Miracle-dz/UniFAR-FTUs huggingface dataset:
Communication and building positive relationships within project teams in non-governmental organizations

Purpose: The aim of the study was to understand the role of communication and building positive relations in the NGO project team and to answer the following questions: (1) what factors and behaviors influence positive relations in the NGO project team? and (2) to what extent direct and indirect communication affect the efficiency of information flow? Design/methodology/approach: The authors conducted a case study in a selected project team operating in a non-governmental organization in Poland. Findings: The results of the study allow one to better understand the specific challenges the selected NGO project team was facing. Thus, they add new knowledge to the issues on effective communication and building positive relationships in NGO project teams. Moreover, the case study outcomes set the guidelines for further in-depth studies of a quantitative nature. Research limitations/implications: Being aware of the limitations resulting from the deliberate selection of the project team for the study, an analysis of the answers obtained was undertaken, the results of which allow one to present the issues of communication and building positive relationships within project teams in non-governmental organizations. In order to make generalizations, further in-depth research in this area should be carried out. Practical implications: In non-governmental organizations, authorities and project managers should increase their competences in the field of effective communication and building positive relationships in project teams in order to successfully implement projects. Social implications: Knowledge of the methods of effective communication and building positive relationships in project teams allows to increase awareness among members of non- governmental organizations of how the ways of working and team involvement affect the success of projects. Originality/value: A case study was conducted in a selected project team operating in an NGO on the importance of communication and building positive relationships. The article is addressed to people involved in NGO project management research and to third-sector entities.
Fully nonlocal quantum correlations

Quantum mechanics is a nonlocal theory, but not as nonlocal as the no-signalling principle allows. However, there exist quantum correlations that exhibit maximal nonlocality: they are as nonlocal as any nonsignalling correlation and thus have a local content, quantified by the fraction p(L) of events admitting a local description, equal to zero. We exploit the known link between the Kochen-Specker and Bell theorems to derive a maximal violation of a Bell inequality from every Kochen-Specker proof. We then show that these Bell inequalities lead to experimental bounds on the local content of quantum correlations that are significantly better than those based on other constructions. We perform the experimental demonstration of a Bell test originating from the Peres-Mermin Kochen-Specker proof, providing an upper bound on the local content pL less than or similar to 0.22.
First principles many-body calculations of electronic structure and optical properties of SiC nanoribbons

A first principles many-body approach is employed to calculate the band structure and optical response of nanometer-sized ribbons of SiC. Many-body effects are incorporated using the GW approximation, and excitonic effects are included using the Bethe–Salpeter equation. Both unpassivated and hydrogen-passivated armchair SiC nanoribbons are studied. As a consequence of low dimensionality, large quasiparticle corrections are seen to the Kohn–Sham energy gaps. In both cases quasiparticle band gaps are increased by up to 2 eV, as compared to their Kohn–Sham energy values. Inclusion of electron–hole interactions modifies the absorption spectra significantly, giving rise to strongly bound excitonic peaks in these systems. The results suggest that hydrogen passivated armchair SiC nanoribbons have the potential to be used in optoelectronic devices operating in the UV-Vis region of the spectrum. We also compute the formation energies of these nanoribbons as a function of their widths, and conclude that hydrogen-saturated ribbons will be much more stable as compared to bare ones.
Investigation of botulism in free-range duck farming in the Mekong Delta, Vietnam

Background: One of the most common diseases in free-range ducks in the Mekong Delta is botulism. Botulism is a poultry disease caused by botulinum exotoxin of Clostridium botulinum. Aim: To evaluate the prevalence of botulism in free-range ducks in the Mekong Delta and the risk of infection by determining the presence of C. botulinum in the farming environment. Methods: Research was carried out on 200 duck flocks with 187,050 individuals raised freely in the fields in the provinces of the Mekong Delta, including An Giang, Can Tho, Hau Giang, and Kien Giang. The ducks were diagnosed with botulism based on clinical symptoms. To demonstrate the presence of botulinum neurotoxins and identify serotype, samples of serum and/or gut were analyzed by mouse bioassay. Samples of soil (n = 600), water (n = 600), crabs (n = 216), and snails (n = 400) were taken from the grazing regions for C. botulinum analysis by PCR assay. Results: There were 1.19% (2,235/187,050) free-range ducks in the Mekong Delta positive for botulism. Clinical symptoms of botulism including limberneck, drooping eyelids–enlarged pupils, and leg paralysis were prevalent across free-range ducks, with the frequency of 87.92% (1,965/2,235), 90.07% (2,013/2,235), and 79.78% (1,783/2,235), respectively. The lesions of pulmonary edema–hemorrhage, hemorrhagic liver, and gas-producing intestines were common, accounting for 86.19% (362/420), 95.48% (401/420), and 92.14% (387/420), respectively. Botulin toxin type C was found in a considerable number of serum samples, accounting for 40.48% (51/126). Meanwhile, the percentage of serum samples containing botulin toxin types E and D was 28.57% (36/126) and 25.40% (32/126), respectively. Clostridium botulinum was detected in the farming environment specifically 17.5% (105/600) in soil, 19.67% (118/600) in water, 8.33% (18/216) in crabs, and 3.00% (12/400) in snails. Conclusion: The free-range ducks in the Mekong Delta were at high risk of botulism because of the latent presence of C. botulinum in the farming environment.
Category-Extensible Human Activity Recognition Based on Doppler Radar by Few-Shot Learning

Radar-based human activity recognition (HAR) has been applied in many fields such as human–computer interaction, smart surveillance, and health assessment. With the development of deep learning, many deep-learning models have been proposed in radar-based HAR to achieve high classification accuracy. Inevitably, new human activity classes appear continuously, and this requires the deep-learning models to efficiently learn novel categories from only a few data samples while at the same time maintaining high accuracy on the initial human activities on which they were trained. Therefore, this article proposes a category-extensible HAR model based on few-shot learning. The classification weight of the new human activity category is quickly generated through the feature vector extracted by the trained feature extractor and the classification weight of the most similar original category. To solve the mismatching of weight value intervals, we also employ the cosine similarity-based classifier. Furthermore, we adopted the large margin in the softmax cross-entropy (LMSC) loss function to improve the model’s performance and depthwise separable convolution to reduce the computation of the model. The experimental results show that the model can quickly adapt to the new human activity classification task and did not sacrifice the performance on category classification of the original activities. With relatively low computational complexity, our method achieves 81.99% of accuracy when each extended category has only one sample to generate the weights and 91.60% when each of them has only five samples in the task of a three-way.
Coherent state quantum key distribution with multi letter phase-shift keying

We present a protocol for quantum key distribution using discrete modulation of coherent states of light. Information is encoded in the variable phase of coherent states which can be chosen from a regular discrete set ranging from binary to continuous modulation similar to phase-shift keying in classical communication. Information is decoded by simultaneous homodyne measurement of both quadratures and requires no active choice of basis. The protocol utilizes either direct or reverse reconciliation both with and without postselection. We analyze the security of the protocol and show how to enhance it by the optimal choice of all variable parameters of the quantum signal.
Remarks on a challenge to the relation between $CPT$ and Lorentz violation

The objection [arXiv:1103.0168] to my theorem [arXiv:hep-ph/0201258] that violation of $CPT$ symmetry implies violation of Lorentz covariance is based on a nonlocal model in which time-ordered products are not well defined. I used covariance of time-ordered products as the condition for Lorentz covariance; therefore the proposed objection is not relevant to my result.
Detection of Human Mental Stress Using Speech Signals

—Nowadays it is very normal for humans to experience mild or moderate mental stress in a variety of situations. A moderate level of stress is beneficial to an individual; yet, excessive stress hurts a person's mental health and is a risk factor for suicidal ideation if ignored.Long-term stress is linked to physical health concerns, according to research.With an increasing number of individuals experiencing stress, it is critical to be able to recognize it early and assist people in addressing and resolving it before significant harm is done. Conventional methods of detecting stress levels include questioning the subject and monitoring facial expression.Stress-related questions are asked throughout the interview to have a better picture of the person's condition. When people are stressed, their brows form differently, their pupils dilate, and their blinking rate may vary.These approaches have limitations in that they may overlook stress events.Research in the stress detection domain has become quite popular. There is a scope of improvement in enhancing the accuracy of the results obtained using various methods. The use of non-invasive techniques for stress detection is quite promising. This research work proposes a system to detect human mental stress using speech signals. The human speech reflects one's mental condition.The proposed research shall analyze speech signals to recognize human mental stress using machine learningtechniques
International Journal of Multidisciplinary Research and Growth Evaluation www.allmultidisciplinaryjournal.com

ISSN (online): 2582-7138 Volume: 03 Issue: 02 March-April 2022 Received: 19-03-2022; Accepted: 08-04-2022 Page No: 504-511 DOI: https://doi.org/10.54660/anfo.20 22.3. 2.17 Abstract This empirical study examines the time-varying spillover and contagion effects between one major future market, one major FOREX market and six major Islamic CDS markets. We use daily data for crude oil future, SAR/EUR and Saudi Arabia CDS markets. The data spans from February 15, 2011 to August 27, 2020, which entails major economic events. In this paper, we deploy DCC-FIGARCH process. The empirical findings indicate volatility effects spilling over from crude oil future returns to SAR/EUR returns and CDS market returns. Dynamic Conditional Correlations provide empirical evidence of strong contagion effects between the market returns. Conclusions of this paper are of interest to investors diversifying their portfolios of the above markets and to financial derivative markets regulators providing regulations for the under investigation derivative markets.
Policy Distillation from World Models

Model-Based Reinforcement Learning (MBRL) is a signiﬁcantly more sample-eﬃcient alternative to model-free reinforcement learning. In MBRL, supervised learning is used to optimize a deep neural network model of the transition and reward dynamics in an environment (i.e. a world model). This leads to a rich training signal which enables training such a world model with fewer environment interactions than typically required to train model-free methods. However, an open question in MBRL remains how to distill eﬀective policies from world models. Here we show that PlaNet, an MBRL method that has been shown to perform well in simulation, is ineﬀective for an in-vivo environment with real-time constraints. In this work, we propose a better alternative by exploiting the gradients of the world model to train a parametric policy model with back-propagation through physics. We have evaluated the performance of PlaNet on an inverted pendulum swing-up task on an in-vivo robot setup. We have found that it is unable to reach an acceptable control frequency and is too intolerant to latency to eﬀectively solve the task. We have evaluated two alternative policy distillation methods: imitation learning and a gradient-based approach. We have found imitation learning ineﬀective and have shown that our gradient-based approach not only allows for faster inference but also achieves better performance than PlaNet. Our results demonstrate that with the right architectures to alleviate model-bias, exploiting the gradients of learned world models can be an eﬀective method for policy distillation in model-based reinforcement learning.
APODIZED PUPIL LYOT CORONAGRAPHS FOR ARBITRARY APERTURES. V. HYBRID SHAPED PUPIL DESIGNS FOR IMAGING EARTH-LIKE PLANETS WITH FUTURE SPACE OBSERVATORIES

We introduce a new class of solutions for Apodized Pupil Lyot Coronagraphs (APLC) with segmented aperture telescopes to remove broadband diffracted light from a star with a contrast level of 1010. These new coronagraphs provide a key advance to enabling direct imaging and spectroscopy of Earth twins with future large space missions. Building on shaped pupil (SP) apodization optimizations, our approach enables two-dimensional optimizations of the system to address any aperture features such as central obstruction, support structures, or segment gaps. We illustrate the technique with a design that could reach a 1010 contrast level at 34 mas for a 12 m segmented telescope over a 10% bandpass centered at a wavelength of λ 0 = ? > 500 nm. These designs can be optimized specifically for the presence of a resolved star and, in our example, for stellar angular size up to 1.1 mas. This would allow one to probe the vicinity of Sun-like stars located beyond 4.4 pc, therefore, fully retiring this concern. If the fraction of stars with Earth-like planets is &eegr; ⊕ = 0.1 ? > , with 18% throughput, assuming a perfect, stable wavefront and considering photon noise only, 12.5 exo-Earth candidates could be detected around nearby stars with this design and a 12 m space telescope during a five-year mission with two years dedicated to exo-Earth detection (one total year of exposure time and another year of overheads). Our new hybrid APLC/SP solutions represent the first numerical solution of a coronagraph based on existing mask technologies and compatible with segmented apertures, and that can provide contrast compatible with detecting and studying Earth-like planets around nearby stars. They represent an important step forward toward enabling these science goals with future large space missions.
CHANGES IN THE FREQUENCY OF B-CELL SUBSETS IN ANCA-ASSOCIATED VASCULITIS AND PEMPHIGUS VULGARIS; A CROSS-SECTIONAL STUDY

Visualization of flow cytometry data using t-SNE analysis B subsets Different distribution of B cell subsets in and Characterization Distribution cell subsets based on the traditional gating of cytometry Abstract Introduction: autoimmune diseases have a high prevalence in the population and can be the result of various disturbances in immunological tolerance. Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) and Pemphigus Vulgaris are two B-cell mediated autoimmune diseases. The mechanisms that trigger these diseases are not fully understood yet. However, changes in function, phenotype, and frequency of B-cells could contribute to the pathogenesis of these diseases. This study aims to investigate which B cell subsets are associated with active AAV and Pemphigus and whether these subsets differ from the healthy controls (HCs). Methods: Fresh blood samples from 3 active GPA patients, 5 active Pemphigus patients, and 5 HC were stained using a multiparameter flow cytometry panel that encompasses the surface markers CD19, CD27, CD28, CD24, and IgD. Data were analyzed using a t-distributed Stochastic Neighbor Embedding (t-SNE) analytical tool to visualize several B-cell clusters based on their expression markers. Five Clusters that had significant differences in the distribution between the patients and HCs were further analyzed using traditional gating methods based on the expression level of their markers. For this purpose, data from 9 GPA- and 15 Pemphigus patients and 15 HCs were used. The percentage of B cells in each cluster was statistically analyzed to determine if the groups had significant differences compared to each other. Results: the t-SNE analysis revealed that there were significant differences in the levels of marker expression in various clusters. Naive B cells were significantly decreased in patient groups compared to the HCs. Only GPA patients had an increased frequency in transitional compared to HCs, while Pemphigus showed decreased frequencies. Double switched memory B cells were greatly increased in 2 out of the 5 pemphigus patients. Switched memory B cells were decreased in both GPA and Pemphigus compared to HCs. Based on the traditional gating of the data, no significant differences were observed between the groups. Conclusions: An overall altered distribution of naive, transitional and memory B cell subsets was found in GPA and Pemphigus patients compared to HCs. However, when GPA and Pemphigus were compared to each other, there were no similarities in the distribution of B cell subsets between these two diseases.
The Eﬀects of Parental Job Displacement on the Educational Outcomes of Children in the Context of High-Stakes Tests

This study investigates the eﬀects of parental job displacement on the educational outcomes of children in the context of Dutch high-stakes test. Exploiting the variation in the timing of job displacement around the test date, this study ﬁnds that children whose parents are displaced before the test date obtain lower language and total test scores, receive lower track placement recommendations and have a lower probability of attending pre-university tracks. Heterogeneity analysis shows that these eﬀects are driven by paternal job displacement.
Effect of supplementation of sodium bicarbonate and yeast bolus on milk production performance of dairy cows

The study was conducted with 36 crossbred lactating cows to compare the effects of sodium bicarbonate and yeast bolus and their combination on milk yield and milk composition. 3 small dairy farms were selected and experiment design of this study was Complete Randomized block Design. Each farms grouped into four, Each group consist of 3 animals. All the animals are in early lactation stage with same feeding schedule. The experimental animals were divided into four treatments. Control, Sodium bicarbonate, Yeast culture bolus and combination of sodium bicarbonate and live yeast culture bolus. The dose of sodium bicarbonate and yeast culture bolus used in this study was 50 g/day/animal and 2 bolus/day/animal. The trial was conducted for 30 days with 10 days for pretrial period and last twenty days milk yield, milk fat and Solid Not fat were recorded. Data was analyzed statistically. In this study, dairy cow supplemented Sodium bicarbonate, Yeast culture bolus and combination of sodium bicarbonate and yeast culture bolus were shown significant ( P <0.01) increase in milk yield and milk fat percentage compared with control. However, Solid Not Fat percentage of milk was not significantly increased in Sodium bicarbonate, combination of sodium bicarbonate and live yeast culture bolus and yeast culture bolus against control.
Uncovering the peatland root microbiome: Environmental factors shaping microbial community structure

This study will examine the effects of simulated whole-ecosystem warming and elevated levels of carbon dioxide on the microbial communities within the root-soil microbiomes of vascular plants in peatlands. Root samples obtained from the SPRUCE site in Minnesota will be used to carefully characterize the microbial communities in the root tissue and the surrounding rhizosphere. The microbial communities can then be examined for any effects of whole ecosystem warming and the enrichment of carbon dioxide in the atmosphere, creating a glimpse into the future of peatlands and the associated effects of climate change drivers. This study marks an important step on a path to a greater understanding of peatland root microbiomes and climate driven effects on these microbial communities.
Narrative Discourse Structure Creation Support System for Reflecting Theme and Emotional Impression

: Authors sometimes create narratives for the purpose of conveying the message ( theme ). In addition, they often start with deciding the emotional genre ( emotional impression ), such as “sad story. ” So far, our research group has defined a narrative discourse structure and has proposed the process for creating it from the theme and emotional impression. The process determines the order of deriving the elements in the discourse structure. However, some authors found difficult to derive them. This paper proposes a system for the step-by-step creation of the discourse structure along with the process by giving supports of deriving the elements.
COMMUNICATION CHANNEL FAILURE PREDICTION IN 5G NETWORKS

vii List of Abbreviations Used . viii Acknowledgements . ix Chapter
Motivating In-Network Aggregation for Distributed Deep Neural Network Training

DNN training is moving from single node to cluster level with the aid of current DNN training frameworks[1, 2]. However, we ﬁnd distributed DNN training time scales only sublinearly with the number of participating nodes in the system. Our experiments show this is due to frequent large-size parameter updates during parameter synchronization which is capped by the network capacity. This is especially relevant as model complexity is growing. We present a comprehensive characterization and pinpoint the network as the bottleneck of DNN training today. We examine In-Network Aggregation (INA) in the context of distributed DNN training which targets directly at eliminating the bottleneck, and show the effectiveness of INA by simulating with existing hardware and DNN Framework, which promises a strong linear scaling of DNN training throughput
Edinburgh Research Explorer State of the art CT and MR imaging and assessment of carotid artery disease: the reporting - a consensus document by the European Society of Cardiovascular Radiology (ESCR)

The European Society of Cardiovascular Radiology (ESCR) is the European specialist society of cardiac and vascular imaging. This society ’ s highest priority is the continuous improvement, development, and standardization of education, training, and best medical practice, based on experience and evidence. The present intra-society consensus is based on the existing scientific evidence and on the individual experience of the members of the ESCR writing group on carotid diseases, the members of the ESCR guidelines committee, and the members of the executive committee of the ESCR. The recommendations published herein reflect the evidence-based society opinion of ESCR. The purpose of this second document is to discuss suggestions for standardized reporting based on the accompanying consensus document part I.