In a recent study devoted to the influence of electromagnetic radiation reaction on the motion of radiating charged particles in magnetized black hole spacetimes the authors claim that the tail term cannot be neglected in the complete DeWitt–Brehme equation, putting into doubt the previous papers where such an approximation was used. Here, we demonstrate by using simple dimensional arguments that such a statement is misleading in many astrophysically relevant situations. In the case of relativistic electrons moving around a stellar-mass black hole, the tail term is ignorable if a magnetic field of at least a few Gauss is present.On the other hand, in different situations, the tail term can be relevant, as demonstrated in the case of orbital widening, where it can even amplify the effect. Full article

Clinical trials with single-agent venetoclax/ABT-199 (anti-apoptotic BCL2 inhibitor) revealed that diffuse large B-cell lymphoma (DLBCL) is not solely dependent on BCL2 for survival. Gaining insight into pathways/proteins that increase venetoclax sensitivity or unique vulnerabilities in venetoclax-resistant DLBCL would provide new potential treatment avenues. Therefore, we generated acquired venetoclax-resistant DLBCL cells and evaluated these together with intrinsically venetoclax-resistant and -sensitive DLBCL lines. We identified resistance mechanisms, including alterations in BCL2 family members that differed between intrinsic and acquired venetoclax resistance and increased dependencies on specific pathways. Although combination treatments with BCL2 family member inhibitors may overcome venetoclax resistance, RNA-sequencing and drug/compound screens revealed that venetoclax-resistant DLBCL cells, including those with TP53 mutation, had a preferential dependency on oxidative phosphorylation. Mitochondrial electron transport chain complex I inhibition induced venetoclax-resistant, but not venetoclax-sensitive, DLBCL cell death. Inhibition of IDH2 (mitochondrial redox regulator) synergistically overcame venetoclax resistance. Additionally, both acquired and intrinsic venetoclax-resistant DLBCL cells were similarly sensitive to inhibitors of transcription, B-cell receptor signaling, and class I histone deacetylases. These approaches were also effective in DLBCL, follicular, and marginal zone lymphoma patient samples. Our results reveal there are multiple ways to circumvent or overcome the diverse venetoclax resistance mechanisms in DLBCL and other B-cell lymphomas and identify critical targetable pathways for future clinical investigations. Full article

Background/Objectives: A highly porous titanium cup with a three-dimensional metal interface was recently introduced to improve biological fixation and survival. However, radiography has revealed concerns regarding these cups, despite their excellent short- and mid-term clinical outcomes. This study compared the clinical and radiographic results of a highly porous titanium cup with those of a hydroxyapatite-coated porous titanium cup after primary total hip arthroplasty (THA). Methods: Fifty-one primary THAs were investigated. A highly porous titanium cup was used in 17 hips, and a hydroxyapatite-coated porous titanium cup was used in 34 hips. No significant differences in preoperative patient demographic characteristics were observed between the two groups. The 2-year postoperative clinical and radiographic results were compared. Results: Radiolucent lines were observed in 13 (76%) of 17 hips with highly porous titanium cups and in none (0%) of 34 hips with hydroxyapatite-coated porous titanium cups (p < 0.001). In the highly porous titanium cup group, radiolucent lines were observed in five hips (29%) in one zone, two hips (11%) in two zones, and six hips (35%) in three zones. No cup loosening was observed in either group. Conclusions: Radiolucent lines were significantly more frequent in highly porous titanium cups. This study suggests that, compared to the three-dimensional structure of porous titanium, the hydroxyapatite coating of porous titanium had a greater influence on bone ingrowth in the short term. The meaning of these findings in the long-term is unclear yet. Full article

Artificial Intelligence (AI) is revolutionising many aspects of radiotherapy (RT), opening scenarios that were unimaginable just a few years ago. The aim of this study is to propose a Deep Leaning (DL) approach able to quickly generate synthetic Computed Tomography (CT) images from low-dose Cone Beam CT (CBCT) acquired on a modern linear accelerator integrating AI. Methods: A total of 53 patients treated in the pelvic region were enrolled and split into training (30), validation (9), and testing (14). A Generative Adversarial Network (GAN) was trained for 200 epochs. The image accuracy was evaluated by calculating the mean and mean absolute error (ME and ME) between sCT and CT. RT treatment plans were calculated on CT and sCT images, and dose accuracy was evaluated considering Dose Volume Histogram (DVH) and gamma analysis. Results: A total of 4507 images were selected for training. The MAE and ME values in the test set were 36 ± 6 HU and 7 ± 6 HU, respectively. Mean gamma passing rates for 1%/1 mm, 2%/2 mm, and 3%/3 mm tolerance criteria were respectively 93.5 ± 3.4%, 98.0 ± 1.3%, and 99.2 ± 0.7%, with no difference between curative and palliative cases. All the DVH parameters analysed were within 1 Gy of the difference between sCT and CT. Conclusion: This study demonstrated that sCT generation using the DL approach is feasible on low-dose CBCT images. The proposed approach can represent a valid tool to speed up the online adaptive procedure and remove CT simulation from the RT workflow. Full article

Atopic dermatitis (AD) is one of the most common chronic inflammatory skin diseases, with an increasing number of targeted therapies available. While biologics to treat AD exclusively target the key cytokines of type 2 immunity, Janus kinase inhibitors target a broad variety of cytokines, including IFN-γ. To better stratify patients for optimal treatment outcomes, the identification and characterization of subgroups, especially with regard to their IFNG expression, is of great relevance, as the role of IFNG in AD has not yet been fully clarified. This study aims to define AD subgroups based on their lesional IFNG expression and to characterize them based on their gene expression, T cell secretome and clinical attributes. RNA from the lesional and non-lesional biopsies of 48 AD patients was analyzed by RNA sequencing. Based on IFNG gene expression and the release of IFN-γ by lesional T cells, this cohort was categorized into three IFNG groups (high, medium, and low) using unsupervised clustering. The low IFNG group showed features of extrinsic AD with a higher prevalence of atopic comorbidities and impaired epidermal lipid synthesis. In contrast, patients in the high IFNG group had a higher average age and an activation of additional pro-inflammatory pathways. On the cellular level, higher amounts of M1 macrophages and natural killer cell signaling were detected in the high IFNG group compared to the low IFNG group by a deconvolution algorithm. However, both groups shared a common dupilumab response gene signature, indicating that type 2 immunity is the dominant immune shift in both subgroups. In summary, high and low IFNG subgroups correspond to intrinsic and extrinsic AD classifications and might be considered in the future for evaluating therapeutic efficacy or non-responders. Full article

The catalytic properties of three copper complexes, [Cu(en)₂](ClO₄)₂ (1), [Cu(amp)₂](ClO₄)₂, (2) and [Cu(bpy)₂](ClO₄)₂ (3) (where en = ethylenediamine, amp = 2-aminomethylpyridine and bpy = 2,2′-bipyridine), were explored upon the oxidation of benzyl alcohol (BnOH). Maximized conversions of the substrates to their respective products were obtained using a multivariate analysis approach, a powerful tool that allowed multiple variables to be optimized simultaneously, thus creating a more economical, fast and effective technique. Considering the studies in a fluid solution (homogeneous), all complexes strongly depended on the amount of the oxidizing agent (H₂O₂), followed by the catalyst load. In contrast, time seemed to be statistically less relevant for complexes 1 and 3 and not relevant for 2. All complexes showed high selectivity in their optimized conditions, and only benzaldehyde (BA) was obtained as a viable product. Quantitatively, the catalytic activity observed was 3 > 2 > 1, which is related to the π-acceptor character of the ligands employed in the study. Density functional theory (DFT) studies could corroborate this feature by correlating the geometric index for square pyramid Cu(II)-OOH species, which should be generated in the solution during the catalytic process. Complex 3 was successfully immobilized in silica-coated magnetic nanoparticles (Fe₃O₄@SiO₂), and its oxidative activity was evaluated through heterogenous catalysis assays. Substrate conversion promoted by 3-Fe₃O₄@SiO₂ generated only BA as a viable product, and the supported catalyst’s recyclability was proven. Reduced catalytic conversions in the presence of the radical scavenger (2,2,6,6-tetrametil-piperidi-1-nil)oxil (TEMPO) indicate that radical and non-radical mechanisms are involved. Full article

This research proposes a 10-step methodology for developing an enhanced IAQ dashboard and classroom index (CI) in higher educational facilities located in arid environments. The identified parameters of the enhanced IAQ dashboard–inspired by the pandemic experience, result from the literature review and the outcome of two electronic surveys of (52) respondents, including health professionals and facility management experts. On the other hand, the indicators included in the CI are based on (80) occupant survey responses, including parameters related to IAQ, Indoor Environmental Quality (IEQ), and thermal comfort, amongst other classroom operative considerations. The CI is further tested in four learning spaces at the American University in Cairo, Egypt. The main contribution of this research is to suggest a conceptual visualization of the dashboard and a practical classroom index that integrates a representative number of contextual indicators to recommend optimal IAQ scenarios for a given educational facility. This study concludes by highlighting several key findings: (1) both qualitative and quantitative metrics are necessary to capture indoor air quality-related parameters accurately; (2) tailoring the dashboard as well as the CI to specific contexts enhances its applicability across diverse locations; and finally, (3) the IAQ dashboard and CI offer flexibility for ad-hoc applications. Full article

Lipophilicity is one of the principal parameters that describe the pharmacokinetic behavior of a drug, including its absorption, distribution, metabolism, elimination, and toxicity. In this study, the lipophilicity and other physicochemical, pharmacokinetic, and toxicity properties that affect the bioavailability of newly synthesized dialkylaminoalkyldiquinothiazine hybrids as potential drug candidates are presented. The lipophilicity, as R_M0, was determined experimentally by the RP-TLC method using RP18 plates and acetone–TRIS buffer (pH 7.4) as the mobile phase. The chromatographic parameters of lipophilicity were compared to computationally calculated partition coefficients obtained by various types of programs such as iLOGP, XLOGP3, WLOGP, MLOGP, SILCOS-IT, LogP, logP, and milogP. In addition, the selected ADMET parameters were determined in silico using the SwissADME and pkCSM platforms and correlated with the experimental lipophilicity descriptors. The results of the lipophilicity study confirm that the applied algorithms can be useful for the rapid prediction of logP values during the first stage of study of the examined drug candidates. Of all the algorithms used, the biggest similarity to the chromatographic value (R_M0) for certain compounds was seen with iLogP. It was found that both the SwissADME and pkCSM web tools are good sources of a wide range of ADMET parameters that describe the pharmacokinetic profiles of the studied compounds and can be fast and low-cost tools in the evaluation of examined drug candidates during the early stages of the development process. Full article

The automatic segmentation of cardiac computed tomography (CT) and magnetic resonance imaging (MRI) plays a pivotal role in the prevention and treatment of cardiovascular diseases. In this study, we propose an efficient network based on the multi-scale, multi-head self-attention (MSMHSA) mechanism. The incorporation of this mechanism enables us to achieve larger receptive fields, facilitating the accurate segmentation of whole heart structures in both CT and MRI images. Within this network, features extracted from the shallow feature extraction network undergo a MHSA mechanism that closely aligns with human vision, resulting in the extraction of contextual semantic information more comprehensively and accurately. To improve the precision of cardiac substructure segmentation across varying sizes, our proposed method introduces three MHSA networks at distinct scales. This approach allows for fine-tuning the accuracy of micro-object segmentation by adapting the size of the segmented images. The efficacy of our method is rigorously validated on the Multi-Modality Whole Heart Segmentation (MM-WHS) Challenge 2017 dataset, demonstrating competitive results and the accurate segmentation of seven cardiac substructures in both cardiac CT and MRI images. Through comparative experiments with advanced transformer-based models, our study provides compelling evidence that despite the remarkable achievements of transformer-based models, the fusion of CNN models and self-attention remains a simple yet highly effective approach for dual-modality whole heart segmentation. Full article

Investigating dependence structures across various fields holds paramount importance. Consequently, the creation of new copula families plays a crucial role in developing more flexible stochastic models that address the limitations of traditional and sometimes impractical assumptions. The present article derives some reasonable conditions for validating a copula of the ratio-type form $uv/(1-\theta f(u\left)g\right(v\left)\right)$. It includes numerous examples and discusses the admissible range of parameter $\theta$, showcasing the diversity of copulas generated through this framework, such as Archimedean, non-Archimedean, positive dependent, and negative dependent copulas. The exploration extends to the upper bound of a general family of copulas, $uv/(1-\theta \varphi (u,v\left)\right)$, and important properties of the copula are discussed, including singularity, measures of association, tail dependence, and monotonicity. Furthermore, an extensive simulation study is presented, comparing the performance of three different estimators based on maximum likelihood, $\rho -$inversion, and the moment copula method. Full article

The Republic of Venice was one of the longest-lived states in modern history, and its stability and survival have been studied through many different angles. One of the main research angles is to try and find pivotal moments in its history that explain its eventual demise. In this paper, through the rigorous statistical analysis of a dataset of marriages by nobles in the Republic, we attempt to define a methodology for the detection of these events through mono and multivariate changepoint analysis, validating the proposed methodology through cross-validation of different procedures, as well as matching the results to historical events. Our analysis shows that these changepoints occur with statistical significance and that they match political and historical events. These results can be built upon for a better understanding of the historical causes of the success and failure of the Republic of Venice and, by extension, other states. Full article

Aiming at the shortcomings of single-sensor sensing information characterization ability, which is easily interfered with by external environmental factors, a method of intelligent perception is proposed in this paper. This method integrates multi-source and multi-level information, including spindle temperature field, spindle thermal deformation, operating parameters, and motor current. Firstly, the internal and external thermal-error-related signals of the spindle system are collected by sensors, and the feature parameters are extracted; then, the radial basis function (RBF) neural network is utilized to realize the preliminary integration of the feature parameters because of the advantages of the RBF neural network, which offers strong multi-dimensional solid nonlinear mapping ability and generalization ability. Thermal-error decision values are then generated by a weighted fusion of different pieces of evidence by considering uncertain information from multiple sources. The spindle thermal-error sensing experiment was based on the spindle system of the VMC850 (Yunnan Machine Tool Group Co., LTD, Yunnan, China) vertical machining center of the Yunnan Machine Tool Factory. Experiments were designed for thermal-error sensing of the spindle under constant speed (2000 r/min and 4000 r/min), standard variable speed, and stepped variable speed conditions. The experiment’s results show that the prediction accuracy of the intelligent-sensing model with multi-source information fusion can reach 98.1%, 99.3%, 98.6%, and 98.8% under the above working conditions, respectively. The intelligent-perception model proposed in this paper has higher accuracy and lower residual error than the traditional BP neural network perception and wavelet neural network models. The research in this paper provides a theoretical basis for the operation, maintenance management, and performance optimization of machine tool spindle systems. Full article

This study evaluates, for the first time, the effects of UV/PMS and UV/H₂O₂/PMS processes on the degradation of sunscreen agents in synthetic and natural water matrices and compares their effectiveness with the more conventional UV/H₂O₂. Investigations were conducted using a mixture of organic UV filters containing 4-methylbenzylidene camphor (4-MBC) and 2-ethylhexyl-4-methoxycinnamate. Among the investigated UV-driven AOPs, UV/PMS/H₂O₂ was the most effective in synthetic water, while in natural water, the highest degradation rate was observed during the degradation of EHMC by UV/PMS. The degradation of UV filters in the UV/PMS system was promoted by sulfate radical (68% of the degradation), with hydroxyl radical contributing approximately 32%, while both radical species contributed approximately equally to the degradation in the UV/H₂O₂/PMS system. The Vibrio fischeri assay showed an increase in inhibition (up to 70%) at specific stages of UV/H₂O₂ treatment when applied to natural water, which further decreased to 30%, along with an increase in UV fluence and progressive degradation. The Pseudomonas putida test recorded minor toxicity (<15%) after treatments. Magnetic biochar utilized in conjunction with UV-driven AOPs exhibited superior performance in eliminating residual contaminants, providing an efficient and sustainable approach to mitigate sunscreen agents in water treatment. Full article

Arthrospira platensis, commonly known as Spirulina, is a photosynthetic filamentous cyanobacterium (blue–green microalga) that has been utilized as a food source since ancient times. More recently, it has gained significant popularity as a dietary supplement due to its rich content of micro- and macro-nutrients. Of particular interest is a water soluble phycobiliprotein derived from Spirulina known as phycocyanin C (C-PC), which stands out as the most abundant protein in this cyanobacterium. C-PC is a fluorescent protein, with its chromophore represented by the tetrapyrrole molecule phycocyanobilin B (PCB-B). While C-PC is commonly employed in food for its coloring properties, it also serves as the molecular basis for numerous nutraceutical features associated with Spirulina. Indeed, the comprehensive C-PC, and to some extent, the isolated PCB-B, has been linked to various health-promoting effects. These benefits encompass conditions triggered by oxidative stress, inflammation, and other pathological conditions. The present review focuses on the bio-pharmacological properties of these molecules, positioning them as promising agents for potential new applications in the expanding nutraceutical market. Full article

The present study investigated the mediating effects of emotional intelligence and self-esteem between youth sports participation and life satisfaction, as well as the comparative effects of different types of sports involvement (team, individual, and non-participation) on these selected variables. A sample of 1053 Portuguese adolescents (612 girls and 441 boys), aged between 12 and 18 years (M = 14.40; SD = 1.55), completed the following self-report measures: the Wong and Law Emotional Intelligence Scale, the Rosenberg Self-Esteem Scale, and the Satisfaction with Life Scale. The structural equation modeling results indicated a complete mediating role of two emotional intelligence dimensions (use of emotion and self-emotional appraisal) and self-esteem in the relationship between sports participation and adolescents’ life satisfaction. Team sport participants reported higher emotional intelligence and self-esteem scores than their non-sport participant counterparts who revealed lower levels of emotion use than their individual sport participant peers. These findings provide novel insights into the potential emotional and psychological mechanisms underlying the association between youth sports participation and life satisfaction. Full article

This study introduces a novel framework, “Comprehensive Optimization and Refinement through Ensemble Fusion in Domain Adaptation for Person Re-identification (CORE-ReID)”, to address an Unsupervised Domain Adaptation (UDA) for Person Re-identification (ReID). The framework utilizes CycleGAN to generate diverse data that harmonize differences in image characteristics from different camera sources in the pre-training stage. In the fine-tuning stage, based on a pair of teacher–student networks, the framework integrates multi-view features for multi-level clustering to derive diverse pseudo-labels. A learnable Ensemble Fusion component that focuses on fine-grained local information within global features is introduced to enhance learning comprehensiveness and avoid ambiguity associated with multiple pseudo-labels. Experimental results on three common UDAs in Person ReID demonstrated significant performance gains over state-of-the-art approaches. Additional enhancements, such as Efficient Channel Attention Block and Bidirectional Mean Feature Normalization mitigate deviation effects and the adaptive fusion of global and local features using the ResNet-based model, further strengthening the framework. The proposed framework ensures clarity in fusion features, avoids ambiguity, and achieves high accuracy in terms of Mean Average Precision, Top-1, Top-5, and Top-10, positioning it as an advanced and effective solution for UDA in Person ReID. Full article

The etiology of the neurodegenerative disease amyotrophic lateral sclerosis (ALS) is complex and considered multifactorial. The majority of ALS cases are sporadic, but familial cases also exist. Estimates of heritability range from 8% to 61%, indicating that additional factors beyond genetics likely contribute to ALS. Numerous environmental factors are considered, which may add up and synergize throughout an individual’s lifetime building its unique exposome. One level of integration between genetic and environmental factors is epigenetics, which results in alterations in gene expression without modification of the genome sequence. Methylation reactions, targeting DNA or histones, represent a large proportion of epigenetic regulations and strongly depend on the availability of methyl donors provided by the ubiquitous one-carbon (1C) metabolism. Thus, understanding the interplay between exposome, 1C metabolism, and epigenetic modifications will likely contribute to elucidating the mechanisms underlying altered gene expression related to ALS and to developing targeted therapeutic interventions. Here, we review evidence for 1C metabolism alterations and epigenetic methylation dysregulations in ALS, with a focus on the impairments reported in neural tissues, and discuss these environmentally driven mechanisms as the consequences of cumulative exposome or late environmental hits, but also as the possible result of early developmental defects. Full article

Flax (Linum usitatissimum L.), as the earliest oil and fiber crop, is a model plant for genetic inferences of plant domestication processes involving multiple domestication events. However, a puzzle has emerged from several genetic studies, as dehiscent cultivated flax is genetically more related to its progenitor pale flax (L. bienne Mill.), and winter cultivated flax is well mixed with oil or fiber cultivated flax, while capsular dehiscence and winter hardiness are the major characteristics of pale flax. For this, a comparative analysis was conducted with 16 Linum samples representing pale flax and four domestication groups of cultivated flax (oil, fiber, winter, and dehiscent) using 454 pyrosequencing, Sanger resequencing and microsatellite data. It was found that the genomic sampling of genetic variants from the three applied methods yielded similar genetic information on pale flax and four groups of cultivated flax. The revealed genetic relationships did not show significant departures from the previous findings, but instead supported an early, independent domestication of a primitive flax lineage for oil use, followed by a subsequent flax domestication process with multiple domestication events for capsular dehiscence, oil, fiber and winter hardiness. Domestication on capsular dehiscence occurred earlier than domestication on winter hardiness. Domestication on winter hardiness was more complicated than domestication on capsular dehiscence. Full article

Focusing on sustainability, the new Common Agricultural Policy (2023–2027) sets ambitious goals for water management, as reducing irrigation water use is a vital issue. Cooperation among farmers, relevant authorities, and researchers plays a significant role in achieving these objectives. Therefore, this study applies a multicriteria mathematical programming model to optimize land use, considering water use, profit, labor, and cost. The model was applied to three farmer groups located in Greece and proved to be valuable in the implementation of irrigation water use. Using the same methodology, two additional cases of farmer groups that utilize drylands are presented in complementary ways to investigate how the new CAP affects non-irrigated land uses. Regarding the irrigated case, reducing water usage involves decreasing the land dedicated to crops characterized by high water demand, such as rice, corn, vetch, and clover. This adjustment stems from the necessity to replace irrigated land with non-irrigated land because climate change demands low water consumption for crops and underscores the importance of the new policy framework to promote sustainable agriculture. As for the non-irrigated case, achieving optimal farm planning entails reducing the cultivated areas of vetch, grassland, and sunflower. This result is driven by the need to increase crops receiving primary subsidies, highlighting the necessity for non-irrigated farms to enhance their profitability through the benefits provided by the Common Agricultural Policy. Lastly, it is important to note that this study significantly contributes to guiding decision-makers in achieving alternative agricultural land uses and farm plans while also aiding in the comprehension of the new cross-compliance rules. Full article

Analyzing the change trend of urban green space (UGS) and exploring related driving forces can provide scientific reference for sustainable development in rapidly urbanizing areas. However, the spatial and temporal driving mechanisms of the drivers on UGS patterns at different scales are still not deeply understood. Based on the GlobeLand30 land cover data, nighttime lighting data and spatial statistics from 2000 to 2020, this study analyzed the size, shape and diversity of UGS in Guangzhou at the urban level, gradient level and township level with multiple landscape indices. Diversity means the richness of UGS patch types. The selected indices include percent of landscape (PLAND), largest path index (LPI), landscape shape index (LSI), aggregation index (AI) and Shannon’s diversity index (SHDI). The spatiotemporal heterogeneity of the drivers was then explored using the spatiotemporal weighted regression (GTWR) method. Results showed the following: (1) During 2000−2020, the total amount of UGS in Guangzhou increased slightly and then decreased gradually. UGS was mainly transferred into artificial surfaces (lands modified by human activities). (2) The UGS landscape showed a non-linear trend along the urban–rural gradient and fluctuated more in the interval of 20–60% urbanization level. PLAND, LPI and AI decreased significantly in areas with higher levels of urbanization. LSI increased and SHDI decreased significantly in areas with lower levels of urbanization. At township level, the landscape indices showed significant spatial autocorrelation. They transformed from discrete changes at the edge and at the junction of the administrative district to large-scale aggregated change, especially in northern areas. (3) The size of UGSs was mainly influenced by natural factors and population density, but their shape and diversity were mainly influenced by socio-economic factors. More regular shapes of green patches were expected in higher urbanization areas. Population agglomeration positively influenced green space patterns in the northeastern and southern regions (Zengcheng, Conghua and Nansha). Meanwhile the negative influence of urban expansion on the green space pattern in the central and southern regions decreased over time. This study contributes to an in-depth understanding of how the key factors affect the different changes of UGS with time and space and provides methodological support for the long-term zoning planning and management of UGS. Full article

The integration of steel fibers into high-strength concrete (HSC) offers a solution to address the brittleness and limited ductility typically associated with conventional HSC structures. To investigate the bonding properties between shaped steel and high-strength concrete with steel fiber (SFRC), thirteen tests of the shaped steel/SFRC specimens are conducted to explore the effects of various factors such as steel fiber volume ratio, concrete strength grade, reinforcement ratio, steel embedment depth, and cover thickness on bond–slip behavior. Three distinct failure modes, such as pushout failure, bond splitting, and yielding failure of steel, are identified during the pushout tests. Three different types of bond strength, such as the initial bond strength, the ultimate bond strength, and the residual bond strength, are observed from the load–slip curves between the shaped steel and concrete. By incorporating nonlinear spring elements, a numerical model for accurately simulating the bond performance between the shaped steel and SFRC specimens is developed. The bond strength between the shaped steel and concrete increase as the concrete strength, cover thickness, steel fiber volume ratio, and stirrup ratio increase, while it decreases as the steel embedment depth increases. A model for the bond strength between shaped steel and SFRC is developed, and it agrees well with the test data. Full article

The issue of sustainability has once again received attention and promotion in the post-COVID-19 pandemic era. Countries worldwide have launched returnable cup services for beverages, such as Taiwan, which is a highly developed market for hand-shaken drinks, and various beverage and convenience stores have been gradually launching this service. However, reasonable usage rates have yet to be achieved. This study aimed to explore the psychological cognition of using a returnable cups service by understanding the motivation affecting the behavior intention through external and internal influencing and categorizing realistic cognition, which observes the motivating factors from three perspectives: passively acquired awareness, autonomous consciousness, and perception in real life for further achieving environmental sustainability. Research found that when consumers’ environmental awareness is insufficient to sacrifice convenience, it is necessary to employ a service strategy design for passive influence. The focal point for influencing consumer attitudes lies in the backend of services, particularly in cup return, which is the chain-closing juncture. The result can provide the beverage industry and governments with a reference to promote returnable cups and contribute to plastic reduction in sustainable development. Full article