Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Critical Thinking Skill of Elementary School Students Through Brain Based Learning

The purpose of this study was to improve the critical thinking skill of elementary school students using Brain Based Learning in PAI subject. This study implemented Brain Based Learning starting from planning, implementation and evaluation. The material developed was integrated with social cases of daily life. This study was conducted at the Rabbi Radiyya Islamic Elementary School and Public School No. 02 of Rejang Lebong. The research design used was one group pretest-posttest design, with data analysis using the N-gain test. The data collection was conducted through tests of critical thinking and observation of student activities. The results of the posttest and pretest showed an increase in students' critical thinking skill. The first post-test obtained an increase of 21% and the second 24%. The result of the N-Gain analysis showed the critical thinking ability in PAI learning of student in the rounding material and the scale increase from the first pretests of 0,42 and the second pretes of 0,52 at SD IT Rabby Radiyya (RR). Then in SD 02 RL the first post-test obtained an increase 0f 21% and the second 32%. The result of the N-Gain analysis showed the critical thinking ability in PAI learning of student in the rounding material and the scale increase from the first pretests of 0,39 and the second pretes of 0,62 at SD IT Rabby Radiyya (RR), of the two result indicate N-gain in the medium category. Therefore, PAI learning through Brain Based Learning was effective.
PD-L1 Expression in Esophageal Squamous Cell Carcinoma: A Comparative Analysis of 3 Different Antibodies

Lei Guo Chinese Academy of Medical Sciences Cancer Institute and Hospital Ying Ji Chinese Academy of Medical Sciences Cancer Institute and Hospital Wei Guo (  guowei@cicams.ac.cn ) Chinese Academy of Medical Sciences Cancer Institute and Hospital Huayu He Chinese Academy of Medical Sciences Cancer Institute and Hospital Peng Song Chinese Academy of Medical Sciences Cancer Institute and Hospital Xuemin Xue Chinese Academy of Medical Sciences Cancer Institute and Hospital Bin Qiu Chinese Academy of Medical Sciences Cancer Institute and Hospital Jianming Ying Chinese Academy of Medical Sciences Cancer Institute and Hospital Shugeng Gao Chinese Academy of Medical Sciences Cancer Institute and Hospital
CATERING TO CATERERS: EXPECTATIONS AND SATISFACTION OF RESTAURANT PARTNERS FROM FOOD ONLINE ORDER AND DELIVERY (FOOD) OPERATOR

Purpose Technology-enabled U commerce revolution is creating a tectonic shift in restaurant service. In this transitionary phase, appreciating the key “take-away” expectations of restaurant partners will strengthen the model. Design/Methodology/Approach This descriptive study is administered through convenience sampling of 123 Restaurant Partners of FOOD Apps. Key expectations from these food delivery services companies were identified and underlying dimensions exposed. Identified attributes are examined through Revised IPA.
Field distribution in cable terminations from a quasi-static approximation of the Maxwell equations

A new model for the evaluation of the electric field in a cable termination realized through a nonlinear stress control tube (SCT), is presented in this paper. It is based on the electro-quasistatic approximation of the Maxwell equations: the Laplace equation describes the field in the nonconducting regions whereas a diffusion-like equation gives the field dynamics in the stress control tube. A numerical model is devised by solving the Laplace equation by finite difference and diffusion equations by the Galerkin method. It is shown that even the well-known RC transmission line model can be derived from this general approach. The underlying approximations leading to the circuital model are discussed in detail. The proposed model, in contrast with the circuital one, allows us to take into account properly the nonlinear SCT characteristics and the actual boundary conditions: in this way both spatial and temporal effects of the nonlinearity are-considered. The numerical results obtained by considering the general field approach and by using the transmission line model are compared.
Mineral elements in muscat sage plant (Salvia sclarea L.) and essential oil

The authors investigated the element content of different parts of muscat sage plant (Salvia sclarea L.) by ICP-OES for 18 elements (Al, B, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, P, Pb, S, V, Zn) and the composition of muscat sage oil during distillation by GC-MS. The es- sential oil was obtained by steam distillation. High Li and Cr concentration was found in plant samples. The essential oil was characterized by four main components: linalool, carvon, linalyl acetate and geranyl acetate and the composition of oil was unchanged during distillation.
Psychopathology Experienced In Pregnancy Loss: Does Post Abortion Syndrome Exist?

Objective: Pregnancy loss is associated with numerous psychological sequelae. The aim of this study is to examine patients with recent pregnancy loss for possible psychiatric diagnoses and the associated psychopathology. Features of post abortion syndrome were also examined for. Methods: Forty seven patients referred to a perinatal psychiatric service following recent termination of pregnancy or miscarriage consented for this prospective case notes review. Data on demographic characteristics, clinical history and management was collected, as well as detailed case histories of women diagnosed with post-abortion syndrome. Results: About two-thirds were between ages 31 to 40 years. Majority (87.2%) was married and childless. Seventy percent did not have previous psychiatric history. Ten patients were suspected to have post abortion syndrome, presenting with guilt, self-blame and having to hide terminations from spouses. Discussion: These findings describe the characteristics of patients who are at risk of developing psychiatric conditions after pregnancy loss. Surveillance for such factors may enable earlier detection and diagnosis. ASEAN Journal of Psychiatry, Vol. 18 (2): July – December 2017: XX XX.
ENVIRONMENTAL BEHAVIOR OF PAHS IN DIANCHI LAKE DISTRIBUTIONS, SOURCES AND RISK ASSESSMENT OF POLYCYCLIC AROMATIC HYDROCARBONS IN SURFACE SEDIMENTS FROM DIANCHI LAKE, CHINA

Polycyclic aromatic hydrocarbons (PAHs) in the priority controlling list of US EPA were systematically evaluated in surface sediments in Dianchi Lake and its estuaries. Total PAH concentrations (ΣPAHs) varied from 210 to 11,070 ng/g dry weight (d.w.) in Dianchi Lake, and from 230 to 12,271 ng/g d.w. in the estuaries. ΣPAHs in sediments from Caohai section were higher than those from Waihai section. The occurrences of PAHs in the Lake were closely related to the distributions of rivers, indicating that the river runoff was an important pathway of PAHs into the Lake. Compared with the US Sediment Quality Guidelines (SQGs), ΣPAHs in most area were below the effect range low (ERL), which implied that the adverse biological effects would occur rarely. The toxic equivalent concentrations of potentially carcinogenic PAHs (TEQ carc ) varied from 19 to 967 ng TEQ/g d.w. , and the higher values were found in northern Caohai area. The proportions of the toxic equivalent quantity (TEQ carc ) to the total TEQs in sediments were all above 96%, suggesting that the carcinogenicity of PAHs could be occurred. Significantly positive correlations between total organic carbon (TOC) and less molecular weight PAHs (2, 3-ring) (LPAHs) were observed in the Lake. Diagnostic ratios showed that the primary source of PAHs in Dianchi Lake and most estuaries is biomass combustion, but is petroleum combustion or petrogenic origin in several other estuaries.
The Structural Interplay between Critical Cultural Awareness, Institutional Identity, Self-Efficacy, Reflective Teaching and Job Performance of EFL Teachers

The present study explored the relational patterns of critical cultural awareness, institutional identity, self-efficacy, reflective teaching, and job performance of Iranian EFL teachers. To this end, 300 Iranian EFL teachers from different private language institutes were selected based on convenience sampling and took part in the study by completing the critical cultural awareness questionnaire, the teachers’ sense of self-efficacy scale, the institutional identity questionnaire, and the reflective teaching questionnaire. Moreover, 1500 EFL students (i.e., five students per teacher) were randomly selected from teachers’ classrooms to take part in the present study. A Structural Equation Modeling (SEM) analysis was adopted, the results of which revealed that all the predictor variables except critical cultural awareness predicted EFL teachers’ job performance. However, self-efficacy was found to be the strongest predictor of Iranian EFL teachers’ job performance. The implications, grounded in the findings of the study, are presented and discussed in more detail in the paper. © 2020 IJSCL. All rights reserved. 1 Professor, Email: soodmand@basu.ac. ir (Corresponding Author) Tel: +98-813-8292530 2 MA, Email: moradi.mahsa419@gmail.com a Bu-Ali Sina University, Iran ARTICLE HISTORY: Received September 2020 Received in Revised form December 2020 Accepted December 2020 Available online December 2020
Case Report ChiariMalformationandAttentionDeficitHyperactivityDisorder

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental condition characterized by inattention, hyperactivity, and impulsivity. Chiari malformations (CM), first described approximately a hundred years ago, refer to a spectrum of hindbrain malformations characterized by cerebellar herniation through the foramenmagnum.We present the case of a 28-year-old woman with ADHD and concurrent Chiari malformation type I (CM-I) that was diagnosed by CT scan. -ere is growing evidence supporting the role of the cerebellum and its associated structures in the pathophysiology of ADHD. -us, a cerebellar malformation such as CM may impact neurological circuitry in a manner favoring the development of a neuropsychiatric disorder such as ADHD. Our case highlights the need for further studies pertaining to the role of the cerebellum in the pathophysiology of ADHD and the importance of considering the presence of CM when evaluating a patient with ADHD.
Running Head: INTERNALIZING SYMPTOMS AND SOCIAL SUPPORT NETWORK

Internalizing symptoms are common and debilitating among adolescents. Network analysis, which models associations among psychopathology, risk factors, and protective factors, may help clarify relationships between social support and internalizing symptoms, including within understudied cultural groups. We performed network analyses of 1) depressive and anxiety symptoms, 2) social support, and 3) all three measures among 658 Kenyan adolescents. In the internalizing symptoms network, worry, nervousness, and feeling down exhibited the highest expected influence. In the social support network, friends showed the greatest expected influence. In the full network, social support from family, friends, and significant others were all negatively associated with internalizing symptoms, and feeling down was a particularly important bridge node between internalizing symptoms and social support. Our findings suggest that feeling down is closely linked to social support in this sample of Kenyan adolescents. The study illustrates the potential of network analysis to aid understanding of psychopathology crossculturally.
WINNIE : Fuzzing Windows Applications with Harness Synthesis and Fast Cloning

—Fuzzing is an emerging technique to automatically validate programs and uncover bugs. It has been widely used to test many programs and has found thousands of security vulnerabilities. However, existing fuzzing efforts are mainly centered around Unix-like systems, as Windows imposes unique challenges for fuzzing: a closed-source ecosystem, the heavy use of graphical interfaces and the lack of fast process cloning machinery. In this paper, we propose two solutions to address the challenges Windows fuzzing faces. Our system, W INNIE , first tries to synthesize a harness for the application, a simple program that directly invokes target functions, based on sample executions. It then tests the harness, instead of the original complicated program, using an efficient implementation of fork on Windows. Using these techniques, W INNIE can bypass irrelevant GUI code to test logic deep within the application. We used W INNIE to fuzz 59 closed-source Windows binaries, and it successfully generated valid fuzzing harnesses for all of them. In our evaluation, W INNIE can support 2.2 × more programs than existing Windows fuzzers could, and identified 3.9 × more program states and achieved 26.6 × faster execution. In total, W INNIE found 61 unique bugs in 32 Windows binaries.
Small changes in choice architecture in self-service cafeterias

The aim of nudging is to casually influence people to choose more beneficial behaviors of their own free will. In the context of mass catering, “nudging” by improving the availability, visibility, and accessibility of healthy meals could help shift people towards healthier food choices. A study was conducted in a university cafeteria and in a school cafeteria to investigate whether simple nudges really do encourage healthier food and drink choices among diners. Using a pre-test/ post-test design, this study investigated, among other things, whether nudging increased the proportion of vegan or vegetarian mains, of fruit as a dessert, of wholegrain snacks, and of water as a drink in the short-, medium-, and long-term. Simple nudges in the university cafeteria led to marked changes in behavior in the desired direction among both students and staff in all three post-test phases. The school cafeteria results were less consistent. Overall, the study showed that nudging is a promising approach and a useful addition to traditional interventions, and it should therefore be pursued further.
The Effects of Dual Acceptor (Na, N) Doping on Zn and O Sites in ZnO

ZnO is an attracted semiconducting material because of the intriguing structural, electronic and optical properties as well as the properties can easily be tuned for applications. However, p-type doping is an essential research interest to overcome the hindering of the applications of n-type ZnO for next-generation advanced electronic and optoelectronic devices. In this article, we focus on the p-type acceptor mono (Na, N) and dual (Na-N) doping effects on the structural, electronic and optical properties of ZnO using first-principles calculations based on the density functional theory (DFT). Detailed DFT analysis reveals that the structure of ZnO distorted resulting in (Na, N) and (Na-N) doping, respectively. Band structure calculation highlights the confirmation of p-type ZnO for both types of doping introduced by acceptor impurity bands at the top of the valence band and pushing the Fermi level into the valence band. The band gap of ZnO is increased for Na and Na-N doping, while decreases for N doping. The widening of the band gap with Na and Na-N doping could be explained by Burstein Moss effect. In this study the band gap can be tuned in between 0.58 and 0.93 eV. Importantly, enhancement of the absorption and photoconductivity in the near band edge region attributed to (Na, N) and (Na-N) could be extended its applications in high-performance p-type based electronic and optoelectronic devices.
A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks

Deep neural networks' remarkable ability to correctly fit training data when optimized by gradient-based algorithms is yet to be fully understood. Recent theoretical results explain the convergence for ReLU networks that are wider than those used in practice by orders of magnitude. In this work, we take a step towards closing the gap between theory and practice by significantly improving the known theoretical bounds on both the network width and the convergence time. We show that convergence to a global minimum is guaranteed for networks with widths quadratic in the sample size and linear in their depth at a time logarithmic in both. Our analysis and convergence bounds are derived via the construction of a surrogate network with fixed activation patterns that can be transformed at any time to an equivalent ReLU network of a reasonable size. This construction can be viewed as a novel technique to accelerate training, while its tight finite-width equivalence to Neural Tangent Kernel (NTK) suggests it can be utilized to study generalization as well.
Modeling Turbulence in Galactic Centers

Turbulence is a prevalent phenomenon in the interstellar medium, and in particular, the environment at the centers of galaxies. For example, detailed observations of the Milky Way’s Central Molecular Zone (CMZ) revealed that it has a complex and turbulent structure. Turbulence on galactic scales is often modeled using star formation and feedback. However, these effects do not appear to be sufficient for explaining the high-velocity dispersion observed in the CMZ, indicating that additional gas-stirring processes are likely to be operating. Here we introduce a proof-of-concept method to drive turbulence in gas that orbits under the influence of a galactic potential. Instead of relying on a particular physical mechanism, we have adopted a Fourier forcing module and have applied it using a smoothed particle hydrodynamics code. To test our method, we performed simulations of a simplistic model of the CMZ. Our turbulence injection method is capable of balancing the self-gravity of the gas, which allows us to run the simulations for long timescales and thereby follow the evolution of the CMZ. Our results show that turbulence induces a flocculent spiral pattern in our model, analogous to that found in galactic-scale simulations. Furthermore, we find that our turbulence injection method induces inward migration of gas, a result consistent with previous numerical simulations. We submit that this injection method is a promising new tool to simulate turbulence in galactic centers.
Measuring Progress in Deep Reinforcement Learning Sample Efficiency

Sampled environment transitions are a critical input to deep reinforcement learning (DRL) algorithms. Current DRL benchmarks often allow for the cheap and easy generation of large amounts of samples such that perceived progress in DRL does not necessarily correspond to improved sample efficiency. As simulating real world processes is often prohibitively hard and collecting real world experience is costly, sample efficiency is an important indicator for economically relevant applications of DRL. We investigate progress in sample efficiency on Atari games and continuous control tasks by comparing the number of samples that a variety of algorithms need to reach a given performance level according to training curves in the corresponding publications. We find exponential progress in sample efficiency with estimated doubling times of around 10 to 18 months on Atari, 5 to 24 months on state-based continuous control and of around 4 to 9 months on pixel-based continuous control depending on the specific task and performance level.
Provable Defense Against Delusive Poisoning

Delusive poisoning is a special kind of attack to obstruct learning, where the learning performance could be signiﬁcantly deteriorated by only manipulating (even slightly) the features of correctly labeled training examples. By formalizing this malicious attack as ﬁnding the worst-case distribution shift at training time within a speciﬁc ∞ -Wasserstein ball, we show that minimizing adversarial risk on the poison data is equivalent to optimizing an upper bound of natural risk on the original data . This implies that adversarial training can be a principled defense method against delusive poisoning. To further understand the internal mechanism of the defense, we disclose that adversarial training can resist the training distribution shift by preventing the learner from overly relying on non-robust features in a natural setting. Finally, we complement our theoretical ﬁndings with a set of experiments on popular benchmark datasets, which shows that the defense withstands six different practical attacks. Both theoretical and empirical results vote for adversarial training when confronted with delusive poisoning.
RMOPP: Robust Multi-Objective Post-Processing for Effective Object Detection

Over the last few decades, many architectures have been developed that harness the power of neural networks to detect objects in near real-time. Training such systems requires substantial time across multiple GPUs and massive labeled training datasets. Although the goal of these systems is generalizability, they are often impractical in real-life applications due to flexibility, robustness, or speed issues. This paper proposes RMOPP: A robust multi-objective post-processing algorithm to boost the performance of fast pre-trained object detectors with a negligible impact on their speed. Specifically, RMOPP is a statistically driven, post-processing algorithm that allows for simultaneous optimization of precision and recall. A unique feature of RMOPP is the Pareto frontier that identifies dominant possible post-processed detectors to optimize for both precision and recall. RMOPP explores the full potential of a pre-trained object detector and is deployable for near real-time predictions. We also provide a compelling test case on YOLOv2 using the MS-COCO dataset.
X-RAY Studies on the Columnar Structures of Discotic Liquid Crystals

Since the discovery of discotic liquid crystals in 1977 [1] the field has grown rapidly with an estimated 3000 compounds belonging to this category. Generally these compounds have flat or nearly flat cores and surrounded by four to eight long chain substituents. A vast majority of these compounds exhibit the columnar mesophase. This phase is characterized by a structure in which thedisc shaped molecules are stacked one on top of the other to form columns, the different columns constituting a two-dimensional lattice. Several variants of the columnar structure have been identified-upright columns, tilted columns, hexagonal lattice, rectangular lattice, etc. The stacking of the discs within the column could be on the one extreme, liquid-like or on the other have a true long range order. Although X-ray measurements on quite a few compounds exhibiting these different structures have been reported, the temperature dependence of the various structural parameters does not seem to have received much attention. We have used an image plate detector to carry out detailed X-ray studies of several compounds exhibiting the columnar phase. Analysis of the X-ray patterns yields, apart from information on the structural symmetry in terms of the planar space groups, quantitative data on (i) the ordering of the chains and the cores of the mesogens, (ii) the core-core correlation length along the column axis and (iii) the intercolumnar spacing. In particular, it is seen that the extent of ordering of the discs within the columns has significant temperature dependence. Data collected as a function of temperature will be presented and questions regarding ordering within the columns addressed, particularly in two compounds, one of which exhibits a columnar to a plastic phase transition and the other, a columnar to a helical phase transition.