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Abstract This study presents a sophisticated numerical simulation model for a forced circulation solar water heating system (FC-SWHs), specifically designed for the unique climatic conditions of Algeria. The model aims to cater to the hot water needs of single-family houses, with a daily consumption of 246 L. Utilizing a dynamic approach based on TRNSYS modeling, the system’s performance in Ain Temouchent’s climate was scrutinized. The model’s validation was conducted against literature results for the collector outlet temperature. Key findings include a maximum monthly average outlet temperature of 38 °C in September and a peak cumulative useful energy gain of 250 W in August. The auxiliary heating system displayed seasonal energy consumption variations, with the highest rate of 500 kJ/hr in May to maintain the water temperature at 60 °C. The energy input at the storage tank’s inlet and the consistent high-level energy output at the hot water outlet were analyzed, with the former peaking at 500 W in May. The system ensured an average water tank temperature (hot, middle and bottom) and water temperature after the mixer, suitable for consumption, ranging between 55 °C and 57 °C. For applications requiring cooler water, the mixer’s exit temperature was maintained at 47 °C. The study’s key findings reveal that the TRNSYS model predicts equal inlet and outlet flow rates for the tank, a condition that is particularly significant when the system operates with high-temperature water, starting at 55 °C. The flow rate at this temperature is lower, at 7 kg/hr, while the water mass flow rate exiting the mixer is higher, at 10.5 kg/hr. In terms of thermal performance, the system’s solar fraction (SF) and thermal efficiency were evaluated. The results indicate that the lowest average SF of 54% occurs in July, while the highest average SF of over 84% is observed in September. Throughout the other months, the SF consistently stays above 60%. The thermal efficiency of the system varies, ranging from 49 to 73% in January, 43–62% in April, 48–66% in July, and 53–69% in October. The novelty of this research lies in its climate-specific design, which addresses Algeria’s solar heating needs and challenges. Major contributions include a thorough analysis of energy efficiency metrics, seasonal auxiliary heating demands, and optimal system operation for residential applications, supporting Algeria’s goal of sustainable energy independence.

The COVID-19 pandemic requires critical re-evaluation of the way Higher Education can help students maximise their learning to adjust and adapt to a new reality. This requires a holistic approach which extends beyond consideration of student learning in formal settings to understanding the role informal learning can play. Whilst research exists on informal independent learning, less focus has been placed on how students collaborate informally as part of their learning process. In this study interviews with HE students in Spain and the UK offer insight into variable but beneficial informal collaborative learning (ICL) practices. The value attributed to ICL emphasises its potential contribution to the current educational landscape and the merit of recognising it as a distinct concept. Further, uneven access and the role of learner maturity signal the potential for universities to enhance learning and increase access by playing an active a role in developing ICL skills and personal networks.

The present work examines that how the fins attached to the inner surface of a vertically oriented pipe affect the flow as well as thermal characteristic of the nanofluid flow when exposed to sunlight-induced heating. A definite thermal boundary condition together with fully established hydrodynamics and thermal conditions is applied that confirms uniform temperature along the sun-exposed pipe walls. Finite volume method, with computational efficiency and solution accuracy, is incorporated. A magnetic damping produces significant changes in the flow patterns within the pipe. A reduction in the velocity distribution is also caused by this damping force. The intensified applied magnetic field impact also changes the velocity distribution. It leads to a flattening of the velocity surface, indicating a decrease in velocity gradient within the flow field. The larger fins work as significant obstacles by altering flow direction and increasing velocity gradients near the solid surface. However, the higher Rayleigh numbers qualitatively change the thermal characteristics within the pipe. Finally, an artificial intelligence-based analysis is presented that correlates our research methodology with a Neural Fitting app. This neural network app is leveraged to enrich the accuracy of the present numerical technique and ensures a robust evaluation of the thermal signature of nanofluid flow within the pipe exposed to sunlight-induced heating.

The flow of fluids through porous media is commonly described using the Darcy model, therefore investigating hybrid nanofluids in this setting is rather new. The present work offers insightful information on how the hybrid nanofluids behave and function in porous medium. The study's conclusions may have an impact on a lot of different engineering applications like filtration systems, chemical reactors, and environmental engineering. The study concentrates on a hybrid nanofluid which consists of Cu and Al₂O₃ nanoparticles. The metallic nanoparticles such as copper have high thermal conductivity and non-metallic nanoparticles such as aluminum oxide are chemically stable and has high thermal resistance. This is the reason that the combination Cu-Al₂O₃ is believed to give better heat transfer composite than using individual nanofluids. By employing proper similarity transformation, the governing PDEs are turned into ODEs. To discretize these ODEs, the central finite difference method is used first. Then the successive over relaxation technique is utilized to numerically solve the nonlinear equations. The findings are summarized in a graphical and tabular format. The impacts of several controlling parameters such as porosity, suction, Schmidt number and volume fraction on flow pattern, thermal properties, and concentration are investigated and discussed. The streamwise and normal velocity profiles fall and those of concentration and temperature rise with increase in the values of the porosity parameter.

Supply chain capabilities are fundamental in driving superior supply chain performance in diverse business environments. This study evaluates the impact exerted by supply chain capabilities on supply chain performance in the fast-growing apparel manufacturing sector in Bangladesh. Focusing on innovativeness, visibility, and collaboration as emerging components of supply chain capabilities, this research examines the associations among these factors and supply chain performance based on the dynamic capability theory. Additionally, the moderating role of digital supply chain deployment is tested in the research model. A total of 159 samples were collected from higher and lower-level supply chain managers and merchandisers from the apparel industry in Bangladesh, through an online survey. Data were analyzed using PLS-SEM to validate the research hypotheses. Findings indicate a significant positive relationship between firms’ innovativeness, visibility, and supply chain performance, while collaboration did not exhibit significant relationship with performance in this study. This indicates the lack of supply chain collaboration within the apparels industry in Bangladesh. The findings also highlight the critical importance of digital supply chain integration to increase both supply chain capacity and performance in this industry. As digital supply chain integration has received much attention in recent literatures, this study contributes to the current theory by refining the relationships between capabilities and performance in supply chain, for the lucrative apparel industry in a developing economy. Consequently, this research adds valuable contribution to the existing body of literature within the realms of supply chain management and Information Technology management. The study also provides meaningful practical insights for managers in the apparel sector to enhancing their supply chain capabilities, which could significantly improve their business performance and competitiveness.

ABSTRACT: Minimizing the utilization of antibiotics in animal production is crucial to prevent the emergence of antimicrobial resistances. Thus, research on alternatives is needed to maintain productivity, sustainability, and animal health. To gain a comprehensive understanding of probiotics’ modes of action on performance, intestinal microbiota, and gut health in poultry, 3 probiotic strains (Enterococcus faecalis CV1028 [EntF], Bacteroides fragilis GP1764 [BacF], and Ligilactobacillus salivarius CTC2197 [LacS]) were tested in 2 in vivo trials. Trial 1 comprised of a negative control group fed basal diet (BD) and 3 treatment groups that received BD with EntF, BacF and LacS. Trial 2 included a negative control group, a positive control group with Zinc-Bacitracin as antibiotic growth promoter (AGP), and 2 groups treated with a blend of probiotics (EntF+BacF+LacS) during 0 to 10 or 0 to 35 d, respectively. Wheat-soybean-rye based diets without exogenous enzymes were used as a challenge model to induce intestinal mild- or moderate-inflammatory process in the gut.In Trial 1, individually administered probiotics improved FCR at 8 d compared to Control, but these positive effects were lost in the following growing periods probably due to the high grade of challenging diet and a too low dose of probiotics. In Trial 2, both Probiotic treatments, administered only 10 or 35 d, significantly improved FCR to the same extent as of the Antibiotic group at the end of the trial. Although the performance between antibiotic and probiotic mixture showed similar values, microbiota analysis revealed different microbial composition at 7 d, but not at 21 d. This suggests that modes of action of the AGP and the tested probiotic blend differ on their effects on microbiome, and that the changes observed during the first days’ posthatch are relevant on performance at the end of the study. Therefore, the probiotics administration only during the first 10 d posthatch was proven sufficient to induce similar performance improvements to those observed in birds fed antibiotic growth promoters throughout the whole experimental trial.

Introduction. The esophagus cancer patients needs early diagnosis to achieve better prognosis. The delay barriers increase progression of diseases to higher stages. The aim of work was to identify and explore the barriers in diagnosis of esophagus cancer and chart the time duration in this process. Material and Methods. The study was conducted in Jinnah Hospital Lahore (JHL), a teaching care hospital of Allama Iqbal Medical College, during a period of one year from July 2019 to July 2020. There were 49.42 % female and 50.57 % male patients. Results. Mean age found to be 56 years. Mean Total delay (TD ) time was 206 days and median Total delay (TD ) time in days were 197 days with 25th and 75th (157, 246) percentiles respectively. Longest delays were found in 51–60 age group and age related (r=0.94) significantly to delays (p=0.0004). Initial symptom of weight loss shows maximum delay and symptoms are highly correlated (r=0.94) with delay (p=0.004). The low income group presents maximum delay. Mean patient delay (PD ) time in days were 142 days with 135 Median and (88, 195) 25th and 75th percentile respectively. Mean, Median, 25th and 75th percentiles for Physician delays (PhyD) times were (20, 18, 16, 23) respectively. Treatment delay (TD ) time (Mean, Median) in days were (18, 18.52) with 25th and 75th (14, 22) percentiles. The education significantly reduces the delays with correlation (r=0.91) and significance (p=0.02). Mean system delay (SD ) time were 25 days and median were 24 days with 25th and 75th (20, 31) percentiles. Conclusion. Illiteracy, financial problems, and unavailability of information related to the cancer and health care system, very limited number of health facilities remains the main causes of these delays.

The crude cell wall of E.cloacae was extracted by using Lysozyme , DNase and RNase enzymes, the contents of the proteins and carbohydrates were 24% and 1.44% respectively . The pathogenicity of the bacteria was studied by testing its lethality, in which the LD50 was identified to both bacterial suspension and the extract of the crude cell wall of bacteria by using white swiss female mice. The value of the LD50 of bacterial suspension was 3.16x109 CFU / ml . The cell wall extract didn’t have any lethal effect on the mice, but it had a great effect on their physiological state which led to a deficit in their weight by an average of 8 grams.

Introduction. Neighbourhood safety is directly linked to the level of disadvantage in the area of residence. Aim. The present research aimed to examine the impact of neighbourhood safety on the academic performance of secondary school students, taking into account gender and socioeconomic background. Methodology and research methods. The current study used a quantitative cross-sectional study design. Data were collected from 448 secondary school students on a voluntary basis. Chi-square and Kendall’s Tau-c (Tc) tests were used to analyse the data and determine the relationship and strength of direction between variables. Results. The findings indicated a significant and positive association between children’s academic performance and neighbourhood crime safety (P < 0.05, Tc = 0.202), as well as feeling safe, walking in the neighbourhood during the day or night (P < 0.05, Tc = 0.127). However, bullying and harassment in the neighbourhood were found to be significantly and negatively associated with academic performance (P > 0.05, Tc = -0.053). When introducing family socioeconomic status as a control variable, the results indicated variation in academic performance in relation to neighbourhood safety. When controlling for student gender, neighbourhood safety had no different effects on academic performance. The findings showed that, in relation to neighbourhood safety, children from families with higher socioeconomic status academically outperform children from lower socioeconomic status families. Scientific novelty. The study not only focused on the connection between neighbourhood safety and academic performance but was also unique in the sense that it also dealt with differences in academic performance based on gender and family socioeconomic level. Practical significance. The study produces a number of interesting conclusions and makes valuable recommendations for significant stakeholders. The primary study recommendations aim is to create a secure, supportive, and protective neighbourhood environment by enforcing the law and encouraging community involvement in order to reduce the threat of crime, violence, and harassment.

Nanofluid technology represents a significant breakthrough in thermal engineering, with widespread applications spanning heat exchangers, cancer treatment, and heat storage systems. Despite its success in improving heat transfer rates in diverse devices, the challenge of enhancing thermal conductivity using nanoparticles looms large. This study aims to elucidate the 2D flow of nanofluid under suction/injection over a stretching wedge. It considers factors such as Brownian and thermophoretic diffusions, nonlinear heat generation, and thermal radiation. Additionally, it examines the effects of viscous dissipation and Joule heating. Through the conversion of governing nonlinear coupled partial differential equations into a system of coupled ordinary differential equations using similarity transformations, numerical solutions are obtained via the Keller-box method. The analysis delves into the significant impacts of relevant parameters on velocity, temperature, concentration, and microorganism fields, presented graphically. Notably, the findings underscore the role of solid particles in enhancing the thermal efficiency of base fluids. These investigation outcomes are vital for controlling heat transferal rates and fluid velocities throughout a variation of manufacturing processes and industrial sectors, guaranteeing the required quality of the ending product. The perceptions garnered from this research hold capacity for a broad range of industrial purposes and carry consequences through countless engineering disciplines, mostly within the range of nanotechnology.

This study aims to pharmacologically validate Haridra Khanda (HK) and Manjishthadi Kwatham (brihat) (MMK) in allergy management using invivo and invitro studies to rationalize the prescription of these two ayurvedic polyherbal drug formulations, which are currently used in Indian government hospitals. Experimental animals received HK and MMK orally from day 0 to day 14 and histamine (1 mg/kg b.w/i.v) and 1 % evans blue (EB) (0.1 mL) via tail vein on day 14. The compound 48/80 (intracutaneous) challenged mice model followed the same technique. The former mimicked acute anaphylaxis and the latter mast cell degranulation. For both models, EB dye leakage was quantified spectrophotometrically to determine vascular permeability. Plasma histamine was measured in Compound 48/80-induced animals using LC-ESI-MS/MS. The guineapig received HK and MMK p.o. and 0.6 % histamine sprayed in a histamine chamber to simulate allergic rhinitis. Blood eosinophil count and sneeze rate were measured in histamine-challenged guineapigs. Goat R.B.C. membrane stability assay (mammalian cell membrane toxicity) and intracellular histamine-induced cytosolic Ca2+ release assay in Chinese hamster ovary (CHO) cells were performed in vitro. For both histamine and Compound 48/80 challenged animals, HK (22.81 % and 14.58 %) and MMK (19.71 % and 22.40 %) significantly reduced EB dye leakage (p

Background: Hydroponic feeding system enables more effective utilization of the entire plant than typical grazing, which only consumes the plant's shoot. Aim: This study evaluated the effects of feeding maize hydroponic fodder on growth performance, nitrogen balance, nutrient digestibility, hematology and blood metabolites of buffalo calves. Methods: Twelve water buffalo calves, weighing an average of 112 +1.18 kg and between 8 and 10 months old, were divided into three treatments, each with four calves. Each group received one of the treatment diets: T1: the basal diet (BD) at 100%; T2: the BD plus hydroponic feed meal (HFM) at 80%: 20%; and T3: the BD plus HFM at 60%: 40%. For 100 days, each animal was fed ad libitum; the first ten days were used for nutritional adaptation, and the final ten days were used for collection. In addition to their basal diet, each animal received 200 g/day of a normal concentrate mixture to meet their maintenance needs. The basal diet included Green Hay (Lucerne) 80% and Wheat straw 20%. Each animal's daily feed consumption was noted. Calves were weighed biweekly to track growth. Upon completion of the experiment, blood samples were obtained. Results: The amount of DM consumed by ruminants fed diets, including hydroponic fodder, was considerably higher (P< 0.05). Similar trends were seen in CP, ADF, and NDF intake. Ingesting of CP was highest in animals fed T3. Animals fed diets comprising Basal diet 60% + HFM 40% had the highest levels of DM and CP digestibility. Animals fed the T3 diet (Basal diet 60% + HFM 40%) showed the best feed conversion values (P˂0.05). Blood metabolites like blood urea nitrogen, creatinine, and glucose showed non-significant variations in all experimental animals. In haematology, a similar trend was seen. Conclusion: Therefore, it can be said that supplementing the diet with more HFM helped growing buffalo calves gain weight, have a lower FCR, and digest their food more efficiently. [Open Vet J 2023; 13(12.000): 1607-1613]

Abstract Background Pancreatic ductal adenocarcinomas (PDAC) are characterized by frequent cell cycle pathways aberrations. This study evaluated safety and efficacy of abemaciclib, a cyclin‐dependent kinase 4 and 6 inhibitor, as monotherapy or in combination with PI3K/mTOR dual inhibitor LY3023414 or TGFβ inhibitor galunisertib versus standard of care (SOC) chemotherapy in patients with pretreated metastatic PDAC. Methods This Phase 2 open‐label study enrolled patients with metastatic PDAC who progressed after 1–2 prior therapies. Patients were enrolled in a safety lead‐in (abemaciclib plus galunisertib) followed by a 2‐stage randomized design. Stage 1 randomization was planned 1:1:1:1 for abemaciclib, abemaciclib plus LY3023414, abemaciclib plus galunisertib, or SOC gemcitabine or capecitabine. Advancing to Stage 2 required a disease control rate (DCR) difference ≥0 in abemaciclib‐containing arms versus SOC. Primary objectives for Stages 1 and 2 were DCR and progression‐free survival (PFS), respectively. Secondary objectives included response rate, overall survival, safety, and pharmacokinetics. Results One hundred and six patients were enrolled. Abemaciclib plus galunisertib did not advance to Stage 1 for reasons unrelated to safety or efficacy. Stage 1 DCR was 15.2% with abemaciclib monotherapy, 12.1% with abemaciclib plus LY3023414, and 36.4% with SOC. Median PFS was 1.7 months (95% CI: 1.4–1.8), 1.8 months (95% CI: 1.3–1.9), and 3.3 months (95% CI: 1.1–5.7), respectively. No arms advanced to Stage 2. No new safety signals were identified. Conclusion In patients with pretreated metastatic PDAC, abemaciclib‐based therapy did not improve DCRs or PFS compared with SOC chemotherapy. No treatment arms advanced to Stage 2. Abemaciclib remains investigational in patients with PDAC.

The influence of Thermophoresis and Brownian motion on the pulsing flow of nano-fluid (blood) through a curved artery with stenosis and post-stenotic dilatation in its interior is investigated numerically. The Herschel-Bulkley model of fluid dynamics accurately represents the fluid's rheology. By applying the mild stenosis condition, the highly coupled momentum, energy, and mass concentration equations can be modelled and reduced. Explicit finite differences methods are used to discretize and solve the non-dimensionalized governing equations associated with the boundary condition. Entropy creation in blood flow due to loss and magnetohydrodynamic processes is also investigated. Graphs and discussions of the effects of changing pertinent geometric and rheological factors on key flow characteristics, such as temperature, velocity, and mass concentration, are provided. Because of the small changes in blood temperature and mass concentration caused by the artery's curvature, it is observed that the radius of the curved channel has a significant impact on blood velocity. An increase in Brownian motion also resulted in a drop in the nano-temperature, a fluid's but the thermophoresis parameter exhibited the reverse behavior.

White mold, caused by the necrotrophic fungus Sclerotinia sclerotiorum, is a challenging disease to common bean cultivation worldwide. In the current study, two non-proteinogenic amino acids (NPAAs), γ-aminobutyric acid (GABA) and ß-alanine, were suggested as innovative environmentally acceptable alternatives for more sustainable management of white mold disease. In vitro, GABA and ß-alanine individually demonstrated potent dose-dependent fungistatic activity and effectively impeded the radial growth and development of S. sclerotiorum mycelium. Moreover, the application of GABA or ß-alanine as a seed treatment followed by three root drench applications efficiently decreased the disease severity, stimulated plant growth, and boosted the content of photosynthetic pigments of treated S. sclerotiorum-infected plants. Furthermore, although higher levels of hydrogen peroxide (H2O2), superoxide anion (O2•−), and malondialdehyde (MDA) indicated that S. sclerotiorum infection had markedly triggered oxidative stress in infected bean plants, the exogenous application of both NPAAs significantly reduced the levels of the three studied oxidative stress indicators. Additionally, the application of GABA and ß-alanine increased the levels of both non-enzymatic (total soluble phenolics and flavonoids), as well as enzymatic (catalase [CAT], peroxidases [POX], and polyphenol oxidase [PPO]) antioxidants in the leaves of S. sclerotiorum-infected plants and improved their scavenging activity and antioxidant efficiency. Applications of GABA and ß-alanine also raised the proline and total amino acid content of infected bean plants. Lastly, the application of both NPAAs upregulated the three antioxidant-related genes PvCAT1, PvCuZnSOD1, and PvGR. Collectively, the fungistatic activity of NPAAs, coupled with their ability to alleviate oxidative stress, enhance antioxidant defenses, and stimulate plant growth, establishes them as promising eco-friendly alternatives for white mold disease management for sustainable bean production.

Derivatives of Schiff-bases possess a great importance in pharmaceutical chemistry. They can be used for synthesizing different types of bioactive compounds. In this paper, derivatives of new Schiff bases have been synthesized from several serial steps. The acid (I) was synthesized from the reaction of dichloroethanoic acid with 2 moles of p-aminoacetanilide. New acid (I) converted to its ester (II) via the reaction of (I) with dimethyl sulphate in the present of anhydrous of sodium carbonate and dry acetone. Acid hydrazide (III) has been synthesized by adding 80% of hydrazine hydrate to the new ester using ethanol as a solvent. The last step included the preparation of new Schiff-bases (IV-VIII) by the reaction of acid hydrazide with appropriate aromatic aldehydes and using glacial acetic acid as a catalyst. New derivatives were diagnosed by FT-IR, and by mass and 1HNMR spectroscopy (some of them). Derivatives (IV-VIII) were screened for their antibacterial against E. Coli (G-) and staph. aureus (G+). All tested compounds were found to have activity against the two kinds of bacteria.

Abstract A tool Smart Glazing Simulator (SGLSim), has been developed to perform parametric simulation analysis of different window systems with several window-to-wall ratios and orientations to compute and compare the annual energy performance. The net annual energy performance of the building is based on the electricity consumption in heating, cooling, interior lighting, and appliances, along with the electricity generation by the photovoltaic (PV) glazing, which is used to evaluate the energy performance of smart glazing. Performing parametric energy simulations and calculating the net annual electricity consumption of different combinations requires building modeling and energy simulation expertise. A web-based parametric tool can assist the user in carrying out the desired studies without requiring extensive technical knowledge. A case study is prepared for India’s warm and humid climatic zone. This study examines the benefits of double pane semi-transparent photovoltaics (STPV) glazing, STPV glazing with dynamic internal blind, and electrochromic (EC) glazing over other traditional glazing systems. The study shows that the optimal net annual electricity consumption in the case of STPV windows is 10–12% less than the optimal value obtained in a simple glazing case. Additionally, the result suggested that glare-controlled interior blinds in the STPV window further reduce the net annual electricity consumption by up to 15% compared to conventional glazing. Similarly, installing the EC glazing reduces the yearly electricity consumption by up to 5% compared to standard glazing.

As a result of its use in the manufacturing and construction industries, research on the flow of nanofluid is rather well-known among academics and professionals in related fields. It is helpful for electrical equipment to utilize it for cooling reasons, which has shown promising results in terms of reducing energy use. As a result, the primary objective of this research is to inspect the impacts that radiation has on the mixed convection of Walters'-B hybridity nanofluid flow of stagnant point in a horizontal circular cylinder under the circumstances of a constant heat flux. It is considered a conventional fluid despite the presence of copper (Cu) and alumina (Al2O3) nanoparticles in the water (H2O) hybridity nanofluid. To make the solution to the resulting controlling system of equations more straightforward, the numerical approach of a neural network with a back-propagation algorithm (NN-BPA) is used. It follows by clarifying how various physical characteristics, such as blended convection, thermal radiation, and stagnant movement, affect temperature, skin friction, thermal transfer, velocity, and graphical profiles of those variables. The LMNN-BPA has the quickest processing algorithm and performs well in general, corresponding to the thorough analysis. Additionally, the mixed convective and viscoelastic properties exhibit both rising and dropping developments regarding skin friction and heat transmission.

CeO2 and CuO nanoparticles (NPs) are used as additives in petrodiesel to enhance engine performance leading to reduced diesel combustion emissions. Despite their benefits, the additive application poses human health concerns by releasing inhalable NPs into the ambient air. In this study, a bioinspired lung cell exposure system, Dosimetric Aerosol in Vitro Inhalation Device (DAVID), was employed for evaluating the toxicity of aerosolized CeO2 and CuO NPs with a short duration of exposure (≤10 min vs. hours in other systems) and without exerting toxicity from non-NP factors. Human epithelial A549 lung cells were cultured and maintained within DAVID at the air-liquid interface (ALI), onto which aerosolized NPs were deposited, and experiments in submerged cells were used for comparison. Exposure of the cells to the CeO2 NPs did not result in detectable IL-8 release, nor did it produce a significant reduction in cell viability based on lactate dehydrogenase (LDH) assay, with a marginal decrease (10%) at the dose of 388 μg/cm2 (273 cm2/cm2). In contrast, exposure to CuO NPs resulted in a concentration dependent reduction in LDH release based on LDH leakage, with 38% reduction in viability at the highest dose of 52 μg/cm2 (28.3 cm2/cm2). Cells exposed to CuO NPs resulted in a dose dependent cellular membrane toxicity and expressed IL-8 secretion at a global dose five times lower than cells exposed under submerged conditions. However, when comparing the ALI results at the local cellular dose of CuO NPs to the submerged results, the IL-8 secretion was similar. In this study, we demonstrated DAVID as a new exposure tool that helps evaluate aerosol toxicity in simulated lung environment. Our results also highlight the necessity in choosing the right assay endpoints for the given exposure scenario, e.g., LDH for ALI and Deep Blue for submerged conditions for cell viability.

Abstract Salt stress and heavy metal are instigating hazard to crops, menace to agricultural practices. Single and combined stresses affecting adversely to the growth and metabolism of plants. To explore salt and heavy metal resistant plant lines as phytoremediants is a need of time. Physiological responses are main adaptive responses of the plants towards stresses. This response varies with species and ecotype as well as type and level of stress. Two cucurbit weeds from two ecotypes were selected to evaluate their physiological adaptations against independent and combined stresses of various levels of salt (NaCl) and heavy metal (NiCl2). Various physiological parameters like water potential, osmotic potential, pressure potential, CO2 assimilation rate, stomatal conductance, chlorophyll a and b, carotenoids, and production of adaptive chemicals like SOD, CAT, proteins, sugars and proline were studied. Citrullus colocynthis showed more adaptive response than Cucumis melo agrestis and desert ecotype was more successful than agricultural ecotype against stresses.

The increasing prevalence of food allergies worldwide and the subsequent life-threatening anaphylactic reactions often have sparse treatment options, providing only symptomatic relief. Great strides have been made in research and in clinics in recent years to offer novel therapies for the treatment of allergic disorders. However, current allergen immunotherapy has its own shortcomings in terms of long-term efficacy and safety, due to the local side effects and the possibility of anaphylaxis. Allergen-specific immunotherapy is an established therapy in treating allergic asthma, allergic rhinitis, and allergic conjunctivitis. It acts through the downregulation of T cell, and IgE-mediated reactions, as well as desensitization, a process of food tolerance without any allergic events. This would result in a protective reaction that lasts for approximately 3 years, even after the withdrawal of therapy. Furthermore, allergen-specific immunotherapy also exploits several routes such as oral, sublingual, and epicutaneous immunotherapy. As the safety and efficacy of allergen immunotherapy are still under research, the exploration of newer routes such as intra-lymphatic immunotherapy would address unfulfilled needs. In addition, the existence of nanoparticles can be exploited immensely in allergen immunotherapy, which would lead to safer and efficacious therapy. This manuscript highlights a novel drug delivery method for allergen-specific immunotherapy that involves the administration of specific allergens to the patients in gradual increasing doses, to induce desensitization and tolerance, as well as emphasizing different routes of administration, mechanism, and the application of nanoparticles in allergen-specific immunotherapy.

Ensuring bridge safety and longevity through precise vehicle load characterization is crucial for maintaining structural integrity and efficiency. This research highlights the efficacy of deep convolutional neural networks (DCNNs) in analyzing bridge responses. The proposed methodology incorporates abridge model developed in ANSYS APDL, integrated subsequently with Universal Mechanism (UM) software for simulating vehicle-bridge interactions, considering factors such as vehicle load, speed, road surface roughness, and ambient noise. To validate the accuracy and robustness of the DCNN models, the study involved training and testing them on diverse datasets, each comprising 250 randomized samples for various parameters such as load, speed, and surface roughness. Two popular deep learning frameworks, ResNet and Inception models, were employed to assess their capability to identify these critical vehicle-bridge interaction characteristics accurately. The results reveal that the Inception model excelled in vehicle load identification, achieving an impressive validation accuracy of 99.9%. In contrast, ResNet outperformed in vehicle speed identification with a99% validation accuracy, surpassing Inception’s 97.9%. Both models exhibited remarkable resilience to noise, with road surface roughness identification demonstrating exceptional performance, including aperfect 100% training accuracy for ResNet and 99.9% for Inception. Furthermore, to validate the noise robustness of the DCNN model, the load identification is conducted under the effects of measurement noise, and the identification results show that the DCNN model can accurately identify vehicle loads with accuracies of 97.9% at 10 dB and 99.7% at 20 dB, respectively. These findings firmly establish the DCNNs’ capability to accurately identify vehicle load, speed, and road surface roughness, emphasizing their potential to significantly improve bridge safety and longevity.

Abstract In the current study, a vertical, 3D-heated plate is used to replicate the generation of heat energy and concentration into Prandtl liquid. We discuss how Dufour and Soret theories relate to the equations for concentration and energy. In order to see how effectively particles, interact with heat and a solvent, hybrid nanoparticles are used. It does away with the phenomena of viscous dissipation and changing magnetic fields. The motivation behind the developed study is to optimize solvent and heat storage uses in the biological and industrial domains. This article's major goal is to explore the aspects of thermal energy and mass transfer that influence how nanoparticles, hybrid nanoparticles, and 3D melting surface sheets behave. Variable thermal efficiency and variable mass transfer are combined. The system of generated PDEs (difference equations) includes the concentration, velocity, and heat energy equations. The numerical calculations are done for Silver (Ag), Molybdenum Disulfide (MoS2) nanoparticles with Ethylene glycol (C2H6O2) as the base fluid using a boundary layer approach to the mathematical formulation. The system of ODEs is formulated through transformations in order to find a solution. A Galerkin finite element algorithm (G-FEA) is adopted to analyze various aspects versus different parameters. It has been found that motion into hybrid nanoparticles is reduced by motion into nanoparticles. Additionally, differences in heat energy and solvent particle sizes are associated with modifications in magnetic, Dufour, Eckert, and Soret numbers. In contrast to hybrid nanostructures, the output of thermal energy is usually observed to be substantially higher. The magnetic field parameter decreases the particle velocity. In contradiction to the Eckert number, bouncy parameter, and magnetic parameter set values, the maximum quantity of heat energy is obtained. variable thermal conductivity's function. The 3D heated vertical surface convective heat transfer of nanofluids and hybrid nanofluids under the impact of a heat source, thermal radiation, and viscous dissipation has not yet been studied, as far as the authors are aware.