Search Results (2,432)

The biological performance and carbon dioxide (CO₂) flux of the novel and emerging concept of a membrane carbonated microalgal biofilm photobioreactor (MC-MBPBR) for wastewater treatment were investigated using mathematical modelling in conjunction with the finite-difference method. A set of differential equations was established to model the performance of an MC-MBPBR. The impacts of CO₂ partial pressure, wastewater characteristics, and biofilm thickness on the concentration profiles and fluxes of CO₂ and nutrients (N and P) to the biofilm of the MC-MBPBR were systematically studied. The modelling results showed profound impacts of these parameters on process efficiency (CO₂ transfer and N and P removals) and the existence of an optimal biofilm thickness for maximum CO₂, N, and P fluxes into the biofilm. Penetration of CO₂ through the biofilm into the bulk water phase might occur under certain conditions. An increase in gaseous CO₂ and increased influent N and P concentrations led to higher CO₂, N, and P fluxes. The optimal biofilm thickness varied with the change in wastewater characteristics and gaseous CO₂ concentration. The modelling results were in relatively good agreement with experimental results from the literature. The proposed mathematical models can be used as a powerful tool to optimize the design and operation of the novel MC-MBPBR for wastewater treatment and microalgae cultivation. Full article

In today’s fierce market competition, enterprises must quickly attract consumers’ attention to products and prompt them to make purchases. Based on regulatory focus theory, this study examines the impact of the congruence between different types of goal framing in advertising (promotion vs. prevention) and product types (hedonic vs. utilitarian) on individual consumer decision-making, as well as the underlying psychological mechanisms. The findings are as follows: (1) A goal-framing effect was observed, such that individuals allocated more attention and exhibited higher purchase intentions toward products presented with promotion-framed advertising. (2) A matching effect between goal-framing type and product type was identified: promotion framing increased purchase intentions for hedonic products, whereas prevention framing increased purchase intentions for utilitarian products. (3) Processing fluency mediated the effect of goal–product matching on consumer decision-making. (4) The presence of time pressure amplified the goal-framing effect, leading to stronger preferences under promotion-framed advertisements, as reflected in both longer fixation durations and higher purchase intentions. By integrating regulatory focus theory with product type matching, this study leverages eye-tracking data to reveal the cognitive processes underlying consumer decision-making and the moderating role of time pressure on goal-framing effects. The findings enrich the motivational perspective in consumer behavior research and provide empirical guidance for designing differentiated advertising strategies and optimizing advertising copy. Full article

High hydrostatic pressure (HHP) significantly modulates microbial metabolism, while chemical epigenetic modifiers are known to reactivate silent biosynthetic gene clusters and induce novel natural products. However, the mechanisms by which these epigenetic modifiers regulate fungal responses under differential pressure conditions, and how such regulation affects natural product biosynthesis, remain completely unexplored. Here, we investigated the hadal fungus Alternaria alternata CIEL23 isolated from 7332 m sediments in the Mariana Trench under epigenetic modifier treatment with contrasting pressures (0.1 MPa vs. 40 MPa). Our results revealed that epigenetic perturbations and high pressure significantly altered fungal phenotypes, gene expression, and secondary metabolite composition. Transcriptome-level analysis of epigenetic regulatory mechanisms under epigenetic modifiers in both pressure conditions (0.1 MPa and 40 MPa) demonstrated that the addition of epigenetic modifiers regulated MAPK pathway-related gene expression in response to the environment stimuli. Under dual stress conditions, the IG, CWI, and HOG branches of the MAPK pathway showed significantly altered activity patterns. These changes were associated with differential the regulation of genes related to hyphal growth, cell wall remodeling, cell cycle progression, and osmolyte synthesis, suggesting the coordinated modulation of multiple cellular processes. These findings provide the mechanistic link between epigenetic modification induced HHP-response changes and regulation in hadal fungi. Our study not only advances understanding of hadal fungal response to dual stressors but also unlocks new possibilities for harnessing their stress-driven metabolic versatility for biotechnological applications. Full article

To address the problem of flow-induced resonance in the valve core assembly of a pilot-operated molten salt regulating valve in a concentrated solar thermal power generation molten salt energy storage system under high pressure differential and high flow rate conditions, the flow-induced vibration characteristics of the pilot-operated molten salt regulating valve were analyzed using computational fluid dynamics (CFD) and fluid–structure interaction modal analysis. The vibration characteristics of the valve core assembly under the excitation force of the molten salt medium were analyzed using the harmonic response method, and the influence of different parameters on the valve core assembly’s vibration characteristics was studied. The results show that under typical operating openings, the first six modal frequencies of the valve core motion assembly are not close to the fluid excitation frequency, indicating that flow-induced resonance does not occur. The maximum vibration stress and displacement of the valve core assembly decrease with increasing damping ratio. With increasing pressure differential, the maximum stress and maximum amplitude of the valve core assembly increase. By changing the valve stem constraint conditions, the vibration stress of the valve core assembly can be reduced. This study provides a reference for the design of flow-induced vibration suppression for pilot-operated molten salt regulating valves and provides guidance for the safe operation of concentrated solar thermal power generation molten salt regulating valves under high pressure differential and high flow rate conditions. Full article

Mobile genetic elements such as integrons are key drivers of microbial evolution, enabling rapid adaptation to environmental pressures through the acquisition and rearrangement of gene cassettes. In this study, we explored the structural diversity and synteny of class 1 integrons (intI1) across a set of agroecosystem-related environments, including digestate, compost, and rhizosphere soils from wheat crops (Triticum durum and T. aestivum). Our results reveal distinct gene cassette architectures shaped by the origin of the samples: digestate harbored the most diverse and complex arrays, while compost displayed streamlined structures. Rhizosphere soils exhibited intermediate configurations, reflecting a dynamic balance between environmental exposure and host influence. Genes associated with resistance to antibiotics and heavy metals, such as qacEΔ1 and ebrA, were differentially distributed, suggesting site-specific selective pressures. The observed patterns of cassette organization and diversity underscore the role of integron synteny as a molecular fingerprint of microbial adaptation. These findings position class 1 integrons as promising bioindicators of soil health and functional resilience, supporting a One Health approach to sustainable agriculture and microbial risk monitoring. Full article

The current green building assessment system suffers from issues such as insufficient coverage of smart indicators, significant biases in subjective weighting, and weak dynamic adaptability, which restrict the scientific promotion of green buildings. This study focuses on the gaps in the quantitative assessment of smart technologies in China’s green building evaluation standards (such as the current Green Building Evaluation Standard). While domestic standards are relatively well-established in traditional dimensions like energy conservation and environmental protection, there are fragmentation issues in the assessment of smart technologies such as the Internet of Things (IoT) and BIM. Moreover, the coverage of smart indicators in non-civilian building fields is significantly lower than that of international systems such as LEED and BREEAM. This study determined the basic framework of the evaluation indicator system through the Delphi method. Drawing on international experience and contextualized within China’s (GB/T 50378-2019) standards, it systematically integrated secondary indicators including “smart security,” “smart energy,” “smart design,” and “smart services,” and constructed dual-drive evaluation dimensions of “greenization + smartization.” This elevated the proportion of the smartization dimension to 35%, filling the gap in domestic standards regarding the quantitative assessment of smart technologies. In terms of research methods, combined weighting using the Analytic Hierarchy Process (AHP) and entropy weight method was adopted to balance subjective and objective weights and reduce biases (the resource conservation dimension accounted for 39.14% of the combined weights, the highest proportion). By integrating the grey clustering model with the whitening weight function to handle fuzzy information, evaluations were categorized into four grey levels (D/C/B/A), enhancing the dynamic adaptability of the system. Case verification showed that Project A achieved a comprehensive evaluation score of 5.223, with a grade of B. Among its indicators, smart-related ones such as “smart energy” (37.17%) and “smart design” (37.93%) scored significantly higher than traditional indicators, verifying that the system successfully captured the project’s high performance in smart indicators. The research results indicate that the efficient utilization of resources is the core goal of green buildings. Especially under pressures of energy shortages and carbon emissions, energy conservation and resource recycling have become key priorities. The evaluation system constructed in this study can provide theoretical guidance and technical support for the promotion, industrial upgrading, and sustainable development of green buildings (including non-civilian buildings) under the dual-carbon goals. Its characteristic of “dynamic monitoring + smart integration” forms differentiated complementarity with international standards, making it more aligned with the needs of China’s intelligent transformation of buildings. Full article

The AP2/ERF transcription factor family plays pivotal roles in plant growth, stress responses, and defense mechanisms, yet its diversity in camphor trees remains underexplored. This study identified 154 AP2/ERF genes in the Camphora officinarum genome, with over 80% belonging to the ERF subfamily, a distribution consistent with other angiosperms. Synteny analysis revealed that tandem and segmental duplications were key drivers of family expansion, suggesting adaptive diversification under ecological pressures. Structural analysis showed that the majority of ERF/RAV subfamily genes possess a single-exon structure, whereas AP2 subfamily genes display muti-exon structures, indicating divergent evolutionary trajectories and potential functional versatility via alternative splicing. Promoter analyses detected numerous hormone- and stress-responsive elements, linking these genes to abscisic acid, auxin, gibberellin signaling, and pathogen defense. Further expression profiling during stem development showed that approximately 60% of CoAP2/ERF genes were constitutively expressed across 17 expression trends, suggesting roles in basal development and stage-specific processes (e.g., lignification). Under Epicoccum poaceicola infection, 23 CoAP2/ERF genes were differentially expressed. Among them, upregulated ERF homologs related to RAP2.2/2.3 suggested roles in hypoxia and antimicrobial responses, while downregulation of ERF5 homologs indicated a growth–defense trade-off, whereby developmental processes are suppressed to prioritize pathogen resistance. Overall, this study deciphers the genomic architecture and structural diversity of CoAP2/ERF genes, along with expression dynamics of these genes in development and biotic stress adaptation of camphor trees. These findings provide critical insights into transcriptional regulation of development and stress responses in camphor trees and establish a theoretical basis for molecular breeding and biotechnological strategies aimed at improving stress resilience in woody plants. Full article

In many scientific and engineering fields, such as hydrogeology, petroleum engineering, geotechnical research, and developing renewable energy solutions, fluid flow modeling in porous media is essential. In these areas, optimizing extraction techniques, forecasting environmental effects, and guaranteeing structural safety all depend on an understanding of the behavior of single-phase flows—fluids passing through connected pore spaces in rocks or soils. Darcy’s law, which results in an elliptic partial differential equation controlling the pressure field, is usually the mathematical basis for such modeling. Analytical solutions to these partial differential equations are seldom accessible due to the complexity and variability in natural porous formations, which makes the employment of numerical techniques necessary. To approximate subsurface flow solutions, traditional methods like the finite difference method, two-point flux approximation, and multi-point flux approximation have been employed extensively. Accuracy, stability, and computing economy are trade-offs for each, though. Deep learning techniques, in particular convolutional neural networks, physics-informed neural networks, and neural operators such as the Fourier neural operator, have become strong substitutes or enhancers of conventional solvers in recent years. These models have the potential to generalize across various permeability configurations and greatly speed up simulations. The purpose of this study is to examine and contrast the mentioned deep learning and numerical approaches to the problem of pressure distribution in single-phase Darcy flow, considering a 2D domain with mixed boundary conditions, localized sources, and sinks, and both homogeneous and heterogeneous permeability fields. The result of this study shows that the two-point flux approximation method is one of the best regarding computational speed and accuracy and the Fourier neural operator has potential to speed up more accurate methods like multi-point flux approximation. Different permeability field types only impacted each methods’ accuracy while computational time remained unchanged. This work aims to illustrate the advantages and disadvantages of each method and support the continuous development of effective solutions for porous medium flow problems by assessing solution accuracy and computing performance over a range of permeability situations. Full article

In this study, a prototype system was developed as a potential alternative to lockdown measures against the spread of airborne infectious diseases such as COVID-19. The system integrates real-time estimation functions for respiratory flow and mask leakage into a low-cost powered air-purifying respirator (PAPR) designed for the general public. Using only a single differential-pressure sensor (SDP810) and a controller (Arduino UNO R4 WiFi), the respiratory flow (Q_3e) is estimated from the differential pressure (ΔP) and battery voltage (V_b), and both the wearing status and leak status are transmitted to and displayed on a smartphone application. For evaluation, a testbench called the Respiratory Airflow Testbench was constructed by connecting a cylinder–piston drive to a mannequin head to simulate realistic wearing conditions. The estimated respiratory flow Q_3e, calculated solely from ΔP and V_b, showed high agreement with the measured flow Q_3m obtained from a reference flow sensor, confirming the effectiveness of the estimation algorithm. Furthermore, an automatic leak detection method based on the time-integrated value of Q_3e was implemented, enabling the detection of improper wearing. This system thus achieves respiratory flow estimation and leakage detection based only on ΔP and V_b. In the future, it is expected to be extended to applications such as pressure control synchronized with breathing activity and health monitoring based on respiratory and coughing analysis. This platform also has the potential to serve as the foundation of a PAPR Wearing Status Network Management System, which will contribute to societal-level infection control through the networked sharing of wearing status information. Full article

The aim of the study was to compare the quality of almond oils obtained using different extraction methods, including cold solvent extraction, Soxhlet extraction, and the Folch method. Oils were extracted from four commercially available almond-based products—unpeeled almonds, blanched almonds, almond flakes, and almond protein concentrate—and compared with a commercially refined almond oil. The extracted oils were analyzed for their fatty acid (FA) composition and selected quality parameters, including acid value, peroxide value, p-anisidine value, the TOTOX index, and specific extinction coefficients (K₂₃₂ and K₂₆₈). Based on the FA profiles, health-related indices such as atherogenic index, thrombogenic index, and hypocholesterolemic/hypercholesterolemic ratio were also calculated. Additionally, the oxidative stability of the oils was assessed using an accelerated method—pressure differential scanning calorimetry. The obtained results demonstrated that the extraction method had a stronger influence on almond oil quality than the type of raw material. Oil extracted from unpeeled almonds using Soxhlet and cold solvent techniques showed better oxidative stability and more favorable FA profiles, while oils obtained using the Folch method and commercial refined oils exhibited higher levels of primary and secondary oxidation products. These findings were further supported by statistical analyses, which revealed distinct groupings based on oxidation indices and lipid composition. Full article

Background: The function and mechanism of N6-methyladenosine (m6A) methylation in pressure-overload cardiac fibrosis remains limited and unclear. This study aims to analyze and predict m6A modifications present in mouse hearts because of transverse aortic constriction (TAC). Materials and Methods: Twelve male C57BL/6 mice were randomly assigned to two groups, TAC group and sham group. The RNA Dot Blot assay was employed to evaluate the overall m6A methylation levels in both TAC and sham mice. The expression level of m6A-related enzymes were investigated through RT-PCR and Western blotting. MeRIP-seq and RNA-seq analyses were conducted to identify differentially modified m6A genes and mRNA expression genes. The protein–protein interaction (PPI) network was carried out to choose potential hub genes. Additionally, the transcription factor (TF)–microRNA (miRNA) coregulatory network and the drug–hub gene interaction network were built based on these hub genes. Furthermore, molecular docking simulations were also performed to analyze the interactions between drugs and hub genes. Results: Compared with the sham group, the TAC group demonstrated elevated levels of global m6A methylation. METTL3 and METTL14 were significantly upregulated, whereas FTO and ALKBH5 were significantly downregulated following TAC. MeRIP-seq analysis identified 17,806 m6A peaks associated with 9184 genes and 16,392 m6A peaks associated with 8550 genes in the TAC and sham groups, respectively. In conjunction with RNA-seq data, 66 genes were identified as exhibiting concurrent differences in both m6A methylation levels and mRNA expression. Six hub genes, Cd33, Irf4, Nr4a2, Hspa1b, Nr4a1, and Adcy1, were identified through the construction of a PPI network. The TF-miRNA coregulatory network contains six hub genes, 31 miRNAs, and 24 TFs. The drug–hub genes interaction network included five hub genes and 36 candidate drugs. Conclusions: The m6A modification is prevalent in TAC-induced cardiac fibrosis and significantly contributes to the fibrotic process by regulating critical genes. In the future, it may emerge as one of the potential cardiac fibrosis therapeutic targets. Full article

Background: Accurate differentiation of Parkinson’s disease (PD) from healthy aging is crucial for timely intervention and effective management. Postural sway abnormalities are prominent motor features of PD. Quantitative stabilometry and machine learning (ML) offer a promising avenue for developing objective markers to support the diagnostic process. This study aimed to develop and validate high-performance ML models to classify individuals with PD and age-matched healthy older adults (HOAs) using a comprehensive set of stabilometric parameters. Methods: Thirty-seven HOAs (mean age 70 ± 6.8 years) and 26 individuals with idiopathic PD (Hoehn and Yahr stages 2–3, on medication; mean age 66 years ± 2.9 years), all aged 60–80 years, participated. Stabilometric data were collected using a force platform during quiet stance under eyes-open (EO) and eyes-closed (EC) conditions, from which 34 parameters reflecting the time- and frequency-domain characteristics of center-of-pressure (COP) sway were extracted. After data preprocessing, including mean imputation for missing values and feature scaling, three ML classifiers (Random Forest, Gradient Boosting, and Support Vector Machine) were hyperparameter-tuned using GridSearchCV with three-fold cross-validation. An ensemble voting classifier (soft voting) was constructed from these tuned models. Model performance was rigorously evaluated using 15 iterations of stratified train–test splits (70% train and 30% test) and an additional bootstrap procedure of 1000 iterations to derive reliable 95% confidence intervals (CIs). Results: Our optimized ensemble voting classifier achieved excellent discriminative power, distinguishing PD from HOAs with a mean accuracy of 0.91 (95% CI: 0.81–1.00) and a mean Area Under the ROC Curve (AUC ROC) of 0.97 (95% CI: 0.92–1.00). Importantly, feature analysis revealed that anteroposterior sway velocity with eyes open (V-AP) and total sway path with eyes closed (TOD_EC, calculated using COP displacement vectors from its mean position) are the most robust and non-invasive biomarkers for differentiating the groups. Conclusions: An ensemble ML approach leveraging stabilometric features provides a highly accurate, non-invasive method to distinguish PD from healthy aging and may augment clinical assessment and monitoring. Full article

Introduction: Sepsis, and particularly septic shock, is a life-threatening condition associated with high mortality rates in the emergency department. Timely interventions can significantly reduce these unacceptably high mortality rates. While some studies have demonstrated reduced mortality with early norepinephrine initiation, there is limited research on this intervention specifically within the emergency department setting. The objective of this study was to determine the association between the time to norepinephrine initiation in the emergency department and in-hospital mortality in adult patients diagnosed with septic shock. Methods: This retrospective cohort study included adult patients diagnosed with septic shock in the emergency department. Demographics, paraclinical variables, and the time to norepinephrine initiation were evaluated. In-hospital mortality was defined as the primary outcome. Finally, a multivariate analysis was performed to develop a nomogram for predicting septic shock mortality from the emergency department. Results: A total of 176 patients were included. A significant difference was documented between the time to norepinephrine initiation (in minutes) and survival rates: median (IQR) 12 (2–29) min for survivors versus 104 (68–181) min for non-survivors (p < 0.001). Similarly, when the time to initiation was divided into three groups (<60, 61–179, >179 min), a differential association with mortality was observed: OR 0.16 (95% CI; 0.08–0.32), OR 5.59 (95% CI; 2.67–11.6), and OR 353 (95% CI; 20.8–5978.9), respectively. Additionally, variables associated with mortality included mean arterial pressure, arterial lactate, and creatinine levels. Conclusions: Early initiation of norepinephrine in the emergency department may lower in-hospital mortality from septic shock without raising arrhythmia rates. Further high-quality studies are needed to confirm this and identify the patients who would benefit most. Full article

This study investigates the impact of different duct designs on the energy-harvesting performance of oscillating-wing systems in both partially and fully confined environments. Numerical simulations were conducted to examine the effects of straight, convergent–straight, and convergent–divergent duct configurations on the aerodynamic forces and overall energy extraction efficiency. Under partial confinement, the convergent–divergent duct demonstrated a significant improvement of 67.5% in power output over the ductless baseline configuration. This enhancement is attributed to the increased incoming flow velocity and amplified pressure difference around the wing, which improve the effectiveness of energy generation. However, the straight and convergent–straight ducts reduced the harvester’s performance due to the diminished flow velocity within each duct. Under full confinement, all duct configurations substantially enhanced energy-harvesting performance, with the convergent–straight duct providing the highest efficiency gain (84.9%). This improvement is primarily due to the increased velocity and pressure differential across the wing surfaces, which maximise the heaving force and overall energy generation performance. These findings highlight the critical role of duct geometry in optimising energy-harvesting performance, both in partially confined and fully confined flow environments. Full article

This study investigates the sustainable livelihoods of households in the coastal forest regions of Quang Tri Province, Vietnam, focusing on identifying the key factors that shape household resilience in the face of socio-economic and environmental challenges. Although the sustainable livelihoods approach is widely established in research, this study differentiates itself by applying a multivariate analysis to explore the relative impacts of various livelihood capitals—human, physical, financial, social, and environmental—specifically within the context of coastal forest ecosystems, a relatively under-researched area in Vietnam. The research identifies both factors affecting livelihood outcomes, emphasizing the role of community resources, seasonal fluctuations, and adaptation strategies. Additionally, the study highlights how environmental changes and natural resource constraints are more detrimental to livelihoods in these regions compared to other rural settings. Through these insights, this paper contributes to the growing body of literature by offering a nuanced understanding of how coastal forest communities can navigate the pressures of climate change, market volatility, and limited resources. The findings underscore the importance of enhancing adaptive capacity and crafting targeted policy interventions to support vulnerable households in the region. This study also highlights the limitations of existing research, emphasizing the need for future studies to integrate the complex interplay of environmental, social, and economic factors in coastal ecosystems. Full article