Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation and Characterization of Mn-Doped (Ba0.85Ca0.15)(Zr0.1Ti0.9)O3 Ceramics

MnO2-doped lead free 0.5[Ba(Zr0.2Ti0.8)O3]-0.5[(Ba0.7Ca0.3)TiO3] ceramics were synthesized by a high-energy ball milling process. We studied the phase formation process along different steps of the mechanical milling. We show that the addition of a small amount of MnO2 (x < 0.5 mol.%) improves the dielectric and ferroelectric properties of the ceramics. It is found that the doping with manganese increases the dielectric constant and reduces the loss, which decreases considerably as the Mn content increases. The remnant polarization of the doped ceramics is increased by 10%.
Evaluation of Auto Pilot Situational Awareness System Using Gunshot Detection Algorithm in a Localized Environment: Case Study Federal Polytechnic Offa, Mini Campus

Gunshot detection technologies are more applicable in many industries for the security enhancement of public places like the Federal Republic Territory FCT Abuja in Nigeria. Many factors affect the accuracy of the gun detection algorithm. This paper describes an audio-based video surveillance system in an auto pilot situational awareness to detect gunshots in Federal Polytechnic Offa. The Time Difference of Arrival (TDOA) of Shock Wave and Muzzle Blast is integrated to estimate the shooter location in the study are. The proposed design and algorithm was validated and shooter origin was resolute that was very close to theoretical values. The video camera is steering regarding the initial position to localize the acoustic source's position. Implementing an auto pilot situational awareness system is an experimental procedure with a gunshot detection algorithm in a localized environment. In the direction of the weapon, the distance between firearms, types of ammunition, types of study environment, and diffraction of audio, the standard feature for gunshot recognition are Mel frequency cepstral coefficients in terms of uniform gamma-tone filters linearly spaced over the whole frequency range from 0KHZ to 16KHZ. Experiments show that our system can detect gunshots with a precision of 93% at a false rejection rate of 5% when the SNR is 10db while proving the estimate of the source direction of the gunshot with an accuracy of one degree. The outcomes reveal that the data generated by the system can be leveraged by the firefighting department to quickly locate the whereabouts of the indoor fires, and the VR gamification scenarios can expedite the development of situational awareness for the trainees. The research recommends a real-time system implementation for protecting the Federal Polytechnic Offa against any form of treats.
IMPLEMENTASI METODE TAHSIN UNTUK MENINGKATKAN KEMAMPUAN MEMBACA AL-QUR’AN DI MI DARUL FALAH

Penelitian ini dilatar belakangi oleh kurangnya kemampuan membaca Al-Qur’an pada anak-anak MI Darul Falah yang terletak di desa Pematang Benteng Hilir, Kecamatan Sungai Tabukan, Kabupaten Hulu Sungai Utara. Penelitian ini bertujuan untuk mengetahui bagaimana implementasi metode tahsin di MI Darul Falah. Penelitian ini merupakan penelitian kualitatif dengan jenis narrative research, untuk teknik pengumpulan data dilakukan dengan proses wawancara, observasi, dan dokumentasi di MI Darul Falah. Teknis analisis data dilakukan dengan model Miles dan Hubberman yaitu dengan mereduksi, mendisplay dan memverifikasi data. Hasil penelitian ini menunjukkan bahwa implementasi metode tahsin memiliki dampak yang besar terhadap peningkatan kemampuan siswa-siswi di MI Darul Falah dalam membaca Al-Qur’an sesuai dengan makharijul huruf dan kaidah-kaidah tajwid. Dalam proses pembelajaran, pengajar menggunakan metode klasikal baca simak. Pengajar juga ikut serta mencontohkan bacaan yang baik dan membenarkan bacaan Al-Qur’an siswa. Selain itu, pengajar juga melakukan permainan yang berkaitan degan ilmu tajwid agar siswa-siswi tidak merasa bosan dalam pembelajaran
A configurational analysis of IT governance: A study of the financial services sector in Ghana

This study seeks to answer the question, what is the right configuration of IT Governance mechanisms that will improve performance? Although few studies have addressed how governance mechanisms improve performance, these studies have adopted a linear approach in assessing the relationships among governance mechanisms. The nature of the linear relationships has not answered the lingering question making this study crucial. The study follows the configurational theories that for IT governance to improve performance, all the governance mechanisms much be implemented coherently. We used Cluster analysis to assess the nature of the configuration in the Ghanaian Financial Services Sector using 7 companies. Our findings confirm our theory that to improve performance, IT Governance mechanisms must be implemented coherently. However, in a fast‐changing environment, there is the need to increase focus on technological mechanisms to provide timely information for decision making, collaboration and reduce information asymmetry. As a contribution to practice, this study recommends that policy makers in the financial space should emphasize the need for adequate IT Governance implementations with the right configuration. Companies in the pension and savings and loan sectors should be encouraged to adopt more technological mechanisms.
Description of the instantaneous stress drop behavior of a cornstraw-potato residue mixture based on stress relaxation models

Studying the stress relaxation characteristics can provide important process parameters for the granulation and briquetting of biomass materials. In this study, a generalized Maxwell model and fractional model were established to describe and analyze the stress instantaneous drop behavior of a cornstraw-potato residue mixture during the stress relaxation process. Stress relaxation characteristic parameters, e.g., the stress instantaneous drop time, were obtained. Using this information, the influence of the compression speed on the stress instantaneous drop time, stress relaxation time ratio, and other parameters were analyzed. In addition, the regression model of the compression frequency and compression speed was established, which provided a method for determining the appropriate compression frequency of the molding equipment according to the compression speed.
Developing a battery of measures for unobtrusive indicators of organisational culture: a research note

Abstract Measuring organisational culture is important for detecting the values and practices that increase organisational risk (e.g., unethical conduct). Self-report methods (e.g., surveys) are mostly used to study culture: however, due to reporting biases and sampling limitations, and the rapid advance of digital data, researchers have proposed unobtrusive indicators of culture (UICs; e.g., drawn from social media, company reports, executive data) as a supplementary methodology for identifying organisations at risk of failure. A UIC is a single measure of organisational culture drawn from data collected without engaging employees, and research using UICs is in its nascent stage. Although various data sources have been established for studying culture unobtrusively, researchers have yet to explore the application of multiple UICs drawn from different data sources. To investigate this, we developed an experimental battery of 83 UICs drawn from seven data sources (e.g., company earnings calls, employee online reviews, executive data), applying diverse analyses (e.g., natural language processing, quantitative analysis of behavioural data) to measure eight dimensions of culture (e.g., governance, integrity). We then applied the battery to assess 312 large European companies. We found that the UICs could distinguish between companies and different industries, and one dimension (customer focus) was associated with an outcome variable commonly used in culture research (Return on Capital Employed). However, we were not able to establish a coherent set of statistically reliable dimensions due to the clustering of UICs by data source. This clustering likely occurred because data sources reflected the values and practices of different stakeholders (e.g., employees, managers), which underscores a conceptualisation of culture that is focused less on shared values across an institution, and more on the values, priorities, and practices experienced by different sub-groups. Future research could structure UICs according to data sources and apply UICs to examine the causes of organisational failure.
Aspects of finite temperature field theories in Ads/CFT

In this dissertation I study some properties of field theories at finite temperature using the AdS/CFT correspondence. I present a general proof of an "inheritance principle" satisfied by a weakly coupled SU(N) (or U(N)) gauge theory with adjoint matter on a class of compact manifolds (like S3). In the large N limit, finite temperature correlation functions of gauge invariant single-trace operators in the low temperature phase are related to those at zero temperature by summing over images of each operator in the Euclidean time direction. As a consequence, various non-renormalization theorems of Af = 4 SuperYang-Mills theory on S3 survive at finite temperature. I use the factorization of the worldsheet to isolate the Hagedorn divergences at all orders in the genus expansion and to show that the Hagedorn divergences can be re-summed by introducing double scaling limits. This allows one to extract the effective potential for the thermal scalar. For a string theory in an asymptotic anti-de Sitter (AdS) spacetime, the same behavior should arise from the boundary YangMills theory. Introducing "vortex" contributions for the boundary theory at finite temperature I will show that this is indeed the case and that Yang-Mills Feynman diagrams with vortices can be identified with contributions from boundaries of moduli space on the string theory side. Finally, I consider the shear viscosity to entropy density ratio in conformal field theories dual to Einstein gravity with curvature square corrections. For generic curvature square corrections I show that the conjectured viscosity bound can be violated. I present the calculation in three different methods in order to check consistency. Gauss-Bonnet gravity is also considered, for any value of the coupling. It is shown that a lower bound (lower than the KSS bound) on the shear viscosity to entropy density ratio is determined by causality in the boundary theory. Thesis Supervisor: Hong Liu Title: Assistant Professor of Physics
MINERνA neutrino detector calibration

MINERνA is a neutrino scattering experiment that uses Fermilab’s NuMI beamline. Its goal is to measure cross-sections for neutrino scattering from different nuclei. Precise knowledge of these cross-sections is vital for current and future neutrino oscillation experiments. In order to measure these values to a high degree of accuracy, it is essential that the detector be carefully calibrated. Here, we describe in-situ calibration and cross-checks.
Comparison of C3 Photosynthetic Responses to Light and CO2 Predicted by the Leaf Photosynthesis Models of Farquhar et al. (1980) and Goudriaan et al. (1985)

The leaf photosynthesis models developed by Farquhar et al. (1980, https://doi.org/10.1007/BF00386231) (FvCB) and Goudriaan et al. (1985, https://doi.org/10.1007/978‐1‐4899‐3665‐3_10) (G85) are both used in Earth system and weather models to quantify ecosystem carbon assimilation. Despite their common role, a systematic comparison between these two photosynthesis models is currently lacking in scientific literature. In this technical report we compared the two models in a systematic way. Hereto we performed a comparative analysis of the model structures as well as the modeled responses of photosynthesis to light and CO2 at leaf level. To facilitate future model comparison, we also constructed a lookup table that presents FvCB model parameters fitted to CO2‐response curves from G85 in a wide natural range in photosynthetic capacity at standardized temperature. The structure of the FvCB model differs fundamentally from the G85 model as the FvCB model considers rate‐limiting processes due to Rubisco capacity, electron transport and triose phosphate utilization in parallel, whereas the G85 model considers Rubisco activity and triose phosphate utilization limitation to act in series scaled with quantum use efficiency. The models also differ fundamentally in terms of the parametrization of dark respiration. Still, both models calculate near‐similar responses of photosynthesis to changes in light and CO2 across a wide range in photosynthetic capacity with only two free parameters each. Our work thereby highlights functional similarities between these model approaches despite fundamental differences in model structure. Hence, standardized parameter sets that yield similar photosynthesis responses to light and CO2 may facilitate intercomparison of Earth system and weather models.
Black Fathers Rising: A QuantCrit Analysis of Black Fathers’ Paternal Influence on Sons’ Engagement and Sense of School Belonging in High School

ABSTRAC This QuantCrit analysis considers Black fathers’ influence on their sons’ engagement and sense of belonging in urban intensive and emergent high schools. Canonical correlations show a significant relationship between Black fathers’ paternal influence and their sons’ engagement and sense of belonging in school. We discuss two QuantCrit interpretation strategies to contextualize and recenter race via Black fathers’ experiential knowledge. Within the proper social-cultural context, these results illuminate a unique paternal educational habitus among Black fathers, which focuses on high levels of academic engagement with a family-centric locus of influence on their sons’ sense of belonging.
Tool condition monitoring for the chipboard drilling process using automatic, signal-based tool state evaluation

An automatic approach to tool condition monitoring is presented, with the best solution achieving overall accuracy of 94.33% and 9 misclassification errors. In the wood industry, cutting tools need to be evaluated periodically. This is especially the case when drills are concerned; since when dulled, the resulting poor-quality product may generate loss for the manufacturing company, due to the need to discard it during quality control. Each tool can be classified either as useful or useless, and the second type should be exchanged as fast as possible. Manual evaluation of tools is time consuming, which results in production downtime. This problem requires a faster, automated, and precise solution for the work environment. In response to this issue, an ensemble algorithm was developed. Different signals were collected for the input data, including feed force, cutting torque, noise, vibrations, and acoustic emission. Based on those signals, a set of 152 initial features was generated, while after feature selection 19 of them were used by the classifiers. Different algorithms were tested and evaluated in terms of overall accuracy and number of errors. The best classifiers were used to prepare ensemble solution, which was able to classify the tools accurately, with very few errors between recognized classes.
Ibuprofen Reduces Testosterone Level in Women With Polycystic Ovary Syndrome

Abstract Context Hyperandrogenism is a central feature of polycystic ovary syndrome (PCOS). In vitro studies have demonstrated that inflammatory stimuli promote whereas ibuprofen inhibits androgen production by ovarian theca-interstitial cells. Objective This work aimed to determine the effects of nonselective inhibitor of cyclooxygenases COX-1 and COX-2 on testosterone levels. Methods A prospective pilot study took place in an academic hospital of women with PCOS defined according to Rotterdam criteria (N = 20). Evaluations were taken at baseline and after 3 weeks of ibuprofen administration (400 mg twice a day or 400 mg 3 times a day, respectively, in women with weight < and ≥ 70 kg). The main outcome measure was total serum testosterone. Results Ibuprofen administration was associated with a decline of total testosterone from 0.75 ± 0.06 ng/mL to 0.59 ± 0.05 ng/mL (P = .008). There was no statistically significant change in the levels of other relevant hormones including dehydroepiandrosterone sulfate, gonadotropins, and insulin. Multiple regression analysis identified the greatest decline of testosterone was independently predicted by baseline testosterone level (P = .004) and by baseline insulin sensitivity index (P = .03). Conclusion Nonselective inhibition of COX-1 and COX-2 leads to selective reduction of testosterone consistent with direct inhibitory effect on ovarian steroidogenesis.
Enterprise Architecture for Network Organizations: A Research Design to Investigate What Elements of EA Help to Reduce Administrative Burdens in Healthcare

Healthcare organizations operate within a network of governments, insurers, inspection services and other healthcare organizations to provide clients with the best possible care. The parties involved must collaborate and are accountable to each other for the care provided. This has led to a diversity of administrative processes that are supported by a multi-system landscape, resulting in administrative burdens among healthcare professionals. Management methods, such as Enterprise Architecture (EA), should help to develop and manage such landscapes, but they are systematic, while the network of healthcare parties is dynamic. The aim of this research is therefore to develop an EA framework that fits the dynamics of network organizations (such as long-term healthcare). This research proposal outlines the practical and scientific relevance of this research and the proposed method. The current status and next steps are also described.
The effect of single dose prophylactic vancomycin before semi-permanent catheterization to prevent catheter related infection; a randomized controlled trial, phase II

Introduction: Catheter-related infections are a common complication and a major cause of morbidity and mortality in hemodialysis patients with tunneled central venous catheters. The optimal strategy for the management and prevention of catheter-related infections is unclear. Objectives: This study is aimed to evaluate the single-dose prophylactic vancomycin efficacy before semi-permanent catheterization to prevent catheter-related infection. Patients and Methods: This randomized double-blind controlled clinical trial was conducted on patients with chronic renal failure requiring hemodialysis and insertion of a double-lumen central venous catheter admitted to Ahvaz Golestan Hospital. The intervention group (n=30) received 1 g of vancomycin intravenously one hour before catheter insertion and the control group (n=30) received an equal amount of normal saline. The incidence of catheter-related infections and other complications for 6 months was evaluated. Results: During the 6-month follow-up, hospitalization due to catheter-related infection and the need for antibiotic administration was observed in 9 patients (30.0%) who received vancomycin and 14 patients (46.7%) in the control group (P=0.184). Catheter extraction due to infection was observed in 4 patients of the vancomycin group (13.3%) and 6 patients of the control group (20.7%) (P=0.451). Complications other than infection were observed in four patients (13.3%) in each group (P=1.000). The mean time to onset of infection was 2.43 ±0.38 months in the control group and 3.85 ± 0.42 months in the vancomycin group (P=0.002). Conclusion: Although a single dose of intravenous vancomycin one hour before insertion of a bi-luminal hemodialysis catheter did not show a significant effect on preventing catheter-related infections over 6 months, it significantly delayed the onset of infection. Trial Registration: The trial protocol was approved by Iranian Registry of Clinical Trial (Ethical code: IR.AJUMS.HGOLESTAN.REC.1399.106 and IRCT code: IRCT20201206049617N1; https://www.irct.ir/trial/52832).
Low-complexity trainable denoising filter structure for image recognition applications

Abstract. Even in modern imaging equipment, different types of noise make their way into the images especially under bad lighting conditions and rough communication channels. While applying denoising filters, the preservation of the edge in images has always been an essential albeit a difficult task. This is particularly important for accuracy of further image processing tasks, such as recognition. We described a denoising approach to process noisy images specific for the task of classification with minimal impact on image resolution using low-complexity operations. Specifically, support vector machine-based machine learning classifiers have been proposed to dynamically select an appropriate filtering kernel while processing individual pixels in the input image. The selection is based on the image features in a local window. The provided experimental results on standard dataset prove that the proposed scheme performs as well as contemporary complex convolutional neural network (CNN)-based approaches for the task of denoising images before classification in the presence of a variety of mixed-type noise. Moreover, the proposed filtering approach can run at much higher speeds than their CNN-based counterparts while delivering similar or better performance. The proposed framework has been made publicly available as open-source code to facilitate further work by researchers and practitioners interested in this area.
Validation of a hybrid coordinate ocean model for the Indian Ocean

An eddy-permitting HYbrid Coordinate Ocean Model (HYCOM) configured for the Indian Ocean has been validated using both in-situ and satellite observations. The present work focuses on a detailed study of the model’s capability to simulate the major surface and subsurface variables realistically. Weekly data from the model for eight years from 1994 to 2001 are used for the evaluation of the surface data. The model simulation of the circulation patterns in the Indian Ocean for both the monsoon seasons and the transition periods matches well with the observations. Comparisons between model and satellite observations for the sea surface temperature (SST) patterns and its temporal evolution showed that the model produces realistic SSTs. The sea level anomalies (SLA) from the model compared with those from the altimeter data confirmed that the model is in good agreement with the observed SLA. A detailed comparison of results from the daily data of the model with the Argo profiles, for the years from 2002 to 2004 showed that the model has a diffuse thermocline with warming in the subsurface waters, but overall, the model simulates the subsurface temperature and salinity patterns well. The validation of the model indicates that the model results are satisfactory and that with improvements in some of the model configurations, it can be implemented in an operational forecasting system for the Indian Ocean.