The largest topological ring of functions endowed with the m-topology

[EN] The purpose of this article is to identify the largest subring of the ring of all real valued functions on a Tychonoff space X, which forms a topological ring endowed with the m-topology.The second author acknowledges the support of NBHM Research Grant 02011/6/2020/NBHM(R.P) R&D II/6277.Chauhan, TK.; Jindal, V. (2022). The largest topological ring of functions endowed with the m-topology. Applied General Topology. 23(2):281-286. https://doi.org/10.4995/agt.2022.1708028128623

Effect of Binary Fuel Blends on Compression Ignition Engine Characteristics: A Review

Diversified research in alternate sources arises become necessity due to higher consumption of fossil fuels along with their adverse impacts on the environment, even to the point of complete elimination of diesel from compression-ignition (CI) engines. Binary fuel blend (a blend of low and high viscous fuel) is one of the best environmentally friendly alternative in CI engines. Blending of methyl ester with edible and nonedible oils in different volumetric ratios has the potency to give a stable mixture and that can be used as a fuel in diesel engines. The main motive for the blending of two fuels is that the inferior properties of one biofuel remunerate from improved properties of the other fuel considerably improves the physicochemical properties of the blend. The present study provides comprehensive information on the emission and performance characteristics of binary biodiesel-oil fuel blends. Most researchers had suggested optimum blends from their respective studies that support capability for complete elimination of diesel from CI engines. Some researchers have used this binary fuel blend with minor adjustments to the engine parameters. These investigations have provided positive results. The comprehensive review concluded that binary fuel approach has potential to completely eliminate diesel from CI engines

Synthesis of Optimal Hybrid Membrane Networks for Seawater Desalination Coupled with Salt Production Processes

Seawater Reverse Osmosis (SWRO) has become a leading desalination technology as a result of the global increase in demand for desalinated water. Several technologies have been developed, which entail salt production, to combat brine disposal issues. Integrating these options significantly impacts the economics and overall footprints of desalination systems. In this work, a novel superstructure-based approach has been developed by building upon earlier work. The main motivation of the proposed methodology is to be able to systematically explore different membrane desalination configurations coupled with salt production technologies. All possible design options have been embedded into the proposed superstructure model, whilst deploying optimization techniques that identify economically optimal solutions. Hence, the method can explore reduced water costs by extracting value from concentrates in the desalination system in the form of salt co-products. This work is the first ever attempt to propose a superstructure-based design approach for this problem. This work considers SWRO and Nanofiltration (NF) membranes as the primary synthesis units of the membrane desalination network. NF membranes offer higher rejections of divalent ions over monovalent ions and offer potential opportunity to selectively channel streams containing high value ions to salt production operations. Furthermore, several Salt Production Processes (SPPs) involving desalination brines have also been considered as a third category for potential synthesis units within the network. A case study involving superstructures of multiple membrane units and SPPs is used to demonstrate the proposed method. A 100,000 m3/day production capacity plant, using the membrane modules FilmTec SW30 and NF270 by Dow, is modelled. First of the two SPP options produces calcium carbonate through sodium carbonate softening in a solid contact clarifier. The second SPP produces sodium chloride through the sequential pond evaporation and evaporative crystallization. The cost optimal membrane network designs with salt production are compared against the base case of SWRO desalination without salt production. The results indicate significant reductions in water costs if salts can be co-produced in desalination systems

Antimicrobial Efficacy of Green Silver Nanoparticles and Potential Implications for Human Health and the Environment

The beginnings of the applications of nanotechnology in the field of health sciences took place in early 2000s. There is a wide range of application of nanoparticles and its uses are emerging rapidly. Nanoparticle synthesis is usually carried out by various physical and chemical methods using various hazardous and toxic chemicals which may have adverse effect in the medical applications. Nevertheless, green synthesis approaches of producing silver nanoparticles are an alternative source of conventional method and is cost effective, environment friendly, easily scaled up for large scale synthesis and in this method there is no need to exploit high pressure, energy, temperature and toxic chemicals as in case of chemical and physical method. In this review, we report, some of the major applications of green synthesis of silver nanoparticles

Predicting suicidal behavior among Indian adults using childhood trauma, mental health questionnaires and machine learning cascade ensembles

Among young adults, suicide is India's leading cause of death, accounting for an alarming national suicide rate of around 16%. In recent years, machine learning algorithms have emerged to predict suicidal behavior using various behavioral traits. But to date, the efficacy of machine learning algorithms in predicting suicidal behavior in the Indian context has not been explored in literature. In this study, different machine learning algorithms and ensembles were developed to predict suicide behavior based on childhood trauma, different mental health parameters, and other behavioral factors. The dataset was acquired from 391 individuals from a wellness center in India. Information regarding their childhood trauma, psychological wellness, and other mental health issues was acquired through standardized questionnaires. Results revealed that cascade ensemble learning methods using a support vector machine, decision trees, and random forest were able to classify suicidal behavior with an accuracy of 95.04% using data from childhood trauma and mental health questionnaires. The study highlights the potential of using these machine learning ensembles to identify individuals with suicidal tendencies so that targeted interinterventions could be provided efficiently.Comment: 11 pages, presnted at the 4th International Conference on Frontiers in Computing and Systems (COMSYS 2023), Himachal Pradesh, October 202

Gangotri glacier dynamics from multi-sensor SAR and optical data

The present study has analyzed dynamics of Gangotri glacier using multiple remote sensing (RS) datasets and ground based observations. Interferometric Synthetic Aperture Radar (InSAR) data pairs from European Remote Sensing satellite (ERS 1/2) tandem pair for spring of 1996, Sentinel-1 SAR pairs and Japanese's Advance Land Observation System (ALOS) PALSAR-2 SAR data for Spring of 2015 were used to derive glacier-surface velocity at seasonal time scale using Differential InSAR (DInSAR) techniques. Bi-static TanDEM-X (Experimental) data was used for the 1st time to estimate glacier surface elevation changes for a period of 22, 44, 88 days during summer of 2012 using InSAR techniques in this study. Annual glacier velocity was also estimated using temporal panchromatic data of LANDSAT-5 (30 m), LANDSAT-7/8 (15 m), Sentinel-2 (10 m) and Indian Remote Sensing Satellite IRS-1C/1D panchromatic (5 m) data during 1998–2019 with feature tracking approach. This study has estimated glacier surface velocity and surface elevation changes for the major parts of Gangotri glacier and its tributary glaciers using medium to high resolution optical and SAR datasets, at annual and seasonal time scale, which is an improvement over earlier studies, wherein snout based glacier recession or only main glacier velocities were reported. The velocity and slope were used to assess glacier-ice thickness distribution using Glabtop-2, slope dependent and laminar flow based methods over the Gangotri group of glaciers. The estimated ice thickness was estimated in the range of 58–550 m for the complete glacier while few small areas in middle &amp; upper regions carry higher thickness of about 607 m. The estimated glacier-ice thickness was found in the range of 58–67 m at the snout region. The estimation was validated using 2014 field measurements from Terrestrial Laser Scanner (TLS) for the first time and correlation was found to be 0.799 at snout of the glacier.</p

The Influence of Natural Barriers in Shaping the Genetic Structure of Maharashtra Populations

BACKGROUND: The geographical position of Maharashtra state makes it rather essential to study the dispersal of modern humans in South Asia. Several hypotheses have been proposed to explain the cultural, linguistic and geographical affinity of the populations living in Maharashtra state with other South Asian populations. The genetic origin of populations living in this state is poorly understood and hitherto been described at low molecular resolution level. METHODOLOGY/PRINCIPAL FINDINGS: To address this issue, we have analyzed the mitochondrial DNA (mtDNA) of 185 individuals and NRY (non-recombining region of Y chromosome) of 98 individuals belonging to two major tribal populations of Maharashtra, and compared their molecular variations with that of 54 South Asian contemporary populations of adjacent states. Inter and intra population comparisons reveal that the maternal gene pool of Maharashtra state populations is composed of mainly South Asian haplogroups with traces of east and west Eurasian haplogroups, while the paternal haplogroups comprise the South Asian as well as signature of near eastern specific haplogroup J2a. CONCLUSIONS/SIGNIFICANCE: Our analysis suggests that Indian populations, including Maharashtra state, are largely derived from Paleolithic ancient settlers; however, a more recent (∼10 Ky older) detectable paternal gene flow from west Asia is well reflected in the present study. These findings reveal movement of populations to Maharashtra through the western coast rather than mainland where Western Ghats-Vindhya Mountains and Narmada-Tapti rivers might have acted as a natural barrier. Comparing the Maharastrian populations with other South Asian populations reveals that they have a closer affinity with the South Indian than with the Central Indian populations

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Penilaian Kinerja Keuangan Koperasi di Kabupaten Pelalawan

This paper describe development and financial performance of cooperative in District Pelalawan among 2007 - 2008. Studies on primary and secondary cooperative in 12 sub-districts. Method in this stady use performance measuring of productivity, efficiency, growth, liquidity, and solvability of cooperative. Productivity of cooperative in Pelalawan was highly but efficiency still low. Profit and income were highly, even liquidity of cooperative very high, and solvability was good