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The Internet of Things (IoT) has transformed multiple industries, providing significant potential for automation, efficiency, and enhanced decision-making. The incorporation of IoT and data analytics in smart grid represents a groundbreaking opportunity for the energy sector, delivering substantial advantages in efficiency, sustainability, and customer empowerment. This integration enables smart grids to autonomously monitor energy flows and adjust to fluctuations in energy demand and supply in a flexible and real-time fashion. Statistical analytics, as a fundamental component of data analytics, provides the necessary tools and techniques to uncover patterns, trends, and insights within datasets. Nevertheless, it is crucial to address privacy and security issues to fully maximize the potential of data analytics in smart grids. This paper makes several significant contributions to the literature on secure, privacy-aware aggregation schemes in smart grids. First, we introduce a Fog-enabled Secure Data Analytics Operations (FESDAO) scheme which offers a distributed architecture incorporating robust security features such as secure aggregation, authentication, fault tolerance and resilience against insider threats. The scheme achieves privacy during data aggregation through a modified Boneh-Goh-Nissim cryptographic scheme along with other mechanisms. Second, FESDAO also supports statistical analytics on metering data at the cloud control center and fog node levels. FESDAO ensures reliable aggregation and accurate data analytical results, even in scenarios where smart meters fail to report data, thereby preserving both analytical operation computation accuracy and latency. We further provide comprehensive security analyses to demonstrate that the proposed approach effectively supports data privacy, source authentication, fault tolerance, and resilience against false data injection and replay attacks. Lastly, we offer thorough performance evaluations to illustrate the efficiency of the suggested scheme in comparison to current state-of-the-art schemes, considering encryption, computation, aggregation, decryption, and communication costs. Moreover, a detailed security analysis has been conducted to verify the scheme’s resistance against insider collusion attacks, replay attack, and false data injection (FDI) attack. Full article

Air pollution has become a significant concern for human health, especially in developing countries. Among Primary Pollutants, particulate matter 2.5 (${\mathrm{PM}}_{2.5}$), refers to airborne particles which have a diameter of 2.5 micrometres or less, and has become a widely used measure for monitoring air quality globally. The standard go-to method usually uses Federal Reference Grade sensors to understand air quality. But, they are quite cost-prohibitive, so the popular alternative is low-cost (LC) air quality sensors. Even LC air quality monitors do not cover many areas, especially across the global south. On the other hand, the ubiquitous use of online social media OSM has led to its evolution in participatory sensing. While it does not function as a physical sensor, it can be a proxy indicator of public perception on the topic under study. OSM platforms such as Twitter/X and Reddit have already demonstrated their value in understanding human perception across various domains, including air quality monitoring. This study focuses on understanding air pollution in a resource-constrained setting by examining how the community perception on social media can complement traditional monitoring. We leverage metadata readily available from social media user data to find patterns with air quality fluctuations before and during the pandemic. We use the US Embassy ${\mathrm{PM}}_{2.5}$ data for baseline measurement. In the study, we empirically analyse the variations in quantitative & intent-based community perception in seasonal & pandemic outbreaks with varying air quality. We compare the baseline against temporal & user-specific attributes of Twitter/X relating to tweets like daily frequency of tweets, tweet lags 1–5, user followers, user verified, and user lists memberships across two timelines: pre-COVID-19 (20 March 2019– 29 February 2020) & COVID-19 (1 March 2020–20 September 2020). Our analysis examines both the quantitative and the intent-based community engagement, highlighting the significance of features like user authenticity, tweet recurrence rates, and intensity of participation. Furthermore, we show how behavioural patterns in the online discussions diverged across the two periods, which reflected the broader shifts in the air pollution levels and the public attention. This study empirically demonstrates the significance of X/Twitter metadata, beyond standard tweet content, and provides additional features for modelling and understanding air quality in developing countries. Full article

Alkali resistance is a critical factor for the long-term performance of glass fibers in cementitious composites. While zirconium oxide doping has proven effective in enhancing the durability of basalt fibers, its high cost and limited solubility motivate the search for viable alternatives. This study presents the first systematic investigation of titanium dioxide (TiO₂) doping in basalt-based glasses across a wide compositional range (0–8 mol%). X-ray fluorescence and diffraction analyses confirm complete dissolution of TiO₂ within the amorphous silicate network, with no phase segregation. At low concentrations (≤3 mol%), Ti⁴⁺ acts as a network modifier in octahedral coordination ([TiO₆]), reducing melt viscosity and lowering processing temperatures. As TiO₂ content increases, titanium in-corporates into tetrahedral sites ([TiO₄]), competing with Fe³⁺ for network-forming positions and displacing it into octahedral coordination, as revealed by Mössbauer spectroscopy. This structural redistribution promotes phase separation and triggers the crystallization of pseudobrukite (Fe₂TiO₅) at elevated temperatures. The formation of a protective Ti(OH)₄ surface layer upon alkali exposure enhances chemical resistance, with optimal performance observed at 4.6 mol% TiO₂—reducing mass loss in NaOH and seawater by 13.3% and 25%, respectively, and improving residual tensile strength. However, higher TiO₂ concentrations (≥5 mol%) lead to pseudobrukite crystallization and a narrowed fiber-forming temperature window, rendering continuous fiber drawing unfeasible. The results demonstrate that TiO₂ is a promising, cost-effective dopant for basalt fibers, but its benefits are constrained by a critical solubility threshold and structural trade-offs between durability and processability. Full article

Background: Prostate cancer is the second most common malignant cancer among men, and according to the predictions, the estimated number of new cases will substantially grow in the coming years. Therefore, the costs of the disease will increase as well. Methods: We conducted a literature review of the state of knowledge about the costs of treatment and the economic burden of prostate cancer. The vast majority of studies were focused on direct costs only, which clearly shows the literature gap. Results: We focused on the estimates of direct costs, i.e., treatment of prostate cancer, adjuvant and neoadjuvant treatment, and supportive and palliative care, and indirect costs. Cost-effectiveness analyses indicated that docetaxel combined with androgen deprivation therapy (ADT) was the most cost-effective strategy for metastatic hormone-sensitive prostate cancer (incremental cost-effectiveness ratio (ICER): USD 13,647). In contrast, novel therapies such as PARP inhibitors and whole-genome-sequencing-guided treatments were not cost-effective unless drug prices were reduced by 47–70%. In the United States, 5-year cumulative treatment costs ranged from USD 48,000 for conservative management to over USD 91,000 for radiotherapy, while out-of-pocket expenses averaged AUD 1172 in Australia. Indirect costs were also considerable, with Slovakia reporting an increase in sick leave costs from EUR 1.2 million in 2014 to EUR 2.1 million in 2022. Conclusions: Metastatic hormone-sensitive prostate cancer and metastatic castration-resistant prostate cancer were the most frequent categories for various treatment cost evaluations. A few specific combinations of drugs were cost-effective only under the condition of dropping the unit prices of a medication. Further summarizing, reviewing, and developing a methodology for standardized comparisons are needed. Full article

Background and Objectives: Albuminuria is a key clinical marker for early detection of diabetic kidney disease (DKD) in individuals with type 2 diabetes mellitus (T2DM). The triglyceride-glucose (TyG) index, a simple surrogate of insulin resistance, has been increasingly investigated for its potential association with renal complications. This study aimed to evaluate the relationship between the TyG index and albuminuria in patients with T2DM and assess its clinical utility as an accessible metabolic marker reflecting early renal involvement. Materials and Methods: This retrospective cross-sectional study included 570 adult patients with confirmed T2DM who were followed at a tertiary internal medicine outpatient clinic between January and December 2024. Participants were classified as albuminuric or non-albuminuric based on spot urine albumin-to-creatinine ratio (ACR) values. Clinical and biochemical parameters were collected from medical records, and the TyG index was calculated as ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. Logistic regression models were used to identify independent factors associated with albuminuria. ROC analysis was performed to evaluate the discriminatory accuracy of the TyG index. Results: The median TyG index was significantly higher in the albuminuric group compared to the non-albuminuric group (10.0 vs. 9.1; p < 0.001) and increased progressively with albuminuria severity (p < 0.001). In multivariate logistic regression analysis, elevated TyG index, hyperlipidemia, and reduced estimated glomerular filtration rate were independently associated with albuminuria. When evaluated as a continuous variable, the TyG index showed strong discriminatory ability (area under curve (AUC) = 0.949; 95% confidence interval (CI): 0.933–0.964). Using the optimal cut-off threshold of 9.6, the TyG index maintained high diagnostic performance (AUC = 0.870; 95% CI: 0.839–0.902; sensitivity 87.7%, specificity 86.3%). Subgroup analyses confirmed the robustness of this association across clinical and demographic variables. Conclusions: In this study, higher TyG index values were significantly associated with the presence and severity of albuminuria in individuals with T2DM. While causality cannot be inferred, the findings suggest that the TyG index may serve as a practical, cost-effective tool for identifying patients at increased risk for early diabetic kidney involvement. Prospective longitudinal studies are needed to confirm its predictive value and clinical applicability. Full article

This study investigates groundwater salinization in a section of a coastal aquifer in Rio Grande do Norte, Brazil, using frequency-domain electromagnetic (FDEM) measurements. With the global expansion of shrimp farming in ecologically sensitive coastal regions, there is an urgent need to assess associated risks and promote sustainable management practices. A key concern is the prolonged flooding of shrimp ponds, which accelerates saltwater infiltration into surrounding areas. To better delineate salinization plumes, we analyzed direct groundwater salinity measurements from 14 wells combined with 315 subsurface apparent conductivity measurements obtained using the FDEM method. Correlating these datasets improved the accuracy of salinity mapping, as evidenced by reduced variance in kriging interpolation. By integrating hydrogeological, hydrogeochemical, and geophysical approaches, this study provides a comprehensive characterization of groundwater salinity in the study area. Hydrogeological investigations delineated aquifer properties and flow dynamics; hydrogeochemical analyses identified salinity levels and water quality indicators; and geophysical surveys provided spatially extensive conductivity measurements essential for detecting and mapping saline intrusions. The combined insights from these methodologies enable a more precise assessment of salinity sources and support the development of more effective groundwater management strategies. Our findings demonstrate the effectiveness of integrating geophysical surveys with hydrogeological and hydrogeochemical data, confirming that shrimp farm ponds are a significant source of groundwater contamination. This combined methodology offers a low-impact, cost-effective approach that can be applied to other coastal regions facing similar environmental challenges. Full article

This paper presents the foot design for humanoid robot Mithra, with the goal of biomimetically improving impact behavior, natural power cycling throughout the gait cycle, and balance. For this purpose, an optimization framework was built which evaluates the human-inspired objectives using a dynamic finite element analysis validated by benchtop experiments. Using this framework and through several concept design iterations, a low-cost, compliant foot was optimized, designed, and fabricated. The analyses showed that the optimized foot significantly outperformed the baseline rigid foot in approaching the characteristics of human feet. The proposed framework is not limited to humanoids and can also be applied to the foot design for lower-limb prostheses and exoskeletons. Full article

Oleosomes are submicron oil bodies of a triacylglycerol core enveloped by a phospholipid monolayer and embedded proteins, forming a naturally assembled nanocarrier with exceptional oxidative resilience, interfacial stability, and biocompatibility. Their unique architecture supports solvent-free extraction, self-emulsification, and near-complete encapsulation of highly lipophilic compounds (log P > 4), including curcumin and cannabidiol, with reported efficiencies exceeding 95%. These plant-derived droplets enhance oral bioavailability through lymphatic uptake and enable targeted delivery strategies such as magnetically guided chemotherapy, which has reduced tumor burden by approximately 70% in vivo. The review critically examines recent advances in oleosome research, spanning botanical sourcing, green extraction technologies, interfacial engineering, xenobiotic encapsulation, pharmacokinetics, and therapeutic applications across oncology, dermatology, metabolic disease, and regenerative medicine. Comparative analyses demonstrate that oleosomes rival or surpass synthetic lipid nanocarriers in encapsulation efficiency, oxidative stability, and cost efficiency while offering a sustainable, clean-label alternative. Remaining challenges, including low loading of hydrophilic drugs, allergenicity, and regulatory standardization, are addressed through emerging strategies such as hybrid oleosome–liposome systems, recombinant oleosin engineering, and stimulus-responsive coatings. These advances position oleosomes as a versatile and scalable platform with significant potential for food, cosmetic, and pharmaceutical applications. Full article

In recent years, there has been a global increase in environmental awareness, which has driven the application of natural materials or the synthesis of novel, environmentally compatible materials. Composite materials hold a prominent position among modern materials and are typically developed to achieve resistance to various damage mechanisms, thereby extending the service life of structures. This study presents the synthesis and characterisation of high-density metal–glass composite materials. The commercially available 316L stainless steel powder was used as the matrix material, while andesite basalt powder was used as the reinforcement phase. Andesite basalt aggregate, ground into powder, is a cost-effective, widely available, and environmentally friendly natural raw material. Powder metallurgy was employed to produce the composite materials. Sintering was performed at 1250 °C for 30 min in a vacuum. The density of the sintered composite samples was analysed as a function of andesite basalt content, with sintering conducted in the presence of a liquid phase. Composite materials were characterised using optical and scanning electron microscopy, X-ray structural analysis, and hardness testing. This study confirmed that the optimal combination of properties was achieved in the composite with 20 wt.% andesite basalt, present as a glass phase within the 316L steel matrix. Full article

Due to their potential to reduce greenhouse gas emissions, light-frame timber buildings (LFTBs) are widely used in seismically active regions. However, their construction in these areas remains limited, primarily due to the high costs associated with continuous anchor tie systems (ATSs), which are required to withstand significant seismic forces. To address this challenge, frictional seismic isolation offers an alternative by enhancing seismic protection. Although frictional base isolation is an effective mitigation strategy, its performance can be compromised by extreme ground motions that induce large lateral displacements, resulting in impacts between the sliders and the perimeter protection ring. The effects of these internal lateral impacts on base-isolated LFTBs remain largely unexplored. To fill this knowledge gap, this study evaluates the collapse capacity of a set of base-isolated LFTBs representative of Chilean real estate developments. Nonlinear numerical models were developed in the OpenSeesPy platform to capture the nonlinear behavior of the superstructure, including the impact effects within the frictional isolation system. Incremental dynamic analyses following the FEMA P695 methodology were performed using subduction ground motions. Collapse margin ratios (CMRs) and fragility curves were derived to quantify seismic performance. Results indicate that frictional base-isolated LFTBs can achieve acceptable collapse safety without ATS, even with compact-size bearings. Code-conforming archetypes achieved CMRs ranging from 1.24 to 1.55, indicating sufficient safety margins. These findings support the cost-effective implementation of frictional base isolation in mid-rise timber construction for high-seismic regions. Full article

This research investigates the optimization of operational efficiency and cost reduction through the enhancement of material flow management within production line stations. Departing from conventional static analyses, the study employs advanced simulation tools to pinpoint performance bottlenecks and inefficiencies via dynamic modelling techniques. The Ishikawa diagram serves as the primary tool for conducting root-cause analysis. Simultaneously, the 5S methodology is implemented to foster workplace organization, standardization, and hygiene practices. In contrast to traditional optimization frameworks, the proposed strategy integrates real-time performance tracking systems, complemented by adaptive feedback mechanisms. This integration permits ongoing assessment of the production process, facilitating iterative improvement cycles. Empirical data gathered from monitored cycle times, equipment utilization rates, and defect frequencies substantiate the validation of implemented changes. The resulting optimized system significantly minimizes downtime and waste, thereby advancing sustainable and scalable operations. Ultimately, this research demonstrates that the fusion of simulation-based insights with lean management principles leads to considerable improvements in manufacturing productivity and overall product quality. Full article

Within the endeavour of describing and analysing delays and their propagations in air transport, a major limitation is represented by the validation of the obtained results. While this can be overcome through synthetic models, those available in the literature mostly aim at simulating the system in a detailed and realistic way, resulting in high complexity and substantial computational costs. We here present SynthATDelays, a minimalist and modular Python package designed to simulate a virtual customisable air transport system and to provide synthetic delay data under tuneable conditions; it is thus designed to support the validation of data-based studies and pipelines. We describe its internal structure and provide examples about how scenarios can be designed and executed. We further show how it can be used to tackle two relevant questions, i.e., the role of operational buffer times in the absorption of delays and the comparison and optimisation of causality tests to detect the propagation thereof. Full article

Background: Globally, uncorrected refractive errors are recognized as the primary cause of visual impairment and blindness. According to a report by the World Health Organization (WHO), providing spectacle lenses at an affordable cost remains a significant challenge, particularly for underprivileged populations in developing countries. This challenge contributes to the low compliance with spectacle wear worldwide. However, the benefits of wearing spectacles are influenced by the perceptions of the population regarding spectacle use. Methods: A quantitative, cross-sectional survey-based study was conducted at a superior educative center in Oman, the University of Buraimi. Participants were recruited from the four major colleges, namely, the College of Health Sciences (COHS), College of Business (COB), College of Engineering (COE), and College of Law (COL), and the Center for Foundation Studies (CFS). This study was conducted over the period from 18 December 2022 to 18 December 2023. Essential data were collected using an electronic questionnaire facilitated by the Google platform. The initial section of the questionnaire outlines this study’s objectives and its benefits to the community. The digital survey comprises three sections: the first section addresses the sociodemographic profile of the participants; the second section explores perceptions related to spectacles; and the third section examines visual symptoms associated with spectacle wear. In this study, a pre-tested survey was administered following consultation with a panel of three subject matter experts who reviewed the clarity and content validity of the test items. Data analyses were performed using descriptive statistics, and linear regression was applied to assess the effect of socioeconomic profile on perceptions of spectacles. Additionally, data entry, processing, and analysis were conducted using SPSS 25 software. The overall mean score for spectacle-related visual symptoms was 2.51 ± 0.75, indicating a moderate level of symptom occurrence. Results: A total of 415 participants (N = 415) were included in this study, comprising 133 males (32.0%) and 282 females (68.0%). The most prominent symptoms related to spectacle perception were “light sensitivity” and “eye pain”, with mean values of 3.03 ± 1.30 and 3.04 ± 1.25, respectively. Additionally, 249 participants (60%) reported moderate concern regarding spectacle-related visual symptoms. Among female participants, 118 (41.8%) exhibited little concern about visual symptoms associated with spectacle wear, whereas this was observed in 25.6% of male participants. Descriptive statistics indicated the mean perceived spectacle-related disadvantages score measured on a scale of 0 to 4 was 2.88 ± 1.16 (57.69% ± 23.15% in percentages), reflecting a moderate perception of such disadvantages. The linear regression model demonstrated statistical significance, as indicated by the likelihood ratio chi-square = 199.194 (df = 15, p < 0.001). The most significant predictor was study major (χ² = 72.922, p < 0.001). Conclusions: The present study indicates that undergraduate students generally exhibit a low perception of the disadvantages associated with wearing spectacles. Randomized sampling should be preferred in future studies to the convenience sampling technique. The most frequently reported visual symptoms include “light sensitivity and eye pain” among spectacle wearers. Therefore, it is imperative to implement health education programs and foundational studies across colleges to address these issues among undergraduate university students. Full article

In response to the increasing demand for environmentally friendly and cost-effective adsorbents in wastewater treatment, this study reports the green synthesis, characterization, and application of a magnetic epichlorohydrin Rosa canina (m-ECH-RC) nanocomposite for removing Safranin O (SO), a commonly used cationic dye in textile effluents. The synthesized material was characterized using Brunauer–Emmett–Teller (BET), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and zeta potential analyses to reveal its surface morphology, pore structure, functional groups, crystallinity, and colloidal stability. Adsorption performance was systematically tested under various conditions, including pH, adsorbent dose, contact time, ionic strength, and initial dye concentration. Kinetic analyses revealed that the adsorption process of Safranin O dye mainly obeys pseudo-second-order kinetics, but intraparticle and film diffusion also contribute to the process. As a result of the Isotherm analysis, it was found that the adsorption process conformed to the Langmuir model. Testing on real textile wastewater samples demonstrated a removal efficiency of 75.09% under optimized conditions. Reusability experiments further revealed that the material maintained high adsorption–desorption performance for up to five cycles, emphasizing its potential for practical use. These findings suggest that m-ECH-RC is a viable and sustainable adsorbent for treating dye-laden industrial effluents. Full article

Acute respiratory infections (ARIs) continue to pose a major global health threat, particularly among vulnerable populations. These infections often present with similar clinical symptoms, complicating accurate diagnosis and facilitating unmonitored transmissions. Genomic surveillance has emerged as an invaluable tool for pathogen identification and monitoring of such infectious pathogens; however, its implementation is frequently limited by high costs. The widespread use of high-throughput sequencing during the COVID-19 pandemic has created an opportunity to repurpose existing genomic platforms for broader respiratory virus surveillance. In this study, we evaluated the feasibility of adapting the Illumina COVIDSeq assay—initially designed for SARS-CoV-2 whole-genome sequencing—for use with Influenza A/B, Respiratory Syncytial Virus (RSV), and Rhinovirus. Positive control samples were processed using two approaches for library preparation: four virus-specific multiple workflows and a combined rapid workflow. Both workflows incorporated pathogen-specific primers for amplification and followed the Illumina COVIDSeq protocol for library preparation and sequencing. Sequencing quality metrics were analysed, including Phred scores, read length distribution, and coverage depth. The study did not identify significant differences in genome coverage and genetic diversity metrics between workflows. Genome Detective consistently identified the correct species across both methods. The findings of this study demonstrate that the COVIDSeq assay can be effectively adapted for multi-pathogen genomic surveillance and that the combined rapid workflow can offer a cost- and labour-efficient alternative with minimal compromise to data quality. Full article