Miracle-dz/UniFAR-FTUs huggingface dataset:
Nitrogen Transformation and Fate in Prairie Wetlands

Agricultural applications of fertilizers and pesticides have increased dramatically in the prairie pothole region since the middle 1960s, and agrochemical contamination ofsurface and groundwater has become a serious environmental concern. There is growing interest in the potential of prairie wetlands as sinks for excess nutrients in this agricultural landscape. As much as 50% ofthe fertilizer nitrogen applied to cultivated crops may be lost as nitrate in agricultural drainage water, and prairie wetlands may be especially effective as nitrate sinks. The effectiveness ofprairie wetlands as sinks for nonpoint source nitrogen loads is likely to depend on the magnitude of nitrate loads and the capacity of the wetlands to remove nitrate by dissimilatory processes. Performance forecast models are needed to evaluate the effectiveness ofprairie wetlands as nitrogen sinks from a watershed scale framework. This will be made significantly more difficult by the spatial and temporal complexity ofprairie pothole wetlands and by their hydrologic diversity. Future research should focus on identifying the principal factors controlling nitrogen transformation in prairie wetlands and on developing general predictive tools for modeling nitrogen fate in these systems. There is probably no region in North America where understanding and managing agriculture's impacts is more critical than in the prairie pothole region. This region comprises the glaciated prairie, an area of some 300,000
Biological Wastes the Tool for Biosorption of Arsenic

Arsenic is now a recognized hazard of water, particularly in the groundwater. The problem of naturally occurring Arsenic in the groundwater is more or less a global reporting. Direct consumption of Arsenic contaminated water is extremely harmful. Thus, a lobby of scientists is engaged in the search of proper, efficient and an economical remedial measure for Arsenic contaminated water. In light of the above, the problem was taken into consideration to study the efficacy of the biological tools in removing the arsenic. On the ground of the literary reports many biological wastes, particularly the agrowastes were found to be potential enough; and they can be employed for biosorption of Arsenic
Almost Sure Exponential Consensus of Linear and Nonlinear Multi-Agent Systems Under Semi-Markovian Switching Topologies and Application to Synchronization of Chaos Systems

This paper researches the almost sure exponential leader-following consensus (ASELFC) of linear and nonlinear multi-agent systems (MASs) under semi-Markovian switching topologies (SMSTs). Differing from existing research works of MASs under SMSTs, we remove the restriction that every topology has a directed spanning tree (DST) rooted in the leader. Only partial switching topologies are requested to have a DST. By employing Lyapunov analysis method and stochastic technique, sufficient conditions for ASELFC are obtained. Finally, the theoretical results are applied to solve the synchronization of Chaos systems by using an example of Chua’s circuits.
Cardiac sympathetic hyperinnervation after myocardial infarction: a systematic review and qualitative analysis

Abstract Background Cardiac sympathetic hyperinnervation after myocardial infarction (MI) is associated with arrhythmogenesis and sudden cardiac death. The characteristics of cardiac sympathetic hyperinnervation remain underexposed. Objective To provide a systematic review on cardiac sympathetic hyperinnervation after MI, taking into account: (1) definition, experimental model and quantification method and (2) location, amount and timing, in order to obtain an overview of current knowledge and to expose gaps in literature. Methods References on cardiac sympathetic hyperinnervation were screened for inclusion. The included studies received a full-text review and quality appraisal. Relevant data on hyperinnervation were collected and qualitatively analysed. Results Our literature search identified 60 eligible studies performed between 2000 and 2022. Cardiac hyperinnervation is generally defined as an increased sympathetic nerve density or increased number of nerves compared to another control group (100%). Studies were performed in a multitude of experimental models, but most commonly in male rats with permanent left anterior descending (LAD) artery ligation (male: 63%, rat: 68%, permanent ligation: 93%, LAD: 97%). Hyperinnervation seems to occur mainly in the borderzone. Quantification after MI was performed in regions of interest in µm2/mm2 (41%) or in percentage of nerve fibres (46%) and the reported amount showed a great variation ranging from 439 to 126,718 µm2/mm2. Hyperinnervation seems to start from three days onwards to >3 months without an evident peak, although studies on structural evaluation over time and in the chronic phase were scarce. Conclusions Cardiac sympathetic hyperinnervation after MI occurs mainly in the borderzone from three days onwards and remains present at later timepoints, for at least 3 months. It is most commonly studied in male rats with permanent LAD ligation. The amount of hyperinnervation differs greatly between studies, possibly due to differential quantification methods. Further studies are required that evaluate cardiac sympathetic hyperinnervation over time and in the chronic phase, in transmural sections, in the female sex, and in MI with reperfusion.
Refinement of Animal Experiments: Replacing Traumatic Methods of Laboratory Animal Marking with Non-Invasive Alternatives

Simple Summary To achieve the highest ethical standards in laboratory research, animal discomfort and the risk of health complications at the identification stage should be minimized. This requires the development of new bioethical yet reliable identification methods or the use of a combination of established non-invasive methods. Abstract Reliable methods for identifying rodents play an important role in ensuring the success of preclinical studies. However, animal identification remains a trivial laboratory routine that is not often discussed, despite the fact that more than 6 million rodents are used in animal studies each year. Currently, there are extensive regulations in place to ensure adequate anesthesia and to reduce animal suffering during experiments. At the same time, not enough attention is paid to the comfort of rodents during routine identification procedures, which can be painful and cause some complications. In order to achieve the highest ethical standards in laboratory research, we must minimize animal discomfort during the identification phase. In this article, we discuss traumatic methods of identification and describe several painless methods for marking in long-term experimental studies. The use of non-traumatic and non-invasive methods requires the renewal of marks as they fade and additional handling of the rodents. Laboratory personnel must be trained in stress-minimizing handling techniques to make mark renewal less stressful.
Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review

In recent years, marked progress has been made in wearable technology for human motion and posture recognition in the areas of assisted training, medical health, VR/AR, etc. This paper systematically reviews the status quo of wearable sensing systems for human motion capture and posture recognition from three aspects, which are monitoring indicators, sensors, and system design. In particular, it summarizes the monitoring indicators closely related to human posture changes, such as trunk, joints, and limbs, and analyzes in detail the types, numbers, locations, installation methods, and advantages and disadvantages of sensors in different monitoring systems. Finally, it is concluded that future research in this area will emphasize monitoring accuracy, data security, wearing comfort, and durability. This review provides a reference for the future development of wearable sensing systems for human motion capture.
FibroVit—Vision transformer-based framework for detection and classification of pulmonary fibrosis from chest CT images

Pulmonary Fibrosis (PF) is an immedicable respiratory condition distinguished by permanent fibrotic alterations in the pulmonary tissue for which there is no cure. Hence, it is crucial to diagnose PF swiftly and precisely. The existing research on deep learning-based pulmonary fibrosis detection methods has limitations, including dataset sample sizes and a lack of standardization in data preprocessing and evaluation metrics. This study presents a comparative analysis of four vision transformers regarding their efficacy in accurately detecting and classifying patients with Pulmonary Fibrosis and their ability to localize abnormalities within Images obtained from Computerized Tomography (CT) scans. The dataset consisted of 13,486 samples selected out of 24647 from the Pulmonary Fibrosis dataset, which included both PF-positive CT and normal images that underwent preprocessing. The preprocessed images were divided into three sets: the training set, which accounted for 80% of the total pictures; the validation set, which comprised 10%; and the test set, which also consisted of 10%. The vision transformer models, including ViT, MobileViT2, ViTMSN, and BEiT were subjected to training and validation procedures, during which hyperparameters like the learning rate and batch size were fine-tuned. The overall performance of the optimized architectures has been assessed using various performance metrics to showcase the consistent performance of the fine-tuned model. Regarding performance, ViT has shown superior performance in validation and testing accuracy and loss minimization, specifically for CT images when trained at a single epoch with a tuned learning rate of 0.0001. The results were as follows: validation accuracy of 99.85%, testing accuracy of 100%, training loss of 0.0075, and validation loss of 0.0047. The experimental evaluation of the independently collected data gives empirical evidence that the optimized Vision Transformer (ViT) architecture exhibited superior performance compared to all other optimized architectures. It achieved a flawless score of 1.0 in various standard performance metrics, including Sensitivity, Specificity, Accuracy, F1-score, Precision, Recall, Mathew Correlation Coefficient (MCC), Precision-Recall Area under the Curve (AUC PR), Receiver Operating Characteristic and Area Under the Curve (ROC-AUC). Therefore, the optimized Vision Transformer (ViT) functions as a reliable diagnostic tool for the automated categorization of individuals with pulmonary fibrosis (PF) using chest computed tomography (CT) scans.
Stopping Methods for Technology Assisted Reviews based on Point Processes

Technology Assisted Review (TAR), which aims to reduce the effort required to screen collections of documents for relevance, is used to develop systematic reviews of medical evidence and identify documents that must be disclosed in response to legal proceedings. Stopping methods are algorithms which determine when to stop screening documents during the TAR process, helping to ensure that workload is minimised while still achieving a high level of recall. This paper proposes a novel stopping method based on point processes, which are statistical models that can be used to represent the occurrence of random events. The approach uses rate functions to model the occurrence of relevant documents in the ranking and compares four candidates, including one that has not previously been used for this purpose (hyperbolic). Evaluation is carried out using standard datasets (CLEF e-Health, TREC Total Recall, TREC Legal), and this work is the first to explore stopping method robustness by reporting performance on a range of rankings of varying effectiveness. Results show that the proposed method achieves the desired level of recall without requiring an excessive number of documents to be examined in the majority of cases and also compares well against multiple alternative approaches.
Monitoring temperate glaciers: combined use of multi-date TerraSAR-X images and continous GPS measurements

This paper highlights the contribution of TerraSAR-X (TSX) High Resolution (HR) images for temperate glacier monitoring. A series of 14 images have been acquired since October 2007 on the Mont-Blanc test area. This area involves well-known temperate glaciers which have been monitored and instrumented ("stick" for annual displacement/ablation, GPS, cavitometer for basal displacement.) for more than 50 years. The combined use of in-situ measurements and multi-temporal images allows to improve the potential of HR SAR measurements. Interpretation of HR images, investigation of interferometric and correlation methods, and the first glacier displacement results are presented.
Cochlear implantation in Aksay University Clinic: A review of 135 cases

Introduction: Around 430 million people today suffer from mild to profound hearing loss and require rehabilitation. One option offered to patients with sensorineural hearing loss is cochlear implantation. Objective: The aim of this study was to determine the complication rate after cochlear implantation over an 8-month period. All complications were divided into 3 main groups: minor postoperative, major postoperative, and device-related failures. Additionally, the methods for prevention and management are discussed. Study design: Retrospective analysis of surgical complications after cochlear implantation. Methods: Our study included a total of 135 children (65 boys and 70 girls) who underwent cochlear implantation in Aksay University Clinic from January 2022 to August 2022. The follow-up period ranged from 8 to 15 months. The mean age at the time of their respective procedures was 3.9 years (age range: 6 months – 17 years 8 months). Results: A total of 21 complications (15.5%) were registered among the 135 patients. Of these, 9 (6.6%) were major complications and 12 (8.8%) were minor. The most prevalent cause of major complications was electrode misplacement (5 patients, 3.7%), while for minor complications it was hematoma (9 patients, 6.6%). In our study, there were more postoperative major complications and the number of complications was generally comparable to the world literature. Conclusion: Cochlear implantation is a safe, modern surgical procedure for treating sensorineural hearing loss and it is associated with a low complication rate. However, patients have to be informed about all possible complications and surgeons have to know the means of optimal prevention.
VogCast: A Framework for Modeling Volcanic Air Pollution and Its Application to the 2022 Eruption of Mauna Loa Volcano, Hawai'i

Volcanic activity and the associated gas emissions into the atmosphere often result in adverse air quality conditions and present a hazard to human health and the environment. Building on a decade‐long effort to provide operational surface sulfur dioxide and sulfate aerosol forecasts for the State of Hawai'i, we present an air quality modeling framework called VogCast. VogCast is designed to simplify ensemble air quality prediction on a regional scale by linking together multiple state‐of‐the‐art models of meteorology, emissions, and dispersion. The framework is open‐source and introduces a new dynamic plume‐rise algorithm for distributing pollutants vertically. Using radar and satellite data, we demonstrate that VogCast reasonably captured the mean injection height, the location, and the general envelope of the vog plume during Mauna Loa's 2022 eruption. The results suggest that during the 12‐day eruption period model performance varied between days with trade and non‐trade wind conditions. Our findings also highlight the importance of sulfur dioxide emission rate and vent parameter inputs for improving forecast accuracy. The broad goal of this work is to better our understanding of vog dispersion and improve air quality prediction for impacted communities.
Structural Equation Modeling Analysis of Factors Affecting the Loyalty of Forest Trail Users

Background and objective: With the increasing public awareness of health due to COVID-19 and the quality of life, people have come to prefer natural spaces with fewer crowds. Public use of forest trails is increasing as a place that satisfies the demand for such natural spaces. As a result, the basic plans for trails and mountaineering support were established, and there has been government-level support such as the establishment of the Korea Mountaineering Support Center, which resulted in a quantitative and qualitative increase in the use of forest trails. Accordingly, efforts must be made to ensure satisfaction and loyalty in using forest trails.Methods: Therefore, this study identified the factors affecting the overall satisfaction and loyalty toward forest trails through structural equation modeling. As for the research data, we used data from the Fact-finding Survey on Forest Welfare Facility Users to analyze the use of forest trails.Results: As a result, safety and comfort, kindness, travel time, and program experience variety had a significant effect directly and indirectly on overall satisfaction and loyalty. Safety and comfort affected personal activity experience variety, while kindness affected program experience variety. For travel time, the direct effect on loyalty showed a positive correlation, but the indirect effect showed a negative correlation.Conclusion: These results showed that safety should be considered a top priority on forest trails, and that long travel time to forest trails could be a factor that increases loyalty by offering various programs. In addition, loyalty has a multifaceted correlation between several factors, suggesting that it is necessary to consider not only direct effects but also indirect effects.
Research Advances of Engineered Exosomes as Drug Delivery Carrier

Exosomes are nanoscale vesicles secreted by living cells that have similar membrane composition to parental cells and carry a variety of proteins, lipids, and nucleic acids. Therefore, exosomes have certain biological activities and play an important role in intercellular communication. On the basis of its potential as a carrier for drug delivery systems, exosomes have been engineered to compensate for the shortage of natural exosomes through various engineering strategies for improving drug delivery efficiency, enhancing targeting to tissues and organs, and extending the circulating half-life of exosomes. This review focuses on the engineered exosomes loading drugs through different strategies, discussions on exosome surface modification strategies, and summarizes the advantages and disadvantages of different strategies. In addition, this review provides an overview of the recent applications of engineered exosomes in a number of refractory and relapsable diseases. This review has the potential to provide a reference for further research and development of engineered exosomes.
Authigenesis of native sulphur and dolomite in a lacustrine evaporitic setting (Hellín basin, Late Miocene, SE Spain)

Abstract Abundant sulphur is present in the Late Miocene evaporitic sequence of the lacustrine Hellín basin in SE Spain. Weathering of Triassic evaporites controlled the chemical composition of the Miocene lake. The lacustrine deposits comprise gypsum, marlstones, diatomites and carbonate beds. Sulphur-bearing carbonate deposits predominantly consist of early diagenetic dolomite. Abundant dolomite crystals with a spheroidal habit are in accordance with an early formation and point to a microbial origin. The carbon isotopic composition of the dolomite (δ13C values between −10 and −4‰) indicates mixing of lake water carbonate and carbonate derived from the remineralization of organic matter by heterotrophic bacteria. Dolomite precipitated syngenetically under evaporitic conditions as indicated by high oxygen isotope values (δ18O between +6 and +11‰). Nodules of native sulphur are found in gypsum, carbonate beds and marlstone layers. Sulphur formed in the course of microbial sulphate reduction, as reflected by its strong depletion in 34S (δ34S values as low as −17‰). Near to the surface many of the sulphur nodules were in part or completely substituted by secondary gypsum, which still reflects the sulphur isotopic composition of native sulphur (−18 to −10‰). This study exemplifies the role of bacterial sulphate reduction in the formation of dolomite and native sulphur in a semi-enclosed lacustrine basin during Late Miocene time.
U-Net Performance for Beach Wrack Segmentation: Effects of UAV Camera Bands, Height Measurements, and Spectral Indices

This study delves into the application of the U-Net convolutional neural network (CNN) model for beach wrack (BW) segmentation and monitoring in coastal environments using multispectral imagery. Through the utilization of different input configurations, namely, “RGB”, “RGB and height”, “5 bands”, “5 bands and height”, and “Band ratio indices”, this research provides insights into the optimal dataset combination for the U-Net model. The results indicate promising performance with the “RGB” combination, achieving a moderate Intersection over Union (IoU) of 0.42 for BW and an overall accuracy of IoU = 0.59. However, challenges arise in the segmentation of potential BW, primarily attributed to the dynamics of light in aquatic environments. Factors such as sun glint, wave patterns, and turbidity also influenced model accuracy. Contrary to the hypothesis, integrating all spectral bands did not enhance the model’s efficacy, and adding height data acquired from UAVs decreased model precision in both RGB and multispectral scenarios. This study reaffirms the potential of U-Net CNNs for BW detection, emphasizing the suitability of the suggested method for deployment in diverse beach geomorphology, requiring no high-end computing resources, and thereby facilitating more accessible applications in coastal monitoring and management.
Datasets with Rich Labels for Machine Learning

Most datasets used for classification use hard labels. In this paper, five new datasets labeled with uncertainty and imprecision by crowdsourcing contributors are presented. Richer labels are modeled with the theory of belief functions, which generalizes several reasoning frameworks with uncertainty, such as possibilities or probabilities. These datasets can be used with classical models using hard labels but also with probabilistic, fuzzy or even evidential models. Several concrete application cases are presented, for which these new datasets provide a useful knowledge representation of the user's uncertainty.
Straightforward Magnetic Resonance Temperature Measurements Combined with High Frame Rate and Magnetic Susceptibility Correction

Proton resonance frequency shift (PRFS) is an MRI-based simple temperature mapping method that exhibits higher spatial and temporal resolution than temperature mapping methods based on T1 relaxation time and diffusion. PRFS temperature measurements are validated against fiber-optic thermal sensors (FOSs). However, the use of FOSs may introduce temperature errors, leading to both underestimation and overestimation of PRFS measurements, primarily due to material susceptibility changes caused by the thermal sensors. In this study, we demonstrated susceptibility-corrected PRFS (scPRFS) with a high frame rate and accuracy for suitably distributed temperatures. A single-echo-based background removal technique was employed for phase variation correction, primarily owing to magnetic susceptibility, which enabled fast temperature mapping. The scPRFS was used to validate the temperature fidelity by comparing the temperatures of fiber-optic sensors and conventional PRFS through phantom-mimicked human and ex vivo experiments. This study demonstrates that scPRFS measurements in agar-gel are in good agreement with the thermal sensor readings, with a root mean square error (RMSE) of 0.33–0.36 °C in the phantom model and 0.12–0.16 °C in the ex vivo experiment. These results highlight the potential of scPRFS for precise thermal monitoring and ablation in both low- and high-temperature non-invasive therapies.