Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Objective Influence Maximization

Influence Maximization (IM) is the problem of finding a set of influential users in a social network, so that their aggregated influence is maximized. The classic IM problem focuses on the single objective of maximizing the overall number of influenced users . While this serves the goal of reaching a large audience, users often have multiple specific sub-populations they would like to reach within a single campaign, and consequently multiple influence maximization objectives. As we show, maximizing the influence over one group may come at the cost of significantly reducing the influence over the others. To address this, we propose IM-Balanced , a system that allows users to explicitly declare the desired balance between the objectives. IM-Balanced employs a refined notion of the classic IM problem, called Multi-Objective IM, where all objectives except one are turned into constraints, and the remaining objective is optimized subject to these constraints. We prove Multi-Objective IM to be harder to approximate than the original IM problem, and correspondingly provide two complementary approximation algorithms, each suit-ing a different prioritization pertaining to the inherent trade-off between the objectives. In our experiments we compare our solutions both to existing IM algorithms as well as to alternative approaches, demonstrating the advantages of our algorithms.
ANOMALOUS TRANSPORT OF INFECTIOUS DISEASES IN STRUCTURED POPULATIONS

Structural properties of populations strongly influence dynamic transport and interaction such as the transmission of infectious diseases. In this paper a hierarchical block model is investigated, that schematically describes the configuration of social communities. It is shown that these models can produce super-diffusive spread and that the balance between intraand inter-community contacts is a suitable factor for controlling the expression of this feature. The qualitative characteristics of epidemics simulated with this model are reproduced in numerical simulations of a basic fractional-in-space differential equation SIR model. Based on a stochastic formulation of the block structure, a preliminary connection between both models can be derived. The results of this paper confirm that certain structural characteristics of interacting populations can be simulated in aggregated models by employing fractional derivatives.
Survey on Chronic Kidney Disease Prediction System with Feature Selection and Feature Extraction using Machine Learning Technique

---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Chronic Kidney Disease (CKD) need to be diagnosed earlier before kidneys fail to work.In order to help doctors or medical experts in prediction of CKD among patients easily, this paper has developed an intelligent system named Chronic Kidney Disease Prediction System (CKDPS) that can predict CKD among patients. The proposed system predict the CKD with minimal feature input instead of dumping all the features which may not relevant to predict the disease.To achieve this we have planned to approach by three feature selection algorithm with combination of two feature Extraction algorithm.After performing feature selection and Feature Extraction, those features will be trained with different Machine Learning algorithm. The accuracy of best combination algorithm will be implemented for predicting the CKD.Finally, Random Forest algorithm is chosen to implement CKDPS as it gives 95% accuracy, precision and recall results.
Study of specificity in adaptability of rice (Oryza sativa L.) genotypes to specific environment

A field experiment was conducted in Randomized Block Design with three replications at three locations viz., Educational and Research Farm, Department of Agricultural Botany, College of Agriculture, Dapoli, Agricultural Research Station, Shirgoan Dist. Ratnagiri and Agricultural Research Station, Phondaghat during Kharif 2016. The AMMI model, which combines the standard analysis of variance with IPC analysis was used to investigate G × E interaction. In AMMI model, the contribution of each genotype and each environment to the GEI is assessed by the use of biplot graph display in which yield means are plotted against the scores of the IPCA 1. In interaction principle axis of AMMI biplot, first interaction principle axis (IPCA I) were favorable for all the characters but the second interaction principle axis (IPCA II) were favorable for characters such as spikelets fertility, grain yield plot-1 (kg), the number of panicles square meter-1, protein content (%), iron content (ppm), amylose content (%), grain yield plant-1(g) and total number of spikelets panicle-1. The genotype viz., RTN-1201-13-2-2-1-32 was found most favourable for all the characters in the entire three environments with high yield, maximum plant height and more content of micronutrients. The genotype viz., RTN1211-4-2-1-1 was found stable for grain yield plot-1, grain yield plant-1 and protein content. The genotypes RTN-120151-2-1-5-48, RTN-1211-5-1-3-5 and RTN-1201-5-1-3-14 were found to be stable for Dapoli and Shirgaon locations for the traits viz., grain yield plant-1, grain yield plot-1 and micronutrients. The genotypes viz., RTN-1201-51-2-1-5-48 and RTN-1211-6-1-3-1-8 were found stable for Shirgaon location for traits viz., spikelet fertility, test weight, plant height, panicle length and micronutrients.
ON THE ARCHITECTURE OF SEMANTIC NETWORKS: A QUANTITATIVE ASSESSMENT OF SUBJECTIVE REPRESENTATIONS

: The increased use of computer aided qualitative data analysis software in social research fields profit from the semantic networks (SN) for the data organization and analysis. However, the validation and scope of these methodologies remains as an open discussion. In the other hand, graph theory methods are a growing field on mathematics but is becoming also important in most research fields, such as social and human sciences. Regardless the similarity between SN and graph theory, no studies have accessed the quantitative architecture of the SN. Here, we explored by quantitative means the subjective component of SN architecture. Overall, differences in the metrics of the SN graphs and loss of global correlation across experts suggested that the topology of SN include a subjective component, important in differentiating cognitive processes between persons. Furthermore, the results suggest that methods such as triangulation should be considered in the analysis of qualitative data.
COMPARATIVE FREE RADICAL SCAVENGING ABILITIES AND PHYTOANTIOXIDANT ACTIVITIES OF THREE SELECTED VEGETABLE, FRUIT AND SPICE JUICE

The inhibition of free radical scavenging ability and natural antioxidants present in plant kingdom can be an important holistic plan in preventing epigenetic diseases. Hence this study aims to analyze three groups i.e. vegetable (tomatoes), fruits (oranges) and spice (garlic) to find best source to reduce free radical activity as these crops are consumed at larger amount. Fresh juice and extract were obtained by screw type juice extractor and further processed for study free radical scavenging ability using DPPH assay and other phytoantioxidant activity. DPPH assay revealed that orange juice (602.48mg/ 100ml) had significant highest free radical scavenging ability compared to tomato and garlic juices (307.46 and 157.01mg/ 100ml) due to ferulic acid. Total phenol was significantly higher in tomato (523.33mg/100ml) owing to few major phenolic compounds. Total Carotenoid and -carotene were statistically significant (P>0.05) in garlic juice extract (5.39 μg/100g; 4.25mg/100ml), followed by tomato (4.36μg/100g; 3.67mg/100ml) and orange (3.33μg/100g; 2.64mg/100ml), respectively. Total flavonoids content has non-significant difference in tomato (29.05mg/100ml) and orange (29.03mg/100ml) juice. Percentage of ascorbic acid content was highest in orange juice (356.35mg/100 ml) as Citrus family has the characteristics of higher ascorbic acid content. This confirms that these juices might protect human as well as animal body from oxidative damage and may cure epigenetic diseases. Our experiment concluded that orange followed by tomato and garlic juice will be best for human health.
EFFECT OF NOVEL LICORICE AND MACA COMBINED PLANT CRUDE AQUEOUS EXTRACT ON LITTER SIZE AND PUPS DNA NORMALITY IN MICE: EXPERIMENTAL MODEL FOR MAMMALS

Licorice and Maca extracts has many beneficial effects that recently many researchers have revealed their interest to investigate the potential valuable effects of these plant extracts. However, there is no study about the effects of a Lico rice and Maca extracts mixture on pups and DNA normality in mice. Therefore the goal of this study is toinvestigates, for the first time, the effects of Lico rice and Maca mixture on the first and second generation of the treated female mice. The dosages of both Licorice (Gg) and Maca (M) were orally administrated for 10 days as following; Gg group (25mg in 0.2ml daily), M group (5mg/0.5ml daily), Gg+M group (0.1ml+0.25ml/day respectively), Gg+M+SO group (0.1 ml +0.25 ml/day respectively) then undergo ovulation induction. The number, weight and teratogenicity of offspring of first and second generation were recorded. The DNA damage was evaluated by COMET assay, manually quantification and categorization into 4 categories (0-3) viavisual scoring of cells. The results of current study found that oral administration of Licorice and Maca combined with super ovulation program in mice age 28 weeks has enhancement in pups numbers compared with 8 weeks old mice with no teratogenic effect on pups of both first and second generations and no DNA damage. It is concluded that the mixture of licorice and maca crude aqueous extract was confirm the option to be used by aged mammals to improve the reproductive fertility status. These results can be utilized for aged human females for further investigation.
An Effective Stroke Prediction System using Predictive Models

---------------------------------------------------------------------- Abstract - This paper provides an effective method for detecting stroke. R language in RStudio is used to conduct data analysis and for the construction of a prediction application. Making a random user be able to test themselves for stroke is the primary objective of this project. The web application and the data analysis parts are made to work on the patients’ characteristics data. The stroke training and test datasets are gathered and exploratory data analysis is performed. The most efficient and accurate variables required to predict stroke in an individual is obtained through Feature Selection and as per the variables gained, the features which influence the disease prognosis is obtained. Predictive modeling is performed on this processed data with various classification models such as Random Forest, Decision tree, Logistic Regression and Support Vector Machines. The web application is made to process user inputs and predict the occurrence of stroke using the most accurate model.
The Mediating Role of Job Satisfaction on the Relationship between Organizational Support, Employee Empowerment and Turnover Intention of Jordanian Auditors

This paper conducted an investigation of the effects of perceived organizational support and employee empowerment on job satisfaction and the latter’s effect on turnover intention, along with its mediating role. Accordingly, data was collected from 103 Jordanian auditors from audit firms and the research model was analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The analysis findings supported a positive relationship between perceived organizational support, employee empowerment and job satisfaction, and a negative one between job satisfaction and turnover intention of Jordanian auditors. The findings also supported indirect effects between perceived organizational support, employee empowerment and turnover intention, through the mediating role of job satisfaction. The study contributes by enriching the theoretical knowledge dedicated to job satisfaction, particularly its mediating role, as underpinned by Social Exchange Theory
Redistribution of fractions of zinc, cadmium and lead in calcareous soils treated with EDTA

Abstract The effect of EDTA (ethylene diamine tetra acetic acid) on the fractionation of Zn, Pb, and Cd in six calcareous soils was investigated. A total of 400 mg kg−1 Zn, 200 mg kg−1 Pb, and 8 mg kg−1 Cd was added to soils as chlorides. Both natural and metal-amended soils were treated with Na2EDTA solution at amounts of 0, 1.0, and 2.0 g kg−1. Metals in the incubated soils were fractionated after 5 months by sequential extraction procedure, in which the metal fractions were defined as exchangeable (EXC), carbonate (CARB), Mn oxide (MNO), Fe oxide (FEO), organic matter (OM) and residual (RES) fractions. Increasing the amounts of EDTA significantly raised Zn concentrations in the EXC and CARB fractions in metal-amended soils. EDTA also increased Cd concentrations in the EXC fraction of the metal-amended soils. Increasing the amount of EDTA raised significantly Pb concentrations in the CARB and MNO fractions in metal-amended soils. In the metal-amended soils, EDTA removed some Pb from RES and OM fractions and redistributed them into CARB and MNO fractions. Based on relative percent in the EXC fraction, the order of solubility was Cd > Zn > Pb for metal-amended soils, before and after adding of EDTA.
The quest for the structure of water and aqueous solutions

During the past 25 years neutron diffraction has made a major contribution to understanding the microscopic structure of water and aqueous solutions. By performing isotope substitution on specific atomic sites, it is possible to develop a comprehensive picture of the way water molecules organize themselves around the ions and molecules which dissolve in or mix with water. The resulting data provide a sensitive, sometimes controversial, test of existing theories of the aqueous systems, which due to their complexity at the microscopic level, can normally only be derived using computer simulation techniques. This paper reviews some of the recent achievements in the field of neutron diffraction from aqueous systems and suggests how future experiments might be interpreted with the aid of computer simulation techniques.
Ellipsometric Chain Length Dependence of Fatty Acid Langmuir Monolayers. A Heads-and-Tails Model

Langmuir monolayers of even n-fatty acids with increasing number N of carbon atoms in the hydrocarbon chain (N = 11−23) were investigated on 1 × 10-2 M HCl aqueous subsolutions by means of Brewster angle ellipsometry. Isotherms, relating the coefficient of ellipticity Δρ to the area per molecule F, were continuously recorded and interpreted on the basis of literature phase diagrams and in situ X-ray reflectivity and diffraction investigations. Δρ/N dependencies for the liquid-expanded (LE), super-liquid or solid (LS/S), and condensed-solid (CS) monolayer phases were extracted from the isotherms at constant areas per molecule: FLE = 28 ± 1 A2, FLS/S = 19.2 ± 0.3 A2, FCS = 18.5 ± 0.3 A2. They show Δρ-discontinuities at the LE−LS and S−CS transitions but no change at the LS−S transition. The experimental Δρ/N data for the solid condensed monolayer were compared with calculated Δρ/N dependencies using the “one-layer” ellipsometric model with bulk isotropic or theoretical anisotropic n/N data. A very good agr.
UPS Spectra of Lithium‐Doped Carbon Nanostructures: Quantum Chemical Simulations

Abstract We present a quantum chemical study on the effect of lithium doping in hydrogen rich carbon nanostructures. To model the hydrogen rich carbon nanostructure we selected hexa‐peri‐hexabenzocoronene, a well‐known polycyclic aromatic hydrocarbon whose UPS spectra have been recorded recently. This study shows that lithium interacts strongly with the carbon nanostructure and does not simply transfer charge to the PAH. As a result, the unusual features observed in the UPS spectra of lithium‐doped HBC are correctly reproduced by the calculations.
An Embedded Polygon Strategy for Quality Improvement of 2D Quadrilateral Meshes with Boundaries

Quadrilateral (or quad) meshes generated by various remeshing and simplification methods for input models with complex structure and boundary configurations often possess elements with minimal quality, which calls for an optimization approach to improve their individual elements’ quality while preserving the boundary features. Many existing methods either fix boundary vertices during optimization or assume a simple boundary configuration. In this paper, we introduce a new quality improvement framework for 2D quad meshes with open boundaries. Our framework aims to optimize the configuration of an embedded polygon constructed based on the one-ring neighbors of each interior vertex. A feature-preserved boundary optimization is also introduced based on the angle configuration of the individual boundary vertices to further improve the quality of the boundary elements. Our framework has been applied to a number of 2D quad meshes with various boundary configurations and compared with other representative methods to demonstrate its advantages.
SURVEY ON MALWARE DETECTION USING DEEP LEARNING METHODS

- Malware has become one of trending issue nowadays. Malware attackers inject malicious codes into the source code thereby malicious actions take place. Malware can be in different forms (such as trojan-horses, worms, computer viruses etc.). Malware identification continues to be a challenge as attackers comp up with new techniques that tackles the detection methods. In earlier times signature-based detection becomes a milestone for detecting malware. Later on, it becomes ineﬃcient in the present condition due to the speedy increase in the number and versions of malware. Many machine learning techniques are relevant nowadays. In this paper a detailed summary done on different machine learning methods in the area of malware detection which includes Support Vector Machine (SVM), Random Forest
The seasonal variation in chemical composition of some of the littoral seaweeds common to scotland. Part I. Ascophyllum nodosum

The ash, iodine, crude protein, mannitol, laminarin and alginic acid contents of samples of Ascophyllum nodosum taken at monthly intervals from April, 1945, to March, 1947, have been determined. The samples were taken from three different habitats in the neighbourhood of Oban in order to show the effect of varying exposure. In general, the loch samples are lower in iodine, total ash, crude proteins, and higher in laminarin and mannitol than the open sea or medium exposed samples. An increase in the mannitol and laminarin contents is accompanied by an increase in the dry weight content and a decrease in the total ash content. The graphs for the mannitol, laminarin and dry weight contents show three distinct peaks in the year, which agree with those in samples of the laminariacea already examined. The drop in mannitol and laminarin which occurs in the laminariaceae in July/August, and is at present the subject of investigation, also occurs in Ascophyllum nodosum. Ascophyllum nodosum is appreciably lower in mannitol and laminarin than the laminariaceae, but laminarin is present throughout the year, whereas it is absent for periods in the laminariaceae so far investigated. This alga is higher in alginic acid than any of the laminariaceae examined. The very slight variations in mannitol, laminarin and alginic acid, throughout the year, enable this alga to be harvested for any particular constituent at any time of the year.
A PRACTICAL FIT FORMULA FOR IONIZATION RATE COEFFICIENTS OF ATOMS AND IONS BY ELECTRON IMPACT:Z= 1–28

Abstract Ionization rates for atoms and ions from H to Ni recommended by the Belfast group, supplemented by data derived from several other sources, are fitted to an analytical expression with four fit parameters. On the grounds of its very simple form and its ability to generally replicate the input data to within a few percentage points, we present this expression as a practical formula for use in computer modeling of plasma processes.
Fluorescence, fluorescence-excitation, and ultraviolet absorption spectra of trans-1-(2-naphthyl)-2-phenylethene conformers

Fluorescence spectra of trans-1-(2-naphthyl)-2-phenylethene (NPE) obtained under varying conditions of excitation wavelength and oxygen concentration in methylcyclohexane are resolved into two distinct components by application of principal component analysis with self-modeling. The key to obtaining unique spectral solutions is the constraint that Stern-Volmer quenching plots for the individual conformers be independent of excitation wavelength. Resolved conformer fluorescence-excitation spectra are obtained by application of principal component analysis on a matrix of fluorescence-excitation spectra. Consistency between pure component fluorescence and fluorescence-excitation spectra is established by use of a two-dimensional fluorescence-excitation emission matrix
Graphite Electrodes Modified with Platinum‐Nickel Nano‐Particles for Methanol Oxidation

Methanol electro‐oxidation is investigated at graphite electrodes modified with various platinum and nickel nano‐particle deposits using cyclic voltammetry. The modified electrodes are prepared by the simultaneous electrodeposition of metals from their salt solutions using potentiostatic and galvanostatic techniques. They show enhanced catalytic activity towards methanol oxidation in KOH solution. The catalytic activity of platinum nano‐particles is found to be significantly affected by the presence of relatively small amounts of nickel deposits. A comparison is made between the electrocatalytic activity of Pt/C and (Pt‐Ni)/C electrodes. The results show that the methanol electro‐oxidation current increases with an increase in the nickel content. In particular, the highest catalytic activity is achieved for platinum to nickel deposits of 95%:5% (wt.‐%), in other cases the catalytic activity decreases. It is found that Ni enhances the catalytic activity of Pt by increasing the number of active sites, as well as through an electron donation process from Ni to Pt. This process takes place once the nickel hydroxide (Ni(OH)2)/nickel oxy‐hydroxide (NiOOH) transformation begins. The effect of the methanol concentration on the methanol oxidation reaction is investigated. The order of reaction, with respect to methanol, at the modified (Pt‐Ni)/C electrode is found to be 0.5.
Hydrogen Sulfide Viscosity Modeling

As regulations for emissions of carbon dioxide and hydrogen sulfide into the atmosphere are becoming stricter and the penalty for violation increases, new and economical ways of reducing these emissions are becoming increasingly important to everyday operations. One promising sequestering option is the injection of acid gas mixtures into formations for disposal/storage. During the design of these acid gas injection schemes a comprehensive knowledge of the thermo-physical properties is of utmost importance in determining the feasibility and size of these operations. Recently, the friction theory (f-theory) for viscosity modeling has been shown to accurately determine the viscosity behavior of a wide range of petroleum fluid systems ranging from natural gases to heavy crude oils. This technique has also been shown to accurately model mixtures containing various concentrations of CO2. However, in the development of the f-theory hydrogen sulfide was not explicitly studied and therefore needs to be accounted f.