A new explicit numerical scheme for enhancement of heat transfer in Sakiadis flow of micro polar fluid using electric field.

This article suggests a fourth-order numerical approach for solving ordinary differential equations (ODEs) that are both linear and nonlinear. The suggested scheme is an explicit predictor-corrector scheme. For linear ODE, the proposed numerical scheme's stability area is discovered. The proposed strategy yields the same stability region as the traditional fourth-order Runge-Kutta method. In addition, partial differential equations (PDEs) are used to develop the mathematical model for the flow of non-Newtonian micro-polar fluid over the sheet and heat and mass transit using electric field effects. These PDEs are further transformed into dimensionless boundary value problems. Boundary value problems are resolved using the proposed shooting-based scheme. The findings show that increasing values of ion kinetic work and Joule heating parameters cause the temperature profile to climb. The results produced by the suggested strategy are compared to those discovered through earlier studies. The results of this study could serve as a starting point for future fluid-flow investigations in a secure industrial environment.

Recognizing Brain Tumors Using Adaptive Noise Filtering and Statistical Features.

The human brain, primarily composed of white blood cells, is centered on the neurological system. Incorrectly positioned cells in the immune system, blood vessels, endocrine, glial, axon, and other cancer-causing tissues, can assemble to create a brain tumor. It is currently impossible to find cancer physically and make a diagnosis. The tumor can be found and recognized using the MRI-programmed division method. It takes a powerful segmentation technique to produce accurate output. This study examines a brain MRI scan and uses a technique to obtain a more precise image of the tumor-affected area. The critical aspects of the proposed method are the utilization of noisy MRI brain images, anisotropic noise removal filtering, segmentation with an SVM classifier, and isolation of the adjacent region from the normal morphological processes. Accurate brain MRI imaging is the primary goal of this strategy. The divided section of the cancer is placed on the actual image of a particular culture, but that is by no means the last step. The tumor is located by categorizing the pixel brightness in the filtered image. According to test findings, the SVM could partition data with 98% accuracy.

Has the Landscape of Immunotherapy for Prostate Cancer Changed? A Systematic Review and Post Hoc Analysis.

Prostate cancer (PCa) is the second leading cause of cancer-causing death in the United States. As the most common malignancy in men, it is pertinent to explore whether novel immunotherapies may improve the quality of life and overall survival (OS) of patient populations. This systematic review and post hoc analysis curates a patient-by-patient pool of evidence adhering to PRISMA Statement 2020 guidelines. In total, 24 patients were analyzed for treatment history and associated variables including prostate-specific antigen (PSA) levels at diagnosis and post-treatment, Gleason score, secondary tumor locations, success/failure of therapy, and post-immunotherapy outcomes including OS. In total, 10 types of immunotherapies were identified with Pembrolizumab (among 8 patients) followed by IMM-101 (among 6 patients) being the most commonly administered. The mean OS for all patients was 27.8 months (24 patients) with the relatively highest mean OS reported with IMM-101 (56 months) followed by tumor-infiltrating lymphocytes (30 months). This research article provides critical insights into the evolving landscape of immunotherapies being tested for PCa and addresses gaps in oncological research to advance the understanding of PCa.

Design and performance analysis of salinity gradient solar pond under different climatic and soil conditions.

A salinity gradient solar pond (SGSP) is capable of storing a significant quantity of heat for an extended period of time. It is a great option for providing hot water at a reduced energy cost. Additionally, SGSP is used in low-temperature industrial applications such as saltwater desalination, space heating, and power generation. Solar pond thermal performance is dependent on a variety of operational variables, including the soil conditions, the climate of the particular site, the thickness of the solar pond layers, the depth of the water table, and the salt content of the pond. As such, this study examines the thermal performance of a solar pond under a variety of operational conditions. The solar pond model is used to test the thermal performance by simulating two-dimensional heat and mass transport equations. The equations are solved using the finite difference technique utilizing MATLAB® scripts. Salt distributions and temperature profiles are computed for a variety of factors influencing SGSP's thermal performance. The main distinguishing variables influencing the thermal performance of SGSP are soil conditions, such as soil texture, types, the moisture level in soil, and water table depth. The final findings indicated that the fine sand dry soil performed better than the other soil types owing to its poor heat conductivity. The economic results indicated that the period of return (POR) of the intended system is around 2 years. The solar pond construction costs such as excavation, transportation, salt and lining, were considered based on the local prices. This modeled study extracted the greatest possible energy is 110W/m2, with the fine sand dry at 62.48°C lowest temperature. This study suggested that the climatic conditions of Lahore is better than climatic conditions of Islamabad. Additionally, deeper water tables are suggested for improved thermal performance of the pond.

How do energy prices and climate shocks affect human health? Insights from BRICS.

The presented work analyzes the energy prices, climate shock, and health deprivation nexus in the BRICS economies for the period 1995-2020. Panel ARDL-PMG technique is used to reveal the underexplored linkages. The long-run estimates of energy prices are observed to be negatively significant to the health expenditure and life expectancy model, whereas, positively significant to the climate change model. These findings suggest that energy prices significantly reduce health expenditures and life expectancy and, thus, increase the death rate in the BRICS economies. The long-run country-wise estimate of energy prices is found negatively significant in case of Brazil, India, China, and South Africa. Alongside, the group-wise significance of CO2 emissions is discovered to be negatively, positively, and insignificant in the cases of life expectancy, death rate, and health expenditure models, respectively. Besides, country-wise long-run estimate of CO2 emissions witnesses negative significance for Russia, India, China, and South Africa.

A Novel Image Encryption Technique Based on Cyclic Codes over Galois Field.

In the modern world, the security of the digital image is vital due to the frequent communication of digital products over the open network. Accelerated advancement of digital data exchange, the importance of information security in the transmission of data, and its storage has emerged. Multiple uses of the images in the security agencies and the industries and the security of the confidential image data from unauthorized access are emergent and vital. In this paper, Bose Chaudhary Hocquenghem (BCH) codes over the Galois field are used for image encryption. The BCH codes over the Galois field construct MDS (maximum distance separable) matrices and secret keys for image encryption techniques. The encrypted image is calculated, by contrast, correlation, energy, homogeneity, and entropy. Histogram analysis of the encrypted image is also assured in this paper. The proposed image encryption scheme's security analysis results are improved compared to the original AES algorithm. Further, security agencies can utilize this work for their confidential image data.

Development of Explicit Schemes for Diffusive SEAIR COVID-19 Epidemic Spreading Model: An Application to Computational Biology.

In this contribution, a first-order time scheme is proposed for finding solutions to partial differential equations (PDEs). A mathematical model of the COVID-19 epidemic is modified where the recovery rate of exposed individuals is also considered. The linear stability of the equilibrium states for the modified COVID-19 model is given by finding its Jacobian and applying Routh-Hurwitz criteria on characteristic polynomial. The proposed scheme provides the first-order accuracy in time and second-order accuracy in space. The stability of the proposed scheme is given using the von Neumann stability criterion for standard parabolic PDEs. The consistency for the proposed scheme is also given by expanding the involved terms in it using the Taylor series. The scheme can be used to obtain the condition of getting a positive solution. The stability region of the scheme can be enlarged by choosing suitable values of the contained parameter. Finally, a comparison of the proposed scheme is made with the existing non-standard finite difference method. The results indicate that the non-standard classical technique is incapable of preserving the unique characteristics of the model's epidemiologically significant solutions, whereas the proposed approaches are capable of doing so. A computational code for the proposed discrete model scheme may be made available to readers upon request for convenience.

EEG in game user analysis: A framework for expertise classification during gameplay.

Video games have become a ubiquitous part of demographically diverse cultures. Numerous studies have focused on analyzing the cognitive aspects involved in game playing that could help in providing an optimal gaming experience by improving video game design. To this end, we present a framework for classifying the game player's expertise level using wearable electroencephalography (EEG) headset. We hypothesize that expert and novice players' brain activity is different, which can be classified using frequency domain features extracted from EEG signals of the game player. A systematic channel reduction approach is presented using a correlation-based attribute evaluation method. This approach lead us in identifying two significant EEG channels, i.e., AF3 and P7, among fourteen channels available in Emotiv EPOC headset. In particular, features extracted from these two EEG channels contributed the most to the video game player's expertise level classification. This finding is validated by performing statistical analysis (t-test) over the extracted features. Moreover, among multiple classifiers used, K-nearest neighbor is the best classifier in classifying game player's expertise level with a classification accuracy of up to 98.04% (without data balancing) and 98.33% (with data balancing).

A decentralized hybrid computing consumer authentication framework for a reliable drone delivery as a service.

The thriving adoption of drones for delivering parcels, packages, medicines, etc., is surging with time. The application of drones for delivery services results in faster delivery, fuel-saving, and less energy consumption. Giant companies like Google, Amazon, Facebook, etc., are actively working on developing, testing, and improving drone-based delivery systems. So far, a lot of work has been done for improving the design, speed, operating range, security of the delivery drones, etc. However, very limited work has been done to ensure a complete and reliable last-mile delivery from the merchant's store to the hands of the actual customer. To ensure a complete and reliable last-mile delivery, a drone must authenticate the consumer before dropping the package. Therefore, in this work, we propose a consumer authentication (Consumer-Auth) hybrid computing framework for drone delivery as a service to make sure that the parcel is perfectly delivered to the intended customer. The proposed Consumer-Auth framework enables a drone to reach the exact destination by using the GPS coordinates of the customer autonomously. After reaching the exact location, the drone waits for the customer to come to the specific pinned location then it starts a two-factor consumer authentication process, i.e., one-time password (OTP) verification and face Recognition. The experimental results manifest the effectiveness of the proposed Consumer-Auth framework to ensure a complete and reliable drone-based last-mile delivery.

CRISPR-Cas13a mediated targeting of hepatitis C virus internal-ribosomal entry site (IRES) as an effective antiviral strategy.

Hepatitis C is an inflammatory liver disease caused by the single-stranded RNA (ssRNA) hepatitis C virus (HCV). The genetic diversity of the virus and quasispecies produced during replication have resulted in viral resistance to direct-acting antivirals (DAAs) as well as impediments in vaccine development. The recent adaptation of CRISPR-Cas as an alternative antiviral approach has demonstrated degradation of viral nucleic acids in eukaryotes. In particular, the CRISPR-effector Cas13 enzyme has been shown to target ssRNA viruses effectively. In this work, we have employed Cas13a to knockdown HCV in mammalian cells. Using a computational screen, we identified several potential Cas13a target sites within highly conserved regions of the HCV internal ribosomal entry site (IRES). Our results demonstrate significant inhibition of HCV replication as well as translation in huh-7.5 cells with minimal effects on cell viability. These findings were validated using a multi-modality approach involving qRT-PCR, luciferase assay, and MTT cell viability assay. In conclusion, the CRISPR-Cas13a system efficiently targets HCV in vitro, suggesting its potential as a programmable therapeutic antiviral strategy.

Evolution of efficacious pangenotypic hepatitis C virus therapies.

Hepatitis C compromises the quality of life of more than 350 million individuals worldwide. Over the last decade, therapeutic regimens for treating hepatitis C virus (HCV) infections have undergone rapid advancements. Initially, structure-based drug design was used to develop molecules that inhibit viral enzymes. Subsequently, establishment of cell-based replicon systems enabled investigations into various stages of HCV life cycle including its entry, replication, translation, and assembly, as well as role of host proteins. Collectively, these approaches have facilitated identification of important molecules that are deemed essential for HCV life cycle. The expanded set of putative virus and host-encoded targets has brought us one step closer to developing robust strategies for efficacious, pangenotypic, and well-tolerated medicines against HCV. Herein, we provide an overview of the development of various classes of virus and host-directed therapies that are currently in use along with others that are undergoing clinical evaluation.

A lightweight and secure two factor anonymous authentication protocol for Global Mobility Networks.

Global Mobility Networks(GLOMONETs) in wireless communication permits the global roaming services that enable a user to leverage the mobile services in any foreign country. Technological growth in wireless communication is also accompanied by new security threats and challenges. A threat-proof authentication protocol in wireless communication may overcome the security flaws by allowing only legitimate users to access a particular service. Recently, Lee et al. found Mun et al. scheme vulnerable to different attacks and proposed an advanced secure scheme to overcome the security flaws. However, this article points out that Lee et al. scheme lacks user anonymity, inefficient user authentication, vulnerable to replay and DoS attacks and Lack of local password verification. Furthermore, this article presents a more robust anonymous authentication scheme to handle the threats and challenges found in Lee et al.'s protocol. The proposed protocol is formally verified with an automated tool(ProVerif). The proposed protocol has superior efficiency in comparison to the existing protocols.

Immunomodulatory and therapeutic role of Cinnamomum verum extracts in collagen-induced arthritic BALB/c mice.

ETHNOPHARMACOLOGICAL RELEVANCE: Cinnamomum verum (CV), also known as 'Dalchini', is the dry bark of the Cinnamomum verum (L.) plant, and has been used as a traditional Pakistani medicine to alleviate pain and inflammation in patients suffering from arthritic rheumatism. It contains alkaloids, triterpenes, Cinnamaldehyde and other volatile oils. The aim of the present study was to investigate the underlying biological effect of ethyl alcohol (EtOH) and methyl alcohol (MeOH) extracts from CV on collagen type-II induced arthritic (CIA) mice. MATERIALS AND METHODS: Gas chromatography mass spectrophotometry was used to perform fingerprinting identification of the EtOH and MeOH extracts. CIA mice model was established by subdermal injections of type-II bovine collagen (CII) on the 1st, 8th and 14th day of the experiment. Ethyl alcohol extract and methyl alcohol extract (1 mg/KgBW, 2 mg/KgBW and 4 mg/KgBW), was orally administered from the 15th day onwards for 2 weeks. Progression of oedema and joint inflammation was measured in the paws using a digital Vernier calliper every 3 days from day 1 till the end of the experiment. The oxidative scavenging ability of cinnamaldehyde was evaluated using a DPPH assay. Similarly, the nitrogen free radical (NOS) production of isolated lymphocytes was evaluated using Greiss's method. The spleen index was calculated and knee joint changes were observed by histopathological sectioning. Western blot analysis was performed on peripheral blood derived serum for CII, CAPN1, TNFα and NFATc3. RESULTS: Extracts were shown to be enriched in trans-cinnamaldehyde and its analogues. Extracts showed good ameliorative effects (p < 0.05) after day 2 of treatment. A greater therapeutic role was observed for the 4 mg/kgBW dosage of the methanolic extract (p < 0.01). Swelling in the spleen was greatly reduced along with the generation of free radicals by lymphocytes, post treatment. There was also an inhibitory role by the extracts on NFATc3 (p < 0.05), TNF-Alpha (p < 0.05), CAII (p < 0.05) and mCalpain (p < 0.05) all proteins involved in RA. CONCLUSION: In this study, it has been demonstrated that administration of CV has a therapeutic potential on CIA. The data suggest that CV could have a potential role in the treatment of RA patients.

Role of circulatory microRNAs in the pathogenesis of hepatitis C virus.

Hepatitis C virus (HCV) is associated with one of the major health problem in world that ultimate results in the liver cirrhosis and leads to carcinoma of hepatocellular components round the world. More than 185 million people were found to be infected with HCV. MicroRNAs are small oligonucleotide RNA having 18-22 nucleotides. Circulating mi-RNAs regulate the replication of HCV and HCV-induced liver fibrosis and HCC. By comparing the expression profiles of mi-RNAs of normal individuals with HCV infected patients, aberrant changes in expression of different mi-RNAs have been observed so it can be predicted that these mi-RNAs are associated with and play a central role in the hepatitis C infection and diseases associated with it. This review demonstrates the major role of circulatory microRNAs in the HCV and HCV associated ailments.

Polymorphisms in DNA repair genes XRCC1 and OGG1 lead to the progression of rheumatoid arthritis in Pakistani patients.

This study points at the elucidation of a possible association of Rheumatoid arthritis (RA) with Ser326Cys in OGG1 Arg194Trp and Arg399Gln polymorphisms of XRCC1 using a sample size of 100 patients and 100 controls from a Pakistani population. This association was determined using Random Fragment Length Polymorphism Analysis as well as the DAS scoring system. In RA, oxidative damage due to free radical production leads to destructive proliferative synovitis showing cellular transformations of synoviocytes into a tumorigenic state. XRCC1 and OGG1 genes, which are part of the DNA Break Excision Repair pathway, manifest various polymorphisms which may cause a variation in the response to inflammation by changing DNA repair potential. Our results showed a significant association between the DAS28 score values as well as the genotypic state of the RA patients. It was seen that the score was significantly higher in GG genotypes thereby corroborating the role of the polymorphism XRCC1 Arg399Gln. Using a Pearson's correlation test it was found to be <0.000003. It has been shown by the results in this research that an increased risk of DNA damage exists when the polymorphic genotypes studied, exist in a RA patient.