Search Results (2,391)

The desert ecosystem harbors a resilient microbial community that sustains plant life under extreme stress. Understanding the endophytic microbiota of desert flora provides key insights into how these microorganisms enable plant survival and maintain ecological balance in arid landscapes. To date, the endophytic bacterial communities of dominant desert plants in the Arabian Peninsula have not been comprehensively characterized. Here, we investigated the endophytic microbiota of five co-adapted desert species, namely, Schweinfurthia papilionacea, Sesuvium verrucosum, Ochtocloa compressa, Helianthemum nummularium, and Convolvulus arvensis. These plants coexist in hyper-arid habitats and exhibit exceptional tolerance to drought, salinity, and nutrient scarcity. We hypothesized that, despite their phylogenetic divergence, these plants host functionally convergent microbial communities shaped by desert selection pressures. Using 16S rRNA gene amplicon sequencing, we obtained 3.4 million high-quality reads from 25 samples. Clustering at 97% similarity revealed 35 phyla and 17 dominant genera, highlighting notable microbial richness and ecological complexity. Alpha-diversity indices showed comparable species richness across hosts, while beta-diversity indicated community differentiation driven by environmental filtering. The dominant phyla included Pseudomonadota, Actinomycetota, Cyanobacteriota, and Bacillota, reflecting microbial adaptation to extreme desert conditions. Functional pathway prediction revealed enrichment of genes associated with DNA repair and protein turnover, suggesting metabolic flexibility and enhanced survival under stress. Overall, this study provides a comparative metagenomic insight into the endophytic bacterial communities of five desert plant species, uncovering a consistent pattern of functional convergence across diverse hosts. The findings suggest the presence of shared functional traits among the endophytic microbiota examined here, offering preliminary evidence for microbial contributions to plant resilience in arid environments. Full article

This manuscript is a continuation of the research published in Fire 2025, 8(8), 302, i.e., it deals with the examination of the cause-and-effect relationships of fires in the Republic of Serbia from the aspect of human safety. Among others, variables related to gender, age, and severity of injuries caused by fires are introduced, on which various methods of statistical analysis and stochastic modeling are first applied. Continuous age variables are modelled using the flexible Generalized Additive Models for Location, Scale, and Shape (GAMLSS) framework, where the Generalized Normal Distribution (GND) is identified as the optimal generative model for injuries, while a Reflected Log-Normal Distribution with positive support (RefLOGND+) provides the best fit for fatalities. The quality of such modeling is formally verified, and the probabilities of injury and death of individuals in certain age categories are predicted, revealing a pronounced concentration of injuries in the working-age population and a markedly higher relative risk of fatal outcomes among elderly individuals. Thereafter, by applying certain Data Mining (DM) techniques, primarily the Apriori algorithm, the most frequently occurring association rules are found, which indicate typical patterns and demographic structure of injuries and deaths in fires in Serbia. Finally, using the CART (Classification and Regression Trees) algorithm, several decision trees are formed that describe the impact and relationship of different causes of fires on injury and death in fires. In this way, some important and frequent patterns are observed that indicate key fire risk factors that significantly affect the demographic structure of human casualties. The results thus obtained provide a basis for developing targeted strategies for fire prevention and improving emergency response planning. Full article

Understanding how pollinators adjust their behavior to maximize reproductive success in resource-limited desert ecosystems is a fundamental ecological question. In this study, we investigated X. mongolicus using a combination of field behavioral observations, pollen identification, nutritional analysis, and morphometric measurements to systematically examine interannual variations in its flower visitation spectrum, foraging behavior, bee bread composition, and offspring body size. Our findings reveal a striking contrast: although this species exhibits polyphagy in flower visitation, it shows dietary specialization in larval nutrition—over 92% of the pollen in its bee bread originates from just two leguminous species, A. mongolicus and O. bicolor. Foraging duration increased with rising temperature and humidity, and bees adapted to strong winds by flying close to the ground. Compared with 2024, the bee bread in 2025 had lower fresh weight but higher crude protein content, and offspring body size was larger—likely due to more abundant spring rainfall in 2025, which improved the flowering performance of A. mongolicus. Collectively, these results indicate that this bee species copes with resource uncertainty in desert habitats through flexible foraging range and highly specialized food storage, with its reproductive success closely tied to the nutritional supply of key plants and precipitation patterns. This study highlights the role of precipitation timing in shaping the nutritional foundation of plant–pollinator interactions, providing a scientific basis for the conservation and management of desert pollinators. Full article

A new odd exponential-type (NOT-Exp) distribution provides a flexible and analytically tractable framework for modeling lifetime data exhibiting non-constant hazard behaviors, including increasing, decreasing, bathtub-shaped, and unimodal forms, which are commonly observed in real-world reliability and survival studies. In this work, a comprehensive inferential methodology is developed for the NOT-Exp model under a unified progressive Type-II hybrid censoring, allowing several traditional censoring designs to be treated as special cases within a single unified structure. The main advantages of the proposed model lie in its ability to capture complex risk dynamics while maintaining mathematical simplicity, making it particularly suitable for censored lifetime data. Classical inference is conducted via maximum likelihood estimation, along with two asymptotic confidence interval constructions based on normal and log-normal approximations for both model parameters and reliability characteristics. In addition, a Bayesian estimation framework is introduced using independent gamma priors and Markov chain Monte Carlo techniques to obtain posterior estimates, credible intervals, and highest posterior density regions. Extensive simulations demonstrate the accuracy, stability, and robustness of the proposed estimators under varying sample sizes, censoring intensities, and prior specifications. Applications to airborne toxicological variation data and bank customer waiting times highlight the practical importance of the methodology, where the NOT-Exp model consistently outperforms twelve competing lifetime distributions according to standard goodness-of-fit criteria. These results confirm that the suggested design gives a strong and versatile tool for analyzing complex censored lifetime data across environmental and service-system applications. Full article

Background: Global supply chains operate in increasingly volatile and technology-intensive environments shaped by digital transformation and artificial intelligence integration. While prior research has emphasized structural and technological enablers of flexibility, the behavioral foundations of supply chain adaptability remain insufficiently explored. Methods: This study develops a conceptual integration of the Kano model and the Cobb–Douglas production function to position managerial attitude as a strategic “delighter” within supply chain systems. The proposed framework models supply chain flexibility as a function of capital, labor, artificial intelligence integration, and managerial attitude within an extended economic representation. Results: The model suggests that managerial attitude acts as a behavioral amplifier that strengthens the performance effects of technological and economic inputs, potentially generating nonlinear gains in responsiveness and adaptive capacity. By distinguishing human-driven, algorithmic, and hybrid attitudinal configurations, the framework clarifies how behavioral orientations influence artificial intelligence adoption and supply chain flexibility, particularly in small and medium-sized enterprise contexts. Conclusions: Although conceptual in nature, the framework provides a formal analytical foundation for future empirical testing and elasticity-based sensitivity analysis in supply chain research. Full article

Speckle patterns generated by coherent illumination of random media are ubiquitous in optical imaging and information processing. However, most existing studies have primarily focused on isotropic or homogeneous speckle fields, while controlled manipulation of speckle patterns with customized geometric morphologies has received comparatively little attention. Here, we propose a random phase-coded array (RPA) as a general framework for generating geometrically reshaped speckle, enabling the formation of nonconventional random light fields whose ensemble-averaged intensity distributions follow prescribed geometric shapes. In this framework, the speckle geometry is determined by the unit-cell structure of the RPA, the unit-cell size governs the overall spatial extent of the speckle pattern, and the illuminating beam size sets the characteristic speckle grain size. These relationships are rigorously validated through theoretical derivations and numerical simulations. As a result, the global statistical envelope of the random light field can be intuitively and flexibly controlled without compromising the fully developed speckle characteristics. Our experimental framework offers a straightforward, scalable, and versatile approach for generating customized random light fields, with potential applications in optical information processing, secure optical communication, computational imaging, and speckle-based metrology. Full article

Developing materials that simultaneously exhibit bulk elasticity and a durable, self-renewing surface is a persistent challenge, as traditional fillers often impair flexibility and sacrificial coatings fail under repeated strain. This paper presents an innovative thiol–ene/polyurethane hybrid system, fabricated via a sequential thermal–UV curing process, which decouples the properties of the highly elastic bulk from those of the robust surface layer. The resulting bulk elastomer achieves an outstanding combination of high strength (20.9 MPa) and exceptional extensibility (990% elongation at break). Crucially, the UV-crosslinked surface forms a dense, abrasion-resistant shield that reduces friction-induced mass loss by 81% compared to the bulk material. This surface layer also exhibits a unique self-renewing capability, effectively restoring its protective function over at least three abrasion cycles and reducing mass loss by 57% after the first recovery cycle relative to an unprotected control. Dynamic mechanical analysis validates the distinct dual-network structure, evidenced by two well-separated glass transition temperatures, which underpin the material’s pronounced shape memory effect. This work provides a design paradigm for creating flexible and durable polymer systems with independently tailored bulk and surface properties, offering significant potential for applications in artificial skin and demanding flexible components. Full article

Background: The purpose of this article is to identify the expectations of Generation Z representatives regarding organizational changes and directions of innovation supporting sustainable development of enterprises, considering social and environmental aspects of working conditions. Methods: The study was conducted in the form of an online survey from 2024–2025. The research sample included 310 people selected using a purposive sampling method, with inclusion criteria covering membership of Generation Z (people born after 1995). In the research questionnaire, “organizational innovations” were operationalized through flexible work arrangements, process digitalization, new models of team collaboration, the development of digital competencies, and solutions supporting work–life balance. “Sustainable development” was conceptualized across three dimensions: social (well-being, inclusivity, CSR), organizational (development opportunities, employment stability), and environmental (ecological responsibility). The Mann–Whitney U test and the Kruskal–Wallis test were used to analyze intergroup differences. Results: Descriptive results (mean scores) indicate that respondents rated flexible work arrangements, opportunities for professional development, and effective team collaboration as the most crucial factors supporting sustainable organizational development. The Mann–Whitney U test showed that women rated the importance of well-being (p = 0.003), work–life balance (p = 0.001), diversity and inclusivity (p = 0.012), and corporate social responsibility (p = 0.008) significantly higher than men. Educational and professional status differentiated the assessment of employment stability (Kruskal–Wallis test, p = 0.021). Although social and environmental aspects are recognized, for the younger generation, the most crucial factors remain direct working conditions and development opportunities that foster innovation. Conclusions: The results of the study may be useful for employers (entrepreneurs and HR managers) in shaping modern HR strategies. This applies to the design of attractive working conditions in the realities of the digital economy. The research fills a gap in understanding the values that young people appreciate in terms of ensuring high-quality working conditions. Full article

Ultrasound imaging is a crucial tool for guiding radiation therapy, particularly for cancers such as pancreatic cancer, where tumors exhibit respiration-induced motion. While flexible ultrasound transducers offer improved anatomical conformity and reduced compression-induced distortion compared to rigid probes, their variable geometry presents significant challenges for conventional beamforming. In this study, we investigate a deep learning-based beamforming framework that directly predicts delayed RF data from raw RF input, bypassing explicit transducer shape estimation and traditional delay-and-sum computations. Building upon an artificial curvature simulation strategy, we systematically analyze the impact of curvature-induced variation and inherent RF noise on model performance and generalizability. We further introduce frequency-domain analysis to quantify RF-level signal variation that may not be apparent in spatial-domain image comparisons. Our results demonstrate that although noise-augmented training improves prediction consistency, reconstruction performance remains limited under the current prototype noise conditions. These findings highlight the importance of RF data diversity and noise characterization in developing clinically robust deep learning beamformers for flexible transducer-based ultrasound-guided radiation therapy. Full article

Historically, the electricity sector in Greece was based on local lignite, which provided a stable and affordable base for electricity production. However, current European policy directions, including decarbonization and climate neutrality by 2050, have accelerated the transformation of traditional energy models, resulting in a gradual phasing-out of fossil fuels and an increasing integration of Renewable Energy Sources (RES). In line with EU policy priorities and in light of the new dynamics shaped by the EU Emissions Trading System (EU ETS), lignite gradually became unprofitable for the national economy, leading the Greek government to announce an accelerated lignite phase-out plan. However, the phase-out of domestic lignite, although consistent with climate objectives, rapidly increased the country’s energy dependency on natural gas and its exposure to natural gas price volatility. At the same time, increased investment in solar and wind technologies has reshaped the electricity mix; yet market design, limited system flexibility and inadequate infrastructure and storage capacity have not allowed the full utilization of RES benefits. This structural gap, in turn, raises critical questions about resilience and affordability. The paper provides evidence on these issues and offers a critical evaluation of the decarbonization pathway that has reshaped the country’s energy dependency. Full article

Background/Objectives: Patients with liver cirrhosis experience a high symptom burden and low Health-Related Quality of Life (HR-QoL). Hepatic encephalopathy (HE) occurs in 75% of patients with cirrhosis but is sparsely described from the patient’s perspective. Due to recurrent cognitive impairment, a marginalized diagnosis, and a healthcare discourse emphasizing involvement and self-responsibility, these patients appear vulnerable when navigating a complex healthcare system. This study aims to explore how patients with chronic liver disease experience living with HE as a recurring condition, and how these patients are met by healthcare professionals (HCPs). Methods: Eight semi-structured interviews were conducted with four patients and four HCPs. Data were analyzed thematically following Braun and Clarke’s six-step analysis within the framework of Interpretive Description. The study was reported according to COREQ Guidelines. Results: The overarching theme “Becoming a different person” captured the profound identity changes experienced by patients. Three main themes emerged: 1. change and loss—in identity and self-understanding, in relationships, in relation to losing control, and in relation to experiencing isolation; 2. new paths—mental and practical alternative strategies; 3. HE in clinical encounters—requiring empathy, flexibility, and continuity. Stigma related to cirrhosis and its association with alcohol further intensified patients’ vulnerability. Conclusions: HE is experienced as a transformative and isolating condition, deeply affecting patients’ autonomy and social roles through vulnerability. The clinical encounter is shaped by the cognitive impairment due to HE, requiring tailored and sensitive care. Full article

A photo-curable silicone-modified resin system based on polydimethylsiloxane (PDMS) was developed and systematically evaluated for stereolithography (SLA)-based 3D printing applications. The resin formulation consisted of bisphenol A ethoxylate dimethacrylate (Bis-EMA) and trimethylolpropane triacrylate (TMPTMA) as reactive monomers, with methacrylate-terminated PDMS (PDMS-MMA) incorporated at concentrations ranging from 0 to 15 wt%. The influence of PDMS-MMA content on key physicochemical properties relevant to SLA processing, including viscosity, mechanical performance, thermal stability, optical transmittance, and curing shrinkage, was systematically investigated. Moderate incorporation of PDMS-MMA improved the mechanical flexibility of the resin, with the tensile strength reaching a maximum value of 5.95 MPa at 5 wt% PDMS-MMA. However, further increases in PDMS-MMA content resulted in a gradual decrease in tensile strength and optical transmittance, indicating the importance of optimizing the formulation composition. Thermogravimetric analysis (TGA) indicated improved thermal stability with increasing PDMS-MMA content, while curing shrinkage decreased progressively as the PDMS fraction increased. Structural printing tests confirmed that the developed resin system exhibited stable layer adhesion and shape fidelity during SLA fabrication, enabling the successful printing of complex three-dimensional structures. These results demonstrate that PDMS-modified acrylate resins provide a promising strategy for balancing mechanical flexibility, dimensional stability, and printability in SLA-based additive manufacturing. Full article

Remotely operated underwater vehicles (ROVs) play a significant role in the domain of underwater robotics, as observed in the field of deep-sea aquaculture. However, conventional stationary suction-tube underwater collection robots often struggle to efficiently collect target organisms located within complex reef environments. To address this limitation, this paper proposes an underwater object suction robot with a variable flexible tube. For vision-based object recognition tasks, stable vehicle motion is essential, as hydrodynamic disturbances can significantly degrade visual accuracy. Therefore, a systematic numerical investigation is conducted into the hydrodynamic characteristics of the ROV under different suction-tube shapes. Computational fluid dynamics (CFD) simulations are used to evaluate the resistance acting on the vehicle. The results provide guidance for motion control strategies aimed at reducing disturbance effects and improving the robustness of underwater robotic vision. Full article

Public project performance is shaped by both organisational capability and governance controls, yet the interaction between these factors remains underexamined in decentralised public administration contexts. This study examines the direct effects of team capability and ethical compliance on project performance, and tests whether ethical compliance conditions the capability–performance relationship. A quantitative explanatory survey design was adopted. Structured questionnaires were administered to 320 senior officers involved in project evaluation, procurement, budgeting and technical oversight, and the data were analysed using PLS-SEM to estimate the hypothesised direct and moderating relationships. Team capability and ethical compliance each have a significant positive effect on project performance, and team capability is positively associated with ethical compliance. The moderating effect of ethical compliance is significant but small in magnitude, indicating that higher levels of compliance modestly attenuate the marginal performance gains associated with greater team capability. These findings suggest that while compliance mechanisms strengthen accountability and directly support performance, they may simultaneously constrain the discretionary flexibility through which capable teams generate incremental improvements. The study contributes to public management research by empirically demonstrating a conditional capability–governance relationship in a local government project context. Given the moderate explanatory power of the model, future research should incorporate additional institutional and political variables to further clarify performance drivers in public-sector project systems. Full article

Background: Mild traumatic brain injury (mTBI) is frequently associated with persistent cognitive and psychosocial symptoms, yet biological correlates of recovery remain poorly understood, particularly among Asian and Pacific Islander (API) populations. Pre-injury psychosocial adversity may further shape post-injury recovery trajectories. This pilot study examined associations between participation in a 2-week, home-based, dual-task cognitive–walking intervention (Daily Brain Exercise; DBE) and changes in cognitive, psychological, and salivary microRNA (miRNAs) measures among APIs with and without a self-reported history of mTBI. Methods: API participants completed remote cognitive testing (CNS Vital Signs), psychosocial assessments (Neuro-QoL), and saliva collection before and after DBE participation. Salivary RNA was purified, and miRNA expression was profiled using nCounter^® Human v3 miRNA Expression Panels (NanoString). Differential expression analyses were conducted using ROSALIND^® platform (OnRamp Bioinformatics, San Diego, CA, USA), a cloud-based bioinformatics analysis system, to calculate fold changes and p-values. Pre-injury psychosocial adversity was assessed via the Trauma History Screen and examined descriptively as a contextual modifier of functional outcomes. Results: Twenty-one APIs (mean age 22.9 years; 76.7% female) were enrolled, including 14 individuals with a self-reported history of mTBI (mean 4.64 years post-injury; 50% with multiple injuries). Following DBE participation, increases in cognitive flexibility and executive function scores were observed in both mTBI and control groups. Additional increases in psychomotor speed, processing speed, sleep disturbance, and depressive symptoms were observed descriptively within the mTBI group. Subgroup analyses suggested variability in pre–post patterns across combinations of mTBI history and pre-injury psychosocial adversity. Exploratory miRNA analyses identified seven miRNAs that were differentially expressed in the mTBI group following DBE (unadjusted p < 0.005), including hsa-miR-7-5p, previously reported in association with neurodevelopmental and neurological pathways. Conclusions: In this pilot, feasibility-focused study, participation in a brief, home-based, dual-task intervention was associated with descriptive changes in selected cognitive and psychosocial measures among APIs, particularly those with a history of mTBI and pre-injury adversity. The observed subgroup patterns warrant confirmation in adequately powered, controlled studies. Exploratory changes in salivary miRNAs co-occurred with functional improvements, thus generating a hypothesis for a future investigation. Full article