Search Results (184)

Pakistan’s construction sector exhibits a disproportionate safety burden, accounting for 19.7% of workplace accidents despite comprising only 9.5% of the industrial workforce. While prior studies have diagnosed safety culture deficiencies through qualitative assessments, behavioral interventions, and risk identification approaches, no research has provided quantitatively prioritized intervention recommendations integrating regulatory mechanisms across project lifecycle phases with role-specific training programs. Grounded in Hudson’s safety culture maturity model and Reason’s organizational accident theory, this study employed a quantitative survey methodology to prioritize regulatory and training interventions for safety culture improvement. A 43-item questionnaire was administered to 105 construction industry professionals across client organizations (21%), contractor firms (30%), and consulting companies (49%) using stratified purposive sampling. Data were analyzed using Relative Importance Index calculations, supplemented by Kruskal–Wallis tests and correlation analyses, with instrument reliability being confirmed through Cronbach’s alpha (α = 0.859). Key findings reveal that 75.2% of respondents reported absence of safety culture implementation at project sites. Stakeholder effectiveness analysis identified sponsoring agencies (RII = 0.869) and regulatory authorities (RII = 0.819) as primary safety culture drivers, with clients demonstrating the lowest influence (RII = 0.568). Training prioritization established personal protective equipment utilization (RII = 0.886) and basic induction protocols (RII = 0.850) as critical worker competencies, while managerial requirements emphasized site-specific briefings (RII = 0.821) and incident protection training (RII = 0.808). Regulatory intervention priorities included safety credit points for contractor licensing (RII = 0.737) and departmental safety manual integration into contracts (RII = 0.726). These findings provide quantitative prioritization to guide resource allocation for safety culture interventions, although the descriptive methodology constrains causal inference regarding intervention effectiveness. Full article

Temporary agency work (TAW) has expanded globally as organizations seek flexibility amid skill shortages and demand volatility. In 2015 the United Nations recognized ‘decent work’ as Sustainable Development Goal (SDG 8), emphasizing sustainable economic growth, fair employment opportunities accessible to all without discrimination, environmental responsibility, and social inclusiveness. This study examines why user organizations (clients) adopt TAW and how these drivers materialize in stakeholder practices that align—or fail to align—with SDG-8 dimensions of decent work. Within a qualitative-dominant, explanatory sequential mixed-methods case study, documentary and statistical analyses were combined with 19 semi-structured interviews across agencies, clients, agency workers, trade unions, and relevant authorities. Inductive thematic analysis identified seven demand-side driver categories and assessed their effects using the SDG-8 pillars as an analytical lens (employment creation, rights at work, social protection, social dialogue). Findings indicate that TAW is primarily deployed to buffer volatility and labour shortages, accelerate hiring, and shift HR administration and parts of risk to agencies, with limited integration of SDG-8–consistent practices. Three cross-cutting gaps emerged: (i) social dialogue is narrow and compliance-oriented, with little strategic focus on decent-work outcomes; (ii) agency-worker voice and representation are weak, and agencies are not consistently recognised as social partners; and (iii) social-sustainability efforts are sparse and ad hoc, with few structured measures for skill development, equal treatment, or clear conversion pathways, while environmentally friendly initiatives are almost completely absent. In Slovenia, TAW fills systemic labour gaps but remains weakly integrated with SDG-8 practices. The study links demand-side drivers to specific decent-work shortfalls and proposes a multi-level policy roadmap—regulatory, industry, TAW agency, and social-dialogue platforms—to advance progress toward social sustainability and environmental responsibility. Full article

Traditional Time-Stamping Authorities provide reliable temporal evidence. However, they operate as single points of trust and do not supply a tamper-evident record of event ordering. This paper presents a standards-compliant extension that anchors each issued timestamp token to a blockchain ledger while preserving full compatibility with existing TSA clients. Our proposal is compliant with RFC 3161. The implementation uses an identifier in the token that is also included in the distributed ledger. Experiments were conducted on the Ethereum and Hyperledger Fabric networks. Our design allows for external verification of the existence and relative ordering of tokens without modifying the RFC-defined validation process. Experimental evaluation compares issuance latency, anchoring time, and transaction cost across both networks. Our work presents a practical and viable approach to enhancing trust in digital signature infrastructures by combining the regulatory reliability of qualified TSAs with the auditability and persistence of distributed ledgers. Full article

Project success is a complex and debated concept in construction project management, even more so for public sector infrastructure projects. This study proposes a new, data-driven methodology to assess the success of public infrastructure projects using a multi-criteria decision-making framework. By utilizing empirical data from 30 completed road infrastructure projects the study applies the Technique for Order Preference by Similarity to Ideal Situation (TOPSIS) method to evaluate performance across four key success criteria: cost, time, quality, and project management. An integrated Success Index (SI) was then calculated using the Simple Additive Weighting (SAW) method under two different weighting scenarios. Results show that projects with shorter durations and simpler scopes consistently achieved higher SI scores, while larger, more complex projects were more prone to delays, cost overruns, and quality issues. This study contributes to scientific research by utilizing real, archival project data rather than relying on expert opinions to quantify project success from the client contracting authority’s perspective rather than that of the contractor. Hence, the proposed model serves as a practical, adaptable tool for public contracting authorities seeking to benchmark and improve project performance. Full article

This study explores the role of egoistic and altruistic values on green real estate purchase intention among young consumers in Canada aged between 20 and 40 years. In addition, this study examines the mediating effects of pro-environmental self-identity between social consumption motivation and green real estate purchase intention. A quantitative cross-sectional research design with an explanatory nature is employed. A total of 432 participating consumers in Canada, comprising 44% men and 48% women, with a graduate educational background accounting for 46.7%, and the ages between 24 and 35 contributing 75.2%, were part of the study, and the data collection used a survey method with a purposive sampling, followed by a respondent-driven method. Descriptive and inferential statistics were performed on the scales used for the study variables. A structural equational model and path analysis were conducted to derive the results, and the relationships were positive and significant. The study results infer the factors contributing to green real estate purchase intention, including altruistic value, egoistic value, social consumption motivation, and pro-environmental self-identity, with pro-environmental self-identity mediating the relationship. This study emphasizes the relevance of consumer values in real estate purchasing decisions, urging developers and marketers to prioritize ethical ideas, sustainable practices, and building a feeling of belonging and social connectedness. Offering eco-friendly amenities and green construction methods might attract clients, but creating a secure area for social interaction is critical. To the best of the authors’ knowledge, this research is the first to explore the role of egoistic and altruistic values on purchase intention, mainly in the housing and real estate sector, with the target consumers being young consumers in Canada. Full article

As the demand for expansive back-end systems in online applications continues to grow, novel frameworks are necessitated to address the escalating operational demands, energy consumption, and associated costs. Traditional Client–Server models, while offering centralized security and reliability, are characterized by their high deployment and maintenance expenses. Conversely, Peer-to-Peer (P2P) models, despite being cost-effective and scalable, are hindered by inherent security and data integrity challenges. Moreover, the lack of a central authority in P2P systems complicates a definitive resolution of scenarios involving stakes, where users cannot withdraw without incurring a tangible loss. In this research work, a hybrid back-end framework is introduced, combining the advantages of both models through the utilization of cryptographic algorithms and Secure Multi-Party Computation (MPC) protocols. The baseline solution is lightweight and fully composable, making it capable of utilizing different more complex slot-in MPC techniques. The proposed framework’s effectiveness is demonstrated through a simplified two-player Spades game, although it is fully generalizable to any application. Evaluations across multiple case studies reveal substantial performance enhancements compared to conventional approaches, particularly post-initialization, highlighting the scheme’s potential as a cost-effective, energy-efficient, and secure solution for modern online applications. Full article

An intrusion detection system (IDS) is a crucial element in cyber security concerns. IDS is a safeguarding module that is designed to identify unauthorized activities in network environments. The importance of constructing IDSs has never been this significant with the growing number of attacks on network layers. This research work was intended to draw the attention of the authors to a different aspect of intrusion detection, considering privacy and the contribution of the features on attack classes. At present, the majority of the existing IDSs are designed based on centralized infrastructure, which raises serious concerns about security as the network data from one system are exposed to another system. This act of sharing the original network data with another server can worsen the current arrangement of protecting privacy within the network. In addition, the existing IDS models are merely a tool for identifying the attack categories without analyzing a further emphasis of the network feature on the attacks. In this article, we propose a novel framework, FEDXAIIDS, converging federated learning and explainable AI. The proposed approach enables IDS models to be collaboratively trained across multiple decentralized devices while ensuring that local data remain securely on edge nodes, thus mitigating privacy risks. The primary objectives of the proposed study are to reveal the privacy concerns of centralized systems and identify the most significant features to comprehend the contribution of the features to the final output. Our proposed model was designed, fusing federated learning (FL) with Shapley additive explanations (SHAPs), using an artificial neural network (ANN) as a local model. The framework has a server device and four client devices that have their own data set on their end. The server distributes the primary model constructed using an ANN among the local clients. Next, the local clients train their individual part of the data set, deploying the distributed model from the server, and they share their feedback with the central end. The central end then incorporates an aggregator model named FedAvg to assemble the separate results from the clients into one output. At last, the contribution of the ten most significant features is evaluated by incorporating SHAP. The entire research work was executed on CICIoT2023. The data set was partitioned into four parts and distributed among the four local ends. The proposed method demonstrated efficacy in intrusion detection, achieving 88.4% training and 88.2% testing accuracy. Furthermore, UDP has been found to be the most significant feature of the network layer from the SHAP analysis. Simultaneously, the incorporation of federated learning has ensured the safeguarding of the confidentiality of the network information of the individual ends. This enhances transparency and ensures that the model is both reliable and interpretable. Federated XAI IDS effectively addresses privacy concerns and feature interpretability issues in modern IDS frameworks, contributing to the advancement of secure, interpretable, and decentralized intrusion detection systems. Our findings accelerate the development of cyber security solutions that leverage federated learning and explainable AI (XAI), paving the way for future research and practical implementations in real-world network security environments. Full article

Counterfeit products cause financial losses for both the manufacturer and the enduser; e.g., fake foods and medicines pose significant risks to the public’s health. Moreover, it is challenging to ensure trust in a product’s supply chain, preventing counterfeit goods from being distributed throughout the network. However, fake product detection methods are expensive and need to be more scalable, whereas a unified traceability system for packaged products is not available. Therefore, this research proposes a product traceability system, named Trusted Traceability Service (TTS), using Blockchain and Self-Sovereign Identity (SSI). The TTS can be incorporated across diverse industries because of its generic and manageable four-layer product packaging strategy. Blockchain-enabled SSI empowers distributed nodes, to verify them without a centralized client–server authorization architecture. Moreover, due to its distributed nature, the proposed TTS framework is scalable and robust, with the use of web3.0 distributed application development. The adoption of Fantom, a public blockchain infrastructure, allows the proposed system to handle thousands of successful transactions more cost-effectively than the Ethereum network. The deployment of the proposed framework in both public and private blockchain networks demonstrated its superiority in execution time and number of successful transactions. Full article

Given the suboptimal responses to medication and cognitive behavioral therapies in the treatment of post-traumatic stress disorder (PTSD), new approaches are needed. Background/Objectives: Therapies that include a somatic component such as Emotional Freedom Techniques (EFT) and Eye Movement Desensitization and Reprocessing (EMDR) have demonstrated efficacy in the treatment of PTSD in numerous clinical trials. This case series introduces the Trauma Reintegration Process (TRP), a psychotherapeutic process developed by the author that can be combined with somatic therapies to enhance their effectiveness, especially in patients with dissociation. Methods: This case series describes the use of TRP in combination with EFT, an energy-based somatic treatment that engages the meridian system of the body through gentle tapping on acupressure points. TRP uses EFT in combination with a focused guided imagery sequence. This case series describes the treatment of two patients: a 20-year-old woman who experienced PTSD and somatic symptoms following a serious motor vehicle accident (MVA) and a 45-year-old woman with a history of severe abuse as a child as well as adult trauma who had also been in a serious MVA. The cases contrast the way TRP can be applied in patients with single versus multiple traumas and who experience dissociation. Results: In both cases, EFT treatment stalled when the patient dissociated. After TRP was introduced, however, the EFT treatment regained momentum, leading to significant improvement in PTSD symptoms including a reduction of nightmares and flashbacks and resolution of other somatic symptoms. Conclusions: The trauma reintegration process (TRP) in combination with EFT has the potential to assist in the memory processing of patients with dissociation and complicated trauma presentation without retraumatizing the client and causing further distress or dissociation. In addition, it provides the patient with a self-empowering method to alleviate any additional traumatic sequelae. Full article

Apnoea may be induced by pharmacological or ventilatory measures in animals under general anaesthesia to prevent motion blur on thoracic computed tomography (CT) sequences. The effectiveness of such methods has previously been reported in terms of CT image quality but not in the success of apnoea induction. Therefore, the purpose of this study was to evaluate the efficacy of two different methods used to induce apnoea. A total of 61 client-owned dogs undergoing general anaesthesia for thoracic CT were randomised to group M (n = 30) and group V (n = 31). In group M, midazolam 0.2 mg kg⁻¹ was administered by rapid intravenous injection. In group V, dogs were mechanically ventilated to maintain normocapnia, before pausing the ventilator for image acquisition. Apnoea was induced in 77% of dogs in group M and 94% in group V (p = 0.08). The onset of apnoea was quicker and of a longer duration in group V (p < 0.001). Changes in cardiorespiratory parameters and the degree of atelectasis were greater following midazolam administration. For these reasons, the authors recommend interruption of mechanical ventilation to induce apnoea in suitable dogs, as it enables the period of apnoea to be more controlled and repeated if required. Full article

This study explores the potential of the Metaverse in designing trade-fair stands for the exhibition of products and services related to the textile sector, with a particular focus on upholstery fabrics. The primary aim is to enhance relations between manufacturers and customers by leveraging virtual environments. This research is part of a broader investigation into the applications of the Metaverse within the framework of Industry 5.0, emphasizing design aspects and user engagement. The applied methodology seeks to extend the functionalities of traditional physical stands while offering a viable alternative for the promotion and sale of textile products. To create the digital environment, the Metaverse platform, Spatial.io, and its Spatial Toolkit—featuring a Unity-based template which allows for the more efficient editing of scenarios in their three-dimensional aspects—were employed. Although the template is subject to certain limitations imposed by Spatial, such as restricted access to Unity’s full capabilities, these constraints were mitigated through effective programming. This enabled the incorporation of a texture selector, allowing users to combine and visualize fabric options dynamically. The authors of this article have designed a virtual stand in alignment with client specifications by applying compositional resources grounded in basic design principles of modernity and simple structural systems. This virtual stand was tested at the Habitat Fair in Valencia 2024. The results demonstrate the promising potential of these emerging technologies in advancing the capabilities of the textile sector. Full article

Unprecedented levels of air pollution in our cities due to rapid urbanization have caused major health concerns, severely affecting the population, especially children and the elderly. A steady loss of ecological balance, without remedial measures like phytoremediation, coupled with alarming vehicular and industrial pollution, have pushed the Air Quality Index (AQI) and particulate matter (PM) to dangerous levels, especially in the metropolitan cities of India. Monitoring and accurate prediction of inhalable Particulate Matter 2.5 (PM2.5) and Particulate Matter 10 (PM10) levels, which cause escalations in and increase the risks of asthma, respiratory inflammation, bronchitis, high blood pressure, compromised lung function, and lung cancer, have become more critical than ever. To that end, the authors of this work have proposed a federated learning (FL) framework for monitoring and predicting PM2.5 and PM10 across multiple locations, with a resultant impact analysis with respect to key health parameters. The proposed FL approach encompasses four stages: client selection for processing and model updates, aggregation for global model updates, a pollution prediction model with necessary explanations, and finally, the health impact analysis corresponding to the PM levels. This framework employs a VGG-19 deep learning model, and leverages Causal Inference for interpretability, enabling accurate impact analysis across a host of health conditions. This research has employed datasets specific to India, Nepal, and China for the purposes of model prediction, explanation, and impact analysis. The approach was found to achieve an overall accuracy of 92.33%, with the causal inference-based impact analysis producing an accuracy of 84% for training and 72% for testing with respect to PM2.5, and an accuracy of 79% for training and 74% for testing with respect to PM10. Compared to previous studies undertaken in this field, this proposed approach has demonstrated better accuracy, and is the first of its kind to analyze health impacts corresponding to PM2.5 and PM10 levels. Full article

Existing research shows some links between wilderness therapy outcomes and familial functioning. However, wilderness therapy programs do not agree on what kind of caregiver involvement is required to improve adolescent program outcomes, nor has research examined different types of family engagement and their impact on adolescent treatment outcomes. Thus, the present study explored the research question: Does caregiver engagement in adolescent wilderness therapy foster improved outcomes? The study sample consisted of 4067 adolescent wilderness therapy clients from 12 different wilderness therapy programs. Using standardized measures and multilevel structural equation modeling, the authors found that caregiver program participation significantly predicted adolescent mental health outcomes of the program, suggesting that the more caregivers were involved in family interventions during the program, the more likely their adolescent child was to improve in the program. The study also found that greater caregiver effort predicted greater mean change in adolescent mental health outcomes of wilderness therapy. This study suggests the importance of enhancing familial interventions in adolescents’ wilderness therapy programs in order to improve adolescent outcomes. Given findings from this study, wilderness therapy programs should consider expanding the ways that they involve families in treatment in order to optimize adolescent outcomes. Full article

The article addresses the issue of the level of trust in the Catholic clergy in Poland among the youngest adult Catholics. The authors formulate their conclusions on the basis of a literature review and their own extensive research conducted among young adult Catholics born after 1995 (Generation Z). The research focused on the level of trust assessed with regard to the hierarchical division of the clergy in the Catholic Church as well as scandals involving priests exposed in recent years. The performed analyses took into account the level of religious commitment of young Catholics and their attitudes towards the role of the hierarchical Church in solving their problems. The research results indicate a significant level of trust in the Pope, a slightly lower level of trust in parish priests, and a very low level of trust in bishops and the institution of the Catholic Church in general. The decisive majority of those following religious observances and declaring compliance with the moral principles in line with Church teachings maintain trust in the institution of the Church. The final conclusions point to the need to manage the trust of the faithful as beneficiaries and clients of religious organisations such as the Church. Full article

The current cybersecurity ecosystem is proving insufficient in today’s increasingly sophisticated cyber attacks. Malware authors and intruders have pursued innovative avenues to circumvent emulated monitoring systems (EMSs) such as honeypots, virtual machines, sandboxes and debuggers to continue with their malicious activities while remaining inconspicuous. Cybercriminals are improving their ability to detect EMS, by finding indicators of deception (IoDs) to expose their presence and avoid detection. It is proving a challenge for security analysts to deploy and manage EMS to evaluate their deceptive capability. In this paper, we introduce the Hydrakon framework, which is composed of an EMS controller and several Linux and Windows 10 clients. The EMS controller automates the deployment and management of the clients and EMS for the purpose of measuring EMS deceptive capabilities. Experiments were conducted by applying custom detection vectors to client real machines, virtual machines and sandboxes, where various artifacts were extracted and stored as csv files on the EMS controller. The experiment leverages the cosine similarity metric to compare and identify similar artifacts between a real system and a virtual machine or sandbox. Our results show that Hydrakon offers a valid approach to assess the deceptive capabilities of EMS without the need to target specific IoD within the target system, thereby fostering more robust and effective emulated monitoring systems. Full article