Miracle-dz/UniFAR-FTUs huggingface dataset:
The improved model of user similarity coefficients computation For recommendation systems

The subject matter of the article is a model of calculating the user similarity coefficients of the recommendation systems. The urgency of the development is determined by the need to improve the quality of recommendation systems by adapting the time characteristics to possible changes in the similarity coefficients of users. The goal is the development of the improved model of user similarity coefficients calculation for recommendation systems to optimize the time of forming recommendation lists. The tasks to be solved are: to investigate the probability of changing user preferences of a recommendation system by comparing their similarity coefficients in time, to investigate which distribution function describes the changes of similarity coefficients of users in time. The methods used are: graph theory, probability theory, radioactivity theory, algorithm theory. Conclusions. In the course of the researches, the model of user similarity coefficients calculating for the recommendation systems has been improved. The model differs from the known ones in that it takes into account the recalculation period of similarity coefficients for the individual user and average recalculation period of similarity coefficients for all users of the system or a specific group of users. The software has been developed, in which a series of experiments was conducted to test the effectiveness of the developed method. The conducted experiments showed that the developed method in general increases the quality of the recommendation system without significant fluctuations of Precision and Recall of the system. Precision and Recall can decrease slightly or increase, depending on the characteristics of the incoming data set. The use of the proposed solutions will increase the application period of the previously calculated similarity coefficients of users for the prediction of preferences without their recalculation and, accordingly, it will shorten the time of formation and issuance of recommendation lists up to 2 times.
Phenolic compound profile characterization by Q-TOF LC/MS in 12 Italian ancient sweet cherry cultivars

Abstract Twelve Italian ancient autochthonous sweet cherry cultivars were characterized for fruit quality parameters, titratable acidity (TA), soluble solids content (SSC) and pH, total phenolic compounds (TPC) and total monomeric anthocyanin (TMA) content and antioxidant activity (AA). TPC, TMA and AA were evaluated by spectrophotometric and Q-TOF LC/MS analysis was performed to identify and quantify single phenolic compounds. SSC, TA, TPC, TMA and AA significantly differ depending on cultivar. Cv. Durona della Marca showed the highest SSC and TA, while pH was less variable among cultivars. The highest TPC (2680.2 mg gallic acid equivalents kg−1 fresh weight, FW), TMA (887.6 mg cyanidin 3-O-glucoside equivalents kg−1 FW) and AA (1.11 μg trolox equivalents mg−1 FW) was found in cv. Nera di Bussolengo. Q-TOF LC/MS analysis allowed to identify and quantify 12 compounds of different classes. The major compounds detected in all the cultivars were neochlorogenic and p-coumaroylquinic acids, (-)-epicatechin, quercetin 3-O-rutinoside and cyanidin 3-O-rutinoside. TPC and TMA have an important role in determining AA. The highlighted differences are ascribable to the genetic traits, because cultivars were grown in the same agronomical, geographical and climatic conditions. This study represents a contribution toward the re-valuation of these ancient cultivars for consumption and breeding programs.
Conversion’s forecast model for ADs in social networks

In this paper, the authors evaluate the characteristics of customers. Established interconnected segmentation and consumer targeting. Formulated groups of consumer characteristics, as well as the characteristics themselves, applicable in a digital environment. Based on data analysis, the effectiveness of targeting by behavioral and psychographic characteristics was determined. The authors proposed a model to predict the conversion rate of advertisements through the use of socio-demographic, psychographic, behavioral and geographical characteristics. The reliability of the models was checked for compliance and its testing. The results obtained during testing turned out to be comparable with the predicted ones, which allowed us to conclude that it is possible to predict conversion rates in order to increase the efficiency of resource use, including when promoting goods and services on social networks.
Innovation and Use of New Teaching Technologies in Undergraduate Learning and Empowerment for the Labour Market

The present study aims to investigate the perspective of students in the business course on innovation and the use of new teaching technologies in undergraduate learning and empowerment for the labour market in a city in northeastern Brazil. The methodology study is qualitative, conducted through a questionnaire tech-nique with open questions with students from a higher education institution, graduates of the business course and others who have already completed and are looking for space in the labour market. The results obtained in the present study suggest a greater participation of the university in the articulation of its trained professionals with the local companies, serving as a support platform and in this way enabling some monitoring of these graduates at the entrance of the local market, through networks of contacts that bring together companies of recent graduates. The conclusion of the study is that there is a complex situation, that despite the difficulties imposed by the economic crisis and lack of local opportu-nities, the chance of getting a job is better for those who, in fact, absorb as much of the knowledge that the course offers and get their diploma.
Data security sharing model based on privacy protection for blockchain‐enabled industrial Internet of Things

With the widespread application of Industrial Internet of Things (IIoT) technology in the industry, the security threats are also increasing. To ensure the safe sharing of resources in IIoT, this paper proposes a data security sharing model based on privacy protection (DSS‐PP) for blockchain‐enabled IIoT. Compared with previous works, DSS‐PP has obvious advantages in several important aspects: (1) In the process of identity authentication, it protects users' personal information by using authentication technology with hidden attributes; (2) the encrypted shared resources are stored in off‐chain database of the blockchain, while only the ciphertext index information is stored in the block. It reduces the storage load of the blockchain; (3) it uses blockchain logging technology to trace and account for illegal access. Under the hardness assumption of Inverse Computational Diffe–Hellman (ICDH) problem, this model is proven to be correct and safe. Through the analysis of performance, DSS‐PP has better performance than the referred works.
A performance‐based multi‐model combination approach to reduce uncertainty in seasonal temperature change projections

Future changes in climate variable exhibit prominent impact on flood magnitudes, crop yields, and freshwater withdrawal. Researchers typically ignore the large degree of uncertainty translated from climate projections to the estimated climate change magnitudes while applying pre‐processing approaches on climate change projections. General Circulation Models (GCM) exhibit substantial uncertainty in projecting future changes in the seasonal temperature, which is evaluated by estimating the shift in either the mean or variance. Bias between the observed changes (1950–1999) and GCM simulated changes vary across models, climate regions, seasons, and under emission scenarios. The simplest approach to reduce model structural uncertainty, equal weighting of GCMs, does not consider superiority of one or multiple GCMs compared to the rest. The current study adopts a performance‐based model combination approach that has shown efficiency in streamflow and weather forecasting, and GCM precipitation simulation. The optimal model combination approach has been modified to combine multi‐model climate change information, while yielding the spatial correlation in climate change information within a geographic region. The optimal model combination approach, along with a simple bias‐correction, is applied on 10 GCMs over nine climate regions across the coterminous United States (CONUS). We found that the optimal combination exhibits lower RMSE values as compared to the equal combination. Correlations between the model combined projections under optimal combination and the observed changes are strong and positive (>0.5). Future (2000–49) model combined projections exhibit an increase in the mean seasonal temperature by 2°C for winter and by 1°C for summer over almost all climate regions.
Interleukin 25 (IL-25) expression in cholangiocarcinoma

Various cytokines are involved in carcinogenesis and tumor progression. Some tumor cells produce cytokines by themselves. Using secretome analysis, a high expression of APEX-1 was found in cholangiocarcinoma (CCA) cell lines. During this secretome analysis, it was found that CCA cell lines overexpressed some cytokines and related molecules, including interleukin 25 (IL-25). In the present study, we first performed precise secretome analysis on cytokines and related molecules in CCA cell lines and identified that IL-25 was overexpressed in CCA cell lines. Then, using immunohistochemical methods, we investigated the expression of IL-25 in the cancer tissues from 20 CCA patients in Northeast Thailand. Correlation between IL-25 expression levels and patients' clinical parameters were analyzed. The results showed that IL-25 expression was significantly (P<0.0001) higher in cancerous tissues than in the normal bile ducts and in the adjacent tissues. Overexpression of IL-25 protein in CCA tissue was confirmed using western blot analysis. Moreover, IL-25 expression in cancerous tissues was significantly (P<0.0015) higher in CCA patients with metastasis than in CCA patients without metastasis. Survival analysis revealed that a high expression of IL-25 was correlated with shorter survival time of CCA patients (P=0.0260). Aberrant expression of IL-25 in CCA tissue was associated with tumor metastasis and poor prognosis, suggesting that IL-25 is a potential prognostic biomarker. Biological roles of IL-25 in CCA genesis and progression should be explored in future.
The Effects of Resistance Wheel Running on Skeletal Muscle Function and Adaptation in C57BL/10SnJ Mice

Background: Resistance wheel running (RWR) can promote resistance-like training adaptations in mouse skeletal muscle (SkM), but its endurance-training effects are lesser known. Methods: Voluntary RWR was modulated as an exercise model to increase mouse hind-limb plantar-flexor torque and to promote endurance-training adaptations. Thirty male mice (cohort 1, n= 16; cohort 2, n= 14), were trained on a prototype RWR system that applied resistance relative to body mass (BM). Mice were sequentially, (1) screened for running ability (screening; 3-days); (2) trained with incremental adjustments to wheel loads (pre-training; 8-weeks); (3) grouped into cage-activity only (CA), and constant Low-0%, Med-15%, or High-25% BM resistance conditions (static training; 5-weeks); (4) trained with resistance adjusted in real-time (dynamic training; cohort 1, 7-weeks; cohort 2, 10-weeks); and (5) sacrificed for various assays. Plantarflexor torque was determined during each training phase. After dynamic training, resistance runners in each cohort were sub-grouped post-hoc by work tertiles. Results: Wheel running distance varied between cohorts (cohort 2 > 1). During dynamic training, wheel running (±added-resistance) improved plantar flexor torque normalized to BM by 19% only in cohort 2 (p= 0.007). Muscle mass and cross-sectional area were unchanged. Runners in both cohorts (±added-resistance) improved maximal running capacity vs. CA-controls (+69% and +115%; both p < 0.05), but metabolic training adaptations were less evident. Conclusions: Wheel running promoted SkM strength and endurance, but there was a greater increase in endurance capacity than strength. This outcome may be due to adaptive signaling interference.
Does Venture Capital Attract Human Capital? Evidence from a Randomized Field Experiment

Attracting talent is widely believed to be critical to the success of a startup. In this paper, we investigate whether potential employee interest in a startup is affected by venture capital funding. We do so by analyzing a field experiment conducted on AngelList Talent, a large online search platform for startup jobs. In the experiment, whether a startup was funded by top-tier VCs and/or whether it was funded recently is randomly highlighted in search results. We find that the same startup receives significantly more interest from potential employees when the fact that it was funded by a top-tier VC is highlighted. In contrast, highlighting the fact that a startup was funded recently has no effect. High-quality job candidates care the most about the identities startup investors. The results provide direct evidence of the certification role played by VCs and their impact on the labor market.
Metal-Organic Framework MIL-53(Fe): Synthesis, Electrochemical Characterization, and Application in Development of a Novel and Sensitive Electrochemical Sensor for Detection of Cadmium Ions in Aqueous Solutions

A metal-organic framework MIL-53(Fe) was successfully synthesized by a simple hydrothermal method. A synthesized MIL-53(Fe) sample was characterized, and results indicated that the formed MIL-53(Fe) was a single phase with small particle size of 0.8 μm and homogeneous particle size distribution was obtained. The synthesized MIL-53(Fe) has been used to modify a glassy carbon electrode (GCE) by a drop-casting technique. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) measurements of the MIL-53(Fe)-modified GCE showed that the MIL-53(Fe) was successfully immobilized onto the GCE electrode surface and the electrochemical behavior of the GCE/MIL-53(Fe) electrode was stable. In addition, several electrochemical parameters of MIL-53(Fe)-modified GCE (GCE/MIL-53(Fe)) including the heterogeneous standard rate constant ( ) and the electrochemically effective surface area ( ) were calculated. Obtained results demonstrated that the synthesized MIL-53(Fe) with the small particle size, highly homogeneous particle size, and high electrochemically effective surface area was able to significantly enhance the electrochemical response signal of the working electrode. Therefore, the GCE/MIL-53(Fe) electrode has been used as a highly sensitive electrochemical sensor for cadmium ion (Cd(II)) monitoring in aqueous solution using differential pulse voltammetry (DPV) technique. The response signal of the electrochemical sensor increased linearly in the Cd(II) ion concentration range from 150 nM to 450 nM with the limit of detection (LOD) of 16 nM.
Detection of Persistent Bovine Viral Diarrhea Virus in Infected Cattle by Immunoperoxidase Method Using Hair Follicles

SUMMARY In this study, a simple immunoperoxidase method using hair follicles (HF-IPO) was established for the detection of bovine viral diarrhea virus (BVDV) in persistently infected (PI) animals. A positive result was observed for samples of hair follicles obtained from 41 cattle PI with BVDV but not for those obtained from 60 uninfected animals. These results highly agreed with those obtained by virus isolation (VI) and reverse transcription-polymerase chain reaction (RT-PCR) performed on blood samples. However, two transiently infected calves with viremia showed a negative result by HF-IPO and a positive result by RT-PCR. Positive results were also confirmed by HF-IPO in VI-negative PI neonatal calves due to possible interference of maternal antibodies. Furthermore, BVDV antigen was detectable for a long period in hair samples stored at −20℃ . These results indicate that HF-IPO can quickly and inexpensively detect PI animals with equal sensitivity to VI and RT-PCR. This method was considered suitable for individual tests in calves with maternal antibodies and suspected PI. Therefore, it could improve the diagnostic efficacy of BVDV infection by adding to the conventional diagnostic procedure.
INTERPLAY BETWEEN SUBSTANCE USE AND HEALTH: BEHAVIOURAL DYNAMICS AMONG FEMALE ADOLESCENTS IN BUTTERWORTH, SOUTH AFRICA

Using an exploratory and descriptive design, as well as interviews and focus group discussions with female adolescents, their parents, former users of substances, social workers, probation officers, community leaders, teachers and police (SAPS), the paper explores the interplay between substance use by female adolescents and their behaviour. Findings revealed that substances use among female adolescents motivated sexual behaviour, sexual engagement was driven by financial goals, there was an increased risk of contracting STIs, excessive consumption of alcohol was normalised, and increased propensity for conflict became evident. The paper recommends that the government and NGOs work together synergistically in order to address substance use among adolescent females.
Keeping electoral peace? Activities of United Nations peacekeeping operations and their effects on election-related violence

In war-torn countries, elections are held to support peacebuilding, but they sometimes trigger new violence. While peacekeeping operations (PKOs) regularly accompany electoral periods, we lack systematic knowledge on how they influence election-related violence. I argue that variation in peacekeepers’ activities is fundamentally important: only if PKOs assist with securing and organizing elections can they reduce election-related violence. Using novel data on PKOs’ election-related activities and accounting for endogeneity in both peacekeeping deployment and activities, the analyses of all 630 elections in conflict-affected countries support this expectation. The result implies that the design of PKOs is crucial for effectively managing post-war political transitions.
There are More than Two Sides to Antisocial Behavior: The Inextricable Link between Hemispheric Specialization and Environment

Human functions and traits are linked to cerebral networks serving different emotional and cognitive control systems, some of which rely on hemispheric specialization and integration to promote adaptive goal-directed behavior. Among the neural systems discussed in this context are those underlying pro- and antisocial behaviors. The diverse functions and traits governing our social behavior have been associated with lateralized neural activity. However, as with other complex behaviors, specific hemispheric roles are difficult to elucidate. This is due largely to environmental and contextual influences, which interact with neural substrates in the development and expression of pro and antisocial functions. This paper will discuss the reciprocal ties between environmental factors and hemispheric functioning in the context of social behavior. Rather than an exhaustive review, the paper will attempt to familiarize readers with the prominent literature and primary questions to encourage further research and in-depth discussion in this field.
Identification of bioactive peptides in kashar cheese and its antioxidant activities

This study analyzed the peptide profile and antioxidant activity in commercially sourced Kashar cheese. The antioxidant activity of Kashar cheese was found to be 41.09 mM Trolox g−1. However, the antioxidant activity of its F3, F4, F5 and F14 fractions was found to be 920.726 mM Trolox g−1, 545.544 mM Trolox g−1 , 783.864 mM Trolox g−1, and 392.12 mM Trolox g−1, respectively. In Kashar cheese, the Tandem Mass Spectrometry (MS/MS) spectrum for the 875 g mol−1 m/z signal was matched to αs1-casein, and it showed that 1012 g mol−1 (875+137) histidine can be a part of 1140 (1012+128) glutamine amino acid. Peptide sequences were matched to 875:RPKHPIK-H-Q peptide 1012:RPKHPIK+H peptide and 1140:RPKHPIKH+Q peptide. It can be concluded that the peptide fractions of Kashar cheese demonstrated antioxidant activity.
Potential Activity of Some Biofertilizer Agents on Antioxidant and Phytochemical Constituents of Faba bean Plant

Faba bean (Viciafabae L.,) is an annual legume crop which is consumed as plant foods for human and animal nutrition. So that, Rhizobium leguminosarum was used as nitrogen fixer with Aphanocapsaalpida and Laurenciaobtusa as biofertilizer agents to enrich faba bean plants with primary and secondary phytochemical content especially: nitrogen, protein, flavonoids, anteoxidants and polyphenolics contents. The results in this study showed that application of Aphanocapsaalbida caused the highest increase of polyphenolic content in the root of faba bean plants followed by the treatment of Rhizobium leguminosarum var. , fabae+ Laurenciaobtusa (10.78,7.97 and 7.54 mg Gallic acids /gm. dry wt. respectively), while the treatment of Laurenciaobtusa + Aphanocapsa albida gave the highest increase in polyphenolic content in the shoots of faba bean plants in compared with the other treatments and control (6.11 mg Gallic acids/gm. Dry wt.). All the treatments caused a significant increase in the shoots and roots antioxidants activity but Aphanocapsaalbida was the superior one. Rhizobium leguminosarum var. faba, caused the highest increase in flavonoids contents in the shoots of faba bean plants followed by Rhizobium leguminosarum var. Faba + Laurenciaobtusa whereas the combination of different treatments caused the highest amounts of flavonoidsin the roots followed by the treatment of Rhizobium leguminosarum var. faba+Laurenciaobtusa. All the treatments caused increase in the both of shoots and roots protein content. The treatment Laurenciaobtusa + Aphanocapsaalbida caused the best result which reached 12.5% and 11.87% in roots and shoots respectively followed by the treatment of Aphanocapsaalbida which caused 11.87% in the both of roots and shoots of faba bean plants.
Incidental capture of sea turtles by industrial bottom trawl fishery in the Tropical South-western Atlantic

The five sea turtle species occurring in Brazilian waters are susceptible to threats, including incidental catches by fisheries. Studies on incidental captures in fishing gears are the main focus of several conservation actions due to high sea turtle fishery mortality worldwide. This study provides the first evaluation of incidental sea turtle catches by industrial bottom trawl fisheries operating in Brazilian waters. Four twin-trawler vessels were monitored between July 2010 and December 2011 by captains who voluntarily completed logbooks. Forty-four turtles were captured during the 1996 tows (8313 fishing hours), resulting in a catch of 5.3 ± 0.8 turtles per 1000 h per unit effort. Captured species included the loggerhead turtle (Caretta caretta, 22 individuals), olive ridley turtles (Lepidochelys olivacea, 21 individuals) and one green turtle (Chelonia mydas). Water depth was the only variable that significantly affected sea turtle captures according to Generalized Linear Models. The capture rates reported in this study ranked sixth in relation to other published studies of similar fisheries occurring worldwide. Considering the importance of this region for sea turtles, the increasing evidence of sea turtle mortality and the goals of the National Action Plan for Conservation of Sea Turtles in Brazil, it is essential to identify the main threats towards these animals and propose mitigating solutions to reduce sea turtle mortality induced by fishing activities. This study provides results that may guide future research and goals in meeting sea turtle conservation strategies.