Analysis of Throughput in Infrastructure based Multi-Radio Network

This paper deals with the design of an infrastructure based network consisting of Multi-radio Hybrid mobile nodes that perform traffic splitting over the network. The multi- radio mobile nodes have a WiMAX and a WiFi Radio that are used in transmitting data traffic over two different radio channels. Data traffic is split statically over a node and transmitted over the two radio channels. We analyse the Throughput and End-to-End delay for data transmission in the network

Search for astrophysical electron antineutrinos in Super-Kamiokande with 0.01wt% gadolinium-loaded water

We report the first search result for the flux of astrophysical electron antineutrinos for energies O(10) MeV in the gadolinium-loaded Super-Kamiokande (SK) detector. In June 2020, gadolinium was introduced to the ultra-pure water of the SK detector in order to detect neutrons more efficiently. In this new experimental phase, SK-Gd, we can search for electron antineutrinos via inverse beta decay with efficient background rejection and higher signal efficiency thanks to the high efficiency of the neutron tagging technique. In this paper, we report the result for the initial stage of SK-Gd with a $22.5\times552$ $\rm kton\cdot day$ exposure at 0.01% Gd mass concentration. No significant excess over the expected background in the observed events is found for the neutrino energies below 31.3 MeV. Thus, the flux upper limits are placed at the 90% confidence level. The limits and sensitivities are already comparable with the previous SK result with pure-water ($22.5 \times 2970 \rm kton\cdot day$) owing to the enhanced neutron tagging

Performance of SK-Gd's upgraded real-time supernova monitoring system

Among multi-messenger observations of the next galactic core-collapse supernova, Super-Kamiokande (SK) plays a critical role in detecting the emitted supernova neutrinos, determining the direction to the supernova (SN), and notifying the astronomical community of these observations in advance of the optical signal. On 2022, SK has increased the gadolinium dissolved in its water target (SK-Gd) and has achieved a Gd concentration of 0.033%, resulting in enhanced neutron detection capability, which in turn enables more accurate determination of the supernova direction. Accordingly, SK-Gd's real-time supernova monitoring system (Abe te al. 2016b) has been upgraded. SK_SN Notice, a warning system that works together with this monitoring system, was released on December 13, 2021, and is available through GCN Notices (Barthelmy et al. 2000). When the monitoring system detects an SN-like burst of events, SK_SN Notice will automatically distribute an alarm with the reconstructed direction to the supernova candidate within a few minutes. In this paper, we present a systematic study of SK-Gd's response to a simulated galactic SN. Assuming a supernova situated at 10 kpc, neutrino fluxes from six supernova models are used to characterize SK-Gd's pointing accuracy using the same tools as the online monitoring system. The pointing accuracy is found to vary from 3-7∘ depending on the models. However, if the supernova is closer than 10 kpc, SK_SN Notice can issue an alarm with three-degree accuracy, which will benefit follow-up observations by optical telescopes with large fields of view

Measurements of the charge ratio and polarization of cosmic-ray muons with the Super-Kamiokande detector

We present the results of the charge ratio (R) and polarization (Pμ0) measurements using the decay electron events collected from 2008 September to 2022 June by the Super-Kamiokande detector. Because of its underground location and long operation, we performed high precision measurements by accumulating cosmic-ray muons. We measured the muon charge ratio to be R=1.32±0.02 (stat.+syst.) at EμcosθZenith=0.7+0.3−0.2 TeV, where Eμ is the muon energy and θZenith is the zenith angle of incoming cosmic-ray muons. This result is consistent with the Honda flux model while this suggests a tension with the πK model of 1.9σ. We also measured the muon polarization at the production location to be Pμ0=0.52±0.02 (stat.+syst.) at the muon momentum of 0.9+0.6−0.1 TeV/c at the surface of the mountain; this also suggests a tension with the Honda flux model of 1.5σ. This is the most precise measurement ever to experimentally determine the cosmic-ray muon polarization near 1 TeV/c. These measurement results are useful to improve the atmospheric neutrino simulations

Tungsten heavy alloys with molybdenum, Y₂O₃ and lanthanum. A review

The consolidated results of studies of tungsten doping with various metals and compounds (Ni, Fe, Cu, Mo, Y₂O₃, La₂O₃) are presented, the advantages of doping with regard to its conditions, microwave and plasma sintering techniques are shown. It has been found that the mechanical properties of tungsten are significantly improved by the addition of the above elements. The resulting heavy fame tungsten can be used to protect against nuclear radiationПредставлено консолідовані результати досліджень легування вольфраму різними металами і сполуками (Ni, Fe, Cu, Mo, Y₂O₃, La₂O₃), показано переваги легування з урахуванням його умов, техніки мікрохвильового і плазмового спікання. Виявлено, що механічні властивості вольфраму значно покращилися при додаванні вищевказаних елементів. Отримані важкі слави вольфраму можуть бути використані для захисту від ядерного випромінювання.Представлены консолидированые результаты исследований легирования вольфрама различными металлами и соединениями (Ni, Fe, Cu, Mo, Y₂O₃, La₂O₃), показаны преимущества легирования с учетом его условий, техники микроволнового и плазменного спекания. Обнаружено, что механические свойства вольфрама значительно улучшились при добавлении вышеуказанных элементов. Полученные тяжелые славы вольфрама могут быть использованы для защиты от ядерного излучения

Biological evaluation of (3β)-STIGMAST-5-EN-3-OL as potent anti-diabetic agent in regulating glucose transport using in vitro model

AbstractAimInsulin resistance is characterized by alterations in insulin signaling components thereby resulting in reduced glucose uptake. The mechanistic role of (3β)-stigmast-5-en-3-ol in augmenting glucose uptake to overcome insulin resistance is deciphered in this study.Main methodsL6 myotubes, rat skeletal muscle model have been used to check the effect of (3β)-stigmast-5-en-3-ol, a plant phytosterol isolated from the ethyl acetate extract of Adathoda vasica on glucose transport. The influence of (3β)-stigmast-5-en-3-ol on various cellular targets of insulin signaling cascade has been evaluated using inhibitors on glucose uptake as well as gene and protein expression to unravel the mechanistic action in triggering glucose uptake.Results(3β)-stigmast-5-en-3-ol promoted glucose uptake in a dose dependent manner under insulin resistant condition. As assessed by inhibitor studies using Genistein (IRTK inhibitor) and Wortmannin (PI3K inhibitor), gene expression and protein expression studies using specific primers and antibodies, an activation of IR-β, IRS-1, PI3K, AKT/PKB, PKC by both the crude and (3β)-stigmast-5-en-3-ol were observed. This suggested that (3β)-stigmast-5-en-3-ol induced glucose uptake functions through the PI3K dependent pathway in L6 myotubes. Both, the crude and (3β)-stigmast-5-en-3-ol activates GLUT 4 transport (evident from increased mRNA levels and redistribution of GLUT4 from intracellular membrane to plasma membrane through translocation studies). Confocal microscopy revealed a substantial increase in redistribution of FITC tagged GLUT4 throughout the cells.ConclusionOur results emphasize the insulin-like effect of (3β)-stigmast-5-en-3-ol in stimulating glucose transport in vitro and provide evidence in its beneficial role possessing antidiabetic property apart from its existing cholesterol lowering efficacy

Molecular basis for the stereospecificity of Candida rugosa lipase (CRL) towards ibuprofen

Biocatalysis and Biotransformation176475-486BOBO

Aloe vera/silk fibroin/hydroxyapatite incorporated electrospun nano?brous scaffold for enhanced osteogenesis

10.1166/jbt.2014.1139Journal of Biomaterials and Tissue Engineering419-1

Thyroid Disease Classification using Machine Learning Algorithms

Thyroid gland is one of the body’s most important glands because it regulates the metabolism of the human body. It controls how the body works by releasing specific hormones into the blood. The two different hormone disorders are hypothyroidism and hyperthyroidism. When these disorders occur, the thyroid gland releases a particular hormone into the blood that regulates the metabolism of the body. Iodine deficiency, autoimmune conditions, and inflammation can contribute to thyroid issues. The disease is diagnosed using a blood test, but there is frequently some noise and disturbance. Techniques for cleaning data can be used to make it simple enough to perform analytics that show the patient's risk of developing thyroid disease. This paper deals with the analysis and classification models used in thyroid disease based on the information gathered from the dataset taken from the UCI machine learning repository. Machine learning plays a crucial role in the detection of thyroid disease. This paper suggests various machine-learning methods for thyroid detection and diagnosis for thyroid prevention