Miracle-dz/UniFAR-FTUs huggingface dataset:
To trust or not to trust? Governance of multidimensional elite sport reality

Abstract The recent reorganization of Finnish elite sport has ended in confusion when examining the goals and modus operandi between key agents in the elite sport system. We investigate the governance of this new structure and ask how this parallel governance structure is understood by agents inside the elite sport system and what is the role of trust and social capital in the combination of centralized and network-based governance? We use an interview sample (n = 16) with key policymakers and agents and questionnaire survey targeting to the national governing bodies of sport (n = 55), with 67% response rate. While use of the network metaphor is shared amongst agents, there is no shared understanding of the governance model. Situated governance-as-legitimacy based on trust and personal relationships is more important than policymakers envisage; personal trust and cumulated individual social capital seems to appear as a more powerful guide to action than system trust.
Multi-Regression Fusion Based Blood Pressure Estimation

Using the traditional cuff based instruments to estimate the blood pressure (BP) values is inconvenient and difficult to have a continuous measurement. On the other hand, using the intelligent watch based instruments to perform the continuous BP estimation for monitoring the human health conditions is convenient and easy. This paper proposes a method for estimating the BP values continuously only using the photoplethysmogram (PPG). First, the PPGs are denoised by the discrete cosine transform (DCT). It is worth noting that the conventional DCT denoising approach only takes the low frequency DCT coefficients. On the other hand, this paper proposes a training based method for selecting the DCT AC coefficients. Here, the DCT AC coefficients refer to those nonDC DCT coefficients. Then, the features based on some specific points in the PPGs are extracted and the feature vectors are categriozed into two classes of the BP values using the random forest (RF) classifier. Third, for each class and each type of the BP values, three popular regressions including the support vector regression (SVR), the RF regression and the L1 norm criterion based linear regression are used to estimate the BP values. These three estimated BP values are fused together via an L2 norm based regression. It is worth noting that different classes and different types of the BP values are considered separately. Hence, each class and each type of the BP values can be estimated more accurately. Moreover, since the multi-model fusion is employed for combining these three regressions, the overall estimation results are more accurate. The computer numerical simulation results show that the average root mean squares errors (RMSEs) of the SBP and the DBP estimated by our proposed method are 9.12 and 8.19, respectively. In fact, our proposed multi-model fusion based BP estimation approach achieves a higher accuracy compared to the individual regressions.
Cooperative Advertising in a Dynamic Three‐Echelon Supply Chain

We propose a model to assess the value of a distributor in a dynamic stochastic cooperative advertising supply chain in which a manufacturer wholesales its product to a distributor who in turn sells it to a retailer. Moreover and importantly, the distributor also intermediates the pricing and advertising decisions between the manufacturer and the retailer. For the resulting three‐player hierarchical game formulation of the supply chain, we characterize the feedback Stackelberg equilibrium in terms of a system of coupled algebraic equations and show it to admit a unique solution. We find that the value added by the distributor to the supply chain depends critically on the nature of the demand function for the product, a result that has practical implications for the kinds of product where having a distributor is most desirable. Second, our model indicates that the presence of the distributor can enhance the margins of both the retailer and the manufacturer relative to the case of no distributor, and provide explicit conditions for this to occur. Third, we present numerical analysis that indicates that if the distributor generates sufficiently large transportation cost savings, then the three‐echelon supply chain can lead in the long run to higher market awareness, lower advertising expenditure, and higher value extracted, relative to the two‐echelon model. Finally, in addition to retailer advertising that is subsidized by the manufacturer, we also provide the manufacturer an option to do national advertising and show its viability.
Personality computing: New frontiers in personality assessment

Personality Computing (PC) is a burgeoning field at the intersection of personality and computer science that seeks to extract personality ‐ relevant information (e.g., on Big Five trait levels) from sensor ‐ assessed information (e.g., written texts, digital footprints, smartphone usage, non ‐ verbal behavior, speech patterns, game ‐ play, etc.). Such sensor ‐ based personality assessment promises novel and often technologically sophisticated ways to unobtrusively measure individual differences in a highly precise, granular, and faking ‐ resistant manner. We review the different conceptual underpinnings of PC; survey how well different types of sensors can capture different types of personality ‐ relevant information; discuss the evaluation of PC performance and psychometric issues (reliability and validity) of sensor ‐ derived scores as well as ethical, legal, and societal implications; and highlight how modern personality and computer science can be married more effectively to provide practically useful personality assessment. Together, this review aims to introduce readers to the opportunities, challenges, pitfalls, and implications of PC.
Antimicrobial activity of the biosynthesized silver nanoparticles of Gossypium hirsutum leaves extract

Silver nanoparticles were successfully synthesized using silver nitrate and Gossypium hirsutum leaves extracts by varying the different concentration of aqueous & ethanolic extract. The Gossypium hirsutum leaves extract was containing phytoconstituents like carbohydrates, proteins, glycosides, flavonoids, alkaloids, tannins and phenolic compounds. Formation of Silver Nano Particles was primarily confirmed by colour change of yellow to brownish color. Silver nanoparticle with phytochemicals was confirmed by UV-Visible spectra by observing peak absorption of aqueous and ethanolic SNP at 430.0 nm and 416.0 nm respectively. Dynamic light scattering of the prepared formulations revealed all the formulation were within nano range, The particle size of SNP were in between 282.1nm to 205.7nm& zeta potential -38.66mV to -4.80mv for aqueous extract & particle size of SNP for ethanolic extract were in between 201.7nm to 156.1nm & zeta potential -29.95mV to -25.36mv. SEM showed the bio synthesized SNP were found to be spherical with rough surface & agglomerated. Antimicrobial activity of biosynthesized SNP was evaluated by means of inhibition zone analysis through well diffusion method, where SNP biosynthesized from aqueous and ethanolic extracts of G.hirsutum showed good antimicrobial activity against studied microorganisms.
Non-Local Attention Learning for Medical Image Classification

In recent years, deep convolutional neural networks (CNNs) have been used with great success in medical image classification. However, within CNNs, the convolutional operation only considers localized regions and the stacking of pooling layers can lead to the loss of information about tiny lesions. In this paper, we propose a non-local attention learning method that models long-range dependencies between pixels to pre-serve global information and help CNNs better identify the tiny lesions. It consists of two main parts, the non-local attention module and the non-local visual context fusion module, one for improving global understanding of the visual scene and one for aggregating non-local visual features. These two modules are used in parallel with the CNN backbone as an auxiliary branch. We conducted extensive experiments on two public medical image datasets and showed that our model achieves the best performance in terms of accuracy, precision, and sensitivity on both datasets compared to other recent models.
Probiotics: Food Supplement for Human Consumption

The human gut microflora contains 1000 of dynamic microbial ecosystem to maintain balance between immune boosting and harmful bacteria. The good bacteria reside in healthy human gut and responsible for increasing energy production, inhibiting pathogenic growth. In unhealthy gut microbiota initiates the development of disorders in human body include metabolic disorder, chronic diarrhea, obesity. The article deals with the study of emerging trends in probiotics and developing industrial probiotics products for human body. At present there are many probiotics foodstuff isolated by industries from natural foods includes vegetables, grain, cereals to use in the form of nutrient supplements. Human Gut can be enriched with natural, low cost Probiotic supplements to improve lifestyle.
Electrospun Nanofibre Air Filters for Particles and Gaseous Pollutants

Nanofibre filters may offer new properties not available in commercial fibre filters. These include a higher surface area and the ability to include novel materials within the fibres. In addition the small size allows potential gains in performance due to the slip-flow phenomenon in which normal gas viscosity does not apply to objects smaller than the mean free path of the gas. We tested the properties of novel electrospun fibre filters generated from polyvinyl alcohol solutions, optionally embedded with nano-grains of photocatalytic TiO2 and activated charcoal. The tested materials exhibited pressure drops in the range of 195 Pa to 2693 Pa for a face velocity of 5.3 cm/s and a removal efficiency greater than 97% for 12–480 nm particles. Basis weights for the filters ranged from 16.6 to 67.6 g/m2 and specific surface areas ranged from 1.4 to 17.4 m2/g. Reactivity towards volatile organic compounds (VOCs) was achieved by irradiating the photocatalytic filters with ultraviolet light. It is necessary to solve the problems connected to the absorbance of VOCs and further reduce the resistance to airflow in order for these filters to achieve widespread use. The incorporation of reactive air filtration into building ventilation systems will contribute to improved indoor air quality.
A comparative study on the effects of a VR and PC visual novel game on vocabulary learning

Abstract Research on vocabulary acquisition in digital game-based learning has been increasing over the years, with advancements in technology giving rise to numerous learning alternatives in second language acquisition. As virtual reality gaming offers new opportunities to explore its effectiveness in language learning, it is thus important to investigate the benefits of virtual reality gaming on English vocabulary learning, as well as the potential in incorporating virtual reality to teaching practices in the classroom. Therefore, this study aims to investigate the effects of virtual reality (VR) and personal computer (PC) gaming on language learners’ vocabulary learning, as well as their affective perception. Thirty Grade 12 high school students participated in this study and were randomly assigned to either the VR or PC group. The VR group played a Sci-fi VR visual novel game, Angels and Demigods, using the Oculus Go whereas the PC group played the same game in the PC version without the VR elements. The gaming session lasted for fifty minutes for both groups. A vocabulary translation and recognition pretest, posttest and delayed posttest were adopted to compare their performance, along with a questionnaire to probe into their perception towards their respective treatment. The results revealed that both the VR group and the PC group were able to gain vocabulary knowledge in both the translation and recognition tests. In comparison, the VR group demonstrated a significantly higher mean score than the PC group in the vocabulary translation delayed posttest. The questionnaire showed that learners in both groups enjoyed playing the visual novel game and were willing to adopt it as a tool for learning vocabulary.
Towards job screening and personality traits estimation from video transcriptions

The paper built on First Impression Challenge from Chalearn V2 Workshop on Explainable Computer Vision Multimedia and Job Candidate Screening Competition CVPR17 by focusing solely on Textual Input in contrast to other Challenge’s participants who considered video or audio modalities. Therefore, the paper aims to develop a new deep learning architecture capable of predicting human personality traits and job interview from the video transcripts. Several feature representations that involve statistical and deep learning have contrasted. Our approach achieved the best score when text modality alone were employed, yielding an average of 89% score in human personality traits and 89.10% value for job interview. The research results will help companies and other organization studying human personality to assess a human personality using a minimum textual resources from the job candidates
The hyperphagic experience in obesity: a phenomenological study of French and Brazilian contexts

Abstract This article aims to understand the hyperphagic experience in the obesity of patients in the French and Brazilian contexts. Using the critical phenomenological method, twenty subjects were interviewed in health services in Paris and in Fortaleza. We note an objectification and expropriation of the body often experienced in the hyperphagic experience in obesity. We highlight the emphasis on health in the French context and on form and aesthetics in the Brazilian context. In Fortaleza, there seems to be a more evidenced discrimination in relation to obesity and a pathological discourse, whereas in Paris this pathologization is viewed from a critical position regarding the treatments. We conclude that the hyperphagic experience in obesity reveals a subject who is often lost in his/her way of being and having a body, and that clinical work must involve the re-appropriation of this body and the recovery of the condition of the autonomous subject.
Selective exposure in different political information environments – How media fragmentation and polarization shape congruent news use

Previous research posits that individual predispositions play an essential role in explaining patterns of selective exposure to political information. Yet the contextual factors in the political information environment have received far less attention. Using a cross-national and quasi-experimental design, this article is one of the first to investigate how political information environments shape selective exposure. We rely on a unique two-wave online survey quasi-experiment in five countries (Switzerland, Denmark, Italy, Poland and the United States) with 4349 participants to test the propositions that (a) the level of polarization and fragmentation in information environments and (b) the type of media source used affect selective exposure. Our results reveal that selective exposure is slightly more frequent among regular social media users but is less common among users of TV, radio and newspapers; crucially, it is more common in information environments that are highly fragmented and polarized. Nevertheless, news users from less fragmented-polarized media landscapes show one surprising yet intriguing behaviour: in a quasi-experimentally manipulated setting with more opportunities to self-select than they may be accustomed to, their coping strategy is to pick larger amounts of congruent news stories. All our findings imply that contextual factors play a crucial role in moderating individuals’ tendency to select information that aligns with their political views.
Severe Pediatric Traumatic Brain Injury Treatment Approaches of Pediatric Intensivists in Turkey PICUs: National Survey Results

Objective: In patients with severe traumatic brain injury, it is possible to obtain a good long-term prognosis, prevent secondary injury, and decrease morbidity and mortality with the administration of appropriate treatments in the acute period. This study aims to evaluate the approaches of the pediatric intensive care specialists in Turkey towards the follow-up and treatment of severe traumatic brain injury by using a survey that had been prepared in light of the current pediatric severe traumatic brain injury guideline. Materials and Methods: The survey, which included 45 questions, was prepared on the SurveyMonkey® system sent by e-mail to the centers, which were members of the Turkish Society of Pediatric Emergency and Intensive Care Medicine. Results: A total of 45 centers participated in the survey. In all centers, computed tomography of the brain was found to be the first choice as an imaging method for traumatic brain injuries. In terms of hyperosmolar therapy, 30 (66.6%) centers stated that they used 3% hypertonic saline, and 16 (35.5%) centers stated using 3% hypertonic saline+mannitol. Forty (86.96%) centers stated that they did not use prophylactic hyperventilation in the first 48 hours. A total of 44 centers (97.78%) stated that they administered prophylactic antiepileptic drugs in the first 7 days while the most preferred antiepileptic drug was levetiracetam. Conclusion: The results of our survey supported that the pediatric intensive care specialists in Turkey planned a large percentage of the treatment for patients with severe traumatic brain injury in line with the published traumatic brain injury guidelines.
The Extracted-Zero: A Practical Solution for Transmission Zeros in Wideband Filters

This letter presents a practical solution to realize finite frequency transmission zeros with independent location for wideband evanescent-mode filters. The method consists of using offline resonators located at the input and/or output of the filter. In contrast with the extracted-pole technique commonly employed for narrowband filters to generate a pole-zero pair, each offline resonator is used here in such a way so that the sole transmission zero is actively used in the filtering function. The latter characteristic is what makes this technique practical for wideband filters as it prevents the presence of unfeasibly strong coupling coefficients, as well as avoiding impractical nonresonating node elements. The offline resonator, which we named extracted-zero, can be coupled to the first or last resonator of a wideband bandpass filter, and it is conveniently realized using the same technology as any other resonator of the filter. The extracted-zero can be seen as a first-order notch filter which is directly embedded into the bandpass filter (instead of being cascaded afterward). The feasibility of this solution is validated by the experimental results of a challenging 225–450-MHz bandpass filter (66.6% fractional bandwidth) which employs 17 inline resonators plus 2 extracted-zeros so as to obtain 50 dB rejection below 195 MHz.
Methods of massive parallel reporter assays for investigation of enhancers

The correct deployment of genetic programs for development and differentiation relies on finely coordinated regulation of specific gene sets. Genomic regulatory elements play an exceptional role in this process. There are few types of gene regulatory elements, including promoters, enhancers, insulators and silencers. Alterations of gene regulatory elements may cause various pathologies, including cancer, congenital disorders and autoimmune diseases. The development of high-throughput genomic assays has made it possible to significantly accelerate the accumulation of information about the characteristic epigenetic properties of regulatory elements. In combination with high-throughput studies focused on the genome-wide distribution of epigenetic marks, regulatory proteins and the spatial structure of chromatin, this significantly expands the understanding of the principles of epigenetic regulation of genes and allows potential regulatory elements to be searched for in silico. However, common experimental approaches used to study the local characteristics of chromatin have a number of technical limitations that may reduce the reliability of computational identification of genomic regulatory sequences. Taking into account the variability of the functions of epigenetic determinants and complex multicomponent regulation of genomic elements activity, their functional verification is often required. A plethora of methods have been developed to study the functional role of regulatory elements on the genome scale. Common experimental approaches for in silico identification of regulatory elements and their inherent technical limitations will be described. The present review is focused on original high-throughput methods of enhancer activity reporter analysis that are currently used to validate predicted regulatory elements and to perform de novo searches. The methods described allow assessing the functional role of the nucleotide sequence of a regulatory element, to determine its exact boundaries and to assess the influence of the local state of chromatin on the activity of enhancers and gene expression. These approaches have contributed substantially to the understanding of the fundamental principles of gene regulation.
TLC Identification of Bacteriocin from Different LAB Clinical Isolates of Najaf Hospitals and in Vitro Evaluation of Its Effectiveness Against three Pathogenic Bacterial Isolates

Probiotics are useful microorganisms that are effective in protecting against pathogenic microorganisms,used to support food to provide beneficial effects to human health by maintaining the natural balance of theintestinal flora and reducing diseases, especially those related to the gastrointestinal tract.The ability of theLactic acid bacteria to produce bacteriocin. In this study 74 samples were collected from various clinicalsources include 31 samples of mouth and 43 samples from Vaginal swabs, for the period July 2018 untilDecember 2018. The results of the isolation and laboratory diagnosis and biochemical testes the ownershipof 43 isolates from lactic acid bacteria in vaginal swab and the highest percentage isolates bacterial (52%)of the samples of the vagina. All isolates showed lactic acid bacteria effectiveness of the microbial agentstoward some negative bacterial species to dye grams diameters ranged between inhibition zones (14 –22mm). Findings showed that RF bacteriocin values produced by the bacterium LAB isolates ranged from(0.45 – 0.57).
Extraction of linear structures from digital terrain models using deep learning

Abstract. This paper explores the role deep convolutional neural networks play in automated extraction of linear structures using semantic segmentation techniques in Digital Terrain Models (DTMs). DTM is a regularly gridded raster created from laser scanning point clouds and represents elevations of the bare earth surface with respect to a reference. Recent advances in Deep Learning (DL) have made it possible to explore the use of semantic segmentation for detection of terrain structures in DTMs. This research examines two novel and practical deep convolutional neural network architectures i.e. an encoder-decoder network named as SegNet and the recent state-of-the-art high-resolution network (HRNet). This paper initially focuses on the pixel-wise binary classification in order to validate the applicability of the proposed approaches. The networks are trained to distinguish between points belonging to linear structures and those belonging to background. In the second step, multi-class segmentation is carried out on the same DTM dataset. The model is trained to not only detect a linear feature, but also to categorize it as one of the classes: hollow ways, roads, forest paths, historical paths, and streams. Results of the experiment in addition to the quantitative and qualitative analysis show the applicability of deep neural networks for detection of terrain structures in DTMs. From the deep learning models utilized, HRNet gives better results.