Abstract: Cracks and holes are commonly found in wooden components, and ancient Chinese wooden buildings represented by Yingxian Wooden Pagoda demonstrate the ability to work with defects. This study systematically investigated the effects of longitudinal cracks and circular holes on the load-bearing capacity of wooden beams through four point bending experiments on 1580 samples. The study focuses on load-bearing capacity as the core indicator and provides calculation formulas for section weakening coefficient and damage tolerance coefficient to quantitatively evaluate the impact of cracks. Research has found that the harmfulness of damage strongly depends on its position within the wooden beam. In the horizontal direction, when the longitudinal crack is located in the pure bending section of the wooden beam, it has little effect on the load-bearing capacity of the wooden beam. Once it deviates to the transverse bending section, the load-bearing capacity of the wooden beam significantly decreases. The hole is most dangerous when it is located in the horizontal center of the wooden beam, and it is also dangerous when it is near the loading point. In the vertical direction, the crack has the greatest impact on the load-bearing capacity of the wooden beam when it is located in the neutral layer, while its impact decreases when it is close to the upper and lower surfaces of the wooden beam. Holes have the least impact when approaching the neutral layer, which is different from the impact pattern of cracks. In addition, the hazard increases when the hole is located in the tension zone of the wooden beam, and decreases when it is located in the compression zone. The anisotropy and fiber structure of wood are the microscopic basis for the damage tolerance mechanical behavior of timber beams.

Abstract: Regenerative rehabilitation can enhance skeletal muscle mass, function, and size following traumatic injuries such as volumetric muscle loss (VML). We previously optimized fibrin-laminin hydrogels for muscle regeneration and an electrically stimulated eccentric contraction training (EST) for muscle rehabilitation. The goal of this study was to examine the combined effect of these two therapies in maximizing tissue recovery. A VML defect was created by removing ~20% of muscle mass from the tibialis anterior (TA) muscle in adult male Lewis rats. The injured TA muscles were treated with fibrin-laminin (FBN450) hydrogel. EST was implemented 2 weeks post-injury at both 100 Hz and 150 Hz frequencies and was continued for 4 weeks. The results showed no improvement in muscle mass or function with combined FBN450 and EST application. Histological analysis revealed reduced type 2B myofiber size and percentage in the combined hydrogel and EST treatment group. Gene expression studies showed increased inflammatory and fibrotic signaling with no concomitant increase in myogenic markers. Collectively, these results indicate that the FBN450 hydrogel therapy did not synergize with EST to improve outcomes following VML.

Abstract: While privacy concerns are traditionally assumed to deter data sharing, this study challenges that consensus within the context of value-aligned green marketing. Drawing on privacy calculus theory and trust-building frameworks, we surveyed 1,136 consumers to investigate the mechanisms driving engagement with AI-driven sustainability initiatives. Following a rigorous attrition analysis to ensure data quality (final N = 482), structural equation modeling reveals a complementary mediation effect: brand trust mediates the relationship between privacy concern and data-sharing willingness (indirect effect = 0.068), yet a significant positive direct effect persists (\beta = .109, p = .010). This finding suggests that privacy-conscious consumers do not exhibit paradoxical behavior but rather exercise privacy self-efficacy—engaging in informed, strategic selectivity where high concern correlates with high competence in managing risks. Furthermore, the study addresses the “Green-AI Paradox”—the tension between AI’s environmental utility and its substantial carbon footprint. We propose a new framework of “Impact Transparency” and introduce the AI Data Usage Efficiency (ADUE) metric for integration into the EU Digital Product Passport. These findings offer a roadmap for marketers and policymakers to foster trust through authentic, outcome-based transparency.

Abstract:

Laryngomalacia is the most common cause of inspiratory stridor in infancy. While most mild cases resolve spontaneously, severe cases may require surgical intervention. We report a case of severe laryngomalacia successfully treated with correction of glosso-larynx (CGL), a surgical procedure originally developed for ankyloglossia with deviation of the epiglottis and larynx (ADEL). The patient showed rapid and sustained improvement without major complications. This case suggests that CGL may represent a simple and minimally invasive therapeutic option for selected cases of severe laryngomalacia.

Abstract: Cantrell syndrome (CS) is a rare congenital disorder involving defects in the thoraco-abdominal midline, the diaphragm, the pericardium, the sternum and the heart. Since the first description of the syndrome, 165 well-documented cases in humans have been reported, reflecting remarkable heterogeneity ranging from complete pentalogy to partial or atypical variants. We conducted a systematic review and classified body wall defects and associated anomalies into the following nine categories: midline defects, lateral defects, and special cases. Each case was reassessed for umbilical cord status, body wall morphology, cardiac anomalies and additional malformations. Midline defects predominated (152/165), with variants of supraumbilical defect being the most frequent; umbilical hernias accounted for ten cases as a distinct subgroup. Lateral defects were rare (nine cases, 5.5%), typically presenting with thoracogastroschisis or lateral thoracoabdominoschisis, and often associated with normal cords. Across all categories, cardiac anomalies were universal, with ventricular and atrial septal defects being the most common. Reclassification revealed that many cases originally labelled as 'classic PC' were better defined as partial or atypical forms. This unified framework clarifies the epidemiology, enhances diagnostic accuracy and, from a One Health perspective, highlights CS as a shared developmental vulnerability across species.

Abstract: The study of emotional body mapping has emerged as a critical tool for understanding the embodied mind, recently integrated into a tripartite framework comprising bottom-up physiological, top-down motor, and conceptual-metaphorical signals (Daikoku et al., 2025). However, current models remain largely descriptive, lacking a formalized account of functional lateralization as a predictive indicator of a subject’s cognitive stance. This paper proposes an integration of the Subjectica model (Shopin, 2025) into the body mapping paradigm to address this operational gap. By conceptualizing the body as a lateralized interface—distinguishing between the Personally-Oriented Left Side (PO-LS) and the Socially-Oriented Right Side (SO-RS) — we provide a methodology for interpreting Asymmetric Neurobehavioral Signals (ANS) through body segmental (BS). This paper introduces the concept of Sensory Circulation (SC) — a continuous flow of sensory signals that determines the level of somatic awareness and engagement through attentional mechanisms. Within the Subjectica framework, sensory circulation is analyzed through the lens of functional lateralization: the PO-LS and the SO-RS. This synthesis enables the interpretation of body maps not as passive affective reports, but as indicators of the subject's active cognitive stance. This approach shifts the analytical focus from the static localization of affect to the dynamic mapping of cognitive orientation. We posit that lateralized embodied patterns serve as a quantifiable link between hemispheric specialization and observable kinematics. This synthesis offers a rigorous neurophenomenological foundation for cognitive science, enabling the objective analysis of the "cognitive alphabet" expressed through the body.

Abstract:

The introduction of drones as part of a future logistics systems could enhance the efficiency of some goods movements but brings with it the prospect of a change to the environment and society. This paper reports on a study which seeks to identify how varied the concerns are amongst both practitioners and citizens and also how different the concerns of the public are from those of practice. The research uses Q-Sort methods to understand the critical variables and clusters of opinions which underlie policy controversies. A Q-Sort was first conducted with 53 professional stakeholders before a common, but reduced size Q-Sort was undertaken with a representative sample across three different local geographies (N = 610) in the UK. The findings suggest many common clusters of viewpoints across the expert and citizen samples, with the key interactions being between the degree of in principle support for drones for delivery and the degree of practical control over their introduction. However, the citizen group was dominated by drone sceptics worried about privacy, terrorism and environmental impacts in a way which was not manifested in the experts. Few differences occurred between places suggesting that simple urban-rural dichotomies do not define groups of opinions.

Abstract: This paper focuses on analyzing the dynamic process, strength and orientation of risk spillovers in the Chinese banking system under the exogenous shock scenario of the COVID-19 pandemic. Using the closing prices of 25 chosen banks on a daily basis, it stratifies the data into three periods: before, during, and after the pandemic. The HP-TVP-VAR-DY model is used to model risk heterogeneity and time-varying features in risk transmission processes. A dynamic topological directional graph is further used to track the core risk sources and paths in risk transmission processes. The key findings obtained from this paper are summarized below: (1) The Total Spillover Index for the banking system persisted at a high level following the outbreak of the COVID-19 pandemic, indicating its high sensitivity to abrupt and large-scale events. (2) Bank risk transmission paths are highly heterogeneous and time-varying in nature. Prior to the pandemic, CCBs were prominent in overall risk output; during the pandemic, JSCBs dominated; while in the post-pandemic period, again CCBs dominated overall risk output. In all periods, SOCBs and RCBs were identified as major risk receivables. (3) Concerning the structural change in interbank risk transmission paths, it exhibits phase-dependent features. In the pre-pandemic period, risk spillovers spread from CIB, CMB to ABC. However, in the pandemic period, interbank risk transmission paths became highly decentralized, indicating significant increases in risk outflows and inflows from RCBs and CCBs, respectively. Moreover, CMBC and SZRCB turned out to become key sources for risk radiation, while overall network mechanisms dominated risk absorption effects. However, in the post-pandemic period, interbank risk transmission paths tend to become re-centralized; BOC turned out to become a core source for risk transformation, indicating a revival in risk-output dominance in network topologies.

Abstract: Glioblastoma (GBM) remains among the most treatment-refractory human malignancies, shaped by profound molecular heterogeneity, extensive genomic instability and an immunosuppressive tumor microenvironment. Radiotherapy represents a cornerstone of current management; however, its therapeutic benefit is frequently limited by adaptive resistance and ineffective antitumor immunity. Emerging evidence indicates that ionizing radiation acts not only as a cytotoxic modality, but also as a potent immunological trigger through the release of damage-associated molecular patterns (DAMPs) and the induction of immunogenic cell death (ICD). In this review, we synthesize recent advances describing how canonical DAMPs—including HMGB1, ATP, calreticulin exposure, mitochondrial and nuclear DNA fragments—coordinate innate and adaptive immune activation via TLR-, RAGE- and cGAS–STING-dependent pathways. We further discuss the dual nature of DAMP signaling, which can either promote durable antitumor immunity or foster chronic inflammation, myeloid reprogramming and tumor tolerance, depending on radiation dose, fractionation, tumor context and concomitant therapies. Special emphasis is placed on how different radiation qualities, particularly proton versus photon irradiation, differentially modulate DAMP release, ICD dynamics and microenvironmental remodeling. Finally, we highlight translational opportunities to exploit DAMP-related signatures as liquid-biopsy biomarkers of response, as rational selectors for combination strategies (including immunotherapy and radiosensitizers), and as biological guides for personalized and adaptive radiotherapy in GBM. Collectively, DAMP-centered radiobiology provides a conceptual framework to integrate immunity into radiation planning and may enable a new generation of biologically informed treatment strategies for glioblastoma.

Abstract: The digital economy, while a pivotal engine for growth, presents a dual challenge in the context of climate goals. Utilizing panel data from 267 Chinese cities covering the period from 2011 to 2022, this study investigates the nonlinear relationship between the digital economy and carbon dioxide emissions, testing its conformity with the Environmental Kuznets Curve (EKC) hypothesis. Moving beyond a static verification, this research introduces a dynamic framework by examining how three exogenous shock variables—green finance, local government fiscal pressure, and climate policy uncertainty—reshape the EKC curve. Specifically, construct an extended EKC model with interaction terms to empirically assess how these exogenous shock variables shift the inflection point horizontally and vertically and alter the curve's slope. Our findings reveal that these factors significantly influence both the timing and peak level of emissions, as well as the efficiency of decarbonization before and after the turning point. This study provides a nuanced understanding of the digital economy's environmental impact, offering policymakers critical insights to navigate the green transition in the digital era.

Abstract:

Maintenance organizations face growing volumes of spare parts, requiring robust classification methodologies to support decision-making. Practitioners continue reliance on simple and single-criterion-specialized methodologies, while research advances toward criteria and threshold specialized classification optimization for operationally visible spare parts or predefined classes revealing criteria dependencies and data completeness requirements. The literature review identifies a gap showing that existing classification methodologies lack inclusion of all spare parts with maintainable asset relevance, consequently excluding, under-prioritizing, or misclassifying essential spare parts leading to the wrong forecasts and inventory policies. Applying design science research, this study develops a holistic spare parts portfolio classification methodology that increases spare parts inclusion and enables class-based decision-making strategy development to address the gap. The methodology classifies spare parts based on their absence and presence across equipment bill of materials, maintenance history, inventory, and inventory policies, enabling identification and inclusion of operationally invisible spare parts. A case study of 32,521 spare parts demonstrates the interventional effects of the methodology. The intervention improved decision-making efficiency by 91%, increased decision throughput ninefold, and transformed a non-transparent decision-making approach with 9% scope completion and 1.7% stock value increase into a transparent strategy-based approach yielding full scope completion and 33.6% scope stock value reduction.

Abstract: Background. Conservative management of port-related bacteremia often includes locally administered antimicrobials, known as antimicrobial lock therapy (ALT). Current guidelines recommend daily replacement of antimicrobial lock solutions (ALS). We aimed to evaluate whether ALS could remain effective with extended dwell times of up to 10 days. Methods. In this randomized clinical trial, patients with noninfected, recently implanted ports were assigned to one of five ALS dwell-time groups, ranging from 1 to 10 days. Each ALS contained heparin plus an antimicrobial at standard intraluminal concentrations: vancomycin 2 mg/mL, teicoplanin 10 mg/mL, linezolid 1.8 mg/mL, daptomycin 5 mg/mL, or tigecycline 4.5 mg/mL. The primary endpoint was the time at which intraluminal drug concentrations decreased below 1 mg/mL (ClinicalTrials.gov NCT01592032). Results. Vancomycin and linezolid concentrations fell significantly below 1 mg/mL after 3 days of dwell time. Daptomycin and tigecycline concentrations decreased significantly after 7 days but remained above 1 mg/mL. Teicoplanin concentrations did not decline significantly after 7 days. Conclusions. Optimal ALS dwell time depends on the antimicrobial agent. Vancomycin and linezolid locks require daily replacement, whereas daptomycin, tigecycline, and teicoplanin locks maintain therapeutic concentrations for up to 7 days. These findings support individualized ALS replacement strategies, potentially reducing the need for daily interventions.

Abstract: Atmospheric rivers (ARs) play a critical role in producing high-impact weather events including extreme precipitation, flooding, gusty winds, and rapid temperature changes. Building upon the recently published EDARA (ERA5-based Dataset for Atmospheric River Analysis), we present S-EDARA, a supplementary dataset that enhances AR impact assessment capabilities through a newer AR detection algorithm and additional impact-related metrics. S-EDARA includes AR shapes identified by the tARget version 4 (ARS4) algorithm, strong integrated vapour transport (SIVT) indicators, and pseudo total precipitation rate (PTPR) fields. The dataset features both numerical data and interactive graphical catalogues displaying ARS4, SIVT, PTPR, gusty winds, and 24-hour temperature changes at 6-hourly intervals. These enhancements enable more comprehensive analysis of AR impacts and characteristics, particularly for regions experiencing rapidly changing meteorological conditions during AR events. The dataset covers the period from 1940 to present and is publicly available through the Federated Research Data Repository.

Abstract: The principles of regeneration are found in different types of cultures, from long time ago. As an interdisciplinary field of research, regenerative medicine, play a great role in tissues and organs damaged reparation with a higher potential in transplantation if necessary. The definition of stem cells can be extended. From this point of view, we can mention taking in consideration the idea in which it is known that these cells form the base of the building body.

Abstract: We establish the estimation of solutions of two classes of weakly singular Wendroff-type integral inequalities of multiple variables with multiple nonlinear terms, apply them to fractional partial differential equations, and give the proof procedures for uniqueness, boundedness and continuous dependence.

Abstract: Forensic ethanol gas standards are used for, among other, the calibration and metrological verification of evidential breath analysers as described in OIML-R126. A correction for the amount fraction ethanol in forensic gas standards due to cylinder wall adsorption is described. The correction was developed for both the national primary measurement standards as well as for derived primary reference materials. A novel method based on the well-known decanting principle was developed and assessed using two suites of gas mixtures with ethanol amount fractions between 50 μmol mol⁻¹ to 1000 μmol mol⁻¹ in nitrogen. From the results, it is inferred that the initial adsorption loss is a function of the amount fraction and an interpolation formula was developed accordingly. To account for differences in adsorption between cylinders, a mixed effects model was used to describe the adsorption loss data with an excess standard deviation to account for between-cylinder effects.

Abstract: Recent conflicts indicate a structural inversion in the economics of warfare. The exposed human warfighter, requiring prolonged training, continuous sustainment, and high replacement cost, now operates at a growing disadvantage relative to low cost, rapidly replaceable machine systems. This paper argues that modern warfare is increasingly governed not by individual skill or platform sophistication, but by logistics, replacement speed, and cost asymmetry under sustained attrition. Using attrition economics and battlefield evidence from the ongoing war in Ukraine, the analysis demonstrates that humans are being displaced from exposed combat roles not primarily by ethical preference, policy choice, or doctrinal failure, but by binding logistical and regeneration constraints. As low cost systems absorb risk at scale, the human role shifts away from the highest-attrition layer toward remote command, supervision, and coordination, while machines assume primacy at the point of contact. This transition is observable in current conflicts and reflects a reversal in the cost structure that has historically defined military effectiveness, rendering the exposed human warfighter economically non-viable under sustained attrition.

Abstract: Federated Learning (FL) has emerged as a transformative distributed learning paradigm that enables collaborative model training without sharing raw data, thereby preserving privacy across large, diverse, and geographically dispersed clients. Despite its rapid adoption in mobile networks, IoT systems, healthcare, finance, and edge intelligence, FL continues to face several persistent and interdependent challenges that hinder its scalability, efficiency, and real-world deployment. In this survey, we present a systematic examination of six core challenges in federated learning: heterogeneity, computation overhead, communication bottlenecks, client selection, aggregation and optimization, and privacy preservation. We analyze how these challenges manifest across the full FL pipeline, from local training and client participation to global model aggregation and distribution, and examine their impact on model performance, convergence behavior, fairness, and system reliability. Furthermore, we synthesize representative state-of-the-art approaches proposed to address each challenge and discuss their underlying assumptions, trade-offs, and limitations in practical deployments. Finally, we identify open research problems and outline promising directions for developing more robust, scalable, and efficient federated learning systems. This survey aims to serve as a comprehensive reference for researchers and practitioners seeking a unified understanding of the fundamental challenges shaping modern federated learning.

Abstract:

The recovery of water and other resources from urban water system (UWS) has long been practiced in many Mediterranean countries, but very little in Croatia, although EU policy is encouraging. The threats posed by climate change, the growing problem of water and food supply, the energy crisis, and environmental pollution encourage resources recovery by applying the circular economy principles within integrated resource management (IRM) framework. The paper analyzes UWS sustainable circulation processes of water, nutrients and energy and their components in coastal tourist areas that strengthening urban system (US) and environment sustainability. The concept that is explored in this paper use dissipative structures theory to analyze the complexity and sustainability of UWS, urban systems (US) and circular economy processes. The paper discusses the potential of UWS as a local resource of nutrients, water and energy, and considers a possible integrated approach to selecting a locally sustainable recovery concepts. It was established that at the heart of effective water, energy and nutrient management in urban areas lays the principle of IRM, which treats entire urban life support systems as an interconnected system. Fitting circular economy strategy within IRM framework increases efficiency of resource recovery, and overall sustainability of tourist environment, economy and ensure sustainable well-being.

Abstract: Prior research has consistently shown that students’ SAT scores are influenced by factors beyond academic ability, including socioeconomic background and ethnicity. This study employed aggregated school-level data from Massachusetts and New York City (NYC) to assess the quantitative relationships between average SAT scores and school-level demographics and interventions. The assessment aims to help regional and national education policymakers identify factors related to school academic merits and devise inclusive and effective ways to promote educational equality. Three analytical methods, multiple linear regression, relaxed Least Absolute Shrinkage and Selection Operator (LASSO), and decision trees, were conducted sequentially to decipher the complex relationships among variables. The analysis showed that schools with high percentages of Black, Hispanic, and low-income students tend to have lower average scores than schools with high percentages of White, Asian, and well-off students. Moreover, socioeconomic disadvantage is the most powerful and consistent predictor of lower SAT scores, with race and good academic preparation (i.e., percent attending college) functioning as secondary influences. The results indicate that SAT score disparities reflect structural inequities, and more SAT preparation resources are needed at schools with higher percentages of Black, Hispanic, and low-income students to level the playing field in SAT testing.