Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine Learning for sport results prediction using algorithms

This paper describes the use of machine learning in sports. Given the recent trend in Data science and sport analytics, the use of Machine Learning and Data Mining as techniques in sport reveals the essential contribution of technology in results and performance prediction. The purpose of this paper is to benchmark existing analysis methods used in literature, to understand the prediction processes used to model Data collection and its analysis; and determine the characteristics of the variables controlling the performance. Finally, this paper will suggest the reliable tool for Data mining analysis technique using Machine Learning.
Broadband Dual-Polarized 2 × 2 MIMO Antenna for a 5G Wireless Communication System

In this study, we proposed an indoor broadband dual-polarized 2 × 2 MIMO (multiple-input and multiple-output) antenna having dimensions of 240 mm × 200 mm × 40 mm, for application in 5G wireless communication systems. The proposed antenna comprised two vertically polarized circular monopole antennas (CMAs), two horizontally polarized modified rectangular dipole antennas (MRDAs), and a ground plane. The distance between the two MRDAs (MRDA1 and MRDA2) was 70.5 mm and 109.5 mm in the horizontal (x-direction) and 109.5 mm vertical (y-direction) directions, respectively. Conversely, the distance between the two CMAs (CMA1 and CMA2) was 109.5 mm and 70.5 mm in the horizontal (x-direction) and vertical (y-direction) directions, respectively. While the CMAs achieved broadband characteristics owing to the optimal gap between the dielectric and the driven radiator using a parasitic element, the MRDAs achieved broadband owing to the optimal distance between the dipole antennas. The observations in this experiment confirmed that the proposed could operate in the 5G NR n46 (5.15–5.925 GHz), n47 (5.855–5.925 GHz), n77 (3.3–4.2 GHz), n78 (3.3–3.8 GHz), and the n79 (4.4–5 GHz) bands. Moreover, it exhibited a wide impedance bandwidth (dB magnitude of S11) of 101% in the 2.3–7 GHz frequency range, high isolation (dB magnitude of S21), low envelope coefficient correlation (ECC), gain of over 5 dB, and average radiation efficiency of 87.19%, which verified its suitability for application in sub-6 GHz 5G wireless communication systems.
Lecture 22 Quality Factor of Cavities and Mode Orthogonality

The quality factor of a cavity or its Q measures how ideal or lossless a cavity resonator is. An ideal lossless cavity resonator will sustain free oscillations forever, while most resonators sustain free oscillations for a finite time due to losses coming from radiation, or dissipation in the dielectric material filling the cavity, or resistive loss of the metallic part of the cavity. Because of losses, the free oscillation in a cavity has electromagnetic field with time dependence as follows:
Predicting microcystin occurrence in freshwater lakes and reservoirs: assessing environmental variables

ABSTRACT Determining the environmental conditions that influence the occurrence and concentration of the cyanobacterial toxin microcystin (MC) is a critical step for predicting cases in which the toxin will adversely affect drinking water sources, recreational waterbodies, and other freshwater ecosystems. Although widely studied, little consensus exists regarding the factors that influence MC on a global scale. The objective of this study was to identify the environmental variables most strongly associated with MC concentrations using observational data from lakes and reservoirs around the world while also addressing the substantial proportions of missing values that a large aggregated dataset often involves. A total of 124 studies containing data from an estimated 2040 lakes and reservoirs in 22 countries was used to construct a global dataset. Variables including <35% of non-missing observations were removed prior to analysis. Missing values for the remaining 12 predictors of MC were imputed using an iterative imputation algorithm based on a random forest approach. Variable selection was performed with generalized additive modeling on the complete case and imputed datasets. Models applied to the imputed data produced lower prediction errors than those fit to the complete dataset. Variables of greatest significance to MC concentration included location (longitude–latitude pairs), total nitrogen, turbidity, and pH. Total phosphorus was not found to be a strong predictor of MC. In addition to assisting water resource managers in protecting their waterbodies against MC, the presented methodologies may provide a useful framework for future water quality modeling while accounting for varying proportions of missing data.
An automated LPG weight monitoring system to assist cost efficient domestic usage

In recent years there has been a rapid development in technology which has made human life easier in several aspects. LPG is a need of every and is widely used for cooking. Some of the common problems experienced during its usage are, the gas cylinders go empty while the peak cooking hours, incognizance of the current status of gasoline present in the container, and the failure to prophesy the working days of the LPG cylinder once installed. All these lead to inconvenience in its use. To deal with these issues Smart Gas Kit is an ideology put forward. It mainly focuses on the application of the IoT used for measuring and displaying the gasoline content present in household LPG cylinder and automatic booking of a new LPG cylinder. The additional advantage of the system also involves predicting the working days of the gasoline content. The continuous weight measurement of gas on regular basis is done using a load cell which is interfaced with a Microcontroller. The current status and the booking notifications are notified to the user on their mobile phones via Bluetooth module. The entire framework work towards making the LPG chamber booking system more automatized without any human intercession.
Numerical Investigation of Endothermic/Exothermic Reaction in MHD Natural Convective Nano-Fluid Flow over a Vertical Cone with Heat Source/Sink

The significance of natural convective MHD flow of nano-fluid over a vertical cone with Brownian motion, viscous dissipation, heat generation, thermophoresis, and chemical reaction in porous surroundings is discussed in this article. The leading non-linear PDEs are transmuted by using applicable similarity transform and the reformed equations, along with the boundary conditions, are numerically solved by finite difference technique of bvp4c code via MATLAB code. The significance of the controlling parameters on velocity, temperature, and concentration are portrayed vividly. Furthermore, skin friction, Nusselt number, and Sherwood number are charted for diverse parameters. It is worth mentioning that impact of heat source ( ) on velocity and temperature is remarkable. Molar species concentration is accentuated with progressive values of Dufour number, while it is the opposite for velocity and temperature profiles. Moreover, thermal energy is absorbed due to the application of endothermic chemical reaction that cools the surroundings, which minimizes the diffusion rate of molecules and, therefore, less molar concentration is occurred. Conduction is the dominant mechanism for heat transport by applying Rayleigh number. The profiles of skin friction, Nusselt number, and Sherwood number are reduced with higher values of Rayleigh number. The present study has an appreciable impact on many engineering applications, such as magnetic storage media, the cooling systems of electronic devices, nuclear power plants, the chemical industry, and many more. HIGHLIGHTS Heat source/sink is a key parameter for rate of heat/mass transfer of nanofluid flow Exothermic chemical reaction plays a dynamic role to boost the nanofluid flow motion Higher Rayleigh number decays the flow rate as well as rate of heat and mass transfer The study incorporates the application of Brownian motion in nanofluid flow Current study has diverse applications in cooling process GRAPHICAL ABSTRACT
E-optimal Experimental Designs for Poisson Regression Models in Two and Three Variables

In the context of generalized linear models, most of the recent studies were on logistic regression models and many of them focussed on optimal experimental designs with concentration on D-optimality. In this research, two- and three-variable Poisson regression models were considered for E-optimization on restricted design space [0, 1]. The two-variable Poisson regression model was not optimal at 3-design points, but was found to be E-optimal at 4-design points (1, 1), (0, 0), (0, 1) and (1, 0) with equal design weights of 0.25. The three-variable Poisson regression model was E-optimal at 4-design points (0, 0, 1), (0, 1, 0), (1, 1, 1) and (1, 0, 0) with each design point having design weights of 0.25. The prediction error variance (PEV) for the two-variable Poisson regression model is 0.35 and that of the three-variable Poisson regression model is 0.68. From this research, the two-variable Poisson regression model is preferred to the three-variable Poisson regression model because of smaller PEV. Keywords: E-optimality; Fisher Information Matrix; Poisson Regression Model; Prediction Error Variance
Common sense and Semantically Grounded Understanding for Effective Room Navigation in Embodied Environment

Previous multi-modal embodied navigation research focused 1 on completing tasks by aligning image features with natural 2 language instructions. In this paper, we investigate if intrinsic 3 features such as common sense and semantic understanding, 4 which are critical for human navigators but ignored in pre-5 vious research, also help artiﬁcial agents navigate in realis-6 tic 3D environments given a high-level linguistic instruction. 7 From our experiments, we observe that common sense helps 8 the agent in long-term planning, while semantic understand-9 ing helps the agent in local planning in the room navigation 10 ( RoomNav ) task. We also propose a novel semantically-11 guided self-supervision mechanism which further improves 12 the performance of the agent on unseen environments. The 13 cross-modal embeddings learned during training suggest that 14 common sense and semantic understanding helps in captur-15 ing the structural and positional patterns of the environment, 16 implying that the agent beneﬁts by inherently learning a map 17 of the environment. 18
Pricing of higher education: The case of top-ranked MBA programs

Tuition fees of full-time MBA programs with similar structure can vary greatly from around USD $20,000 to USD $220,000. This paper explores the effects of post-graduation salary, reputation, and their interaction on such high discrepancy in MBA tuition. Using a unique dataset of international MBA programs, we found that program value is positively correlated with post-graduation salary. This relationship is stronger for more prestigious programs whose values are impacted more by graduate outcomes. In addition, this relationship is greater for North American programs, but smaller for European programs, suggesting a geographical effect. These results provide managerial implications for program administrators and universities offering professional business programs. These insights can be extended to other industries of intangible experience goods.
"Effect of P Rates Combined With PDB on Nutrients Uptake by Wheat Grown Under Organic Farming of Sandy Soil Using 15N Tracer Technique"

Received: 8th Feb. 2021 Accepted: 16th June 2021 Under field conditions, wheat response to organic amendments and B. megatherium inoculation as well as different rates of natural rock P fertilizer (NRP) was traced. Animal manure, peanut straw and quail feces were added in combination with P0, P50 and P100 kg ha levels and both factors were tested with or without bacterial inoculation. The grain yield of wheat was higher with 192 kg ha than rate 96 kg ha while both of them surpassed the un-fertilized control. Inoculated plants, under all NRP levels, resulted in a higher grain yield than the un-inoculated ones. In inoculated plants, grain yield was significantly higher with quail feces additives than animal manure and peanut residues. B. megatherium induced slight increases in N uptake as compared to the un-inoculated plants. However, peanut residues resulted in N uptake values slightly higher than either quail feces or animal manure. Increasing rock-P levels increased N uptake over the unfertilized or those received 96 kg ha treatments. Supply with quail feces had increased P uptake over those resulted from peanut residues and animal manure. Quail feces resulted in a relative increase of P uptake by about 5% and 15%; 16% and 19%; 17% and 4% over peanut and animal manure for P0, P50 and P100, respectively. Inoculation with B. megatherium had, to some extent, enhanced K uptake by grains comparable to the un-inoculated one when plants treated with peanut residues. Nitrogen portion derived from (Ndforg) peanut straw and quail feces to inoculated plants was relatively increased, on mean average basis, by about 19% and 16%, respectively over the un-inoculated plants. Efficient use of N derived from peanut straw, quail feces (Org-NUE %) and urea-NUE% by inoculated plants slightly increased under all rock-P levels over those of the un-inoculated plants.
Anemia of inflammation in patients with colorectal cancer: Correlation with interleukin-1, interleukin-33 and galectin-1

Background Patients with colorectal cancer (CRC) have anemia often present as a consequence of chronic bleeding from tumor. The exact role of lL-33, Galectin-l and IL-l in the pathological genesis of anemia in colorectal cancer patients has not been elucidated yet. The main goal of this research was to analyze Gal-l, IL-l and lL-33 systemic values in anemic and non-anemic CRC patients. Methods Concentrations of IL-33, Galectin-1 and IL-1 have been studied in blood samples of 55 CRC patients (27 without anemia and 28 with anemia). Results CRC patients with anemia had more severe and local advanced disease compared to CRC non-anemic patients. Anemia positively correlated with higher nuclear grade, lymph and blood vessel invasion, as well as with higher TNM stage, detectable metastatic lesions in lung and liver and peritoneal carcinomatosis. Significantly higher IL-33, Gal-1 and IL-1 concentration have been found in sera of patients with CRC and detected anemia. CRC patients mostly had microcytic anemia, while ferritin values were in normal range. Analysis revealed positive mutual correlation between serum values of galectin-1, IL-1 and IL-33 in CRC patients. Level of hemoglobin negatively correlated with serum IL-33, Gal-1 and IL-1. We have analyzed the Receiver Operating Characteristic (ROC) curves of serum IL-33, Gal-1 and IL-1 showed that these cytokines can be treated as additional markers for anemia of inflammation in CRC patients. Conclusions Predomination of Galectin-1, IL-1 and IL-33 in anemic CRC patients implicates on their potential role in anemia genesis and further development.
INFLUENCE OF CUSTOMER FOCUS ON COMPETITIVENESS OF FOOD AND BEVERAGE MANUFACTURING FIRMS IN KENYA

Purpose: Manufacturing firms are critical to the economic growth and development through provision of products and employment. Their competitiveness is therefore critical. The firms have been facing steep competition from foreign companies due to increased globalization. Strategic drivers have been found to be key enablers of firm competitiveness and performance. It is on this basis that the study sought to establish the influence customer focus on the competitiveness of food and beverage processing companies in Kenya. Methodology: The study was informed by commitment trust theory. Empirical studies were reviewed to provide the basis for research gaps to be filled by the current study. Descriptive research design was employed while the target population was the 187 food and beverage processing firms in Kenya. A census was used where all the 187 companies were contacted. Structured questionnaire was used to obtain the primary data which was analyzed through mixed method analysis. Descriptive statistics were used to analyze quantitative data while qualitative data was analyzed through content analysis. Inferential statistics were used to analyze the relationship between variables through the regression model. The findings were presented in form of tables, pie-charts and bar-graphs. Findings: It was established that customer focus was upheld in most of the surveyed food and beverage processing companies where after sale services, customer engagement and customer contacting were the main platforms applied. It was concluded that while most of the food and beverage processing firms recognized key strategic drivers (customer focus) as a major aspects of competitiveness, most of the firms did not practically embrace the drivers which could explain their continued lack of competitiveness. Unique contribution to theory, practice and policy: The study recommended that for the food and beverage processing companies to take their place in the local and global market, the management should embrace and keenly focus on customer focus.
Preparation and Ferroelectric Properties of Bi4-xErxTi3O12 Thin Films

Er2O3-doped bismuth titanate (Bi4-xErxTi3O12, BET) and pure Bi4Ti3O12 (BIT) thin films with random orientation were fabricated on Pt/Ti/SiO2/Si substrates by rf magnetron sputtering technique. The experimental results indicated that Er doping into BIT also result in a remarkable improvement in ferroelectric property. The Pr and the Ec values of the BET film with x=0.75 were 21 μC/cm2 and 80 kV/cm, respectively.
A Preliminary Scoring Model to Predict In-hospital Mortality Risk for Geriatric Patients with Delirium

BACKGROUND: Elderly patients are at an increased risk of death, particularly those with altered mental status. AIM: We aimed to develop a scoring model from simple clinical data and routine laboratory testing to aid in predicting in-hospital mortality risk for geriatric patients with delirium. METHODS: A total of 73 hospitalized geriatric patients with delirium were included in the study. A multivariate regression analysis employed to obtain independent risk factors to predict in-hospital mortality. All patients were followed until dead or discharged from hospital. The formula of (B/SE)/lowest B/SE was used to calculate the scores for each variable with strong discrimination power to be included in scoring system. RESULTS: A total of 25 (34.2%) of patients were death when being hospitalized. The mean age of the patients was 73.27 ± 7.8. From a total of 20 probable variables, three variables were then included in constructing the scoring model; no caregiver (p < 0.012), abnormal diastolic blood pressure (p < 0.05), and abnormal serum SGOT levels (p < 0.03). Each variable was scored as 1, following the use of formula. Total score ranges from 0 to maximum of 3. The cutoff score of ≥ 2 provided the best accuracy with sensitivity of 40% and specificity of 89.6% (p < 0.001). The probability of in-hospital mortality was 8.8%, 32.6%, 70.8%, and 92.4% for the total score of 0, 1, 2, and 3, respectively. CONCLUSION: This novel scoring system with simple examination may aid to identify geriatric patients with delirium which possess higher risk for in-hospital mortality.
The Influence of Female Leadership Towards Performance: Evidence from Western European Financial Firms

Does the appearance of women at the executive position in the boardroom make any differences in firm performance, especially in the financial sector which is well-known to be a male dominated sector? Inspired by that question, our study aims to explore the influence of female leadership in firm performance. We investigate this relationship from a comprehensive dataset comprising of 310 listed financial institutions from 21 Western European countries. The endogeneity concerns were removed using a Two stage approach least square (2SLS) and Generalized method of moments (GMM). Critically, we demonstrated that women's appearance at alternative managerial levels, including the chairperson, executive, and total female directors in the boardroom, negatively influences both firm accounting and market-based performance. We further explore that the percentage of women in the boardroom (excepting non-executive female directors) has a negative impact on performance only in low-performing firms. Our findings argue with previous studies which encouraged more involvement of women at higher managerial levels. We believe that women's unique characteristics are addressed to alleviate interest behavior, but they tend to reduce the performance of financial firms.
Determination of groundwater potential distribution of Ceylanpinar Plain (Turkey) in Upper Mesopotamia by using geographical information techniques and Fuzzy-AHP with MCDM

The Ceylanpinar Plain is an important part of Upper Mesopotamia and one of the largest plains of Turkey, is in danger of facing water scarcity due to global climate change. For this reason, the potential of groundwater resources is important. In this study, groundwater potential zones in the Ceylanpinar Plain basin were investigated utilizing a weighted overlay analysis method combined with fuzzy analytical hierarchy process (FAHP) multi-criteria decision-making (MCDM) approaches and geoinformation technologies. The groundwater potential zone map was created using 10 theme layers that were produced and processed in a geographic information system (GIS) environment (GPZM). After that, possible groundwater zones were identified and classified into five categories: very good, good, medium, poor, and very poor. By assessing the present open well distribution and yield data of selected wells within the research catchment, the predicted groundwater potential zones (GWPZ) was confirmed. As a result, 17% of the study area was found to be very good, 39% good, 20% moderate, 21.4% poor and 2.6% very poor. This study provides a key estimate and crucial information for regional water administrators and officials in southeast Turkey by giving a map of the groundwater potential region, in order to ensure sustainable groundwater management.
Guidelines for Neural Network System Architecture Diagrams

Diagrams are often used to describe system architectures in Computer Science. Neural network systems are no exception. Without any framework or guidelines establishing good practices for their design, the current state is heterogeneous and evolving. Investigation of this ﬁeld necessarily employs mixed methods. The research aims to improve diagrammatic representation of neural network systems by 1) deriving appropriate requirements and metrics 2) selecting appropriate representational guidelines and 3) create and implement an iterative framework for improving a set of diagram guidelines.