A natural heme deficiency that exists in cells outside of the circulation broadly compromises the heme contents and functions of heme proteins in cells and tissues. Recently, we found that the signaling molecule, nitric oxide (NO), can trigger or repress the deployment of intracellular heme in a concentration‐dependent hormetic manner. This uncovers a new role for NO and sets the stage for it to shape numerous biological processes by controlling heme deployment and consequent heme protein functions in biology.

The increasing global demand for energy necessitates devoted attention to the formulation and exploration of mechanisms of thermal heat exchangers to explore and save heat energy. Thus, innovative thermal transport fluids require to boost thermal conductivity and heat flow features to upsurge convection heat rate, and nanofluids have been effectively employed as standard heat transfer fluids. With such intention, herein, we formulated and developed the constitutive flow laws by utilizing the Rossland diffusion approximation and Stephen’s law along with the MHD (...) effect. The mathematical formulation is based on boundary layer theory pioneered by Prandtl. Governing nonlinear partial differential flow equations are changed to ODEs via the implementation of the similarity variables. A well-known computational algorithm BVPh2 has been utilized for the solution of the nonlinear system of ODEs. The consequence of innumerable physical parameters on flow field, thermal distribution, and solutal field, such as magnetic field, Lewis number, velocity parameter, Prandtl number, drag force, Nusselt number, and Sherwood number, is plotted via graphs. Finally, numerical consequences are compared with the homotopic solution as a limiting case, and an exceptional agreement is found. (shrink)

Caffeine, a known CNS stimulant is given as an adjunct component in most abused drugs which could be fatal with repeated administration in many circumstances. This paper presents a study to investigate the effect of repeated administration of caffeine at high dose on rat liver, and discusses ethical and policy issues of caffeine use. Long Evans rats were treated with pure caffeine solution in distilled water through intragastric route once daily for consecutive 56 days. Three groups of rats recognized as (...) low dose, high dose and control group received 6mg caffeine / kg BW, 12mg caffeine / kg BW and distilled water, respectively. Rat plasma was examined for liver transaminases and alkaline phosphatases concentrations which were significantly increased in plasma as compared to the control. Both rat plasma and liver homogenate were subjected to estimate malondialdehyde, advanced oxidation protein product, nitric oxide, antioxidant enzyme catalase, glutathione and superoxide dismutase activity. MDA, AOPP, NO levels increased and SOD activity decreased significantly in both plasma and liver as compared to those of control where as CAT and GSH activity remain unchanged. Rat liver tissues were studied histochemically with Hematoxylin and Eosin, and Picro Sirius Red staining. Significantly increased infiltration of inflammatory cells and progressive deposition of collagen fibre were visible in liver tissue of caffeine treated both dose groups as compared to the control. Long term administration of caffeine at higher dose, significantly contributes to liver inflammation and consequent fibrogenesis. This raises significant ethical and policy issues. (shrink)

As the world keeps advancing, the need for automated interconnected devices has started to gain significance; to cater to the condition, a new concept Internet of Things has been introduced that revolves around smart devicesʼ conception. These smart devices using IoT can communicate with each other through a network to attain particular objectives, i.e., automation and intelligent decision making. IoT has enabled the users to divide their household burden with machines as these complex machines look after the environment variables and (...) control their behavior accordingly. As evident, these machines use sensors to collect vital information, which is then the complexity analyzed at a computational node that then smartly controls these devicesʼ operational behaviors. Deep learning-based guessing attack protection algorithms have been enhancing IoT security; however, it still has a critical challenge for the complex industries’ IoT networks. One of the crucial aspects of such systems is the need to have a significant training time for processing a large dataset from the networkʼs previous flow of data. Traditional deep learning approaches include decision trees, logistic regression, and support vector machines. However, it is essential to note that this convenience comes with a price that involves security vulnerabilities as IoT networks are prone to be interfered with by hackers who can access the sensor/communication data and later utilize it for malicious purposes. This paper presents the experimental study of cryptographic algorithms to classify the types of encryption algorithms into the asymmetric and asymmetric encryption algorithm. It presents a deep analysis of AES, DES, 3DES, RSA, and Blowfish based on timing complexity, size, encryption, and decryption performances. It has been assessed in terms of the guessing attack in real-time deep learning complex IoT applications. The assessment has been done using the simulation approach and it has been tested the speed of encryption and decryption of the selected encryption algorithms. For each encryption and decryption, the tests executed the same encryption using the same plaintext for five separate times, and the average time is compared. The key size used for each encryption algorithm is the maximum bytes the cipher can allow. To the comparison, the average time required to compute the algorithm by the three devices is used. For the experimental test, a set of plaintexts is used in the simulation—password-sized text and paragraph-sized text—that achieves target fair results compared to the existing algorithms in real-time deep learning networks for IoT applications. (shrink)

Numerous organizations have faced substantial environmental performance challenges resulting from more than a half-century of worldwide industrialization. Grounded in social learning theory and recourse-based view theory, this study explores environmental performance and its impact on employees and industry outcomes. Drawing on a cross-sectional online survey of 500 full-time employees working in the chemical industry in Lahore, Pakistan. The results revealed a significant positive influence of Green HRM practices on employees’ Green innovation as well as on environmental performance. Additionally, significant influences (...) of study variables were recorded on outcomes such as green compensation and reward, green performance management and appraisal, green training and development, and green recruitment and selection. Several key policy insights related to consumer resistance to innovation in low income societies and future research directions are suggested, along with theoretical and practical implications. (shrink)

Psychotherapists and counsellors confront several ethical dilemmas as they tend to provide effective services. There has been much debate among psychotherapists and counsellors alike around the utility of therapeutic contracts. Some view contracts as being restrictive to the therapeutic process and often hindering the work done in sessions. In contrast, many counsellors and psychotherapists use those agreements to revisit specific therapeutic topics and establish the guidelines necessary for this professional arrangement. No matter the opinion or preference of contracts, the development (...) of written and/or verbal consent of specific topics in psychotherapy remains essential. This remains one of the formal features of the arrangement and starting relationship in current counselling and psychotherapy practice. This paper aims to discuss the necessity and ethical demand of therapeutic contract in counselling and psychotherapy practice. (shrink)