Miracle-dz/UniFAR-FTUs huggingface dataset:
Standardized Protocol for Chest Tube Management for Trauma Patients Significantly Decreases Complications

Background As health care shifts to a value-based model with a focus on patient outcomes per dollar spent, it is important to develop and evaluate standardized protocols that ultimately lead to improved patient outcomes and decreased hospital complications. Prior to our chest tube protocol, chest tube management at our Trauma Center was nonuniform and surgeon-specific. The aim of this study was to (1) develop an institutional standardized protocol for chest tube management at our Level II Trauma Center and (2) compare patient outcomes before and after the implementation of our protocol. Methods An institutional, standardized protocol was initiated at our Level II-Certified Trauma Center teaching hospital in 2014. An IRB-approved, single-institution retrospective chart review was performed between January 2011 and May 2017, in order to capture the 3 years prior and 3 years after protocol implementation. All patients with a diagnosis of hemothorax or pneumothorax (H/PTX) from blunt or penetrating trauma that resulted in a >24 French chest tube placement were included in the study. Patients were excluded if interventional radiology (IR) placed the chest tube, the mechanism was nontraumatic, or the patient expired at index hospitalization. Univariate analyses were performed to evaluate significant differences in patient outcomes before and after the implementation of the protocol. Results A total of 143 patients were analyzed for this study, with 43 preprotocol patients and 100 postprotocol patients. Hospital length of stay (LOS), persistent H/PTX, and the need for further surgical intervention all improved after the implementation of the standardized protocol (p < 0.04). Conclusions Our standardized protocol for chest tube management at our Level II Trauma Center significantly improved patient outcomes and can serve as a model for similar institutions.
Understanding Roles and Entities: Datasets and Models for Natural Language Inference

We present two new datasets and a novel attention mechanism for Natural Language Inference (NLI). Existing neural NLI models, even though when trained on existing large datasets, do not capture the notion of entity and role well and often end up making mistakes such as "Peter signed a deal" can be inferred from "John signed a deal". The two datasets have been developed to mitigate such issues and make the systems better at understanding the notion of "entities" and "roles". After training the existing architectures on the new dataset we observe that the existing architectures does not perform well on one of the new benchmark. We then propose a modification to the "word-to-word" attention function which has been uniformly reused across several popular NLI architectures. The resulting architectures perform as well as their unmodified counterparts on the existing benchmarks and perform significantly well on the new benchmark for "roles" and "entities".
Effects of sedimentation on productivity, nutrient cycling, and community composition in riparian forests associated with ephemeral streams at Ft. Benning, GA, USA

Riparian forests serve an essential function in preserving water quality through the filtering of sediments and nutrients from surface runoff. However, little is known about the impact of sediment deposition on productivity in riparian forests. Sediment inputs may act as a subsidy to forest productivity by providing additional nutrients for plant uptake or may act as a stress by creating anoxic soil conditions. This study determined how sediment deposition affected riparian forests along ephemeral headwater streams at Ft. Benning, GA, USA. Aboveand belowground productivity, LAI, and standing crop biomass were compared along a gradient of current sedimentation rates in 17 riparian forests. Annual litterfall production was determined from monthly collections using 0.25 m traps; woody biomass was determined from annual DBH measurements using species-specific allometric equations; fine root productivity was determined using sequential coring; LAI was measured by expanding specific leaf area by annual litterfall production; and shrub biomass was determined using species-specific biomass equations based on height and root collar diameter. Significant declines in litterfall, woody biomass production, fine root production, LAI, and shrub biomass were found with as little as 0.1-0.4 cm yr sedimentation. We conclude that the levels of sedimentation in 14 this study do not subsidize growth in riparian forests, but create a stress similar to that found under flooded conditions.
Fractal analysis is a useful tool for evaluating prostate tissue remodeling caused by ethanol consumption and androgen therapy

Abstract Alcohol has been widely consumed for centuries and is linked to the aggravation of diseases. Several studies have shown that excessive consumption of ethanol results in morphophysiological changes in the male reproductive system. One of the effects of ethanol is the decrease in testosterone concentration and hormonal therapies are an alternative to minimize the changes resulting from chronic alcoholism. Qualitative studies were commonly carried out to evaluate the male histopathological alterations resulting from ethanol consumption, being necessary quantitative and non-subjective techniques. This study analyzes the importance of fractal analysis as a useful tool to identify and quantify tissue remodeling in rats submitted to ethanol consumption and hormone therapy with testosterone. Prostate of animals submitted to chronic ethanol consumption showed tissue disorganization, which was confirmed by an increasing of fractal dimension. Regarding the prostatic stroma, collagen fractal dimension and quantification revealed lower values in animals that were only submitted to androgen therapy. Thus, we can conclude that the fractal analysis was a useful tool to quantify tissue changes caused by ethanol consumption and androgen therapy.
Stress Energy Tensor Study in Fluid Mechanics

This paper is to summarize the involvement of the stress energy tensor in the study of fluid mechanics. In the first part we will see the implication that carries the stress energy tensor in the framework of general relativity. In the second part, we will study the stress energy tensor under the mechanics of perfect fluids, allowing us to lead third party in the case of Newtonian fluids, and in the last part we will see that it is possible to define space-time as a no-Newtonian fluids.
Nutrient Deficiencies Impact on the Cellular and Metabolic Responses of Saxitoxin Producing Alexandrium minutum: A Transcriptomic Perspective

Dinoflagellate Alexandrium minutum Halim is commonly associated with harmful algal blooms (HABs) in tropical marine waters due to its saxitoxin production. However, limited information is available regarding the cellular and metabolic changes of A. minutum in nutrient-deficient environments. To fill this gap, our study aimed to investigate the transcriptomic responses of A. minutum under nitrogen and phosphorus deficiency. The induction of nitrogen and phosphorus deficiency resulted in the identification of 1049 and 763 differently expressed genes (DEGs), respectively. Further analysis using gene set enrichment analysis (GSEA) revealed 702 and 1251 enriched gene ontology (GO) terms associated with nitrogen and phosphorus deficiency, respectively. Our results indicate that in laboratory cultures, nitrogen deficiency primarily affects meiosis, carbohydrate catabolism, ammonium assimilation, ion homeostasis, and protein kinase activity. On the other hand, phosphorus deficiency primarily affects the carbon metabolic response, cellular ion transfer, actin-dependent cell movement, signalling pathways, and protein recycling. Our study provides valuable insights into biological processes and genes regulating A. minutum’s response to nutrient deficiencies, furthering our understanding of the ecophysiological response of HABs to environmental change.
The Potentials of Raising Muscovy duck (Cairina moschata) in Bangladesh- A Review

Bangladesh is a developing country where duck production could play an important role for the rural economy, nutrition and health of the coastal people. Crop production in coastal areas is challenging and crops being deficient in many micronutrients, plant-based complementary foods are insufficient to meet the deficient micronutrients. Further, Bangladesh being a riverine country of the south Asia, many rivers, haors, coastal areas, marshy lands, ponds, lakes, water reservoirs, wetlands, canals and creeks are available, where muscovy ducks can be reared easily, but chicken production is not sensible or feasible at all. Climate of Bangladesh is especially suitable for rearing them. Many people of Bangladesh like duck meat more than the chicken meat. Meat and eggs are the most important sources of dietary protein for the people of Bangladesh. Ducks could play an important role in providing animal protein (meat and egg) and income sources for the rural people. In this connection, the Muscovy duck could be a special one in contributing greater amount of meat, as it is comparatively bigger in size than the indigenous ducks (4.6-6.8 kg for male). Moreover, the duck is well- fleshed, light dark carcass, good flavored meat with less fat than the other common ducks. Their egg size is bigger and egg production is 100-125 per year under good management condition. An adult muscovy provides more meat than the similar aged chicken. They can survive better in hot, humid weather than the other common ducks. The per unit price of muscovy duck meat is more than the other duck meats. Therefore, raising muscovy duck either in small or large scale production might be a promising enterprise in Bangladesh.
Phytochemical Analysis of Careya arborea Roxb. Root Extracts: A Qualitative Analytical Approach

The examination of phytochemicals and identifying the presence of bioactive substances within plants used for medicinal purposes; ultimately promotes the advancement of medication exploration. In this paper, a qualitative analysis was carried out on the root extracts of Careya arborea Roxb . with different solvents. The qualitative examination confirmed several phytocompounds in the extracts of C. arborea roots. The water extract had the maximum extraction yield of 18.97 g/100 g, while the petroleum ether extract exhibited the lowest extraction yield of 8.28 g/100 g. The presence of various bioactive constituents in C. arborea facilitates its use by conventional herbal healers and allows for its application in the treatment of numerous ailments. The research unveiled the distinct attributes of individual raw substances, rendering them appropriate for recognition and regulation in order to improve the market value of the plants
Offline Trajectory Generation for Bipedal Robot Using Linear Inverted Pendulum Model

Reduced order model (ROM)-based controllers have proved to be effective to generate stable bipedal locomotion. However, it is important to understand the limitations and effectiveness of these models without implementing any controllers. This study highlights the versatility of the Linear Inverted Pendulum Model (LIPM) at various walking speeds. Firstly, the Centre of Mass (COM) trajectory has been generated using the LIPM model, and the foot motion trajectory has been created using a sixth-order polynomial function. The trajectory is generated using a predefined step length, speed of locomotion and COM height. Secondly, the task space trajectory has been converted into a joint space trajectory through inverse kinematics for a 6-degree-of-freedom leg. To facilitate the proper walking motion the contact between the foot sole and the ground is implemented. Finally, a simple bipedal robot in MATLAB/Simulink has been modelled and the generated trajectories were implemented.
Engagement-Free and Contactless Bed Occupancy and Vital Signs Monitoring

This article presents the design and evaluation of an engagement-free and contactless vital signs and occupancy monitoring system called BedDot. While many existing works demonstrated contactless vital signs estimation, they do not address the practical challenge of environment noises, online bed occupancy detection, and data quality assessment in the real-world environment. This work presents a robust signal quality assessment algorithm consisting of three parts: 1) bed occupancy detection; 2) movement detection; and 3) heartbeat detection, to identify high-quality data. It also presents a series of innovative vital signs estimation algorithms that leverage the advanced signal processing and Bayesian theorem for contactless heart rate (HR), respiratory rate (RR), and interbeat interval (IBI) estimation. The experimental results demonstrate that BedDot achieves over 99% accuracy for bed occupancy detection, and MAE of 1.38 BPM, 1.54 BPM, and 24.84 ms for HR, RR, and IBI estimation, respectively, compared with an FDA-approved device. The BedDot system has been extensively tested with data collected from 75 subjects for more than 80 h under different conditions, demonstrating its generalizability across different people and environments.
Cavitation erosion and corrosion-cavitation synergism behaviour of CoCrFeNiMnTi x high entropy alloy coatings prepared by laser cladding

ABSTRACT Cavitation erosion and corrosion-cavitation synergism behavior of CoCrFeNiMnTi x (x = 0.5, 1.0, 1.5, 2.0 in atomic ratio) high entropy alloy coatings were analyzed. The sample with x = 1.0 showed the best cavitation erosion resistance due to the low weight loss and the maximum erosion rate. The protective ability of passivation film also displayed an increased first and then decreased tendency with the increase of Ti content as indicated by corrosion-cavitation synergism determined by open circuit potential method under cavitation erosion and quiescence condition. The sample with x = 1.0 displayed good re-passivation ability of passivation film according to open circuit potential behavior under cavitation erosion and quiescence condition. In general, the sample with x = 1.0 exhibited the highest cavitation erosion, the best self-repairing ability of the passivation film under the corrosion-cavitation synergism condition, which showed a great potential in the application of ocean engineering field as fluid-passing parts.
High-Accuracy, High-Gain Phased Array Utilizing Matrix-Sum and Tunable Amplifier Techniques

This paper presents an 8-element phased array system and proposes a novel beam control method—namely, matrix-sum method—that can achieve beam steering and beam-width control. The system architecture comprises an $8\times 8$ phase matrix network and a 1-to-8 real number weighting network. The 1-to-8 real number weighting network simultaneously supplies the required weighting value to all input ports of the phase matrix network, enabling the adjustment of the phase difference and power ratio between adjacent output signals and thereby generating the desired beam. According to the equations used to calculate the weighting values, the matrix-sum method requires only real number weighting to achieve beam synthesis with steering and tapering functions if used with a suitable phase matrix. Comparison results revealed that for the same number of control bits, the proposed method system exhibited higher beam-steering accuracy and system gain in different beam pattern cases than phased array systems that use conventional and vector-sum phase shifters. The proposed phased array system was fabricated and experimentally investigated at 3.5 GHz. The results indicated that it achieved fully controllable beam steering with a fine beam resolution of 1° steps. Additionally, the system’s sum, difference, and tapering beam patterns were accurate compared with ideal beam patterns.
Chemical risk assessment for storage of hazardous materials in the context of Land Use Planning.

Historical technological accidents caused in numerous occasions the major environmental pollution and the loss of many human lives. Lessons learned from these accidents contributed significantly to the development of technological safety in two ways: technological and legislative. After three years from the adherence of Romania to EU, a coherent legislation for land-use planning is still missing in the context of Article 12 of Seveso Directive. Nowadays there are more than 200 Seveso-type economical operators in Romania, most of them with major risk, located close to areas highly vulnerable for population or environment. The elaboration of risk assessment studies for the technological accidents prevention, land-use planning and emergency planning is necessary and essential for these sites. Based on these studies the population can be informed, instructed and prepared for accidents, thus saving many lives. In this paper the development of a risk assessment methodology for land-use and emergency planning is proposed for Seveso-type sites, where large quantities of dangerous, explosive, flammable or toxic substances are stored, handled or processed. Three case studies were considered while elaborating this methodology. These case studies include technological accident scenarios for the storage of common hazardous substances: propane, chlorine and ammonium nitrate. Several methodologies applied in the EU member states were approached and the proposed methodology is based on the results of this research.
Synergistic Pulmonoprotective Effect of Natural Prolyl Oligopeptidase Inhibitors in In Vitro and In Vivo Models of Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) is a highly morbid inflammatory lung disease with limited pharmacological interventions. The present study aims to evaluate and compare the potential pulmonoprotective effects of natural prolyl oligopeptidase (POP) inhibitors namely rosmarinic acid (RA), chicoric acid (CA), epigallocatechin-3-gallate (EGCG) and gallic acid (GA), against lipopolysaccharide (LPS)-induced ARDS. Cell viability and expression of pro-inflammatory mediators were measured in RAW264.7 cells and in primary murine lung epithelial and bone marrow cells. Nitric oxide (NO) production was also assessed in unstimulated and LPS-stimulated RAW264.7 cells. For subsequent in vivo experiments, the two natural products (NPs) with the most favorable effects, RA and GA, were selected. Protein, cell content and lipid peroxidation levels in bronchoalveolar lavage fluid (BALF), as well as histopathological changes and respiratory parameters were evaluated in LPS-challenged mice. Expression of key mediators involved in ARDS pathophysiology was detected by Western blotting. RA and GA favorably reduced gene expression of pro-inflammatory mediators in vitro, while GA decreased NO production in macrophages. In LPS-challenged mice, RA and GA co-administration improved respiratory parameters, reduced cell and protein content and malondialdehyde (MDA) levels in BALF, decreased vascular cell adhesion molecule-1 (VCAM-1) and the inducible nitric oxide synthase (iNOS) protein expression, activated anti-apoptotic mechanisms and down-regulated POP in the lung. Conclusively, these synergistic pulmonoprotective effects of RA and GA co-administration could render them a promising prophylactic/therapeutic pharmacological intervention against ARDS.
Swarm-intelligent elephant herding optimized support vector machine for predicting heart disease

Considering the significant worldwide mortality rate of cardiac disease, early and precise prognosis is essential to enhancing patient outcomes. The accuracy, effectiveness, and dependability of the heart disease prediction techniques currently in use, however, continue to encounter difficulties. Therefore, it is essential to create novel strategies that can get beyond these constraints and offer a better way to forecast cardiac disease. A novel advanced elephant herding optimised support vector machine (AEHO-SVM) technique utilized for the study in suggest method for predicting cardiovascular disease. A heart disease dataset is used to assess the efficacy of the suggested AEHO-SVM algorithm. To deal with missing values, normalise the data, and minimise dimensionality, the dataset is pre-processed. The AEHO-SVM approach aims to maximise classification accuracy while lowering the possibility of misdiagnosis by optimising the hyperplane separation and changing the support vectors iteratively. A number of metrics, like sensitivity, accuracy, f-measure, and specificity are used for assess model's performance. The experiment show that the AEHO-SVM technique works better than conventional methods and achieves good predictive accuracy for the diagnosis of heart disease. A suggested AEHO-SVM technique makes use of the collective thinking of elephant herding and its built-in optimisation skills to provide a more effective and trustworthy prediction method.
Hierarchical Autoencoder Frequency Features for Stress Detection

Stress has a significant negative impact on people, which has made it a primary social concern. Early stress detection is essential for effective stress management. This study proposes a Deep Learning (DL) method for effective stress detection using multimodal physiological signals - Electrocardiogram (ECG) and Electrodermal activity (EDA). The extensive latent feature representation of DL models has yet to be fully explored. Hence, this paper proposes a hierarchical AutoEncoder (AE) feature fusion on the frequency domain. The latent representations from different layers of the autoencoder are combined and given as input to the classifier - Convolutional Recurrent Neural Network with Squeeze and Excitation (CRNN-SE) model. A two-set performance comparison is performed (romannum 1) performance on frequency band features, and raw data are compared. (romannum 2) autoencoders trained on three cost functions - Mean Squared Error (MSE), Kullback-Leibler (KL) divergence, and Cosine similarity performance are compared on frequency band features and raw data. To verify the generalizability of our approach, we tested it on four benchmark datasets- WAUC, CLAS, MAUS and ASCERTAIN. Results show that frequency band features showed better results than raw data by 4-8%, respectively. MSE loss produced better results than other losses for both frequency band features and raw data by 3-7%, respectively. The proposed approach considerably outperforms existing stress detection models that are subject-independent by 1-2%, respectively.
The Effect of the ‘Fast Game’ in Handball on the Final Ranking of Teams in Major International Competitions

The main purpose of that study was to identify which of the independent variables that measured fast play tactics (Fast Throw-Offs and Fast Breaks) could predict a team's ranking in a high-level tournament. Researchers collected statistical data on the teams that took part in the final tournament of the Men’s EHF EURO 2022