Miracle-dz/UniFAR-FTUs huggingface dataset:
Danish University Colleges The Students’ Experiences with Live Video-Streamed Teaching Classes Jelsbak,

The Bachelor's Degree Programme of Biomedical Laboratory Science at VIA Faculty of Health Sciences offers a combination of live video-streamed and traditional teaching. It is the student’s individual choice whether to attend classes on-site or to attend classes from home via live video-stream. Our previous studies revealed that the live-streamed sessions compared to on-site teaching reduced interaction and dialogue between attendants, and that the main reasons were technological issues and the teacher’s choice of teaching methods. One of our goals therefore became to develop methods and implement technology to facilitate interaction through increased technological transparency. In this paper, we present and discuss organizational and educational designs as seen from the student’s point of view. We do so by investigation of how students experience participation, interaction and technological transparency in the live video-streamed teaching sessions during a 5-year period of continuous development of technological and pedagogical solutions for livestreamed teaching. Data describing student’s experiences were gathered in a longitudinal study of four sessions from 2012 to 2017 using a qualitative method inspired from mobile probes (Ørngreen & Jørgensen, n.d.). The research results document a continuous progress in technological transparency, as the live video-streamed classes increasingly support the student’s flexibility in ways of attending and interacting in classes. The analysis shows that the students have different needs (as a learning space for individual concentration or a space for highly focused collaboration) and that the technology can meet these different needs. It also shows that there are challenges, similar to many other classrooms. In this live-stream classroom interaction is facilitated through teacher driven support, resulting in classes where students can interact and collaborate equally with on-site students. We therefore argue for a sociocultural understanding of learning as situated, mediated and distributed, which this e-learning-solution support.
Selenium supplementation to broiler diets

The present study was conducted to determine the effect of selenium supplementation on performance of broiler chicks. 300 broiler chicks (Lohmann) were divided into three groups of equal weight and numbers. Group (A) fed on broiler diet, group (B) fed on broilers diet + 3% vegetable oil and group (C) fed on broiler diet + 3% vegetable oil + 0.12S ppm Selenium. Feed intake, body weight, weight gain, feed conversion ratio, respiratory rate, body temperature and some carcass characteristics were examined for the significance of effect of diet treatment using one way analysis of variance. Feed intake was not affected by dietary treatments, however, body weight was Significantly (P<0.05) increased in group Band C, compared to group A. Carcasses analysis showed no significant variations among dry matter, ether extract and ash for the three dietary groups. For CP, group C was significantly (P<0.05) higher compared to group A and B. Group (B) had Significantly (P<O.OS) higher dressing percentage than group (A). Group (C) had significantly (P<O.OS) higher blood selenium concentration than group (A) and (B). With the exception of the breast tenderness, sensory evaluation was not affected by the dietary treatment. Group (C) was significantly (P<O.OS) tender than group (A) and (B). No mortality was reported during the experimental period. The study concluded that selenium and vegetable oil supplementation in broiler diets significantly improved weight gain, final body weight and meat quality without increase of feeding cost.
3D Shape Reconstruction of Plant Roots in a Cylindrical Tank From Multiview Images

We propose a method for reconstructing a 3D shape of live plant roots submerged in a transparent cylindrical hydroponic tank from multiple-view images for root phenotyping. The proposed method does not assume special devices and careful setups, but the geometry and material of the tank are assumed known. First, we estimate the intrinsic and extrinsic camera parameters by the SfM algorithm, and the scale and axis of the tank are estimated by chamfer matching. Second, we apply the ray tracing considering the refraction for each view, the input images are mapped to the voxels, and then multiview voxels at the same location are robustly merged to reconstruct the 3D shape. Finally, the root feature extracted from the voxel is binarized and thinned by applying the 3D Canny operator. The proposed method was applied to real a dataset, and the reconstruction results are presented.
WST 48.8 EB1.5 corr

This study was conducted with a BNR (biological nutrient removal) process with an external nitrification and switching arrangement of anoxic and oxic stages. It was observed that the SPRR (specific phosphorus release rate) and SDNR(specific denitrification rate) were greatly affected by the organic loads, and SDNR had a higher temperature effect than other kinetic rates including nitrification. It was further observed that the stoichiometric values like PHA (poly hydroxyalkanoate) stored for P release and PHA consumed for P uptake also varied. Variations of % Px(phosphorus content) and PHA as intracellular matter suggest the PAOs were more active at lower temperatures with this process configuration, where more than 70% of NH4-N and phosphorus were removed at temperatures below 10°.
ULTRA-CONTEXT: MAXIMIZING THE CONTEXT FOR BETTER IMAGE CAPTION GENERATION

ULTRA-CONTEXT: MAXIMIZING THE CONTEXT FOR BETTER IMAGE CAPTION GENERATION ANKIT KHARE, M.S. Computer Science The University of Texas at Arlington, 2019 Supervising Professor: Dr. Manfred Huber Several combinations of visual and semantic attention have been geared towards developing better image captioning architectures. In this work we introduce a novel combination of word-level semantic context with image feature-level visual context, which provides a more holistic overall context for image caption generation. This approach does not require training any explicit network structure, using any external resource for training semantic attributes, or supervision during any training step. The proposed architecture addresses the significance of learning to find context at three levels to achieve a better trade-off as well as a balance between the two lines of attentiveness (wordlevel and image feature-level). The structure of the visual information is very different from the structure of the captions to be generated. Encoded visual information is unlikely to contain the maximum level of structural information needed for correctly generating the textual description in the subsequent decoding phase. Attention mechanisms aim at streamlining the two modalities of language and vision but often fail to find a balance be-
Supplementary Material Budget-Aware Adapters for Multi-Domain Learning

Visual Decathlon challenge Following previous works [3, 5, 6, 7], we employ the Wide ResNet WRN-284-B(3,3), i.e., 28 convolutional layers with widening factor of 4 and the original “basic” block (2 convolutions using 3 × 3 kernel size). As in [6, 5], random crops of 64 × 64 pixels are used to feed the network during training. The optimizer parameters are set following [3, 5], where SGD with momentum is employed for the classifier and Adam for the rest of the architecture with initial learning rates of 0.001 and 0.0001, respectively. The model is trained with batch size of 32 for 60 epochs; after 45 epochs, the learning rates are decayed by a factor of 10. The real-valued switches (s̃c) are initialized with a value of 0.001. In addition to random cropping, in regards to training data augmentation, horizontal mirroring is also applied with a 50% probability, except for four datasets (DTD, Omniglot, SVHN, and GTSR) on which it could be either harmful or useless. During training, the models for all the domains are initialized using the ImageNet pre-trained weights and these weights are kept fixed, i.e., only the domain-specific parameters (s̃c, Batch Normalization and classifiers) are learned. At test time, we follow the procedure proposed in [2] and used in [5]. We employ a ten-crop strategy for
Internet of Things: A Survey for the Individuals' E-Health Applications

In today's world, the Internet of Things (IoT), which is a fairly new technology, has become a popular topic for discussion. Meanwhile, the increasing demand for personalized healthcare with the assistance of new technologies has created new applications called e-health IoT applications; however, researchers are still attempting to find its applications, therefore they have not been able to focus on comparing these applications. We have aimed at understanding the benefits of e-health IoT applications in comparison to one another. Therefore, this study is an attempt to provide a list of e-health IoT applications for individuals and to prioritize them. The Fuzzy Analytical Hierarchy Process (FAHP) method has been used, which is a method for Multi-Criteria Decision Making (MCDM) and a useful tool for prioritizing multiple alternatives based on criteria. Eight important criteria, based on a comprehensive literature review and experts’ opinions, were determined. Then, by using the FAHP method, the weight of each criterion was calculated. As a result, seven applications identified for individuals were prioritized based on the weight of each criterion and the score of each application in each criterion. Health Effectiveness, Empowerment, Safety, Privacy, and Peace of Mind are the most important criteria in e-health IoT applications for individuals; Cost Saving, round-the-clock Access, and Time-Saving are in the next levels of importance. The results also show that Chronic disease management, Medication reminders, Health monitoring, Air quality, Fall detection, Sleep control and Fitness were respectively ranked as first, second, third, fourth, fifth, sixth and seventh among the IoT applications.
In North America, the loss of grassland habitat from conversion

24 In 2006-10, effects of four different cattle stocking rates (0, 14.4, 28.8, and 43.2 animal unit 25 months) were compared, representing 0, 20, 32, and 46% utilization of vegetation by domestic 26 livestock, on vegetation structure (as indexed by visual obstruction), and songbird population and 27 apparent nest density, community composition, and diversity in a Pacific Northwest bunchgrass 28 prairie in northeastern Oregon, USA. Overall paddock-level visual obstruction decreased and 29 structural heterogeneity increased with increasing stocking rates, and those effects carried over 30 one year after grazing had ceased. Most species were able to locate nesting sites regardless of 31 differences in visual obstruction, except western meadowlark and vesper sparrow, for which 32 obstruction was lower in paddocks with higher stocking rates. Apparent nest density for 33 grasshopper sparrows was negatively affected by higher stocking rates. Grazing effects on 34 absolute songbird population density were restricted to negative effects of higher stocking rates 35 on savannah sparrows, but this relationship was not observed until one year after grazing had 36 ceased. Songbird community composition differed between control and heavily-grazed 37 paddocks, driven by an increase in the proportion of horned larks and a decrease in the 38 proportion of savannah sparrows in heavily-grazed paddocks from pre-treatment to post39 treatment years. Bird diversity indices were unaffected by stocking rate. Negative effects of 40 high stocking rates on densities of two species and absence of any clear positive effect for the 41 other three species suggest high stocking rates as applied in this experiment may not provide 42 suitable habitat for all grassland songbirds. The absence of negative responses of density to low 43 and moderate stocking rates suggests these grazing regimes generally provided suitable habitat 44 for all species. 45
A stroke-t kapott egyének rehabilitációs eszközeiben jelentős fejlődést mutató hatékony technikák áttekintése

A stroke characterized as a sudden onset of symptoms that can cause a wide range of different problems. If the stroke affecting the right side of the brain the problems occurs on the left side of the body and inversely (affecting the left side of the brain, the problems occurs on the right side). Stroke victims often lose proper function of at least one hand and fingers . With exercises, the survivors have been changed to recover their hand functions, in this paper we are going through the most effective technologies based on stroke hand rehabilitation with the devices which could do that exercises. During the last few years, interest has been growing for the hand rehabilitation technologies, FES “function electrical assimilation” has been widely used to restore upper limb functions in people with hand disability and it has improved their ability to perform their activities of daily living (ADL)
Knockout and Geno-Tagging Alleles in Zebrafish

a Key Laboratory of Cell Proliferation and Differentiation of the Ministry of 7 Education, Peking University Genome Editing Research Center, College of Life 8 Sciences, Peking University, Beijing 100871, P. R. China; 9 b Laboratory of Chemical Genomics, School of Chemical Biology and 10 Biotechnology, Peking University Shenzhen Graduate School, Shenzhen 518055, P. 11 R. China; 12 c Gcrispr (Tianjin) Genetic Technology, Tianjin 301700, P. R. China; 13
Preserving Multi-level Semantics in Conventional Two-Level Modeling Techniques

Conceptual models are often built with techniques that propose a strict stratification of entities into two classification levels: a level of types (or classes) and a level of instances. Multi-level conceptual modeling extends the conventional two-level scheme by admitting that types can be instances of other types, giving rise to multiple levels of classification (individuals, classes, metaclasses, metametaclasses, and so on). As a result, multi-level models capture not only invariants about individuals, but also invariants about types themselves, which become regular elements of the domain of inquiry (first-class citizens). Despite the benefits of the multi-level approach, the vast majority of tools for conceptual modeling are still confined to the two-level scheme, and hence cannot accommodate multi-level entities. This paper proposes a transformation of multi-level to two-level models that preserves the semantics of the original multi-level model. We employ the systematic reification of the instance facet of a class and its linking to the type facet. The feasibility of the approach is demonstrated by a transformation of ML2 (multi-level) models to Alloy (two-level) specifications.
Fully Probabilistic Design for Stochastic Discrete System with Multiplicative Noise

In this paper, a novel algorithm based on fully probabilistic design (FPD) is proposed for a class of linear stochastic dynamic processes with multiplicative noise. Compared with the traditional FPD, the new procedure is presented to deal with multiplicative noise and the system parameters are estimated online using linear optimisation methods. The performance index is characterised by the Kullback-Leibler divergence (KLD) distance. The generalised probabilistic control law is obtained by solving a generalised Riccatti equation that takes the multiplicative noise into consideration. To demonstrate the effectiveness of the proposed method, a numerical example is given and the results are compared with the traditional FPD.
Aquatic Microbial Ecology 79:221

Increases in atmospheric carbon dioxide (CO2) change ocean chemistry, as dissolved CO2 leads to a reduction in the seawater pH. Many marine taxa have been shown to be affected by ocean acidification; however, information on marine fungi is lacking. We analyzed the effect of pH on mycoplankton communities. The pH of microcosms was adjusted to a value mimicking the predicted ocean acidification in the near future. Fungal communities were analyzed using a double-marker gene approach, allowing a more detailed analysis of their response using 454 pyrosequencing. Mycoplankton communities in microcosms with in situ and adjusted water pH values differed significantly in terms of structure and diversity. The differences were mainly abundance shifts among the dominant taxa, rather than the exclusion of fungal groups. A sensitivity to lower pH values was reported for several groups across the fungal kingdom and was not phylogenetically conserved. Some of the fungal species that dominated the communities of microcosms with a lower pH were known pathogenic fungi. With the increasing awareness of the significant role fungi play in marine systems, including performing a diverse range of symbiotic activities, our results highlight the importance of including fungi in further research projects studying and modeling biotic responses to the predicted ocean acidification.
Computation of Transient Electromagnetic Fields Surrounding Grounding Systems

New hybrid approach for predicting electromagnetic environment of grounding systems un der lightning strike is presented. In this approach three methods are summarized: antenna theory how analytic al formulas are developed; modified images theory and transmission line theory. This method can be either directly in time domain, it’s very easy to understand, reasonably accurate and time efficient.
Effects of National Institute for Learning Development Educational Therapy for students with learning difficulties

This research project was undertaken in partial fulfillment of a Doctor of Education degree at Regent University in Virginia Beach. Only limited information from the study is presented in this article. To access the complete study, including a full literature review, complete presentations of group demographics and statistical procedures as well as findings regarding written expression, please contact NILD. The National Institute for Learning Development (NILD) is a nonprofit organization dedicated to training educators to work with children and adults with learning difficulties through an individualized program of educational therapy. NILD defines educational therapy as an intervention that first determines a student’s patterns of learning strengths and weaknesses and then provides intense instruction in a one‐to‐one setting to remediate the identified educational weaknesses. NILD Educational Therapy ® focuses primarily on basic academic skills such as reading, spelling, written expression, and mathematics. Improved skills are developed to achieve grade‐level academic proficiency using a combination of direct instruction (Carnine, Silbert, & Kameenui, 1997) and mediated‐ learning strategies (Feuerstein, 1980). NILD educational therapists are professionals who create a supportive learning environment and offer an intensive intervention to students with learning challenges based on the appraisal of information received from parents, classroom teachers, and psychoeducational evaluations.
Religiosity, Personality Development and Protective Mechanism against Disobedience: A Review

This paper reviews selected articles on the role of religiosity in two main aspects: personality development and protective mechanism against disobedience. In the first part, several studies consistently found that religiosity and personality are highly correlated. Agreeableness and Honesty-Humility are two main personality characteristics that reflect the personality of religious people. These findings correspond to the existing literature on Islamic principle of akhlak vis-a-vis personality that indicated the desirable and virtuous characteristics of people with faith. The second part is on the role of religiosity as a protective mechanism against various acts of disobedience. Reviews of selected work indicated that generally, higher religiosity cause the lower involvement in alcoholic drinking, tax evasion, depressive syndrome and drug usages. New studies on exploring the underlying process on causation effects of religiosity from Islamic perspective, on the personality development and as protective mechanism against different forms of disobediences are thus, strongly recommended. Keywords: Religiosity; personality; protective mechanism; disobedience
A comparison of a Convolutional Neural Network and an Extreme Learning Machine for obscured traffic sign recognition

The present paper compares two neural network architectures for traffic sign recognition (TSR). First, a convolutional neural network (CNN) pre-trained for object recognition and retrained for TSR. Second, a single-hidden-layer feed forward neural network (SLFN), trained by an extreme learning machine (ELM) algorithm with a histogram of oriented gradient (HOG) feature extractor. The comparison focusses on recognition accuracy and computational costs regarding normal as well as obscured traffic signs. The models are trained and tested on a combination of traffic signs from the German TSR benchmark dataset, the Belgium traffic sign classification dataset and the revised mapping and assessing the state of traffic infrastructure (revised MASTIF) datasets. Results show an advantage of the ELM in recognition accuracy, computational costs and robustness on obscured traffic signs.
Use of data processing for rapid detection of the prostate-specific antigen biomarker using immunomagnetic sandwich-type sensors

Diagnosis of cancer using electroanalytical methods can be achieved at low cost and in rapid assays, but this may require the combination with data treatment for determining biomarkers in real samples. In this paper, we report an immunomagnetic nanoparticle-based microfluidic sensor (INμ-SPCE) for the amperometric detection of the prostate-specific antigen (PSA) biomarker, the data of which were treated with information visualization methods. The INμ-SPCE consists of eight working electrodes, reference and counter electrodes. On the working electrodes, magnetic nanoparticles with secondary antibodies with the enzyme horseradish peroxidase were immobilized for the indirect detection of PSA in a sandwich-type procedure. Under optimal conditions, the immunosensor could operate within a wide range from 12.5 to 1111 fg·L−1, with a low detection limit of 0.062 fg·L−1. Multidimensional projections combined with feature selection allowed for the distinction of cell lysates with different levels of PSA, in agreement with results from the traditional enzyme-linked immunosorbent assay. The approaches for immunoassays and data processing are generic, and therefore the strategies described here may provide a simple platform for clinical diagnosis of cancers and other types of diseases.