Robust Optimal Power Flow under Industrial Cyberattacks and Renewable Uncertainty

/0 Comments/in /by

The digitalization of electric-power operation couples optimal power flow (OPF) with measurement systems, communication networks and increasingly variable renewable generation. Power system operators may have to make dispatch decisions using load measurements that have been altered by false-data injection attacks. At the same time, actual renewable power generation may differ from what was forecast. When these two problems occur together, the system may need more balancing capacity than would be expected if each uncertainty were considered separately. This paper examines both effects through a scenario-based robust direct-current optimal power flow (DC-OPF) approach. The proposed model determines generator schedules and upward and downward reserves with ensuring that the system can respond to bounded combinations of corrupted load measurements and renewable forecast errors. The approach focuses on reducing their operational consequences. It assumes that the operator does not know the exact amount of corruption measurement but can define reasonable limits for measurement errors and renewable uncertainty. The study uses the publicly available PGLib-OPF v23.07 IEEE 14-bus and IEEE 30-bus networks, with additional renewable generation and cyberattack scenarios introduced for testing. The results show that the robust approach increases preventive operating costs by 0.98% for the 14-bus system and 1.97% for the 30-bus system compared with a deterministic OPF using a standard 10% balancing-reserve rule. In 3,000 out-of-sample scenarios for each network, the robust schedule avoided emergency load shedding within the defined uncertainty limits. By comparison, the deterministic approach required load shedding in 62.77% of the IEEE 30-bus scenarios, with an average of 2.56 MW and a maximum of 18.93 MW of unserved power. These results suggest that the benefit of robust OPF is not simply a change in how generation is scheduled. More importantly, it helps place reserve capacity where it can be used effectively, reducing the risk that corrupt measurements and unexpected renewable fluctuations will prevent the power system from operating within its physical limits.

Piezoelectric Materials for Piezocatalysis and Piezo-Photocatalysis: Fundamentals, Mechanisms, Materials and Environmental Applications

/0 Comments/in /by

Piezocatalysis and piezo-photocatalysis have emerged as promising approaches for environmental remediation by utilizing mechanical energy alone or in combination with light to drive redox reactions. This review systematically summarizes the fundamental principles and mechanisms of piezoelectricity, piezocatalysis, photocatalysis, and piezo-photocatalysis, with particular emphasis on charge separation and reactive species generation. Recent advances in piezoelectric materials, including conventional and emerging materials, transition-metal chalcogenides, perovskites, and layered bismuth-based materials, are discussed together with strategies for improving catalytic performance. Their applications in pollutant degradation, heavy-metal removal, water purification, disinfection, and microbial inactivation are further reviewed. Finally, current challenges and future perspectives related to material design, energy utilization, mechanistic understanding, stability, and practical application are highlighted. This review provides an integrated perspective on piezoelectric catalytic systems and their potential for sustainable environmental remediation.

Evaluating the Accuracy and Usability of an Academic Digital Information Assistant Chatbot Based on Retrieval-Augmented Generation for Academic Learning Grant Services

/0 Comments/in /by

Information services for student grant programmes require answers that are fast, consistent, and grounded in official documents, while the rules themselves change with every programme cycle. This study evaluates AIDA (Academic Digital Information Assistant), a university academic service chatbot, within the domain of an academic learning grant programme. Following a Design Science Research framework, the evaluation proceeded in two cycles. The first measured answer accuracy through the assessment of three programme administrators across 32 test questions on the dimensions of relevance, correctness, and completeness. The second measured usability through the Chatbot Usability Questionnaire administered to 76 student users. The first cycle yielded 90.6% relevance, 81.3% correctness, 90.6% completeness, and an overall pass rate of 81.3%, with inter-rater agreement between 82% and 85%. All six failing items shared a single root cause, namely timeline information that had not been updated to the current programme period; three of them were nonetheless judged relevant and complete, rendering the error difficult for users to detect. The second cycle produced a usability score of 67.72 (SD 11.93) with a reliability of 0.865, highest on ease of use and lowest on conversational naturalness and error handling. The study concludes that the principal constraint on administrative service chatbots lies not in language understanding but in the governance of content freshness, and proposes a knowledge base update mechanism tied to the programme calendar.

Environmental Impacts of Ionizing Radiation: Sources, Pathways, and Environmental Consequences

/0 Comments/in /by

Ionizing radiation is a significant physical factor that, in cases of improper exposure or the release of radioactive materials into the environment, can impact environmental quality, the health of living organisms, and ecosystem balance. These radiations originate from natural sources such as cosmic rays, radionuclides in the Earth’s crust, and radon gas as well as artificial sources resulting from medical, industrial, and nuclear activities. This article aims to examine the environmental impacts of ionizing radiation, emphasizing the fundamentals of nuclear physics and the pathways of radionuclide transport within the environment. Conducted using a literature review and a descriptive-analytical approach, the study focuses on concepts such as radioactive decay, half-life, radionuclide activity, radiation type and energy, and radiation-matter interaction. Furthermore, it investigates the dispersion and transport pathways of radioactive materials in air, water, soil, and sediments, as well as their entry into plants, animals, and the food chain. Analysis of the literature indicates that the persistence and transport of radionuclides in the environment depend not solely on their radioactive activity but also on factors such as half-life, chemical properties, soil composition, climatic conditions, and bioavailability. Additionally, exposure to ionizing radiation may, under certain conditions, cause cellular damage and biological alterations in living organisms; however, the nature and severity of these consequences depend on the absorbed dose, dose rate, type of radiation, and the biological sensitivity of the organisms. Consequently, understanding the fundamentals of nuclear physics and simultaneously examining radionuclide transport pathways is essential for a better understanding of the environmental impacts of ionizing radiation. This study can provide the necessary scientific foundation for future field research on radioactive contamination across various environmental compartments.

Implementation and Performance Evaluation of an IoT-Based Multi-Sensor Water Quality Monitoring System for Nile Tilapia Ponds Using an ESP32 Microcontroller

/in /by

Water quality strongly governs the growth, health, and survival of Nile tilapia (Oreochromis niloticus), yet many small- and medium-scale ponds are still monitored manually through periodic sampling, which is labor-intensive, infrequent, and prone to error. This study designed, implemented, and evaluated an Internet of Things (IoT)-based monitoring system that integrates seven sensors with a single ESP32 microcontroller: five water quality sensors (pH, total dissolved solids [TDS], dissolved oxygen [DO], turbidity, and temperature) and two environmental sensors (rainfall and light intensity). Following a research and development (R&D) approach with a waterfall model, the prototype transmitted data to a web-based IoT platform and displayed readings on a local OLED screen. The system was evaluated through component voltage measurements, a 7-day monitoring trial with pond water (May 4–10, 2026), a functionality test by two expert validators, and a usability test with 10 respondents. All sensors and the microcontroller operated as intended, with measured component voltages of 3.7–4.9 V. Over the trial, mean values were 26.48 °C for temperature, 7.31 for pH, 1,060.67 ppm for TDS, 3.41 mg/L for DO, and 39.68 NTU for turbidity; the persistently low DO indicated a need for supplementary aeration. The overall usability score was 83.08%, classified as “very feasible.” The results show that a low-cost, single-board multi-sensor system can provide continuous, remotely accessible records of pond conditions to support decision-making in sustainable tilapia aquaculture. Validation against calibrated reference instruments under field conditions is the recommended next step.

Effect of Environmental Temperature on the Lower Bound of the Entropic Uncertainty Relation in the Presence of Quantum Memory

/in /by

Because realistic quantum systems inevitably interact with their surroundings, understanding how environmental factors affect the entropic uncertainty relation remains a major challenge. In this work, we analyze how ambient temperature impacts the lower bound of the memory-assisted entropic uncertainty relation. We model the coupling between the system and its thermal environment using a generalized amplitude damping channel, featuring temperature-dependent parameters. Notably, we find that the uncertainty lower bound drops when the damping parameter (r) decreases, and rises when it increases. By contrast, shifting the parameter) p (yields much smaller variations. This stark difference highlights our main novel finding: in a finite-temperature environment, the lower bound of the entropic uncertainty relation is significantly more sensitive to the damping parameter (r) than to (p). Ultimately, these results offer a clearer look at how thermal reservoirs influence open quantum systems and affect practical quantum information processing.

Tumor Detection with PET and CT: A Comparative Physical Review

/in /by

Positron emission tomography (PET) is an important molecular imaging modality in oncology because it provides functional and metabolic information that complements the anatomical information obtained from computed tomography (CT). However, the ability of PET to detect tumors is fundamentally determined by several physical characteristics of the imaging system, including spatial resolution, sensitivity, image contrast, noise, photon attenuation, scatter, random coincidences, and partial-volume effects. This review aims to examine the physical basis of PET for tumor detection and to compare its principal imaging characteristics with those of CT. A comparative narrative review was conducted using relevant literature on PET physics, detector instrumentation, image formation, image-quality determinants, tumor detectability, and the physical principles of CT. The reviewed evidence indicates that PET provides high sensitivity to radiotracer distribution and functional abnormalities, making it particularly valuable for detecting metabolically active tumors. However, its relatively limited spatial resolution and susceptibility to attenuation, scatter, noise, and partial-volume effects can restrict the detection and accurate characterization of small or low-contrast lesions. In contrast, CT provides superior anatomical detail and spatial resolution through X-ray attenuation measurements but offers substantially less direct functional information. The evidence therefore indicates that PET and CT possess complementary physical capabilities: PET is primarily advantageous for functional and metabolic tumor characterization, whereas CT is superior for anatomical localization and structural delineation. Understanding these physical differences is essential for interpreting the respective strengths and limitations of PET and CT in tumor detection and for optimizing their complementary use in hybrid PET/CT imaging.

Evaluation of the Role of Local Government in Strengthening Flash Flood Disaster Mitigation Capacity in Teluk Wondama Regency

/in /by

Teluk Wondama Regency remains highly exposed to flash-flood hazards, particularly along the Wasior-Wondiboy-Rasiei corridor, where settlements, public services, transport networks, and government functions are concentrated. The 2010 Wasior flash flood demonstrated the severity of potential consequences, while current evidence indicates that mitigation capacity still requires systematic strengthening. This study evaluates the role of local government in flash-flood mitigation, identifies enabling and constraining factors, and formulates strategies to strengthen mitigation capacity. A qualitatively oriented mixed-methods approach was applied within an evaluative case-study design. Data were obtained from disaster-management, development-planning, spatial-planning, environmental, program, and budget documents; semi-structured interviews with nine purposively selected informants; field observations in Wasior, Wondiboy, and Rasiei; and descriptive quantitative scoring of 30 indicators across six mitigation-capacity dimensions. The local government has performed roles as regulator and planner, coordinator, facilitator, service implementer, development controller, and community enabler; however, these roles have not yet formed a fully integrated mitigation system. The overall capacity score was 54 of 120, equivalent to 45.0 on a 0-100 scale and categorized as less adequate. Policy-planning and spatial planning-watershed management each scored 50, whereas technical systems-early warning-evacuation and community capacity each scored 40. The principal finding is a persistent gap between normative capacity and operational functionality. Priority strategies include updating risk and disaster-management plans, strengthening inter-agency coordination, operationalizing the emergency operations center and sub-watershed-based early warning, testing evacuation networks, controlling risk-prone land use, sustaining preventive financing, and institutionalizing community preparedness.

Water Demand Management in the Island of Crete, Greece

/in /by

The supply and demand management of water resources in Crete is necessary to avoid water shortages in the island predicted in the future due to climate change. Water demand management in Crete should aim not simply to reduce water consumption, but to ensure that available water is used efficiently, economically and sustainably. Several studies related to water resources in Crete have been reviewed and the water consumption in several sectors has been estimated. The island is sufficient in water resources under average meteorological conditions while climate change is foreseen to reduce water precipitation in the coming decades resulting in water shortages. Agriculture is by far the greatest water consumer in the island using around 80% of the total water use. Crete’s tourism industry is growing fast while its share in total water demand is around 3%. Several technical and non-technical measures can be used to reduce the water demand in Crete. The efficient use of water in agriculture and tourism can reduce significantly the total water consumption which was estimated at 610.94 hm3 in 2016. A 10% reduction in water consumption in these two sectors can reduce the total annual water consumption in the island by 8.15 % or by 49.78 hm3/year. Appropriate water pricing, use of financial tools, awareness raising and education of several water-related stakeholders would contribute in the decrease of water demand in Crete. The results of the current study could be used from policy makers, local and regional authorities as well as from water-related organizations in the island.