Search Results (248)

Thrust vectoring technology significantly improves the manoeuvrability and environmental adaptability of unmanned aerial vehicles by dynamically regulating the direction and magnitude of thrust. In this paper, the principles and applications of mechanical thrust vectoring technology, fluidic thrust vectoring technology and the distributed electric propulsion system are systematically reviewed. It is shown that the mechanical vector nozzle can achieve high-precision control but has structural burdens, the fluidic thrust vectoring technology improves the response speed through the design of no moving parts but is accompanied by the loss of thrust, and the distributed electric propulsion system improves the hovering efficiency compared with the traditional helicopter. Addressing multi-physics coupling and non-linear control challenges in unmanned aerial vehicles, this paper elucidates the disturbance compensation advantages of self-disturbance rejection control technology and the optimal path generation capabilities of an enhanced path planning algorithm. These two approaches offer complementary technical benefits: the former ensures stable flight attitude, while the latter optimises flight trajectory efficiency. Through case studies such as the Skate demonstrator, the practical value of these technologies in enhancing UAV manoeuvrability and adaptability is further demonstrated. However, thermal management in extreme environments, energy efficiency and lack of standards are still bottlenecks in engineering. In the future, breakthroughs in high-temperature-resistant materials and intelligent control architectures are needed to promote the development of UAVs towards ultra-autonomous operation. This paper provides a systematic reference for the theory and application of thrust vectoring technology. Full article

The conservation of 19th-century heritage shophouses in Peunayong, Banda Aceh, illustrates a global challenge where material deterioration, structural decline, and weak governance intersect. Previous studies often examined these dimensions separately—focusing on architectural authenticity, structural safety, or heritage policy—but rarely in an integrated manner. This study addresses that gap by combining facade condition surveys, non-destructive structural testing, and policy analysis to evaluate the state and future of Peunayong’s historic shophouses. Fieldwork on 45 buildings employed visual documentation, interviews, questionnaires, and Schmidt Hammer and Ultrasonic Pulse Velocity (UPV) tests. The visual observation was measured using a Likert scale. Results show that 62.3% of shophouses experienced severe facade damage, primarily due to unregulated renovations erasing historical features. Windows, ornaments, and fascia boards were among the most degraded. Structural tests revealed that while some shophouses retained safe load-bearing capacity, others showed critical weaknesses below safety thresholds. Policy analysis highlighted an implementation deficit: despite recognition of Peunayong in urban spatial plans, the buildings remain unregistered as cultural heritage, leaving them unprotected and subject to uncontrolled alterations. Currently, 55.6% retain original facade features, while 44.4% have been modified. By framing conservation as a triple crisis of authenticity loss, structural vulnerability, and policy failure, this study contributes methodological and empirical insights to heritage debates, advocating for enforceable regulations, technical monitoring, and community-supported conservation. Full article

With the rapid growth of global shipping, accurate vessel traffic prediction is essential for waterway management and navigation safety. This study proposes the Fusion Spatio-Temporal Transformer (FSTformer) to address non-Gaussianity, non-stationarity, and spatiotemporal heterogeneity in traffic flow prediction. FSTformer incorporates a Weibull–Gaussian Transformation for distribution normalization, a hybrid Transformer encoder with Heterogeneous Mixture-of-Experts (HMoE) to model complex dependencies, and a Kernel MSE loss function to enhance robustness. Experiments on AIS data from the Fujiangsha waters of the Yangtze River show that FSTformer consistently outperforms baseline models across multiple horizons. Compared with the best baseline (STEAformer), it reduces MAE, RMSE, and MAPE by 3.9%, 1.8%, and 6.3%, respectively. These results demonstrate that FSTformer significantly improves prediction accuracy and stability, offering reliable technical support for intelligent shipping and traffic scheduling in complex waterways. Full article

Background and clinical significance: Paget’s disease of bone involves anomalies of the bone metabolism; however, the presence of tumor-derivate abnormal parathyroid hormone (PTH) levels does not represent one of these disturbances. To our best knowledge, the association with normocalcemic variant of primary hyperparathyroidism has been limitedly reported, and here we introduce such an unusual overlap in a male suffering from osteoporosis. Case presentation: A 71-year-old, non-smoker man was hospitalized for mild, nonspecific dysphagia, asthenia, decreased appetite, and mild weight loss during the latest 2 months. His medical history included cardiovascular conditions and an abnormal PTH level with normal serum calcium under daily cholecalciferol supplements (tested twice during latest 12 months). The lab findings pointed out a normocalcemic primary hyperparathyroidism (PTH of maximum 163 pg/mL, and total calcium of 9.3 mg/dL) caused by a right parathyroid tumor of 1.2 cm, as confirmed by computed tomography (CT). Additionally, CT showed a left humerus lesion suggestive of Paget’s disease of bone, a confirmation that also came from the whole-body bone scintigraphy. The subject presented increased P1NP and osteocalcin, CrossLaps as bone formation, and resorption markers, with normal total alkaline phosphatase. CT scan also detected multiple vertebral fractures and small kidney stones. Zoledronate i.v. (3 mg, adjusted for creatinine clearance) was administered, taking into consideration all three bone ailments (Paget’s disease, high PTH/calcium, and osteoporosis) with further follow-up. Conclusions: This case highlights the following technical notes based on a real-life setting: 1. Despite the mentioned bone diseases, no bone pain was present. Loss of appetite, dysphagia, and asthenia may be a consequence of mineral metabolism disturbances. 2. The panel of blood bone turnover markers levels might be related to both hyperparathyroidism and Paget’s disease; notably, rare cases of Paget’s disease with normal alkaline phosphatase were prior reported. 3. A meticulous differentiation between secondary and primary hyperparathyroidism is required. In this instance, lack of hypocalcaemia and vitamin D deficiency was suggestive of the diagnosis of a primary variant. 4. Kidney stones, osteoporosis, and osteoporotic fractures may be correlated with both conditions, as well, while a dual perspective of the therapy, since the patient was not a parathyroid surgery candidate, included a first dose of zoledronate with consecutive long-term follow-up. To our best knowledge, the co-presence of normocalcemic variant of primary hyperparathyroidism represents an exceptional finding in a patient synchronously diagnosed with Pagetic lesions and osteoporosis complicated with vertebral fractures. Full article

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, in part due to late diagnosis and limited prognostic tools. In recent years, microRNAs, small, non-coding regulators of gene expression, have emerged as key modulators of tumor metabolism, microenvironmental crosstalk, and therapeutic response in HCC. This narrative review synthesizes evidence published from January 2000 through April 2025, focusing on four interrelated themes: (1) miRNA-driven metabolic rewiring; (2) circulating and exosomal miRNAs as diagnostic and (3) predictive biomarkers; (4) miRNA-based therapeutic strategies. We conducted a targeted PubMed search using terms related to HCC, miRNA biology, biomarkers, metabolism, and therapy, supplemented by manual reference mining. Preclinical and clinical studies reveal that loss of tumor-suppressor miRNAs and gain of oncomiRs orchestrate glycolysis, lipid and glutamine metabolism, and stromal-immune remodeling. Circulating miRNA signatures, including single- and multimarker panels, demonstrate diagnostic AUCs up to 0.99 for early-stage HCC and distinguish HCC from cirrhosis more accurately than alpha-fetoprotein. Predictively, miRNAs such as miR-21 and miR-486-3p correlate with sorafenib resistance, while tissue and exosomal miRNAs forecast recurrence and survival after curative therapy. Therapeutic manipulation, restoring tumor-suppressor miRNAs via mimics or AAV vectors and inhibiting oncomiRs with antagomirs or LNA oligonucleotides, yields potent anti-tumor effects in models, affecting cell cycle, apoptosis, angiogenesis, and immune activation. Despite technical and delivery challenges, early-phase trials validate target engagement and inform safety optimization. In this review, we highlight opportunities to integrate miRNA biomarkers into surveillance algorithms and combine miRNA therapeutics with existing modalities, charting a roadmap toward precision-guided management of HCC. Full article

As the reserves of these raw materials continue to dwindle, their extraction is becoming increasingly difficult, with shaft depth increasing and sometimes exceeding three kilometres. As shaft depths increase, the costs, as well as the risks of mining and other shaft operations, increase non-linearly. There is also a significant increase in the costs associated with condition assessment, which depend on the inspection and testing method used and increase with the lifetime of the facility. New technical and organisational solutions are emerging to meet these requirements. This paper addresses the operation of steel ropes. This article analyses the results of strength tests on two selected modern hoisting rope designs that have recently come into service. These structures are relatively unknown to users in terms of their wear. In their operation, significant problems of condition assessment and safety, as well as disqualification due to the level of wear reached, arise. Strength tests were performed using classic non-destructive methods (tensile test, torsion test, bending test) to assess the technical condition of ropes after their replacement. The tests on two rope structures carried out before and after they were put down by expert decision were analyzed. The results of these tests were statistically processed and presented graphically to determine similarities and differences. Statistical analyses were used to evaluate the results by examining the distribution of variable strength parameters. All results were commented on, and specific and general conclusions were drawn. The article presents the conclusions, the most important of which is that new and complex ropes exhibit varying degrees of wear across the layers. This is due to their compaction process. These should be useful to users of similar rope designs, personnel carrying out the obligatory tests imposed by the legislation, and those making strategic decisions regarding the operation of entire mining plants. The analyses may contribute to the subsequent assessment of the technical condition of new ropes, which in many cases have wear parameters (corrosion, strength loss, etc.) assessed in a subjective, not quantitative, manner. Full article

The article presents a mathematical description of the thermal phenomena occurring both inside and on the surfaces of a homogeneous plate subjected to an external heat flux on one side. Analytical formulae for thermal excitation, with a given duration and constant power, are derived, enabling the determination of temperature increases on both the heated and unheated surfaces of the plate under specific heat transfer conditions to the surroundings. Convective heat transfer, with individual heat transfer coefficients on both sides of the slab, is considered; however, radiative heat loss can also be included. The solution of the problem obtained using two methods is presented: the method of separation of variables (MSV) and the Laplace transform (LT). The advantages and disadvantages of both analytical formulae, as well as the impact of various factors on the accuracy of the solution, are discussed. Among others, the MSV solution works well for a sufficiently long time, whereas the LT solution is better for a sufficiently short time. The theoretical considerations are illustrated with diagrams for several configurations, each representing various heat transfer conditions on both sides of the plate. The presented solution can serve as a starting point for further analysis of more complex geometries or multilayered structures, e.g., in non-destructive testing using active thermography. The developed theoretical model is verified for a determination of the thermal diffusivity of a reference material. The model can be useful for analyzing the method’s sensitivity to various factors occurring during the measurement process, or the method can be adapted to a pulse of known duration and constant power, which is much easier to implement technically than a very short impulse (Dirac) with high energy. Full article

This paper presents a case study of the Honduran electricity system and evaluates the technical impact of integrating distributed generation through modeling and simulation using Pandapower, (version 3.1.0) an open-source Python tool. A multi-criteria methodology was applied to select connection nodes considering the voltage sensitivity (∆V/MW), loss factor, available thermal capacity (headroom), and hosting capacity. The analysis focused on voltage stability, power losses, and line loading under various distributed generation scenarios. This methodology prioritized buses with critical voltages and significant loads. The case study model included official data from the Honduran National Dispatch Center. The simulations included a redispatch scheme for conventional generators to maintain power balance in all scenarios (20–100% distributed generation profiles), using GEN (controllable output) and SGEN (fixed output) components. The results show that with 50% distributed generation relative to local demand, voltages at critical buses improved by up to 0.14 p.u. Total active losses decreased by 9%, and reactive losses decreased by 44%. Additionally, indirect improvements were observed in non-intervened buses, as well as load relief in lines and transformers. These results confirm that strategic distributed generation injections combined with redispatch can improve supply quality and operational efficiency in weak and radial network topologies. The proposed methodology is scalable and able to be replicated in other power systems, providing technical input for energy planning and renewable energy integration in developing countries. Full article

This study aimed to identify and analyse the main difficulties faced by family farmers in producing and supplying vegetables through short food supply chains. Semi-structured interviews were conducted with seven family farmers in a large city in southern Brazil. We sought to include at least one farmer supplying each of the main identified outlets: schools, restaurants, supermarkets, street markets, and consumer groups. Contacts were obtained through rural producer organisations. Data were recorded, transcribed, and analysed using thematic analysis. Three groups of difficulties emerged: (i) production—including seasonality, pest, and disease management, climate-related losses, and limited technical support; (ii) sales—such as price competition, logistical challenges, and inconsistent demand; and (iii) consumption—particularly low consumer habits regarding vegetable purchase and preparation, and preference for non-seasonal products. The study concludes that the main challenges to strengthening short food supply chains are the limited engagement of young people in farming, lack of specialised technical assistance, climate-related risks, bureaucratic barriers, and the high costs of organic certification. Farmers also reported logistic difficulties and constraints in supplying restaurants due to demand for a narrow range of products disregarding seasonality. At the consumer level, habits shaped by conventional food systems emerged as obstacles. Strategies such as alternative markets, farmer organisations, supportive public policies, and initiatives to promote cooking skills and consumer awareness are key to enhancing resilience and expanding the supply of healthy foods. Full article

Technical losses (TLs) in power systems are an inevitable outcome of energy dissipation in components such as conductors, transformers, and transmission lines. These losses arise from the combined effects of material properties, operational conditions, and environmental factors, creating ongoing challenges for energy efficiency and grid sustainability. Their reduction requires a coordinated approach that integrates material improvements, smart grid technologies, and optimized operational practices. Reducing TLs not only improves economic efficiency but also contributes significantly to global sustainability efforts by enabling more efficient energy use and reducing carbon emissions associated with power generation. A review of recent publications shows that the literature on network losses is heavily skewed toward non-technical losses (NTLs), with TL-focused studies being fewer, often dated, and lacking comprehensive scope. This paper addresses the existing research gap by presenting a comprehensive, section-oriented taxonomy of TL mechanisms in power systems, accompanied by precise definitions for each category and a direct linkage between these categories and applicable loss mitigation measures. In addition, selected real-world projects and global initiatives aimed at reducing TLs, together with current regulatory approaches, emerging trends in this domain, and an assessment of the maturity level of technologies employed for TL reduction, are analyzed. This study aims to serve as a scientific reference to support future research and to guide policymakers, regulators, and utilities in developing more effective strategies for minimizing TLs. Full article

Mine water hazards represent one of the principal threats to safe coal mine operations; therefore, accurately predicting mine water inflow is critical for drainage system design and water hazard mitigation. Because mine water inflow is governed by the combined influence of multiple hydrogeological factors and thus exhibits pronounced non-linear characteristics, conventional approaches are inadequate in terms of forecasting accuracy and medium- to long-term predictive capability. To address this issue, this study proposes a Chaos-Autoformer-based method for predicting mine water inflow. First, the univariate inflow series is mapped into an m-dimensional phase space by means of phase-space reconstruction from chaos theory, thereby fully preserving its non-linear features; the reconstructed vectors are then used to train and forecast inflow with an improved Chaos-Autoformer model. On top of the original Autoformer architecture, the proposed model incorporates a Chaos-Attention mechanism and a Lyap-Dropout scheme, which enhance sensitivity to small perturbations in initial conditions and complex non-linear propagation paths while improving stability in long-horizon forecasting. In addition, the loss function integrates the maximum Lyapunov exponent error and earth mode decomposition (EMD) indices so as to jointly evaluate dynamical consistency and predictive performance. An empirical analysis based on monitoring data from the Liangshuijing Coal Mine for 2022–2025 demonstrates that the trained model delivers high accuracy and stable performance. Ablation experiments further confirm the significant contribution of the chaos-aware components: when these modules are removed, forecasting accuracy declines to only 76.5%. Using the trained model to predict mine water inflow for the period from June 2024 to June 2025 yields a root mean square error (RMSE) of 30.73 m³/h and a coefficient of determination (R²) of 0.895 against observed data, indicating excellent fitting and predictive capability for medium- to long-term tasks. Extending the forecast to July 2025–November 2027 reveals a pronounced annual cyclical pattern in future mine water inflow, with markedly higher inflow in summer than in winter and an overall slowly declining trend. These findings show that the Chaos-Autoformer can achieve high-precision medium- and long-term predictions of mine water inflow, thereby providing technical support for proactive deployment and refined management of mine water hazard prevention. Full article

Advanced Persistent Threats (APT) are stealthy multi-step attacks, often executed over an extensive time period and tailored for a specific attack target. APTs represent a “low and slow” type of cyberattack, meaning that they most often remain undetected until the consequence of the attack becomes evident. Energy infrastructure, including power grids, oil and gas infrastructure, offshore wind installations, etc., form the basis of a modern digital nation. In addition to loss of power, financial systems, banking systems, digital national services, etc., become non-operational without electricity. Loss of power from an APT cyberattack could result in loss of life and the possibility of creating digital chaos. Digital payments becomes unavailable, digital identification is affected, and even POS terminals need to run on emergency power, which is limited in time, resulting in challenges in paying for food and beverages. Examples of Advanced Persistent Threats (APTs) targeting energy infrastructures include Triton, which in 2017 aimed to manipulate the safety systems of a petrochemical plant in Saudi Arabia, potentially leading to catastrophic physical consequences. Another significant incident is the Industroyer2 malware attack in 2022, which targeted a Ukrainian energy provider in an attempt to disrupt operations. The paper combines APT knowledge with energy infrastructure domain expertise, focusing on technical aspects while at the same time providing perspectives on societal consequences that could result from APTs. Full article

In recent years, graph neural networks (GNNs) have shown powerful performance in processing non-Euclidean data. However, similar to other machine-learning algorithms, GNNs can amplify data bias in high-risk decision-making systems, which can easily lead to unfairness in the final decision-making results. At present, a large number of studies focus on solving the fairness problem of GNNs, but the existing methods mostly rely on building complex model architectures or rely on technical means in the field of non-GNNs. To this end, this paper proposes FairCNCB (Fair Graph Neural Network based on Counterfactual and Category Balance) to address the problem of class imbalancing in minority sensitive attribute groups. First, we conduct a causal analysis of fair representation and employ the adversarial network to generate counterfactual node samples, effectively mitigating bias induced by sensitive attributes. Secondly, we calculate the weights for minority sensitive attribute groups, and reconstruct the loss function to achieve the fairness of sensitive attribute classes among different groups. The synergy between the two modules optimizes GNNs from multiple dimensions and significantly improves the performance of GNNs in terms of fairness. The experimental results on the three datasets show the effectiveness and fairness of FairCNCB. The performance metrics (such as AUC, F1, and ACC) have been improved by approximately 2%, and the fairness metrics (△sp, △eo) have been enhanced by approximately 5%. Full article

Anal cancer is a rare malignancy with rising incidence. Definitive treatment with radiation and concurrent chemotherapy represent the standard of care for patients with non-metastatic disease. Advances in radiation delivery through the use of intensity-modulated radiotherapy have significantly reduced the toxic effects of treatment. Adaptive radiotherapy (ART) has emerged as a strategy to further enhance treatment precision and individualize therapy in response to patient-specific changes during the course of chemoradiotherapy. The rationale for ART in anal cancer stems from the recognition that significant anatomic and tumor changes can occur throughout the 5–6-week treatment course, including tumor shrinkage, weight loss, and variable rectal/bladder filling. This review discusses the role of ART in contemporary anal cancer management. We overview the principles of ART, delineate the technical workflows (including both computed tomography (CT) and MR-guided approaches), and examine how adaptive techniques are applied in treatment planning and delivery. We also review the clinical evidence to date, including dosimetric studies and emerging clinical trial data on ART in anal cancer, particularly its impact on outcomes and toxicity. Full article

Cross-border energy trading activity via interconnection has received much attention in Southern Asia to help the South Asian Association for Regional Cooperation (SAARC) region’s energy deficit states. This research article proposed a smart metering system to reduce energy losses and increase distribution sector efficiency. The implementation of smart metering systems in utility management plays a pivotal role in advancing several Sustainable Development Goals (SDGs), i.e.; SDG (Affordable and Clean Energy), and SDG Climate Action. By enabling real-time monitoring, accurate measurement, and data-driven management of energy resources, smart meters promote efficient consumption, reduce losses, and encourage sustainable behaviors among consumers. The adoption of a smart metering system along with Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis, socio-economic analysis, current challenges, and future prospects was also investigated. Besides the economics of the electrical distribution system, one feeder with non-technical losses of about 16% was selected, and the cost–benefit analysis and cost–benefit ratio was estimated for the SAARC region. The import/export ratio is disturbing in various SAARC grids, and a solution in terms of community microgrids is presented from Pakistan’s perspective as a case study. The proposed work gives a guidelines for SAARC countries to reduce their losses and improve their system functionality. It gives a composite solution across multi-faceted evaluation for the betterment of a large region. Full article