The Impact of TQM on Performance Measurement: Empirical Study of Bahraini Private Universities

An investigation on the impact of TQM dimensions on the performance of universities is the core of this paper based on Lecturers perception in Bahrain Private Universities. Also, to investigate the effect of Performance Measurement due to the demographic data of Lecturers in Bahrain Private Universities (Gender, Age, Experience, and Education Level). Correlational and quantitative methods were used in the study. The instrument for this research is the questionnaire that was developed to address all studied variables. The target population was 517 lecturers that work in the Bahrain private universities from 13 universities and with a sample size of 100 lecturers. The researchers used SPSS version 26 for all statistical analyses, and Descriptive analysis included mean and standard deviation computation. Meanwhile, Pearson correlation, regression analysis, T-test, and One Way ANOVA test were incorporated into the inferential analysis. The results show that Continuous Improvement, Education and Training, and Quality of Work Life significantly affect performance measurement, while Resources and Teamwork significantly not contributed to explaining performance measurement. Furthermore, there is no significant effect on Performance Measurement due to Gender and Education Level. Moreover, the results disclosed a significant effect on Performance Measurement due to Age and Experience

Rethinking Ductility -- A Study Into the Size-Affected Fracture of Polymers

Ductility quantifies a material's capacity for plastic deformation, and it is a key property for preventing fracture driven failure in engineering parts. While some brittle materials exhibit improved ductility at small scales, the processes underlying this phenomenon are not well understood. This work establishes a mechanism for the origin of ductility via an investigation of size-affected fracture processes and polymer degree of conversion (DC) in two-photon lithography (TPL) fabricated materials. Microscale single edge notch bend ($\mu$SENB) specimens were written with widths from 8 to 26 $\mu$m and with different laser powers and post-write thermal annealing to control the DC between 17\% and 80\%. We find that shifting from low to high DC predictably causes a $\sim$3x and $\sim$4x increase in strength and bending stiffness, respectively, but that there is a corresponding $\sim$6x decrease in fracture energy from 180 $J/m^2$ to 30 $J/m^2$. Notably, this reduced fracture energy is accompanied by a ductile-to-brittle transition (DBT) in the failure behavior. Using finite element analysis, we demonstrate that the DBT occurs when the fracture yielding zone size ($r_p$) approaches the sample width, corresponding with a known fracture size-affected transition from flaw-based to strength-based failure. This finding provides a crucial insight that ductility is a size-induced property that occurs when features are reduced below a characteristic fracture length scale and that strength, stiffness, and toughness alone are insufficient predictors of ductility.Comment: 17 pages, 6 figure

Date Palm Leaflet-Derived Carbon Microspheres Activated Using Phosphoric Acid for Efficient Lead (II) Adsorption

\ua9 2024 by the authors.The removal of lead metals from wastewater was carried out with carbon microspheres (CMs) prepared from date palm leaflets using a hydrothermal carbonization process (HTC). The prepared CMs were subsequently activated with phosphoric acid using the incipient wetness impregnation method. The prepared sample had a low Brunauer–Emmet–Teller (BET) surface area of 2.21 m2\ub7g−1, which increased substantially to 808 m2\ub7g−1 after the activation process. Various characterization techniques, such as scanning electron microscopy, BET analysis, Fourier transform infrared, and elemental analysis (CHNS), were used to evaluate the morphological structure and physico-chemical properties of the CMs before and after activation. The increase in surface area is an indicator of the activation process, which enhances the absorption properties of the material. The results demonstrated that the activated CMs had a notable adsorption capacity, with a maximum adsorption capacity of 136 mg\ub7g−1 for lead (II) ions. This finding suggests that the activated CMs are highly effective in removing lead pollutants from water. This research underscores the promise of utilizing activated carbon materials extracted from palm leaflets as an eco-friendly method with high potential for water purification, specifically in eliminating heavy metal pollutants, particularly lead (II), contributing to sustainability through biomass reuse

Reconstruction and measurement of (100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

We describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration

Design and construction of the MicroBooNE Cosmic Ray Tagger system

The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the detector records many cosmic muon tracks in each beam-related detector trigger that can be misidentified as signals of interest. To reduce these cosmogenic backgrounds, we have designed and constructed a TPC-external Cosmic Ray Tagger (CRT). This sub-system was developed by the Laboratory for High Energy Physics (LHEP), Albert Einstein center for fundamental physics, University of Bern. The system utilizes plastic scintillation modules to provide precise time and position information for TPC-traversing particles. Successful matching of TPC tracks and CRT data will allow us to reduce cosmogenic background and better characterize the light collection system and LArTPC data using cosmic muons. In this paper we describe the design and installation of the MicroBooNE CRT system and provide an overview of a series of tests done to verify the proper operation of the system and its components during installation, commissioning, and physics data-taking

Design, construction and operation of the ProtoDUNE-SP Liquid Argon TPC

The ProtoDUNE-SP detector is a single-phase liquid argon time projection chamber (LArTPC) that was constructed and operated in the CERN North Area at the end of the H4 beamline. This detector is a prototype for the first far detector module of the Deep Underground Neutrino Experiment (DUNE), which will be constructed at the Sandford Underground Research Facility (SURF) in Lead, South Dakota, U.S.A. The ProtoDUNE-SP detector incorporates full-size components as designed for DUNE and has an active volume of 7 × 6 × 7.2 m3. The H4 beam delivers incident particles with well-measured momenta and high-purity particle identification. ProtoDUNE-SP\u27s successful operation between 2018 and 2020 demonstrates the effectiveness of the single-phase far detector design. This paper describes the design, construction, assembly and operation of the detector components

A Deep Neural Network for Pixel-Level Electromagnetic Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber

We have developed a convolutional neural network (CNN) that can make a pixel-level prediction of objects in image data recorded by a liquid argon time projection chamber (LArTPC) for the first time. We describe the network design, training techniques, and software tools developed to train this network. The goal of this work is to develop a complete deep neural network based data reconstruction chain for the MicroBooNE detector. We show the first demonstration of a network's validity on real LArTPC data using MicroBooNE collection plane images. The demonstration is performed for stopping muon and a $\nu_\mu$ charged current neutral pion data samples

Searching for solar KDAR with DUNE

The observation of 236 MeV muon neutrinos from kaon-decay-at-rest (KDAR) originating in the core of the Sun would provide a unique signature of dark matter annihilation. Since excellent angle and energy reconstruction are necessary to detect this monoenergetic, directional neutrino flux, DUNE with its vast volume and reconstruction capabilities, is a promising candidate for a KDAR neutrino search. In this work, we evaluate the proposed KDAR neutrino search strategies by realistically modeling both neutrino-nucleus interactions and the response of DUNE. We find that, although reconstruction of the neutrino energy and direction is difficult with current techniques in the relevant energy range, the superb energy resolution, angular resolution, and particle identification offered by DUNE can still permit great signal/background discrimination. Moreover, there are non-standard scenarios in which searches at DUNE for KDAR in the Sun can probe dark matter interactions

Deep underground neutrino experiment (DUNE) near detector conceptual design report

The Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents