Understanding the modification mechanism of C₉ petroleum resin (C₉PR) on styrene–butadiene–styrene (SBS) polymer modified asphalt properties is of significant importance. In this paper, dynamic shear rheometer (DSR), storage stability, fluorescence morphology (FM), scanning electron microscope (SEM), Fourier transform-infrared (FTIR) spectrometer, and molecular dynamic (MD) simulation were adopted to evaluate the rheological, chemical, and microstructure molecular motion state of C₉PR and SBS composite modified asphalt at different aging states. The DSR storage results indicate that the addition of C₉PR could improve the high-temperature property, storage stability, and temperature susceptibility. FM and SEM results indicate that the network microstructure was enhanced and the roughness between polymer resins and virgin asphalt was improved at the microscopic scale. The MD results indicate that the heterogeneity between C₉PR and SBS modified asphalt was demonstrated, and the bonding energies were enhanced with the addition of C₉PR. Moreover, the FTIR results indicate that new function groups were generated in addition to C₉PR. In general, the addition of C₉PR is a good approach to promote high-quality polymer modified asphalt (PMA) for pavement engineering. Full article

To strengthen major transportation infrastructure projects’ (MTIPs’) organizational resilience and fortify their capacity for crisis management and project risk prevention. In this paper, based on the resilience theory development process, the connotation of organizational resilience of MTIPs is defined, and 20 influencing factors of organizational resilience of MTIPs are extracted from four categories of stability, redundancy, adaptability, and rapidity according to the literature analysis and case study method. The significance, causality, and multilevel recursive order structure of the influencing factors were investigated by the fuzzy DEMATEL-ISM approach, and their driving and dependent characteristics were analyzed through MICMAC. The results indicate that risk warning and prediction, human resources management, inter-organizational synergies, resource reserve situations, organizational leadership, and organizational learning are the crucial factors of organizational resilience in MTIPs. There are three levels and five ranks in the multilevel recursive rank structure of the factors affecting MTIPs’ organizational resilience. Among them, risk warning and prediction, equipment condition and performance, human resources management, and organizational leadership have the deepest impact on organizational resilience in MTIPs. The findings can clarify ideas for subsequent research on organizational resilience in this area and inform project decision-makers in developing strategies for optimizing organizational resilience. Full article

Due to huge investments by both the public and private sectors, artificial intelligence (AI) has made tremendous progress in solving multiple real-world problems such as disease diagnosis, chatbot misbehavior, and crime control. However, the large-scale development and widespread adoption of AI have been hindered by the model-centric mindset that only focuses on improving the code/architecture of AI models (e.g., tweaking the network architecture, shrinking model size, tuning hyper-parameters, etc.). Generally, AI encompasses a model (or code) that solves a given problem by extracting salient features from underlying data. However, when the AI model yields a low performance, developers iteratively improve the code/algorithm without paying due attention to other aspects such as data. This model-centric AI (MC-AI) approach is limited to only those few businesses/applications (language models, text analysis, etc.) where big data readily exists, and it cannot offer a feasible solution when good data are not available. However, in many real-world cases, giant datasets either do not exist or cannot be curated. Therefore, the AI community is searching for appropriate solutions to compensate for the lack of giant datasets without compromising model performance. In this context, we need a data-centric AI (DC-AI) approach in order to solve the problems faced by the conventional MC-AI approach, and to enhance the applicability of AI technology to domains where data are limited. From this perspective, we analyze and compare MC-AI and DC-AI, and highlight their working mechanisms. Then, we describe the crucial problems (social, performance, drift, affordance, etc.) of the conventional MC-AI approach, and identify opportunities to solve those crucial problems with DC-AI. We also provide details concerning the development of the DC-AI approach, and discuss many techniques that are vital in bringing DC-AI from theory to practice. Finally, we highlight enabling technologies that can contribute to realizing DC-AI, and discuss various noteworthy use cases where DC-AI is more suitable than MC-AI. Through this analysis, we intend to open up a new direction in AI technology to solve global problems (e.g., climate change, supply chain disruption) that are threatening human well-being around the globe. Full article

The growing importance of environmental efficiency in reducing carbon emissions has prompted scientists around the world to intensify their efforts to prevent the destructive effects of a changing climate and a warming planet. Global carbon emissions rose by more than 40% in 2021, leading to significant variations in the planet’s weather patterns. Nevertheless, a significant proportion of natural resources continue to be exploited. To prepare for this challenge, it is essential to implement a sustainable approach in the construction industry. Biobased materials are made primarily from renewable raw materials like hemp, straw, miscanthus, and jute. These new materials provide excellent thermal and acoustic performance and make optimum use of local natural resources such as agricultural waste. Nowadays, cement is one of the most important construction materials. In an attempt to meet this exciting challenge, biobased materials with low-carbon binders are one of the proposed solutions to create a more insulating and less polluting material. The aim of this review is to investigate and to analyze the impact of the incorporation of different types of biobased materials on the mechanical, thermal, and hygric performance of a mix using different types of binder. Full article

Renewable energy resources are playing a crucial role in minimizing fossil fuel emissions. Integrating machine learning techniques with tidal power forecasting could greatly enhance the accuracy and reliability of predictions, which is crucial for efficient energy production and management. A hybrid approach combining different methods often yields better results than relying on individual techniques. The accuracy of tidal current power is very important, especially for smart grid applications. This work proposes hybrid adaptive neuro-fuzzy inference system (ANFIS) with the Kalman filter (KF) and a neuro-wavelet (WNN) for tidal current speed, direction, and power forecasting. The turbine used in this study is driven by a direct drive permanent magnet synchronous generator (DDPMSG). The predictions of individual and hybrid models including the ANFIS, the Kalman filter, and the WNN for tidal current speed and the power it generates are compared with another dataset as a way of validation which is the tidal currents direction. Also, other published work results in the literature are compared to the proposed work. Different hybrid models are proposed for smart grid integration. The results of this work indicate that the hybrid model of the WNN and the ANFIS for tidal current power or speed forecasting has the highest performance compared to all other models. Full article

Robotic manipulators are critical for industrial automation, boosting productivity, quality, and safety in various production applications. Key factors like the payload, speed, accuracy, and reach define robot performance. Optimizing these factors is crucial for future robot applications across diverse fields. While 6-Degrees-of-Freedom (DoF)-articulated robots are popular due to their diverse applications, this research proposes a novel 5-DoF robot design for industrial automation, featuring a combination of three prismatic and two revolute (2R) joints, and analyzes its workspace. The proposed techno-economically efficient design offers control over the robot manipulator to achieve any reachable position and orientation within its workspace, replacing traditional 6-DoF robots. The kinematic model integrates both parallel and serial manipulator principles, combining a Cartesian mechanism with rotational mechanisms. Simulations demonstrate the end effector’s flexibility for tasks like welding, additive manufacturing, and material inspections, achieving the desired position and orientation. The research encompasses the design of linear and rotational actuators, kinematic modeling, Human–Machine Interface (HMI) development, and welding application integration. The developed robot demonstrates a superior performance and user-friendliness in welding. The experimental work validates the design’s optimized joint trajectories, efficient power usage, singularity avoidance, easy access in application areas, and reduced costs due to fewer actuators. Full article

The aim of the present research was to determine if the developed ovo−vegetarian sausage (SO), which was made with 15% chickpea flour, 51% albumin and 34% soy protein concentrate, exhibited improved physicochemical and sensory characteristics compared to vegetarian sausages available on the local market (classic vegan sausage, SC; vegan fine herb sausage, SH; and quinoa sausage, SQ). According to the physicochemical results, the developed sample, SO, presented significant differences (p < 0.05) compared to the others, including higher protein content, lower pH and a higher a* value. Three types of sensory analyses were conducted—flash profile, overall liking and purchase intention (to determine consumers’ willingness to purchase the product)—with the first involving 15 consumers and the second and third involving 60 participants each. Descriptors for each sample were determined using the vocabulary provided by consumers in the flash profile analysis. Descriptors for SO included ‘elastic’, ‘smell of cooked corn’, ‘characteristic flavor’, ‘pasty’, ‘soft’ and ‘pastel color’, contributing to its greater overall liking and purchase intention compared to the others. Through the hierarchical multiple factor analysis, a positive correlation was observed between the texture and sensory descriptors of the flash profile. Conversely, a correlation was found between the physicochemical characteristics (pH, a_w, color) and overall liking and purchase intention. Full article

Making plant breeding programs less expensive, fast, practical, and accurate, especially for soybeans, promotes the selection of new soybean genotypes and contributes to the emergence of new varieties that are more efficient in absorbing and metabolizing nutrients. Using spectral information from soybean genotypes combined with nutritional information on secondary macronutrients can help genetic improvement programs select populations that are efficient in absorbing and metabolizing these nutrients. In addition, using machine learning algorithms to process this information makes the acquisition of superior genotypes more accurate. Therefore, the objective of the work was to verify the classification performance of soybean genotypes regarding secondary macronutrients by ML algorithms and different inputs. The experiment was conducted in the experimental area of the Federal University of Mato Grosso do Sul, municipality of Chapadão do Sul, Brazil. Soybean was sown in the 2019/20 crop season, with the planting of 103 F2 soybean populations. The experimental design used was randomized blocks, with two replications. At 60 days after crop emergence (DAE), spectral images were collected with a Sensifly eBee RTK fixed-wing remotely piloted aircraft (RPA), with autonomous takeoff control, flight plan, and landing. At the reproductive stage (R1), three leaves were collected per plant to determine the macronutrients calcium (Ca), magnesium (Mg), and sulfur (S) levels. The data obtained from the spectral information and the nutritional values of the genotypes in relation to Ca, Mg, and S were subjected to a Pearson correlation analysis; a PC analysis was carried out with a k-means algorithm to divide the genotypes into clusters. The clusters were taken as output variables, while the spectral data were used as input variables for the classification models in the machine learning analyses. The configurations tested in the models were spectral bands (SBs), vegetation indices (VIs), and a combination of both. The combination of machine learning algorithms with spectral data can provide important biological information about soybean plants. The classification of soybean genotypes according to calcium, magnesium, and sulfur content can maximize time, effort, and labor in field evaluations in genetic improvement programs. Therefore, the use of spectral bands as input data in random forest algorithms makes the process of classifying soybean genotypes in terms of secondary macronutrients efficient and important for researchers in the field. Full article

Saffron (Crocus sativus) floral by-products are a source of phenolic compounds that can be recovered and used in the nutraceutical, pharmaceutical, or cosmetic industries. This study aimed to evaluate the phenolic compounds’ extraction using green extraction techniques (GETs) in saffron floral by-products and to explore the influence of selected extraction techniques on the phytochemical composition of the extracts. Specifically, ultrasound-assisted extraction (UAE), subcritical water extraction (SWE), and deep eutectic solvents extraction (DESE) were used. Phenolic compounds were identified with (HR) LC-ESI-QTOF MS/MS analysis, and the quantitative analysis was performed with HPLC-PDA. Concerning the extraction techniques, UAE showed the highest amount for both anthocyanins and flavonoids with 50:50% v/v ethanol/water as solvent (93.43 ± 4.67 mg/g of dry plant, dp). Among SWE, extraction with 96% ethanol and t = 125 °C gave the best quantitative results. The 16 different solvent mixtures used for the DESE showed the highest amount of flavonoids (110.95 ± 5.55–73.25 ± 3.66 mg/g dp), while anthocyanins were better extracted with choline chloride:butane-1,4-diol (16.0 ± 0.80 mg/g dp). Consequently, GETs can be employed to extract the bioactive compounds from saffron floral by-products, implementing recycling and reduction of waste and fitting into the broader circular economy discussion. Full article

This research explores the utilization of powder fused filament fabrication (PFFF) for producing tungsten carbide-cobalt (WC-10Co) hardmetals, focusing on binder formulations and their impact on extrusion force as well as the influence of printing variables on the green and sintered density of samples. By examining the interplay between various binder compositions and backbone contents, this study aims to enhance the mechanical properties of the sintered parts while reducing defects inherent in the printing process. Evidence suggests that formulated feedstocks affect the hardness of the sintered hardmetal—not due to microstructural changes but macrostructural responses such as macro defects introduced during printing, debinding, and sintering of samples. The results demonstrate the critical role of polypropylene grafted with maleic anhydride (PP-MA) content in improving part density and sintered hardness, indicating the need for tailored thermal debinding protocols tailored to each feedstock. This study provides insights into feedstock formulation for hardmetal PFFF, proposing a path toward refining manufacturing processes to achieve better quality and performance of 3D printed hardmetal components. Full article

The effects of exposure to airborne particulate matter with a size of 10 μm or less (PM₁₀) on C57BL/6 mouse corneas, their response to Pseudomonas aeruginosa (PA) infection, and the protective effects of SKQ1 were determined. C57BL/6 mouse corneas receiving PBS or SKQ1 were exposed to control (air) or PM₁₀ for 2 weeks, infected, and the disease was documented by clinical score, PMN quantitation, bacterial plate count, RT-PCR and Western blot. PBS-treated, PM₁₀-exposed corneas did not differ at 1 day postinfection (dpi), but exhibited earlier (3 dpi) corneal thinning compared to controls. By 3 dpi, PM₁₀ significantly increased corneal mRNA levels of several pro-inflammatory cytokines, but decreased IL-10, NQO1, GR1, GPX4, and Nrf2 over control. SKQ1 reversed these effects and Western blot selectively confirmed the RT-PCR results. PM₁₀ resulted in higher viable bacterial plate counts at 1 and 3 dpi, but SKQ1 reduced them at 3 dpi. PM₁₀ significantly increased MPO in the cornea at 3 dpi and was reduced by SKQ1. SKQ1, used as an adjunctive treatment to moxifloxacin, was not significantly different from moxifloxacin alone. Exposure to PM₁₀ increased the susceptibility of C57BL/6 to PA infection; SKQ1 significantly reversed these effects, but was not effective as an adjunctive treatment. Full article

This paper explores the economic trends and identifies speculative bubbles within the emerging metaverse, based on the specific example of Decentraland, which is represented by its underlying native token MANA.For comparability, we consider three further tokens: SAND, ETH, and BTC.The study shows price prediction and provides further insight into bubble behavior to provide a deeper insight into the real trend and situation of the metaverse. When comparing all considered tokens, evidence of comovement and positive as well as negative bubbles is identified. This paper makes use of proven modeling techniques, such as SARIMA, for price prediction and LPPLS for financial bubble identification, visualization, and time stamping. Full article

Evaluating the access to and quality of healthcare services from the users’ perspective is an important assessment process to identify priorities. This study assessed the profile of health service usage and the views of the Unified Health System (SUS) users about the access to and quality of SUS public health services. A cross-sectional study was conducted with participants from the Coastal Lowlands Region of the Rio de Janeiro State/Brazil, between August and November 2023. The association between categorical variables was analyzed using the Pearson Chi-Square test, using R software 4.3. A total of 200 individuals were interviewed using a 66-question survey instrument. Participants who reported using SUS services more frequently rated this system as essential (p-value = 0.031). However, overall, 64% of participants rated the quality of care to be very bad/bad and 34.9% rated access as very bad/bad. Access was considered poor by respondents who used public services rarely or sometimes (p-value = 0.002). In terms of accessing SUS services consultations provided by specialists (e.g., neurologists), these were available only in another municipality (p-value = 0.001). Many participants were SUS dependent for health services, and gaps and weaknesses were observed regarding users’ perspectives of the access to and quality of SUS health care. Policymakers should prioritize evaluations and dialogue with the community to make SUS services responsive and to optimize value-for-money in health service planning. Full article

The Sustainable Development Goals (SDG) include sustainable cities and communities. The availability of housing for young people is a contemporary global problem, and the severity of housing problems for young people in many countries is widely discussed and raises important policy questions. Generation Z, described as digital, critical, adventurous, open-minded and, above all, mobile people, is now entering adulthood. The study attempted to identify the housing preferences of young people to determine whether they prefer renting a flat or owning one. Although generation Z differs from older generations in many respects, their perception of the housing issue does not differ significantly from the attitudes presented by older generations. The dominant model of the housing system in Poland, the non-commodified-familial model, which prefers ownership over renting, is also shared by the youngest generation. Hence, the conclusion addressed to the public authorities and the financing system is to enable the expansion of the credit offer supported by a long-term savings plan aimed at young people. Renting as an alternative way of securing housing needs is also perceived positively, with nearly 80% of respondents stating that they would be able to live in rented accommodation, mainly due to greater mobility, rising property prices and reluctance to take out a long-term loan. Hence, we suggest the need to support institutional renting along the lines of other countries with similar housing systems. Full article

Abstract: Reactive powder concrete (RPC) is a new generation concrete with high strength, used in special structures, and its use is increasing day by day. In this study, instead of using high-strength aggregates typically used in RPC, wastes released in ferrochrome production were used. In addition, the possibility of using fibers obtained from end-of-life automobile tires (ELT), instead of the micro steel fibers typically used in RPC, was investigated. Thus, sustainable green reactive powder concrete (GRPC), the material which is obtained from waste materials except the binder and chemical additive, has been developed. As ferrochrome wastes, olivine, serpentine, rum, slag, and pure waste were used as powder and aggregate in GRPC. Firstly, in GRPC without fiber, the physical and mechanical properties of ferrochrome wastes were examined by using different ratios. Then, the optimum mixture was selected, and different ratios of industrial steel and ELT fiber were added to this mixture. As a result, the compressive strength of GRPC using olivine and pure waste (ferrochrome slag) is close to the reference RPC. However, it is 28% more economical. The flexural strength of the samples with a 4% addition of industrial or ELT fiber increased by 182% and 213%, respectively, compared to the reference sample without fiber. With the use of 4% ELT fiber (by volume) in GRPC, the flexural strength increased by 11% compared to the use of industrial steel fiber. In terms of cost, with the use of ferrochrome waste and ELT fiber, GRPC was 48% more economical. When examined in terms of the flexural and compressive unit strength cost, GRPC was approximately 41% more economical. As a result of this study, high-performance concrete with high mechanical properties that is economical, sustainable, and environmentally friendly has been produced by evaluating the use of waste materials. Full article

Based on a sample of 8271 mothers, this study explored a set of psychological and sociodemographic factors associated with their vocabulary, drawing on data from a large, nationally representative sample of children born in 2000. The dependent variable was maternal vocabulary assessed when cohort members were at fourteen years of age, and the mothers were in their mid-forties. Data were also collected when cohort members were at birth, 9 months old, and at ages 3 and 7 years. Correlational analysis showed that family income at birth, parent–child relationship quality at age 3, maternal educational qualifications at age 11, and maternal personality trait Openness at age 14 were significantly and positively associated with maternal vocabulary. It also showed maternal malaise at 9 months and children’s behavioral adjustment at age 7, and maternal traits Neuroticism and Agreeableness at age 14 were significantly and negatively associated with maternal vocabulary. Maternal age was also significantly and positively associated with vocabulary. Regression analysis showed that maternal age, malaise, parent–child relationship quality, children’s behavioral adjustment, maternal educational qualifications, and traits Openness and Agreeableness were significant predictors of maternal vocabulary, accounting for 33% of total variance. The implications and limitations are discussed. Full article

Myocardial fibrosis is an important factor in the progression of cardiovascular diseases. However, there is still no universal lifetime method of myocardial fibrosis assessment that has a high prognostic significance. The aim of the study was to determine the significance of ventricular endomyocardial biopsies for the assessment of myocardial fibrosis and to identify the severity of myocardial fibrosis in different cardiovascular diseases. Material and Methods: Endomyocardial biopsies (EMBs) of 20 patients with chronic lymphocytic myocarditis (CM), endomyocardial fragments obtained during septal reduction of 21 patients with hypertrophic cardiomyopathy (HCM), and 36 patients with a long history of hypertensive and ischemic heart disease (HHD + IHD) were included in the study. The control group was formed from EMBs taken on 12–14 days after heart transplantation (n = 28). Also, for one patient without clinical and morphological data for cardiovascular pathology, postmortem myocardial fragments were taken from typical EMB and septal reduction sites. The relative area of fibrosis was calculated as the ratio of the total area of collagen fibers to the area of the whole biopsy. Endocardium and subendocardial fibrosis were not included in the total biopsy area. Results: The relative fibrosis area in the EMBs in the CM patient group was 5.6 [3.3; 12.6]%, 11.1 [6.6; 15.9]% in the HHD + IHD patient group, 13.4 [8.8; 16.7]% in the HCM patient group, and 2.7 [1.5; 4.6]% in the control group. When comparing the fibrosis area of the CM patients in repeat EMBs, it was found that the fibrosis area in the first EMBs was 7.6 [4.8; 12.0]%, and in repeat EMBs, it was 5.3 [3.2; 7.6]%. No statistically significant differences were found between the primary and repeat EMBs (p = 0.15). In ROC analysis, the area of fibrosis in the myocardium of 1.1% (or lower than one) was found to be highly specific for the control group of patients compared to the study patients. Conclusion: EMB in the assessment of myocardial fibrosis has a questionable role because of the heterogeneity of fibrotic changes in the myocardium after having COVID-19. Full article

The aim of this study was to investigate the interferon tau (IFNt) concentration in the peripheral maternal blood during the early phase of pregnancy in buffalo cows and improve the knowledge on the physiological importance of circulating IFNt, evaluating the possible interaction with pregnancy-associated glycoproteins (PAGs) and progesterone (P4). Blood samples were taken from buffalo cows on day 0 (day of AI), 7, 14, 18, 28, and 40 post insemination for the IFNt, PAG, and P4 analysis and to determine the IFNt mRNA expression. The animals were categorized ex post into Pregnant, Non-pregnant and Embryo mortality groups. The interferon value was influenced by group (p = 0.003), being always higher in pregnant buffalo cows than in non-pregnant ones, while the embryo mortality group showed intermediate values between those for pregnant and non-pregnant animals. The mRNA expression of IFNt was not influenced by groups or any time points. The regression analysis that included IFNt as the independent variable showed that PAGs, from day 18 (p < 0.01), and P4, from day 28 (p < 0.05), were positively associated with IFNt values. The close associations among IFNt, PAGs and P4 demonstrate that all three molecules work together for fetal–placental well-being and pregnancy support. Unfortunately, the great individual variability in circulating IFNt makes this analysis unsuitable for early pregnancy diagnosis. Full article

Objectives: In recent years, minimally invasive approaches have been used with increasing frequency, even for more complex aortic procedures. However, evidence on the practicability and safety of expanding minimally invasive techniques from isolated operations of the ascending aorta towards more complex operations such as the hemiarch replacement is still scarce to date. Methods: A total of 86 patients undergoing elective surgical replacement of the ascending aorta with (n = 40) or without (n = 46) concomitant proximal aortic arch replacement between 2009 and 2023 were analyzed in a retrospective single-center analysis. Groups were compared regarding operation times, intra- and postoperative complications and long-term survival. Results: Operation times and ventilation times were significantly longer in the hemiarch replacement group. Despite this, no statistically significant differences between the two groups were observed for the duration of the ICU and hospital stay and postoperative complication rates. At ten-year follow-up, overall survival was 82.6% after isolated ascending aorta replacement and 86.3% after hemiarch replacement (p = 0.441). Conclusions: Expanding the indication for minimally invasive aortic surgery towards the proximal aortic arch resulted in comparable postoperative complication rates, length of hospital stay and overall long-term survival compared to the well-established minimally invasive isolated supracommissural ascending aorta replacement. Full article

Background/Objectives: Bariatric surgery candidates require presurgical physical training, therefore, we compared the metabolic effects of a constant moderate-intensity training program (MICT) vs. a high-intensity interval training (HIIT) in this population. Methods: Seventeen participants performed MICT (n = 9, intensity of 50% of heart rate reserve (HRR) and/or 4–5/10 subjective sensation of effort (SSE)) or HIIT (n = 8, 6 cycles of 2.5 min at 80% of the HRR and/or 7–8/10 of SSE, interspersed by 6 cycles of active rest at 20% of the FCR) for 10 sessions for 4 weeks. After training, tissue samples (skeletal muscle, adipose tissue, and liver) were extracted, and protein levels of adiponectin, GLUT4, PGC1α, phospho-AMPK/AMPK, collagen 1 and TGFβ1 were measured. Results: Participants who performed MICT showed higher protein levels of PGC-1α in skeletal muscle samples (1.1 ± 0.27 vs. 0.7 ± 0.4-fold change, p < 0.05). In the liver samples of the people who performed HIIT, lower protein levels of phospho-AMPK/AMPK (1.0 ± 0.37 vs. 0.52 ± 0.22-fold change), PGC-1α (1.0 ± 0.18 vs. 0.69 ± 0.15-fold change), and collagen 1 (1.0 ± 0.26 vs. 0.59 ± 0.28-fold change) were observed (all p < 0.05). In subcutaneous adipose tissue, higher adiponectin levels were found only after HIIT training (1.1 ± 0.48 vs. 1.9 ± 0.69-fold change, p < 0.05). Conclusions: Our results show that both MICT and HIIT confer metabolic benefits in candidates undergoing bariatric surgery; however, most of these benefits have a program-specific fashion. Future studies should aim to elucidate the mechanisms behind these differences. Full article

To improve the handling stability of distributed drive electric vehicles, this paper introduces an electronic differential control strategy based on the stability criterion of the phase plane method. The strategy first plots the distributed electric vehicle’s center of mass side angle and center of mass angular speed on the phase plane, and then it analyzes the vehicle’s stability under various working conditions to determine the parameters that ensure the stability performance. Subsequently, an adaptive fuzzy control strategy is employed to achieve fast and accurate distribution of the torque to each wheel, thereby enhancing the vehicle’s stability. A joint simulation platform is constructed using MATLAB/Simulink and CarSim. A comparison with the traditional electronic differential strategy demonstrates that the proposed distribution strategy based on phase plane stability exhibited excellent stability. Full article

The soldering process for aerospace applications follows stringent requirements and standards to ensure the reliability and safety of electronic connections in aerospace systems. For this reason, the quality control phase plays an important role to guarantee requirements compliance. This process often requires manual control since technicians’ knowledge is fundamental to obtain effective quality check results. In this context, the authors have developed a new open source dataset (SolDef_AI) to implement an innovative methodology for printed circuit board (PCB) defect detection exploiting the Mask R-CNN algorithm. The presented open source dataset aims to overcome the challenges associated with the availability of datasets for model training in this specific research and electronics industrial field. The dataset is open source and available online. Full article