Child sexual abuse (CSA) in sport remains a focal issue within Australia's national safeguarding agenda, prompting calls for more comprehensive, system-oriented prevention strategies. Football, the most widely participated organised sport among Australian children and adolescents, offers a representative context for examining CSA prevention and management across diverse communities and governance structures. The aim of this study was to understand the control structure of the current safeguarding system in football in Australia using the Systems Theoretic Accident Model and Processes (STAMP). A STAMP control structure was developed through a multi-phase validation process. Nineteen subject-matter experts (14 females, 5 males; mean age=46.1, SD=10.8) with an average of 5.8years (SD=7.6) in their current safeguarding roles and a further average 10years (SD=10.8) of related experience, recruited through targeted sampling across multiple levels of the safeguarding system, participated in the study. The resulting control structure model included 161 actors and organisations across 7 hierarchical levels of the broader sports system, 120 control mechanisms, and 94 feedback mechanisms across six hierarchical levels. The STAMP control structure supports a systems-thinking understanding of risk propagation and highlights how structural vulnerabilities and control mechanisms can contribute to safeguarding inadequacies. The developed control structure enables the identification of structural vulnerabilities, supports the detection of leading indicators of CSA, and informs systemic safeguarding reform. By integrating actionable feedback, the model promotes adaptive learning and a shift from compliance-driven reporting to proactive, system-wide responsiveness.

Programmable amylose architectures via α-glucan phosphorylase coupling: From process variables to structure-property map.

Tropical forests are often problematic for states. They have been described as both zones of refuge and frontiers and their ‘unruliness’ has justified state intervention throughout the centuries. Currently, forest areas and their governance are impacted by transnational conservation and extractive frontiers. Yet, I ask whether remote mountainous forestlands still provide a zone of refuge free of state control. If they do, what is the relationship between the (possibly) spatially overlapping concepts of frontier and zone of refuge? I examine this question through an ethnographic case study of the forest in Ranomafana National Park, in the south-east of Madagascar. I analyse the state-controlling versus state-evading dynamic in the region, beginning with the refugees escaping the Merina Empire, continuing with colonial resource extraction and forest reserve creation during the 1947 uprising, and finally focusing on the violent cycles in the 2010s–2020s, involving artisanal gold mining, banditry and an increasing militarisation of conservation. The study problematises the conventional understanding of gold mining and conservation as rivals by showing that as commodity frontiers both advance territorialisation and the elimination of the zone of refuge. In Ranomafana, the interplay between conservation and other commodity frontiers has accelerated this process: conservation enclosure has removed local structures of land control and care, making way for the gold frontier, leading to a violent competition over the land, and ultimately eroding the refuge and dispossessing local peasants. The results contribute to the literature on frontiers and state-building by clarifying that zones of refuge exist due to a lack of territorial authorities and frontiers because of an excess of them, thus making them two opposite processes at the edge of state control.

Design and fabrication of complex quartz glass samples with a negative Poisson's ratio effect

From roads to oceans: Pollution pathways of end-of-life tires in coastal and marine environments.

Understanding program execution and analyzing algorithm efficiency are essential yet challenging tasks for students and developers. The system provides a multi-panel interface consisting of a code editor, a node-based graphical visualization of execution flow, and a step-by-step textual explanation of program behavior. The proposed system processes the input code only after it is fully written and syntactically correct, ensuring accurate parsing and reliable output. Once validated, the system will identify control structures such as loops, conditional statements, and recursion, and generate a node-based execution graph that illustrates the program flow dynamically. Each node represents a computational step, enabling users to trace execution in a structured and visual manner. In addition, the system incorporates an automated complexity analyzer that determines time complexity (e.g., ) and space complexity (e.g., ) based on detected patterns and nesting levels. The visualizer supports both general Java programs and Data Structures and Algorithms (DSA), making it suitable for educational, debugging, and analytical purposes. Unlike existing tools, the proposed system integrates node-based visualization, real-time execution tracing, and automated complexity analysis in a single platform supporting both general Java programs and DSA problems.

The Dynamic Voltage Restorer is a custom power device employed to alleviate voltage issues at load terminals. In today's world, power quality has emerged as a significant concern. This is particularly true with the advent of advanced devices that are highly sensitive to the quality of the power supply. Power quality issues manifest as deviations in voltage, current, or frequency, leading to failures in end-user equipment. A prominent issue addressed here is power sag. To tackle this challenge, custom power devices are implemented. Among these devices is the Dynamic Voltage Restorer (DVR), recognized as the most efficient and effective modern custom power device utilized in power distribution networks. The DVR injects the necessary voltage in series with the supply voltage via an injection transformer to correct the voltage amplitude, phase, and harmonic components in the line. This paper discusses the development, simulation, and analysis of a Dynamic Voltage Restorer (DVR) using MATLAB/SIMULINK. To improve the voltage sag restoration capability of the DVR, this paper focuses on the creation of a control structure utilizing a Discrete PWM pulse generator. Furthermore, this paper explores a new control algorithm based on the abc to dq0 transformation for pulse generation. The results indicate that the developed DVR possesses a strong capability to restore voltage levels during sag conditions.

A sliding mode active disturbance rejection tracking control scheme based on the Smith predictive control structure is proposed for the front steering wheel of tractors, aiming to address the challenges of time delay and unknown disturbances in the angle tracking process. In the control system design, the effects of time delay and disturbances on the angle tracking performance are thoroughly considered, based on the established steering system model. A time delay processing structure is designed based on the Smith predictive control principle, and linear extended state observer is designed to realize synchronous estimation for the un-delayed angle output and the controller output. A simple Sliding Mode Controller (SMC) is introduced to replace the linear feedback controller in active disturbance rejection control (ADRC) to improve the accuracy and disturbance rejection performance. Simulation charts and performance evaluating indexes show that the proposed control method has obvious advantages in tracking accuracy, robustness and disturbance rejection in comparison with other methods. The angle tracking error is no more than 0.055rad even under the interference of white noise signal. The proposed method effectively mitigates the impact of time delay and disturbance, it can significantly enhance the dynamic response performance of the steering system.

In recent years, the rapid expansion of electric vehicle (EV) charging infrastructure and the increasing penetration of renewable energy sources require highly efficient and dynamically robust power electronic interfaces. In photovoltaic (PV)-assisted EV charging stations and DC microgrids, bidirectional DC-DC converters (BDCs) are essential for managing power flow between PV arrays, battery energy storage systems, and the DC bus supplying EV chargers. This paper presents a novel voltage and current control design for a BDC operating in a PV-powered DC microgrid oriented to EV charging applications. Following a detailed mathematical model of the converter, a digital current controller and a predictive voltage regulator were developed using Model-Based Predictive Control (MBPC). The proposed cascade control structure enables accurate DC bus voltage regulation and seamless bidirectional power flow under dynamic load variations representative of EV charging and discharging scenarios. The control scheme was evaluated in MATLAB/SIMULINK® and experimentally validated through Field-Programmable Gate Array (FPGA)-based test benches using an OPAL-RT real-time (RT) simulator, integrating the RT-LAB and RT-eFPGAsim environments. The predictive controller achieved precise regulation in both buck and boost modes, reaching efficiencies of 97.07% and 98.57%, respectively. The results demonstrate that integrating MBPC with RT validation provides high performance, fast dynamic response, and computational efficiency, making the proposed approach suitable for renewable-integrated EV charging stations and next-generation DC microgrid-based mobility systems.

Measuring fast dynamic processes with dynamic light scattering over wide fields of view is critical for applications ranging from blood flow imaging to characterizing complex fluids, yet is often limited by the need for expensive, high frame rate cameras. Here, we introduce sinusoidal intensity modulation speckle imaging (SIMSI), a technique that overcomes this hardware limitation by encoding information about fast dynamics into images captured with long camera exposures. Within each exposure, we sinusoidally modulate the illumination intensity, yielding frequency selective speckle variance measurements that sample the power spectral density (PSD) of intensity fluctuations. By sweeping the modulation frequency across exposures, SIMSI maps the PSD while preserving high signal-to-noise long exposures. We fit the measured spectra with a flexible model and report a spectral cutoff frequency [Formula: see text] as a flow index. In controlled flow microfluidic phantoms, SIMSI PSD estimates agree with the reference PSD measurements from a coaligned high-speed detector, and the derived [Formula: see text] varies linearly with the imposed flow velocity ([Formula: see text]). In vivo in the mouse cortex, the SIMSI derived [Formula: see text] maps distinguish vascular compartments with distinct spectral signatures. Finally, SIMSI tracks the spatiotemporal evolution of cortical blood flow changes for ten days following ischemic stroke. SIMSI provides a robust and accessible method for wide field, frequency domain characterization of fast dynamics using standard cameras. This advance enables a richer characterization of complex systems and has wide ranging applications in biomedicine, engineering, and physics.

Formation control of unmanned surface vehicles (USVs) in complex marine environments is required to contend with strongly coupled, high-dimensional disturbances. A Multi-Agent Active Disturbance Rejection Control (MAADRC) framework is developed for this purpose. The design centers on a distributed extended state observer (DESO) coupled with a dual-channel feedback structure—NEFL-GCO and LGL-FC—that collectively maintains formation geometry. Three main ideas underpin the approach. First, a bandwidth-efficient distributed observation scheme enables agents to share disturbance estimates while using substantially less communication bandwidth. Second, an adaptive consensus compensation mechanism accommodates parameter variations as formations evolve. Third, a formation-compatible obstacle avoidance algorithm enhances reliability in congested waters. To evaluate the control structure and optimize its parameters, a multi-agent reinforcement learning (MARL) method—specifically Multi-Agent Proximal Policy Optimization (MAPPO)—is employed. The MARL agent tunes two critical parameters: observer bandwidth and nonlinear feedback gain, thereby establishing a performance baseline. After ten million training steps, the MAPPO-optimized MAADRC achieves a tracking root-mean-square error (RMSE) of 1.18 m. This value lies within 3% of the manually tuned result of 1.21 m, indicating that the bandwidth parameterization is near-optimal. Extensive simulations incorporating realistic wind, wave and current disturbances demonstrate a dynamic obstacle avoidance success rate maintaining an expected level, alongside consistently low formation tracking errors. Collectively, these findings confirm the resilience and practical utility of the proposed framework in demanding maritime settings.

With the advancement of autonomous technologies, the need for robust control strategies in unstructured environments is becoming increasingly important. The ability to track a trajectory and accurately control the motion of a robot is a key aspect of mobile robotics and is essential if wheeled mobile robots (WMRs) are to successfully perform tasks and function in the real world. Due to the complex and unstructured working environments, the control systems of WMRs must deal with difficulties such as extreme non-linear behaviors of the dynamic systems, unmodeled parameters of the systems, and external disturbances. This paper presents an adaptive fuzzy gain scheduling PID controller that addresses the challenges posed by structured uncertainties like kinematic wheel slips, random actuator noise, and external disturbances. The controller is based on a robust cascaded control structure that can be used for tracking the desired trajectory. The robustness of the controller is ensured by uniformly ultimately bounded analysis. The control system incorporates adaptive fuzzy logic and PID control to achieve a more advanced level of trajectory-tracking control. The control systems enhance fuzzy logic and PID control with an adaptive capability aimed at improving the systems' robustness against external disturbances. Changes in the robot dynamics or the environment may happen, but the controller can adjust its parameters in real time and achieve the desired result due to the controller's adaptation mechanism. The efficacy of the controller is validated using extensive simulations for tracking complex lemniscate (∞) curves. The results are compared with conventional PID and adaptive dynamic control methods to demonstrate that the proposed controller reduces the RMS tracking error. The results clearly demonstrate that the controller can reject disturbances while achieving precise navigation even for 100% variations in the parameters. The results presented in this paper provide a computationally efficient framework to bridge the gap between kinematics and dynamics for real-time robotic applications.

Conjugated conductive metal-organic frameworks (MOFs) have garnered widespread attention in the field of optoelectronics due to their excellent electrical conductivity and unique porous structures. Currently, the interaction between MOF materials and semiconductors predominantly relies on van der Waals forces, which weaken the transport efficiency of interfacial carriers and limit their application in the field of photodetectors. Here, we constructed a ZnO/conjugated conductive MOF core-shell array through in situ growth and successfully fabricated a position-controllable self-powered UV photodetector. Our results confirm that the ordered and controllable microrod array structure can effectively reduce charge hopping at disordered interfaces, promote directional carrier migration, and significantly enhance the photodetector's light absorption efficiency. Furthermore, the conjugated conductive MOFs, which serve as a surface passivation transport layer, function as a functional interface to effectively passivate the surface defects of ZnO, reduce the carrier trapping efficiency, and improve the fast-response characteristics of the device. It is noteworthy that the photodetector fabricated via the in situ growth method achieved a rapid response with a rise time of 1.062 ms and recorded a maximum photovoltaic responsivity of 3109 V/W. This study offers a new perspective for the broader integration of emerging MOF materials into advanced optoelectronic devices.

Islanded photovoltaic microgrids with limited inertial support can undergo steep frequency excursions after sudden generation loss or abrupt load changes. This paper develops and evaluates a synthetic inertia strategy supported by a supercapacitor energy storage unit for fast frequency containment in this type of system. The proposed approach commands rapid active-power injection or absorption from the measured rate of change of frequency, thereby emulating the immediate inertial contribution usually associated with rotating machines while preserving a simple and physically interpretable control structure. The supercapacitor is represented through a resistance–capacitance model that includes equivalent series resistance and is interfaced through a bidirectional buck–boost power converter subject to practical current, voltage, and power limits. Rather than claiming a fundamentally new storage-support concept, the contribution of this paper lies in providing a transparent and constraint-consistent benchmark that integrates measured operating profiles, explicit supercapacitor limits, hybrid frequency–RoCoF support, and stress-aware comparative assessment under a common set of plant assumptions. The methodology is assessed in time-domain simulations under representative benchmark disturbances, including an approximately ten percent photovoltaic generation loss, a ten percent load increase, and a combined event. Performance is evaluated through the peak rate of change of frequency, frequency nadir, integral error indices, time outside the admissible band, and supercapacitor stress indicators such as current peaks, voltage depletion, and energy throughput. An additional non-ideal assessment is also included to examine the behavior of the RoCoF-based support law under bounded frequency-measurement perturbations and delayed control action. A complementary variability-driven case based on a highly fluctuating measured irradiance window is also used to examine the behavior of the adaptive energy-management mechanism under repeated photovoltaic-power variations. A local small-signal analysis is also included to show that the selected gain region is dynamically plausible in the unsaturated regime. The results show that the proposed adaptive hybrid strategy improves the overall frequency response while maintaining admissible supercapacitor operation, thus providing a stronger methodological basis for rapid frequency support in islanded photovoltaic microgrids.

ABSTRACT Governance of sustainable development increasingly relies on voluntary standards and commitments, the credibility and effectiveness of which hinge on accountability—ensuring actors align with shared goals and follow through on them. However, voluntary initiatives operate outside traditional control structures and blend elements of state, market, and community governance. This study examines how accountability is constructed and practiced through the lens of accountability logics. Using Finland's Commitment 2050 platform as a case, it analyzes how bureau–legal, economic–managerialist, and community logics shape the motivations, standards, processes, and consequences of account‐giving. The findings indicate that commitment‐based accountability emerges from the shifting and often uneven balance between these logics. While Commitment 2050 fosters multiple motivations and relations, accountability remains largely unrewarded and unsanctioned. This flexibility can broaden participation but weaken effectiveness and legitimacy. Future studies should examine how logic configurations evolve and how voluntary initiatives can achieve credible flexibility.

Governments allocate substantial financial resources to secondary education to enhance learning quality and institutional development. These resources require prudent management through effective financial control systems to ensure accountability, transparency, and optimal utilization. However, audit reports in public secondary schools in Kenya persistently reveal financial mismanagement, weak procurement practices, inadequate infrastructure, and recurring fiscal crises. This study examined how financial control practices shape financial management performance in public secondary schools in Kenya. The study was anchored in Systems Theory. A concurrent nested design was employed within a mixed-methods research approach. The target population comprised 239 public secondary schools in Kericho County, from which a stratified sample of 72 schools (30%) was selected. Units of observation included 72 principals, 72 bursars, 72 student presidents, one County School Auditor, and 24 Boards of Management chairpersons. Stratified, purposive, and simple random sampling techniques were utilized. Data were collected through questionnaires, interview guides, and document analysis. Instrument validity was established through content and construct validation, while reliability was assessed using Cronbach's alpha. Quantitative data were analyzed using inferential statistical techniques; qualitative data were analyzed thematically and presented through tables, figures, and emergent themes. Findings revealed weak implementation of financial management policies, limited stakeholder involvement, and inadequate enforcement of financial control mechanisms across many secondary schools. The study concluded that effective financial control significantly influences financial management outcomes in public secondary schools. It recommends that the Ministry of Education and Boards of Management strengthen financial control structures, clearly delineate the authority and responsibilities of school bursars within institutional hierarchies, and enhance stakeholder participation in financial oversight. This study contributes original empirical evidence underscoring the critical role of robust financial control systems in advancing accountability and sound financial management in public secondary schools.

China’s expanding engagement has reconfigured established patterns of regional interaction that historically reflected India’s predominant influence, without necessarily constituting a formalised structure of hierarchical control. This research paper analyses China’s increasing influence in Nepal and Bhutan via economic engagement, infrastructural diplomacy, political alignment, and territorial assertiveness, evaluating its consequences for India’s national security and regional status. The Belt and Road Initiative (BRI), more cooperation on security issues, and more diplomatic activity in Nepal have made Kathmandu less dependent on New Delhi. This has made it easier for Beijing to strengthen its political and strategic ties. China’s claim to territory in Bhutan, especially over Doklam and Sakteng, as well as its 2021 three-step plan to resolve the border issue, show that China is trying to weaken India’s power and shift the balance of power in the Himalayas. Through qualitative analysis of policy documents and scholarly literature, the study illustrates how Nepal and Bhutan are utilising a hedging strategy to enhance their autonomy amid the intensifying Sino-Indian rivalry. Instead of implying a total erosion of India’s standing, the study contends that the expansion of Chinese engagement has diminished the exclusivity of India’s influence while simultaneously introducing heightened strategic complexity into the management of frontier regions. It ends by outlining policy options for India to rebuild confidence, boost connectivity, and engage in proactive diplomacy to keep its strategic power in the Himalayan area.

This study examines the influence of Blockchain Technology, Internal Control, and Company Size on Audit Report Lag (ARL) in manufacturing companies listed on the IDX Syariah for the 2021-2025 period, focusing on the potential of digital innovation and oversight mechanisms to enhance financial reporting efficiency. Utilizing a quantitative approach with multiple regression analysis, data were collected through purposive sampling from the annual reports of issuers consistently listed in the sharia index. The results indicate that, both partially and simultaneously, Blockchain Technology, Internal Control, and Company Size have no significant effect on audit report lag. The very low Adjusted R-squared value suggests that the adoption of blockchain technology and internal control structures is currently still administrative or a matter of regulatory compliance, thus failing to fundamentally transform conventional substantive audit procedures. This research provides a contribution to regulators and audit practitioners to accelerate the development of digital-based audit standards and encourage the strengthening of internal control quality so that it can provide a tangible contribution to financial reporting efficiency in the Indonesian sharia capital market.

To address the inherent underactuation of active suspension systems under bounded external disturbances, a robust ride quality control strategy is developed within the high order fully actuated (HOFA) system framework. Departing from conventional active suspension controllers formulated in a first-order state-space framework, this study revisits the problem from the perspective of high-order system dynamics. By incorporating auxiliary control inputs, the original high-order suspension dynamics are structurally decoupled and reformulated into an equivalent fully actuated form. Based on the reconstructed fully actuated model and employing the direct parameter method within the HOFA framework, a robust stabilization controller for vehicle ride comfort regulation is devised while attenuating bounded external disturbances via a robust compensatory term. The proposed framework preserves the system’s high-order physical properties and enables explicit controller design, significantly simplifying the control structure and stability analysis. Furthermore, rigorous Lyapunov-based analysis theoretically guarantees the global stability of the closed-loop system, with all state variables converging to an arbitrarily small neighborhood of the desired equilibrium. Finally, extensive numerical simulations, corroborated by analytical investigations, confirm the validity and superior performance of the proposed method.

This research introduces a new blackboard control mechanism designed to address the weaknesses of conventional systems in managing complex, multilayered problem domains. Existing approaches are constrained by rigid, sequential control structures and limited scalability, making them unsuitable for environments that require adaptive and flexible decision-making. The proposed mechanism provides a standardized coordination framework capable of prioritizing several primary problems along with their associated subproblems. As a proof of concept, the control mechanism is applied to the domain of sustainable timber harvesting, a field characterized by interdependent tasks such as inventory assessment, growth prediction, ecological impact mitigation, and strategic tree selection. The mechanism supports dynamic problem prioritization according to a policy-based technique, allowing the system to adapt to progressing problem-solving needs. This study demonstrates the potential of an improved blackboard control mechanism to enhance decision support in complex, real-world domains.