Miracle-dz/UniFAR-FTUs huggingface dataset:
Histopathology and Tumor Necrosis Factor-α Expression in The Kidney of an Asphyxial Cardiac Arrest Rat Model

Multiple organ injuries in patients with post cardiac arrest syndrome (PCAS) after cardiac arrest (CA) is associated with mortality. Among multiple organ injuries after return of spontaneous circulation (ROSC), renal dysfunction can lead to acute kidney injury, which is known to be associated with high mortality. This renal injury is associated with a systemic infl ammatory response syndrome mediated by ischemia reperfusion by ROSC following CA. However, the mechanism remains unclear. Therefore, the objective of this study was to determine, the relationship between the expression of tumor necrosis factor-α (TNF-α), a pro-infl ammatory cytokine, and renal injury in PCAS. In the present study, asphyxial CA was induced in Sprague-Dawley rats with normothermia and the survival rate was measured at two days after ROSC. The rats in each group (n=6) were sacrificed at 6 h, 12 h, 1 day, and 2 days after ROSC. Renal injury was analyzed with by Masson’s trichrome stain, TNF-α immunohistochemistry (IHC) and western blot. The mortality was 72% at 12 h after ROSC and the survival rate of rats was decreased to 24% 2 days after ROSC. Histopathological score in the renal tissue after CA showed a significant increase at 6 h than sham group. The expression level of TNF-α in the renal cortex tissue was also increased at 6 h after CA based on both IHC and western blot results. After CA, the renal histopathological injury was significantly increased at 6 h after ROSC with a proportional increase of TNF-α expression in the kidney tissue leading to rapid injury to the kidney.
Autonomy and Coordinating Mechanisms of State-Society Boundary Organizations in Mainland China

Article history Received: 21 December 2021 Accepted: 21 January 2022 Published Online: 24 January 2022 State-society boundary organizations face the challenge to maintain autonomy as well as flexibilities to respond to various goals and needs of state and non-state actors. Chinese state used to exert much control over intermediary NGOs (boundary organizations) and some have become bureaucratized. Recent reforms have sought to transform them to be more autonomous from the government and more responsive to NGOs. This paper investigates the managerial autonomy and coordinating mechanisms of 29 intermediary NGOs in Shanghai, Beijing and Guangdong. Regardless whether they are initiated by the state or non-state actors, as boundary organizations, they can effectively play a bridging role when they simultaneously deploy multiple mechanisms to sustain autonomy and at the same time integrate differences of interests between state and non-state actors.
Layer-Wise Neural Network Compression via Layer Fusion

This paper proposes layer fusion - a model compression technique that discovers which weights to combine and then fuses weights of similar fully-connected, convolutional and attention layers. Layer fusion can signiﬁcantly reduce the number of layers of the original network with little additional computation overhead, while maintaining competitive performance. From experiments on CIFAR-10, we ﬁnd that various deep convolution neural networks can remain within 2% accuracy points of the original networks up to a compression ratio of 3.33 when iteratively retrained with layer fusion. For experiments on the WikiText-2 language modelling dataset, we compress Transformer models to 20% of their original size while being within 5 perplexity points of the original network. We also ﬁnd that other well-established compression techniques can achieve competitive performance when compared to their original networks given a sufﬁcient number of retraining steps. Generally, we observe a clear inﬂection point in performance as the amount of compression increases, suggesting a bound on the amount of compression that can be achieved before an exponential degradation in performance.
Research_9861463 1..10

Contact electrification (CE) involves a complex interplay of physical interactions in realistic material systems. For this reason, scientific consensus on the qualitative and quantitative importance of different physical mechanisms on CE remains a formidable task. The CE mechanism at a water/polymer interface is a crucial challenge owing to the poor understanding of charge transfer at the atomic level. First-principle density functional theory (DFT), used in the present work, proposes a new paradigm to address CE. Our results indicate that CE follows the same trend as the gap between the highest occupied and lowest unoccupied molecular orbitals (HOMO and LUMO) of polymers. Electron transfer occurs at the outmost atomic layer of the water/polymer interface and is closely linked to the functional groups and atom locations. When the polymer chains are parallel to the water layer, most electrons are transferred; conversely, if they are perpendicular to each other, the transfer of charges can be ignored. We demonstrate that a decrease in the interface distance between water and the polymer chains leads to CE in quantitative agreement with the electron cloud overlap model. We finally use DFT calculations to predict the properties of CE materials and their potential for triboelectric nanogenerator energy harvesting devices.
Activity of ethanolic extracts of spices grown in Tanzania against important fungal pathogens and early blight of tomato

Lengai, G. M. W. , Mbega, E. R. & Muthomi, J. W. (2021). Activity of ethanolic extracts of spices grown in Tanzania against important fungal pathogens and early blight of tomato. Bulg. J. Agric. Sci., 27 (6) , 1108–1117 The nutritional and economic value of tomato is universally recognized yet its production in many regions is still low due to, among other reasons, fungal diseases. Farmers have desperately relied on synthetic chemical pesticides to manage the diseases but the chemicals, in spite of their efficacy, are associated with residual detrimental effects on human health and environment. The objective of this study was to evaluate the antifungal activity of selected spices against important fungal pathogens of tomato. Bioactive compounds from seven spices namely clove, black pepper, turmeric, ginger, lemongrass, cinnamon and cardamom powders were extracted in ethanol and tested for antifungal activity against Alternaria solani, Fusarium oxysporum f. sp lycopersici and Pythium sp. in poisoned food bioassay. The most active spice extracts were further tested for efficacy against early blight of tomato under field conditions. All extracts were significantly active against the tested fungal pathogens by about 85%. Clove extract was the most active against all the pathogens inhibiting their growth 100%. Ginger, black pepper and turmeric extracts inhibited growth of all the pathogens by between 74-80%. Lemongrass extract was the least active with an antifungal activity of about 49%. Under field conditions, clove remained active in reducing early blight disease load by about 36% compared to the negative control. The antifungal activity demonstrated by the spice extracts is an indication that they could be relied upon for disease control and this study recommends their consideration, especially clove, for formulation into a botanical fungicide for management of early blight of tomato.
Norm Form Equations and Linear Divisibility Sequences 1 3 . Index Form Equations over Biquadratic Fields

In [2], I show that certain families of quartic norm form equations lead to recurrence sequences that are also linear divisibility sequences. In an ongoing project, I am studying index form equations to find explicit information about monogenic quartic fields, which I expect can be used to strengthen the results in [2] and provide a family of sequences that satisfy a conjecture proposed by Silverman in [20]. In a forthcoming joint paper with Fuchs and Ye, we give bounds on lifts of Markoff triples modulo p. In the following sections, I briefly introduce each of these projects, and provide statements of main results and proposed future work.
Reducing Transaction Costs using Intraday Forecasts of Limit Order Book Slopes

Market participants who need to trade a significant number of securities within a given period can face high transaction costs. In this paper, we document how improvements in intraday liquidity forecasts can help to reduce total transaction costs. We compare various approaches, including autoregressive and machine learning models, to forecast intraday transaction costs computed on comprehensive ultra-high-frequency limit order book data for a sample of NYSE stocks from 2002 to 2012. Our results indicate that improved liquidity forecasts can significantly decrease total transaction costs. In particular, simple models capturing seasonality in market liquidity tend to outperform alternative models.
Automatic Infant Face Veriﬁcation via Convolutional Neural Networks

In this paper, we investigate how convolutional neural networks (CNN) can learn to solve the veriﬁcation task for faces of young children. One of the main issues of automatic face veriﬁcation approaches is how to deal with facial changes resulting from aging. Since the facial shape and features change drastically during early childhood, the recognition of children can be challenging even for human observers. Therefore, we design CNNs that take two infant photographs as input and verify whether they belong to the same child. To speciﬁcally train our CNNs to recognize young children, we collect a new infant face dataset including 4,528 face images of 42 subjects in the age range of 0 to 6 years. Our results show an accuracy of up to 85 percent for face veriﬁcation using our dataset with no overlapping subjects between the training and test data, and 72 percent in the FG-NET dataset for the age range from 0 to 4 years.
GEAR: A Margin-based Federated Adversarial Training Approach

Previous studies have shown that federated learning (FL) is vulnerable to well-crafted adversarial examples. Some recent efforts tried to combine adversarial training with FL, i.e., federated adversarial training (FAT), in order to achieve adversarial robustness in FL. However, most of the existing FAT works suffer from either low natural accuracy or low robust accuracy. Moreover, none of these works provide a more in-depth understanding of the challenges behind adversarial robustness in FL. To address these issues, we pro-pose a novel marGin-based fEderated Adversarial tRaining Approach called GEAR. It encourages the minority classes to have larger margins by introducing a margin-based cross-entropy loss, and regularizes the decision boundary to be smooth by introducing a regularization loss, thus providing a better decision boundary for the global model. To the best of our knowledge, this work is the first to investigate the impact of decision boundary on FAT and delivers the best natural accuracy and robust accuracy in FL by far. Extensive experiments on multiple datasets across various settings all validate the effectiveness of our proposed method. For example, on SVHN dataset, GEAR can improve the natural accuracy and robust accuracy (against FGSM attack) of the best baseline method (FedTRADES) by 20.17% and 10.73%, respectively.
CSRP 572 – Low Overhead Self-Checking Combinational and Sequential Circuits Designed by Evolution

Evolutionary techniques are applied to the design of self-checking digital circuits in simulation. For the combinational and sequential benchmarks attempted, evolved designs are totally self-checking with respect to single stuck-at faults in mission logic, have no latency and use signiﬁcantly less resources than hand-designed equivalents. The approach can be extended to evolve fail-safe circuits, analog self-test, and self-checking checkers under multiple faults
The implementation of plyometrics circuit model to increase jump power

The purpose of this study was to determine the difference in the effect of plyometrics circuit model based on the analysis of vertical jump movement on the increasing of jump power. This study used an experimental method consisting of two variables, namely the manipulative independent variable (exercise model) and the dependent variable (jump power). The research design was one group pre-test and post-test design. The sample used in this study was 10 students of the third semester of sports majoring in Health, Physical Education, and Recreation (HPER). The sample was taken by using purposive random sampling. Jump power data was measured by vertical jump test. The data analysis technique used Paired Samples Test. The prerequisite test used the sample normality test (Kolmogorov-Smirnov Test with α = 0.05) and the homogeneity of variance test (Levene Test with α = 0.05). Based on the results of the study, it showed that there was a significant difference between the pre-test and post-test of plyometrics circuit training model to increase jump power, Tscore = 12.31 > Ttable = 1.83 (p<0.05).
Toward Detecting Polycyclic Aromatic Hydrocarbons on Planetary Objects with ORIGIN

Polycyclic aromatic hydrocarbons (PAHs) are found on various planetary surfaces in the solar system. They are proposed to play a role in the emergence of life, as molecules that are important for biological processes could be derived from them. In this work, four PAHs (pyrene, perylene, anthracene, and coronene) were measured using the ORganics Information Gathering INstrument system (ORIGIN), a lightweight laser desorption ionization-mass spectrometer designed for space exploration missions. In this contribution, we demonstrate the current measurement capabilities of ORIGIN in detecting PAHs at different concentrations and applied laser pulse energies. Furthermore, we show that chemical processing of the PAHs during measurement is limited and that the parent mass can be detected in the majority of cases. The instrument achieves a 3σ detection limit in the order of femtomol mm−2 for all four PAHs, with the possibility of further increasing this sensitivity. This work illustrates the potential of ORIGIN as an instrument for the detection of molecules important for the emergence or presence of life, especially when viewed in combination with previous results by the instrument, such as the identification of amino acids. ORIGIN could be used on a lander or rover platform for future in situ missions to targets in the solar system, such as the icy moons of Jupiter or Saturn.
Blade-Resolved CFD Simulations of a Periodic Array of NREL 5 MW Rotors with and without Towers

A fully resolved (FR) NREL 5 MW turbine model is employed in two unsteady Reynoldsaveraged Navier–Stokes (URANS) simulations (one with and one without the turbine tower) of a periodic atmospheric boundary layer (ABL) to study the performance of an infinitely large wind farm. The results show that the power reduction due to the tower drag is about 5% under the assumption that the driving force of the ABL is unchanged. Two additional simulations using an actuator disc (AD) model are also conducted. The AD and FR results show nearly identical tower-induced reductions of the wind speed above the wind farm, supporting the argument that the AD model is sufficient to predict the wind farm blockage effect. We also investigate the feasibility of performing delayed-detached-eddy simulations (DDES) using the same FR turbine model and periodic domain setup. The results show complex turbulent flow characteristics within the farm, such as the interaction of large-scale hairpin-like vortices with smaller-scale blade-tip vortices. The computational cost of the DDES required for a given number of rotor revolutions is found to be similar to the corresponding URANS simulation, but the sampling period required to obtain meaningful time-averaged results seems much longer due to the existence of long-timescale fluctuations.
The Role of Personal Worries and Trust in Authorities in Explaining Risk Perception among Students from the University

This article aims to analyze the role of personal worries and trust in authorities in risk perception among young people in Hong Kong by quantitative data. According to the frequency analysis, all variables in the present study have shown a standard normal distribution curve. Factor analysis was applied to test the internal consistency, detect the reliability, and establish the structural validation of the measures. Based on correlation analysis, linear regression analysis and logistic regression analysis, five hypotheses are correct: (1) the more personal worries students have, the higher level of risk perception they perceive; (2)the amount of student’ personal worries negatively associate with their trust in authorities; (3)student who distrust in authorities tends to have higher level of risk perception; (4)student’ distrust in authorities will mediate the effects of their personal worries on their risk; (5) there is a positive and reciprocal effect between students' fear and risk perception. And three hypotheses are wrong: (1) the amount of student's personal words positively correlated with their distrust in authorities; (2) student who trust in authorities tens to have lower level of risk perception perceived governmental controllability, the lower amount of risk will be perceived by students; (3)the higher level of students’ perceived governmental controllability, the lower amount of risk will be perceived by students. The present study may serve as a pilot study, and the findings may potentially provide some insights for policymakers and government staffs in order to better understand the mechanism of risk perception and create an atmosphere of safety.
EFICIÊNCIA DAS EMPRESAS E AGRESSIVIDADE TRIBUTÁRIA: EVIDÊNCIAS DO BRASIL COMPANY EFFICIENCY AND TAX AGGRESSIVENESS: EVIDENCE FROM BRAZIL EFICIENCIA DE LAS EMPRESAS Y AGRESIVIDAD TRIBUTARIA: EVIDENCIAS DE BRASIL

This paper studies whether there is a relation between the operational efficiency measured through the Data Envelopment Analysis (DEA) models and the tax aggressiveness of the Brazilian public companies listed on B3 between the period of 2010 to 2015. The main hypothesis is that companies that are more operational efficient are in average less tax aggressive. Or, in other words, we predict that the less operational efficient companies have usually to engage in tax aggressiveness strategies more often. An efficiency score was calculated considering the outputs and inputs of the companies, classifying them according to the Data Envelopment Analysis (DEA) models to determine the relative company’s operational efficiency. The tax aggressiveness was measured by the difference between the Effective Tax Rates (ETR) and the average of ETR of companies from specifics economic sectors. Five relevant economic sectors were evaluated. A Data Panel model was estimated using the fixed effects. Considering the regression of all sectors, the results confirmed the hypothesis that companies that are more operational efficient in average tend to be less tax aggressive. However, when the samples were separated by sectors, only in the Energy and Textile Sectors this relation is significant.
A MOBILE COLLABORATIVE VISUAL SYSTEM TO SUPPORT KNOWLEDGE CREATION

Knowledge Management (KM) is a critical activity inside organizations. It has been said to be a differentiating factor and an important source of competitiveness. An important part of the knowledge asset an organization has is tacit knowledge, which is knowledge that is not formalized yet and is difficult to share. KM supporting systems help people inside an organization to convert this tacit knowledge into explicit knowledge and to share it. This paper presents the design, implementation, and preliminary tests of a KM system called MCKC, for Mobile Collaborative Knowledge Creation, supporting face-to-face knowledge creation and sharing in mobile scenarios, allowing people to create, make explicit and share their knowledge with their co-workers, using visual metaphors, gestures and sketches to implement the human-computer interface.
Evaluation of breast lesion by ultrasonography during pregnancy

Introduction: The use of colour Doppler ultrasonography (CDUS) for characterizing breast lesions has increased in recent years. The presence and distribution of blood vessels associated with malignant lesions is visualized by CDUS. Doppler criteria such as resistive index (RI), pulsatility index (PI), and flow velocity are used to distinguish benign from malignant lesions. Materials and Methods: This is a prospective and observational study conducted at tertiary care teaching hospital over a period of 6 months. All female Patients irrespective of age who came for ultrasound breast examination with suspected breast lesions, complain of pain, palpable lump, breast complaints like nipple discharge, retraction, skin thickening were included in the study. Sixty pregnant or /and lactating females who came for ultrasound examination were done such as proper application of compression, transducer positioning, and image labelling. Results: In our study, most of the subjects were 21-40 years i.e., 27 out of 60 (45%) followed by 41-60 years, i.e., 21 out of 60 (35%). There were total of 39 benign cases, Fibroadenoma (53) being the commonest, followed by least being Fibroadenoma with atypia, Lipoma and others. In this study, the age range of patients presenting with breast lesions was 18–60 years with mean age 47.4 years. 23 patients were breast lesions occurred in the age group of 31-40 years, 21 were younger age between 18-30 years and 14 were between 41-60 years. Conclusions: Evaluation of the pregnant patients who present with a breast problem is challenging. Although ultrasound may characterise the finding in many cases, mammography and even MRI may have a role in the management of these patients.
Trace Elements and Oxidative Stress in Hypertensive Disorders of Pregnancy

Background: Pre-eclampsia is defined as the onset of hypertension after mid-pregnancy; a systemic disease of the later stages of pregnancy that affects about 5 7% of all pregnancies and is the most common. Typically, blood pressure elevations and pre-eclampsia occur in the late second or third trimesters and gestational outcome is hardly affected. Material and Methods: This is perspective and observational study conducted in the Department of Biochemistry in association of Department of General Medicine over a period of six months. In this study investigation was done to determine the contribution of different biochemical parameters of females suffering from preeclampsia and Eclampsia. The study was carried out on Case group 60 pre-eclampsia and eclampsia patients compare to Control group 60 normal pregnant females. Selection criteria; Control: Normal pregnant females randomly selected from the hospital who is not suffering from any other medical disorder. Cases: All the patients of preeclampsia and Eclampsia will be admitted in the hospital. Results:The systolic blood pressure in case group was 171.3 ± 5.1 mmHg and control group 129.4 ± 5.2 mmHg. On the other hand, diastolic blood pressure in case group was 98.54 ± 4.3 mmHg and control group 79.59 ± 4.7 mmHg. Oxidative marker between Case and control group was statistically significantly difference. MDA in case group was 3.01 ± 0.41nmol/mL and Control 1.61 ± 0.32 nmol/mL. Antioxidant marker between Case and control group was statistically significantly difference. In case group Glutathione peroxidase 8.93 ± 2.64 μmol/ml and control group 15.75 ± 2.12 μmol/ml. Conclusion: In our study increase MDA in PE and eclampsia, when compared to pregnant women. In addition, we also found decrease of antioxidant such as Glutathione in PE and eclampsia, when compared to pregnant women. In our study lower maternal plasma iron, zinc and copper were significantly decreased throughout pregnancy in who subsequently developed PE and eclampsia.