Miracle-dz/UniFAR-FTUs huggingface dataset:
DEFATTED MAIZE GERM IN EQUINE

This study investigated the inclusion levels of defatted maize germ (DMG) in the diet of horses by determining the apparent digestibility coefficients of the nutrients, and the physicochemical parameters of feaces and blood samples. Four adult horses, weighing 483.3 ± 27.5 kg average, arranged in 4x4 Latin square were used. The energy provided by the diets came from hay, 50% (Jiggs hay), and from the concentrate, 50%, with increasing DMG levels (0, 10, 20 and 30%). Digestibility was determined using samples from total feaces collection. The characteristics of color, consistency, pH and buffering capacity (BC) 5 and 6 of the feaces were determined daily during the collection days. The blood samples were collected by venipuncture of the jugular, with vacuum tubes, to determine the concentration of glucose, triglycerides, cholesterol and insulin using biochemical kits and the concentration of short-chain fatty acids, by gas chromatography. The diets did not affect significantly (P> 0.05) the digestibility of nutrients, fecal pH (mean 6.7), buffering capacity at pH 5 (22.7) and pH 6 (6.9), and fecal concentration of short-chain fatty acids. Likewise, diets did not affect significantly (P> 0.05) the blood concentrations of glucose, insulin, cholesterol, and total short-chain fatty acids. However, diets changed significantly (P <0.05) the blood concentrations of triglycerides, described by the equation ŷ = 30.62 + 0.26x. The triglycerides, glucose and insulin variables also changed significantly (P <0.05) over time, according to the following equations: ŷ = 32.30 + 0.87x; ŷ = 85.93 + 3.17x – 0.61x2; and y = 3.19 + 1.38x – 0.22x2, respectively. The defatted maize germ can be included up to 30% of the concentrate (up to 9.6% of the diet) without changing the diet apparent digestibility coefficient, and feaces and blood physicochemical parameters. This ingredient can be an alternative for high fiber diets and can contribute to formulating diets with lower glycemic and insulinemic indexes.
The Fast Merging Module ( FMM ) for readout status processing in CMS DAQ

The Fast Merging Module (FMM) is part of the Trigger Throttling System (TTS). The TTS adapts the trigger frequency to the DAQ capacity in order to avoid congestions and overflows. The states of all data sources (~640 in the case of CMS) are read out and merged by the FMM to obtain the status of each detector partition. The functionality and the design of the FMM are presented in this paper.
Bacterial Community Structure of Fermenting Grains in Fen Wine

Fen wine is a typical representative of Daqu Fen-flavor liquor with traditional solid-state separation fermentation and secondary pure-steaming technology. Due to the non-sterile and open solid-state fermentation procedure, the bacteria community involved exhibit a high complexity. This makes it difficult to control the fermentation process, which is critical to the overall quality and taste of the Fen wine. In this study, we applied the Illumina MiSeq to characterize the overall bacteria species during the fermentation of grains. The results showed the changes of bacteria community structure, including the number of species and their relative quantity, which will help to standardize the fermentation procedure and provide a valuable quality control standard. Key words: Fen Wine; Fermenting Grains; Bacterial Diversity; High- Throughput Sequencing
Federated Meta-Learning : Democratizing Algorithm Selection Across Disciplines and Software Libraries-- Proposal , v 1 – Joeran Beel

There is an ever-growing number of tools for automating the machine learning pipeline, both commercial and open source. Auto-sklearn [11, 15], Auto Weka [14], ML-Plan [18], and H2O.ai are only some examples. In addition, the auto∗ movement reached other areas of data science in the wider sense, for instance, the recommender-system community with LibRec-Auto [17]. A key component many of these auto∗ and algorithm selection tools is the algorithm selection and configuration process, which is subject to intensive research [1–3, 6, 7, 9, 10, 12, 13, 16, 20, 22, 24]. In some disciplines, like the SAT community, automated algorithm selection tools like SATzilla achieved remarkable improvements compared to ́standard ́ algorithms [25]. Meta-learning is one of the most promising techniques to warm-starting the algorithm selection and configuration process [12]. With meta-learning, a machine learning model is trained to predict how algorithms will perform on a given task. That predicted algorithm can then either be applied directly to solve the task, or further be optimized. The meta-learning model is built based on the past performance of algorithms on a large number of tasks (datasets). The tasks are typically described through metafeatures, and for new unseen tasks, the most performant algorithms can be predicted through the meta-learner. Metalearning is not only used for predicting the performance of machine learning algorithms but for almost any kind of algorithm selection in various disciplines (SAT [25]; recommender systems [5, 8]; reference parsing [21].).
Real-time Performance of Embedded Platform for Autonomous Driving Using Linux and a GPU

Autonomous driving systems and advanced driver assistance systems (ADAS) have been developed to improve driving safety. These systems are becoming increasingly complicated, and the computing power they require continues to increase. Software platforms, such as Automotive Grade Linux, are being developed to handle the complexity of autonomous driving, and graphical processing units (GPUs) are being used in these systems for tasks such as recognition of driving environments, deep learning, and localization. However, to the best of our knowledge, the real-time performance of Linux combined with a GPU for ADAS has not yet been reported. In this study, we developed lane keeping and collision avoidance systems to evaluate the real-time performance of Linux and a GPU. The experimental results show that the real-time performance of the system could be improved using widely available versions of Linux without software customization. Also, although the GPU execution speed was sufficiently high, camera image capture was relatively slow and created a bottleneck in the system.
A guideline to French firm-level trade data

French customs data have been widely used in the recent empirical literature to study various trade-related topics. While access to these data is relatively easy, there is little documentation that can help researchers identify questions that such data can tackle and construct a dataset which best fits the question under study. This note provides such guidance, with a special focus on longitudinal studies. We describe the characteristics of data collection which has consequences for the scope and information available to researchers. We provide a list of minimum data trimming steps that allow recovering consistent time-series as well as more advanced algorithms that we argue are useful when using the data for more particular purposes. Finally, we provide broad statistics about the structure of the data.
OPTIMUM WOOL HARVEST INTERVAL OF ANGORA RABBITS UNDER ORGANISED FARM CONDITIONS IN EAST CHINA

The present study was conducted to evaluate the commercial lifespan and optimum wool harvest interval of Angora rabbits. One hundred shorn Angora rabbits were housed in an organised farm to describe the wool production curve. It showed that the optimum wool harvest interval was 75 d, when fibre length reached 55.0 mm. Wool production was lower from the 3rd to the 6th mo (young stage) than from 7th to 28th mo and rapidly decreased from 28th to 31st mo and was the lowest from 31st to 33rd mo of age. Feed intake-towool production ratio was higher from 3rd to 4th and from 7th to 9th mo of age than during the adult stage, and increased from 31st to 33rd mo of age. Daily weight gain was significantly higher from 3rd to 4th mo of age than in any other periods of the adult stage, and was negative from 23rd to 33rd mo of age. Therefore, the study reveals that the commercial lifespan of Angora rabbits was approximately 28 mo. Furthermore, wool production was higher in spring and winter than in autumn, and was the lowest in summer. Concomitantly, feed intake-to-wool production ratio was lower in spring than in autumn and winter, and was the highest in summer. Finally, daily weight gain was higher in spring and autumn than in winter, and was the lowest in summer. This indicates that wool production was depending on the season, and decreased significantly in summer. Moreover, the spring provided the best conditions for Angora rabbits.
The Impact of U . S . Interest Rate Changes on Emerging Market Countries under cost-push shocks and natural rate shocks

This paper analyzes the impact of U.S. interest rate changes under cost-push shocks and natural rate shocks on, and these shocks’ transmission to emerging market countries. The theoretical model of a small open economy finds that changed exchange rate (exchange rate channel) is negative USD depreciation under cost-push shock, while positive USD appreciation under natural rate shock. The differences under two shocks are amplified through domestic bonds (financial market channel) and terms of trade (trade market channel). Then, real output of emerging economy with PPIbased Taylor rule is positive under both shocks and less volatile under cost-push shock given same magnitude of shocks. This paper also uses Bayesian local projections to test empirical sample that consists of 5 emerging and 5 developed countries. As the prediction of model, exchange rate channel has significant and different effects under both shocks. The empirical results reveal cost-push shocks cause larger volatility than natural rate shocks for each country, due to their characteristics large deviation and less persistence. Under natural rate shocks, consumption tends to be more volatile than output in emerging economies while consumption is less volatile than output in developed economies. However, consumption is roughly as volatile as output under cost-push shocks in both emerging and developed economies.
A Simulated Annealing based approach for solving SplitSearch

Real-time applications that provide location-based services according to the user queries, can in general be modelled as large-sized combinatorial optimization problems. The primary criterion in such commonly used location-based services is to provide an optimal solution from a dynamically-changing solution space, which is exponential in the input size, meeting realtime constraints. In this paper, we discuss a heuristic approach based on Simulated Annealing technique to address one such location-specific problem of SplitSearch. With a user requesting for ’n’ services and there being ’m’ providers for each of these ’n’ services, SplitSearch addresses the selection of the optimal set of providers, with respect to the distance travelled, that can satisfy the requested services. The paper illustrates the improvement in the quality of the solution thus obtained in comparison with that of Greedy approach. A mathematical formulation is also proposed for the problem, in the form of an Integer Linear Program (ILP).
Transforming Probabilistic Programs into Algebraic Circuits for Inference and Learning

Probabilistic (logic) programs are routinely compiled into arithmetic circuits. During such a compilation step, the logic representation of a probabilistic program is transformed into an arithmetic representation. We show that this transformation and the resulting circuits cannot only be used for discrete probabilistic inference, but also for a number of other tasks such as differentiation, learning and probabilistic inference in the discrete-continuous domain. 1 Probabilistic Programming via Weighted Model Counting Probabilistic programming extends high-level general purpose programming languages with probabilistic primitives. This allows for concisely modelling complex probability distributions without having to deal with the intricacies of probabilistic inference. One such probabilistic programming language is ProbLog (Fierens et al., 2015), where a probabilistic model consists of a set of probabilistic logical rules and probabilistic logical facts. We give an example program in Figure 1a. ProbLog performs probabilistic inference by reducing the task of computing the probability of a query being satisfied to the task of weighted model counting (WMC) (Chavira and Darwiche, 2008). Definition 1. (WMC) Given are 1) a propositional logic theory φ over a set of variables b representing the program and query and 2) a labeling function α : L → [0, 1], mapping literals in L from the variables in b to their probabilities. The weighted model count of a theory φ is then defined as: WMC(φ, α|b) = ∑bI |=φ ∏bi∈bI α(bi) (1) where bI denotes an interpretation satisfying φ. 1 0.6::burglary. 2 0.2::earthquake. 3 0.5::alarm_on. 4 5 alarm :alarm_on, burglary. 6 alarm :alarm_on, earthquake. (a) The ProbLog program alarm
The Role of Human Relations and Interactions in Designing Memory-Related Models for Sensor Networks

Recently, the use of Wireless Sensor Networks has become substantial in most of our life aspects. These networks have many issues and challenges at the design phase (e.g., memory and power consumption). There exists a huge amount of works and studies that offer and provide solutions for many of these challenges. However, the issues of predicting memory requirements and memory management have not received enough attention in sensor networks literature. Yet, most of the studies in this field focus on issues related to power consumption and connectivity of sensor nodes. This paper has two main purposes: first, we propose a metric for measuring the strength of a relation between two sensors. In the proposed metric, we involve three important characteristics of human relations and interactions: encounter frequencies, duration of encounters, and regularities of encounters. We then exploit this metric in predicting memory requirements in a sensor network. Second, based on the estimated memory size, we propose an approach for memory management in a sensor network. The proposed approach is based on two concepts: social capital in sociology and preferential return in human mobility. The results show that our approach is effective in managing sensor memories comparing to other approaches in the literature. Copyright © 2016 IFSA Publishing, S. L.
Direction-discrimination training improves reading fluency in dyslexics 1 Direction-Discrimination Training Improves Reading Fluency in Dyslexics and Provides Evidence that Dyslexia Results from Magnocellular Timing Deficits

This study examined the effects of direction-discrimination training on reading performance in normal and dyslexic second graders. Participants were divided into two groups: Dyslexic and normal readers. Each of these groups was randomly split into three subgroups, each of which used a different training regimen (direction-discrimination, word, and no training). This study found that not only can dyslexic readers be differentiated from normal readers by their significantly lower sensitivity to the direction of movement, but that their motion sensitivity and reading proficiency improved significantly and permanently following a short course (biweekly 10-minute sessions for 15 weeks) of directiondiscrimination training. These improvements in reading fluency, comprehension, spelling, and word identification were found only for dyslexics in the subgroup using the direction-discrimination training regimen. Finally, these results provide evidence that timing deficits in the magnocellular pathways underlie dyslexics' poor reading skills. _____________________________________________________________________________________ A child’s visual system is maturing rapidly up until the age of 8 (Thatcher et al. 1987; Van Sluyters et al. 1990), the period when a child is learning to read. There is much cortical plasticity during this period, and age seven is the middle of the developmental period for learning direction discrimination (Lawton, 2000; Lawton, 2008), so the current study focused on second graders, who average seven years of age. Many children have difficulty with reading. In fact, sixty-seven percent of fourth grade students across the nation do not read proficiently (National Assessment of Educational Progress (2007)). Recent research (Vidyasagar, 1999; Lawton, 2000, 2004, 2007) suggests that children who are inefficient readers have timing deficits between their magnocellular (dorsal stream) and linked parvocellular (ventral stream) pathways that prevents efficient reading. While not all inefficient readers are dyslexic, this timing deficit is particularly pronounced
Title: Physiological profile of Asian elite youth soccer players Running title: Physiological profile of youth soccer players

Objective: The purposes of this study are to provide information about the physiological characteristics of Asian elite youth soccer players (a) for strength and conditioning specialists to design training program based on players’ physiological characteristics; and b) for coach to design an appropriate play tactic. Design: Sixteen Chinese elite youth male players (height: 173 ± 5.2cm; weight: 64.2 ± 8.1kg; age: 16.2 ± 0.6year) from the U-17 national team participated in the following tests in the current study: (a) maximal vertical jump; (b) isokinetic muscular strength tests of knee joint at angular velocities of 60, 120, 180, 240, and 300deg/s; (c) maximal oxygen consumption (VO2max); (d) one repetition maximum (1RM) strength test; and (e) 30m sprint. Results: As compared to European and African players, Asian youth players have less jump height and shorter body height. They also have poor performance in isokinetic muscular strength of quadriceps and hamstrings (especially at high speed), VO2max, 1RM strength test, sprint starts, and 20-30m sprints. Conclusions: A specialised training in jumping performance, high-speed movement, muscular strength at high contraction speed, endurance running, short distance sprint (i.e. 5m), and 20-30m sprints are recommended for Asian elite youth soccer players (or players with similar physique and ability).
Increasing Awareness of Cellular Signals on Smartphones using Augmented Reality

Augmented Reality (AR) can be used to enhance consumed information visually and textually. When it comes to a cellular signal strength, a user might be skeptic how strong it is, actually. Some may concern about good signal receiving in terms of coverage area, whereas some may concern about health affection. In this work, we aimed to increase awareness of cellular signals on smartphones using Augmented Reality (AR) technology. The invisible cellular signal is visualized on smartphones virtually with 3D objects and text information. The System Usability Scale (SUS) score shows that the usability of our application is above average with score of 69.75.
ANALYSIS OF SEISMIC ANISOTROPY IN LOS HUMEROS GEOTHERMAL FIELD , PUEBLA , MEXICO .

This study presents the results from the analysis of seismic anisotropy in Los Humeros Geothermal Field, Mexico, correlating the parameters of anisotropy: polarization (θ) of the fast shear-wave qs1 and time delay (δt) of the shear-waves qS1 and qS2, with the tectonics and horizontal stress state in Los Humeros Field. By correlating and studying the phenomenon of birefringence or double refraction of shear-waves, we managed to watch matches in the directions of polarization (θ) and fracturing present in-situ. The analysis includes two study periods: 1997 to 2002 and 2004 to 2008, in which we identified three areas of seismic anisotropy with the same direction of stress, fracturing and/or faulting: zone with efforts in NE-SW 200 direction, mainly due to regional tectonic stresses, zone E-W (NE-SW 85 °), an area with high structural complexity, mainly produced by the variation of the stress in the E-W direction, however most of the faults are inflicted in these directions, and finally the zone NW-SE 45 0, produced by stress with less tectonic influence, according to the associated fractures and polarization analysis in the stations.
Mining social media divides: an analysis of K-12 U.S. School uses of Twitter

ABSTRACT This study utilizes public data mining to explore participation divides of all available K-12 institutional Twitter accounts in the U.S. (n = 8275 accounts, n = 9,216,853 tweets). Results indicated that U.S. schools used Twitter to broadcast information on a variety of topics in a unidirectional manner and that hashtags included a variety of intended purposes, including affinity spaces, education topics, emotive language, and events. Those schools in wealthier, more populated areas were more likely to use Twitter, with wealthy, suburban schools being the most likely to use it and poor, rural schools being the least likely. Furthermore, factors such as charter school status and urbanity influenced the content of school tweets on key issues, with schools in more populated areas tweeting more about coding and college than schools in less populated areas and charter schools tweeting more about college and the politicized educational issue of common core than non-charters. These results reveal participation differences between schools based upon demographics and provides a basis for conducting future large-scale work on publicly available artifacts, such as school tweets, that may be meaningfully used as education research data.
Introduction Extracting Perceptual Structures in Line Patterns

The purpose of perceptual grouping is to organize image data in a scene without the aid of semantic knowledge. The resulting groups identify significant structural relationships which are helpful in scene interpretation. The perceptual organization process starts with the primitives or tokens obtained from the images and groups "similar" tokens. It groups dots into blobs, blobs into larger blobs, edge segments into longer curves or complex structures, etc. The similarity among tokens is defined in terms of intrinsic properties of primitives and their spatial relationship in the image plane. Previous work closely related to grouping and extraction of perceptual structure in vision includes the clustering of d-dimensional dot patterns,3,2, 1, 13 the orientation detection in glass patterns12,8 and dot patterns,19,20,21 the extraction of structure from a raw primal sketch,7,6, 15 and clustering of one-dimensional line segments.4, 10 The principles of perceptual organization, which have been studied by Gestalt psychologists16 and others6, 17, 19,20,21 include organization based on proxi111ity, collinearity, curvilinearity, symmetry, parallelism, repetition, and closure. However, it is still very difficult to define quantitative similarity measures among tokens. Additional problems arise due to conflicts between the rules of perceptual organization applied to a given pattern.