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Peri-operative management of cyanotic congenital heart disease in a patient of sickle cell disease (SCD) can be challenging. We report a case of Tetralogy of Fallot and homozygous SCD with history of multiple blood transfusions and sickle cell crises who underwent intracardiac repair. Hemoglobin S level was reduced from 75% pre-operative to 21.8% postoperative with a combination of pre-operative blood transfusion, intraoperative exchange transfusion, and normothermic cardiopulmonary bypass (CPB). Pre-operative optimization and safe intraoperative conduct were essential to avoid sickling crises.

Wireless communication highly depends on the cellular ground base station (GBS). A failure of the cellular GBS, fully or partially, during natural or man-made disasters creates a communication gap in the disaster-affected areas. In such situations, public safety communication (PSC) can significantly save the national infrastructure, property, and lives. Throughout emergencies, the PSC can provide mission-critical communication and video transmission services in the affected area. Unmanned aerial vehicles (UAVs) as flying base stations (UAV-BSs) are particularly suitable for PSC services as they are flexible, mobile, and easily deployable. This manuscript considers a multi-UAV-assisted PSC network with an observational UAV receiving videos from the affected area’s ground users (AGUs) and transmitting them to the nearby GBS via a relay UAV. The objective of the proposed study is to maximize the average utility of the video streams generated by the AGUs upon reaching the GBS. This is achieved by optimizing the positions of the observational and relay UAVs, as well as the distribution of communication resources, such as bandwidth, and transmit power, while satisfying the system-designed constraints, such as transmission rate, rate outage probability, transmit power budget, and available bandwidth. To this end, a joint UAVs placement and resource allocation problem is mathematically formulated. The proposed problem poses a significant challenge for a solution. Considering the block coordinate descent and successive convex approximation techniques, an efficient iterative algorithm is proposed. Finally, simulation results are provided which show that our proposed approach outperforms the existing methods.

The global challenge of feeding an ever-increasing population to maintain food security requires novel approaches to increase crop yields. Photosynthesis, the fundamental energy and material basis for plant life on Earth, is highly responsive to environmental conditions. Evaluating the operational status of the photosynthetic mechanism provides insights into plants’ capacity to adapt to their surroundings. Despite immense effort, photosynthesis still falls short of its theoretical maximum efficiency, indicating significant potential for improvement. In this review, we provide background information on the various genetic aspects of photosynthesis, explain its complexity, and survey relevant genetic engineering approaches employed to improve the efficiency of photosynthesis. We discuss the latest success stories of gene-editing tools like CRISPR-Cas9 and synthetic biology in achieving precise refinements in targeted photosynthesis pathways, such as the Calvin-Benson cycle, electron transport chain, and photorespiration. We also discuss the genetic markers crucial for mitigating the impact of rapidly changing environmental conditions, such as extreme temperatures or drought, on photosynthesis and growth. This review aims to pinpoint optimization opportunities for photosynthesis, discuss recent advancements, and address the challenges in improving this critical process, fostering a globally food-secure future through sustainable food crop production.

Oxidative stress impairs the structure and function of the cell, leading to serious chronic diseases. Antioxidant-based therapeutic and nutritional interventions are usually employed for combating oxidative stress-related disorders, including apoptosis. Here, we investigated the hepatoprotective effect of oligosaccharides, produced through Pichia pastoris-mediated fermentation of water-soluble polysaccharides isolated from Lepidium sativum (cress) seed mucilage, on chromium(VI)-induced oxidative stress and apoptosis in mice. Gel permeation chromatography (GPC), using Bio-Gel P-10 column, of the oligosaccharides product of fermentation revealed that P. pastoris effectively fermented polysaccharides as no long chain polysaccharides were observed. At 200 µg/mL, fractions DF73, DF53, DF72, and DF62 exhibited DPPH radical scavenging activity of 92.22 ± 2.69%, 90.35 ± 0.43%, 88.83 ± 3.36%, and 88.83 ± 3.36%, respectively. The antioxidant potential of the fermentation product was further confirmed through in vitro H2O2 radical scavenging assay. Among the screened samples, the highest H2O2 radical scavenging activity was displayed by DF73, which stabilized the free radicals by 88.83 ± 0.38%, followed by DF53 (86.48 ± 0.83%), DF62 (85.21 ± 6.66%), DF72 (79.9 4± 1.21%), and EPP (77.76 ± 0.53%). The oligosaccharide treatment significantly alleviated chromium-induced liver damage, as evident from the increase in weight gain, improved liver functions, and reduced histopathological alterations in the albino mice. A distinctly increased level of lipid peroxide (LPO) free radicals along with the endogenous hepatic enzymes were evident in chromium induced hepatotoxicity in mice. However, oligosaccharides treatment mitigated these effects by reducing the LPO production and increasing ALT, ALP, and AST levels, probably due to relieving the oxidative stress. DNA fragmentation assays illustrated that Cr(VI) exposure induced massive apoptosis in liver by damaging the DNA which was then remediated by oligosaccharides supplementation. Histopathological observations confirmed that the oligosaccharide treatment reverses the architectural changes in liver induced by chromium. These results suggest that oligosaccharides obtained from cress seed mucilage polysaccharides through P. pastoris fermentation ameliorate the oxidative stress and apoptosis and act as hepatoprotective agent against chromium-induced liver injury.

Excessive accumulation of extracellular matrix (ECM) components within the liver leads to a pathological condition known as liver fibrosis. Alcohol abuse, non-alcoholic fatty liver disease (NAFLD), autoimmune issues, and viral hepatitis cause chronic liver injury. Exploring potential therapeutic targets and understanding the molecular mechanisms involved in liver fibrosis are essential for the development of effective interventions. The goal of this comprehensive review is to explain how the PI3K/AKT signaling pathway contributes to the reduction of liver fibrosis. The potential of this pathway as a therapeutic target is investigated through a summary of results from in vivo and in vitro studies. Studies focusing on PI3K/AKT activation have shown a significant decrease in fibrosis markers and a significant improvement in liver function. The review emphasizes how this pathway may prevent ECM synthesis and hepatic stellate cell (HSC) activation, ultimately reducing the fibrotic response. The specific mechanisms and downstream effectors of the PI3K/AKT pathway in liver fibrosis constitute a rapidly developing field of study. In conclusion, the PI3K/AKT signaling pathway plays a significant role in attenuating liver fibrosis. Its complex role in regulating HSC activation and ECM production, demonstrated both in vitro and in vivo, underscores its potential as a effective therapeutic approach for managing liver fibrosis and slowing disease progression. A comprehensive review of this field provides valuable insights into its future developments and implications for clinical applications.

Objective: To investigate the association between the tumour budding of colorectal carcinoma and its histological type, grade, lymph node metastasis, and pathological stage. Study Design: Cross-sectional study Place and Duration of Study: Histopathology Department, Armed Forces Institute of Pathology, Rawalpindi Pakistan, from Dec 2021 to Mar 2023. Methodology: One hundred and twenty colorectal carcinoma patients were examined for existence and severity using Hematoxylin and Eosin-stained sections. According to the number of tumour buds, cases were categorised as low grade (20/200X). These categories were related to lymph node involvement, histological type and grade, and pathological staging. In challenging cases, pan-cytokeratin immunohistochemistry labelling was conducted to confirm tumour budding. Results: The mean age of presentation was 55.78±12.47 years. The most common site of involvement was the ascending colon 66(55%), followed by the recto-sigmoid colon 29(24.2%). Most cases were conventional adenocarcinoma 80(67%), followed by mucinous carcinoma 31(26%). Most cases were moderately differentiated 62(52%) and were stage III 79(66%). Forty-two (35%) had low-grade, and thirty-four (28.3%) had intermediate-grade and high-grade tumour budding. Tumour budding significantly correlates with tumour size, histological grade, invasion extent, and lympho-vascular invasion (p-value

The use of fractal–fractional derivatives has attracted considerable interest in the analysis of chaotic and nonlinear systems as they provide a unique capability to represent complex dynamics that cannot be fully described by integer-order derivatives. The fractal–fractional derivative with a power law kernel is used in this paper as an analytical tool to analyze the dynamics of a chaotic integrated circuit. Using coupled ordinary differential equations of classical order, the complexity of an integrated circuit is modeled. The classical order model is generalized via fractal–fractional derivatives of the power law kernel. Moreover, this paper is concerned with investigating the Ulam stability of the model and conducting theoretical studies in order to analyze equilibrium points, identify unique solutions, and verify the existence of such solutions. By examining the complex dynamics that result in chaotic behavior, these investigations shed light on the fundamental properties of integrated circuits. For the purpose of exploring the non-linear fractal–fractional order system, a numerical algorithm has been developed to facilitate our analysis. MATLAB software has been used to implement this algorithm, making it possible to carry out detailed simulations. Simulating solutions are accomplished using 2D and 3D portraits, which provide visual and graphical representations of the results. Throughout the simulation phase, particular attention is given to the impact of fractional order parameter and fractal dimension. As a result of this study, we have gained a comprehensive understanding of the behavior of the system and its response to variations in values.

Abstract Through the broad usage of cloud computing and the extensive utilization of next-generation public clouds, people can share valuable information worldwide via a wireless medium. Public cloud computing is used in various domains where thousands of applications are connected and generate numerous amounts of data stored on the cloud servers via an open network channel. However, open transmission is vulnerable to several threats, and its security and privacy are still a big challenge. Some proposed security solutions for protecting next-generation public cloud environments are in the literature. However, these methods may not be suitable for a wide range of applications in a next-generation public cloud environment due to their high computing and communication overheads because if security protocol is strengthened, it inversely impacts performance and vice versa. Furthermore, these security frameworks are vulnerable to several attacks, such as replay, denial-of-service (DoS), insider, server spoofing, and masquerade, and also lack strong user anonymity and privacy protection for the end user. Therefore, this study aims to design an elliptic curve cryptographic (ECC) based data access control protocol for a public cloud environment. The security mechanism of the proposed protocol can be verified using BAN (Burrows-Abadi-Needham) logic and ProVerif 2.03, as well as informally using assumptions and pragmatic illustration. In contrast, in the performance analysis section, we have considered the parameters such as the complexity of storage overheads, communication, and computation time. As per the numerical results obtained in the performance analysis section, the proposed protocol is lightweight, robust, and easily implemented in a practical next-generation cloud computing environment.

Abstract The monitoring of human activities using simple body worn sensors is an important and emerging area of research in machine learning. The sensors capture a large amount of data in a short period of Time in a relatively un-obtrusive manner. The sensor data might have different transitions to be used for deification of different user activities. Therefore, change point detection can be used to classify the transition from one underlying distribution to another. The automatic and accurate change point detection is not only used for different events, however, can also be used for generating real world datasets and responding to changes in patient vital signs in critical situation. Moreover, the huge amount of data can use the current state-of-the-art cloud and edge computing platforms to process the change detection locally and more efficiently. In this paper, we used multivariate exponentially weighted moving Average (MEWMA) for online change point detection. Additionally, genetic algorithm (GA) and particle swarm optimization (PSO) is used to automatically identify an optimal parameter set by maximizing the F-measure. The optimisation approach is implemented over an edge cloud platform so that the data can be processed locally and more accurately. Furthermore, we evaluate our approach against multivariate cumulative sum (MCUSUM) from state-of the-art in terms of different metric measures such as accuracy, precision, sensitivity, G-means and F-measure. Results have been evaluated based on real data set collected using accelerometer for a set of 9 distinct activities performed by 10 users for total period of 35 minutes with achieving high accuracy from 99.3% to 99.9% and F-measure up to 62.94%.

Abstract Better electrical insulation and thermal properties of vegetable oil with nanoparticles are crucial for its uses as a replacement for conventional previous lubricants used in heavy and light industries for cutting and machining. In this study, a magnetohydrodynamic (MHD) flow of a Brinkman-type nanofluid is used to investigate an infinite vertical plate with chemical reaction, heat radiation, and MHD flow. In order to improve the machining and cutting powers of regular vegetable oil, four distinct types of nanoparticles were selected to be the base fluid. The problem is modeled by coupled system partial differential equations (PDEs), and the results are generalized by the Caputo-Fabrizio fractional differential operator for the exponential non-singular kernel. In order to prepare nanofluids, four different types of nanoparticles, namely graphene oxide (GO), molybdenum disulfide (MoS2), titanium dioxide (TiO2), and aluminum oxide (Al2O3) are suspended separately in vegetable oil. The results of skin friction, the Nusselt number, and the Sherwood number are computed in various tables. It is found that GO nanoparticles, (followed by MoS2, TiO2, and Al2O3) are the materials that can heat transfer at the maximum rate. The heat transfer rate for GO is found to be the greatest with an enhancement up to 19.83% when 4% of nanoparticles are dispersed, followed by molybdenum disulfide at 16.96%, titanium dioxide at 16.25%, and alumina at 15.80%.

Abstract In this paper, the newly developed Fractal-Fractional derivative with power law kernel is used to analyse the dynamics of chaotic system based on a circuit design. The problem is modelled in terms of classical order nonlinear, coupled ordinary differential equations which is then generalized through Fractal-Fractional derivative with power law kernel. Furthermore, several theoretical analyses such as model equilibria, existence, uniqueness, and Ulam stability of the system have been calculated. The highly non-linear fractal-fractional order system is then analyzed through a numerical technique using the MATLAB software. The graphical solutions are portrayed in two dimensional graphs and three dimensional phase portraits and explained in detail in the discussion section while some concluding remarks have been drawn from the current study. It is worth noting that fractal-fractional differential operators can fastly converge the dynamics of chaotic system to its static equilibrium by adjusting the fractal and fractional parameters.

Abstract Several scientists are interested in recent developments in nanotechnology and nanoscience. Grease is an essential component of many machines and engines because it helps keep them cool by reducing friction between their various elements. In sealed life applications including centralized lubrication systems, electrical motors, bearings, logging and mining machinery, truck wheel hubs, construction, landscaping, and gearboxes, greases are also utilized. Nanoparticles are added to convectional grease to improve its cooling and lubricating properties. More specifically, the current study goal is to investigate open channel flow while taking grease into account as a Maxwell fluid with MoS 2 nanoparticles suspended in it. The Caputo-Fabrizio time-fractional derivative is used to convert the issue from a linked classical order PDE to a local fractional model. To determine the precise solutions for the velocity, temperature, and concentration distributions, two integral transform techniques the finite Fourier sine and the Laplace transform technique are jointly utilized. The resultant answers are physically explored and displayed using various graphs. It is important to note that the fractional model, which offers a variety of integral curves, more accurately depicts the flow behavior than the classical model. Skin friction, the Nusselt number, and the Sherwood number are engineering-related numbers that are quantitatively determined and displayed in tabular form. It is determined that adding MoS 2 nanoparticles to grease causes a 19.1146% increase in heat transmission and a 2.5122% decrease in mass transfer. The results obtained in this work are compared with published literature for the accuracy purpose.

Network on Chip (NoC) has emerged as a potential substitute for the communication model in modern computer systems with extensive integration. Among the numerous design challenges, application mapping on the NoC system poses one of the most complex and demanding optimization problems. In this research, we propose a hybrid improved whale optimization algorithm with enhanced genetic properties (IWOA-IGA) to optimally map real-time applications onto the 2D NoC Platform. The IWOA-IGA is a novel approach combining an improved whale optimization algorithm with the ability of a refined genetic algorithm to optimally map application tasks. A comprehensive comparison is performed between the proposed method and other state-of-the-art algorithms through rigorous analysis. The evaluation consists of real-time applications, benchmarks, and a collection of arbitrarily scaled and procedurally generated large-task graphs. The proposed IWOA-IGA indicates an average improvement in power reduction, improved energy consumption, and latency over state-of-the-art algorithms. Performance based on the Convergence Factor, which assesses the algorithm’s efficiency in achieving better convergence after running for a specific number of iterations over other efficiently developed techniques, is introduced in this research work. These results demonstrate the algorithm’s superior convergence performance when applied to real-world and synthetic task graphs. Our research findings spotlight the superior performance of hybrid improved whale optimization integrated with enhanced GA features, emphasizing its potential for application mapping in NoC-based systems.

Abstract Numerical simulations of non-linear Casson nanofluid flow were carried out in a microchannel using the fractal-fractional flow model. The nano-liquid is prepared by dispersing Cadmium Telluride nanoparticles in common engine oil. Using relative constitutive equations, the system of mathematical governing equations has been formulated along with initial and boundary conditions. Dimensionless variables have been used to obtain the non-dimensional form of the governing equations. The fractal-fractional model has been obtained by employing the fractal-fractional operator of the exponential kernel. As the exact solution of the non-linear fractal-fractional model is very tough to find, therefore the formulated model has been solved numerically via the Crank-Nicolson scheme. Various plots are generated for the inserted parameters. From the analysis, it has been observed that a greater magnitude of the electro-kinetic parameter slows down the fluid's velocity. It is also worth noting that the fractional and classical models can also be derived from the fractal-fractional model by taking the parameters tend to zero. From the analysis, it is also observed that in response to 0.04 volume fraction of cadmium telluride nanoparticles, the rate of heat transfer (Nusselt number) and rate of mass transfer (Sherwood number) increased by 15.27% and 2.07% respectively.

Abstract Gold nanoparticles are commonly used as a tracer in laboratories. They are biocompatible and can transport heat energy to tumor cells via a variety of clinical techniques. As cancer cells are tiny, properly sized nanoparticles were introduced into the circulation for invasion. As a result, gold nanoparticles are highly effective. Therefore, the current research investigates the magnetohydrodynamic free convection flow of Casson nanofluid in an inclined channel. The blood is considered as a base fluid, and gold nanoparticles are assumed to be uniformly dispersed in it. The above flow regime is formulated in terms of partial differential equations. The system of derived equations with imposed boundary conditions is non-dimensionalized using appropriate dimensionless variables. Fourier's and Fick's laws are used to fractionalize the classical dimensionless model. The Laplace and Fourier sine transformations with a new transformation are used for the closed-form solutions of the considered problem. Finally, the results are expressed in terms of a specific function known as the Mittag-Leffler function. Various figures and tables present the effect of various physical parameters on the achieved results. Graphical results conclude that the fractional Casson fluid model described a more realistic aspect of the fluid velocity profile, temperature, and concentration profile than the classical Casson fluid model. The heat transfer rate and Sherwood number are calculated and presented in tabular form. It is worth noting that increasing the volume percentage of gold nanoparticles from 0 to 0.04 percent resulted in an increase of up to 3.825% in the heat transfer rate.

This study aims to extend the Fama-French three-factor model by including human capital as a fourth factor. For this purpose, we have collected data from 164 non-financial firms from July 2010 to June 2020. To evaluate the validity and applicability of our augmented human capital-based four-factor model, we apply the two-pass time series regression proposed by Fama-Macbeth (1973). We find that small firms outperform big firms, value stocks firms outperform growth stocks firms, and low-labor-income firms outperform high-labor-income firms. The augmented human capital-based four-factor model is valid and applicable in the context of the Pakistan equity market. The empirical results motivate academia and all investors to consider human capital in investment decisions.

Numerous real-world applications can be solved using the broadly adopted notions of intuitionistic fuzzy sets, Pythagorean fuzzy sets, and q-rung orthopair fuzzy sets. These theories, however, have their own restrictions in terms of membership and non-membership levels. Because it utilizes benchmark or control parameters relating to membership and non-membership levels, this theory is particularly valuable for modeling uncertainty in real-world problems. We propose the unique concept of linear Diophantine fuzzy set with benchmark parameters to overcome these restrictions. Different numerical, analytical, and semi-analytical techniques are used to solve linear systems of equations with several fuzzy numbers, such as intuitionistic fuzzy number, triangular fuzzy number, bipolar fuzzy number, trapezoidal fuzzy number, and hexagon fuzzy number. The purpose of this research is to solve a fuzzy linear system of equations with the most generalized fuzzy number, such as Triangular linear Diophantine fuzzy number, using an analytical technique called Homotopy Perturbation Method. The linear systems co-efficient are crisp when the right hand side vector is a triangular linear Diophantine fuzzy number. A numerical test examples demonstrates how our newly improved analytical technique surpasses other existing methods in terms of accuracy and CPU time. The triangular linear Diophantine fuzzy systems of equations’ strong and weak visual representations are explored.

Interleukin-17F (IL-17F), considered a pro-inflammatory cytokine, has been shown to contribute to skeletal tissue degradation and hence chronic inflammation in rheumatoid arthritis (RA). In this study we utilized bioinformatics tools to analyze the effect of three exonic SNPs (rs2397084, rs11465553, and rs763780) on the structure and function of the IL-17F gene, and evaluated their association with RA in Pakistani patients. The predicted deleterious and damaging effects of identified genetic variants were assessed through the utilization of multiple bioinformatics tools including PROVEAN, SNP&GO, SIFT, and PolyPhen2. Structural and functional effects of these variants on protein structures were evaluated through the use of additional tools such as I-Mutant, MutPred, and ConSurf. Three-dimensional (3D) models of both the wild-type and mutant proteins were constructed through the utilization of I-TASSER software, with subsequent structural comparisons between the models conducted through the use of the TM-align score. A total of 500 individuals, 250 cases and 250 controls, were genotyped through Tri-ARMS-PCR method and the resultant data was statistically analyzed using various inheritance models. Our bioinformatics analysis showed significant structural differences for wild type and mutant protein (TM-scores and RMSD values were 0.85934 and 2.34 for rs2397084 (E126G), 0.87388 and 2.49 for rs11465553 (V155I), and 0.86572 and 0.86572 for rs763780 (H161R) with decrease stability for the later. Overall, these tools enabled us to predict that these variants are crucial in causing disease phenotypes. We further tested each of these single nucleotide variants for their association with RA. Our analysis revealed a strong positive association between the genetic variant rs763780 and the risk of developing rheumatoid arthritis (RA) at both the genotypic and allelic levels. The genotypic association was statistically significant[χ2 = 111.8; P value

Chemical kinetics is a branch of chemistry that is founded on understanding chemical reaction rates. Chemical kinetics relates many aspects of cosmology, geology, and even in some cases of, psychology. There is a need for mathematical modelling of these chemical reactions. Therefore, the present research is based on chemical kinetics-based modelling and dynamics of enzyme processes. This research looks at the two-step substrate-enzyme reversible response. In the two step-reversible reactions, substrate combines with enzymes which is further converted into products with two steps. The model is displayed through the flow chart, which is then transformed into ODEs. The Atangana-Baleanu time-fractional operator and the Mittag-Leffler kernel are used to convert the original set of highly nonlinear coupled integer order ordinary differential equations into a fractional-order model. Additionally, it is shown that the solution to the investigated fractional model is unique, limited, and may be represented by its response velocity. A numerical scheme, also known as the Atangana-Toufik method, based on Newton polynomial interpolation technique via MATLAB software, is adopted to find the graphical results. The dynamics of reaction against different reaction rates are presented through various figures. It is observed that the forward reaction rates increase the reaction speed while backward reaction rates reduce it.

Objective: To analyse histopathological findings in gastric biopsies of patients with dyspepsia using an updated Sydney System. Study Design: Retrospective longitudinal study. Place and Duration of Study: Histopathology Department, Najran Armed Forces Hospital (NAFH), Saudi Arabia, from Jan 2013 to Mar 2020. Methodology: A total of 408 cases whose gastric biopsies were included in the study, and their histological features were studied. Results: Among 408 patients included in the study, 191(46.8%) were males, and 217(53.2%) were females. The mean age was 37.0±15.0 years. A total of 343 patients showed gastritis, which was mild 152(44.3%), moderate 158(46.1%) and severe 33(9.6%), respectively. The activity was observed in 200(49.0%) patients. H.pylori infection was observed in 196(48.0%) patients and intestinal metaplasia in 9(2.2%) patients. Conclusion: Most of the cases with dyspepsia showed histological evidence of gastritis. However, a significant number of patients had no gastric mucosal abnormality. Therefore, adequate and timely treatment of H.pylori infection can significantly reduce related morbidity.

The present study aims to investigate the Casson nanofluids flow theoretically over a vertical Riga plate. The temperature and concentration with ramped and isothermal wall conditions are considered. Moreover, the fluid is considered electrically conducted. Concrete is considered as a base fluid while clay nanoparticles are added to it. The present flow regime is formulated in terms of a system of partial differential equations. Using dimensionless variables, the system of equations with the imposed boundary conditions is non-dimensionalized. The Laplace transform technique is used to calculate the exact solutions for the temperature, concentration, and velocity distributions. The effect of various embedded parameters on the velocity, temperature, and concentration fields are shown graphically and discussed physically. The variation in the skin friction for various values of clay nanoparticles volume fraction is shown in tabular form. The results indicate that adding 4% clay nanoparticles, enhanced the skin friction up to 7.04% in instance of ramped wall temperature (RWT) and 11.13% in isothermal wall temperature (IWT). This result is worth noting because the increase in skin friction causes rapid compaction of the cementitious materials and improves the tensile strength of the concrete.

While operating upon the brain, deep seated lesions need to be approached by using retractor’s system, due to the soft and gelatinous nature of the brain. Using a conventional rigid, fixed retractor system for brain retraction appears harmful. As an alternative Thudicam Nasal Speculum (TNS) retractors can be used. This study was aimed to explore the outcome of TNS retractors in brain surgery. The cross-sectional study was conducted at Ziauddin University hospital north campus and National Medical Center Defense, Karachi, Pakistan, during a period between August 2019 to March 2020. A total of 60 patients were included (42 males and 18 females), with a median age of 25 years. In all these cases intra-cranial hematoma were removed with unremarkable damage, in aneurysm clipping it was found useful, without damaging adjacent areas and extraction of brain tumors was found to be very easy and non-damaging to the surrounding brain tissue. Patients had a follow-up period of about 03 months and contusion, ischemia or brain edema was not present in any patient. Only one patient died during second month after surgery due to Ischemic stroke of contra-lateral MCA. The study concludes that using TNS retractors was very helpful and non-damaging to the brain.

Malnutrition is mainly caused by iron and zinc micronutrient deficiencies affecting about half of the world's population across the globe. Biofortification of staple crops is the right approach to overcome malnutrition and enhance nutrient contents in the daily food of humans. This study aimed to evaluate the role of foliar application of iron and zinc in Trichoderma harzianum treated soil on various growth characteristics, quality, and yield of wheat varieties. Plants were examined in the absence/presence of T. harzianum, and iron and zinc micronutrients in both optimal and high-stress conditions. Although the symbiotic association of T. harzianum and common wheat is utilized as an effective approach for wheat improvement because of the dynamic growth promoting the ability of the fungus, this association was found tremendously effective in the presence of foliar feeding of micronutrients for the enhancement of various growth parameters and quality of wheat. The utilization of this approach positively increased various growth parameters including spike length, grain mass, biomass, harvest index, and photosynthetic pigments. The beneficial role of T. harzianum in combination with zinc and iron in stimulating plant growth and its positive impact on the intensities of high molecular weight glutenin subunits (HMW-GS) alleles make it an interesting approach for application in eco-friendly agricultural systems. Further, this study suggests a possible alternative way that does not merely enhances the wheat yield but also its quality through proper biofortification of iron and zinc to fulfill the daily needs of micronutrients in staple food.

A swarm of robots is the coordination of multiple robots that can perform a collective task and solve a problem more efficiently than a single robot. Over the last decade, this area of research has received significant interest from scientists due to its large field of applications in military or civil, including area exploration, target search and rescue, security and surveillance, agriculture, air defense, area coverage and real-time monitoring, providing wireless services, and delivery of goods. This research domain of collective behaviour draws inspiration from self-organizing systems in nature, such as honey bees, fish schools, social insects, bird flocks, and other social animals. By replicating the same set of interaction rules observed in these natural swarm systems, robot swarms can be created. The deployment of robot swarm or group of intelligent robots in a real-world scenario that can collectively perform a task or solve a problem is still a substantial research challenge. Swarm robots are differentiated from multi-agent robots by specific qualifying criteria, including the presence of at least three agents and the sharing of relative information such as altitude, position, and velocity among all agents. Each agent should be intelligent and follow the same set of interaction rules over the whole network. Also, the system’s stability should not be affected by leaving or disconnecting an agent from a swarm. This survey illustrates swarm systems’ basics and draws some projections from its history to its future. It discusses the important features of swarm robots, simulators, real-world applications, and future ideas.

Due to globalization in the semiconductor industry, malevolent modifications made in the hardware circuitry, known as hardware Trojans (HTs), have rendered the security of the chip very critical. Over the years, many methods have been proposed to detect and mitigate these HTs in general integrated circuits. However, insufficient effort has been made for hardware Trojans (HTs) in the network-on-chip. In this study, we implement a countermeasure to congeal the network-on-chip hardware design in order to prevent changes from being made to the network-on-chip design. We propose a collaborative method which uses flit integrity and dynamic flit permutation to eliminate the hardware Trojan inserted into the router of the NoC by a disloyal employee or a third-party vendor corporation. The proposed method increases the number of received packets by up to 10% more compared to existing techniques, which contain HTs in the destination address of the flit. Compared to the runtime HT mitigation method, the proposed scheme also decreases the average latency for the hardware Trojan inserted in the flit’s header, tail, and destination field up to 14.7%, 8%, and 3%, respectively.

The abrogation of Multifiber Arrangement in the year 2005 pushed many developing nations into tough competition. Within the textile industry, despite having many advantages apparel manufacturing and exporting organizations (AMEOs) in developing nations are experiencing decline in their supply chain supply chain performance. Developing a comprehensive model to explore and classify factors, which affect the supply chain performance, is extremely significant. Owing to limited research in this area, an exploratory qualitative study involving a variety of organizations in apparel supply chain was carried out, in combination with a literature review, to determine the causes behind that decline. The outcome of preliminary exploratory study and literature review aided in the proposal of a conceptual framework. Employing that framework, a questionnaire survey was designed and piloted to support a quantitative study, which was conducted in the Karachi region in Pakistan. Collected data were analyzed by employing structural equation modeling. Results indicate that a number of factors have a strong influence on the supply chain performance of AMEOs. Apart from contributing to the literature, this study can also be of interest to managers and practitioners from the textile industry, as it clearly indicates areas on which AMEOs need to focus in order to improve their performance.

In this paper, the newly developed fractal-fractional differential and integral operators are used to analyze the dynamics of chaotic system based on image encryption. The problem is modeled in terms of classical order nonlinear, coupled ordinary differential equations that are then generalized through fractal-fractional differential operator of Mittag-Leffler kernel. In addition to that, some theoretical analyses, such as model equilibria, existence, and uniqueness of the solutions, have been proved. Furthermore, the highly non-linear problem is solved by adopting a numerical scheme through MATLAB software. The graphical solution is portrayed through 2D and 3D portraits. Some interesting results are concluded considering the variation of fractional-order parameter and fractal dimension parameter.

Nanofluid is an innovative heat transfer fluid with the potential to significantly enhance the heat transfer performance of traditional fluids. By adding various types of nanoparticles to ordinary base fluids, several attempts have been made to boost the rate of heat transfer and thermal conductivity. The unsteady electrically conducting flow of Brinkman-type nanofluid over an infinite vertical plate with ramping wall temperature and concentration is investigated in this article. Water is taken as the base fluid, and multi-walled carbon nanotubes are distributed equally throughout it. The Caputo-Fabrizio fractional derivative, which has a non-singular kernel, is used to generalize the classical model. The Laplace transform technique has been utilized to achieve exact solutions. Furthermore, various graphs for fractional and physical parameters are used to represent the solutions. All figures are drawn for both conditions, that is, ramped and isothermal wall temperature and concentration. The velocity field increases for greater values of thermal and mass Grashof numbers while the reverse effect is observed for Hartman number, Brinkman parameter and volume fraction. Moreover, the obtained results are also reduced to the already published results in order to show the validation of the present results. The results are used to calculate the skin friction, Nusselt number, and Sherwood number. The heat transfer of pure water is increased by 17.03% when 4% of nanoparticles are added to it which will of course increase the efficiency of solar collectors and solar pools. Moreover, the mass transfer decreases by 3.18% when 4% of nanoparticles which are dispersed in it.

Network on chip (NoC) is a promising communication infrastructure for multiple cores on a chip to exchange data efficiently. In such NoC architecture, application mapping is a process of assigning tasks to the processing cores. An optimized application mapping technique enhances the performance of a chip and reduces the entire chip’s energy consumption. The optimization of application mapping is essential in the design of NoC. In this study, a greedy algorithm is utilized as the first technique to place the maximum communicating tasks together to give the main algorithm a head start. Then, a meta-heuristic Cuckoo Search via Lévy flight is employed further to optimize the placement of tasks on the NoC cores. The greedy algorithm furnishes a relatively pre-processed base to the cuckoo search optimization (CSO), which eventually helps in the fast convergence of the main algorithm. The analysis of the results shows that the proposed algorithm outperformed the state-of-the-art techniques in NoC application mapping in terms of various performance metrics, such as communication cost, energy consumption, and average packet latency.

In recent years, the rapid and significant development of emerging markets has globally led to insight from potential investors and academicians seeking to assess these markets in terms of risk inheritance. Therefore, this study aims to explore the validity and applicability of the capital asset pricing model (henceforth CAPM) and multi-factor models, namely Fama–French models, in Pakistan’s stock market for the period of June 2010–June 2020. This study collects data on 173 non-financial firms listed on the Pakistan stock exchange, namely the KSE-100 index, and follows Fama-MacBeth’s regression methodology for empirical estimation. The empirical findings of this study conclude that small portfolios (small-size companies) earn considerably higher returns than big portfolios (large-size companies). Ultimately, the risk associated with portfolio returns is reported to be higher for small portfolios (small-size companies) than for big portfolios (large-size companies). According to the regression output, the CAPM was found to be valid for explaining the market risk premium above the risk-free rate. Similarly, the FF three-factor model was found to be valid for explaining time-series variation in excess portfolio returns. Later, we added human capital into FF three- and five-factor models. This study found that the human capital base six-factor model outperformed the other competing asset pricing models. The findings of this study indicate that small portfolios (small-size companies) earn more returns than big portfolios (large-size companies) to reward the investor for taking extra risks. Investors may benefit by timing their investments to maximize stock returns. Company investment in human capital adds reliable information, replicates the value of the company and, in the long term, helps investors make rational decisions.

The decreasing size of the transistor has increased the vulnerability towards faults. Increasing number of cores on a single chip has made the concept of Network on Chip (NoC) a standard communication backbone among cores. This facility comes with vulnerability of faults in the system due to decreasing size of transistors. A permanent fault in the network leads to undesirable consequence such as permanent blocking of flits or failure of the whole router. Preserving the router in the operational state has a significant impact on the reliability of the system. Permanent fault in buffers and pipeline stages of the router has a high impact on performance. The proposed router architecture Protector provides faults protection to both buffers and pipelines stages by exploiting the concepts of borrowing from other resources, using bypass paths and by creating multiple paths to reach output. The proposed router incurred an area overhead of 30% as compared to the baseline design. Reliability analysis using Silicon Protection Factor indicates that the proposed router has better fault tolerance efficiency as compared to state of the art. Latency analysis using PARSEC and SPLASH-2 benchmarks indicates proposed router incurs 13% and 16% latency overhead in the presence of faults.

Network-on-chip (NoC) is evolving as a better substitute for incorporating a large number of cores on a single system-on-chip (SoC). The dependency on multi-core systems to accomplish the high-performance constraints of composite embedded applications is on the rise. This leads to the realization of efficient mapping approaches for such complex applications. The significance of efficient application mapping approaches has increased ever since the embedded applications have become more complex and performance-oriented. This paper presents the detailed comparative analysis and categorization of application mapping approaches with current trends in NoC design implementation. These approaches target to improve the performance of the whole system by optimizing communication cost, energy, power consumption, and latency. Apart from the categorization of the discussed approaches, comparison of communication cost, power, energy, and latency of the NoC system carried out on real applications like VOPD and MPEG4. Moreover, the best technique identified in each category based on the evaluation of performance results.

Objective: To evaluate the effect of open reduction and internal fixation on radial head fracture and assess the post-operative function. Methods: This prospective observational study was conducted from June 2016 to July 2017 at Liaquat National Hospital and Medical College, Karachi. Altogether, 28 patients with radial head and neck fractures were enrolled in our study. These patients were admitted to the hospital and their fractures were fixed with open reduction and internal fixation. Baseline information of the patients was collected, and patient-rated elbow evaluation scores were calculated. Results: Out of the 28 patients, 21 were male and 7 were female. Besides, 16 fractures were on the right side and 12 were on the left side and 17 involving the dominant hands. In addition, 8 patients had Mason type II fracture and 20 had Mason type III fracture. The mean age of patients was (31.0 ± 8.0) years, and the mean follow-up is (1.2 ± 0.5) years. The mean average patient-rated elbow evaluation scores were (27.64 ± 1.60) at 1-year follow-up. Conclusions: The majority of the patients who had radial head fractures and treated by open reduction and internal fixation have attained an excellent range of motion postoperatively.

Small and medium enterprise (SMEs) adds a critical contribution concerning progression in economies in terms of employment and growth irrespective of economies standing and positioning. Trade and industrial resumption afterwards the East Asian crunch of 90s and 2009 international monetary crises influence the economies to establish a sturdier base for local industries especially SMEs. The trade and business sector globally are facing modifications which instigating from modern description of innovation and entrepreneurialism. Which reviving the excellence of production and services, technological advancement, and workplace innovation. Which is imposing pressure on businesses and strategic makers for refurbishment of approaches and stratagems aligned with the domestic business development models. Consequently, inferred a latest prototype for SMEs to enforce businesses to be more dynamic, effectual and up to date. Similarly, SMEs in Pakistan are functioning under constant constraints due to lacking in advancement and evolution in operational, administrative and procedural dominions. Therefore, these forces the need for innovation to deal with challenges effectively and to ensure its existence competitively both in a local and international markets. The purpose of this study was to add significantly in the literature of ‘workplace innovation’ and proposing the model of workplace innovation especially in context of SMEs.

The ever-shrinking size of a transistor has made Network on Chip (NoC) susceptible to faults. A single error in the NoC can disrupt the entire communication. In this paper, we introduce Defender, a fault-tolerant router architecture, that is capable of tolerating permanent faults in all the parts of the router. We intend to employ structural modifications in baseline router design to achieve fault tolerance. In Defender we provide the fault tolerance to the input ports and routing computation unit by grouping the neighboring ports together. Default winner strategy is used to provide fault resilience to the virtual channel arbiters and switch allocators. Multiple routes are provided to the crossbar to tolerate the faults. Defender provides improved fault tolerance to all stages of routers as compared to the currently prevailing fault tolerant router architectures. Reliability analysis using silicon protection factor (SPF) and Mean Time to Failure (MTTF) metrics confirms that our proposed design Defender is 10.78 times more reliable than baseline unprotected router and then the current state of the art architectures.

Purpose This study examined the effect of leverage, debt maturity on corporate financial performance of non-financial firms listed at the Pakistan Stock Exchange. Targeted population of this study was 100 firm listed at PSX as KSE-100 index out of which 74 non-financial firms were selected from 28 different sectors for the period of 5 years 2013 to 2017. Design/Methodology/Approach: Financial performance measured by ROA, ROE, while leverage, short term leverage, long term leverage taken as independent variables, four variables were taken as control which are size, current ratio, sale growth, tangibility. On the basis of Hausman test, results of random effect model were found appropriate. Findings: ST and LT Leverage have a negative significant and insignificant effect on financial performance (ROA) respectively, moreover long term leverage has a positive and significant but short has a negative and insignificant effect on ROE. The results of the control variables showed that size has a negative and significant effect on ROA and ROE, whereas current ratio has insignificant and negative effect on ROA, ROE. Sale growth has a positive and insignificant effect on firms ROA and ROE. Tangibility has insignificant and negative effect on financial performance. Implications/Originality/Value: This study is consistent with traditional trade-off theory and recommended that management of the non-financial firms listed at the PSX should employ minimal debt level or use an optimal level of capital structure and also to attract good management thus to improve their financial performance.

This paper is introducing a new concept of triangular linear Diophantine fuzzy numbers (TLDFNs) in a generic way. We first introduce the concept of TLDFNs and then study the arithmetic operations on these numbers. We find a method for the ranking of these TLDFNs. At the end, we formulate the linear and quadratic equations of the types A+X=B,A·X+B=C, and A·X2+B·X+C=D where the elements A,B,C, and D are TLDFNs. We provide a procedure for the solution of these equations using s,t,u,v-cut and also provide the examples.

The present study reveals contrasting responses of photosynthesis to salt stress in two C4 species: a glycophyte Setaria viridis (SV) and a halophyte Spartina alterniflora (SA). Specifically, the effect of short-term salt stress treatment on the photosynthetic CO2 uptake and electron transport were investigated in SV and its salt-tolerant close relative SA. In this experiment, at the beginning, plants were grown in soil then were exposed to salt stress under hydroponic conditions for two weeks. SV demonstrated a much higher susceptibility to salt stress than SA; while, SV was incapable to survive subjected to about 100 mM, SA can tolerate salt concentrations up to 550 mM with slight effect on photosynthetic CO2 uptake rates and electrons transport chain conductance (gETC). Regardless the oxygen concentration used, our results show an enhancement in the P700 oxidation with increasing O2 concentration for SV following NaCl treatment and almost no change for SA. We also observed an activation of the cyclic NDH-dependent pathway in SV by about 2.36 times upon exposure to 50 mM NaCl for 12 days (d); however, its activity in SA drops by about 25% compared to the control without salt treatment. Using PTOX inhibitor (n-PG) and that of the Qo-binding site of Cytb6/f (DBMIB), at two O2 levels (2 and 21%), to restrict electrons flow towards PSI, we successfully revealed the presence of a possible PTOX activity under salt stress for SA but not for SV. However, by q-PCR and western-blot analysis, we showed an increase in PTOX amount by about 3–4 times for SA under salt stress but not or very less for SV. Overall, this study provides strong proof for the existence of PTOX as an alternative electron pathway in C4 species (SA), which might play more than a photoprotective role under salt stress.

Objective(s): To present a brief overview of various natural sources of antimicrobials with the aim of highlighting invertebrates living in polluted environments as additional sources of antimicrobials. Materials and Methods: A PubMed search using antibacterials, antimicrobials, invertebrates, and natural products as keywords was carried out. In addition, we consulted conference proceedings, original unpublished research undertaken in our laboratories, and discussions in specific forums.Results: Representative of a stupefying 95% of the fauna, invertebrates are fascinating organisms which have evolved strategies to survive germ-infested environments, yet they have largely been ignored. Since invertebrates such as cockroaches inhabit hazardous environments which are rampant with pathogens, they must have developed defense mechanisms to circumvent infections. This is corroborated by the presence of antimicrobial molecules in the nervous systems and hemolymph of cockroaches. Antimicrobial compounds have also been unraveled from the nervous, adipose, and salivary glandular tissues of locusts. Interestingly, the venoms of arthropods including ants, scorpions, and spiders harbor toxins, but also possess multiple antimicrobials.Conclusion: These findings have rekindled the hopes for newer and enhanced therapeutic agents derived from a plentiful and diverse resource to combat fatal infectious diseases. Such antimicrobials from unusual sources can potentially be translated into clinical practice, however intensive research is needed over the next several years to realize these expectations.

Objective: To determine the serum magnesium levels in patients with diabetic retinopathy. Study Design: Descriptive cross sectional study. Place and Duration of Study: Department of Medicine, Combined Military Hospital Lahore, Six months from Nov 2014 to May 2015. Patients and Methods: A total of 50 cases of type 2 Diabetes Mellitus were included in the study. Serum magnesium levels, fasting blood sugar and HbA1c were recorded in all patients. Retinopathy was confirmed by direct Ophthalmoscopy. Results: In our study, out of 50 cases, 30% (n=15) were between 20-40 years of age while 70% (n=35) were between 41-65 years of age. Mean ± SD was calculated as 46.12 ± 7.76 years. Forty-six percent (n=23) were males and 54% (n=27) were females. Mean fasting blood sugar was calculated as 8.06 ± 0.49 mmol/L. Mean HbA1C was calculated as 7.11± 0.30 while mean serum magnesium levels were calculated as 1.15 ± 0.15 mg/dl. Conclusion: Mean magnesium levels in patients with diabetic retinopathy were significantly lower than the magnesium levels that were taken as the reference suggesting a possible role of hypomagnesaemia in increasing the risk of retinopathy amongst patients with diabetes.

Mapping application task graphs on intellectual property (IP) cores into network-on-chip (NoC) is a non-deterministic polynomial-time hard problem. The evolution of network performance mainly depends on an effective and efficient mapping technique and the optimization of performance and cost metrics. These metrics mainly include power, reliability, area, thermal distribution and delay. A state-of-the-art mapping technique for NoC is introduced with the name of sailfish optimization algorithm (SFOA). The proposed algorithm minimizes the power dissipation of NoC via an empirical base applying a shared k-nearest neighbor clustering approach, and it gives quicker mapping over six considered standard benchmarks. The experimental results indicate that the proposed techniques outperform other existing nature-inspired metaheuristic approaches, especially in large application task graphs.

Objective: To compare surgical outcomes of acute acetabular transverse fracture using ilioinguinal and Stoppa approach.Methods: Twenty five patients who managed with ilioinguinal approach (group A) at a mean follow-up of (32.3±4.6) mo and 30 patients who managed with Stoppa approach (group B) at a mean follow-up of (29.7±3.8) mo were prospectively reviewed. The study was approved by the hospital ethical review committee (IRB approval no: 0189-2007). Patients were called for routine follow up and follow-up durations were set. End points of the study were: (1) blood loss was measured intraoperatively by measuring the blood loss in the suction drain and counting blood stained gauze and postoperatively by assessing hemoglobin after 6 h of surgery; (2) functional outcome was demonstrated using the Harris hip score; (3) reduction quality and radiological results were demonstrated by Matta scoring system.Results: Mean blood loss (intraoperatively + postoperatively) was (1 175.8±310.2) mL and (1 115.7±285.1) mL in patients operated with ilioinguinal and Stoppa approach, respectively. Mean operative time was (242.3±60.8) min and (198.9±50.3) min in patients operated with ilioinguinal and Stoppa approach, respectively. Functional outcome, radiological outcome and reduction quality showed no significant difference between two approaches. Complication rate was 36.0% in group A (9 patients) and 13.3% in group B (4 patients).Conclusions: Our study concludes that Stoppa approach allows less blood loss and operative time with fewer complications.

Speech emotion recognition (SER) plays a significant role in human–machine interaction. Emotion recognition from speech and its precise classification is a challenging task because a machine is unable to understand its context. For an accurate emotion classification, emotionally relevant features must be extracted from the speech data. Traditionally, handcrafted features were used for emotional classification from speech signals; however, they are not efficient enough to accurately depict the emotional states of the speaker. In this study, the benefits of a deep convolutional neural network (DCNN) for SER are explored. For this purpose, a pretrained network is used to extract features from state-of-the-art speech emotional datasets. Subsequently, a correlation-based feature selection technique is applied to the extracted features to select the most appropriate and discriminative features for SER. For the classification of emotions, we utilize support vector machines, random forests, the k-nearest neighbors algorithm, and neural network classifiers. Experiments are performed for speaker-dependent and speaker-independent SER using four publicly available datasets: the Berlin Dataset of Emotional Speech (Emo-DB), Surrey Audio Visual Expressed Emotion (SAVEE), Interactive Emotional Dyadic Motion Capture (IEMOCAP), and the Ryerson Audio Visual Dataset of Emotional Speech and Song (RAVDESS). Our proposed method achieves an accuracy of 95.10% for Emo-DB, 82.10% for SAVEE, 83.80% for IEMOCAP, and 81.30% for RAVDESS, for speaker-dependent SER experiments. Moreover, our method yields the best results for speaker-independent SER with existing handcrafted features-based SER approaches.

Real-world business processes are dynamic, with event logs that are generally unstructured and contain heterogeneous business classes. Process mining techniques derive useful knowledge from such logs but translating them into simplified and logical segments is crucial. Complexity is increased when dealing with business processes with a large number of events with no outcome labels. Techniques such as trace clustering and event clustering, tend to simplify the complex business logs but the resulting clusters are generally not understandable to the business users as the business aspects of the process are not considered while clustering the process log. In this paper, we provided a multi-stage hierarchical framework for business-logic driven clustering of highly variable process logs with extensively large number of events. Firstly, we introduced a term contrail processes for describing the characteristics of such complex real-world business processes and their logs presenting contrail-like models. Secondly, we proposed an algorithm Novel Hierarchical Clustering (NoHiC) to discover business-logic driven clusters from these contrail processes. For clustering, the raw event log is initially decomposed into high-level business classes, and later feature engineering is performed exclusively based on the business-context features, to support the discovery of meaningful business clusters. We used a hybrid approach which combines rule-based mining technique with a novel form of agglomerative hierarchical clustering for the experiments. A case-study of a CRM process of the UK’s renowned telecommunication firm is presented and the quality of the proposed framework is verified through several measures, such as cluster segregation, classification accuracy, and fitness of the log. We compared NoHiC technique with two trace clustering techniques using two real world process logs. The discovered clusters through NoHiC are found to have improved fitness as compared to the other techniques, and they also hold valuable information about the business context of the process log.

Network-on-chip (NoC) architectures have become a popular communication platform for heterogeneous computing systems owing to their scalability and high performance. Aggressive technology scaling makes these architectures prone to both permanent and transient faults. This study focuses on the tolerance of a NoC router to permanent faults. A permanent fault in a NoC router severely impacts the performance of the entire network. Thus, it is necessary to incorporate component-level protection techniques in a router. In the proposed scheme, the input port utilizes a bypass path, virtual channel (VC) queuing, and VC closing strategies. Moreover, the routing computation stage utilizes spatial redundancy and double routing strategies, and the VC allocation stage utilizes spatial redundancy. The switch allocation stage utilizes run-time arbiter selection. The crossbar stage utilizes a triple bypass bus. The proposed router is highly fault-tolerant compared with the existing state-of-the-art fault-tolerant routers. The reliability of the proposed router is 7.98 times higher than that of the unprotected baseline router in terms of the mean-time-to-failure metric. The silicon protection factor metric is used to calculate the protection ability of the proposed router. Consequently, it is confirmed that the proposed router has a greater protection ability than the conventional fault-tolerant routers.

Most cancer care is delivered in the community, while most clinical trials exist in academic centers. We analyzed clinical trial accrual of a tertiary care cancer center and its affiliated community sites to better understand what types of trials accrued at the community sites and whether community accrual increased ethnic diversity. The institutional clinical trial database was searched for solid tumor accruals during 2018–2019. Patient’s race was abstracted, and trial’s funding source, phase, and disease type/stage were tabulated. Of 3689 accruals, 133 were at community sites, representing 26 unique trials while the main campus accrued to 93 unique trials. Community site accruals were highest for breast and colorectal cancer, but patients with less common cancers such as renal, nasopharyngeal, and gastric cancer were also accrued at community sites. Accruals occurred to randomized trials, as well as phase Ib and translational biomarker studies. Minority patients constituted 20.0% and 32.5% of community site accruals for therapeutic and non-therapeutic trials respectively, compared to 20.6% and 29.8% of main campus accruals for therapeutic and non-therapeutic trials, respectively. We conclude that community sites affiliated with an academic cancer center can accrue to a broad spectrum of clinical trials while enhancing racial diversity in participation of clinical trials. Further expansion of access to clinical trials in community sites is necessary to broaden patient access to state-of-the-art and next-generation treatment options.

The advent of new devices, technology, machine learning techniques, and the availability of free large speech corpora results in rapid and accurate speech recognition. In the last two decades, extensive research has been initiated by researchers and different organizations to experiment with new techniques and their applications in speech processing systems. There are several speech command based applications in the area of robotics, IoT, ubiquitous computing, and different human-computer interfaces. Various researchers have worked on enhancing the efficiency of speech command based systems and used the speech command dataset. However, none of them catered to noise in the same. Noise is one of the major challenges in any speech recognition system, as real-time noise is a very versatile and unavoidable factor that affects the performance of speech recognition systems, particularly those that have not learned the noise efficiently. We thoroughly analyse the latest trends in speech recognition and evaluate the speech command dataset on different machine learning based and deep learning based techniques. A novel technique is proposed for noise robustness by augmenting noise in training data. Our proposed technique is tested on clean and noisy data along with locally generated data and achieves much better results than existing state-of-the-art techniques, thus setting a new benchmark.

Indicators measuring industrial international competitiveness are being continuously improved. However, so far, there is no unified perfect indicator to measure the level of international competitiveness of the industry. Based on the market share index (MS), trade competitiveness index (TC), revealed comparative advantage index (RCA), and relative trade advantage index (RTA), we constructed a comprehensive international competitiveness index by combining the variation coefficient and the entropy method. This study aims to compare and evaluate the international competitiveness of the wood processing industry (ICWPI) in Vietnam using a comprehensive international competitiveness index. The data is collected from the top 22 countries and the total import and export volume of the wood processing industry from the repository of official international trade statistics (UN Comtrade) database for 2001−2017. The results found that it is more accurate to use the combined variation coefficient and the entropy method to evaluate the international competitiveness of the wood processing industry, compared to using only a single index. The growth rate of international competitiveness of Vietnam increased rapidly from 2001 to 2007 but slowed from 2008 to 2017. Vietnam has the advantages of natural resources, low labor costs and favorable geographical location. However, the low productivity gains and added industry value have led to a gradual decline in the international competitiveness growth rate of Vietnam’s wood processing industry.

In this study, we assessed the impact of the Billion Trees Afforestation Program (BTAP) on the livelihood of local household in Khyber Pakhtunkhwa Province (KPK). BTAP is the largest ban-logging afforestation program in Pakistan, which aims to conserve natural forests, promoting rural livelihoods and reducing poverty. Primary data from 360 local inhabitants were collected and analyzed using descriptive and econometric methodologies that include ordered logit model and ordinary least squares (OLS) respectively. In specific, a wealth index, household income, and five assets of sustainable livelihood have been considered to measure the impact of BTAP. We found that there is a strong and positive contribution of BTAP to the improvement of a rural community’s livelihood. Results showed that BTAP based households earn 4% more income and possess around 35% more assets. These findings suggest that BTAP has considerable effect on increase in livelihood assets. This study continues the discussion with several practical implications of this along with recommendations for future research.