Miracle-dz/UniFAR-FTUs huggingface dataset:
Construction of a Mental Health Education Model for College Students Based on Fine-Grained Parallel Computing Programming

Mental health and mental health problems of college students are becoming more and more obvious, and there is more and more negative news caused by psychological problems, and society from all walks of life has given high attention to this problem. Given the new situations and new problems, how to keep up with the times and reform and innovate in the content, method, and path of psychological education in colleges and universities is an important work of ideological and political education in colleges and universities. Because fine-grained category information can provide rich semantic clues, fine-grained parallel computing techniques are widely used in tasks such as sensitive feature filtering, medical image classification, and dangerous goods detection. In this study, we adopt a fine-grained parallel computing programming approach and propose a multiobjective matrix regular optimization algorithm that can simultaneously perform the joint square root, low-rank, and sparse regular optimization for bilinear visual features, which is used to stabilize the higher-order semantic information in bilinear features, improve the generalization ability of features, and apply it to the construction of mental health education models for college students to promote the construction of mental health education bases, improve mental health education network platform, and strengthen the construction of mental health education data platform. A new practical aspect has been added to the abstract. The saliency-guided data augmentation method in this study is an improvement on random data augmentation but reduces the randomness in the data augmentation process and significantly improves the results. The best result belongs to SCutMix data augmentation, which improves by 1.9% compared to the baseline network.
Financial Decision-Making in Neurological Patients

Financial abilities (FA) are a multi-dimensional domain comprising a wide range of conceptual, pragmatical, and judgmental skills ranging from basic abilities, such as bill payment, to high level abilities, such as financial decision-making (FDM). Preserved FDM abilities include the capacity to recognize fraud attempts, and they are fundamental for a person’s independence. Previous studies have reported decreased FDM in older adults and in patients with mild cognitive impairment (MCI), who consequently become more susceptible to fraud attempts. However, FDM has scarcely been investigated in other neurological populations, and it is unclear whether FDM may be predicted by more basic FA. The aim of the present study was to investigate FDM across patients with MCI, Parkinson’s disease (PD), or stroke, as well as healthy controls (HC), and to explore to what extent FDM could be inferred by other FA. We collected FDM and FA performances using the NADL-F short battery. Performances in the NADL-F short subtests were compared among groups. Additionally, the relationship between the scores at the FDM subtest and the performance obtained in other financial subtests of the NADL-F short were investigated for each group of participants. MCI patients performed worse than HC in FDM and in several FA domains. Conversely, FDM was relatively preserved in our sample of PD and stroke patients. In HC, FDM was associated with numeracy and financial knowledge applied to everyday situations, whereas this was true with some basic FA in both MCI and PD patients. No significant association was observed in stroke patients. Our results suggest that FDM is a complex ability, only partially inferable from other FA.
Cable yarding productivity models: a systematic review over the period 2000–2011

ABSTRACT The efficiency of cable-based yarding systems has been studied extensively, resulting in numerous work productivity models (i.e. models predicting the ratio between output and time). Productivity models are used in both research and operations management, but are laborious to develop. Efficient use of existing models is essential, but there is a lack of overviews of available models. Therefore, work productivity models developed in recent years were compiled, with the aim of increasing their visibility, accessibility and comparability to potential users and other interested parties. This compilation should facilitate comparisons and evaluations of the models and their influential parameters, and the synthesis of existing models. A systematic review of the international scientific literature on cable logging published between 2000 and 2011 was performed. Twenty-one publications describing productivity models were identified. These publications originated from four different continents, with most coming from Asia (specifically, Turkey). Many similarities were found between the models. For instance, more than half use yarding distance as an independent variable, whereas lateral yarding distance and load characteristics were used in only a third of the models. However, there were also many differences in terms of modeling praxis, model features, included parameters and the units used. Analysis of the compiled models suggests some potentially fruitful directions for future work in the field of cable logging productivity. More generally, model compilations such as that presented herein enable a range of analyses and harmonizations that benefit all kinds of forest operations.
Preclinical and Clinical Medical Students’ Perception of the Learning Environment: A Reference to the Forensic Medicine and Clinical Toxicology Course

Purpose Understanding learning environments is vital for developing curricula. This study aims to evaluate medical students’ achievements and perception of learning environments considering the Forensic Medicine and Clinical Toxicology course as an analog for the curricular transition process. Methods A cross-sectional study was conducted among undergraduate medical students at the Faculty of Medicine, Tanta University, from August 2020 to October 2021. Using the Dundee Ready Education Environment Measure (DREEM) questionnaire, the perception of 621 students (of which 307 were enrolled in the integrated curriculum and 314 in the traditional curriculum) were compared. Furthermore, the appropriate tests of significance and correlations were used to compare students’ perception according to their enrollment, age, gender, and previous year grade point average. Results The mean overall DREEM score was 121.04 ± 22.35, implying a more positive than negative learning environment, that is, a more positive learning perception, with students’ perceptions of teachers moving in the right direction, students’ academic self-perceptions getting more on the positive side, more positive attitudes regarding student’s perceptions of the learning environment, and not-too-bad student’s social self-perception. Medical students enrolled in the integrated curriculum showed higher DREEM scores, with significantly better learning and academic self-perceptions (p < 0.05). Knowledgeable, qualified faculties are the most significant characteristic feature in both systems. A significant number of students achieved excellent grades in the integrated curriculum (n = 740 out of 1076, 68.8%) than in the traditional one (n = 470 out of 961, 48.9%) (p < 0.0001). Conclusion This study revealed a smooth, successful transition from the traditional to integrated curriculum among Egyptian medical students. The main areas for improvements are focusing on factual teaching, implementing student-centered teaching activities, promoting students’ memorizing, and engaging students in activities that may help them enjoy learning.
Climate Factors and Maize Price Volatility in Developing Countries: Evidence from Benin

Changes in climate conditions are expected to significantly alter food production patterns and increase food price volatility, leading to challenges for food and nutrition security. Thus, this paper aims to investigate the extent to which climate factors contribute to the volatility of maize price in Benin, using monthly data from 7 markets. To this end, an autoregressive condi tional heteroskedasticity in mean (ARCH-M) model is estimated. Mean and variance equations of monthly maize price are specified as functions of temperature, rainfall of the growing season and a set of control variables including a policy variable and the international price of maize with an ARCH(1) term in the variance equation. The findings from the mean equation sug gest that rainfall has a negative effect on maize prices. Moreover, the estimation results from the variance equation indicate that rainfall and temperature are negatively associated with price volatility. Therefore, the findings indicate that climate change will affect maize price volatility.
Crabgrass as an equine pasture forage: impact of establishment method on yield, nutrient composition, and horse preference

Abstract Warm-season grasses (WSG) incorporated into traditional cool-season rotational grazing systems to increase summer yields are typically established in monoculture in separate pasture areas. Few studies have evaluated alternative interseeded establishment of WSG, despite potential benefits for improving biodiversity and land-use efficiency. The objective of this study was to determine the impact of establishment method (monoculture vs. interseeded) on crabgrass pasture forage yield, nutritive value, and preference under equine grazing. Three adult standardbred mares grazed two main plots on two consecutive days (8 hr/d) for three grazing events in 2019: Jul 28/29 (GRAZE 1), Aug 20/30 (GRAZE 2), Oct 1/2 (GRAZE 3). Each main plot contained four replicates of three treatments: mixed cool-season grass (CSG); Quick-N-Big crabgrass (CRB) [Digitaria sanguinalis (L.) Scop. ] interseeded into existing cool-season grass (INT), and CRB established as a monoculture (MON). The cool-season grass mix included Inavale orchardgrass [Dactylis glomerata (L.)], Tower tall fescue [Lolium arundinaceum (Schreb.) Darbysh. ], and Argyle Kentucky bluegrass [Poa pratensis (L.)]. Herbage mass (HM) and sward height (SH) were measured prior to each grazing event and samples were collected (0800–1000 h) for chemical composition analysis. Observed grazing time (GT) in each sub-plot as determined by 5-min scan sampling was utilized as marker of horse preference. Forage HM was greater in MON (8043 ± 1220 kg/ha) than CSG (5001 ± 1308 kg/ha; P = 0.003), with a trend for greater total HM in MON vs. INT (6582 ± 1220 kg/ha: P = 0.06), but HM did not differ between INT and CSG. The SH was also greatest for MON (28 ± 1.11; INT: 23.6 ± 1.11; CSG: 19.7 ± 1.37 cm; P < 0.003). Forage nutrients (digestible energy and crude protein) were largely similar across treatments and met requirements of horses at maintenance. Horse GT was lower in MON (22.6 ± 3.77 min/sub-plot) than in INT (31.9 ± 3.79 min/sub-plot; P = 0.003) and there was a trend for lower GT in MON vs. CSG (29.9 ± 4.17 min/sub-plot: P = 0.07). These results indicate interseeding CRB would not effectively increase yields of traditional cool-season grass equine rotational grazing systems and would not supply similar levels of summer forage provided by monoculture establishment. Results of this study also suggest horses may prefer cool-season grass pasture forage over warm-season crabgrass.
Ethno-botanical Survey and Chemical Study of Medicinal Plants Traditionally used to Treat Anemia in Yakoma Territory (Nord Ubangi), Democratic Republic of the Congo

Aims of the Study: To identify plant species traditionally used to treat anemia in Yakoma territory and to evaluate their chemical composition. Place and Duration: Yakoma Territory (survey) and University of Kinshasa (Phytochemical study), from August and October 2019. Methods: Ethnobotanical survey according to the "snowball" sampling technique among traditional healers (based on the free consent of the respondents), chemical analyses of plant materials (chemical screening, TLC, phytomarkers content, minerals composition) according to standard methods. ED-XRF was used for mineral analysis. Microsoft Excel version 2010, Origin version 8.5 Pro and IBM SPSS statistics version 20 software packages were used for data processing and analysis. Results and Discussion: The survey showed that 18 plant species are traditionally used by Ngbandi traditional healers to treat anemia in Yakoma territory. They belong to 16 families and 17 genera. The most used organs are the leaves (68.4%) and the roots (10.5%). Decoction and infusion are the most used mode of preparation (33.3% each), followed by cooking (22.2%) and maceration (11.1%). The oral route (77.8%) is the most used mode of administration followed by the enema (16.7%) and the anal route (5.6%). Morphological types consist of herbs and trees (33.3% each) and shrubs and lianas (16.7% each). The biotope types consist of forest plants (44.4%), cultivated plants/Crops (38.9%), marshy ground plants (11.1%) and ruderal plants (5.6%). These plants belonging to five biological types: erected therophytes (44.4%), mesophanerophytes (27.8%), microphanerophytes and climbing phanerophytes (11.1% each) and lianescent phanerophytes (5.56%). These anti-anemic plant species are mostly Pantropical and Afro-tropical (39% of species each) followed by Guineo-Congolese (17% of species) and American (5%). Chemical analysis revealed the presence of alkaloids, anthocyanins, flavonoids, anthraquinones and terpenoids and various minerals including iron, zinc, copper, calcium, magnesium and manganese. Conclusion: In the current state of knowledge, the survey of anemic plants from this part of the Democratic Republic of the Congo is reported for the first time.
Quasi-breakdown of ultrathin gate oxide under high field stress

A new oxide failure mode of ultrathin gate oxide is reported. During high constant current stressing, V/sub G/ variation with time shows two distinct modes, i.e., a stable mode and a fluctuation mode named as quasi-breakdown. Once the quasi-breakdown starts, gate current in low field abruptly increases. From the experimental results, it could be concluded that the quasi-breakdown occurs when injected electrons travel in the oxide conduction band ballistically. Localized physical damage near the Si/SiO/sub 2/ interface is believed to be the cause of the quasi-breakdown, The great increase of gate current after the quasi-breakdown was modeled by a superposition of F-N tunneling current and direct tunneling current with a finite series resistance, and a good agreement has been found. <<ETX>>
A gestão da inovação nas PME's da Beira Interior: as perspetivas dos gestores

Perante a atual conjuntura, as empresas estao inseridas num mercado empresarial cada vez mais competitivo, tornando-se urgente uma adaptacao ou modificacao da sua gestao. Sabe-se que e atraves da inovacao que as empresas conseguem ser competitivas, pelo que e importante a sua implementacao constante e a consequentemente procura de novos produtos e de novos processos de producao, para poderem fazer face a concorrencia e manterem a sua posicao competitiva no mercado. Dada a importância do estudo da tematica da inovacao nas empresas, este artigo tem como objetivo analisar as diferentes perspetivas da inovacao nas pequenas e medias empresas (PME’s) da Beira Interior de Portugal. Na metodologia adotada utilizou-se como instrumento de investigacao o questionario do CIS III 2008 e o tratamento estatistico dos dados foi elaborado com base numa analise fatorial. Da analise dos dados podemos concluir, que os gestores inovam tendo em conta tres perspetivas muito importantes: por um lado com o objetivo de reduzir custos e assegurar a sustentabilidade ambiental, por outro pela necessidade de atualizacao, e por outro, numa perspetiva de orientacao para o mercado.
Dentists’ perceptions on present and future dental practice during the COVID-19 pandemic: An embedded study

Background: The emergence of the COVID-19 pandemic has placed a significant burden on everyone. Although dental professionals are at an increased risk of COVID-19 infection, currently, very little is known about how oral health professionals and their professions could be affected by the pandemic. This study aims to investigate dentists' perceptions on present and future dental practice in light of the COVID-19 pandemic. Methods: We conducted an embedded mixed-methods study at Manipal College of Dental Sciences, Mangalore, with Indian dentists registered with the Dental Council of India. Results: Of the 976 participating dentists, 61% were females, 32% were 40 years of age or younger. Nearly half of the respondents (54%) acknowledged that the lockdown measures caused them a severe financial burden, and 56% were seriously concerned about being a source of infection to their family, friends, and community. Although 79% felt very comfortable or somewhat comfortable going back to work, they were all worried that Personal Protective Equipment (PPE) use would increase their financial burden and impact the number of patients seeking care. Even though a vast majority received the necessary information regarding returning to practice from their concerned dental regulatory bodies, some were unsure about the reuse of the PPEs because of the conflicting information they received. Conclusion: The COVID-19 pandemic affected participants' professional lives negatively. Their major concerns were being a source of infection to their families and community. Providing information to dental professionals in a timely manner may prepare dentists to provide safe care to their patients while protecting themselves, their staff, and their families.
Gain and maximum output of implantable hearing devices in patients with moderate to severe sensorineural hearing loss

Background: To determine the dynamic range and the maximum output of three current middle ear implants and to discuss optimal candidacy for middle ear implantation. Study Design: Clinical study. Material and Methods: Gain and output measurements were compared for three types of middle ear implants: the Otologics middle ear transducer (MET), the Vibrant Soundbridge (VSB), and the Direct Acoustic Cochlear Stimulator (DACS). The per formance of these selected implants in users with severe, predominantly sensorineural, hearing loss (50–65 dB HL) was studied. Patients with chronic external otitis and sensorineural hearing loss used either a MET (n=9) or a VSB (n=9) implant. Patients with a predominantly sensorineural hearing loss after surgically treated otosclerosis used a DACS ( n=4). Patients were selected from two different implant teams but evaluated with the same protocol. The relative gain at threshold level was deter mined, viz. the bone-conduction threshold minus the aided soundfield threshold, divided by the bone-conduction threshold. Input–output measurements were performed with the devices in linear amplification mode and with unlimited output. In this latter data set, the maximum output and the input dynamic range of the devices were determined. Results: The relative gain for each of the three implants was comparable; however, the values were slightly lower than the gen erally accepted target values. The input dynamic range of the devices varied, with the widest range for the DACS and Oto logics devices. Conclusion: The results from this study indicate that the first generation DACS device is a good option for patients with mod erate/severe sensorineural hearing loss and surgically treated otosclerosis who require a hearing implant.
Comparison of Kernel Support Vector Machine Multi-Class in PPKM Sentiment Analysis on Twitter

PPKM is the Indonesian government's policy to deal with the spread of the coronavirus since early 2021. Until now, PPKM is still the main topic to prevent the spread of COVID-19. This policy has generated various responses from the public, especially on Twitter. A sentiment analysis process is needed to process the text obtained from Twitter. Sentiment analysis is a form of representation of text mining and text processing. This study aims to analyze public sentiment towards PPKM through data obtained from Twitter using the multi-class SVM algorithm. In implementing multi-class SVM, an analysis of the Polynomial and RBF kernels was carried out on the One Against One and One Against Rest methods which showed that the combination of One Against Rest and the Polynomial kernel obtained the best accuracy, which was 98.9%. Unlike the case with the combination of One Against One and Kernel RBF, which obtained the worst accuracy, 77.6%. The best model produces precision, recall, and f1-score values ​​of 97%, 98%, and 97%. Based on the confusion matrix results, the best model has a positive class distribution = 912, neutral = 51, and negative = 26. Overall, the model that uses polynomial kernel produces higher accuracy, both applied to the One Against One and One Against Rest methods. In contrast, the model that uses the RBF kernel produces lower accuracy and is significantly different when applied to the One Against One and One Against Rest methods. The model results show that public sentiment towards the PPKM policy is positive to be continued consistently to suppress the spread of the COVID-19 virus.
Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features

Time-series data arises in many real-world applications (e.g., mobile health) and deep neural networks (DNNs) have shown great success in solving them. Despite their success, little is known about their robustness to adversarial attacks. In this paper, we propose a novel adversarial framework referred to as Time-Series Attacks via STATistical Features (TSA-STAT). To address the unique challenges of time-series domain, TSA-STAT employs constraints on statistical features of the time-series data to construct adversarial examples. Optimized polynomial transformations are used to create attacks that are more effective (in terms of successfully fooling DNNs) than those based on additive perturbations. We also provide certified bounds on the norm of the statistical features for constructing adversarial examples. Our experiments on diverse real-world benchmark datasets show the effectiveness of TSA-STAT in fooling DNNs for time-series domain and in improving their robustness.
Bilinear $ \theta $-type Calderón-Zygmund operators and its commutators on generalized variable exponent Morrey spaces

In this paper, we discuss the boundedness of bilinear $ \theta $-type Calderón-Zygmund operators on the generalized variable exponent Morrey spaces. In addition, the corresponding results of commutators generated by bilinear $ \theta $-type Calderón-Zygmund operators with BMO functions on these spaces is also obtained.