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Abstract This study was designed to develop water-saving irrigation strategy for citrus cultivation at Xinping County, Yunnan, China. This county has a mountainous landscape with resources of natural rivers. Based on the local standard water quota (DB53/T168-2019) of Yunnan Province, Xinping County falls into the dry-hot valley VI -2 zone. We developed a Smart Sprinklers irrigation system to meet the actual irrigation requirements of citrus plants with multiple benefits starting from economic to social and environmental protection. We considered the specific situation of the project area, and then design an irrigation system for citrus orchard. Hydraulic calculations determined the suitable materials and sizes for pipes, valves, and irrigation equipment, based on the area’s water demand favoring micro-sprinkler irrigation. Following technical standards, we selected appropriate equipment for designing the pipe network, including the layout, positioning, and installation of the pumping station, moisture meters, weather station, and pest monitoring system. Further research could investigate the adoption of renewable energy to enhance system sustainability and examine the transferability of these systems to different crops and similar geographic regions. It is concluded that this technology and design is very useful for the cultivation of citrus plants in hilly areas.

Abstract With the expansion of the manufacturing sector, it has become crucial to incorporate sustainable production methods in order to remain competitive in the market. This study focuses on addressing the needs of the manufacturing industry by conducting a sustainability analysis of electric discharge machining for SS310 alloy. The analysis explores the impact of various electrode materials, for instance, copper and brass, as well as different machining variables, including discharge current (I = 4–12 A), spark gap (SG = 6–12 mu), pulse duration (Pon = 15–45 μs), and duty cycle (DC = 75–85%) using Taguchi method. The objective is to optimize the machining performance measures, which includes material removal rate (MRR), surface roughness (Ra), electrode wear (EW), and energy consumption (EC). In addition, the economic analysis of the machining process takes into account factors such as energy cost, dielectric consumption cost, EW cost, labor cost, and machine depreciation cost for both types of electrodes. Furthermore, the study investigates the carbon emissions resulting from EC, dielectric consumption, and EW to assess the environmental impact of the machining process. Multi-criteria decision-making approach is employed to assess the sustainability of the machining process by taking into account several performance, cost and environmental factors simultaneously. From empirical analysis, it has been observed that the copper electrode outperformed the brass electrode in terms of MRR (2.67 mm3/min), Ra (3.36 µm), EW (0.272 g), and EC (145.08 kJ) due to its superior electrical and thermal characteristics. In the cost analysis, copper offered lower costs for EC (2.02 PKR) attributed to its higher electrical conductivity while higher costs in terms of EW (5.5 PKR) and dielectric consumption (5.2 PKR) than brass. However, the analysis of labor and machine depreciation costs revealed that the application of copper electrode results in lower costs (80.1 and 99.3 PKR, respectively) than the brass electrode primarily due to its shorter machining time. The analysis of the environmental impact showed that the utilization of a copper electrode leads to reduced carbon emissions of 9.8 g CO2 due to its lower EC during the machining process. However, the copper electrode results in higher emissions from EW (5.07 g CO2) and dielectric consumption (54.58 g CO2) compared to the brass electrode. Based on the multi-criteria decision-making using the composite desirability function approach, it is evident that the copper electrode exhibits superior performance in terms of MRR, Ra, and total machining cost. Conversely, the brass electrode demonstrates better performance in terms of overall carbon emissions.

Abstract This study provides thorough computational and experimental assessments of four types of novel synthesized thiosemicarbazones. The compounds were effectively synthesized using a condensation reaction between thiosemicarbazide and fluorenone, producing a remarkable range of 70–88%. Additional chemical structures were examined utilizing spectroscopic methods, including Fourier-transform infrared spectroscopy (FTIR), NMR spectroscopy, and ultraviolet-visible spectroscopy. The computational analyses utilized DFT using the M06/6-311G (d, p) technique. The electrical characteristics, including the stability of orbitals via energy exchange between a donor and acceptor, can be evaluated by natural bond orbital (NBO) analysis. The nonlinear optical (NLO) properties were analyzed to detect any prohibited energy gaps. FTIR and UV-visible data were computed using the identical M06/6–311G (d, p) level of theory. The NBO test has confirmed the occurrence of charge separation due to the efficient transfer of electrons from the donor to the acceptor unit over the π bridge. The molecular chemical softness and hardness are dependable indications of a molecule’s chemical stability. A significant magnitude of the absolute value of polarizability and hyper-polarizability indicates considerable dispersion of electric charge. The outcomes derived from Density Functional Theory (DFT) generally align well with experimental findings.

Engineering tool designs through geometrical changes and surface texturing is gaining attention to enhance the tribological behaviour in metal processing industries. However, understanding the interactions of these designs with machining parameter selection considered time-taking process through various trial and error experiments. In this study, three-step novel modelling approach for optimal prediction of dry turning parameters is proposed. Firstly, an economical design of experiment approach is opted to evaluate two inserts with distinct designs with machining parameters such as cutting speed (VCS), feed rate (FR), and depth of cut (DOC). Secondly, the open-source supervised machine learning architecture search as carried out to map process characteristics such as surface evolution, tool wear, and chip morphology (width and thickness). Lastly, an evolutionary optimization method is applied to democratize multi-objective process characteristics’ learnings to facilitate machinists and users within manufacturing community. An artificial neural network (ANN) based modelling has been performed to find the correlation between the predicted and the experimental values. It has been found that, an ANN based modelling gave the better results by strongly giving the R2 nearly equal to unity in training, and equal to unit for testing and validation for the response measures. According to non-dominated sorting genetic algorithm (NSGA-II), the results of turning operation of AISI D2 steel in terms of tool life (TLIFE), surface asperities (Ra, Rt, Rz), chip width (CW) and chip thickness (CTH) have been enhanced when compared to the experimental results to the NSGA-II suggested optimal settings. It has been found that the TLIFE, Ra, Rt, Rz, CW and CTH, improved by 354.05 %, 93.87 %, 81.35 %, 88.01 %, 127.01 %, and 124.71 %, respectively, when parametric combinations (VCS = 100 m/min, FR = 0.2 mm/rev, DOC = 0.5 mm, and INType = Xcel) are used.

Introduction: This review is specifically aimed at providing deeper understanding of the ground state Hanle effect through novel methods of atomic vapor interaction with resonant light. Electromagnetically Induced Transparency (EIT) and absorption (EIA) are the primary phenomena in this context. EIT is a process in which destructive interference at absorption frequencies within a medium is caused by a control laser and makes the medium clear to the probe laser light. It should be noted that this transparency is crucial for turning on/off the light pulses, slowing down or stopping in several cases, thus enhancing the effectiveness of atomic magnetometers. However, constructive interference that occurs in EIA raises the density of the medium, which is advantageous for achieveing precise measurements. Thus, studying Hanle effect contribute in development of commercially valuable applications and the improvement of atomic clocks. Objective: The objective of this study is to review the fundamental principles of the Hanle effect, EIT, EIA, and coating methods for alkali atoms. These principles and techniques are essential for improving the sensitivity and functionality of atomic magnetometers and other quantum devices. By understanding and applying these phenomena, significant progress has been made in the development of high-precision measurement tools and quantum technologies. Results: Advancements in atomic magnetometer sensitivity represent a rapidly growing area of interest that has made the significant progress in the development of quantum devices. This review consolidates the state of art research and development of fundamental principles and practical applications of the Hanle effect, EIT, EIA, and coating methods for alkali atoms. It highlights how advancements in EIT and EIA have contributed to the sensitivity improvements of atomic magnetometers, and show the importance of coating methods for maintaining system integrity and performance. These developments are essential in revolutioning of modern quantum technologies and precision measurement devices.

This research investigates the hard part turning of DC53 tool steel, which is engineered for better mechanical properties compared to AISI D2 tool steel, using Xcel cubic boron nitride. The machining input parameters such as workpiece hardness (different heat treatments), cutting speed, feed rate, and depth of cut are used to thoroughly evaluate process science across conflicting machinability attributes such as cutting tool life, machined workpiece surface roughness, volume of material removed, machine tool power consumption, and tool-workpiece zone temperature. A full factorial design of experiments with two levels, resulting in 16 experiments, is performed with statistical parametric significance analysis to better control process variability. Multiple artificial neural network (ANN) architectures are generated to accurately model the non-linearity of the process for better prediction of key characteristics. The optimized architectures are used as prediction models to a non-sorting genetic algorithm (NSGA-II) to determine the optimal compromise among all conflicting responses. The significance analysis highlighted that heat treatment is the most influential variable on machinability, with a significance of 74.63% on tool life, 59.03% on roughness, 66.45% on material removed, 38.03% on power consumption, and 29.60% on interaction-zone temperature. The confidence of all ANN architectures is achieved above 0.97 R2 to accurately incorporate parametric relations with physical mechanisms. The compromise against conflicting machinability attributes identified by NSGA-II optimization results in a 92.05% increase in tool life, a 91.83% increase in volume removed, a 33.33% decrease in roughness, a 26.73% decline in power consumption, and a 9.61% reduction in machining temperature. The process variability is thoroughly analyzed using statistical and physical analyses and computational intelligence, which will guide machinists in better decision-making.

Abstract The non-conventional manufacturing technologies are notorious when it comes to productivity and processing time in production-related industries. However, the aerospace and other high-end sectors enjoy another quality matrix of these processes and compromise on the processing time. For instance, the machinability of hard-to-cut materials such as Ti6Al4V aerospace alloy for micro-impressions is challenging and commonly carried out through non-conventional processes. Among these processes, the electric discharge machining (EDM) is famous for machining Ti6Al4V. In the current study, the EDM process is enhanced through modified dielectrics such as kerosene with non-ionic liquids (span 20, 60, and 80) and cryogenically treated tool electrodes (aluminum and graphite), and is compared to the conventional kerosene-based process. A three-phase experimental campaign is deployed to explore parametric effects including modified dielectric conditions (non-ionic liquid type and concentration), tool material, and machine parameter pulse ON:OFF time. A total of 60 experiments (54 modified dielectrics and 6 as baseline) were performed to explore process physics. The statistical analyses show that the unmodified process (kerosene dielectric-based) results in the least favorable results 0.58 mm3/min against cryo-graphite and 1.2 mm3/min against cryo-aluminum electrodes. However, the modified dielectrics outperform and improve process dynamics by altering dielectric conditions through hydrophilic-lipophilic balance. Surface morphological analysis shows significantly shallow craters on the machined surface showing evidence of effective flushing through a modified dielectric (S-20) as compared to a kerosene-based dielectric. A thorough microscopical, statistical, and scanning electron-based analysis is carried out to explain the process and correlate significant improvements.

Hybrid aluminium matrix composites (HAMCs) are highly valued in manufacturing sectors but are difficult to machine conventionally due to reinforcements' inherent hardness and abrasiveness. This research finds high-speed wire electric discharge machining (WEDM) to be a potent solution for machining stir-squeeze-casted HAMC (AA2024 with ceramic nanoparticles: Al2O3, SiC, Si3N4, BN) and creating complex profiles with superior erosion characteristics. The erosion performance has been assessed in terms of material removal rate (MRR) for different profiles (plane, angular, and curve), and wire wear ratio (WWR) by employing machining variables, i.e., pulse voltage (PV), pulse current (PI), wire feed rate (WFR), pulse (P), and drum speed (DS). Results revealed that MRR_curve has highest MRR (37.84 mm3/min), followed by MRR_angular (36.07 mm3/min) and MRR_plane (34.40 mm3/min). The lowest WWR (0.0094%) was achieved at lower magnitudes of machining variables. The microscopic observations unveil shallow craters, minute-sized melt redeposits, and micro-pores on machined surface under the conditions of PV = 90 V, PI = 2 A, WFR = 13 m/min, P = 20 mu, and DS = 40 Hz. Optimization using non-dominated-sorting-genetic algorithm (NSGA-II) resulted in significant enhancements of 75.37, 73.90, and 76.01% in MRR_plane, MRR_angular, and MRR_curve, respectively, and a depreciation of 16.50% in WWR.

As a therapeutic approach for cancer, hyperthermia involves selectively increasing the temperature of affected tissues while preserving adjacent healthy tissues. This study explores the efficacy of pristine and coated silver, copper, and gold nanostructures such as nanorods, nanospheres, and nanoellipsoids for hyperthermia. This study performed finite element analysis to assess the relative performance of pristine nanostructures and those covered with different coating thicknesses. The metallic nanostructures were enclosed within the spherical zone of malignant tissue of 500 nm size, and the ambient temperature of these nanostructures was increased to 42–46 °C. Thermal equilibrium was reached after 0.1 μs of heating in the treatment region. Compared to other geometries, the nanorods quickly attained the required temperature in the treatment region. The nanorods with 1 nm coating thickness showed a fast heating response compared to 2 and 3 nm coatings. Silver, gold, and copper nanorods reached a temperature of 44.2, 43.6, and 43.5 °C, respectively, after 0.1 μs of heating. Gold-coated silver nanorods were discovered to be most efficient at achieving the highest temperature of 44.2 °C.

Abstract In this study nutritionally enriched apple and date jam was developed by replacing sugar with natural and artificial sweeteners stevia and sorbitol. Three different types of samples were prepared. Sample T1 was prepared by using stevia as a sweetener agent. Sample T2 was prepared by using sorbitol as a sweetener agent. Sample T3 was prepared by using a mixture of stevia and sorbitol as sweetener agents. Standard apple jam was used as a control sample labeled as T4 and was used for comparison analysis. The developed product was analyzed by physiochemical analysis and sensory evaluation. Microbial analysis was done to study the shelf life study of the developed product. The study showed that stevia and sorbitol could be used for jam preparation. Sample T3 also showed intermediate values of acidity and pH as 4.14 and 1.90, respectively, moreover, total soluble solids (TSS) was observed as 65.16 °Brix, T3 also showed an intermediate level of energy values. Sample T3 having sorbitol and stevia sweetener agents had the highest rate of overall acceptability. Storage studies of all samples show that with the passage of time all sensory characteristics of all treatments decreased.

Tool steels such as AISI D2 are famous in the manufacturing industry because of their engineering applications. The precise interplay of improved hardness and toughness makes the machining of complex geometries challenging through conventional machining options. Therefore, non-conventional processes such as wire electric discharge machining (WEDM) are preferred because of their simultaneous machining and surface modification actions. To investigate the complex process parameters and their sensitivity, material removal rate (MRR) and cutting surface roughness (SR) are the corresponding performance measure characteristics for WEDM machining on AISI D2 tool steel. The L18 mixed-level Taguchi technique has been used for obtaining combinations of experiments on two levels of thickness and three levels of other remaining factors (21 × 33). Analysis of variance (ANOVA) and signal-to-noise ratio have been applied to measure the magnitude of effects on each control factor, to investigate the optimum levels of input process parameters on machining characteristics, and to identify their significance. ANOVA analysis revealed that, for both responses, all main effect variables are highly significant, with p-values equal to zero. Moreover, the coefficient of determination (R2) value in the ANOVA findings for both responses is above 97%, indicating the high reliability of the model. In addition, the composite desirability (dG) is considered to maximize MRR and minimize the SR during WEDM of D2; the better combination of optimum levels of machining parameters (T = 25.4 mm, Pon = 4 µs, SV = 95 V, and WT = 5 kg-f) has a dG of 0.5614.

Background & Aims: The collimator angle significantly impacts radiation leakage between the multi-leaf collimator (MLCs) leaves. This study aims to examine dose-volume evaluation in planning target volume (PTV) and organs at risk (OARs) for Head & Neck patients undergoing volumetric-modulated arc therapy (VMAT) with 2.5 arcs and varying collimator angles. Materials & Methods: In this experimental study, five patients with nasopharyngeal cancer were selected for treatment with the VMAT method. CT images were prepared using a CT simulator and transferred to the treatment planning system. For optimizing VMAT plans, volume and dose constraints were applied to OARs and PTVs by the algorithm. Then, the doses were calculated using the AAA algorithm. Results: Although no significant differences were observed in DVH curves across different collimator angles, other parameters exhibited variations. Notably, in Head & Neck cancer patients, optimal values for dose conformity, homogeneity, MUs, and gradient index were found at collimator angles of 20° and 30°. Additionally, OAR sparing was favorable at these angles. Based on target coverage, homogeneity, and MUs, the collimator angles were optimized for VMAT planning. Conclusion: Our findings offer valuable guidance to clinical medical physicists in making informed decisions regarding collimator angles. The dosimetric analysis underscores the importance of selecting the optimal collimator angle for accurate PTV coverage.

Value stream mapping (VSM) is an initial and critical tool for deploying lean concepts in the manufacturing and service sectors, including hospitals. Therefore, the aim of this research is to analyze the current working environment of a radiology department, identify the wastes in the operations by mapping the current patient flow, and test the best possible improvement plan with the help of discrete event simulation modeling using the Arena platform to develop an optimum future map to mitigate the wastes. Therefore, the current patient flow in the x-ray section of a radiology department was mapped using VSM for two types of patients named routine (RP) and procedure (PP). VSM results highlighted a high waiting time (TWT) of 188 and 3732 min for RP and PP. A total of seven scenarios were developed and analyzed to determine the impact of changes on five key performance indicators. Simulation results of the current scenario showed that there were 567 patients coming out of the system with a lead time of 200 and 926 min for RP and PP. Total waiting time obtained for RP and PP was 177 and 860 min, with a maximum wait time of 31 min/patient and an average of 43 patients in the system (WIP). The simulation results of the seventh scenario provided the best results, with 6% improvement in the number of patients getting out of the system and 75% and 55% decreased lead time for RP and PP. Total waiting time for RP and PP was reduced by 80% and 60%, with WIP falling by 62%. Arena Optimizer showed that by adding a technician and radiologist to the system, the optimum patient waiting time in the queue would be 6 min, and the lead time for RP and PP would be (160) and (884 min), respectively. Based on it, a future VSM was created; it provided a reduction of 72% and 60% in (TWT) for RP and PP, which could improve the number of patients to be entertained by the radiology services without adding any new x-ray machines. The results of the present case provide healthcare planners with a road map to discover the waste in operations since the monetary investment and organizational dedication required drive out non-value activities. Therefore, simulation helps to select the best possible improvement strategy for the system without pausing and making physical changes in busy and complex units of hospitals.

Introduction: Pakistan has the highest burden of Tuberculosis (TB) worldwide and the 5th highest prevalence of multi- drug resistant (MDR) TB worldwide. There is scarce data on the socioeconomic characteristics and factors associated with the patients presenting with drug resistant-TB in Pakistani context. Aims & Objectives: To determine the association of different variables with rifampin resistance (RR) in new and previously treated cases of pulmonary (PTB) and extra-pulmonary TB (EPTB) Place and Duration of Study: It was a cross-sectional study conducted at Gulab Devi Hospital Lahore, a tertiary care trust hospital. Data was collected from Oct 2021 to December 31, 2021. Material & Method: By applying convenient sampling technique, 202 individuals were interviewed, and data was recorded on a self-constructed questionnaire. Data was analyzed using SPSS version 24.0. Frequency tables were generated for sociodemographic variables as well as the site of TB and Chi square test was applied to find association between categorical variables. P value of

Objective: To identify the relationship between injection needle threat as a mode of disciplining children and acquired dental phobia in pediatric patients. Methods: This cross-sectional study was conducted at University College of Dentistry, Lahore, Pakistan between December 2021 and November 2022. The study included individuals under the age of 18 years who were presented during the survey and scheduled for pulpotomy or pulpectomy treatment. The study assessed two primary outcomes: dental anxiety and childhood needle threat. Dental anxiety was evaluated using the Modified Children's Dental Anxiety Scale, while childhood needle threat was measured by observing the child's responses to scenarios involving needles. Results: Of total 200 pediatric patients, the mean age was 12.04 ±2.34 years. Mild dental anxiety level was observed in 56 (28.0%) patients, moderate in 122 (61.0%) patients and severe in 22 (11.0%) patients. Childhood needle threat was observed in 94 (47.0%) patients. Patients with mild dental anxiety were 0.86 times significantly less likely to have needle threat as compared to patients with severe dental anxiety (cOR 0.14, 95% CI 0.04 to 0.48, p-value 0.002). Similarly, patients with moderate dental anxiety were 0.83 times significantly less likely to have needle threat as compared to patients with severe dental anxiety (cOR 0.17, 95% CI 0.05 to 0.55, p-value 0.003). Conclusion: The study revealed that most children exhibited moderate dental anxiety, with a notable incidence of dental phobia. Those with higher anxiety levels felt more threatened by needles, underscoring the need to avoid using needles as a mode of discipline.

Governments and industries are developing aggressive policies to reduce carbon emissions and shift from fossil fuels to renewable energy. On the other hand, industries struggle to reduce energy consumption and depend on production lot sizes to control energy requirements. In this regard, energy-efficient processing through CNC machine tools can potentially influence energy demand and requires energy-aware power consumption strategies for machining processes. For manufacturing a single product, predicting energy demand can be decisive in determining parametric control and other factors. Previously analytical models have been largely used to model machining requirements and energy demand. However, these models largely depend on parameterization and do not facilitate the integration of external sub-systems. Therefore, in this paper, an artificial intelligence-based power reduction strategy is developed and implemented on single material (Inconel 718), four control parameters (cutting speed, feed rate, depth of cut and flow rate) and two sub-systems (minimum quantity lubrication (MQL) and nanofluids-based minimum quantity lubrication (NF-MQL)). The paper employs four machine learning algorithms,’ K-Nearest Neighbor’, ‘Gaussian Regression’, ‘Decision Tree’, and ‘Logistic Regression’, to evaluate their functionality in predicting power consumption (Pc) of CNC machining systems using a real experimental data set. As per evaluation based on five performance metrics (R-square, MSE, RMSE, MAE, and MedAE), ‘Decision Tree’ has achieved the most accurate power consumption predictions. The comparative results highlight ‘Decision Tree’ as the most better predictor with the optimal max_depth of 2 showing Pc MQL R2 of 0.915 and Pc NF-MQL R2 of 0.931.

ABSTRACTThe rapid increase in agricultural waste is rising across the globe and is a big environmental challenge. The utilization of ginger waste as a valuable product is very limited. The up-cycling of ginger waste is an effective approach for valorization. Ginger waste contains many bio-active compounds. These bioactive compounds possess various functional and bio-active properties. The literature has indicated that ginger and its waste is a rich source of shogaol zingerone and gingerols, these bioactive components contribute to pungency and aroma characteristics These compounds have a wide range of antimicrobial, antioxidant, and anti-inflammatory properties. Furthermore, these have a key role in skin health and the digestive system. The current review consolidates the compositional, functional, medicinal, bioactive, and health-endorsing attributes of ginger waste. The use of ginger wastes for the development of various functional and nutraceutical products is also in the limelight of this paper.

Abstract This research aims to fabricate an AlSi10Mg parts using Laser Powder Bed Fusion technique with enhanced structural integrity. The prime novelty of this research work is eliminating the balling and sparring effects, keyhole and cavity formation by attaining effective melt pool formation. Modelling of the Laser Powder Bed Fusion process parameters such as Laser power, scanning speed, layer thickness and hatch spacing is carried out through Complex Proportional Assessment technique to optimize the parts' surface attributes and to overcome the defects based on the output responses such as surface roughness on scanning and building side, hardness and porosity. The laser power of 350 W, layer thickness of 30 µm, scan speed of 1133 mm/s, and hatch spacing of 0.1 mm produces significantly desirable results to achieve maximum hardness and minimum surface roughness and holding the porosity of

In this manuscript, we have addressed wave propagation challenges within heterogeneous media and hyperbolic interface model. A hybrid numerical approach is introduced for solving these problems, combining the finite difference method and Haar wavelet collocation method. The method entails approximating the second-order space partial derivative through a truncated Haar wavelet series, while the temporal derivative is approximated using finite difference method. For linear hyperbolic interface model, the resulting algebraic systems are solved using the Gauss elimination technique. In the case of non-linear problems, the nonlinearity is addressed through the quasi-Newton linearization formula. To assess the accuracy of the proposed technique, we compute the computational rate of convergence, root mean square errors and maximum absolute errors employing various collocation points. The proposed method perform very well and produces a stable solution if sharp transitions exists in the solution space or if there is a discontinuity between initial and boundary conditions, whereas, the other existing method loses its accuracy in such cases. The numerical experiments, stability and rate of convergence both theoretical and computational, confirm the accuracy and diverse applicability of the method.

Solid waste management is one of the biggest challenges of the current era. The combustible fractions in the waste stream turn out to be a good energy source if converted into refuse-derived fuel. Researchers worldwide are successfully converting it into fuel. However, certain challenges are associated with its application in gasifiers, boilers, etc. to co-fire it with coal. These include high moisture content, low calorific value, and difficulty to transport and store. The present study proposed torrefaction as a pretreatment of the waste by heating it in the range of 200 °C–300 °C in the absence of oxygen at atmospheric pressure. The combustible fraction from the waste stream consisting of wood, textile, paper, carton, and plastics termed as mixed waste was collected and torrefied at 225 °C, 250 °C, 275 °C, and 300 °C for 15 and 30 min each. It was observed that the mass yield and energy yield decreased to 45% and 62.96% respectively, but the energy yield tended to increase by the ratio of 1.39. Proximate analysis showed that the moisture content and volatile matter decreased for torrefied samples, whereas the ash content and fixed carbon content increased. Similarly, the elemental analysis revealed that the carbon content increased around 23% compared to raw samples with torrefaction contrary to hydrogen and oxygen, which decreased. Moreover, the higher heating value (HHV) of the torrefied samples increased around 1.3 times as compared to the raw sample. This pretreatment can serve as an effective solution to the current challenges and enhance refuse-derived fuel's fuel properties.

A flexible distribution for the analysis of bounded data is proposed. The new model is generalized through the transmuted approach, and the resultant model is named “transmuted modified Lehmann-type II distribution.” A comprehensive analysis of key characteristics is performed, including the shape of the model, survival, and hazard function, analytical expressions of mode, quantile function, ordinary moments, quantile function, and stress–strength reliability. Some famous entropy measures are also derived. The model parameters have been estimated using four distinct methods, including maximum likelihood estimation, Anderson Darling, Cramer–von Misses, and ordinary least squares. A detailed simulation study is used to evaluate the behavior of all derived estimators. Finally, a dataset was used to demonstrate the utility of the proposed distribution.

Among recent developments in manufacturing industries, the laser-powder bed fusion process (L-PBF) is gaining attention for manufacturing complex and functional parts through the selective melting of powders. However, post-processing is required to improve further the quality of L-PBF parts which corresponds to machinability challenges. In this study, stainless steel grade SS 316L manufactured through L-PBF is subjected to high-speed turning to explore the influence of process variables. The cutting speed, CS (125 m/min, 175 , and 225 m/min), depth of cut, DOC (0.45 and 0.90 mm), and feed rate, FR (0.225 and 0.337 mm/rev) are used for process analysis. Machining performance (surface roughness and tool life) and sustainability aspects (energy consumption, carbon emissions, economics) are taken as response metrics. Parametric optimization to achieve desired response characteristics is carried out. The optimized parametric levels achieved an 87.66% goal of lowering machining cost, 80.94% goal of minimizing carbon emissions, 99.25% goal of decreasing specific energy, 100% goal of enhancing tool life, and 98.95% goal of reducing surface roughness. The present research can be used as a basis for comparative analysis of sustainable machining routes (lubrication-based or production tooling) and as a fundamental guideline for machinists in the metal processing industry.

Abstract The additive manufacturing technique of material extrusion has challenge of excessive process defects and not achieving the desired mechanical properties. The industry is trying to develop certification to better control variations in mechanical attributes. The current study is a progress towards understanding the evolution of processing defects and the correlation of mechanical behavior with the process parameters. Modeling of the 3D printing process parameters such as layer thickness, printing speed, and printing temperature is carried out through L27 orthogonal array using Taguchi approach. In addition, CRITIC embedded WASPAS is adopted to optimize the parts' mechanical attributes and overcome the defects. Flexural and tensile poly-lactic acid specimens are printed according to ASTM standards D790 and D638, respectively, and thoroughly analyzed based on the surface morphological analysis to characterize defects. The parametric significance analysis is carried out to explore process science where the layer thickness, print speed, and temperature significantly control the quality and strength of the parts. Mathematical optimization results based on composite desirability show that layer thickness of 0.1 mm, printing speed of 60 mm/s, and printing temperature of 200 °C produce significantly desirable results. The validation experiments yielded the maximum flexural strength of 78.52 MPa, the maximum ultimate tensile strength of 45.52 MPa, and maximum impact strength of 6.21 kJ/m2. It is established that multiple fused layers restricted the propagation of cracks with minimum thickness due to enhanced diffusion between the layers.

In this paper, a novel rotation and scale invariant approach for texture classification based on Gabor filters has been proposed. These filters are designed to capture the visual content of the images based on their impulse responses which are sensitive to rotation and scaling in the images. The filter responses are rearranged according to the filter exhibiting the response having largest amplitude, followed by the calculation of patterns after binarizing the responses based on a particular threshold. This threshold is obtained as the average energy of Gabor filter responses at a particular pixel. The binary patterns are converted to decimal numbers, the histograms of which are used as texture features. The proposed features are used to classify the images from two famous texture datasets: Brodatz, CUReT and UMD texture albums. Experiments show that the proposed feature extraction method performs really well when compared with several other state-of-the-art methods considered in this paper and is more robust to noise.

Biopsies are one of the most common ways to diagnose and make a prognosis of prostate cancer. Transrectal and Transperineal approaches are used to access the prostate for biopsy. Advancements in Magnetic Resonance Imaging (MRI) offer a clear visualization of soft tissues and improved volumetric clarity. Real time MRI guidance can significantly change the paradigm of soft tissue biopsy. Proposed is a device with the ability to collect the tissue samples taken by a biopsy needle during an MRI guided Prostate biopsy and store them temporarily. This could help avoid interruption during the process and make the entire process teleoperated. The proposed design consists of a double layer of paper, rolling over a set of pulleys. Paper collects and stores the core tissue sample. Experiments have been performed to optimize paper tension, speed, and size. Tissue collection performance improvement is noticed with optimum paper tension, speed, and size. A test has also been performed in an MRI environment to check MR compatibility of the device. The device is MRI conditional and demonstrates a maximum of 13.1% SNR reduction in MR images. The proposed device exhibits the potential to be integrated with an MRI safe or conditional robotic manipulator for real time MRI guided Prostate biopsy.

In this modern era where Industry 4.0, plays a crucial role in enhancing productivity, quality, and resource utilization by digitalizing and providing smart operation to industrial systems. Therefore, there is a need to establish a framework that enhances productivity and quality of work to achieve the net-zero from industry. In this study, a comprehensive and generic analytical framework has been established to mitigate or lessen the research and technological gap in the manufacturing sector. In addition to that, the key stages involved in artificial intelligence (AI) based modelling and optimization analysis for manufacturing systems have also been incorporated. To assess the proposed AI framework, electric discharge machining (EDM) as a case study has been selected. The focus enlightens the emergence of optimizing the material removal rate (MRR) and surface roughness (SR) for Inconel 617 (IN617) material. A full factorial design of the experiment was carried out for experimentation. After that, an artificial neural network (ANN) as a modelling framework is selected, and fine-tuning of hyperparameters during training has been carried out. To validate the predictive performance of the trained models, an external validation (Valext) test has been conducted. Through sensitivity analysis (SA) on the developed AI framework, the most influential factors affecting MRR and SR in EDM have been identified. Specifically, powder concentration (Cp) contributes the most to the percentage significance, accounting for 79.00 % towards MRR, followed by treatment (16.35 %) and 4.67 % surfactant concentration (Sc). However, the highest % significance in SR is given by Sc (36.86 %), followed by Cp (33.23 %), and then treatment (29.90 %), respectively. Furthermore, a parametric optimization has been performed using the framework and found that MRR and SR are 93.75 % and 58.90 % better than experimental data. This successful performance optimization proposed by the framework has the potential for application to other manufacturing systems.

Objective: To compare the effectiveness of combining Magnesium Sulphate with Amiodarone vs Magnesium Sulphate to prevent cardiac arrhythmias in Coronary Artery Bypass Grafting (CABG) patients. Study Design: Quasi-Experimental Study. Place and Duration of Study: Armed Forces Institute of Cardiology/National Institute of Heart Diseases Rawalpindi Pakistan, from Jul 2022 to Mar 2023. Methodology: Two hundred and sixty-two (n=262) Coronary Artery Bypass Graft patients, eligible for the study, were enrolled through consecutive sampling and divided into group A - experiment group (3 mg/kg amiodarone+30 mg/kg magnesium sulphate was given, n1=131) and group B- control group (30 mg/kg magnesium sulphate was given, n2=131) by non-random allocation lottery method at the removal of the aortic cross-clamp. The statistical package for social science, SPSS version 26:00 was used to analyse the data. Mean±SD was calculated for continuous variables whereas for categorical variables, percentages and frequencies were calculated. Chi-square test was utilized to find the association and student t-test was applied to find the mean difference between the study groups. Results: Study participants consisted of 194(74.1%) males and 68(26.0%) females. The patients' mean age was 57.29±9.88 years and 58.30±10.69 years respectively, in group-A and group-B. The frequency of pre and post-operative cardiac dysrhythmias was considerably different in both groups. In group-A, 22(16.7%) patients developed dysrhythmias, while in control group,dysrhythmias occurred in 49 (37.4%) patients (p-value

Objective: To determine the dose of Protamine required for reversal of Heparin effect in Coronary Artery Bypass Grafting (CABG). Study Design: Quasi-experimental study. Place and Duration of Study: Adult Cardiac Surgery Unit, Armed Forces Institute of Cardiology/National Institute of Heart Diseases, Rawalpindi Pakistan, from May to Dec 2022. Methodology: Total 382 patients were included in this study through consecutive sampling and were divided into two groups (n=191 participants in each group). After induction of anesthesia, baseline Activated Clotting Time (ACT) was measured. About 300units/kg of unfractionated Heparin was given non-randomly before establishing Cardiopulmonary Bypass (CPB). After termination of CPB, Protamine was administered in doses of 1 mg/kg and 1.5 mg/kg to Group-A and Group-B respectively. Protamine was diluted in 20ml of saline, and administered at a rate of 100ml/hr. Once Protamine was administered, blood sample was taken after 5min for ACT measurement. If this ACT was within 10% of baseline, it was taken as sign for reversal of Heparin effect. Student t-test and Chi-square test were applied to compare the groups and level of significance taken was p

Postmodern organizations strive to cultivate open innovation systems to foster product innovation and commercialization. Cultural dynamics can be a massive obstacle in flourishing the inbound and outbound open innovation in many organizations. However, little is known about the effect of different types of culture on the open innovation dimensions. This research aimed to investigate the role of cultural subtleties in nurturing inbound and outbound open innovation in the organizations. A quantitative research design was employed, and data were collected from a random sample of 231 managers from the automotive industry. Structural Equation Modeling (SEM) was used to test the hypotheses using Smart PLS. The results indicated that hierarchy culture, associated with formal rules and regulations, negatively affects the inbound and outbound open innovation. The Market culture has a positive relationship with inbound and outbound open innovation while adhocracy culture could positively impact the inbound open innovation only. On the other hand, clan culture has a negative effect on the outbound open innovation. We concluded that the organizational culture focused on internal integrations is more suitable for outbound open innovation, and the type of organizational culture focused on external differentiation is more likely to support inbound open innovation.

This review article focused on the mechanical properties of sisal, coir and hemp fiber-reinforced concrete composites and several factors affecting the mechanical properties of natural fiber-reinforced concrete (NFRC) composites. Several treatments were applied to improve the surface of natural fiber for improving the strength and durability of composites. Recently researchers have investigated the mechanical properties by using NaOH treatments effects of sisal, coir and hemp fibers-reinforced concrete composite are highlighted in this study. A variety of recent studies showed that sodium hydroxide (NaOH) treatment plays a significant role in the adhesion of fiber concrete composites. It was found that NaOH improves the mechanical properties of the natural fiber-reinforced composites. Further, the treatment techniques for the modification of these natural fibers by improving the surface of these natural fibers are discussed. In the same way, previous research has investigated the effect of thermal stability and water absorption on the mechanical properties. Generally, this review article was aimed to highlight, gather, and explore the previous reported research studies leading the mechanical properties of sisal, coir and hemp fiber and its polymer composites to deliver a basis source of data and literature to expose it as composite materials like synthetic fibers.

There are so many verses in the holy Quran and Hadith, which told us about the status, importance and rights of women in Islam. Islam is the only religion who has given women the status of human beings, even now if the women should be given their rights which Islam has provided them, they can play their role in the development of society in form of perfect mother, daughter, sister and wife. Generally, nowadays it’s been thought that west has given too many rights to women and Islam has captured them in houses, but in the reality its totally wrong perception. Now this is very important to elaborate true image of women’s rights which Islam has given to them in the better way, infect this is the duty of every Muslim.

Vehicular Ad-Hoc Networks (VANETs) are a challenging yet active research area. It offers a wide range of applications, including Intelligent Transport System (ITS), effective road traffic monitoring, efficient traffic flow and road safety applications. During real-time data gathering for emergency scenarios, the fixed silent segments cause a problem for smooth communication. Moreover, the critical ITS operations may be delayed due to this problem. This paper proposes a Real-Time Traffic-Aware Data Gathering Protocol (TDG) where the dynamic segmentation switching is adopted to handle the communication limitations. TDG is lightweight and dynamically designed for collecting and forwarding data packets based on current and rapid evolving traffic conditions. The primary objective is to reduce network and data communication overhead to incorporate real-time data collection time constraints. TDG implements a data aggregation scheme for data analysis to fetch information based on location, speed, vehicle id and neighbour count. Moreover, a data extraction scheme is implemented to increase data retrieval and data utilization effectiveness in an intelligent way at the base station. Extensive simulation and evaluation results validate that our proposed solution outperforms existing data gathering protocols in effectiveness, efficiency, delay, communication overhead and data transmission rate.

Design of a vision-based traffic analytic system for urban traffic video scenes has a great potential in context of Intelligent Transportation System (ITS). It offers useful traffic-related insights at much lower costs compared to their conventional sensor based counterparts. However, it remains a challenging problem till today due to the complexity factors such as camera hardware constraints, camera movement, object occlusion, object speed, object resolution, traffic flow density, and lighting conditions etc. ITS has many applications including and not just limited to queue estimation, speed detection and different anomalies detection etc. All of these applications are primarily dependent on sensing vehicle presence to form some basis for analysis. Moving cast shadows of vehicles is one of the major problems that affects the vehicle detection as it can cause detection and tracking inaccuracies. Therefore, it is exceedingly important to distinguish dynamic objects from their moving cast shadows for accurate vehicle detection and recognition. This paper provides an in-depth comparative analysis of different traffic paradigm-focused conventional and state-of-the-art shadow detection and removal algorithms. Till date, there has been only one survey which highlights the shadow removal methodologies particularly for traffic paradigm. In this paper, a total of 70 research papers containing results of urban traffic scenes have been shortlisted from the last three decades to give a comprehensive overview of the work done in this area. The study reveals that the preferable way to make a comparative evaluation is to use the existing Highway I, II, and III datasets which are frequently used for qualitative or quantitative analysis of shadow detection or removal algorithms. Furthermore, the paper not only provides cues to solve moving cast shadow problems, but also suggests that even after the advent of Convolutional Neural Networks (CNN)-based vehicle detection methods, the problems caused by moving cast shadows persists. Therefore, this paper proposes a hybrid approach which uses a combination of conventional and state-of-the-art techniques as a pre-processing step for shadow detection and removal before using CNN for vehicles detection. The results indicate a significant improvement in vehicle detection accuracies after using the proposed approach.

The revolution of IoT highly impacts on different applications such as remote sensing, smart cities, and remote digital healthcare. People use IoT devices for performing business transactions, daily tasks, and healthcare monitoring. IoT devices generate huge amounts of data assets that have potential applications. Biometrics is a potential application of sensors data. The traditional biometric methods such as PINs, passwords are exposed to numerous attacks such as replication, repeated passwords, etc. Sensors’ data-based continuous authentication methods are suitable for maintaining users’ privacy and security in mobile IoT systems. Most of the existing authentication methods have applied motion-based sensors for building users’ identification profiles. The proposed method uses motion sensors and biomedical sensors for reliable and multi-factor user authentication. In this article, we have introduced an IoT sensors data analytics framework to construct user authentication models. We apply the fiducial points-based feature extraction method data for extracting discriminative features. These features act as unique user profiles for authentication purposes. We have performed a detailed analysis of the proposed approach using the publically available datasets. The experiments elaborate on the effectiveness of IoTauth for improved authentication results.

Shaykh Ghulām Rasūl al-Sa‘īdī, an Indian-subcontinent contemporary commentator wrote tafsīr with a scholarly prelude/introduction. Additionally, he derived necessary references to Quranic verses along with the syntactic views in quite expressive and simple manner. Thus, his remarkable tafsīr; tafsīr al-tibyān al-Qur’ān, and more particularly his prelude/preface, expounds on the issues faced by ordinary people and makes valuable addition in layman understanding about the meaning of the text. Therefore, this article presents a descriptive and analytical study of the prelude/introduction to his commentary so that it becomes easy for the reader to know the views and ideas of Shaykh Ghulām Rasūl al-Sa‘īdī before delving into his tafsīr work.

Objective: To compare two techniques of activated clotting time (ACT) measurement by two different devices to evaluate the correlation and agreement between these techniques at different points of time during cardiac surgery. Study Design: Comparative Cross-sectional Study. Study settings: Cardiac Anesthesia Department, Armed Forces Institute of Cardiology and National Institute of Heart Diseases, Rawalpindi Pakistan, from Feb 2022 to Apr 2022. Methodology: 100 patients undergoing CABG surgery on pump were included by non-probability consecutive sampling technique. Two devices operating on different techniques of measurement were used to measure ACT at four different points of time during surgery. Same sample was used to measure ACT from both devices. Data was collected and analysed by SPSS V.20.0. Pearson's chi square test and paired sample t-test were applied to measure the significance. Linear regression analysis was done to find correlation and Bland Altman plot was used for checking agreement between ACT values from both devices.p-value less than 0.05 was considered significant. Results: Out of 100, male patients were 79 and female patients were 21. Their mean age was 54.18±11.91 years and mean weight was 79.06±18.49 kg. Moderate positive correlation was found with Pearson r value of 0.55. There was poor agreement between the ACTs measured by two devices. On average Hem R measures ACT 63.54±50.83 seconds higher than Hem JSP. Average mean and median values for Hem R group are 400.03±59.39 sec and 397.75sec respectively and for Hem JSP group are 336.49±44.63 sec and 340.5 sec respectively. Conclusion: There is moderate positive correlation but poor agreement between the values of ACT measured by Hem R and Hem JSP due to different techniques of measurement so these should not be used interchangeably.

Almighty Allah had bestowed upon his Prophet (PBUH) the best companions who spread all over the world by sacrificing their comfort, home and wealth for the propagation of true faith and religion. The Companions, (may Allah be pleased with them), have been chosen by Allah Almighty for the companionship of His Prophet and been set an example for whole Ummah, because of them getting benefit directly from the light of Prophethood. The work of writing the biography of the Companions in the style of da'wah is of great importance, and effective for practical application also. Obtaining guidance from their biographies can save the Ummah from going astray, and it has been emphasized to follow them. Now these events need to be repeated again and again for the nourishment of the heart and mind, the movement of emotions, the passion for life and wealth, and the virtues of migration and Nuṣrah, so that one may realize his lack of faith and be guided to make true deeds. In this article, we shall try to understand the preaching of true faith, the method and character of the Companions and the Salaf-i-Ṣalihīn in the scenario of the present age. This article will discuss the components and importance of preaching, the attributes of the preacher in the light of the Qurān, Sunnah and biographies of the Companions. Then its practical application to the present age will be compared and conclusion will be drawn.

Teeth segmentation plays a pivotal role in dentistry by facilitating accurate diagnoses and aiding the development of effective treatment plans. While traditional methods have primarily focused on teeth segmentation, they often fail to consider the broader oral tissue context. This paper proposes a panoptic-segmentation-based method that combines the results of instance segmentation with semantic segmentation of the background. Particularly, we introduce a novel architecture for instance teeth segmentation that leverages a dual-path transformer-based network, integrated with a panoptic quality (PQ) loss function. The model directly predicts masks and their corresponding classes, with the PQ loss function streamlining the training process. Our proposed architecture features a dual-path transformer block that facilitates bi-directional communication between the pixel path CNN and the memory path. It also contains a stacked decoder block that aggregates multi-scale features across different decoding resolutions. The transformer block integrates pixel-to-memory feedback attention, pixel-to-pixel self-attention, and memory-to-pixel and memory-to-memory self-attention mechanisms. The output heads process features to predict mask classes, while the final mask is obtained by multiplying memory path and pixel path features. When applied to the UFBA-UESC Dental Image dataset, our model exhibits a substantial improvement in segmentation performance, surpassing existing state-of-the-art techniques in terms of performance and robustness. Our research signifies an essential step forward in teeth segmentation and contributes to a deeper understanding of oral structures.

The recent research was performed to investigate the toxicity of As and Cd in suburban area of Sargodha, Punjab, Pakistan. Water, soil and forage samples were collected for this purpose in summer and winter season and analysis was done via wet digestion to determine the concentration of selected heavy metals. The mean concentration of As and Cd in water was found above the permissible maximum limit. Mean concentration of Cd in soil and forages was lower than the allowed limit whereas As which was higher than the PML in forages. So, continuous use of domestic wastewater for irrigation purpose should be avoided in order to secure the area from any hazard in near future.

Heavy metals are considered as most important contaminations due to industrialization of countries and an influence on its existence in soil, plant and milk. A study was carried out to check manganese content in soil, forage and milk at three sites of city Jhang, Punjab, Pakistan. All samples (milk, soil, water, fodder plants and ground water) were analyzed for manganese by Atomic Absorption Spectrophotometer. Different health indices were also studied to check Mn flow in food chain. Level of Mn in samples was found within acceptable limits. Manganese level was higher in soil samples collected from Site-III than other sites. Manganese showed higher value (2.595 to 10.402 mg/kg) in soil than other samples. Fodders were found to accumulate manganese from 0.008 to 0.022 mg/kg. Manganese concentration was found to be 0.1482 to 1.241 mg/L, 0.164 to 0.9708 mg/L in water and milk, respectively. BCF and PLI values for manganese were also found to be less than 1. Estimated daily intake (EDI) and THQ of manganese are found within permissible limits in milk of cows feeding on fodders irrigated with wastewater and ground water. So, use of wastewater for irrigation purpose should be properly checked due to possible toxic effects.

More than 60% of the population of Pakistan has no access to safe drinking water. Industrial zones near populated areas make conditions more severe due to continuous contamination. The aim of this study was to use statistical tools for correlation and source identification and health risk assessment of contamination due to Sundar Industrial Estate (SIE), Lahore, Pakistan. Drinking and wastewater samples were collected from SIE and analyzed for physical, chemical, microbial, and heavy metals analysis. Results showed that heavy metals and microbial contamination were beyond the National Drinking Water Quality Standards of Pakistan while high values of chemical oxygen demand (COD) and biochemical oxygen demand (BOD) wastewater were responsible for contamination of drinking water through seepage. There was a medium to strong correlation among parameters of all samples as indicated by Pearson correlation and analysis of variance. Principal component analysis and cluster analysis indicated sources of contamination, i.e., refuse leachate and untreated effluent discharges as main source of pollutants for drinking water. Health risk assessment showed a high intake of heavy metals through drinking water. Hazard quotient and hazard index indicated high probability of non-carcinogenic risk while cancer risk assessment suggested that out of every 100 of the population 93 people may suffer carcinogenic effects. HIGHLIGHTS Samples showed high bacterial and heavy metals contamination due to untreated effluent.; Statistical modeling showed strong correlation and seepage as the main source of pollution.; The hazard quotient and hazard index (for non-carcinogenic risk) values are >1.; Risk assessment showed 93 people out of 100 of population may suffer from cancer.;

Tactical software defined radio (SDR) networks demand stringent requirements of latency, throughput, and reliability. In the past, significant efforts have been made to achieve maximal efficiency with modifications and improvements either in an individual layer or through the cross-layer design of its working protocol. In this paper, we propose a novel cross-layer design consisting of adaptive multi-input medium access control (AMI-MAC) layer along with an intelligent channel allocation scheme supported by a multiband multimode physical layer. A cognitive engine further empowers this cross-layer design approach to achieve high throughput, improved quality of service (QoS), and adaptive range capabilities. The proposed physical layer exhibits a mixed use of narrowband and wideband waveforms accommodating different range requirements as per demanded QoS. The uniqueness of the proposed physical layer enables SDR to operate in hybrid topology by receiving multiple narrowband signals of different bandwidths with the same configuration of wideband RF front end. The proposed AMI-MAC design ensures a reduction in both control and data phase latency. MAC layer ensures the maximal utilization of the time and frequency spectrum. Bandwidth and delay optimization is also managed by the proposed trio of the physical layer, MAC, and cognition to reduce latency and achieve desired QoS. Simulation results are presented to show the superiority of the proposed design over conventional tactical radio MAC.

Infrastructure-less (sometimes known as ad-hoc) networking paradigm is very appealing and potentially shaping its future into almost all emerging networks (i.e., IoT, wireless sensor networks, vehicular ad-hoc networks, emergency, and tactical radio networks, etc.). However, when conventional networking protocols are used, such networks often perform poorly, mainly because of interference within the network and limited network throughput. Recent advancements in wireless communications have enabled full-duplex (FD) operation by suppressing self-interference, which can theoretically double the network throughput. However, conventional medium access control (MAC) protocols like carrier-sense multiple access with collision avoidance (CSMA/CA) favor half-duplex (HD) operation and fail to benefit from FD transmission opportunities. This article proposes a novel hybrid MAC protocol for full-duplex ad-hoc networks. The proposed MAC combines time division multiple access (TDMA) and IEEE 802.11 distributed coordination function (DCF) strengths in chains of time-slotted contention-based control frames and collision-free data frames. The aim is to fully utilize FD transmission opportunities to increase network throughput. The proposed protocol modifies request-to-send (RTS) and clear-to-send (CTS) frames in IEEE 802.11 DCF MAC to form FD-RTS/CTS frames. These frames are used to enable collision-free FD communications among neighbors. The proposed scheme mitigates conventional MAC issues like hidden-node problem (HNP) and exposed-node problem (ENP). It also allows concurrent FD data transmissions in a collision-free manner. The model is generic and can be applied to any ad-hoc wireless network. In this article, the design is applied to a single channel ad-hoc network with FD transceivers. We compared the proposed design with IEEE 802.11 CSMA/CA protocol with both HD and FD transceivers. The simulation results show a 30% gain in throughput, reduced latency, and fairness among participating wireless nodes.

Unlike commercial networks, the tactical networks drive in a critical environment and without a backbone infrastructure. These networks involve mission-critical operations that are dependent on the rapid and reliable transfer of delay-sensitive data to conduct command and control (C2). Owing to the decentralized and dynamic nature, tactical networks need to survive by maintaining seamless and simultaneous time-sensitive communication among software-defined radios (SDRs). Under mobility and dynamic network topology, link status continuously changes that cause substantial packet loss, and degrade network performance. It is challenging to maintain the connectivity between communicating nodes and find a suitable time for sending control messages (e.g., packet forwarding and route discovery), known as control phase time (CPT). Given a maximum transmission range for narrowband (NB) and wideband (WB) communication, the knowledge of link duration between communicating radios are of major concern, particularly for low latency and reliable communication requirements. Many existing techniques focus on topology control by exchanging mobility parameters in control transmissions, increasing the delay in data transmission. Therefore, it is a non-trivial task to calculate the expected time for the control transmissions due to the confrontation of speed and random movement of nodes. This paper presents a novel methodology to estimate a suitable time to execute the control phase based on the lifetime of communication links between SDRs in tactical MANETs. It uses stochastic distribution to make a network capable of effectively figuring out operative connectivity. The proposed methodology evaluates the maximum network connectivity based on the distances between communicating radios and radio transmission ranges for different quality-of-service (QoS) requirements. The simulation results validate that the proposed methodology’s CPT estimations are more appropriate for the timely link-formations in tactical radio MANETs. The proposed technique is generic and can be applied to any MANET environment using different mobility models.

Great biocompatibility and superior mechanical properties of titanium alloys (Ti6Al4V) stimulate the use of this material frequently in biomedical, defence, and aeronautical industries. In these applications, the end parts generally have complex curved profiles. Through conventional means of machining, complex profiles with high dimensional accuracy are not easily achievable due to difficult-to-cut nature of Ti6Al4V. Wire Electric Discharge Machining (WEDM) is a promising alternative to cut the complex features like angular and curved features. In this research, convex and concave profiles are machined in Ti6Al4V through WEDM. The influence of four machining parameters, namely servo voltage, wire feed, pulse On- and Off-time, over the geometrical accuracies of convex and concave profiles along with corner radii have been comprehensively investigated. The L27 orthogonal array was taken as the design of the experiment, and the results are evaluated in terms of statistical (ANOVA and signal-to-noise ratio) and microscopic morphology by Scanning Electron Microscopy (SEM). Optimized combination of machining parameters are sought capable of resulting in minimum geometric deviations (0.250% overcut in convex and 0.236% undercut in concave profiles) and corner radii of 0.106 mm. Moreover, the SEM analysis has confirmed that the discharge energy and erosion phenomenon significantly affect the profile accuracy as well as the surface integrity. In addition to optimized parameters the provision of wire offset, ranging within 0.169–0.173 mm, can further mitigate the geometric deviations of the actual machined profiles from the designed geometries.

Objectives: The occurrence of psychiatric co-morbidity and factors related to psychiatric comorbidity among COVID-19 patients in hospital setting. Study Design: Cross sectional research design. Place and Duration of Study: Was conducted at Combined Military Hospital Multan, from Apr 2020 to May 2020. Methodology: A purposive sample of 81 in patients diagnosed with COVID-19 was gathered from Combined Military Hospital Multan. Psychometric tests Depression Anxiety and Stress Scale and Multi dimensional Scale of Perceived-Social-Support were administered to assess study variables. Bivariate correlation analysis was used to find relationship between variables. Linear Regression was analyzed to gather causal relationships between study variables. Results: The results of current study indicated that among eighty one COVID-19 patients 21% of participants were having symptoms of depression, 31 patients (38%) were experiencing symptoms of anxiety, 36 patients (44%) were facing stress and 54% COVID-19 patients reported to have lack of social support respectively. Perceived-social support significantly negative correlated with depression, anxiety and stress. Moreover, stress significantly positively predicted whereas social support significantly negatively predicted depression and anxiety. Conclusion: Psychiatric co-morbidity especially the occurrence of anxiety and stress was high and perceived social support was less amongst patients suffering from COVID-19. The findings of the study highlighted the need of thoughtful efforts to be put by health department and government organizations to prevent impending psychological catastrophe that emerged over the lives of COVID-19 sufferers.

This research work concerns the analysis of the impact of changes in size of grain on the geotechnical characteristics of alluvial soils. So, collected soil samples from The University of Lahore, Lahore, Pakistan. In this research work, special experiments performed moisture, strainer analysis, hydrometer analysis, Atterberg limit (liquid limit and plastic limit), direct shear testing, and unspecified compression testing on our models. After these experiments, it is observed that as the density increases, the internal friction angle of the soil and the unknown force of the soil also increases. It has been observed that moisture content does not greatly affect silt and sand properties, as in the case of clay.

This study compares the media constructions of Malala Yousafzai in two Pakistani English newspapers, The News International and Daily Times vis-à-vis the events that occurred during three stages of her life. The study identifies these as “Malala the Taliban’s target and Nobel laureate”, and “Malala the United Nations Messenger of Peace”. Employing Fairclough’s CDA, it probes the ideological representations of these events in these newspapers’ editorials. The findings suggest that both newspapers constructed Malala’s positive identity during all three stages. However, in so doing, the use of a particular clause structure and lexis employed in these editorials helped one newspaper avoid naming the Taliban in a determinate term. Hence, this served to mitigate the Taliban’s “agency” as perpetrators. The other newspaper, by availing the same method of representation, pushed its political agendas and appeared to toe a similar line as some Western newspapers do on certain burning issues of international significance.