Miracle-dz/UniFAR-FTUs huggingface dataset:
How do Net Operating Loss Carryforwards Affect Firm Investment Decisions? By:

We investigate whether the existence of net operating loss (NOL) carryforwards affects firm investment decisions. When a firm has a large NOL carryforward sufficient to reduce taxable income to zero, any tax benefit from new investments is not received immediately, but rather adds to the NOL carryforward and is deferred until a future year. Thus, these investments may have a lower net present value, as compared to firms without NOL carryforwards. We examine the relation between NOL carryforwards and four types of investment – capital expenditures, R&D, foreign subsidiary investment, and intangibles – and find a significantly negative relation. We create a new measure of NOL carryforwards focusing on useable NOLs created during overall loss years. Our results are robust to using four different measures of NOL carryforwards as well as two measures of the marginal tax rate. In sum, when firms become non-taxable, as evidenced by the existence of NOL carryforwards and a decline in the marginal tax rate, managers reduce tax-favored investments as the expected tax benefits from these investments decline. JEL Classifications: H25, H32, M41, M48
EVALUATION OF THE PHYTOCHEMICAL COMPOSITIONS AND ANTIOXIDANT ACTIVITY OF PEPPER FRUIT (Dennettia tripetala) SEEDS AND PEELS

The phytochemical screening and antioxidant activities of pepper fruit (Dennettia tripetala) were studied. Four different solvents; methanol, ethanol, butanol and water were used for the extractions for the phytochemicals assay which revealed that the seeds and peels of the unripe and ripe pepper fruit (Dennettia tripetala) contains significant amount of these plant chemicals. The quantitative phytocehmical and antioxidant activities was assayed by investigating their 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, reducing power, hydrogen peroxide (H2O2) scavenging activity, hydroxyl radical scavenging activity, total flavonoid, alkaloid and total phenolic content. DPPH radical scavenging activity for the seeds of ripe pepper fruit was the highest (82.46+0.16 %) and the lowest value (76.95+0.17 %) was recorded for the peel of the ripe fruit. The peel and seeds of the unripe pepper fruit had 80.09+0.30 % and 80.53+0.21 % respectively. For the reducing power activity, the unripe peel 76.34+0.61 %, ripe peel 68.45+0.23 %, the ripe and unripe seeds having 69.08+2.23 % and 73.66+1.88 % respectively. The hydrogen peroxide (H2O2) scavenging activity for the ripe peel 5.60+0.62 % was the lowest while unripe peel 30.67+1.13 % was the highest. Hydroxyl radical activities of Dennetia tripetala revealed that the ripe peel had 17.23+0.58 %, the unripe peel 15.61+0.58 %, the ripe fruit seeds 4.58+2.02 % and the unripe seeds had 28.00+3.40 % while flavonoids contents had a range of 74.03+0.78 75.66+0.38%. Alkaloid however recorded 0.19± 0.01 mg/100g for the unripe seed as the highest value while the ripe peel recorded 0.16±0.02 mg/100g as the lowest. Keyword: Antioxidant, phytochemical, scavenging activity, Butylatedhydroxytoluene and Dennettia tripetala.
CMAR_A_244748 5131..5139

*These authors contributed equally to this work Purpose: ACT001 is a novel sesquiterpene lactone derivative with anticancer effects, including the reversal of tamoxifen resistance in estrogen receptor-positive breast cancer cells. However, few studies have investigated the anticancer effects of ACT001 in triple-negative breast cancer (TNBC), a highly aggressive cancer with a poor prognosis. This study aimed to investigate the effects of ACT001 on TNBC and the potential mechanism underlying these effects. Materials and Methods: The anticancer effects of ACT001 on the murine TNBC cell line 4T1 were evaluated by Cell Counting Kit-8 assay, animal experiments, TUNEL staining, flow cytometry, immunofluorescence, enzyme-linked immunosorbent assay, and Western blotting analysis. Results: ACT001 induced apoptosis in 4T1 cells by upregulating B cell lymphoma 2-associated X protein expression. Moreover, ACT001 markedly decreased levels of secretory granulocytemacrophage colony stimulating factor (GM-CSF) in 4T1 tumors, decreased the number ofmyeloidderived suppressor cells (MDSCs), and reduced angiogenesis. Furthermore, GM-CSF promoted angiogenesis and the proliferation of MDSCs in a dose-dependent manner. Finally, ACT001 suppressed phospho-NF-κB and IκB-α levels in 4T1 cells, thereby further decreasing GM-CSF levels. Conclusion: Our results suggest that ACT001 exerts its anticancer effects by inducing apoptosis in murine TNBC cell line 4T1 and regulates the tumor microenvironment by attenuating angiogenesis and accumulation of MDSCs in 4T1 tumors. The underlying mechanism may involve the suppression of NF-κB activity.
Unequal burden of COVID-19 in Hungary: a geographical and socioeconomic analysis of the second wave of the pandemic

Introduction We describe COVID-19 morbidity, mortality, case fatality and excess death in a country-wide study of municipalities in Hungary, exploring the association with socioeconomic status. Methods The spatial distribution of morbidity, mortality and case fatality was mapped using hierarchical Bayesian smoothed indirectly standardised ratios. Indirectly standardised ratios were used to evaluate the association between deprivation and the outcome measures. We looked separately at morbidity and mortality in the 10 districts with the highest and 10 districts with the lowest share of Roma population. Results Compared with the national average, the relative incidence of cases was 30%–36% lower in the most deprived quintile but the relative mortality and case fatality were 27%–32% higher. Expressed as incidence ratios relative to the national average, the most deprived municipalities had a relative incidence ratio of 0.64 (CI: 0.62 to 0.65) and 0.70 (CI: 0.69 to 0.72) for males and females, respectively. The corresponding figures for mortality were 1.32 (CI: 1.20 to 1.44) for males and 1.27 (CI: 1.16 to 1.39) for females and for case fatality 1.27 (CI: 1.16 to 1.39) and 1.32 (CI: 1.20 to 1.44) for males and females, respectively. The excess death rate (per 100 000) increased with deprivation levels (least deprived: 114.12 (CI: 108.60 to 119.84) and most deprived: 158.07 (CI: 149.30 to 167.23)). The 10 districts where Roma formed the greatest share of the population had an excess mortality rate 17.46% higher than the average for the most deprived quintile. Conclusions Those living in more deprived municipalities had a lower risk of being identified as a confirmed COVID-19 case but had a higher risk of death. An inverse association between trends in morbidity and mortality by socioeconomic conditions should be a cause for concern and points to the need for responses, including those involving vaccination, to pay particular attention to inequalities and their causes.
Validity and reliability of the dimensional assessment scale after myocardial infarction

RESUMO Objetivou-se avaliar as evidências de confiabilidade e a validade do questionário de Avaliação Multidimensional de Qualidade de Vida em pacientes após o infarto do miocárdio. Estudo metodológico. A confiabilidade foi verificada por meio da análise da consistência interna e pelo teste-reteste (α de Cronbach). A reprodutibilidade foi verificada com a avaliação intra e interexaminadores. A validade do instrumento foi calculada por meio da validade de constructo e critério através da validade convergente e concorrente. A amostra foi composta por 83 pacientes, sendo 51 pacientes internados e 32 ambulatoriais. Todos os domínios apresentam correlação significativa com escore geral. O questionário de Avaliação Multidimensional de Qualidade de Vida possui evidências de validade e confiabilidade em comparação ao questionário SF-36 com correlação de 0,89 (p<0,01). O Alfa de Cronbach obtido nos pacientes internados ambulatoriais foi de 0,85 e 0,83 respectivamente. O instrumento apresenta evidências de confiabilidade e validade para aplicação no Brasil em ambientes ambulatoriais e hospitalares.
Literature Survey: Data-driven Approach for Selection of an Ensemble Model of Profane Words Detection in Social Media

- Strong language is common to most cultures, but what makes the language blasphemous; vary from region to region of the world. In social media, people chat with each other without necessary face-to-face interaction, hence promoting a sense of being liberal without breaking the cultural norms, resulting in an increased in the use of profanity in cyber space. Although most social media platforms have developed profane filters to censor profanity but the cyber bullies have continuously improve on their profanity techniques to make the existing filters less and less effective. This has led to a major problem in social media resulting in potentially serious adverse effects on young users if undetected. It is against this background that the study was motivated to explore the literature survey of data-driven approach for selection of an ensemble model for profane words detection in social media, in order to improve the accuracy and reliability in detecting profane chats. In order to achieve this goal, the study explored books, scholarly articles and all other sources published and unpublished relevant to profane detection model in social media and their relevant technological theories. By so doing, it provided a body of knowledge, using a three phase approach of: summarizing, comparing & contrasting and criticizing & synthesizing of all sources in relation to the profanity problem being investigated. The outcome of the survey was two folds: the contribution of the body of knowledge to the development of the ensemble model and the designing of the data-driven methodology.
Preimplantation Genetic Testing for Aneuploidy Improves Live Birth Rates with In Vitro Produced Bovine Embryos: A Blind Retrospective Study

Approximately one million in vitro produced (IVP) cattle embryos are transferred worldwide each year as a way to improve the rates of genetic gain. The most advanced programmes also apply genomic selection at the embryonic stage by SNP genotyping and the calculation of genomic estimated breeding values (GEBVs). However, a high proportion of cattle embryos fail to establish a pregnancy. Here, we demonstrate that further interrogation of the SNP data collected for GEBVs can effectively remove aneuploid embryos from the pool, improving live births per embryo transfer (ET). Using three preimplantation genetic testing for aneuploidy (PGT-A) approaches, we assessed 1713 cattle blastocysts in a blind, retrospective analysis. Our findings indicate aneuploid embryos have a 5.8% chance of establishing a pregnancy and a 5.0% chance of given rise to a live birth. This compares to 59.6% and 46.7% for euploid embryos (p < 0.0001). PGT-A improved overall pregnancy and live birth rates by 7.5% and 5.8%, respectively (p < 0.0001). More detailed analyses revealed donor, chromosome, stage, grade, and sex-specific rates of error. Notably, we discovered a significantly higher incidence of aneuploidy in XY embryos and, as in humans, detected a preponderance of maternal meiosis I errors. Our data strongly support the use of PGT-A in cattle IVP programmes.
Programming word embeddings in Snap!

Word embeddings is a technique in natural language processing whereby words are ​ embedded in a high-dimensional space. They are used in sentiment analysis, entity detection, recommender systems, paraphrasing, text summarisation, question answering, translation, and historical and geographic linguistics. We describe a Snap! library that contains 20,000 word embeddings in 15 languages. Using a block that reports a list of 300 numbers for any of the known words, one can create programs that search for similar words, find words that are the average of other words, explore cultural biases, and solve word analogy problems. These programs can work in a single language or rely upon the alignment of the word embedding spaces of different languages to perform rough translations. To compute with word embeddings one needs to perform vector arithmetic. This can be accomplished by providing vector arithmetic blocks. More advanced users can instead take advantage of Snap! ’s support of higher-order functions to use list mapping blocks to perform the vector operations.
Pain catastrophizing in patients with primary dysmenorrhea: Its relationship with temperament traits and impulsivity

Hatice Harmancı1, Jule Eriç Horasanlı2 1Department of Psychology, Faculty of Social Sciences and Humanities, KTO Karatay University 2Department of Gynecology and Obstetrics, Faculty of Medicine, Necmettin Erbakan University, Konya, Turkey Pain catastrophizing in patients with primary dysmenorrhea Pain catastrophizing in patients with primary dysmenorrhea: Its relationship with temperament traits and impulsivity
Reinforcement of age estimation in forensic tools to detect Child Sexual Exploitation Material

—Several image-based approaches for estimating the age of a person are available in computer vision literature. However, most of them perform poorly on minors and young adults, especially when the eyes are occluded. This type of occlusion is common in Child Sexual Exploitation Materials (CSEM), in order to hide the identity of victims. We introduce an approach that builds Soft Stagewise Regression Network (SSR-Net) models with natural and eye-occluded facial images, to estimate the age of minors and young adults. Our proposal reduces the Mean Absolute Error from 7 . 26 to 6 . 5 , and 6 . 81 to 4 . 07 for SSR-Net pre-trained models on the IMDB and MORPH datasets, respectively.
RECOVERY OF MISSING DATA USING ENHANCED PROBABILISTIC MATRIX FACTORIZATION

: Recommendation systems are one of the most widespread forms of machine learning in modern society. Whether you are looking for your next show to watch on Netflix or listening to an automated music playlist on Spotify, recommender systems impact almost all aspects of the modern user experience. One of the most common ways to build a recommendation system is with matrix factorization, which finds ways to predict a user’s rating for a specific product based on previous ratings and other users’ preferences. In this project, we compare and contrast several PMF-based models by applying them to find missing values in music recommendation system. Motivated by the observation that incorporating user network information is not as effective as constraining the user feature vector with latent constraint similarity matrix, we developed Constrained Kernelized PMF (cKPMF) model. We show that cKPMF is the most effective model for our task at hand among the models explored in this project. In this article we formulate the missing value estimation as a recommender system problem.
Credit Card Fraud Detection Using Bagging and Boosting Algorithms

: The term Credit Card Fraud indicates that the defrauder is using your credit card credentials or has stolen your credit card for his/her financial benefit. Research tells us that due to economic expansion in recent years, credit card spending has increased. This eventually leads to increase in fraudulent credit card transactions. In the last few years, this has been a predominant issue; it causes a huge loss to the companies and the cardholder. The paper talks about machine learning techniques such as Logistic Regression, Naïve Bayes, Boosting Classifier and Bagging classifier to detect credit card frauds.
‘WOMEN’S WORK’ IN INDONESIA’S SOCIAL MEDIA-BASED ONLINE STORE BUSINESSES: Social Reproduction and the Feminization of Work1

This paper seeks to analyze ‘women’s work’ in Indonesia’s social media-based online shop businesses by looking at the forms of work that emerge in those businesses. This paper employs qualitative research methods by using transcribed in-depth interviews with 20 informants from six cities in Indonesia. By looking at flexibility as the defining characteristic of exploitation under platform capitalism, home as the central working space in the social media-based online store, and the ongoing process of feminization of work in the online business sector, this study advances two claims. First, the intersection between platform capitalism and logistics revolution in the online shop businesses has created new forms of work. Second, the social mediabased online store, which is mostly operated by women, shows that flexibility and feminization of work under platform capitalism have impacted on the lives of the women business operators and their work. A closer look at the emergence of social media-based online stores also reveals how social reproduction work shapes ‘women’s work’ in online store businesses.
INFLUENCE OF STRATEGIC POSITIONING ON ADOPTION OF FINANCIAL MANAGEMENT PRACTICES IN THE CONTEXT OF SMALL INDUSTRIES

The objective of the study was to identify the influence of strategic positioning on the adoption of financial management tools in the context of small industries in the AMUREL (Brazilian Portuguese abbreviation for the Laguna Region Municipalities Association) micro-region and, additionally, to seek an answer to the hypothesis about the possibility that the level of use of financial management practices is equal in small companies regardless of strategic positioning adopted. Methodology classified as descriptive and quantitative was used and the data collection has taken place by means of a questionnaire based on the so-called Contingency Theory in the analysis of the strategic positioning and in the financial management tools of the four stages listed by the International Federation of Accountants. As a result, it has been found that the management practices of the first and second stages are the most used (with an average of 55.91% and 69.32%, respectively) when compared with the instruments belonging to the third (40%) and fourth stages (44.46%). The main contribution of the study is to point out statistical evidence that the strategic positioning chosen by small industries does not affect the level of use of financial tools in this business context.
Masquerade Attack Analysis for Secured Face Biometric System

Biometrics systems are mostly used to establish an automated way for validating or recognising a living or nonliving person's identity based on physiological and behavioural features. Now a day’s biometric system has become trend in personal identification for security purpose in various fields like online banking, e-payment, organizations, institutions and so on. Face biometric is the second largest biometric trait used for unique identification while fingerprint is being the first. But face recognition systems are susceptible to spoof attacks made by nonreal faces mainly known as masquerade attack. The masquerade attack is performed using authorized users’ artifact biometric data that may be artifact facial masks, photo or iris photo or any latex finger. This type of attack in Liveness detection has become counter problem in the today's world. To prevent such spoofing attack, we proposed Liveness detection of face by considering the countermeasures and texture analysis of face and also a hybrid approach which combine both passive and active liveness detection is used. Our proposed approach achieves accuracy of 99.33 percentage for face anti-spoofing detection. Also we performed active face spoofing by providing several task (turn face left, turn face right, blink eye, etc) that performed by user on live camera for liveness detection.
Purification and characterization of β-N-acetylglucos-aminidase from Grifola frondosa

Using commercial API-ZYM screening kits, highly active α-glucosidase, β-glucosidase, and β-N-acetylglucosaminidase were found in Grifola frondosa, having potential for carbohydrate utilization. Of these, β-N-acetylglucosaminidase, which converts chitin to N-acetylglucosamine, was purified and characterized. The recovery was 24.5%, and the purified enzyme had a specific activity 0.67 U/mg protein. Chitinase activity was confirmed by zymogram analysis. The enzyme was also shown to be β-N-acetylglucosaminidase, as N-acetylglucosamine was the main hydrolysis product from colloidal chitin. Thus, the molecule was named NAG38, to indicate β-N-acetylglucosaminidase activity and a molecular weight of 38 kDa, as determined by sodium dodecyl sulfate polyacrylamide gel electrophoresis. Enzymatic activity was optimal at pH 7.0 and 50 °C, with Km and Vmax values of 0.112 mM and 0.570 μmol/min/mg protein against p-nitrophenyl N-acetyl-β-D-glucosaminide. The bioactivity was inhibited by Hg2+, Ag+, Mg2+, Zn2+, Ca2+, and Mn2+, with residual enzyme bioactivity only 11.1% after incubation in Hg2+, but was not substantially inhibited by Ba2+, K+, and Na+.
ANALYSIS OF ELEARNING SUCCESS FACTORS

: In this paper, the DeLone and McLean’s updated information system model was used to evaluate the success of an eLearning system and its courses. In order to adapt this model to eLearning, success metrics suitable for eLearning were defined for each of the evaluation stages. Furthermore, the success metrics for eLearning evaluation are expanded by providing several systems for quantifying the given success metrics. The results presented in this paper are based on courses that were taught both online and traditionally in three different subject areas: graphic design, information technology and management. Of particular interest were success metrics which can provide quantifiable data from the eLearning system itself, in order to evaluate academic achievement and usage of learning materials. The results from different courses were used to illustrate the implementation and evaluation of these success metrics for both online and traditional students.
The State of the Art in Model Predictive Control Application for Demand Response

Demand response programs have been used to optimize the participation of the demand side. Utilizing the demand response programs maximizes social welfare and reduces energy usage. Model Predictive Control is a suitable control strategy that manages the energy network, and it shows superiority over other predictive controllers. The goal of implementing this controller on the demand side is to minimize energy consumption, carbon footprint, and energy cost and maximize thermal comfort and social welfare. This review paper aims to highlight this control strategy's excellence in handling the demand response optimization problem. The optimization methods of the controller are compared. Summarization of techniques used in recent publications to solve the Model Predictive Control optimization problem is presented, including demand response programs, renewable energy resources, and thermal comfort. This paper sheds light on the current research challenges and future research directions for applying model-based control techniques to the demand response optimization problem.
Predictive Model for FFT Scalability Performance

— In order to introduce more efficient high performance computing (HPC) applications we need to construct a performance model for the complex heterogeneous systems. Most of the HPC applications, as in the molecular dynamics simulation implement the FFT parallel algorithm that consumes a major portion of the application execution time. This work constructs a model that can be used to decide the execution plan scalability and highlight major factors that impact directly the algorithm performance. The parallel FFT algorithm is used as a case study for our modelling procedure. This paper aims to explore the most impacting parameters of the parallel FFT algorithms execution where other platform and hardware-dependent factors are not included.