Miracle-dz/UniFAR-FTUs huggingface dataset:
Economical Recovery of By-products in the Mining Industry

The U.S. Department of Energy (DOE) Office of Industrial Technologies, Mining Industry of the Future Program, works with the mining industry to further the industry's advances toward environmental and economic goals. Two of these goals are (1) responsible emission and by-product management and (2) low-cost and efficient production (DOE 1998). DOE formed an alliance with the National Mining Association (NMA) to strengthen the basis for research projects conducted to benefit the mining industry. NMA and industry representatives actively participate in this alliance by evaluating project proposals and by recommending research project selection to DOE. Similarly, the National Research Council (NRC) has recently and independently recommended research and technology development opportunities in the mining industry (NRC 2001). The Oak Ridge National Laboratory (ORNL) and Colorado School of Mines engineers conducted one such project for DOE regarding by -product recovery from mining process residue. The results of this project include this report on mining industry process residue and waste with opportunity for by-product recovery. The U.S. mineral processing industry produces over 30,000,000 metric tons per year of process residue and waste that may contain hazardous species as well as valuable by-products. This study evaluates the copper, lead, and zinc commodity sectors which generate between 23,300,000 and 24,000,000 metric tons per year. The distribution of residual elements in process residues and wastes varies over wide ranges* because of variations in the original ore content as it is extracted from the earth's crust. In the earth's crust, the elements of interest to mining fall into two general geochemical classifications, lithophiles and chalcophiles** (Cox 1997). Groups of elements are almost always present together in a given geochemical classification, but the relative amounts of each element are unique to a particular ore body. This paper generally describes copper, lead, and zinc mining operations and their associated process wastes and residues. This description can serve as a basis for identifying those process residues and waste that contain both impurities and products which currently cannot be economically recovered. This information could be used to develop a market-based approach to by-product recovery by evaluating potential revenue generated from the sale of by-products along with innovative recovery techniques.
Patients as health influencers: motivations and consequences of following cancer patients on Instagram

ABSTRACT Patient health influencers have become new sources of information on social media. In our study, we investigated the motivations and consequences of following accounts of Instagram influencers from the nonprofit Blogger 4 Charity, all of whom have suffered from cancer and shared their experiences with their followers. Following a cross-sectional survey of 1,601 followers, we performed structural equation modelling to investigate how different types of followers varied according to motivation, information gain, and behaviour change. Whereas followers directly affected (i.e. have suffered from cancer) scored highest for social interaction and expression motivations for following the accounts, indirectly affected followers (i.e. have relatives or friends suffering from cancer) and general interest followers scored higher for perceived information gain and behaviour change induced by following them. Thus, following such social media accounts may help directly affected followers to emotionally cope with their health conditions via expressive, interactive activities and indirectly affected and general interest followers to gain information and adopt healthier behaviours.
QBD based Design and Characterization of Proniosomal Transdermal Delivery of Atenolol and Glibenclamide Combination: An Innovative Approach

There are numerous circumstances where chronic disease is associated with other disorders, especially in diseases like diabetes with noncommunicable disease risk factors, such as hypertension. This study shows a novel and innovative combinational proniosomal delivery of combination to beat the reactions by complex therapeutic regimen, and to improve patient compliance after controlling combinational transdermal delivery of Glibenclamide (GLB) and Atenolol (ATN) which have not been tried actually. To achieve the above reason, proniosomes were prepared and optimized utilizing Box-Behnken design. The ideal formulation was chosen by a point prediction method and formulation showed vesicle size of 562 ± 1.223 nm, entrapment efficiency of GLB & ATN 97.037 ± 1.43% and 96.230 ± 1.62% respectively which were found in concurrence with the predicted value. The optimized combinational proniosomal gel (OCPG) formulation was additionally assessed for in vitro drug release, In vitro drug permeation, and in vivo pharmacokinetic study. The OCPG formulation shows the greatest flux over the rabbit skin (128.609 ± 2.24 mg/cm/h and 322.054 ± 1.53 mg/ cm/h) of GLB and ATN respectively. The results indicated desired release and permeation profiles. OCPG showed significantly (p < 0.001) pharmacokinetic contemplate exhibited that transdermal proniosomal formulation demonstrated improvement in bioavailability of two drugs 129.30 and 174.62 times respectively as that of the oral formulation. Overall the results show that controlled release GLB and ATN provesicles offer a useful and promising transdermal delivery system for the treatment of type II diabetes and hypertension by using design. Henceforth this may be an achievement in treating diabetic hypertensive patient.
Statistical Method for the Evaluation of Railway Systems Modifications

This paper describes how railway production plans daily face random events. Therefore, before setting up modifications for the railway system (changing the network, new signaling system, new timetable, etc.), its robustness to stochastic events must be estimated. Tests cannot actually be carried out, which is why the SNCF uses a traffic simulator developed by its research department. Until now, the timetable robustness has been estimated by considering a few small incidents and their simulated consequences on train delays. The new approach we are working on consists of taking into account the stochastic dimension in the evaluation of robustness. The methodology is divided into three parts that: (1) identify the randomness to be taken into account when evaluating robustness; (2) study the robustness of the railway system to: determine experimental design, carry out simulations, aggregate results; and (3) evaluate the lack of precision in the results. The objective of this paper is to develop the required statistical methods and to design a decision tool following the three steps above. It will help the infrastructure managers to evaluate, in a statistical manner, the robustness of various railway system configurations.
A Gaussian Process Regression Model for Forecasting Stock Exchange of Thailand

A stock price index measures the change in several share prices, which can describe the market and assist investors in deciding on a specific investment. Thus, foreseeing the stock price index benefits investors in creating a better investment strategy. However, forecasting the stock price index can be challenging due to its non-linearity, non-stationary and high uncertainty. Gaussian process regression (GPR) is an attractive and powerful approach for prediction, especially when the data fluctuates over time with fewer restrictions. Besides, the GPR gains advantages over other forecasting techniques as it can offer predictions with uncertainty to provide margin errors. In this study, we evaluate the use of GPR to predict the stock price of Thailand (SET). The SET data are divided into 2 datasets; the data in the year 2015 - 2020 and the data in the year 2020 due to the massive change during the COVID-19 pandemic. The prediction results from the GPR are then compared to the machine learning approaches, artificial neural network (ANN) and recurrent neural network (RNN) using evaluation scores; the root mean square error (RMSE), the mean absolute error (MAE), the mean absolute percentage error (MAPE) and the Nash-Sutcliffe efficiency (NSE). The results indicate that the GPR is superior to the ANN and RNN for both datasets as it provides a high prediction accuracy. Moreover, the results suggest that the GPR is less sensitive to the number of input lags in the model. Therefore, the GPR is more favorable for the prediction of SET than the ANN and RNN. HIGHLIGHTS The Gaussian process regression (GPR) was applied to predict the stock price index of Thailand (SET) The predictive performance of the GPR was compared to artificial neural networks (ANNs) and recurrent neural networks (RNNs) The results indicate that GPR outperformed the other methods as it provided a high prediction accuracy along with prediction intervals GRAPHICAL ABSTRACT
Identifying capital for school improvement: recommendations for a whole school approach to ESD implementation

Abstract The present study explores how school improvement in combination with a teacher professional development (TPD) project influenced the implementation of education for sustainable development (ESD) in five Swedish schools, when employing a whole school approach. Interviews were conducted with three teachers from each school. Shulman and Shulman’s four forms of capital for capacity building were used as a framework for the data analysis. The impact of the project on the schools’ pedagogical activities varied considerably between the schools. The transformative potential in ESD was realized to a greater extent in the schools characterized by high levels of moral capital – i.e. trust – than in the schools characterized by more individual and traditional ways of working. Three general conclusions concerning ESD implementation are drawn: 1) Prior to launching a whole school project for ESD, it is desirable to make an inventory of the capacity building capital at participating schools, and to identify contextual factors constituting external pressure on the building of capital. 2) The school improvement project and the TPD need to be locally adjusted to the available capital. 3) A strategy for adapting the project to the various external pressures needs to be developed.
Noise-Resilient Depth Estimation for Light Field Images Using Focal Stack and FFT Analysis

Depth estimation for light field images is essential for applications such as light field image compression, reconstructing perspective views and 3D reconstruction. Previous depth map estimation approaches do not capture sharp transitions around object boundaries due to occlusions, making many of the current approaches unreliable at depth discontinuities. This is especially the case for light field images because the pixels do not exhibit photo-consistency in the presence of occlusions. In this paper, we propose an algorithm to estimate the depth map for light field images using depth from defocus. Our approach uses a small patch size of pixels in each focal stack image for comparing defocus cues, allowing the algorithm to generate sharper depth boundaries. Then, in contrast to existing approaches that use defocus cues for depth estimation, we use frequency domain analysis image similarity checking to generate the depth map. Processing in the frequency domain reduces the individual pixel errors that occur while directly comparing RGB images, making the algorithm more resilient to noise. The algorithm has been evaluated on both a synthetic image dataset and real-world images in the JPEG dataset. Experimental results demonstrate that our proposed algorithm outperforms state-of-the-art depth estimation techniques for light field images, particularly in case of noisy images.
Design of Mine Monitoring System Based on ZigBee Wireless Network Technology

The paper,a mine monitoring system framework based on ZigBee wireless sensor networks of studying IEEE802.15. 4 standard communication protocol is proposed.This paper mainly introduces the design of wireless sensor network node of temperature,humidity and gas oncentration monitoring in the coal mine,software and hardware of data acquisition and transmission are designed in mine wireless network monitoring system.The monitoring signal acquisition and wireless transmission are realized.This design solves a lot of monitoring of wireless networking,the mine monitoring system has been successfully applied.
Time-Driven Activity-Based Costing for Healthcare Provider Supply Chain Processes

In a time when healthcare costs continue to rise, nearly a third of hospital operating expenses are related to supplies, and the healthcare supply chain is complex, it is pertinent for healthcare providers to have a clear understanding of their healthcare supply chain process costs. Having a clear picture into how these costs are driven and where opportunities for cost reductions exist can support supply chain efficiencies. In this research, we develop a TimeDriven Activity-Based Costing (TDABC) supply chain cost management tool for healthcare providers. A TDABC management system can provide healthcare providers with valuable product and process supply chain cost information by investigating logistics activities, resource consumption, and time drivers. Based on prior expertise, existing literature, and a field study conducted with a 200-bed, not-for-profit hospital, a healthcare provider supply chain (HPSC) TDABC approach and supporting spreadsheet-based tool were developed to support cost measurement and management within the HPSC. ACKNOWLEDGEMENTS I would first like to thank my family for their unconditional love and support not only for the last 2 years but my whole life. To my dad for always encouraging me to move forward and “not let the turkeys get me down. ” Thank you dad for always being a phone call away and allowing me to vent when it was needed. También dedico este tesis para mi mama que me a enseñado que siempre debemos de reír y ser humildes. Gracias mama por tu honestidad, amor, y abrazos. For my brother who honestly is the best person I know and the reason I work so hard at everything I do. Thank you Miguel for your unconditional love, for calling me out when I am being crazy, and for being the best brother anybody could possibly wish for. Also the rest of my family and friends who have shaped me into what I am today, which hopefully is a kind and giving person. Lastly I would like to thank all the faculty and staff of the Industrial Engineering Department at the U of A. Thank you guys for a wonderful two years and making the move away from Texas that much more bearable. You guys are full of love and support and I couldn’t have asked for a better experience. DEDICATION I would like to dedicate this thesis to my family who have inspired and motivated me to follow my passions and be a beacon of God’s light to others, you guys mean everything to me. Thank you for always believing in me, even when I didn’t believe in myself. TABLE OF CONTENTS
Cross-linguistic gender congruency effects during lexical access in novice L2 learners: evidence from ERPs

ABSTRACT Herein we present electrophysiological evidence of extremely rapid learning of new labels in a second language (L2) for existing concepts, via computerized games. However, the effect was largely constrained by crosslinguistic grammatical gender congruency. We recorded ERPs both prior to exposure with the L2 and following a 4-day training session. Prior to exposure, no modulation of the N400 component was found as a function of the correct Match vs. Mismatch of audio presentation of words and their associated images. Post-training, a large N400 effect emerged for Mismatch compared to Match trials, but only for trials on which the L2 words shared grammatical gender in the learners' L1. Behavioral results showed that all L2 words were learned equally as well, independent of gender congruency across the L1 and the L2. The results demonstrate that crosslinguistic grammatical gender congruency influences lexical activation during the initial stages of establishing a new L2 lexicon.
Functional outcome of distal end femur fracture treated with locking compression plate

Aim of the study: The aim of this study is to assess the functional outcome of distal femur fracture treated with a locking compression plate. Materials and methods: The study was conducted from July 2019 to February 2021 at Dr BR Ambedkar Medical College and Hospital with follow-up period of six months. 20 skeletal mature patients fulfilling the inclusion criteria with distal end femur fractures were surgically treated with distal femoral locking compressive plate using a direct lateral approach. The clinical assessment was conducted for at least a period of 6 months postoperatively using the oxford knee scoring system. Results: At six months of follow-up, 10 patients achieved range between 120 to 140°, 9 achieved between 100 to 120 and 1 had 95° flexion. In the present study, 18 out of 20 cases (90%) showed a radiological union at 3 months’ follow-up. 2 cases (10%) had radiological union at 6 months (24 weeks) of follow-up. In the present study, 85% of cases that is 17 of 20 cases had Oxford Knee Score of more than 41, 2 cases that is 10% had a score between 34 and 40, and only 1 had a score between 27 and 33. In the present study, 17 cases, i.e., 85% showed excellent functional outcome, while 2 cases showed good and 1 case had a fair outcome. Conclusion: The use of LCP in distal femoral fracture promotes early radiological union, good knee range of movement and early recovery when fracture fixation is done following all the basic principles of fracture fixation. Finally, it can be concluded that the use of LCP provides a good functional outcome for distal femur fractures, particularly in osteoporotic bones.
Implementation of SKONI-Hybrid Intrusion Detection System to Mitigate Network Attacks

Intrusion Detection System (IDS) has been of interest to researchers for some time now and can provide advance warning against impending attacks due to its in-depth detection and logging of malicious activities. Most of the current intrusion detection systems have mainly concentrated on detection of intrusions with no mechanism incorporated to respond to such intrusions. Also popular intrusion detection systems detect attacks based on policy or signature and hence are able to detect known attacks only. However a hybrid intrusion detection system detects both known and unknown attacks. In this paper, we report the development of a hybrid intrusion detection system (SKONI-HIDS) that was implemented in the Department of Computer Science, University of Benin, in 2013 using Snort (an open source intrusion detection system) to detect known attacks and a statistical model to detect unknown attacks. SKONI-HIDS was trained for detection of unknown attacks using this statistical model. The information needed for training SKONI-HIDS was collected from a LAN consisting of a server (with Internet access), ten (10) clients and a switch. Clients on this network were assigned IP addresses: 192.168. 0.0/24 and 192.168. 1.0/24. We tested SKONI-HIDS by using live traffic on our LAN. The results were quite encouraging as SKONI-HIDS was able to detect real attacks performing both signature based and anomaly detection and finally, SKONI-HIDS was also able to prevent attacks from succeeding by automatically reconfiguring firewall rules.
PCR and Culture n Determination of Infectious Aortic Aneurysm

Infectious aortic aneurysm leads to poor prognosis and high mortality rate as high as 50% due to delayed/missed diagnosis. Early use of appropriate antibiotics and adequate surgical debridement would improve outcome of patients, which is dependent on diagnosis on time. It takes as long as 7 days before a certain bacterium could be isolated/biochemical identificated. It is difficult to differential these bacteria by the isolation/biochemical identification on time. Direct detection of a certain bacterium using molecular diagnostic assays such for PCR with specific primers is a preferred option for rapid diagnosis, but requires sophisticated laboratories. A high degree of clinical suspicion should be the key for a diagnosis of infectious aortic aneurysm in endemic areas.
Simulated Annealing for Neural Architecture Search

Gradient-based Neural Architecture Search (NAS) approaches have achieved remarkable progress in the automated machine learning community. However, previous methods would cause much search time and huge computation resources in a big search space for seeking an optimal network structure. In this work, we propose a novel Simulated Annealing algorithm for NAS, namely SA-NAS , by adding perturbations to the gradient-descent for saving search cost and boosting the predictive performance of the search architecture. Our proposed algorithm is easy to be adapted to current state-of-the-art methods in the literature. We conduct extensive experiments on various benchmarks where the results demonstrate the effectiveness and efﬁciency of our SA-NAS in reducing search time and saving computation resources. Compared to previous differentiable methods, our SA-NAS achieves comparable or better predictive performance under the same setting.
Exploring initial teacher education student teachers’ beliefs about reflective practice using a modified reflective practice questionnaire

ABSTRACT The proposition that teaching is a reflective profession is prominent within educational discourse. Theories that underpin reflection are a critical component of initial teacher education (ITE) programmes. This study aims to assess the reliability of the modified Reflective Practice Questionnaire (RPQ) in a population of ITE students; and to compare the study findings to other studies using the RPQ in other professions. This study reports cross-sectional findings for reflective capacity in ITE students undertaking three different ITE programmes, the Bachelor of Arts (Hons) (BA) Education [n=91], Professional Graduate Diploma in Education (PGDE) Primary [n=209] and Secondary [n=167], in one Scottish university. Findings show that the modified RPQ reliably assesses reflective capacity (Cronbach’s alpha 0.82), which differs depending on the programme of study followed. BA students’ reflective capacity is higher than that of PGDE (P) but is not different to PGDE (S) students. PGDE (P) students differing from BA students in terms of Reflection-in-Action (RiA), Self-Appraisal (SA), Confidence (general) (CG), and Confidence (communication) (CC), whereas PGDE (S) and BA students differ in terms of SA, CG CC and Stress interacting with Pupils (SiP). This study indicates student teachers’ reflective capacity is higher than those found in studies of other professions.