Miracle-dz/UniFAR-FTUs huggingface dataset:
IDComparison of Base Excess Approach Versus Stewart ’ s Physicochemical Method for the Evaluation of Metabolic Acid-Base Disturbances in Critically ill Patients Infected with SARS-CoV-2 SARS-CoV-2 ile

Objective: Complex metabolic acid-base disturbances can be seen in critically ill patients infected with the SARS-CoV-2 virus. For arterial blood gas (ABG) analysis, base excess (BE) approach enables limited evaluation of the etiological factors. The Stewart’s physicochemical approach, on the other hand, may not reveal etiological agents adequately. In this study, we aimed to compare BE approach versus physicochemical method for the evaluation of metabolic acid-base disturbances in critically ill patients infected with SARS-CoV-2. Method: Between March 2020 and May 2020, ABG analysis results of a total of 113 patients (71 males, 42 females) infected with SARS-CoV-2 and hospitalized in the adult intensive care units were retrospectively analyzed. The patients were divided into groups according to the BE approach and evaluated for physicochemical components. The ABG and some electrolyte values were compared among groups. Results: The most common acidotic components according to the Stewart’s method were hyperphosphatemia (84.9%), but low strong ion difference (SID) acidosis (62.2%) in patients with metabolic acidosis according to the BE approach. Low SID acidosis (50%) and hyperphosphatemia (30.9%) in patients with normal BE and hyperphosphatemia (77.7%) in patients with metabolic alkalosis according to the BE approach were observed. In patients with metabolic acidosis according to BE approach, 71.6% of the patients had hypoalbuminemia and 24.5% of the cases had high SID alkalosis among the Stewart’s alkalosis components. Strong ion gap (SIG) acidosis was seen in 11.1% and low SID acidosis was seen in 11.1% in patients with metabolic acidosis according to the BE approach. Conclusion: Physiochemical approach seems to provide additional information regarding the etiological factors and unravel the invisible part of the iceberg for the evaluation of metabolic acid-base disturbances in critically ill patients infected with the SARS-CoV-2 virus.
PerfJIT: Test-Level Just-in-Time Prediction for Performance Regression Introducing Commits

Performance issues may compromise user experiences, increase the cost resources, and cause field failures. One of the most prevalent performance issues is performance regression. Due to the importance and challenges in performance regression detection, prior research proposes various automated approaches that detect performance regressions. However, the performance regression detection is conducted after the system is built and deployed. Hence, large amounts of resources are still required to locate and fix performance regressions. In our paper, we propose an approach that automatically predicts whether a test would manifest performance regressions given a code commit. In particular, we extract both traditional metrics and performance-related metrics from the code changes that are associated with each test. For each commit, we build random forest classifiers that are trained from all prior commits to predict in this commit whether each test would manifest performance regression. We conduct case studies on three open-source systems (Hadoop, Cassandra, and OpenJPA). Our results show that our approach can predict tests that manifest performance regressions in a commit with high AUC values (on average 0.86). Our approach can drastically reduce the testing time needed to detect performance regressions. In addition, we find that our approach could be used to detect the introduction of six out of nine real-life performance issues from the subject systems during our studied period. Finally, we find that traditional metrics that are associated with size and code change histories are the most important factors in our models. Our approach and the study results can be leveraged by practitioners to effectively cope with performance regressions in a timely and proactive manner.
Testing Nanomaterials of Unknown Toxicity: An Example Based on Platinum Nanoparticles of Different Shapes

Manipulation of the physicochemical properties of materials at the nanoscale has the potential to significantly improve their electronic, diagnostic, and therapeutic performance. Because of the intended use of nanomaterials and the potential for accidental exposures, it is important to determine if there is any unique toxicity of the nanoscale materials as compared to the bulk. A likely portal of entry following accidental exposure is the lung. As has been demonstrated for nanosized ambient air-borne particles that are largely insoluble, [1–4] engineered nanoparticles (NPs) may also evade macrophage-me-diated particle clearance mechanisms at the site of deposition in the lungs, potentially coming into contact with epithelial and endothelial cells and translocating to distant sites. Inflammation and oxidant stress responses may occur as a result of prolonged retention and unique physicochemical properties of the NPs. It is thought that NPs, either on their own or when combined with cells, produce oxidant species that cause injury to and antioxidant depletion in cells or tissues. [5–7] The same properties that can be manipulated to produce unique characteristics at the nanoscale, such as size, shape, composition, crystal phase, and surface coatings, may also impart toxicity that is not observed with larger particles or bulk samples. We report here the use of Pt NPs to assess shape-dependent uptake, oxidative stress, and inflammatory responses in cultured human umbilical vein endothelial and lung epithelial cells. We also present data from cell-free particle reactivity assays and results from initial in vivo exposures using these Pt NPs. Accompanying data regarding the agglomeration state of these particles in various media, particle size and surface area are also included. It is
ENGLISH LANGUAGE TEACHERS' BELIEFS AND PRACTICES TO PROMOTE LEARNER AUTONOMY

Many researches have been examined learner autonomy in other countries in recent years. Teachers’ beliefs and practices towards learner autonomy at the tertiary level in Vietnam are, however, very marginalized and neglected. This study investigated 385 English language teachers’ perceptions and practices to promote learner autonomy using the quantitative approach with the combination of the adapted Borg & Al-Busaidi’s 2012 questionnaire with the researcher-made items. The results indicated that teachers have high beliefs on learner autonomy; they think it is feasible and desirable to promote learner autonomy in English language teaching and learning. Most of teachers agreed on the factors which limit learner autonomy, and there is no difference in the perceptions regarding the gender in terms of promoting learner autonomy. Therefore, it is necessary for the teachers to encourage the learner autonomy in English language teaching and learning with some pedagogical implications for innovating teaching methodology.
First-principles study of lithium-doped carbon clathrates under pressure

We present a theoretical study of the behavior under pressure of the two hypothetical C46 and Li8C46 type-I carbon clathrates in order to obtain new information concerning their synthesis. Using ab initio calculations, we have explored the energetic and structural properties under pressure of these two carbon based cage-like materials. These low-density metastable phases show large negative pressure transitions compared to diamond, which represent a serious obstacle to their synthesis. However, we show that a minimum energy barrier can be reached close to 40 GPa, suggesting that synthesis of the Li-clathrate under extreme conditions of pressure and temperature may be possible. The electronic band structure with related density of states behavior under pressure, as well as the dependence of the active Raman modes with pressure are also examined.
Relationships Between Athlete Activist Identities and Resilience in College Athletes

Many high-profile athletes have engaged in athlete activism and continued to remain successful both in sport and activism. Although several barriers have been documented preventing athletes from engaging in activism (e.g., public criticism, status and job loss, withdrawal of funding, anticipated distress; Cunningham & Regan, 2012), activism itself has also been connected to several positive outcomes (e.g., improved confidence, self-concept, belief in change, agency, life meaning; Klar & Kasser, 2009; Rabkin, McElhiney, Harrington, & Horn, 2018). Indeed, both sport and activism provide opportunities for athlete activists to develop resilience. Therefore, the purpose of the present study was to examine the relationships between athletic identity (AI), activist identity and commitment (AIC), stress control mindset, and mental toughness. NCAA student-athletes (N = 204) reported low AIC overall. Regression models did not suggest that AI and AIC predict SCM or MT as expected, but correlations did provide evidence that SCM and MT are positively related. Possible explanations for these findings are discussed.
VITON-GT: An Image-based Virtual Try-On Model with Geometric Transformations

The large spread of online shopping has led computer vision researchers to develop different solutions for the fashion domain to potentially increase the online user experience and improve the efficiency of preparing fashion catalogs. Among them, image-based virtual try-on has recently attracted a lot of attention resulting in several architectures that can generate a new image of a person wearing an input try-on garment in a plausible and realistic way. In this paper, we present VITON-G T, a new model for virtual try-on that generates high-quality and photo-realistic images thanks to multiple geometric transformations. In particular, our model is composed of a two-stage geometric transformation module that performs two different projections on the input garment, and a transformation-guided try-on module that synthesizes the new image. We experimentally validate the proposed solution on the most common dataset for this task, containing mainly t-shirts, and we demonstrate its effectiveness compared to different baselines and previous methods. Additionally, we assess the generalization capabilities of our model on a new set of fashion items composed of upper-body clothes from different categories. To the best of our knowledge, we are the first to test virtual try-on architectures in this challenging experimental setting.
Translation Analysis of Sexist Attitudes in Ronggeng Dukuh Paruk Novel (Analisis Terjemahan Sikap Seksis

This study aims to determine which translation techniques are supposed to be used to convey sexist attitudes to the target language and its impact for the translation quality in terms of accuracy, acceptability, and readability. To achieve this goal, the researchers use descriptive-qualitative method. Data are taken from 141 utterances collected through content analysis and Focus Group Discussion. Furthermore, the data are analyzed by using taxonomy and componential analysis to see the cultural value of the utterances. The result shows that there are 14 techniques applied in translating, namely established equivalence, explicitation, modulation, pure borrowing, implicitation, paraphrase, generalitation, transposition, reduction, addition, discursive creation, particularization, compensation, and deletion. Moreover, it reveals that the translation techniques determine the translation quality. Meanwhile, the use of paraphrase produces a low quality translation in the target language. In addition, the application of discursive creation results in non-sexist translation for two utterances. The results of this study are expected to be beneficial for translators in translating sexist attitudes from the source text into the target text, which have different cultures.
Fouling control in a gravity-driven membrane (GDM) bioreactor treating primary wastewater by using relaxation and/or air scouring

Gravity-driven membrane bioreactors (GD-MBR) have been proposed as a sustainable water treatment due to the low energy requirements in terms of operation. The objective of this study is to investigate the effect of different physical cleaning strategies on the membrane performance in a gravity-driven membrane bioreactor treating primary wastewater. The Optical Coherence Tomography (OCT) allowed evaluating the impact of the physical cleaning on the biomass developed on the membrane surface. Applying relaxation did not enhance the membrane performance, however, it led to an increase in thickness and a decrease in the biomass specific hydraulic resistance. Using air scouring under continuous filtration increased the biomass specific hydraulic resistance by compressing the biomass (~50% decrease in thickness). When air scouring was applied at the end of a relaxation cycle, a higher biomass removal and a significant increase in flux (250%) were observed. Biopolymers were found to constitute 55% of the fouling layer. This study highlighted the suitability of an in-situ monitoring approach as a key tool to evaluate the impact of different physical cleaning strategies on the biomass removal in membrane filtration process.
Effect of Essential Oils Versus Home Remedies on Relieving Signs of Acute Respiratory Tract Infection among Children

Acute Respiratory Infection (ARI) accounts for more than 94 million cases annually and 1.9 million deaths among children worldwide. ARI is the most common cause of illness and mortality in children under five years old. The purpose of this study was to investigate the effect of essential oils versus home remedies on relieving signs and symptoms of ARI among children. This study was a non-randomized clinical trial done on 100 children who were assigned to two groups. The severity of symptoms, cough and sleep difficulty were compared in the two groups by using Structured Interview Schedule and the Canadian Acute Respiratory Illness and Flu Scale (CARIFS). The entire group that received essential oils (100%) had mild level of cough and sleep difficulty after 7 days post-intervention, while 72% of the control (home remedies) group had a moderate level of these symptoms. Moreover, there was a marked decrease in all CARIFS items in the intervention group with decreased fever, vomiting, irritability, sore throat and headache post-intervention and there was a highly statistically significant difference among all CARIFS items between control and intervention groups at 7 days post-intervention. Mixture of five essential oils used in this study had more effect than home remedies on relieving signs and symptoms of ARI and this treatment is suggested as a safe and cost effective method to reduce ARI among children.
Use of industrial wastes for the synthesis of belite clinker ; Aprovechamiento de residuos industriales para la síntesis de clínker belítico

The synthesis of belite clinker was studied using industrial wastes: paper sludge, cement kiln dust and rice husk ashes, as substitutes for natural raw materials. Wastes were characterized by XRF, XRD and TG analysis. Different formulations were prepared to produce clinker at 1300, 1350 and 1400 °C. The clinker obtained was characterized using optical microscopy, XRD and f-CaO content determined by ethylene glycol method. Finally, the hydration of prepared cements with the clinkers was evaluated by isothermal microcalorimetry. It was found that by mixing paper sludge, cement kiln dust and rice husk ashes, it is possible to obtain belite clinker with f-CaO content below 0.5%, in clinkering temperatures between 1350 °C and 1400 °C without the use of natural raw materials. It was found that these cements have a high hydration kinetic, far above the rate of Ordinary Portland Cement, due mainly by the amorphous phase content in clinkers obtained.
Toward a dynamic model for the near-wall region based on reduced representations

As a continuation of previous efforts (partly conducted during the CTR Summer Program in 2014), the near-wall region of a weakly compressible boundary layer will be studied. Reduced-order representations based on the Dynamic Mode Decomposition (DMD) will be coupled with sparsity-promoting system identification techniques to arrive at a low-dimensional dynamic representation of the near-wall dynamics. Particular emphasis will be put on the feasibility of a localized identification of a reduced-order model that can be globally applied over the spatial extent of a transitioning boundary layer. The recently developed parallel DMD algorithm will facilitate this type of analysis. In a second step, a driven state-space model is derived from the identified structures, and a transfer function between coherent velocity input and coherent stress output in a user-specified wall-parallel plane is constructed. This transfer function acts as a map between resolved velocity fields (from Large-Eddy Simulations, LES) and resolved stress components (entering the subgrid-scale model) and is intended to alleviate the resolution requirements of wall-resolved LES.
Fully Convolutional Networks for Local Earthquake Detection

Automatic earthquake detection is widely studied to replace manual detection, however, most of the existing methods are sensitive to seismic noise. Hence, the need for Machine and Deep Learning has become more and more significant. Regardless of successful applications of the Fully Convolutional Networks (FCN) in many different fields, to the best of our knowledge, they are not yet applied in earthquake detection. In this paper, we propose an automatic earthquake detection model based on FCN classifier. We used a balanced subset of STanford EArthquake Dataset (STEAD) to train and validate our classifier. Each sample from the subset is re-sampled from 100Hz to 50Hz then normalized. We investigated different, widely used, feature normalization methods, which consist of normalizing all features in the same range, and we showed that feature normalization is not suitable for our data. On the contrary, sample normalization, which consists of normalizing each sample of our dataset individually, improved the accuracy of our classifier by ∼16% compared to using raw data. Our classifier exceeded 99% on training data, compared to ∼83% when using raw data. To test the efficiency of our classifier, we applied it to real continuous seismic data from XB Network from Morocco and compared the results to our catalog containing 77 earthquakes. Our results show that we could detect 75 out of 77 earthquakes contained in the catalog. Keywords—Earthquake detection; fully convolutional networks; data normalization; classification
REGULATION OF BUD-BURST TIMING BY TEMPERATURE AND PHOTOREGIMEs;_,_. DURING DORMANCY 1/

1/ Robert K. Campbell­ . , . r' Hlttra.fiot. tf»l Abstract,--In Douglas-fir, vegetative buds throughout most 1 or all of the "dormant" period have the potential ability for ex-· tension growth in response to temperatures above freezing. In terms of actual growth or development, this ability can be meas­ ured as a rate for each temperature within the normal range. Thus, potential ability can be conceptualized as a temperature response curve. Data from several experiments suggest that po­ tential abilit an be described by an equation of the form +gx 100/ y = K/ (l+e ); where, 100/ y is developmental rate and is temperature. Other parameters in the equation change continu­ ously during dormancy in response to complex, interacting environ­ mental cues provided by chilling temperature, duration, and time and by photoperiod. Bud-burst timing reflects the growth that accrues during winter and spring in response to temperature pat­ tern and changing potential developmental rates. The model may be appropriate, in principle, for other perennial species.
Spline R-Function and Applications in FEM

R-function is a widely used tool when considering objects obtained through the Boolean operations start from simple base primitives. However, there is square root operation in the representation. Considering that the use of splines will facilitate the calculations within the CAD system, in this paper, we propose a system of R-functions represented in spline form called Spline R-function (SR). After transforming the function ranges of two base primitives to a new coordinate system, a series of sign constraints following a specific Boolean operation are derived and the spline R-function can be formulated as a piecewise function. Representation of SR in both Bézier form and B-spline form have been given. Among which the Bézier ordinates are determined with the help of the B-net method through setting up a series of relations according to the sign constraints and properties of R-functions. The construction processes for both Boolean intersection and union operations with different smoothness are discussed in detail. Numerical experiments are conducted to show the potential of the proposed spline R-function. AMS subject classifications: 68U07, 65D18, 65D30
Effects of Virtual Laboratory Simulation Package and Demonstration Instructional Strategy on the Achievement of Secondary School Students in Biology

: This study investigated the Effects of Computer Laboratory Simulation and Practical Demonstration Instructional Strategy on the Achievement of Secondary School Students in practical Biology. The research design adopted for the study was Pretest-Posttest experimental group design. The population is all secondary school students in Minna Metropolis. Purposive sampling technique was used to select two secondary schools in Minna metropolis, Niger State Nigeria. The two Schools were randomly assigned to experimental group (computer simulation group) and control group (Demonstration teaching methods) respectively. Finally, stratified simple random sampling technique was used to select the 60 SSII students. The experimental group had 30 (15 males – 15 females) students and control 30 (15 males – 15 females) students. A Computer simulation laboratory Package (CSLP) was developed treatment instrument for this study. The instrument that was used in collecting data for the study was researcher adopted Biology Practical Achievement Test (BPAT). The instrument was pilot tested and its reliability coefficient determined as 0.74 using Kuder Richardson (KR-21). The data collected was subjected to analysis using t-test at 0.05 alpha level of significance. The results revealed that there is significant difference between the experimental groups and control group. The experimental group had a significant improvement in performance after they were exposed to treatment and was also found to be gender friendly Based on the findings it was recommended that Computer Laboratory Simulation Package should be adopted by biology teachers in teaching practical biology at secondary schools, since it has been found to improved academic performance.
Impact of the Affordable Care ActMedicaid Expansions onMarriage and Divorce Decisions

Access to health insurance through dependent coverage is a benefit of marriage that a substantial part of the population relies upon in the United States. Thus, policies that change eligibility criteria and costs of alternative sources of insurance may affect marital decisions. I use data from the American Community Survey to study the causal impact of the Medicaid expansions of 2014 on marriage and divorce decisions among low-educated, non-elderly adults over 26 years of age. I employ a difference-in-differences identification strategy that exploits variation in time and status of Medicaid expansion in states. The results indicate that among the sample considered, there is a relative reduction in the likelihood of being newly married in Medicaid expansion states compared to states that did not expand Medicaid. The results are larger for women whose likelihood of being newly married falls by 11.6 percent. I also find suggestive evidence of the ACA being associated with an increase in divorces, although the results are not causal. These results support the proposition that Medicaid serves as an alternative source of coverage in place of dependent coverage.