As industrial modernization advances rapidly, the need for energy becomes increasingly urgent. This paper aims to enhance the current burner design by optimizing the combustion calorific value, minimizing pollutant emissions, and validating the accuracy of the burner model using experimental data from previous studies. The enhanced porous medium burner model is used to investigate the burner’s combustion and pollutant emission characteristics at various flow rates, equivalence ratios, combustion orifice sizes, and porosity of porous media. In comparison with the previous model, the combustion traits during ethylene combustion and the emission properties of pollutants under various operational circumstances have been enhanced with the enhanced porous medium burner model. The maximum temperature of ethylene combustion in the enhanced model is 174 k higher than that before the improvement, and the CO emissions are reduced by 31.9%. It is believed that the findings will serve as a guide for the practical implementation of porous media combustion devices. Full article

Ground subsidence often occurs over a large area. Although traditional monitoring methods have high accuracy, they cannot perform wide-area ground deformation monitoring. Synthetic Aperture Radar (SAR) interferometry (InSAR) technology utilizes phase information in SAR images to extract surface deformation information in a low-cost, large-scale, high-precision, and high-efficiency manner. With the increasing availability of SAR satellite data and the rapid development of InSAR technology, it provides the possibility for wide-area ground deformation monitoring using InSAR technology. Traditional time-series InSAR methods have cumbersome processing procedures, have large computational requirements, and rely heavily on manual intervention, resulting in relatively low efficiency. This study proposes a strategy for wide-area InSAR multi-scale deformation monitoring to address this issue. The strategy first rapidly acquires ground deformation information using Stacking technology, then identifies the main subsidence areas by setting deformation rate thresholds and visual interpretation, and finally employs advanced TS-InSAR technology to obtain detailed deformation time series for the main subsidence areas. The Turpan Basin in Xinjiang, China, was selected as the study area (7474.50 km²) to validate the proposed method. The results are as follows: (1) The basin is generally stable, but there is ground subsidence in the southern plain area, mainly affecting farmland. (2) From 2016 to 2019, the maximum subsidence rate in the farmland area was approximately 0.13 m/yr, with a maximum cumulative subsidence of about 0.25 m, affecting a total area of approximately 952.49 km². The subsidence mainly occurred from late spring to mid-autumn, while lifting or subsidence mitigation occurred from late autumn to early spring. The study also analyzed the impacts of rainfall, geographical environment, and human activities on subsidence and found that multiple factors, including water resource reduction, overexploitation, geological characteristics, and the expansion of human activities, contributed to the subsidence problem in the Turpan Basin. This method contributes to wide-area InSAR deformation monitoring and the application of InSAR technology in engineering. Full article

Functional connectivity (FC) obtained from resting-state functional magnetic resonance imaging has been integrated with machine learning algorithms to deliver consistent and reliable brain disease classification outcomes. However, in classical learning procedures, custom-built specialized feature selection techniques are typically used to filter out uninformative features from FC patterns to generalize efficiently on the datasets. The ability of convolutional neural networks (CNN) and other deep learning models to extract informative features from data with grid structure (such as images) has led to the surge in popularity of these techniques. However, the designs of many existing CNN models still fail to exploit the relationships between entities of graph-structure data (such as networks). Therefore, graph convolution network (GCN) has been suggested as a means for uncovering the intricate structure of brain network data, which has the potential to substantially improve classification accuracy. Furthermore, overfitting in classifiers can be largely attributed to the limited number of available training samples. Recently, the generative adversarial network (GAN) has been widely used in the medical field for its generative aspect that can generate synthesis images to cope with the problems of data scarcity and patient privacy. In our previous work, GCN and GAN have been designed to investigate FC patterns to perform diagnosis tasks, and their effectiveness has been tested on the ABIDE-I dataset. In this paper, the models will be further applied to FC data derived from more public datasets (ADHD, ABIDE-II, and ADNI) and our in-house dataset (PTSD) to justify their generalization on all types of data. The results of a number of experiments show the powerful characteristic of GAN to mimic FC data to achieve high performance in disease prediction. When employing GAN for data augmentation, the diagnostic accuracy across ADHD-200, ABIDE-II, and ADNI datasets surpasses that of other machine learning models, including results achieved with BrainNetCNN. Specifically, in ADHD, the accuracy increased from 67.74% to 73.96% with GAN, in ABIDE-II from 70.36% to 77.40%, and in ADNI, reaching 52.84% and 88.56% for multiclass and binary classification, respectively. GCN also obtains decent results, with the best accuracy in ADHD datasets at 71.38% for multinomial and 75% for binary classification, respectively, and the second-best accuracy in the ABIDE-II dataset (72.28% and 75.16%, respectively). Both GAN and GCN achieved the highest accuracy for the PTSD dataset, reaching 97.76%. However, there are still some limitations that can be improved. Both methods have many opportunities for the prediction and diagnosis of diseases. Full article

Traditional laboratory-based water quality monitoring and testing approaches are soon to be outdated, mainly because of the need for real-time feedback and immediate responses to emergencies. The more recent wireless sensor network (WSN)-based techniques are evolving to alleviate the problems of monitoring, coverage, and energy management, among others. The inclusion of the Internet of Things (IoT) in WSN techniques can further lead to their improvement in delivering, in real time, effective and efficient water-monitoring systems, reaping from the benefits of IoT wireless systems. However, they still suffer from the inability to deliver accurate real-time data, a lack of reconfigurability, the need to be deployed in ad hoc harsh environments, and their limited acceptability within industry. Electronic sensors are required for them to be effectively incorporated into the IoT WSN water-quality-monitoring system. Very few electronic sensors exist for parameter measurement. This necessitates the incorporation of artificial intelligence (AI) sensory techniques for smart water-quality-monitoring systems for indicators without actual electronic sensors by relating with available sensor data. This approach is in its infancy and is still not yet accepted nor standardized by the industry. This work presents a smart water-quality-monitoring framework featuring an intelligent IoT WSN monitoring system. The system uses AI sensors for indicators without electronic sensors, as the design of electronic sensors is lagging behind monitoring systems. In particular, machine learning algorithms are used to predict E. coli concentrations in water. Six different machine learning models (ridge regression, random forest regressor, stochastic gradient boosting, support vector machine, k-nearest neighbors, and AdaBoost regressor) are used on a sourced dataset. From the results, the best-performing model on average during testing was the AdaBoost regressor (a $\overline{MAE}$ of 14.37 counts/100 mL), and the worst-performing model was stochastic gradient boosting (a $\overline{MAE}$ of 42.27 counts/100 mL). The development and application of such a system is not trivial. The best-performing water parameter set (Set A) contained pH, conductivity, chloride, turbidity, nitrates, and chlorophyll. Full article

The high mortality rate among patients with acute myocardial infarction (AMI) is one of the main problems of modern cardiology. It is quite obvious that there is an urgent need to create more effective drugs for the treatment of AMI than those currently used in the clinic. Such drugs could be enzyme-resistant peptide analogs of glucagon-like peptide-1 (GLP-1). GLP-1 receptor (GLP1R) agonists can prevent ischemia/reperfusion (I/R) cardiac injury. In addition, chronic administration of GLP1R agonists can alleviate the development of adverse cardiac remodeling in myocardial infarction, hypertension, and diabetes mellitus. GLP1R agonists can protect the heart against oxidative stress and reduce proinflammatory cytokine (IL-1β, TNF-α, IL-6, and MCP-1) expression in the myocardium. GLP1R stimulation inhibits apoptosis, necroptosis, pyroptosis, and ferroptosis of cardiomyocytes. The activation of the GLP1R augments autophagy and mitophagy in the myocardium. GLP1R agonists downregulate reactive species generation through the activation of Epac and the GLP1R/PI3K/Akt/survivin pathway. The GLP1R, kinases (PKCε, PKA, Akt, AMPK, PI3K, ERK1/2, mTOR, GSK-3β, PKG, MEK1/2, and MKK3), enzymes (HO-1 and eNOS), transcription factors (STAT3, CREB, Nrf2, and FoxO3), K_ATP channel opening, and MPT pore closing are involved in the cardioprotective effect of GLP1R agonists. Full article

Background and Objectives: The influence of montelukast (MK), an antagonist of cysLT1 leukotriene receptors, on lung lesions caused by experimental diabetes was studied. Materials and Methods: The study was conducted on four groups of six adult male Wistar rats. Diabetes was produced by administration of streptozotocin 65 mg/kg ip. in a single dose. Before the administration of streptozotocin, after 72 h, and after 8 weeks, the serum values of glucose, SOD, MDA, and total antioxidant capacity (TAS) were determined. After 8 weeks, the animals were anesthetized and sacrificed, and the lungs were harvested and examined by optical microscopy. Pulmonary fibrosis, the extent of lung lesions, and the lung wet-weight/dry-weight ratio were evaluated. Results: The obtained results showed that MK significantly reduced pulmonary fibrosis (3.34 ± 0.41 in the STZ group vs. 1.73 ± 0.24 in the STZ+MK group p < 0.01) and lung lesion scores and also decreased the lung wet-weight/dry-weight (W/D) ratio. SOD and TAS values increased significantly when MK was administered to animals with diabetes (77.2 ± 11 U/mL in the STZ group vs. 95.7 ± 13.3 U/mL in the STZ+MK group, p < 0.05, and 25.52 ± 2.09 Trolox units in the STZ group vs. 33.29 ± 1.64 Trolox units in the STZ+MK group, respectively, p < 0.01), and MDA values decreased. MK administered alone did not significantly alter any of these parameters in normal animals. Conclusions: The obtained data showed that by blocking the action of peptide leukotrienes on cysLT1 receptors, montelukast significantly reduced the lung lesions caused by diabetes. The involvement of these leukotrienes in the pathogenesis of fibrosis and other lung diabetic lesions was also demonstrated. Full article

One way to reduce the negative impact of human activity on the natural environment is to use natural, easily available and relatively cheap to produce compounds in industrial processes. One such compound is naturally occurring calcium carbonate (CaCO₃). This compound has adsorption properties so that it can be an alternative to commonly used adsorbents. The aim of this work is to determine the possibility of using CaCO₃ to remove pharmaceutical substances such as sulfadiazine and tetracycline from water. The CaCO₃ used in this work was synthesised using our own method, which allows the production of CaCO₃ particles with nanometric size. In the conducted research, calcium carbonate was used in the form of a suspension in purified solutions and as an inorganic filling of the developed membranes. The mass of pharmaceutical substances removed from their aqueous solutions was determined in the tests carried out. Based on the results obtained, it can be concluded that CaCO₃ has the ability to adsorb both tetracycline and sulfadiazine. In suspension tests, the mass of the removed substances per unit mass of adsorbent was 1.52 mg/g and 6.85 mg/g, respectively. In turn, in the case of the integrated process using the developed membranes, the mass of the removed substances per unit mass of adsorbent was 109 mg/g and 97 mg/g. Full article

As water and electrical networks cannot be entirely independent, a more integrated approach, the water–energy nexus (WEN), is developed. A WEN is the basis of a smart city where water and electrical networks are interconnected and integrated by implementing efficient management strategies. Accordingly, this study develops a dynamic co-optimization model for designing and operating an integrated power and water system. The proposed co-optimization model minimizes the total annual and operational costs of a micro-WEN system while capturing its optimum design values and operating conditions and meeting the demands of the electrical and water networks. Furthermore, this work presents a plan for transitioning from thermal desalination to reverse osmosis (RO) desalination in the United Arab Emirates (UAE). The key objective is to decouple electricity and water production, effectively tackling the issue of operating the UAE’s power plants at low efficiency during the winter while ensuring an adequate water supply to meet the growing demand. The results show that the co-optimization model provides a significant reduction in the total operational cost with the integration of photovoltaic energy and shifting to RO. Most importantly, the micro-WEN system is optimized over multiple timescales to reduce the computation effort and memory requirements. Full article

The objective of this work is to compare the levels of bioactive compounds in fresh and freeze-dried basil leaves (Ocimum basilicum), using methodological procedures that follow internationally recommended and accepted standards. The results show comparisons of bioactives between fresh and freeze-dried leaves, respectively, with results expressing the average levels of vitamin C (9.50–63.3 mg/100 g); total polyphenols (1.8–3.9 mgEAG/g); flavonoids (0.73–1.78 mg/g); chlorophyll a (2287.8–1003.8 μg/100 g); chlorophyll b (2606–2287 μg/100 g) and total carotenoids with averages of 16.71–20.6 mg/100 g). Regarding color, there was variation in the parameters L*, a*, and b* of the dry sample, but the tendency towards green e (a+) and yellow (b−) was maintained. Infrared analysis (FTIR) demonstrated the presence of functional groups related to cellulose, hemicellulose, and lignin. Thermogravimetry (TG/DTG) shows stability in the range of 234 °C, showing a more intense mass loss at 294.6 °C. Given the data, it is possible to infer that the application of freeze-drying produces few changes in bioactive compounds and chemical groups and maintains good thermal stability, proving to be a viable alternative to increasing the commercialization of basil leaves, as it prolongs their useful life, and increases the forms of food applications. Full article

Underwriters play a pivotal role in the IPO process. Information entropy, a tool for measuring the uncertainty and complexity of information, has been widely applied to various issues in complex networks. Information entropy can quantify the uncertainty and complexity of nodes in the network, providing a unique analytical perspective and methodological support for this study. This paper employs a bipartite network analysis method to construct the relationship network between underwriters and accounting firms, using the centrality of underwriters in the network as a measure of their influence to explore the impact of underwriters’ influence on the distribution of interests and audit outcomes. The findings indicate that a more pronounced influence of underwriters significantly increases the ratio of underwriting fees to audit fees. Higher influence often accompanies an increase in abnormal underwriting fees. Further research reveals that companies underwritten by more influential underwriters experience a decline in audit quality. Finally, the study reveals that a well-structured audit committee governance and the rationalization of market sentiments can mitigate the negative impacts of underwriters’ influence. The innovation of this paper is that it enriches the content related to underwriters by constructing the relationship network between underwriters and accounting firms for the first time using a bipartite network through the lens of information entropy. This conclusion provides new directions for thinking about the motives and possibilities behind financial institutions’ cooperation, offering insights for market regulation and policy formulation. Full article

Functional foods with probiotics are safe and effective dietary supplements to improve overweight and obesity. Thus, altering the intestinal microflora may be an effective approach for controlling or preventing obesity. This review aims to summarize the experimental method used to study probiotics and obesity, and recent advances in probiotics against obesity. In particular, we focused on studies (in vitro and in vivo) that used probiotics to treat obesity and its associated comorbidities. Several in vitro and in vivo (animal and human clinical) studies conducted with different bacterial species/strains have reported that probiotics promote anti-obesity effects by suppressing the differentiation of pre-adipocytes through immune cell activation, maintaining the Th1/Th2 cytokine balance, altering the intestinal microbiota composition, reducing the lipid profile, and regulating energy metabolism. Most studies on probiotics and obesity have shown that probiotics are responsible for a notable reduction in weight gain and body mass index. It also increases the levels of anti-inflammatory adipokines and decreases those of pro-inflammatory adipokines in the blood, which are responsible for the regulation of glucose and fatty acid breakdown. Furthermore, probiotics effectively increase insulin sensitivity and decrease systemic inflammation. Taken together, the intestinal microbiota profile found in overweight individuals can be modified by probiotic supplementation which can create a promising environment for weight loss along enhancing levels of adiponectin and decreasing leptin, tumor necrosis factor (TNF)-α, interleukin (IL)-6, monocyte chemotactic protein (MCP)-1, and transforming growth factor (TGF)-β on human health. Full article

This paper provides insights into the four key behaviors and mechanisms of the aging to failure of batteries in micro-overcharge cycles at different temperatures, as well as the changes in thermal stability. The test results from a scanning electron microscope (SEM) and an energy-dispersive spectrometer (EDS) indicate that battery failure is primarily associated with the rupture of cathode materials, the fracturing and pulverization of electrode materials on the anode current collector, and the formation of lithium dendrites. Additionally, battery safety is influenced by environmental temperatures and the battery’s state of health (SOH), with failed batteries exhibiting the poorest stability and the highest mass loss rates. Under isothermal conditions, micro-overcharge leads to battery failure without thermal runaway. Thus, temperature stands out as the most influential factor in battery safety. These insights hold significant theoretical and practical value for the development of more precise and secure battery management systems. Full article

Familial Alzheimer’s disease (FAD) is a complex and multifactorial neurodegenerative disorder for which no curative therapies are yet available. Indeed, no single medication or intervention has proven fully effective thus far. Therefore, the combination of multitarget agents has been appealing as a potential therapeutic approach against FAD. Here, we investigated the potential of combining tramiprosate (TM), curcumin (CU), and the JNK inhibitor SP600125 (SP) as a treatment for FAD. The study analyzed the individual and combined effects of these two natural agents and this pharmacological inhibitor on the accumulation of intracellular amyloid beta iAβ; hyperphosphorylated protein TAU at Ser²⁰²/Thr²⁰⁵; mitochondrial membrane potential (DY_m); generation of reactive oxygen species (ROS); oxidized protein DJ-1; proapoptosis proteins p-c-JUN at Ser⁶³/Ser⁷³, TP53, and cleaved caspase 3 (CC3); and deficiency in acetylcholine (ACh)-induced transient Ca²⁺ influx response in cholinergic-like neurons (ChLNs) bearing the mutation I416T in presenilin 1 (PSEN1 I416T). We found that single doses of TM (50 μM), CU (10 μM), or SP (1 μM) were efficient at reducing some, but not all, pathological markers in PSEN 1 I416T ChLNs, whereas a combination of TM, CU, and SP at a high (50, 10, 1 μM) concentration was efficient in diminishing the iAβ, p-TAU Ser²⁰²/Thr²⁰⁵, DJ-1Cys¹⁰⁶-SO_3, and CC3 markers by −50%, −75%, −86%, and −100%, respectively, in PSEN1 I417T ChLNs. Although combinations at middle (10, 2, 0.2) and low (5, 1, 0.1) concentrations significantly diminished p-TAU Ser²⁰²/Thr²⁰⁵, DJ-1Cys¹⁰⁶-SO_3, and CC3 by −69% and −38%, −100% and −62%, −100% and −62%, respectively, these combinations did not alter the iAβ compared to untreated mutant ChLNs. Moreover, a combination of reagents at H concentration was able to restore the dysfunctional ACh-induced Ca²⁺ influx response in PSEN 1 I416T. Our data suggest that the use of multitarget agents in combination with anti-amyloid (TM, CU), antioxidant (e.g., CU), and antiapoptotic (TM, CU, SP) actions might be beneficial for reducing iAβ-induced ChLN damage in FAD. Full article

Locating petroleum-productive wells using informed geological data, a conventional means, has proven to be tedious and undesirable by reservoir engineers. The former numerical simulator required a lengthy trial-and-error process to manipulate the variables and uncertainties that lie on the reservoir to determine the best placement of the well. Hence, this paper examines the use of a global genetic algorithm (GA) to optimize the placement of wells in complex reservoirs, rather than relying on gradient-based (GB) methods. This is because GB approaches are influenced by the solution’s surface gradient and may only reach local optima, as opposed to global optima. Complex reservoirs have rough surfaces with high uncertainties, which hinders the traditional gradient-based method from converging to global optima. The explicit focus of this study was to examine the impact of various initial well placement distributions, the number of random solution sizes and the crossover rate on cumulative oil production, the optimization of the synthetic reservoir model created by CMG Builder, CMOST, and IMEX indicated that using a greater number of random solutions led to an increase in cumulative oil production. Despite the successful optimization, more generations are required to reach the optimal solution, while the application of GA on our synthetic model has proven efficient for well placement; however, different optimization algorithms such as the improved particle swarm (PSO) and grey wolf optimization (GWO) algorithms could be used to redefine well-placement optimization in CMG. Full article

The purpose of this study was to develop an agro-healing program using rural resources for stressed adults and to measure its effectiveness. A one-day agro-healing program was developed using the resources of a care farm located in Cheongju, South Korea. A total of 37 adults in their 20s to 50s who were experiencing mild or more severe stress participated in the agro-healing program. Analysis of stress-related psychological and emotional indicators of the agro-healing program revealed that post-treatment stress, anxiety, and depression indicators of the healing program significantly decreased (p < 0.05). Furthermore, mood state, vitality, and resilience indicators increased significantly, which demonstrated effectiveness in improving the mental health of participants with mental health issues. A Pearson correlation analysis between each psychological and emotional variable after the program found that stress had a significant correlation with all variables. Subjective vitality had a full mediating effect on the relationship between stress and resilience. Finally, the one-day agro-healing program was found to help relieve symptoms in adults with stress. Full article

The aim of this study was to analyze the long-term results of different locoregional treatments for colorectal cancer liver metastases (CRLM), including transarterial chemoembolization (TACE), laser-induced thermotherapy (LITT) and microwave ablation (MWA). A total of 2140 patients with CRLM treated at our department between 1993 and 2020 were included in this retrospective study. The patients were divided into the following groups: LITT (573 patients; median age: 62 years), TACE + LITT (346 patients; median age: 62 years), MWA (67 patients; median age: 59 years), TACE + MWA (152 patients; median age: 65 years), and TACE (1002 patients; median age: 62 years). Median survival was 1.9 years in the LITT group and 1.7 years in the TACE + LITT group. The median survival times in the MWA group and TACE + MWA group were 3.1 years and 2.1 years, respectively. The median survival in the TACE group was 0.8 years. The 1-, 3-, and 5-year survival rates were 77%, 27%, and 9% in the LITT group and 74%, 18%, and 5% in the TACE + LITT group, respectively. The corresponding survival rates were 80%, 55%, and 33% in the MWA group, 74%, 36%, and 20% in the TACE + MWA group and 37%, 3%, and 0% in the TACE group, respectively. The long-term results of this study demonstrate the efficacy of locoregional treatments in treating patients with CRLM. The longest survival was found in the MWA group, followed by the combination therapy of TACE and MWA. Full article

The activation of endothelial cells is crucial for immune defense mechanisms but also plays a role in the development of atherosclerosis. We have previously shown that inflammatory stimulation of endothelial cells on top of elevated lipoprotein/cholesterol levels accelerates atherogenesis. The aim of the current study was to investigate how chronic endothelial inflammation changes the aortic transcriptome of mice at normal lipoprotein levels and to compare this to the inflammatory response of isolated endothelial cells in vitro. We applied a mouse model expressing constitutive active IκB kinase 2 (caIKK2)—the key activator of the inflammatory NF-κB pathway—specifically in arterial endothelial cells and analyzed transcriptomic changes in whole aortas, followed by pathway and network analyses. We found an upregulation of cell death and mitochondrial beta-oxidation pathways with a predicted increase in endothelial apoptosis and necrosis and a simultaneous reduction in protein synthesis genes. The highest upregulated gene was ACE2, the SARS-CoV-2 receptor, which is also an important regulator of blood pressure. Analysis of isolated human arterial and venous endothelial cells supported these findings and also revealed a reduction in DNA replication, as well as repair mechanisms, in line with the notion that chronic inflammation contributes to endothelial dysfunction. Full article

Streptococcus suis (S. suis) is a zoonotic pathogen capable of causing severe diseases in humans and pigs, including meningitis, sepsis, polyserositis, arthritis, and endocarditis. This study aimed to investigate the biological characteristics of 19 strains of S. suis isolated from diseased pigs in Hubei Province between 2021 and 2023. Through bioinformatics analysis, we investigated the serotype, MLST, pan-genome characteristics, SNP, AMR, and ICE of the 19 S. suis isolates. Among the 19 S. suis strains, ten serotypes were identified, and serotype 9 was the most prevalent (21.05%). Ten new alleles and nine new sequence types (STs) were discovered, with ST28 and ST243 emerging as the predominant STs. The results of the pan-genomic analysis of S. suis indicate that there are 943 core genes, 2259 shell genes, and 5663 cloud genes. Through SNP evolutionary analysis, we identified a strong genetic similarity between SS31 and the reference genome P1/7. The analysis of antibiotic resistance genes revealed widespread presence of erm(B) and tet(O) genes among 19 strains of S. suis. This association may be linked to the high resistance of S. suis to lincosamides, macrolides, and tetracyclines. Integrative and conjugative elements (ICEs) and integrative and mobilizable elements (IMEs) were identified in 16 strains, with a carriage rate of 84.21%, and resistance genes were identified within the ICE/IME elements of 8 strains. Antimicrobial susceptibility testing revealed that all strains showed sensitivity to vancomycin and lincomycin but resistance to tilmicosin, tiamulin, amoxicillin, and doxycycline. This study contributes to our understanding of the genomic diversity of S. suis in Hubei Province of China, providing essential data for the comprehensive prevention and control of S. suis infections in China. Full article

Background: Most people believe that student–athletes experience fewer difficulties related to mental health than non-sport participants. However, several studies have shown high depression levels or emotional difficulties in adolescent athletes. Most secondary school students have access to athletic trainers in their schools. Secondary school athletic trainers (SSATs) are medical professionals who can provide health care for student–athletes, and they could be appropriate supporters in providing mental health management in secondary schools. However, there are no studies that have addressed their preparedness and confidence level to manage potential risk factors and mental health disorders. This study aims to ascertain preparedness and confidence levels from SSATs’ perspectives in handling mental health disorders using a survey based on the mental health management guidelines and consensus statement. Methods: This is a cross-sectional study design. The research team created an online survey questionnaire based on the National Athletic Trainers’ Association (NATA) Mental Health Guidelines for Secondary School and Interassociation Recommendation: A Consensus Statement. Utilizing the NATA Research Survey Service, the online survey was emailed to SSATs who self-categorized as secondary school athletic trainers in the NATA membership system. (n = 171, 65% completion rate). SPSS was used to analyze the survey data. Result: This study found that 29.2% of SSATs reported they have policies or guidelines regarding mental health disorders management for minors. The most frequent policy was mandatory reporting in cases in which an individual is being abused or neglected (80.5%). The highest confidence area was aligned with the most frequent policy. The least frequent policy was considering unique stressors and triggers with student–athletes to recognize the potential mechanisms that may cause a mental illness or exacerbate an existing mental illness (58.5%). Even though the least frequent policy was not aligned with the least confidence area, it was the second lowest confidence level. This study identified significant differences between two different employment structures: school-based employment and hospital-based employment structures. Policies were more common in school-based employment than in hospital-based employment structures. Conclusion: This study demonstrated the gap between organizational and individual preparation. The majority of SSATs respondents expressed moderate to high confidence in their ability to manage mental health disorders, despite the lack of mental health policies or procedures in their secondary schools. This study recommends that SSATs create guidelines or procedures in the areas where they are least confident and prepared to offer mental health management for minor student–athletes. They can use the interassociation recommendations and the NATA guidelines for mental health care to close the gap. Full article

Thinning is a silvicultural process in which trees are both harvested selectively and systematically removed from a stand to enhance forest management and ecosystem dynamics. However, this practice is challenged by the mechanical damage to residual trees, and the nature of this damage, particularly on stand damage during mechanized row-thinning and manual selective thinning, in South Korea is unknown. Therefore, objectives of this study were to compare stand damage levels and wound characteristics between three different thinning operations: manual selective, manual row-, and mechanized row-thinning. After thinning, 12%, 15%, and 10% of the residual damaged trees were observed in manual selective, manual row-, and mechanized row-thinning, respectively. Both types of row-thinning predominantly demonstrated damages at the stem and butt region, whereas in manual selective thinning, the most of the damages occurred on the roots. Manual selective thinning exhibited a slightly larger average wound size (207 cm²) compared to mechanized row- (181 cm²) and manual row-thinning (165 cm²). The wound sizes on the stem in mechanized row-thinning were significantly higher than manual selective (p < 0.05). These results may be helpful in understanding exposure to damage among different thinning types and in managing its occurrence in future practices. Full article

The mechanical characteristics and sliding friction behaviors of AA7075 samples were studied in regard to structural states formed in them by ECAP and depending on the ECAP pass number. In addition, the effect of a counterbody’s material on the tribological characteristics of the samples was investigated by the examples of AISI 52100 steel, alumina Al₂O₃ and silicon nitride Si₃N₄. Vibration acceleration and acoustic emission signals with parameters such as acoustic emission energy and median frequency were used for characterizing the sliding regimes. The structural state and mechanical properties of the ECAPed AA7075 samples significantly affected their wear behaviors in dry sliding. The counterbody material had a significant influence on the formation of a transfer layer and the subsurface deformation of samples. The dynamic behavior of the tribosystem was studied and the relationship between the sliding parameters, vibrometry and acoustic emission signals was established. Full article

Lymphoproliferative diseases are a heterogeneous set of malignant clonal proliferations of lymphocytes. Despite well-established diagnostic criteria, the diagnosis remains difficult due to their variety in clinical presentation and immunophenotypic profile. Lymphoid T-cell disorders are less common than B-cell entities, and the lack of a clear immunophenotypic characteristic makes their identification hard. Flow cytometry turned out to be a useful tool in diagnosing T-cell disorders and to resolve complicated cases, especially if the number of analyzable neoplastic cells is small. We present a case of a 55-year-old man with simultaneous lymphoproliferative neoplastic T-cell clones, one αβ and the other γδ, identified and characterized by flow cytometry (FC), exploiting the variable expression intensity of specific markers. However, the patient’s rapid decline made it impossible to define a differential diagnosis in order to confirm the identity of the γδ clone, which remains uncertain. This case is added to the few other cases already documented in the literature, characterized by the co-existence of T-large granular lymphocytic leukemia (T-LGLL)-αβ and T-LGLL-γδ/Hepatosplenic T-cell lymphoma (HSTCL). Our case underlines the key role of sensitive diagnostic tools in the assessment of potential relationship between the diagnosis, prognosis, and treatment in the two pathologies. Full article