Explore the vast range of titles available.

Emergency evacuations in built environments pose significant challenges for individuals with disabilities, yet traditional simulation models often fail to account for heterogeneous mobility needs. While considerable advances have been made in pedestrian dynamic modeling, a critical gap persists in the realistic incorporation of disability-specific movement limitations and environmental barriers. This paper presents an inclusive evacuation simulation framework based on an extended social force model, explicitly integrating wheelchair users and visually impaired individuals. The model modifies agent parameters such as desired speed, relaxation time, body size, and barrier navigation capability to reflect empirical observations. Key enhancements include a probabilistic falling mechanism under high crowd pressure and dynamic interaction with environmental obstacles. A single-room evacuation scenario involving 50 agents, including 20% disabled individuals, was simulated using this framework. Results demonstrated that the presence of disabled individuals increased total evacuation time by approximately 50% compared to an all-able-bodied crowd, led to a 40% reduction in peak evacuation throughput after crowd falls, and caused arching, clogging, and faster-is-slower effects to intensify. Two fall incidents occurred within the first 4 s, resulting in partial door blockage and additional delays. Heatmaps revealed localized congestion zones induced by mobility impairments, and kinetic energy analysis illustrated significant dissipation due to frictional interactions at the exit. The findings underscore the necessity of inclusive modeling to identify critical vulnerabilities in evacuation plans and highlight the importance of design interventions such as wider doorways, alternative accessible exits, and controlled evacuation flow for heterogeneous crowds. This work offers a robust foundation for performance-based inclusive design and supports future extensions into multi-level structures, dynamic assistance modeling, and optimization-based evacuation planning.

In contemporary building design and management, catering to the needs of individuals with disabilities presents a multifaceted challenge. Buildings tailored to accommodate individuals with disabilities, featuring accessibility features are integral in various contexts, which are essential to ensure equitable access and usability for individuals with disabilities. However, research in disability-friendly building construction and management has been relatively limited due to the diverse and evolving needs of demographic. Factors like designing efficient wheelchair routes, maintaining escalators and elevators, and managing hearing aid systems all impact a building’s operation. This paper utilizes simulation modeling in optimizing buildings designed for individuals with disabilities which presents a paradigm shift in inclusive building design, resulting in substantial improvements in accessibility and efficiency. The model creates a network representation of the building, incorporating delays and queue systems to simulate people and resource flow, accounting for bottlenecks and constraints to determine the optimal resource allocation and operational timing for disability-friendly buildings. By assessing various scenarios and conducting optimization analyses, the model identifies the best combination of resources and schedules to minimize delays, enhance accessibility, and ensure the building functions optimally, meeting regulatory requirements and the needs of individuals with disabilities. Through the implementation of the model, Equipment and Machinery resources optimization significantly saves duration by 15.17 and 14.29%, respectively. Overall optimization results show a duration reduction from 1450 to 930 days, saving 35.86% and a productivity limits improvement varies between 30 and 36%. These gains translate into cost savings, reducing operational expenses and potentially speeding up return on investment.

Purpose Rhegmatogenous retinal detachment (RRD) is a sight-threatening condition requiring prompt surgical intervention. Various adjunctive techniques are employed to enhance subretinal fluid drainage and retinal reattachment. This study aimed to evaluate the outcomes of perfluorocarbon liquid (PFCL) versus posterior retinotomy (PR) during pars plana vitrectomy (PPV) for RRD, focusing on anatomical success, visual acuity, intraocular pressure (IOP), and complications. Methods This is a prospective randomized controlled trial that included 58 eyes with RRD, divided into Group A (PFCL, n  = 29) and Group B (PR, n  = 29). Preoperative assessments included best-corrected visual acuity (BCVA), IOP, axial length, lens status, macula status, and PVR grade. Outcomes were evaluated at 1 week, 1 month, 2 months, and 3 months postoperatively. Primary outcomes included retinal reattachment rates and the number of operations; secondary outcomes included BCVA, IOP changes, complications like cataract development, retinal redetachment, epiretinal membrane (ERM) formation, and single-surgery success. Results Retinal reattachment rates were comparable (76% in Group A vs. 66% in Group B, p  = 0.387), as well as the number of operations ( p  = 0.375). Moreover, BCVA improved significantly in both groups ( p  < 0.05), with no intergroup differences. IOP increased postoperatively in both groups ( p  < 0.001), with no significant differences. No differences were observed in cataract formation or retinal redetachment. However, ERM incidence was significantly higher in the PR group (27% vs. 11%, p  = 0.049). Conclusion PFCL and PR are effective for RRD repair, with similar anatomical and visual outcomes. However, PFCL may reduce ERM risk, making it preferable in certain cases. These findings guide surgical decision-making and highlight the need for further research. Trial registration The study was retrospectively registered at ClinicalTrials.gov (NCT06919211) on April 4, 2025.

Bacillus cereus is a significant foodborne bacterium that is prevalent in a variety of dietary products. This study aimed to assess the contamination rate, enterotoxin genes, and antibacterial susceptibility of B. cereus detected in 20 samples each of minced beef, beef shawarma, beef burger, beef kofta, beef sausage, chicken shawarma, chicken kofta, chicken kabab, and chicken sausage that were acquired from a variety of markets in the Aswan Governorate, Egypt. In addition, the antimicrobial impact of Apple cider vinegar (ACV) on B. cereus was investigated. The highest B. cereus levels were found in beef kofta samples (2.44×103 ± 0.18×102 CFU/g) and beef sausage (1.88×103 ± 0.12×102 CFU/g). On an average, 30% of the samples were contaminated with B. cereus. All of the putative isolates showed B. cereus DNA according to PCR findings of the gyrB gene. Most of the strains (16/54) had the hblA gene, which was substantially more abundant than hblC (7/54) and hblD (5/54). However, nheA was detected in 10/54 samples and was substantially more prevalent than nheB (5/54) and nheC (3/54). Of the strains, 10 out of 54 have cytK. By comparison, the cesB detection rate was just 6/54, indicating that emetic strains are less frequent in meat products than diarrhea strains. Most strains were resistant to ampicillin, cefoxitin, and colistin (100% each), while they were entirely sensitive to imipenem, nalidixic acid, and vancomycin, rendering them the most significant antibiotics. By the agar well diffusion technique, all concentrations of ACV (10%, 30%, 70%, and 100%) were confirmed to have significant inhibitory activities against B. cereus, suggesting that ACV could be employed as a natural antimicrobial preservative in meat products.

ABSTRACT Camel meat and edible offal are regarded as exotic meats around the world. However, such meat kinds are regarded as emerging meat sources rich in animal-derived protein in particular countries such as Egypt and Saudi Arabia. Camel meat and offal supplies humans with part of their needs from essential amino acids, minerals, vitamins, and polyunsaturated fatty acids. Toxic metals such as lead (Pb), cadmium (Cd), arsenic (As), and mercury (Hg) are of no-known physiological importance. The objectives of the present study were to quantitatively estimate the residual levels of Pb, Cd, As, and Hg in camel meat and edible offal including round, liver, kidney, and tongue in samples collected from Zagazig slaughterhouse, Egypt and Al-Ahsa slaughterhouse, Saudi Arabia. Dietary intakes and potential health risks associated with the consumption of camel meat and edible offal among Saudi and Egyptian populations were additionally calculated in a comparative way. The obtained results indicated that edible offal including liver, kidney and tongue had higher levels of the tested metals compared with the muscle. Samples collected from Egypt had significantly (p< 0.05) higher metal residues than that collected from Saudi Arabia. Cadmium content exceeded the established maximum permissible limits (MPL) in 65%, 20%, and 70% of liver, kidney, and tongue samples collected from Egypt, while only 35%, and 20% of the Saudi liver and kidney samples exceeded MPL. Arsenic residue levels exceeded MPL in 50%, 50%, and 25% of the Egyptian liver, kidney, and tongue samples. None of the examined samples exceeded MPL for Pb, and Hg. Calculation of the hazard ratio (HR), and hazard index (HI) for Egyptian and Saudi adults and children indicated that HI was higher than one for Egyptian children consuming liver, kidney, and tongues of the camel. Therefore, it is highly recommended to reduce the daily consumption of such offal samples, particularly among children in Egypt.

Coastal regions face significant threats from tsunamis, which cause severe damage to infrastructure and human life. Due to their infrequent occurrence, accurately assessing tsunami hazards remains challenging, complicating risk evaluation despite their potentially catastrophic impact. This dissertation aims to enhance the understanding of structural and community vulnerability to tsunamis by developing advanced assessment methodologies. The research first evaluates structural fragility under tsunami loads and then expands to community-level vulnerability, offering insights for risk mitigation and resilience enhancement. A key component of this study is the use of fragility and vulnerability curves, which quantify the probability of structural failure under tsunami forces. These curves, based on cumulative log-normal distributions, provide critical insights for risk assessment and disaster management decision-making. This dissertation develops a comprehensive analytical approach for evaluating the fragility of structures subjected to tsunami loads. Through advanced numerical simulations, it examines structural behavior under extreme tsunami conditions, providing critical insights into their response. The proposed simulation approach is applied to selected structures, with the results analyzed to enhance understanding of structural fragility under tsunami loading, supporting the development of more resilient infrastructure in tsunami-prone regions. This dissertation presents three studies focused on the vulnerability of structures subjected to tsunami waves. The first study focuses on the tsunami vulnerability analysis of a reinforced concrete (RC) building classified as Tsunami Risk Category II. It examines the impact of different load distributions on the structural response during a tsunami event. The study also defines the inundation depth and flow velocity for dynamic assessments of the structural model. To quantify the effects of tsunamis on building performance, fragility relationships are derived from nonlinear dynamic response history analysis, utilizing a novel structural reliability method. The findings highlight that the number of tsunami cycles significantly influences the vulnerability of reinforced concrete structures, with a uniform load distribution being recommended for its conservatism. The second study examines the tsunami vulnerability of structures through numerically simulated tsunami waves, analyzing their propagation and impact on coastal dynamics and structural fragility. This study investigates the effects of various factors, including bathymetric features, alongside tsunami wave parameters. The simulation tool FUNWAVE-TVD is employed to model tsunami propagation and inundation. These tsunami intensity measures are then used to develop fragility curves to evaluate the structural probability of failure under different tsunami conditions. The study shows that higher Manning coefficients, steeper slopes, and longer wave periods reduce fragility, while more tsunami cycles and higher crest amplitudes significantly increase vulnerability, providing valuable insights for coastal resilience. The third study focuses on assessing the vulnerability of structures to 2D tsunami waves, with the goal of enhancing resilience in the coastal community of Kahului, Maui. A numerical simulation approach is developed to evaluate the fragility of selected structures under various tsunami scenarios through nonlinear dynamic time history analyses. The study aims to develop fragility curves for commercial, residential, and industrial buildings within the community, specifically examining the effects of wave amplitude, wave period, and other structural parameters. The findings indicate that both offshore tsunami amplitude and wave period significantly influence structural vulnerability, while building characteristics, such as design and materials, further impact the vulnerability of individual structures. Emphasizing the importance of estimating structural vulnerability, the study seeks to improve the accuracy of risk assessments and inform decision-making in disaster management. In conclusion, this research aims to advance the resilience of structures subjected to tsunami loads and to develop methods for assessing the vulnerability and performance of these structures. It highlights the importance of accurate vulnerability evaluation under varying tsunami wave conditions, considering factors such as bathymetric changes, wave characteristics, and structural types, to enhance risk assessment and decision-making in disaster management. The findings provide critical insights into the behavior of structures under tsunami loads and contribute to improved designs for both new and existing structures, including commercial, residential, and industrial buildings in coastal areas. Ultimately, these studies offer the potential to mitigate the economic and societal impacts of tsunami-related damage and inform effective coastal planning and disaster mitigation strategies.

Purpose Adrenocortical carcinoma (ACC) is a rare, aggressive pediatric malignancy. Advanced ACC requires multimodal treatment, including surgery and systemic chemotherapy including cisplatin, etoposide, doxorubicin, and mitotane. This is associated with significant gastrointestinal toxicity, resulting in many patients being unable to complete scheduled therapy. Often, supplemental nutrition is required if oral intake during treatment is poor. We assessed the frequency of nutritional supplement use in pediatric patients treated for advanced ACC. Methods This was a retrospective observational study of patients with ACC treated at St. Jude Children’s Research Hospital over 10 years (2012–2022). Patient demographics, treatment received, and the need for supplemental enteral or parenteral nutrition were reviewed. Results A total of 18 patients with ACC were treated from 2012 to 2022, with 11 having advanced ACC. 54.5% of patients required supplemental nutrition, both enteral and parenteral. All patients requiring supplemental nutrition were intolerant of oral intake, with a mean weight loss of 13.8% (range: 5.9–35%). Mean duration of nutritional support was 362 ± 337 days. Patients requiring supplemental nutrition tended to be younger than others (mean age: 4.45 ± 3.63 vs. 9.14 ± 4.59 years; median age: 3.35 vs. 8.40 years; range: 0.90–11.0 vs. 3.30–15.1 years) ( p  = 0.082). Conclusions Most patients with stage IV ACC require nutritional support during their treatment course, especially younger patients. Preemptive feeding tube placement should be considered to avoid delays in treatment.

A main function of network intrusion detection systems (NIDSs) is to monitor network traffic and match it against rules. Oblivious NIDSs (O-NIDS) perform the same tasks of NIDSs but they use encrypted rules and produce encrypted results without being able to decrypt the rules or the results. Current implementations of O-NIDS suffer from slow searching speeds and/or lack of generality. In this paper, we present a generic approach to implement a privacy-preserving O-NIDS based on hybrid binary gates. We also present two resource-flexible algorithm bundles built upon the hybrid binary gates to perform the NIDS’s essential tasks of direct matching and range matching as a proof of concept. Our approach utilizes a Homomorphic Encryption (HE) layer in an abstract fashion, which makes it implementable by many HE schemes compared to the state-of-the-art where the underlying HE scheme is a core part of the approach. This feature allowed the use of already-existing HE libraries that utilize parallelization techniques in GPUs for faster performance. We achieved a rule encryption time as low as 0.012% of the state of the art with only 0.047% of its encrypted rule size. Also, we achieved a rule-matching speed that is almost 20,000 times faster than the state of the art.

Medicinal plants provide a wide range of active compounds that can be exploited to create novel medicines with minimal side effects. The current study aimed to identify the anticancer properties of Juniperus procera (J. procera) leaves. Here, we demonstrate that J. procera leaves’ methanolic extract suppresses cancer cells in colon (HCT116), liver (HepG2), breast (MCF-7), and erythroid (JK-1) cell lines. By applying GC/MS, we were able to determine the components of the J. procera extract that might contribute to cytotoxicity. Molecular docking modules were created that used active components against cyclin-dependent kinase 5 (Cdk5) in colon cancer, aromatase cytochrome P450 in the breast cancer receptor protein, the -N terminal domain in the erythroid cancer receptor of the erythroid spectrin, and topoisomerase in liver cancer. The results demonstrate that, out of the 12 bioactive compounds generated by GC/MS analysis, the active ingredient 2-imino-6-nitro-2H-1-benzopyran-3-carbothiamide proved to be the best-docked chemical with the chosen proteins impacted by DNA conformational changes, cell membrane integrity, and proliferation in molecular docking studies. Notably, we uncovered the capacity of J. procera to induce apoptosis and inhibit cell growth in the HCT116 cell line. Collectively, our data propose that J. procera leaves’ methanolic extract has an anticancer role with the potential to guide future mechanistic studies.

Pediatric dental image analysis faces critical challenges in disease detection due to missing or corrupted pixel regions and the unique developmental characteristics of deciduous teeth, with current Latent Diffusion Models (LDMs) failing to preserve anatomical integrity during reconstruction of pediatric oral structures. We developed two novel biologically-inspired loss functions integrated within LDMs specifically designed for pediatric dental imaging: Gum-Adaptive Pixel Imputation (GAPI) utilizing adaptive 8-connected pixel neighborhoods that mimic pediatric gum tissue adaptive behavior, and Deciduous Transition-Based Reconstruction (DTBR) incorporating developmental stage awareness based on primary teeth transition patterns observed in children aged 2–12 years. These algorithms guide the diffusion process toward developmentally appropriate reconstructions through specialized loss functions that preserve structural continuity of deciduous dentition and age-specific anatomical features crucial for accurate pediatric diagnosis. Experimental validation on 2,255 pediatric dental images across six conditions (caries, calculus, gingivitis, tooth discoloration, ulcers, and hypodontia) demonstrated superior image generation performance with Inception Score of 9.87, Fréchet Inception Distance of 4.21, Structural Similarity Index of 0.952, and Peak Signal-to-Noise Ratio of 34.76, significantly outperforming eleven competing diffusion models. Pediatric disease detection using enhanced datasets achieved statistically significant improvements across five detection models: +0.0694 in mean Average Precision [95% CI: 0.0608–0.0780], + 0.0606 in Precision [0.0523–0.0689], + 0.0736 in Recall [0.0651–0.0821], and + 0.0678 in F1-Score [0.0597–0.0759] (all p  < 0.0001), enabling pediatric dentists to detect early-stage caries, developmental anomalies, and eruption disorders with unprecedented accuracy. This framework revolutionizes pediatric dental diagnosis by providing pediatric dentists with AI-enhanced imaging tools that account for the unique biological characteristics of developing dentition, significantly improving early detection of oral diseases in children and establishing a foundation for age-specific dental AI applications that enhance clinical decision-making in pediatric dental practice.