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Abstract Hydromagnetically associated heat convection can greatly enhance the performance of high-efficiency thermal appliances and renewable energy sources through an optimized design. This investigation examines the production of thermodynamic irreversibility and heat convection for a double lid-driven flow within a partially porous stratified hexagonal enclosure. The top and bottom-wall are moving in the opposite direction with an equal velocity U0. The top-wall and the bottom-wall are kept at temperature Tc and Th (Th $$>$$ > Tc) while the slanted walls are assumed to be thermally insulated. A constant magnetic field is employed in the horizontal x-direction. The hexagonal cavity was filled with a micropolar hybrid nanofluid Ag-MgO/water. The system of dimensionless equations was solved by the finite difference method (FDM) associated with successive over-relaxation (SOR), successive under-relaxation (SUR), and Gauss–Seidel iteration tactics and required results are computed with problem specific program in MATLAB code. The results indicate that the Ra and the thickness of the porous layer (Xp) significantly influences heat convection and thermal irreversibility processes. The Nuavg and STotal rises 6.299% and 3.373% as ‘ $${\upphi }_{{\text{hnf}}}$$ ϕ hnf ’ enhances from 0 to 4%, respectively. Furthermore, as the values of Ra, Ha, K0, and $${\upphi }_{{\text{hnf}}}$$ ϕ hnf increase, Beavg experiences a decline of 53.73%, 11.04%, 38.36%, and 0.09% respectively. Also, movement of wall has a significant impact on heat transfer rates and entropy production. The present study may be extended in numerous areas to mimic the problems like—(1) onset of thermo-mechanical process for solid–fluid interaction in a conduit. (2) Thermos-chemical process with extraction of ions in two-phase fluid for double layer plating on a continuously moving sheet, as region of porous stratum saturated with a class of fluid and region without porous medium occupied with other fluid.

6G mobile network technology will set new standards to meet performance goals that are too ambitious for 5G networks to satisfy. The limitations of 5G networks have been apparent with the deployment of more and more 5G networks, which certainly encourages the investigation of 6G networks as the answer for the future. This research includes fundamental privacy and security issues related to 6G technology. Keeping an eye on real-time systems requires secure wireless sensor networks (WSNs). Denial of service (DoS) attacks mark a significant security vulnerability that WSNs face, and they can compromise the system as a whole. This research proposes a novel method in blockchain 6G-based wireless network security management and optimization using a machine learning model. In this research, the deployed 6G wireless sensor network security management is carried out using a blockchain user datagram transport protocol with reinforcement projection regression. Then, the network optimization is completed using artificial democratic cuckoo glowworm remora optimization. The simulation results have been based on various network parameters regarding throughput, energy efficiency, packet delivery ratio, end–end delay, and accuracy. In order to minimise network traffic, it also offers the capacity to determine the optimal node and path selection for data transmission. The proposed technique obtained 97% throughput, 95% energy efficiency, 96% accuracy, 50% end–end delay, and 94% packet delivery ratio.

ABSTRACTThe intermittent network connectivity and unawareness of global network knowledge are remarkable challenges when designing efficient Position-based Opportunistic Routing (POR) for Delay Tolerant Networks (DTNs). The best progress set selection of POR effectively handles the intermittent connectivity issue and improves the reliable performance of DTNs. Hence, the optimal progress set selection and catching capacity decide the routing reliability of DTN-POR. This paper proposes a context-aware DTN-POR protocol STAP to ensure reliable DTN routing with minimum overhead STAP design is divided into three folds: application diversity and network failures, context-aware best progress set selection, and enhanced caching management. The application diversity and network failure switch the nodes in harsh environments to DTN mode for transmitting the data packets successfully to the destination. Selecting context-aware relay nodes ensures highly successful data transmissions in the absence of end-to-end connectivity. The probability estimation maximizes the data reachability by considering unique node and application-level context attributes in the best progressive set. Finally, the enhanced catching management strategy limits the number of data copies with effective catch invalidation, resulting in minimum overhead. The proposed STAP accomplishes better results in different scenarios and improves the packet delivery ratio with a minimum duplication rate.

Wireless sensor networks (WSNs) enable communication among sensor nodes and require efficient energy management for optimal operation under various conditions. Key challenges include maximizing network lifetime, coverage area, and effective data aggregation and planning. A longer network lifetime contributes to improved data transfer durability, sensor conservation, and scalability. In this paper, an enhanced dual-selection krill herd (KH) optimization clustering scheme for resource-efficient WSNs with minimal overhead is introduced. The proposed approach increases overall energy utilization and reduces inter-node communication, addressing energy conservation challenges in node deployment and clustering for WSNs as optimization problems. A dynamic layering mechanism is employed to prevent repetitive selection of the same cluster head nodes, ensuring effective dual selection. Our algorithm is designed to identify the optimal solution through enhanced exploitation and exploration processes, leveraging a modified krill-based clustering method. Comparative analysis with benchmark approaches demonstrates that the proposed model enhances network lifetime by 23.21%, increases stable energy by 19.84%, and reduces network latency by 22.88%, offering a more efficient and reliable solution for WSN energy management.

Information Technology’s development increases day by day, making life easier in terms of work and progress. In these developments, knowledge management is becoming mandatory in all the developing sectors. However, the conventional model for growth analysis in organizations is tedious as data are maintained in ledgers, making the process time consuming. Media Ecology, a new trending technology, overcomes this drawback by being integrated with artificial intelligence. Various sectors implement this integrated technology. The marketing strategy of Huawei Technologies Co. Ltd. is analyzed in this research to examine the advantages of Media Ecology Technology in integration with artificial intelligence and a Knowledge Management Model. This combined model supports sensor technology by considering each medium, the data processing zone, and user location as nodes. A Q-R hybrid simulation methodology is implemented to analyze the data collected through Media Ecology. The proposed method is compared with the inventory model, and the results show that the proposed system provides increased profit to the organization. Paying complete attention to Artificial intelligence without the help of lightweight deep learning models is impossible. Thus, lightweight deep models have been introduced in most situations, such as healthcare management, maintenance systems, and controlling a few IoT devices. With the support of high-power consumption as computational energy, it adapts to lightweight devices such as mobile phones. One common expectation from the deep learning concept is to develop an optimal structure in case time management.

Agriculture is the backbone of any developing or developed country that makes any living to survive. To make food available throughout the year, it is necessary to know about agriculture and the work and strategies involved. Hence, agricultural courses have to be introduced to higher education students. Additionally, agriculture-related methods are available in many higher education institutions for longer. However, students and teachers will face difficulties in real-time practical classes during certain challenging circumstances. These situations require the teacher to utilize trending technologies to improve the teaching and learning process and to make it more manageable. In this study, for this process, a novel neural network-based recognition algorithm (NN-RA) is implemented that works similarly to a backpropagation neural network (BP-NN) to provide a practical agriculture course. The proposed BP-NN is compared with the existing NN-RA, I-SC, and I-VDT algorithms based on the data transfer and signal-to-noise ratio. From the results, it can be observed that the proposed BP-NN attains a higher accuracy in data transfer of 99%.

The present study aimed to investigate the incidence of Methicillin-Resistant Staphylococcus aureus strains (MRSA) and inducible clindamycin resistant S. aureus (ICRSA) among postoperative wound infected patients. A total of 94 S. aureus strains were isolated by conventional laboratory methods from 135 swab samples collected from post-operative wound infected patients in Khartoum State hospitals. The isolated strains were screened for MRSA by using cefoxitin disc. ICRSA strains was detected by D-test and their susceptibility to antimicrobial agents was done by modified Kirby-Bauer’s disc diffusion method. Ninety-four S. aureus isolates were screened for MRSA strains, we found 42 (45%) of isolates were MRSA and 52 (55%) of strains were methicillin-sensitive S. aureus (MSSA) phenotype. The incidence of ICRSA, constitutive clindamycin resistant (CCRSA) and erythromycin resistant (ERSA) strains among S. aureus isolates were 15.9% (15/94), 9% (8/94) and 2.12% (2/94), respectively. ICRSA resistant strains were slightly more frequent among MRSA, when compared with MSSA strains (16.67% (7/42) vs. 15.38% (8/52)). In addition, 33% of ICRSA strains were found resistant to both co-trimoxazole and gentamicin, while, 23% of strains were resistant to vancomycin. This study concluded that MRSA strains was nearly accounted a half of clinical isolates, which need more attention by improving hospitals environment heath quality. ICRSA isolates were detected within both MRSA and MSSA strains and the D test must be implemented as routine susceptibility test to avoided clindamycin treatment failure.

Fifty-four patients taking minocycline for acne or rosacea were assessed for adverse effects. Their mean duration of treatment was 17 months, and their average cumulative dose was 47 g. No symptoms attributable to the therapy were reported. Biochemistry and haematology profiles were normal. There was no evidence of an adverse effect on thyroid function. Skin pigmentation was detected in eight patients (14·8%). Five patients had diffuse facial pigmentation, and three patients had localized pigmentation at the site of a scar or injury. Diffuse pigmentation occurred only in patients who had been on treatment for 3 years or more: 50% of such patients were affected. Age and solar damage may also have been factors in this type of pigmentation. Localized pigmentation occurred at sites of previous tissue damage, and was not directly related to the duration of therapy. Patients who receive long-term minocycline therapy should be regularly monitored for the development of pigmentation. [ABSTRACT FROM AUTHOR]

We report a patient with severe Crohn's disease and the short bowel syndrome on parenteral feeding who was not responding to conventional therapy and underwent treatment with cyclosporin (CyA) given initially intravenously and subsequently orally in each of two courses. Plasma drug concentrations were largely kept within the therapeutic range but wide variability was observed on oral therapy. Improvement both clinically and by objective assessment, was observed on intravenous CyA therapy, but was not sustained when the drug was given orally for several months. None of the side effects observed resisted treatment or was severe enough to warrant discontinuation of therapy. These findings suggest that there may be a place for intravenous CyA therapy in patients with severe Crohn's disease who do not respond to conventional therapy or to oral treatment with CyA. [ABSTRACT FROM PUBLISHER]

Basal ganglia calcification was found as an incidental finding in 42 out of 7000 patients who underwent computed tomography. The calcification showed on plain skull radiography when the maximum density on computed tomography exceeded 100 Hounsfield units. The 26 patients with basal ganglia calcification detected on computed tomography who were available for follow-up, were investigated with matched controls. No clinical features of basal ganglia calcification were noted. Twenty-four patients had no significant metabolic abnormality and two patients had parathyroid disorder identified. [ABSTRACT FROM AUTHOR]

Sinus histiocytosis with massive lymphadenopathy is a distinct clinical entity, with ophthalmic involvement in 10% of patients. Orbital as well as eyelid lesions have been described as part of the extra-lymph node involvement of this disorder. We recently examined a young boy with sinus histiocytosis with a bulbar conjunctival mass and chronic dacryocystitis. [ABSTRACT FROM PUBLISHER]