The current study reports on the impact of a series of functional alkoxysilanes on the wettability and structure of a well-established silicon/zirconium hybrid anticorrosion sol–gel coating. The selected functional alkoxysilanes comprise tetra ethylorthosilicate (TEOS), 3-glycidyloxypropyltrimethoxysilane (GPTMS), 3-aminopropyltriethoxysilane (APTES) and vinyltriethoxysilane (VTES) and are incorporated at various concentrations (1, 5, 10 and 20%) within the silicon/zirconium sol–gel material. The prepared materials are successfully processed as coatings and cured at different temperatures in the range of 100–150 °C. The characterisation of the structures and surfaces is performed by dynamic light scattering (DLS), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), silicon nuclear magnetic resonance spectroscopy (²⁹Si-NMR), atomic force microscopy (AFM) and static water contact angle (WCA). Structural characterisations (DLS, FTIR,²⁹Si-NMR) show that the functional alkoxysilanes effectively bind at the surface of the reference sol–gel material, resulting in the formation of functional core–shell nanoparticles. WCA results show that the hydrophobic properties of all materials decrease with curing temperature, and AFM analysis demonstrated that this behaviour is associated with a decrease in roughness. The physico-chemical processes taking place are critically assigned and discussed. Full article

This research aimed to explore the healing impacts of Melittin treatment on gastrocnemius muscle wasting caused by immobilization with a cast in rabbits. Twenty-four rabbits were randomly allocated to four groups. The procedures included different injections: 0.2 mL of normal saline to Group 1 (G1-NS); 4 μg/kg of Melittin to Group 2 (G2-4 μg/kg Melittin); 20 μg/kg of Melittin to Group 3 (G3-20 μg/kg Melittin); and 100 μg/kg of Melittin to Group 4 (G4-100 μg/kg Melittin). Ultrasound was used to guide the injections into the rabbits’ atrophied calf muscles following two weeks of immobilization via casting. Clinical measurements, including the length of the calf, the compound muscle action potential (CMAP) of the tibial nerve, and the gastrocnemius muscle thickness, were assessed. Additionally, cross-sectional slices of gastrocnemius muscle fibers were examined, and immunohistochemistry and Western blot analyses were performed following two weeks of therapy. The mean regenerative changes, as indicated by clinical parameters, in Group 4 were significantly more pronounced than in the other groups (p < 0.05). Furthermore, the cross-sectional area of the gastrocnemius muscle fibers and immunohistochemical indicators in Group 4 exceeded those in the remaining groups (p < 0.05). Western blot analysis also showed a more significant presence of anti-inflammatory and angiogenic cytokines in Group 4 compared to the others (p < 0.05). Melittin therapy at a higher dosage can more efficiently activate regeneration in atrophied gastrocnemius muscle compared to lower doses of Melittin or normal saline. Full article

Herein, a catalytic amplification enhanced dual-signal immunochromatographic assay (ICA) based on Pt nanoparticles (Pt NPs) modified with Ti₃C₂Tx MXene (Ti₃C₂Tx@Pt) was first developed for chloramphenicol (CAP) in animal-derived foods. Due to the large specific surface area and abundant active sites of Ti₃C₂Tx@Pt, they can be loaded with hundreds of Pt NPs to enhance their catalytic activity, resulting in a significant increase in the detection sensitivity; the sensitivity was up to 50-fold more sensitive than the reported ICA for CAP. The LODs of the developed method for milk/chicken/fish were 0.01 μg/kg, the LOQs were 0.03 μg/kg and the recovery rates were 80.5–117.0%, 87.2–118.1% and 92.7–117.9%, with corresponding variations ranging from 3.1 to 9.6%, 6.0 to 12.7% and 6.0 to 13.6%, respectively. The linear range was 0.0125–1.0 μg/kg. The results of the LC-MS/MS confirmation test on 30 real samples had a good correlation with that of our established method (R² > 0.98), indicating the practical reliability of the established method. The above results indicated that an ICA based on the Ti₃C₂Tx@Pt nanozyme has excellent potential as a food safety detection tool. Full article

Everyday activity incurs carbon footprints, which are classified as personal, production, organizational and national, and may be assessed by input–output analysis (IOA), life-cycle assessment (LCA), or the combination of LCA and IOA methods. Notwithstanding international standards, like ISO 14064 and Publicly Available Specification (PAS) released for standardization, carbon footprint results can vary and sometimes lack consistency that due to variations in data sources, crossover boundary definitions, and operational boundaries for indirect emissions. The novelty of this study is the direct utilization of condensed water in an existing cooling water system, without the need for prior wastewater treatment, as typically required for greywater. The lack of practical case studies exploring the water–energy nexus in the context of reclaiming condensed water for evaporative cooling tower systems makes this research particularly significant. This highlights that condensed water can be a straightforward and cost-effective solution for both water conservation and energy savings. This case study highlights the benefits of reclaiming condensed water as supplementary cooling water, which proved effective in water quality treatment and dilution augmentation, considering that a higher cycle of concentration (CoC) was achieved, leading to reduced bleed-off that resulted in a water saving of 44% for make-up and 80% for bleed-off water, and energy savings from 6.9% to 13.1% per degree Celsius of condensing refrigerant temperature (CRT). The analytical assessment revealed that reclaiming condensed water is a promising answer for green building and is a by-product of condensation without extra power demands, avoiding the generation of an increased carbon footprint and exacerbation of greenhouse gas (GHG) emissions from freshwater resource extraction, and for the production of energy-efficient devices or substitutions. By eliminating the need for wastewater treatment, this research enhances the practicality and feasibility of direct use of condensed water in various applications. This approach not only promotes sustainability by conserving water and energy but also renews interest among proponents of green building practices. It has the potential to accelerate the adoption of this method and integrate it into green building designs. Full article

In this systematic literature review, we delve into the realm of intention recognition within the context of digital forensics and cybercrime. The rise of cybercrime has become a major concern for individuals, organizations, and governments worldwide. Digital forensics is a field that deals with the investigation and analysis of digital evidence in order to identify, preserve, and analyze information that can be used as evidence in a court of law. Intention recognition is a subfield of artificial intelligence that deals with the identification of agents’ intentions based on their actions and change of states. In the context of cybercrime, intention recognition can be used to identify the intentions of cybercriminals and even to predict their future actions. Employing a PRISMA systematic review approach, we curated research articles from reputable journals and categorized them into three distinct modeling approaches: logic-based, classical machine learning-based, and deep learning-based. Notably, intention recognition has transcended its historical confinement to network security, now addressing critical challenges across various subdomains, including social engineering attacks, artificial intelligence black box vulnerabilities, and physical security. While deep learning emerges as the dominant paradigm, its inherent lack of transparency poses a challenge in the digital forensics landscape. However, it is imperative that models developed for digital forensics possess intrinsic attributes of explainability and logical coherence, thereby fostering judicial confidence, mitigating biases, and upholding accountability for their determinations. To this end, we advocate for hybrid solutions that blend explainability, reasonableness, efficiency, and accuracy. Furthermore, we propose the creation of a taxonomy to precisely define intention recognition, paving the way for future advancements in this pivotal field. Full article

Pediatric multiple sclerosis (MS) and neuromyelitis optica (NMO) are rare acquired demyelinating syndrome with limited epidemiological data available, particularly in non-Western setting. This study aimed to demonstrate the epidemiology of pediatric MS and NMO in South Korea and to analyze of healthcare utilization and economic burden associated with these conditions. Using a nationwide population-based database from the Korean Health Insurance Review and Assessment Service database, we identified pediatric cases (age < 20 years) of MS and NMO from 2016 to 2020. We analyzed incidence, prevalence, healthcare utilization and medical costs. The study found low age-standardized incidence and prevalence rates for pediatric MS and NMO in South Korea. There was a marked disparity in healthcare utilization between urban and rural areas. Most healthcare interactions occurred in tertiary hospitals in urban settings, particularly in Seoul. The study also highlighted the substantial economic burden associated with the management of rare diseases, with annual variability in medical costs. Pediatric MS and NMO are extremely rare in South Korea, with significant regional disparity in healthcare utilization. The findings emphasize the need for targeted healthcare policies to improve access and reduce disparities, particularly for chronic and rare diseases requiring specialized care. Full article

An arbitrary Lagrangian-Eulerian lattice Boltzmann flux solver (ALE-LBFS) coupled with the mode superposition method is proposed in this work and applied to study two- and three-dimensional flutter phenomenon on dynamic unstructured meshes. The ALE-LBFS is applied to predict the flow field by using the vertex-centered finite volume method with an implicit dual time-stepping method. The convective fluxes are evaluated by using lattice Boltzmann solutions of the non-free D1Q4 lattice model and the viscous fluxes are obtained directly. Additional fluxes due to mesh motion are calculated directly by using local conservative variables and mesh velocity. The mode superposition method is used to solve for the dynamic response of solid structures. The exchange of aerodynamic forces and structural motions is achieved through interpolation with the radial basis function. The flow solver and the structural solver are tightly coupled so that the restriction on the physical time step can be removed. In addition, geometric conservation law (GCL) is also applied to guarantee conservation laws. The proposed method is tested through a series of simulations about moving boundaries and fluid–structure interaction problems in 2D and 3D. The present results show good consistency against the experiments and numerical simulations obtained from the literature. It is also shown that the proposed method not only can effectively predict the flutter boundaries in both 2D and 3D cases but can also accurately capture the transonic dip phenomenon. The tight coupling of the ALE-LBFS and the mode superposition method presents an effective and powerful tool for flutter prediction and can be applied to many essential aeronautical problems. Full article

Toll-like receptors (TLRs) are vital components of the innate immune system, serving as the first line of defense against pathogens by recognizing a wide array of molecular patterns. This review summarizes the critical roles of TLRs in immune surveillance and disease pathogenesis, focusing on their structure, signaling pathways, and implications in various disorders. We discuss the molecular intricacies of TLRs, including their ligand specificity, signaling cascades, and the functional consequences of their activation. The involvement of TLRs in infectious diseases, autoimmunity, chronic inflammation, and cancer is explored, highlighting their potential as therapeutic targets. We also examine recent advancements in TLR research, such as the development of specific agonists and antagonists, and their application in immunotherapy and vaccine development. Furthermore, we address the challenges and controversies surrounding TLR research and outline future directions, including the integration of computational modeling and personalized medicine approaches. In conclusion, TLRs represent a promising frontier in medical research, with the potential to significantly impact the development of novel therapeutic strategies for a wide range of diseases. Full article

Between 2 and 8.5% of patients who recover from COVID-19 do not develop antibodies, and the durability of IgG antibodies is under scrutiny. Therefore, the presence and persistence of IgM and IgG antibodies were evaluated in a group of patients diagnosed with SARS-CoV-2 from May to August 2020. Out of 2199 suspected COVID-19 cases, 1264 were confirmed for SARS-CoV-2 by rRT-PCR; 328 consented to participate in the study, with 220 participants followed for 9 months, including 124 men (56%) and 96 women (44%). The primary symptoms were headache, dry cough, and fever. IgG antibodies developed in 95% of patients within 4 weeks post-diagnosis, and a second evaluation at 9 months showed that 72.7% still had detectable IgG antibodies. The presence of IgM in one individual (0.45%) suggested the possibility of reinfection. Full article

Electric vehicles (EVs) are becoming more and more popular as they provide significant environmental benefits compared to fossil-fuel vehicles. However, they represent substantial loads on the power grid, and the scheduling of EV charging can be a challenge, especially in large parking lots. This paper presents a metaheuristic-based approach parallelized on multicore processors (CPU) and graphics processing units (GPU) to optimize the scheduling of EV charging in a single smart parking lot. The proposed method uses a particle swarm optimization algorithm that takes as input the arrival time, the departure time, and the power demand of the vehicles and produces an optimized charging schedule for all vehicles in the parking lot, which minimizes the overall charging cost while respecting the chargers’ capacity and the parking lot feeder capacity. The algorithm exploits task-level parallelism for the multicore CPU implementation and data-level parallelism for the GPU implementation. The proposed algorithm is tested in simulation on parking lots containing 20 to 500 EVs. The parallel implementation on CPUs provides a speedup of 7.1x, while the implementation on a GPU provides a speedup of up to 247.6x. The parallel implementation on a GPU is able to optimize the charging schedule for a 20-EV parking lot in 0.87 s and a 500-EV lot in just under 30 s. These runtimes allow for real-time computation when a vehicle arrives at the parking lot or when the electricity cost profile changes. Full article

In assessing individual cardiovascular risk, dyslipidemia is known for emerging as a pivotal factor significantly contributing to major cardiovascular events. However, dyslipidemic patients frequently present with concurrent medical conditions, each with varying frequencies of occurrence; cholangitis, whether acute or chronic, and hepatic steatosis, along with associated conditions, are strongly associated with specific forms of dyslipidemia, and these associations are reasonably well elucidated. Conversely, evidence linking biliary disease to hepatic steatosis is comparatively scant. This narrative review aims to bridge this gap in knowledge concerning the interplay between dyslipidemia, cholangitis, and hepatic steatosis. By addressing this gap, clinicians can better identify patients at heightened risk of future major cardiovascular events, facilitating more targeted interventions and management strategies. The review delves into the intricate relationships between dyslipidemia and these hepatic and biliary clinical conditions, shedding light on potential mechanisms underlying their associations. Understanding these complex interactions is crucial for optimizing cardiovascular risk assessment as well and devising tailored treatment approaches for patients with dyslipidemia and associated hepatic disorders. Moreover, elucidating these connections empowers clinicians with the knowledge needed to navigate the multifaceted landscape of cardiovascular risk assessment and management effectively. By exploring the intricate relationships between dyslipidemia, cholangitis, and hepatic steatosis (without forgetting the possible clinical consequences of hepatic steatosis itself), this review not only contributes to the existing body of knowledge but also offers insights into potential avenues for further research and clinical practice. Thus, it serves as a valuable resource for healthcare professionals striving to enhance patient care and outcomes in the context of cardiovascular disease and associated hepatic conditions. Full article

The R2R3-MYB gene family, encoding plant transcriptional regulators, participates in many metabolic pathways of plant physiology and development, including flavonoid metabolism and anthocyanin synthesis. This study proceeded as follows: the JrR2R3-MYB gene family was analyzed genome-wide, and the family members were identified and characterized using the high-quality walnut reference genome “Chandler 2.0”. All 204 JrR2R3-MYBs were established and categorized into 30 subgroups via phylogenetic analysis. JrR2R3-MYBs were unevenly distributed over 16 chromosomes. Most JrR2R3-MYBs had similar structures and conservative motifs. The cis-acting elements exhibit multiple functions of JrR2R3-MYBs such as light response, metabolite response, and stress response. We found that the expansion of JrR2R3-MYBs was mainly caused by WGD or segmental duplication events. Ka/Ks analysis indicated that these genes were in a state of negative purifying selection. Transcriptome results suggested that JrR2R3-MYBs were widely entangled in the process of walnut organ development and differentially expressed in different colored varieties of walnuts. Subsequently, we identified 17 differentially expressed JrR2R3-MYBs, 9 of which may regulate anthocyanin biosynthesis based on the results of a phylogenetic analysis. These genes were present in greater expression levels in ‘Zijing’ leaves than in ‘Lvling’ leaves, as revealed by the results of qRT-PCR experiments. These results contributed to the elucidation of the functions of JrR2R3-MYBs in walnut coloration. Collectively, this work provides a foundation for exploring the functional characteristics of the JrR2R3-MYBs in walnuts and improving the nutritional value and appearance quality of walnuts. Full article

Autosomal polycystic kidney disease (ADPKD) is the most common genetic form of kidney failure, reflecting unmet needs in management. Prescription of the only approved treatment (tolvaptan) is limited to persons with rapidly progressing ADPKD. Rapid progression may be diagnosed by assessing glomerular filtration rate (GFR) decline, usually estimated (eGFR) from equations based on serum creatinine (eGFRcr) or cystatin-C (eGFRcys). We have assessed the concordance between eGFR decline and identification of rapid progression (rapid eGFR loss), and measured GFR (mGFR) declines (rapid mGFR loss) using iohexol clearance in 140 adults with ADPKD with ≥3 mGFR and eGFRcr assessments, of which 97 also had eGFRcys assessments. The agreement between mGFR and eGFR decline was poor: mean concordance correlation coefficients (CCCs) between the method declines were low (0.661, range 0.628 to 0.713), and Bland and Altman limits of agreement between eGFR and mGFR declines were wide. CCC was lower for eGFRcys. From a practical point of view, creatinine-based formulas failed to detect rapid mGFR loss (−3 mL/min/y or faster) in around 37% of the cases. Moreover, formulas falsely indicated around 40% of the cases with moderate or stable decline as rapid progressors. The reliability of formulas in detecting real mGFR decline was lower in the non-rapid-progressors group with respect to that in rapid-progressor patients. The performance of eGFRcys and eGFRcr-cys equations was even worse. In conclusion, eGFR decline may misrepresent mGFR decline in ADPKD in a significant percentage of patients, potentially misclassifying them as progressors or non-progressors and impacting decisions of initiation of tolvaptan therapy. Full article

The Lorenz curve is used to describe the relationship between the cumulative proportion of household income and the number of households of an economy. The extent to which the Lorenz curve deviates from the line of equality (i.e., y = x) is quantified by the Gini coefficient. Prior models are based on the simulated and empirical data of income distributions. In biology, the Lorenz curves of cell or organ size distributions tend to have similar shapes. When the Lorenz curve is rotated by 135 degrees counterclockwise and shifted to the right by a distance of $\sqrt{2}$, a three-parameter performance equation (PE), and its generalized version with five parameters (GPE), accurately describe this rotated and right-shifted curve. However, in prior studies, PE and GPE were not compared with the other Lorenz equations, and little is known about whether the skewness of the distribution could influence the validity of these equations. To address these two issues, simulation data from the beta distributions with different skewness values and six empirical datasets of plant (organ) size distributions were used to compare PE and GPE with three other Lorenz equations in describing the rotated and right-shifted plant (organ) size distributions. The root-mean-square error and Akaike information criterion were used to assess the validity of the two performance equations and the three other Lorenz equations. PE and GPE were both validated in describing the rotated and right-shifted simulation and empirical data of plant (organ) distributions. Nevertheless, GPE worked better than PE and the three other Lorenz equations from the perspectives of the goodness of fit, and the trade-off between the goodness of fit and the model structural complexity. Analyses indicate that GPE provides a powerful tool for quantifying size distributions across a broad spectrum of organic entities and can be used in a variety of ecological and evolutionary applications. Even for the simulation data from hypothetical extreme skewed distribution curves, GPE still worked well. Full article

Titanium and its alloys have been widely employed as dental implant materials. However, polymicrobial infection is still one of the most common reasons for implant failure, which has already become a worldwide problem and poses a threat to human health. In this study, a titanium-based (Ti-based) superhydrophobic coating was effectively created by anodization followed by hydrophobic modification of 1H,1H,2H,2H-perfluorodecyltriethoxysilane (FAS), which shows a high water contact angle (WCA) of 159.9 ± 5.8° and a low water sliding angle (WSA) of 2.7 ± 2.2°. The thickness of the anodized samples is from 500 nm to 4 µm as the anodizing voltage increases. The Ti-based superhydrophobic coating demonstrated the existence of Ti, O, C, F, and Si elements, and the corresponding phase compositions are Ti and anatase. The results showed that the Ti-based superhydrophobic coating has good biocompatibility to co-culture with L929 cells for 1, 3, and 5 days. It was also proven that the as-prepared Ti-based superhydrophobic coating has enhanced antibacterial abilities against Staphylococcus aureus (S. aureus) and Porphyromonas gingivalis (P. gingivalis, P.g) after 4, 12, and 24 h. Moreover, the Ti-based superhydrophobic coating can significantly reduce platelet adhesion and activation. In addition, the Ti-based superhydrophobic coating also exhibits a considerable positive shift in the corrosion potential (E_corr) and a decline of one order of magnitude in the corrosion current density (J_corr), showing good anticorrosive properties. It was also found that the capsule around the Ti-based superhydrophobic coating was thinner than that of bare Ti after implantation for 7, 15, and 28 days, indicating its good biosafety. Therefore, the as-prepared Ti-based superhydrophobic coating can be a suitable candidate for Ti-based implants in dental applications. Full article

(1) Background: The sustainable development of rural areas has become a critical factor in global economic and social transformation. As an essential part of China’s rural ecological and cultural system, traditional villages are now facing a crisis of yearly decline, and sustainable development has become a meaningful way to solve the problem. This study utilized morphological indicator analysis and the SDGs as an evaluation framework to reveal the correlation and driving factors between traditional villages’ spatial form and sustainability indicators. From the perspective of the spatial form, this approach has specific reference significance for improving the sustainability of traditional villages. (2) Methods: A framework for detecting the driving factors of rural sustainability based on four dimensions (morphology, environment, economy, and society) was constructed. A geographic information system (GIS) was used to analyze the geographic patterns and morphological indicator characteristics of traditional villages in Jiangsu Province, and GeoDetector was used to analyze the driving mechanisms of the spatial patterns of sustainability in traditional villages, providing the basis for spatial zoning and differentiated policy design for the construction, planning, and management of sustainable villages. (3) Results: ➀ The spatial patterns and morphological characteristics of traditional villages exhibit prominent geographical imbalances and significant cluster cores. ➁ The high-density and low-aspect-ratio rural form in the southern region (where rural industries are developed) promotes good economic sustainability in rural areas but also leads to poor environmental performance. The rural areas in the southwest and north (high-density forest areas) have medium density and a high aspect ratio, and the lack of agricultural space and external connections affects their social performance. The main focus is on poverty reduction and urban cooperation. The central and northern lakeside areas and the eastern coastal areas (important ecological protection areas) have low density and high aspect ratios, which have helped them to achieve excellent environmental performance but also led to contradictions in environmental, economic, and social performance. Maintaining low-density patterns, using clean energy, and protecting terrestrial and underwater biodiversity are essential to the sustainability of the rural environment. The agglomeration of spatial patterns promotes cooperation between rural and urban areas and improves industrial development, contributing to the sustainability of the rural economy. Improving social welfare and agricultural development contributes to the sustainability of rural societies. ➂ The impacts of various factors vary significantly; for example, Life below Water (SDG14), Climate Action (SDG13), and No Poverty (SDG1) are the most prominent, followed by Partnerships for the Goals (SDG17), Affordable and Clean Energy (SDG7), and Recent Work and Economic Growth (SDG8). (4) Conclusions: It is recommended that the government, with the driving mechanisms, divide the spatial management zoning of traditional villages in Jiangsu into three types of policy areas: environmental-oriented, economic-oriented, and social-oriented. Differentiated and targeted suggestions should be proposed to provide a critical decision-making basis for protecting and utilizing traditional villages in Jiangsu and similar provinces, as well as to help promote rural revitalization and sustainable rural construction in China. Full article

The use of hydrogen-blended natural gas presents an efficacious pathway toward the rapid, large-scale implementation of hydrogen energy, with pipeline transportation being the principal method of conveyance. However, pipeline materials are susceptible to hydrogen embrittlement in high-pressure hydrogen environments. Natural gas contains various impurity gases that can either exacerbate or mitigate sensitivity to hydrogen embrittlement. In this study, we analyzed the mechanisms through which multiple impurity gases could affect the hydrogen embrittlement behavior of pipeline steel. We examined the effects of O₂ and CO₂ on the hydrogen embrittlement behavior of L360 pipeline steel through a series of fatigue crack growth tests conducted in various environments. We analyzed the fracture surfaces and assessed the fracture mechanisms involved. We discovered that CO₂ promoted the hydrogen embrittlement of the material, whereas O₂ inhibited it. O₂ mitigated the enhancing effect of CO₂ when both gases were mixed with hydrogen. As the fatigue crack growth rate increased, the influence of impurity gases on the hydrogen embrittlement of the material diminished. Full article

The L 1 region of bovine adenovirus (BAdV)-3 encodes a multifunctional protein named protein VII. Anti-protein VII sera detected a protein of 26 kDa in transfected or BAdV-3-infected cells, which localizes to nucleus and nucleolus of infected/transfected cells. Analysis of mutant protein VII identified four redundant overlapping nuclear/nucleolar localization signals as deletion of all four potential nuclear/nucleolar localization signals localizes protein VII predominantly to the cytoplasm. The nuclear import of protein VII appears to use importin α (α-1), importin-β (β-1) and transportin-3 nuclear transport receptors. In addition, different nuclear transport receptors also require part of protein VII outside nuclear localization sequences for efficient interaction. Proteomic analysis of protein complexes purified from recombinant BAdV-3 expressing protein VII containing Strep Tag II identified potential viral and cellular proteins interacting with protein VII. Here, we confirm that protein VII interacts with IVa2 and protein VIII in BAdV-3-infected cells. Moreover, amino acids 91–101 and 126–137, parts of non-conserved region of protein VII, are required for interaction with IVa2 and protein VIII, respectively. Full article

The silkworm Bombyx mori, the second most varied group of insects, is a fascinating insect that belongs to the Lepidoptera species. We aimed to deepen our knowledge about the composition and significance of amino acids (AA) from the sericulture chain to fish. AAs are the most prevalent molecules throughout the growth process of silkworms. We described AAs classification, occurrence, metabolism, and functions. Online datasets revealed that the essential AAs (EAA) level in fish meal and silkworm pupae (SWP) is comparable. SWP have a high content of methionine and lysine, which are the principal limiting AAs in fish diets, indicating that SWP have nutritional potential to be added to fish diets. Additionally, an overview of the data analyzed displays that SWP have a higher protein efficiency ratio than fish meal, the classical protein-rich source (>1.19 times), and compared to soybean meal, the second-most preferred source of protein in aquaculture (>2.08 times), indicating that SWP can be considered effective for animal feeding. In this study, we provide an overview of the current knowledge concerning AAs, paying special emphasis to EAAs and explaining, to some extent, certain mechanisms and functions of these compounds, from mulberry leaves to larvae–pupae and fish diets. Full article

To optimize electron energy for in situ imaging of large biological samples up to 10 μm in thickness with nanoscale resolutions, we implemented an analytical model based on elastic and inelastic characteristic angles. This model has been benchmarked by Monte Carlo simulations and can be used to predict the transverse beam size broadening as a function of electron energy while the probe beam traverses through the sample. As a result, the optimal choice of the electron beam energy can be realized. In addition, the impact of the dose-limited resolution was analysed. While the sample thickness is less than 10 μm, there exists an optimal electron beam energy below 10 MeV regarding a specific sample thickness. However, for samples thicker than 10 μm, the optimal beam energy is 10 MeV or higher depending on the sample thickness, and the ultimate resolution could become worse with the increase in the sample thickness. Moreover, a MeV-STEM column based on a two-stage lens system can be applied to reduce the beam size from one micron at aperture to one nanometre at the sample with the energy tuning range from 3 to 10 MeV. In conjunction with the state-of-the-art ultralow emittance electron source that we recently implemented, the maximum size of an electron beam when it traverses through an up to 10 μm thick bio-sample can be kept less than $10\mathrm{n}\mathrm{m}$. This is a critical step toward the in situ imaging of large, thick biological samples with nanometer resolution. Full article

This paper presents a unified Lyapunov-based predefined-time stability theorem that includes three sufficient conditions. The standard theoretical analysis method for achieving predefined-time stability of non-linear systems using this theorem is provided within the framework of Lyapunov theory. The developed Lyapunov-based theorem facilitates the establishment of equivalence between the existing Lyapunov theorems concerning predefined-time stability. Furthermore, when the presented sufficient conditions are relaxed, the predefined-time stability conclusion for non-linear systems degenerates into a finite-time one. Consequently, a standard non-singular sliding mode control framework based on the unified Lyapunov-based theorem is developed for a Lagrangian system to ensure its predefined-time stability. Exemplary numerical simulation results are subsequently given, in order to illustrate the convergence behavior of the system states and confirm that the controlled systems are predefined-time stable. Full article

In the healthcare field, diagnosing disease is the most concerning issue. Various diseases including cardiovascular diseases (CVDs) significantly influence illness or death. On the other hand, early and precise diagnosis of CVDs can decrease chances of death, resulting in a better and healthier life for patients. Researchers have used traditional machine learning (ML) techniques for CVD prediction and classification. However, many of them are inaccurate and time-consuming due to the unavailability of quality data including imbalanced samples, inefficient data preprocessing, and the existing selection criteria. These factors lead to an overfitting or bias issue towards a certain class label in the prediction model. Therefore, an intelligent system is needed which can accurately diagnose CVDs. We proposed an automated ML model for various kinds of CVD prediction and classification. Our prediction model consists of multiple steps. Firstly, a benchmark dataset is preprocessed using filter techniques. Secondly, a novel arithmetic optimization algorithm is implemented as a feature selection technique to select the best subset of features that influence the accuracy of the prediction model. Thirdly, a classification task is implemented using a multilayer perceptron neural network to classify the instances of the dataset into two class labels, determining whether they have a CVD or not. The proposed ML model is trained on the preprocessed data and then tested and validated. Furthermore, for the comparative analysis of the model, various performance evaluation metrics are calculated including overall accuracy, precision, recall, and F1-score. As a result, it has been observed that the proposed prediction model can achieve 88.89% accuracy, which is the highest in a comparison with the traditional ML techniques. Full article