Miracle-dz/UniFAR-FTUs huggingface dataset:
Concurrent emergence of Marburg virus disease in Tanzania and Equatorial Guinea: a ticking time bomb

Marburg virus disease (MVD) is a highly fatal viral hemorrhagic fever disease caused by a zoonotic virus, the Marburg virus, which is closely related to ebolaviruses within the family Filoviridae. For the first time, Tanzania and Equatorial Guinea are both experiencing MVD outbreaks simultaneously. Hitherto, neither of the 2 countries has reported any case of MVD, even though the virus has been isolated previously in nearby countries and the reservoir, the Egyptian fruit bat, is known to exist in both countries. The clinical manifestations of the disease become apparent after a 2–21-day incubation period and are characterized by constitutional symptoms such as high fever, malaise, and severe headache. They may progress to cause multiple organ dysfunctions within 5–7 days of onset and eventual death. The fatality rate can reach 90% if an early diagnosis and supportive care are not given, just like in the case of Ebola. Current evidence suggests that the concurrent outbreaks and the presence of MVD cases and/or clusters within several districts without epidemiological linkage imply undetected community transmission. Consequently, theWorldHealthOrganization rates the overall risk of regional transmission as high. This calls for African countries’ adequate preparedness to inform swift responses to MVD outbreaks. This article aims to examine the epidemiology of MVD in Tanzania and Equatorial Guinea, the drivers of MVD outbreaks, challenges to control, the current public health response, and propose contextual recommendations that can be adopted to control the current outbreaks and prevent regional and global transmission.
I nternational J ournal of V eterinary S cience

Study was conducted on 10 goat fetuses(5 from group I-CR length upto 20 cm and 5 from group II-CR length 20 cm and above), 5 neonatal goats (group III) and 5 adult goats (group IV ) to study the configuration of collagen fibers in the skin of Capra hircus . Connective tissue in the dermis is composed of the fibrous proteins collagen, elastin, and reticulin in which collagen accounts for 70% of the total fibres. The observation (Transmission Electron Microscopic study) revealed that the fibre formation in the sections of group I fetuses was not apparent. In group II fetuses the collagen fibres appeared to arise at the angles of the fibroblast cell mainly in deep zone of dermal matrix. Micrographs show very clear histogenesis of fibres in this group. In group II (around 30 to 35 cm CR length) fetuses the growth in due course of time elevated very high. There is clear view of histogenesis of collagen fibres in fetal stage and remarkable changes with the growing age. The collagen assimilation was intense in group III goats coupled with a dynamic rearrangement of the tender collagen bundles in the dermal region. In group IV showing distribution of dense collagen bundles found in rigorously scattered and slack slender groups running parallel to the epidermis. In this group samples the variation is associated with a loss of fibrous tissue, slower rate of cellular renewal, and a reduced vascular and glandular network.
Exploratory Data Analysis And Crime Prediction In San Francisco

Exploratory Data Analysis And Crime Prediction In San Francisco by Isha Pradhan Crime has been prevalent in our society for a very long time and it continues to be so even today. The San Francisco Police Department has continued to register numerous such crime cases daily and has released this data to the public as a part of the open data initiative. In this paper, Big Data analysis is used on this dataset and a tool that predicts crime in San Francisco is provided. The focus of the project is to perform an in-depth analysis of the major types of crimes that occurred in the city, observe the trend over the years, and determine how various attributes, such as seasons, contribute to specific crimes. Furthermore, the proposed model is described that builds on the results of the performed predictive analytics, by identifying the attributes that directly affect the prediction. More specifically, the model predicts the type of crime that will occur in each district of the city. After preprocessing the dataset, the problem reduced to a multi-class classification problem. Various classification techniques such as K-Nearest Neighbor, Multi-class Logistic Regression, Decision Tree, Random Forest and Naïve Bayes are used. Lastly, our results are experimentally evaluated and compared against previous work.The proposed model finds applications in resource allocation of law enforcement in a Smart City.
A new approach to sustainable tourism: Beyond environmental protection: The case of the Souss-Massa region

The tourism industry is ranked among the largest industries in the world. However, the degrading effects of tourism have become a major concern and must be addressed quickly. From this negative perspective, the concept of sustainable tourism has emerged in the field of reducing the effects of tourism activities, which has become almost universally accepted as a desirable and politically appropriate approach to tourism development. Our article presents the main ideas of sustainable tourism in the Souss Massa region. It involves economic, environmental, and socio-cultural aspects through the planning and management of tourism. In addition, we deal with the historical background of the idea of sustainability and the main international events regarding this topic while highlighting the negative effects of tourism that can be avoided by applying the principles of sustainable development.
Acute Effects of Different Warm-up Methods on Dynamic Balance

Frequently used methods for warm-up are after-jogging static stretching performed at the aerobic intensity or loaded exercises applied in the dynamic style. Studies report that voluntary contractions to be performed from a mild level such as dynamic warm-up to high intensity before performing an athletic activity will increase power production and performance by activating the nerve-muscle function while static stretching decreases the relevant performance. Studies examining the effect of warm-up protocols on the balance performance in the literature are scarce. The aim of this study is to examine the acute effects of static and dynamic warm-up methods on balance performance. 3 different warm-up protocols were applied to fifty Physical Education and Sports students (21.5 ± 1.8 years, 177.7 ± 6.2 cm and 77.7 ± 5.4 kg) on non-consecutive days. Protocol A consisted of 5-minute low-intensity running and Protocol B consisted of static stretching exercises for the lower extremity following Protocol A (at intervals of 30 sec. and 10 sec. twice accompanied by pain). Protocol C was dynamic stretching (each exercise was repeated twice for 10 m. at increasing intensity after resting for 10 seconds) following Protocol A. The subjects performed the Star Excursion Balance Test after each warm-up protocol (Grible & Robinson, 2008). Protocols A, B, and C were compared with the variance analysis (ANOVA) and posthoc methods in repeated measurements. It was determined that there is a significant increase in all balance performances in Protocol B when compared to Protocol A (p<0,05). It can be said that both static stretching and dynamic stretching practices increase the balance performance. The most striking result of this study is that the expected negative effect of static stretching did not occur. Thus, warm-up methods that include static or dynamic stretching can be used before activities requiring dynamic balance in sports such as gymnastics.
Rethinking ﬁ re-adapted species in an altered ﬁ re regime

Novel combinations of ﬁ re regime and forest type are emerging in areas affected by climate change, ﬁ re exclusion, and other stressors. Species interactions following wild ﬁ re in these areas are not well understood. In Sierra Nevada mixed-conifer forests, large patches of stand-replacing ﬁ re were once rare but are becoming increasingly prevalent and are quickly revegetated by native shrubs. There is uncertainty as to which tree species are best adapted to recover in the resulting post-ﬁ re environments. We introduce a conceptual framework for understanding how the altered ﬁ re regime in the Sierra Nevada may affect species composition. We investigate an understudied link in this framework: how juvenile ponderosa pine ( Pinus ponderosa ) and white ﬁ r ( Abies lowiana ) growth and mortality rates are affected by shrub competition following stand-replacing ﬁ re. We measured juvenile conifer growth in relation to shrub competition in ﬁ ve ﬁ re footprints ranging from 8 to 35 yr old and >400 ha in size. To test whether reductions in conifer growth may lead to increased mortality, we also evaluated how recent tree growth predicts mortality of similarly aged juvenile trees in nearby managed stands. We found that juvenile ponderosa pine growth was negatively associated with nearby shrub competition, but white ﬁ r growth was not. Both species grew slower preceding mortality, with a steeper relationship found in ponderosa pine. Across the range of shrub competition in this study, expected pine annual relative growth rate varied from 0.27 to 0.10, which corresponded to an eleven-fold difference in annual probability of mortality (0.1 – 1.1%, respectively). These results show that ponderosa pine is sensitive to shrub competition following wild ﬁ re in terms of both growth and survival while white ﬁ r is less sensitive, presumably due to its high shade tolerance. Though pines are generally considered ﬁ re-adapted, this study argues that post-ﬁ re species interactions in a novel ﬁ re regime may exacerbate the already shifting species composition toward shade-tolerant species, which are less well adapted to survive through future ﬁ res and to persist in future drier, warmer climates.
Benchmark Evaluation for Tasks with Highly Subjective Crowdsourced Annotations: Case study in Argument Mining of Political Debates

This paper assesses the feasibility of using crowdsourcing techniques for subjective tasks, like the identification of ar-gumentative relations in political debates, and analyses their inter-annotator metrics, common sources of error and disagreements. We aim to address how best to evaluate subjective crowdsourced annotations, which often exhibit significant annotator disagreements and contribute to a “quality crisis” in crowdsourcing. To do this, we compare two datasets of crowd annotations for argumentation mining performed by an open crowd with quality control settings and a small group of master annotators without these settings but with several rounds of feedback. Our results show high levels of disagreement between annotators with a rather low Krippen-dorf’s alpha, a commonly used inter-annotator metric. This metric also fluctuates greatly and is highly sensitive to the amount of overlap between annotators, whereas other common metrics like Cohen’s and Fleiss’ kappa are not suitable for this task due to their underlying assumptions. We evaluate the appropriateness of the Krippendorf’s alpha metric for this type of annotation and find that it may not be suitable for cases with many annotators coding only small subsets of the data. This highlights the need for more robust evaluation metrics for subjective crowdsourcing tasks. Our datasets provide a benchmark for future research in this area and can be used to increase data quality, inform the design of further work, and mitigate common errors in subjective coding, particularly in argumentation mining.
Lithium ion Battery Aging: Battery Lifetime Testing and Physics-based Modeling for Electric Vehicle Applications

Electrification of vehicles is one solution in reducing emissions from the transport sector, and in particular to limit tail-pipe emissions in cities. In order to make the electrification successful and cost effective, there is a high demand for longer drive range and longer battery lifetime. By improving the understanding for the underlying aging mechanisms of vehicle lithium ion batteries, the utilization can be improved and thus cost effective. This thesis contributes with an extensive test matrix for lifetime testing, including calendar and cycling aging, on large commercial cells for automotive applications. The test matrix is constructed to investigate the effect of temperature, C-rate, SOC level, test procedure and DOD. A physics-based model including SEI formation, film resistance increase and loss of electrode volume fraction as a function of number of cycles is constructed. Aging parameters were determined through parameterizing the model using calibration experiments. Lifetime cycling data show that the expected temperature dependence can not be seen for 10% DOD for SOC levels below 50% SOC, it is first for SOC levels higher than 60% that this is observed. Also SOC levels higher than 30% is accelerating the aging, while SOC levels below this show very low aging effects, however, when using cycling in the whole SOC interval, the classical decreased lifetime with higher temperatures were obtained. For cells tested in different DODs, but with the same cut-off voltage, longer lifetime was observed for the small DOD, although the initial aging was similar up to 1200 FCE. After that, the aging decelerated for the small DODs while it accelerated for the large DODs.
Eliciting Opinions on Health Messaging During the COVID-19 Pandemic: Qualitative Survey Study

Background Effective public health messaging has been necessary throughout the COVID-19 pandemic, but stakeholders have struggled to communicate critical information to the public, especially in different types of locations such as urban and rural areas. Objective This study aimed to identify opportunities to improve COVID-19 messages for community distribution in rural and urban settings and to summarize the findings to inform future messaging. Methods We purposively sampled by region (urban or rural) and participant type (general public or health care professional) to survey participants about their opinions on 4 COVID-19 health messages. We designed open-ended survey questions and analyzed the data using pragmatic health equity implementation science approaches. Following the qualitative analysis of the survey responses, we designed refined COVID-19 messages incorporating participant feedback and redistributed them via a short survey. Results In total, 67 participants consented and enrolled: 31 (46%) community participants from the rural Southeast Missouri Bootheel, 27 (40%) community participants from urban St Louis, and 9 (13%) health care professionals from St Louis. Overall, we found no qualitative differences between the responses of our urban and rural samples to the open-ended questions. Participants across groups wanted familiar COVID-19 protocols, personal choice in COVID-19 preventive behaviors, and clear source information. Health care professionals contextualized their suggestions within the specific needs of their patients. All groups suggested practices consistent with health-literate communications. We reached 83% (54/65) of the participants for message redistribution, and most had overwhelmingly positive responses to the refined messages. Conclusions We suggest convenient methods for community involvement in the creation of health messages by using a brief web-based survey. We identified areas of improvement for future health messaging, such as reaffirming the preventive practices advertised early in a crisis, framing messages such that they allow for personal choice of preventive behavior, highlighting well-known source information, using plain language, and crafting messages that are applicable to the readers’ circumstances.
Did Physical Activity Prevent Burnout Among Family Physicians in Slovenia During the COVID-19 Pandemic?

Background The COVID-19 pandemic ampli�ed the existing problem of burnout among healthcare workers. Physical activity has positive effects on the entire body and mental health, and may prevent burnout. Objectives: Determine the relationship between physical activity and prevalence of burnout among Slovenian family physicians (FPs) and family medicine trainees (FMTs) during the COVID-19 pandemic. Methods: Cross-sectional observational study of Slovenian FPs and FMTs addressing sociodemographic variables, type and duration of physical activity and assessing burnout using the Maslach Burnout Inventory. Data was analysed using various bivariate statistical tests. Results: 1230 FPs and FMTs were invited to participate in the study, 282 completed the survey (22.9% response rate), 243 (86.2%) FPs and 39 (13.8%) FMTs. Total burnout score (MBI TOT ) during the COVID-19 pandemic was high in 48.6% of the FPs and FMTs; 62.8% scored high for emotional exhaustion (EE), 40.1% high for depersonalization (DP) and 53.5% low for personal accomplishment (PA). Compared to FMTs, EE and MBI TOT was higher in FPs (p < 0.001 and p = 0.010, respectively). There was no difference when comparing physical activity and burnout during the COVID-19 pandemic. Conclusions: No relationship was found between physical activity and burnout. FPs experienced signi�cantly more burnout than FMTs.
Sound Reconstruction of an Overdetermined Mixture in a Mini Plant: An Experimental Study

In this study, we propose a sound-based signal analysis technique emitted by rotating machines. Three water pump machines are set in a row to reflect a mini plant. We raise an overdetermined case with four sensors that are used to record three machines’ signal sounds with unbalanced, normal and bearing fault conditions. We use non-negative matrix factorization (NMF) approach to reconstruct the signal sounds of each machine which had previously been mixed. Based on the results, the type of engine damages can be determined based on the fundamental frequency of each machine. The first reconstructed signal Ŝ1 is similar to the baseline signal of normal machine with LSD of 1 and MSE of 5.84 × 10−9 The second reconstructed signal Ŝ2 has a similarity to the baseline signal of the machine with bearing fault with LSD of 1 and MSE of 1.10 × 10−7, while the third reconstruction signal Ŝ3 is similar to the machine’s baseline signal with unbalanced condition,that is, LSD of 1.02 and MSE of 1.38 × 10−8.
Comparison of Cerebral Blood Volume during Cold and Warm Stimulation in Elderly and Young Subjects

Background: Dementia involves a neuronal loss in the primary somatosensory cortex of the parietal lobe, causing dementia patients to perceive pain stimuli hardly. The function of temperature sensation declines. Studies measuring brain blood volume using near-infrared light have reported that patients suffering from dementia have less activation than healthy elderly people. However, the majority of these studies used tests related to cognitive function and the frontal lobe, and few have examined thermal sensation. Objective: The present study aimed to investigate the effect of cold and warm stimulation on cerebral blood volume in elderly and young subjects. Material and Methods: This observational study measured changes in oxygenated hemoglobin concentrations in the frontal cortex during cold and warm stimulation in elderly and young subjects using a near-infrared light device. The mean and standard deviation of the change in oxygenated hemoglobin concentration before and after cold and warm stimulation, as well as the center-of-gravity values, were compared between the young and the elderly. Results: During warm stimulation, the younger subjects showed an increase in blood oxygenated hemoglobin levels; however, the difference was not significant. For the elderly, no change was observed during the task. The center of gravity values was lower in the young compared to the elderly which was similar to the reaction threshold. No significant changes were observed during cold stimulation. Conclusion: Thermal sensation thresholds were impaired in the elderly compared to the young; however, cerebral blood volume changes were unclear.
Intralayer-Connected Spiking Neural Network with Hybrid Training Using Backpropagation and Probabilistic Spike-Timing Dependent Plasticity

Spiking neural networks (SNNs) are highly computationally efficient artificial intelligence methods due to their advantages in having a biologically plausible computational framework. Recent research has shown that SNN trained using backpropagation (SNN-BP) exhibits excellent performance and has shown great potential in tasks such as image classification and security detection. However, the backpropagation method limits the dynamics and biological plausibility of the neural models in SNN, which will limit the recognition and simulation performance of SNN. In order to make neural models more similar to biological neurons, this study proposes a leaky integrate-and-fire (LIF) neuron model with dense intralayer connections, as well as efficient forward and backward processes in BP training. The new model will make the interaction between neurons within the layer more frequent, enhancing the intrinsic information exchange capability of SNN. An effective probabilistic spike-timing dependent plasticity (STDP) method is also proposed to reduce the overweighted connections between neurons, as well as a hybrid training method using BP and probabilistic STDP. The training method combines the advantages of BP and STDP to improve the performance of SNN models. An intralayer-connected SNN with hybrid training (ISNN-HY) is proposed with the combination of these improvements. The proposed model was evaluated on three static image datasets and one neuromorphic dataset. The results showed that the performance of ISNN-HY is superior to that of other SNN-BP models. The proposed method also makes it possible to accurately simulate biological neural systems.
A VARIATIONAL APPROACH FOR DETECTING FEATURE LINES ON MESHES

特征线是基本形状描述符并且广泛地被用于计算机图形，电脑辅助的设计，处理的图象，并且 non-photorealistic 显示。 这份报纸为在多角形的网孔上检测通用特征线介绍一个统一变化框架。 经典 Mumford-Shah 模型被扩大到表面。 用集中方法和分离微分几何学，我们 discretize 建议变化模型到顺序的联合稀少的线性系统。 通过适合的二次的多项式，我们为提取在表面上定义的功能的山谷开发一个方法。 我们的途径在检测过程上提供灵活、直觉的控制，并且是容易的实现。 几措施功能为特征线的不同类型被设计，并且我们把我们的途径用于各种各样的多角形的网孔从对测量模型合成。 实验两个都表明我们的算法的有效性和结果的视觉质量。
Talent management and job satisfaction of medical personnel in Polish healthcare entities

Background There is a mass exodus of qualified medical personnel in countries such as Poland. As a result, it is becoming increasingly important to study the satisfaction of medical personnel employed in public healthcare entities and the factors influencing this satisfaction. One such factor is the quality of talent management. Purpose The study aimed to assess the quality of talent management in Polish healthcare entities and its impact on the job satisfaction of medical personnel. The study also considered the impact of other demographic, organizational and behavioral factors on medical personnel satisfaction, such as social competencies, job mobility, orientation toward the patient, gender and education stage. Methods A questionnaire for healthcare professionals was used to collect data. A total of 747 respondents (506 defined as medical talent) participated in the survey. A 5-point Likert scale was adopted to assess job satisfaction and talent management practices. Reliability analysis was conducted to investigate the properties of this scale and the items that comprise it. The data was analyzed using descriptive statistics and structural equation modeling. Results The survey showed that the quality of talent management in Polish healthcare institutions is not well assessed. Professional satisfaction of medical personnel working in Polish public healthcare entities depends mainly on talent management measured by talent motivation, talent development, employee appraisal and organizational culture. Among the factors that have a positive but smaller impact on job satisfaction are job mobility and the education stage. The impact of gender, patient orientation and social competence had the smallest but most significant impact on job satisfaction. Conclusion Healthcare organizations should improve their talent management strategy to meet healthcare professionals’ current and future demands and improve their job satisfaction.