Miracle-dz/UniFAR-FTUs huggingface dataset:
Tourists Perceptions of Road Safety in Malta

The aim of this research is to understand tourists perceptions about road safety in the Maltese islands. Its objective is to determine the issues related to road safety that are experienced by tourists visiting the country and to suggest interventions that might improve road safety in local tourist areas. Road accidents can have far-reaching effects including death and serious injuries. Despite tourism being one of the largest contributors towards the GDP of Malta, there is a lack of research that studies the effect of road safety on tourists visiting the country.A qualitative research design using narrative inquiry was utilized in order to understand the experiences and perceptions of three participants. A collaborative narrative was written for each participant and, following the process of thematic narrative analysis, a total of three common narrative themes together with four sub-themes were identified. These highlight three main factors which affect tourists perceptions of road safety in Malta: (1) excessive amount of traffic on Maltas roads; (2) lack of discipline by Maltese road users; and (3) inadequate pedestrian zones. Conclusions drawn from this study indicate that these issues can be addressed through policy changes, such as increasing pedestrian zones and enhancing pedestrian safety within the existing urban context, more bicycle lanes in the Maltese road network, improving the frequency and reliability of the public transport service, and stricter enforcement. Finally, recommendations for further research on the topic of road safety within the local context are discussed.
In Silico Characterization of RNASEH2A Pathogenic Variants and Identification of Novel Splice Site Donor Variant c.549+1G>T in Indian Population

Background Aicardi-Goutieres syndrome (AGS) is a genetic disorder that has variable manifestations including neurological, immunological, and sometimes other system involvement in various combinations. Considering the high genetic and clinical diversity of AGS and the importance of RNASEH2 complex in the biological system, it is important to take a systematic approach to delineate the genetic diagnosis and impact of missense mutations. Methods Clinical targeted gene sequencing followed by Sanger validation was performed in an individual with the clinical features of AGS. Protein modeling studies of all the reported RNASEH2A missense variants till date were performed using freely available web servers BioGrid, ShinyGO. Protein structures were visualized using Pymol. Results and discussion We identified a novel homozygous splice site donor variant c.549+1G>T in RNASEH2A. Furthermore protein-interactome studies identifiedpotential genetic interactors that include RNASEH2A, RNASEH2B, TYMS, RNASEH2C, RPA1, ORC3, ORC2, CDC6, PCNA, LIG1, PRIM1, RFC2, DUT, GINS1, MCM7, FEN1, MCM4, GINS2, CDK4, and MCM5. Identified genes were mapped to specific pathways using SHINY GO. DNA replication and cell cycle, centrosome cycle, post-replication repair, nucleic acid and metabolic process, cellular response to stress, DNA metabolic process, nucleic acid phosphodiester bond hydrolysis, RNA phosphodiester bond hydrolysis, and DNA biosynthetic process were identified as the linked pathways with the prioritized genes. Conclusion In conclusion, a sophisticated genotype and phenotype correlation followed by linking the genes to the key biological pathways opens new avenues to understand disease pathology and plan for therapeutic interventions.
Some aspects of the influence of the vertical wind speed gradient on the blade aerodynamics loads in high class wind generators

The powerful wind generators, producing electric power on the order of megawatts are with impressive sizes. The studies on the interaction between the air flow and the wind turbine usually assume the airflow as homogeneous in vertical direction. While for smaller wind turbines this assumption does not lead to significant inaccuracies, for powerful generators the vertical gradient of the wind velocity causes a dependence of the aerodynamic interaction from the angle of rotation of the propeller and leads to a significant cyclic variability of the forces and moments acting on the blades, even for a flow considered as stationary in time. The study of this problem is important for strength loads and fatigue calculations as well as for an implementation of an individual pitch-control of the blades, which could allow a synthesis of a regulation depending on the angular position of the turbine. This could contribute to higher performance and higher reliability.
Thermally tunable water-substrate broadband metamaterial absorbers

The naturally occurring water has frequency dispersive permittivity at microwave frequencies and thus is a promising constituent material for broadband absorbers. Here, we develop water as the dielectric spacer in the substrate of metal-backed metamaterial (MM) absorbers. The designed substrate is a hybrid of water and a low-permittivity dielectric material. Such a design allows tight packaging of water and easy fabrication of the absorber. We obtain broadband absorption at temperatures of interest by designing the hybrid substrate and MM inclusions. Additionally, the absorption performance of the water-substrate MM absorbers could be tunable according to the environment temperature. We experimentally demonstrate the broadband and thermally tunable absorption performance. We expect that water could replace dielectric layers in other structural MM absorbers to achieve the broadband and thermally tunable absorption performance.
The Coach-created Motivational Climate in Professional Football

The purpose of this study was to investigate how three Italian professionalcoaches who have coached at the highest level of European football (Serie A in Italy)motivate their players. Specific attention was given to the type of motivational climatethat the coach tries to create as well as the importance of the relationship between theplayer and coach and the subsequent effect on motivational levels. Therefore, the studylooked to provide further insight into the importance of the player-coach relationship inaccordance with the self-determination theory. The study employed a qualitative researchdesign. Semi-structured interviews were recorded and transcribed, and the data wasanalysed utilizing a thematic analysis approach. The findings of the study show that evenat the highest levels of professional football, coaches look to create a mastery motivationalclimate. The importance of a strong player-connection built on mutual trust, respect, andeffective feedback was an underpinning theme throughout the study. Showing empathy,providing the perception of choice, and initiative-taking opportunities as well as a rationalefor tasks were some of the methods through which the coaches tried to increase theirplayers perception of autonomy, competence, and relatedness.
A configuration model for correlation matrices

Correlation matrices are a major type of multivariate data. To examine properties of a given correlation matrix, a common practice is to compare the same quantity between the original correlation matrix and reference correlation matrices, such as those derived from random matrix theory, that partially preserve properties of the original matrix. We propose a model to generate such reference correlation and covariance matrices for the given matrix. Correlation matrices are often analysed as networks, which are heterogeneous across nodes in terms of the total connectivity to other nodes for each node. Given this background, the present algorithm generates random networks that preserve the expectation of total connectivity of each node to other nodes, akin to configuration models for conventional networks. Our algorithm is derived from the maximum entropy principle. We will apply the proposed algorithm to measurement of clustering coefficients and community detection, both of which require a null model to assess the statistical significance of the obtained results.
Cybersecurity Through Thesis in Laurea University of Applied Sciences

Information technology and its applications surround us and those have become crucial to our lives. However, the understanding of the digital world is not as strong. Successful and functional cybersecurity is a vital component for the defence of a civilised society. This study looks at how cybersecurity has been handled in thesis written at one University of Applied Sciences and what kind of topics have been chosen by thesis writers, and what is written about cybersecurity in them to understand how cybersecurity is seen in higher education. The goal of this paper was to find out how cybersecurity has been handled in theses and what kind of topics have been chosen by thesis writers. The two research questions are: what theses have been published that handle cybersecurity; and how does cybersecurity in them? As typical of a case study, attention is paid to a small number of cases (n = 15) attempting to describe the phenomenon they represent. Of the fifteen theses, two were master’s and thirteen bachelor’s theses, and mostly completed in Safety, Security and Risk Management, Security Management, and Business information technology programmes. Based on the results in this case, cyber security is being examined or developed from several, different points of view and in multidisciplinary ways.
Discovery of a Hot Symbiotic Star in the Cold Antarctic Sky: Symbiotics Are Outliers in SkyMapper uvgriz Photometry

Discovery of a hot symbiotic star in the cold antarctic sky: symbiotics are outliers in SkyMapper uvgriz photometry Adrian B. Lucy, ∗ J. L. Sokoloski, 2 N. E. Nuñez, C. Wolf, 5 T. Bohlsen, and G. J. M. Luna 8, 9 1Columbia University, Dept. of Astronomy, 550 West 120th Street, New York, NY 10027, United States 2Large Synoptic Survey Telescope Corporation, 933 North Cherry Ave, Tucson, AZ 85721, United States 3Instituto de Ciencias Astronómicas, de la Tierra y del Espacio (ICATE-CONICET), Av. España Sur 1512, J5402DSP, San Juan, Argentina 4Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611, Australia 5ARC Centre of Excellence for All-sky Astrophysics (CAASTRO) 6Mirranook Observatory, Boorolong Rd, Armidale, NSW, 2350, Australia 7CONICET-Universidad de Buenos Aires, Instituto de Astronomı́a y F́ısica del Espacio (IAFE), Av. Inte. Güiraldes 2620, C1428ZAA, Buenos Aires, Argentina 8Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Buenos Aires, Argentina 9Universidad Nacional Arturo Jauretche, Av. Calchaqúı 6200, F. Varela, Buenos Aires, Argentina
Application of Machine Learning Prediction of Individual SARS-CoV-2 Vaccination and Infection Status to the French Serosurveillance Survey From March 2020 to 2022: Cross-Sectional Study

Background The seroprevalence of SARS-CoV-2 infection in the French population was estimated with a representative, repeated cross-sectional survey based on residual sera from routine blood testing. These data contained no information on infection or vaccination status, thus limiting the ability to detail changes observed in the immunity level of the population over time. Objective Our aim is to predict the infected or vaccinated status of individuals in the French serosurveillance survey based only on the results of serological assays. Reference data on longitudinal serological profiles of seronegative, infected, and vaccinated individuals from another French cohort were used to build the predictive model. Methods A model of individual vaccination or infection status with respect to SARS-CoV-2 obtained from a machine learning procedure was proposed based on 3 complementary serological assays. This model was applied to the French nationwide serosurveillance survey from March 2020 to March 2022 to estimate the proportions of the population that were negative, infected, vaccinated, or infected and vaccinated. Results From February 2021 to March 2022, the estimated percentage of infected and unvaccinated individuals in France increased from 7.5% to 16.8%. During this period, the estimated percentage increased from 3.6% to 45.2% for vaccinated and uninfected individuals and from 2.1% to 29.1% for vaccinated and infected individuals. The decrease in the seronegative population can be largely attributed to vaccination. Conclusions Combining results from the serosurveillance survey with more complete data from another longitudinal cohort completes the information retrieved from serosurveillance while keeping its protocol simple and easy to implement.
Shape Analysis of Defect-Laden Data

Shape analysis is a well-established tool for processing surfaces. It is often a first step in performing tasks such as segmentation, symmetry detection, and finding correspondences between shapes. Shape analysis is traditionally employed on well-sampled surfaces where the geometry and topology is precisely known. When the form of the surface is that of a point cloud containing nonuniform sampling, noise, and incomplete measurements, traditional shape analysis methods perform poorly. Although one may first perform reconstruction on such a point cloud prior to performing shape analysis, if the geometry and topology is far from the true surface, then this can have an adverse impact on the subsequent analysis. Furthermore, for triangulated surfaces containing noise, thin sheets, and poorly shaped triangles, existing shape analysis methods can be highly unstable. This thesis explores methods of shape analysis applied directly to such defect-laden shapes. We first study the problem of surface reconstruction, in order to obtain a better understanding of the types of point clouds for which reconstruction methods contain difficulties. To this end, we have devised a benchmark for surface reconstruction, establishing a standard for measuring error in reconstruction. We then develop a new method for consistently orienting normals of such challenging point clouds by using a collection of harmonic functions, intrinsically defined on the point cloud. Next, we develop a new shape analysis tool which is tolerant to imperfections, by constructing distances directly on the point cloud defined as the likelihood of two points belonging to a mutually common medial ball, and apply this for segmentation and reconstruction. We extend this distance measure to define a diffusion process on the point cloud, tolerant to missing data, which is used for the purposes of matching incomplete shapes undergoing a nonrigid deformation. Lastly, we have developed an intrinsic method for multiresolution remeshing of a poor-quality triangulated surface via spectral bisection.
Impact of Spices on Micronutrients, Phenolic Compounds, in Vitro and in Vivo Antioxidant Potentialities in Eggplant Leaves Cooked with Water

: Eggplant leaves ( Solanum macrocarpon ) are rich in nutrients which are unfortunately lost during cooking. To reduce micronutrients losses and enhance antioxidant potentialities, they were cooked in water for 30 minutes with onion, ginger and Guinea pepper. The analyzes focused on the determination of vitamin C, β-carotene, phenolic compounds, free radical-scavenging and lipid peroxidation inhibitory activities. In Wistar rats, thiobarbituric acid reactive substances (TBARS), superoxide dismutase (SOD) and glutathione peroxidase activities were also evaluated during 1 month. The results indicated that vitamin C remained low in eggplant leaves cooked with onion and spices. Cooked eggplant market leaves β-carotene content (187.11 µg/100 FM) increase from 447.43 µg/100 FM (with onion) to 905.44 µg/100 FM (with Guinea pepper). Ginger, Guinea pepper and onion improved eggplant field leaves free radical scavenging activities, which previous IC 50 value (12.00 µg/ml) became 0.67, 0.83 and 3.08 µg/ml respectively. TBARS rate increased only for rats which received eggplant market leaves cooked with onion from 0.02 to 0.03 nmol/ml. SOD activities increased during the firsts 2 weeks of experiment. Glutathione peroxidase activities is high in serum of rats which received eggplant field leaves cooked with onion (18.70 nmol/min/ml). Onion, ginger and Guinea pepper enhance eggplant antioxidant potentialities during cooking.
Near-field mean flow dynamics of a cylindrical canopy patch suspended in deep water

The time-averaged flow dynamics of a suspended cylindrical canopy patch with a bulk diameter of $D$ is investigated using large-eddy simulations (LES). The patch consists of $N_{c}$ constituent solid circular cylinders of height $h$ and diameter $d$ , mimicking patchy vegetation suspended in deep water ( $H/h\gg 1$ , where $H$ is the total flow depth). After validation against published data, LES of a uniform incident flow impinging on the canopy patch was conducted to study the effects of canopy density ( $0.16\leqslant \unicode[STIX]{x1D719}=N_{c}(d/D)^{2}\leqslant 1$ , by varying $N_{c}$ ) and bulk aspect ratio ( $0.25\leqslant AR=h/D\leqslant 1$ , by varying $h$ ) on the near-wake structure and adjustment of flow pathways. The relationships between patch geometry, local flow bleeding (three-dimensional redistribution of flow entering the patch) and global flow diversion (streamwise redistribution of upstream undisturbed flow) are identified. An increase in either $\unicode[STIX]{x1D719}$ or $AR$ decreases/increases/increases bleeding velocities through the patch surface area along the streamwise/lateral/vertical directions, respectively. However, a volumetric flux budget shows that a larger $AR$ causes a smaller proportion of the flow rate entering the patch to bleed out vertically. The global flow diversion is found to be determined by both the patch geometrical dimensions and the local bleeding which modifies the sizes of the patch-scale near wake. While loss of flow penetrating the patch increases monotonically with increasing $\unicode[STIX]{x1D719}$ , its partition into flow diversion around and beneath the patch shows a non-monotonic dependence. The spatial extents of the wake, the flow-diversion dynamics and the bulk drag coefficients of the patch jointly reveal the fundamental differences of flow responses between suspended porous patches and their solid counterparts.
Investigating the Levels of Liver Lipogenic and Lipolytic Enzymes in Rat with High-Fat Diet and Sucrose Solution Underwent Progressive Resistance Training

Objective: Consuming too much fat or carbohydrates stimulates lipogenesis and excess fat is stored in non-fat tissues, including the liver, and manifests as obesity and fatty liver disease. This study aimed to investigate the effect of eight weeks of progressive resistance training (PRT) on the liver levels of some enzymes affecting lipid metabolism in rats fed a high-fat diet and sucrose solution. Materials and Methods: Twenty-four male wistar rats with 5 weeks of age were randomly divided into two groups: standard diet (SD) (n=8) and high-fat diet and sucrose solution (HFDS) (n=16). Twelve weeks later, HFDS group was divided into two groups: sedentary (HS) and PRT (HPRT). The PRT program was implemented 3 days a week for 8 weeks. Gene expression of AMPKα1, SCD-1, ATGL and FASN enzymes affecting lipid metabolism in liver tissue and its fat content were investigated. Results: HFDS significantly increased the body weight (P: 0.001) and significantly decreased the liver expression of ATGL and FASN (P: 0.001, P: 0.011). Eight weeks of PRT did not show a significant difference in the expression of AMPKα1, SCD-1, ATGL and FASN genes. Rats fed HFDS had considerably higher levels of triglyceride (TG) and total cholesterol (TC) in their liver tissue (P: 0.004, P: 0.001) and PRT did not affect them (P: 0.959, P: 0.809 respectively). Conclusion: It seems that eight weeks of PRT will not change liver lipid metabolism enzymes. Therefore, modifying the diet and changing it, will probably show different results after PRT.
Improved hochwald construction of unitary matrix codebooks via eigen coordinate transformations

FIELD: physics; communications. SUBSTANCE: invention relates to wireless communication systems. More specifically, versions of the invention relate to design and using codebooks based on unitary matrices. The method of making a codebook involves deriving a first codeword P 1 in Euclidean coordinates, transforming the first codeword to eigen coordinates, applying Hochwald construction to the first codeword in eigen coordinates to obtain several codewords in eigen coordinates and transforming the several codewords in eigen coordinates to several codewords in Euclidean coordinates to form the codebook. EFFECT: making codebooks which are closer to optimum codebooks, which enable efficient storage and extraction of codewords. 22 cl, 4 dwg, 2 tbl
Adaptive backstepping neural control of state‐delayed nonlinear systems with full‐state constraints and unmodeled dynamics

In this paper, the problem of adaptive neural control is discussed for a class of strict‐feedback time‐varying delays nonlinear systems with full‐state constraints and unmodeled dynamics, as well as distributed time‐varying delays. The considered nonlinear system with full‐state constraints is transformed into a nonlinear system without state constraints by introducing a one‐to‐one asymmetric nonlinear mapping. Based on modified backstepping design and using radial basis function neural networks to approximate the unknown smooth nonlinear function and using a dynamic signal to handle dynamic uncertainties, a novel adaptive backstepping control is developed for the transformed system without state constraints. The uncertain terms produced by state time delays and distributed time delays are compensated for by constructing appropriate Lyapunov‐Krasovskii functionals. All signals in the closed‐loop system are proved to be semiglobally uniformly ultimately bounded. A numerical example is provided to illustrate the effectiveness of the proposed design scheme.
Study on Fault Feature Extraction of Rolling Bearing Based on Improved WOA-FMD Algorithm

The vibration signal of rolling bearing fault is nonlinear and nonstationary under the interference of background noise, and it is difficult to extract fault features from it. When feature mode decomposition is used to analyze signals, prior parameter settings can easily affect the decomposition results. Therefore, a fault feature extraction method based on improved whale optimization algorithm is proposed to optimize feature modal decomposition parameters. The improved WOA integrates Lévy flight and adaptive weight, and envelope entropy is used as fitness function to optimize feature modal decomposition parameters. The feature mode decomposition of the original signal is performed using the optimal combination of parameters to obtain multiple IMF components. The optimal IMF component envelope demodulation analysis is selected according to the kurtosis value, and the fault feature is extracted through the envelope spectrum. Comparing the LMWOA method with PSO and WOA methods by simulated and experimental signals, the results show that the optimization speed of LMWOA is faster than that of other methods. Compared with CEEMD, VMD, and FMD methods, the improved WOA-FMD method has higher fault feature ratio and can accurately extract fault features under noise interference. This method can effectively solve the parameter adaptive ability and improve the accuracy of fault diagnosis, which has practical significance.