Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiparticulate Drug Delivery System for Gastrointestinal Tuberculosis

Drug solubility poses numerous challenges in design of formulations for drugs with poor aqueous solubility. Ethionamide is an antitubercular drug belonging to biopharmaceutical classification system class II drug having less aqueous solubility. Nanosuspensions were prepared by using various solvents such as methanol, ethanol, acetone and chloroform and it was prepared using anti-solvent precipitation technique by using probe sonication. Various stabilizers such as tocopherolpolythytlene glycol succinate, polyvinylpyrrolidone and tween 80 singly or in combination were studied. A 32 factorial design was employed to study the effect of independent variables, concentration of stabilizers and stirring speed on particle size and cumulative percent drug release. The particle size of the optimized batch was 97.54 ± 8.47 nm with polydispersity index of 0.36 and zeta potential -10.1 ± 2.3 mV. The cumulative percent drug release of optimized batch was found to be 95.01 ± 1.16% in 60 min. Optimized batch was ultracentrifuged and evaluated for saturation solubility studies, stability and powder X-ray Diffraction studies. Optimized nanosuspension was loaded on Espheres by spraying in a coating pan and then coating of Eudragit controlled release polymers. The coated Espheres were evaluated for drug content, friability, scanning electron microscopy, ex-vivo permeation studies and drug release kinetics studies. The friability value for primary coated sphere was found to be 0.8 ± 0.12% and for secondary was 1% and the best fit model was found to be Korsmeyer-Peppas model which is indicative of diffusion controlled release. Ex vivo diffusion studies revealed a moderate increase in permeability.
Design of Grid-Tied PV System with Single-Phase Transformerless Inverter Using Fuzzy Control Based Charge Pump Circuit Concept

In this paper proposes a single phase transformer less photovoltaic inverter for grid connect PV system. In this topology we are developing the concept of a charge pump circuit in order to eliminate the leakage current. We are utilizing the fuzzy controller in this paper. We are comparing the fuzzy controller with other controller. The neutral of the grid is directly connected to the negative polarity of the PV panel that creates a constant common mode voltage and zero leakage current. During the negative cycle, the charge pump circuit generates the negative output voltage of the proposed inverter. Therefore according to the proportional resonant control strategy is used to control the injected current. There are various advantage of the proposed inverter they are the neutral of the grid is directly connected to the negative terminal of the PV panel, so the leakage current is eliminated, its compact size; low cost; the used dc voltage of the proposed inverter is the same as the full-bridge inverter (unlike neutral point clamped (NPC), active NPC, and half-bridge inverters); flexible grounding configuration; capability of reactive power flow; and high efficiency. By using simulation result we can verify the concept of the proposed inverter and its practical application in grid-tied PV systems.
The Role of a School Leader in Academic Outcomes: Between Self-efficacy and Outcome Expectations

This quantitative study investigated the relationships among elementary school principals’ efficacy beliefs (Instructional, Moral, and Management Leadership), principals’ goal expectations for student achievement (expected outcome), and their impacts on actual student achievement. Two hundred and fifty elementary school principals completed an electronic survey seeking information on their self-efficacy, school outcome expectation, actual school outcome, and personal and school demographics. Bandura’s Social Cognitive Theory guided the study. Findings show higher significant correlations between principal outcome expectation and actual school academic outcome compared to selfefficacy expectation and actual school academic outcome. Regression analysis revealed that unlike self-efficacy expectation, outcome expectation predicted actual school academic outcome.
Three essays on gay and lesbian rights legislation

THREE ESSAYS ON GAY AND LESBIAN RIGHTS LEGISLATION David R. Christafore This dissertation consists of three essays that provide empirical evidence that informs the ongoing debate over the passage of gay and lesbian rights legislation. In Chapter 2 the difference-in-difference-in-difference methodology is used to examine the effect that the passage of a private employment anti-discrimination law has on the relative earnings and employment of gays and lesbians. The results of this analysis indicate that the passage of this law does not have an impact on either relative earnings or employment for lesbians, but it does have an impact on these labor market outcomes for gays. In particular, the passage of this anti-discrimination law increases the relative earnings for gays by 7.5% and reduces their relative probability of being employed by 2.4%. In Chapter 3 a gravity model of stateto-state gay and lesbian migration flows over the period 1995-2000 is estimated in order to analyze the revealed preferences of gays and lesbians for private and public employment anti-discrimination, hate crime, and domestic partnership laws. The results of this examination indicate that private employment anti-discrimination laws reduce in-migration, while public employment anti-discrimination and hate crime laws increase in-migration. Therefore, it appears that gays and lesbians prefer to live in places with public employment anti-discrimination and hate crime laws, and not in places with private employment antidiscrimination laws. In Chapter 4 a spatial hedonic autoregressive model is estimated for the Columbus, OH MSA to examine the impact that the percentage of gay and lesbian households in conservative and liberal neighborhoods has on the house prices in those neighborhoods. The results of the analysis indicate that a . 1% point increase in the percentage of gay and lesbian households increases house prices in liberal neighborhoods by . 81% and reduces house prices by . 24% in conservative neighborhoods. Thus, evidence is provided that is consistent with gay and lesbian households being an amenity to liberal neighborhoods, but a disamenity, likely due to prejudice, to conservative neighborhoods.
Floating-Point Extension for Containing Error in the RISC-V Architecture

This article discusses modifications to IEEE 754 floating-point units to help researchers and scientists monitor and control errors in scientific applications. To accomplish this, support is added to the RISC-V simulation environment through gem5 architecture simulator to give the ability to identify possible elements lost during rounding. The use of the SoftFloat arithmetic validation suite is utilized and added to gem5. Simulation results are presented indicating good performance and the ability to monitor arbitrary precision. Results are also given on implementation in System on Chip designs using the Global Foundries cmos32soi technology along with ARM standard-cells. The results indicate an approximately 5% increase in area with less than 3% increase in energy over traditional IEEE 754 floating-point multipliers.
Classification, Design and Evaluation of Endoscope Robots

With development of endoscopic surgery and medical robotics, surgery using endoscope robots has become a representative of robotic surgery. This chapter describes classification, design methods and evaluation methods of endoscope robots. Expectations for a minimally invasive surgery have increased year by year with the dramatic advancement of image diagnosis technology, including CT and MRI. A camera (endoscope) and surgical instruments are inserted into tiny holes made in the patients’ abdomen or chest region for surgical procedures. Compared to abdominal or open chest surgery, endoscopic surgery has less pain and has a greater advantage in cosmetic appearance as well as the economic advantages, resulting in its growing popularity. The most distinctive feature of endoscopic surgery is that the surgical field is observed through images taken by an endoscope, rather than the naked eye. The most important element to surgical safety and efficient operating is how well an endoscope reveals the field of view during surgery. Generally, a camera assistant operates the endoscope. The operation of the endoscope needs fine adjustment for the angle of the field of view and the distance of the surgical area as well as correct aiming of the endoscope at the surgical field. Camera assistants sometimes operate the endoscope according to instructions of a surgeon; however, camera assistants need to operate the endoscope using their judgment in understanding the surgeon’s intentions so that they can move the endoscope according to how the surgery is progressing moment to moment. The operation of an endoscope by camera assistants requires as much proficiency as that of surgeons. There are not many surgeons who have sufficient proficiency in endoscopic surgery, which requires special techniques. In fact, it is not unusual for surgery to be interrupted due to a camera assistant not being sufficiently proficient in using the endoscope and is unable to obtain the exact field of surgery required. To solve this problem, "endoscope robots that can hold and position an endoscope instead of a human camera assistant" (Fig. 1) have been developed. Fig. 1(a) shows a usual endoscopic
A Review on Robust Language Identification

Automatic language identification of audio data has become an important pre-processing step for speech/speaker recognition. In order to identify the language on short utterance is critical challenge for achieving accurate performance. In this paper, we review language identification methods. First we discuss Phonotactic systems use phone recognition and language modelling (PRLM) . The second category of LID techniques attempts to classify languages by using Gaussian mixture models (GMMs) to capture the acoustic properties of speech. For the accuracy of language identification on short utterances the proposed system works on robust language classification that transforms the spoken words to a low dimensional i-vector representation on which language classification methods are applied. Language classification model use the approach of universal background model for the better performance.
Development of Indonesian Spoken Language Technologies for Multilingual Speech-to-Speech Translation System

In this paper, we present the recent advancements in the development of Indonesian spoken language technologies towards a multilingual speech-to-speech translation system. These comprise the development of speech recognition, language translation, and speech synthesis systems. All the system models are based on a corpus-based approach and were statistically trained using a collection of speech and language data. The experimental results reveal that the Indonesian speech recognition system could achieve 92.47% word accuracy on travel domain, while the BLEU (bilingual evaluation understudy) machine translation score was about 0.57 and 0.6 for Indonesian-Japanese and Indonesian-English translations, respectively. The quality of Indonesian synthesized speech was also smooth and perfectly intelligible.
Optics Design and Beam Dynamics simulation for a VHEE Radiobiology beam line at PRAE accelerator

The Platform for Research and Applications with Electrons (PRAE) is a multidisciplinary R&D facility gathering subatomic physics, instrumentation, radiobiology and clinical research around a high-performance electron accelerator with beam energies up to 70 MeV. In this paper we report the complete optics design and performance evaluation of a Very High Energy Electron (VHEE) innovative radiobiology study, in particular by using Grid mini-beam and FLASH methodologies, which could represent a major breakthrough in Radiation Therapy (RT) treatment modality.
A High Gain Bipolar Pulse Generator with Low Voltage Input Source

This paper proposes a pulsed power generator which consists of two types of switched-capacitor booster modules. A doubling mode module employed to elevate the input voltage to a specified level and, constant mode module is used to increase the elevated voltage into the finally intended bipolar output voltage. Also, the proposed modular structure does not utilize any switches across the load. Other advantage of the proposed structure is its lower current stress on source and every circuit component near it. In comparison with Marx Generator (MG) based topologies, the number of circuit components has been significantly reduced, which led to cost-saving and prevention of circuit control complexity. Calculation of the capacitors is presented. Experimental tests and simulations are performed on a five-module system which confirms the high performance of the proposed topology.
Road Infrastructure and Enterprise Dynamics in Ethiopia * February 2015

We analyse the relationship between road infrastructure quality and location choice and entry size of manufacturing firms in Ethiopia. We use GIS based panel data on town-level measures of road infrastructure and census based panel data on firms. Our dataset covers a period of considerable improvements in road infrastructure as a result of major public investments. We find that local infrastructure is important for entry, while more extensive market connectivity is important for the entry of large firms. We conclude that improved infrastructure has been associated with favourable outcomes with respect to entry patterns and firm size in Ethiopia’s manufacturing sector.
Compositional Pre-Training for Semantic Parsing with BERT

Semantic parsing the conversion of natural language utterances to logical forms is a typical natural language processing task. Its applications cover a wide variety of topics, such as question answering, machine translation, instruction following or regular expression generation. In our project, we investigate the performance of Transformer-based sequence-to-sequence models for semantic parsing. We compare a simple Transformer Encoder-Decoder model built on the work of [4] and a Encoder-Decoder model where the Encoder is BERT [1], a Transformer with weights pre-trained to learn a bidirectional language model over a large dataset. Our architectures have been trained on semantic parsing data using data recombination techniques described in [2]. We illustrated how Transformer-based Encoder Decoder architectures could be applied to semantic parsing. We evidenced the benefits of BERT as the Encoder of such architectures and pointed to some of the difficulties in fine-tuning it on limited data while the Decoder has to be trained from scratch. We have been mentored by Robin Jia from Stanford University’s Computer Science Department.
Crisis and contagion in financial networks: a dynamic approach

RÉSUMÉ We study the dynamics of a connected banking sector where the financial links between banks are explicitly modelled, including the liquidation procedures in the case of the failure of an individual bank. This model of banking network allows us to simulate the bankruptcy contagion process and quantify the extent of a banking crisis. We discuss the impact of various structural parameters on the contagion process.
Is this question sincere ? Identifying insincere questions on Quora using BERT and variations

The flagging of insincere questions on internet forums is an ongoing challenge for online communities that rely heavily on the faith and support of their users. We develop and train three variations of the BERT model on a dataset provided by Quora to predict whether posted questions are sincere or insincere. We compare our model’s performance to the well-performing alternative architecture of LSTM + GRU and present an extensive discussion on the observed advantages and weaknesses of the BERT model in this context.
Differentially Private Community Detection in Attributed Social Networks

Community detection is an effective approach to unveil social dynamics among individuals in social networks. In the literature, quite a few algorithms have been proposed to conduct community detection by exploiting the topology of social networks and the attributes of social actors. In practice, community detection is usually conducted by third parties like advertisement companies, hospitals, with access to social networks for different purposes, which can easily lead to privacy breaches. In this paper, we investigate community detection in social networks aiming to protect the privacy of both the network topologies and the users’ attributes. In particular, we propose a new scheme called differentially private community detection (DPCD). DPCD detects communities in social networks via a probabilistic generative model, which can be decomposed into subproblems solved by individual users. The private social relationships and attributes of each user are protected by objective perturbation with differential privacy guarantees. Through both theoretical analysis and experimental validation using synthetic and real world social networks, we demonstrate that the proposed DPCD scheme detects social communities under modest privacy budget.
Interfacing Toolbox for Robotic Arms with Real-Time Adaptive Behavior Capabilities

Industrial robotic systems are increasingly being used to perform tasks requiring in-loop adaptive behavior to accommodate the demands of data-driven and autonomous manufacturing in the era of Industry 4.0. Achieving effective integration and the full potential of robotic systems presents significant challenges. This paper presents a C++ language-based toolbox, developed to facilitate the integration of industrial robotic arms with server computers, sensors and actuators. The new toolbox, namely the “Interfacing Toolbox for Robotic Arms” (ITRA), is fully flexible and extensible. It is capable of controlling multiple robots simultaneously, thus providing the opportunity for sophisticated manufacturing operations to be coordinated among multiple robots. ITRA can be used to achieve fast adaptive robotic systems, with latency as low as 30ms. Moreover, ITRA is cross-platform, allowing great flexibility between different computer architectures. The paper describes the architecture of ITRA, presents all its functions and gives some application examples.
A system for TRECVID MED by MCIS

—We designed a simple system for the 2014 TRECVID Multimedia Event Detection [1]. Except the videos provided by NIST, we only used the BVLC Reference CaffeNet model ﬁle distributed besides Caffe [2]. Our system follows the standard pipeline and consists two parts: feature extraction and classiﬁ-cation. The feature extraction part is implemented by Caffe and the classiﬁcation is implemented by LIBSVM [3]. Based on the results, we think that the contribution mainly comes from the feature extraction part. We learned that Convolutional Neural Networks (CNN) is a powerfully model and hope that a easy accessible spatio-temporal CNN model for videos will be available soon.
Lattice Resonances in Optical Metasurfaces With Gain and Loss

Periodic lattices of strongly scattering objects coupled to active media are of central importance in applied nanophotonics, serving as light-emitting metasurfaces of tailored emission properties and promising an attractive platform for testing novel physical concepts and realization of unprecedented light-shaping functions. We provide an overview of the semianalytical Green function method with Ewald lattice summation applied to the investigation of surface lattice resonances in periodic arrays of resonant nanoscatterers with gain and loss. This theory is meant as a minimal model for plasmonic lattices and metasurfaces with gain: minimal in complexity, yet sufficiently rich to be a self-consistent, fully retarded multiple scattering model. It enables to include the electromagnetic interactions between electric and/or magnetic point dipoles of arbitrary orientation and arrangement, taking into account retardation and tensorial nature of these interactions and including radiation damping. It gives access to the far-field observables (reflection/transmission), as well as to the photonic band structure of guided modes. At the same time, it does not violate the optical theorem, as opposed to the commonly used tight-binding or quasi-static models. After extending the lattice Green function formalism to include gain and loss in the unit cell, we demonstrate the effects of parity-time (PT) symmetry breaking in active-lossy plasmonic arrays: the emergence of exceptional points, nontrivial topology of photonic bands, diverging effective unit-cell polarizability, and spin polarization in the PT-broken phase.
Title Assessing general cognitive and adaptive abilities in adults with Down syndrome : a systematic review

Background: Measures of general cognitive and adaptive ability in adults with Down syndrome (DS) used by previous studies vary substantially. This review summarises the different ability measures used previously, focusing on tests of intelligence quotient (IQ) and adaptive behaviour (AB), and where possible examines floor effects and differences between DS subpopulations. We aimed to use information regarding existing measures to provide recommendations for individual researchers and the DS research community. Results: Nineteen studies reporting IQ test data met inclusion for this review, with 17 different IQ tests used. Twelve of these IQ tests were used in only one study while five were used in two different studies. Eleven studies reporting AB test data met inclusion for this review, with seven different AB tests used. The only AB scales to be used by more than one study were the Vineland Adaptive Behaviour Scale (VABS; used by three studies) and the Vineland Adaptive Behavior Scale 2nd Edition (VABS-II; used by two studies). A variety of additional factors were identified which make comparison of test scores between studies problematic, including different score types provided between studies (e.g. raw scores compared to age-equivalent scores) and different participant inclusion criteria (e.g. whether individuals with cognitive decline were excluded). Floor effects were common for IQ tests (particularly for standardised test scores). Data exists to suggest that floor effects may be minimised by the use of raw test scores rather than standardised test scores. Raw scores may, therefore, be particularly useful in longitudinal studies to track change in cognitive ability over time. Conclusions: Studies assessing general ability in adults with DS are likely to benefit from the use of both IQ and AB scales. The DS research community may benefit from the development of reporting standards for IQ and AB data, and from the sharing of raw study data enabling further in-depth investigation of issues highlighted by this review.
EFFECT OF MARKET RISK ON PENSION FUND ’ S INVESTMENT PERFORMANCE IN NIGERIA

The objective of this study is to empirically assess the effects of market risk on pension fund investments in Nigeria; considering the relationship between return on a portfolio and risk-free rate plus other factors such as stock market returns. The essence of pension funds investment is to create a portfolio with assets which maturity will align with the expected return that can off-set such responsibilities despite volatilities in the market place. Using risk-adjusted return as a proxy for investment performance and market risk as the explanatory variable; the study utilized the ordinary least square (OLS) regression using panel data for sampled PFAs between 2007 to 2015.Results revealed that the coefficient of market risk is not significant at any of the conventional levels signifies that the effect is statistically negligible. The paper recommends PFAs should increase their investment in risky assets to give them the opportunity of reaping more returns and portfolio performance. It further recommends that efficient and optimal investment portfolio mix on behalf of retirees to hedge against risk of eroding the long term funds and thus ensuring more returns on investment.