Miracle-dz/UniFAR-FTUs huggingface dataset:
Accuracy Examination of the SDCM Augmentation System in Aerial Navigation

The paper presents a modified algorithm for determining the accuracy parameter of the system for differential corrections and monitoring (SDCM) navigation solution in air navigation. For this purpose, a solution to determine the resultant accuracy parameter was proposed by using two on-board global navigation satellite system (GNSS) receivers. The mathematical algorithm takes into account the calculation of a single point positioning accuracy for a given GNSS receiver and a weighting factor combining the position error values. The weighting factor was determined as a function of the number of tracked GNSS satellites used in the SDCM single point positioning solution. The resultant accuracy parameter was expressed in ellipsoidal coordinates BLh (B—latitude, L—longitude, h—ellipsoidal height). The study used GNSS kinematic data recorded by two on-board receivers: Trimble Alloy and Septentrio AsterRx2i, located in a Diamond DA 20-C1 aircraft. The test flight was performed near the city of Olsztyn in north-eastern Poland. Calculations and analyses were performed using RTKLIB software and the Scilab environment. On the basis of the performed tests, it was found that the proposed algorithm for SDCM system allows for improvement in the determination of the resultant accuracy value by 56–80% in relation to the results of position errors from a single GNSS receiver. Additionally, the proposed algorithm was tested for the European Geostationary Navigation Overlay Service (EGNOS) system, and in this case, the improvement in the accuracy parameter was even better and was in the range of 69–89%. The resulting SDCM and EGNOS positioning accuracy met the International Civil Aviation Organization (ICAO) certification requirements for SBAS systems in air navigation. The mathematical algorithm developed in this work was tested positively and can be implemented within the SBAS augmentation system in air navigation.
Enzyme activity after applying alkaline biosolids to agricultural soil

Abstract Municipal wastewater biosolids are nutrient-rich residuals with potential as crop fertilizer, if their alkalinity does not adversely affect soil biochemical processes. This study assessed the potential soil enzyme activity after three annual applications of biosolids in a conventionally tilled field under silage corn (Zea mays L.). Biosolids were municipal wastewater sludge treated by mesophilic anaerobic digestion, lime stabilization, or composting, compared with urea fertilizer and an unfertilized control. Generally, the potential soil enzyme activity did not change with biosolids application, but the N-acetylglucosaminidase activity increased in soil amended with lime-stabilized biosolids, which also had higher soil pH and greater soil NH4+ concentration.
A PARALLAX-BASED DISTANCE ESTIMATOR FOR SPIRAL ARM SOURCES

The spiral arms of the Milky Way are being accurately located for the first time via trigonometric parallaxes of massive star-forming regions with the Bar and Spiral Structure Legacy Survey, using the Very Long Baseline Array and the European VLBI Network, and with the Japanese VLBI Exploration of Radio Astrometry project. Here we describe a computer program that leverages these results to significantly improve the accuracy and reliability of distance estimates to other sources that are known to follow spiral structure. Using a Bayesian approach, sources are assigned to arms based on their (l, b, v) coordinates with respect to arm signatures seen in CO and H i surveys. A source's kinematic distance, displacement from the plane, and proximity to individual parallax sources are also considered in generating a full distance probability density function. Using this program to estimate distances to large numbers of star-forming regions, we generate a realistic visualization of the Milky Way's spiral structure as seen from the northern hemisphere.
Mathematical Estimation of Axial Length Increment in the Control of Myopia Progression

This study aims to evaluate the existing mathematical approach for the theoretical estimation of axial length (AL) in a cross-sectional study, developing a new mathematical model and testing it in a longitudinal sample. Many professionals do not have a device to measure the AL due to clinic space and cost of equipment. However, this parameter plays an important role in the assessment of myopia progression to monitor treatment effects with myopia control strategies. First, a cross-sectional study based on the mathematical equation proposed by Morgan was performed. The AL was estimated based on the mean values of keratometry and spherical equivalent in 1783 subjects (52% female), aged 14.6 ± 4.6 years (6 to 25 years), of whom 738 were myopic, 770 emmetropic and 275 hyperopic. On average, the AL estimated with the Morgan formula was 0.25 ± 0.48 mm larger than the real AL value (95% limits of agreement: +0.70 to −1.20 mm). The study by gender, ametropia, type of astigmatism and age showed statistically significant differences between the real AL and predicted AL_Morgan (r > 0.750, spearman). Based on the previous sample, a multiple linear regression was applied, and a new mathematical model was proposed. The model was tested on a longitudinal sample of 152 subjects whose mean age was 13.3 ± 3.1 years (9 to 24 years) and of whom 96 were female (64%). The sample consisted of 46 myopes, 82 emmetropes and 24 hyperopes. The longitudinal study of the differences in axial length at one year between the models showed no statistically significant differences and that the mathematical equations are valid for estimating differences in axial increment for ages between 9 and 24 years, despite errors in the predicted value for axial length.
Durability Evaluation of Concrete in Cold and Arid Regions Based on Grey Relational Theory

Aiming at the outstanding problem of concrete durability in cold and arid regions, the Datonghe-Qingwangchuan Diversion Project in Gansu Province, China, was used as a typical research area, and erosion products were determined by field sampling and laboratory XRD analysis. Three durability evaluation indices, namely, the mass loss rate, relative dynamic elastic modulus (RDEM), and compressive strength loss rate, were measured via indoor accelerated testing. Based on grey relational theory, a concrete durability evaluation model was constructed. The critical failure values of the three evaluation indices were introduced as a set of data to optimize the model and determine the grey relational degree of each group of concrete specimens under different working conditions. The results show that using the test results and the optimized grey relational analysis evaluation model, the concrete specimens mixed with an air-entraining agent have strong resistance to composite erosion. The durability of concrete specimens with an air-entraining agent content of 0.016% and fly ash content of 15% is better, and a high content (30%) of fly ash accelerates the damage of concrete specimens. The model calculations are consistent with the test results. This method can solve the problem of the durability of concrete specimens in the whole test cycle not being fully evaluated. The results of the study provide useful references for concrete mix proportion optimization and durability evaluation problems.
A hybrid approach for enhancing and optimizing the power quality and power flow in Smart Grid Connected System

This article proposes a hybrid approach for power flow management and power quality (PQ) improvement in smart grid (SG) system. The proposed methodology is designed into two phases, power flow management is the first stage and power quality improvement is the second stage of the system. The key purpose of the proposed method is “to regulate that power flow depends on variation of source and load side parameters deliver the highest PQ. ” The initial phase of power flow management is executed by using Improved Binary Sailfish Optimizer (IBSFO) approach. The control signal is recognized by the IBSFO approach against active and reactive power variation. The second phase of power quality enhancement is implemented by K2ORBFNN, which is the combination of Kho‐Kho optimization (KKO) and Radial Basis Function Neural Network (RBFNN). The gain parameter of the proportional integral (PI) controller is tuned based on load current, DC link, and voltage sources using K2ORBFNN approach. The prediction of optimal control signal minimizes the error which is obtained by RBFNN approach. The proposed method is utilized to attain compensating non‐linear load current harmonics, compensating reactive load power requirement, compensating unbalanced load current with neutral current. Finally, the performance of proposed system is executed in the MATLAB platform and performance is compared with existing techniques. The efficiency under the trails of 100, 200, 500, and 1000 attains 99.1673%, 99.4567%, 99.8402%, and 99.9879%.
Two new Nesticus Thorell, 1869 (Araneae: Nesticidae) from caves in northwest Georgia, USA

Abstract. We describe two new Nesticus Thorell, 1869 from Walker County, Georgia, USA. Nesticus lula sp. nov. is known from two caves on the eastern edge of Lookout Mountain and N. cressleri sp. nov. is known from three caves on Pigeon Mountain. Morphological and molecular evidence indicates the distinctiveness of both species when compared to other Nesticus from the southern Appalachians. Nesticus lula has reduced eyes and N. cressleri is eyeless. Both species are of conservation concern, as they are known from only a handful of sites spanning extremely limited ranges. This work contributes to our understanding of cave biodiversity in Georgia and of the Nesticus radiation in the southern Appalachians.
Podcasts: A generator of non-formal learning

The present study examines the relationship between the use of podcasts (mp3 files) as a non-formal learning tool. The study´s epistemological origins lie in Dewey's pragmatism and learning and reflection theory, including the learning approach at University College of Northern Denmark’s (UCN) “Reflective Practice-based Learning” (RPL). This paper focuses on how podcasts can increase students’ learning and reflection skills by using podcasts as a generator for non-formal learning. The study is based on two different classes that attend an extended course in digital technologies and project management at the Danish University of Applied Science (UCN). The study applies integrated mixed-method data collection: observations, a quantitative survey, and semi-structured interviews. The observations were carried out during four (project management) and seven (digital technologies) full-day lectures in two different classes. These offered an insight into the extent to which the students acquired knowledge by listening to podcasts between classes. The quantitative data consisted of a survey of 65 students, all of whom participated in the courses. The survey was performed as a part of the evaluation at the final course lectures. The semi-structured interviews (ten in all) were used to investigate how the use of podcasts affects students' reflective skills. Ten semi-structured interviews were conducted. The data in this study finds that podcasts/podcasting can have a positive effect on students’ non-formal learning in higher education. Established on the findings, there is evidence indicating podcasts as a supplement in higher education can increase students´ motivation toward non-formal learning. The study reveals that podcasts hold the potential to stimulate the student's non-formal learning and increase the students’ reflective skills. Based on this evidence, further research is suggested e.g. studies that include an extended investigation on the benefits of students’ non-formal learning by using podcasts.
Analysis of the velocity-distance diagrams in the presence of the Great Attractor

In the present paper we study the appearance of velocity-distance diagrams, when the distances are calculated by either the direct or the inverse Tully-Fisher (TF) relation and when the velocity field is generated by a spherically symmetric mass concentration, and try to understand some contradicting reports on the kinematics close to the Great Attractor (GA). Since the application of Malmquist corrections for the distance moduli is not a straightforward task in the presence of a general velocity field, we also searched for methods for obtaining a minimally biased subsample from the data with direct TF-distance and tested the influence of the chosen inverse relation
Influence of end-effect and end-winding on the electromagnetic losses and efficiency in high speed permanent magnet machines

Permanent-magnet excitation machines (SPMMs) having mounted magnet on the outer surface of their rotor are preferred for high speed applications such as turbochargers, mechanical turbo-compounding systems, racing engines and fuel pumps, over other types of machines including induction and switched-reluctance machines, since the SPMMs integrate the features of high torque density, compact rotor structure, high reliability and simple structure. However, in the SPMMs, due to the need for a retaining sleeve for the rotor, a large magnetic airgap results and consequently a large magnet thickness is required, hence the magnetic end-effect is relatively high. On the other hand, the use of an overlapping distributed winding leads to a significantly large end-winding length. Hence, the end-effect and the end-winding influences on the performances of a high-speed SPMM is considered in this paper. With a view to get the impact of the end-effect, a comparison between three-dimensional (3D-FEA) results and counterparts two-dimensional finite element analyses (2D-FEA) have been conducted. Results show that, higher efficiency at low torque and low speed due to the low electromagnetic losses and at high speeds due to the high flux-weakening capability are seen when the influences of end-effect as well as end-winding are taken into account.
Combined electronic medical records and gene polymorphism characteristics to establish an anti-tuberculosis drug-induced hepatic injury (ATDH) prediction model and evaluate the prediction value

Background Anti-tuberculosis drug-induced hepatic injury (ATDH) lacks specific diagnostic markers. The characteristics of gene polymorphisms have been preliminarily used for the risk classification of ATDH, and the activation of Pregnane X receptor/aminole-vulinic synthase-1/forkhead box O1 (PXR/ALAS1/FOXO1) axis is closely related to ATDH. Therefore, we consider combining general clinical features of the electronic medical record, laboratory indications, and genetic features of key genes in this axis for predictive model construction to help early clinical diagnosis and treatment. Methods The general characteristics derived from the Hospital Information System (HIS) medical record system, the biochemical tests and hematology tests were detected by Roche automatic biochemical immunoassay analyzer cobas8000 and Sysmex automatic hemocytometer XE2100. The single nucleotide polymorphisms (SNPs) genotyping work was conducted with a custom-designed 48-plex SNP scan® TM Kit. A total of 746 cases were included which were divided into training set and validation set according to the ratio of 3:2 randomly. Taking the occurrence of confirmed ATDH as the outcome variable, lasso regression and logistic regression were used to identify the predictors preliminarily. alanine aminotransferase, aspartate aminotransferase, monocyte, uric acid, albumin, fever, the polymorphisms of rs4435111 (FOXO1) and rs3814055 (PXR) were chosen from all variables to combine the predictive model. The goodness of fit, predictive efficacy, discrimination, and consistency, and clinical decision curve analysis was used to assess the clinical applicability of the models. Results The best model had a discriminant efficacy C-index of 0.8164, a sensitivity of 34.25%, specificity of 97.99%, a positive predictive value of 78.13% and negative predictive value of 87.69%, the two-tailed value of Spiegelhalter Z test of consistency test S:P =0.896, maximum absolute difference Emax =0.147, and average absolute difference Eave =0.017. In the validation set, performance was close. The clinical decision curve showed the clinical applicability of the prediction model when the prediction risk threshold was between 0.1 and 0.8. Conclusions The ATDH prediction model was constructed using a machine learning approach, combining general characteristics of the study population, laboratory indications, and SNP features of PXR and FOXO1 genes with good fit and certain predictive value, and has potential and value for clinical application.
Hydrodynamic Performance of a Floating Offshore Oscillating Water Column Wave Energy Converter

A floating oscillating water column (OWC) wave energy converter (WEC) supported by mooring lines can be modelled as an elastically supported OWC. The main objective of this paper is to investigate the effects of the frequency ratio on the performance of floating OWC (oscillating water column) devices that oscillate either vertically or horizontally at two different mass ratios (m = 2 and 3) through two-dimensional computational fluid dynamics simulations. The frequency ratio is the ratio of the natural frequency of the system to the wave frequency. Simulations are conducted for nine frequency ratios in the range between 1 and 10. The hydrodynamic efficiency achieves its maximum at the smallest frequency ratio of 1 if the OWC oscillates horizontally and at the largest frequency ratio of 10 if the OWC oscillates vertically. The frequency ratio affects the hydraulic efficiency of the vertical oscillating OWC significantly stronger than that of the horizontal oscillating OWC, especially when it is small. The air pressure and the volume oscillation in OWC is not affected much by the horizontal motion of the OWC but is significantly affected by the vertical motion, especially at small frequency ratios.
Community-Based Interventions for the Prevention and Control of Cutaneous Leishmaniasis: A Systematic Review

We reviewed the evidence on community-based interventions for the prevention and control of cutaneous leishmaniasis (CL). Community initiatives tailored towards awareness and mobilisation are regarded as a priority area in the Neglected Tropical Disease Roadmap 2021–2030 by the World Health Organization. We searched nine electronic databases for intervention-based studies. Two independent reviewers screened and assessed the articles for methodological quality using predefined criteria. We conducted a meta-analysis using a random effects model, along with narrative synthesis. Thirteen articles were eligible for inclusion, of which 12 were quantitative studies (quasi-experimental with control group and pre-post interventions) and one qualitative study. All articles reported on health education interventions aimed at changing people’s knowledge, attitudes, and practices (KAP) in relation to CL. Participant groups included students, mothers, housewives, volunteer health workers, and residents in general. An increased score was recorded for all outcomes across all interventions: knowledge (SMD: 1.85, 95% CI: 1.23, 2.47), attitudes (SMD: 1.36, 95% CI: 0.56, 2.15), and practices (SMD: 1.73, 95% CI: 0.99, 2.47). Whilst our findings show that educational interventions improved people’s knowledge, attitudes, and practices about CL, we argue that this approach is not sufficient for the prevention and control of this disease. Knowledge does not always translate into action, particularly where other structural barriers exist. Therefore, we recommend the design of more innovative community-based interventions with a broader focus (e.g., stigma, financial barriers, and healthcare access).
Mechanisms for generating realistic annotated Internet topologies

Researchers involved in designing network services and protocols rely on results from simulation and emulation environments to evaluate correctness, performance and scalability. To better understand the behavior of these applications and to predict their performance when deployed across the Internet, the generated topologies that serve as input to simulated and emulated environments must closely match real network topologies with respect to a wide range of graph metrics proposed in the literature. Values for a particular graph metric may capture a graph's resilience to failure or its routing efficiency. Unfortunately, there are typically no known algorithms to generate graphs matching one or more proposed metrics and there is little understanding of the relationships among individual metrics or their applicability to different settings. Furthermore, the generated topologies must also be annotated with observed network characteristics that, for instance, include latencies for the edges in a router- level graph, and AS membership for the nodes in the graph. Finally, it should be possible to rescale a given topology to a variety of sizes while still maintaining its essential characteristics. We present a new, systematic approach for analyzing and synthesizing network topologies. We first introduce a unifying series of properties, the dK-series of probability distributions, specifying all degree correlations within d-sized subgraphs of a given graph G. Increasing values of d capture progressively more properties of G and, in the limit, describes the graph in its entirety. Using the dK- series, we construct random graphs and demonstrate that these graphs reproduce, with increasing accuracy, all important metrics of measured and modeled Internet topologies. The nature of the dK-series implies that it will also capture any future metric that may be proposed. Further, we scale the generated graphs to a wide range of sizes while still preserving the graph's structure. Finally, we propose techniques to annotate these topologies and specifically describe our scheme to annotate Internet router graphs with AS-membership as well as whether a router is peering or internal
Bioactive Hydroxyapatite-Magnesium Phosphate Coatings Deposited by MAPLE for Preventing Infection and Promoting Orthopedic Implants Osteointegration

In this study, we used the matrix-assisted pulsed laser evaporation (MAPLE) technique to obtain hydroxyapatite (Ca10(PO4)6(OH)2) and magnesium phosphate (Mg3(PO4)2) thin coatings containing bone morphogenetic protein (BMP4) for promoting implants osteointegration and further nebulized with the antibiotic ceftriaxone (CXF) to prevent peri-implant infections. The samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), selected area electron diffraction (SAED), infrared microscopy (IRM) and Fourier-transform infrared spectroscopy (FT-IR). Furthermore, the antimicrobial properties were evaluated on Staphylococcus aureus biofilms and the cytocompatibility on the MC3T3-E1 cell line. The obtained results proved the potential of the obtained coatings for bone implant applications, providing a significant antimicrobial and antibiofilm effect, especially in the first 48 h, and cytocompatibility in relation to murine osteoblast cells.