All articles published by MDPI are made immediately available worldwide under an open access license. No special
permission is required to reuse all or part of the article published by MDPI, including figures and tables. For
articles published under an open access Creative Common CC BY license, any part of the article may be reused without
permission provided that the original article is clearly cited. For more information, please refer to
https://www.mdpi.com/openaccess.
Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature
Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for
future research directions and describes possible research applications.
Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive
positive feedback from the reviewers.
Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world.
Editors select a small number of articles recently published in the journal that they believe will be particularly
interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the
most exciting work published in the various research areas of the journal.
This study systematically evaluates the influence of copper (Cu) addition in gas-shielded solid wires on the microstructure and cryogenic toughness of X80 pipeline steel welds. Welds were fabricated using solid wires with varying Cu contents (0.13–0.34 wt.%) under identical gas metal arc welding
[...] Read more.
This study systematically evaluates the influence of copper (Cu) addition in gas-shielded solid wires on the microstructure and cryogenic toughness of X80 pipeline steel welds. Welds were fabricated using solid wires with varying Cu contents (0.13–0.34 wt.%) under identical gas metal arc welding (GMAW) parameters. The mechanical capacities were assessed via tensile testing, Charpy V-notch impact tests at −20 °C and Vickers hardness measurements. Microstructural evolution was characterized through optical microscopy (OM), scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). Key findings reveal that increasing the Cu content from 0.13 wt.% to 0.34 wt.% reduces the volume percentage of acicular ferrite (AF) in the weld metal by approximately 20%, accompanied by a significant decline in cryogenic toughness, with the average impact energy decreasing from 221.08 J to 151.59 J. Mechanistic analysis demonstrates that the trace increase in the Cu element. The phase transition temperature and inclusions is not significant but can refine the prior austenite grain size of the weld, so that the total surface area of the grain boundary increases, and the surface area of the inclusions within the grain is relatively small, resulting in the nucleation of acicular ferrite within the grain being weak. This microstructural transition lowers the critical crack size and diminishes the density for high-angle grain boundaries (HAGBs > 45°), which weakens crack deflection capability. Consequently, the crack propagation angle decreases from 54.73° to 45°, substantially reducing the energy required for stable crack growth and deteriorating low-temperature toughness.
Full article
High-density polyethylene (HDPE) pipes are widely used in urban natural gas pipeline systems due to their excellent mechanical and chemical properties. However, welding joints are critical weak points in these pipelines, and defects, such as cold welding—caused by reduced temperature or/and insufficient pressure—pose
[...] Read more.
High-density polyethylene (HDPE) pipes are widely used in urban natural gas pipeline systems due to their excellent mechanical and chemical properties. However, welding joints are critical weak points in these pipelines, and defects, such as cold welding—caused by reduced temperature or/and insufficient pressure—pose significant safety risks. Traditional non-destructive testing (NDT) methods face challenges in detecting cold welding defects due to the polymer’s complex structure and characteristics. This study presents a microwave-based NDT system for detecting cold welding defects in thermal fusion welds of HDPE pipes. The system uses a focusing antenna with a resonant cavity, connected to a vector network analyzer (VNA), to measure changes in microwave parameters caused by cold welding defects in thermal fusion welds. Experiments conducted on HDPE pipes welded at different temperatures demonstrated the system’s effectiveness in identifying areas with a lack of fusion. Mechanical and microstructural analyses, including tensile tests and scanning electron microscopy (SEM), confirmed that cold welding defects lead to reduced mechanical properties and lower material density. The proposed microwave NDT method offers a sensitive, efficient approach for detecting cold welds in HDPE pipelines, enhancing pipeline integrity and safety.
Full article
Pathological conditions of the spinal cord have been found to be associated with cervical spondylotic myelopathy (CSM). This study aims to explore the feasibility of automatic deep-learning-based classification of the pathological condition of the spinal cord to quantify its severity. A Diffusion Tensor
[...] Read more.
Pathological conditions of the spinal cord have been found to be associated with cervical spondylotic myelopathy (CSM). This study aims to explore the feasibility of automatic deep-learning-based classification of the pathological condition of the spinal cord to quantify its severity. A Diffusion Tensor Imaging (DTI)-based spinal cord pathological assessment method was proposed. A multi-dimensional feature fusion model, referred to as DCSANet-MD (DTI-Based CSM Severity Assessment Network-Multi-Dimensional), was developed to extract both 2D and 3D features from DTI slices, incorporating a feature integration mechanism to enhance the representation of spatial information. To evaluate this method, 176 CSM patients with cervical DTI slices and clinical records were collected. The proposed assessment model demonstrated an accuracy of 82% in predicting two categories of severity levels (mild and severe). Furthermore, in a more refined three-category severity classification (mild, moderate, and severe), using a hierarchical classification strategy, the model achieved an accuracy of approximately 68%, which significantly exceeded the baseline performance. In conclusion, these findings highlight the potential of the deep-learning-based method as a decision-making support tool for DTI-based pathological assessments of CSM, offering great value in monitoring disease progression and guiding the intervention strategies.
Full article
This paper studies the distributed robust predefined-time sliding mode control (DRPSC) problem for high-order heterogeneous multi-agent systems under input saturation while considering external disturbances and model uncertainties. Firstly, a distributed predefined-time state observer (PTSO) is designed for each agent to achieve individual estimation
[...] Read more.
This paper studies the distributed robust predefined-time sliding mode control (DRPSC) problem for high-order heterogeneous multi-agent systems under input saturation while considering external disturbances and model uncertainties. Firstly, a distributed predefined-time state observer (PTSO) is designed for each agent to achieve individual estimation of the state information of the virtual leader within a predefined time, and the observer does not need to count on the global information of the system. Secondly, a predefined-time auxiliary dynamic system (PTADS) is developed to solve the actuator’s input saturation problem. Thirdly, a distributed predefined-time sliding mode controller (PTSMC) is proposed, which ensures that the error converges to a small region near zero within a predefined time and combines H∞ control to deal with the lumped uncertainty disturbances in the system to improve the robustness of the system. In addition, a memory event-triggered mechanism (METM) is designed to reduce the communication frequency of the underactuated AUV-USV multi-agent system and reduce the consumption of communication resources. Finally, Lyapunov theory is employed to prove that the closed-loop system is predefined-time stable, and the simulation results demonstrate that the proposed method is effective.
Full article
Distributed energy resource systems offer improved energy utilization and reduced transmission losses by decentralizing power generation and load management. However, the power quality is often compromised by inefficient customer-side equipment, such as single-phase induction motors, which suffer from low efficiency and poor power
[...] Read more.
Distributed energy resource systems offer improved energy utilization and reduced transmission losses by decentralizing power generation and load management. However, the power quality is often compromised by inefficient customer-side equipment, such as single-phase induction motors, which suffer from low efficiency and poor power factor. To address this issue, this paper proposes a permanent magnet retrofitting method for single-phase induction motors, which replaces the squirrel-cage rotor with a permanent magnet rotor while preserving the original stator and winding structure. The proposed method aims to enhance motor performance without significant structural changes. A single-phase induction motor was retrofitted using the proposed method, and its performance was evaluated through finite element simulations to verify the effectiveness of the design approach. This study also investigated the key factors influencing motor starting performance after the introduction of permanent magnets. This study presents a practical and effective method for the permanent magnet retrofitting of single-phase induction motors, which contributes to improving motor efficiency and enhancing power quality in distributed energy resource systems.
Full article
Background/Objectives: Chronic pain and eating disorders are two prevalent and disabling pediatric health concerns, with serious, life-threatening consequences. These conditions can co-occur, yet little is known about best practices addressing comorbid pain and eating disorders. Delayed intervention for eating disorders may have
[...] Read more.
Background/Objectives: Chronic pain and eating disorders are two prevalent and disabling pediatric health concerns, with serious, life-threatening consequences. These conditions can co-occur, yet little is known about best practices addressing comorbid pain and eating disorders. Delayed intervention for eating disorders may have grave implications, as eating disorders have one of the highest mortality rates among psychological disorders. Moreover, chronic pain not only persists but worsens into adulthood when left untreated. This study aimed to understand pediatric clinicians’ experiences with adolescents with chronic pain and eating disorders. Methods: Semi-structured interviews were conducted with hospital-based physicians (N = 10; 70% female; M years of experience = 15.3) and psychologists (N = 10; 80% female; M years of experience = 10.2) specializing in anesthesiology/pain, adolescent medicine/eating disorders, and gastroenterology across the United States. Audio transcripts were coded, and thematic analysis was used to identify key themes. Results: Clinicians described frequently encountering adolescents with chronic pain and eating disorders. Clinicians described low confidence in diagnosing comorbid eating disorders and chronic pain, which they attributed to lack of screening tools and limited training. Clinicians collaborated with and consulted clinicians who encountered adolescents with chronic pain and/or eating disorders. Conclusions: Results reflect clinicians’ desire for additional resources, training, and collaboration to address the needs of this population. Targets for future research efforts in comorbid pain and eating disorders were highlighted. Specifically, results support the development of screening tools, program development to improve training in complex medical and psychiatric presentations, and methods to facilitate more collaboration and consultation across health care settings, disciplines, and specialties.
Full article
In ecosystems, spatial structure plays a fundamental role in shaping the observed dynamics. In particular, the availability and distribution of unoccupied sites—potential habitats—can strongly affect species persistence. However, mathematical models of ecosystems based on ordinary differential equations (ODEs) often neglect the explicit representation
[...] Read more.
In ecosystems, spatial structure plays a fundamental role in shaping the observed dynamics. In particular, the availability and distribution of unoccupied sites—potential habitats—can strongly affect species persistence. However, mathematical models of ecosystems based on ordinary differential equations (ODEs) often neglect the explicit representation of these unoccupied sites. Here, probabilistic cellular automata (PCA) are used to reproduce two basic ecological scenarios: competition between two species and a predator–prey relationship. In these PCA-based models, unoccupied sites are taken into account. Subsequently, a mean field approximation of the PCA behavior is formulated in terms of ODEs. The variables of these ODEs are the numbers of individuals of both species and the number of empty cells in the PCA lattice. Including the empty cells in the ODEs leads to a modified version of the Lotka–Volterra system. The long-term behavior of the solutions of the ODE-based models is examined analytically. In addition, numerical simulations are carried out to compare the time evolutions generated by these two modeling approaches. The impact of explicitly considering unoccupied sites is discussed from a modeling perspective.
Full article
Helium (He) accumulation in tungsten—widely used as a plasma-facing material in fusion reactors—can lead to clustering, trap mutation, and eventual formation of helium bubbles, critically impacting material performance. To clarify the atomic-scale mechanisms governing this process, we conducted systematic molecular statics and molecular
[...] Read more.
Helium (He) accumulation in tungsten—widely used as a plasma-facing material in fusion reactors—can lead to clustering, trap mutation, and eventual formation of helium bubbles, critically impacting material performance. To clarify the atomic-scale mechanisms governing this process, we conducted systematic molecular statics and molecular dynamics simulations across a wide range of vacancy cluster sizes (n = 1–27) and temperatures (500–2000 K). We identified the onset of trap mutation through abrupt increases in tungsten atomic displacement. At 0 K, the critical helium-to-vacancy (He/V) ratio required to trigger mutation was found to scale inversely with cluster size, converging to ~5.6 for large clusters. At elevated temperatures, thermal activation lowered the mutation threshold and introduced a distinct He/V stability window. Below this window, clusters tend to dissociate; above it, trap mutation occurs with near certainty. This critical He/V ratio exhibits a linear dependence on temperature and can be described by a size- and temperature-dependent empirical relation. Our results provide a quantitative framework for predicting trap mutation behavior in tungsten, offering key input for multiscale models and informing the design of radiation-resistant materials for fusion applications.
Full article
Tebuconazole (TBZ), a triazole-class fungicide widely used in agriculture, is frequently detected in aquatic environments due to runoff and leaching, where it poses a threat to non-target aquatic organisms. This study investigates the acute toxicity of TBZ on juvenile rainbow trout (Oncorhynchus [...] Read more.
Tebuconazole (TBZ), a triazole-class fungicide widely used in agriculture, is frequently detected in aquatic environments due to runoff and leaching, where it poses a threat to non-target aquatic organisms. This study investigates the acute toxicity of TBZ on juvenile rainbow trout (Oncorhynchus mykiss), a commercially important cold-water fish species. The 96 h LC50 value was determined to be 9.05 mg/L using probit analysis. In addition to mortality, the physiological responses of fish exposed to both LC50 and maximum tolerance concentration (MTC; 6 mg/L) were evaluated through haematological and histological assessments. TBZ exposure significantly suppressed key haematological parameters, particularly WBC, RBC, HGB, HCT, and LYM, indicating immunosuppression and potential hypoxia. Histological examination revealed progressive and regressive damage in gill tissues, including epithelial lifting, hyperplasia, and hypertrophy, which were more severe in the LC50 group. These alterations were quantified using a semi-quantitative scoring system. Additionally, significant changes in biochemical parameters such as ALT, AST, creatinine, total protein, and glucose levels were observed, further indicating hepatic and renal dysfunctions induced by TBZ exposure. The findings demonstrate that TBZ exposure induces substantial physiological and structural impairments in rainbow trout, highlighting the importance of assessing the ecological risks of fungicide contamination in aquatic environments. The study also provides a dose–response model that can be used to estimate mortality risk in aquaculture operations exposed to TBZ.
Full article
Background: Several epidemiological studies have indicated that metabolic syndrome (MetS) after renal transplantation is caused by an accumulation of non-immunological risks of renal transplantation, and affects the prognosis of the kidney and the patient by increasing the risk of arteriosclerosis and cardiovascular complications.
[...] Read more.
Background: Several epidemiological studies have indicated that metabolic syndrome (MetS) after renal transplantation is caused by an accumulation of non-immunological risks of renal transplantation, and affects the prognosis of the kidney and the patient by increasing the risk of arteriosclerosis and cardiovascular complications. The incidence of MetS in Japanese renal transplant recipients is 14.9 to 23.8%, but its effects on cardiovascular events and kidney prognosis are not clear. Here, we report the results of a longitudinal study on MetS in renal transplant recipients. Methods: A retrospective cohort study was conducted in 104 stable renal transplant recipients who attended our outpatient department from January 2006 to June 2007 and were diagnosed with MetS at least 6 months after renal transplantation until 31 December 2020, or did not have MetS. The impact of MetS on composite vascular events was examined using multivariate Cox proportional hazards analysis. Results: The hazard ratios for the impact of MetS on composite vascular events diagnosed by NCEP Japan, NCEP Original, NCEP Asia, and IDF criteria on composite vascular events were 2.78 (95% CI: 1.15 to 6.75, p = 0.024), 2.65 (95% CI: 1.04 to 6.80, p = 0.042), 2.37 (95% CI: 0.93 to 6.01, p = 0.070), and 1.91 (95% CI: 0.77 to 4.75, p = 0.164), respectively. P for interaction was used to test the influence of each indicator, but was not statistically significant. Conclusions: MetS is a robust risk factor for graft loss and development of cardiovascular events in Japanese renal transplant recipients, even during long-term follow-up. This finding emphasizes the importance of monitoring and managing MetS in this population to improve long-term outcomes.
Full article
This study introduces a novel approach for minimizing assembly errors in wind turbine gearboxes using a hybrid optimization algorithm, Particle Swarm-Bacteria Foraging Optimization (PSBFO). By integrating error-driven task sequencing and real-time error feedback with the PSBFO algorithm, we developed a comprehensive framework tailored
[...] Read more.
This study introduces a novel approach for minimizing assembly errors in wind turbine gearboxes using a hybrid optimization algorithm, Particle Swarm-Bacteria Foraging Optimization (PSBFO). By integrating error-driven task sequencing and real-time error feedback with the PSBFO algorithm, we developed a comprehensive framework tailored to the unique challenges of gearbox assembly. The PSBFO algorithm combines the global search capabilities of PSO with the local refinement of BFO, creating a unified framework that efficiently explores task sequencing, minimizing misalignment and torque misapplication assembly errors. The methodology results in a 38% reduction in total assembly errors, improving both process accuracy and efficiency. Specifically, the PSBFO algorithm reduced errors from an initial value of 50 to a final value of 5 across 20 iterations, with components such as the low-speed shaft and planetary gear system showing the most substantial reductions. The 50 to 5 error reduction represents a significant decrease in assembly errors from an unoptimized (50) to an optimized (5) sequence, achieved through the PSBFO algorithm, by minimizing dimensional deviations, torque mismatches, and alignment errors across 26 critical gearbox components. While the primary focus is on wind turbine gearbox applications, this approach has the potential for broader applicability in error-prone assembly processes in industries such as automotive and aerospace, warranting further validation in future studies.
Full article
Integrated rice–crayfish (Oryza sativa–Procambarus clarkii) co-culture (RC) systems have gained prominence due to their economic benefits and ecological sustainability; however, the interactions between soil properties and microbial communities in such systems remain poorly understood. This study evaluated the effects
[...] Read more.
Integrated rice–crayfish (Oryza sativa–Procambarus clarkii) co-culture (RC) systems have gained prominence due to their economic benefits and ecological sustainability; however, the interactions between soil properties and microbial communities in such systems remain poorly understood. This study evaluated the effects of the RC systems on soil physicochemical characteristics and microbial dynamics in paddy fields of southern Henan Province, China, over the 2023 growing season and subsequent fallow period. Using a randomized complete design, rice monoculture (RM, as the control) and RC treatments were compared across replicated plots. Soil and water samples were collected post-harvest and pre-transplanting to assess soil properties, extracellular enzyme activity, and microbial community structure. Results showed that RC significantly enhanced soil moisture by up to 30.2%, increased soil porosity by 9.6%, and nearly tripled soil organic carbon compared to RM. The RC system consistently elevated nitrogen (N), phosphorus (P), and potassium (K) throughout both the rice growth and fallow stages, indicating improved nutrient availability and retention. Elevated extracellular enzyme activities linked to carbon, N, and P cycling were observed under RC, with enzymatic stoichiometry revealing increased microbial nutrient limitation intensity and a shift toward P limitation. Microbial community composition was significantly altered under RC, showing increased biomass, a higher fungi-to-bacteria ratio, and greater relative abundance of Gram-positive bacteria, reflecting enhanced soil biodiversity and ecosystem resilience. Further analyses using the Mantel test and Random Forest identified extracellular enzyme activities, PLFAs, soil moisture, and bulk density as major factors shaping microbial communities. Redundancy analysis (RDA) confirmed that total potassium (TK), vector length (VL), soil pH, and total nitrogen (TN) were the strongest environmental predictors of microbial variation, jointly explaining 74.57% of the total variation. Our findings indicated that RC improves soil physicochemical conditions and microbial function, thereby supporting sustainable nutrient cycling and offering a promising, environmentally sound strategy for enhancing productivity and soil health in rice-based agro-ecosystems.
Full article
The human Tau protein stands for one of the most conspicuous and crucial hallmarks of Alzheimer’s disease (AD) diagnosis, along with other tauopathies. However, the assay for direct detection of tiny Tau protein concentrations in human samples continues to pose a significant challenge
[...] Read more.
The human Tau protein stands for one of the most conspicuous and crucial hallmarks of Alzheimer’s disease (AD) diagnosis, along with other tauopathies. However, the assay for direct detection of tiny Tau protein concentrations in human samples continues to pose a significant challenge for the early diagnosis of AD. Thus, an amplification-based strategy is required. In this proposed work, we established an impedimetric immunosensor to detect human Tau-441 protein in PBS buffer using a sandwich approach, wherein we employed two distinct monoclonal antibodies (HT7 and BT2) that specifically recognize the amino acids 159–198 of the target protein. Through this strategy, we were able to detect as low as 0.08 pg/mL. These findings were attributed to the use of a biotinylated antibody (BT2)-streptavidin complex, which facilitated the amplification of the normalized signal, resulting in a lower limit of detection in comparison to the directly based immunosensors. Subsequently, we investigated the designed immunosensor to assess the assay’s selectivity in the presence of different off-targets, and no cross-interaction was recorded. The outcomes of our study provide valuable new insights into the application of sandwich-based assay as a highly sensitive and selective immunosensor for the detection of small protein.
Full article
Myeloid-derived growth factor (MYDGF), named in reference to its secretion from myeloid cells in bone marrow, is a novel protein with anti-apoptotic and tissue-repairing properties. MYDGF is found in various human tissues affected by different diseases. To date, however, MYDGF expression has yet
[...] Read more.
Myeloid-derived growth factor (MYDGF), named in reference to its secretion from myeloid cells in bone marrow, is a novel protein with anti-apoptotic and tissue-repairing properties. MYDGF is found in various human tissues affected by different diseases. To date, however, MYDGF expression has yet to be reported in the nervous system. Herein, we demonstrate for the first time that MYDGF mRNA levels increased in the zebrafish retina 1 h after optic nerve injury (ONI). MYDGF-producing cells were located in the photoreceptors and infiltrating leukocytic cells. We prepared the retina for MYDGF gene knockdown by performing intraocular injections using either MYDGF-specific morpholino or the CRISPR/Cas9 system. Under these MYDGF-knockdown retinal conditions, anti-apoptotic Bcl-2 mRNA was suppressed; in comparison, apoptotic caspase-3 and inflammatory TNFα mRNA were significantly upregulated in the zebrafish retina after ONI compared to the control. Furthermore, heat shock factor 1 (HSF1) was evidently suppressed under these conditions, leading to a significant number of apoptotic neurons. These findings indicate that MYDGF is a key molecule in the stimulation of neuronal regeneration in the central nervous system.
Full article
by
Francesco Monaco, Annarita Vignapiano, Stefania Landi, Ernesta Panarello, Benedetta Di Gruttola, Naomi Gammella, Silvia Adiutori, Eleonora Acierno, Valeria Di Stefano, Ilaria Pullano, Giulio Corrivetti and Luca Steardo Jr
Background: Art therapy is increasingly recognized as a valuable complementary intervention for individuals with eating disorders (EDs), who frequently experience comorbid anxiety and difficulties with emotional regulation. However, few studies have examined its short-term effects on state and trait anxiety within structured clinical
[...] Read more.
Background: Art therapy is increasingly recognized as a valuable complementary intervention for individuals with eating disorders (EDs), who frequently experience comorbid anxiety and difficulties with emotional regulation. However, few studies have examined its short-term effects on state and trait anxiety within structured clinical settings. Methods: This pilot study involved 19 adolescent females (mean age 17.7 ± 2.1 years) diagnosed with anorexia nervosa (AN) or bulimia nervosa (BN) and admitted to the Mariconda Regional Residence for Eating Disorders (ASL Salerno, Italy) in residential or semi-residential treatment. Participants completed a structured six-week cycle of weekly textile-based art therapy sessions, designed to promote emotional expression and body reconnection. State and trait anxiety levels were assessed pre- and post-session using the State-Trait Anxiety Inventory (STAI). Repeated-measures ANOVA was used to analyze state anxiety changes; a linear mixed-effects model was applied to trait anxiety. Results: State anxiety significantly decreased immediately after sessions (p = 0.002). A significant main effect of session (p = 0.01) and a time × session interaction (p = 0.025) indicated variability across sessions. Trait anxiety showed a non-significant trend toward reduction (p = 0.11); however, reductions were significant at sessions 4 (p = 0.015), 5 (p < 0.001), and 6 (p = 0.005). Conclusions: Art therapy may offer immediate reductions in state anxiety and may contribute to a longer-term reduction in trait anxiety with 4–6 sessions. These findings support integrating creative interventions within multidisciplinary ED treatment programs. Future research with larger samples and control groups is needed to confirm and expand upon these preliminary results.
Full article
Dense aggregations of species in the family Pinnidae give soft substrata a specific characterization. They may influence the biological and physical properties of the surrounding sediments. Bottom-trawl samplings performed in the Sea of Marmara revealed populations of a large pinnid species, particularly at
[...] Read more.
Dense aggregations of species in the family Pinnidae give soft substrata a specific characterization. They may influence the biological and physical properties of the surrounding sediments. Bottom-trawl samplings performed in the Sea of Marmara revealed populations of a large pinnid species, particularly at depths of 40–45 m in soft substrata. Both morphological and DNA analyses confirmed the species’ taxonomic identity as Atrina fragilis. This species had a population density ranging from 31 to 469 ind.km−2, and the shell lengths ranged from 21.3 to 31 cm. A total of 47 macrozoobenthic species belonging to eight taxonomic groups were found on the shells of ten live and nine dead A. fragilis individuals. Polychaeta accounted for 53% of the total number of species and 75% of the total number of individuals. Among these species, Protula tubularia and Serpula concharum comprised almost 30% of all epifaunal populations. Community parameters changed according to the shell length and width. Different faunal assemblages were encountered on the shells. Given the ecological significance of A. fragilis as both a habitat-forming and sensitive benthic species, conservation measures should prioritize the protection of known habitats and the regulation of activities that lead to seabed disturbance.
Full article
Cardiovascular diseases (CVDs) remain the leading cause of death globally, underscoring the urgent need for data-driven early diagnostic tools. This study proposes a multilayer artificial neural network (ANN) model for heart disease prediction, developed using a real-world clinical dataset comprising 13,981 patient records.
[...] Read more.
Cardiovascular diseases (CVDs) remain the leading cause of death globally, underscoring the urgent need for data-driven early diagnostic tools. This study proposes a multilayer artificial neural network (ANN) model for heart disease prediction, developed using a real-world clinical dataset comprising 13,981 patient records. Implemented on the Orange data mining platform, the ANN was trained using backpropagation and validated through 10-fold cross-validation. Dimensionality reduction via principal component analysis (PCA) enhanced computational efficiency, while Shapley additive explanations (SHAP) were used to interpret model outputs. Despite achieving 83.4% accuracy and high specificity, the model exhibited poor sensitivity to disease cases, identifying only 76 of 2233 positive samples, with a Matthews correlation coefficient (MCC) of 0.058. Comparative benchmarks showed that random forest and support vector machines significantly outperformed the ANN in terms of discrimination (AUC up to 91.6%). SHAP analysis revealed serum creatinine, diabetes, and hemoglobin levels to be the dominant predictors. To address the current study’s limitations, future work will explore LIME, Grad-CAM, and ensemble techniques like XGBoost to improve interpretability and balance. This research emphasizes the importance of explainability, data representativeness, and robust evaluation in the development of clinically reliable AI tools for heart disease detection.
Full article
Background/Objectives: Traditional hearing aid noise reduction algorithms offer no additional benefit in noisy situations for bimodal cochlear implant (CI) users with a CI in one ear and a hearing aid (HA) in the other. Recent breakthroughs in deep neural network (DNN)-based noise
[...] Read more.
Background/Objectives: Traditional hearing aid noise reduction algorithms offer no additional benefit in noisy situations for bimodal cochlear implant (CI) users with a CI in one ear and a hearing aid (HA) in the other. Recent breakthroughs in deep neural network (DNN)-based noise reduction have improved speech understanding for hearing aid users in noisy environments. These advancements could also boost speech perception in noise for bimodal CI users. This study investigated the effectiveness of DNN-based noise reduction in the HAs used by bimodal CI patients. Methods: Eleven bimodal CI patients, aged 71–89 years old, were fit with a Phonak Audéo Sphere Infinio 90 HA in their non-implanted ear and were provided with a Calm Situation program and Spheric Speech in Loud Noise program that uses DNN-based noise reduction. Sentence recognition scores were measured using AzBio sentences in quiet and in noise with the CI alone, hearing aid alone, and bimodally with both the Calm Situation and DNN HA programs. Results: The DNN program in the hearing aid significantly improved bimodal performance in noise, with sentence recognition scores reaching 79% compared to 60% with Calm Situation (a 19% average benefit, p < 0.001). When compared to the CI-alone condition in multi-talker babble, the DNN HA program offered a 40% bimodal benefit, significantly higher than the 21% score seen with the Calm Situation program. Conclusions: DNN-based noise reduction in HA significantly improves speech understanding in noise for bimodal CI users. Utilization of this technology is a promising option to address patients’ common complaint of speech understanding in noise.
Full article
by
Jeanette Carrera-Cevallos, Christian Muso, Julio C. Chacón Torres, Diego Salazar, Lander Pérez, Andrea C. Landázuri, Marco León, María López, Oscar Jara, Manuel Coronel, David Carrera and Liliana Acurio
Magenta Cherry or Eugenia (Syzygium paniculatum Gaertn) is an underutilized berry species with an interesting source of functional components. This study aimed to evaluate these berries’ morphometric, nutritional, and phytochemical characteristics at two ripening stages, CM: consumer maturity (CM) and OM: over-maturity. Morphometric
[...] Read more.
Magenta Cherry or Eugenia (Syzygium paniculatum Gaertn) is an underutilized berry species with an interesting source of functional components. This study aimed to evaluate these berries’ morphometric, nutritional, and phytochemical characteristics at two ripening stages, CM: consumer maturity (CM) and OM: over-maturity. Morphometric analysis revealed size and weight parameters comparable to commercial berries such as blueberries. Fresh fruits were processed into pulverized material, and in this, a proximate analysis was evaluated, showing high moisture content (88.9%), dietary fiber (3.56%), and protein (0.63%), with negligible fat, indicating suitability for low-calorie diets. Phytochemical screening by HPLC identified gallic acid, chlorogenic acid, hydroxycinnamic acid, ferulic acid, quercetin, rutin, and condensed tannins. Ethanol extracts showed stronger bioactive profiles than aqueous extracts, with significant antioxidant capacity (up to 803.40 µmol Trolox/g via Ferric Reducing Antioxidant Power (FRAP assay). Fourier-transform infrared spectroscopy (FTIR) and Raman spectroscopic analyses established structural transformations of hydroxyl, carbonyl, and aromatic groups associated with ripening. These changes were supported by observed variations in anthocyanin and flavonoid contents, both higher at the CM stage. A notable pigment loss in OM fruits could be attributed to pH changes, oxidative degradation, enzymatic activity loss, and biotic stressors. Antioxidant assays (DPPH, ABTS, and FRAP) confirmed higher radical scavenging activity in CM-stage berries. Elemental analysis identified minerals such as potassium, calcium, magnesium, iron, and zinc, although in moderate concentrations. In summary, Syzygium paniculatum Gaertn fruit demonstrates considerable potential as a source of natural antioxidants and bioactive compounds. These findings advocate for greater exploration and sustainable use of this native berry species in functional food systems.
Full article
Supplier selection is a crucial factor for ensuring compliance with the circular economy’s principles. Existing approaches often overlook the integration of circularity and risk assessment in supplier evaluation, limiting their effectiveness in achieving sustainability goals. This paper addresses this gap by applying suitable
[...] Read more.
Supplier selection is a crucial factor for ensuring compliance with the circular economy’s principles. Existing approaches often overlook the integration of circularity and risk assessment in supplier evaluation, limiting their effectiveness in achieving sustainability goals. This paper addresses this gap by applying suitable criteria and proposing a structured decision-making model for circular supplier selection. The model innovatively integrates Multi-Criteria Decision Analysis (MCDA) techniques with risk evaluation, providing a comprehensive framework for assessing suppliers in circular supply chains. By advancing the theoretical understanding of circular supplier selection, this research contributes to both academia and practice, reinforcing the alignment between supply chain decision-making and the Sustainable Development Goal (SDG), particularly Target 12.5.
Full article
To address the challenge of dispatching emergency resources for community residents under extreme ice disaster, this paper proposes an emergency resource dispatch strategy based on pre-disaster prediction and dynamic scheduling. First, the fast Newman algorithm is employed to cluster communities, optimizing the preprocessing
[...] Read more.
To address the challenge of dispatching emergency resources for community residents under extreme ice disaster, this paper proposes an emergency resource dispatch strategy based on pre-disaster prediction and dynamic scheduling. First, the fast Newman algorithm is employed to cluster communities, optimizing the preprocessing of resource scheduling and reducing scheduling costs. Subsequently, mobile energy storage vehicles and mobile water storage vehicles are introduced based on the ice disaster trajectory prediction to enhance the efficiency and accuracy of post-disaster resource supply. A grouped scheduling strategy is adopted to reduce cross-regional resource flow, and the dispatch routes of mobile energy storage and water vehicles are dynamically adjusted based on real-time traffic network conditions. Simulations on the IEEE-33 node system validate the feasibility and advantages of the proposed strategies. The results demonstrate that the grouped dispatch and scheduling strategies increase user satisfaction by 24.73%, average state of charge (SOC) by 30.23%, and water storage by 31.88% compared to global scheduling. These improvements significantly reduce the cost of community energy self-sustainability, enhance the satisfaction of community residents, and ensure system stability across various disaster scenarios.
Full article
Temperature monitoring in extreme environments, such as coal-fired power plants, was addressed by designing and testing wireless patch antennas for use in machine learning-aided temperature estimation. The sensors were designed to monitor the temperature and health of boiler systems. Wireless interrogation of the
[...] Read more.
Temperature monitoring in extreme environments, such as coal-fired power plants, was addressed by designing and testing wireless patch antennas for use in machine learning-aided temperature estimation. The sensors were designed to monitor the temperature and health of boiler systems. Wireless interrogation of the sensor was performed using a Vector Network Analyzer (VNA) and a pair of interrogation antennas to capture resonance behavior under varying thermal and spatial conditions with sensitivities ranging from 0.052 to 0.20 . Sensor calibration was conducted using a Long Short-Term Memory (LSTM) model, which leveraged temporal patterns to account for hysteresis effects. The calibration method demonstrated improved performance when combined with an LSTM model, achieving up to a 76% improvement in temperature estimation error when compared with Linear Regression (LR). The experiments highlighted an innovative solution for patch antenna-based non-contact temperature measurement, which addresses limitations with conventional methods such as RFID-based systems, infrared, and thermocouples.
Full article
The process of designing reinforced concrete (RC) buildings has traditionally relied on manually evaluating a limited number of layout alternatives—a time-intensive process that may not always yield the most functionally efficient solution. This research introduces a parametric algorithmic model for the automated optimization
[...] Read more.
The process of designing reinforced concrete (RC) buildings has traditionally relied on manually evaluating a limited number of layout alternatives—a time-intensive process that may not always yield the most functionally efficient solution. This research introduces a parametric algorithmic model for the automated optimization of RC buildings with solid slab systems. The model automates and optimizes the layout process, yielding measurable improvements in spatial efficiency while maintaining compliance with structural performance criteria. Unlike prior models that address structural or architectural parameters separately, the proposed framework integrates both domains through a unified generative design approach within a BIM environment, enabling automated evaluation of structurally viable and architecturally coherent slab layouts. Developed within the parametric visual programming environment in Dynamo for Revit, the model employs a generative design (GD) engine to explore and refine various design alternatives while adhering to structural constraints. By leveraging a BIM-based framework, this method enhances efficiency, optimizes resource utilization, and systematically balances structural and architectural requirements. The model was validated through three case studies, demonstrating cost reductions between 2.7% and 17%, with material savings of up to 13.38% in concrete and 20.87% in reinforcement, achieved within computational times ranging from 120 to 930 s. Despite the current development being limited to vertical load scenarios and being most suitable for regular slab-based configurations, the results demonstrated the model’s effectiveness in optimizing grid dimensions and reducing material quantities and costs, and highlighted its ability to streamline early-stage design processes.
Full article
Background: The development of antimicrobial resistance is a major public health issue, in which dentists play a significant role by prescribing 7–11% of worldwide antibiotics. The aim of this study is to evaluate the self-perception and knowledge of antibiotic therapy in fifth-year
[...] Read more.
Background: The development of antimicrobial resistance is a major public health issue, in which dentists play a significant role by prescribing 7–11% of worldwide antibiotics. The aim of this study is to evaluate the self-perception and knowledge of antibiotic therapy in fifth-year undergraduate dental students. Methods: This is a cross-sectional observational study based on the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines. An electronic survey consisting of 18 questions was conducted with fifth-year students enrolled in the 2022/23 and 2023/24 academic years. The data were analyzed using descriptive and inferential statistical methods. Results: A total of 139 students (76.4%) completed the questionnaire. A total of 71.9% of students considered that they had received adequate education in antibiotic therapy, particularly in Oral Surgery (89.2%) and Periodontics (86.3%). The theoretical classes (3.50 ± 0.98) and practical sessions (3.18 ± 1.29) provided the knowledge that had the greatest influence on their education. They showed high self-confidence in diagnosing an infection (3.49 ± 0.73) and in choosing the appropriate antibiotic and dosage (3.26 ± 0.73). Over 76% of students answered correctly regarding the need for antibiotic prescriptions in various practical scenarios, except in the replantation of avulsed permanent teeth (54%). Conclusions: Dental students’ knowledge of antibiotics should be reinforced, as a high percentage answered correctly regarding the indications for antibiotics in pulpal and periapical diseases, but students performed less well regarding the choice of antibiotic and dosage in patients without sensitivity to β-lactams.
Full article
This study applied the Stimulus–Organism–Response Theory to investigate the impact of sustainable destination management on perceived luxury service quality, taking into account the mediating role of perceived environmental responsibility and the moderating effect of tourist environmental awareness. Data were obtained from 541 tourists
[...] Read more.
This study applied the Stimulus–Organism–Response Theory to investigate the impact of sustainable destination management on perceived luxury service quality, taking into account the mediating role of perceived environmental responsibility and the moderating effect of tourist environmental awareness. Data were obtained from 541 tourists in Northern Cyprus, and the analysis was conducted using Herman’s single-factor test in SPSS version 23 and partial least squares structural equation modeling in SmartPLS version 4.1.1.2. The study’s results revealed a significant positive influence of sustainable destination management on both perceived luxury service quality and environmental responsibility. Furthermore, the study showed a significant positive relationship between perceived environmental responsibility and perceived luxury service quality. Additionally, tourist environmental consciousness was found to be an important influencing factor in perceived luxury service quality. The mediating role of perceived environmental responsibility was revealed to be a significant partial mediator between sustainable destination management and perceived luxury service quality pathways. Although environmental awareness revealed an insignificant moderating influence on the relationship between sustainable destination management and perceived luxury service quality, it indicated a negative significant moderating influence on the relationship between perceived environmental responsibility and perceived luxury service quality. The study highlights how assessments of luxury services are contingent upon perceived environmental responsibility through sustainable destination activities. Emphasizing both academic and management perspectives, it encourages future research to explore broader psychological and contextual factors. Therefore, it underscores the strategic necessity of sustainability in enhancing the luxury tourism experience.
Full article
Background: Temporomandibular disorders (TMD) are common musculoskeletal conditions affecting the temporomandibular joints, masticatory muscles, and associated structures. Their etiology is complex and multifactorial, involving anatomical, behavioral, and psychosocial contributors. Parafunctional habits such as clenching, grinding, and abnormal jaw positioning have been proposed as
[...] Read more.
Background: Temporomandibular disorders (TMD) are common musculoskeletal conditions affecting the temporomandibular joints, masticatory muscles, and associated structures. Their etiology is complex and multifactorial, involving anatomical, behavioral, and psychosocial contributors. Parafunctional habits such as clenching, grinding, and abnormal jaw positioning have been proposed as contributing factors, yet their individual and cumulative contributions remain unclear. This exploratory cross-sectional study aimed to evaluate the prevalence and severity of parafunctional habits and their association with TMD in medical students—a group exposed to elevated stress levels. Subjects were examined in Krakow, Poland, using the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) protocol. Methods: Participants completed a 21-item Oral Behavior Checklist (OBC) assessing the frequency of oral behaviors on a 0–4 scale. A self-reported total parafunction load was calculated by summing individual item scores (range: 0–84). Logistic regression was used to evaluate associations between individual and total parafunction severity scores and TMD presence. Results: The study included 66 individuals aged 19–30. TMD was diagnosed in 55 participants (83.3%). The most commonly reported habits were resting the chin on the hand (90.9%) and sleeping in a jaw-compressing position (86.4%). Notably, jaw tension (OR = 14.5; p = 0.002) and daytime clenching (OR = 4.7; p = 0.027) showed significant associations with TMD in the tested population. Each additional point in the total parafunction score increased TMD odds by 13.6% (p = 0.004). Conclusions: These findings suggest that parafunctional behaviors—especially those involving chronic muscle tension or abnormal mandibular positioning—may meaningfully contribute to the risk of TMD in high-stress student populations. Moreover, the cumulative burden of multiple low-intensity habits was also significantly associated with increased TMD risk. Early screening for these behaviors may support prevention strategies, particularly among young adults exposed to elevated levels of stress.
Full article