Sci, Volume 8, Issue 8 (August 2026) – 42 articles

Sustainable manufacturing increasingly demands environmentally friendly machining strategies, and dry machining has become recognized as a sustainable alternative to conventional coolant-assisted processes. This study presents a framework built on a machine learning technique for optimizing the dry machining performance of Super Duplex Stainless Steel (SDSS 2507) using textured cutting inserts. Gaussian process regression (GPR) models were developed to predict maximum roughness depth (R_max) and maximum flank wear (VB_max). Gaussian data augmentation was employed to enhance model generalization. The predictive performance was strong, with R² values recorded above 0.95 on testing datasets. To identify optimal machining parameters, GPR was integrated with particle swarm optimization (PSO), enabling independent optimization of R_max and VB_max. The framework achieved reductions of 13.97% in R_max and 30.70% in VB_max compared to experimental benchmarks. The results confirm the effectiveness of data-driven optimization in enhancing surface quality, tool performance, and intelligent machining control. Full article

Mesh resolution is a central source of numerical uncertainty in two-dimensional flood modelling because it controls terrain representation, wetting–drying transitions, computational cost, and the transferability of calibrated parameters. Yet controlled evidence remains limited on whether two widely used solvers exhibit the same resolution response patterns across flood magnitudes. This study compares calibrated model configurations developed in HEC-RAS 2D version 7.0 and SMS 13.0–TUFLOW Classic for a mountainous to low-gradient reach of the Little River, Tennessee, USA, using identical terrain, land cover roughness, and hydrological boundary data. The models were calibrated with the 6–11 April 2025 event and independently validated with the 11–16 March 2026 event. A factorial experiment comprising two models, five cell sizes (15–55 ft), and five flow conditions (the observed event and Q₅₀, Q₁₀₀, Q₂₀₀, and Q₅₀₀ design floods) resulted in 50 simulations. The study simultaneously evaluates resolution sensitivity within each calibrated model and inter-model convergence under a common scenario matrix. Inundation extent was most resolution-sensitive during the lower-magnitude observed event, whereas inter-model extent differences decreased as flood magnitude increased. Outlet hydrographs and peak discharges were comparatively stable, but local water-depth distributions became less consistent as the mesh was coarsened, particularly in SMS-TUFLOW. HEC-RAS retained greater depth consistency, plausibly because its sub-grid property tables preserve cell-scale volume and conveyance information. Overall, mesh adequacy was output- and solver-specific, indicating that grid selection should be based on the intended hydraulic output and supported by explicit spatial stability testing. Full article

The tropical fruits velvet tamarind, baobab, and African locust beans are used as foods and in beverages for medicinal purposes. They are important sources of nutrients and bioactive compounds. This research focused on the bioactive composition in the fruit pulps and seeds of these African plant species. Spectrophotometric analysis of the total phenolic and flavonoid contents, the antioxidant capacity (DPPH, FRAP, and ABTS assays), the quantification and profile of phenolic compounds, hydrosoluble vitamins B and C (HPLC), and fatty acids (GC-FID), and the toxicological analysis of amygdalin (HPLC) and elements (XRF) were assessed. The fruit velvet tamarind exhibited the highest TPC, TFC, and antioxidant capacity, with seed content higher than pulp, primarily due to naringin (54.45 mg/100 g). Baobab presented the second highest TPC and TFC content and antioxidant capacity, with pulp being higher than seed, mainly due to vitamin C (79.97 mg/100 g) and rutin (47.92 mg/100 g). Several bioactive compounds were quantified, such as vitamin C, various hydroxycinnamic acids (caffeic, p-coumaric, chlorogenic, ferulic), hydroxybenzoic acids (gallic, vanillic), and polyphenols (quercetin, catechin, epicatechin, rutin, naringin, procyanidin, kaempferol), as well as fatty acids from the ω-3 and ω-6 series. Amygdalin was not detected in any seeds, and Cd content was higher than 0.05 mg/kg of dry weight. Full article

‘Genetic zipper’ technology—based on CUAD (Contact Unmodified Antisense DNA) biotechnology, briefly CUADb—represents a step forward in eco-friendly pest control. This unique innovative approach is based on a fundamentally new biological mechanism—a two-step DNA containment (DNAc) mechanism. DNAc employs short, unmodified antisense DNA molecules to selectively degrade target pre-rRNA and/or rRNA in insect pests recruiting up-regulated RNase H1 and RT-RNase H during DNAc, disrupting protein synthesis and causing the down-regulation of kinases due to ATP insufficiency and ultimately leading to high mortality rates. Demonstrating exceptional speed and precision, this technology enables the design of effective and selective DNA pesticides (oligonucleotide pesticides) for no less than 15% of known insect pests in a single day. In this review, we highlight the simplicity and global applicability of this technology using case studies involving 12 economically significant pest species, including hemipterans and one spider mite, from five continents. These oligonucleotide pesticides, computationally predicted via the DNAInsector web tool, are supposed to offer 80–90% efficacy against target pests within one–two weeks under laboratory or field conditions. Their action is primarily non-systemic, requiring direct contact. Oligonucleotide pesticides are environmentally safe, biodegradable, and highly specific, reducing risks to non-target organisms. The ‘genetic zipper’ technology not only provides a powerful tool for researchers and practitioners but also opens a new era in DNA-programmable pest management, where personalized, algorithm-driven pesticides can be easily created and applied for sustainable agriculture. Full article

The large-scale integration of photovoltaic generation into distribution grids has introduced significant operational challenges, including voltage excursions, reverse power flows, and increased variability. Battery energy storage systems (BESSs) offer a versatile solution by providing coordinated active- and reactive-power support. However, their scheduling in active distribution networks is challenging because of the non-convex alternating-current (AC) power-flow equations, the nondifferentiability of battery-degradation modeling, and uncertainty in renewable generation and demand. This paper proposes a two-stage methodology for the day-ahead operation of BESSs in ADNs. In the first stage, parallel particle swarm optimization (PPSO) determines the hourly active- and reactive-power schedules of the BESS units. In the second stage, a matrix-based multi-period AC power flow based on successive approximations evaluates the schedules and verifies voltage, thermal, converter-capability, and state-of-charge (SoC) constraints. A rainflow-counting degradation model is incorporated into the objective function to account for cycling and calendar aging costs. The methodology is assessed through ablation analyses comparing active-power-only and coordinated P–Q dispatches, degradation-unaware and degradation-aware scheduling, and serial and parallel PSO implementations. It is validated on modified 33-, 69-, and 136-node systems under deterministic and uncertainty-based operating conditions, including 100 demand and PV-generation scenarios. PPSO is compared with parallel versions of the adaptive Jaya algorithm (AJAYA), genetic algorithm (GA), multi-verse optimizer (MVO), salp swarm algorithm (SSA), grey wolf optimizer (GWO), and vortex search algorithm (VSA), using operating-cost reduction, computational time, solution variability, feasibility indicators, BESS lifetime, and weekly cost analysis. Additionally, exact one-sided Wilcoxon signed-rank tests with Holm adjustment are used to assess the statistical significance of the economic differences between PPSO and the benchmark methods. Results show that PPSO provides the lowest or most competitive operating costs and the shortest computational time in the evaluated cases, while all network and storage constraints remain satisfied. Full article

Background: Acute kidney injury (AKI) is a common complication following cardiac surgery and is associated with increased morbidity and mortality. Contemporary national estimates of its clinical and economic burden in the United States remain limited. Methods: We conducted a retrospective cross-sectional study using the Nationwide Inpatient Sample (NIS) for 2022–2023. Adult hospitalizations undergoing coronary artery bypass grafting (CABG), valve surgery, or combined CABG and valve surgery were identified using ICD-10-PCS codes. Hospitalizations with end-stage kidney disease were excluded. The primary exposure was AKI. Outcomes included in-hospital mortality, length of stay (LOS), non-home discharge, and hospitalization cost. Survey-weighted multivariable regression models were used to evaluate the independent association between AKI and study outcomes. Results: The final cohort included 133,801 hospitalizations, representing an estimated 669,005 cardiac surgery hospitalizations nationally. AKI occurred in 123,240 weighted hospitalizations (18.4%). Compared with hospitalizations without AKI, those with AKI had higher unadjusted mortality (7.21% vs. 0.71%), longer LOS (14.4 vs. 6.3 days), greater rates of non-home discharge (68.1% vs. 41.2%), and higher hospitalization costs ($97,452 vs. $56,253). After adjustment for demographic, socioeconomic, clinical, and procedural characteristics, AKI remained independently associated with in-hospital mortality (adjusted odds ratio [aOR] 9.91, 95% confidence interval [CI] 8.95–11.00), non-home discharge (aOR 2.52, 95% CI 2.42–2.63), prolonged LOS (adjusted rate ratio [aRR] 1.88, 95% CI 1.85–1.91), and increased hospitalization costs (cost ratio 1.59, 95% CI 1.56–1.61). AKI was associated with an adjusted incremental cost of $33,497 per hospitalization, corresponding to an estimated national attributable cost burden of $4.13 billion during the study period. Conclusions: AKI complicates nearly one in five cardiac surgery hospitalizations in the United States and is associated with substantially increased mortality, healthcare utilization, and hospitalization costs. These findings highlight the significant clinical and economic burden of cardiac surgery–associated AKI and support continued efforts to improve prevention, risk stratification, and perioperative management. Full article

This study developed surface-functionalized polylactic acid (PLA) films by depositing electrospun gelatin/chitosan (GE/CH) nanofibrous coatings formulated with and without bioactive phenolic compounds (curcumin and anthocyanin). Evaluating various polymer blending ratios and operational parameters revealed that a GE:CH ratio of 7:3 (v/v), processed at an applied voltage of 25 kV and a collector speed of 300 rpm, provided the most stable electrospinning behavior among those tested, yielding a uniform nanoscale fibrillar network. The deposition of this selected GE/CH layer onto the PLA substrate significantly improved the composite bilayer film’s tensile strength and oxygen barrier properties, although it increased macroscopic opacity. Furthermore, active coatings containing 0.25% and 0.50% (w/w) curcumin or anthocyanin were successfully processed. This 0.50% level was the maximum concentration quantitatively evaluated in the present study, as preliminary observations suggested poorer processability at higher concentrations, which induced premature gelation and needle clogging. While interactions (mostly non-covalent physical interactions) associated with the phenolic compounds synergistically reinforced the mechanical rigidity and reduced the water vapor permeability of the bilayer films, the macroscopic bioactive functionality was limited. The low loading concentrations, coupled with severe optical masking and restricted aqueous extraction, resulted in moderate antioxidant activity (10.31–30.46% DPPH radical inhibition) and no visually detectable halochromic (pH-responsive) color changes. Overall, these findings highlight a significant functional trade-off in the design of active coatings, where structural and mass transport barrier enhancements are achieved, but macroscopic bioactive functionality is constrained, underscoring the necessity for advanced encapsulation strategies in future developments. Full article

This paper proposes that the origin of life may be understood as a cascade of dynamical integration events governed by Painlevé transcendental equations—a class of nonlinear differential equations arising widely in physics, from quantum mechanics to general relativity. Four prebiotic subsystems (mineral catalysts, information polymers, free-energy transducers, and lipid membranes) undergo progressive coupling, tracing a stepwise cascade ($\mathrm{PVI}\to \mathrm{PV}\to {\mathrm{PIII}}^{D_6}\to {\mathrm{PIII}}^{D_7}\to {\mathrm{PIII}}^{D_8}$) along the Chekhov confluence diagram, culminating in the LUCA (Last Universal Common Ancestor). Each step corresponds to a specific biochemical integration event. The Painlevé framework is explicitly phenomenological: it classifies dynamical regimes of subsystem coupling rather than deriving biochemical mechanisms from first principles. A central quantitative feature is a characteristic separation parameter (${\Delta }_{\min }\approx 0.15$) between effective subsystem rates ($r_i={\tau }_i^{-1}$), with oscillation frequencies scaling as $\omega \propto r^{1/2}{\Delta }^{-1/2}$. Several prospective test systems are identified, including the Belousov–Zhabotinsky reaction, the formose reaction, and chemically monitored extreme environments. Existing literature is used to define operational protocols, but no retrospective dataset is treated here as an independent validation of the proposed value of ${\Delta }_{\min }\approx 0.15$. In particular, the formose calculation below is explicitly an illustrative model calculation whose parameters remain to be measured. The framework offers a potential unification of the RNA World, Metabolism-First, and Protocell theories as sequential stages of a single cascade; provides an indicative timeline (4.4–3.5 Ga) anchored to geological constraints; and makes quantitative, falsifiable predictions. A dedicated Scope and Limitations section discusses what the approach does and does not claim. Full article

Battery energy storage systems can reduce the operating cost of active distribution networks while supporting voltage control through their power electronic converters. This paper develops an application-specific multi-operator Differential Evolution (DE) framework for the coordinated active and reactive power scheduling of distributed battery energy storage systems in radial distribution networks with photovoltaic generation. The optimization model minimizes the daily operating cost associated with conventional energy supply, photovoltaic and storage operation and maintenance, and battery degradation. Candidate schedules encode hourly active and reactive power references for three storage converters, producing a 144 dimensional decision vector for a 24 h horizon. Each candidate is repaired to satisfy active power, state of charge, terminal energy, and converter apparent power limits before being evaluated through an alternating current power flow based on matrix successive approximations. The search framework generates three competing trial schedules per target individual by combining established best-guided, random, and current-to-random DE mutation families with a discrete parameter pool, a common feasibility-repair operator, and greedy selection after AC network evaluation. The method is tested on modified 33-node and 69-node active distribution networks and compared with AJAYA, genetic algorithm, multiverse optimizer, and particle swarm optimization. In the deterministic 33-node case, Differential Evolution obtains the lowest best cost, USD 6846.206, and the largest best cost reduction, 2.1838 percent. The scenario study performs separate deterministic optimizations for pre-generated operating realizations and is therefore interpreted as a scenario-conditioned sensitivity assessment rather than as stochastic or robust optimization of one here-and-now schedule. In this assessment, DE achieves the largest average savings: 2.3487 percent in the 33-node network and 2.9314 percent in the 69-node network. Voltage magnitudes, branch loading, converter ratings, and cyclic state of charge constraints are satisfied in all evaluated cases. The results identify the proposed framework as a competitive day-ahead solver within the evaluated cases, while no claim of global optimality or universal superiority over alternative optimizers is made. Full article

Peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC-1α), encoded by PPARGC1A, plays an important role in the regulation of mitochondrial biogenesis, metabolism, and energy balance. Alterations in PGC-1α function have been found in type 2 diabetes mellitus (T2DM) and neurodegenerative diseases (NDs), but molecular similarities in these pathologies have not been comprehensively studied yet. The current systematic review provides a synthesis of preclinical data on the role of PGC-1α in relation to T2DM and NDs. This study was performed in accordance with the PRISMA 2020 statement. PubMed, Scopus, Web of Science and ScienceDirect were screened for studies published between January 2015 and March 2025. Preclinical studies, including in vivo animal studies with and without in vitro studies, were evaluated for risk of bias according to the SYRCLE checklist and modified CAMARADES checklist. Due to the high heterogeneity, data were qualitatively synthesized. Eleven preclinical studies met the inclusion criteria. Decreased PGC-1α signalling was indicated to be linked to mitochondrial dysfunction, oxidative stress, glucose metabolism impairment, insulin resistance and neurodegeneration via AMPK, SIRT1, CREB, FOXO, PPARγ, Parkin/PARIS, and BDNF pathways. Pharmacological interventions and exercise support increased PGC-1α signalling, potentially improved mitochondrial functions and metabolism and facilitated neuronal survival. Though most studies had a low risk of bias, methodological limitations were quite prevalent. PGC-1α is a key molecular mediator between metabolic dysfunction and neurodegeneration and is a potential target for intervention. However, more rigorous translational and clinical studies are required for the validation of results. This systematic review has not been prospectively registered. Full article

This study explores the development of low-friction, water-based coatings tailored for industrial applications in pharmaceutical glass packaging. The study focuses on scalable deposition strategies to obtain durable low-friction coatings suitable for industrial implementation. To balance mechanical performance and application efficiency, two different application approaches based on a two-component coating (aminosilane primer and lubricant) were investigated. In the first case, the coating is deposited in two steps, while in the second, a single deposition step is used. Characterization through contact-angle measurements and X-ray photoelectron spectroscopy confirmed successful deposition of the primer on the glass surface. Scratch resistance tests revealed an increase in the critical load for fracture initiation from 4.5 N for uncoated glass to 6.5 N for the best-performing coating, indicating improved resistance to surface damage. Friction performance was assessed via tribological tests, which demonstrated that the primer–lubricant coatings achieved the lowest coefficient of friction (approximately 0.2), compared with uncoated glass (stabilizing at approximately 0.3 after an initial value of 0.5) and lubricant-only coatings (approximately 0.4–0.5), confirming the beneficial role of the primer in the coating system. Representative profilometry measurements indicated sub-micrometric coating thicknesses, while UV–Vis measurements confirmed that the coatings preserved the high optical transparency of the glass substrate, with average visible transmittance values above 90%. Furthermore, the successful implementation of the coating using an automated spray system demonstrates its potential for scalable industrial production. These findings support the potential of environmentally sustainable water-based coatings for pharmaceutical glass packaging by combining improved mechanical performance with preserved optical transparency and compatibility with scalable spray deposition. Full article

Breast cancer is associated with systemic inflammation and increased cardiovascular risk, and anthracycline chemotherapy may contribute to persistent myocardial injury. This study aimed to evaluate acute changes in inflammatory cytokines and plasma redox status after the first anthracycline cycle and to assess long-term ventricular function after 10 years in women with breast cancer. We conducted a prospective study of 17 patients with breast cancer treated with anthracycline-based chemotherapy at Salvador Hospital, Santiago, Chile. Plasma cytokines were measured at baseline (day −7) and on day +3 after the first cycle using a MILLIPLEX Luminex^® assay. Echocardiographic assessment of left ventricular systolic and diastolic function, together with oxidative stress parameters, was performed at baseline and after 10 years of follow-up. Anthracycline exposure was associated with an acute increase in several cytokines related to inflammatory and vascular remodeling, including EGF, eotaxin, MCP-1, and VEGF. In addition, markers of redox imbalance suggested an acute pro-oxidant response after treatment. At long-term follow-up (10 years), left ventricular ejection fraction (LVEF) remained within the normal range in all patients. However, integrative echocardiographic assessment revealed impaired left ventricular relaxation, evidenced by significant reductions in the mitral inflow E/A ratio, and septal and lateral e′ velocities with respect to baseline, despite preserved estimated filling pressures. These alterations were accompanied by persistent oxidative stress, reflected by persistently elevated levels of lipid peroxidation markers, such as in vivo 8-isoprostanes. In this pilot cohort, anthracycline chemotherapy induced an early inflammatory and oxidative response that was not associated with overt long-term systolic dysfunction but was accompanied by persistent biochemical and diastolic alterations. These findings support the concept of a long-term subclinical cardiotoxic phenotype and highlight the potential value of combining echocardiographic assessment with circulating redox and inflammatory biomarkers to improve long-term cardiovascular surveillance in breast cancer survivors. Full article

Renewable-powered agricultural water systems are often assessed as solar-pumping devices, but their sustainability depends on a service chain linking crop-water demand, hydraulic duty point, power electronics, storage, water quality, governance, operation and end-of-life management. This structured integrative review synthesizes peer-reviewed and practice-oriented evidence on photovoltaic pumping, hybrid renewable irrigation, grid-interactive pumps, micro-hydro assistance and renewable-powered brackish-water reverse osmosis (PV-RO). Evidence was screened across four source families and coded by service function, energy architecture, hydraulic duty and dominant sustainability pathway; recurring combinations were consolidated using explicit separation and merge rules. It develops an archetype-based screening framework for ex ante appraisal of irrigation, desalination and circularity risks. Seven technology-service archetypes are identified: direct PV pumping, PV-to-tank pumping, PV with electrical buffering, grid-interactive PV pumping, PV–wind hybrid irrigation, micro-hydro-assisted irrigation and PV-RO water making. The framework links each archetype to its operating envelope, evidence maturity, enabling subsystems, sustainability pathways, minimum indicators and ordinal triggers for deeper due diligence. Hydraulic storage is usually the lowest-regret reliability buffer for open-field irrigation, whereas batteries are justified mainly when pressure stability, fertigation timing or night-time operation has high agronomic value. PV-RO is a distinct water-making archetype and is environmentally defensible only where feed-water characterization, energy recovery, pretreatment, product-water agronomy, membrane management and permitted concentrate disposal are embedded in design. Two synthetic applications demonstrate archetype selection and due-diligence escalation. Responsible deployment requires service-oriented screening that integrates hydraulic design, groundwater governance, procurement quality assurance, circularity obligations and social inclusion before field implementation. Full article

Proteomics has emerged as a powerful tool for advancing our understanding of brain disorders by enabling large-scale characterization of protein expression, post-translational modifications, and interaction networks. Neurological conditions are often characterized by complex and dynamic molecular changes that are not fully captured by traditional diagnostic approaches. Proteomic technologies, particularly mass spectrometry-based and affinity-based methods, offer the ability to identify disease-specific protein signatures and elucidate underlying pathophysiological mechanisms, including neurodegeneration, neurodevelopment and neuroinflammation and alterations happening to the extracellular matrix and body fluid homeostasis. In recent years, artificial intelligence has emerged as a powerful tool to proteomics, enabling improved analysis of complex biological datasets. This integration has significantly enhanced the discovery of biomarkers for early diagnosis, disease stratification, and monitoring of therapeutic responses. Thus, cerebrospinal fluid and blood-based proteomic analyses have revealed promising candidates for neurological diseases. This review summarizes current advances in proteomics across a range of brain disorders, highlighting key molecular pathways, biomarker discovery efforts, and evolving clinical applications. Furthermore, it outlines future directions, including the application of machine learning for improved biomarker identification and precision medicine. Full article

Type 2 diabetes mellitus (T2DM) is increasingly managed through lifestyle measures, yet the value of pairing structured exercise with a well-characterised phytotherapeutic adjunct remains poorly defined. We examined whether adding Nigella sativa (NS) to combined aerobic and resistance exercise (EX) yields greater improvements in metabolic, inflammatory, and oxidative-stress markers than exercise alone in men with T2DM. In this three-arm randomised controlled trial, 90 sedentary, non-smoking men (aged 40–60 years; T2DM duration > 2 years; glycated haemoglobin (HbA1c) 6.5–9.0%; body mass index (BMI) < 30 kg/m²) were allocated 1:1:1 to control, EX, or EX + NS (2 g/day; n = 30 per group) for four weeks. Fasting blood samples obtained before and after the intervention were used to measure glycaemic indices (fasting blood glucose (FBG) and fructosamine), a lipid panel (total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-c), and high-density lipoprotein cholesterol (HDL-c)), inflammatory markers (tumour necrosis factor-α (TNF-α), interleukin-4 (IL-4), and adiponectin), and oxidative-stress markers (thiobarbituric acid–reactive substances (TBARS) and catalase activity). Outcomes were analysed by two-way repeated-measures analysis of variance (time × group), with partial eta-squared (η_p²) and 95% confidence intervals (CIs) reported for all principal effects. Relative to control, both exercise arms significantly improved body composition and glycaemic, lipid, inflammatory, and oxidative-stress profiles (all p < 0.05). The time × group interaction was significant for every outcome except systolic and diastolic blood pressure and triglycerides. Compared with EX alone, EX + NS produced significantly greater improvements in FBG, HDL-C, TBARS, and catalase activity; changes in fructosamine, total cholesterol, TNF-α, IL-4, and adiponectin favoured EX + NS directionally but did not reach significance after correction for multiple comparisons. Triglycerides, LDL-C, and blood pressure did not differ between the two exercise arms. These hypothesis-generating findings support NS as a candidate adjunct to structured exercise for selected metabolic and redox outcomes, and warrant larger, longer, sex-balanced confirmation. Full article

Electrochemical treatment can provide contaminant destruction, phase separation, ionic polishing, and resource recovery; however, performance cannot be judged by removal efficiency alone. This structured critical review compares electro-oxidation (EO), electrocoagulation (EC), electro-Fenton (EF), electrodialysis (ED), electrodeionization (EDI), capacitive deionization (CDI), flow-electrode CDI (FCDI), and bioelectrochemical systems (BES) in municipal wastewater, industrial effluents, sludge-related applications, and treatment side-streams. Searches of Scopus, Web of Science Core Collection, and PubMed were updated to 22 July 2026, and the evidence was assessed according to treatment function, wastewater realism, operating mode, durability, residual fate, energy and cost boundaries, resource recovery, and life cycle implications. Recent advances include porous flow-through anodes, oxygen-efficient cathodes, selective ion separation materials, and pilot BES configurations. However, scale-up remains constrained by electrode aging, by-products, sludge and concentrate management, oxygen transfer, fouling, competing ions, internal resistance, biological instability, and incomplete long-term economic and environmental evidence. The quantitative results show that the energy, cost, and carbon outcomes depend strongly on the treatment function and system boundary. The evidence for sludge and biosolids is less mature than that for liquid wastewater. Therefore, electrochemical technologies are best positioned as function-specific units within hybrid treatment trains rather than as universal replacements for conventional treatments. Full article

Chronic inflammation is closely associated with cancer progression through the promotion of angiogenesis and tumor-supportive signaling pathways. Tumor necrosis factor-α–induced protein 8-like 2 (TIPE2) regulates leukocyte polarization through phosphoinositide transport and represents a promising therapeutic target for solid tumors. However, the large hydrophobic cavity of TIPE2 presents a significant challenge for inhibitor design. In this work, a quadrant docking grid system was developed to enable fragment docking in defined regions of the binding cavity, facilitating fragment linking with minimal overlap and maximal spatial coverage. To our knowledge, this is the first application of a quadrant grid docking strategy for fragment-based inhibitor design. Fragments were screened using AutoDock Vina 1.2.3 and selected based on both binding affinity and predicted aqueous solubility. The highest-binding linked compounds, F1-F12 and F1-F13, exhibited binding affinities of −12.4 and −11.5 kcal mol⁻¹, respectively. Rational modifications yielded compounds MF112 and MF113 with improved predicted ADME properties while maintaining strong binding affinities of −11.7 kcal mol⁻¹. Molecular dynamics simulations demonstrated stable binding complexes over 5 ns trajectories, with RMSD stabilization after approximately 1–2 ns. These results demonstrate that quadrant-based fragment docking provides an effective strategy for designing inhibitors targeting proteins with large binding cavities and provides promising lead compounds for the development of TIPE2 inhibitors. Full article

Maintaining genetic diversity is essential for the long-term conservation of migratory freshwater fishes facing increasing anthropogenic pressures. Prochilodus magdalenae (bocachico), one of Colombia’s most economically and ecologically important freshwater fish species, supports artisanal fisheries, regional food security, and the livelihoods of local communities but has experienced population declines associated with overfishing, habitat degradation, and hydrological alteration. This study evaluated the genetic diversity and population structure of wild and hatchery-associated P. magdalenae from northern Colombia using sequence-based microsatellite genotyping (SSR-GBS). Sixty individuals (48 wild adults from three localities in the Department of Sucre and 12 hatchery-associated fingerlings from Cereté) were genotyped at seven polymorphic microsatellite loci. Wild populations retained high genetic diversity and exhibited weak but significant genetic differentiation (FST = 0.017, p = 0.003), with only 2% of the molecular variation distributed among populations and high estimated gene flow (Nm = 14.899). Hatchery-associated fingerlings consistently exhibited lower allelic richness while maintaining relatively high heterozygosity. Rarefied allelic richness did not differ significantly among populations (Kruskal–Wallis, p = 0.400); however, hatchery-associated fish consistently showed lower values, highlighting the value of allelic richness as a complementary indicator for evaluating hatchery-produced stocks. These findings provide a genetic baseline for the conservation of P. magdalenae and support incorporating routine genetic monitoring into supportive breeding and restocking programs. Full article

m-phenylenediamine sulfate (mPDS) is used as an oxidative hair dye intermediate and is permitted in cosmetic products in Korea at concentrations up to 3%. However, quantitative data on its dermal absorption remain limited. This study evaluated the in vitro dermal absorption of mPDS using a Franz diffusion cell system. An LC–MS/MS method was developed and validated for quantifying mPDS in receptor fluid, skin, wash solution, and tape-stripped stratum corneum samples. The method showed excellent linearity (r² ≥ 0.9951), with overall accuracy of 85.9–110.9% and precision of 0.7–10.9%, meeting regulatory validation criteria. Dermal absorption studies were performed using mini-pig dorsal skin that satisfied integrity requirements. Oxidative hair dye formulations containing mPDS at 0.7% or 2.1% were applied at 10 mg/cm², and receptor fluid samples were collected for 24 h. Most of the applied dose was recovered in the wash fraction after removal at 30 min. Dermal absorption was 2.90 ± 1.27 and 4.75 ± 2.06 µg/cm² for 0.7% and 2.1% mPDS, respectively. These findings provide quantitative dermal absorption data to support regulatory exposure characterization of mPDS. Full article

Janus nanoparticles (JNPs), named after the bi-faced Roman God has emerged as a hot topic in the present era of nanoscience because of their chemical, structural and physical uniqueness. These particles stand out in the crowd as they are composed of two or more faces with contrasting functional properties in the same molecule. The need for two or more functions in a single molecule that can be used in chemical, biological or physical fields, such as delivering drugs combined with imaging, is the need of the hour and JNPs open gates for addressing this issue as these self-tailored particles have found their application in various in vivo and in vitro domains. However, despite their vivid application, a larger sector of application still needs to be explored. Synthesis methods involve masking, self-assembly and microfluidics, and comparative analysis of these methods, listing their pros and cons, would assist in overcoming the difficulties in the commercialisation of these particles. Moreover, the systematic analysis of differences in their structure with reference to their functionality and characterisation methods would lead us to a better understanding of the subject. This review discusses the various synthesis strategies and their comparison, the anisotropic nature of the JNPs conferring various distinguished properties, their application in emulsion stabilisation, bio-imaging, drug-targeting, drug-delivery, and biosensing domains, the characterisation methods involved, challenges and future aspects. The future aspects section maps a few hypotheses that might be useful in expanding the horizons of usage. The novelty of this review lies in the critical analyses of the synthesis methods and characterisation. Each type of JNP has been analysed for its advantages and limitations, and probable hypotheses to address the existing challenges have been jotted down. Full article

The present research investigates the relationship between urban regeneration initiatives and residential real estate market dynamics by assessing market price appreciation associated with the factors most commonly considered in housing transactions. The study focuses on the Esquilino district in the city of Rome (Italy) with particular attention to the redevelopment of Piazza dei Cinquecento, the major public space located in front of Roma Termini railway station. The intervention aims to improve urban accessibility, reduce traffic congestion, and enhance public space quality through a new spatial configuration and the creation of a tree-lined area. The objective of the study is to verify whether, and to what extent, the ongoing regeneration project has influenced residential property values. To achieve this goal, an econometric analysis is implemented to quantify the contribution of different housing and locational attributes to residential asking prices and to identify the variables that significantly affect value formation within the local market. Given that the initiative is still in progress and approaching completion, the analysis adopts a diachronic perspective by comparing two distinct temporal stages: the ante project phase (second half of 2021) and the in itinere phase (first half of 2025). Building on the findings of a previous pre-intervention study, the research systematically examines changes in market behaviors over time, with the dual purpose of identifying variations in price determinants and analyzing the associations between the current urban transformations and the residential real estate market. The results indicate a substantial stability in the main determinants of residential property prices across the two periods, suggesting that the regeneration initiative has not yet been fully capitalized into market behaviors. However, variations in the contribution and functional relationships of some spatial variables highlight preliminary signs of market adjustment during the ongoing transformation process. The study highlights the importance of monitoring for assessing how urban regeneration processes are progressively incorporated into real estate market dynamics. The proposed framework provides a transferable tool for evaluating regeneration processes in different urban contexts, supporting evidence-based decision-making and the comparative assessment of urban transformation strategies. Full article

Background: Prolonged smartphone use has been proposed to influence postural alignment and pulmonary function; however, continuous relationships among these variables remain uncertain in young adults. Methods: Thirty healthy university students completed assessments of device-recorded average daily smartphone screen time over the preceding seven days, craniovertebral and shoulder-C7 angles during natural standing, forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and positive and negative affect. Eight Spearman correlations were evaluated using 5000-resample bootstrap confidence intervals and Holm adjustment for multiple comparisons. Separate linear regression models examined smartphone screen time as a predictor of FVC and FEV1 after adjustment for biological sex and height. Results: None of the primary correlations was statistically significant after Holm adjustment. The largest estimate was observed between smartphone screen time and FVC (ρ = −0.242, 95% CI −0.540 to 0.101; Holm-adjusted p = 1.000). In adjusted models, smartphone screen time was not significantly associated with FVC (B = −0.054 L per additional hour/day, 95% CI −0.127 to 0.019; Holm-adjusted p = 0.280) or FEV1 (B = −0.027 L per additional hour/day, 95% CI −0.123 to 0.068; Holm-adjusted p = 0.561). Secondary exploratory analyses identified an inverse correlation between shoulder-C7 angle and negative affect and positive correlations between FVC and height and body weight. Conclusions: Statistically significant primary associations among seven-day smartphone screen time, standing postural alignment, and pulmonary function were not detected. These findings do not establish that the variables are independent and should be interpreted cautiously given the small sample and wide confidence intervals. Full article

The growing demand for sustainable alternatives to conventional plastic packaging has promoted the development of biodegradable materials derived from agro-industrial residues. In this study, starch extracted from green banana peel waste was used to produce biodegradable starch–glycerol films for food-packaging applications. Nine film formulations (PPM1–WP6) were prepared using starch obtained through different extraction approaches, including parenchyma-only and whole-peel processing, with and without sodium metabisulfite treatment. The extracted starches were characterized through proximate composition analysis, Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and differential scanning calorimetry (DSC). The resulting films were evaluated for structural, thermal, mechanical, and barrier properties using FTIR, X-ray diffraction (XRD), SEM, dynamic mechanical analysis (DMA), water vapor permeability (WVP), and water solubility (WS). The films exhibited characteristic starch functional groups, semicrystalline structures, thermal degradation temperatures ranging from 283 to 302 °C, and viscoelastic behavior associated with plasticized polymeric matrices. Increasing glycerol concentration improved film flexibility, whereas sodium metabisulfite treatment enhanced mechanical strength. Films prepared from whole-peel starch showed higher WVP and WS values than those obtained from parenchyma starch. A randomized factorial design was used to optimize film performance for maximum tensile strength and minimum water solubility. Among the evaluated formulations, PPM2 (4% starch with sodium metabisulfite treatment) was identified as the optimal formulation and was statistically validated. These findings demonstrate the potential of green banana peel waste as a sustainable source of starch for developing biodegradable films with promising applications in food packaging. Full article

During the last decade, there has been an emergence of isolated scientific studies that have been selectively cited to support claims apparently contradicting the broader evidence base, thus opening the door for scepticism on the one hand and “evidence-based” conspiracies on the other. This dangerous development in science and its wider perception within the population have been facilitated by the rapid growth and digital discoverability of the scientific literature, making it easier to search selectively for the publications that lend support to any, and often the most bizarre, hypotheses. This bias of selective reading of literature constitutes a major challenge for modern science and scientific communication. AI-based tools may help broaden evidence retrieval, yet their outputs require transparent validation and expert oversight to minimise selection bias and to ensure reliable interpretation. Full article

Selenium (Se) is an essential trace element in animals and humans, usually acquired via nutrition and thus often dependent on the Se content of the soil from where the food crops originate. The uneven distribution of Se in soils may therefore result in regional Se deficiencies, often further exacerbated due to climate change and its subsequent effects on Se speciation (i.e., the chemical forms in which Se occurs) and the element’s mobility. In recent years, biofortification has emerged as a promising approach to address this issue. This review provides an overview of how climate-driven changes in Se cycling influence soil Se availability and discusses the resulting implications for plant resilience, crop biofortification and dietary Se supply. Although plants do not require Se per se, an increased Se content of plants may improve their yields, antioxidant defences, and tolerance to various—climate (change)-related—stresses such as drought, salinity, and oxidative stress at low concentrations. So far, selenite (SeO₃²⁻) and selenate (SeO₄²⁻) are the most commonly employed Se species in agriculture, often via foliar and soil applications, and due to their excellent solubility in water are subject to leaching or other weather-related limitations. Alternative Se compounds, such as Se nanoparticles (SeNPs) and selenium sulfide (SeS₂) present promising approaches that may enable a more controlled Se release in soils. Nonetheless, their long-term agronomic performance and environmental behaviour require further investigations. Full article

Diagnosing skin diseases remains a clinical challenge due to the visual similarity among diverse dermatological conditions. This study presents a prototype deep learning–powered system for multi-class dermatological screening, implemented through a cloud-based architecture and accessed via a smartphone interface. A pre-trained Convolutional Neural Network (CNN), EfficientNetV2B3, was fine-tuned on a composite dataset encompassing nine disease categories. The model achieved promising performance, with an accuracy of 0.87, precision of 0.87, recall of 0.87, and an F1 score of 0.86, indicating its potential reliability for automated classification. Prototype validation was conducted using a cloud API (Google Cloud Storage + PostMan) to verify the inference pipeline and user interaction. While the current implementation demonstrates the feasibility of cloud-based dermatological screening, real-device mobile performance metrics such as latency, model size, and memory consumption remain future work. Users can capture or upload skin images, which are processed to generate preliminary diagnostic feedback, including symptom descriptions and general treatment information. While not intended to replace professional medical evaluation, the prototype serves as a proof-of-concept tool for initial screening and early intervention. This work illustrates how artificial intelligence (AI) can be harnessed in mobile health applications to expand access to dermatological care and supports broader initiatives to integrate AI into healthcare delivery. Full article

Background: Artificial intelligence (AI) is increasingly embedded in critical care nursing through monitoring, decision support, and documentation systems, yet nurses’ readiness to use it remains uncertain, particularly in the Middle East region. Critical care nurses are central to AI implementation at the bedside, and their AI-related literacy and fears can influence safe and ethical integration into clinical practice. Aim: To assess AI-related literacy and fears among critical care nurses in Oman and the associated factors. Methods: A nationwide cross-sectional survey was conducted among critical care nurses (N = 477) working in tertiary hospitals in Oman. The Multidimensional Artificial Intelligence Literacy Scale and the Fear towards AI Scale were used to measure AI literacy and fears, respectively. Results: The participants had low overall AI literacy (146.62 ± 84.03), and low AI self-efficacy and AI self-competency. The lowest level of literacy was related to creating AI (2.43 ± 2.63). On the other hand, participants reported moderate overall fear towards AI and moderate levels of fear related to job issues and humanity and ethics. Age, marital status, levels of education, receipt of prior computer or information technology, AI-related training, and work experience, were significant predictors of AI literacy. The predictors of AI self-efficacy and AI competence are presented. Conclusions: Nurses working in critical care settings in Oman reported low levels of AI literacy, but moderate fears related to AI, and this provides an opportunity to build AI competencies and capacity. There is need for deliberate and structured continuing education programs to build capacity for AI utilization, competence, and self-efficacy among critical care nurses. Structured, hands-on AI training that integrates ethical reflection for older nurses with more experience but limited professional education is needed and essential to support safe and equitable AI utilization by critical care nurses in Oman. Full article

Compost quality assessment remains challenging due to substantial variation in standards, analytical methods, and reporting practices across jurisdictions and end-use applications. Differences in testing protocols and quality criteria limit data comparability among studies and compost products, while the absence of a common classification architecture hinders consistent interpretation of compost quality. This study proposes the Compost Pharmacopoeia Framework (CPF), a conceptual framework inspired by the organisational structure of pharmacopoeial systems. Existing standards, including AS 4454:2012, PAS 100:2018, and Regulation (EU) 2019/1009, were critically analysed to identify inconsistencies in physical, chemical, and biological quality assessment. Based on this analysis, the CPF integrates hierarchical classification, analytical methods, application-specific quality criteria, and reference materials within a unified framework for compost characterisation and reporting. The framework further introduces method equivalence concepts to facilitate comparison across non-equivalent analytical approaches. A representative experimental system is used to illustrate how compost quality information can be organised and interpreted within the proposed structure. In the representative nitrogen-regulated green-waste composting case, total nitrogen loss remained below 20%, while treatments were differentiated according to pH stability, nitrogen conservation, and germination performance, illustrating how CPF-organised data can support specific function interpretation. The CPF provides a foundation for improved data comparability, knowledge integration, and application-oriented compost classification, supporting more consistent communication among researchers, regulators, producers, and end-users. Full article

Climate change and wildfire are often treated as separate policy problems, although their costs and ecological consequences converge in fire-prone landscapes. This critical integrative review examines the evidence requirements that connect Mediterranean wildfire-risk governance, restoration, biomass use, carbon accounting, ecosystem services, public procurement and professional capacity. A purposive, theme-based synthesis combines peer-reviewed research, international standards, European Union assessments and audit reports, and Greek implementation documents; Greece is used as a policy case within a wider Mediterranean evidence base. Building on the living- and green-infrastructure literature, this review treats forests as living public infrastructure: dynamic systems whose public functions depend on maintenance, ecological limits and repeated verification. It distinguishes evidence synthesis from policy recommendation and evaluates recurrent shortcuts such as unmaintained fuel continuity, tree planting without diagnosis, carbon dioxide equivalent (CO₂e) claims without credible baselines or permanence strategies, and monitoring platforms without field validation. The resulting framework links risk diagnosis, prioritised intervention, field measurement, integrity gates and public audit. Its scientific contribution is to specify a common evidence chain through which prevention, restoration and climate claims can be compared and tested rather than accepted as activity counts or communication outputs. Full article

The formation of asphalt–resin–paraffin deposits (ARPDs) and gas hydrate deposits (GHDs) in oil wells equipped with electric submersible pumps (ESPs) remains a significant challenge in the oil and gas industry. This study aims to develop an inhibitory technology to prevent these deposits by utilizing the synergistic effect of chemical reagents combined with the optimization of ESP operating parameters. Based on previously published mathematical modeling and laboratory studies by the authors, this work presents the technological implementation of the inhibition system and its economic assessment. Specifically, optimal reagent dosages were calculated considering their synergistic interactions, a periodic injection regime was established, and the impact on the well’s mean time between failures (MTBF) was evaluated. Results demonstrate that optimizing ESP parameters shifts the onset depth of GHD formation by 119.4 m (25%) and ARPD formation by 72.6 m (6%). The application of the selected ARPD inhibitor at 0.055 wt.% reduced the thermodynamic hydrate inhibitor (methanol) dosage by 12.17% and enabled a transition from continuous to periodic methanol injection. Consequently, the predicted MTBF increased from 277 to 419 days (+50%). An eight-year economic analysis showed a positive net present value with a payback period of 14 months. Thus, the proposed technology is recommended for field testing in high-paraffin, low-resin oil fields operating under permafrost conditions. Full article

Understanding the clinical and hospital trajectory of fatal COVID-19 cases is essential to clarify disease progression and support healthcare planning. This study analyzed the temporal trajectory of patients with confirmed COVID-19 who died in Campo Grande, Brazil, during 2021–2022. A retrospective observational study was conducted using secondary data from 3572 fatal cases. Time intervals between symptom onset, hospitalization, intensive care unit (ICU) admission, and death were calculated. Survival analyses were performed using Kaplan–Meier curves and Cox proportional hazards regression. Most patients were aged 61–80 years (48%), male (55%), and had at least one reported risk factor (86%). The most frequent comorbidities were cardiopathy (56%), diabetes mellitus (35%), and obesity (20%). The mean time from symptom onset to hospitalization was 7.70 days, while the mean time from symptom onset to death was 22.87 days. Survival analyses showed significant differences according to age, neurologic disease, pneumopathy, and obesity. In the multivariable Cox model, age remained independently associated with shorter survival time. Fatal COVID-19 cases were characterized by a relatively short interval from symptom onset to hospitalization and a prolonged in-hospital course until death. By characterizing the timing of clinical deterioration, ICU admission, and death, these findings may inform regional assessments of critical care demand, expected ICU bed occupancy, and capacity planning during periods of increased healthcare demand. Full article

Membrane technologies play a role in water treatment, energy conversion, and industrial separation processes; however, their performance is limited by fouling, polarization phenomena, transport inefficiencies, and energy consumption. This study presents a review of the integration of computational fluid dynamics and machine learning in membrane technologies, complemented by an environmental and engineering assessment of representative membrane materials. A systematic literature screening based on PRISMA guidelines was conducted using the Scopus (Elsevier B.V., Amsterdam, The Netherlands) and Web of Science (Clarivate, Philadelphia, PA, USA) databases, yielding 1421 records, of which 54 studies met the predefined relevance criteria. The analysis revealed a transition from conventional physics-based approaches toward hybrid simulation–machine learning frameworks, with artificial neural networks, surrogate models, and optimization emerging as the dominant methodologies. Energy consumption was identified as the most frequently investigated variable, particularly in desalination, fuel cell, electrodialysis, and hydrogen production systems. A complementary material-level assessment showed that conventional polymeric membranes, especially polyamide-based systems, remain dominant due to their performance and economic feasibility, whereas advanced materials such as graphene, carbon nanotubes, and perovskites offer promising functional properties but face challenges. The findings highlight the potential of integrated simulation–machine learning–material assessment frameworks to accelerate the development of intelligent and sustainable membrane technologies for future applications. Full article

Micronutrient deficiencies, collectively known as hidden hunger, affect more than two billion people worldwide and remain a major challenge for sustainable agriculture, global food security and human nutrition. Crop biofortification has emerged as a sustainable agricultural strategy to enhance the concentration and bioavailability of essential micronutrients in edible plant tissues while reducing reliance on post-harvest fortification and dietary supplementation. This review provides an integrated analysis of the soil, plant physiological, agronomic and molecular processes governing biofortification efficiency in agricultural systems. Particular emphasis is placed on how soil formation, mineralogy, nutrient speciation, organic matter and rhizosphere interactions regulate micronutrient availability, root uptake, translocation and accumulation in crops. The review further examines plant physiological mechanisms involved in nutrient acquisition and partitioning, together with the contribution of beneficial microorganisms, precision agriculture and digital technologies to improving nutrient-use efficiency under diverse agricultural conditions. Conventional breeding, agronomic biofortification, transgenic approaches and genome-editing technologies are critically evaluated as complementary strategies for developing nutrient-enriched and climate-resilient crop varieties. Particular attention is also given to nutrient bioavailability, post-harvest stability and consumer acceptance, which ultimately determine the nutritional effectiveness of biofortified crops. Furthermore, the review discusses how climate change modifies soil properties, plant physiology and crop productivity, thereby influencing micronutrient availability, nutrient accumulation and the long-term effectiveness of biofortification programmes. By integrating advances in soil science, plant physiology, agronomy and molecular biology, this review identifies current challenges, knowledge gaps and future research priorities for developing resilient biofortification strategies capable of supporting sustainable agricultural systems and improving global nutritional security. Full article

Marine oil spills represent a critical environmental threat. Petroleum contamination systematically accumulates in the world’s oceans, driving severe and long-term damage to the biodiversity of vulnerable coastal ecosystems. As its primary objective, this study assesses the ocean’s intrinsic genetic capacity to degrade aliphatic and aromatic hydrocarbons. Using the Ocean Gene Atlas v2.0 (OGA2) database, bacterial metabolic pathways were profiled via a four-marker framework: PF00487 (AlkB) and PF03433 (LadA) for medium and long-chain alkanes, alongside PF00355 and PF00848 domains for aromatic ring activation. The analyses revealed that while salinity levels between 34–36 PSU sustain baseline abundances, temperature acts as a primary selective filter, segregating microbial communities into distinct thermal niches. Medium-chain aliphatic potential (PF00487) is ubiquitous, reaching maximum values in surface polar waters near 0 °C before declining with depth. Conversely, long-chain machinery (PF03433) is restricted to warm surface hotspots. Aromatic-degrading potential (PF00355/PF00848) displayed high thermal resilience, narrowing vertically except for a mesopelagic cluster in the Arabian Sea. Global taxonomic analysis confirmed the dominance of Pseudomonadota (59%), which was mainly represented by the class Gammaproteobacteria (15%), with Alcanivorax (10%) as the most abundant genus. On the other hand, aromatic degraders persist as a low-abundance seed bank. In conclusion, the mere presence of specific genes does not automatically imply metabolic expression; actual in situ biodegradation remains strictly governed by transcriptional triggers and environmental factors. Full article

This study assesses the technical performance and environmental impact of traditional and eco-efficient materials used in civil construction in Colombia through a structured synthesis of scientific, technical, and regulatory evidence covering the period 2010–2025. The analysis integrates mechanical performance indicators, environmental footprint metrics, and the national regulatory framework supporting sustainable material adoption. Results show that conventional materials—Portland cement, structural steel, ceramic bricks, and timber—remain essential due to their proven structural reliability but are also responsible for the highest contributions to CO₂ emissions, energy consumption, and resource depletion. In contrast, eco-efficient alternatives, including blended concretes with mineral additions, geopolymers, rammed earth, Guadua angustifolia, and natural biocomposites, achieve carbon emission reductions between 40% and 85% while maintaining comparable mechanical performance for specific applications. Colombian policies—notably Resolutions 1257 of 2021 and 0194 of 2025—promote waste valorization and low-impact materials, yet their implementation remains limited by technical, economic, and knowledge barriers. The findings support a decision-oriented framework for material selection that balances structural efficiency with environmental responsibility. Full article

Series resistance (Rs) is a key parameter that limits photovoltaic cell performance; however, its conventional estimation from current–voltage measurements requires electrical contact and controlled testing conditions. In this study, a nondestructive image-based methodology is proposed to estimate Rs in crystalline silicon photovoltaic cells using electroluminescence images and a Sugeno-type adaptive neuro-fuzzy inference system. A dataset of 666 electroluminescence images was processed using normalized grayscale histogram descriptors, and reference Rs values were obtained from I-V characterization. Three global radiometric descriptors corresponding to low-, medium-, and high-intensity pixel fractions were used as model inputs. The ANFIS model achieved high predictive performance, with a testing RMSE of 0.0065 Ω and an R² value of >0.98. These results indicate that the global EL intensity distributions contain information related to resistive losses. However, further validation under different acquisition conditions and using independent datasets is required before field-scale deployment. The proposed approach provides a compact and interpretable framework for rapid photovoltaic cell screening based on electroluminescence imaging, complementing conventional electrical characterization under controlled laboratory conditions. Full article

Cadmium (Cd) is absorbed by plants and bioaccumulated in their tissues, and its ingestion may cause adverse effects on human health. However, information on the relationship between soil moisture and Cd bioaccumulation in cocoa-growing soils remains limited. The objective of this study was to evaluate the effect of different irrigation volumes (50, 75, 100, and 125%) on Cd bioaccumulation and biomass production in two cocoa genotypes (EET-103 and CCN-51), as well as on soil pH and electrical conductivity (EC), in two soils from El Oro and Guayas, Ecuador. A split-plot design was used with three factors: A (soils), B (genotypes), and C (irrigation). The variables evaluated included plant height, stem diameter, shoot and root dry biomass, Cd absorption, translocation, and bioaccumulation, as well as soil pH and EC. The highest dry matter production and Cd bioaccumulation were observed in genotype EET-103 grown in El Oro soil and in genotype CCN-51 grown in Guayas soil. A higher irrigation volume (125%) increased the pH of El Oro soil and reduced Cd bioaccumulation by 38.48%, whereas pH decreased in Guayas soil under the same irrigation condition. In El Oro soil, pH and EC showed an inversely proportional relationship. These results suggest that irrigation management and the selection of cocoa genotypes with lower affinity for Cd may be useful strategies to reduce Cd bioaccumulation in cocoa plants. Full article

Smart and sustainable construction requires methods that jointly manage construction processes, carbon emissions, energy supply, and decision-making. This study develops a renewable energy (RE)-aware carbon digital twin using Siemens Tecnomatix Plant Simulation, version 2022 (Siemens Digital Industries Software, Plano, TX, USA), hereafter referred to as STPS, and artificial intelligence (AI)-based multi-objective optimization. The framework integrates activity records, equipment-demand profiles, renewable-generation data, battery-storage states, emission factors, cost parameters, schedule indicators, and reinforcement learning (RL) state–action–reward records within a discrete-event simulation environment. Construction activities are represented through event-driven source, queue, buffer, processor, resource-pool, transporter, event-controller, table-file, and sink objects, enabling predecessor validation, resource allocation, processing, completion tracking, and key performance indicator (KPI) updates. The energy layer coordinates equipment demand, solar photovoltaic (PV) generation, battery charging and discharging, grid electricity, diesel backup, RE share, battery state of charge (SOC), and emissions. The AI-control layer observes carbon, cost, delay, queue length, utilization, idle time, renewable share, and SOC; filters infeasible actions; evaluates corrective interventions; and ranks policies under carbon, delay, and SOC constraints. Three scenarios are evaluated: diesel–grid baseline operation, rule-based solar-battery operation, and AI-controlled renewable-aware operation. The AI-controlled scenario achieved 16,850 kg carbon dioxide equivalent (kg CO₂e), a cost of 2.28 million United States dollars (M USD), a delay of 4.2 h, an 81.6% RE share, 86.7% resource utilization, and 8.6% idle time. Relative to the diesel–grid baseline, it reduced emissions by 32.2%, cost by 18.0%, delay by 66.7%, and diesel-equivalent energy by 97.7%, while increasing RE share by 69.3 percentage points. Reward-weight sensitivity results show that the balanced policy preserves low-carbon performance across stakeholder priorities. The findings demonstrate that integrating digital twins, RE dispatch, and AI-based decision control can support data-driven, optimized low-carbon construction management. Full article

The digitalization of healthcare systems has transformed the production, storage, and sharing of clinical information. While electronic health records (EHRs) enhance care efficiency, accessibility, and continuity, they simultaneously introduce complex ethical, legal, and cybersecurity challenges that directly affect patient interests. This narrative review examines the emerging rights associated with digital health records, particularly the right to privacy and the right to be forgotten, alongside threats to confidentiality, cybersecurity, and patient safety. A comprehensive literature search was conducted across PubMed, Web of Science, MEDLINE, and the Cochrane Library. First, the right to be forgotten appears particularly relevant for oncological patients facing financial discrimination and for individuals asserting gender identity rights, yet it cannot be unconditionally extended to genetic data, given its relevance to relatives and future generations. Second, confidentiality risks are amplified by re-identification vulnerabilities, unauthorized access by personnel, and the broad connectivity of digital systems. Third, the secondary use of data from EHRs, including artificial intelligence (AI) integration, commercial exploitation, and large language model training, raises substantial privacy concerns. Fourth, ransomware, phishing, and data breaches can erode patient trust. In this article, we analyze these issues within the evolving European regulatory framework, highlighting the tension between individual privacy rights and broader public interests. We argue that robust data protection must be balanced with scientific progress and that this requires opt-in consent frameworks, staff training, and transparent AI governance. Full article

Bibliometric analysis is widely used to map scientific fields, identify influential publications, and visualize thematic structures, but maps, rankings, and network clusters cannot by themselves produce a scientifically critical review. This article proposes the Bibliometric-Assisted Critical Review (BACR) framework as a writing-oriented conceptual and pedagogical model for authors, doctoral researchers, supervisors, and reviewers working with large and heterogeneous literatures. BACR is presented as a methodological framework and authoring heuristic, not as an empirical study, a new reporting standard, or a substitute for systematic reviews, scoping reviews, meta-analyses, or conventional bibliometric reviews. The framework distinguishes a broad bibliometric corpus from a narrower critical reading corpus and explains how bibliometric signals can be translated into reading decisions, appraisal questions, synthesis moves, and transparent reporting practices. Its practical outputs include a nine-phase writing process, a bibliometric-to-critical translation matrix, a critical appraisal template, a worked mini-example, a recommended manuscript architecture, a preliminary checklist, and a table of common errors. BACR is intended to help authors use science mapping to strengthen, rather than replace, close reading and critical synthesis. The framework is still preliminary and needs to be adapted to specific fields, tested through pilot applications, and validated. Full article

Metal/graphene composites with a metal matrix and graphene reinforcement are very promising innovative materials due to their improved mechanical and physical properties. In this paper, the possibility of fabricating a composite from a graphene network filled with nickel (Ni), copper (Cu) and aluminum (Al) nanoparticles is shown by molecular dynamics simulation. Composites are obtained by hydrostatic compression at 0.7 of the melting temperature of the metal nanoparticles. It is found that the Ni/graphene composite exhibits the highest ultimate tensile strength (89.5 GPa) and Young’s modulus (296.9 GPa) compared to 35.1 and 65.9 GPa for Cu/graphene and 36.8 and 109.1 GPa for Al/graphene, respectively. The Ni nanoparticles were uniformly distributed throughout the graphene network, providing high strength. Indentation simulations confirm this trend: the Ni/graphene composite exhibits a hardness 1.7 times higher than that of pure crumpled graphene, while Al/graphene shows a value 2.2 times lower, which directly correlates with the tensile strength. The Cu/graphene composite has the best ductility (fracture strain of 0.75 versus 0.45 for Ni/graphene and 0.47 for Al/graphene) due to the easier sliding between the Cu nanoparticles and the graphene during tensile loading. The Al/graphene composite has low strength and ductility because the Al nanoparticles tend to coagulate inside the graphene network and hardly interact with the graphene. For Cu/graphene and Al/graphene composites, fracture occurs at the metal/graphene interface. The results show that it is possible to fabricate metal/graphene composites that are much stronger than pure metal by deformation-temperature treatment. In addition, the mechanical properties can be modified by varying the type of metal. Full article

Biochar has emerged as one of the most promising nature-based strategies for improving soil quality, enhancing crop productivity and supporting climate-smart agriculture. However, the agronomic performance of biochar remains highly variable because its effects are governed by complex interactions among feedstock characteristics, pyrolysis conditions, soil properties and management practices. This review synthesizes recent advances in biochar research (2019–2026), examining how production variables determine biochar physicochemical properties and how these properties subsequently influence soil functioning, plant performance and long-term agricultural sustainability. The review integrates evidence on feedstock selection, pyrolysis technologies, biochar modification strategies and the relationships between biochar properties and soil physical, chemical and biological processes. Particular attention is given to crop productivity, nutrient use efficiency, stress mitigation, contaminant immobilization, greenhouse gas mitigation and long-term soil resilience. Across the literature, the most consistent agronomic benefits were observed when biochar was applied to degraded or resource-limited soils and integrated with complementary management practices, whereas responses were often limited under fertile soils, low application rates or short experimental periods. Rather than identifying a universally superior biochar, the evidence indicates that agronomic performance depends on matching biochar characteristics to specific production objectives and environmental conditions. Based on these findings, this review proposes a transition from generalized biochar application towards optimized deployment strategies supported by standardized characterization, long-term multi-site validation and integrated environmental and economic assessments. This synthesis provides a comprehensive framework for guiding future research and facilitating the effective implementation of biochar within sustainable and regenerative agricultural systems. Full article