University of Engineering and Technology, Lahore

A hip joint fracture includes a break in the thigh (femur) or coxa bone near the pelvis. During fracture healing, stability and weight bearing by the affected limb are key indicators to measure patients’ improvement. Conventionally, the rehabilitation effectiveness is monitored through clinical examinations, patients’ feedback, and few studies also reported instrumented gait evaluations. A gap remains there to numerically quantify the recovery in patients’ stability and weight bearing in response to rehabilitation therapies. This study introduces Nyquist and Bode (N&B) methods to analyse the instrumented gait signals further and evaluate gait stability in hip fracture patients during weight loading and unloading transitions. The centre of pressure (CoP) data was recorded using force plates for conditions: coxa hip fracture (HC), femur hip fracture (HF), and normal hip joint (NH). The time rate of CoP signals illustrated two major impulses during the loading and unloading phases which were modelled in time and frequency domains. The frequency models were further analysed by applying N&B methods and stability margins were computed for both impaired and healthy conditions. Results illustrated a significant decrease (Kruskal–Wallis’s test, p < 0.001) in the intralimb walking stability of both fracture conditions. Further, Spearman’s correlation between CoP velocities of fractured and intact limbs illustrated significant interlimb dependencies to maintain walking stability (p < 0.001) during weight loading and unloading transitions. Overall, the HF impairment illustrated the least intralimb walking stability and relatively greater interlimb dependencies. Clinically, these methods and findings are important to measure the recovery in patients undergoing rehabilitation after a hip joint or other lower limb impairments.

Road toll tax contributes significantly in the economic development of any nation. In developing countries, the toll tax collection is carried out either manually or electronically. However, both approaches suffer from various challenges, including prolonged waiting times, lack of transparency, high operational costs, and concerns regarding data security and privacy. This research aims to address these challenges using a blockchain-based system. The proposed system employs advanced image processing techniques, specifically “You Only Look Once” version 5 (YOLOv5), to accurately capture and store vehicles’ registration numbers in a local server situated at toll plazas. Subsequently, the vehicle identification, along with the driver’s credentials, is transmitted to an application server, where an Ethereum smart contract verifies the information and automatically deducts the toll charges from the driver’s account. The results from this study indicate that the proposed system effectively reduces vehicle waiting time and facilitates uninterrupted vehicular movement. Additionally, the system ensures transaction transparency, safeguards the security and privacy of vehicle details, facilitates non-stop payments, rendering unnecessary cash payments or radio-frequency identification scanning at toll booths, and incorporates a decentralized architectural framework to enhance security and mitigate potential system failures.

We consider recently constructed black holes in the Einstein SU(N)-non-linear sigma model and study the Joule–Thomson expansion and observable characteristics. We calculate Joule–Thomson coefficient, inversion curves and isenthalpic curves to investigate the heating and cooling phases in $$T-P$$ T - P plane of the considered model. Our findings reveal distinct behavior of these black holes different from those reported in existing studies. Notably, inversion curves vanish in the heating regions, resulting in the black holes consistently remaining in the cooling phase. Additionally, we investigate the impact of the flavor number N on the Joule–Thomson expansion of these black holes. We observe that employing higher values of enthalpy and flavor number N extends the ranges of isenthalpic and inversion curves but the black holes remain in cooling phase. We also study the shadow and visual characteristics of the these black hole focusing on its illumination by two theoretical models of static accretion. We analyze that higher flavor numbers have high peaks of observed intensities and it shifts to smaller impact parameter which leads to smaller images.

This review presents an overview of the antitumor properties of various platinum(II) complexes of dithiocarbamates. It has been noticed that in several cases the activity is greater than cisplatin, while their toxicity level is low. The monofunctional platinum(II)-dithiocarbamate complexes comprising a labile chloride ligand possess the most effective cytotoxic behavior among the complexes discussed here. The bis(dithiocarbamato) complexes on the other hand show poor anti-proliferative potential. The complexes manifest their antitumor activity through DNA interaction that takes place via covalent bonding, intercalation or electrostatic interaction. The study of apoptotic activity in some cases suggests that these complexes trigger apoptosis, which causes the cell death. The induction of apoptosis is correlated with the generation of reactive oxygen species, the cell cycle arrest and the inhibition of NF-kB activity. The protective effects of dithiocarbamates against the platinum-induced toxicity have been explained. Dithiocarbamates were found to control the side effects of cisplatin and the anticancer activity of cisplatin was significantly improved in the presence of a dithiocarbamate. The study highlights that platinum(II) complexes of dithiocarbamates may be regarded as promising anticancer agents because of their effective cytotoxic properties and their potential to overcome cisplatin resistance.

Enhancing the nanosized‐electrolyte's characteristics in Lithium‐driven micro‐batteries (LIMBs) is indispensable to improve the overall efficiency, security, and lifespan of these energy devices, designing nano‐sized electrolyte with a wide electrochemical stability window while keeping them compatible with electrode materials is one of the improvement goals. Battery technologies must go through this optimization process in order to be used practically. A sensing mechanism to keep an eye on the health of Li‐ion energy devices through the magnetization. Magnetic micro‐fluidic patterns that change could be a sign of battery deterioration or other problems with performance. Li‐ion battery health is one application of magnetic sensing that you can do with magnetic sensing. Battery health variations and other performance problems can be found using magnetic mass transport patterns. Present study examines the effects of magnetic field on Eyring–Powel mass transport in nano‐porous channels over a stretching sheet. The principal equations exhibiting the phenomenon are transformed into non‐linear differential equation by second‐order approximation by using a similarity transformation. Furthermore, a semi‐analytic technique named optimal homotopy asymptotic method (OHAM) is used to solve the transformed Eyring–Powell model. The numerical results demonstrated the impact of variations in velocity, skin‐friction coefficient and Sherwood number for the proposed scheme.

The daily discharge of textile dye wastewater has led to widespread water contamination on a global scale. The objective of this study was to associate the abilities of graphene oxide, perovskite, biochar, and chitosan with nano-zeolites to create a hybrid that can be employed to treat wastewater contaminants. Zeolite-based nanohybrid composites are innovative adsorbents that are both cost-effective and highly effective towards contaminants removal. The co-precipitation approach was employed to synthesize nanozeolite which was then incorporated with GO into the nanocomposites including zeolite/perovskite/graphene oxide, zeolite/biochar/graphene oxide and zeolite/chitosan/graphene oxide (Z/FZTO/GO, Z/BCH/GO and Z/CS/GO), followed by the adsorptive removal of Basic Violet 16 dye. The adsorption capacity was calculated with varying conditions of pH (2–11), adsorbent dose (0.05–0.5 g/50 mL), BV 16 dye concentration (10–150 mg/L), time of contact between adsorbent and BV 16 dye (5–90 min) and temperature (35–65 °C). It was concluded that adsorption capacity increased with an increase in pH, time, and initial BV 16 dye concentration. However, the adsorption capacity decreases with increase in zeolite composite dose and temperature. The BV 16 dye adsorption efficiencies were found in the following order Z/FZTO/GO˃Z/CS/GO˃Z/BCH/GO. Thermodynamic studies indicated spontaneous adsorption, and exothermic reactions. The outcomes demonstrated that adsorption was accompanied by pseudo second⁻order kinetics, and Freundlich adsorption isotherms as evidenced by the high correlation coefficients and adsorption capacities near the experimental values. The adsorption potential for BV 16 dye removal was significantly affected by various concentrations of electrolytes, heavy metal ions, and surfactants due to competition for limited binding sites. 0.5 N HCl concentration was identified as the most effective agent for the desorption. These approaches are economical, ecofriendly, and easy to manufacture. Graphical Abstract

Through experimental and theoretical studies, this research explores the materials, structural, and environmental aspects of multi‐grade concrete (MGC), a potentially sustainable structural concrete. The experimental part investigates the compressive, split cylinder, flexural, and shear strengths of MGC, essential parameters for the design of structural members composed of MGC. It also provides the relationships between various strengths. The compressive behavior is correlated with the cracking pattern and the confinement effect caused by the end platens. The theoretical study involves determining the carbon emissions (CEs) and modifying ASTM/ACI expressions for the flexural tensile strength (FTS) and shear capacity applicable to MGC. Three uni‐grade concretes (UGCs) with distinct materials, properties, and grades: grade 17 (G17), grade 25 (G25), and grade 30 (G30), were poured in layers of varied thicknesses to make two variants of MGC. Experimental investigations showed that the higher‐strength concrete (HSC) confined the lower‐strength concrete (LSC) part thus increasing the compressive strength. Replacing 50% of LSC with HSC led to an increase in compressive and shear strengths by 21% and 40%, respectively. The shear strength values of reinforced MGC beams observed experimentally are aligned with those obtained through the modified expressions developed by the authors. A trade‐off analysis among the strengths, CEs, and costs of UGC and MGC can aid in selecting MGC customized to specific requirements, thereby contributing to the development of sustainable structural concrete.

Existing literature has overlooked investigating the factors that foster attachment in counterfeit consumers. This research developed and validated a model that considers social, personal, functional, and economic factors influencing brand attachment and purchase intention. The moderating effect of hedonic benefits was researched under well-established theories—the theory of planned behavior (TPB) and attachment theory. A multi-wave method using purposive sampling was applied to collect 529 responses from consumers about counterfeiting. This data was then analyzed through structural equation modeling (SEM) in AMOS 24.0. The results of the model fit indices of measurement (χ²/df = 2.1927; RMSEA = 0.048) and structural model (χ²/df = 2.552; RMSEA = 0.054) are indicated as satisfactory. The study found that most factors—social, personal, functional, and economic—have a significant positive association with brand attachment to counterfeit products. However, we found that transactional value, conformity, and novelty have an insignificant relationship with brand attachment. The findings also confirmed that brand attachment has a positive relationship with purchase intentions for luxury counterfeit products. Further, hedonic benefits positively moderate the relationship between brand attachment and the willingness to buy luxury counterfeit goods. This research contributes to the body of knowledge on brand attachment, psychology, consumer behavior, TPB, and attachment theory. The study aids luxury and apparel businesses and acknowledges limitations by offering research directions.

Flow-induced vibrations (FIV) were considered as unwanted vibrations analogous to noise. However, in a recent trend, the energy of these vibrations can be harvested and converted to electrical power. In this study, the potential of FIV as a source of renewable energy is highlighted through experimental and numerical analyses. The experimental study was conducted on an elastically mounted circular cylinder using helical and leaf springs in the wind tunnel. The Reynolds number (Re) varied between 2300–16000. The motion of the cylinder was restricted in all directions except the transverse direction. The micro-electromechanical system (MEMS) was mounted on the leaf spring to harvest the mechanical energy. Numerical simulations were also performed with SST k–ω turbulence model to supplement the experiments and were found to be in good agreement with the experimental results. The flow separation and vortex shedding induce aerodynamic forces in the cylinder causing it to vibrate. 2S vortex shedding pattern was observed in all of the cases in this study. The maximum dimensionless amplitude of vibration (A/D) obtained was 0.084 and 0.068 experimentally and numerically, respectively. The results showed that the region of interest is the lock-in region where maximum amplitude of vibration is observed and, therefore, the maximum power output. The piezoelectric voltage and power output were recorded for different reduced velocities (Ur = 1–10) at different resistance values in the circuit. It was observed that as the amplitude of oscillation of the cylinder increases, the voltage and power output of the MEMS increases due to high strain in piezoelectric transducer. The maximum output voltage of 0.6V was observed at Ur = 4.95 for an open circuit, i.e., for a circuit with the resistance value of infinity. As the resistance value reduced, a drop in voltage output was observed. Maximum power of 10.5μW was recorded at Ur = 4.95 for a circuit resistance of 100Ω.

Charcoal rot disease, caused by Macrophomina phaseolina, poses a major threat to tomatoes. Encapsulating biocontrol bacteria in alginate offers a novel and effective solution with advantages in viability, shelf life, and controlled release. The current research was conducted to develop alginate beads of biocontrol bacteria and to evaluate their inhibitory capacity against M. phaseolina in combination with essential metal iron (Fe) using in vitro and in planta tests. In vitro, Pseudomonas chlororaphis subsp. chlororaphis (PCC-01) exhibited 71% antifungal activity. It also had plant growth-promoting traits of indole-3-acetic acid, hydrogen cyanide, phosphate, and mineral solubilization. FTIR and UV–vis spectra specified good affinity of PCC-01 and alginate, as revealed by changes in the intensity of peaks, particularly at the protein regions (1600–1200 cm⁻¹). The bacterial-loaded alginate beads had excellent properties of encapsulation efficiency (96.20%), swelling ratio (66.47%), moisture content (92.50%), size [1.31 mm (wet) and 0.70 mm (dry)], and ensured slow release of entrapped bacteria up to 120 days. PCA-based biplot, hierarchical clustering, and heat map analysis for in vitro bioassays verified that the antifungal activity of PCC-01-alginate beads improved in nutrient medium supplemented with Fe (91–98%), followed by Mn (74–86%) and Zn (60–76%) via dual culture and modified dual culture methods. In planta, multivariate statistical analyses based on 18 traits related to growth parameters, yield, and biochemical indices of the tomato plants confirmed the greater disease-managing potential of Fe-amended alginate beads of PCC-01 through maximal economic benefits. Therefore, different formulations of PCC-01 and Fe could be prepared and commercialized as a single application product for sustainable and profitable tomato crop production.

An integrated approach combining finite element modelling, machine learning, and experimental verification was proposed for developing process maps to optimize the LPBF process for AlSi10Mg alloy. A transient thermal simulation model was validated to predict single-layer melt pool size by modifying laser beam power, scan rate, feedstock bed depth, and preheating of feedstock. Using the verified model, a pool of data was generated to develop a backpropagation neural network to predict melt pool dimensional ratios indicating printing defects. It was found that beyond process parameters, powder bed thickness and preheating temperature impacted defect formation. Excessively high preheating temperatures increased the lack of fusion defects by transforming melt pool dynamics from conduction to keyhole mode. Optimal combinations were identified as 30.0 μm thickness with 90.0 and 120.0 °C preheating and 50.0 μm thickness with 120.0 °C preheating. By reducing iterative physical testing, the integrated process mapping approach enables accelerated qualification of LPBF parameters for AlSi10Mg alloy.

Titanium alloy Ti-6Al-4 V holds a prominent status within the aerospace sector owing to its remarkable strength-to-weight ratio. However, its low thermal conductivity and high tensile strength present machining obstacles, resulting in elevated tool temperatures and mechanical stress. In aircraft manufacturing, drilling is essential, yet using solid carbide drills conventionally leads to considerable tool wear. Prior investigations aimed at enhancing tool longevity have explored diverse cutting methodologies, spanning from flood cooling to minimum quantity lubrication (MQL). Despite these efforts, persistent challenges endure. Therefore, this study introduces an innovative approach, leveraging titanium aluminum nitride (TiAlN)-coated indexable centerless inserts to bore holes in Ti-6Al-4 V under three distinct cutting conditions: dry, flood cooling, and MQL. These conditions are scrutinized across varied feed rates (60 mm/min, 100 mm/min, and 120 mm/min) with a fixed spindle speed of 1200 rpm. The study’s primary focus is on key output parameters, including surface roughness (SR), tool life, and cutting temperature. From the parametric and surface topographic analysis, the findings reveal that under the flood cutting approach with a 60-mm/min feed rate, the indexable inserts excelled when drilling Ti-6Al-4 V. This combination delivered a better surface quality (Ra = 1.66 µm), extended tool life (27,814.27 mm³ material removed and 18 holes drilled), and lower cutting temperature (881°F). Additionally, scanning electron microscopy (SEM) analysis corroborates that most common types of wear observed were abrasion, delamination, cracking, and edge fracture.

Antibiotics, as emerging pollutants, cause a range of environmental issues due to their toxic and mutagenic effects, making their removal challenging. The objective of this study is to create a novel and promising photocatalyst. Cu-TiO2-Aluminosilicate nanocomposite was successfully synthesized using a solvothermal process. A range of analytical techniques were employed to characterize Cu-TiO2-Aluminosilicate nanocomposite, like SEM, XRD, UV-Vis, FTIR, BET, and TGA. The Taguchi method of experimental design (L16) was employed to optimize the photocatalysis process and determine the significance of investigated operating variables such as pH (2–8), photocatalyst dose (0.1–0.4 g/L), initial concentration (10–25 mg/L) and temperature (298–328 K). The experimental findings demonstrated that Cu-TiO2-Aluminosilicate nanocomposite exhibited a remarkable photocatalytic activity. The maximal photocatalytic degradation achieved was 89.95% with optimum conditions of pH 4, dosage 0.1 g/L, initial concentration 15 mg/L, and temperature 318 K. The significance of the model was validated using analysis of variance (p < 0.05). Among the factors studied, pH, temperature and initial concentration were found the most influential. Additionally, the first-order kinetic model (R² = 0.994) demonstrated the strongest correlation with the experimental data indicated by the kinetic study results. The results of reusability experiments showed that prepared nanocomposite maintains its reusability from 89.95 to 68% after three cycles of application. The toxicity assessment of the treated solutions revealed higher cell viability in Scenedesmus and Chlorella sp. Therefore, based on the comprehensive findings, it can be concluded that Cu-TiO2-Aluminosilicate nanocomposite is a novel photocatalyst for effective removal of antibiotics.

In this paper, we investigate the heat transfer characteristics of magnetohydrodynamics (MHD) with Williamson hybrid nanofluid (HNF), considering the influence of bioconvection as well as a chemical reaction on a stretched surface. We observe no investigation on bioconvection Williamson HNFs flow in the literature, which is a novel contribution to the literature. The recent study seeks to enhance the heat transfer rate by investigating inclined magnetic field, along with the interplay of bioconvection and chemical reactions. The employed hybrid nanoparticles consist of titanium dioxide (TiO 2 ) and copper (Cu) suspended in base fluid (water). The governing partial differential equations (PDEs) are changed into nonlinear ordinary differential equations (ODEs) through an appropriate similarity transformation. These ODEs are subsequently analyzed employing the MATLAB bvp4c approach numerically. This study presents comprehensive insights into the behavior of distinct parameters, conveyed through phase portraits of temperature, velocity, nanoparticle concentration, as well as microorganism density profiles. The results showed that the momentum profile was inversely affected by increasing Williamson parameter, magnetic force, and inclination angle, while the temperature was boosted with advanced magnetic field, radiation parameter as well as Brownian motion parameter values.

This work is designed by coupling fly ash (FA) with dune sand (DS) for high-strength geopolymer activated in an alkaline environment under pressure-applied casting. Initially, the proportion of FA and DS is optimized with the least activator dosage to obtain higher than the compressive strength of 50 MPa. A uniaxial pressure is applied on a semi-dry mixture containing the least activators and immediately demolded, involving rapid production for the industrialization purpose of the paving blocks. The experimental study revealed that the FA-DS proportion of 1:1, with a liquid-to-solid ratio of 0.16, achieved a compressive strength of 54.4 MPa. Consequently, the coupling of DS provides an occupying effect and reduces the required activator quantity. The strength gain mechanism is discussed at the molecular level by analyzing Fourier-transform infrared. Finally, the technical performance of the strength and the density is evaluated on the real size 203 × 101 × 80 mm prism and compared with the commercially available conventional concrete blocks. Besides, the enviro-economic performance in terms of CO2 emissions and the cost are analysed as well. It is concluded that the developed block is a more environmentally sustainable and economically viable alternative to conventional concrete blocks.

Hydrogels are excellent options for strain sensors as they can stretch, endure mechanical stress, and possess multifunctional qualities. Resistive sensors are particularly promising among the diverse hydrogel strain sensors available. This is attributed to their dedicated focus on improving the indicators of strain‐sensing performance, simplicity of equipment, straightforward sensing mechanisms, and easy design of conductive hydrogels. Various approaches have been explored to create conductive hydrogels, including conductive fillers, conductive polymers, and ionic approaches. This review thoroughly explores diverse approaches for developing advanced conductive hydrogels for resistive‐type hydrogel strain sensors. The focus is particularly on their electrical conductivity and sensing performance indicators, distinguishing them as valuable resources for researchers in the field of strain sensors. First, diverse approaches for achieving electrical conductivity in hydrogels are introduced. The subsequent discussion delves into the multifunctionality of these conductivity approaches for hydrogels. In addition, it also scrutinizes recent applications of strain sensors. Overall, it offers comprehensive updates on the performance indicators such as sensitivity, working range and linearity, response and recovery times, and hysteresis of strain sensors using diverse approaches to conductive hydrogels. This study also includes the latest trends and future perspectives of resistive‐type hydrogel strain sensors.

This research addresses the challenges of emission reduction and fuel consumption in engines by investigating modifications in fuel properties using graphene oxide (GO) nanoparticles and diethyl ether as oxygenated additives. Characterization tests were conducted to determine the size, energy, and content of graphene and oxygen molecules in synthesized GO nanoparticles. Pongamia Pinnata Oil Methyl Ester (POME) was prepared through a transesterification process and blended with diesel to obtain a B20 blend. This POME (B20) was further mixed with GO nanoparticles at 40, 80, and 100 mg L-1 concentrations and supplemented with 3 vol% of diethyl ether. The blending process involved stirring, bath sonication, and probe sonication. A Common Rail Direct Injection diesel engine was employed with a toroidal combustion chamber and a 7-hole fuel injector nozzle. The engine maintained a steady speed of 1800 rpm, an injection timing set at 23ºbTDC, and a fixed compression ratio of 18.5 while operating under five different loads. At maximum loading conditions, the addition of 100 ppm GO nanoparticles and 5 vol% of Diethyl ether resulted in a 19.7% enhancement in Brake Thermal Efficiency (BTE) and a 10.71% reduction in Brake Specific Fuel Consumption. Furthermore, there was a significant reduction observed in CO, HC, and smoke emissions by 47.9%, 70.3%, and 23.8%, respectively. The addition of these fuel additives increased combustion characteristics such as Heat Release Rate, Cumulative Heat Release Rate, peak pressure, and in-cylinder pressure, while concurrently decreasing the Ignition Delay period and Exhaust Gas Temperature.