Miracle-dz/UniFAR-FTUs huggingface dataset:
E-Business Impact on SCM in the apparel industry operating

This thesis examines the impact of e-Business in the B2B segment of the Supply Chain between UK retailers and Sri Lankan manufacturers in the apparel sector. The literature review explored four interrelated themes, two of them informed by an exploratory study. Research collating these four themes is scarce, especially in the apparel sector although there is considerable research on supply chain management and information sharing, which adopts a quantitative approach. However, there is a relative lack of qualitative research into behavioural issues. Based on the literature review, 12 main research questions were formulated. Following a qualitative, approach respondents in five Sri Lankan apparel manufacturers were interviewed in an explanatory study comprised of 35 interviews. An innate analytical framework consisting of themes, attributes and categories (TAC) was developed for data analysis. A conceptual model incorporating three category combinations was developed, disclosing internal, external and holistic reasons for ICT implementation. Analysis of the findings suggests that, more than speed of delivery, visibility of information is the main benefit facilitated by new ICT, compared with traditional methods. The findings indicate that security is the main concern and the main barrier is remote plant location for conducting e-Business. The data indicate that 80 per cent of investigated companies do not have an appropriate level of ICT capability. Moreover, a manufacturer’s communication capability and information sharing are mainly decided by the dependency on the lead firm. Manufacturers that deal with multiple lead firms experience compatibility problems due to the lack of a hybrid system. Manufacturers also need to set realistic expectations for a communication system and employee motivation should be included in the evaluation criteria. In conclusion, building a few longer-term relationships, including an information sharing policy is considered crucial for achieving the true potential of e-Business
LOCUS: User-Perceived Delay-Aware Service Placement and User Allocation in MEC Environment

In the multi-access edge computing environment, app vendors deploy their services and applications at the network edges, and edge users offload their computation tasks to edge servers. We study the user-perceived delay-aware service placement and user-allocation problem in edge environment. We model the MEC-enabled network, where the user-perceived delay consists of computing delay and transmission delay. The total cost in the offloading system is defined as the sum of service placement, edge server usage and energy consumption cost, and we need to minimize the total cost by determining the overall service-placing decision and user-allocation decision, while guaranteeing that the user-perceived delay requirement of each user is fulfilled. Our considered problem is formulated as a Mixed Integer Linear Programming problem, and we prove its NP-hardness. Due to the intractability of the considered problem, we propose a LOCal-search based algorithm for USer-perceived delay-aware service placement and user-allocation in edge environment, named LOCUS, which starts with a feasible solution and then repeatedly reduces the total cost by performing local-search steps. After that, we analyze the time complexity of LOCUS and prove that it achieves provable guaranteed performance. Finally, we compare LOCUS with other existing methods and show its good performance through experiments.
DIAGNOSTIC VALUE OF METHODS FOR SENSITIZATION DETERMINATION IN PEOPLE WITH ALLERGIC RHINITIS (REVIEW OF LITERATURE AND OWN DAT

Objective was to review the literature on the diagnostic value of various methods for determining sensitization in patients with allergies, to study the parameters of the specificity and sensitivity of skin testing and laboratory determination of specific IgE. Materials and methods. 88 patients with allergic rhinitis were examined by three different methods of specific allergic diagnosis (in vivo and in vitro) in accordance with the guidelines of the ethics committee of the National Pirogov memorial medical university, all were beyond the acute period. The inclusion criteria were allergic rhinitis diagnosis (both intermittent and persistent) with proven sensitivity to domestic allergens. Skin prick test was carried out according to the classical testing procedure in accordance with regulatory documents with commercial extracts of allergens. Western blot testing for specific IgE levels was performed using RIDA qLine test systems (R-Biopharm AG, Darmstadt, Germany) and Euroline (Euroimmun). The sIgE concentration was converted to a nominal scale (grades) according to the following rules: < 0.35 IU mL-1-level 0 (negative), (0.36-0.69) IU mL-1-level 1 (boundary levels ), (0.7-3.49) IU mL-1-level 2 (slightly elevated), (3.50-17.4) IU mL1-level 3 (moderately elevated), (17.5-49,9) IU mL-1-level 4 (high levels), (50-100) IU mL-1-level 5 (very high levels) and > 100 IU mL1-level 6 (extremely high levels). Results and discussion. The results of two systems for determining the specific IgE to D. Pteronissinus by Rida AllergyScreen and Euroline have a systematic difference in rates (-1.27 kU / l). Between the data of skin testing with D. Pteronissinus allergens and detection of specific IgE by the Rida AllergyScreen method, there is good agreement between the results, there is satisfactory agreement between the results of the research between the data of skin testing with allergens D. Pteronissinus and the detection of specific IgE by the Euroline method.
Speech Emotion Recognition Using Sequential Capsule Networks

Speech emotion recognition (SER) is an indispensable part of fluid human-machine interaction and attracts lots of research attentions. Recent work on SER has successfully applied convolutional neural networks (CNNs) to learn feature representations from speech spectrograms. However, the fundamental problem of CNNs is that the spatial information in spectrograms is lost, which includes positional and relationship information of low-level features, such as pitch and formant frequencies. We propose a novel architecture of sequential capsule networks (CapNets) by leveraging the advantange of CapNets that spatial information can be preserved in capsules and passed to upper capsule layers via dynamic routing. Also, the dynamic routing algorithm provides an effective alternative to pooling or storing recurrent hidden states for obtaining utterance-level features from the sequential capsule outputs. To further improve the model's ability to capture contextual information, we introduce a recurrent connection to the sequential structure. The experimental comparison of the proposed systems and previously published systems using CNNs and recurrent neural networks (RNNs) based on the IEMOCAP corpus demonstrates the effectiveness of the proposed sequential CapNets.
Real-Time Detection of Cucumber Leaf Diseases Based on Convolution Neural Network

In this paper, we proposed an object detection algorithm based on deep learning for NVIDIA Jetson Xavier NX to detect cucumber leaf diseases in real time. We collected cucumber leaves images from the experimental base of Anhui Academy of Agricultural Sciences, and labeled dataset by VGG Image Annotatort. Based on the one-stage detection network YOLO v5, firstly, the size of anchors were obtained by cluster analysis of the dataset, and a variety of data augmentation was carried out for to enrich the background information, The feature fusion network is improved, and different scale features are given different weights. Based on these optimizations, our model achieved 84.6 mAP on our dataset with 34.7 MB parameters, 4.9 ms inference time on NVIDIA Geforce GTX1080Ti, and 23 FPS with 512×640 resolution on NVIDIA Jetson Xavier NX, being faster than previous detectors, basically met the purpose of real-time.
Analysis of the impact of faults in a photovoltaic generator

Throughout this article, we have identified an electrical model based on Bishop's one that mathematically even represents the actual behavior of a PV cell heavily involved in the production of a PV generator (PVG). It turns out that the performance of PVG is intrinsically linked to operating, manufacturing or environmental conditions. The nonlinear model that we have retained due to the atypical behavior of the semiconductors used in the manufacture of the panels, reveals to us faults requiring an efficient diagnosis. We present some results of simulations under Matlab, which characterize the impact and influence of certain PVG faults on the performance of the studied system. The good operating prospects resulting from the simulation results are very encouraging for further work in the field of fault diagnosis and prognosis.
deterioration of oral health as a risk factor for high performance athletes

*Corresponding author: Alfredo Cueto, Faculty of Dentistry, University Andres Bello Avenue Valparaiso no. 1560, Vina del Mar, Chile. Tel: +56 0322845108; E-mail: alfredocuetourbina@yahoo.es Citation: Alfredo Cueto, Sebastián Valdebenito, Héctor Oñate, Sebastián Espinoza, Daniela Muñoz (2017) Deterioration of Oral Health as a Risk Factor for High-Performance Athletes. Dent Adv Res 2: 120. DOI: 10.29011/2574-7347.100020
Machine learning model for credit card fraud detection- a comparative analysis

In today's world, we are on an express train to a cashless society which has led to a tremendous escalation in the use of credit card transactions. But the flipside of this is that fraudulent activities are on the increase; therefore, implementation of a methodical fraud detection system is indispensable to cardholders as well as the card-issuing banks. In this paper, we are going to use different machine learning algorithms like random forest, logistic regression, Support Vector Machine (SVM), and Neural Networks to train a machine learning model based on the given dataset and create a comparative study on the accuracy and different measures of the models being achieved using each of these algorithms. Using the comparative analysis on the F_1 score, we will be able to predict which algorithm is best suited to serve our purpose for the same. Our study concluded that Artificial Neural Network (ANN) performed best with an F_1 score of 0.91.
Sexual assault and fatal violence against women during the Irish War of Independence, 1919–1921: Kate Maher’s murder in context

At the height of the Irish War of Independence, 1919–1921, 45-year-old Kate Maher was brutally raped. She subsequently died of terrible wounds, almost certainly inflicted by drunken British soldiers. This article discusses her inadequately investigated case in the wider context of fatal violence against women and girls during years of major political instability. Ordinarily her violent death would have been subject to a coroner’s court inquiry and rigorous police investigation, but in 1920, civil inquests in much of Ireland were replaced by military courts of inquiry. With the exception of medical issues, where doctors adhered to their ethical responsibility to provide clear and concise evidence on injuries, wounds and cause of death, courts of inquiry were cursory affairs in which Crown forces effectively investigated and exonerated themselves. This article adopts a microhistory approach to Maher’s case to compare how civilian and military systems differed in their treatments of female fatalities. Despite the fact that the medical evidence unequivocally showed that the attack was of a very violent sexual nature, the two soldiers directly implicated were not charged with rape or any other sexual offence. In her case, and in those of other women who died violently while in the company of soldiers and policemen, prosecutions of the men involved resulted in acquittal by military court martial. This was so both for women portrayed as of immoral character and for others assumed to be ‘respectable’. It also reflects on the wider question of sexual violence during the Irish War of Independence, concluding that while females experienced a range of gender-determined threats and actions such as armed raids on their homes, the ‘bobbing’ of hair and other means of ‘shaming’, rape, accepted as the most serious act of sexual assault, was regarded by all combatants as beyond the pale.
Effect of Phosphorus, Vermicompost and PSB on Seed Yield, Yield Attributes and Economics of Blackgram (Vigna Mungo L.)

A field experiment was conducted to study the effect of phosphorus, vermicompost and PSB inoculation on growth, yield and quality of black gram during Kharif 2011 on the farm of Agronomy department, at college of Agriculture, Latur. The research showed that the application of 75 kg P2O5ha-1 recorded highest seed yield (1194 kg ha-1) and yield attributes as well as high economic returns but it was found at par with 50 kg P2O5ha-1. The higher B: C ratio (1.58) was recorded at 50 kg P2O5ha-1. Therefore, it is recommended to apply 50 kg phosphorus ha-1 to black gram crop. The superior development and yield parameters were recorded by the combine application of vermicompost and PSB inoculation. It was also found superior in respect of gross monetary return but higher net monetary return (18377 kg ha-1) and B: C ratio (1.74) was obtained by the application of PSB inoculation. Hence it is recommended to apply PSB inoculation to black gram.
A Modified Streamtube Model for Vertical Axis Wind Turbines

This work introduces a modified double-multiple streamtube model for Vertical Axis Wind Turbines (VAWT) that takes into account some parameters that were neglected till now. For example, the model considers the directions of the flow, rather than assuming that the flow is parallel to the free-wind. Also a formulation is established to calculate the effect of inclination of the blades in any direction. The modifications are facilitated by considering the momentum conservation in a direction perpendicular to the force (which was abandoned in the traditional models). The model results are compared to other models and to experimental results with a fair agreement.
Overcoming Dormancy and Influence of Light on the Physiological Quality of Senna cana (Fabaceae) Seeds

Environmental factors affect the germination process, like the presence of seed coat and the quality of light; these informations are still scarce for many native species from Brazil, especially for Senna cana, which there are no adequate standards and methodologies to be used in germination tests. The aim of this research was to recommend adequate pre-germinative treatment(s) to overcome seed dormancy, and determine the degree of influence of different light regimes in seed germination of S. cana. Two experiments were carried out: T1-evaluation of different methods of dormancy overcoming (intact seeds (control), T2-imbibition of the intact seeds for 24 hours (in distilled water), T3-scarified seeds with sandpaper n° 100 in the hilum opposite region, T4-scarified seeds with sandpaper n° 100 in the region the hilo opposite region and imbibition in water (in distilled water) for 24 hours; T5-imbibition in water at 80°C); 2-Influence of light quality on seed germination and vigor (white light, red light, far red light and absence of light). The evaluated parameters were: first germination count, percentage of germination, IVG (Germination speed index), MGT (Mean germination time). Treatments were compared by Tukey at 5% probability. The best method for overcoming seed dormancy was mechanical scarification with sandpaper nº 100. The germination of the seeds of S. cana can be classified as indifferent to the luminosity, despite germinative response be greater under white and red light.
Estimation of Forearm Supination/Pronation Motion Based on EEG Signals to Control an Artificial Arm

In recent years, many myoelectric arms that are controlled based on electromyogram (EMG) signals of amputee’s stump or residual muscles have been proposed. In the cases of above elbow amputees, however, the muscles which generate the forearm, wrist and hand motions do not remain. Therefore, most myoelectric arms for above elbow amputees have less degree of freedom and its dexterity is relatively poor compared with a human upper-limb. To improve the quality of life of above elbow amputees and to increase their mobility in daily life activities, some additional input signals must be prepared. One of the strong candidates of the additional input signals is an electroencephalogram (EEG) signal. An EEG signal is an electric signal that can be measured along a scalp, so that it can be measured even with an above elbow amputee. In this study, an artificial arm for above elbow amputees is controlled based on EMG and EEG signals. In this paper, the EEG-based motion estimation method is proposed to control the forearm supination/pronation motion of the artificial arm. The angle, angular velocity, and angular acceleration of the forearm motion are estimated under several velocities by using EEG signals.
The Added Benefit of Opicapone When Used Early in Parkinson's Disease Patients With Levodopa-Induced Motor Fluctuations: A Post-hoc Analysis of BIPARK-I and -II

Introduction: Opicapone (OPC) was efficacious in reducing OFF-time in two pivotal trials in patients with Parkinson's disease (PD) and end-of-dose motor fluctuations (BIPARK-I and -II). Post-hoc analyses of these trials evaluated the efficacy of OPC following pre-defined segmentation of the wide spectrum of motor fluctuations in PD. Methods: Data from matching treatment arms in BIPARK-I and -II were combined for the placebo (PLC) and OPC 50-mg groups, and exploratory post-hoc analyses were performed to investigate the efficacy of OPC 50 mg vs. PLC in subgroups of patients who were in “earlier” vs. “later” stages of both their disease course (e.g., duration of PD <6 years vs. ≥6 years) and levodopa treatment pathway (e.g., number of daily levodopa intakes <4 vs. ≥4). Efficacy variables included changes from baseline in absolute OFF-time and total ON-time. Results: The Full Analysis Set included 517 patients (PLC, n = 255; OPC 50 mg, n = 262). OPC 50 mg was significantly more effective than PLC in reducing OFF-time and increasing ON-time in the majority of subgroup analyses (p < 0.05). Moreover, patients in “earlier” stages of both their disease course and levodopa treatment pathway experienced numerically greater efficacy when using OPC 50 mg, in comparison with those in “later” stages. Conclusion: OPC 50 mg was efficacious over the whole trajectory of motor fluctuation evolution in PD patients. There was also a signal for enhanced efficacy in patients who were earlier vs. later in their disease course and levodopa treatment pathway.
The Chinese Adolescent Cohort Study: Design, Implementation, and Major Findings

The importance of diet quality on children's growth is being increasingly recognized. The Chinese Adolescent Cohort (CAC) is a longitudinal cohort study to comprehensively investigate the health impacts of nutritional factors on child growth. From 2013 to 2018, 6,967 children aged 6–8 years have been recruited from 23 primary schools in Sichuan, Guizhou, and Chongqing, which have been planned to be followed up annually until their age of 15 years. Regular assessments included the measurement of height, weight, waist circumference, and skinfold thicknesses; pubertal development was examined by trained investigators according to Tanner stages; dietary intake was obtained by three 24-h recalls and food frequency questionnaire; validated questionnaires were used to estimate socio-demographic characteristics, physical activity, and sedentary behaviors. Findings from the CAC baseline and the first follow-up data suggested that higher protein intake among girls and unhealthy eating habits among children might increase the risk for childhood obesity. Also, higher intakes of grain and meat and lower overall diet quality and intakes of dietary fiber and tuber might be associated with advanced pubertal development. Those results indicated that the CAC study could contribute to the development of strategies for optimizing Chinese children's health.
Sex Differences in Affective Dysfunction and Alterations in Parvalbumin in Rodent Models of Early Life Adversity

The early life environment markedly influences brain and behavioral development, with adverse experiences associated with increased risk of anxiety and depressive phenotypes, particularly in females. Indeed, early life adversity (ELA) in humans (i.e., caregiver deprivation, maltreatment) and rodents (i.e., maternal separation, resource scarcity) is associated with sex-specific emergence of anxious and depressive behaviors. Although these disorders show clear sex differences in humans, little attention has been paid toward evaluating sex as a biological variable in models of affective dysfunction; however, recent rodent work suggests sex-specific effects. Two widely used rodent models of ELA approximate caregiver deprivation (i.e., maternal separation) and resource scarcity (i.e., limited bedding). While these approaches model aspects of ELA experienced in humans, they span different portions of the pre-weaning developmental period and may therefore differentially contribute to underlying mechanistic risk. This is borne out in the literature, where evidence suggests differences in trajectories of behavior depending on the type of ELA and/or sex; however, the neural underpinning of these differences is not well understood. Because anxiety and depression are thought to involve dysregulation in the balance of excitatory and inhibitory signaling in ELA-vulnerable brain regions (e.g., prefrontal cortex, amygdala, hippocampus), outcomes are likely driven by alterations in local and/or circuit-specific inhibitory activity. The most abundant GABAergic subtypes in the brain, accounting for approximately 40% of inhibitory neurons, contain the calcium-binding protein Parvalbumin (PV). As PV-expressing neurons have perisomatic and proximal dendritic targets on pyramidal neurons, they are well-positioned to regulate excitatory/inhibitory balance. Recent evidence suggests that PV outcomes following ELA are sex, age, and region-specific and may be influenced by the type and timing of ELA. Here, we suggest the possibility of a combined role of PV and sex hormones driving differences in behavioral outcomes associated with affective dysfunction following ELA. This review evaluates the literature across models of ELA to characterize neural (PV) and behavioral (anxiety- and depressive-like) outcomes as a function of sex and age. Additionally, we detail a putative mechanistic role of PV on ELA-related outcomes and discuss evidence suggesting hormone influences on PV expression/function which may help to explain sex differences in ELA outcomes.