Miracle-dz/UniFAR-FTUs huggingface dataset:
Encapsulation of precipitated calcium carbonate fillers using carboxymethyl cellulose /polyaluminium chloride: preparation and its influence on mechanical and optical properties of paper

Inorganic fillers are usually used in papermaking industry to reduce production costs and enhance paper optical properties. As an attempt to improve fillers application in papermaking, carboxymethyl cellulose (CMC) and poly aluminum chloride (PAC) were used to encapsulate precipitated calcium carbonate (PCC) ﬁller and modify its surfaces. In the first step, the optimum conditions for filler treatment (i.e. pH, CMC and PAC contents) were obtained. Through the second step, different amounts of CMC-encapsulated PCC were added to fiber suspension and some hand-sheets were made. Then, the effect of modified filler addition in different levels of 20, 25, and 35% on mechanical and optical properties of paper was investigated. The PAC dosage was found to be a critical factor for effective encapsulation of PCC fillers by carboxymethyl cellulose. When the dosages of CMC and PAC were 4% and 0.8% (based on the dry weight of PCC), respectively, ﬁller modiﬁcation caused to improve signiﬁcantly the retention by more than twice. Strength properties of the hand-sheets fabricated with the CMC/PAC-modified PCC were also found to be significantly better than those obtained with the unmodified PCC at similar levels of filler content. In addition, the brightness and opacity of the ﬁlled papers at 30% addition of CMC-modified fillers were strikingly enhanced to 88.45 and 77%, respectively. SEM observations of the filled papers also demonstrated that CMC-encapsulated ﬁller particles were clustered and retained efficiently onto the fiber network. The present method for modification of PCC may provide an alternative approach to increase the filler amount in the paper structure by alleviating filler drawbacks.
MUSCAT: the Mexico-UK Sub-Millimetre Camera for AsTronomy

The Mexico-UK Sub-millimetre Camera for AsTronomy (MUSCAT) is a large-format, millimetre-wave camera consisting of 1,500 background-limited lumped-element kinetic inductance detectors (LEKIDs) scheduled for deployment on the Large Millimeter Telescope (Volcán Sierra Negra, Mexico) in 2018. MUSCAT is designed for observing at 1.1 mm and will utilise the full 40 field of view of the LMTs upgraded 50-m primary mirror. In its primary role, MUSCAT is designed for high-resolution follow-up surveys of both galactic and extra-galactic sub-mm sources identified by Herschel. MUSCAT is also designed to be a technology demonstrator will provide the first on-sky demonstrations of novel design concepts such as horn-coupled LEKID arrays and closed continuous cycle miniature dilution refrigeration. Here we describe some of the key design elements of the MUSCAT instrument such as the novel use of continuous sorption refrigerators and a miniature dilutor for continuous 100-mK cooling of the focal plane, broadband optical coupling to Aluminium LEKID arrays using waveguide chokes and anti-reflection coating materials as well as with the general mechanical and optical design of MUSCAT. We will explain how MUSCAT is designed to be simple to upgrade and the possibilities for changing the focal plane unit that allows MUSCAT to act as a demonstrator for other novel technologies such as multi-chroic polarisation sensitive pixels and on-chip spectrometry in the future. Finally, we will report on the current status of MUSCAT's commissioning.
Estimating the Demand for Domestic and Imported Cigarettes in Rwanda

Objective: This paper aims to estimate the demand for domestic and imported cigarettes using quarterly time series data from Rwanda. Method: Demand functions were estimated using the Autoregressive Distributive lag (ARDL) and the Seemingly Unrelated Regression (SUR) models. Data were derived from the Ministry of Finance through the Rwanda Revenue Authority (RRA). Results: The price elasticity of demand for domestic and imported cigarettes ranged from 0.479 and -0.875. This indicates that a 10% increase in real prices would reduce cigarette consumption by 4.79% to 8.75% in Rwanda. The estimates also found the price elasticity of the imported cigarettes to be higher than that of the domestic cigarettes, indicating that smokers are more responsive, or elastic, to price changes in imported cigarettes. Concerning cross price effects, the estimates indicate that domestic and imported cigarettes are complements with cross-price elasticities of -1.087 for domestic and -0.534 for imported cigarettes. Conclusion: Rates of taxation in Rwanda rate still remain significantly lower than those imposed by some developing countries, despite recent changes in tax policy. Our results show that an increase in the rates of excise tax on tobacco would have a significant effect in reducing cigarette consumption as well as generating additional tax revenues. Introduction Smoking causes a huge economic burden to society; this effect is even more pronounced for a developing African countries (Kidane et al., 2015). Since the recognition of the health hazards of cigarette consumption in the 1960s, cigarette consumption has been steadily declining in most developed countries (Hsieh, Hu and Lin, 1999). Although the prevalence of smoking has decreased in countries with higher per capita income over the past decades, cigarette use has increased in countries with lowand mid-level per-capita income (Gajalakshmi, Jha, Ranson, and Nguyen, 2000; Ross and Al-Sadat, 2007). The declining demand for cigarettes in developed countries and increased consumption in developing countries has forced multinational cigarette manufacturers to either establish their companies in low and middle 1 Economics of Tobacco Control Project, University of Cape Town, South Africa: ngehernest@gmail.com 2 Department of Health Sciences, University of York, United Kingdom
A Multi-Context Character Prediction Model for a Brain-Computer Interface

Brain-computer interfaces and other augmentative and alternative communication devices introduce language-modeing challenges distinct from other character-entry methods. In particular, the acquired signal of the EEG (electroencephalogram) signal is noisier, which, in turn, makes the user intent harder to decipher. In order to adapt to this condition, we propose to maintain ambiguous history for every time step, and to employ, apart from the character language model, word information to produce a more robust prediction system. We present preliminary results that compare this proposed Online-Context Language Model (OCLM) to current algorithms that are used in this type of setting. Evaluation on both perplexity and predictive accuracy demonstrates promising results when dealing with ambiguous histories in order to provide to the front end a distribution of the next character the user might type.
Association of a novel single nucleotide polymorphism at the exon‑2 of Insulin-Like Growth Factor 1 (IGF1) gene with phenotypic variants in goats

The Insulin-Like Growth Factor 1 plays a key role in foetal development and post natal growth. The objectives of this study were to characterise the complete coding sequence of caprine IGF1 gene in two indigenous goat breeds of India: Malabari and Attappady Black, to detect polymorphisms of IGF1 gene, to investigate their effects on body size traits and to ascertain the relative expression of IGF1 mRNA in muscle tissues of goats belonging to low and high body weight groups. All the four exons of caprine IGF1 gene were amplified and characterized by PCR-SSCP in 298 goats, revealing two genotypes (CC and CT) at exon 2. Sequencing of the PCR products from each genotype revealed a novel SNP, g.80C>T (GenBank accession No. KM974180), which caused a non-synonymous mutation (Thr48Met),causing differences in IGF1 protein structure. Association analysis of the loci indicated CT genotypes have higher body length (P<0.01), chest circumference (P<0.01) and body length index (P<0.05) than CC genotypes. Two novel PCR-RFLPs were designed for the rapid detection of the genotypes. The quantitative real time PCR demonstrated a difference in the expression of IGF1 mRNA in muscle tissues of the low and high body weight groups, but it was not significant (P>0.05). The results of the *Corresponding author: Dr. Naicy Thomas, M.V. Sc. , PhD, Assis. Prof., Department of Animal Breeding, Genetics and Biostatistics, College of Veterinary and Animal Sciences, Mannuthy, Thrissur-680651, Kerala, India, Phone: +91 94 4611 9307; E-mail: naicy@kvasu.ac. in
An Empirical Study of Android Test Generation Tools in Industrial Cases

User Interface (UI) testing is a popular approach to ensure the quality of mobile apps. Numerous test generation tools have been developed to support UI testing on mobile apps, especially for Android apps. Previous work evaluates and compares different test generation tools using only relatively simple open-source apps, while real-world industrial apps tend to have more complex functionalities and implementations. There is no direct comparison among test generation tools with regard to effectiveness and ease-of-use on these industrial apps. To address such limitation, we study existing state-of-the-art or state-of-the-practice test generation tools on 68 widely-used industrial apps. We directly compare the tools with regard to code coverage and fault-detection ability. According to our results, Monkey, a state-of-the-practice tool from Google, achieves the highest method coverage on 22 of 41 apps whose method coverage data can be obtained. Of all 68 apps under study, Monkey also achieves the highest activity coverage on 35 apps, while Stoat, a state-of-the-art tool, is able to trigger the highest number of unique crashes on 23 apps. By analyzing the experimental results, we provide suggestions for combining different test generation tools to achieve better performance. We also report our experience in applying these tools to industrial apps under study. Our study results give insights on how Android UI test generation tools could be improved to better handle complex industrial apps.
Study of Face Recognition Techniques: A Survey

With the rapid growth in multimedia contents, among such content face recognition has got much attention especially in past few years. Face as an object consists of distinct features for detection; therefore, it remains most challenging research area for scholars in the field of computer vision and image processing. In this survey paper, we have tried to address most endeavoring face features such as pose invariance, aging, illuminations and partial occlusion. They are considered to be indispensable factors in face recognition system when realized over facial images. This paper also studies state of the art face detection techniques, approaches, viz. Eigen face, Artificial Neural Networks (ANN), Support Vector Machines (SVM), Principal Component Analysis (PCA), Independent Component Analysis (ICA), Gabor Wavelets, Elastic Bunch Graph Matching, 3D morphable Model and Hidden Markov Models. In addition to the aforementioned works, we have mentioned different testing face databases which include AT & T (ORL), AR, FERET, LFW, YTF, and Yale, respectively for results analysis. However, aim of this research is to provide comprehensive literature review over face recognition along with its applications. And after in depth discussion, some of the major findings are given in conclusion.
The e¤ect of location on nding a job in the Paris region

An important but empirically debated issue in spatial economics is whether spatial differences in unemployment reect residential sorting on invidividual characteristics or a true e¤ect of location. We investigate this issue in the 1,300 French muncipalities that constitute the Paris region and across which there is overwhelming evidence of spatial disparities in unemployment durations. We resort to a methodology that enables us to disentangle individual and unspeci ed local e¤ects. In order to control for individual determinants, we estimate a proportional hazard model strati ed by municipality using an exhaustive dataset of all unemployment spells starting in the rst semester of 1996. This model allows us to recover a survival function for each municipality that is purged of individual observed heterogeneity. We show that only around 30% of the disparities in the observed determinants of the survival rates relate to individual variables. Nearly 70% of the remaining disparities are captured by local indicators which we show to be mainly correlated with local measures of residential segregation. We are also able to show that local and individual characteristics reinforce one another in their contribution to spatial disparities in unemployment duration.
Towards Robust Visual Odometry with a Multi-Camera System

We present a visual odometry (VO) algorithm for a multi-camera system and robust operation in challenging environments. Our algorithm consists of a pose tracker and a local mapper. The tracker estimates the current pose by minimizing photometric errors between the most recent keyframe and the current frame. The mapper initializes the depths of all sampled feature points using plane-sweeping stereo. To reduce pose drift, a sliding window optimizer is used to refine poses and structure jointly. Our formulation is flexible enough to support an arbitrary number of stereo cameras. We evaluate our algorithm thoroughly on five datasets. The datasets were captured in different conditions: daytime, night-time with near-infrared (NIR) illumination and nighttime without NIR illumination. Experimental results show that a multi-camera setup makes the VO more robust to challenging environments, especially night-time conditions, in which a single stereo configuration fails easily due to the lack of features.
Functional health literacy: reflections and concepts on its impact on the interaction among users, professionals and the health system

Letramento funcional em saude (LFS) e o grau pelo qual os individuos tem a capacidade para obter, processar e entender informacoes basicas e servicos necessarios para a tomada de decisoes adequadas em saude. O tema preocupa pesquisadores/profissionais da saude/formuladores de politicas publicas. Sua natureza interdisciplinar, relacional e interacional indica que o LFS sofre a influencia dos sistemas de saude/educacional, midia, familia, ambiente de trabalho/comunidade/decisao politica. Analisam-se conceitos de LFS versus interacao usuarios-profissionais-sistema de saude, norteando-se pelas questoes: Em que consiste o LFS? Em que medida interfere na comunicacao entre usuarios, profissionais e sistema de saude? Quais sao suas consequencias na saude publica? Medidas para elevacao do LFS devem melhorar as competencias individuais e servicos de saude humanizados, aperfeicoando suas comunicacoes, escritas/orais, satisfazendo as necessidades/habilidades dos usuarios.
Microbial and metabolic profiling reveal strong influence of water table and land-use patterns on classification of degraded tropical peatlands

Tropical peatlands from southeast Asia are under- going extensive drainage, deforestation and degradation for agriculture and human settlement purposes. This is resulting in biomass loss and subsidence of peat from its oxidation. Molecular profiling approaches were used to understand the relative influences of different land-use patterns, hydrologi- cal and physicochemical parameters on the state of degraded tropical peatlands. As microbial communities play a critical role in biogeochemical cascades in the functioning of peat- lands, we used microbial and metabolic profiles as surrogates of community structure and functions, respectively. Profiles were generated from 230 bacterial 16 S rDNA fragments and 145 metabolic markers of 46 samples from 10 sites, includ- ing those from above and below water table in a contiguous area of 48 km 2 covering five land-use types. These were de- graded forest, degraded land, oil palm plantation, mixed crop plantation and settlements. Bacterial profiles were most in- fluenced by variations in water table and land-use patterns, followed by age of drainage and peat thickness in that or- der. Bacterial profiling revealed differences in sites, based on the duration and frequency of water table fluctuations and on oxygen availability. Mixed crop plantations had the most diverse bacterial and metabolic profiles. Metabolic profil- ing, being closely associated with biogeochemical functions, could distinguish communities not only based on land-use types but also their geographic locations, thus providing a finer resolution than bacterial profiles. Agricultural inputs, such as nitrates, were highly associated with bacterial com- munity structure of oil palm plantations, whereas phosphates and dissolved organic carbon influenced those from mixed crop plantations and settlements. Our results provide a ba- sis for adopting molecular marker-based approaches to clas- sify peatlands and determine relative importance of factors that influence peat functioning. Our findings will be useful in peatland management by providing a basis to focus early efforts on hydrological interventions and improving sustain- ability of oil palm plantations by adopting mixed cropping practices to increase microbial diversity in the long term.
Population and Civil War

Medical and public health innovations in the 1940s quickly resulted in significant health improvements around the world. Countries with initially higher mortality from infectious diseases experienced greater increases in life expectancy, population, and - over the following 40 years - social conflict. This result is robust across alternative measures of conflict and is not driven by differential trends between countries with varying baseline characteristics. At least during this time period, a faster increase in population made social conflict more likely, probably because it increased competition for scarce resources in low income countries.
ChromaCode: A Fully Imperceptible Screen-Camera Communication System

Hidden screen-camera communication techniques emerge as a new paradigm that embeds data imperceptibly into regular videos while remaining unobtrusive to human viewers. Three key goals on imperceptible, high rate, and reliable communication are desirable but conflicting, and existing solutions usually made a trade-off among them. In this paper, we present the design and implementation of <sc>ChromaCode</sc>, a screen-camera communication system that achieves all three goals simultaneously. In our design, we consider for the first time color space for perceptually uniform lightness modifications. On this basis, we design an outcome-based adaptive embedding scheme, which adapts to both pixel lightness and regional texture. Last, we propose a concatenated code scheme for robust coding and devise multiple techniques to overcome various screen-camera channel errors. Our prototype and experiments demonstrate that <sc>ChromaCode</sc> achieves remarkable raw throughputs of <inline-formula><tex-math notation="LaTeX">$>$</tex-math><alternatives><mml:math><mml:mo>></mml:mo></mml:math><inline-graphic xlink:href="zhang-ieq1-2956493.gif"/></alternatives></inline-formula>700 kbps, data goodputs of 120 kbps with BER of 0.05, and with fully imperceptible flicker for viewing proved by user study, which significantly outperforms previous works.
Integrating Reinforcement Learning Agents for Error Correction in Abstract Syntax Trees

Automated code synthesis is one of the holy grails of computer science. Despite the promise of code synthesis, many attempts to solve the problem fail largely due to the enormous state space of all programs and the sparsity of the reward space for partially functioning generated code. We introduce a neural architecture that allows for error-correction in abstract syntax trees (ASTs). To do so, we model the process of writing a program as a type of game, where the action space is limited to a series of nondifferentiable operations on ASTs. The network, acting as an agent equipped with a prosthetic integrated development environment (IDE), is trained by meta-reinforcement learning algorithms that allow the agent to narrow the search space and find programs more efficiently than brute force search. By making syntactically correct adjustments to an AST, the agent receives feedback from the IDE and adjusts its policy accordingly. To solve the issue of sparse and infrequent rewards, we propose a stack trace evaluator running a modified Smith-Waterman algorithm against the ground truth stack trace. As a proof of concept, we propose that this architecture be tested on simple programs with limited arguments and outputs like sorting, merging, and concatenating lists.
Compact Modeling of Tunnel Field Effect Transistor for Ultra-Low Power Design Applications

The IC technology always aims at increasing the package density and the speed. The VLSI technology which is governed by MOSFETs for the past couple of decades. In an attempt to increase the package density the size of the MOSFETS has been scaled down. As the size of the MOSFETs is scaled downwards, sub-threshold leakage current and leakage power in the ICs is increasing. The continued scaling has reached stagnation and further miniaturization of the MOSFET is facing major challenges. The conventional MOSFETs at short channel lengths suffer from high OFF-state leakage currents. They also suffer from numerous other short channel effects. Hence, as an alternative to the MOSFETs, TFETs have been widely studied. TFETs have the asymmetrical source/drain doping profile and they operate as reverse-biased, gated p-i-n tunnel diodes. The onoff switching mechanism in TFETs can be achieved by the gate-voltage induced band-to-band tunneling (BTBT) at the source-channel tunnel junction only. Where as in conventional MOSFETs, only the carriers with energy exceeding the source-channel thermal barrier will contribute the on-state current. TFETs are promising candidates for low power CMOS applications. Modelling the effects of non-idealities on the drain current of a TFET is also an important aspect. High on-state current (Ion), high on-off ratio and steep SS are the critical aspects in TFET design. In, this paper the silvaco TCAD simulation results for both conventional MOSFET & SOI Tunnel field effect transistor and its structure are shown.
Supplementary Material for Learning Priors for Semantic 3 D Reconstruction

In this supplementary document, we provide further insights and details about our novel multi-scale optimization scheme. In particular, we prove the adjointness of the transformation matrices of the primal and dual update steps of the unrolled optimization. Moreover, we detail the upsampling operators of the multi-scale scheme and show further examples of learned shape priors across different scale levels. Finally, we present additional experimental results which emphasize the fact that our method with unrolled optimization performs well when trained on little data, while traditional fully convolutional networks fail to reach comparable accuracy levels when trained with the same amount of data. 1 Multi-scale Optimization Scheme This section provides additional details of our proposed multi-scale optimization scheme. Derivation and Intuition. As described in the paper, the main energy in a single-scale setting can be numerically minimized using the first-order primaldual (PD) algorithm in [1] with the following update steps: