Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis and characterization of Fe3O4@SiO2 sub-nano core/shell with SiO2 derived from rice husk ash

This study aims to synthesize and characterize Fe3O4@SiO2 sub-nanoparticles (SNPs) with high saturation magnetization (SM). The research process was conducted in simple and environmentally friendly conditions. The results of ultraviolet-visible (UV-Vis) spectroscopy and X-ray diffraction (XRD) analysis presented that the Fe3O4@SiO2 SNPs were well formed and the phase change of Fe3O4 NPs did not happen in Fe3O4@SiO2 SNPs. Transmission electron microscope (TEM) analysis showed that the Fe3O4@SiO2 SNPs are in a fairly spherical shape with a core/shell structure and a diameter in a range of 100 nm to 500 nm. Fourier transform infrared spectrometry (FT-IR) spectra of Fe3O4@SiO2 SNPs presented some absorption peaks indicating the existence of Si-O-Si, O-Si-O, Fe-O and Fe-O-Si. The SM of Fe3O4 particles and Fe3O4@SiO2 SNPs determined via vibrating sample magnetometer (VSM) were 50.9 emu.g−1 and 19.5 emu.g−1, respectively. All the above results provide clear evidence that the Fe3O4 particles were coated by SiO2 to form sub-nano core/shell with great SM.
DAM: Deadblock Aware Migration Techniques for STT-RAM-Based Hybrid Caches

Last Level Caches (LLCs) play a critical role in reducing the number of costly off-chip memory accesses. Hence, there is a demand to make the LLCs larger to meet the requirements of growing dataset size of emerging data-intensive applications. Non-volatile STT-RAM-based caches with high memory density are a promising alternative to satisfy such a demand. However, STT-RAM-based caches have high write-latency and write energy. Therefore, researchers proposed a unified cache consisting of both SRAM and STT-RAM portions to handle expensive writes in these large hybrid LLCs. However, these large LRU-managed LLCs still remain underutilized due to the presence of a significant fraction of deadblocks (zero-reuse blocks) in them. By choosing the deadblock as an eviction candidate, we show a significant reduction in the LLC misses. Our work considers the entire set of the hybrid cache to select the deadblock as an eviction candidate. Therefore, we propose Deadblock-based Victim Selection (DVS), a deadblock-aware replacement policy. We observe that in up to 40 percent of cases, evicting a deadblock on an LLC miss requires migration of a cache block within the cache set. To incorporate this opportunity into DVS, we augment it with a cache block migration strategy and propose Deadblock-based Migration (DM) policy. The detailed evaluation on the SPEC CPU2006 workloads shows that DVS and DM enhance the performance of the system by up to 13 and 52 percent, respectively. Our results demonstrate that a cache replacement policy that is both deadblock-aware and migration-aware is essential in improving the performance of large hybrid LLCs.
Commuters’ Perceptions on Service Quality of Bus Rapid Transit Systems: Evidence from the Cities of Ahmedabad, Surat and Rajkot in India

Urban public transport is gaining significant importance in today’s world. This is evident from the fact that it has found its place in United Nations Development Programme’s Sustainable Development Goals in the eleventh goal pertaining to ‘Sustainable cities and communities’. The competitiveness of the cities largely depends on the robustness of their transport systems. In India there has been huge spending on the public transport projects in cities across the country. Ahmedabad, Surat and Rajkot from Gujarat, India have been the beneficiaries of these investments. Capturing the demand side quality of services is very important for such projects and hence the attempt has been made to study whether the commuters’ perceptions on quality of services of Bus Rapid Transit systems vary across different demographic cohorts. There are nine demographic cohorts used for the study. SERVPERF model has been adopted to study the performance of Bus Rapid Transit systems in the said citied. The performance is evaluated over the six factors namely; tangibles, empathy, cleanliness, reliability, safety and affordability. It has been found that Surat tops among the three cities followed by Rajkot and Ahmedabad on various service quality factors. Also commuters’ perception towards quality of service dimensions vary across demographic cohorts like gender, time of travel, education, employment status, length of patronization and purpose of trip.
Commonality of Emotional Trauma in Performing Arts: Implications for Training Programs

This article examines Adverse Childhood Experiences (ACE) scores among university performing arts students, the role of trauma as a muse and creative outlet, and attraction to the performing arts as a result of experienced trauma. Descriptive and Chi Square analysis reveal significant concentrations of ACE scores were discovered in 3 of the 10 ACE categories for performing arts majors, specifically psychological abuse, emotional neglect, and having a family member with mental illness. Additionally, performing arts students (n = 95) had a higher total average ACE score compared to other majors (n = 322). Research indicates a strong correlation between number of ACE scores and negative physical and psychological outcomes in adults (Felitti et al., 1998). Numerous methods centered on difficult emotions are employed to assist performing artists in honing their craft, physically, cognitively, and psychologically; thereby creating a complex relationship between creative inspiration from past traumatic events and destructive force to the whole person. These dynamics result in implications for performing arts preparatory programs, such as how to address these issues in their curriculum for holistic education and development of one’s artistic range and abilities.
An mHealth Physical Activity Intervention for Latina Adolescents: Iterative Design of the Chicas Fuertes Study

Background Only 3% of Latina teens meet the national physical activity (PA) guidelines, and these habits appear to persist into adulthood. Developing effective interventions to increase PA in Latina teens is necessary to prevent disease and reduce disparities. Mobile technologies may be especially appropriate for this population, but mobile health (mHealth) intervention content must be designed in collaboration with the target population. Objective This study aims to develop an mHealth PA intervention for Latina adolescents using a multistage iterative process based on the principles of human-centered design and multiple iterations of the design phase of the IDEAS (Integrate, Design, Assess, Share) framework. Methods On the basis of the feedback from a previous pilot study, the planned intervention included visual social media posts and text messaging, a commercial wearable tracker, and a primarily visual website. The development of the requested mHealth intervention components was accomplished through the following 2 phases: conducting focus groups with the target population and testing the usability of the final materials with a youth advisory board (YAB) comprising Latina adolescents. Participants for focus groups (N=50) were girls aged 13-18 years who could speak and read in English and who were recruited from local high schools and after-school programs serving a high proportion of Latinos. Facilitated discussions focused on experience with PA and social media apps and specific feedback on intervention material prototypes and possible names and logos. Viable products were designed based on their feedback and then tested for usability by the YAB. YAB members (n=4) were Latinas aged 13-18 years who were not regularly active and were recruited via word of mouth and selected through an application process. Results The focus group discussions yielded the following findings: PA preferences included walking, running, and group fitness classes, whereas the least popular activities were running, swimming, and biking. Most participants (n=48, 96%) used some form of social media, with Instagram being the most favored. Participants preferred text messages to be sent no more than once per day, be personalized, and be positively worded. The focus group participants preferred an intervention directly targeting Latinas and social media posts that were brightly colored, included girls of all body types, and provided specific tips and information. Modified intervention materials were generally perceived favorably by the YAB members, who provided suggestions for further refinement, including the shortening of texts and the incorporation of some Spanish phrases. Conclusions Latina teens were generally enthusiastic about an mHealth PA intervention, provided that the materials were targeted specifically to them and their preferences. Through multiple iterations of development and feedback from the target population, we gained insight into the needs of Latina teens and joined with industry partners to build a viable final product.
PTSD as a future-oriented survival strategy

Posttraumatic stress disorder (PTSD) is generally conceptualized as a disorder of the past, with symptoms intruding into the present. By definition, the disorder occurs after a traumatic event, hence the term post-traumatic. PTSD and its symptoms, including flashbacks and hyper-arousal, can also be conceptualized as a future-oriented survival strategy, however. Looking at PTSD as a disorder of the future leads to an additional set of treatment strategies and techniques. These are illustrated with a case vignette.
A Deep Learning Framework for Coronavirus Disease (COVID-19) Detection in X-Ray Images

Coronavirus, a large family of viruses, causes illness in both humans and animals. The novel coronavirus (COVID-19) came up in Wuhan in December 2019. This deadly COVID-19 pandemic has become very fast-spreading and currently present in several countries worldwide. The timely detection of patients who have COVID-19 is vitally important. To this end, scientists are working on different detection methods.In this paper, a grid search (GS) and pre-trained model aided convolutional neural network (CNN) model is proposed to detect COVID-19 in X-Ray images. In the proposed method, the GS method is employed to optimize the hyperparameters of CNN, which directly affects classification performance. Three pre-trained CNN models (GoogleNet, ResNet18 and ResNet50), which can be used for classification, feature extraction and transfer learning purposes were used for transfer learning in this study. The proposed method was trained using the training and validation subdatasets of the collected dataset and detail evaluations are presented according to different performance metrics. According to the experimental studies, the best results were obtained with the GS and ResNet50 aided model.
Marks, and their proportioning between examinations, tutorials and assignment, as determinants of the performance of nursing students in a pharmacology course

Background In programs with higher proportions of marks allocated to ongoing assessment, the students have higher overall marks than those with a lower proportion allocated to assessment. Little or no attention has been made to how the allocation affects the academic success of students in individual courses. The purpose of this study was to determine how the allocation of marks to examinations, tutorials and an assignment affects the performance of nursing students in a pharmacology course. Methods For students who passed a pharmacology course (i) the marks for examinations and ongoing assessment (tutorials and/or an assignment) were compared, and (ii) regression line and correlation analysis was undertaken to determine any association between these marks. In addition, for completing students, modelling was undertaken to determine the effects of changing the allocation of marks on passing and failing rates. Results Nursing students who passed a pharmacology course obtained significantly lower marks in examinations than ongoing assessment, and for the ongoing assessment, lower marks in the assignment than tutorials. Regression line analysis showed that the marks in ongoing assessment (tutorials and/or the assignment) versus examination marks were a poor line-fit. The correlation coefficients between ongoing assessment and examinations were weak to moderate. A high percentage of students passed the course (> 90%) and, modelling for completing students, showed that decreasing the marks for examination would have led to slightly more students passing the pharmacology course with higher grades. In contrast, increasing the marks for examination would have dramatically decreased the number of students passing the course, and their grades. Conclusions The allocation of marks can have a major effect on student performance. As ongoing assessment is not a good predictor of performance in examination this has implications for students who rely on passing examinations for their advancement. For instance, nursing students in some countries (e.g. USA) are required to pass examinations prior to registration, whereas in others (e.g. Australia) they are not. Consideration needs to be given as to whether it is appropriate for nursing students who fail examinations to pass courses/programs.
A Review of Recent Researches and Reflections on Geospatial Artificial Intelligence

The technological progress in the field of artificial intelligence (AI) has brought new opportunities and challenges to the intelligent development and innovative research in geospatial related fields. Geospatial artificial intelligence (GeoAI) refers to the interdisciplinary research direction that combines geography, earth science and artificial intelligence, and seeks to solve major scientific and engineering problems in human-environmental interaction systems through the research and development of spatial intelligence in machines to improve the dynamic perception, intelligent reasoning and knowledge discovery of geographic phenomena and earth science processes. This paper briefly summarizes the historical origins of GeoAI development, introduces spatially explicit and implicit AI models, reviews recent GeoAI research and applications(including spatial representation learning, spatiotemporal prediction and spatial interpolation, monitoring of geographic resources and environment, cartography, and geo-text data semantic analysis), and identifies several potential research challenges and directions for the future development of GeoAI.
Comparison between parents’ and patients’ satisfaction level towards cleft management using Cleft Evaluation Profile

Cleft lip and/or palate (CLP) are common facial birth defects that occur among the children and adults (Noor et al., 2007). The occurrence of CLP was reported to be approximately 1 in 700 live births in Europe (Ali & Sahito, 2015). Meanwhile, 1 in 611 children in Malaysia was born with CLP in 2007 (NOHSS, 2007). A recent study revealed that Asians are more commonly affected with this cranio-facial abnormality compared to Caucasians (Natsume & Kawai, 1986).
A New Microscopic Approach to Traffic Flow Classification Using a Convolutional Neural Network Object Detector and a Multi-Tracker Algorithm

Traffic congestion is a significant issue in urban areas and can cause adverse effects. In this paper, our proposal categorizes the traffic activity from video through three steps: vehicle monitoring, feature extraction, and classification. The vehicle monitoring step comprises an object detector based on a convolutional neural network and multi-object tracker. The feature extraction step uses information related to each detected vehicle, in various points of the road, to represent the traffic condition through three features: density, flow, and velocity. We tested on the UCSD dataset and achieved the best performance with 98.82% of accuracy, which outperformed the state-of-the-art methods.
Optimal Control of Oxidizing Rate for Iron Precipitation Process in Zinc Hydrometallurgy

In the iron removal process in zinc hydrometallurgy, the reaction conditions to form goethite precipitate are difficult to achieve, in which the oxidizing rate of ferrous ion has to be strictly controlled to remove the iron ion from leach solution by goethite. On the basis of dynamic model for iron removal process and according to the forming conditions of goethite precipitate and procedure requirements, the optimal setting model of reactor outlet ferrous ion concentration is investigated in this paper. An optimal control model of oxidizing rate for iron precipitation process is established. The optimal control problem is transformed to a nonlinear mathematical programming problem by control parameterization method. The mathematical programming problem is then solved utilizing state transition optimization algorithm to obtain the optimal control of oxygen and zinc oxide to make the oxidizing rate in the best conditions of forming goethite precipitate. Numerical simulations validate that the optimal control of oxidizing rate can not only satisfy the forming conditions of goethite precipitate but also stabilize the production process.
An advanced ion guide for beam cooling and bunching for collinear laser spectroscopy of rare isotopes

AN ADVANCED ION GUIDE FOR BEAM COOLING AND BUNCHING FOR COLLINEAR LASER SPECTROSCOPY OF RARE ISOTOPES By Bradley Ryan Barquest A next generation beam cooler and buncher has been developed and commissioned at NSCL to provide bunched, low energy spread ion beams for collinear laser spectroscopy of rare isotopes. Low energy spread beams reduce the Doppler broadening observed in the fluorescence spectrum, thus improving the resolution achievable in a measurement. Bunched beams permit the reduction of background in fluorescence spectra, thus dramatically improving the signal to noise ratio of the measurement. The beam cooler and buncher features a novel electrode design intended to simplify construction and maintenance, as well as permit the use of large radiofrequency (RF) amplitudes for more efficient beam cooling, especially in the case of high beam currents. A series of ion optical simulations were carried out to determine the design parameters and anticipated bunched beam characteristics. Additional studies using a prototype electrode structure and ion guide system were undertaken to test the performance of the proposed design. The ion guide also serves as a component of the NSCL gas stopping facility. Based on the results of simulation, prototype and ion guide test results, the BECOLA beam cooler and buncher was developed and commissioned. Buncher efficiency, bunched beam energy spread, time width, and transverse emittance were measured using a stable ion source. In addition, the BECOLA collinear laser spectroscopy facility and the beam cooler and buncher were commissioned using a beam of the rare isotope K. The results of ion optical simulations, prototype tests, ion guide studies, and BECOLA cooler and buncher characterization measurements are presented and discussed. The results indicate a successful commissioning of the beam cooler and buncher, along with the rest of the BECOLA facility, with a rare isotope beam, and the systematic studies indicate efficient delivery of low emittance, low energy spread bunched beams well suited for collinear laser spectroscopy.
Agronomic Efficiency of Herbicide Tolerant Crops in Peninsular India—A Review

Crops made resistant to herbicides by biotechnology are being widely adopted in various parts of the world and several herbicide resistant crops have become available in many countries for commercial cultivation. But in India, the technology of herbicide tolerant crops is in initial stage of field evaluation. Hence, field trials have been carried out to evaluate and consolidate the agronomic advantages of herbicide tolerant transgenic cotton and maize. Herbicide tolerant stacked traits of maize and cotton have been evaluated under Bio-safety Research Level (BRL I) as confined field trials for its agronomic efficiency on weed control and enhanced crop productivity at Tamil Nadu Agricultural University (TNAU), Coimbatore and Punjab Agricultural University (PAU), Ldhiana for many years. In both crops, potassium salt formulation of glyphosate was sprayed at different doses (900, 1,350, 1,800, 2,700, 3,600 and 5,400 g a.e./ha twice at 25 days after sowing (DAS) and 60 DAS in cotton and 900, 1,800 and 3,600 g a.e. /ha at 25 DAS in maize). Evaluation was made on weed control efficiency, phyto-toxicity on crops, yield and economics and carry over effects on the succeeding crops. Application of glyphosate at 2,700 g a.e. /ha recorded lower weed density, dry weight and higher weed control efficiency (WCE) in cotton. Post-emergence (POE) glyphosate at 900, 1,800 and 3,600 g a.e. /ha registered lower weed density, dry weight and higher WCE in transgenic Hishell and 900 M Gold and in 30V92 and 30B11 corn hybrids. Post-emergence application of glyphosate in transgenic maize hybrids did not affect the germination percent, vigour and yield of succeeding green gram in the transgenic maize trials and sunflower, soybean and pearl millet in cotton trials. Phytotoxicity symptoms were not observed in cotton with glyphosate at lower doses viz., 900, 1,350, 1,800 and 2,700 g a.e. /ha. Higher doses viz. 3,600 g a.e. /ha and 5,400 g a.e. /ha were noticed with phytotoxicity symptoms at early stages of herbicide application. Glyphosate applied at 900, 1,350, 1,800 and 2,700 g a.e. /ha recorded more number of bacteria, fungi and actinomycetes compared to atrazine treatments. Higher grain yield was recorded with POE application of glyphosate at 900, 1,800 and 3,600 g a.e. /ha in Hishell and 900 M Gold transgenic hybrids and higher net return and benefit cost ratio were recorded in glyphosate at 1,800 g a.e. /ha in transgenic 900 M Gold in all the four seasons. Post-emergence application of glyphosate at 900 g a.e. /ha and 1,800 g a.e. /ha registered higher grain yield in transgenic 30V92 and 30B11 corn hybrids. In maize and cotton transgenic crops, post-emergence weed management with glyphosate proved to be the better management option for the control of weeds.
Does the efficiency of public investment in human capital affect the country’s economic development?

Modern theories of economic growth emphasize the meaning of the investment in human capital as the most profitable. Although the positive relationship between public investment in human capital and the country’s economic development is commonly accepted, the answer to the question of whether the efficiency of this investment is crucial for welfare, is no longer so obvious. The aim of this study is to recognize the relationship between the technical efficiency of public spending on human capital and the economic development in the sample of 28 EU states. For this purpose DEA method was applied to evaluate the efficiency of public expenditure on healthcare and education in order to build human capital. Then, DEA scores were correlated with countries’ economic development indicators expressed by GDP per capita. The study proves that the commonly accepted dependency between the potential of human capital and countries’ welfare is not reflected in the correlation between countries’ GDP per capita and the DEA efficiency of public investment in human capital