Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlated Matrix Factorization for Recommendation with Implicit Feedback

: The implicit feedback primarily recommendation problem once solely the user history is offered however there aren't any ratings—is a far tougher task than the express feedback based recommendation problem, thanks to the inherent uncertainty of the interpretation of such user feedbacks. Recently, implicit feedback drawback is being received additional attention, as application oriented analysis gets additional engaging at intervals the sphere. This paper focuses on a typical matrix factorisation methodology for the implicit drawback and investigates if recommendation performance is improved by applicable data format of the feature vectors before coaching. we tend to gift a general data format framework that preserves the similarity between entities (users/items) once making the initial feature vectors, wherever similarity is outlined mistreatment e.g. context or data. We tend to demonstrate however the planned data format framework is in addition to radio frequency algorithms. We tend to experiment with numerous similarity functions, totally different context and data primarily based similarity ideas. The analysis is performed on 2 implicit variants of the MovieLens 10M dataset and 4 world implicit databases. We tend to show that the data format considerably improves the performance of the radio frequency algorithms by most ranking measures.
Big Data: Analytical Solutions, Research Challenges and Trends

The term Big Data refers to an extensive collections of digital data generating every second. Produced datasets come in structured, semi-structured, and unstructured formats throughout the world, which is difficult for the traditional database management systems to analyze. Recently, big data analytics emerges as an essential research area due to the popularity of the Internet and the advent of new Web technologies. This growing area of research represents a multi-disciplinary that attracts researchers from various research fields. Interested researchers are invited to design, develop, and implement several tools, technologies, architecture, and platforms for analyzing these large volumes of data. This paper begins with a brief introduction to big data and related concepts, including the main characteristics of big data, followed by discussions of the most significant open research challenges and emerging trends. Next, reviewing a study of big data analytics, the advantages of using big data solutions, and the preliminary assessments required before migrating from traditional solutions. Finally, presenting a review of the recent main applications to obtain a broad perspective of big data analytics.
4 Techniques for Characterizing Lignin

Many techniques are available to characterize lignin. The techniques presented in this chapter are considered nondegradative, which are commonly applied to lignin. A brief discussion of lignin structure is included with this chapter to aid the reader in understanding why the discussed characterization techniques are appropriate for the study of lignin. Because the chemical structure and composition of lignin vary from source, type of lignin, and isolation method, as discussed in the preceding chapters, characterization is important. Obtaining the molecular weight of a lignin sample can give information, such as degree of polymerization, even before investigating the chemical structure. Chemical structure characterization is most often accomplished using spectroscopic methods. Understanding the chemical structure can be useful in determining lignin sources, degradation of lignin samples, relationship between physical properties and thermal properties, selecting appropriate modification methods, and determining the efficacy of modifications. Chemical structure characterization techniques discussed in this chapter include ultraviolet (UV) spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and X-ray photoelectron spectroscopy (XPS). Physical properties such as thermal and mechanical properties can be related back to the chemical structure. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) are often employed during the investigation of thermal properties of lignin, while dynamic mechanical analysis (DMA) can be used to investigate both thermal and mechanical properties. In each section, a brief introduction to each technique is followed by examples of its application to lignin. Finally, the reader is directed toward select resources that are available for a more complete understanding of these methods, and their applicability to lignin.
Carbapenem Resistance in Gram-negative Bacteria in South-western Nigeria: The Role of Extended-spectrum β-lactamase CTX-M-15

Objective: To determine the role of extended-spectrum β-lactamases in carbapenem-resistant Gram-negative bacteria from south-western Nigeria. Methods: Twenty-seven carbapenem-resistant isolates that were found to be non-carbapenemase producers (15 Escherichia coli, 9 Klebsiella pneumoniae and 3 Pseudomonas aeruginosa) were further studied. These isolates were subjected to analysis including phenotypic and genotypic detection of various β-lactamases, efflux activity, outer membrane protein, plasmids replicon typing, detection of transferable genes and resistances and typing using random amplified polymorphic DNA tests. Results: No isolates demonstrated de-repression of efflux, but all showed either complete loss or reduced production of outer membrane proteins. Transconjugants from these strains contained various genes including plasmid-mediated quinolone resistance and extended-spectrum beta-lactamases. All the transconjugants carried the blaCTX-M-15 gene. The transconjugants had varying minimum inhibitory concentrations of carbapenems ranging from 0.03 μg/ml to 8 μg/ml. Varying resistances to other antimicrobial agents were also transferred with the plasmids. The donor isolates were not clonally related by molecular typing. Conclusion: Resistance to carbapenem antibiotics in this sample was not mediated only by carbapenemases but also by production of extended-spectrum β-lactamases (largely CTX-M-15), accompanied by protein loss. This was an important mechanism underpinning carbapenem resistance in these clinical isolates of various species.
Micro-motion Forms Classification of Space Cone-shaped Target Based on Convolution Neural Network

─ In this paper, the echo models with different micro-motion forms (spin, tumbling, precession, and nutation) of space cone-shaped target are built. Different from the ideal point scatterers model, the radar echo contains the contribution from the complex radar cross section (RCS) of point scatterer vs aspect angle. And a convolution neural network (CNN) model for micro-motion forms classification based on the micro-Doppler characteristics in spectrograms is presented. The simulation results show that our method can discriminate different micro-motion forms effectively and the overall accuracy is 97.24%. Different levels of additive white Gaussian noise are added to simulate noise-contaminated radar echo. It has been found that the presented method has a stronger anti-noise ability than support vector machine (SVM). When the Signal-to-Noise Ratio (SNR) of Gaussian white noise is 10 dB, the overall accuracy of our algorithm is 29.79% higher than that of SVM.
Deposited in DRO : 13 March 2020 Version of attached

Despite the spectacular success of vaccines in preventing infectious diseases, fears about their safety and other anti-vaccination claims are widespread. To better understand how such fears and claims persist and spread, we must understand how they are perceived and recalled. One influence on the perception and recall of vaccination-related information might be universal cognitive biases acting against vaccination. An omission bias describes the tendency to perceive as worse, and recall better, bad outcomes resulting from commissions (e.g. vaccine side effects) compared to the same bad outcomes resulting from omissions (e.g. symptoms of vaccine preventable diseases). Another factor influencing the perception and recall of vaccination-related information might be people’s attitudes towards vaccines. A confirmation bias would mean that pre-existing pro-vaccination attitudes positively predict perceptions of severity and recall of symptoms of vaccine preventable diseases and negatively predict perceptions of severity and recall of vaccine side effects. To test for these hypothesized biases, 202 female participants aged 18–60 (M = 38.15, SD = 10.37) completed an online experiment with a between-subjects experimental design. Participants imagined that they had a 1-year old child who suffered from either vaccine side effects (Commission Condition) or symptoms of a vaccine-preventable disease (Omission Condition). They then rated a list of symptoms/side effects for their perceived severity on a 7-point Likert scale. Finally, they completed a surprise recall test in which they recalled the symptoms/side effects previously rated. An additional scale was used to measure their attitudes towards vaccines. Contrary to the hypotheses, perceptions of severity and the recall of symptoms/side effects were not associated with experimental condition, failing to support the omission bias, nor did they interact with attitudes towards vaccines, failing to support the confirmation bias. This cast doubt on the possibility that the spread of anti-vaccination claims can be explained by these particular universal cognitive biases. PLOS ONE PLOS ONE | https://doi.org/10.1371/journal.pone. 0228898 March 4, 2020 1 / 16 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111
Of economics and statistics: the “Gerschenkron effect”

The “Gerschenkron effect” refers to the purported biases of early-weighted and late-weighted indices of production. If production is properly measured in what economists mean by “real” terms, the “Gerschenkron effect” does not exist at all. Fondazione Luigi Einaudi, Turin, email: stefano.fenoaltea@unito.it How to cite this article: Fenoaltea S. : (2019), “Of economics and statistics: the “Gerschenkron effect””, PSL Quarterly Review, 72 (290): 195-205 DOI: https://doi.org/10.13133/2037-3643_72. 290_2 JEL codes: C19, C43, N00
Model of Performance Improvement of Certified Teachers in Private Vocational Schools

Purpose: This study aimed to investigate a performance development model of the certified teachers at private vocational schools through school principal leadership, working environment, and teachers’ alleviating motivation. Research Method: This research was conducted using a descriptive correlation approach with a multiple regression analysis. The data were collected using a purposive random sampling technique with total respondents of 118 certified teachers from various private vocational schools in Tegal, Central Java, Indonesia. The data were gathered through questionnaires and then analyzed using SPSS 12. Findings: The regression analysis testing results indicated that (1) school principal leadership with the correlation coefficient of 0.83 positively and significantly influenced the performance of certified teachers by 82.8%, (2) working environment with the correlation coefficient of 0.877 positively and significantly influenced the performance of certified teachers by 87.7%, and (3) affiliating motivation with the correlation coefficient of 0.035 did not positively and significantly influence the performance of certified teachers by 3.50%. The results of multiple regression analysis showed that performance of certified teachers was influenced by school principal leadership, working environment, and teachers’ affiliating motivation. Implications for Research and Practice: Based on the research results, it is suggested that the private vocational principals should continuously improve their leadership and create positive working environments as these variables positively influence teachers’ performance, while teachers’ affiliating motivation should also be considered
EFFECT OF LIGHT SOURCE AND DIETARY ENERGY LEVEL ON CARCASS CUTS DISTRIBUTION OF BROILER CHICKENS

The present trial aimed to study the effect of light source and dietary energy level on some carcass cuts distribution of male and female broilers. One hundred and eighty one-day-old, male and female, Hubbard broiler chicks, were distributed in a factorial design. Experimental treatments were assigned by applying 3 metabolizable energy (ME) levels [standard recommendation (SR); SR + 100 kcal/ kg diet and SR + 200 kcal/ kg diet, for both starter and grower feeding phases], and 2 light sources [fluorescent; light-emitting diodes, LED] in 6 treatments, 3 replicates per treatment and 10 birds / replicate. The results indicated that all composition parameters of breast, thigh and drumstick (skin and subcutaneous fats, muscles and bone percentages), were not significantly affected by different dietary energy levels, light sources or bird sex. Additionally, there were no significant differences between treatments on skin and subcutaneous (SC) fats distribution of carcass parts, but LED had increased fats percentages than fluorescent. In addition, this parameter increased with birds fed medium level of dietary energy than other treatments. Furthermore, there were no significant differences between fluorescent and LED treatments or bird sex on muscles percentage of carcass parts, but there were significant differences between dietary energy levels. In addition, chicks fed high dietary energy diets had significantly higher percentages of drumstick muscles. Likewise, there were no significant differences between treatments on bone percentages of carcass parts, but LED decreased total percentage compared with that of fluorescent. Also, mid and high dietary energy level decreased total percentage of bone distribution compared with that of the low dietary energy. Overall results of the present trial, declared that LED light source and low dietary energy had improved carcass composition compared to other treatments. Therefore, it could be advice to use LED lighting in farms to reduce costs of broiler production and to improve physiological status of birds.
Correlation Between Serum Creatinine & Urine Albumin in Diabetic Nephropathy Patients

Diabetic nephropathy has some distinct stages and each of the stages are individually defined according to different amount of albumin excreted through urine. Serum creatinine is a very common tool of renal assessment in diabetic nephropathy. This study aims at observation of existing correlation between serum creatinine and urine albumin in diabetic nephropathy patients. This cross sectional observational study has been conducted on 50 diabetic patients admitted to medicine department of Dhaka Medical College Hospital. Patients were included in this study after fulfilling inclusion and exclusion criteria in a period January 2018 to June 2018. After selection, data were collected by structured questionnaire. Then 24 hour urinary total protein, urine for microalbumin, complete blood count, fasting blood sugar, two hours postprandial blood sugar, HbA1C, serum creatinine report were collected and analyzed it with the help of SPSS 16.0 MS excel. Among total 50 patients, 34 patients were diagnosed on the basis of microalbuminuria and the rest were found to have raised urinary total protein. The male patients were 54 percent of the total population. Most of the patients were in between the age of 57 to 67 years. The r value is insignificant in two graphs where serum creatinine was compared with urine microalbumin and serum creatinine respectively, which suggests absence of linear or any other correlation between these two components. The estimated Glomerular Filtration Rate (eGFR) was calculated by MDRD equation individually. Staging was done on the base of eGFR. Only 41.37% of the patients with microalbuminuria, showed eGFR consistent with its staging while only 31.5% of the patients with proteinuria showed respective expected eGFR. And the difference between the mean serum creatinine in two groups was insignificant. This study has shown that, the serum creatinine has no linear correlation with urinary albumin in diabetic nephropathy patients. So, commonly used serum creatinine based formula to calculate the estimated GFR cannot reflect the amount of urinary protein excretion all the time. So it can misinterpret the staging of the disease which can delay the appropriate treatment of the patient. J Dhaka Medical College, Vol. 27, No.2, October, 2018, Page 141-147
Big Data Analytics using Deep LSTM Networks: A Case Study for Weather Prediction

A R T I C L E I N F O A B S T R A C T Article history: Received: 23 November, 2019 Accepted: 31 January, 2020 Online: 09 March, 2020 Recurrent Neural Networks has been widely used by researchers in the domain of weather prediction. Weather Prediction is forecasting the atmosphere for the future. In this proposed paper, Deep LSTM networks has been implemented which is the variant of RNNs having additional memory block and gates making them capable of remembering long term dependencies. Fifteen years hourly meteorological data of Brazil weather stations for the period of 2000-2016 collected from Kaggle.com has been analyzed for 1 hour and 24-hour time lag using Keras libraries on Spark framework. Hidden layers of the network have been increased up to three to examine its impact on accuracy of the network and it was found that network with 2 hidden layers provides good accuracy in lesser learning runtime. From the experimental results, it is also concluded that Adam optimizer provides best results when compared with SGD and RMSProp optimizer.
The impact of social support on the quality of life of the elderly from rural areas

Objective. The purpose of this article is to explore social support influence on the quality of life of elderly people from rural areas and to examine whether there are differences between the quality of life of the old people living in the family and those who live alone. Methods. An epidemiological observation study was performed, and it was a cross section study. The sample consisted of 110 subjects. Berlin Social Support scale was used with the aim to measure social support, and to assess the quality of life a 10-point Likert scale was used. Normal K-K Plot and histogram graphs were used to test the agreement of the sample distributions with the normal distribution, as well as the tests: Kolmogorov-Smirnov and Shapiro-Wilk. The Kruskal Wallis and Wilkisson test sum scores were used to test for differences in overall social support and the quality of life. Results. All social support parameters affect life satisfaction. These differences are statistically significant (p<0.05), which was also shown by Spirman's correlation. Respondents who rated the relationships with housemates as excellent had the highest average grade of satisfaction with life (7.38), while those who rated these relationships as horrible had the lowest average grade of satisfaction with life (1.57). Frequent contacts with close relatives and friends on a weekly basis correlate with a greater life satisfaction degree. Conclusion. It can be concluded that the index of total social support and all of its subgroups correlate with subjective life satisfaction of elders.
Enhancing Financial Performance through Supply Chain Innovation (SCI) with mediating role of Robustness and Resilience Capability in Thailand’s manufacturing sector

Purpose: Main objective of this research is to assess the relation between SCI and risk management capabilities of firms and to focus that how innovation and risk affect financial performance. Methodology: In order to analyze the hypotheses developed in this study, survey method in the form of questionnaire was adopted to collect data from the manufacturing firms of Thailand. The data collected in then analyzed by using different statistical tools including SPSS and AMOS. Findings: Outcomes of research clearly shows that SCI has significant positive impact on the level of risk associated with firms including both robust and resilience risk factors in terms of technological advancements. The results show that these variables are inter-related with each other which means that with the increase in innovativeness, the risk associated with it also increases as a result the financial performance of firms also increases. Implications: The research provides data and an addition in literature related to SC management by investigating the impact of innovation on risk and performance levels of firms. It also provides help to mangers to critically analyze and to make sound decisions related to impacts of technological processes on their Supply chain (SC) practices globally. Novelty: This study is unique in its own perspective because it has focused on the relationship of SC innovation, risk management as well as financial performance altogether of the manufacturing firms that are involved in international levels of SC in Thailand.
EFFECT OF FEED RESTRICTION WITH SUPPLEMENTATION OF PROBIOTIC WITH ENZYMES PREPARATION ON PERFORMANCE, CARCASS CHARACTERISTICS AND ECONOMIC TRAITS OF BROILER CHICKENS DURING FINISHER PERIOD

The objective of this study was to investigate the response of broiler chicks to feed restriction at finisher period (5-6 weeks) of age and supplementation of (probiotic + enzymes preparation) on performance, carcass characteristics and economical traits. A total number of 180 Hubbard broiler chickens 5 weeks of age were weighed and divided into six dietary treatments of 30 chicken each with 3 replicates (10 chicken in each), in 2 x 3 factorial design as follow: T1: Chickens fed basal diet ad-libitum without supplementation, T2: Chickens fed basal diet ad-libitum + Zado® (0.5 Kg/ ton), T3: Chickens fed basal diet ad-libitum + AmphiBact® (0.5 Kg/ ton), T4: Chickens fed (T1 diet), restricted for 6 hours / day, T5: Chickens fed (T2 diet), restricted for 6 hours / day, T6: Chickens fed (T3 diet), restricted for 6 hours / day. The results indicated that: Productive performance of broiler chicks including live body weight (LBW); daily weight gain (DWG); feed conversion ratio (FCR), performance index (PI), production efficiency factor (PEF), protein conversion ratio (PCR) and energy conversion ratio (ECR) were not affected significantly by feed restriction (R), feed supplementation, (F) and interaction (R*F) at experimental period (5-6 weeks of age). Daily feed intake (DFI) recorded a significant response due to feed restriction only. Carcass characteristics (edible parts, inedible parts, carcass cuts and drumstick traits) indicated that (R), (F) and interaction (R*F) had no significant effects except dressed carcass and neck percentages. Economic evaluation showed that, chicks fed diet supplemented with (Zado®, 0.5 Kg/ ton) in either ad-libitum or restricted regime had the best relative economic efficiency (REE) and mean economic efficiency of all restricted-fed groups, increased (REE) by 3.4% as compared with the corresponding values of the ad-libitum groups. Based on the experimental results, it is concluded that supplementing broiler chicks under ad-libitum or restricted-fed regime with (Zado®, 0.5 Kg/ ton) could be better approach to improve relative economic efficiency during finisher period.
The non-financial factors impact on the enterprises activity efficiency

The estimation procedure of non-financial analysis integral index for comprehensive evaluation the enterprises economic efficiency is substantiated in the article . The mechanism for predicting enterprise activity using neural network architecture of multilayer perceptron is grounded. The technique the impact of non-monetary indices on the enterprises’ annual performance results was further developed. The advantages and perspectives of integrated enterprises accounting system to assess the investment management effectiveness for all components, their interdependence and role in achieving the company’s global goal highlighted. Non-monetary factors of the enterprise performance are generalized.