Miracle-dz/UniFAR-FTUs huggingface dataset:
Smoke detection in compressed video

Early detection of fires is an important aspect of public safety. In the past decades, devices and systems have been developed for volumetric sensing of fires using non-conventional techniques, such as, computer vision based methods and pyro-electric infrared sensors. These systems pose an alternative for more commonly used point detectors, which suffer from transport delay in large and open areas. The ubiquity of computing and recent developments on novel hardware alternatives, like memristor crossbar arrays, promise an increase in the number of deployments of such systems. Existing video-based methods have been developed for the analysis of uncompressed spatio-temporal sequences. In order to respond the growing demand of such systems, techniques specifically aimed at analyzing compressed domain video streams should be developed for early fire detection purposes. In this paper, a Markov model and wavelet transform based technique is proposed to further improve the current state-of-the-art methods for video smoke detection by detecting signs of smoke existence in the MJPEG2000 compressed video.
Contrast in monsoon precipitation over oceanic region of north Bay of Bengal and east equatorial Indian Ocean

This study explores the possible causes of rainfall distribution over the two major oceanic raining regions of the north Bay of Bengal (nBoB) and the east equatorial Indian Ocean (eEIO). Despite 17% difference in vertically averaged humidity, there is almost 34% difference in mean rainfall over these two regions. The climatological seasonal [June–September (JJAS)] mean (standard deviation) rainfall over nBoB region is always higher (lower) than that over the eEIO region in all the independent data used. The eEIO region has a much larger percentage of low stratiform and convective rainfall (<5 mm day−1) distribution as compared to nBoB, which is totally opposite in case of moderate stratiform and convective rainfall (>5 mm day−1) distribution. This is further substantiated by a much lower values of outgoing long‐wave radiation (OLR) in nBoB (<200 W m−2) as compared to the eEIO (217 W m−2) region. Mean Hadley circulation along with relative vorticity/divergence profile supports more intense (gentle) updrafts over nBoB (eEIO) region. Latent heat (LH) is almost three times at the upper level (∼8 km) in case of nBoB as compared to eEIO; however, at the lower level (∼3 km) LH is marginally higher over eEIO region. Microphysical variables, namely cloud ice optical thickness and cloud ice water path, are in much larger quantities over nBoB as compared to eEIO. Furthermore, the cold (warm) rain processes dominate among other microphysical processes over nBoB (eEIO) region. Thus, the interplay among large‐scale dynamics, thermodynamics and microphysics is very crucial in the formation of deep clouds and convective rain over the nBoB region and similarly shallow clouds and stratiform rain over the eEIO region. This study will be very useful to guide present‐day coupled models for proper representation of different rain components over the nBoB and eEIO region.
A Method for Training Object Scale Estimation System using Feature Extraction Enhancement with Depth Estimation

In recent years, machine learning-based object scale estimation has been growing in popularity, as the significance of the technology lies in its potential for use in many industry fields. Although several methods have been proposed, the possible applications of this technique are limited due to its insufficient accuracy. Hence, a human-level accurate system is needed for the technology to be applied in the real-world domain. This research paper proposes a novel object scale estimation system that incorporates the feature extractor, disentangled feature maps, depth estimator, object localizer, and ground truth depth map. The input of the proposed system is an image, which is inputted into the feature extractor to create disentangled feature maps. These feature maps are then extracted by the depth estimator to generate a depth map, and by the object localizer to create a predicted bounding box around the object. The trained feature extractor can extract disentangled size-related features from the inputted image by jointly training the depth estimator and object localizer. The use of disentangled features boosts the performance of the proposed system. In addition, we propose an actual scale converter module to calculate the actual size of the inputted object. Throughout the experiments, the proposed method has proven that it is superior compared to other state-of-the-art methods. The proposed method achieves an IoU (Intersection over Union) value of 0.8113 on the COCO dataset.
Shear Wave Velocity results of non-alcoholic fatty liver disease in diabetic patients

Amac: Non-alkolik yagli karaciger hastaligi bulunan Tip II diyabetes mellituslu hastalarda, Shear Wave Elastography (SWV) ile karaciger sertligi derecesini degerlendirmek amaclandi. SWV elastografi degerleri ile hepatik steatoz derecesi, karaciger aminotransferazlari, lipit profili ve vucut kitle indeksi karsilastirildi. Gerec ve Yontemler: Bu vaka-kontrol calismasinda, dahiliye klinigine basvuran non-alkolik yagli karaciger hastaligi olan 110 hasta, (57 erkek, 53 kadin, ortalama yas 50,17) ve kontrol grubunda karaciger hastaligi olmayan 50 saglikli yetiskin (26 erkek, 24 kadin), yas ortalamasi (48,26) calismaya alindi. Her bireyde karaciger parankiminin sag lobundan toplam on olcum icin alindi. Hastalarda hepatik steatozun sonografik derecesi, SWV degerleri ve es zamanli alinan laboratuvar degerleri karsilastirildi. Bulgular: SWV ortalama hiz degeri hasta grubunda 2,26 ± 0,5 m/sn) olarak hesaplandi; Kontrol grubunda 1,71±0,3 m/sn; Grade I steatozu olan hastalarda 2,15±0,6 m/sn; Grade II steatozlu hastalarda 2,25±0,4 m/s, grade III steatozlu hastalarda 2,72±0,4 m/s. SWV degerleri hasta ve kontrol gruplarinda istatistiksel olarak anlamli bir fark oldugunu gostermektedir (p < 0,01). Her uc grade karaciger steatozu ile SWV degerlerinin arasinda, istatistiksel olarak anlamli bir farki yoktu. Sonuc: Akustik radiyasyon forse impuls, kanda trigliserit, aspartat transaminaz ve alanin transaminaz artisiyla birlikte, karacigerdeki (ortalama SWV degerleri 2 ve uzerinde ise) doku sertliginin artisinin tespitinde kullanilabilir.
Measuring commuters perceptions of service quality of selected public bus services in the city of Johannesburg

The quality of public transport services receives frequent media coverage and is often the cause of civil unrest. Whilst the developed world moves towards lower car usage and higher levels of public transport use, South Africa’s public transport system remains unable to provide the commuter with an attractive alternative to the private car. This paper uses a modified SERVQUAL model to consider the gap between commuters’ perceptions of service quality and their expectations. The study measures five dimensions of service quality, i.e. reliability, the extent of the service, comfort, safety and affordability. These five dimensions comprise 25 attributes in total. Respondents were targeted from the Greater Johannesburg area, as the largest urban population in the country. The results indicate gaps in some of the dimensions and a number of attributes were identified as having influenced the perception of service quality significantly enough to lead to customer dissatisfaction. The study provides public transport operators and government departments responsible for the provision and subsidisation of public transport with a tool characterised by a good degree of openness and flexibility, to fit individual needs. It might also be of interest for practitioners wishing to explore the main drivers of satisfaction among transport users. Recommendations for improvement in service quality have been made. Keyword: SERVQUAL, public transport, service quality, South Africa
The Impact of Primary Work Stressors on Work Performance among University Lecturers in Shaanxi, with Self-efficacy as a Moderating Variable

This study delves into the relationship between the primary sources of work stress and work performance among university lecturers in Shaanxi Province, China, with the introduction of self-efficacy as a key moderating variable. Drawing on foundational theories like the Job Demands-Resources Model and Self-Efficacy Theory, the research framework incorporates ten hypotheses. Employing quantitative analysis, the study, based on convenient sampling, gathered 433 valid responses from university lecturers in Shaanxi. Findings reveal that intrinsic job factors positively influence work performance, while interpersonal relationships, career development, university atmosphere, and work-family conflict have negative effects. Self-efficacy effectively moderates the relationships between intrinsic job factors, career development, work-family conflict, and work performance. This research contributes empirical support to concepts and theories related to work stress and work performance, providing a practical basis for policies in stress and performance management for university lecturers and offering valuable suggestions for individual stress regulation and enhancing personal competitiveness.
Implications of Artificial Intelligence for Teaching and Learning

Artificial Intelligence (AI) has significantly transformed teaching and learning, facilitating a shift from teacher-centered to student-centered education. This review outlines the broad implications of AI for education and synthesizes both the opportunities and challenges associated with its implementation. Examining over 55 papers related to the impacts of AI on education, the review encompasses various educational contexts, avoiding a singular focus on specific types of education or the teaching of AI alone. According to the review, AI introduces new opportunities for creating intelligent content that enhances learning experiences, fostering interactivity and a student-centered approach. Smart content enables instructors to integrate multimedia, interactive tools, AI-related wearables, and information technologies, diversifying learning modes and engaging students more effectively. The creation of smart content aligns with smart education frameworks to ensure efficient content development. AI also contributes to the development of intelligent tutoring systems, which simulate human tutors to deliver personalized and adaptive educational experiences. These systems can host smart content, enabling independent learning. Additionally, AI improves virtual learning environments by analyzing student data to tailor content and delivery methods based on individual needs. It automates tasks such as grading and feedback, allowing teachers to concentrate on other essential responsibilities. While AI brings significant benefits, it is not without limitations. Challenges include infrastructure requirements, considerations of inclusion and equity, teacher readiness and preparation, data quality and inclusivity, profit orientation, data privacy and ethical concerns, and the potential for unequal access. Addressing these limitations is crucial for maximizing the positive impacts of AI in the realm of education.
Neutrophil extracellular traps - a potential trigger for the development of thrombocytopenia during extracorporeal membrane oxygenation

Neutrophil extracellular traps (NETs) have recently emerged as a potential link between inflammation, immunity, and thrombosis, as well as other coagulation disorders which present a major challenge in the context of extracorporeal membrane oxygenation (ECMO). By examining blood from ECMO patients for NETs and their precursors and correlating them with clinical and laboratory biomarkers of coagulation and inflammation, this study aims to evaluate the association between the presence of NETs in the bloodstream of ECMO patients and the development of potentially severe coagulation disorders during ECMO therapy. Therefore, blood samples were collected from healthy volunteers (n=13) and patients receiving veno-venous (VV) ECMO therapy (n=10). To identify NETs and their precursors, DNA and myeloperoxidase as well as granulocyte marker CD66b were visualized simultaneously by immunofluorescence staining in serial blood smears. Differentiation of DNA-containing objects and identification of NETs and their precursors was performed semiautomatically by a specific algorithm using the shape and size of DNA staining and the intensity of MPO and CD66b signal. Neutrophil extracellular traps and their precursors could be detected in blood smears from patients requiring VV ECMO. Compared to volunteers, ECMO patients presented significantly higher rates of NETs and NET precursors as well as an increased proportion of neutrophil granulocytes in all detected nucleated cells. A high NET rate prior to the initiation of ECMO therapy was associated with both increased IL-6 and TNF-α levels as an expression of a high cytokine burden. These patients with increased NET release also presented an earlier and significantly more pronounced decrease in platelet counts and ATIII activity following initiation of therapy compared with patients with less elevated NETs. These findings provide further indications for the development of immune-mediated acquired thrombocytopenia in ECMO patients.
Refined Numerical Simulation in Wind Resource Assessment and Wind Power Forecasting

An approach based on off-line, one-way nesting between a meteorological model, WRF, and a commercial CFD model, FLUENT, is applied to perform finescale wind simulations over realistic complex terrain. The refined WRF/FLUENT system was applied to assess the wind resource in the northern Poyang Lake region and forecast the wind power of the Yangmeishan wind farm in Yunnan. The results showed that the approach is viable for the assessment and forecasting of wind energy.
Reconstruction of Cardiac Images using the Confocal Laser Scanning Microscope

We suggested a cardioid aperture in the processing of cardiac images using the confocal laser scanning microscope (CSLM). We calculated the Point Spread Function (PSF) corresponding to the cardioid aperture and the cardiac images by using the FFT algorithm. Then, we studied the effect of the image rotation on the PSF. In addition, we computed the autocorrelation corresponding to the cardiac images and cardiac aperture and compared them with the autocorrelation of the uniform circular aperture. Also, we computed the cross-correlation of aligned and rotated cardiac images. Finally, we imaged the cardiac images using the confocal scanning microscope provided with the circular and cardioid shapes of apertures. The MATLAB code is used in the formation of all images and plots.
Development of a Rapid Retrieval Method for Cloud Optical Thickness and Cloud-Top Height Using Himawari-8 Infrared Measurements

We have developed a rapid simplified algorithm to retrieve cloud optical thickness and cloud-top height from measurements of the infrared split-window bands of Himawari-8. The method is based on a rapid calculation model for clear-sky brightness temperatures and empirical equations for cloud, for which the coeffi- cients are determined by a fit to a more rigorous radiative-transfer model. This method can be applied regardless of regions excluding the polar regions and season by taking into account the temperature, humidity, sea surface temperature, and surface emissivity. In this study, we have demonstrated that this method captures well the diurnal cycle of cloud amounts of different cloud types in the warm-pool region around Indonesia. With an accelerated retrieval process by a factor of around 1,000 compared with the the phys- ics-based retrieval, our rapid cloud retrieval algorithm yielded cloud amounts that agree quantitatively with those from a more rigorous, physics-based cloud retrieval method.
Does the Differential Structure of Space-Time Follow from Physical Principles?

This article examines Wigner’s view on the unreasonable effectiveness of mathematics in the natural sciences, which was based on Cantor’s claim that ‘mathematics is a free creation of the human mind’. It is contended that Cantor’s claim is not relevant to physics because it was based on his power set construction, which does not preserve neighborhoods of geometrical points. It is pointed out that the physical notion of Einstein causality can be defined on a countably infinite point set M with no predefined mathematical structure on it, and this definition endows M with a Tychonoff topology. Under Shirota’s theorem, M can therefore be embedded as a closed subspace of RJ for some J. While this suggests that the differentiable structure of RJ may follow from the principle of causality, the argument is constrained by the fact that the completion processes (analyzed here in some detail) required for the passage from QJ to RJ remain empirically untestable.
Seasonal fish and invertebrate communities in three northern California estuaries

The majority of Northern California estuaries are small, flooded, river valleys that are largely unstudied due to their small sizes and remote locations. Yet these estuaries serve as important nursery areas for many marine fish species including rockfish, flatfish, smelt, and herring, and they are vital to anadromous species such as Chinook Salmon (Oncorhynchus tshawytscha) and Steelhead (O. mykiss). I sampled the summer and winter fish and invertebrate communities of the Big, Mad, and Ten Mile river estuaries. Fish were sampled via beach seine or fyke net and invertebrates were sampled via benthic cores, June 2014-June 2016. This research is part of a larger suite of studies establishing baseline conditions in Northern California Marine Protected Areas (MPAs). Big and Ten Mile river estuaries in Mendocino County were designated as MPAs in 2012. The Mad River Estuary in Humboldt County was selected as a non-MPA site to investigate its potential as a reference estuary. In the Mad River Estuary, additional sampling was conducted and a diet study was carried out on the feeding habits of two benthic fishes: Pacific Staghorn Sculpin (Leptocottus armatus) and English Sole (Parophrys vetulus). iii Fish abundance and diversity varied more by season (i.e. summer, winter) than by estuary, while invertebrate diversity varied more by estuary than by season. The Big River Estuary had the strongest ocean connection and the most marine fish and invertebrate species. The Mad River Estuary fish and invertebrate communities were most similar to the Ten Mile River Estuary, which had the least ocean connectivity and species diversity. Additional sampling in the Mad River Estuary showed that fish and invertebrate communities were diverse from spring through fall, and that invertebrate communities within an estuary differed more by upstream distance than by season. Staghorn Sculpin diet in the Mad River Estuary varied by location of capture, but not by season.
Gentle or intense grape crushing

Crushing releases juice from grapes and increases the speed of skin extraction. Classically, this process was performed by foot treading but the process started to be mechanised in the early 19th century. Quite vigorous crushing equipment has sometime been used, but relatively gentle overlapping lobe roller crushers are now widely used (when crushing is performed at all). Recently there has been some renewed interest in different and more intense crushing equipment because of the potential for enhanced colour extraction or reduced skin contact time in red wine production. Simon Nordestgaard, from The Australian Wine Research Institute, reports on the evolution of grape crushing equipment and some of the new crushers being proposed that operate on different principles as well as research questions that remain.
Epidemiology of childhood acute leukemias in marginalized populations of the central-south region of Mexico: results from a population-based registry

Introduction Acute leukemias (AL) are the main types of cancer in children worldwide. In Mexico, they represent one of the main causes of death in children under 20 years of age. Most of the studies on the incidence of AL in Mexico have been developed in the urban context of Greater Mexico City and no previous studies have been conducted in the central-south of the country through a population-based study. The aim of the present work was to identify the general and specific incidence rates of pediatric AL in three states of the south-central region of Mexico considered as some of the marginalized populations of Mexico (Puebla, Tlaxcala, and Oaxaca). Methods A population-based study was conducted. Children aged less than 20 years, resident in these states, and newly diagnosed with AL in public/private hospitals during the period 2021-2022 were identified. Crude incidence rates (cIR), standardized incidence rates (ASIRw), and incidence rates by state subregions (ASIRsr) were calculated. Rates were calculated using the direct and indirect method and reported per million children under 20 years of age. In addition, specific rates were calculated by age group, sex, leukemia subtype, and immunophenotype. Results A total of 388 cases with AL were registered. In the three states, the ASIRw for AL was 51.5 cases per million (0-14 years); in Puebla, it was 53.2, Tlaxcala 54.7, and Oaxaca de 47.7. In the age group between 0-19 years, the ASIRw were 44.3, 46.4, 48.2, and 49.6, in Puebla, Tlaxcala, and Oaxaca, respectively. B-cell acute lymphoblastic leukemia was the most common subtype across the three states. Conclusion The incidence of childhood AL in the central-south region of Mexico is within the range of rates reported in other populations of Latin American origin. Two incidence peaks were identified for lymphoblastic and myeloid leukemias. In addition, differences in the incidence of the disease were observed among state subregions which could be attributed to social factors linked to the ethnic origin of the inhabitants. Nonetheless, this hypothesis requires further investigation.
T cell senescence: a new perspective on immunotherapy in lung cancer

T cell senescence is an indication of T cell dysfunction. The ability of senescent T cells to respond to cognate antigens is reduced and they are in the late stage of differentiation and proliferation; therefore, they cannot recognize and eliminate tumor cells in a timely and effective manner, leading to the formation of the suppressive tumor microenvironment. Establishing methods to reverse T cell senescence is particularly important for immunotherapy. Aging exacerbates profound changes in the immune system, leading to increased susceptibility to chronic, infectious, and autoimmune diseases. Patients with malignant lung tumors have impaired immune function with a high risk of recurrence, metastasis, and mortality. Immunotherapy based on PD-1, PD-L1, CTLA-4, and other immune checkpoints is promising for treating lung malignancies. However, T cell senescence can lead to low efficacy or unsuccessful treatment results in some immunotherapies. Efficiently blocking and reversing T cell senescence is a key goal of the enhancement of tumor immunotherapy. This study discusses the characteristics, mechanism, and expression of T cell senescence in malignant lung tumors and the treatment strategies.