Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of the Effect of Retarder and Expander on the Strength and Cracking Performance of Rubber Concrete Based on Back Propagation Neural Network

The advantages of rubber concrete (RC) are good ductility, fatigue resistance, and impact resistance, but few studies have been conducted on the effects of different rubber admixtures on the strength of RC and the cracking performance of rubber mortar. In this study, the compressive and flexural tests of rubber concrete and the crack resistance test of rubber mortar were carried out by changing the rubber content and adding expansion agent and retarder in this test. The test results show that the strength of RC decreases with the increase in rubber admixture. At 15% of rubber admixture, the expansion agent and retarder increase the compressive strength and flexural strength of RC the most; the compressive strength increased to 116% (22.6 MPa) and 109% (21.2 MPa), and the flexural strength increased to 111% (4.02 MPa) and 116%. (4.21 MPa). At the same rubber admixture, the expander improves the cracking time of the rubber mortar by about 3 times, and the retarder improves the cracking time of the rubber mortar by about 1.6 times. The BP neural network (BPNN) was established to simulate and predict the compressive and flexural strengths of RC with different admixtures and the cracking time of rubber mortar. The simulation results show that the predicted 7-day compressive strength of RC fits best with the actual value, with a value of 0.994, and the predicted 28-day flexural strength was closest to the measured value, with an average relative error of 1.7%. It was shown that the calculation results of the artificial intelligence prediction model are more accurate. The simulation results and test results show that the expander and retarder significantly improve the strength of RC as well as the cracking performance of rubber mortar.
Community Structure and Diversity of Endophytic Bacteria in Melon (Cucumis melo L.) Seeds

Endophytic bacteria play a crucial role in the life cycle of Spermatophyta, and exploring the beneficial interactions between seeds and endophytic bacteria is an effective strategy for sustainable agricultural development and improved crop productivity. In this study, we employed Illumina Hiseq high-throughput sequencing technology to analyze the amplified fragments of microbial 16S rRNA sequences from melon seeds of MR-1, HH and their F1 generation, which displayed varying levels of resistance to bacterial fruit blotch disease. Initially, we extracted endophytes from eight melon samples and performed sequencing, obtaining an average of 84,758 effective tags per sample. At the 97% similarity level, the number of operational taxonomic units (OTUs) derived from melon seed endophytes ranged from 447 to 492. After filtering out low-level OTUs, we obtained an average of 65,866 valid tags from the eight samples, representing approximately 160 genera and 167 species across eight phyla. It was found that the composition of the endophyte communities in the eight samples was basically similar, and their abundance showed some variability. Furthermore, we utilized the KO and COG databases to functionally predict the genes of endophytes in melon seeds. The analysis revealed a significant enrichment of genes associated with pathways related to protein synthesis, carbohydrate metabolism, substance transport, and metabolite synthesis. These findings greatly contribute to our understanding of endophytic bacteria in melon seeds and serve as a vital reference for the selection and breeding of high-quality melon seeds, as well as the prevention of seed diseases.
Transcriptomic Profiling of Influenza A Virus-Infected Mouse Lung at Recovery Stage Using RNA Sequencing

Influenza A virus (IAV) is known to cause mild to severe respiratory illness. Under some conditions, the infection can lead to pneumonia (viral or bacterial), acute respiratory distress syndrome, and other complications that can be fatal, especially in vulnerable populations such as the elderly, young children, and individuals with underlying health conditions. Despite previous studies, little is known about the host immune response and neuroimmune interactions in IAV infection. Using RNA sequencing, we performed transcriptomic analysis of murine lung tissue 21 days post infection (dpi) with IAV (H1N1) in order to find the differentially expression genes (DEGs) related to the host immune response and neuroimmune interactions inside the lung during recovery. Among 792 DEGs, 434 genes were up-regulated, whereas 358 genes were down-regulated. The most prominent molecular functions of the up-regulated genes were related to the immune response and tissue repair, whereas a large proportion of the down-regulated genes were associated with neural functions. Although further molecular/functional studies need to be performed for these DEGs, our results facilitate the understanding of the host response (from innate immunity to adaptive immunity) and neuroimmune interactions in infected lungs at the recovery stage of IAV infection. These genes might have potential uses as mechanistic/diagnostic biomarkers and represent possible targets for anti-IAV therapies.
Spatial Variability in Salt Marsh Drainage Controlled by Small Scale Topography

Water movement in coastal wetlands is affected by spatial differences in topography and vegetation characteristics as well as by complex hydrological processes operating at different time scales. Traditionally, numerical models have been used to explore the hydrodynamics of these valuable ecosystems. However, we still do not know how well such models simulate water‐level fluctuations beneath the vegetation canopy since we lack extensive field data to test the model results against observations. This study utilizes remotely sensed images of sub‐canopy water‐level change to understand how marshes drain water during falling tides. We employ rapid repeat interferometric observations from the NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar instrument to analyze the spatial variability in water‐level change within a complex of marshes in Terrebonne Bay, Louisiana. We also used maps of herbaceous aboveground biomass derived from the Airborne Visible/Infrared Imaging Spectrometer‐Next Generation to evaluate vegetation contribution to such variability. This study reveals that the distribution of water‐level change under salt marsh canopies is strongly influenced by the presence of small geomorphic features (<10 m) in the marsh landscape (i.e., levees, tidal channels), whereas vegetation plays a minor role in retaining water on the platform. This new type of high‐resolution remote sensing data offers the opportunity to study the feedback between hydrodynamics, topography and biology throughout wetlands at an unprecedented spatial resolution and test the capability of numerical models to reproduce such patterns. Our results are essential for predicting the vulnerability of these delicate environments to climate change.
Experimental validation of motion sensor Physilog®5 applied to shoulder joint

The main motivation of this paper is to verify the idea of using the Physilog®5 unit for the patients with shoulder movement difficulties. The attached sensor to the patient’s arm then measures motion during which the patient should follow certain paths. Finally, if a patient has difficulty with motion requirements, some typical pattern for their problem should emerge. By analysing these patterns, a database of typical problems could be created, which could assist doctors in determining a patient’s diagnosis.The experiment is focused on Physilog® concerning the 5th generation. The goal is to experimentally identify and verify the performance of this generation during relatively large motions of the upper limb. For this purpose, an experimental stand representing spherical joint with an accurate absolute position sensing is assembled and calibrated. Subsequently, the three Physilog®5 sensors are mounted on this stand at different positions.
The Impact of Romantic Attachment Styles on Jealousy in Young Adults

Background Romantic attachment is reflected in various aspects of dyadic interaction in a couple, since it is a self-reinforcing system of cognitive, emotional and behavioral patterns. Romantic jealousy was shown to be associated with dimensions of attachment insecurity in various studies worldwide. Objectives To identify differences in expressions of romantic jealousy based on romantic attachment style. To determine the influence of attachment-related anxiety and attachment-related avoidance on cognitive, emotional, and behavioral jealousy. Design The sample comprised 171 heterosexual individuals. The “Experiences in Close Relationships — Revised” questionnaire (ECR-R; Fraley, Waller, & Brennan, 2000; adapted for Russian by Chursina, 2022) and “Multidimensional Jealousy Scale” (MJS; Pfeiffer, & Wong, 1989) were used. Results A number of significant differences were identified between insecure and secure attachment styles. Avoidant attachment is characterized by cognitive jealousy, ambivalent attachment is characterized by cognitive and behavioral jealousy, while dismissing attachment showed no significant differences in the manifestations of jealousy in comparison with secure attachment style. Emotional jealousy is equally characteristic of all types. The primacy of romantic attachment in relation to cognitive and behavioral jealousy was also proved. Conclusion The experience of jealousy differs among romantic attachment styles. Attachment-related anxiety is a predictor of intrusive thoughts and behavioral manifestations of jealousy, while attachment-related avoidance is less, the greater the manifestation of jealousy behaviors.
Poverty and inequality in real-world schizophrenia: a national study

Background Schizophrenia has high socioeconomic impact among severe psychiatric disorders. Aims To explore clinician-reported and patient-reported inequities between patients under the poverty threshold vs. the others. Method 916 patients consecutively recruited in 10 national centers received a comprehensive standardized evaluation of illness severity, addictions and patient-reported outcomes. Results 739 (80.7%) of the patients were classified in the poverty group. This group had poorer objective illness outcomes (lower positive, negative, cognitive, excitement/aggressive and self-neglect symptoms and lifetime history of planned suicide) in multivariate analyses. While they had similar access to treatments and psychotherapy, they had lower access to socially useful activities, couple’s life, housing and parenthood. They had also more disturbed metabolic parameters. On the contrary, the poverty group reported better self-esteem. No significant difference for depression, risky health behavior including addictions and sedentary behavior was found. Interpretation The equity in access to care is attributed to the French social system. However, mental and physical health remain poorer in these patients, and they still experience poor access to social roles independently of illness severity and despite healthcare interventions. These patients may have paradoxically better self-esteem due to decreased contact with society and therefore lower stigma exposure (especially at work). Schizophrenia presents itself as a distinct impoverished population concerning health-related outcomes and social integration, warranting focus in public health initiatives and improved treatment, including tailored interventions, collaborative care models, accessible mental health services, housing support, vocational training and employment support, community integration, education and awareness, research and data collection, culturally competent approaches, and long-term support.
Design of a trusted shift of Coordination Forms: Supporting Collaboration to handle future non-human intelligent collaborators (NICs)

We introduce principles for designing collaboration among special operation forces (SOF) and future non-human intelligent collaborators (NICs), focusing on interdependence and emergent dynamics of workflow. We discuss a dynamic mixed-initiative human-autonomy teaming (HAT) coordination concept, where multiple military SOF teams collaborate together with autonomous capabilities. We argue that effective tactical actions requires shift of coordination forms, i.e. who is enacting coordination functions, which in military command and control (C2) terminology is formalized as coordination authority. Coordination forms could shift according to a set of requirements and we discuss how to elicit experiences of such coordination from simulated missions where human teammates and/or NICs have had to make choices of coordination form. We formulate a set of hypotheses remaining to be empirically analyzed. We draw on collaboration research investigating socio-technical systems where machine teammates collaborate with human teammates to achieve a common goal.
Apatite thermochronometry within a knickzone near the Higher Himalaya front, central Nepal: No resolvable fault motion in the past one million years

We combine apatite fission track ages and track‐length measurements with apatite (U‐Th)/He ages to test the hypothesis that active near‐surface faulting is absent at the transition between the Higher and Lower Himalayan physiographic provinces in central Nepal. Fifteen samples define a 2.5‐km‐long, nearly constant‐elevation transect that crosses the largest knickzone on the Modi River in central Nepal. This knickzone could have resulted from modern faulting near the ancient Main Central thrust or from river incision following landslide dam breaching. Apatite fission track ages from the transect are generally ca. 1 Ma, and apatite He ages, selected by considering He concentrations, are 0.5–0.8 Ma. There is no discernable age difference between any of the samples outside 2σ uncertainty. Cooling rates are >100°C/Myr and are uniform across the sample transect. We calculate an average exhumation rate of ∼3 mm/yr across the region, with rates deduced from the fission track data equal to those extracted from the He ages. According to our new data, no fault in our study area has undergone a time‐averaged slip rate faster than 4 mm/yr during the past 1 Myr.
Isolating coccoliths from sediment for geochemical analysis

Trace element analysis of open‐marine sedimentary carbonates provides a wealth of paleoclimate data. At present, the majority of this data is obtained from foraminifera tests. Complications regarding the variability of conditions experienced by foraminifera throughout test formation and the influence of diagenetic processes on sample chemistry limit the value of foraminifera samples in certain situations. Coccoliths, the calcium carbonate plates produced by coccolithophores, represent a second major pelagic open‐marine carbonate source with the potential to provide a wide range of valuable trace element proxy data but which have, until now, been unavailable for analysis of many trace elements because of clay contamination. Here we describe a novel technique, which utilizes fast sorting flow cytometry, to enable the production of clay‐free sedimentary coccolith samples.
Hybrid-Algorithm-Based Full Coverage Search Approach With Multiple AUVs to Unknown Environments in Internet of Underwater Things

In the development of Internet of Underwater Things (IoUT), the unknown nature of the underwater environment is a challenging issue. In various domains related to IoUT, utilizing autonomous underwater vehicles (AUVs) for unmanned and autonomous missions has become an inevitable trend. Considering the particularity of underwater environments, this study proposes a hybrid-algorithm-based full coverage search approach to searching moving targets in unknown underwater environments. This approach combines the improved Voronoi clustering strategy, the improved artificial bee colony (ABC) algorithm, the improved line-of-sight (LOS) technique, and the artificial potential field (APF) method to enhance the efficiency of underwater full coverage search (FCS). First, the improved Voronoi clustering strategy is employed to partition the entire underwater region and allocate each part to an AUV. Second, to enhance the search capability of AUVs, a full-dimensional ABC algorithm with adaptive factor is designed to plan global paths for AUVs to search for targets, and the paths are further smoothed using the improved acrlong SLOS technique. During the navigation of the AUVs along the global paths, obstacles may be detected; thus, the APF method is utilized to dynamically plan local paths for AUVs to avoid obstacles. Experimental results demonstrate that the proposed approach significantly improves the efficiency of underwater FCS.
Using Cooperative Learning to Teach the Sustainable Development Goals

This article advocates for the use of cooperative learning by students and others toward the achievement of the United Nations’ Sustainable Development Goals (SDGs). First, the Goals are explained. Second, background is provided on cooperative learning, including explanation of eight cooperative learning principles and exemplification of how one cooperative learning technique might mobilize the eight principles. Third, how cooperative learning fits with student centered learning is explored. Fourth, two cooperative learning techniques are explained for their particular relevance to efforts to achieve the SDGs. These techniques are Group Investigation and Cooperative Debate. Fifth, two cooperative learning principles, positive interdependence and cooperation as a value, and their links to SDGs receive further exploration. Finally, we consider cooperative learning as a Swiss Army Knife and discuss its versatility with SDG examples.
The Calculation and Evaluation of an Ultrasound-Estimated Fat Fraction in Non-Alcoholic Fatty Liver Disease and Metabolic-Associated Fatty Liver Disease

We aimed to develop a non-linear regression model that could predict the fat fraction of the liver (UEFF), similar to magnetic resonance imaging proton density fat fraction (MRI-PDFF), based on quantitative ultrasound (QUS) parameters. We measured and retrospectively collected the ultrasound attenuation coefficient (AC), backscatter-distribution coefficient (BSC-D), and liver stiffness (LS) using shear wave elastography (SWE) in 90 patients with clinically suspected non-alcoholic fatty liver disease (NAFLD), and 51 patients with clinically suspected metabolic-associated fatty liver disease (MAFLD). The MRI-PDFF was also measured in all patients within a month of the ultrasound scan. In the linear regression analysis, only AC and BSC-D showed a significant association with MRI-PDFF. Therefore, we developed prediction models using non-linear least squares analysis to estimate MRI-PDFF based on the AC and BSC-D parameters. We fitted the models on the NAFLD dataset and evaluated their performance in three-fold cross-validation repeated five times. We decided to use the model based on both parameters to calculate UEFF. The correlation between UEFF and MRI-PDFF was strong in NAFLD and very strong in MAFLD. According to a receiver operating characteristics (ROC) analysis, UEFF could differentiate between <5% vs. ≥5% and <10% vs. ≥10% MRI-PDFF steatosis with excellent, 0.97 and 0.91 area under the curve (AUC), accuracy in the NAFLD and with AUCs of 0.99 and 0.96 in the MAFLD groups. In conclusion, UEFF calculated from QUS parameters is an accurate method to quantify liver fat fraction and to diagnose ≥5% and ≥10% steatosis in both NAFLD and MAFLD. Therefore, UEFF can be an ideal non-invasive screening tool for patients with NAFLD and MAFLD risk factors.
The role of low-mass star clusters in the formation of massive stars

Las estrellas masivas suponen la principal fuente de inyeccion de energia y turbulencia en el medio interestelar de las galaxias. Sin embargo, a pesar de su importancia, los procesos que conducen a su formacion estan todavia lejos de estar bien entendidos, siendo uno de los temas mas debatidos de la Astrofisica moderna. Se han propuesto varias teorias para intentar explicar la formacion de las estrellas masivas: i) colapso gravitacional monolitico; ii) coalescencia de estrellas de masa baja en cumulos estelares muy densos; y iii) acrecion competitiva de material por parte de estrellas de masas bajas e intermedias en el seno del pozo del potencial gravitacional del cumulo estelar. Mientras que la teoria clasica de colapso monolitico requiere bajos niveles de fragmentacion de la condensacion de gas natal, los modelos de coalescencia y de acrecion competitiva requieren altos niveles de fragmentacion, dando lugar a una poblacion densa de estrellas de baja masa. Por lo tanto, para distinguir entre las distintas teorias, es crucial establecer el grado de fragmentacion de la condensacion natal mediante el estudio de la distribucion de estrellas de baja masa en las regiones de formacion de estrellas masivas.
The Detection of Colorectal Cancer through Machine Learning-Based Breath Sensor Analysis

Colorectal cancer (CRC) is the third most common malignancy and the second most common cause of cancer-related deaths worldwide. While CRC screening is already part of organized programs in many countries, there remains a need for improved screening tools. In recent years, a potential approach for cancer diagnosis has emerged via the analysis of volatile organic compounds (VOCs) using sensor technologies. The main goal of this study was to demonstrate and evaluate the diagnostic potential of a table-top breath analyzer for detecting CRC. Breath sampling was conducted and CRC vs. non-cancer groups (105 patients with CRC, 186 non-cancer subjects) were included in analysis. The obtained data were analyzed using supervised machine learning methods (i.e., Random Forest, C4.5, Artificial Neural Network, and Naïve Bayes). Superior accuracy was achieved using Random Forest and Evolutionary Search for Features (79.3%, sensitivity 53.3%, specificity 93.0%, AUC ROC 0.734), and Artificial Neural Networks and Greedy Search for Features (78.2%, sensitivity 43.3%, specificity 96.5%, AUC ROC 0.735). Our results confirm the potential of the developed breath analyzer as a promising tool for identifying and categorizing CRC within a point-of-care clinical context. The combination of MOX sensors provided promising results in distinguishing healthy vs. diseased breath samples. Its capacity for rapid, non-invasive, and targeted CRC detection suggests encouraging prospects for future clinical screening applications.