Miracle-dz/UniFAR-FTUs huggingface dataset:
Children’s Exposures to Pyrethroid Insecticides at Home: A Review of Data Collected in Published Exposure Measurement Studies Conducted in the United States

Pyrethroid insecticides are frequently used to control insects in residential and agriculture settings in the United States and worldwide. As a result, children can be potentially exposed to pyrethroid residues in food and at home. This review summarizes data reported in 15 published articles from observational exposure measurement studies conducted from 1999 to present that examined children’s (5 months to 17 years of age) exposures to pyrethroids in media including floor wipes, floor dust, food, air, and/or urine collected at homes in the United States. At least seven different pyrethroids were detected in wipe, dust, solid food, and indoor air samples. Permethrin was the most frequently detected (>50%) pyrethroid in these media, followed by cypermethrin (wipes, dust, and food). 3-phenoxybenzoic acid (3-PBA), a urinary metabolite of several pyrethroids, was the most frequently (≥67%) detected pyrethroid biomarker. Results across studies indicate that these children were likely exposed to several pyrethroids, but primarily to permethrin and cypermethrin, from several sources including food, dust, and/or on surfaces at residences. Dietary ingestion followed by nondietary ingestion were the dominate exposure routes for these children, except in homes with frequent pesticide applications (dermal followed by dietary ingestion). Urinary 3-PBA concentration data confirm that the majority of the children sampled were exposed to one or more pyrethroids.
LARGE AREA SURVEY FOR z = 7 GALAXIES IN SDF AND GOODS-N: IMPLICATIONS FOR GALAXY FORMATION AND COSMIC REIONIZATION

We present results of our large area survey for z′-band dropout galaxies at z = 7 in a 1568 arcmin2 sky area covering the SDF and GOODS-N fields. Combining our ultra-deep Subaru/Suprime-Cam z′- and y-band (λeff = 1 μm) images with legacy data of Subaru and Hubble Space Telescope, we have identified 22 bright z-dropout galaxies down to y = 26, one of which has a spectroscopic redshift of z = 6.96 determined from Lyα emission. The z = 7 luminosity function yields the best-fit Schechter parameters of ϕ* = 0.69+2.62 −0.55 × 10−3 Mpc−3, M*UV = −20.10 ± 0.76 mag, and α = −1.72 ± 0.65, and indicates a decrease from z = 6 at a >95% confidence level. This decrease is beyond the cosmic variance in our two fields, which is estimated to be a factor of ≲2. We have found that the cosmic star formation rate density drops from the peak at z = 2–3 to z = 7 roughly by a factor of ∼10 but not larger than ∼100. A comparison with the reionization models suggests either that the universe could not be totally ionized by only galaxies at z = 7, or more likely that properties of galaxies at z = 7 are different from those at low redshifts having, e.g., a larger escape fraction (≳0.2), a lower metallicity, and/or a flatter initial mass function. Our SDF z-dropout galaxies appear to form 60 Mpc long filamentary structures, and the z = 6.96 galaxy with Lyα emission is located at the center of an overdense region consisting of four UV bright dropout candidates, which might suggest an existence of a well-developed ionized bubble at z = 7.
Decentralized $H_\infty$ Sampled-Data Fuzzy Filter for Nonlinear Interconnected Oscillating Systems With Uncertain Interconnections

This paper proposes a decentralized <inline-formula><tex-math notation="LaTeX">$H_\infty$</tex-math></inline-formula> sampled-data fuzzy filter design for nonlinear interconnected systems composed of multiple subsystems with uncertain interconnections and variable sampling intervals. The interconnected system and the decentralized filter are modeled using Takagi–Sugeno fuzzy systems. To derive the filter-design conditions, the estimation error dynamics are modeled, and the <inline-formula><tex-math notation="LaTeX">$H_\infty$</tex-math></inline-formula> filter performance inequality is defined. The filter performance inequality is aimed at minimizing the ratio of the estimation error to the sum of the norm of the disturbance and oscillating system. The sufficient conditions for the filter design are derived using the Wirtinger-based integral inequality and expressed in the form of linear matrix inequalities. Finally, the performance of the proposed filter-design techniques is demonstrated through two simulation examples.
Discrepancy sets and pseudorandom generators for combinatorial rectangles

A common subproblem of DNF approximate counting and derandomizing RL is the discrepancy problem for combinatorial rectangles. We explicitly construct a poly(n)-size sample space that approximates the volume of any combinatorial rectangle in [n]/sup n/ to within o(1) error. The construction extends the previous techniques for the analogous hitting set problem, most notably via discrepancy preserving reductions.
Separation of concerns in feature diagram languages: A systematic survey

The need for flexible customization of large feature-rich software systems, according to requirements of various stakeholders, has become an important problem in software development. Among the many software engineering approaches dealing with variability management, the notion of Software Product Line (SPL) has emerged as a major unifying concept. Drawing from established disciplines of manufacturing, SPL approaches aim to design repertoires of software artifacts, from which customized software systems for specific stakeholder requirements can be developed. A major difficulty SPL approaches attempt to address is the modularization of software artifacts, which reconciles the user's needs for certain features and the development and technical constraints. Towards this end, many SPL approaches use feature diagrams to describe possible configurations of a feature set. There have been several proposals for feature diagram languages with varying degrees of expressiveness, intuitiveness, and precision. However, these feature diagram languages have limited scalability when applied to realistic software systems. This article provides a systematic survey of various concerns of feature diagrams and ways in which concerns have been separated. The survey shows how the uncertainty in the purpose of feature diagram languages creates both conceptual and practical limitations to scalability of those languages.
Automated Forelimb Tasks for Rodents: Current Advantages and Limitations, and Future Promise

Rodent tests of function have advanced our understanding of movement, largely through the human training and testing and manual assessment. Tools such as reaching and grasping of a food pellet have been widely adopted because they are effective and simple to use. However, these tools are time-consuming, subjective, and often qualitative. Automation of training, testing, and assessment has the potential to increase efficiency while ensuring tasks are objective and quantitative. We detail new methods for automating rodent forelimb tests, including the use of pellet dispensers, sensors, computer vision, and home cage systems. We argue that limitations in existing forelimb tasks are driving the innovations in automated systems. We further argue that automated tasks partially address these limitations, and we outline necessary precautions and remaining challenges when adopting these types of tasks. Finally, we suggest attributes of future automated rodent assessment tools that can enable widespread adoption and help us better understand forelimb function in health and disease.
Research on bottleneck resources focused flow path design

The current flow path design models might lead to complicated scheduling and unbalanced bottleneck resources in some cells. A bottleneck resources focused flow path model is proposed in this paper. The number of the ultimate cells and the average load of the bottleneck resources are considered in the model. The proposed model can dynamically form high efficient virtual production cells, balance the average load of the bottleneck resources in cells and help to reduce the complexity of scheduling later on. Genetic algorithm is designed to solve the proposed model. The validity of the model and algorithm are verified by corresponding case studies.
Maximum-likelihood detection of sources among Poissonian noise

A maximum likelihood (ML) technique for detecting compact sources in images of the X-ray sky is examined. Such images, in the relatively low exposure regime accessible to present X-ray observatories, exhibit Poissonian noise at background flux levels. A variety of source detection methods are compared via Monte Carlo, and the ML detection method is shown to compare favourably with the optimized-linear-filter (OLF) method when applied to a single image. Where detection proceeds in parallel on several images made in different energy bands, the ML method is shown to have some practical advantages which make it superior to the OLF method. Some criticisms of ML are discussed. Finally, a practical method of estimating the sensitivity of ML detection is presented, and is shown to be also applicable to sliding-box source detection.
Preference elicitation without numbers

The development of autonomous multi-agent systems acting upon the interests of one or more users involves the elicitation of preferences of these users. In decision theory, models have been developed with which one is able to perform this elicitation. Some common anomolies have been identified to existing models for applying preference elicitation in electronic commerce settings. This paper presents a novel preference elicitation model based on cross modality matching.
CS 229 Project : Using Vector Representations to Augment Sentiment Analysis Training Data

While the accuracy of supervised sentiment classification algorithms has steadily increased in recent years, acquiring new human-labeled sentiment data remains expensive. In this paper, we explore the effectiveness of increasing the training data set size for sentiment classification algorithms by adding unlabeled phrases whose sentiments are inferred by their proximity to labeled training phrases. This study was carried out in the context of two softmax classifiers, each trained on movie review phrases with sentiments labeled between 1 (very negative) and 5 (very positive), using pretrained vectors to represent individual words. We find that augmenting the training data of these softmax classifiers can improve the classification accuracy of one of our models by up to 5%, while the other neither improves nor deteriorates.
MELODY EXTRACTION FROM POLYPHONIC MUSIC: MIREX 2011

In this paper we describe our submission for the audio melody extraction task of the Music Information Retrieval Evaluation eXchange (MIREX) 2011 campaign. The system presented here is an updated version of the one submitted to last year’s campaign. Following a detailed analysis of each step of our method, system parameters have been optimised for melody extraction and the implementation is now more efficient. Two variants of the system have been submitted, each making use of a different spectral transform, allowing us to asses whether the difference between them is significant for overall performance. Following the description of the system, we describe the data-sets and metrics used for evaluation. This is followed by a summary of the results and some conclusions.
Enhancing recommender systems by incorporating social information

Although recommendation techniques have achieved distinct developments over the decades, the data sparseness problem of the involved user-item matrix still seriously influences the recommendation quality. Most of the existing techniques for recommender systems cannot easily deal with users who have very few ratings. How to combine the increasing amount of different types of social information such as user generated content and social relationships to enhance the prediction precision of the recommender systems remains a huge challenge. In this paper, based on a factor graph model, we formalize the problem in a semi-supervised probabilistic model, which can incorporate different user information, user relationships, and user-item ratings for learning to predict the unknown ratings. We evaluate the method in two different genres of datasets, Douban and Last.fm. Experiments indicate that our method outperforms several state-of-the-art recommendation algorithms. Furthermore, a distributed learning algorithm is developed to scale up the approach to real large datasets.
The Research of Text Classification Technology Based on Improved Maximum Entropy Model

In this paper, it studies the Techniques of Text Categorization based on maximum entropy models, and gives technical solutions for the network through improved technology, which contains a large number of documents. This paper describes an method based on improved maximum entropy model for text classification, a features selection method and pretreatment methods, the experimental results with good accuracy and recall, has played a certain role for large amounts of text, to meet the requirements of practical application.
Formulasi Gel Handsanitizer Minyak Atsiri Daun Sereh (Cymbopogon nardus) dengan Hidroxy Propyl Methyl Cellulose (HPMC) sebagai Gelling Agent

Gel antiseptik tangan yang beredar di pasaran saat ini sebagian besar berbahan dasar alkohol.Pemakaian berulang sebagai sediaan pembersih tangan dapat menyebabkan kekeringan dan iritasi padakulit. Salah satu yang dapat dijadikan sebagai bahan dasar pengganti alkohol adalah sereh (Cymbopogonnardus). Dilakukan tiga kali pengujian yaitu, uji pendahuluan terhadap konsentrasi minyak, uji sifatfi sik sediaan gel dan uji replikasi yang dimodifi kasi. Berdasarkan uji pendahuluan yang dilakukanminyak atsiri daun sereh dapat membunuh bakteri Escherichia coli pada konsentrasi 5% dan bakteriStaphylococus aureus pada konsentrasi 10%. Daya sebar sediaan pada uji sifat fi sik antara 5,5-6 cmdengan pH 7-9 dan daya lekat 1 detik. Uji replika yang dimodifi kasi menunjukkan penurunan jumlahkoloni bakteri yang signifi kan pada setiap konsetrasi formula dari ketiga kelompok uji. Signifi kansi inimenunjukkan adanya penghambatan bakteri yang disebabkan oleh penggunaan gel pembersih tangan.Berdasarkan uji organoleptis tingkat kesukaan masyarakat dan uji antibakteri sediaan gel pembersihtangan dipilih konsentrasi 10% sebagai sediaan yang disukai masyarakat dan dapat menghambatpertumbuhan bakteri.
A multilevel analysis of contextual risk factors for intimate partner violence in Ghana

While extant research suggests that context, structural socioeconomic and cultural factors matter in intimate partner violence research, quantitative research on the subject in sub-Saharan Africa, and in particular Ghana, has disproportionately focused on prevalence and individual level correlates of spousal violence. This research has ignored the role of the structural socioeconomic and cultural factors and contexts in understanding the causes and consequences of spousal violence in a setting where family life is heavily influenced by traditional norms and beliefs. These norms and beliefs may lead to inadequate and ineffective interventions geared at preventing or reducing spousal violence and its consequences. Guided by an integrated theoretical approach, this study addresses these issues by estimating a multilevel logistic regression model where the effects of both individual and community level risk factors for spousal violence are assessed. Data for the study come from the Ghana Demographic and Health Survey and the Ghana Population and Housing Census. The findings confirm the salient role of structural socioeconomic and cultural factors, such as patriarchal norms and residential instability, in the perpetration of spousal violence against women. Policy implications of these findings and directions for further research are discussed.
Autonomous navigation for an unmanned mobile robot in urban areas

Mobile robot has attracted intense research interest in recent years due to numerous potential application. The capability of autonomous navigation is critical for a mobile robot when performing a wide range of military and civilian tasks in urban areas. An autonomous navigation system for an unmanned mobile robot in urban areas is presented in this paper, including location subsystem and navigation tracking subsystem. An inexpensive single GPS receiver and inertial sensors as gyro, compass and encoders are deployed in the location subsystem. The important contribution is the GPS/DR fusing algorithm, which tries to fuse the information coming from GPS and DR. Meanwhile the kalman filters are introduced to smooth the GPS location information based on the Markov model and improve the accuracy of Dead Reckoning(DR) location. In the navigation tracking subsystem, the heading angle tracking is achieved by subdivision speed control and trajectory linearization control algorithm is designed to follow line path. Then the errors of east, north direction and distance, are put forward to describe the performance of the robot location and navigation. The experiments carried out on the differential drive tracked mobile robot demonstrate that the whole navigation system is feasible and reliable.
3D Spectroscopy and the Virtual Observatory

Integral field, or 3D, spectroscopy is the technique of obtaining spectral information over a two-dimensional, hopefully contiguous, field of view. While there is some form of astronomical 3D spectroscopy at all wavelengths, there has been a rapid increase in interest in optical and near-infrared 3D spectroscopy. This has resulted in the deployment of a large variety of integral-field spectrographs on most of the large optical/infrared telescopes. The amount of IFU data available in observatory archives is large and growing rapidly. The complications of treating IFU data as both imaging and spectroscopy make it a special challenge for the virtual observatory. This article describes the various techniques of optical and near-infrared spectroscopy and some of the general needs and issues related to the handling of 3D data by the virtual observatory.
Mahalanobis distance on Grassmann manifold and its application to brain signal processing

Multi-dimensional data such as image patterns, image sequences, and brain signals, are often given in the form of the variance-covariance matrices or their eigenspaces to represent their own variations. For example, in face or object recognition problems, variations due to illuminations, camera angles can be represented by eigenspaces. A set of the eigenspaces is called the Grassmann manifold, and simple distance measurements in the Grassmann manifold, such as the projection metric have been used in conventional researches. However, in linear spaces, if the distribution of patterns is not isotropic, statistical distances such as the Mahalanobis distance are reasonable, and their performances are higher than simple distances in many problems. In this paper, we introduce the Mahalanobis distance in the Grassmann manifolds. Two experimental results, an object recognition problem and a brain signal processing, demonstrate the advantages of the proposed distance measurement.
Programa Nacional de Melhoria do Acesso e da Qualidade da Atenção Básica (PMAQ-AB): modelização da política no âmbito nacional

Pretendeu-se identificar os elementos constituintes do arcabouço teórico do PMAQ-AB e, assim, sistematizar o modelo lógico deste programa. Para tanto, foi realizado estudo de avaliação que abrange revisão e análise de documentos, dentre os quais foram incluídos 35 referentes à intervenção proposta no âmbito nacional. Com base na elaboração do modelo foi possível compreender a plausibilidade lógica da proposta. Podese presumir que esse resultado permitirá a ampliação da visão de avaliação para as questões de organização relacionadas ao programa, ao tornar possível uma comparação entre o programa como fora previsto e o que tem sido, de fato, implementado nos diversos contextos dos municípios brasileiros.
Blind compute-and-forward

Compute-and-forward (C&F) relaying usually requires channel state information (CSI) at the receivers so that an “optimal” scale factor can be computed for the purposes of decoding. In this paper, a blind C&F scheme - i.e., one not requiring CSI - is developed. Rather than attempting to compute the optimal scale factor, this new scheme seeks one (or more) “good” scalars, i.e., scalars which allow correct decoding despite possibly being sub-optimal. The region of all such good scalars is characterized. To find a good scalar, a computationally efficient scheme, involving error-detection and a hierarchically organized list, is proposed. Simulation results show that this blind C&F scheme achieves - for a class of lattices admitting an efficient trellis decoder - the same throughput as its CSI-enabled counterpart, at the expense of, approximately, a ten-fold increase in computational complexity in the high-throughput region.
Development of a Observe-By-Wire System for Forklifts Using Haptic Interfaces

This paper proposes a new concept of a haptic user interface for forklifts. The haptic interface is developed including valuable features and we named it "observe-by-wire" (OBW), which can give operators maximum visibility for safe operation. Particularly, the use of a OBW can help human to overcome the problems related to the blind spots caused by the mast configuration of forklifts. The OBW transmits distance information between forks and obstacles to operator in term of force feedback information. It is expected to be useful in emergency cases such as: moving large boxes, lack of illumination in warehouses. We have created OBW system, modeled the fork and its operations. Experiments were carried out with a group of seven subjects. The experimental results indicated that the OBW system can improve the visibility and operating performance of forklift's drivers. In particular, The OBW could give a haptic-based interaction channel between the drivers and vehicles regardless to the height of masts as well as intensity of illumination.
Microparticles – messengers of biological information

• Introduction • Microparticles • Methodological aspects • Understanding microparticles – from biomarker to messenger • Understanding microparticles – intercellular communication pathways ‐ MP as signalling molecules ‐ Transfer of complete receptor proteins ‐ MP as exchange vectors of mRNA • Conclusions and perspectives • Conflict of interest
I feel it in my fingers: haptic guidance on touch surfaces

Touch screens are on the rise and replace traditional knobs and buttons at a fast pace. However, their lack of tangible guidance and feedback can become a problem in scenarios where visual attention is scarce. Besides dynamic tactile feedback by vibrations, the usability of touch screens can be improved by static haptic structures such as shaped or structured surfaces. In this paper we describe the prototype of an in-vehicle application using unimanual four-finger interaction and haptic guidance in order to avoid visual distraction from the primary task of driving. We built a low fidelity prototype with static haptics using an Android tablet and silicone foil. A user study showed that flexible positioning of touch buttons mapped to the user's fingers was more convenient and produced fewer errors than fixed positioning. A curved haptic border provided the user with orientation and allowed a new selection mode: dragging buttons over the edge resulted in a reduced interaction time when compared to double tapping. We present several different variants for unimanual multifinger interaction on planar and non-planar surfaces. Our results can support the development of future concepts for blind interaction.