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Background Dengue is becoming more common in Pakistan with its alarming spreading rate. A historical review needs to be carried out to find the root causes of dengue dynamics, the factors responsible for its spread and lastly to formulate future strategies for its control. Methods We searched (January, 2015) all the published literature between 1980 and 2014 to determine spread/burden of dengue disease in Pakistan. Results A total of 81 reports were identified, showing high numbers of dengue cases in 2010, 2011, and 2013. The tendency of dengue to occur in younger than in older age groups was evident throughout the survey period and all four serotypes were recorded, with DENV1 the least common. Most dengue hemorrhagic fever (DHF) cases fell in the 20–45 years age range. High frequencies tended to be observed first in the Southern coastal region characterized by mild winters and humid warm summers and then the disease progressed towards the lowland areas of the Indus plain with cool winters, hot summers and monsoon rainfall. Based on this survey, new risk maps and infection estimates were identified reflecting public health burden imposed by dengue at the national level. Conclusions Our study showed that dengue is common in the three provinces of Pakistan, i.e., Khyber Pakhtunkhwa (KP), Punjab and Sindh. Based on the literature review as well as on our study analysis the current expansion of dengue seems multifactorial and may include climate change, virus evolution, and societal factors such as rapid urbanization, population growth and development, socioeconomic factors, as well as global travel and trade. Due to inadequate remedial strategies, effective vector control measures are essential to target the dengue vector mosquito where high levels of human-vector contact occur. The known social, economic, and disease burden of dengue is alarming globally and it is evident that the wider impact of this disease is grossly underestimated. An international multi-sectoral response, outlined in the WHO Global Strategy for Dengue Prevention and Control, 2012–2020, is now essential to reduce the significant influence of this disease in Dengue endemic areas. Overall gaps were identified in knowledge around seroprevalence, dengue incidence, vector control, genotype evolution and age-stratified serotype circulation.

This paper deals with the impact of corrosion on the mechanical properties of steel in reinforced concrete. Steel bars were extracted from a 27-year-old corroded reinforced concrete beam that had been exposed to a chloride environment. Bars with different degrees of corrosion and with different corrosion pit depths were tested in tension. A comparison was made between nominal and true stress for corroded and control steel specimens. It was noted that the degree of corrosion strongly affected the mechanical properties of the steel, particularly the ultimate stress and strain. Interestingly, the true yield strength of all the corroded steel bars remained almost constant while their true ultimate strength was considerably increased. A reduction of the ultimate elongation appeared to be the major effect of corrosion and affected the compliance with standards.

Triterpenes possess anti-inflammatory and anti-nociceptive effects. In this study anti-inflammatory activities of Asparacosin A were evaluated' using cyclooxygenases 1 and 2 (COX-1/2) inhibition assays. Moreover, anti-nociceptive activities were assessed by carrageenan-induced paw edema test, xylene-induced ear edema tests, and acetic acid-induced writhing and formalin tests. Additionally molecular docking was conducted to elucidate the binding mechanism of the compound and to correlate the findings with the data. Oral administration of Asparacosin A at the doses of 10, 20, and 40 mg/kg induced significant anti-inflammatory effects ( < 0.05, < 0.01, and < 0.001) in a dose-dependent manner in both models. Asparacosin A also inhibited the human recombinant COX-2 enzyme and caused a dose-dependent decrease in the levels of TNF-α, IL-1β, and PGE2 in the carrageenan-induced paws. Moreover, Asparacosin A displayed significant anti-nociceptive effects ( < 0.05, < 0.01, < 0.001) at the doses of 10, 20, and 40 mg/kg in acetic-acid induced writhing test. However, in formalin test, Asparacosin A (10-40 mg/kg, p.o) produced anti-nociceptive effects only in the late phase, similar to the effect observed with the reference drug celecoxib (50 mg/kg, p.o). Molecular docking was carried out on both COX-1 and COX-2 structures which revealed that Asparacosin A targets allosteric binding site similar to the binding mode of the selective COX inhibitor. In conclusion, Asparacosin A exhibits anti-inflammatory and peripheral anti-nociceptive activities which are likely mediated inhibition of COX-2 enzyme and inflammatory cytokines. Furthermore, Asparacosin A can serve as a model to obtain new and more selective potent anti-inflammatory and anti-nociceptive drugs.

The escalation of global urbanization and industrial expansion has resulted in an increase in the emission of harmful substances into the atmosphere. Evaluating the effectiveness of titanium dioxide (TiO 2 ) in photocatalytic degradation through traditional methods is resource-intensive and complex due to the detailed photocatalyst structures and the wide range of contaminants. Therefore in this study, recent advancements in machine learning (ML) are used to offer data-driven approach using thirteen machine learning techniques namely XG Boost (XGB), decision tree (DT), lasso Regression (LR2), support vector regression (SVR), adaBoost (AB), voting Regressor (VR), CatBoost (CB), K-Nearest Neighbors (KNN), gradient boost (GB), random Forest (RF), artificial neural network (ANN), ridge regression (RR), linear regression (LR1) to address the problem of estimation of TiO 2 photocatalytic degradation rate of air contaminants. The models are developed using literature data and different methodical tools are used to evaluate the developed ML models. XGB, DT and LR2 models have high R 2 values of 0.93, 0.926 and 0.926 in training and 0.936, 0.924 and 0.924 in test phase. While ANN, RR and LR models have lowest R 2 values of 0.70, 0.56 and 0.40 in training and 0.62, 0.63 and 0.31 in test phase respectively. XGB, DT and LR2 have low MAE and RMSE values of 0.450 min -1 /cm 2 , 0.494 min -1 /cm 2 and 0.49 min -1 /cm 2 for RMSE and 0.263 min -1 /cm 2 , 0.285 min -1 /cm 2 and 0.29 min -1 /cm 2 for MAE in test stage. XGB, DT, and LR2 have 93% percent errors within 20% error range in training phase. XGB has 92% and DT, and LR2 have 94% errors with 20% range in test phase. XGB, DT, LR2 models remained the highest performing models and XGB is the most robust and effective in predictions. Feature importances reveal the role of input parameters in prediction made by developed ML models. Dosage, humidity, UV light intensity remain important experimental factors. This study will impact positively in providing efficient models to estimate photocatalytic degradation rate of air contaminants using TiO 2 .

Coconut products such as oil, milk powder, activated carbon, and desiccated coconut are increasingly in demand, leading to higher coconut production and a surplus of coconut fibers. Despite their excellent physical and mechanical properties, these fibers are often discarded or burned due to limited research into alternative uses, contributing to environmental pollution. This study evaluates the potential of coconut fibers in hot mix asphalt (HMA) to reduce waste and enhance their mechanical performance. Central composite design (CCD) was adopted to optimize fiber-modified HMA mixes using response surface methodology (RSM) based on Marshall testing. Sixty Marshall samples with varying fiber content, bitumen content, and fiber length were prepared to develop the RSM model based on 20 runs. Fiber content (%), fiber length (mm), and bitumen content (%) were considered as factors, while marshall stability (KN) and flow (mm) were taken as responses. The optimized mix, containing 0.28% coconut fibers (approximately 13 mm in length) and 4. 16% bitumen, achieved a marshall stability of 18. 02 kN and a flow of 3.12 mm. Validation of the optimized solution with the experimental trials showed an error of 7.05% for marshall stability and 6. 11% for marshall flow. Indirect tensile strength testing showed a 5% higher tensile strength for the optimized dry mix compared to the 1.29 KN observed for control samples. Furthermore, the tensile strength ratio between dry and wet samples was recorded to be higher than the threshold of 80% for both control and optimized HMA mixes. Moreover, the indirect tensile stiffness modulus (ITSM) for control samples recorded at 5 °C was higher than the optimized mix. However, the optimized HMA mixes resulted in around 13%, 6%, and 2.16% higher ITSM at 15 °C, 20 °C, and 25 °C, respectively, in reference to the control mix. Furthermore, the indirect tensile fatigue testing revealed that the control mix performed better than the optimized mix. Nonetheless, the optimized mix showed steady behavior against stress variation as compared to the control mix. Overall, this study demonstrates the effective use of RSM to optimize the Marshall mix design, reducing laboratory testing. Additionally, it was observed that optimized fiber-modified HMA mixes exhibit superior mechanical properties compared to control samples, paving the roads for sustainable and efficient asphalt technologies.

Aedes aegypti and Aedes albopictus play a fundamental role in transmission of dengue virus to humans. A single infected Aedes mosquito is capable to act as a reservoir/amplifier host for dengue virus and may cause epidemics via horizontal and vertical modes of dengue virus (DENV) transmission. The present and future dengue development can be clarified by understanding the elements which help the dissemination of dengue transmission. The current study deals with molecular surveillance of dengue in addition to ecological and social context of 2013 dengue epidemics in Swat, Pakistan. Herein, we reported dengue vectors surveillance in domestic and peridomistic containers in public and private places in 7 dengue epidemic-prone sites in District Swat, Pakistan from July to November 2013. Using the Flaviviruses genus-specific reverse transcriptase (RT) semi nested-PCR assay, we screened blood samples (N = 500) of dengue positive patients, 150 adult mosquito pools and 25 larval pools. The 34 adult and 7 larval mosquito pools were found positive. The adult positive pools comprised 30 pools of Ae. aegypti and 4 pools of Ae. albopictus, while among the 7 larval pools, 5 pools of Ae. aegypti and 2 pools of Ae. albopictus were positive. The detected putative genomes of dengue virus were of DENV-2 (35% in 14 mosquito pools & 39% in serum) and DENV-3 (65% in 27 mosquito pools & 61% in serum). The higher vector density and dengue transmission rate was recorded in July and August (due to favorable conditions for vector growth). About 37% of Ae. aegpti and 34% Ae. albopictus mosquitoes were collected from stagnant water in drums, followed by drinking water tanks (23% & 26%), tires (20% & 18%) and discarded containers (10% & 6%). Among the surveyed areas, Saidu was heavily affected (26%) by dengue followed by Kanju (20% and Landikas (12%). The maximum infection was observed in the age group of <15 (40%) followed by 15-45 (35%) and >45 (25%) years and was more in males (55.3%) as compare to females (44.7%). The increase in vector mosquito density and the subsequent viral transmission was determined by a complex interplay of ecological, biological and social factors. The suitable environmental conditions and discriminable role of Aedes through trans-ovarial transmission of DENV is indispensable in the recent geographic increase of dengue in Pakistan. Climate change affects the survival and dispersion of vectors as well as the transmission rates of dengue. Control of Aedes mosquitoes (vectors) and elimination of breeding sources must be emphasized and prioritized. Such actions may not only reduce the risk of dengue transmission during epidemics, but also minimize the chances of dengue viruses establishment in new (non endemic) areas of the region.

Concrete is used worldwide as a construction material in many projects. It exhibits a brittle nature, and fibers' addition to it improves its mechanical properties. Polypropylene (PP) fibers stand out as widely employed fibers in concrete. However, conventional micro-PP fibers pose challenges due to their smooth texture, affecting bonding within concrete and their propensity to clump during mixing due to their thin and soft nature. Addressing these concerns, a novel type of PP fiber is proposed by gluing thin fibers jointly and incorporating surface indentations to enhance mechanical anchorage. This study investigates the incorporation of macro-PP fibers into high-strength concrete, examining its fresh and mechanical properties. Three different concrete strengths 40 MPa, 45 MPa, and 50 MPa, were studied with fiber content of 0–1.5% v/f. ASTM specifications were utilized to test the fresh and mechanical properties, while the RILEM specifications were adopted to test the bond of bar reinforcements in concrete. Test results indicate a decrease in workability, increased air content, and no substantial shift in fresh concrete density. Hardened concrete tests, adding macro-PP fibers, show a significant increase in splitting tensile strength, bond strength, and flexural strength with a maximum increase of 34.5%, 35%, and 100%, respectively. Concrete exhibits strain-hardening behavior with 1% and 1.5% fiber content, and the flexural toughness increases remarkably from 2.2 to 47.1. Thus, macro PP fibers can effectively improve concrete's mechanical properties and resistance against crack initiation and spread.

Flexible pavements using conventional bitumen are prone to suffering severe distress in hot climates, particularly rutting and moisture-induced damage. This study explores synergistic effects of waste-derived High-Density Polyethylene (HDPE) and Bakelite as dual modifiers for asphalt mixtures under Pakistan’s extreme climate, where summer temperatures exceed 45 °C. Modified mixtures were prepared via wet process using HDPE (3%, 6%, 9% by weight of optimum bitumen content) combined with 6% Bakelite, evaluated against control mixtures (60/70 bitumen, NHA Class-B gradation). Performance assessment included indirect tensile strength, moisture susceptibility (TSR), resilient modulus, and Hamburg wheel tracking tests. The optimal 6%HDPE + 6%Bakelite formulation achieved remarkable improvements over control: 24.7% higher dry ITS (0.647 MPa), 48.7% higher conditioned ITS (0.617 MPa), 95.36% TSR (19% above specifications), 43.7% greater resilient modulus (4866 MPa), and 27.4% lower rutting depth (2.38 mm). These enhancements are likely associated with the development of a stiffer polymer resin network between HDPE and rigid Bakelite particles, which appears to provide a favorable balance between mixture flexibility and stiffness. At 9% HDPE, performance degradation in strength and moisture-related properties suggests possible phase separation, although rutting resistance continued improving. This dual-modification strategy provides sustainable, cost-effective enhancement of pavement durability in hot climates while addressing waste management challenges, offering significant potential for reducing maintenance costs and extending service life.

This study presents an experimental and finite element analysis of reinforced concrete beams with solid, hollow, prismatic, or non-prismatic sections. In the first part, a total of six beams were tested under four-point monotonic bending. The test matrix was designed to provide a comparison of structural behavior between prismatic solid and hollow section beams, prismatic solid and non-prismatic solid section beams, and prismatic hollow and non-prismatic hollow section beams. The intensity of shear was maximum in the case of prismatic section beams. The inclusion of a tapered section lowered the demand for shear. In the second part, Nonlinear Finite Element Modeling was performed by using ATENA. The adopted modeling strategy resulted in close agreement with experimental crack patterns at ultimate failure. However, the ultimate failure loads predicted by nonlinear modeling were generally higher than their corresponding experimental results. Whereas in the last part, the developed models were further extended to investigate the effect of the strength of concrete and ratio of longitudinal steel bars on the ultimate load-carrying capacity and cracking behavior of the reinforced concrete beams with solid, hollow, prismatic, or non-prismatic sections. The ultimate loads for each beam predicted by the model were found to be in close agreement with experimental results. Nonlinear modeling was further extended to assess the effects of concrete strength and longitudinal reinforcement ratio on failure patterns and ultimate loads. The parametric study involved beams reinforced with glass fiber-reinforced polymer (GFRP) bars against shear and flexural failure. In terms of ultimate load capacities, diagonal cracking, and flexural cracking, beams strengthened with GFRP bars demonstrated comparable performance to the beams strengthened with steel bars.

Bitumen shows visco-elastic behavior, exhibiting both elastic and viscous properties as predicted by dynamic response and phase angle. Modern asphalt bituminous pavements face issues such as early-stage fatigue cracks, rutting, and permanent deformations due to low-temperature cracking, high-temperature deformation, moisture susceptibility, and overloading. These pavement distresses result in the formation of potholes, alligator cracks, and various deformations, which accelerate the need for rehabilitation and maintenance. To address these concerns, this study focused on utilizing Nitrile Butadiene Rubber derived from surgical gloves as an additive in conventional asphalt pavements to assess its effect on stiffness. Nitrile Butadiene Rubber was added in intervals of 2%, 4%, 6%, and 8% to conventional bituminous pavement. The rheological properties, marshall properties, dynamic modulus, and phase angle were evaluated for varying percentages of Nitrile Butadiene Rubber at different temperature, and frequency. The dynamic response was determined using a simple performance tester at four different temperatures (4.4 °C, 21.1 °C, 37.8 °C, and 54.4 °C) and six different frequencies (0.1, 0.5, 1, 5, 10, and 25 Hz). Response surface methodology was employed to establish a relationship between input and output variables and to optimize the amount of Nitrile Butadiene Rubber in the mix based on dynamic modulus and phase angle. The study concluded that adding up to 6% of Nitrile Butadiene Rubber improved Marshall stability, while higher percentages led to reduced stability. A similar trend was observed in the dynamic modulus, which peaked with the addition of 6% Nitrile Butadiene Rubber, regardless of frequency and temperature. The response surface methodology model indicated that coupling the percentage of Nitrile Butadiene Rubber with frequency increased the dynamic modulus at a constant temperature, with the highest value occurring at 4.4 °C. However, the dynamic modulus decreased as the temperature rose for the same combinations of Nitrile Butadiene Rubber percentages and frequencies. Numerical optimization suggested that a maximum of 5.9% Nitrile Butadiene Rubber should be added to achieve the highest dynamic modulus and lowest phase angle.