Miracle-dz/UniFAR-FTUs huggingface dataset:
Apigenin prevents TNF-α induced apoptosis of primary rat retinal ganglion cells

TNF-α has recently been identified to be a mediator of retinal ganglion cell (RGC) death, while glial cells are relatively protected against this death stimulus. Exposure of RGCs to TNF-α is thought to contribute to RGC apoptosis. Apigenin is a flavone with powerful anti-inflammatory properties that exists naturally in various plants and Chinese medicine. In our study, MTT assays showed that apigenin significantly inhibited the decrease of RGC viability induced by TNF-α in a dose-dependent manner. Pretreatment with apigenin prevented TNF-α-induced apoptosis in a dose-dependent manner as shown by flow cytometry. The production of ATP and the total oxygen uptake were also promoted after apigenin administration. TNF-α stimulation led to a significant reduction of bcl-2 and enhancement of bax, which was reversed by apigenin treatment. Apigenin treatment also alleviated the increased caspase-3 activity induced by TNF-α. Moreover, luciferase reporter assay indicated that apigenin dose-dependently decreased NF-κB activation induced by TNF-α, but had no significant effect on activation of AP-1. Collectively, these data demonstrated that apigenin alleviated TNF-α-induced apoptosis through inhibition of caspase-dependent apoptotic pathway and activation of nuclear factor-kappaB. Therefore, apigenin may be developed as an anti-apoptotic drug to treat retinopathy.
VARYING PERSPECTIVES OF GROUNDED THEORY APPROACH: A CRITICAL LITERATURE REVIEW

This research work was conducted to explore the divergent perspective of notable proponents and authors who had employed Grounded Theory in their respective research endeavors. Discriminating the varying viewpoints of grounded theory is essential in strengthening the degree of understanding on the extent grounded theory can be utilized in a given social concerns and issues under qualitative design. In immersing into the context, situation and the personal interests of the proponents gave the researcher an opportunity to explore Grounded Theory according to their level of perspective without putting the researcher’s personal bias. Having traced the progression of grounded theory through rigorous critical review on literature and comparative analysis on the unique features and application as employed by relevant authors, resulted to the idea that grounded theory revolved with time. This meant that in using grounded theory in their research it resulted to a new variant of grounded theory. This implied that grounded theory is consistent with its principle which is theory generation. That following the tenets of grounded theory approach and its methodology, it resulted to finding a relevant theory that was a by-product of grounded theory itself.
Bioinformatic Algorithm and Prediction to Control SARS-Cov-2 Spike Protein Variant on COVID-19 Pandemic Progression

Recently severe SARS-CoV-2 variant carrying the Spike protein amino acid change D614G has become the most prevalent form in the global COVID-19 pandemic. Systemic tracking algorithms of variant frequencies revealed a recurrent pattern of G614 increase at multiple geographical levels, the shift occurred even in narrow scope of local epidemics. The consistency of this pattern was highly statistically significant, suggesting that the G614 variant may have fitness advantage. Based on findings that the G614 variant grows to a higher titer as pseudo-typed visions. These findings illuminate changes important for mechanistic understanding of the virus and support continuing surveillance of Spike mutations to aid with development of immunological interventions. Furthermore, predictive stewardship would be conducted for protection and limitation of transmissibility.
Investor Sentiment and Mispricing Anomalies

This paper attempts to investigate the effect of investor sentiment on mispricing anomalies, including value premium, earnings to price, gross profitability, operating profitability, return to assets, and V/P ratio. Via bi-variate analysis and regression analysis, I find these anomalies are stronger in the periods with higher investor sentiment. The effect is robust after controlling for Fama-French three factors. The results are consistent with the idea that investors are more likely to misprice stocks when investor sentiment is high, leading stronger mispricing anomalies in such higher investor sentiment periods. The limitation of this study is that it only includes tests for six misplacing anomalies and does not cover the detection of a large number of anomalies. The value of this study is it is the first study to investigate the effect of investor sentiment on V/P anomaly and to explore these misplacing anomalies as a whole. More importantly, through this study, I actually tested the impact of investor sentiment on investor valuation accuracy.
ANALISIS SENTIMEN TERHADAP PEMINDAHAN IBU KOTA PADA MEDIA SOSIAL TWITTER MENGGUNAKAN ALGORITMA NAIVE BAYES BERBASIS PARTICLE SWARM OPTIMIZATION Karsito1,

Analisis Sentimen Twitter merupakan teknik untuk mengidentifikasi sentimen atau pendapat dalam tweet dan kemudian mengkategorikannya ke dalam tweet positif atau tweet negatif. Salah satu topik yang sering dibahas pada media sosial twitter adalah pemindahan Ibu Kota Jakarta ke Kalimantan Timur. Algoritma naive bayes merupakan metode pengklasifikasian probabilistik sederhana untuk klasifikasi teks. Masalah dalam pengkalsifikasian ialah kurang optimalnya akurasi yang dihasilkan sehingga perlu seleksi fitur tambahan untuk meningkatkan akurasi menjadi lebih optimal. Tujuan dari penelitian ini adalah untuk mengoptimasi algoritma naive bayes dengan seleksi fitur particle swarm optimization. Dari hasil pengujian yang dilakukan dengan mengubah nilai population size dan inertia weight pada parameter particle swarm optimization hasil akurasi terbaik yang diperoleh adalah 91,50% sedangkan pengujian naive bayes tunggal diperoleh hasil akurasi sebesar 78,88%. Dengan demikian dapat disimpulkan bahwa penerapan seleksi fitur bebasis particle swarm optimization dapat mengatasi masalah seleksi fitur pada algoritma naive bayes sehingga dapat meningkatkan akurasi dalam menganalisis sentimen pengguna Twitter terhadap pemindahan Ibu Kota. Dari hasil akurasi tersebut dapat diketahui bahwa 35% pengguna twitter memberikan sentimen positif sedangkan 65% memberikan sentimen negatif terhadap pemindahan Ibu Kota Jakarta ke Kalimantan.
Aroma features of honey measured by sensory evaluation, gas chromatography-mass spectrometry, and electronic nose

ABSTRACT To study the aroma features of different varieties of honey, five honey samples from different botanical origins were characterized by sensory evaluation, gas chromatography-mass spectrometry and electronic nose analysis. The sensory evaluation results gave a good reflection of the honey’s different aroma characteristics. A total of 55 volatile compounds were identified by headspace solid-phase micro-extraction followed by gas chromatography-mass spectrometry, and among these compounds, 13 were found in all of the honey samples. A number of differences were observed in the composition of volatile components from the five types of honey. Twenty-two compounds were selected as typical odor-active compounds which co-varied well with the five sensory attributes by partial least squares regression. The correlation results between the sensory profiles and electronic nose data showed that the electronic nose could give comparable results in predicting the sensory attributes of honey. In conclusion, the combination of sensory evaluation, gas chromatography-mass spectrometry analysis of volatile compounds, and electronic nose data with partial least squares regression analysis could be applicable for the overall analysis of aroma features for honey.
FOOD PRODUCT ACCEPTANCE AND PREFERENCE PREDECTION THROUGH AUTOMATED FACIAL EXPRESSION ANALYSIS

This paper presents a system for determining consumer acceptance and preferences of food products through emotion recognition. Changes in facial expressions of 80 test subjects while tasting five different food samples were captured using the Microsoft Kinect sensor. The expressions were compared to the consumers’ sensory evaluations. To determine the facial expressions in every video frame, a neural network was trained and different supervised learning techniques (such as support vector machines, multilayer perceptron and regression trees) were
Running head: THE EFFECT OF PRIOR ABUSE ON HORSE BEHAVIOUR 1 THE EFFECT OF PRIOR ABUSE ON BEHAVIOURAL RESPONSES TO EMOTIONAL EXPRESSION IN THE DOMESTIC HORSE (EQUUS CABALLUS)

Several domestic species have shown discriminatory abilities when judging the level of affect in human faces. In other words, they can distinguish between positive (happy) and negative (angry) human facial expressions. As a species that relies heavily upon humans for survival, such recognition abilities aid domestic species in their interactions with human handlers. What has yet to be explored is whether former experiences of neglect or abuse influences subsequent behaviours in response to varying degrees of human emotion, expressed through facial expressions. Previous research suggests that poor welfare conditions, such as former experiences of abuse and neglect, can affect subsequent judgments of future events. Such that abused horses may have a diminished expectation of positive events, which often leads to an enhanced awareness of threatening stimuli, thereby, eliciting avoidance behaviour. The present study aims to add to the current literature by examining differences in behavioural responses to positive (happy) and negative (angry) human facial expressions, between horses with and without former experiences of abuse and neglect. Eleven horses were assigned to one of two experimental groups; 5 horses with known, prior experiences of abuse, and the remaining 6 horses served as the control group, with no prior experiences of abuse. Horses were presented with counterbalanced photographs of positive and negative human facial expressions, and their behavioural responses were recorded. Our results indicated that horses with previous experiences of abuse were more likely to hold a pessimistic bias, involving a diminished anticipation of positive events (decreased optimism), and an increased occurrence of stress-related behaviours. Alongside the insights that these findings provide into interspecific communication, they highlight the impact of welfare conditions on domestic horses wellbeing, cognition, and related behaviours. THE EFFECT OF PRIOR ABUSE ON HORSE BEHAVIOUR 4
Effects of ingredients and cooking time on total phenolic content and antioxidant activity of different homemade tomato sauces

Tomato is one of the most consumed fruits in the world. Tomato sauce, a tomato product, is one of the mother sauces that has been developed by Escoffier (1846-1935). Nowadays, tomato sauce has been adapted by each country according to their own culinary culture. In the current study four different tomato sauce recipes were investigated in the context of their antioxidant activity and total phenolic content. Hydrophilic and lipophilic extractions of samples were evaluated separately. It was found that there is a relationship between total phenolic content and antioxidant activity in hydrophilic extraction. However, no similar correlation was found between total phenolic content and antioxidant activity in lipophilic extraction. According to the results, the highest antioxidant activity of both hydrophilic and lipophilic extractions was observed in S1 with the values 25.53±1.01 and 45.48±2.06 respectively. In lipophilic extraction, S2 had the lowest antioxidant activity with 32.77±1.07, because of the lack of the ingredients high in lipophilic antioxidant compounds. It was observed that the shortest cooking time with 10 min provide the highest retention of antioxidant activity and total phenolic content in this sauce. Also, antioxidant activity of lipophilic extraction for longer cooking time applied sauces (S4) could be kept high with ingredients such as carrot. It can be suggested that adding of ingredients which have antioxidant activity may be useful for providing bioactive properties in long cooking time procedures and it should be noted that the length of cooking time negatively affected the TPC values.
Assessing the long-term sustainability of the groundwater resources in the Bacchiglione basin (Veneto, Italy) with the Mann–Kendall test: suggestions for higher reliability

The social, economic, and ecological importance of the aquifer system within the Bacchiglione basin (Veneto, IT) is noteworthy, and there is considerable disagreement among previous studies over its sustainable use. Investigating the long-term quantitative sustainability of the groundwater system, this study presents a statistical methodology that can be applied to similar cases. Using a combination of robust and widely used techniques, we apply the seasonal Mann–Kendall test and the Sen’s slope estimator to the recorded groundwater level timeseries. The analysis is carried out on a large and heterogeneous proprietary dataset gathering hourly groundwater level timeseries at 79 control points, acquired during the period 2005–2019. The test identifies significant decreasing trends for most of the available records, unlike previous studies on the quantitative status of the same resource which covered the domain investigated here for a slightly different period: 2000–2014. The present study questions the reason for such diverging results by focusing on the method’s accuracy. After carrying out a Fourier analysis on the longest available timeseries, for studies of groundwater status assessment this work suggests applying the Mann–Kendall test to timeseries longer than 20 years (because otherwise the analysis would be affected by interannual periodicities of the water cycle). A further analysis of two 60-year-long monthly timeseries between 1960 and 2020 supports the actual sustainable use of the groundwater resource, the past deployment of the groundwater resources notwithstanding. Results thus prove more reliable, and meaningful inferences on the longterm sustainability of the groundwater system are possible. Parole chiave: test stagionale Mann-Kendall, test Sen’s Slope, sostenibilità, livello delle acque sotterranee, Bacchiglione.
A review of the current state of Pico and Nanosatellites: some applications in Latin America and other regions of the world

Small satellites have been a fundamental factor in the constant growth of space technologies from 60 years ago. Since the space war began during the Cold War, thousands of satellites have been put into low orbit to carry out radio frequency applications, analysis and sending satellite images of the earth, joint research tasks for space exploration on artificial satellites, as well as missions in other astronomical bodies. By 2019, more than 50 countries around the world have put into orbit at least 1 small satellite, which accounts for the persistent work to increase the applications of these devices and the need make known the potential of these elements for research and for technological applications. Due to this, the present article was based on the documentary search to carry out a review of the current state of small satellites, and especially of nano and pico satellites. The research defined 3 phases for the writing of this document: choice of databases and search engines according to the research area, use of selection algorithms using logical discrimination chains and, finally, extensive analysis of the chosen documents for the writing of the article. All the information was presented through statistical graphs with detailed information from years of publication, language, region, terms, and areas the greatest research of small satellites. It was found that CubeSat and CanSat are the types of nano and pico satellite with the greatest predilection for research by universities and technological institutions, given its low cost and in most cases its easy implementation.
Manipulating the reactivity of nanoscale catalysts

This thesis presents the results of three di erent projects, all with focus on heterogeneous catalysis. The rst part concerns the investigation of the structure sensitivity of the CO dissociation reaction on a Ru(0 1 54) single crystal and nanoparticulate ruthenium. The second part is an investigation of a model Cu/Ru system for ammonia oxidation and the deployment the system on a high surface area support. The last part of the thesis presents the dynamical changes of an industrial Cu/ZnO/Al2O3 catalyst during a pretreatment in hydrogen. The structure sensitivity of ruthenium for the CO dissociation reaction is investigated by TPD. The importance of the step sites for CO dissociation is made clear in two separate experiments. By blocking the step sites with sulfur, carbon deposition is completely suppressed as a consequence of CO dissociation. The reverse tendency is found inducing defects to the single crystal by sputtering. The defects improve the activity of the single crystal by a factor of 8 for the methanation reaction. CO desorption is studied on both a ruthenium single crystal and on ruthenium nanoparticles. In an collaborative project relating CO desorption, a crossover in CO desorption on a ruthenium single crystal and ruthenium nanoparticles is found. The investigation found that it is possible to shift between the CO TPD behavior of the two di erent systems. It is shown that sputtering the Ru(0 1 54) single crystal, a desorption pro le similar to that of nanoparticles can be obtained. Equally, the desorption pro le of a at ruthenium single crystal can be obtained by annealing a thin lm of nanoparticles to 900 K for 10 min. In the second project it is found that forming a pseudomorphic overlayer of copper on ruthenium enhances the activity compared to both copper and ruthenium. A volcano shaped curve of the activity is found as a function of the copper overlayer thickness. The volcano has an optimum at a copper overlayer thickness of 2 Å corresponding to a coverage of 0.78 ML. The Cu/Ru system is deployed to a real catalyst on a high surface area support. The catalyst also proved to be more active than both copper and ruthenium. The importance of Cu being an overlayer is investigated by co-evaporation and co-incipient wetness impregnation of the thin lm and real catalyst respectively. Incorporating copper in ruthenium did not have any bene cial e ect on the Cu/Ru system. The dynamical changes of an industrial Cu/ZnO/Al2O3 catalyst are investigated by three
Computational-imaging-based optical coherence tomography in time- and frequency-domain

A computational 3D imaging system is developed that enables polychromatic, depthresolved, diffraction-limited imaging of semi-transparent objects. By combining coherent diffractive imaging (CDI) and optical coherence tomography (OCT), we reconstruct tomographic images of 3D objects from a set of wavelengthand phase-resolved diffraction patterns, using numerical methods to achieve image quality beyond the hardware limits of the optical systems used. We implement both timeand frequency-domain versions of full-field OCT systems, and for both versions we demonstrate fully lensless, as well as high-numerical-aperture configurations. We provide a comparison and overview of these different practical approaches to depth-resolved computational imaging. Furthermore, we demonstrate depth-resolved imaging of multilayer samples with an isotropic resolution in the μm range over a depth range that extends well beyond the depth-of-focus given by the numerical aperture of the imaging system. © 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Fadeli Yusuf Afif; Ukhti Ciptawaty /Influence of Competitiveness, Corruption and Foreign Direct Investment on Economic Growth of ASEAN Developing Countries / 80-89

The purpose of this study is to look at the condition of the country's competitiveness and its influence on ASEAN economic growth. The data used is panel data consisting of time series data for 2009 2019 and cross section of five ASEAN countries with the highest level of competitiveness. The variables used are economic growth, competitiveness, corruption perception index, political risk, and foreign direct investment. The analysis tool used is panel data regression, the Random Effect Model (REM). The results show that competitiveness and foreign direct investment have a positive and significant effect on economic growth, while the corruption perception index has no effect on economic growth in 5 ASEAN countries.
Empirical Study on Microsoft Malware Classification

A malware is a computer program which causes harm to software. Cybercriminals use malware to gain access to sensitive information that will be exchanged via software infected by it. The important task of protecting a computer system from a malware attack is to identify whether given software is a malware. Tech giants like Microsoft are engaged in developing anti-malware products. Microsoft's anti-malware products are installed on over 160M computers worldwide and examine over 700M computers monthly. This generates huge amount of data points that can be analyzed as potential malware. Microsoft has launched a challenge on coding competition platform Kaggle.com, to predict the probability of a computer system, installed with windows operating system getting affected by a malware, given features of the windows machine. The dataset provided by Microsoft consists of 10,868 instances with 81 features, classified into nine classes. These features correspond to files of type asm (data with assembly language code) as well as binary format. In this work, we build a multi class classification model to classify which class a malware belongs to. We use K-Nearest Neighbors, Logistic Regression, Random Forest Algorithm and XgBoost in a multi class environment. As some of the features are categorical, we use hot encoding to make them suitable to the classifiers. The prediction performance is evaluated using log loss. We analyze the accuracy using only asm features, binary features and finally both. xGBoost provide a better log-loss value of 0.078 when only asm features are considered, a value of 0.048 when only binary features are used and a final log loss of 0.03 when all features are used, over other classifiers.
Setting the Stage for Major Depressive Disorder Recovery: Strategies for the Busy Primary Care Provider

Michael E. Thase, MD Professor of Psychiatry, Department of Psychiatry, Mood and Anxiety Disorders Treatment and Research Program, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania This supplement is jointly provided by Medical Education Resources and CMEology. The supplement is supported by an independent educational grant from Takeda Pharmaceuticals U.S.A. , Inc. and Lundbeck. It was edited and peer reviewed by The Journal of Family Practice.