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Fulltext Enhancing automotive cooling systems: composite fins and nanoparticles analysis in radiators

Ramesh Kumar R, Karthik K, Elumalai PV, Elumalai R, Chandran D, Prakash E, et al.

Sci Rep, 2024 Feb 13;14(1):3650.
PMID: 38351203 DOI: 10.1038/s41598-024-52141-0

Composites are driving positive developments in the automobile sector. In this study investigated the use of composite fins in radiators using computational fluid dynamics (CFD) to analyze the fluid-flow phenomenon of nanoparticles and hydrogen gas. Our world is rapidly transforming, and new technologies are leading to positive revolutions in today's society. In this study successfully analyzed the entire thermal simulation processes of the radiator, as well as the composite fin arrangements with stress efficiency rates. The study examined the velocity path, pressure variations, and temperature distribution in the radiator setup. As found that nanoparticles and composite fins provide superior thermal heat rates and results. The combination of an aluminum radiator and composite fins in future models will support the control of cooling systems in automotive applications. The final investigation statement showed a 12% improvement with nanoparticles, where the velocity was 1.61 m/s and the radiator system's pressure volume was 2.44 MPa. In the fin condition, the stress rate was 3.60 N/mm2.
Fulltext Author Correction: Enhancing automotive cooling systems: composite fins and nanoparticles analysis in radiators

Ramesh Kumar R, Karthik K, Elumalai PV, Elumalai R, Chandran D, Prakash E, et al.

Sci Rep, 2024 Mar 05;14(1):5467.
PMID: 38443484 DOI: 10.1038/s41598-024-56013-5
Three week compared to seven week run-in period length and the assessment of pre-randomization adherence: A study within a trial

Collister D, Mbuagbaw L, Guyatt G, Devereaux PJ, Tennankore KK, Reis G, et al.

Contemp Clin Trials, 2021 08;107:106466.
PMID: 34098039 DOI: 10.1016/j.cct.2021.106466

BACKGROUND/AIMS: To examine how measuring adherence at 3 weeks by self-report and pill counts compares to measurements at 7 weeks in a pre-randomization run-in period.
METHODS: Study within a trial of an international parallel group randomized controlled trial (RCT) that compares spironolactone to placebo. Adults receiving dialysis enter an 8-week active run-in period with spironolactone. Adherence was assessed by both self-report and pill counts in a subgroup of participants at both 3 weeks and 7 weeks.
RESULTS: 332 participants entered the run-in period of which 166 had complete data. By self-report, 146/166 (94.0%) and 153/166 (92.2%) had at least 80% adherence at 3 and 7 weeks respectively (kappa = 0.27 (95% C.I. 0.16 to 0.38). By pill counts, the mean (SD) adherence was 96.5% (16.1%) and 92.4% (18.2%) at 3 and 7 weeks respectively (r = 0.32) with a mean (SD) difference of 3.1% (17.8%) and a 95% limit of agreement from -31.7% to +37.9%. The proportion of adherent participants by self-report and pill counts at 3 weeks agreed in 87.4% of participants (McNemar's p-value 0.58, kappa 0.11, p = 0.02) and at 7 weeks agreed in 92.2% (McNemar's p-value 0.82, kappa 0.47, p
Fulltext Predicting the thermal distribution in a convective wavy fin using a novel training physics-informed neural network method

Chandan K, Saadeh R, Qazza A, Karthik K, Varun Kumar RS, Kumar RN, et al.

Sci Rep, 2024 Mar 25;14(1):7045.
PMID: 38528081 DOI: 10.1038/s41598-024-57772-x

Fins are widely used in many industrial applications, including heat exchangers. They benefit from a relatively economical design cost, are lightweight, and are quite miniature. Thus, this study investigates the influence of a wavy fin structure subjected to convective effects with internal heat generation. The thermal distribution, considered a steady condition in one dimension, is described by a unique implementation of a physics-informed neural network (PINN) as part of machine-learning intelligent strategies for analyzing heat transfer in a convective wavy fin. This novel research explores the use of PINNs to examine the effect of the nonlinearity of temperature equation and boundary conditions by altering the hyperparameters of the architecture. The non-linear ordinary differential equation (ODE) involved with heat transfer is reduced into a dimensionless form utilizing the non-dimensional variables to simplify the problem. Furthermore, Runge-Kutta Fehlberg's fourth-fifth order (RKF-45) approach is implemented to evaluate the simplified equations numerically. To predict the wavy fin's heat transfer properties, an advanced neural network model is created without using a traditional data-driven approach, the ability to solve ODEs explicitly by incorporating a mean squared error-based loss function. The obtained results divulge that an increase in the thermal conductivity variable upsurges the thermal distribution. In contrast, a decrease in temperature profile is caused due to the augmentation in the convective-conductive variable values.
Nipah virus: epidemiology, pathology, immunobiology and advances in diagnosis, vaccine designing and control strategies - a comprehensive review

Singh RK, Dhama K, Chakraborty S, Tiwari R, Natesan S, Khandia R, et al.

Vet Q, 2019 Dec;39(1):26-55.
PMID: 31006350

Nipah (Nee-pa) viral disease is a zoonotic infection caused by Nipah virus (NiV), a paramyxovirus belonging to the genus Henipavirus of the family Paramyxoviridae. It is a biosafety level-4 pathogen, which is transmitted by specific types of fruit bats, mainly Pteropus spp. which are natural reservoir host. The disease was reported for the first time from the Kampung Sungai Nipah village of Malaysia in 1998. Human-to-human transmission also occurs. Outbreaks have been reported also from other countries in South and Southeast Asia. Phylogenetic analysis affirmed the circulation of two major clades of NiV as based on currently available complete N and G gene sequences. NiV isolates from Malaysia and Cambodia clustered together in NiV-MY clade, whereas isolates from Bangladesh and India clusterered within NiV-BD clade. NiV isolates from Thailand harboured mixed population of sequences. In humans, the virus is responsible for causing rapidly progressing severe illness which might be characterized by severe respiratory illness and/or deadly encephalitis. In pigs below six months of age, respiratory illness along with nervous symptoms may develop. Different types of enzyme-linked immunosorbent assays along with molecular methods based on polymerase chain reaction have been developed for diagnostic purposes. Due to the expensive nature of the antibody drugs, identification of broad-spectrum antivirals is essential along with focusing on small interfering RNAs (siRNAs). High pathogenicity of NiV in humans, and lack of vaccines or therapeutics to counter this disease have attracted attention of researchers worldwide for developing effective NiV vaccine and treatment regimens.