Miracle-dz/UniFAR-FTUs huggingface dataset:
Steady Laminar Flow Decreases Endothelial Glycolytic Flux While Enhancing Proteoglycan Synthesis and Antioxidant Pathways

Endothelial cells in steady laminar flow assume a healthy, quiescent phenotype, while endothelial cells in oscillating disturbed flow become dysfunctional. Since endothelial dysfunction leads to atherosclerosis and cardiovascular disease, it is important to understand the mechanisms by which endothelial cells change their function in varied flow environments. Endothelial metabolism has recently been proven a powerful tool to regulate vascular function. Endothelial cells generate most of their energy from glycolysis, and steady laminar flow may reduce endothelial glycolytic flux. We hypothesized that steady laminar but not oscillating disturbed flow would reduce glycolytic flux and alter glycolytic side branch pathways. In this study, we exposed human umbilical vein endothelial cells to static culture, steady laminar flow (20 dynes/cm2 shear stress), or oscillating disturbed flow (4 ± 6 dynes/cm2 shear stress) for 24 h using a cone-and-plate device. We then measured glucose and lactate uptake and secretion, respectively, and glycolytic metabolites. Finally, we explored changes in the expression and protein levels of endothelial glycolytic enzymes. Our data show that endothelial cells in steady laminar flow had decreased glucose uptake and 13C labeling of glycolytic metabolites while cells in oscillating disturbed flow did not. Steady laminar flow did not significantly change glycolytic enzyme gene or protein expression, suggesting that glycolysis may be altered through enzyme activity. Flow also modulated glycolytic side branch pathways involved in proteoglycan and glycosaminoglycan synthesis, as well as oxidative stress. These flow-induced changes in endothelial glucose metabolism may impact the atheroprone endothelial phenotype in oscillating disturbed flow.
A novel cost-effective power supply model for industrial appliances based on triangular magnetic shunt transformer design

This paper presents a new design of a magnetic shunt transformer for use in industrial microwave generators. The proposed transformer has a triangular shape and offers several advantages over existing transformer designs, including reduced volume and maintenance costs. We provide a detailed analysis of the transformer's dimensions and an equivalent model of the three-phase high voltage power supply system. The results of this study have significant implications for the field of industrial microwave generator design and could lead to the development of more efficient and costeffective systems. The resulting model is comprised of saturable inductors capable of accounting for the non-linear phenomena of saturation. The power supply is simulated using MATLAB/Simulink with a neuro-fuzzy ANFIS approach. The results are compared to experimental validations of a single-phase reference power supply for a magnetron, validating the proposed power supply. Additionally, the simulation results demonstrate the effectiveness of the proposed design, which outperforms existing transformers in terms of volume, energy efficiency and maintenance costs.
Analysis of portable system for sound acquisition of vehicles powered by internal combustion engines

In this paper a portable system for acquisition of sound generated by passenger vehicles powered by internal combustion engines is described and analyzed. The acquisition system is developed from scratch and tested in order to satisfy the requirements such as high-quality of audio recordings, high mobility, robustness and privacy respect. With this acquisition system and adequate signal processing, the main goal was to collect a large amount of clear audio recordings that will form a quality dataset. In further research, this dataset will be used for machine learning model training and testing, i.e. for developing a system for automatic recognition of the type of car engine based on fuel.
Development of interactive e-modules to improve students’ scientific literacy abilities: A literature review

This research aims to investigate the development of the interactive e- Module in the context of improving students' scientific literacy skills. The approach employed in this research involved a systematic literature review, detailing the latest developments from 2019 to 2023 in the use of interactive e-Modules to enhance scientific literacy among students in Indonesia and abroad. The Meta-synthesis techniques were applied in this research. The samples utilized were sourced from 2019-2023 and were retrieved from international journals Google Scholar, Scopus, and Eric with the keyword "Interactive e-module and Scientific literacy”. A total of 233 journal articles were obtained and after being reviewed 209 articles were eliminated because they did not include international articles relevant to this research. Consequently, only 24 articles were used in this research. This type of research used Systematic Literature Review (SLR). The research findings indicate that the E-Module is based on Discovery Learning, STEM (Science, Technology, Engineering, and Mathematics), PBL (Problem-Based Learning), PjBL (Project-Based Learning), IBL (Inquiry-Based Learning), SETS (Science, Environment, Technology, Society), SSI (Socio Scientific Issues), and Flipped classroom can improve students' Scientific Literacy. The type of technology used in making E-Modules included Macromedia Flash, Virtual Laboratory, Flip PDF Professional, PhET Applications, and Articulate Storyline. The implications of this literature review are anticipated to provide direction for the development of educational policies, curriculum design, and further research to increase scientific literacy in the digital era.
The Dysferlinopathies Conundrum: Clinical Spectra, Disease Mechanism and Genetic Approaches for Treatments

Dysferlinopathies refer to a spectrum of muscular dystrophies that cause progressive muscle weakness and degeneration. They are caused by mutations in the DYSF gene, which encodes the dysferlin protein that is crucial for repairing muscle membranes. This review delves into the clinical spectra of dysferlinopathies, their molecular mechanisms, and the spectrum of emerging therapeutic strategies. We examine the phenotypic heterogeneity of dysferlinopathies, highlighting the incomplete understanding of genotype-phenotype correlations and discussing the implications of various DYSF mutations. In addition, we explore the potential of symptomatic, pharmacological, molecular, and genetic therapies in mitigating the disease’s progression. We also consider the roles of diet and metabolism in managing dysferlinopathies, as well as the impact of clinical trials on treatment paradigms. Furthermore, we examine the utility of animal models in elucidating disease mechanisms. By culminating the complexities inherent in dysferlinopathies, this write up emphasizes the need for multidisciplinary approaches, precision medicine, and extensive collaboration in research and clinical trial design to advance our understanding and treatment of these challenging disorders.
Translation, validation, and first application of the Greek version of an irritable bowel syndrome severity scoring system

Background The Irritable Bowel Syndrome Severity Scoring System (IBS-SSS) is a self-administered questionnaire that categorizes patients according to symptom severity. We aimed to translate and adapt the English IBS-SSS, validate the Greek version, and detect factors predictive of IBS severity. Methods The original English version was obtained from the Rome Foundation, and the final Greek version arose through a process of translation, comprehensibility evaluation and back-translation. The 141 participants enlisted in the study were enrolled from 2 tertiary hospitals and were divided into 2 groups (98 patients and 43 healthy volunteers). We evaluated the questionnaire properties based on COSMIN criteria. Results The recruited patients reported either diarrhea-predominant (34.7%), constipation-predominant (28.6%), or mixed subtype (36.7%) IBS. No significant variations were found regarding the frequency and intensity of abdominal pain and flatulence among the 3 IBS subtypes. Severity scores among healthy volunteers were significantly lower compared to IBS patients, irrespective of their disease subtype (P<0.001). The Cronbach coefficient (α) was calculated at 0.953, suggesting high inter-item internal consistency. The intraclass correlation coefficient was calculated and found to be high, suggesting good responsiveness of the questionnaire. Two-way MANOVA evaluation showed that demographic variables (age, family status, body mass index [BMI], smoking, and alcohol consumption) in the Greek population affect the IBS-SSS score and syndrome severity. Conclusions The Greek version of IBS-SSS is a reliable, valid and responsive tool for assessing Greek IBS patients’ symptom severity. Older age, smoking, alcohol use and higher BMI are indicative of greater symptom severity.
SoBat Kanker smartphone application to improve oral chemotherapy adherence among cancer patients in Indonesia: Development, usability, and feasibility pilot study

This study aimed to design, develop, and evaluate the usability and feasibility of the SoBat Kanker smartphone application to improve oral chemotherapy adherence among Indonesian cancer patients. This mixed-methods study was conducted from January 2022 to April 2023 at the National Cancer Centre, Jakarta. This study was conducted in two sequential phases: Phase I focused on developing the app using a user-centered design approach and evaluating the app using a System Usability Scale (SUS), and Phase II focused on the feasibility test of the app using one group pre-post-test design. Medication adherence was measured to test the feasibility of use using the oral chemotherapy adherence scale. The SoBat Kanker app was successfully developed in Bahasa Indonesia and was available in the Google Play Store. The app features consisted of a list of patient medications and alarm reminders for taking a drug, chatting with a pharmacist, medication information, and a diary with reminders to keep appointments related to refilling prescriptions and attending the hospital. The average system usability (SUS) score was 85.33, indicating grade A and excellent system usability. Preliminary adherence outcome measure showed significant adherence improvement in pre-post intervention at 6-week follow-up (p < 0.001). Smartphone application programs may be useful and support cancer patients taking medication as prescribed. In this usability and feasibility study, the SoBat Kanker app showed acceptable, easy-to-use, and improved medication adherence. However, further studies are necessary for efficacy testing in a large-scale randomized controlled trial.
Analysis of Uplink and Downlink Spatial Channel Reciprocity When Using Asymmetric Transceiver

—A novel millimeter-wave massive MIMO system using asymmetric transceiver, i.e., unequal number of transmitting (Tx) and receiving (Rx) radio frequency chains, is expected to maintain the advantages of conventional fully digital beamforming architectures, but partly reduce the implementation cost and power consumption. However, uplink and downlink radio channels may become non-reciprocal due to the different dimensions of Tx-Rx antenna arrays. In this paper, we analyze the reciprocity of radio channels observed by practical antenna patterns with different beamwidths. Two metrics are leveraged to measure spatial channel reciprocity based on 142 GHz outdoor channel measurement data and 28 GHz indoor ray-tracing simulation data. The power angular spectrum reciprocity of uplink and downlink radio channels does not hold when the beam pattern of base station Tx array becomes much narrower than that of Rx array. Meanwhile, it becomes increasingly likely that in the extreme case (e.g., significant beamwidth difference between Tx and Rx beam patterns), pronounced angle reciprocity can still be observed in the sparse channels with less multipath components.
Congestion Pricing, Air Pollution and Children's Health

This study examines the effects of a congestion tax in central Stockholm on ambient air pollution and the health of local children. We demonstrate that the tax reduced ambient air pollution by 5–15 percent and the rate of acute asthma attacks among young children. We do not see corresponding changes in accidents or hospitalizations for nonrespiratory conditions. As the change in health was more gradual than the change in pollution, it may take time for the full health effects of changes in pollution to materialize if the mechanism is pollution. Hence, short-run estimates of pollution reduction programs may understate long-run health benefits.
Intelligent agriculture system using low energy and based on the use of the internet of things

The field of smart agriculture is ranked among the top areas that uses the internet of things (IoT), whose goal is to increase the quantity and quality of agricultural productivity. The aim of this work is to realize a new device that will be cost-effective, reliable, and autonomous using a solar panel to provide electricity in large-scale agricultural fields, ESP32 to interconnect IoT sensors and the long range (LoRa) data transmission protocol to guarantee connectivity in places where there is no internet, whose objective is to monitor and irrigate agricultural fields only when there is a need for water. The data received by the sensors is sent to mobile app users via the Blynk cloud. The performance of our new approach is measured in terms of energy savings. This new model of irrigation and smart monitoring will improve the efficiency of farming techniques.
Advances in the Clinical Diagnostics to Equine Back Pain: A Review of Imaging and Functional Modalities

Simple Summary Back pain in horses is a common occurrence and has been considered to be an important factor affecting the well-being of horses. Its occurrence may be related to soft-tissue lesions, osseous injuries, tack-associated problems, or neurological disorders. In addition to conventional diagnostic methods, there are also more sophisticated ones, such as scintigraphy or computed tomography. Advanced diagnostic modalities include algometers, determination of lameness with inertial sensor systems, biometric mats, and geometric morphometrics methods, electromyography, as well as functional electrical stimulation. The purpose of this review article is to summarize the main back diseases in horses, as well as to provide an overview of their traditional, but also modern diagnostic methods. Although traditional diagnostic methods remain the foundation of orthopedic examination and back diseases, the use of new methods will allow for a better understanding of the pathogenesis of these diseases and will also allow for the objective monitoring of the rehabilitation and training process. Abstract Back pain is common in ridden horses. Back diseases in horses include Impinging Dorsal Spinous Processes, Ventral Spondylosis, Osteoarthritis of Articular Process, Intervertebral Discs Disease, Vertebral Fractures, Conformational Abnormalities, Desmopathy of the Supraspinous Ligament, Desmopathy of the Intraspinous Ligament, and Longissimus Muscle Strain. Back pain may also develop as a result of lameness (particularly hindlimb lameness). A poorly fitting saddle and an unbalanced rider are also considered important factors influencing the development of back pain in horses. The conventional diagnosis of equine back pain includes a clinical examination and diagnostic imaging examination using ultrasound, radiography, and thermography. Advanced diagnostic modalities of equine back pain involve the objectification of standard procedures through the use of algometers, a lameness locator, biometric mats, and the geometric morphometrics method. In addition to modern diagnostic methods, such as computed tomography and scintigraphy, advances in the diagnosis of equine back pain include the use of electromyography and functional electrical stimulation. The aim of this review article is to familiarize clinicians with the usefulness and capabilities of conventional diagnostic protocols and advanced diagnostic modalities. Although orthopedic examination and traditional diagnostic methods will remain the foundation of the diagnosis of back diseases, modern methods meet the growing expectations towards high-performance horses and allow for deeper diagnostics and objective monitoring of rehabilitation and training progress.
Risk assessment in cryptocurrency portfolios: a composite hidden Markov factor analysis framework

In this paper, we deal with the estimation of two widely used risk measures such as Value-at-Risk (VaR) and Expected Shortfall (ES) in a cryptocurrency context. To face the presence of regime switching in the cryptocurrency volatilities and the dynamic interconnection between them, we propose a Monte Carlo-based approach using heteroskedastic factor analysis and hidden Markov models (HMM) combined with a structured variational Expectation-Maximization (EM) learning approach. This composite approach allows the construction of a diversified portfolio and determines an optimal allocation strategy making it possible to minimize the conditional risk of the portfolio and maximize the return. The out-of-sample prediction experiments show that the composite factorial HMM approach performs better, in terms of prediction accuracy, than some other baseline methods presented in the literature. Moreover, our results show that the proposed methodology provides the best performing crypto-asset allocation strategies and it is also clearly superior to the existing methods in VaR and ES predictions.
An Enkf-Based Scheme for Snow Multivariable Data Assimilation at an Alpine Site

Abstract The knowledge of snowpack dynamics is of critical importance to several real-time applications especially in mountain basins, such as agricultural production, water resource management, flood prevention, hydropower generation. Since simulations are affected by model biases and forcing data uncertainty, an increasing interest focuses on the assimilation of snow-related observations with the purpose of enhancing predictions on snowpack state. The study aims at investigating the effectiveness of snow multivariable data assimilation (DA) at an Alpine site. The system consists of a snow energy-balance model strengthened by a multivariable DA system. An Ensemble Kalman Filter (EnKF) scheme allows assimilating ground-based and remotely sensed snow observations in order to improve the model simulations. This research aims to investigate and discuss: (1) the limitations and constraints in implementing a multivariate EnKF scheme in the framework of snow modelling, and (2) its performance in consistently updating the snowpack state. The performance of the multivariable DA is shown for the study case of Torgnon station (Aosta Valley, Italy) in the period June 2012 - December 2013. The results of several experiments are discussed with the aim of analyzing system sensitivity to the DA frequency, the ensemble size, and the impact of assimilating different observations.
Successful treatment of lung cancer coexisting with B‑cell lymphoma with pembrolizumab following rituximab‑included chemotherapy: A case report

The combined occurrence of lung cancer and B-cell lymphoma, such as mucosa-associated lymphoid tissue (MALT) lymphoma, is rare. The efficacy and safety of immune checkpoint inhibitors (ICIs) remain unknown in this population of patients, and the occurrence of ICI-induced exacerbation of lymphoma is concerning. The present study describes a case of successful treatment with pembrolizumab following rituximab-containing chemotherapy for lung cancer complicated by MALT lymphoma. The patient was a 69-year-old woman diagnosed with MALT lymphoma based on a biopsy of stomach ulcerative lesions, and advanced lung cancer based on a biopsy of a lymph node in the left pulmonary hilum. Complete remission was achieved after one cycle of rituximab and bendamustine therapy for MALT lymphoma. Pembrolizumab monotherapy was subsequently initiated, resulting in a good response for lung cancer without recurrence or exacerbation of the lymphoma. In conclusion, the present study suggested that pembrolizumab, following rituximab-containing therapy, could be a treatment option for patients with lung cancer coexisting with MALT lymphoma.
Blockchain in Online Games and What Can Be Learned from It

In recent years, with the booming development of Internet technology, the types of online game products and gameplay have become more and more diversified, and the market size and revenue of the world's online games have shown a steady growth trend. In the formation of a perfect industrial chain and high entry threshold at the same time, due to the over-centralized management, can not meet the expectations of the user community, resulting in low user stickiness, the number of users to grow into a bottleneck situation. Blockchain technology has the unique value of decentralization, data security and credible transaction, which can effectively solve the pain points of online games and become a new direction for traditional online games to break through the development bottleneck. By deconstructing the existing specific cases of successful combination of blockchain technology and online games, this paper elaborates the realization path of successful application of blockchain technology in online games, and analyzes in detail the core logic of successful combination and mutual adaptation of blockchain technology and online game industry, which is committed to providing useful guidance for future related research.
Atmospheric dispersal of maize pollen over the Aquitaine region

The on-going introduction of genetically modified maize is generating research on the possibilities for coexistence. Following recent experimental evidence for the presence of maize pollen in the atmosphere up to heights of about 1-2 km, a modelling tool has been developed to simulate long range dispersal and deposition. Here we present the model basis and preliminary results confirming the measurements performed from an instrumented aircraft.
Cross-Modal Hashing With Feature Semi-Interaction and Semantic Ranking for Remote Sensing Ship Image Retrieval

Cross-modal hashing plays a pivotal role in large-scale remote sensing (RS) ship image retrieval. RS ship images often exhibit similar overall appearance with subtle differences. Existing hashing methods typically employ feature non-interaction strategies to generate common hash codes, which may not effectively capture the correlations between cross-modal ship images to reduce intermodality discrepancies. To address this issue, we propose a novel cross-modal hashing approach based on feature semi-interaction and semantic ranking (FSISR) for RS ship image retrieval. Our FSISR approach not only captures intricate correlations between different ship image modalities, but also enables the construction of hash tables for large-scale retrieval. FSISR comprises a feature semi-interaction module and a semantic ranking objective function. The semi-interaction module utilizes clustering centers from one modality to learn the correlations between two modalities and generate robust shared representations. The objective function optimizes these representations in a common Hamming space, consisting of a shared semantic alignment loss and a margin-free ranking loss. The alignment loss employs a shared semantic layer to preserve label-level similarity, while the ranking loss incorporates hard examples to establish a margin-free loss that captures similarity ranking relationships. We evaluate the performance of our method on benchmark datasets and demonstrate its effectiveness for cross-modal RS ship image retrieval. https://github.com/sunyuxi/FSISR.