Brain–computer interface (BCI) systems include signal acquisition, preprocessing, feature extraction, classification, and an application phase. In fNIRS-BCI systems, deep learning (DL) algorithms play a crucial role in enhancing accuracy. Unlike traditional machine learning (ML) classifiers, DL algorithms eliminate the need for manual feature extraction. DL neural networks automatically extract hidden patterns/features within a dataset to classify the data. In this study, a hand-gripping (closing and opening) two-class motor activity dataset from twenty healthy participants is acquired, and an integrated contextual gate network (ICGN) algorithm (proposed) is applied to that dataset to enhance the classification accuracy. The proposed algorithm extracts the features from the filtered data and generates the patterns based on the information from the previous cells within the network. Accordingly, classification is performed based on the similar generated patterns within the dataset. The accuracy of the proposed algorithm is compared with the long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM). The proposed ICGN algorithm yielded a classification accuracy of 91.23 ± 1.60%, which is significantly (p < 0.025) higher than the 84.89 ± 3.91 and 88.82 ± 1.96 achieved by LSTM and Bi-LSTM, respectively. An open access, three-class (right- and left-hand finger tapping and dominant foot tapping) dataset of 30 subjects is used to validate the proposed algorithm. The results show that ICGN can be efficiently used for the classification of two- and three-class problems in fNIRS-based BCI applications. Full article

Objectives: This retrospective case-controlled study aimed to evaluate the association between the severity of fall-related injuries and fall-risk-increasing drugs (FRIDs) in hospitalized patients. Methods: Data were collected from Changhua Christian Hospital, Taiwan, of all adult inpatients who experienced falls between January 2017 and December 2021, and were divided into two groups based on whether they sustained severe fall-related injuries. Retrospective data that may affect the severity of fall-related injuries and the use of FRIDs were investigated. Results: Among 1231 documented cases of falls, 26 patients sustained severe fall-related injuries. Older patients and those with osteoporosis were more susceptible to more severe injuries from a fall. The use of mobility aids and osteoporosis medications showed protective effects against fall injuries. No significant association was observed between fall-related injuries and comorbidities or FRIDs. Multivariate analysis confirmed the inverse correlation between the use of mobility aids, osteoporosis medications, and fall severity. Patients with osteoporosis exhibited significantly higher odds of sustaining more severe injuries with a fall (odds ratio = 3.02, 95% confidence interval: 1.21–7.53). Conclusions: This study highlights the importance of addressing risk factors associated with fall severity among hospitalized patients. Providing mobility aids to persons at greater risk. Full article

Cancer stem cells (CSCs) play a key role in tumor progression, as they are often responsible for drug resistance and metastasis. Environmental pollution with polystyrene has a negative impact on human health. We investigated the effect of polystyrene nanoparticles (PSNPs) on cancer cell stemness using flow cytometric analysis of CD24, CD44, ABCG2, ALDH1 and their combinations. This study uses simultaneous in vitro cell lines and an in silico machine learning (ML) model to predict the progression of cancer stem cell (CSC) subpopulations in colon (HCT-116) and breast (MDA-MB-231) cancer cells. Our findings indicate a significant increase in cancer stemness induced by PSNPs. Exposure to polystyrene nanoparticles stimulated the development of less differentiated subpopulations of cells within the tumor, a marker of increased tumor aggressiveness. The experimental results were further used to train an ML model that accurately predicts the development of CSC markers. Machine learning, especially genetic algorithms, may be useful in predicting the development of cancer stem cells over time. Full article

Previous studies suggested that spring precipitation over the tropical western Pacific Ocean can influence the development of El Niño–Southern Oscillation (ENSO). To identify crucial precipitation patterns for post-spring ENSO evolution, a singular value decomposition (SVD) method was applied to spring precipitation and sea surface temperature (SST) anomalies, and three precipitation and ENSO types were obtained with each highlighting precipitation over the Maritime Continent (MC) or western north Pacific (WNP). High MC spring precipitation corresponds to the slow decay of a multi-year La Niña event. Low MC spring precipitation is associated with a rapid El Niño-to-La Niña transition. High WNP spring precipitation is related to positive north Pacific meridional mode and induces the El Niño initiation. Among the three ENSO types, ocean current and heat content behave differently. Based on these spring precipitation and oceanic factors, a statistical model was established aimed at predicting winter ENSO state. Compared to a full dynamical model, this model exhibits higher prediction skills in the winter ENSO phase and amplitude for the period of 1980–2022. The explained total variance of the winter Niño-3.4 index increases from 43% to 75%, while the root-mean-squared error decreases from 0.82 °C to 0.53 °C. The practical utility and limitations of this model are also discussed. Full article

Objectives: This study entailed a weekly analysis of real-world data (RWD) on the safety and efficacy of intravitreal (IVT) faricimab in neovascular age-related macular degeneration (nAMD). Methods: A retrospective, single-centre clinical trial was conducted at the Department of Ophthalmology, University Hospital Zurich, University of Zurich, Switzerland, approved by the Cantonal Ethics Committee of Zurich, Switzerland. Patients with nAMD were included. Data from patient charts and imaging were analysed. The safety and efficacy of the first faricimab injection were evaluated weekly until 4 weeks after injection. Results: Sixty-three eyes with a complete 4-week follow-up were enrolled. Six eyes were treatment-naïve; fifty-seven eyes were switched to faricimab from another treatment. Neither group showed signs of retinal vasculitis during the 4 weeks after injection. Central subfield thickness (CST) and volume (CSV) showed a statistically significant decrease compared to the baseline in the switched group (CST: p = 0.00383; CSV: p = 0.00702) after 4 weeks. The corrected visual acuity returned to the baseline level in both groups. The macular neovascularization area decreased in both groups, but this was not statistically significant. A complete resolution of sub- and intraretinal fluid after 4 weeks was found in 40% (switched) and 75% (naïve) of the treated patients. Conclusions: The weekly follow-ups reflect the structure–function relationship beginning with a fast functional improvement within two weeks after injection followed by a return to near-baseline levels after week 3. The first faricimab injection in our cohort showed a high safety profile and a statistically significant reduction in macular oedema in switched nAMD patients. Full article

The global food trade network (FTN) is a critical infrastructure for achieving the Sustainable Development Goals (SDGs). The FTN’s vulnerability to geopolitical conflicts, public health crises, and climate change events directly impacts food security and the ability to meet the SDGs. This study aims to analyze the dynamic evolution of the vulnerability of FTN, focusing on the period from 2000 to 2022, to aim for strategies for enhancing the resilience and sustainability of the global food system. Based on complex network analysis, we examine the structural characteristics and evolution of FTN for four major crops: soybeans, wheat, rice, and maize. We identify a trend towards increased network density and regionalization, with a decline in average shortest path length (ASPL) and an increase in the average clustering coefficient (ACC). These changes indicate a shift towards a more interconnected and resilient FTN in response to various shocks, including the COVID-19 pandemic and the Russia–Ukraine conflict. The findings suggest that the global FTN has adapted to increase resilience, which is essential for achieving the SDGs related to food security and sustainable development. The study’s insights can guide policy interventions to further strengthen the network against future shocks and promote global food security. Full article

Cooperative adaptive cruise control (CACC) is one of the main features of connected and autonomous vehicles (CAVs), which uses connectivity to improve the efficiency of adaptive cruise control (ACC). The addition of reliable communication systems to ACC reduces fuel consumption, maximizes road capacity, and ensures traffic safety. However, the performance, stability, and safety of CACC could be affected by the transmission of outdated data caused by communication delays. This paper proposes a Lyapunov-based nonlinear controller to mitigate the impact of time-varying delays in the communication channel of CACC. This paper uses Lyapunov–Krasovskii functionals in the stability analysis to ensure semi-global uniformly ultimately bounded tracking. The efficaciousness of the proposed CACC algorithm is demonstrated in simulation and through experimental implementation. Full article

Orthodontic space closure following tooth extraction is often hindered by alveolar bone deficiency. This study investigates the therapeutic use of nuclear factor-kappa B (NF-κB) decoy oligodeoxynucleotides loaded with polylactic-co-glycolic acid nanospheres (PLGA-NfDs) to mitigate alveolar bone loss during orthodontic tooth movement (OTM) following the bilateral extraction of maxillary first molars in a controlled experiment involving forty rats of OTM model with ethics approved. The decreased tendency of the OTM distance and inclination angle with increased bone volume and improved trabecular bone structure indicated minimized alveolar bone destruction. Reverse transcription-quantitative polymerase chain reaction and histomorphometric analysis demonstrated the suppression of inflammation and bone resorption by downregulating the expression of tartrate-resistant acid phosphatase, tumor necrosis factor-α, interleukin-1β, cathepsin K, NF-κB p65, and receptor activator of NF-κB ligand while provoking periodontal regeneration by upregulating the expression of alkaline phosphatase, transforming growth factor-β1, osteopontin, and fibroblast growth factor-2. Importantly, relative gene expression over the maxillary second molar compression side in proximity to the alveolus highlighted the pharmacological effect of intra-socket PLGA-NfD administration, as evidenced by elevated osteocalcin expression, indicative of enhanced osteocytogenesis. These findings emphasize that locally administered PLGA-NfD serves as an effective inflammatory suppressor and yields periodontal regenerative responses following tooth extraction. Full article

Flavonoids and stilbenoids, crucial secondary metabolites abundant in plants and fungi, display diverse biological and pharmaceutical activities, including potent antioxidant, anti-inflammatory, and antimicrobial effects. However, conventional production methods, such as chemical synthesis and plant extraction, face challenges in sustainability and yield. Hence, there is a notable shift towards biological production using microorganisms like Escherichia coli and yeast. Yet, the drawbacks of using E. coli and yeast as hosts for these compounds persist. For instance, yeast’s complex glycosylation profile can lead to intricate protein production scenarios, including hyperglycosylation issues. Consequently, Corynebacterium glutamicum emerges as a promising alternative, given its adaptability and recent advances in metabolic engineering. Although extensively used in biotechnological applications, the potential production of flavonoid and stilbenoid in engineered C. glutamicum remains largely untapped compared to E. coli. This review explores the potential of metabolic engineering in C. glutamicum for biosynthesis, highlighting its versatility as a cell factory and assessing optimization strategies for these pathways. Additionally, various metabolic engineering methods, including genomic editing and biosensors, and cofactor regeneration are evaluated, with a focus on C. glutamicum. Through comprehensive discussion, the review offers insights into future perspectives in production, aiding researchers and industry professionals in the field. Full article

Although, in recent years, it has been common to monitor players in team sports using EPTSs (Electronic Performance and Tracking Systems) devices, most of the studies have focused on the optimization of individual performance rather than collective work or tactical analysis. Moreover, almost all these studies focus on men’s teams with little focus on women’s teams. In this work, data from women’s soccer teams at different levels (competition and grassroots) have been collected using both a low-cost personally developed EPTS and a commercial EPTS. With these systems, we have built a dataset consisting of more than 16 million records, paying special attention to spatio-temporal variables collected in the form of geographical coordinates. Different methods have been applied to the collected dataset to solve the problem of determining the position (individual role) of each player on the field based solely on spatio-temporal variables. The methods include algorithms based on clustering, centroid calculation, and computer vision. We have verified the effectiveness of these methods and propose an alternative method based on image recognition algorithms applied to heat maps generated from the position of the players monitored during the matches. As shown in this paper, the validity of the proposed method has been verified, exceeding the performance of existing methods and extending the range of application of these techniques. Full article

Microdroplets generated in microfluidic devices are attracting attention as a new chemical reaction field and are expected to improve reactivity. One of the effects of microscaling is that the ratio of the force that acts on the diffusion and movement of substances to gravity is different from that of ordinary solvents. Recently, we proposed a hypothesis for determining reaction acceleration through micro-miniaturization: If a reaction is inhibited by setting the volume and viscosity of the solution to conditions that are unfavorable to the reaction on a normal scale, that reaction can be promoted in microfluidics. Therefore, for the purpose of this verification, (1) we used an amino acid Schiff base copper(II) complex with an azobenzene group to demonstrate the polarization-induced orientation in a polymer film (the redirection that is mechanically maintained in a soft matter matrix). Numerical data on optical anisotropy parameters were reported. (2) When the reaction is confirmed to be promoted in laminar flow in a microfluidic device and its azo derivative, a copper(II) complex is used to increase the solvent viscosity or diffusion during synthesis on a normally large scale. We will obtain and discuss data on the investigation of changing the solvent volume as a region. The range of experimental conditions for volume and viscosity did not lead to an improvement in synthetic yield, nor did (3) the comparison of solvents and viscosity for single-crystal growth of amino acid Schiff base copper(II) complexes having azobenzene groups. A solvent whose viscosity was measured was used, but microcrystals were obtained using the diffusion method. Full article

With respect to a traditional point-to-point (P-P) network, a hub-and-spoke (H-S) network not only uses a smaller number of links/paths but also utilizes the scale economy advantage on consolidated flows on hub–hub links and at hubs. However, the inevitable delays through hubs have always been a critical concern. Therefore, this paper develops an H-S model considering flow delay costs and applies the model to a logistics case in Eastern China. The integer quadratic term in the model’s objective function is linearized using the algebraic method. Our model is applied to develop an H-S network for its 13-node express package delivery operation, using the particle swarm optimization (PSO) algorithm. The results show using the H-S can save more than 14.1% of the total cost annually. The model also provides an applied case to the H-S configuration, especially for urban express delivery logistics in China. Full article

Background: Wound healing competence is implied in the nursing profession, but there is no standardized content regulation for wound care in university curricula. The primary objective of this study was to identify the barriers to the acquisition of knowledge about skin integrity impairment. Methods: A quasi-experimental pre-test and post-test study with an ad hoc questionnaire involved 304 students (control: 165; intervention: 139) from June to July 2023. A 10-hour educational intervention focused on skin integrity assessment and treatment was conducted. Results: The control group, scoring 17 ± 0.22 out of a maximum of 61, achieved a significantly lower final test score (p < 0.001) compared to the wound care educational intervention group, with the pre-test group scoring 30 ± 0.76 and the post-test group scoring 43 ± 0.61. The educational intervention in wound care program improved nursing students' knowledge of prevention, assessment/diagnosis, treatment, lower limb wounds, and wound bed preparation by replacing the number of "Don't know" answers in the post-test group with correct answers. Conclusions: The barriers identified to the acquisition of knowledge about skin integrity impairment in nursing studies are the following: the transversality of teaching, the teaching and evaluation system, and the variability in the training of professionals and teachers in charge of their education. The educational intervention can be used to consolidate knowledge and to enhance students’ self-confidence in caring for patients with wounds. Full article

(1) Background: Various guidelines address patient preparation and its importance for venous blood sampling, such as the GP41 guideline issued by the Clinical Laboratory Standards Institute (CLSI) and the blood collection guidelines published by the World Health Organisation. Recommendations provided by national societies or international organisations in the field of radiology, such as The Contrast Media Safety Committee of the European Society of Urogenital Radiology, or in the field of laboratory medicine, such as the Working Group for Preanalytical Phase (WG-PRE) of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and the Latin American Working Group for Preanalytical Phase (WG-PRE-LATAM) of the Latin American Confederation of Clinical Biochemistry (COLABIOCLI), also guide this practice. There is a notable lack of understanding regarding the viewpoints held by non-laboratory healthcare professionals concerning the significance of patient preparation for laboratory testing and the impact of typical factors associated with patient preparation. This study endeavours to bridge this gap by assessing the attitude of non-laboratory healthcare professionals in Lithuania regarding these pivotal aspects. (2) Methods: A self-designed anonymous questionnaire was disseminated among 141 public healthcare institutions in Lithuania. The internal consistency of the questionnaire was evaluated by computing Cronbach’s alpha. Descriptive statistics were utilised for the variables, while comparisons of attitude among groups were conducted using Mann–Whitney U (for two groups) or Kruskal–Wallis (for more than two groups) for categorical and discrete indicators. The Kruskal–Wallis post-hoc test was employed for pairwise comparisons. A significance level of p-Value < 0.05 was applied to establish statistical significance. (3) Results: A total of 158 respondents constituted two distinct groups of healthcare professionals: nurses and physicians. Most of the participants either agreed or strongly agreed that patient preparation could introduce bias into laboratory test results. Professionals with less than 20 years of work experience or those who attended training in patient preparation for sampling within a 5-year timeframe exhibited stronger agreement regarding different preanalytical factors in patient preparation and their impact on laboratory test results compared to their counterparts. (4) Conclusions: Non-laboratory healthcare professionals who participated in this survey consider proper patient preparation for laboratory testing to be a significant step towards obtaining accurate test results. They also recognize the commonly acknowledged preanalytical factors as important for ensuring reliable test results. However, attitudes towards the importance of several preanalytical factors vary depending on whether non-laboratory healthcare professionals have more or less than 20 years of work experience, as well as whether they have attended any training on this topic within the last five years or have never attended such training. Full article

The aim of this work was the investigation of novel organocatalysts for the Michael addition of diethyl malonate to β-nitrostyrene. The methodology of the study included NMR titration, reaction monitoring by NMR spectroscopy and electrospray ionization mass spectrometry (ESI-MS), product characterization by MALDI, IR spectroscopy, scanning electron microscopy (SEM), thermal gravimetric analysis (TGA), and elemental analysis. As a result, evidence of supramolecular interactions between two pairs of components of the reaction was found. In addition to the supramolecular complexes, an unusual reaction, i.e., the Michael addition of NH-bispidines to β-nitrostyrene, was found, which led to previously unknown oligomers of β-nitrostyrene. A new mechanism for the catalytic action of NH-bispidine was proposed, which involved catalysis not by the initial organocatalyst but rather by its adduct with β-nitrostyrene. Thus, in this reaction, N-benzylbispidine acted as an initiator, and the real catalyst was the betaine formed during the initiation stage. Full article

Tidal flat plays an important role in coastal development because of its ecological and spatial resources. We take the southern tidal flat in the macro-tidal turbid Hangzhou Bay as an example to study the long-term (1990–2020) evolution of the muddy tidal flat, using remote sensing data and field observational data. The detailed bathymetric elevation of the tidal flat is obtained, using remote sensing images of Landsat and Sentinel-2, combined with the real-time kinematic (RTK) data. The correlation coefficient between the remote sensing data and the RTK data is 0.73. The tidal flat and vegetation areas are affected by reclamation. The total tidal flat area decreased by 467.78 km². The vegetation area declined from 64.98 km² in 2000 to 13.41 km² in 2015 and recovered to 41.62 km² in 2020. The largest change in tidal flat slope occurs in the eastern and western sides of the tidal flat, compared with the wide middle part. The total length of tidal creeks decreased to 45.95 km in 2005 and then increased to 105.83 km in 2020. The middle- and low-grade tidal creeks accounted for 91.4%, with a curvature slightly larger than 1 in 2020. High-grade tidal creeks occur inside the vegetation areas, with less bending and fewer branch points. Vegetation promotes the development of tidal creeks but limits the lateral swing and bifurcation. These results provide a basis for the management of global tidal flat resources and ecosystems. Full article

Satellite remote sensing plays a significant role in the detection of smoke from forest fires. However, existing methods for detecting smoke from forest fires based on remote sensing images rely solely on the information provided by the images, overlooking the positional information and brightness temperature of the fire spots in forest fires. This oversight significantly increases the probability of misjudging smoke plumes. This paper proposes a smoke detection model, Forest Smoke-Fire Net (FSF Net), which integrates wildfire smoke images with the dynamic brightness temperature information of the region. The MODIS_Smoke_FPT dataset was constructed using a Moderate Resolution Imaging Spectroradiometer (MODIS), the meteorological information at the site of the fire, and elevation data to determine the location of smoke and the brightness temperature threshold for wildfires. Deep learning and machine learning models were trained separately using the image data and fire spot area data provided by the dataset. The performance of the deep learning model was evaluated using metric MAP, while the regression performance of machine learning was assessed with Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The selected machine learning and deep learning models were organically integrated. The results show that the Mask_RCNN_ResNet50_FPN and XGR models performed best among the deep learning and machine learning models, respectively. Combining the two models achieved good smoke detection results (Precision_smoke = 89.12%). Compared with wildfire smoke detection models that solely use image recognition, the model proposed in this paper demonstrates stronger applicability in improving the precision of smoke detection, thereby providing beneficial support for the timely detection of forest fires and applications of remote sensing. Full article

To ensure efficient inspection using the magnetic flux leakage (MFL) method, generating a flux density near the saturation level within the tested material is essential. This requirement brings high flux density conditions in the system’s pole regions. Hence, leakage flux within the slot is excessively triggered, leading to distortion of the defect signal. In this context, the system dimensions stand out as one of the most significant factors affecting the mentioned flux distributions. Therefore, various alternative solutions with different system dimensions arise in the design process of the MFL system. This study proposes a magnetic equivalent circuit (MEC) model to achieve optimal system design. The proposed MEC model is designed considering the nonlinear behavior of the material, leakage flux, and fringing effects. Verification results demonstrate that the MEC model consistently tracks the finite element analysis (FEA) results in calculating the flux densities. Furthermore, the relative errors in the flux density calculations of the tested material are at a maximum level of 10.2% and an average of 5.2% compared to the FEA. These findings indicate that the proposed MEC model can be effectively utilized in rapid prototyping and optimization procedures of MFL system design by providing fast solutions with reasonable accuracy. Full article

This study, conducted by searching keywords such as “maternal lupus”, “neonatal lupus”, and “congenital heart block” in databases including PubMed and Scopus, provides a detailed narrative review on fetal and neonatal lupus. Autoantibodies like anti-Ro/SSA and anti-La/SSB may cross the placenta and cause complications in neonates, such as congenital heart block (CHB). Management options involve hydroxychloroquine, which is able to counteract some of the adverse events, although the drug needs to be used carefully because of its impact on the QTc interval. Advanced pacing strategies for neonates with CHB, especially in severe forms like hydrops, are also assessed. This review emphasizes the need for interdisciplinary care by rheumatologists, obstetricians, and pediatricians in order to achieve the best maternal and neonatal health in lupus pregnancies. This multidisciplinary approach seeks to improve the outcomes and management of the disease, decreasing the burden on mothers and their infants. Full article

Working memory impairments are common in neurodevelopmental conditions, potentially impacting how neurodivergent students experience cognitive load during learning. We conducted a survey with 231 participants focused on students with attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and dyslexia. Parametric tests and a regression analysis were used to investigate the relationship between neurodiversity and perceived cognitive load in online learning. Neurodivergent students reported significantly higher extraneous cognitive load (ECL) in online learning compared to their neurotypical peers. However, no significant differences in perceived intrinsic and germane cognitive load were found between the two groups. Neurodiversity, and specifically ADHD, positively predicted perceived ECL in online learning. This study provides novel insights into the association between neurodiversity and cognitive load in online learning, suggesting a need for targeted support to help neurodivergent students reduce ECL in online learning environments and highlighting the importance of promoting inclusive educational practices that meet the needs of all students. Full article

Elevated atmospheric reactive nitrogen (Nr) emissions and the subsequent nitrogen (N) deposition have negatively impacted the global environment, particularly in China. In order to assess the long-term trends in atmospheric N deposition in the south of China, Taojiang County in Hunan Province was selected as a representative rural area for study. We analyzed interannual variation in atmospheric Nr, including gaseous ammonia (NH₃), nitrogen dioxide (NO₂), nitrate acid (HNO₃) vapor, particulate ammonium (NH₄⁺), and nitrate (NO₃⁻) in air and NH₄⁺-N and NO₃⁻-N in precipitation from 2011 to 2020. The 10-year average atmospheric wet-plus-dry N deposition was 41.9 kg N ha⁻¹ yr⁻¹, which decreased by approximately 24% after 2012, indicating that NH₃ and NO_x emissions were effectively reduced by emission controls introduced in 2013. Wet deposition accounted for approximately 74% of the total N deposition and was significantly influenced by annual precipitation amount. Reduced N (NH₃, pNH₄⁺, and NH₄⁺ in rainwater) was the dominant form, comprising approximately 58% of the total N deposition, while oxidized N (pNO₃⁻, NO₂, HNO₃, and NO₃⁻ in rainwater) accounted for 42% of the total N deposition. Atmospheric HNO₃, NO₂, and NH₃ concentrations and deposition declined by 30–80% over the decade, while particulate NH₄⁺ and NO₃⁻ concentrations and deposition remained at relatively stable levels, which suggests that ongoing research and policy should focus on rural particulate pollution. Future strategies must concentrate on the integrated control of NH₃ and NO_x emissions to mitigate air pollution and protect human health, particularly in rural areas because current abatement efforts are primarily directed toward urban areas and the industrial sector, whereas non-point source NH₃ pollution, influenced mainly by agricultural activities, dominates in rural regions. Full article

High-entropy alloys are promising candidates expected to be applied in transportation equipment serving in extreme environments due to their excellent properties. CoCrFeMnNi high-entropy alloy is a typical representative of them, and its low temperature performance is excellent. In this study, to evaluate the feasibility of forming HEA shells, the deformation behavior of CoCrFeMnNi under a plane-stress state at lower temperatures was thoroughly studied. Firstly, a thin-walled HEA tube was fabricated using hot extrusion and further formed into a thin shell for uniaxial tensile and biaxial bulging tests. Subsequently, uniaxial tensile tests at cryogenic temperatures were conducted. Both the strength and the ductility improves as the temperature decreases from −160 °C to −196 °C. Then, a systematic low-temperature bulging test was performed using isothermal dome tests and the thickness uniformity analysis of the bulged specimens was carried out. In addition, grain microstructural observation using EBSD was characterized analyze the possible deformation mechanism at the cryogenic temperature under the biaxial stress state. This study, for the first time, investigated the biaxial deformation behavior of HEA. Considering the plane-stress state deformation is the dominant type in the thin-walled shell deformation, this study enables us to provide direct guidance for various sheet-forming processes of HEAs. Full article