Miracle-dz/UniFAR-FTUs huggingface dataset:
Cucumber (Cucumis sativus L.) Fruit and Combination with Losartan Attenuate the Elevation of Blood Pressure in Hypertensive Rats Induced by Angiotensin II

Objectives Cucumis sativus L. (C. sativus) is vegetable commonly used for managing blood pressure and often consumed in combination with standard antihypertensive therapy, despite lack of scientific evidence supporting their use. Combination of herbs and standard medication could have positive or negative effects. Therefore, this study aimed to evaluate the antihypertensive activity of C. sativus and the combined effect with losartan in the hypertensive rat model induced by angiotensin II. Angiotensin II is a component of the renin-angiotensin-aldosterone system that, upon binding to its receptor, constricts blood vessels leading to elevation of blood pressure. Methods In an antihypertensive study, rats received C. sativus orally at doses of 9, 18, 27, and 36 mg/kg (full dose); while in a combination study, animals received losartan 2.25 mg/kg combined by either with C. sativus 9 or 18 mg/kg. The standards group received losartan 2.25 mg/kg or 4.5 mg/kg (full dose). Results Blood pressure was measured using the tail-cuff method. C. sativus significantly attenuated angiotensin II-induced hypertension as observed in groups receiving C. sativus at 9, 18, 27, and 36 mg/kg at 30 minutes after induction showed the average change (Δ) of systolic blood pressure (SBP) and diastolic blood pressure (DBP) with respect to time zero were 28.8/18.3, 24.8/15.8, 22.8/15.5, and 11.5/9.0 mmHg, respectively. Whereas the average change (Δ) of SBP and DBP in the rats receiving the combination of half doses of C. sativus and losartan were 8.8/9.0 mmHg, respectively. These diminished effects were better than a full dose of C. sativus and comparable with a full dose of losartan (6.5/7.8 mmHg). Conclusion The present findings indicate that C. sativus dose-dependently blocks blood pressure elevation induced by angiotensin II. The combination of half dose of C. sativus and losartan has an additive effect in lowering blood pressure.
Fit for Duty Assessment of Driver Fatigue based on Statistical Modelling of Cardiovascular Parameters

Driver fatigue is a risk factor for road crashes. Fit for duty technologies could play a pivotal role in countering these crashes. Heart rate variability (HRV) and the pulse wave shape are inﬂuenced by the autonomic nervous system and are therefore aﬀected by fatigue. This work focusses on modelling their relationship with fatigue and is based on data recorded in a simulated driving study. Six diﬀerent multivariate linear regression models, using either stepwise variable selection or principal component analysis, are presented in this study. To account for diﬀerences in physiology, individual participant baselines for HRV and pulse wave parameters are introduced. Stepwise regression using any kind of baseline yields the most promising results. The most promising predictors are the ratio LFHF between low and high frequency components of HRV and heart rate. Finally, a stepwise regression model with a baseline, which has an adjusted R 2 statistic of 0 . 17 , is proposed for further use. Nevertheless, further research with an extended dataset is necessary, incorporating a more diverse participant group and a higher number of recordings from severely sleepy drivers.
Identification and validation of key biomarkers associated with macrophages in nonalcoholic fatty liver disease based on hdWGCNA and machine learning

Background: NAFLD has attracted increasing attention because of its high prevalence and risk of progression to cirrhosis or even hepatocellular carcinoma. Therefore, research into the root causes and molecular indicators of NAFLD is crucial. Methods: We analyzed scRNA-seq data and RNA-seq data from normal and NAFLD liver samples. We utilized hdWGCNA to find module-related genes associated with the phenotype. Multiple machine learning algorithms were used to validate the model diagnostics and further screen for genes that are characteristic of NAFLD. The NAFLD mouse model was constructed using the MCD diet to validate the diagnostic effect of the genes. Results: We identified a specific macrophage population called NASH-macrophages by single-cell sequencing analysis. Cell communication analysis and Pseudo-time trajectory analysis revealed the specific role and temporal distribution of NASH-macrophages in NAFLD. The hdWGCNA screening yielded 30 genes associated with NASH-macrophages, and machine learning algorithms screened and obtained two genes characterizing NAFLD. The immune infiltration indicated that these genes were highly associated with macrophages. Notably, we verified by RT-qPCR, IHC, and WB that MAFB and CX3CR1 are highly expressed in the MCD mouse model and may play important roles. Conclusions: Our study revealed a macrophage population that is closely associated with NAFLD. Using hdWGCNA analysis and multiple machine learning algorithms, we identified two NAFLD signature genes that are highly correlated with macrophages. Our findings may provide potential feature markers and therapeutic targets for NAFLD.
Involvement or attachment theory: Exploring the determinants and consequences of individual (work) involvement with particular reference to escape motivation

ABSTRACT The following research on individual involvement and escape motivation is presented to open the possibility that studies of ‘involvement’ may reveal different areas for psychotherapy than the predominant concept of ‘attachment’, which has formed the basis of new and existing therapies. Particularly, whether notions of ‘involvement capacity’, ‘escape motivation’ and other involvement typologies, as well as the psychological/sociological interplay between individual and organisational/societal perspectives, are pertinent for psychotherapy. The previously unpublished research, a follow-up to a 1979 study, again combining psychological and sociological methodologies for researching involvement, reinforced that a significant theme, not given attention in the literature, was that people also work to escape from their personal problems. Organisational/managerial perspectives are contrasted with individual perspectives and notions as Etzioni’s moral and alienative involvement are re-evaluated. Mixed methods were used including Bruner’s narrative analysis, Weber’s ideal types, and a phenomenological stance influenced by existentialism and psychoanalysis. The results arising from this empirical study of people who are nurses in the context of a subsequent literature review indicate they are motivated to get involved in work: to escape personal problems; earn money; and, for the satisfaction from the work itself. There are also detrimental effects arising from the ‘emotional labour’ required.
Artificial Intelligence Based Robust Clinical Data Classification for Intradialytic Hypotension Diagnosis

The demands for communication and computation technologies are growing in daily lives, which drives the utilization of sustainable artificial intelligence (AI) in various applications, particularly healthcare. Intradialytic hypotension (IDH) becomes a common problem at the time of hemodialysis treatment. Forecasting whether patients would face IDH during hemodialysis (HD) was not a simple task. IDH can be linked with many risk factors, means that conventional statistical methods cannot identify the relations that affect it. In this regard, the usage of methods related to machine learning (ML) could allow the detection of complex relations, as they could solve complexities without being explicitly programmed. The deep learning (DL) method will use training data for discovering underlying patterns and helpful in building methods and fitting the optimal method for prediction. In this aspect, this article presents a Robust Deep Learning based Clinical Data Classification for IDH (RDLCDC-IDH) diagnosis. The presented RDLCDC-IDH model aims to detect and classify IDH effectually and timely manner. In the presented RDLCDC-IDH model, data preprocessing is performed to transform it into a compatible format. To properly detect and classify IDH, the RDLCDC-IDH technique make use of deep convolutional neural network (DCNN) method. For effectual hyperparameter adjustment of the DCNN model, the sparrow search optimization (SSO) algorithm is exploited in this work. To demonstrate the enhanced outcomes of the RDLCDC-IDH technique, a wide-ranging simulations can be made. The experimentation outcomes highlighted the enhanced results of the RDLCDC-IDH method on IDH diagnosis.
Insulators Used in Outdoor Power Applications: Materials and Coatings

The optimum design of the electrical insulation system is essential for robust operation of the power grid and its equipment/devices. Accordingly, choosing the insulating material is crucial, so the insulation can withstand suffering the high stresses caused by abnormal operating conditions and external effects. The solid insulating materials, like ceramics and plastics, have been used vastly in the power applications since they can satisfy the required electrical and mechanical aspects. In this work, the outdoor insulators are demonstrated and classified into single and composite materials. Although they have been operating effectively, the faults still occur causing failure of the device or the whole system. Consequently, the failure causes are illustrated. Coating the insulator surface is discussed elaborately since it aims at enhancing the insulator performance to cope with the adverse effects causing the failure. Either hydrophobic (HP) or field graded material (FGM) coating is used depending on the failure cause. The research works that investigated coating same material insulators are compared together. The comparisons serve as a useful guide for choosing the proper coating and might be helpful for future work prospective developments.
A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net

The recent surge in the use of Deep Neural Networks (DNNs) has also made its mark in the field of Audio Enhancement (AE), providing much better quality than the classical methods. Although, there are dedicated audio processing DNNs, yet, many recent models of AE have utilized U-Net: a DNN based on Convolutional Neural Network (CNN), fundamentally developed for image segmentation. It is found that the useful features hidden in the time domain are highlighted when the audio signal is converted to a spectrogram, which can be treated as an image. In this article, we will review the recent work, utilizing U-Nets for different AE applications. Different than other published reviews, this review focuses entirely on AE techniques based on image U-Nets. We will discuss the need for AE, U-Net comparison to other DNNs, the benefits of converting the audio to 2D, input representations that are useful for different AE applications, the architecture of vanilla U-Net and the pre-trained models, variations in vanilla architecture incorporated in different E models, and the state-of-the-art AE algorithms based on U-Net in various applications. Apart from speech and music, this article discusses a wide range of audio signals e.g. environmental, biomedical, bioacoustics, and industrial sounds, not covered collectively in a single article in previously published studies. The article ends with the discussion of colored spectrograms in future AE applications.
Non-suicidal self-injury in adolescents with mood disorders and the roles of self-compassion and emotional regulation

Objective We aimed to investigate the characteristics and psychological mechanism of non-suicidal self-injury (NSSI) in adolescents with mood disorders. We examined how self-compassion and emotional regulation affected NSSI and tested the mediating role of self-compassion in the link between emotional regulation and NSSI. Method We recruited outpatient and inpatient adolescent patients with bipolar and related disorders or depressive disorders (DSM-5), with a focus on NSSI. We also recruited healthy controls from the community. We collected demographic and clinical data. The Adolescent Self-injury Questionnaire, Self-compassion Scale (SCS), and Emotion Regulation Questionnaire (ERQ) were used to assess the frequency and severity of NSSI, level of self-compassion, and emotional regulation. Results In total, we recruited 248 adolescent patients with mood disorders (N = 196 with NSSI, and 52 without NSSI) and 212 healthy controls. NSSI was significantly associated with the female sex, lower levels of education and less use of cognitive reappraisal strategies, lower levels of self-warmth, and higher levels of self-coldness. Multivariate analysis of variance showed that there were significant differences in the scores of ERQ, cognitive reassessment score, and the scores of SCS among the three groups, but no statistical differences in expressive suppression score among the three groups. Self-warmth had a mediating effect between cognitive reappraisal and NSSI behavior. Conclusion NSSI is prevalent among adolescent patients with mood disorders in clinical settings, especially among girls and those with lower levels of education and less cognitive reappraisal strategies. More clinical attention is needed. Self-compassion and its factors may mediate the association between emotional regulation and NSSI. Clinical implications and future research directions were discussed.
Study of Mobile Robot Operations Related to Lunar Exploration

Mobile robots extend the reach of exploration in environments unsuitable, or unreachable, by humans. Far-reaching environments, such as the south lunar pole, exhibit lighting conditions that are challenging for optical imagery required for mobile robot navigation. Terrain conditions also impact the operation of mobile robots; distinguishing terrain types prior to physical contact can improve hazard avoidance. This thesis presents the conclusions of a trade-off that uses the results from two studies related to operating mobile robots at the lunar south pole. The lunar south pole presents engineering design challenges for both tele-operation and lidar-based autonomous navigation in the context of a near-term, low-cost, short-duration lunar prospecting mission. The conclusion is that direct-drive tele-operation may result in improved science data return. The first study is on demonstrating lidar reflectance intensity, and near-infrared spectroscopy, can improve terrain classification over optical imagery alone. Two classification techniques, Naive Bayes and multi-class SVM, were compared for classification errors. Eight terrain types, including aggregate, loose sand and compacted sand, are classified using wavelet-transformed optical images, and statistical values of lidar reflectance intensity. The addition of lidar reflectance intensity was shown to reduce classification errors for both classifiers. Four types of aggregate material are classified using statistical values of spectral reflectance. The addition of spectral reflectance was shown to reduce classification errors for both classifiers. The second study is on human performance in tele-operating a mobile robot over timedelay and in lighting conditions analogous to the south lunar pole. Round-trip time delay between operator and mobile robot leads to an increase in time to turn the mobile robot around
Atmospheric Modeling Data Assimilation And Predictability

Thank you very much for reading atmospheric modeling data assimilation and predictability. As you may know, people have look numerous times for their favorite novels like this atmospheric modeling data assimilation and predictability, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they are facing with some infectious bugs inside their computer.
The Psychological Well-Being of Young Women Entering into Child Marriages

The phenomenon of child marriage is a problem that occurs worldwide. Adolescents who engage in child marriage tend not to achieve psychological well-being. This is closely related to emotional maturity in resolving family conflicts. This research uses qualitative methods with a phenomenological approach. The data collection procedure consisted of interviews and documentation for 3 participants with a marital background, as they were engaged out of wedlock and pregnant. The results showed that young women who underwent child marriage did not have good psychological well-being. This is evident in the aspects of self-acceptance, positive relationships with others, autonomy, mastery of the environment, Purpose in life and personal growth. Young women's psychological well-being is also affected by several factors, including support, change, compassion, motivation, counsel, problem solving, and knowledge of marriage. Adolescents who are successful and able to overcome their problems are said to reach a state of psychological well-being, which means that this leads to the state of individuals who are able to face various things that can trigger problems in their lives.
The Effect of Confining Pressure and Water Content on Compressive Strength and Deformation of Ice‐Rich Silty Sand

The characteristics of ice‐rich frozen soils are important to engineering design in cold‐climate regions. Previous work has concentrated on uniaxial strength properties, and limited data exist on triaxial strength and deformation as a function of volumetric ice content and confining pressure. Triaxial compressive tests carried out on ice‐rich frozen silty sand indicated that the strength decreases to a minimum and then increases up to that of pure ice for a range of volumetric ice contents. However, the effect of confining pressure on the strength depends on the volumetric ice content itself. The strength was at a nearly constant minimum level when the volumetric ice content was between 48.2 and 65.1 per cent, dominated by the cohesion of the ice matrix. In contrast, at volumetric ice contents of > 27.2 to < 50.2 per cent and > 80.9 per cent, the strength increased with increasing confining pressure. The volumetric ice contents corresponding to maximum failure strain and minimum strength were 50.2 and 61.9 per cent, respectively. Thus, in this range an increase of about 10 per cent in volumetric ice content causes the failure strain to drop to the value for pure ice. The results indicate that there is a transition zone when the volumetric ice content is between 50.2 and 61.9 per cent that separates sample behaviour from that of frozen soil to that of pure ice. Copyright © 2016 John Wiley & Sons, Ltd.
Lexical and cognitive development of children learning regional languages: Studies from the Netherlands

Regional language speakers are subject to negative social judgments. In this contribution, I provide an overview of research in the Netherlands with children who are regional language learners against the backdrop of this deficit perspective. Findings on the lexical and cognitive development of children from Fryslân, a northern Dutch province, and Limburg, a southern Dutch province, demonstrate that regional language acquisition is neither associated with language delays nor with any cognitive difficulties. Linguistic overlap between Frisian and Limburgish, on the one hand, and Dutch, on the other hand, results in ample opportunities to share linguistic resources, experiences, and knowledge. Especially unbalanced children benefit from this cross-linguistic overlap because they can make use of their stronger language to perform in the weaker language. Cross-linguistic regularities between the regional and national language are helpful and support performance in the regional language. Results on cognitive effects suggest that regional language learners have some selective attention advantages. Although significant, the effects are small, the advantages do not last long, and they require sufficient exposure to and proficiency in the regional language.
Optimal Bell’s Palsy Treatment: Steroids, Antivirals, and a Timely and Personalized Approach

Importance: The optimal treatment approach for patients with Bell’s palsy, a condition characterized by acute facial nerve palsy, remains unclear. The present study was designed to provide insights into the most effective treatment strategies, whether steroids alone or steroids plus antiviral agents, as well as the optimal timing of treatment initiation. Objective: To investigate the impact of treatment modalities and timing on the recovery rates of Bell’s palsy patients and to assess the roles of individual factors. Design, Setting, and Participants: This retrospective analysis included 1504 patients with Bell’s palsy who visited Kyung Hee University Hospital. Patients were divided based on the treatment modality (steroid monotherapy vs. combined steroid and antiviral therapy) and the timing of treatment initiation (≤72 vs. >72 h). Main Outcomes and Measures: The primary outcome was the recovery rate, as assessed by the House–Brackmann (HB) grade. Secondary outcomes included factors such as age, electroneurography (ENoG) and electromyography (EMG) results, and comorbid conditions. Results: A combined comparison of patients treated with steroids plus antivirals and steroids alone, stratified by treatment start time, showed that recovery rates were highest in patients who received steroid monotherapy initiated within 72 h (OR 2.36; p < 0.05). Patients with severe Bell’s palsy tended to benefit more from combined therapy when treatment was initiated within 72 h. The recovery rate was higher in patients who received steroid monotherapy than combined therapy (86.32% vs. 79.25%, p < 0.05). Initiating treatment beyond 72 h was associated with a higher recovery rate than starting treatment within 72 h (85.69% vs. 76.92%, p < 0.05). An evaluation of the factors affecting recovery showed that patients aged 20 to 39 years had a higher recovery rate than other age groups (OR 1.47; p < 0.05). Fairly predictive EMG results were associated with significantly higher recovery rates (OR 3.52; p < 0.05). Conclusions: These findings underscore the importance of individualized treatment approaches in Bell’s palsy management. Steroid monotherapy remains effective, although combined treatment may have potential advantages, especially in patients with more severe disease. The best treatment results were achieved when steroid treatment was administered within 72 h. Our results suggest that there may be more flexibility in the application of the 72 h treatment period if we consider the time of treatment initiation alone, but this should take into account patient behavior patterns and the limitations of retrospective analysis. Further research is warranted to validate these findings and refine treatment recommendations for patients with Bell’s palsy.