Search Results (1,151)

Factor analysis is a well-known statistical method to describe the variability of observed variables in terms of a smaller number of unobserved latent variables called factors. Even though latent factors are conceptually independent of each other, their influence on the observed variables is often joint and synergistic. We propose to quantify the synergy of the joint influence of factors on the observed variables using O-information, a recently introduced metric to assess high-order dependencies in complex systems; in the proposed framework, latent factors and observed variables are jointly analyzed in terms of their joint informational character. Two case studies are reported: analyzing resting fMRI data, we find that DMN and FP networks show the highest synergy, consistent with their crucial role in higher cognitive functions; concerning HeLa cells, we find that the most synergistic gene is STK-12 (AURKB), suggesting that this gene is involved in controlling the HeLa cell cycle. We believe that our approach, representing a bridge between factor analysis and the field of high-order interactions, will find wide application across several domains. Full article

Optimal sensorimotor control depends on response timing. With age, it is broadly assumed that reaction time (RT) increases as cognitive function declines. However, it is not clear if the literature supports this assumption. The purpose of this work was to review the association between cognition and upper extremity RT in older adults. We conducted a search using Scopus database with four inclusion criteria: (1) healthy, community-dwelling adults over 60 years old, (2) upper extremity movement, (3) cognitive assessment, and (4) RT measure. Twenty-five of the 1608 articles screened met the inclusion criteria. Only nine studies directly or indirectly assessed the association between cognition and RT. Our interpretation of the literature was further limited by inconsistency in test selection and measurement interdependence that could be addressed by future studies. We present a conceptual framework to guide research assessing the influence of cognition on sensorimotor control with age. Full article

Articulated Tugs and Barges (ATBs) are increasingly recognised for their effectiveness in transporting chemicals, petroleum, bulk goods, and containers, primarily due to their exceptional flexibility and fuel efficiency. Recent projections indicate that the ATB market is on track for significant growth, which is expected to lead to an increase in the annual growth rate from 2025 to 2032. This study aims to analyse the current advancements in ATB technology and provide insights into the ATB fleet and the systems that connect tugboats and barges. Furthermore, it highlights the advantages of this transportation system, especially regarding its role in enhancing energy efficiency within the maritime transport sector. Currently, there is limited information available in the public domain about ATBs compared to other commercial vessels. The analysis reveals that much of the required information for modern ATB design is not accessible outside specialised design companies. The study also focuses on conceptual design aspects, which include the main dimensions, articulated connections, propulsion systems, and machinery, concluding with an evaluation of economic viability. Special emphasis is placed on defining the main dimensions, which is a critical part of the complex design process. In this context, the ratios of length to beam (L/B), beam to draft (B/D), beam to depth (B/T), draft to depth (T/D), and power to the number of tugs cubed (Pw/N³) are established as design control parameters in the conceptual design phase. This aspect underscores the novelty of the present study. Additionally, the economic viability is analysed in terms of both CAPEX (capital expenditures) and OPEX (operational expenditures). While CAPEX does not significantly differ between the methods used in different types of commercial ships, OPEX should account for the unique characteristics of ATB vessels. Full article

The digital business environment is rapidly evolving with advancements in information technology (IT), increasing the risk of information security incidents. Grounded in the resource-based view and in contingency theory, this study adopts a different approach from prior research by conceptualizing security management activities not as mere risk control mechanisms, but as strategic innovation drivers that can enhance corporate performance (sales revenue and operating profit). The authors develop a research model with six independent variables, including internal and external security management activities, CISO role configuration (independent or dual-role with CIO), and investment levels in IT and information security. The dependent variables include sales revenue and operating profit, with ISMS or ISO certification as a moderating variable. Using information security (IS) disclosures and financial data from 545 Korean firms that have reported their security management activities to the Ministry of Science and ICT, multiple regression and moderation analyses reveal that high IT investment negatively impacts performance, but this effect is mitigated when formal security systems, like ISMS or ISO, are in place. The results suggest that integrating recognized security frameworks into management strategies can enhance both innovation and financial outcomes, encouraging a proactive approach to security management. Full article

Canine morbillivirus (CDV), the cause of canine distemper, is a pathogen affecting many hosts. While modified live virus (MLV) vaccines are crucial for controlling the disease in dogs, cases of vaccine-related infections have been found in both domestic and wild animals. Specifically, the America-1 and Rockborn-like vaccine genotypes are concerning due to their spread and ability to transmit between different species. This study conducted a review and analysis of molecular detections of these strains in various carnivores (domestic, captive, synanthropic, and wild species). This study used a conceptual model considering host ecology and the domestic–wild interface to evaluate plausible transmission connections over time using Linear Directional Mean (LDM) and Weighted Mean Centre (WMC) methods. Statistical analyses examined the relationship between how likely a strain is to spread and factors like host type and vaccination status. The findings showed that the America-1 genotype spread in a more organised way, with domestic dogs being the main source and recipient, bridging different environments. Synanthropic mesocarnivores also played this same role, with less intensity. America-1 was most concentrated in the North Atlantic and Western Europe. In contrast, the Rockborn-like strain showed a more unpredictable and restricted spread, residual circulation from past use rather than ongoing spread. Species involved in vaccine-related infections often share characteristics like generalist behaviour, social living, and a preference for areas where domestic animals and wildlife interact. We did not find a general link between a host vaccination status and the likelihood of the strain spreading. The study emphasised the ongoing risk of vaccine-derived strains moving from domestic and synanthropic animals to vulnerable wild species, supporting the need for improved vaccination approaches. Mapping these plausible transmission routes can serve as a basis for targeted surveillance, not only of vaccine-derived strains, but of any other circulating genotype. Full article

Cybersecurity threats increasingly originate from human actions within organizations, emphasizing the need to understand behavioral factors behind non-compliance with information security policies (ISPs). Despite the presence of formal security policies, insider threats—whether accidental or intentional—remain a major vulnerability. This study addresses the gap in behavioral cybersecurity research by developing an integrated conceptual model that draws upon Operant Conditioning Theory (OCT), Protection Motivation Theory (PMT), and the Theory of Planned Behavior (TPB) to explore ISP compliance. The research aims to identify key cognitive, motivational, and behavioral factors that shape employees’ intentions and actual compliance with ISPs. The model examines seven independent variables of perceived severity: perceived vulnerability, rewards, punishment, attitude toward the behavior, subjective norms, and perceived behavioral control, with intention serving as a mediating variable and actual ISP compliance as the outcome. A quantitative approach was used, collecting data via an online survey from 302 employees across the public and private sectors. Structural Equation Modeling (SEM) with SmartPLS software (v.4.1.1.2) analyzed the complex relationships among variables, testing the proposed model. The findings reveal that perceived severity, punishment, attitude toward behavior, and perceived behavioral control, significantly and positively, influence employees’ intentions to comply with information security policies. Conversely, perceived vulnerability, rewards, and subjective norms do not show a significant effect on compliance intentions. Moreover, the intention to comply strongly predicts actual compliance behavior, thus confirming its key role as a mediator linking cognitive, motivational, and behavioral factors to real security practices. This study offers an original contribution by uniting three well-established theories into a single explanatory model and provides actionable insights for designing effective, psychologically informed interventions to enhance ISP adherence and reduce insider risks. Full article

Background: Wearable movement sensors can measure upper limb (UL) activity, but single variables may not capture the full picture. This study aimed to replicate prior work identifying five multivariate categories of UL activity performance in people with stroke and controls and expand those findings to other UL conditions. Methods: Demographic, self-report, and wearable sensor-based UL activity performance variables were collected from 324 participants (stroke n = 49, multiple sclerosis n = 19, distal UL fracture n = 40, proximal UL pain n = 55, post-breast cancer n = 23, control n = 138). Principal component (PC) analyses (12, 9, 7, or 5 accelerometry input variables) were followed by cluster analyses and numerous assessments of model fit across multiple subsets of the total sample. Results: Two PCs explained 70–90% variance: PC1 (overall UL activity performance) and PC2 (preferred-limb use). A five-variable, five-cluster model was optimal across samples. In comparison to clusters, two PCs and individual accelerometry variables showed higher convergent validity with self-report outcomes of UL activity performance and disability. Conclusions: A five-variable, five-cluster model was replicable and generalizable. Convergent validity data suggest that UL activity performance in daily life may be better conceptualized on a continuum, rather than categorically. These findings highlight a unified, data-driven approach to tracking functional changes across UL conditions and severity of functional deficits. Full article

Integrating blockchain into healthcare devices offers the potential for improved data control but faces significant usability and acceptance challenges. This study addresses this gap by evaluating CipherPal, an improved blockchain-enabled Smart Fidget Toy prototype, using a multi-framework approach to understand the interplay between technology, design, and user experience. We synthesized insights from three complementary frameworks: an expert review assessing adherence to Web3 Design Guidelines, a User Acceptance Toolkit assessment with professionals based on UTAUT2, and an extended three-day user testing study. The findings revealed that users valued CipherPal’s satisfying tactile interaction and perceived benefits for well-being, such as stress relief. However, significant usability barriers emerged, primarily related to challenging device–application connectivity and data synchronization. The multi-framework approach proved valuable in revealing these core tensions. While the device was conceptually accepted, the blockchain integration added significant interaction friction that overshadowed its potential benefits during the study. This research underscores the critical need for user-centered design in health-related blockchain applications, emphasizing that seamless usability and abstracting technical complexity are paramount for adoption. Full article

Water source identification and dynamic assessment are critical for mining safety, particularly in mines governed by complex geological structures. The hydrochemical mixing model demonstrates a natural advantage for early warning of water intrusion compared to geophysical monitoring techniques. This study discusses core issues related to the mixing model, including the conceptual framework, selection of end-members, and choice of tracers, and formulates principles for general applicability. In this study, three sources were identified using the conceptual model and hydrochemical analysis: water in F7 (main fault), shallow fracture water, and river water. A correlation analysis and variability analysis were applied to determine the tracers, and the ¹⁸O, D, Cl, B, and Li were determined. The end-members of the three sources are time-dependent in July and September, especially the shallow fracture water’s end-members. The dynamics of the mixing ratios of the three sources suggest that river water contributes only to the inrush (1–4%), with this being especially low in September, as the increasing hydraulic gradient from south to north prevents recharge. The water in F7 accounts for at least 70% of the inrush water. Shallow fracture water accounts for the rest and increases slightly in September as the precipitation increases in mining-disturbed areas. Finally, this work makes the later water control work more targeted. Full article

This paper introduces a unified and systematic design methodology for robotic systems that is generalizable across a wide range of applications. It integrates rigorous mathematical formalisms such as kinematics, dynamics, control theory, and optimization with advanced simulation tools, ensuring that each design decision is grounded in provable theory. The approach defines clear phases, including mathematical modeling, virtual prototyping, parameter optimization, and theoretical validation. Each phase builds on the previous one to reduce unforeseen integration issues. Spanning from conceptualization to deployment, it offers a blueprint for developing mathematically valid and robust robotic solutions while streamlining the transition from design intent to functional prototype. By standardizing the design workflow, this framework reduces development time and cost, improves reproducibility across projects, and enhances collaboration among multidisciplinary teams. Such a generalized approach is essential in today’s fast-evolving robotics landscape where rapid innovation and cross-domain applicability demand flexible yet reliable methodologies. Moreover, it provides a common language and set of benchmarks that both novice and experienced engineers can use to evaluate performance, facilitate knowledge transfer, and future-proof systems against emerging application requirements. Full article

This paper presents studies of a digital twin system. A conceptual model of the system is proposed to be used to control an industrial robot and can be integrated into different fields of application such as industry, manufacturing, farming, livestock breeding and others. On the principle of software engineering, the overall architecture of the system is developed, and its constituent elements are presented in detail. A kinematic analysis of the considered industrial robot is presented. To realize the digital twin, a simulation model of the industrial robot was developed to fully meet the dimensions and kinematic characteristics of the real one. Experiments have been made on the operation of the system so as to compare the movements of the real and simulated robot. The results obtained show almost identical motions both in the end effector of the robots and in the motions of each of the joints. A short methodology for the steps of creating systems using digital twins is presented to assist developers and scientists. Full article

Life Cycle Impact Assessments (LCIAs) examine the environmental impacts of products using life cycle inventories (LCIs) of quantified inputs and outputs of a product through its life cycle. Currently, estimated impacts from mining are dominated by long-term metal release from tailings due to inaccurate assumptions regarding metal release and transport within and from mine materials. A conceptual model approach is proposed to support the development of a new database of LCI data, applying mechanistic processes required for the release and transport of metals through tailings and categorizing model inputs into ‘bins’. The binning approach argues for accuracy over precision, noting that precise metal release rates are likely impossible with the often-limited data available. Three case studies show the range of forecasted metal release rates, where even after decades of monitoring within the tailings and underlying aquifer, metal release rates span several orders of magnitude (<100 mg/L to >100,000 mg/L sulfate at the Faro Mine). The proposed tool may be useful for the development of a new database of LCI data, as well as to analyze mine’s regional considerations during designs for risk evaluation, management and control prior to development, when data is also scarce. Full article

This article investigates the political cost of poverty in democracies marked by deep social divisions. We develop a probabilistic voting model that incorporates clientelism as a strategic tool employed by elite political parties to secure electoral support from non-elite voters. Unlike models based on ideological proximity, our framework conceptualizes party competition as structured by the socioeconomic composition of their constituencies. We demonstrate that in contexts of high inequality and widespread poverty, elite parties face structural incentives to deploy clientelistic strategies rather than universalistic policy agendas. Our model predicts that clientelistic expenditures by elite parties increase proportionally with both inequality (GINI index) and poverty levels, rendering clientelism a rational and cost-effective mechanism of political control. Empirical evidence from a cross-national panel (2013–2019) confirms the theoretical predictions: an increase of the 1 percent in the GINI index increase a 1.3 percent in the clientelism, even after accounting for endogeneity and dynamic effects. These findings suggest that in divided democracies, poverty is not merely a condition to be alleviated, but a political resource that elites strategically exploit. Consequently, clientelism persists not as a cultural residue or institutional failure, but as a rational response to inequality-driven constraints within democratic competition. Full article

Transparency is a key requirement for some classes of robots, exoskeletons, and assistive devices (READs), where safe and efficient human–robot interaction is crucial. Typical fields that require transparency are rehabilitation and industrial contexts. However, the definitions of transparency adopted in the literature are heterogeneous. It follows that there is a need to clarify, summarize, and assess how transparency is commonly defined and measured. Thus, the goal of this review is to systematically examine how transparency is conceptualized and evaluated across studies. To this end, we performed a structured search across three major scientific databases. After a thorough screening process, 20 out of 400 identified articles were further examined and included in this review. Despite being recognized as a desirable and essential characteristic of READs in many domains of application, our findings reveal that transparency is still inconsistently defined and evaluated, which limits comparability across studies and hinders the development of standardized evaluation frameworks. Indeed, our screening found significant heterogeneity in both terminology and evaluation methods. The majority of the studies used either a mechanical or a kinematic definition, mostly focusing on the intrinsic behavior of the device and frequently giving little attention to the device impact of the user and on the user’s perception. Furthermore, user-centered or physiological assessments could be examined further, since evaluation metrics are usually based on kinematic and robot mechanical metrics. Only a few studies have examined the underlying motor control strategies, using more in-depth methods such as muscle synergy analysis. These findings highlight the need for a shared taxonomy and a standardized framework for transparency evaluation. Such efforts would enable more reliable comparisons between studies and support the development of more effective and user-centered READs. Full article

In response to the challenges of urbanization, digitalization, and the e-commerce surge intensified by the COVID-19 pandemic, Smart Urban Logistics (SUL) has become a key framework for addressing last-mile delivery issues, congestion, and environmental impacts. This study introduces a System Dynamics (SD)-based approach to investigate how urban logistics and access management policies may interact. At the center, there is a Causal Loop Diagram (CLD) that illustrates dynamic interdependencies among fleet composition, access regulations, logistics productivity, and environmental externalities. The CLD is a conceptual basis for future stock-and-flow simulations to support data-driven decision-making. The approach highlights the importance of route optimization, dynamic access control, and smart parking management systems as strategic tools, increasingly enabled by Industry 4.0 technologies, such as IoT, big data analytics, AI, and cyber-physical systems, which support real-time monitoring and adaptive planning. In alignment with the Industry 5.0 paradigm, this technological integration is paired with social and environmental sustainability goals. The study also emphasizes public–private collaboration in designing access policies and promoting alternative fuel vehicle adoption, supported by specific incentives. These coordinated efforts contribute to achieving the objectives of the 2030 Agenda, fostering a cleaner, more efficient, and inclusive urban logistics ecosystem. Full article