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The CdSe 0.3 Te 0.7 thin films of various thicknesses were deposited onto a glass substrate using a homemade spray pyrolysis technique at a substrate temperature of 573 K. The XRD pattern shows a mixed hexagonal and cubic crystal structure with additional TeO 2 peaks. The SEM image showsthe CdSe 0.3 Te 0.7 layer is homogeneous, free of cracks, and completely covers the surface of the substrate. The EDAX pattern shows the presence of well-defined peaks related to Cd, Se, and Te, confirming the successful preparation of CdSe 0.3 Te 0.7 films. The optical spectra of CdSe 0.3 Te 0.7 thin film show a decrease in bandgap up to 1.51 eV with an increase in thickness of 1033 nm, and the bandgap increases to 1.52 eV at 1207 nm.

Neutrino fluxes could arise due to annihilation of Weakly Interactive Massive Particles (WIMPs) in the center of the sun. We study the prospects of search for muon events due to such neutrinos at the upcoming Iron CALorimeter (ICAL) detector to be housed at India-based Neutrino Observatory (INO). Although the atmospheric neutrinos will pose a serious background to the signal neutrinos produced through WIMP annihilation, the former could be supressed significantly by using the directional property of signal neutrinos. For 50kt×10 years of ICAL running and WIMP masses (mχ) between 3-100 GeV, we perform a χ2 analysis and present expected exclusion regions in the σβख़ - mx and σβι - mx plane, where σβख़ and σβι are the WIMP-nucleon Spin-Dependent (SD) and Spin-Independent (SI) scattering cross-sections, respectively. For mx = 25 GeV, the expected 90 % C.L. exclusion limit on σβख़ are σβॄ < 7.82 x 10−41 cm2 for τ+τ− channel and σβख़ < 1.23 10−39 cm2 for 66 channel. For same m×, the expected 90 % C.L. exclusion limits on σβι are σβι < 8.97 × 10−43 cm2 for τ +τ− channel and σβι < 1.43×10−41 cm2 for 66 channel.

A bstract Neutrino oscillation experiments provide a unique window in exploring several new physics scenarios beyond the standard three flavour. One such scenario is quantum decoherence in neutrino oscillation which tends to destroy the interference pattern of neutrinos reaching the far detector from the source. In this work, we study the decoherence in neutrino oscillation in the context of the ESSnuSB experiment. We consider the energy-independent decoherence parameter and derive the analytical expressions for P μe and P μμ probabilities in vacuum. We have computed the capability of ESSnuSB to put bounds on the decoherence parameters namely, Γ 21 and Γ 32 and found that the constraints on Γ 21 are competitive compared to the DUNE bounds and better than the most stringent LBL ones from MINOS/MINOS+. We have also investigated the impact of decoherence on the ESSnuSB measurement of the Dirac CP phase δ CP and concluded that it remains robust in the presence of new physics.

A bstract This study provides an analysis of atmospheric neutrino oscillations at the ESSnuSB far detector facility. The prospects of the two cylindrical Water Cherenkov detectors with a total fiducial mass of 540 kt are investigated over 10 years of data taking in the standard three-flavor oscillation scenario. We present the confidence intervals for the determination of mass ordering, θ 23 octant as well as for the precisions on sin 2 θ 23 and Δ m 31 2 . It is shown that mass ordering can be resolved by 3 σ CL (5 σ CL) after 4 years (10 years) regardless of the true neutrino mass ordering. Correspondingly, the wrong θ 23 octant could be excluded by 3 σ CL after 4 years (8 years) in the case where the true neutrino mass ordering is normal ordering (inverted ordering). The results presented in this work are complementary to the accelerator neutrino program in the ESSnuSB project.

A bstract Neutrino oscillations constitute an excellent tool to probe physics beyond the Standard Model. In this paper, we investigate the potential of the ESSnuSB experiment to constrain the effects of flavour-dependent long-range forces (LRFs) in neutrino oscillations, which may arise due to the extension of the Standard Model gauge group by introducing new U(1) symmetries. Focusing on three specific U(1) symmetries — L e − L μ , L e − L τ , and L μ − L τ , we demonstrate that ESSnuSB offers a favourable environment to search for LRF effects. Our analyses reveal that ESSnuSB can set 90% confidence level bounds of V eμ < 2.99 × 10 − 14 eV, V eτ < 2.05 × 10 − 14 eV, and V μτ < 1.81 × 10 − 14 eV, which are competitive to the upcoming Deep Underground Neutrino Experiment (DUNE). It is also observed that reducing the systematic uncertainties from 5% to 2% improves the ESSnuSB limits on V αβ . Interestingly, we find limited correlations between LRF parameters and the less constrained lepton mixing parameters θ 23 and δ CP , preserving the robustness of ESSnuSB’s sensitivity to CP violation. Even under extreme LRF potentials ( V αβ ≫ 10 − 13 eV), the CP-violation sensitivity and δ CP precision remain largely unaffected. These results establish ESSnuSB as a competitive experimental setup for probing LRF effects, complementing constraints from other neutrino sources and offering critical insights into the physics of long-range forces.

ESSnuSB is a design study for an experiment to measure the CP violation in the leptonic sector at the second neutrino oscillation maximum using a neutrino beam driven by the uniquely powerful ESS linear accelerator. The reduced impact of systematic errors on sensitivity at the second maximum allows for a very precise measurement of the CP violating parameter. This review describes the fundamental advantages of measurement at the second maximum, the necessary upgrades to the ESS linac in order to produce a neutrino beam, the near and far detector complexes, and the expected physics reach of the proposed ESSnuSB experiment, concluding with the near future developments aimed at the project realization.

The diversity among surgical directors for liver, kidney, and pancreas transplant departments has not been previously evaluated. We aim to quantify the sex and racial demographics of transplant department leaders and assess the impact on patient outcomes. Demographics were collected for 116 liver, 192 kidney, and 113 pancreas transplant directors using Organ Procurement and Transplantation Network (OPTN) directory and program websites. Scientific Registry of Transplant Recipients (SRTR) 5-tier program outcomes rankings were obtained for each program and matched to leader demographics. A retrospective analysis of transplant recipients from 2010 to 2019 was performed using the United Network for Organ Sharing (UNOS) database. 91.5% of transplant surgical directors were male. 55% of departments had a Non-Hispanic White leader. Asian, Hispanic and Black transplant chiefs were at the helm of 23.3%, 9%, and 5% of divisions respectively. Multivariate cox regression analysis did not identify any differences in patient outcomes by transplant director demographics. There is a paucity of female and URM leaders in transplant surgery. Initiatives to promote research, mentorship, and career advancement opportunities for women and URM are necessary to address the current leadership disparity. •There are few female and URM leaders in transplant surgery— 91.5% were male and 55% were Non-Hispanic White.•Asian, Hispanic, and Black transplant chiefs were at the helm of 23.3%, 9%, and 5% of divisions respectively.•Transplant surgical director demographics do not impact patient outcomes.

The global fitness company estimates that by 2030, Chronic Obstructive Pulmonary Disease (COPD) will be the third leading cause of death in the world. Computerized Tomography (CT) of the lungs includes a number of structures that may be important in the prognosis and evaluation of lung disease. CT images of the lungs show a section of the chest that constitutes a large number of systems, including blood vessels, arteries, respiratory vessels, pulmonary pleura, and parenchyma, each with its own information. For this reason, the phasing of the lung systems is very important for the analysis and diagnosis of lung diseases. Segmentation is an important step in the photographic structure for the correct diagnosis of lung disease, as it delimits lung systems on CT images. Of course, imaging strategies can aid in computer analysis if the lung area is properly obtained. After the segmentation procedure, an automatic technique is used to identify possible diseases on CT scans of the lungs so the radiologist can focus on the prognosis of the patient. Several studies have shown promising results in detecting violations.

The novel coronavirus disease (COVID-19), with a start line in China, has spread hastily amongst human beings dwelling in other international locations, and is coming near approximately 34,986,502 instances worldwide in line with the facts of Edith Cowan University (ecu) Centre for disorder prevention and control. There are a restrained number of COVID-19 test kits to be had in hospitals due to the growing cases day by day. Consequently, it is important to implement an automated detection machine as a brief opportunity diagnosis choice to prevent COVID-19 spreading among human beings. Fusion was considered as a concatenation between the two-person vectors on this context. Speckle-affected and coffee-fine X-ray images along with top first-class pictures have been utilized in our test for carrying out exams. If training and trying out are done with best selected right fine X-ray photos in a super situation, the output accuracy can be observed higher. However, this doesn't constitute a real-existence situation, wherein the photo database would be a mixture of each appropriate- and poor-first-rate pictures. Therefore, this technique of the use of different excellent snap shots could test how nicely the machine can react to such real-lifestyles situations. A modified anisotropic diffusion filtering technique become hired to take away multiplicative speckle noise from the test photographs. The software of these techniques ought to successfully conquer the restrictions in enter photograph quality. Subsequent, the function extraction changed into finished on the test photographs. Ultimately, the Convolutional Neural Network (CNN) classifier accomplished a type of X-ray photographs to pick out whether or not it changed into COVID-19 or until now. Pneumonia, an interstitial lung sickness, is the main reason of loss of life in children under the age of five. It accounted for approximately 16% of the deaths of kids below the age of 5, killing around 880,000 kids in 2016 according to a look at conducted with the aid of United Nations International Children's Emergency Fund (UNICEF). Affected children were mostly much less than two years old. Well timed detection of pneumonia in youngsters can assist to the technique of restoration. This paper gives convolutional neural community fashions to accurately hit upon pneumonic lungs from chest X-rays, which can be utilized inside the actual global by using medical practitioners to treat pneumonia. Experimentation was conducted on Chest X-Ray images dataset to be had on Kaggle.