Miracle-dz/UniFAR-FTUs huggingface dataset:
Serum Oxytocin Levels in Patients with Ankylosing Spondylitis and Non-Radiographic Axial Spondyloarthritis and their Association with Disease Activity

ABSTRACT Objectives Spondyloarthritis refers to a group of chronic inflammatory diseases that particularly involve the sacroiliac joints and spine but may also have an influence on extra-articular involvement in some patients. Oxytocin is a peptide hormone released from the hypothalamus and stored in the pituitary gland. It is known to have anti-inflammatory effects. The aim of this study was to investigate the serum levels of oxytocin and their potential association with disease activity and spinal mobility in patients with ankylosing spondylitis (AS) and non-radiographic axial spondyloarthritis (nrAxSpA). Material and Methods Seventy-one patients with nrAxSpA, 38 patients with AS and 67 healthy control subjects were included in this study. Disease activity was assessed by the Bath Ankylosing Spondylitis Disease Activity Index, and spinal mobility by the Bath Ankylosing Spondylitis Metrologic Index. Laboratory examinations included complete blood count, ESR, CRP and oxytocin tests. Results There was no significant difference in serum levels of oxytocin among the 3 groups (p=0.973). However, serum levels of oxytocin correlated negatively with both ESR (r=− 0.359, p=0.027), CRP (r=− 0.316, p=0.056) and BASDAI scores (r=− 0,448, p=0.005) in patients with AS. On the other hand, serum levels of oxytocin had a negative correlation only with ESR in patients with nrAxSpA (r=− 0.321 p=0.009). Conclusion This study lays the foundation for further studies that may aim to investigate how addition of oxytocin to the treatment regimen impacts on disease activity in patients with AS who exhibit particularly low levels of oxytocin during the active disease period.
Investigation into the Impact of the Composition of Ethanol Fuel Deposit Control Additives on Their Effectiveness

An increasing percentage of ethanol in fuel leads to significant changes in polarity and solubility, which makes conventional gasoline deposit control additives (DCAs) difficult to dissolve in ethanol fuels, resulting in the formation of deposits on engine elements. Critical areas of deposit formation in an engine are constituted by inlet valves, combustion chambers, and fuel injectors. As a consequence, operational parameters of the engine are disturbed to a large extent by the total effect of the deposits. To prevent the aforementioned phenomena, in the operation of engines fueled with ethanol-containing blends, it is necessary to use specifically prepared DCAs. The paper briefly presents a process of development of DCAs dedicated to high-ethanol fuels. Each of the prepared DCA formulations contained a substance having detergent-emulsifying properties (referred to in the text as DEM), a carrier oil, and a solvent. The composition and ratios of components used in the DCA, by testing their effectiveness in engine deposit formation, are verified. A motor station and a test procedure developed for this purpose were used. In search of alternative solutions to conventional polyisobutyleneamines (PIBA) and polyetheramines (PEA) surfactants, which have good solubility in hydrocarbons but not in ethanol, a substance with a benzoxazine structure and a Mannich base were synthesized. Their chemical structures were confirmed by nuclear magnetic resonance (NMR) DCAs were developed, and the effectiveness of their action was verified. Moreover, attention was paid to the dosage level of the DEM and the carrier oil in the DCA. Finally, it was confirmed in the studies carried out that DCAs used for improvement of conventional hydrocarbon engine gasolines are not efficient enough when used in E85 fuels. In the case of the latter, DCAs that have been specifically developed for such fuels should be used, because they have a different chemical structure, and are soluble in the ethanol-gasoline mixture in any ratio of both components.
Driver Behavior Classification at Stop-Controlled Intersections Using Video-Based Trajectory Data

Understanding how drivers behave at stop-controlled intersection is of critical importance for the control and management of an urban traffic system. It is also a critical element of consideration in the burgeoning field of smart infrastructure and connected and autonomous vehicles (CAV). A number of past efforts have been devoted to investigating the driver behavioral patterns when they pass through stop-controlled intersections. However, the majority of these studies have been limited to qualitative descriptions and analyses of driver behavior due to the unavailability of high-resolution vehicle data and sound methodology for classifying various driver behaviors. In this paper, we introduce a methodology that uses computer-vision vehicle trajectory data and unsupervised clustering techniques to classify different types of driver behaviors, infer the underlying mechanism and compare their impacts on safety. Two major types of behaviors are investigated, including vehicle stopping behavior and vehicle approaching patterns, using two clustering algorithms: a bisecting K-means algorithm for classifying stopping behavior, and the improved density-based spatial clustering of applications with noise (DBSCAN) algorithm for classifying vehicle approaching patterns. The methodology is demonstrated using a case study involving five stop-controlled intersections in Montreal, Canada. The results from the analysis show that there exist five distinctive classes of driver behaviors representing different levels of risk in both vehicle stopping and approaching processes. This finding suggests that the proposed methodology could be applied to develop new safety surrogate measures and risk analysis methods for network screening and countermeasure analyses of stop-controlled intersections.
A robust migration velocity analysis through an asymptotic inverse via generalised Radon transform

Migration velocity analysis (MVA) has been widely used for large scale model construction. To make full use of the wavefield information and obtain stable inversion results, wave-equation-based methods, such as differential semblance optimisation (DSO) or travel-time tomography, become popular in recent years. Compared with traditional ray-based methods, wave-equation-based methods are intrinsically more robust, which can accurately describe subsurface wave phenomenon and thus solve multipathing problem occurred in ray-based methods especially in dramatically lateral variation areas. Although robust for wave-equation-based methods, the inversion results can be severely affected by spurious oscillations, such as migration smile, due to uneven illumination and limited geometry observations. To eliminate those artefacts and improve imaging and inversion results, we introduce a new asymptotic inversion method in subsurface offset domain based on two-way wave equation. The new method, derived from the generalised Radon transform, introduces a new weighting function which can be treated as an approximate inverse under the assumption of high-frequency approximation. By applying the new weighting function to the practical applications, the imaging artefacts can be significantly attenuated. Furthermore, we extend the new method to DSO with a new form of velocity inversion expressions. We also give three numerical examples to illustrate the effectiveness of the method. It appears smooth and is free of artefacts both in gradients and imaging results, which leads to stable imaging and reliable model update.
Identification of Long Noncoding RNAs in Distinct Subtypes of Mouse Retinal Ganglion Cells 

Background: Emerging evidence indicates that long noncoding RNAs (lncRNAs) are important regulators of various biological processes, and their expression can be altered following certain pathological conditions, including central nervous system injury. Retinal ganglion cells (RGCs), whose axons form the optic nerve, are a heterogeneous population of neurons with more than 20 molecularly distinct subtypes. While most RGCs, including the ON-OFF direction-selective RGCs (ooDSGCs), are vulnerable to axonal injury, a small population of RGCs, including the intrinsically photosensitive RGCs (ipRGCs), are more resilient. Results: By performing systematic analyses on RNA-sequencing data, here we identify lncRNAs that are expressed in ooDSGCs and ipRGCs with and without axonal injury. Our results reveal a repertoire of different classes of lncRNAs, including long intergenic noncoding RNAs and antisense ncRNAs that are differentially expressed between these RGC types. Strikingly, we also found dozens of lncRNAs whose expressions are altered markedly in response to axonal injury, some of which are expressed exclusively in either one of the subtypes. Moreover, analyses into these lncRNAs unraveled their neighboring coding genes, many of which encode transcription factors and signaling molecules, suggesting that these lncRNAs may act in cis to regulate important biological processes in these neurons. Lastly, guilt-by-association analysis showed that lncRNAs are correlated with apoptosis associated genes, suggesting potential roles for these lncRNAs in RGC survival.Conclusions: Overall, the results of this study reveal RGC type-specific expression of lncRNAs and provide a foundation for future investigation of the function of lncRNAs in regulating neuronal type specification and survival.
Art as an attractive methodology of resilience and self-esteem

The objective of this research is to know the relationship between the level of self-esteem and resilience that people with intellectual disabilities have and the methodology of work including art. In this study, a mixed methodology has been used, the resilience indicator chosen in this research was the level of self-esteem. For the collection of data, a Likert scale and a semi-structured interview were used. The results show that there are significant differences between the self-esteem of people with intellectual disabilities that are influenced by methodologies that include art, concerning to other methodologies.
Lipid Oxidation Kinetics of Pistachio Powder During Different Storage Conditions

The effects of storage temperatures (15, 25, 35, and 40°C) and relative humidity (11, 33, 73 and 87%) on peroxide value, lipid oxidation and shelf life of stored pistachio powder studied in this project. Results showed that the changes in lipid oxidation follow zero-order reaction kinetic. Additionally, the highest inhibition (or activation) energy (Ea) for oxidation of fatty acid molecules and forming hydro-peroxides reached to ∼50 kJ/mol at relative humidity of 33%, which corresponds to monolayer moisture content of pistachio powder. Thermodynamic analysis of these reactions indicated that these reactions are endothermic (ΔH++ > 0) and nonspontaneous (ΔG++ > 0) processes. Practical Applications Pistachio nut (Pistachia vera L.) is one of the most popular nuts in the world with its high nutritional value and unique flavor as a snack and a food ingredient (as powder or kernel). It is also used as a main part of many traditional Persian foods such as Gaz, Baghlava and Ghotab. Fat oxidation is one of the main factors for quality loss in pistachio, i.e., changes in nutritional and organoleptic properties of this product during storage period. The main object of this research is the kinetic effects of different storage temperature and RH on auto-oxidation of pistachio powder's lipid during storage period. Generally, the results are applicable by pistachio powder's workstations and their producing factories during processing and storage for controlling the shelf life.
Challenges in the Identification and Interpretation of Phenological Shifts: Anthropogenic Influences on Adult Migration Timing in Salmonids

Abstract Migration timing has evolved in many animals, allowing them to maximize breeding and feeding success by matching seasonal changes in abiotic conditions and resource pulses. These seasonal changes can shift with the climate, resulting in mismatches between migrations and resource availability unless the populations respond through phenotypic plasticity or evolutionary adaptation. It is common, however, for factors unrelated to climate to affect phenology. Salmon are an exceptionally well-studied group of fishes whose breeding migrations can serve as a template to consider the complex factors affecting migration phenology. In this paper, hypotheses for explaining changes in adult salmon migration phenology are reviewed. Pathways through which climate change may influence migration timing are first summarized, including shifting migration cues, limiting freshwater conditions, changes in distribution and conditions at sea, and alterations in embryo development. Alternative causes of phenological change in salmon are then explored including anthropogenic modifications of river habitat, demographic effects, hatcheries, and fisheries. The effects of these factors on phenology can mimic and mask climate effects, making it challenging to disentangle the causal basis of observed patterns. Instead of inferring shifts from trends in timing data (as is often done), it is suggested that specific mechanistic hypotheses be proposed and tested rigorously, and alternative causes systematically ruled out. Overall, it is challenging to attribute causation to phenological change, but salmon exemplify the many ways in which migration timing can change, including shifts due to climate and other processes.
DeapSECURE Computational Training for Cybersecurity Students: Improvements, Mid-Stage Evaluation, and Lessons Learned

DeapSECURE is a non-degree computational training program that provides a solid high-performance computing (HPC) and big-data foundation for cybersecurity students. DeapSECURE consists of six modules covering a broad spectrum of topics such as HPC platforms, big-data analytics, machine learning, privacy-preserving methods, and parallel programming. In the second year of this program, to improve the learning experience, we implemented a number of changes, such as grouping modules into two broad categories, “big-data” and “HPC”; creating a single cybersecurity storyline across the modules; and introducing post-workshop (optional) “hackshops”. Two major goals of these changes are, firstly, to effectively engage students to maintain high interest and attendance in such a non-degree program, and, secondly, to increase knowledge and skill acquisition. To assess the program, and in particular the changes made in the second year, we evaluated and compared the execution and outcomes of the training in Year 1 and Year 2. The assessment data shows that the implemented changes have partially achieved our goals, while simultaneously providing indications where we can further improve. The development of a fully on-line training mode is planned for the next year, along with a reproducibility pilot study to broaden the subject domain from cybersecurity to other areas, such as computations with sensitive data.
Modified Power Factor Correction (PFC) Control and Printed Circuit Board (PCB) Design for High-Efficiency and High-Power Density On-Board Charger

This paper presents a modified power factor correction (PFC) ON/OFF control and three-dimensional (3D) printed circuit board (PCB) design for a high-efficiency and high-power density onboard charger (OBC). By alternately operating one of two boost modules of the PFC stage at a 50% or less load condition, the proposed PFC control can reduce the load-independent power loss of the PFC stage, such as core loss and capacitor charging loss of switches. It enables OBCs to have high efficiency across a wide output power range and better thermal performance. The 3D-PCB design decouples a trade-off relationship of the PCB trace design and heat spreader design, increasing the power density of OBCs. A 3.3 kW prototype composed of an interleaved totem-pole bridgeless boost PFC converter and full-bridge (FB) LLC converter has been built and tested to verify the proposed PFC control and 3D-PCB effectiveness design. The prototype has 95.7% full power efficiency (98.2% PFC stage efficiency) and 52 W/in3 power density.
Real-world Effectiveness of Glecaprevir/Pibrentasvir (GLE/PIB) for Chronic Hepatitis C Infection: Evidence From a German Single-center Cohort Study

Background: Glecaprevir/pibrentasvir (GLE/PIB) is the latest approved pan-genotypic direct-acting antiviral agent (DAA) for the treatment of chronic hepatitis C virus (HCV) infection. However, real-world data of GLE/PIB in European patient cohorts are limited. Methods: A single-center cohort of 100 unselected HCV patients seen at the Outpatient Clinic of the University Medical Center Hamburg-Eppendorf from October 2017 until September 2019 was retrospectively analyzed by chart review with a special focus on demographic clinical and virologic aspects as well as treatment compliance outcome. Results: A total of 99 patients with chronic HCV infection (genotype (GT) 1 - 6), who started antiviral treatment with GLE/PIB, were included. Treatment duration lasted from 4 to 16 weeks. The primary endpoint was a sustained virological response at week 12 (SVR12) after the end of treatment (EoT). Only three patients (3/100; 3%) were diagnosed with liver cirrhosis by non-invasive measures. Ten patients (10/100; 10%) were pre-treated with Interferon (IFN) containing regiments. Most patients received 8 weeks of treatment (96/100; 96%). One patient discontinued treatment after four weeks due to poor compliance (1/100; 1%). A high number of patients were lost to follow-up (22/100; 22%). All patients who were regularly seen to follow-up visits (76/100; 76%) achieved SVR12 (76/76; 100%). Virological relapse occurred in none of the patients. Adverse events (AEs) were rarely reported (4 patients) (4/100; 4%), and none of these patients discontinued treatment. Conclusions: This study demonstrated that initial and re-treatment with GLE/PIB were effective and safe in a German cohort with chronic HCV infection in real-life settings, regardless of GT.
Development of Higher Yield Ozonizer Based on Nano-Seconds Pulsed Discharge

Abstract Energy efficient generation of ozone is very important because ozone is being used increasingly in a wide range of industrial applications. In this study, ultra-short duration pulsed streamer discharges with a duration of 5 ns hava been used to produce ozone in a wire-to-cylinder electrode reactor. The triaxial Blumlein configuration is used for the nano-seconds pulsed generator. Ozone concentration and ozone production yield were measured at various applied voltages (50 to 70 kV), and pulse repetitions (10 to 60 pps) at atomospheric pressure in oxygen and air. The experimental results showed that the ozone concentration (g/m3) increased with increasing applied pulse voltage and pulse repetition rate. Higher ozone concentrations were obtained in the oxygen-fed ozonizer than in the air-fed ozonizer. The ozone production yield (g/kWh) was high at low ozone concentration, and higher ozone yield was obtained with lower applied voltages. Characterization maps of ozonizers based on different discharge methods (nano-seconds pulsed discharge, DBD, DBD with narrow-gap, surface discharge, pulsed corona discharge, DC corona, superimposed discharge methods and a commercial ozonizer) were presented with oxygenfed and air-fed cases. A nano-seconds pulsed discharge showed the highest ozone yield in the characterization maps for both the oxygen-fed and air-fed cases, where the highest ozone yield were 544 and 239 g/kWh in the oxygen-fed and air-fed cases, respectively.
Analysis of Online Learning Implementation and Student Learning Activities in the Covid-19 Pandemic Era and Its Problems

Corona Virus Disease 2019 (COVID-19) has been declared by WHO as a pandemic and the Government of Indonesia based on Presidential Decree No.11 of 2020 concerning Determination of Public Health Emergencies. COVID-19 is a public health emergency that requires efforts to overcome it. In the education sector, the Covid-19 pandemic has accelerated education 4.0 with a distance learning system by utilizing information technology. In the education sector, teaching and learning activities, which usually take place face-to-face /offline, this time must be done online. The research aims to analyze the application of online learning at the Agricultural Development Polytechnic (Polbangtan) Malang and student learning activities in the application of online learning both from the aspects of independence and the development of critical thinking. The research method used is a mixed-method (mixing method). A qualitative approach is used to determine the implementation of online learning. A quantitative approach is used to determine student activities in online learning. The sample in this study were 105 students. This research was conducted in the Citizenship course. The results showed that the implementation of online learning at Polbangtan Malang was carried out through various platforms such as Google Classroom, LMS Moodle, WhatsApp, Gmail, and YouTube. In its application, there are several obstacles and problems faced by students such as internet network factors, internet quotas, and learning platforms that have not been mastered. Students in online learning activities are classified as very good in the interval X ≥ 11.7, the level of independent learning and critical thinking of students is also classified as very good. The findings above indicate that student learning activities in the Citizenship course are classified as very good even though they are carried out online. The application of online learning must pay attention to several factors of constraints and problems faced by students. With these findings, the application of online learning in the future can be carried out wisely by paying attention to the effectiveness of activities, the efficiency of internet quota, and the substance of the material being taught.
Reliability and Validity of the Lactate Pro 2 Analyzer

ABSTRACT This study evaluated the reliability of the portable Lactate Pro 2 analyzer (LP2), and its validity compared to a laboratory-based analyzer, YSI 1500 Sport (YSI). Blood samples (n = 258) were collected during 44 graded incremental rowing tests, with data from 17 tests used to quantify load, heart rate, and oxygen consumption at lactate threshold. Inter-LP2 reliability was high with coefficient of variation = 3.3%; Bland Altman 95% limits of agreement varied from ± 0.3 mmol.L−1 for blood lactate (BLa) ≤4.0 mmol.L−1 to −1.6 to +1.4 mmol.L−1 for BLa >8.0 mmol.L−1, with minimal systematic bias. Despite LP2 measurements being ~1.42 times higher than YSI measurements, no significant differences (P > .05) were detected when quantifying load, heart rate, or oxygen consumption data at lactate threshold. The results support using different LP2 devices interchangeably, especially when BLa ≤ 8 mmol.L−1, and using the LP2 to identify training intensities at lactate threshold.