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Children with occipital meningoencephalocele associated with Arnold–Chiari III malformation present unique challenges to anesthesiologists. Meningoencephalocele is a congenital anomaly wherein meninges, brain, and cerebrospinal fluid (CSF) are herniated through defect in the skull. Challenges to anesthesiologists include difficult airway, latex allergy, bleeding, CSF loss, and autonomic disturbances. Here, we report a late case of a 9-month-old male child with occipital encephalocele associated with Arnold–Chiari III malformation. The child underwent surgical correction under general anesthesia without any adverse event. The anticipated difficult airway was secured with prior planning and teamwork. Multidisciplinary care and careful planning are essential to safeguard the perioperative outcomes for patients with meningoencephalocele wherein difficult airway, blood loss, autonomic dysfunction, and perioperative hypothermia are major concerns.

Abstract Background Patent ductus arteriosus is one of the most common cardiac conditions affecting the neonates. Considering the lack of studies done on this topic in healthcare settings in Khyber Pakhtunkhwa province, this study aims to find out the comparative effectiveness of paracetamol and ibuprofen in management of PDA in our healthcare setting to conclude a better management option for the condition. Objective To find and compare the effectiveness of paracetamol and ibuprofen in the closure of patent ductus arteriosus in preterm neonates. Methodology This randomized controlled trial was conducted in the Department of Nursery and Neonatal Intensive Care Unit, Khyber Teaching Hospital, Peshawar, Pakistan, from 10th April 2024 to 10th October 2024. A total of 256 neonates of both genders with patent ductus arteriosus were included. Group A received oral paracetamol, and Group B received oral ibuprofen. The effectiveness of the treatments was evaluated at the end of the treatment period. Results The age range in this study was from 48 to 96 h, with a mean age of 71.79 ± 13.10 h in Group A and 73.40 ± 11.81 h in Group B. Efficacy was observed in 107 (83.6%) patients in Group A compared to 90 (70.3%) patients in Group B, showing a statistically significant difference (P = 0.011). Conclusion Our study has concluded that paracetamol is more effective than ibuprofen in closing patent ductus arteriosus. The trials were retrospectively registered at NIH Trial Registry (NCT06601114) https://clinicaltrials.gov/study/NCT06601114 dated 15/09/2024.

High strength concrete (HSC) is essential for large-scale projects, such as bridges, dams, and high-rise buildings, as it allows for reduced dimensions of beams and columns. This experimental study investigates the effect of polyester fiber on the compressive and split tensile strength properties of HSC grade C60. A total of 90 concrete mixes were prepared, incorporating polyester fiber at varying volumes of 0%, 0.2%, 0.3%, 0.4%, and 0.5%, with curing periods ranging from 3 to 28 days. The results demonstrate that the inclusion of polyester fiber significantly enhances the mechanical properties of HSC, with optimal compressive strength achieved at 0.3% fiber content, leading to a 14.17% increase compared to the control mix. Additionally, split tensile strength improved by 40.63% at 0.2% fiber content and by 65.68% at 0.3% fiber content. Although the slump decreased by 14% to 57% with increased fiber content, no bleeding or segregation was observed in any of the mixes. These findings underscore the potential of polyester fiber to improve the performance of high strength concrete in structural applications.

Energy crises are becoming a problem for many, most of the energy being produced is utilized in buildings. Building design and materials that are used in buildings play a vital role in saving electricity. Sustainable cities are one of the eleventh goal of Sustainable Development Goals to be achieved and this study is in context of SDGs for developing tools to create this globe sustainable and efficient society for humans. Phase change material is a type of material that can absorb and release heat energy as it changes between solid and liquid states. This ability to store and release thermal energy makes PCM a promising material for use in building insulation, Heating Ventilation Air Conditioning Systems, and other energy efficient applications. The use of PCM in buildings has the potential to significantly reduce energy consumption and improve thermal comfort levels. By incorporating PCM into building envelopes, such as walls, roofs, and floors, the material can absorb excess heat during the day and release it at night, helping to regulate indoor temperatures and reduce the need for heating and cooling systems. This study investigates the impact of using PCM in building envelopes. In this regard office building rooms are modelled in CAD software and are simulated in energy plus software. The simulation results are validated by considering the experiment and numerical study as a reference from paper. Model room is simulated for Hyderabad, Pakistan. Building envelopes without PCM have conduction rate of around 106.6 W/m2, whereas building envelopes with PCM have conduction rate around 42 W/m2. This shows that utilization of PCM reduced heat conduction up to around 40%. PCM reduced energy consumption of around 33.25 kWh/year/m2. Results show that without PCM air temperature was above the thermal comfort value. it reached 300C in hot months, it reduced up to 270C with the incorporation of PCM.

In last two decades, Smart Antenna Systems (SAS) as well as Multiple Input Multiple Output (MIMO) systems have emerged as strong and efficient contenders for 5G wireless communication networks due to the advantages they may bring based on the improvements in transmission and reception of electromagnetic signals with respect to omnidirectional antennas. Although there is a fair amount of academic software previously available in this field, cross-use systems simulators do not utilize sufficient wireless system requirements to implement all requirements, and therefore, they do not provide the opportunity to emulate on the broadest lines where SAS or MIMO is more widely used. In this work, a new idea will be formed to improve MIMO 5th generation (5G) smart antenna using adaptive equalizer technology. This new proposal will appear distinctly and noticeably to improve the performance and efficiency of transmission and reception, in addition to its high sensitivity.

Advanced research in biomedical engineering, together with rising treatment standards and the demand for non-conventional methods, have contributed to the explosive growth of the field of dentistry known as regenerative dentistry. Stem cells, scaffolds, and bioactive substances are the three main elements of tissue engineering, the field that forms the basis of regenerative dentistry. Because of these remarkable properties, stem cells produced from dental tissue are very relevant in this field. In a wide spectrum of dental specializations, regenerative techniques have brought novel options to many established treatment protocols. Consider the alternative to conventional root canal therapy provided by pulp revascularization and other regenerative endodontic procedures. Thanks to 3-D bioprinting and computer-aided design, which have revolutionized oral and maxillofacial tissue engineering, modified guided tissue regeneration procedures are gradually replacing standard surgical and nonsurgical periodontal therapy. This paper provides an overview of the most current therapeutic approaches that have been used in clinical settings and highlights the importance of dental tissue-derived stem cells for regenerative dentistry.

The permanent magnet synchronous motor (PMSM) control is demanding task because, which is a nonlinear multivariable coupling system. The vector control has been widely used in the control of PMSM system, where the rotor position information is needed for close loop control system. The mechanical sensors are used for rotor position, which increased the cost of the system. These sensors can be eliminated by adopting the sensorless control methods. In this paper a new continuous terminal sliding mode observer (CTSMO) based speed sensorless control method is proposed, which is substitute of the conventional SMO (CSMO). The suggested the CTSMO is robust against parametric change and load disturbances, which is used to estimate the speed and rotor position from the back EMF (BEMF) of the PMSM system. The conventional SMO needs the low pass filter (LPF), position compensation techniques and sigmoid function instead of sign function to decrease the chattering phenomena. To eliminate the chattering phenomena effectively the new CTSMO based speed sensorless method is designed in this paper, which has also ability of minimization of the speed and rotor position error. The stability of the proposed technique is analyzed by Lyapunov function, the simulation have been carried out for the validation of the suggested technique.

Abstract Systematic crises may disrupt well‐designed nutrition interventions. Continuing services requires understanding the intervention paths that have been disrupted and adapting as crises permit. Alive & Thrive developed an intervention to integrate nutrition services into urban antenatal care services in Dhaka, which started at the onset of COVID‐19 and encountered extraordinary disruption of services. We investigated the disruptions and adaptations that occurred to continue the delivery of services for women and children and elucidated how the intervention team made those adaptations. We examined the intervention components planned and those implemented annotating the disruptions and adaptations. Subsequently, we detailed the intervention paths (capacity building, supportive supervision, demand generation, counselling services, and reporting, data management and performance review). We sorted out processes at the system, organizational, service delivery and individual levels on how the intervention team made the adaptations. Disruptions included decreased client load and demand for services, attrition of providers and intervention staff, key intervention activities becoming unfeasible and clients and providers facing challenges affecting utilization and provision of services. Adaptations included incorporating new guidance for the continuity of services, managing workforce turnover and incorporating remote modalities for all intervention components. The intervention adapted to continue by incorporating hybrid modalities including both original activities that were feasible and adapted activities. Amidst health system crises, the adapted intervention was successfully delivered. This knowledge of how to identify disruptions and adapt interventions during major crises is critical as Bangladesh and other countries face new threats (conflict, climate, economic downturns, inequities and epidemics).

Advanced thermal management technologies represent an important research frontier because such materials and systems show promise for enhancing personal physiological comfort and reducing building energy consumption. These technologies typically offer the advantages of excellent portability, user-friendly tunability, energy efficiency, and straightforward manufacturability, but they frequently suffer from critical challenges associated with poor breathability, inadequate wash stability, and difficult fabric integration. Within this broader context, our laboratory has previously developed heat-managing composite materials by drawing inspiration from the color-changing skin of the common squid. Herein, we describe the design, fabrication, and testing of breathable, washable, and fabric-integrated variants of our composite materials, which demonstrate state-of-the-art adaptive infrared properties and dynamic thermoregulatory functionalities. The combined findings directly advance the performance and applications scope of our bioinspired thermoregulatory composites and ultimately may guide the incorporation of desirable multifunctionality into other wearable technologies.

Abstract Faults in transmission lines cause instability of power system and result in degrading end users sophisticated equipment. Therefore, in case of fault and for the quick restoration of problematic phases, reliable and accurate fault detection and classification techniques are required to categorize the faults in a minimum time. In this work, 500 kV transmission line (Jamshoro‐New Karachi), Sindh, Pakistan has been modeled in MATLAB. The discrete wavelet transform (DWT) has been used to extract features from the transient current signal for different faults in 500 kV transmission line under various parameters such as fault location, fault inception angle, ground resistance and fault resistance and time series data has been obtained for fault classification. Moreover, the temporal convolutional neural network (TCN) is used for fault classification in 500 kV transmission network due to its robust framework. From simulation results, it is found that faults in 500 kV transmission line are classified with 99.9% accuracy. Furthermore, the simulation results of the TCN model compared to bidirectional long short‐term memory (BiLSTM) and Gated Recurrent Unit (GRU) and it has been found that TCN model is capable of classifying faults in 500 kV transmission line with high accuracy due to its ability to handle long receptive field size, less memory requirement and parallel processing due to dilated causal convolutions. Through this work, the meantime to repair of 500 kV transmission line can be reduced.

Abstract Upper limb amputation severely impairs tactile perception, limiting daily activities. Developing a near‐natural replacement with prosthetic devices requires improving user sensory experiences during object interactions. The ideal upper limb prosthesis should provide real‐time sensory feedback, mirroring natural experiences. Current prostheses struggle with providing adequate tactile feedback due to sensory limitations. Inspired by the sensory properties of skin, we present a micro‐fabricated, multiplexed electronic skin (e‐skin) with actuators for sensory feedback in upper limb amputation. The piezoelectric‐capacitive sensor array detects static pressure, temperature, vibration, and texture, with integrated actuators stimulating the skin to provide real‐time feedback. The sensors integrate with actuators via readout electronics, making the system standalone and easy to use. The flexible, compact sensor array design (two pixels within a 1 cm² footprint) detects a wide range of pressure (0.5–10 kPa), temperature (22–60 °C), vibration (35–100 Hz), and texture (2.5–45 Hz), suitable for daily use. The e‐skin, attached to a prosthetic finger, is tested for feasibility on human volunteers with wrist‐mounted actuators. Statistics are used to quantitatively assess system performance. The integration of multiplexed sensors and actuators enhances tactile feedback, improving the quality of life for people with upper limb amputations.

Plants encounter various biotic and abiotic stresses throughout their lifecycle, which can adversely impact their productivity and lead to yield loss. This ultimately results in a significant decline in food production with global pressure on declining agriculture. The agrochemical pesticides have been proven effective in controlling various diseases in major crops, their excessive use poses significant risks to the environment and human health and negatively impacts non-target host microbiota. Novel approaches in the form of host plant microbiome as an alternative strategy to overcome these stresses have recently gained increasing attention. Emerging evidence suggests that plants subjected to biotic and abiotic stress experience diverse microbial local (diffusible) and distant (volatile organic compounds) metabolites and respond with the expression of defense genes (transcriptomic variations) that result in changing leaf and root exudates and alter resident microbial community structure. The relative abundance of symbiotic microorganisms under stress may favor plant survival and enhance adaptation during stress. Thus, to counter the negative effects, introducing an efficient microbiome into the host crop is highly desirable due to the attractive functional potential of the phytomicrobiome. Here, we summarize more effective and reproducible strategies to use microbial activities in crop production and protection to promote a suitable agricultural environment. In addition, detailed molecular mechanisms of phytomicrobiome in stimulating plant immune system, the interaction between microbiome and plant defense system, and defense strategies of microbiome against biotic and abiotic factors have been described. Finally, we explored the plant-based strategies for microbiome engineering and bioinformatics methods to predict microbiome functions.

Keratinocytes in mucosal and skin tissues maintain tissue integrity via desmosomes and desmoglein-3 (Dsg3). Pemphigus Vulgaris (PV) is a life-threatening autoimmune blistering disease characterized by autoantibodies against Dsg3, disrupting desmosomes. Nuclear factor erythroid 2–related factor 2 (Nrf2) regulates oxidative stress responses crucial for skin tissue protection. Although the pathogenesis of PV is known, the detailed molecular events remain unclear. This study investigates changes in Nrf2 expression in keratinocytes following pathogenic anti-Dsg3 antibody AK23 exposure, using dose- and time-dependent studies employing immunofluorescence analysis. N/TERT keratinocytes were cultured in keratinocytes serum-free medium and treated with AK23 at varying doses (5 µg/mL,40µg/mL,75µg/mL) and durations (2, 6, 24 h). Immunofluorescence staining was performed to assess the expression of Nrf2 and Dsg3. All fluorescent images were analyzed using ImageJ software. A dose-dependent increase in Dsg3 was noted following AK23 treatment, while Nrf2 expression and subcellular localization varied. Time-course analyses showed decreased Nrf2 at 24 h and increased Dsg3 levels. Early time-point (2 and 6 h) variations were evident in Nrf2 levels. This study highlights the impact of AK23 on Nrf2 expression, potentially disrupting Nrf2-mediated cytoprotection and implicating oxidative stress (ROS generation) in PV pathogenesis. Further investigation is necessary to validate the findings.

According to the researchers, the aim of this study is to determine the impact of the flipped learning approach on fifth-year students' understanding of reading content during their last year of preparatory education. To confirm the results of the study, the null hypothesis was developed, which claims that the experimental group's mean scores are not statistically significant when compared to the control group's mean scores when using the flipped learning strategy. To test the effectiveness of flipped learning, an experimental approach was used to create two equivalent experimental groups with a control group. One group learned by the flipped learning strategy and the other used the regular method for the second course (2019-2020) over eight weeks, with three classes each week. According to the findings, there are significant differences between experimental and control group means of reading comprehension and experimental group favor. The divergence in these parameters is a result of the experimental group using the Flipped Learning Strategy in their lessons.

Abstract Bladder volume measurement is critical for early detection and management of lower urinary tract dysfunctions. Current gold standard is invasive, and alternative technologies either require trained personnel or do not offer medical grade information. Here, we report an integrated wearable ultrasonic bladder volume monitoring device for accurate and autonomous continuous monitoring of the bladder volume. The device incorporates flexible and air-backed ultrasonic transducers and miniaturized control electronics with wireless data transmission capability. We demonstrate the real-life application of the device on healthy volunteers with various bladder shapes and sizes with high accuracy. Apart from the lower urinary tract dysfunctions, the proposed technology could also be adapted for various wearable ultrasonic applications.

Background: The provision of dental care in Pakistan is limited, with less than 5% of the population having access to qualified dental practitioners. The lack of contextually relevant local dental guidelines further adds to the problem. We developed clinical practice guidelines (CPGs) and referral pathways to improve primary care for common oral diseases. Methods: Using the GRADE-ADOLOPMENT approach, recommendations from source guidelines (developed in Europe and the United States) were adopted (retained as is or with minor changes), adapted (modified according to the local context), or excluded (omitted due to lack of local relevance). The guidelines included diseases such as periodontitis, dental pain, intraoral swelling, and oral cavity malignancies. The end result was a set of locally relevant CPGs, which were then used to formulate referral pathways, with the incorporated suggestions being based on a thorough evidence review process. Results: We included four recommendations, three of which were adopted with minor modifications to the referral pathway. These changes focused on assessing potentially malignant oral conditions and counseling for risk factors. No content changes were needed for the CPGs of the other two disorders. We developed referral pathways for three specific oral conditions, detailing primary care physicians’ roles in diagnosis, initial treatment, and timely referral. Conclusion: Contextually relevant dental CPGs and referral pathways can improve patient outcomes in Pakistan. Our study produced four additional recommendations focused on risk factor counselling and mitigation, which could potentially reduce the burden of oral malignancies in our local population.

In data-scarce regions, prudent planning and precise decision-making for sustainable development, especially in agriculture, remain challenging due to the lack of correct information. Remotely sensed satellite images provide a powerful source for assessing land use and land cover (LULC) classes and crop identification. Applying remote sensing (RS) in conjunction with the Geographical Information System (GIS) and modern tools/algorithms of artificial intelligence (AI) and deep learning has been proven effective for strategic planning and integrated resource management. The study was conducted in the canal command area of the Lower Chenab Canal system in Punjab, Pakistan. Crop features/classes were assessed using the Normalized Difference Vegetation Index (NDVI) algorithm. The Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m and Landsat 5 TM (thematic mapper) images were deployed for NDVI time-series analysis with an unsupervised classification technique to obtain LULC classes that helped to discern cropping pattern, crop rotation, and the area of specific crops, which were then used as key inputs for agricultural mechanization planning and resource management. The accuracy of the LULC map was 78%, as assessed by the error matrix approach. Limitations of high-resolution RS data availability and the accuracy of the results are the concerns observed in this study that could be managed by the availability of good quality local sources and advanced processing techniques, that would make it more useful and applicable for regional agriculture and environmental management.

Populus spp. belongs to the deciduous flowering plants in the family Salicaceae, primarily located in the Northern Hemisphere, including Trans-Himalayan, cold arid desert Ladakh. In Ladakh, it is predominantly cultivated in irrigated land patches along the riverbanks. This plant holds significant economic value as its wood is extensively used in furniture-making and house constructions. Recently, a highly successful pest, identified as Pheosia albivertex (Hampson 1983), was observed infesting the Populus plantations, marking a new record of insect infestation. The pest causes complete defoliation, particularly during midsummer, which is the prime foliage period. The initial sighting of this insect occurred in Dyanguchay village, Suru-valley, Kargil district of the union territory of Ladakh. However, during a thorough three-year-and-five-month investigation from April 2019 to August 2022, it was found spreading to neighbouring areas. Consequently, without timely control measures, it poses a significant threat to the popular plantation in Ladakh and other adjoining areas.

This study examines the Hall current characteristics in hybrid nanofluid flow over a rotating disc, incorporating the effects of magnetic fields and nonlinear thermal radiation. The hybrid nanofluid is a novel blend of copper (Cu) and titanium dioxide (TiO2) nanoparticles in water, with the flow behavior further enhanced by adding single-wall carbon nanotubes (SWCNT) and multi-wall carbon nanotubes (MWCNT) with CoFe2O4. The study uniquely addresses the impact of nanoparticle shapes on flow dynamics, crucial in the evolving field of nanotechnology, where carbon nanotubes (CNTs) find applications in energy storage, fracture toughness, and electromagnetic interactions. Advanced machine learning techniques, such as physics-informed neural networks and hybrid models, are employed to improve predictions, using synthetic data based on governing partial differential equations. Solutions are derived via the new iterative method (NIM) and the bvp4c function in Mathematica. The modified New Iterative Method (NIM) integrated with Physics-Informed Neural Networks (PINNs) to address challenges in modeling nonlinear hybrid nanofluid dynamics. This novel approach marks a significant advancement in predictive fluid dynamics. The findings reveal intricate interactions within the nanofluid flow, with graphical analyses illustrating the influence of varied parameters on component behavior and heat transmission. This integration of computational and machine learning methods enhances the understanding of complex flow dynamics, marking a significant advancement in fluid dynamics research.

Background Cigarette smoking is the most common form of tobacco use worldwide. With the frequent introduction of new dental materials, the effect of smoking on their optical properties such as long term color stability, should to be thoroughly investigated. Objective This in-vitro study aims to investigate the effect of smoking on the optical properties of contemporary dental ceramics used currently for restoration of teeth. Methods Five different materials in two shades (B1 and C1) were used with 15 samples from each pressable lithium disilicate (Emax), layered lithium disilicate (Lmax), porcelain fused to metal (PFM), monolithic zirconia (MZr) and layered zirconia (LZr) were used (n = 75). The samples were exposed to conventional cigarette smoke and color stability was assessed at four different time intervals i.e., baseline, 1 week, 1 month and 6 months. CIELAB color space (CIE L*a*b*) values were used to evaluate the color difference (ΔE). A one-way analysis of variance (Anova) was used for statistical analysis of ΔE. Significant P-value was kept as 3.3 which is higher than the acceptable range. Lowest color change was observed in Emax and PFM.

This paper investigates the effect of nonlinear thermal radiation on SWCNT-TiO2 and MWCNT-CoFe2O4 nanoparticles suspended in a water-based hybrid nanofluid, flowing past rotating disks. The study employs the Cattaneo-Christov heat flux model to capture the influence of non-Fourier heat conduction. The rotational motion of the disks generates the fluid flow, and the governing partial differential equations are transformed into dimensionless forms using similarity variables. These equations are then solved using a New Iterative Technique (NIT) in Mathematica, which is known for its rapid convergence and accuracy. The analysis focuses on the behavior of various parameters, including velocity components (û, vˆ, ŵ), temperature (Tˆ), and thermal conductivity (kˆ), under different heat transfer conditions. Graphical representations illustrate the effects of these parameters, providing insights into the thermal and fluid dynamic performance of the hybrid nanofluid. The study demonstrates that the NIT is highly effective for solving complex fluid dynamics problems, offering precise and swift solutions. NIM provide an efficient and accurate solution for complex nonlinear problems, overcoming the limitations of traditional methods. This approach enhances computational efficiency and solution accuracy in modeling hybrid nanofluid behavior. This research contributes to the understanding of hybrid nanofluids in engineering applications, particularly in optimizing heat transfer in systems involving rotating machinery.

In the dynamic world of construction projects, fostering innovation is paramount. This study investigates the transformative potential of shared leadership as a catalyst for team innovation. We examine knowledge-sharing density as a critical mediator through the lens of knowledge management. We adopted a mixed methods approach, collecting multi-wave and multi-source field data and using social network measures. The results demonstrate shared leadership acts as a direct driver of knowledge-sharing density, facilitating innovation in construction projects. Knowledge-sharing density emerges as a transformative force, mediating the impact of shared leadership on team innovation. This intricate relationship unveils hidden potential for innovation within construction teams. Results also show the influence of team open-mindedness norms, which moderate the direct link between knowledge-sharing density and team innovation and the indirect influence of shared leadership. This study pioneers an integrated approach to understanding leadership and knowledge management in the construction sector, with important insights for team leadership, knowledge-sharing, and project performance.

Steel-fiber-reinforced concrete (SFRC) has replaced traditional concrete in the construction sector, improving fracture resistance and post-cracking performance. However, extreme temperatures degrade concrete's material characteristics including stiffness and strength. The construction industry increasingly embraces machine learning (ML) to estimate concrete properties and optimize cost and time accurately. This study employs independent ML methods, gene expression programming (GEP), multi-expression programming (MEP), XGBoost, and Bayesian estimation model (BES) to predict SFRC compressive strength (CS) at high temperatures. 307 experimental data points from published studies were utilized to develop the models. The models were trained using 70 % of the dataset, with 15 % for validation and 15 % for testing. Iterative hyperparameter adjustment and trial-and-error refining achieved optimum predictions. All the models were evaluated using correlation (R) values for training, validation, and testing datasets. MEP showed slightly lower R-values of 0.923, 0.904, and 0.949 than GEP, which performed consistently with 0.963, 0.967, and 0.961. XGBoost had the greatest training R-value of 0.997 but dropped in validation (0.918) and testing (0.896). BES model exhibited commendable performance with scores of 0.986, 0.944, and 0.897. GEP and XGBoost exhibited great accuracy, with GEP sustaining constant accuracy across all datasets, highlighting its potency in predicting CS. Interpreting model predictions using SHapley Additive exPlanation (SHAP) highlighted temperature over heating rate. CS improved significantly as the steel fiber volume fraction (Vf) reached 1.5 %, plateauing thereafter. The proposed models are valid and accurate, providing designers and builders with a practical and adaptable method for estimating strength in SFRC structural applications, particularly under high-temperature conditions.

ABSTRACT Lentils that are considered powerhouse of healthy calories are traditionally consumed in different regions of the world. With the increasing awareness regarding lentils' health‐related benefits, it is getting popular among people of all ages. The rising demand also necessitated the increase in global lentil production with Canada grabbing the top rank among the global producers. This review discussed lentil's trade‐related statistics, along with in depth details of various popular cuisines, and consumption patterns observed in Asia, Middle East, Africa, the United States, Canada, Europe, and Mediterranean region. Lentils are added as ingredient in soups, rice cuisines, pasta, flat breads, salads, nuggets, and burger patties and thus carry its name throughout the food menus from appetizers and salads to main course meals.

The prevalence of infectious diseases and rapid population expansion has increased the number of medical facilities. Due to the patients' limited mobility, these hospitals are more susceptible to fire disasters. Both Pathfinder and Fire Dynamic simulators were used to calculate the required safe evacuation time (RSET), heat release rate, visibility, temperature, CO, and oxygen effects on temperature, and available safe evacuation time (ASET). The safety egress of the medical hospital was then evaluated by comparing the available safe evacuation time (ASET) and required safe evacuation time (RSET). The simulation findings showed that the egress guides depend on delay time when delay time increases the egress guides drop. We also studied the importance of egress route decisions and suggested that at least 20 to 30 egress guides be on duty in the medical facility. The safety criteria for the medical facility have been proposed based on the delay time with the normalized egress guides. The high oxygen concentration in a hospital can put the medical staff and patients in danger and limit the required safe egress time to less than 150s. The proposed measures can be used to assess the evacuation safety of a typical medical hospital in use relatively quickly and efficiently.

Concrete is the second-most used material globally and significantly impacts the environment by emitting a large amount of carbon dioxide (CO2). This scientometric review investigates the sustainable use of waste glass (WG) in concrete. Our study examines the impact of waste glass powder (WGP) on the mechanical and fresh characteristics of concrete and its environmental implications, enhanced by a machine learning prediction model. We observed a progressive increase in research activity on WGP-based concrete since 2000, indicating the growing interest in this area. The primary focus areas are engineering and material science, reflecting the application potential, structural performance, and material properties of WGP-based concrete. Our discussions highlight the significant benefits of WGP in concrete, including its potential to reduce landfill usage, environmental pollution, and enhance properties such as strength, sulfate resistance, alkali–silica reaction resistance, and freeze–thaw resistance. The review also explores the microstructure of glass powder (GP)-based concrete, illuminating the complex interactions between glass particles and the concrete matrix, which influence the material’s overall performance. Environmental impact assessments underscore the necessity for sustainable construction practices and waste reduction. Utilizing machine learning prediction models helps optimize the composition of GP-based concrete, thus enhancing material performance and durability. This review provides a comprehensive analysis of using WG in concrete, contributing to the field’s understanding and informing future research and innovations to optimize WG use in concrete applications.

A detailed examination of the effects of double stratification on the magnetized second grade nanofluid created by a stretching sheet within the porous medium has been carried out in this study. The CBC (convective boundary conditions) and NH (Newtonian heating) conditions are utilized for the analysis. The relevant similarity transformations are defined in order to transform the governing nonlinear PDEs into dimensionless ODEs. The transformed equations are numerically treated with bvp4c in Matlab software package. The computations are expressed in tabular and graphical forms. The flow parameters involved in the modeling are demonstrated on temperature, velocity, and concentration of nanofluid. The calculations of Nusselt number − θ ′ ( 0 ) , Sherwood number − ϕ ′ ( 0 ) and skin-friction coefficient C fx ( 0 ) against the distinct values ofconstraints for general, CBC and NH are expressed to examine the flow situation. The numeric computations are matched with the literature published earlier for particular cases which shows the validity of current computations. It is noted that the skin friction is decreasing with an increment in second grade parameter. Flow velocity is increased by rising the second grade parameter.