessment scores and the percentage cross-sectional area of stem necrosis. Moreover, the response of inoculated stem segments corresponded to the reaction of intact plants despite the variation in the used methodology. Three cacao genotypes (CATIE 1000, T85/799 and MXC 67) were resistant or moderately resistant to F. decemcellulare and L. theobromae. These genotypes could be useful sources of resistance to both pathogens and other wilt causing pathogens in cacao.
Psychophysics of vibrotactile stimulation

The effects of a wide range of stimulus parameters upon the psychophysical responses of subjects are important to an understanding of the functional characteristics of neural systems that underlie responses to cutaneous mechanical stimulation and the interactions that may occur between these systems. This understanding may also be useful to design considerations in the development of devices for tactile communication. This paper begins with a brief description of the two major systems in terms of psychophysical measurements and then focuses on a more detailed examination of possible interactions between them. The effects of time and space variables, such as frequency, temporal and intensity relationships between stimuli, area of stimulation, and surface gradients on the skin, are considered.
Self-care with the skin of Community Health Agents

This document gives formatting guidelines for authors preparing papers for publication in the International Journal of Engineering and Applied Sciences. The authors must follow the instructions given in the document for the papers to be published. The margins must be set as follows: Top = 1.7cm, Bottom = 1.7cm, left = 1.7cm, Right = 1.7cm. Paper Title must be in Font Size 22, with Single Line Spacing. Authors Name must be in Font Size 11. Abstract should contain at least 250 words. Abstract explanation should be Times New Roman font, 09 Size, Bold, Single line spacing, text alignment should be justified. References and Author’s Profile must be in Font Size 8, Hanging 0.25 with single line spacing.
COVID-19 Twitter Monitor: Aggregating and Visualizing COVID-19 Related Trends in Social Media

Social media platforms offer extensive information about the development of the COVID-19 pandemic and the current state of public health. In recent years, the Natural Language Processing community has developed a variety of methods to extract health-related information from posts on social media platforms. In order for these techniques to be used by a broad public, they must be aggregated and presented in a user-friendly way. We have aggregated ten methods to analyze tweets related to the COVID-19 pandemic, and present interactive visualizations of the results on our online platform, the COVID-19 Twitter Monitor. In the current version of our platform, we offer distinct methods for the inspection of the dataset, at different levels: corpus-wide, single post, and spans within each post. Besides, we allow the combination of different methods to enable a more selective acquisition of knowledge. Through the visual and interactive combination of various methods, interconnections in the different outputs can be revealed.
ITLS ‐ WP ‐ 15 ‐ 15 Collecting longitudinal data from freight operators : survey design and implementation

Freight transport research has generally been limited by a lack of data of the breadth and quality available for passenger transport, particularly in terms of behavioural data. Although there are a number of reasons for this lack of data, the challenges of collecting freight data including the expense, participant burden and confidentiality issues are amongst the most significant. Although some improvements in technology and survey design have allowed for the collection of more behavioural freight data more improvements would be beneficial. This paper discusses the survey design and implementation of a survey intended to collect longitudinal behavioural data on the responses of freight transport firms to the introduction of environmental policies. The design of the survey is centred around a hypothetical scenario where respondents are asked how they would complete a given freight task within common constraints including time windows and delivery requirements. One of the key components of the survey design is a dynamic component that is intended to simulate the changing business environment to which firms are required to adapt. This paper also looks at the participant burden involved in completing the survey and compares how this differs depending on how respondents completed the survey.
EMPIRICAL ANALYSIS OF ROUGH SET CATEGORICAL CLUSTERING TECHNIQUES BASED ON ROUGH PURITY AND VALUE SET JAMAL UDDIN UNIVERSITI TUN HUSSEIN ONN MALAYSIA

Clustering a set of objects into homogeneous groups is a fundamental operation in data mining. Recently, attention has been put on categorical data clustering, where data objects are made up of non-numerical attributes. The implementation of several existing categorical clustering techniques is challenging as some are unable to handle uncertainty and others have stability issues. In the process of dealing with categorical data and handling uncertainty, the rough set theory has become well-established mechanism in a wide variety of applications including databases. The recent techniques such as Information-Theoretic Dependency Roughness (ITDR), Maximum Dependency Attribute (MDA) and Maximum Significance Attribute (MSA) outperformed their predecessor approaches like Bi-Clustering (BC), Total Roughness (TR), Min-Min Roughness (MMR), and standard-deviation roughness (SDR). This work explores the limitations and issues of ITDR, MDA and MSA techniques on data sets where these techniques fails to select or faces difficulty in selecting their best clustering attribute. Accordingly, two alternative techniques named Rough Purity Approach (RPA) and Maximum Value Attribute (MVA) are proposed. The novelty of both proposed approaches is that, the RPA presents a new uncertainty definition based on purity of rough relational data base whereas, the MVA unlike other rough set theory techniques uses the domain knowledge such as value set combined with number of clusters (NoC). To show the significance, mathematical and theoretical basis for proposed approaches, several propositions are illustrated. Moreover, the recent rough categorical techniques like MDA, MSA, ITDR and classical clustering technique like simple K-mean are used for comparison and the results are presented in tabular and graphical forms. For experiments, data sets from previously utilized research cases, a real supply base management (SBM) data set and UCI repository are utilized. The results reveal significant improvement by proposed techniques for categorical clustering in terms of purity (21%), entropy (9%), accuracy (16%), rough accuracy (11%), iterations (99%) and time (93%). PTT PERP UST AKA AN TUN KU T UN AMI NAH
Performance Evaluation of a Combination of the Parallel Bisection Method and the Block Inverse Iteration Method with Reorthogonalization for Eigenvalue Problems on MIC processor

— We discuss the implementation, performance tuning, and evaluation of an eigensolver of real symmetric tridiag-onal matrices using the bisection method and the block inverse iteration method with reorthogonalization on Intel Xeon Phi (Xeon Phi) many integrated core (MIC) processor. We develop an OpenMP thread parallel program for the eigensolver for Xeon Phi and experimentally determine the optimal block size parameter for both the MIC and CPU environments. Moreover, we perform experiments for evaluating the performance of the algorithm with the optimal block size. The eigensolver exhibits higher computation speed and accuracy in the MIC environment than the MRRR algorithm, which is known as the conventional high-speed eigensolver.
Vector Shape Classification and Z indexing

—Vector images are the compact representation of shapes using hard mathematics. Shapes are stored compactly and render efficiently. The advantage of these vector images is that images can be fraction of size as compare to the bitmap. Much work has been done on digital images from different perspective not only to find detail parametric definition of shapes but also their display mechanism. However, this paper is to justify these shapes and then their order of display. Vector shapes consist of different shapes such as line, ellipse, rectangle etc. It is necessary to identify these shapes and their mathematical formulas. We will discuss the shapes with their extracted parametrical identification using formulas and their drawl by using Z index.
Constrained Concealment Attacks against Reconstruction-based Anomaly Detectors in Industrial Control Systems

Recently, reconstruction-based anomaly detection was proposed as an effective technique to detect attacks in dynamic industrial control networks. Unlike classical network anomaly detectors that observe the network traffic, reconstruction-based detectors operate on the measured sensor data, leveraging physical process models learned a priori. In this work, we investigate different approaches to evade prior-work reconstruction-based anomaly detectors by manipulating sensor data so that the attack is concealed. We find that replay attacks (commonly assumed to be very strong) show bad performance (i.e., increasing the number of alarms) if the attacker is constrained to manipulate less than 95% of all features in the system, as hidden correlations between the features are not replicated well. To address this, we propose two novel attacks that manipulate a subset of the sensor readings, leveraging learned physical constraints of the system. Our attacks feature two different attacker models: A white box attacker, which uses an optimization approach with a detection oracle, and a black box attacker, which uses an autoencoder to translate anomalous data into normal data. We evaluate our implementation on two different datasets from the water distribution domain, showing that the detector’s Recall drops from 0.68 to 0.12 by manipulating 4 sensors out of 82 in WADI dataset. In addition, we show that our black box attacks are transferable to different detectors: They work against autoencoder-, LSTM-, and CNN-based detectors. Finally, we implement and demonstrate our attacks on a real industrial testbed to demonstrate their feasibility in real-time.
TINEA CORPORIS AND TINEA CRURIS IN QINGDAO:AN AETIOLOGICAL INSPECTION

Objective To understand the structure of pathogenic fungi that cause tinea corporis and tinea cruris in Qingdao. Methods From August 2010 to August 2011,354 patients with tinea corporis or tinea cruris were seen in our hospital,the scurf from afflicted parts was collected and investigated microscopically,the pathomycetes were isolated and cultured,and the strains identified. Results A total of seven kinds of pathogenic fungus,222 strains,were isolated,of which,Trichophyton rubrum 153 strains(68.9%),Trichophyton mentagrophytes 42(18.9%),Candida 17(7.7%),Microsporum canis five(2.3%),Microsporum gyseum two(0.9%),Trichophyton tonsurans two(0.9%) and Trichophyton soudanense one(0.4%). Conclusion At present,the pathogenic bacteria responsible for tinea corporis and tinea cruris in Qingdao is mainly Dermatophytes,followed by Candida.Trichophyton rubrum is the most commonly seen dermatophyte.
Safety Analysis System using Smart Helmet

— In this paper, we introduce a safety analysis system based on our previous research [1]. The proposed method uses a smart helmet to collect data through experimental tests on construction worksites, and we design a safety analysis algorithm that can be applied to the safety management of actual construction worksites based on the data. Smart helmet is designed and implemented to detect dangerous situations and prevent accidents on the construction worksites by using the following three sensors. Acceleration sensor for a sudden falling analysis of construction worker, carbon monoxide sensor for ﬁre or gas leak analysis of construction sites, and ultrasonic sensor for objects falling analysis. As shown by our experimental test results, we expect that the proposed method can be used for prevention of accidents at the construction worksites and for quick response in case of an accident.