Miracle-dz/UniFAR-FTUs huggingface dataset:
Variables that Influence Platelet Function Analyzer-100™ Closure Times in Healthy Algerian Adults

Context: The Platelet Function Analyzer (PFA-100™) assesses primary hemostasis in vitro under high shear stress to simulate the conditions to which platelets are exposed at the site of an injured blood vessel wall. Aims: We investigated preanalytical variables in healthy Algerian adults, and we also assess the performance of the test. Subjects and Methods: Closure time (CT) was measured in 302 well-characterized healthy Algerian adults with the collagen/epinephrine (CEPI) and the collagen/adenosine diphosphate (CADP) cartridges. Results: Age and sex did not affect CT values. Blood group O was associated significantly with longer CEPI CT and CADP CT than non-O groups (P s804; 0.0001 for both). CTs were shorter in samples collected in the morning vs the afternoon (P < 0.0001 for both). We found a strong positive correlation between CT CEPI and CT CADP with r = 0.72 and P < 0.001 and an inverse mean correlation between von Willebrand factor level and CT with r = −0.56, r = −0.45 for CT CEPI and CT CADP, respectively P < 0.001. Duplicate analysis of PFA-100™ CT revealed a mean difference of 3.6% ±19.1% for the CEPI cartridge and 1.5% ±10% for the CADP cartridge. The mean coefficient of variation was 7.4% for the CADP CT and 7.6% for the CEPI CT. No marked difference between test positions. Conclusions: The PFA-100™ showed good reproducibility. The variables influencing the test in healthy Algerian adults are similar to Western and Asian populations. Standardization of preanalytical and analytical conditions is essential for obtaining reliable PFA-100™ results.
Effects of In-Package Sulfur Dioxide Generators, Package Liners, and Temperature on Decay and Desiccation of Table Grapes

Six kilograms of Emperor grapes ( Vitis vinifera L.) were packed in vented corrugated cartons with a bottom excelsior cushion pad, then inoculated with berries infected with Botrytis cinerea Pers. The packs were either not treated with SO 2 or given an initial SO 2 room fumigation or provided with a quick-release (QR) in-package SO 2 generator (1.5 g NaHSO 3 affixed to a paper sheet) placed on top of the fruit. In some cartons, an unvented polyethylene liner enclosed the cushion pad, fruit, and a QR generator. After six days at 25°C, untreated vented packs with no poly liner had 90% decayed berries, those that had been room fumigated 55%, and those with the generator 80%. The stems of these packs were very dry and brown and the berries very soft from desiccation. Grapes in the unvented poly liners had 1% decayed berries, and stems were still plump and green and the berries fairly turgid. Unvented packs held for six days at 10° C and at O°C had respectively 1% and 0% decayed berries, and the condition of the packs was rated respectively good and excellent. Inoculated Thompson Seedless grape packs ( V. vinifera L.) held at 25°C in unvented poly liners with a QR generator had no decay until the fourth day. Grapes with a modified QR generator (2.7 g NaHSO 3 ) had no decay until the fifth day. Fruit in a poly liner with 6 mm diameter vents on a 112 mm spacing (0.23% vented area) had significantly more decay than that in an unvented liner packed with either the 1.5 or 2.7 g generator. A vented area of 0.92% generally increased decay during six days, but with an area of 3.68% decay was less. Drying and browning of stems and softness of berries was related directly to the amount of vented area. The three SO 2 treatments significantly retarded browning of stems, and the amount of browning was related inversely to dose of SO 2 . Weight loss was 0.1% after six days for grapes in an unvented liner, but was 3.75% if the liner had 0.23% vented area. With 0.92% vented area the loss was 4.3% and with a vented area of 3.68% the loss of 6.5%. This last value exceeds signficantly the 5.7% weight loss for the vented Kraft liner.
Existing EFL Pedagogies in Thai Higher Education: Views from Thai University Lecturers

Since English is extensively used among linguacultural users to access life opportunities, it has become a requisite foreign language in the Thai educational system. To prepare Thai learners for this new changing role of English and reduce English Language Teaching dependency on the native English variety, this study aimed to explore English lecturers’ voices in Thai universities on existing English as a Foreign Language (EFL) pedagogies at the Thai tertiary level with the research question: how do English lecturers in Thai universities perceive EFL in Thai universities? Data was collected through semi-structured interviews with 25 Thai EFL university lecturers selected from ten different universities in Thailand and analyzed using content analysis. The finding reveals that EFL-oriented pedagogy plays a dominant role in English language teaching (ELT) education in Thai classrooms, illustrating three main salient themes from the study: (1) EFL pedagogies; (2) EFL materials; and (3) EFL curriculums. The result shows that the pedagogy is less responsive in the changing roles of English use and its widespread worldwide, especially among diverse linguacultural interlocutors. Hence, English university lecturers should reconsider, adjust, and made more practical glocal changes in English language teaching for the purpose of language teaching, language planning and predicting language change.
Contextual Barriers of Respectful Workplace in Nursing: A Focused Ethnography

Background: Respectful relationship among nurses is an important influencing factor of positive work environment and nursing outcomes. Disrespectful interpersonal behaviors set the scene for an unpleasant and unhealthy workplace in nursing. This can be harmful to persons and their organization and affect health care outcomes. This study was designed in order to search for contextual barriers to respectful behaviors in the context of nursing. Materials and Methods: This study was a focused ethnography that was carried out in medical-surgical wards of Shahid Chamran Hospital in Isfahan in 2018-2019. The data collection method consisted of 140 h of participant observation and semi-structured interviews with 34 informants. The nformants comprised 29 nurses, 2 assistant nurses, a physician, and 2 patients who were selected by purposive sampling. The first author of the study made direct observations as an outsider. The data were analyzed by Spradley's method. Results: Three main categories and eight subcategories were obtained from data analysis that are as follows: 1) Personal self: challenges of perceived respect (negative self-concept, unpleasant feelings, and ineffective communication), 2) Organizational-based perceived disrespect (poor organizational climate, inadequate job condition, restrictive organizational structure), 3) Social self: challenges of showed respect (implicit social norms, cultural gap). Conclusions: Individual and social attitudes, interactive communication, and organizational factors are the contextual determinants of a respectful workplace in nursing. Consequently, improving self-concept and effective communication skills as well as adjust organizational conditions and value conceptualization in society may effect a respectful workplace in nursing.
The Patients' Experiences of Burden of Neurofibromatosis: A Qualitative Study

Background: Neurofibromatosis Type 1 (NF1) is a common autosomal disorder; the criteria for the diagnosis of NF1 includes café au lait spots, freckling, and Neurofibromas (NF). Skin symptoms have a major impact on patients' Quality of Life (QOL) but little is known about the burden of the disease on patients. The aim of this study was to explore the experiences of patients with NF. Materials and Methods: Using purposive sampling, 20 participants were enrolled in this qualitative content analysis study. The study was carried out between 2019 and 2020. Unstructured interviews and field notes were used to gather data. Data collection was stopped when data saturation was achieved. Results: Data analysis revealed 14 subcategories and 4 categories including “failing and falling behind in life”, “deprivation and restriction”, “social isolation”, and “ineffective adaptation to the disease”, which indicate the perception of patients with NF. Conclusions: In addition to the physical burden due to physical complications and problems, NF imposes a high degree of psychological and social burden on patients causing mental conflicts, which in turn results in them failing and falling behind in life. These findings illustrate the need to develop strategies and use multidisciplinary approaches to support patients, and thus to reduce the burden of NF.
Posterior Urethral Polyp in Children

Background: Polyps of the urethra is a rare cause of obstruction of the lower urinary tract. The clinical presentation is not specific; the symptoms vary and may be isolated or associated, including acute retention of urine, dysuria, and hematuria. Ultrasound and voiding urethrocystography guide the diagnosis. Urethrocystoscopy confirms the diagnosis and allow the treatment. Our aim is to bring to light this rare condition and report our experience in the management of posterior urethral polyps. Subject and Methods: A retrospective study of posterior urethral polyp presented from 2008 to 2019 was performed. Charts were evaluated for clinical presentation, management, pathology findings, and long term follow-up. Results: Six patients were recorded. Dysuria and hematuria are the most reported features. Ultrasonography and voiding cystourethrogram made the diagnosis in 4 patients out of 6. Urethrocystoscopy made the diagnosis and transurethral resection in all our patients. Conclusions: Posterior urethral polyp is a rare benign tumor in children. Urethrocystscopy allow both diagnostic and therapeutic.
Evaluating the Efﬁcacy of Data Augmentation Using Generative Adversarial Networks For Identiﬁcation of Leukemia Cells

The classiﬁcation of Leukemia cells using machine learning models are poised to have great beneﬁts in healthcare such as reduced diagnosis time and improved efﬁciency. However, the lack of labeled training data sets due to hospital patient privacy rules and difﬁculty of obtaining professionally labeled images makes it nearly impossible to get access to sufﬁciently large datasets needed to train such models. In this project, we propose a method for novel data generation of cell images by leveraging the Wasserstein GAN with Gradient Penalty (WGAN-GP). Additionally, our technique proves that the accuracy of a leukemia cell binary classiﬁer which was originally only trained on real cells can be improved when training data is augmented with generated images from our GAN generator .
Panchromatic Type II Photoinitiator for Free Radical Polymerization Based on Thioxanthone Derivative

A new photoinitiator for free radical photopolymerization, belonging to the thioxanthone derivatives, was synthesized and characterized. It was found that the compound absorbs over the whole UV–vis spectrum with relatively high absorption coefficients. Fluorescence studies reveal that three different singlet excited states are responsible for this absorption. Phosphorescence and laser flash photolysis evidence the formation of a triplet state from which a photoreduction can occur. Consequently, initiating radicals were formed which are able to initiate the photopolymerization of methyl methacrylate in DMF. Finally, the photopolymerization of acrylates was performed in film at different wavelengths such as 392, 476, 532, and 632 nm, emphasizing the possibility to use this novel photoinitiator when panchromatic irradiation is required.
CS 230 Project Milestone: Multimodal Financial Market-Crash Prediction and Market-Health Analysis

In this paper, we propose a multi-modal deep-learning methodology to predict the next market crash so that policy-makers and the treasury can be better prepared take preventative measures. Given the inter-connectedness of modern markets and increased susceptibility to volatility, we strive to build upon existing literature in the ﬁeld and develop a model that incorporates both quantitative ﬁnancial market data and qualitative sentiments from news headlines to better predict such market-crashes. In our model, we test a variety of encoder architectures and ultimately achieve an AUC of approximately 0 . 8 across the task using multiple dense layers and dropout.
Thin-film solid-state rechargeable lithium battery

This paper describes the optimization and the materials technology required for fabricating thin-film solid-state rechargeable lithium batteries. The following materials were selected, deposited and optimized: a glassy lithium-phosphorus oxynitride electrolyte (LiPON) between a lithium (Li) anode and crystalline lithium-cobalt dioxide cathode (LiCoO2), deposited by RF-sputtering. Ti/Pt layers, deposited by evaporation (using the e-beam technique) were used in contacts and a silicon nitride thin film (Si3N4), deposited by Hot-wire CVD protects the battery. This technology allows batteries with a potential of 4.5 V, typical capacities of 50 μA. cm and charge discharge rates up to 4C.
Entrepreneurship Perception during the first COVID-19 Shock : Mental Representations of Entrepreneurship and Preferences of Business Models during the Pandemic

We examine the explicit business model preferences and implicit mental representations of entrepreneurship in the early phase of the crisis. We find that the crisis comes with adaptations in both. During crisis, society is open for new business models, even though people increasingly rely on established economic actors instead of opening up towards newly founded firms. We conclude that the early and sudden impact of the crisis influences the entrepreneurial culture onwards and therefore potentially future entrepreneurial activities.
Masking private user information using Natural Language Processing

The Internet brings a lot of efficiency to our lives but we must be aware that everyone exchanges a huge amount of data while interacting with the internet. One of the most important leisure activities one gets from the internet is to be able to socialize. For example, social media has become part and the core of our lives. With more than 2.3 billion active users, data privacy is an issue of concern. The world of the internet has become full of frauds hunting for personal information they leverage for their immoral activities. So, coming up with an algorithm that could secure data and process it such that no private data is involved, and machines continue to be trained with greater data. This could mean a dataset with data that is processed in a manner to make it anonymous. If there is any private information, we will mask that information with pseudo data. We use Named Entity Recognition using Deep Learning for identifying and masking personal information. In this paper, we will discuss how we mask private data. This model will be a successful technique to hide one’s personal information to achieve complete data privacy .
IN-PLANE STATIC CYCLIC TESTS ON TRADITIONAL ROMANIAN HOUSES’ WALLS

The traditional houses in Romania are mainly made of timber. Depending on the availability, the timber frames have different types of infills, from earth with straw, to mud bricks and wattle and daub. Recently, the traditional construction methods are being lost with time passing, and the actual seismic behavior was never studied experimentally in Romania. The paper presents an experimental program conducted on three types of traditional Romanian houses, which were found as predominant in areas around the main seismic source of Romania, Vrancea. The main parameters obtained by static cyclic tests are discussed and compared.
Serpentine StarCraft II Agent - Danger Noodle

In June of 2019 team Serpentine submitted a StarCraft II minigame agent to the FruitPunch AI Competition, which was the debut competition of our team. In this competition we designed and implemented a machine learning based agent that was able to play a variation on a StarCraft II game. We managed to end in ﬁrst place using a reinforcement learning setup with a neural network, implementing Q-learning and an epsilon greedy training policy. We managed to create coherent behaviour that allowed us to win. However scripted tactics still appeared superior and the approach did not generalize well against stationary opponents. A more structured implementation approach, modular enough to test diﬀerent parts of the algorithm automatically and to debug much more eﬃciently, is required to solve problems like this in the future. Going forward we believe that separating concerns during implementation for these kinds of algorithms is essential in order for them to be usable.
DJEnsemble: a Cost-Based Selection and Allocation of a Disjoint Ensemble of Spatio-temporal Models

Consider a set of black-box models – each of them independently trained on a different dataset – answering the same predictive spatio-temporal query. Being built in isolation, each model traverses its own life-cycle until it is deployed to production, learning data patterns from different datasets and facing independent hyper-parameter tuning. In order to answer the query, the set of black-box predictors has to be ensembled and allocated to the spatio-temporal query region. However, computing an optimal ensemble is a complex task that involves selecting the appropriate models and defining an effective allocation strategy that maps the models to the query region. In this paper we present DJEnsemble, a cost-based strategy for the automatic selection and allocation of a disjoint ensemble of black-box predictors to answer predictive spatio-temporal queries. We conduct a set of extensive experiments that evaluate DJEnsemble and highlight its efficiency, selecting model ensembles that are almost as efficient as the optimal solution. When compared against the traditional ensemble approach, DJEnsemble achieves up to 4X improvement in execution time and almost 9X improvement in prediction accuracy.
Adapting Convex Techniques for Greedy Layerwise Learning

Convex duals of nonconvex optimization problems allow us to ﬁnd optimal solutions quickly and efﬁciently. Recent work by [Pilanci & Ergen 2020][7] has found nonconvex duals for the task of training shallow, fully-connected ReLU networks. In this paper, we explore extending convex training techniques to deeper networks by using a greedy layerwise training approach (introduced in the paper Belilovsky et al. 2019)[3]). We ﬁnd that adding layers in this way often allows us to increase test accuracy. Further, column normalization is required to make layerwise learning effective in this context. We achieved ﬁnal test accuracy of 50 . 1% on the CIFAR-10 dataset compared to 45 . 9% with single-layer architectures.
In-vitro Evaluation of Antioxidant Potency of Organic Extracts of Leaves of Corchorus depressus Linn.

Aim: Evaluation of free radical scavenging and lipid peroxidation inhibitory activities of commercially available leaves of Corchorus depressus Linn. by in-vitro chemical analysis. Methodology: Four different solvent extracts methanol-CDM, ethanol-CDE, ethyl acetate-CDEA and hexane-CDH were studied for their free radical scavenging activities using 1-diphenyl-2picrylhydrazyl (DPPH) radical assay method and the results were expressed as SC50 values. The lipid peroxidation inhibitory activities of three different concentrations (0.1, 0.5 and 1.0 mg/mL) were evaluated using β-carotene-linoleic acid model system and the results were expressed as oxidation rate ratio (ROR), antioxidant activity (AA) and antioxidant activity coefficient (CAA). L-Ascorbic acidAA, α-tocopherol-TOC and BHT were used as reference compounds. The total polyphenol contents of these extracts were also determined using Folin-Ciocalteau reagent. Results: The total polyphenol contents of extracts were decreased in the order of: CDM > CDE > CDEA >> CDH. In DPPH radical assay, CDM exhibited higher free radical scavenging activity Original Research Article Nessa and Khan; EJMP, 14(4): 1-13, 2016; Article no.EJMP. 26006 2 (SC50: 216.27 μg/mL) than CDE (327.84 μg/mL) and CDEA (544.28 μg/mL). In comparison with natural antioxidants AA and TOC, the overall ranking was decreased in the order of: AA > CDM > TOC > CDE > CDEA >> CDH. In β-carotene-linoleic acid model system, CDM also exhibited higher protective activity against lipid peroxidation than other extracts as it exhibited lower ROR (0.4903 to 0.2752) and higher AA (50.96 to 72.47) and CAA (280.58 to 513.13) respectively amongst the studied extract. In comparison with BHT and TOC, CDM exhibited promising potency than TOC. Amongst the studied concentration 0.5 and 1.0 mg/mL were the mostly potent antioxidant against oxidation of linoleic acid. Conclusion: CDM exhibited most propitious antioxidant activities irrespective of the method undertaken in this study. CDM and CDE had protective activity against oxidation of fatty acid as well as both efficiently scavenged free radicals.
Laboratory study of physical barrier efficiency for worker protection against SARS-CoV-2 while standing or sitting

Abstract Transparent barriers were installed as a response to the SARS-COV-2 pandemic in many customer-facing industries. Transparent barriers are an engineering control that intercept particles traveling between customers and workers. Information on the effectiveness of these barriers against aerosols is limited. In this study, a cough simulator was used to represent a cough from a customer. Two optical particle counters were used (one on each side of the barrier, labeled customer and worker) to determine the number of particles that migrated around a transparent barrier. Ten configurations were tested with six replicates for both sitting and standing scenarios, representing nail salons and grocery stores, respectively. Barrier efficiency was calculated using a ratio of the particle count results (customer/worker). Barriers had better efficiency (up to 93%) when its top was 9 to 39 cm above cough height and its width was at least 91 cm. Barriers that extended 91 cm above table height for both scenarios blocked 71% or more of the particles between 0.35–0.725 µm and 68% for particles between 1 to 3 µm. A barrier that blocked an initial cough was effective at reducing particle counts. While the width of the barriers was not as significant as the height in determining barrier efficiency it is important that a barrier be placed where interactions between customers and workers are most frequent. Bystander exposure was not taken into consideration along with other limitations.
A ResNet-50-based Transfer Learning and Ensemble Method for Structural Health Monitoring

In Structural Health Monitoring (SHM), engineers and inspectors analyze images of damaged buildings, and assess whether said buildings are structurally sound. In this report, we present deep learning solutions to three visual classiﬁcation tasks that are performed in SHM: Scene-Level classiﬁcation, Collapse-Mode classiﬁcation, and Damage-Level classiﬁcation. Our algorithms are trained on data from the PEER Hub Image Net ( Φ -Net), which had curated datasets for the three tasks we worked on. For all three tasks, we show how by starting with a ResNet-50 architecture and then applying transfer learning and ensembling, we are able to match, and in one case outperform, the state of the art. Furthermore, we present an analysis of sources of error in our model, and demonstrate that the most common sources of error are mislabeled data or data with ambiguous labels on the boundary between classes.