Search Results (17,127)

Interest in microalgae-based technologies has emerged in recent years as a response to environmental challenges and the global food crisis, for providing alternative and sustainable food products. This study used temperature variations between 18 and 32 °C and nitrogen-to-phosphorus (N:P) ratios between 1.9 and 42.6 to model and optimize growth and composition of Chlorella vulgaris, a nutritionally interesting species. Lower temperatures appear ideal for this strain. An increase in average biomass productivity was observed with decreasing temperature, leading to a maximum of 122.27 mg_dw L⁻¹ d⁻¹ at 18 °C on the fourth day of cultivation. The maximum productivities for total proteins, fatty acids, carbohydrates, and pigments were, respectively, 26.9 mg L⁻¹ d⁻¹, 26.4 mg L⁻¹ d⁻¹, 16.0 mg L⁻¹ d⁻¹, and 2.41 mg L⁻¹ d⁻¹, all referring to 18 °C. The fatty acid, carotenoid, and amino acid profiles were also ascertained; several indicators suggested that cultivation of these microalgae under the aforementioned optimal conditions holds potential for the food industry. The high proportion of polyunsaturated fatty acids—including two essential fatty acids; the high production of lutein, and the presence of several essential amino acids are among the favorable indicators. Overall, the information generated by this study is helpful to support future pilot studies aimed at the commercial production of microalgae-derived products. Full article

The rapid expansion of e-commerce and on-demand logistics has intensified the need for cost-effective and reliable urban distribution systems. This paper investigates an energy-aware routing problem for electric vehicle fleets operating from multiple depots under time-varying traffic conditions. We propose a novel multi-depot vehicle routing model that jointly incorporates time-dependent travel speeds, simultaneous pickup and delivery operations, and time window constraints. The model explicitly captures key operational realities, including battery capacity limitations, load- and speed-dependent energy consumption, synchronized pickup-delivery requirements, and soft time windows. The objective is to minimize total operational cost by simultaneously optimizing depot assignments, vehicle routes, and service schedules. Given the NP-hard nature of the problem, we develop a two-stage heuristic solution framework. In the first stage, a spatio-temporal clustering strategy is employed to assign customers to depots efficiently. In the second stage, route construction and improvement are performed using an enhanced Adaptive Large Neighborhood Search (ALNS) algorithm equipped with problem-specific destroy and repair operators. Computational experiments on adapted benchmark instances demonstrate that the proposed approach consistently produces high-quality solutions and exhibits robust convergence behavior. In addition, sensitivity analyses provide managerial insights, revealing an optimal range of vehicle energy capacity and an economically efficient speed band that balances travel time and energy consumption. Full article

Emergency messages and augmented reality (AR) are becoming integral to intelligent vehicular systems, but their existence poses significant challenges due to conflicting requirements. Emergency short messages demand ultra-low latency and strict reliability, while AR contents require larger data transfers with more flexible but still location-sensitive deadlines. To address this, a joint problem of roadside unit (RSU) assignment and transmission scheduling in multi-server, multi-user MEC-enabled vehicular networks is studied. The problem is formulated as an NP-hard optimization task and a two-stage framework is proposed. First, the penalty-minimizing RSU selection (PMRS) algorithm assigns requested content to RSUs by minimizing combined deadline and coverage penalties. Then a hybrid scheduling algorithm called deadline-aware priority scheduling (DAPS) is proposed, which integrates earliest-deadline-first and simulated annealing to prioritize emergency traffic while efficiently serving AR content. We benchmark the proposed framework against classical heuristics and metaheuristics. The results verify that the proposed approach can outperform the baseline methods under various realistic vehicular mobility and traffic conditions. Full article

The invasive fall armyworm (Spodoptera frugiperda) threatens Philippine crops, highlighting the need for sustainable pest management. This study therefore optimizes the green synthesis of silver nanoparticles (AgNPs) from water hyacinth (Eichhornia crassipes), an abundant and problematic aquatic weed, as a potential pest control tool. Methanolic leaf extracts were prepared under varying methanol concentrations, temperatures, and extraction times, and total phenolic content was quantified using the Folin–Ciocalteu method. SEM–EDX confirmed the formation of silver nanoparticles synthesized from Eichhornia crassipes (Ec-AgNPs), with particles observed at ≤100 nm. Optimal extraction occurred at 47 °C, 90% methanol, and 76 min, maximizing phenolic yield. Overall, results suggest phenolic content and extract volume influence nanoparticle size and stability, with larger extract volumes increasing agglomeration risk. Pesticidal efficacy was not evaluated; further work is needed to assess pest control performance. Full article

Background: The aim of this study was to derive and internally validate a prescriptive clinical prediction rule (CPR) for identifying baseline factors associated with short-term clinical improvement in patients with neck pain (NP) undergoing a manual therapy (MT)-based physiotherapy program. Methods: A prospective cohort study was conducted, including 71 patients with NP (18–65 years). Participants received six MT-based sessions over three weeks. Baseline assessments included Pain Intensity Numeric Rating Scale (PI-NRS), Neck Disability Index (NDI), Body Mass (BM), Body Mass Index (BMI), International Physical Activity Questionnaire-Short Form (IPAQ-SF), Hospital Anxiety and Depression Scale (HADS), Minnesota Satisfaction Questionnaire-Short Form (MSQ), and Craniovertebral Angle (CVA). Clinical improvement was defined using the Global Perceived Effect Scale (GPES-7). Univariate analyses, receiver operating characteristic (ROC) curve analysis, and forward stepwise logistic regression were performed to derive the predictive model. Results: Fifty-six participants (78.9%) reported moderate to complete improvement. BM ≥ 76.5 kg and MSQ score ≤ 42.5 were retained in the final regression model. When both predictors were present, the probability of clinical improvement increased to 96.43% (positive likelihood ratio = 7.58). The model demonstrated adequate fit (Nagelkerke R² = 0.247; Hosmer–Lemeshow p = 0.804). Internal validation yielded an optimism-corrected AUC of 0.741, suggesting minimal overfitting. Conclusions: Higher BM and lower MSQ score were associated with greater short-term improvement following MT in patients with NP. These findings highlight the relevance of integrating physical and psychosocial factors in prescriptive rehabilitation approaches. External validation of this CPR is required before clinical implementation. Full article

Inhalation is a primary route of exposure to engineered nanomaterials (ENMs), enabling particles to penetrate deeply into the lungs and subsequently leading to adverse health effects. Human health risk assessment addresses the potential risk posed by ENMs. The aim was achieved by measuring the emissions of ENMs using real-time instrumentation and subsequently applying the data to evaluate associated human health risks using ModelRisk. Emissions during the synthesis of silver nanoparticles (AgNPs), gold nanoparticles (AuNPs), graphene 2D (G2D) nanomaterials, multiwalled carbon nanotubes (MWCNT) and the application of AuNPs on black carbon electrodes were monitored using a NanoScan SMPS Model 3910 and Optical Particle Sizer (OPS) Spectrometer Model 3330. The derived mass-based time-weighted average concentrations were reported for AgNPs and MWCNTs in comparison with occupational exposure limits (OELs). AgNP concentrations of 0.36 µg/m³ and 3.99 µg/m³ for the NanoScan SMPS and OPS, respectively, exceeded the OEL of 0.19 µg/m³, whereas MWCNT concentrations (0.261 µg/m³) remained below the OEL of 1 µg/m³. AuNP synthesis resulted in particle number concentrations exceeding the provisional nano reference value of 20,000 particles/cm³ for the OPS data (3.74 × 10⁴ particles/cm³), whereas application of AuNPs on carbon black electrodes was below this limit. Although no OEL exists for graphene, risk estimates indicated potential adverse health effects like those observed for AgNPs, AuNPs, and MWCNTs. Measured exposure concentrations were applied in a human health risk assessment model, highlighting ENM concentration as a key determinant of risk. These findings emphasise the need for continuous monitoring, further risk assessment studies, and proactive risk management strategies. Full article

Silver nanoparticle (AgNP)-based products have been increasingly applied in aquaculture due to their antimicrobial properties and capacity to modulate host immunity. This study investigated the biological activities of synthesized silver nanowires (AgNWs), with particular emphasis on their anti-Vibrio efficacy and immunomodulatory effects, to evaluate their potential application in shrimp aquaculture. Antibacterial activity was assessed using nonlinear regression analysis to determine minimum inhibitory concentrations (MICs) against three major Vibrio pathogens, while cytotoxicity and immune responses were evaluated using white shrimp hemocytes through cell viability assays and in vitro gene expression analysis, respectively. AgNWs exhibited antibacterial effects on Vibrio parahaemolyticus, Vibrio alginolyticus, and Vibrio harveyi, with MIC values of 873.7, 58.78, and 672.1 μg/mL, respectively. Hemocyte viability remained above 90% at AgNW concentrations of up to 1000 mg/L, indicating good biocompatibility. AgNWs significantly upregulated immune-related lipopolysaccharide and β-1,3-glucan-binding protein (LGBP) and Toll gene expression at specific concentrations, indicating immunostimulation. These results suggest that AgNWs possess antibacterial activity and immunomodulatory potential with low cytotoxicity, supporting their promise as a novel functional agent for shrimp disease management. Full article

Jujube (Ziziphus jujuba Mill.) cultivation in arid regions of China faces severe soil constraints, including high alkalinity, low organic matter content, and poor water retention. Although soil amendments have demonstrated potential for improving soil quality, their combined effects on soil–plant–microbe interactions in desert agroecosystems remain poorly understood. This study conducted a three-year field experiment in a desert jujube orchard in southern Xinjiang, China, to evaluate six nitrogen fertilizer management strategies: urea alone (CK) or combined with biochar (NB), bentonite (NP), graphene (NS), biochar plus bentonite (NBP), or microbial inoculants (NW). Soil physicochemical properties, enzyme activities, bacterial community structure, and jujube yield were analyzed. Structural equation modeling (SEM) was employed to elucidate the pathways linking soil amendments to crop productivity. Results showed that NBP was the most effective in improving soil physical structure, significantly reducing bulk density and enhancing water retention capacity compared to the control. The NBP treatment also enhanced soil organic matter (30% increase), available phosphorus (119% increase), and urease activity (44% increase), resulting in the highest jujube yield (7.14 kg per tree). Bacterial community analysis revealed that NBP significantly increased Shannon diversity and enriched Actinobacteriota and Proteobacteria. SEM analysis indicated that urease activity served as a significant mechanistic pathway linking soil organic matter improvements to enhanced crop productivity. These findings demonstrate that combined application of biochar and bentonite with nitrogen fertilizer represents an effective strategy for improving soil quality, enhancing microbial functionality, and increasing crop yield in desert jujube orchards, providing a practical and synergistic amendment combination for sustainable soil management and productivity enhancement in arid agroecosystems. Full article

The inhomogeneity of the evaporation duct significantly influences electromagnetic propagation. Based on observation data from four buoy stations in the northern South China Sea (SCS) and European Centre for Medium-Range Weather Forecasts (ECMWF) data, the Naval Postgraduate School (NPS) model is employed to calculate the evaporation duct height (EDH). The concept of information entropy is used to assess the horizontal inhomogeneity of the evaporation duct and the evaporation duct height entropy (EDHE) is defined as the assessment index. The research findings are as follows: (1) The probability of EDH differences based on statistical methods between stations falling within the range of −2 m to 2 m remains above 60%, with uniformity characteristics showing minimal variation throughout the day. (2) The EDHE can better quantify the horizontal inhomogeneous characteristics of EDH between buoy stations compared to statistical methods. (3) The monthly variation characteristics of EDHE between buoy stations based on ECMWF reanalysis data are quite consistent with actual observations, but it overestimates the EDHE values. Therefore, the EDH derived from ECMWF data leads to an overestimation of inhomogeneity characteristics compared to buoy observations. Full article

Plant functional traits, as indicators of community responses to disturbances, are key drivers of ecosystem service multifunctionality (ESMF). However, the relative contribution of these traits to ESMF across different steppe types remains unclear. Using data from 101 sampling sites across Inner Mongolia’s meadow steppe (MS), typical steppe (TS), and desert steppe (DS), we examine the contributions and driving mechanisms of abiotic (climate and soil) and biotic factors (23 community-weighted mean functional traits and diversity indices) to ESMF across different steppe types. Our results show significant differences in ESMF across steppe types, with a decreasing trend from MS to TS to DS. Crucially, the driving factors of ESMF shift fundamentally across steppe types. In MS, ESMF is primarily driven by biotic factors (e.g., stem N:P ratio), whereas as aridity increases, abiotic factors (e.g., aridity and soil clay content) become more influential, ultimately dominating ESMF in DS. This shift from niche differentiation to environmental filtering as the dominant mechanism provides a crucial framework for predicting ecosystem service responses to global change. It highlights the importance of context-dependent grassland conservation strategies, advocating for location-specific management based on environmental gradients. Full article

Upon the challenges of climate change and the demand for energy sustainability, nuclear power (NP) units not only provide clean electricity but are also equipped for cogeneration to achieve energy cascade utilization; this represents a key avenue for improving the overall efficiency and achieving the comprehensive utilization of nuclear energy. However, following the heating retrofitting stage, there exists a risk that the supply control valve of the unit may accidentally open completely during operation, which increases the risk of over-powering. Therefore, this study designs response schemes for second-generation large pressurized water reactor NP plants (NPPs) under the accidental full-open condition of the heat-supply control valve. Specifically, an integrated model encompassing the nuclear steam supply system, secondary circuit system, thermal energy supply system (TESS), and related control systems was constructed using the optimal estimation program and 3KeyMaster simulation platform. Subsequently, two response schemes were designed for the accidental full-open valve scenario under two operation modes—namely, the “Reactor Follows Turbine + TESS” and “Turbine Follows TESS” modes. Finally, on the basis of the established simulation platform, the scenario of accidental full opening of the heat-supply control valve was simulated and verified. Ultimately, the results indicate that the response scheme implemented under the “Turbine Follows TESS” mode is more effective in suppressing nuclear overpower when the heat supply control valve accidentally opens fully. Thus, overall, this study provides a feasible accident response strategy and critical technical reference for NPPs involving cogeneration and energy cascade utilization. Full article

Surface plasmon resonance (SPR) sensors based on nanostructured metasurfaces offer enhanced sensitivity through engineered electromagnetic responses. In this study, we present an analytical and numerical investigation of the plasmonic behavior of gold nanopillar (Au-NP) and nanohole (Au-NH) arrays under both p- and s-polarized illumination, employing the Effective Medium Theory (EMT) in combination with the Transfer Matrix Method (TMM). The study combines Effective Medium Theory (EMT) and the Transfer Matrix Method (TMM) to describe the macroscopic optical response of multilayer plasmonic systems. For p-polarization, the nanostructure geometry strongly modulates the real and imaginary parts of the effective permittivity, with nanoholes supporting stronger SPR coupling and reduced optical losses compared to nanopillars. Under s-polarization, the effective permittivity remains largely invariant, primarily driven by the filling fraction. The analysis reveals that polarization-dependent behavior arises from boundary-condition-mediated coupling mechanisms governing surface plasmon excitation, aligning with classical plasmonic theory. Benchmarking against analytical dispersion relations and published experimental data for Au/BK7 systems shows close agreement within ±2°, confirming the physical consistency of the EMT–TMM framework. These results provide a systematic description of how polarization and filling fraction jointly modulate SPR coupling. The results offer a foundation for the rational design of plasmonic coatings and SPR-supporting metasurfaces by elucidating macroscopic coupling trends; however, no quantitative sensor performance metrics, such as refractive index sensitivity or figure of merit, are evaluated in this work. Full article

The pronounced heterogeneity of high-Andean soils constitutes a critical constraint to the sustainable productivity of quinoa in southern Peru, where current yields (1.6 t ha⁻¹) remain well below potential (>5 t ha⁻¹). This study aimed to develop a spatially predictive model of a weighted soil quality index (SQIw), the edaphic supply of nitrogen (N), phosphorus (P) and potassium (K), and the agricultural gypsum requirement by integrating edaphoclimatic covariates through regression–kriging. A total of 198 quinoa-cultivated soil samples were analysed; a minimum data set (MDS) was defined using correlation and principal component analyses, and regression–kriging was applied to map SQIw and the variables of interest. The MDS comprised electrical conductivity (EC), organic matter (OM), available P, exchangeable Na, sand, clay, and effective cation exchange capacity (ECEC); exchangeable Na (Wi = 0.160) and available P (Wi = 0.158) received the largest weights in the SQIw. SQIw values ranged from 0.22 to 0.84 and supported a five-class soil quality taxonomy; spatial modelling revealed a dominance of moderate-quality soils across the territory (85.21% of the agricultural area, 13,461.19 ha). The model achieved R² = 0.56, RMSE = 0.05, and MAE = 0.04 for SQIw. Most of the area (12,175.65 ha; 77%) exhibited an intermediate gypsum requirement (9.73–14.33 t ha⁻¹). Nitrogen and phosphorus showed the greatest territorial limitations, whereas potassium was largely non-limiting (84.82–570.17 kg ha⁻¹). These results indicate that sodicity and N–P deficiencies are the primary functional constraints; the generated maps enable prioritisation of gypsum amendments and targeted variable-rate fertilisation strategies to optimise the sustainability of quinoa production in the Altiplano. Full article

Diabetic kidney disease (DKD) persists as the leading cause of chronic kidney disease (CKD) and often leads to end-stage renal disease (ESRD). Worldwide, 30–50% of patients with diabetes are affected by DKD, while DKD contributes to about half of ESRD. Previously, DKD had been defined based on overt proteinuria—that is, a urine albumin-to-creatinine ratio (UACR) above 300 mg/g—after a stage of microalbuminuria (UACR 30–300 mg/g). However, emerging data suggest that a significant number of patients develop renal functional decline without albuminuria, suggesting that DKD can occur in the absence of protein excretion. This phenotype of normoalbuminuric or non-proteinuric DKD (NA-DKD or NP-DKD) is emerging as an important clinical entity. It is characterized by a gradual decline in renal function, commonly with an annual reduction in estimated glomerular filtration rate (eGFR) > 3 mL/min/1.73 m² or an eGFR < 60 mL/min/1.73 m², while the UACR remains < 30 mg/g. Growing rates of NP-DKD expose limitations inherent in traditional models of DKD pathogenesis and underscore the need for diagnostic and therapeutic paradigms that are not reliant on albuminuria-only criteria. Here, we present a comprehensive review of the NP-DKD to guide a more inclusive model of DKD pathogenesis, its diagnosis, and therapy. Full article

This work presents a classical theoretical framework in which combinatorial optimization emerges from the nonlinear relaxation of coupled real-valued phase fields governed by a global Lyapunov energy functional. Each computational element (CF-bit) evolves in a bistable periodic potential while pairwise interactions encode problem-specific couplings, enabling gradient-descent minimization of QUBO and Ising objective functions. The key contribution is an explicit global energy functional from which all dynamics are derived, guaranteeing monotonic energy descent under damping. This distinguishes the approach from several existing oscillator-based Ising architectures where the governing dynamics contain non-gradient terms and an explicit global Lyapunov functional has not been derived in their standard formulations. Numerical simulations on instances up to 20 bits demonstrate deterministic phase-locking convergence, with optional transient noise improving the exploration of rugged landscapes. While limited in scale and not overcoming NP-hardness, this work provides a conceptual framework showing how discrete optimization can emerge from continuous classical dynamics with a mathematically transparent energy structure. Full article