Search Results (146)

This paper proposes a novel microgrid (MG) architecture designed for telecommunication base stations in non-interconnected regions, with the main objective of mitigating mobile service interruptions caused by power outages. This research consists of three key modules: the first module on resources and components, the second module on characterization, and the third module on design and methodology. The first module presents a comprehensive identification and description of the resources and components of the microgrid within the base station; the second module characterizes the topology and specific configurations of the microgrid; and the last module covers a new methodology for the installation of microgrids in geographic areas lacking electrification, which becomes the contribution of this research work. The novelty of this research presents new control architectures, energy management, and system optimization, including technical–economic analysis. The research outcome highlights the economic and social benefits for both local communities and mobile phone service providers. This research aims to establish a guideline on how these factors affect the focus region of this research. With this technological proposal, a continuous and uninterrupted mobile service is achieved, thus improving the quality of service and minimizing the failures induced by electricity in non-interconnected areas. The tests and validation of the system were carried out with Homer Pro software, integrating socioeconomic and environmental factors. The results obtained present a key solution for this type of application, minimizing costs and increasing reliability for users. Full article

Metabolic syndrome (MetS) is a complex condition characterized by a group of interconnected metabolic abnormalities. Due to its increasing prevalence, better predictive markers are needed. Therefore, this study aims to develop predictive models for MetS by integrating adipokines, metabolic and cardiovascular risk factors, and anthropometric indices. Data were collected from 381 subjects aged 20 to 59 years (242 women and 139 men) from Guadalajara, Jalisco, Mexico, who were classified as having MetS or non-MetS based on the ATP-III criteria. Four supervised machine learning models were developed—Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost)—and their performance was evaluated using the Area under the Curve (AUC), calibration curves, Decision Curve Analysis (DCA), and local interpretability analysis. The RF and XGBoost models achieved the highest AUCs (0.940 and 0.954). The RF and LR models were the best calibrated and showed the highest net benefit in DCA. Key variables included age, anthropometric indices (BRI and DAI), insulin resistance measures (HOMA-IR), lipid profiles (sdLDL-C and LDL-C), and high-molecular-weight adiponectin, used to classify the presence of MetS. The results highlight the usefulness of specific models and the importance of anthropometric variables, cardiovascular risk factors, metabolic profiles, and adiponectin as indicators of MetS. Full article

Small-scale wind turbines (SWTs) represent a promising solution for the energy transition and the decentralization of electricity generation in non-interconnected areas. Conventional strategies to improve SWT performance often rely on active pitch control, which, while effective at rated conditions, is too costly and complex for small systems. An alternative is passive pitch control through bend–twist coupling in the blade structure, which enables self-regulation and improved power generation. This work proposes a novel blade design methodology for a 5 kW SWT that integrates passive bend–twist coupling with conventional pitch adjustment, thereby creating a hybrid passive–active control strategy. The methodology encompasses the definition of aerodynamic blade geometry, laminate optimization via genetic algorithms combined with finite element analysis, and experimental characterization of composite materials. Aerodynamic–structural interactions are studied using one-way fluid–structure simulations, with responses analyzed through the blade element momentum method to assess turbine performance. The results indicate that the proposed design enhances power generation by about 4%. The study’s originality lies in integrating optimization, structural tailoring, and material testing, offering one of the first demonstrations of combined passive–active pitch control in SWTs, and providing a cost-effective route to improve efficiency and reliability in decentralized renewable energy systems. Full article

Armed conflicts continue to severely impact human populations and essential infrastructure, particularly water supply systems. This study examines the Yechilla area, a high-intensity battle corridor during the Tigray (between 12°15′26″ 14°57′49″ N latitude; and 36°20′57″–39°58′54″ E longitude) war (2020–2022). Using Cochran’s formula, a representative sample of 89 water schemes was selected for onsite assessment. Additional data on damages to water offices, personnel, equipment, and related infrastructure were gathered through face-to-face interviews with local officials and water professionals, onsite visits, and reviews of governmental and non-governmental archives, and previous studies. The findings reveal that 48.3% of water schemes in the study area are non-functional (does not deliver water), which is a significant increase from pre-war non-functionality rates of approximately 7.1% regionally and 21.1% nationally. Despite the Pretoria peace agreement, non-functionality levels remain critically high two years after conflict. Damage includes partial impairments, lack of technical and spare part support, complete destruction, and looting of water scheme components. The widespread destruction of civilian water infrastructure during the Tigray conflict underscores the insufficiency of existing international legal frameworks, such as the International Humanitarian Law and International Water Law, which are inadequately protecting civilians and their property. Understanding the broader consequences of armed conflicts requires examining the indirect effects and the complex interactions within and between social, economic, and environmental systems. These interconnected impacts are essential to fully grasp how conflict affects livelihoods and human security on a wider scale. Full article

Global malnutrition and hunger represent crises of alarming magnitude, threatening progress toward all the Sustainable Development Goals (SDGs). The drivers of food insecurity and malnutrition are complex and interconnected, including conflict, climate change, migration, population aging, and the erosion of social capital. Despite some progress in specific areas, current trends reveal insufficient advancement toward key global nutrition and diet-related, non-communicable disease targets, confirming the persistent double burden of malnutrition. Without urgent, multisectoral action—including investments in integrated nutrition policies, resilient food systems, and conflict resolution—the goal of achieving Zero Hunger by 2030 remains unlikely. The World Food Program estimates that in 2025, 319 million people will face acute food insecurity; if current trends persist, approximately 582 million people could still be chronically undernourished by 2030. Furthermore, overweight and obesity are projected to continue rising globally, with adult obesity prevalence expected to reach 19.8% in 2030. This narrative review synthesizes current global trends in malnutrition—both undernutrition and overnutrition—and food insecurity; it explores the root causes driving these crises and analyzes the scientific literature to inform future research in the critical years leading up to the 2030 Agenda deadline. It calls for coordinated global efforts that prioritize vulnerable populations, which are essential to reversing the current trajectory of malnutrition and hunger. Since nutrition is a fundamental component of sustainable development, achieving the SDG 2 targets is essential to the accomplishment of all 17 goals. Full article

The digital revolution has profoundly influenced the automotive industry, shifting the paradigm from conventional vehicles to smart cars (SCs). The SCs rely on in-vehicle communication among electronic control units (ECUs) enabled by assorted protocols. The Controller Area Network (CAN) serves as the de facto standard for interconnecting these units, enabling critical functionalities. However, inherited non-delineation in SCs— transmits messages without explicit destination addressing—poses significant security risks, necessitating the evolution of an astute and resilient self-defense mechanism (SDM) to neutralize cyber threats. To this end, this study introduces a lightweight intrusion mitigation mechanism based on an adaptive momentum-based deep denoising autoencoder (AM-DDAE). Employing real-time CAN bus data from renowned smart vehicles, the proposed framework effectively reconstructs original data compromised by adversarial activities. Simulation results illustrate the efficacy of the AM-DDAE-based SDM, achieving a reconstruction error (RE) of less than 1% and an average execution time of 0.145532 s for data recovery. When validated on a new unseen attack, and on an Adversarial Machine Learning attack, the proposed model demonstrated equally strong performance with RE < 1%. Furthermore, the model’s decision-making capabilities were analysed using Explainable AI techinques such as SHAP and LIME. Additionally, the scheme offers applicable deployment flexibility: it can either be (a) embedded directly into individual ECU firmware or (b) implemented as a centralized hardware component interfacing between the CAN bus and ECUs, preloaded with the proposed mitigation algorithm. Full article

Multimode VCSELs coupled into waveguides can be a practical path toward realizing commercially viable photonic interposer chips. The experimental coupling of multimode VCSEL light to a non-silicon waveguide fabricated using a CMOS-compatible process is demonstrated. The GaP prism was tested and adopted as a coupling method. Both conventional and cavity-type optical waveguides, fabricated from CMOS-compatible PECVD SiO₂, Si₃N₄, and SiO_xN_y materials, were evaluated. The average propagation loss transmitted through the cavity-type waveguide was measured as 0.444 dB/cm. A polyimide micro-lens, cavity-type waveguide, and a GaP prism coupler are developed to inject the multimode VCSEL light into the waveguide measuring the net coupling loss of 0.762 dB. The packaged size of VCSEL has an area of 0.4 mm² and a height of 0.64 mm. MUX/DeMUX was designed on the bottom of the prism. A light source, a modulator, and MUX/DeMUX are all located in the same area of the prism bottom in VCSEL-based interconnections. Full article

In water-stressed regions of South Africa, the expansion of extractive industries is compounding the effects of climate change and poor governance, threatening local water security and socio-ecological resilience for hydrosocial justice. This chapter examines the proposed Jindal iron-ore mine in Melmoth, KwaZulu-Natal and its anticipated impact on water availability, quality, and governance. Drawing on in-depth interviews with farmers, residents, and environmental stakeholders, the findings reveal a region already suffering from recurrent droughts, El Niño-related climate variability, and over-allocated water resources. Findings reveal concern that the mine would further strain surface and groundwater systems, especially given the industrial demands already placed on the Goedertrouw dam. Other concerns about potential water contamination from tailings, dust, and runoff echo experiences from neighbouring mining areas, where degraded water quality has affected both domestic use and cultural practices. The study also uncovers governance gaps, including weak regulatory oversight, non-compliance with environmental safeguards, and flawed consultation processes that overlook downstream impacts. By situating Melmoth within wider debates on extractivism, climate stress, and environmental justice, the paper calls for an urgent reconsideration of extractive approvals in ecologically vulnerable regions that threaten water security, livelihoods, cultural practices, and sense of place. Ignoring interconnected dimensions risks reinforcing existing vulnerabilities, undermining resilience, and entrenching long-term injustices. Full article

Electrochemical water splitting represents a sustainable approach for hydrogen production, yet efficient hydrogen evolution reaction (HER) catalysts operating in alkaline environments remain critically needed. Herein, we report the fabrication of Co₃O₄–NiS₂ nanocomposites synthesized through a facile coprecipitation and subsequent thermal treatment method. Detailed characterization via physicochemical techniques confirmed the successful formation of a hybrid Co₃O₄–NiS₂ heterostructure with tunable compositional and morphological characteristics. Among the synthesized catalysts (Co–Ni–1, Co–Ni–2, and Co–Ni–3), the Co–Ni–2 sample demonstrated optimal structural integration, displaying interconnected nanosheet morphologies and balanced elemental distribution. Remarkably, Co–Ni–2 achieved exceptional HER performance in 1 M KOH electrolyte, requiring an ultralow overpotential of only 84 mV at 10 mA cm⁻² and exhibiting a favorable Tafel slope of 67.5 mV dec⁻¹. Electrochemical impedance spectroscopy and electrochemical surface area measurements further substantiated the superior electrocatalytic kinetics, rapid charge transport, and abundant active site accessibility in the optimized Co–Ni–2 composite. Additionally, Co–Ni–2 demonstrated outstanding durability with negligible activity decay over 5000 cycles. This study not only highlights the strategic synthesis of Co₃O₄–NiS₂ nanostructures but also provides valuable insights for designing advanced, stable, and efficient non-noble electrocatalysts for sustainable hydrogen generation. Full article

Galectin-3 (Gal-3) is a β-galactoside-binding lectin that mediates diverse signaling events in multiple cell types, including immune cells. It is also a prognostic indicator for multiple clinically important disorders, including cardiovascular disease. Gal-3 binds to cell surface glycans to form lattices that modulate surface receptor signaling and internalization. However, the tissue-specific regulation of Gal-3 surface expression remains poorly understood. Here, we review evidence for the involvement of Gal-3 in cell surface signaling, intranuclear events, and intracellular trafficking. Our focus will be on the O-GlcNAc modification as a regulator of Gal-3 biosynthesis, non-canonical secretion, and recycling. We argue that the nutrient-driven cytoplasmic hexosamine biosynthetic pathway (HBP) and endomembrane transport mechanisms generate unique pools of nucleotide sugars. The differing levels of nucleotide sugars in the cytosol, endoplasmic reticulum (ER), and Golgi apparatus generate differential thresholds for the responsiveness of O-GlcNAc cycling, N- and O-linked glycan synthesis/branching, and glycolipid synthesis. By regulating Gal-3 synthesis and non-canonical secretion, O-GlcNAc cycling may serve as a nexus constraining Gal-3 cell surface expression and lattice formation. This homeostatic feedback mechanism would be critical under conditions where extensive glycan synthesis and branching in the endomembrane system and on the cell surface are maintained by elevated hexosamine synthesis. Thus, O-GlcNAc cycling and Gal-3 synergize to regulate Gal-3 secretion and influence cellular signaling. In humans, Gal-3 serves as an early-stage prognostic indicator for heart disease, kidney disease, viral infection, autoimmune disease, and neurodegenerative disorders. Since O-GlcNAc cycling has also been linked to these pathologic states, exploring the interconnections between O-GlcNAc cycling and Gal-3 expression and synthesis is likely to emerge as an exciting area of research. Full article

The sustainable development of eco-tourism is significantly influenced by multiple conditions within spatiotemporally continuous geographic scenarios. However, existing evaluations of the development value of eco-tourism resources (Eco-TRDVs) are non-spatial and do not sensitively represent their complex relationships. This study proposed a GIS approach for evaluating regional Eco-TRDVs by mapping the complex interconnections with spatial distances. Inherent and external conditions for evaluating Eco-TRDVs were classified under three indicators and digitized using GIS and remote sensing technologies. Then, the analytic hierarchy process and GIS cost distance analysis were introduced to define the initial values and cumulate Eco-TRDVs with distances. Taking the Taihang Honggu National Forest Park, China, as the case area, the Eco-TRDVs over the entire area in 2017 and 2020 were mapped. The results present a continuous spatial variability of Eco-TRDVs and comprehensively reflect the complex interconnections of constraint elements with spatial distances. The evaluation is sensitive to the intrinsic value of poles, as evidenced by the high development values and high-density distribution of their contours. Source additions improve the evaluation considerably, with transportation networks having a greater impact than economic development zones and urban elements. Furthermore, aggravated fragmentation of the price flow field increases spatial heterogeneity. The development value shows a negative linear correlation with distance. The proposed approach handles the spatially oriented relationships of the multi-conditions, and supports future planning and monitoring of spatial-temporal changes in eco-tourism development. Full article

Wildfires are complex natural disasters that significantly impact ecosystems and human communities. The early detection and prediction of forest fire risk are necessary for effective forest management and resource protection. This paper proposes an innovative early detection system based on a wireless sensor network (WSN) composed of interconnected Arduino nodes arranged in a hybrid circular/star topology. This configuration reduces the number of required nodes by 53–55% compared to conventional Mesh 2D topologies while enhancing data collection efficiency. Each node integrates temperature/humidity sensors and uses ZigBee communication for the real-time monitoring of wildfire risk conditions. This optimized topology ensures 41–81% lower latency and 50–60% fewer hops than conventional Mesh 2D topologies. The system also integrates artificial intelligence (AI) algorithms (multiclass logistic regression) to process sensor data and predict fire risk levels with 99.97% accuracy, enabling proactive wildfire mitigation. Simulations for a 300 m radius area show the non-dense hybrid topology is the most energy-efficient, outperforming dense and Mesh 2D topologies. Additionally, the dense topology achieves the lowest packet loss rate (PLR), reducing losses by up to 80.4% compared to Mesh 2D. Adaptive routing, dynamic round-robin arbitration, vertical tier jumps, and GSM connectivity ensure reliable communication in remote areas, providing a cost-effective solution for wildfire mitigation and broader environmental monitoring. Full article

Combining the properties of organic and inorganic components with high surface areas and large pore volumes opens up countless possibilities for designing materials tailored to a wide range of advanced applications. As the majority of mesoporous hybrid materials are siliceous, the development of cost-effective synthetic approaches to produce water-stable hybrids with controlled porosity and functionality remains essential. Herein, we describe an original strategy for the synthesis of bridged mesoporous titania–bisphosphonate hybrids based on a one-step, template-free, non-hydrolytic sol–gel process. The reaction between Ti(OiPr)₄ and several flexible or rigid bisphosphonate esters, in the presence of acetic anhydride (Ac₂O) leads to the formation of TiO₂ anatase nanorods interconnected by fully condensed bisphosphonate groups. The general method that we depict is quantitative and low cost. All materials are mesoporous with very high specific surface areas (up to 520 m²·g⁻¹) and pore volumes (up to 0.93 cm³·g⁻¹). Full article

Wood displays three-dimensional characteristics at both macroscopic and microscopic scales. Accurately reconstructing its 3D structure is vital for a deeper understanding of the relationship between its anatomical characteristics and its physical and mechanical properties. This study aims to apply X-ray micro-computed tomography (XμCT) for the high-resolution, non-destructive visualization and quantification of softwood anatomical features. Six typical softwood species—Picea asperata, Cupressus funebris, Pinus koraiensis, Pinus massoniana, Cedrus deodara, and Pseudotsuga menziesii—were selected to represent a range of structural characteristics. The results show that a scanning resolution of 1–2 μm is suitable for investigating the transition from earlywood to latewood and resin canals, while a resolution of 0.5 μm is required for finer structures such as bordered pits, ray tracheids, and cross-field pits. In Pinus koraiensis, a direct 3D connection between radial and axial resin canals was observed, forming an interconnected resin network. In contrast, wood rays were found to be distributed near the surface of axial resin canals but without forming interconnected structures. The three-dimensional reconstruction of bordered pit pairs in Pinus massoniana and Picea asperata clearly revealed interspecific differences in pit morphology, distribution, and volume. The average surface area and volume of bordered pit pairs in Pinus massoniana were 1151.60 μm² and 1715.35 μm³, respectively, compared to 290.43 μm² and 311.87 μm³ in Picea asperata. Furthermore, XμCT imaging effectively captured the morphology and spatial distribution of cross-field pits across species, demonstrating its advantage in comprehensive anatomical deconstruction. These findings highlight the potential of XμCT as a powerful tool for 3D analysis of wood anatomy, providing deeper insight into the structural complexity and interconnectivity of wood. Full article

This study develops a novel Lyrebird Optimization Algorithm (LOA), a technique inspired by the wild behavioral strategies of lyrebirds in response to potential threats. In a two-area interconnected power system that includes non-reheat thermal stations, this algorithm is applied to handle load frequency control (LFC) by optimizing the parameters of a Proportional–Integral–Derivative controller with a filter (PIDn). This study incorporates generation rate constraints (GRCs). The efficiency of the provided LOA-PIDn is evaluated through simulations under various disturbance scenarios and is compared against other well-established optimization techniques, including the Ziegler–Nichols (ZN), genetic algorithm (GA), Bacteria Foraging Optimization Algorithm (BFOA), Firefly Approach (FA), hybridized FA and pattern search (hFA–PS), self-adaptive multi-population elitist Jaya (SAMPE-Jaya)-based PI/PID controllers, and Teaching–Learning-Based Optimizer (TLBO) IDD/PIDD controllers. The results demonstrate the LOA’s ability to minimize the integral of time multiplied by absolute error (ITAE) and achieve significantly lower settling times for the two-area frequencies and transferred power variances in comparison with other methods. The comprehensive comparison and the inclusion of real-world constraints validate the LOA as a robust and effective tool for addressing complex optimization challenges in modern power systems. Full article