A Hybrid Regression Model for improving prediction accuracy

The main disadvantage of Regression tree is that it assigns the same predicted value, average value, for all the tuples which satisfies the same corresponding splitting criterion. K-Nearest Neighbors (KNN) is sensitive to irrelevant or redundant features because all features contribute to the similarity. In this paper a hybrid regression model based on Regression tree (RT) and KNN is proposed which overcomes the above two problems. The performance of proposed model is compared with KNN for 10 types of distance measures. The performance of proposed model is also compared with RT, K-Nearest neighbour regression (KNN), Support Vector Regression (SVR) through a Monte Carlo simulation study. The simulation result indicates that hybrid model outperforms all other regression model irrespective of sample size when the observations are from normal distributions as well as t-distributions. The working of the proposed model is illustrated for a real-life application on global warming data of Delhi.: Regression Tree, Hybrid model, KNN, SVR, Gini Index

Investigation of deformation of the cornea during tonometry using FEM

A three dimensional finite element model of the human eye is developed to evaluate the force which will be applied over the surface of cornea during tonometry and gonioscopy tests. The standard tonometers and gonioscopy experiences deformation from 0.5mm to 3mm of the cornea is adopted during both point contact and boundary contact on the surface of the cornea. The results demonstrate the maximum force experienced by the tonometer with point contact at the center of the cornea for the maximum possible deformation of the cornea during tonometry. The study also analyzes for the force experienced by the tonometer or goniolens with boundary layer contact for the defined deformation of the cornea along the direction from cornea towards the retina

TIRSPEC : TIFR Near Infrared Spectrometer and Imager

We describe the TIFR Near Infrared Spectrometer and Imager (TIRSPEC) designed and built in collaboration with M/s. Mauna Kea Infrared LLC, Hawaii, USA, now in operation on the side port of the 2-m Himalayan Chandra Telescope (HCT), Hanle (Ladakh), India at an altitude of 4500 meters above mean sea level. The TIRSPEC provides for various modes of operation which include photometry with broad and narrow band filters, spectrometry in single order mode with long slits of 300" length and different widths, with order sorter filters in the Y, J, H and K bands and a grism as the dispersing element as well as a cross dispersed mode to give a coverage of 1.0 to 2.5 microns at a resolving power R of ~1200. The TIRSPEC uses a Teledyne 1024 x 1024 pixel Hawaii-1 PACE array detector with a cutoff wavelength of 2.5 microns and on HCT, provides a field of view of 307" x 307" with a plate scale of 0.3"/pixel. The TIRSPEC was successfully commissioned in June 2013 and the subsequent characterization and astronomical observations are presented here. The TIRSPEC has been made available to the worldwide astronomical community for science observations from May 2014.Comment: 20 pages, 21 figures, 2 tables. Accepted for publication in Journal of Astronomical Instrumentatio

PROCESS OPTIMISATION OF PILOT SCALE BIODIESEL PRODUCTION FROM PONGAMIA AND WASTE COOKING OIL FEEDSTOCK

Biodiesel is the most promising renewable alternative fuel for fossil diesel fuel, which can be produced even in rural settings of an economically backward sector of developing countries. Biodiesel can be produced from non-edible seed oils or used edible oil sources by a transesterification reaction. Biodiesel feedstock differ according to geographic location, therefore, it is essential to optimise the biodiesel production process at least in pilot scale for each source to obtain highest biodiesel yield to be used for domestic purpose. In the present study, biodiesel was produced from non-edible Pongamia seed oil and Waste Cooking Oil separately using the 50 L capacity pilot scale reactor. The crucial reaction parameters such as catalyst (NaOH) concentration, alcohol (Methanol) volume and reaction time were optimised through Box-Behnken Design (BBD) approach to maximise the biodiesel yield. In the optimised pilot study, the biodiesel yield of 89.1% from Pongamia oil and 96% from Waste Cooking Oil sources were obtained. Also, the biodiesels produced by pilot scale met the requisite quality standards of ASTM, EU and India

Proceedings of a workshop to address animal methods bias in scientific publishing

Animal methods bias in scientific publishing is a newly defined type of publishing bias describing a preference for animal-based methods where they may not be necessary or where nonanimal-based methods may already be suitable, which impacts the likelihood or timeliness of a manuscript being accepted for publication. This article covers the output from a workshop between stakeholders in publishing, academia, industry, government, and non-governmental organizations. The intent of the workshop was to exchange perspectives on the prevalence, causes, and impact of animal methods bias in scientific publishing, as well as to explore mitigation strategies. Output from the workshop includes summaries of presentations, breakout group discussions, participant polling results, and a synthesis of recommendations for mitigation. Overall, participants felt that animal methods bias has a meaningful impact on scientific publishing, though more evidence is needed to demonstrate its prevalence. Significant consequences of this bias that were identified include the unnecessary use of animals in scientific procedures, the continued reliance on animals in research—even where suitable nonanimal methods exist, poor rates of clinical translation, delays in publication, and negative impacts on career trajectories in science. Workshop participants offered recommendations for journals, publishers, funders, governments, and other policy makers, as well as the scientific community at large, to reduce the prevalence and impacts of animal methods bias. The workshop resulted in the creation of working groups committed to addressing animal methods bias and activities are ongoin

Divalent Metal Vinylphosphonate Layered Materials: Compositional Variability, Structural Peculiarities, Dehydration Behavior, and Photoluminescent Properties

A family of M-VP (M = Ni, Co, Cd, Mn, Zn, Fe, Cu, Pb; VP = vinylphosphonate) and M-PVP (M = Co, Cd; PVP = phenylvinylphosphonate) materials have been synthesized by hydrothermal methods and characterized by FTIR, elemental analysis, and thermogravimetric analysis (TGA). Their structures were determined either by single crystal X-ray crystallography or from laboratory X-ray powder diffraction data. The crystal structure of some M-VP and M-PVP materials is two-dimensional (2D) layered, with the organic groups (vinyl or phenylvinyl) protruding into the interlamellar space. However, the Pb-VP and Cu-VP materials show dramatically different structural features. The porous, three-dimensional (3D) structure of Pb-VP contains the Pb center in a pentagonal pyramid. A Cu-VP variant of the common 2D layered structure shows a very peculiar structure. The structure of the material is 2D with the layers based upon three crystallographically distinct Cu atoms; an octahedrally coordinated Cu2+ atom, a square planar Cu2+ atom and a Cu+ atom. The latter has an unusual co-ordination environment as it is 3-coordinated to two oxygen atoms with the third bond across the double bond of the vinyl group. Metal-coordinated water loss was studied by TGA and thermodiffractometry. The rehydration of the anhydrous phases to give the initial phase takes place rapidly for Cd-PVP but it takes several days for Co-PVP. The M-VP materials exhibit variable dehydration-rehydration behavior, with most of them losing crystallinity during the process.Proyecto nacional MAT2010-15175 (MICINN, España

Meta-analysis of HNF1A-MODY3 variants among human population

BACKGROUND : Previously, numerous case-control studies have highlighted variants responsible for Maturity onset diabetes of young (MODY). However, these studies have been conducted among diverse populations and hence yielded contradictory results. We, therefore, performed a meta-analysis to precisely find the association of SNPs with the disease for the HNF1A gene. OBJECTIVE : Meta-analysis of clinically defined studies deciphering mutations in the HNF1A gene responsible for the development of MODY3 was conducted among various populations to determine associations using statistical approaches. METHODS : The curation of 505 research articles published between the years 2000–2021 was carried out. Visualization of data-related protocols and statistical-analysis were conducted, which led to the identification of highly prevalent mutations among different populations (majorly Europe). Further comparison between the frequencies of the control (healthy population) and test (diseased population) dataset generated through curation was performed. RESULTS : We identified nine MODY3 mutations (rs587776825, rs1169288, rs1800574, rs2464196, rs137853244, rs137853238, rs587780357, rs137853240 and rs137853243) at the genome-wide significance level ( p < 5.0 × 10−8). The present study confirmed that the data does not follow a normal distribution. Further, the data was confirmed to be a more homogenous type with frequencies having a significant association with the disease. CONCLUSION : This meta-analysis found significant associations of mutations in HNF1A with MODY3, consistent with previous studies. Our findings should help elucidate the mutations in a compiled form responsible for causing MODY3.https://link.springer.com/journal/40200hj2023Consumer ScienceFood Scienc