Guidance Framework Research Articles

Green career education and guidance through the perceptions and experiences of career practitioners in English secondary schools.

The transition to a low carbon economy, climate change mitigation and adaptation, and nature restoration are expected to lead to a transformation of economic sectors. This will require a growth in green skills, a receptiveness to green roles and an understanding of the potential greening of all sectors. Plant suggests that green career education and guidance could provide the bridge between the emerging greener labour market and career development in schools. This article presents inductive qualitative research, using semi-structured interviews and reflexive thematic analysis (RTA) to explore the perceptions of career practitioners in English secondary schools revealing a broad spectrum of understanding and approach. A nascent green career education and guidance framework has emerged from a synthesis of existing literature and the research findings.

Tracing the trajectory of vocational education research on career adaptability: a bibliometric study

Reports on the evaluation of the most relevant themes on career adaptability through bibliometric analysis using the keyword “career adaptability” as its input aims to get a comprehensive view of current issues and trends in career adaptability research. The VOSviewer software in collaboration with Microsoft Excel and Open Refine was adopted as tool to visualize the network of authors, countries of origins and keywords in publication data mined on June 19 2022. The analysis found a total of 728 scientific publication from 1981 to 2022. The results show that in the last 15 years the number of career adaptability publications has grown very significantly. The United States is a major country contributing of publications. Author analysis presents Nota L as the most prolific author, while Savickas L is a prominent author while Guan Y is the writer with the best writing network with 8 other writers on career adaptability. Academic Press Inc. dominates the publication with 22.94% of it is production. Keyword analysis shows that career adaptability studies in the last two decades have focused on the theme of career planning through the establishment of a career guidance framework that aims to create prosperity.

Balancing Athletic and Academic Excellence: A Quantitative Study of Student-Athletes' Time Management Strategies

This study focuses on the unique challenges faced by student-athletes and explores how they find a balance between competitive sports and academic pursuits. Through a one-year longitudinal study of 360 college athletes from a variety of sports and academic backgrounds, we deeply analyzed the relationship between time management strategies and academic achievement, athletic performance, and psychological health. The study used quantitative research methods to analyze the data and revealed several key time management strategies that were associated with significant improvements in academic and athletic performance. In particular, we discovered a novel "flexible focus" strategy that enabled students to quickly switch their attention between learning and training while maintaining high efficiency. In addition, the study found the moderating effects of social media use, sleep patterns, and nutritional intake on time management effects. Based on these findings, we proposed a comprehensive "dual-track development model" to provide a practical guidance framework for student-athletes, coaches, and educators. This model is not only applicable to traditional college sports programs, but also considers the emerging field of e-sports, providing a new perspective for understanding and supporting the comprehensive development of student-athletes in the 21st century. The results of this study have important implications for higher education policy, athletic training program design, and the development of student support services, providing an empirical basis for promoting the comprehensive development of student-athletes.

Ethics in social listening in infodemic management in health emergencies

Abstract Issue During the COVID-19 pandemic and subsequent outbreaks, health organizations have increased the use of social listening to inform infodemic management and outbreak response activities. This demonstrated the need to provide ethical guidance to organizations, and individuals engaging in social listening practices before, during and after public health emergencies, whilst protecting human rights. Description of the problem Social listening as a public health activity draws on analysis of conversations in social media, internet platforms, and feedback from geographically localized communities. Infodemic insights are generated rapidly, to support agile action by health organizations that improves outbreak response, health information delivery, community engagement, or reduction of unintended harm experiences by communities. Social listening involves use of social media and internet trace data, which were traditionally not used in public health for understanding community expressions, WHO convened a panel of experts to develop a framework on ethical considerations for social listening in infodemic management to provide recommendations for health authorities and researchers on practical tools that support setting up new data analysis and use of insights hereto not used in routine. Results The guidance framework has been structured into segments that vary from ethical principles and challenges in social listening and generation of infodemic insights, alignment with human rights, substantive principles, procedural principles, and practical guidance for translating these principles into real-world practice. Lessons This guidance aims to illuminate the intricate ethical dimensions of social listening and stress the urgent need for ethical guidance in this realm. The framework is a comprehensive inquiry of the ethical scope in social listening, providing valuable insights, practical guidance, and case studies to enhance understanding of this critical global health issue. Key messages • While essential, social listening and infodemic insights come with ethical risks, including potential harm to populations in vulnerable situations, erosion of trust, and misuse of data. • This ethical framework will govern social listening practices and ensure responsible and ethical social listening.

Prevention of Trafficking in Organs, Tissues, and Cells.

Trafficking in human organs, cells, and tissues has long been a source of concern for health authorities and professionals, and several international ethical guidance documents and national laws have affirmed the prohibition of trade in these substances of human origin (SoHOs). However, despite considerable attention to the issue of organ trafficking, this remains a substantial and widespread problem internationally. In contrast, trafficking in cells, tissues, and medical products derived from SoHOs has received comparatively little attention, and the extent and nature of such trafficking remain largely unknown. Consequently, as part of the 2023 Global Summit on Convergence in Transplantation held in Santander, Spain, an ethics working group was assigned the task of formulating actionable recommendations to support the prevention of trafficking in all SoHOs. In reporting on this work, we review factors that may influence the persistent trafficking of SoHOs, explore the potential difficulties associated with the collection and reporting of data about suspected trafficking activities, and argue that more practical and consistent guidance, training, and regulatory frameworks are needed internationally to support effective reporting, sharing of data, and collaborative responses to suspected trafficking cases. We also discuss the importance of psychosocial evaluation of living donors as a strategy to detect and prevent organ trafficking and strive to advance the implementation of this well-established recommendation by outlining minimum standards for psychosocial evaluation of living donors.

Boosting Career Success: Innovative Behavioral Measures for Guiding Saudi Secondary School Graduates

This study developed and validated a comprehensive behavioral measure for career guidance among secondary school graduates in Saudi Arabia, aiming to integrate soft skills, personality traits, attitudes, and cognitive factors to fill gaps in existing career guidance frameworks. Using a cross-sectional design, data were collected from 814 secondary school students (M_age = 16.47) from diverse urban (n = 407) and rural (n = 407) settings in Saudi Arabia. Multigroup latent profile analyses (LPA) were employed to identify distinct career decision-making profiles among students. The study explored whether urban and rural students exhibited different patterns of engagement in career guidance behaviors. Three distinct engagement profiles were identified: high, moderate, and low engagement, consistent across both settings. High engagement profiles were characterized by high self-efficacy, proactive career exploration, and low anxiety, linked to better career decision outcomes and greater satisfaction with career guidance. Variance analysis using the Games-Howell post hoc test was conducted to compare the profiles based on key behavioral measures such as self-efficacy, career exploration behavior, and anxiety. To further understand the contextual factors influencing these profiles, a multinomial regression analysis examined the impact of teacher support and resilience on career guidance engagement levels. Results indicated that higher levels of teacher support and resilience significantly predicted membership in high engagement profiles. These findings highlight the importance of incorporating behavioral components into career guidance programs, particularly those tailored to address the specific needs of urban and rural students in Saudi Arabia, ultimately supporting the broader educational and workforce development goals of Vision 2030.

Juristic Differences on Salat Within the Maliki School and Its Relevance to Nigerian Muslims

Salat, or Islamic prayers, is central to Muslim devotion globally. However, different schools of Islamic jurisprudence interpret and apply Salat uniquely. The Maliki school stands out for its distinct approach, influencing how Salat is performed. In Nigeria, where Maliki jurisprudence predominates among Muslims, these differences are especially relevant. Nigeria's diverse Muslim population offers an ideal setting to explore how Maliki jurisprudence impacts Salat practice and religious identity. This study examines the unique interpretations and rulings of the Maliki school regarding Salat, focusing on prayer methodology such as mode of Iqᾱmah, Adhᾱn, recitations, Al-Qunũt, Qabd and Sadl, and evaluates their relevance to Nigerian Muslims. The research employs textual analysis and comparative jurisprudence to uncover doctrinal differences and practical implications of Maliki rulings on Salat. Empirical data from Nigerian Muslim communities shed light on how these differences affect contemporary Salat practices and perceptions. Findings revealed that Maliki jurisprudence remains influential among Nigerian Muslims, providing a foundational framework for religious guidance. Despite divergence, the core principles of Shari’ah and its sources remain intact. Conclusively, the paper emphasisesthe importance of fostering dialogue and understanding among scholars, policymakers, and religious leaders to enhance spiritual experiences and communal cohesion in Nigerian Muslim society.

Bounded Containment Maneuvering Protocols for Marine Surface Vehicles With Quantized Communications and Tracking Errors Constrained Guidance: Theory and Experiment.

A new type of containment maneuvering protocols for multiple marine surface vehicles (MSVs) is developed to follow a parameterized path in this work, where the tracking errors are constrained within finite time and the information needed to be transmitted is quantized during coordination. To achieve containment maneuvering of multiple MSVs, a two-objective coordinated control framework is proposed. For the geometric objective, by developing tan-type barrier Lyapunov functions (BLFs) and extended Lyapunov condition-based finite-time guidance laws, the performance of the parameterized line-of-sight guidance framework, including convergence speed and tracking error constraints, is improved. For the dynamic objective, based on quantized control strategy and smooth saturation functions, novel bounded containment maneuvering protocols are proposed to dramatically alleviate the burden of communications among MSVs and ensure more faster dynamic behavior on tracking the path updating speed. Both theoretical analysis and experimental tests with comparative studies illustrate the validity of the proposed containment maneuvering strategy.

Lightweight medical image segmentation network with multi-scale feature-guided fusion

In the field of computer-aided medical diagnosis, it is crucial to adapt medical image segmentation to limited computing resources. There is tremendous value in developing accurate, real-time vision processing models that require minimal computational resources. When building lightweight models, there is always a trade-off between computational cost and segmentation performance. Performance often suffers when applying models to meet resource-constrained scenarios characterized by computation, memory, or storage constraints. This remains an ongoing challenge. This paper proposes a lightweight network for medical image segmentation. It introduces a lightweight transformer, proposes a simplified core feature extraction network to capture more semantic information, and builds a multi-scale feature interaction guidance framework. The fusion module embedded in this framework is designed to address spatial and channel complexities. Through the multi-scale feature interaction guidance framework and fusion module, the proposed network achieves robust semantic information extraction from low-resolution feature maps and rich spatial information retrieval from high-resolution feature maps while ensuring segmentation performance. This significantly reduces the parameter requirements for maintaining deep features within the network, resulting in faster inference and reduced floating-point operations (FLOPs) and parameter counts. Experimental results on ISIC2017 and ISIC2018 datasets confirm the effectiveness of the proposed network in medical image segmentation tasks. For instance, on the ISIC2017 dataset, the proposed network achieved a segmentation accuracy of 82.33 % mIoU, and a speed of 71.26 FPS on 256 × 256 images using a GeForce GTX 3090 GPU. Furthermore, the proposed network is tremendously lightweight, containing only 0.524M parameters. The corresponding source codes are available at https://github.com/CurbUni/LMIS-lightweight-network.

Developing an integrated and collaborated evaluation index system for crude oil supply chains: A case study from China

The crude oil supply chain involves production, transportation, refining, marketing, storage and trade with numerous interconnected links and complex interrelationships. Enhancing the overall value of crude oil supply chains depends on the coordinated development of their upper, middle and lower reaches. However, the absence of a scientific and objective evaluation index system for collaborative development within the crude oil industry precludes identification of weak links that require improvement, thereby impeding supply chain development decision-making. This study aims to construct an integrated and coordinated development evaluation index system for crude oil supply chains, providing a crucial reference framework for scientific evaluation, guidance, and assessment of crude oil supply chains. Taking China's crude oil supply chain as a case study, this research analyzes the current state of crude oil supply chain research and employs the 5 dimensions of SCOR as the primary evaluation index to examine production, transportation, refining, marketing, storage, and trading. An evaluation index system for integrated and coordinated development of the crude oil supply chain is presented, followed by the development of an evaluation model combining the combination weighting method with the TOPSIS approach. The index system and model established in this study are applied to PetroChina. The findings indicate that PetroChina achieved the highest integration and coordination level in 2021, with a score of 0.578, attributed to optimal supply chain efficiency; conversely, the integration coordination degree in 2017 was subpar, with a score of only 0.468, primarily due to the supply chain's lack of responsiveness. This evaluation index system and model offer a comprehensive assessment of the development in each link and aspect within the supply chain, which can intuitively reflect the weak points of the supply chain and provide essential theoretical support for integrated and coordinated development of PetroChina.

Neural-Rendezvous: Provably Robust Guidance and Control to Encounter Interstellar Objects

Interstellar objects (ISOs) are likely representatives of primitive materials invaluable in understanding exoplanetary star systems. Due to their poorly constrained orbits with generally high inclinations and relative velocities, however, exploring ISOs with conventional human-in-the-loop approaches is significantly challenging. This paper presents Neural-Rendezvous—a deep-learning-based guidance and control framework for encountering fast-moving objects, including ISOs, robustly, accurately, and autonomously in real time. It uses pointwise minimum norm tracking control on top of a guidance policy modeled by a spectrally normalized deep neural network, where its hyperparameters are tuned with a loss function directly penalizing the model predictive control state trajectory tracking error. We show that Neural-Rendezvous provides a high probability exponential bound on the expected spacecraft delivery error, the proof of which leverages stochastic incremental stability analysis. In particular, it is used to construct a non-negative function with a supermartingale property, explicitly accounting for the ISO state uncertainty and the local nature of nonlinear state estimation guarantees. In numerical simulations, Neural-Rendezvous is demonstrated to satisfy the expected error bound for 100 ISO candidates. This performance is also empirically validated using our spacecraft simulator and in high-conflict and distributed unmanned aerial vehicle swarm reconfiguration with up to 20 unmanned aerial vehicles.

Requirements for Playbook-Assisted Cyber Incident Response, Reporting and Automation

Cybersecurity playbooks assume an increasingly important role as threat-specific documents for guiding operators in the context of cyber incident response. However, these playbooks are mostly unstructured or semi-structured, which significantly limits their utility when it comes to automating response and reporting steps, complying with cybersecurity directives, or sharing best practices for incident response across organisations. We thus argue that cybersecurity playbooks must transition to interoperable and machine-readable formats from generation, via management and utilisation to cross-organisational sharing. In this work, we identify and structure key requirements based on expert interviews as a first step toward this transition. From these requirements, we derive a framework for further guidance during the transition to structured security playbooks and their utilisation in a tool-assisted fashion. We discuss the implications of our framework and lessons learned before outlining directions for future research.

Dynamic Analysis and Temporal Governance of Safety Risks: Evidence from Underground Construction Accident Reports

Due to the complexity and dynamics of underground construction projects, safety risk management has experienced significant challenges restricting the sustainable development of underground space. The research on risk causal chains and risk coupling has yet to reveal the dynamic interactive characteristics of these risk factors and their temporal relationships over time. This study utilized a complex system view for safety risk analysis, using 37 accident investigation reports of underground construction projects. Combined with two novel and emerging analytical methods, temporal qualitative comparative analysis and crisp-set qualitative comparative analysis, this study discusses the temporal relationship of risk factors to the cause of accidents and explores the multi-actor coupling characteristics of management risk. The findings indicate that (1) compared with general construction projects, underground construction should pay more attention to management safety risks because they have an obvious time lag effect expressed in all accident causation paths, namely, preceding management risk, management risk, and machine/material risk cross-concurrently, and management risk initiation and (2) underground construction project management risks have three key main paths, namely, single-actor-dominated management deficiency (supervisors, owners, and subcontractors that cause management risks as a single-core actor) and dual-actor-dominated management deficiency (owner and subcontractor as dual core actors of management risk). Multi-actor-dominated management deficiency (owners, subcontractors, and supervisors are the multiple core actors of management risk). This study thus developed a temporal governance framework of underground construction safety risks based on the synergy of multi-actors and proposed risk governance strategies, such as synergistic multi-actor governance, to consider the temporal relationship of safety risk. This study further reveals the temporal and coupling characteristics of safety risks to enrich the risk casual chain theory and risk coupling theory and establish a systematic risk analysis framework for new guidance for safety and risk management for underground construction projects.

Empirical Evidence on Corporate Social Responsibility A Case Study of Chinese Companies in Pakistan

This paper investigated the state of corporate social responsibility (CSR) practices among Chinese companies operating in Pakistan. Findings reveal that while most Chinese firms have dedicated CSR programs, the strategic focus and long-term developmental impacts vary; enhancing corporate reputation rather than creating ethical value or empowering local communities was the dominant motivation. Key CSR activity areas include education, healthcare, and environmental initiatives, aligned with local socioeconomic needs. Although positive impacts are acknowledged, local stakeholders perceive CSR effects to be limited lacking strategic direction; challenges around political sensitivities, security risks, and coordination issues were highlighted. The paper advocates for a more strategic, participatory and sustainable CSR approach focused on long-term capacity building. Guidance frameworks attuned to local contexts can enable companies to balance business goals with lasting social value.

The Synergy of Financial Innovation, Corporate Social Responsibility, and HRM Morale: A Systematic Review on Their Impact on Firm Image and Business Interest

This study aims to explore the synergy between financial innovation, Corporate Social Responsibility (CSR), and Human Resource Management (HRM) morale, focusing on their collective impact on firm image and business interest. Utilizing a qualitative approach through a systematic literature review, this research synthesizes findings from recent empirical studies to provide a comprehensive understanding of how these elements interact to create a sustainable competitive advantage. The systematic review follows the PRISMA guidelines to ensure rigor and transparency in identifying, selecting, and analyzing relevant literature. The results of the study indicate that financial innovation, particularly through fintech and blockchain technologies, enhances operational efficiency and aligns with broader societal goals through sustainable finance practices. CSR is shown to significantly improve firm image by fostering trust and loyalty among stakeholders, while HRM morale is identified as a critical factor in enhancing organizational resilience, especially during crises such as the COVID-19 pandemic. The most significant finding is the synergistic relationship between financial innovation, CSR, and HRM morale, which collectively contribute to a sustainable competitive advantage that enhances firm performance and stakeholder engagement. The study concludes that integrating these elements into a cohesive strategy is essential for firms seeking long-term success in the modern business environment. The implications are significant for both theory and practice, offering a novel framework for future research and practical guidance for managers.

Exploring the Confluence of Financial Innovation, Human Resource Strategies, and Marketing Management: A Systematic Literature Review on Profit Maximization and Business Attraction

This study aims to explore the intricate relationships between financial innovation, human resource (HR) strategies, and marketing management, and how their integration drives organizational success, particularly in terms of profitability and business attraction. Utilizing a systematic literature review, the research synthesizes findings from various academic sources to provide a balanced and comprehensive understanding of these interdependencies. The methodology focuses on analyzing the existing literature to identify the conditions under which financial innovation, HR strategies, and marketing management can be most effectively integrated. The results indicate that financial innovations such as fintech and blockchain significantly enhance organizational profitability when aligned with strategic HR practices and customer-centric marketing approaches. The study further reveals that the successful implementation of these innovations requires substantial investments in employee training and adaptive marketing strategies that resonate with consumer needs. The findings underscore the importance of adopting a holistic approach, where financial innovation, HR, and marketing are treated as interconnected components of a unified business strategy. This integration not only enhances competitiveness but also positions organizations to navigate the challenges of a rapidly evolving business environment. The study offers valuable theoretical and managerial implications, providing a framework for future research and practical guidance for business leaders and policymakers on leveraging these domains for sustainable growth.

Generative AI in American and Canadian courts: a ‘training’ approach to regulation

ABSTRACT Increased usage of generative artificial intelligence (AI) within the legal profession has prompted responses from the judiciary, resulting in the issuance of various practice directives. The spectrum of these directives ranges from conservative recommendations to more radical measures demanding lawyers to disclose their use of generative AI in the preparation of legal documents or certify the absence of such software in their creation. This article explores the development of a comprehensive framework for judicial guidance on generative AI use in legal proceedings in Canada, highlighting key elements of such guidance. The author contemplates a ‘training’ approach to regulating generative AI use in legal proceedings, focusing more on the user than the technology itself. This approach emphasises the need for judicial guidance to balance constructive engagement with generative AI with lawyers’ ethical responsibilities.

Smart mechanoluminescent phosphors: A review of zinc sulfide‐based materials for advanced mechano‐optical applications

AbstractThe quest for mechanoluminescence (ML) in zinc sulfide (ZnS) spans more than a century, initially sparked by observations of natural minerals. There has been a resurgence in research into ML materials in recent decades, driven by advances in optoelectronic technologies and a deeper understanding of their luminescent properties under mechanical stress. ZnS, in particular, has garnered attention owing to its remarkable ability to sustain luminescence after more than 100,000 mechanical stimulations, positioning it as a standout candidate for optoelectronic applications. In contrast to conventional photoluminescent and electroluminescent light sources, ZnS composite elastomers have emerged as flexible, stretchable self‐powered light sources with considerable practical implications. This review introduces the development history, ML mechanisms, prototype ML devices, ZnS‐based ML material preparation methods, and their diverse applications spanning environmental mechanical‐to‐optical energy conversion, E‐signatures, anti‐counterfeiting, wearable information sensing devices, advanced battery‐free displays, biomedical imaging, and optical fiber sensors for human–computer interactions, among others. By integrating insights from ML‐optics, mechanics, and flexible optoelectronics, and by summarizing pertinent perspectives on current scientific challenges, application technology hurdles, and potential solutions for emerging scientific frontiers, this review aims to furnish fundamental guidance and conceptual frameworks for the design, advancement, and cutting‐edge application of novel mechanoluminescent materials.

A novel hybrid method integrating multi-objective optimization with emergy analysis for building renewal strategy

Building renewal has become a promising approach for improving energy efficiency and reaching carbon neutrality targets. Two renewal strategies, namely, the retrofitting of existing buildings and their demolition and reconstruction of a new one, are often explored and compared to determine which strategy is the optimal one. However, the decision is still uncertain due to the large domain space of strategies and the lack of comprehensive methods. This paper, therefore, presents a novel hybrid method to help decision-makers identify the optimal building renewal strategy based on the integration of multi-objective optimization algorithm with emergy analysis. A simulation-based non-dominated sorting genetic algorithm is developed to select the optimal retrofitting strategy, where dynamic simulation model is created in EnergyPlus software and non-dominated sorting genetic algorithm is written in Python. Then, the equivalent reconstruction strategy is projected by the optimal retrofitting strategy while meeting mandatory standards. A comparison between the optimal retrofitting strategy and the equivalent reconstruction strategy can be made by applying emergy analysis considering the whole life cycle phase. A fictional office building was chosen as a case study to illustrate the practical implementation of the proposed method. High-cost building retrofitting strategies were found to consistently yield the highest energy savings and thermal comfort, and the energy use decreased by 4.63 % to 48.25 %. The input emergy of the original building, retrofitting building and reconstruction building are 3.16E + 20 sej, 1.41E + 21 sej, and 1.46E + 21 sej, respectively, and the output emergy are 2.39E + 20 sej, 1.66E + 20 sej, and 4.76E + 19 sej. The results also indicate that the sustainability of the retrofitting strategy is better than that of the reconstruction strategy. This paper provides a guidance method and framework for decision-makers and policy-makers to identify the optimal building renewal strategy for reducing the energy use and achieving carbon peak targets.

Modifying the Health Star Rating nutrient profiling algorithm to account for ultra-processing.

To modifythe Australian and New Zealand Health Star Rating to account for ultra-processing and compare the alignment of the modified ratings with NOVA classifications and the current Australian Dietary Guidelines classifications of core (recommended foods) and discretionary (foods to limit). Data was cross-sectionally analysed for 25 486 products. Four approaches were compared to the original Health Star Rating: (1) five 'negative' points added to ultra-processed products (modification 1; inclusion approach); (2) ultra-processed products restricted to a maximum of 3.0 Health Stars (modification 2; capping approach); (3 and 4) same approach used for modifications 1 and 2 but only applied to products that already exceeded 10 'negative' points from existing Health Star Rating attributes (modifications 3 and 4, respectively; hybrid approaches). Alignment occurred when products (i) received <3.5 Health Stars and were NOVA group 4 (for NOVA comparison) or discretionary (for Dietary Guidelines comparison), or (ii) received ≥3.5 Health Stars and were NOVA groups 1-3 or core. All Health Star Rating modifications resulted in greater alignment with NOVA (ranging from 69% to 88%) compared to the original Health Star Rating (66%). None of the modifications resulted in greater alignment to the Dietary Guidelines classifications overall (69% to 76%, compared with 77% for the original Health Star Rating), but alignment varied considerably by food category. If ultra-processing were incorporated into the Australian and New Zealand Health Star Rating, consideration of ultra-processing within the broader dietary guidance framework would be essential to ensure coherent dietary messaging to Australians.