Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective and Efficient Learning at Scale

How to enable efficient and effective machine learning at scale has been a longstanding problem in modern artificial intelligence, which also motivates this thesis research. In particular, we aim at solving the following problems:1. How to efficiently train a machine learning model? 2. How to speed up inference after the model is trained? 3. How to make the model generalize better? We approach those problems from two perspectives: models and algorithms. On one hand, we design novel models that are intrinsically fast to train and/or test. On the other, we develop new algorithms with rapid convergence guarantee. Not surprisingly, the above three problem are not mutually exclusive and thus solving one of them might also benefit others. For example, 1) a new model that can enableparallel computation helps accelerate both training and inference; 2) a fast algorithm can save time for hyper-parameter tuning and/or make it affordable for training withmore data, which in return boosts the generalization performance. This thesis consists of two parts. The first part presents new machine learning models with a focus on sequential data such as natural language processing andquestion answering. Firstly, we propose a model, LSTM-Jump, that can skip unimportant information in text, mimicking the skimming behavior of human reading.Trained with an efficient reinforcement learning algorithm, this model can be several times faster than a vanilla LSTM in inference time. Then we introduce a text encoding model that totally discards recurrent networks, which thus fully supports parallel training and inference. Based on this technique, a new question-answering model, QANet, is proposed. Combined with data augmentation approach via backtranslation, this model stays at the No.1 place in the competitive Stanford Question and Answer Dataset (SQuAD) from March to Aug 2018, while being times fasterthan the prevalent models. It was also the deepest neural network model for NLP when invented. The second part proposes large scale learning algorithms with provable convergence guarantee. To enable fast training of neural networks, we propose a general gradient normalization algorithm for efficient deep networks training. This methodcan not only alleviate the gradient vanishing problem, but also regularize the model to achieve better generalization. When the amount of training data becomes huge, we need appeal to distributed computation. We are particularly interested in the ubiquitous problem, empirical risk minimization, and propose a few algorithms to attack the challenges posed by the distributed environment. We first show that a randomized primal-dual coordinate method DSPDC can achieve a linear convergence rate in the single-machine setting. Then by further leveraging the structural information of the problem, we propose an asynchronous algorithm DSCOVR, which enjoys a linear convergence rate as well on the distributed parameter server environment,by executing periodical variance reduction.
Behavioral Model for RF Power Transistors Based on Canonical Section-Wise Piecewise Linear Functions

A new, frequency-domain, behavioral modeling methodology for radio frequency (RF) power transistors, based on canonical section-wise piecewise linear (CSWPL) functions, is presented in this article. The basic theory of the proposed model for fundamental, harmonic, and dc responses is provided within. Compared with the existing nonlinear behavioral models, which require tables of coefficients to account for varying input powers, the model described in this article is able to predict transistor behavior over the entire Smith chart, at different levels of input power, from the linear region to strongly nonlinear region, with only a single set of model coefficients. Model verification is performed at fundamental, harmonic, and dc frequencies through comparisons with simulated data from a reference nonlinear circuit model and with experimental data from separate 10- and 2-W GaN HEMT devices, over a wide range of load conditions. The models can predict, accurately, the optimal area on the Smith chart for maximum fundamental output power. Furthermore, the ability of the model to interpolate across input power levels is also tested, with excellent fidelity to the simulated and measured data obtained. Compared with a 2-D polynomial-based model, the proposed method provides for a more accurate prediction, while using fewer model coefficients.
Assessment of Antihelminthic Efficacy of Mebendazole 500 mg against Soil- Transmitted Helminths in a High Risk Area of Cameroon

Background: The three major soil-transmitted helminths (STHs) (Ascaris lumbricoides, Trichuris trichiura and Necator americanus/Ancylostoma duodenale) cause the highest burden on public health particularly in the sub-saharian regions of Africa. Although albendazole (ABZ) or mebendazole (MEB) is widely used as preventive antihelminthic treatment, there still exist variation in the efficacy of these drugs and standard threshold efficacy limits are not yet well established for all the three STHs. Original Research Article Nadyne et al.; IJTDH, 25(3): 1-13, 2017; Article no.IJTDH. 35402 2 Aim: The objective of this study was to evaluate the efficacy of single dose Mebendazole (500mg) against these three STHs. Methodology: A random control trial was conducted among school children residing in a high risk area of Cameroon. A toatal of 410 school-aged children in the Lolodorf neighbourhood were screened using the Kato katz technic followed by treatment of participants with a single dose of mebendazole (500 mg). Ten weeks post-treatment, children provided a single stool sample which was examined using the same diagnostic method. Efficacy was assessed by the Cure Rate (CRs) and Egg Reduction rate (ERRs). Results: Globally, 259 (63.2%) were infected for one or more STHs.The highest CRs were observed for A. lumbricoides (93.9%) followed by hookworms (70.8%) and T. trichiura (60.7%), for an overall CR of 59.1%. CRs varied considerable by age for hookworms and by type of infection for T. trichiura and hookworms. The prevalence reduction rate was highiest for A. lumbricoides (91.4%) followed by hookworms (61.0%) and T. trichiura (46.3%). ERRs were highiest for A. lumbricoides (94.5%) while this values were low for hookworms (52.9%) and T. trichiura (39.9%). The ERRs were affected for T. trichiura and hookworms by pre-treatment egg count for sex, different classes of infection intensity and types of infection. Conclusion: Our findings suggest the efficacy of single dose mebendazole 500 mg against A. lumbricoides and to a lesser extent on hookworms with low drug effect on T. trichiura. Further development and validation of standard protocols for antihelminthic drugs efficacy has to be established.
‘Studying in this England is wahala (trouble)’: analysing the experiences of West African students in a UK higher education institution

ABSTRACT ‘Studying in this England is Wahala’ critically analyses social/academic experiences of 12 West African overseas undergraduate/postgraduate students in a London University. It discusses structural and individual factors impacting on decisions to study here, including perceptions of differences between quality of university education in the UK and ‘back home’. To analyse this, I draw on the ‘Push-Pull’ model and Gidden’s (1991) Structuration approach as theoretical frameworks. I also examine students’ experiences of adapting to life in the UK, views on teaching and learning experiences in the UK and their home countries, and strategies used to facilitate their educational success. In so doing positives and challenges faced by students are highlighted. These were largely shaped by staff-student relationships, some of which were positive and supportive. In others, racism was prevalent, which reflects ongoing debates about Black and Minority Ethnic (BAME) student experiences in UK Higher Education institutions.
ANALISIS KEMAMPUAN LITERASI SAINS PADA ASPEK KONTEKS DAN KNOWLEDGE MENGGUNAKAN COOPERATIVE PROPLEM SOLVING (CPS) DENGAN STRATEGI HEURISTIK

Penelitian ini bertujuan untuk mengetahui implementasi model pembelajaran cooperative problem solving dengan strategi heuristik terhadap kemampuan literasi sains. Penelitian ini dilaksanakan di MTs. Saiful Ulum Kecamatan Tanjungbumi. Berdasarkan hasil penelitian diperoleh: (1) terdapat perbedaan literasi sains peserta didik yang menggunakan model Pembelajaran cooperative problem solving dengan strategi heuristik dengan nilai signifikansi 0,000 0,05, sedangkan –Ztabel ≥ Zhitung ≥ Ztabel (-5,172 ≥ -5,173 ≤ 5,172). (2) kemampuan literasi sains kelas kontrol aspek konteks memperoleh presentase 37% dengan kategori sains kurang sekali, aspek knowledge sebesar 47% dengan kategori kurang sekali. Rata-rata kemampuan level literasi sains berada pada level 2, 3, dan 4. Kemampuan literasi sains peserta didik pada kelas ekperimen aspek konteks memperoleh presentase 58% dengan kategori kurang sedangkan pada aspek knowledge memperoleh rata-rata presentase 71% dengan kategori cukup. Rata-rata kemampuan level literasi sains berada pada level 3, 4, 5, dan 6. Hal ini menunjukkan bahwa ada hubungan antara pembelajaran pemecahan masalah dalam melatihkan kemampuan literasi sains.
Preparing anesthesiology residents to lead: a leadership seminar

The purpose of this paper is to discuss a unique leadership curriculum developed at the University of Florida and its impact on the leadership skills and values of the anesthesiology residents since its conception. The authors instituted a voluntary anesthesiology residency leadership development program at their institution to fill a perceived gap in leadership training. Mounting evidence reveals that strong clinical leadership skills improve outcomes for patients and health-care institutions. Additionally, this growing body of literature indicates that optimal outcomes result from effective team behaviors and skills, which are directed through the requisite clinical leadership. Unfortunately, adding leadership training into the existing medical education curriculum is a formidable challenge regardless of the level of learner. ,To evaluate learners, the authors used the Aspiring leaders in Healthcare-Empowering individuals, Achieving excellence, Developing talents instrument, which is a validated and reliable assessment of leadership competency in health-care professionals. In 2017, the authors surveyed the past five graduating classes from the department (classes of 2012-2016), using the two graduating classes before the program’s implementation as a historical control group. ,The survey was sent to 96 people, of whom 70 responded (73 per cent). Those participants who usually or always participated in the program responded with higher leadership-readiness skills scores than those who occasionally, rarely or never participated in the program. Notably, those who had participated in another leadership development course at any time had higher skills scores than those who had never participated. ,The study’s data provide evidence that residents who either, often or always participated in the leadership development program perceived themselves to be better equipped to become effective health-care leaders as opposed to residents who never, rarely or occasionally participated.
Prevalence of self-medication and its pattern in medical students: a cross sectional study from Karnataka

Background: Self-medication is becoming a common type of self-care behavior among the population of many countries. Obtaining and consuming drugs without the advice of physician either for diagnosis, prescription or surveillance is called self-medication. The objectives of the study were to study prevalence and existing pattern of self-medication and its determinants among the medical students. Methods: A cross sectional descriptive study was conducted involving 200 medical students by systemic random sampling method using pretested semi-structured proforma. Analysis was done using SPSS and results were presented. Chi square and odds ratio (OR) was used as statistical tool. Results: Out of 200 students, 66.5% students were from 22-24 years of age group (mean age 20.2±1.4 years, p<0.05). Prevalence of self-medication was 93%, of which 53.8% were girls and 46.2% were boys (p>0.05). Majority of the students (95.2%) were self-medicating with allopathy drugs. 51.6% responded that they were getting quick relief with self-medication. 82% were aware about the possible adverse effects (OR 0.5, p>0.05). Self-medication was practiced by 78% students for upper respiratory tract infection, headache (70%), fever (67.7%) and gastrointestinal upset (36%). Majority (83%) students consumed paracetamol tablet for various health related reasons followed by cough syrups (55.3%), nonsteroidal anti-inflammatory drugs (54.3%), antibiotics (23.1%). Conclusions: Prevalence of self-medication was high in spite of awareness of possible adverse effects amongst students. Also, the knowledge of selection of appropriate drug for self-medication was observed to be poor.
Hazel plantation planning using GIS and multicriteria decision analysis

Spatial and environmental conditions on the agricultural land are invariable components and any plantation planning should take them into consideration. The conducted research presented methodology for suitability calculation of hazel plantations based on multicriteria analysis, performed in Vukovar-Srijem County. Nine criteria representing topographic, climate, pedology and infrastructure properties were modelled in GIS environment. Values of created layers were standardized using stepwise standardization and their respective weights were calculated by Analytical Hierarchical Process. These values were integrated using weighted linear combination, resulting with suitability values. The surrounding area of the City of Ilok had the highest suitability for hazel plantation in the studied locality, with maximum suitability 4.1 out of 5.0. Suitability was visualized on a thematic map, which enables farmers to interpret the data.
Engineering students’ actions in a mathematical modelling task: Mediating mathematical understandings in a computer algebra system

Many engineering subjects rely on the interpretation of symbolic, numeric and graphic representations. Engineering students have challenges pertaining to their mathematical understanding of their actions with a computer algebra system (CAS). We investigated how a mathematical modelling task could mediate varied levels of mathematical understanding. When engineering students are exposed to a CAS environment, they habitually engage in programming activities without considering the computerised outputs. The purpose of this paper was to ascertain South African engineering students’ actions that can mediate broader levels of mathematical understanding in a CAS by utilising the Pirie-Kieren model of growth in mathematical understanding. Thirteen participants agreed to engage collaboratively in a mathematical modelling task. The task was analysed by means of content analysis following a deductive research approach. The findings disclosed that engineering students interdepend on paper-and-pen, computerised and reflective actions in their growth of mathematical understanding. Engineering students can be assisted in mediated and folding-back actions in order to fluctuate back and forth on their way to a more sound mathematical understanding. Explicit planning and sequence of subtasks can support engineering students to merge new levels of mathematics understanding with past comprehensions. Thoroughly planned modelling tasks can mediate novel levels of mathematical understanding when engineering students learn with a CAS. tollgates.
Improving Efficiency of Photovoltaic Cell Using Nanomaterials

Conventional solar cells are not economical and are recently too expensive to the manufacturers for extensive-scale electricity generation. Cost and efficiency is most vital factor in the accomplishment of any solar technology. In order to improve the conversion efficiency, the major research in thirdgeneration photovoltaic (PV) cells is directed toward retaining more sunlight using nanotechnology. Advancement in nanotechnology solar cell via quantum dots (QDs) could reduce the cost of PV cell and additionally enhance cell conversion efficiency. Silicon quantum dots (Si-QDs) are semiconductor nano crystals of nanometers dimension whose electron-holes are confined in all three spatial dimensions. Quantum dots have discrete electronic states. Quantum dots have capacity to change band gap with the adjustment in size of quantum dot. As the quantum dots size fluctuates over a wide range that demonstrates the variety of band gap so it will assimilate or discharge light. In this paper, the generic mathematical models of PV cell are adopted and then I-V and P-V characteristic curves are obtained from selected parameters using MATLAB software. The essential parameters are taken from datasheets. I-V and P-V characteristics curves are obtained for selected model. Silicon quantum dots have the tunable band gap that is added to conventional PV cell and obtain the I-V and P-V curves. After simulation, efficiency and power of Conventional PV cell to quantum dots based PV cell is compared. The property of quantum dots is used in extending the band gap of solar cells and increasing the maximum proportion of incident sunlight absorbed, hence improving efficiency.
Hot Extrusion Enhanced Homogenization of Microstructure in a Spray Deposition Aluminum Alloy

Homogeneous heat treatment serves the significant roles in eliminating the segregation and tuning the microstructure of alloy ingot. It usually cost tremendous power and time to achieve a homogeneous microstructure for aluminum alloys. In this article, the hot extrusion was directly introduced on the spray deposited aluminum alloy 7055 ingot before performing heat treatment to explore the newly feasible homogeneous routine. Equiaxed grains without dendrites or PPB were obtained in our current parameters of spray deposition, which allowed the as-deposited alloy to be deformed without being subjected to pre-homogeneous heat treatment. Significant amount of stored energy was produced during hot extrusion at 420 °C with area reduction ratio of 6.25, which effectively promoted the homogeneity of microstructure and reduced significantly the heat treatment time. A newly feasible short routine, heat treatment at 450 °C /6 h + 470 °C/1 h following the hot extrusion, proved capable of obtaining a homogeneous microstructure for the spray deposited aluminum alloy 7055.
The Antibacterial Effects of Quaternary Ammonium Salts in the Simulated Presence of Inhibitors in Root Canals: A Preliminary In-Vitro Study

To investigate the antibacterial effects of two newly developed quaternary ammonium salts (QAMs)-dimethylaminododecyl methacrylate (DMADDM) and dimethylaminohexadecyl methacrylate (DMAHDM), in the presence of various root canal inhibitors. Streptococcus gordonii, Enterococcus faecalis, Lactobacillus acidophilus and Actinomyces naeslundii were used. Dentine, dentine matrix and dead bacteria were selected as inhibitors. The antimicrobial efficacy of monomers of DMADDM and DMAHDM was tested against suspensions formed by mixtures of four bacterial species in or without the presence of inhibitors. The inhibition results were compared with chlorhexidine (CHX) and sodium hypochlorite (NaOCl). One-way analyses of variance (ANOVA) followed by Tukey’s multiple comparison test was performed to determine significant differences. The antibacterial effects of DMADDM and DMAHDM were variably inhibited dentine, dentine matrix and dead bacteria. CHX and NaOCl showed substantivity and they inhibited bacteria present in suspension. The concentration of compound decreased in the dentine block due to constant release. Bacterial colonies on the dentine surface and dentine tubules were significantly inhibited by DMADDM and DMAHDM. The antibacterial effects of DMADDM and DMAHDM could be inactivated by dentine, dentine matrix and dead bacteria, while DMADDM and DMAHDM could inhibit bacteria colonization on the dentine surface and kill bacteria present in dentinal tubules. The antibacterial effects of DMADDM and DMAHDM as free monomers in the presence of inhibitors was evaluated for the first time. They could help inhibit the residual bacteria on the dentine surface and in dentinal tubules that may cause persisting infection. Therefore the novel QAMs showed great potentials as root canal medication.
Distinct neural ensemble response statistics are associated with recognition and discrimination of natural sound textures

Significance Being able to recognize and discriminate natural sounds, such as from a running stream, a crowd clapping, or ruffling leaves, is a critical task of the normal functioning auditory system. Humans can easily perform such tasks, yet they can be particularly difficult for the hearing impaired and they challenge our most sophisticated computer algorithms. This difficulty is attributed to the complex physical structure of such natural sounds and the fact they are not unique: they vary randomly in a statistically defined manner from one excerpt to the other. Here we provide evidence that the central auditory system is able to encode and utilize statistical sound cues for natural sound recognition and discrimination behaviors. The perception of sound textures, a class of natural sounds defined by statistical sound structure such as fire, wind, and rain, has been proposed to arise through the integration of time-averaged summary statistics. Where and how the auditory system might encode these summary statistics to create internal representations of these stationary sounds, however, is unknown. Here, using natural textures and synthetic variants with reduced statistics, we show that summary statistics modulate the correlations between frequency organized neuron ensembles in the awake rabbit inferior colliculus (IC). These neural ensemble correlation statistics capture high-order sound structure and allow for accurate neural decoding in a single trial recognition task with evidence accumulation times approaching 1 s. In contrast, the average activity across the neural ensemble (neural spectrum) provides a fast (tens of milliseconds) and salient signal that contributes primarily to texture discrimination. Intriguingly, perceptual studies in human listeners reveal analogous trends: the sound spectrum is integrated quickly and serves as a salient discrimination cue while high-order sound statistics are integrated slowly and contribute substantially more toward recognition. The findings suggest statistical sound cues such as the sound spectrum and correlation structure are represented by distinct response statistics in auditory midbrain ensembles, and that these neural response statistics may have dissociable roles and time scales for the recognition and discrimination of natural sounds.