Miracle-dz/UniFAR-FTUs huggingface dataset:
Climate change and potential distribution of potato (Solanum tuberosum) crop cultivation in Pakistan using Maxent

The impacts of climate change are projected to become more intense and frequent. One of the indirect impacts of climate change is food insecurity. Agriculture in Pakistan, measured fourth best in the world, is already experiencing visible adverse impacts of climate change. Among many other food sources, potato crop remains one of the food security crops for developing nations. Potatoes are widely cultivated in Pakistan. To assess the impact of climate change on potato crop in Pakistan, it is imperative to analyze its distribution under future climate change scenarios using Species Distribution Models (SDMs). Maximum Entropy Model is used in this study to predict the spatial distribution of Potato in 2070 using two CMIP5 models for two climate change scenarios (RCP 4.5 and RCP 8.5). 19 Bioclimatic variables are incorporated along with other contributing variables like soil type, elevation and irrigation. The results indicate slight decrease in the suitable area for potato growth in RCP 4.5 and drastic decrease in suitable area in RCP 8.5 for both models. The performance evaluation of the model is based on AUC. AUC value of 0.85 suggests the fitness of the model and thus, it is applicable to predict the suitable climate for potato production in Pakistan. Sustainable potato cultivation is needed to increase productivity in developing countries while promoting better resource management
The Effect of Financial Leverage on Stock Returns with Corporate Social Responsibility Disclosure as Moderating Variable (Empirical Study on Mining Companies Listed on Indonesia Stock Exchange in 2016-2018)

: Stock returns are the results obtained from stock investments. The main purpose of investors investing their capital is to get high returns. In order to get high returns, investors are also faced with high risk that may occur. This study aimed to determine the effect of financial leverage on stock returns with corporate social responsibility disclosure as moderating variable on mining companies listed on Indonesia Stock Exchange in 2016-2018. The sampling method used was purposive sampling and 29 companies used as samples. Moderated Regression Analysis (MRA) was used in this study as data analysis technique. Based on the results, financial leverage has a positive effect on stock return. The higher level of financial leverage used by company, the higher stock return obtained by investors. Corporate social responsibility disclosure can strengthen the effect of financial leverage on stock returns. Corporate social responsibility disclosure in the company’s annual report causes investors to be more interested in investing their capital in the company.
A Method for Assessment of Text Complexity Based on Knowledge Graphs

The study explores the problem of assessing text complexity. In this paper we focus on measuring conceptual complexity and propose using knowledge graphs to this end. On the first stage of the research, RuThes-Lite thesaurus, a linguistic knowledge base with a total size of over 100,000 text entries (words and collocations), was used to elicit concepts in the texts of schoolbooks and represent text fragments as graphs. In the second series of experiments, we assessed complexity of English texts using knowledge graphs WordNet and Wikidata. Finally, we identified graph-based semantic characteristics of texts impacting complexity. The most significant research findings include identification of statistically significant correlations of the selected features, such as node degree, number of connected nodes, average shortest path, with text complexity.
Rebuttal of Fermi’s denial of nuclear electrons: Part II: Adapting the XBPS method to the description of the Neutron’s internal structure

The assertion that no potential can exist which is capable of holding an electron within the small volume of a neutron, with the requisite 500 MeV kinetic energy expected for it on the basis of the de Broglie p=h/λ relation, is considered in detail. The present work assesses this claim on the basis of recent theoretical developments which make use of the exponentially damped Breit-Pauli-Schrödinger (XPBS) equation. It is pointed out that the known extreme penetrating power of the neutrino does not constitute proof that the particle must possess a null charge-to-mass ratio. The XBPS Hamiltonian operator is thereupon adapted so as to include potentially significant short-range interactions involving the neutrino and its anti-particle. Calculations are presented which show that a neutrino charge-to mass ratio which is within the 0.5-0.7 a.u. range lead to a minimum energy for the neutron which is in good agreement with the observed value of +0.7825 MeV relative to that of its constituent particles (proton, electron and anti-neutrino) separated to infinity.
Quantifying the Fleet Composition at Full Adoption of Shared Autonomous Electric Vehicles: An Agent-based Approach

Exploring the impact of full adoption of fit-for-demand shared and autonomous electric vehicles on the passenger vehicle fleet of a society. Shared Eutonomous Electric Vehicles (SAEVs) are expected to have a disruptive impact on the mobility sector. Reduced cost for mobility and increased accessibility will induce new mobility demand and the vehicles that provide it will be fit-for-demand vehicles. Both these aspects have been qualitatively covered in recent research, but there have not yet been attempts to quantify fleet compositions in scenarios where passenger transport is dominated by fit-for-demand, one-person autonomous vehicles. To quantify the composition of the future vehicle fleet when all passenger vehicles are autonomous, shared and fit-for-demand and where cheap and accessible mobility has significantly increased the mobility demand. An agent-based model is developed to model detailed travel dynamics of a large population. Numerical data is used to mimic actual driving motions in the Netherlands. Next, passenger vehicle trips are changed to trips with fit-for-demand vehicles, and new mobility demand is added in the form of longer tips, more frequent trips, modal shifts from public transport, redistribution of shared vehicles, and new user groups. Two scenarios are defined for the induced mobility demand from SAEVs, one scenario with limited increased mobility demand, and one scenario with more than double the current mobility demand. Three categories of fit-for-demand vehicles are stochastically mapped to all vehicle trips based on each trip's characteristics. The vehicle categories contain two one-person vehicle types and one multi-person vehicle type. The simulations show that at full adoption of SAEVs, the maximum daily number of passenger vehicles on the road increases by 60% to 180%. However, the total fleet size could shrink by up to 90% if the increase in mobility demand is limited. An 80% reduction in fleet size is possible at more than doubling the current mobility demand. Additionally, about three-quarters of the SAEVs can be small one-person vehicles. Full adoption of fit-for-demand SAEVs is expected to induce new mobility demand. However, the results of this research indicate that there would be 80% to 90% less vehicles required in such a situation, and the vast majority would be one-person vehicles. Such vehicles are less resource-intense and, because of their size and electric drivetrains, are significantly more energy-efficient than the average current-day vehicle. This research indicates the massive potential of SAEVs to lower both the cost and the environmental impact of the mobility sector. Quantification of these environmental benefits and reduced mobility costs are proposed for further research.
English language learning for engineering students: application of a visual-only video teaching strategy

Community colleges in the USA are one of the best institutions for international students, English language learners (ELLs), non-traditional students, returning students, and those without a pass in standardised examinations to complete their two-year university coursework and an associate degree. However, the limited proficiency in English language skills has made it a hard topic for international and non-native English speakers, particularly engineering students. In this study, the application was investigated of a visual-only video teaching strategy (VOVTS) as a teaching and learning tool for English language teaching at a community college in California, USA. The results demonstrate that after the semester-long freshman English class for ELL engineering students, which incorporated the VOVTS, both the instructor and the students expressed significantly positive opinions for the teaching strategy that made use of a social media learning platform. These findings contribute to the knowledge on alternative teaching strategies through social media learning platforms for language learning classrooms for engineering students.
QUALITATIVE AND ORGANOLEPTIC PROPERTIES OF suya PRODUCED FROM SELECTED MUSCLES OF NIGERIAN LOCAL DUCKS RAISED IN DIFFERENT LOCATIONS OF EKITI STATE

Production of easy, highly nutritive, cheap and affordable ready-to-eat meat products as delicacy should consistently be made available to ameliorate shortage of animal protein in the diets. The study investigated the effect of different locations on qualities and sensory properties of suya produced from breast and drum stick muscles of Nigerian indigenous breed of ducks. A 24 indigenous breed duck of 24 months old of an average live weight of ±3.5kg for the drakes (male) and ±2.5kg for females were randomly selected from household keepers within three different locations in Ekiti State. The birds were acclimatized for two weeks and quarantined. Six ducks were randomly selected from treatment group, weighed prior slaughtering, carcasses dissected into standard cuts. The breast muscles were filleted and weighed. The breast and drum stick muscles were chilled at 4°C in a polythene bags overnight. Suya ingredients were prepared and muscles processed into suya. Suya were roasted on a smokeless fire to internal temperature of 700C and cooled before weight was taken. Suya was evaluated for cook loss, cook yield; organoleptic properties, moisture content, shear force, Thiobarbituric Acid Reacting Substance (Tbars) and pH. The study revealed that meat qualities (thaw loss, cook loss, cook yield and pH values) significantly differs (p<0.05); shear force of suya of female muscles differ significantly (p<0.05) between locations and Tbars values did not differ (p>0.05) in suya samples of breast and drum stick muscles derived from male and female ducks from different locations. The overall best organoleptic properties was rated in breast suya meat of male from location A (Ekiti Central) while the drum stick suya was best rated in female duck of location B (Ekiti North).
Perpetrator Blame Attribution in Heterosexual Intimate Partner Violence: The Role of Gender and Perceived Injury

Partner violence resulting in physical injury is more often blamed on men than women for perpetrating the same offence, as men are often perceived to be more capable of inflicting injury. The current study used vignettes in a mixed-model design to examine the influence of perpetrator and observer gender, and weapon presence on observer blame. A split-plot analysis of variance produced a significant effect of perpetrator gender and an interaction effect of perpetrator gender and weapon presence. These findings suggest that perpetrator gender may be more important than weapon presence when examining observer perceptions.
USP24-GSDMB complex promotes bladder cancer proliferation via activation of the STAT3 pathway

Background: Bladder cancer is the fourth and tenth most common malignancy in men and women worldwide, respectively. One of the main reasons for the unsatisfactory therapeutic control of bladder cancer is that the molecular biological mechanism of bladder cancer is complex. Gasdermin B (GSDMB) is one member of the gasdermin family and participates in the regulation of cell pyroptosis. The role of GSDMB in bladder cancer has not been studied to date. Methods: TCGA database was used to exam the clinical relevance of GSDMB. Functional assays such as MTT assay, Celigo fluorescent cell-counting assay, Annexin V-APC assay and xenografts were used to evaluate the biological role of GSDMB in bladder cancer. Mass spectrometry and immunoprecipitation were used to detect the protein interaction between GSDMB and STAT3, or GSDMB and USP24. Western blot and immunohistochemistry were used to study the relationship between USP24, GSDMB and STAT3. Results: In this study, bioinformatics analysis indicated that the mRNA expression level of GSDMB in bladder cancer tissues was higher than that in adjacent normal tissues. Then, we showed that GSDMB promoted bladder cancer progression. Furthermore, we demonstrated that GSDMB interacted with STAT3 to increase the phosphorylation of STAT3 and modulate the glucose metabolism and promote tumor growth in bladder cancer cells. Besides, we also showed that USP24 stabilized GSDMB to activate STAT3 signaling, which was blocked by the USP24 inhibitor. Conclusions: We suggested that aberrantly up-regulated GSDMB was responsible for enhancing the growth and invasion ability of bladder cancer cells. Then, we showed that GSDMB could bind to STAT3 and activate STAT3 signaling in bladder cancer. Furthermore, we also demonstrated that USP24 interacted with GSDMB and prevented GSDMB from degradation in bladder cancer cells. Therefore, the USP24/GSDMB/STAT3 axis may be a new targetable signaling pathway for bladder cancer treatment.
Investors’ Beliefs and Cryptocurrency Prices*

We explore the impact of investors’ beliefs on cryptocurrency demand and prices using three new individual-level surveys. We find that younger individuals with lower income and education are more optimistic about the future value of cryptocurrencies, as are late investors. We then estimate the cryptocurrency demand functions using a structural model with rich heterogeneity in investors’ beliefs and preferences. To identify the model, we combine observable beliefs with an instrumental variable strategy that exploits variation in the production of different cryptocurrencies. Counterfactual analyses show that: i) entry of late optimistic investors increased the price of cryptocurrencies on average by about 38% during the boom in January 2018; ii) growing concerns among investors about the sustainability of energy-intensive Proof-of-Work cryptocurrencies lead to portfolio reallocations toward non Proof-of-Work cryptocurrencies and alternative investment opportunities, with Bitcoin and Ethereum experiencing the largest losses. JEL codes: D84, G11, G41.
Prevalence Of Gallstone In Relation To Age, Sex And Body Mass Index In Tikrit City

gallstones are common diseases in many countries of the world , and incidence rate may reach about 20 % . Most cases of gallstones occur in females , the incidence rate may reach four times to one in comparison between women and men , mainly in fatty , fertile , age of forty female , gall stones are rare before age of 20 years ,but; may occur at any age . many cases are not diagnosed because they do not cause any signs or symptoms , and thus can only be diagnosed accidently by routine abdominal ultrasound. The aim of study is to evaluate the relationship between age,sex and body mass index as risk factors for gallstone. a cross sectional study was conducted in Tikrit city during the period from early of May to the end of October 2019 . 468 were enrolled in present study , and only 95 patients were diagnosed as a case of gallstone (29 male , 66 female). All patients attending private ultrasound clinic with different complains, data was collected by using certain questionnaire. The results showed that, There was highly significant statistical relationship (P – value ≤0.05) between body mass index mean in both gallstone cases(26.628±5.808) and, in cases without gallstone(22.225±1.316). In the present study there was high statistically significant relation(Pvalue ≤ 0.05) between body mass index measurement above 25(31.97727273± 3.747859149) and measurement below 25(21.85882353± 1.616313889) in patients with gallstone. The present study conclude that , Body mass index more than 25 considered as an important risk factor for gallstone.
Assessing the Value of Video Resources in Extension-led Natural Resources Management Continuing Education Programs

Effective delivery of continuing education programs can improve their impact. Using the first of four two-week modules of a professional short course, we tested outcomes of a flipped classroom approach, comparing professional foresters’ completion rates, preference for, and perceived value of pre-module content delivered via video and reading. Participants in the National Advanced Silviculture Program self-reported significantly higher pre-module completion rates, preference for, and perceived value of video over reading. This simple study suggests the potential for video to serve as an accessible and preferred format for delivery of key content to supplement an in-person continuing education program.
Monitoring of vitamin K-dependent proteins in perioperative and critical care patients

9 List of publications . 11 Abbreviations . 13 Introduction . 15 History . 15 Different forms of vitamin K . 16 Sources of vitamin K and recommended daily intake . 17 Dietary sources . 17 Vitamin K production by intestinal flora . 18 Recommended daily intake . 18 Synthetic vitamin K concentrates . 18 The vitamin K cycle . 19 Intestinal absorption and transport of vitamin K . 20 Vitamin K-dependent proteins (VKDPs) . 20 Coagulation factors . 20 Matrix Gla protein (MGP) . 21 Osteocalcin (OC) . 22 Growth arrest-specific gene 6 protein (Gas6) . 22 Gla rich protein (GRP) . 22 Markers of vitamin K status . 22 Implication of vitamin K’s involvement in disease . 23 Cardiovascular disease . 23 Sepsis . 24 Pulmonary disease . 25 Osteoporosis . 25 Cancer . 25 Neurodegenerative disease . 26 Normal haemostasis . 26 Coagulopathy in perioperative and critically ill patients . 28 Aims . 31 Study I . 31 Study II . 31 Study III . 31 Study IV . 31 Study V . 31
Examining Students’ Intentions to Use Energy-Efficient Products: An Application of Theory of Planned Behaviour

 Energy-efficient products can reduce the threat of global climate. This research aims to examine students’ intentions to use energy-efficient products by using theory of planned behaviour as the guiding principle. Data were analysed using descriptive analysis via the Statistical Package for Social Sciences (SPSS). The results of descriptive analysis revealed that of the twenty-six items assessed, two statements which represented the environmental awareness factor were the top important aspects highlighted by the respondents in respect to positive perception towards energy-efficient products. They reported that “the main cause of the climate change is a lack of environmental risk perceptions”. This is followed by statement “current environmental situations are very serious for our future”. Moreover, belief factor is also strongly upholding by the participants in this research. They asserted that reliability is important when considering energy-efficient products. Indeed, they strongly believe that environment is important when considering energy-efficient products. The findings advanced body of knowledge on student intentions to use energy-efficient products, which is not much enclosed in the literature in Malaysian context. Direction for future research is also furnished.
Exact Algorithms for Lot-Sizing Problems with Multiple Capacities in Each Time Period, Piecewise Concave Production Cost Functions, and Subcontracting

We study new generalizations of the classical capacitated lot-sizing problem with concave production (or transportation), holding, and subcontracting cost functions in which the total production (or transportation) capacity in each time period is the summation of capacities of a subset of n available machines (or vehicles) of different capacities. We refer to this problem as multi-capacitated lot-sizing problem without or with subcontracting, and denote it by MCLS or MCLS-S, respectively. These are NP-hard problems if n is a part of the input and polynomially solvable for n = 1. In this paper, we address an open question: Does there exist a polynomial time exact algorithm for solving the MCLS or MCLS-S with fixed n ≥ 2? We present exact fixed-parameter tractable (polynomial) algorithms that solve MCLS and MCLS-S in O(T 2n+3) time for a given n ≥ 2. We also reformulate MCLS-S as a lot-sizing problem with piecewise concave production cost functions (denoted by LS-PC-S) and present a new exact algorithm for LS-PC-S that takes O(T 2 n+1+1) time to solve MCLS-S. For an example, in order to solve the MCLS-S with twenty vehicles (n = 20) of different capacities, the latter takes O(T 2097153) time while the former takes O(T 43) time. Furthermore, for n = 2, we introduce extended formulation for the MCLS with Wagner-Whitin costs. We perform computational experiments to evaluate the efficiency of our algorithms and their parallel computing implementation, in comparison to CPLEX 12.7. The results of these experiments show that our algorithms are computationally efficient and stable.
THE LONG-TERM EFFECTS OF AFRICA’S SLAVE TRADES*

* A previous version of this paper was circulated under the title “Slavery, Institutional Development, and Long-Run Growth in Africa. ” I am grateful to the editor, Edward Glaeser, and three anonymous referees for comments that substantially improved this paper. I also thank Daron Acemoglu, Robert Bates, Albert Berry, Loren Brandt, Jon Cohen, Bill Easterly, Stanley Engerman, Azim Essaji, Joseph Inikori, Martin Klein, Pat Manning, Ted Miguel, Jim Robinson, Aloysius Siow, Ken Sokoloff, Dan Trefler, Chris Udry, Jeffrey Williamson, and seminar participants at the University of British Columbia, the University of California Los Angeles, the University of California San Diego, Harvard University, the University of Michigan, New York University, Pennsylvania State University, the University of Rochester, the University of Southern California, the University of Toronto, York University, the CIFAR, the SED Conference, the CEA Meetings, the SSHA Meetings, the ITAM Summer Camp in Macroeconomics, the IEHC, the NBER, and the WGAPE meetings for valuable comments and suggestions. I thank Maira Avila and Ken Jackson for excellent research assistance.
PREDICTION OF COVID-19 FATALITY CASES BASED ON REGRESSION TECHNIQUES

The COVID-19 was first reported to affect human life in Wuhan city, within the Hubei province of China in December 2019. An analysis of around 75,465 cases of COVID19 in China has revealed that the virus is transmitted between people from the blowout of respiratory droplets through sneezing and coughing. Corona is the world's most viral threat warning to people's health and the best pandemic in the world record. This paper presents a comparative study of regression techniques for the prediction of fatality cases due to Coronavirus. The objective of this paper is to predict the fatality cases of the top five affected countries which severely fight against COVID19. Time series forecasting analysis based on machine learning models like Linear Support Vector Regression (LSVR), Random Forest Regression, and Decision Tree Regressions are deployed to predict the fatality cases in the upcoming days. A comparative analysis is also carried out to identify which model best predicts the fatality cases. Covid-19 Data is considered from January 23, 2020, to October 30, 2020.