Search Results (53)

Objectives: Food insecurity (FI) represents a significant global public health issue, yet existing literature presents inconsistent findings regarding its association with mortality risk. This systematic review and meta-analysis aimed to synthesize available evidence to evaluate the relationship between FI and mortality. Setting: A systematic search was conducted using the ISI Web of Science, PubMed/MEDLINE, and Embase databases without any date limitation until February 18, 2025. Hazard ratios (HR) and 95% confidence intervals (CI) were pooled using a random-effects model, while validated methods examined quality and publication bias via Newcastle–Ottawa Scale, Egger’s regression asymmetry, and Begg’s rank correlation tests, respectively. Results: Findings from 19 studies demonstrated a significant association between FI and increased risk of mortality (HR = 1.23; 95% CI: 1.16, 1.30; I² = 83.1%; p < 0.001; n = 19). Subgroup analyses indicated a dose–response relationship, with mortality risk increasing by FI severity: mild (HR = 1.16; 95% CI: 1.10, 1.22; I² = 0.0%; p < 0.001; n = 9), moderate (HR = 1.19; 95% CI: 1.07, 1.31; I² = 83.2%; p = 0.001; n = 10) and severe (HR = 1.52; 95% CI: 1.25, 1.86; I² = 94.9%; p < 0.001; n = 10). Additional subgroup analyses revealed a significant association between FI and both all-cause mortality (HR = 1.26; 95% CI: 1.18, 1.35; I² = 82.0%; p < 0.001; n = 16), and cardiovascular-related mortality (HR = 1.24; 95% CI: 1.11, 1.39; I² = 42.8%; p < 0.001; n = 7), but not cancer-related mortality. Conclusions: Persistent FI appears to contribute to an increased risk of mortality. Hence, it is important to maintain continuity and strengthen current programs aimed at combating FI, which may help reduce FI-related mortality. Full article

Soft lithography with microfabricated molds is a widely used manufacturing method. Recent advancements in 3D printing technologies have enabled microscale feature resolution, providing a promising alternative for mold fabrication. It is well established that the curing of PDMS is influenced by parameters such as temperature, time, and curing agent ratio. This study was conducted to address inconsistencies in PDMS curing observed when using different 3D-printed mold materials during the development of a Lab-on-a-Chip (LoC) system, which is typically employed for investigating the effect of hydrodynamic cavitation on blood clot disintegration. To evaluate the impact of mold material on PDMS curing behavior, PDMS was cast into molds made from polylactic acid (PLA), polyethylene terephthalate (PET), resin, and aluminum, and cured at controlled temperatures (55, 65, and 75 °C) for various durations (2, 6, and 12 h). Curing performance was assessed using Soxhlet extraction, Young’s modulus calculations derived from Atomic Force Microscopy (AFM), and complementary characterization methods. The results indicate that the mold material significantly affects PDMS curing kinetics due to differences in thermal conductivity and surface interactions. Notably, at 65 °C, PDMS cured in aluminum molds had a higher Young’s modulus (~1.84 MPa) compared to PLA (~1.23 MPa) and PET (~1.17 MPa), demonstrating that the mold material can be leveraged to tailor the mechanical properties. These effects were especially pronounced at lower curing temperatures, where PLA and PET molds offered better control over PDMS elasticity, making them suitable for applications requiring flexible LoC devices. Based on these findings, 3D-printed PLA molds show strong potential for PDMS-based microdevice fabrication. Full article

Background: According to the World Health Organization (WHO), approximately 5% of children and 2.5% of adults suffer from attention deficit hyperactivity disorder (ADHD). This disorder can have significant negative consequences on people’s lives, particularly children. In recent years, methods based on artificial intelligence and neuroimaging techniques, such as MRI, have made significant progress, paving the way for development of more reliable diagnostic tools. In this proof of concept study, our aim was to investigate the potential utility of neuroimaging data and clinical information in combination with a deep learning-based analytical approach, more precisely, a novel feature extraction technique for the diagnosis of ADHD with high accuracy. Methods: Leveraging the ADHD200 dataset, which encompasses demographic information and anatomical MRI scans collected from a diverse ADHD population, our study focused on developing modern deep learning-based diagnostic models. The data preprocessing employed a pre-trained Visual Geometry Group16 (VGG16) network to extract two-dimensional (2D) feature maps from three-dimensional (3D) anatomical MRI data to reduce computational complexity and enhance diagnostic power. The inclusion of personal attributes, such as age, gender, intelligence quotient, and handedness, strengthens the diagnostic models. Four deep-learning architectures—convolutional neural network 2D (CNN2D), CNN1D, long short-term memory (LSTM), and gated recurrent units (GRU)—were employed for analysis of the MRI data, with and without the inclusion of clinical characteristics. Results: A 10-fold cross-validation test revealed that the LSTM model, which incorporated both MRI data and personal attributes, had the best diagnostic performance among all tested models in the diagnosis of ADHD with an accuracy of 0.86 and area under the receiver operating characteristic (ROC) curve (AUC) score of 0.90. Conclusions: Our findings demonstrate that the proposed approach of extracting 2D features from 3D MRI images and integrating these features with clinical characteristics may be useful in the diagnosis of ADHD with high accuracy. Full article

As urbanization continues to expand, the design and structure of urban spaces increasingly influence the experiences of individuals, whether intentionally or inadvertently. These effects can result in both positive and negative experiences, with urban facilities generally designed to enhance the comfort and well-being of citizens. However, in certain cases, these spaces can provoke adverse emotional reactions, such as anxiety. Anxiety, a prevalent mental health disorder, is more commonly observed in urban environments than in rural areas. Among various urban settings, rail transport in large cities is often cited as one of the most stressful environments for passengers. In light of the significance of this issue, this study seeks to explore how physical and perceptual components can reduce anxiety and encourage greater use of intra-urban rail transportation. Utilizing a qualitative research approach, the study employed directional content analysis to investigate this topic. Data were collected and analyzed through an exploratory methodology with the assistance of MAXQDA software. The analysis began with guided content coding, drawing on theoretical frameworks pertinent to the research. Through this process, 2387 initial codes were identified, which were then categorized into nine main themes, with the relationships between these codes clarified. The findings were inductively derived from the raw data, leading to the development of a foundational theoretical framework. The study, employing a personalized strategy, identified three key factors that contribute to anxiety: physical, perceptual, and environmental components. Physical factors, such as accessibility, lighting, and signage, were found to have a significant impact on passengers’ psychological well-being. Perceptual factors, including personal perceptions, stress, and fear, played a crucial role in exacerbating anxiety. Additionally, environmental factors, particularly the design of metro networks, rail lines, and flexible transportation lines, such as car-sharing and micromobility, were found to significantly contribute to the overall anxiety experienced by passengers. Moreover, the study suggests that anxiety triggers can be mitigated effectively through the implementation of well-designed policies and management practices. Enhancing the sense of security within transit spaces was found to increase citizens’ willingness to utilize rail transportation. These findings indicate that targeted interventions aimed at improving both the physical and perceptual aspects of the transit environment could enhance the commuter experience and, in turn, foster greater use of rail systems. Full article

Background/Objectives: Biofilm-embedded bacteria, such as Pseudomonas aeruginosa (P. aeruginosa), are highly resistant to antibiotics, making their treatment challenging. Plant-based natural compounds (PBCs) and metal(loid)-based antimicrobials (MBAs) are promising alternatives. This study evaluated the minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), and synergistic effects of zinc sulfate (ZnSO₄), carvacrol (CV), and antibiotics (ciprofloxacin [CIP], tobramycin [TOB], and azithromycin [AZM]) against P. aeruginosa PAO1. Methods: The MIC and MBC of ZnSO₄, CV, and antibiotics were determined using a 96-well plate method. Cytotoxicity was assessed via MTT assay. Fractional inhibitory concentration (FIC), fractional bactericidal concentration (FBC), minimal biofilm inhibition concentration (MBIC), and minimum biofilm eradication concentration (MBEC) indices were calculated for each combination of agents. Checkerboard assays identified interactions, and the effectiveness of combinations was further evaluated in a mouse chronic lung infection model with treatments delivered intratracheally, intraperitoneally, and orally. Results: TOB had the lowest MIC and MBC values, proving most effective against P. aeruginosa PAO1. Strong synergy was observed with CV + ZnSO₄ (CV + Zn) combined with CIP, CV with CIP, and CV + Zn with TOB, as indicated by low FIC indices. CV + Zn with TOB and CV with TOB had low FBC indices, while CV + Zn with AZM showed antagonism. In vivo, intratracheal TOB + CV + Zn reduced lung inflammation and tissue involvement, yielding the best histopathological outcomes. The MIC of CIP and TOB was reduced 5-fold and 4-fold, respectively, when combined with CV + Zn. Conclusions: CV + Zn demonstrated strong synergistic effects with antibiotics and effectively managed P. aeruginosa lung infections in mice. These findings highlight its potential as an innovative therapy for biofilm-associated infections. Full article

Cracks in reinforced concrete structures compromise strength and durability, particularly in high-performance centrifugal concrete (HPC) piles, where degradation can become irreversible. Despite their high density and low permeability, HPC piles remain vulnerable to cracking, sulfate attack, and chloride penetration, necessitating innovative durability solutions. While self-healing concrete has been widely studied, its application in HPC piles remains unexplored, representing a critical research gap. This study investigates the synergistic use of Bacillus sphaericus bacteria and flax fibers to enhance crack healing, permeability reduction, and mechanical performance in HPC piles. In this research, HPC specimens were fabricated using a specialized centrifugal device and casting process. During the mixing phase, bacteria and flax fibers were incorporated into the concrete. The fresh mix was then spun to form the final specimens. To evaluate bacterial self-healing performance of specimens, controlled random cracks were induced using a compression testing machine. Thereafter, a series of compressive strength tests, 30 min water absorption tests (BS 1881), scanning electron microscopy (SEM) combined with energy dispersive X-ray spectroscopy (EDS), and EDS mapping (MAP) were conducted to evaluate self-healing efficiency. Results demonstrated that bacterial activation upon cracking led to calcium carbonate precipitation, effectively sealing cracks, reducing permeability, and enhancing compressive strength. Optimizing bacterial and fiber content further influenced water absorption and mechanical properties in both cubic and centrifugally cast specimens. This study bridges a critical gap by introducing biomaterial-based self-healing in HPC piles, offering a sustainable, cost-effective, and long-term strategy for enhancing the durability of deep foundation systems in aggressive environments. Full article

Two species of wild sheep inhabit Iran: Asiatic mouflon (Ovis gmelini) and urial (O. vignei). Phylogenetic relationships between populations distributed in this country are complex and still remain unclear. This study aimed to clarify, by genetic assessment, the phylogenetic status of Kerman wild sheep, considered to be a hybrid of the two species. For this purpose, we created a dataset that included specimens of O. gmelini, O. vignei, and Kerman sheep. We applied genome-wide SNP genotyping technology to analyze population structure and genetic diversity of these groups. Using Neighbor-Net and PCA plots, it was demonstrated that Kerman sheep were differentiated from other groups and occupy an intermediate position between O. gmelini and O. vignei. Using Admixture analysis, two ancestral components were identified in this population; however, admixed ancestry was not confirmed by f3 statistics. Genetic diversity in Kerman wild sheep was significantly higher than in any group of O. vignei, but lower than in O. gmelini. Additionally, we examined complete mitochondrial genomes and it was demonstrated that the matrilineal ancestor of Kerman sheep belonged to O. vignei. Our results lead to the conclusion that Kerman wild sheep can be recognized as a separate subspecies of O. vignei. Full article

Despite the increasing concerns regarding meeting the world’s future food demand, there is still a substantial quantity of food loss and waste (FLW), particularly concerning fruits and vegetables. In the case of Kermanshah province, inefficiencies within the leafy vegetable supply chpain (LVSC) contribute to an alarming annual waste of 39% of leafy vegetables. Although several studies have proposed strategies and recommendations for mitigating this waste, the actual impact of these interventions on reducing FLW has not been thoroughly examined or quantified. Using System Dynamic Modeling, this study offers a novel approach to quantify the impact of interventions on waste reduction. The quantification results reveal four key interventions reducing vegetable waste at the production stage: biotic (31.2%) and abiotic stress control (14.4%), improved educational services (23.2%), and access to quality inputs (15.2%). Furthermore, the results suggest that early-stage factors in the LVSC play a crucial role in determining waste accumulation in later stages. Improvements in packaging facilities and cold supply chain infrastructure, along with better coordination and information sharing among stakeholders at the market stage, significantly help reduce waste. Additionally, effective planning for household food shopping is emphasized as a crucial strategy for minimizing waste at the consumption stage. This holistic approach focuses on the interconnectedness of actions across various stages of the supply chain and their combined effect on decreasing the overall waste of leafy vegetables. Full article

Shallow foundations supporting high-rise structures are often subjected to extreme lateral loading from wind and seismic activities. Nonlinear soil–foundation system behaviors, such as foundation uplift or bearing capacity mobilization (i.e., rocking behavior), can act as energy dissipation mechanisms, potentially reducing structural demands. However, such merits may be achieved at the expense of large residual deformations and settlements, which are influenced by various factors. One key factor which is highly influential on soil deformation mechanisms during rocking is the foundation embedment depth. This aspect of rocking foundations is investigated in this study under varying subgrade densities and initial vertical factors of safety (FSv), using the PIV technique and appropriate instrumentation. A series of reduced-scale slow cyclic tests were performed using a single-degree-of-freedom (SDOF) structure model. This study first examines the deformation mechanisms of strip foundations with depth-to-width (D/B) ratios of 0, 0.25, and 1, and then explores the effects of embedment depth on the performance of square foundations, evaluating moment capacity, settlement, recentering capability, rotational stiffness, and damping characteristics. The results demonstrate that the predominant deformation mechanism of the soil mass transitions from a wedge mechanism in surface foundations to a scoop mechanism in embedded foundations. Increasing the embedment depth enhances recentering capabilities, reduces damping, decreases settlement, increases rotational stiffness, and improves the moment capacity of the foundations. This comprehensive exploration of foundation performance and soil deformation mechanisms, considering varying embedment depths, FSv values, and soil relative densities, offers insights for optimizing the performance of rocking foundations under lateral loading conditions. Full article

Objectives: The objective of this investigation was to compile existing observational research and quantify the potential association between ultra-processed foods (UPFs) and the risk of insomnia using meta-analysis. Setting: We conducted a systematic search of the PubMed/MEDLINE, Scopus, and ISI Web of Science databases with no restrictions until 29 June 2024. Odds ratios (OR) and 95% confidence intervals (CI) were aggregated using a random-effects model, while the Newcastle-Ottawa Scale and Egger’s regression asymmetry test assessed study quality and publication bias, respectively. Results: Analysis of data from seven studies showed a significant positive association between higher intake of UPFs and an increased risk of insomnia (OR = 1.53; 95% CI: 1.20, 1.95; I² = 62.3%; p = 0.014). Subgroup analysis indicated this positive relationship was particularly strong under the NOVA food classification (OR = 1.57; 95% CI: 1.03, 2.40; I² = 78.5%; p = 0.009; n = 3) and with snack intake (OR = 1.33; 95% CI: 1.04, 1.71; I² = 0.0%; p < 0.001; n = 2), compared to adherence to Western dietary patterns. Moreover, subgroup analysis based on age group showed that higher UPF intake was significantly associated with increased risk of insomnia among adolescents (OR = 1.55; 95% CI: 1.21, 1.99; I² = 57.4%; p < 0.001) but not in adults. Conclusions: Our findings underscore a significant association between higher consumption of UPFs and increased risk of insomnia, particularly among adolescents. Further research is necessary to explore the intricacies of this association and to ensure the generalizability of these results. Full article

This work aims to analyze the effects of the main process parameters of fused filament fabrication (FFF) on the mechanical properties and part weight of 3D-printed thermoplastic polyurethane (TPU). Raster angle (RA), infill percentage (IP), and extruder temperature (FFF) in the ranges of 0–90°, 15–55%, and 220–260 °C, respectively, were considered as the FFF input parameters, and output variables part weight (PW), elongation at break (E), maximum failure load (MFL), ratio of the maximum failure load to part weight (Ratio), and build time (BT) were considered as responses. The Response Surface Methodology (RSM) and Design of Experiments (DOE) were applied in the analysis. Subsequently, the RSM approach was performed through multi-response optimizations with the help of Design-Expert software. The experimental results indicated a higher maximum failure load is achieved with an increased raster angle and decreased extruder temperature. ANOVA results show that ET has the most significant effect on elongation at break, with elongation at break decreasing as ET increases. The raster angle does not significantly affect the part weight of the TPU samples. The ratio of the maximum failure load to part weight of samples decreases with an increase in IP and ET. The results also indicated that the part weight and build time of FFF-printed TPU samples increase with an increase in IP. An ET of 220 °C, RA of 0°, and IP of 15% are the optimal combination of input variables for achieving the minimal part weight; minimal build time; and maximum elongation at break, maximum failure load, and ratio of the maximum failure load to part weight. Full article

Background and Introduction: Cardiac imaging is crucial for diagnosing heart disorders. Methods like X-rays, ultrasounds, CT scans, and MRIs provide detailed anatomical and functional heart images. AI can enhance these imaging techniques with its advanced learning capabilities. Method: In this scoping review, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) Guidelines, we searched PubMed, Scopus, Web of Science, and Google Scholar using related keywords on 16 April 2024. From 3679 articles, we first screened titles and abstracts based on the initial inclusion criteria and then screened the full texts. The authors made the final selections collaboratively. Result: The PRISMA chart shows that 3516 articles were initially selected for evaluation after removing duplicates. Upon reviewing titles, abstracts, and quality, 24 articles were deemed eligible for the review. The findings indicate that AI enhances image quality, speeds up imaging processes, and reduces radiation exposure with sensitivity and specificity comparable to or exceeding those of qualified radiologists or cardiologists. Further research is needed to assess AI’s applicability in various types of cardiac imaging, especially in rural hospitals where access to medical doctors is limited. Conclusions: AI improves image quality, reduces human errors and radiation exposure, and can predict cardiac events with acceptable sensitivity and specificity. Full article

There has been a tendency in oil and gas industry towards the adoption of multilateral wells (MLWs) with completions that incorporate multiple types of flow control devices (FCDs). In this completion technique, passive inflow control devices (ICDs) or autonomous inflow control devices (AICDs) are positioned within the laterals, while interval control valves (ICVs) are installed at lateral junctions to regulate the overall flow from each lateral. While the outcomes observed in real field applications appear promising, the efficacy of this specific downhole completion combination has yet to undergo comparative testing against alternative completion methods that employ a singular flow control device type. Additionally, the design and current evaluations of such completions are predominantly based on analytical tools that overlook dynamic reservoir behavior, long-term production impacts, and the correlation effects among different devices. In this study, we explore the potential of integrating various types of flow control devices within multilateral wells, employing dynamic optimization process using numerical reservoir simulator while the Grey Wolf Optimizer (GWO) is used as optimization algorithm. The Egg benchmark reservoir model is utilized and developed with two dual-lateral wells. These wells serve as the foundation for implementing and testing 22 distinct completion cases considering single-type and multiple types of flow control devices under reactive and proactive management strategies. This comprehensive investigation aims to shed light on the advantages and limitations of these innovative completion methods in optimizing well and reservoir performance. Our findings revealed that the incorporation of multiple types of FCDs in multilateral well completions significantly enhance well performance and can surpass single-type completions including ICDs or AICDs. However, this enhancement depends on the type of the device implemented inside the lateral and the control strategy that is used to control the ICVs at the lateral junctions. The best performance of multiple-type FCD-based completion was achieved through combining AICDs with reactive ICVs which achieved around 75 million USD profit. This represents 42% and 22% increase in the objective function compared to single-type ICDs and AICDs installations, respectively. The optimal settings for ICD and AICD in individual applications may significantly differ from the optimal settings when combined with ICVs. This highlights a strong correlation between the different devices (control variables), proving that using either a common, simplified analytical, or a standard sequential optimization approach that do not explore this inter-dependence between devices would result in sub-optimal solutions in such completion cases. Notably, the ICV-based completion, where only ICVs are installed with lateral completion, demonstrated superior performance, particularly when ICVs are reactively controlled, resulting in an impressive 80 million USD NPV which represents 53% and 30% increase in the objective function compared to single-type ICDs and AICDs installations, respectively. Full article

Sources such as wind or severe seismic activity often exert extreme lateral loading onto the shallow foundations supporting high-rise structures such as bridge piers, buildings, shear walls, and wind turbine towers. Such loading conditions may cause the foundation to exhibit nonlinear responses such as uplift and bearing capacity mobilization of the supporting soil (i.e., rocking behavior). Previous numerical and experimental studies suggest that while such inelastic behaviors may engender residual deformations in the soil–foundation system, they offer potential benefits to the overall integrity of structures through dissipating energy and reducing inertia forces transmitted to the superstructure, thereby limiting seismic demand on structural elements. This study investigates the effect of footing shape on the rocking performance of shallow foundations in different subgrade densities and initial vertical factor of safety (FSv). To this end, a series of reduced-scale slow cyclic tests under 1 g condition were conducted using a single degree of freedom (SDOF) structure model. The performance of different footing shapes was studied in terms of moment capacity, recentering ratio, rocking stiffness, damping ratio, and settlement. For three foundations with different length-to-width ratios, the results indicate that increasing the safety factor and length-to-width ratio leads to thinner, S-shaped moment–rotation curves, mainly owing to the enhanced recentering capability and the P-δ effect. Moreover, across all foundation types, the repetition of a limited loading cycles with consistent rotation amplitude does not cause stiffness degradation or moment capacity reduction. Full article