Traditional anti-corrosion and anti-fouling coatings struggle against the harsh marine environment. Our study tackled this by introducing a novel dual-layer hydrogel (A-H DL) coating system. This system combined a Cu₂O–SiO₂–acrylic resin primer for anchoring and controlled copper ion release with a dissipative double-network double-anchored hydrogel (DNDAH) boasting superior mechanical strength and anti-biofouling performance. An acrylamide monomer was copolymerized and cross-linked with a coupling agent to form the first irreversible network and first anchoring, providing the DNDAH coating with mechanical strength and structural stability. Alginate gel microspheres (AGMs) grafted with the same coupling agent formed the second reversible network and second anchoring, while coordinating with Cu²⁺ released from the primer to form a system buffering Cu²⁺ release, enabling long-term antibacterial protection and self-healing capabilities. FTIR, SEM, TEM, and elemental analyses confirmed the composition, morphology, and copper distribution within the A-H DL coating. A marine simulation experiment demonstrated exceptional stability and anti-fouling efficacy. This unique combination of features makes A-H DL a promising solution for diverse marine applications, from ship hulls to aquaculture equipment. Full article

The most important source of human life support is water. During the development of mineral water fields, unsustainable patterns of production and consumption have been observed, which could lead to environmental damage and the deterioration of mineral water quality and sources. In this work, a procedure for determining the modified link’s parameters, replacing the static and dynamic indicators of the hydrodynamic process, is proposed. Recording the parameters at the different filtration coefficients along the spatial coordinates allows the environmental safety of aquifers to be increased and the pressure of the reservoir to be stabilized. The presented approach allows the accuracy of the process used to control the reservoir’s pressure to be increased. Full article

Irregularity in the plane layout of a building structure and the vertical discontinuity of lateral resistance components could lead to torsion and result in the brittle failure of a structure. According to the characteristics of the conventional island main building of nuclear power plants, this paper focuses on the conventional island main building of the CAP1400 nuclear power plant (NPP) in Shidaowan as the research object. A prototype structure model of the main building was developed using ABAQUS software. The seismic response of the structure under multidimensional ground motion was studied by inputting the X-direction and Y-direction translational and torsional components of ground motion in ABAQUS. The results demonstrate that the overall transverse displacement of the structure under bidirectional ground motion was significantly higher than that under unidirectional earthquakes, which was about 20%. Under a multidimensional frequent earthquake, the transverse displacement of the structure increased by about 13% on average compared with that under a bidirectional earthquake; the longitudinal increase was the largest, at about 28%. Finally, the lateral displacement of each layer of the steel-reinforced concrete (SRC) frame-bent main building structure with few walls proposed in this article decreased by an average of about 17% compared to the traditional SRC frame-bent main building structure. The longitudinal displacement was reduced by about 14% compared to the traditional SRC frame-bent main building structure. Full article

Investigating the effects of natural rainfall on the soil moisture for sloping farmland is extremely important for comprehending a variety of hydrological processes. Rainfall regimes can elicit different responses to soil moisture at the depth of soil layers, and the responses may differ depending on the landscape position of the sloping farmland. This paper utilized the surface runoff natural rainfall and soil moisture measured on sloping farmland with conventional tillage and contour tillage in the red soil area of China to investigate the influence of natural rainfall events on soil moisture content and to evaluate if the response results were consistent across the four rainfall regimes. Natural rainfall events were classified into different four regimes in line with rainfall duration, rainfall amount, and the maximum 30 min rainfall intensity (I₃₀) by the k-means clustering method, including advanced, intermediate, uniform and delayed regimes. The result showed that the advanced regime was the predominant one in the study area, which represented 45.9% of the total rainfall events. The rainfall regimes influenced the surface runoff coefficient and runoff depth on sloping farmland for conventional and contour tillage, with the uniform regime generating the highest runoff coefficient (5.20% and 5.82%) and runoff depth (2.00% and 2.05%), respectively. For the conventional tillage, soil moisture at a depth of 0–20 cm increased appreciably when the rainfall amount was larger than 20 mm and larger than 30 mm for the advanced regime. For the contour tillage, soil moisture in 20–40 cm layer increased for the advanced regime when the rainfall amount was larger than 15 mm and 30 mm, while the values were modified with rainfall duration and the antecedent dry day (ADD). A longer rainfall duration had a more obvious effect on soil moisture increasing in deep soil. At a depth of 20 cm, the ADD showed an appreciably positive correlation with the increment in soil moisture, which means that a brief ADD produces a compounding effect for a natural rainfall event. The present results underline the complexity of the effect of the rainfall events on soil moisture under two tillage measures for different rainfall regimes and suggest that the advanced regime significantly affects the distinction of soil moisture and the contour tillage can effectively reduce soil water loss and enhance water storage on the sloping farmland with red soil, presenting a theoretical basis for local soil and water conservation research and sloping farmland conservation tillage management. Full article

In order to clarify the mechanical response of permeable asphalt pavements under a temperature effect, the mechanical responses of different types of permeable asphalt pavements, which were based on a self-developed drainage SBS-modified asphalt mixture with fiber, were simulated using ANSYS finite element software(APDL 19.2). The influence of temperature and temperature change on the mechanical behavior of the permeable asphalt pavements was studied, and the mechanical responses of the pavements at different driving speeds was analyzed. The results show that the extreme values of surface deflection, compressive strain of the soil foundation top surface, and the shear stress and tensile stress of the upper-layer bottom of the three kinds of pavements under dynamic load were about 10% smaller than those under static loads, and the extreme values under different temperature conditions were 28%~50% larger than the values obtained without different temperature conditions. During the 12 h heating process, the mechanical indexes of the three types of pavements with axle loads were consistent with the change law of temperature, and the peak values of the mechanical indexes under dynamic loads were smaller than those under static loads. In addition, the mechanical indexes of the three types of pavements under dynamic loads had the same law of change with speed under the same conditions, and the values were less than the extreme values under static loads, but the degree of influence was different. Full article

For small target objects on fast-moving conveyor belts, traditional vision detection algorithms equipped with conventional robotic arms struggle to capture the long and short-range pixel dependencies crucial for accurate detection. This leads to high miss rates and low precision. In this study, we integrate the traditional EMA (efficient multi-scale attention) algorithm with the c2f (channel-to-pixel) module from the original YOLOv8, alongside a Faster-Net module designed based on partial convolution concepts. This fusion results in the Faster-EMA-Net module, which greatly enhances the ability of the algorithm and robotic technologies to extract pixel dependencies for small targets, and improves perception of dynamic small target objects. Furthermore, by incorporating a small target semantic information enhancement layer into the multiscale feature fusion network, we aim to extract more expressive features for small targets, thereby boosting detection accuracy. We also address issues with training time and subpar performance on small targets in the original YOLOv8 algorithm by improving the loss function. Through experiments, we demonstrate that our attention-based visual detection algorithm effectively enhances accuracy and recall rates for fast-moving small targets, meeting the demands of real industrial scenarios. Our approach to target detection using industrial robotic arms is both practical and cutting-edge. Full article

Following the global financial crisis, an increasing amount of attention has been directed towards examining the Beveridge curve (BC), which indicates the relationship between unemployment and vacancy rates. This research analyzes the unemployment–vacancy rate dynamics in the Turkiye labor market during both the global financial crisis and COVID-19 periods. The findings from this study demonstrate that the labor market exhibits deteriorating efficiency, as evidenced by movement of BC away from the origin. The unemployment and vacancy rates both increase over time, with a leftward (rightward) shift of BC during the global financial crisis (COVID-19) period. The study also reveals that both crises had no significant effect on unemployment–vacancy rate dynamics. In the Turkish labor market, there exists a situation where the vacancy rate is in shortfall of the unemployment level in Turkiye. This creates a positive relationship between these two factors. The labor market in Turkiye experiences inefficiencies as it struggles to generate a sufficient number of jobs to meet the demand from job seekers. Full article

Photocatalysts with different molar ratios of Ag-modified ZnO to g-C₃N₄ were prepared through an electrostatic self-assembly method and characterized through techniques such as X-ray diffraction, Fourier transform infrared spectroscopy, and scanning electron microscopy. The resulting Ag-ZnO/g-C₃N₄ photocatalysts exhibited a unique 1D-0D-2D morphology and Z-type heterojunction. Moreover, g-C₃N₄ nanosheets with large layer spacing were prepared using acid treatment and thermal stripping methods. The Z-type heterostructure and localized surface plasmon resonance effect of Ag nanowires enabled high-speed electron transfer between the materials, while retaining large amounts of active substances, and broadened the light response range. Because of these features, the response current of the materials improved, and their impedance and photoluminescence reduced. Among the synthesized photocatalysts, 0.05Ag-ZnO/g-C₃N₄ (molar ratio of g-C₃N₄/ZnO: 0.05) exhibited the highest photocatalytic performance under UV–visible light. It degraded 98% of methylene blue in just 30 min, outperforming both g-C₃N₄ (21% degradation in 30 min) and Ag-ZnO (84% degradation in 30 min). In addition, 0.05Ag-ZnO/g-C₃N₄ demonstrated high cycling stability. Full article

Human papillomavirus (HPV) is a common sexually transmitted infection. Despite a safe and effective vaccine, uptake continues to be suboptimal. Recently, focus has moved to college campuses in an effort to increase vaccination rates. Little is known about the extent of efforts to reach graduate students on college campuses in the United States and the vaccination rates within this subpopulation. This scoping review assessed the literature on knowledge, attitudes, beliefs, and behaviors about HPV and HPV vaccination among graduate and post-baccalaureate professional students in the United States. This review also aims to identify areas for further research to improve institutions’ abilities to create health programming to increase HPV awareness and HPV vaccination coverage on their campuses. Publications focusing on knowledge, attitudes, beliefs, and behaviors about HPV and HPV vaccination in post-baccalaureate students were included. The systematic review of PubMed, CINAHL, and Embase identified 2562 articles, and 56 articles met all inclusion criteria and were included in this scoping review. A majority of the reviewed studies investigated some combination of knowledge, attitudes, behaviors, and beliefs about HPV and the HPV vaccine in students in professional programs such as medicine. Study design approaches were primarily cross-sectional, utilizing web-based survey distribution methods. HPV vaccination status and HPV screening behaviors were primarily measured through participant self-report. There is limited research investigating post-baccalaureate student knowledge, attitudes, beliefs, and behaviors about HPV and HPV vaccination. There is a need for researchers to further investigate the needs of graduate students to create informative and effective HPV programming. Full article

To address the issue of local optima encountered during the multi-objective optimization process with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm, this paper introduces an enhanced version of the NSGA-II. This improved NSGA-II incorporates polynomial and simulated binary crossover operators into the genetic algorithm’s crossover phase to refine its performance. For evaluation purposes, the classic ZDT benchmark functions are employed. The findings reveal that the enhanced NSGA-II algorithm achieves higher convergence accuracy and surpasses the performance of the original NSGA-II algorithm. When applied to the machining of the high-hardness material 20MnCrTi, four algorithms were utilized: the improved NSGA-II, the conventional NSGA-II, NSGA-III, and MOEA/D. The experimental outcomes show that the improved NSGA-II algorithm delivers a more optimal combination of process parameters, effectively enhancing the workpiece’s surface roughness and material removal rate. This leads to a significant improvement in the machining quality of the workpiece surface, demonstrating the superiority of the improved algorithm in optimizing machining processes. Full article

The development of gel electrophoresis-based biodetection assays for point-of-care analysis are highly demanding. In this work, we proposed a ratiometric gel electrophoresis-based biosensing platform by employing catalytic hairpin assembly (CHA) process functions as both the signal output and the signal amplification module. Two types of nucleic acids, DNA and miRNA, are chosen for demonstration. The proposed strategy indeed provides a new paradigm for the design of a portable detection platform and may hold great potential for sensitive diagnoses. Full article

Physics is living an era of unprecedented cross-fertilization among the different areas of science. In this perspective review, we discuss the manifold impact that state-of-the-art cold and ultracold-atomic platforms can have in fundamental and applied science through the development of platforms for quantum simulation, computation, metrology and sensing. We illustrate how the engineering of table-top experiments with atom technologies is engendering applications to understand problems in condensed matter and fundamental physics, cosmology and astrophysics, unveil foundational aspects of quantum mechanics, and advance quantum chemistry and the emerging field of quantum biology. In this journey, we take the perspective of two main approaches, i.e., creating quantum analogues and building quantum simulators, highlighting that independently of the ultimate goal of a universal quantum computer to be met, the remarkable transformative effects of these achievements remain unchanged. We wish to convey three main messages. First, this atom-based quantum technology enterprise is signing a new era in the way quantum technologies are used for fundamental science, even beyond the advancement of knowledge, which is characterised by truly cross-disciplinary research, extended interplay between theoretical and experimental thinking, and intersectoral approach. Second, quantum many-body physics is unavoidably taking center stage in frontier’s science. Third, quantum science and technology progress will have capillary impact on society, meaning this effect is not confined to isolated or highly specialized areas of knowledge, but is expected to reach and have a pervasive influence on a broad range of society aspects: while this happens, the adoption of a responsible research and innovation approach to quantum technologies is mandatory, to accompany citizens in building awareness and future scaffolding. Following on all the above reflections, this perspective review is thus aimed at scientists active or interested in interdisciplinary research, providing the reader with an overview of the current status of these wide fields of research where cold and ultracold-atomic platforms play a vital role in their description and simulation. Full article

(1) This paper, based on the characteristics of complex steel structures as well as difficult points in the process of their detailed design, introduces the product design concept of DfMA (Design for Manufacturing and Assembly) from the manufacturing industry and studies the detailed design method of BIM-FEM model conversion. The BIM software Revit (2020) is used as the basis for the BIM detailed design of the project, which achieves the purpose of rapid modeling and provides a detailed design model basis for finite element analysis. (2) Utilizing the Revit API and C# for secondary development as the technical means, this approach involves converting the geometric entity model described by CSG-Brep into an APDL stream. This creates an interface with the finite element analysis software ANSYS (12.0) to implement the detailed design of BIM-FEM model conversion, optimizing the algorithm for converting complex analysis models that require high precision for special-shaped steel structures. (3) This research addresses issues such as the disconnection between the design, manufacturing, and construction of special-shaped steel structures, providing support for design decisions. Moreover, it enhances the detailed design method by improving the standardization of special-shaped components under the condition of design diversity. (4) These studies provide sustainability for engineering design, manufacturing, and construction projects, enabling the maximization of benefits and product lifecycle management (PLM) through these projects. (5) Finally, a case study analysis was conducted on the Wuhan City New Generation Weather Radar Construction Project, designed by the Central South Architectural Design Institute (CSADI), to verify the detailed design of BIM-FEM model conversion. This proved the scientific validity, practicality, and necessity of this research. Full article

Objective: Familial isolated hypoparathyroidism is a rare genetic disorder due to no or low production of the parathyroid hormone, disturbing calcium and phosphate regulation. The resulting hypocalcemia may lead to dental abnormalities, such as enamel hypoplasia. The aim of this paper was to describe the full-mouth rehabilitation of a 15-year-old girl with chronic hypocalcemia due to a rare congenital hypoparathyroidism. Clinical considerations: In this patient, in the young adult dentition, conservative care was preferred. Onlays or stainless-steel crowns were performed on the posterior teeth, and direct or indirect (overlays and veneerlays) were performed on the maxillary premolars, canines, and incisors, using a digital wax-up. The mandibular incisors were bleached. The treatment clearly improved the patient’s oral quality of life, with fewer sensitivities, better chewing, and aesthetic satisfaction. The difficulties were the regular monitoring and the limited compliance of the patient. Conclusion: Despite no clinical feedback in the literature, generalized hypomineralized/hypoplastic teeth due to hypoparathyroidism in a young patient can be treated as amelogenesis imperfecta (generalized enamel defects) with a conservative approach for medium-term satisfactory results. Highlights: This study provides new insights into the management of enamel hypoplasia caused by familial isolated hypoparathyroidism, helping to improve patient outcomes in similar cases. Full article

Online sexual grooming (a manipulative process in which the perpetrator locates a young person and creates an abusive relationship with the child that involves sexual exploitation) poses significant challenges to parents. This study examined how parents of adolescent victims of online sexual grooming experienced guiding their children through the event. This qualitative study, conducted in Israel, was based on semi-structured in-depth interviews with 15 parents who guided their adolescents who had been subjected to online sexual grooming. Results indicate that the parents reported a spectrum of emotions, from insecurity and guilt to a sense of control and satisfaction in managing the situation. Also, the reluctance of some parents to engage with the education system indicates potential trust issues. The study demonstrates the urgent need for targeted interventions to equip parents and educational professionals with the necessary knowledge for prevention and effective response to online sexual grooming. Implications for future research, policy, and practice are discussed. Full article

The foundation of materials science and engineering is the establishment of process–microstructure–property links, which in turn form the basis for materials and process development and optimization. At the heart of this is the characterization and quantification of the material’s microstructure. To date, microstructure quantification has traditionally involved a human deciding what to measure and included labor-intensive manual evaluation. Recent advancements in artificial intelligence (AI) and machine learning (ML) offer exciting new approaches to microstructural quantification, especially classification and semantic segmentation. This promises many benefits, most notably objective, reproducible, and automated analysis, but also quantification of complex microstructures that has not been possible with prior approaches. This review provides an overview of ML applications for microstructure analysis, using complex steel microstructures as examples. Special emphasis is placed on the quantity, quality, and variance of training data, as well as where the ground truth needed for ML comes from, which is usually not sufficiently discussed in the literature. In this context, correlative microscopy plays a key role, as it enables a comprehensive and scale-bridging characterization of complex microstructures, which is necessary to provide an objective and well-founded ground truth and ultimately to implement ML-based approaches. Full article

The Internet of Things (IoT) with non-orthogonal multiple access (NOMA) has been anticipated to offer diverse real-time applications, wherein the crux is to guarantee the age of information (AoI) for dynamic traffic. However, the traffic temporal variation provokes the interdependence between queue status and interference, in which context the AoI performance remains to be further explored. In this paper, an analytical framework is established to characterize the AoI performance in NOMA-IoT networks with random Bernoulli and deterministic periodic arrivals. Particularly, a numerical algorithm is devised to obtain the queue service rate, and tractable expressions for AoI violation probability and average AoI under both the first-come first-served (FCFS) and the preemptive last-come first-served (LCFS-PR) service disciplines are derived. Simulations are conducted to validate the proposed analysis. The results unveil that LCFS-PR conduces to better AoI performance than FCFS, and yet the gain diverges for each device with different traffic arrival configurations. In addition, the result shows that with sporadic traffic arrival, the periodic pattern outperforms the Bernoulli pattern, whereas this advantage gradually diminishes with more frequent packet arrival. Full article

The aim of this study was to characterize the genotype and phenotype heterogeneity of patients with SCN1A gene mutations in the Polish population, fulfilling the criteria for the diagnosis of Dravet syndrome (DRVT). Particularly important was the analysis of the clinical course, the type of epileptic seizures and the co-occurrence of additional features such as intellectual disability, autism or neurological symptoms such as ataxia or gait disturbances. Based on their results and the available literature, the authors discuss potential predictors for DRVT. Identifying these early symptoms has important clinical significance, affecting the course and disease prognosis. 50 patients of the Pediatric Neurology Clinic of the Institute of Mother and Child in Warsaw clinically diagnosed with DRVT and carriers of SCN1A pathogenic variants were included. Clinical data were retrospectively collected from caregivers and available medical records. Patients in the study group did not differ significantly in parameters such as type of first seizure and typical epileptic seizures from those described in other studies. The age of onset of the first epileptic seizure was 2–9 months. The co-occurrence of intellectual disability was confirmed in 71% of patients and autism in 18%. The study did not show a correlation between genotype and phenotype, considering the severity of the disease course, clinical symptoms, response to treatment, the presence of intellectual disability, autism symptoms or ataxia. From the clinical course, a significant problem was the differentiation between complex febrile convulsions and symptoms of DRVT. The authors suggest that parameters such as the age of the first seizure, less than one year of age, the onset of a seizure up to 72 h after vaccination and the presence of more than two features of complex febrile seizures are more typical of DRVT, which should translate into adequate diagnostic and clinical management. The substantial decrease in the age of genetic verification of the diagnosis, as well as the decline in the use of sodium channel inhibitors, underscores the growing attention of pediatric neurologists in Poland to the diagnosis of DRVT. Full article

$\kappa$ Draconis is a binary system with a classical Be star as the primary component. Its emission-line spectrum consists of hydrogen lines, notably the H$\alpha$ line with peak intensity ratio (V/R) variations phase-locked with the orbital period P = 61.55 days. Among binaries demonstrating the Be phenomenon, $\kappa$ Dra stands out as one of a few systems with a discernible mass of its secondary component. Based on more than 200 spectra obtained in 2014–2023, we verified the physical parameters and constructed the mass function. We used part of these data obtained in 2014–2021 to investigate regions in the circumstellar disk of the primary component that emit the H$\alpha$ line using the Doppler tomography method. The results show that the disk has a non-uniform density distribution with a prominent enhancement at ${\mathrm{V}}_y$ ≈ 99 km ${\mathrm{s}}^{-1}$ and ${\mathrm{V}}_x$$\approx -6$ km ${\mathrm{s}}^{-1}$ that corresponds to a cloud-like source of the double-peaked H$\alpha$ line profile. We argue that this enhancement’s motion is responsible for the periodic variations in the H$\alpha$ V/R ratio, which is synchronised in orbital phase with the radial velocity (RV) of absorption lines from the atmosphere of the primary component. Full article

This systematic review and meta-analysis evaluated the combined effects of clinician-led and community-based group exercise interventions on a range of health outcomes in adults with type 2 diabetes mellitus. Our literature search spanned Medline, Scopus, PubMed, Embase, and CINAHL databases, focusing on peer-reviewed studies published between January 2003 and January 2023. We included studies involving participants aged 18 years and older and articles published in English, resulting in a dataset of eight studies with 938 participants. Spanning eight peer-reviewed studies with 938 participants, the analysis focused on the interventions’ impact on glycemic control, physical fitness, and anthropometric and hematological measurements. Outcomes related to physical fitness, assessed through the six-minute walk test, the 30 s sit-to-stand test, and the chair sit-and-reach test, were extracted from five studies, all of which reported improvements. Anthropometric outcomes from seven studies highlighted positive changes in waist circumference and diastolic blood pressure; however, measures such as body mass index, systolic blood pressure, weight, and resting heart rate did not exhibit significant changes. Hematological outcomes, reviewed in four studies, showed significant improvements in fasting blood glucose, triglycerides, and total cholesterol, with glycemic control evidenced by reductions in HbA1c levels, yet LDL and HDL cholesterol levels remained unaffected. Ten of the fifteen outcome measures assessed showed significant enhancement, indicating that the intervention strategies implemented may offer substantial health benefits for managing key type 2 diabetes mellitus-related health parameters. These findings in combination with further research, could inform the refinement of physical activity guidelines for individuals with type 2 diabetes mellitus, advocating for supervised group exercise in community settings. Full article

Pattern recognition systems always misclassify anomalies, which can be dangerous for uninformed users. Therefore, anomalies must be filtered out from each classification. The main challenge for the anomaly filter design is the huge number of possible anomaly samples compared with the number of samples in the training set. Tailoring the filter for the given classifier is just the first step in this reduction. Paper tests the hypothesis that the filter trained in avoiding “near” anomalies will also refuse the “far” anomalies, and the anomaly detector is then just a classifier distinguishing between “far real” and “near anomaly” samples. As a “far real” samples generator was used, a Generative Adversarial Network (GAN) fake generator that transforms normally distributed random seeds into fakes similar to the training samples. The paper proves the assumption that seeds unused in fake training will generate anomalies. These seeds are distinguished according to their Chebyshev norms. While the fakes have seeds within the hypersphere with a given radius, the near anomalies have seeds within the sphere near cover. Experiments with various anomaly test sets have shown that GAN-based anomaly detectors create a reliable anti-anomaly shield using the abovementioned assumptions. The proposed anomaly detector is tailored to the given classifier, but its limitation is due to the need for the availability of the database on which the classifier was trained. Full article