Miracle-dz/UniFAR-FTUs huggingface dataset:
Avian Bornaviruses in Wild Aquatic Birds of the Anseriformes Order in Poland

Bornaviruses are a diverse family of viruses infecting various hosts, including birds. Aquatic bird bornavirus 1 (ABBV-1) and aquatic bird bornavirus 2 (ABBV-2) have been found in wild waterfowl but data on their prevalence are scarce. To gain knowledge on the occurrence of ABBVs in Poland, samples originating from dead birds of the Anseriformes order collected in 2016–2021 were tested with a real time RT-PCR method targeting the ABBVs genome. A total of 514 birds were examined, including 401 swans, 96 ducks and 17 geese. The presence of ABBV-1 RNA was detected in 52 swans (10.1% of all tested birds) from 40 different locations. No positive results were obtained for ducks and geese. Sequences of about 2300 bases were generated for 18 viruses and phylogenetic analysis was performed. A relatively low genetic diversity of the examined ABBV-1 strains was observed as all were gathered in a single cluster in the phylogenetic tree and the minimum nucleotide identity was 99.14%. The Polish strains were closely related to ABBV-1 identified previously in Denmark and Germany, but a limited number of sequences from Europe hinders the drawing of conclusions about interconnections between Polish and other European ABBVs. The results of the present study provide new insights into the distribution and genetic characteristics of ABBVs in wild birds in Europe.
Nutrition-Related Content on Instagram in the United States of America: Analytical Cross-Sectional Study

Background: The Internet is today the largest platform for food distribution, and there are concerns about the impact that digital marketing has in the field of nutrition by promoting non-evidence-based recommendations. The purpose of this study was to describe the user profile that draws on Instagram to follow nutrition-related content versus not, and to analyze the frequency and type of content of the information provided by nutritional influencers. Methods: A cross-sectional study involving randomly selected United States residents having an Instagram account was performed. Participants completed an anonymous online survey link. Results: From 898 respondents, 78.7% were women, and 75.6% were Millennials. Scientific evidence present in the posts was 14.3%. Influencers promoted a product or a brand in more than 90% of posts. Women followed more nutrition-related content than men (p < 0.001). Millennials, followed by Generation-Z, followed more nutrition-related content (p < 0.001). There were no significant relationships between the following status of nutrition-related content with BMI, type of job, household income, education degree, or smoking habits. Conclusions: Women and Millennials followed more nutrition-related content. Scientific evidence was scarce and commercial interest in the network was evident. The vast majority of the posts were not based on scientific evidence and instead promoted a product/supplement.
Improvements in Awareness and Testing Have Led to a Threefold Increase Over 10 Years in the Identification of Monogenic Diabetes in the U.K.

OBJECTIVE Maturity-onset diabetes of the young (MODY) is a rare monogenic form of diabetes. In 2009, >80% of U.K. cases were estimated to be misdiagnosed. Since then, there have been a number of initiatives to improve the awareness and detection of MODY, including education initiatives (Genetic Diabetes Nurse [GDN] project), the MODY probability calculator, and targeted next-generation sequencing (tNGS). We examined how the estimated prevalence of MODY and other forms of monogenic diabetes diagnosed outside the neonatal period has changed over time and how the initiatives have impacted case finding. RESEARCH DESIGN AND METHODS U.K. referrals for genetic testing for monogenic diabetes diagnosed >1 year of age from 1 January 1996 to 31 December 2019 were examined. Positive test rates were compared for referrals reporting GDN involvement/MODY calculator use with those that did not. RESULTS A diagnosis of monogenic diabetes was confirmed in 3,860 individuals, more than threefold higher than 2009 (1 January 1996 to 28 February 2009, n = 1,177). Median age at diagnosis in probands was 21 years. GDN involvement was reported in 21% of referrals; these referrals had a higher positive test rate than those without GDN involvement (32% vs. 23%, P < 0.001). MODY calculator usage was indicated in 74% of eligible referrals since 2014; these referrals had a higher positive test rate than those not using the calculator (33% vs. 25%, P = 0.001). Four hundred ten (10.6%) cases were identified through tNGS. Monogenic diabetes prevalence was estimated to be 248 cases/million (double that estimated in 2009 because of increased case finding). CONCLUSIONS Since 2009, referral rates and case diagnosis have increased threefold. This is likely to be the consequence of tNGS, GDN education, and use of the MODY calculator.
Effects of Microwaves, Ultrasonication, and Thermosonication on the Secondary Structure and Digestibility of Bovine Milk Protein

Cow’s milk is considered an excellent protein source. However, the digestibility of milk proteins needs to be improved. This study aimed to evaluate the relationship between the functional properties of milk proteins and their structure upon microwave, ultrasound, and thermosonication treatments. The protein content, digestibility, and secondary-structure changes of milk proteins were determined. The results demonstrated that almost 35% of the proteins in the untreated samples had a α-helix structure and approximately 29% a β-sheet and turns structure. Regarding the untreated samples, the three treatments increased the α-helices and correspondingly decreased the β-sheets and turns. Moreover, the highest milk protein digestibility was observed for the ultrasound-treated samples (90.20–94.41%), followed by the microwave-treated samples (72.56–93.4%), whereas thermosonication resulted in a lower digestibility (68.76–78.81%). The milk protein content was reduced as the microwave processing time and the temperature increased. The final milk protein available in the sample was lower when microwave processing was conducted at 75 °C and 90 °C compared to 60 °C, whereas the ultrasound treatment significantly improved the protein content, and no particular trend was observed for the thermosonicated samples. Thus, ultrasound processing shows a potential application in improving the protein quality of cow’s milk.
Reconstruction of the artificial knee joint using a reverse engineering approach based on computer-aided design

Abstract A greater flexion angle in total knee arthroplasty (TKA) is desirable for replacing the human knee joint damage of people living in the Middle East and Asian regions. This flexion angle is a significant clinical factor affecting the range of motion for patients. Therefore, this study aims to optimise the flexion angle in the design of the Artificial Knee Joint (AKJ) by tailoring the Posterior tibial slope (PTS) and thickness of the Posterior Femoral Condyle (PFC). The 3D CAD model of AKJ was obtained from the reverse engineering (RE) process. Furthermore, the physical model used as a standard implant produced by DePuy, Cruciate Substituting (CS)-Revision type. The obtained 3D models were subsequently converted into CAD for the reconstruction process. Reconstruction of the CAD Model with the customised PTS and FPC components provided the flexion angle in the range of 149.9°–166.7°, which is required for the motion suitable for Middle Eastern and Asian people. The results may be used as a reference standard for doctors in hospitals or industries to design AKJ with Asian ergonomics.
Regulatory Role of Phospholipids in Hepatitis C Virus Replication and Protein Function

Positive-strand RNA viruses such as hepatitis C virus (HCV) hijack key factors of lipid metabolism of infected cells and extensively modify intracellular membranes to support the viral lifecycle. While lipid metabolism plays key roles in viral particle assembly and maturation, viral RNA synthesis is closely linked to the remodeling of intracellular membranes. The formation of viral replication factories requires a number of interactions between virus proteins and host factors including lipids. The structure–function relationship of those proteins is influenced by their lipid environments and lipids that selectively modulate protein function. Here, we review our current understanding on the roles of phospholipids in HCV replication and of lipid–protein interactions in the structure–function relationship of the NS5A protein. NS5A is a key factor in membrane remodeling in HCV-infected cells and is known to recruit phosphatidylinositol 4-kinase III alpha to generate phosphatidylinositol 4-phosphate at the sites of replication. The dynamic interplay between lipids and viral proteins within intracellular membranes is likely key towards understanding basic mechanisms in the pathobiology of virus diseases, the mode of action of specific antiviral agents and related drug resistance mechanisms.
Nutritional Regimes Enriched with Antioxidants as an Efficient Adjuvant for IBD Patients under Infliximab Administration, a Pilot Study

Antioxidants are privileged candidates for the development of adjuvants able to improve the efficiency of pharmacological therapies, particularly for chronic inflammatory syndromes. During the last 20 years, anti-TNFα (tumor necrosis factor alpha) monoclonal antibodies infusion has been the biological therapy most frequently administered but there is still large space for improvement in disease remission rates and maintenance. In this context, nutritional bioactive compounds contained in dietary patterns or included as supplements, may act as adjuvants for the induction and maintenance of IBD (inflammatory bowel diseases) remission. To verify this possibility, a single-center preliminary study (SI-CURA, Soluzioni Innovative per la gestione del paziente e il follow up terapeutico della Colite UlceRosA) was designed and carried out to evaluate whether a daily administration of purple corn supplement could improve the response to Infliximab (IFX) infusion of IBD patients with both Crohn’s disease (CD) and ulcerative colitis (UC). A cohort of 47 patients was enrolled in the study. Biological samples were collected before the first and the third IFX infusion. All patients received nutritional guidelines, 27 of them received commercial red fruit tea with low anthocyanins content, while 20 received a purple corn supplement with a high anthocyanin content. Results show that the administration of an antioxidant-enriched purple corn supplement could improve IFX-mediated disease remission in terms of circulating inflammatory markers. Comparison between CD and UC patients revealed that, at this anthocyanin dosage, the purple corn extract administration improved the IFX response in CD but not in UC patients. Our results may pave the way for a new metacentric study of CD patients, recruiting a wider cohort and followed-up over a longer observational time.
The impact of meteorological factors and PM2.5 on COVID-19 transmission

Abstract In this study, we analysed the relationship between meteorological factors and the number of patients with coronavirus disease 2019 (COVID-19). The study period was from 12 April 2020 to 13 October 2020, and daily meteorological data and the daily number of patients with COVID-19 in each state of the United States were collected. Based on the number of COVID-19 patients in each state of the United States, we selected four states (California, Florida, New York, Texas) for analysis. One-way analysis of variance ( ANOVA), scatter plot analysis, correlation analysis and distributed lag nonlinear model (DLNM) analysis were used to analyse the relationship between meteorological factors and the number of patients with COVID-19. We found that the significant influencing factors of the number of COVID-19 cases differed among the four states. Specifically, the number of COVID-19 confirmed cases in California and New York was negatively correlated with AWMD (P < 0.01) and positively correlated with AQI, PM2.5 and TAVG (P < 0.01) but not significantly correlated with other factors. Florida was significantly correlated with TAVG (positive) (P < 0.01) but not significantly correlated with other factors. The number of COVID-19 cases in Texas was only significantly negatively associated with AWND (P < 0.01). The influence of temperature and PM2.5 on the spread of COVID-19 is not obvious. This study shows that when the wind speed was 2 m/s, it had a significant positive correlation with COVID-19 cases. The impact of meteorological factors on COVID-19 may be very complicated. It is necessary to further explore the relationship between meteorological factors and COVID-19. By exploring the influence of meteorological factors on COVID-19, we can help people to establish a more accurate early warning system.
Exploring Academic Leadership of University Teachers under the Chinese Contemporary Philosophy and Social Science (Xin Wen Ke) Construction Innovation Context

Abstract Chinese Xin Wen Ke construction innovation is the integration of philosophy and social science, scientific technology, and industry, with the combination of diverse academic subjects and concentrations. Through academic orientation, resources integration, and behavioral modeling, academic leadership of university teachers can be effectively promoted, and the applicative solutions for the emerging obstacles in the process of the combination can be provided. It also can boost the quality of academic leadership of university teachers in relation to orientating values and philosophies, locating the goals, promoting cooperation, and refining achievements. According to recent research, to analyze the contents and structures can foster the quality development in academic leadership of university teachers. This article will draw an overall assessment on different components of academic leadership of university teachers under Chinese Xin Wen Ke construction innovation context, including research reviews and definitions, functions, structures analysis, and cultivation methods, aiming to provide evidence to demonstrate its significance.
Associations between maternal iron supplementation in pregnancy and offspring growth and cardiometabolic risk outcomes in infancy and childhood

It was previously observed that maternal iron supplementation in pregnancy was associated with increased offspring size and adiposity at birth, possibly mediated through increased risk of gestational diabetes. In this study we explored associations of maternal iron supplementation in pregnancy with postnatal offspring growth in infancy and indices of cardiometabolic disease risk factors such as glucose tolerance, insulin sensitivity and blood pressure in mid-childhood (at ~9.5 years of age) in the Cambridge Baby Growth Study. In infancy adiposity-promoting associations with maternal iron supplementation in pregnancy were evident at 3 months of age (e.g. mean difference in skinfold thickness: {beta}=+0.15 mm, p=0.02, in n=341 whose mothers supplemented versus 222 that did not; waist circumference: {beta}=+0.7 cm, p=0.04, in n=159 and 78, respectively) but differences lessened after this time (e.g. 3-12 month change in mean difference in skinfold thickness: {beta}=-0.2 mm, p=0.03, in n=272 and 178, respectively). At ~9.5 years of age associations with maternal iron supplementation in pregnancy were not evident for markers of growth, glucose tolerance, insulin sensitivity or secretion. However, children whose mothers supplemented with iron in pregnancy had lower mean arterial blood pressures ({beta}=-1.0 mmHg, p=0.03, in n=119 and 78, respectively). These results suggest that most of the associations of maternal iron supplementation in pregnancy on growth and adiposity evident at birth disappear during infancy, but there may be some evidence of long-term nutritional programming evident later in childhood.
Hydrophobicity Loss of HTV Silicone Rubbers with different ATH Filler Types under AC Corona Discharges

This paper presents a comparative evaluation of the hydrophobicity performances of high-temperature vulcanizing (HTV) silicone rubber samples having different filler types and filler concentrations. Four different alumina trihydrate (ATH) filler types and three different filler ratios (10, 30, and 50 wt%) are considered. With the base HTV, a total of 13 different samples is exposed to AC corona discharges for two hours to assess the hydrophobicity performance of the samples. For each sample type, four test specimens are used to take more robust results. At specific time intervals, the contact angles of the samples are measured in three different locations. The results show that the specimen with 50 wt% of the precipitated ATH filler has the best performance in terms of hydrophobicity loss under AC corona discharges.
Frequency distribution of the first response time of fire fighting

Arrival of firemen at the fire scene instantly after they receive the alarm is of great significance for controlling the fire and reducing the casualties and property losses.The first response time TF represents the response efficiency of firemen.Fire statistical data of Japan from 1995 to 2003 are analyzed by SPSS and it is found that the frequency of TF fits well with the log-normal distribution,as can be verified by the results of the P-P verification and the U verification.The correlation coefficients of the data fittings are all higher than 0.9. The fire statistical data of a city in China from 2000 to 2009 shows the same law.The expected value of the log-normal distribution represents the statistical average of TF.The results may be used in the optimization model for the location-allocation of fire stations.
Balanced News Neural Network for a News Recommender System

News recommender systems face unique challenges due to the rapidly changing readers’ interests over time. Some of the reader’s interests are long-term, and some are short-term that need to be addressed in a news recommender system. Diversification is also required in a news recommender system to keep readers engaged in the reading process and expose them to various viewpoints. We propose a deep neural network for the news recommendation problem that learns multi-faceted news representations from the news content. The proposed model also learns the reader’s long-term interests from the whole click history and the short-term ones from the click history using LSTMs. The attention mechanism is used to learn a reader’s diversified interests. We give different levels of attention to the news and reader components. Experiments on two news datasets have shown the superiority of our proposed method compared to state-of-the-art methods.
Quality analysis of mobile applications with special focus on security aspects

Smart phones and mobile apps have become an essential part of our daily lives. It is necessary to ensure the quality of these apps. Two important aspects of code quality are maintainability and security. The goals of my PhD project are (1) to study code smells, security issues and their evolution in iOS apps and frameworks, (2) to enhance training and teaching using visualisation support, and (3) to support developers in automatically detecting dependencies to vulnerable library elements in their apps. For each of the three tools, dedicated tool support will be provided, i.e., GraphifyEvolution, VisualiseEvolution, and DependencyEvolution respectively. The tool GraphifyEvolution exists and has been applied to analyse code smells in iOS apps written in Swift. The tool has a modular architecture and can be extended to add support for additional languages and external analysis tools. In the remaining two years of my PhD studies, I will complete the other two tools and apply them in case studies with developers in industry as well as in university teaching.
Design and Performance Evaluation of Channel Coding Schemes for Information Technologies

The article studies the efficiency of channel codes coding. The study covered issues related to determining the energy gain of coding. For this purpose, turbo codes, LDPC codes, polar codes were compared. The work contains the developed schemes of encoders and decoders of channel codes for those developed using a hardware description language (HDL). The results of comparing the resources used for the implementation of encoders and decoders and comparing their performance are obtained. Research indicates a high efficiency of turbo codes in coding schemes. The results of comparing the productivity of different channel codes can be used to design practical coding and decoding schemes in information channels.
Estimating the Rate of Occurrence of Geometric Process With Exponential Distribution

Geometric process (GP) is an important alternative to the Non homogeneous Poisson process (NHPP), in which arrival time is modeled with the trend, in this paper, we consider the problem of parameter estimation for geometric process, when the first arrival is distributed as an Exponential distribution (EXP). Parametric estimation methods including Maximum likelihood (ML), nonparametric estimation method including modified moments (MM), and a semi-parametric estimation method including modified least squares (MLS) chat were used in this paper, to achieve the goal of the paper, the model will be simulated and applied to one the important aspects of life, which is stopping of the gas power plant in Mosul.
Training Automated Test Oracles to Identify Semantic Bugs

Can a machine find and fix a Semantic Bug? A Semantic Bug is a deviation from the expected program behaviour that causes to produce incorrect outputs for certain inputs. To identify this category of bugs, the knowledge on the expected program behaviour is essential. The reason is that a program with a semantic bug does not fail (i.e., crash or hang) in the middle of the execution in most scenarios. Thus, only a human (a user or a developer) knowing the correct program behaviour can detect this kind of bug by observing the output. However, identifying bugs solely through human effort is not practical for all software. A Test Oracle is any procedure used to differentiate the correct and incorrect behaviours of a program. This dissertation mainly focuses on developing learning techniques to produce Automated Test Oracles for programs with semantic bugs. Also, discovering methods to incorporate human knowledge effectively for the learning techniques is another concern. The automated test oracles could make semantic bug detection more efficient. Also, such test oracles could guide Automated Program Repair tools to generate more accurate fixes for semantic bugs.