Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Understanding Feeding Motivation and Management Factors Affecting Feeding Behaviour in Limit-Fed Dairy Heifers

Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA)/University of Guelph Production Systems research grant and a Campbell Centre for the Study of Animal Welfare research grant. This project was also supported through contributions from the Canadian Foundation for Innovation (CFI) and the Ontario Research Fund. Angela Greter was supported through NSERC Alexander Graham Bell Canadian Graduate Student scholarship
Temporal Affixation in Polish Sign Language

Abstract:The following article undertakes another analysis of affixation in Polish Sign Language (PJM). This time the question concerns affixes carrying temporal significance. In a previous issue of this journal, negative affixation in PJM was discussed. As it turns out, in addition to these negative morphemes, PJM also possesses suffixes that relate to time: year, day, hour, minute and second. It has been observed that these affixes have undergone partial or complete grammaticalization. As discussed in this paper, there are some restrictions on the use of temporal suffixes, which are caused by numeral incorporation. In addition to these affixes, there are also two morphemes in PJM, which do not represent a time measure. One of these signifies the completion of an educational stage and the other refers to the future performance of an action.
Podcasting in Higher Education: Toy or Tool?

Podcasting is the creation of audio or video files for use on ipods and other mp3 players. It allows the user to view or listen to downloadable files wherever or whenever desired. In higher education, podcasting is experiencing extraordinary growth. While a significant volume of literature exists both lauding and lamenting the incorporation of podcasts into university curricula, the authors were unable to find any empirical studies in either the academic or popular press evaluating any benefits or detriments attributable to educational applications of podcasting. This paper presents the pilot for an empirical study of the effectiveness of podcasting as a course supplement.
Weighted Norm Inequalities for Marcinkiewicz Integrals with Non-Smooth Kernels on Spaces of Homogeneous Type

In this article, we obtain some weighted estimates for Marcinkiewicz integrals with non-smooth kernels on spaces of homogeneous type. The weight w considered here belongs to the Muckenhoupt’s class A∞. Moreover, weighted estimates for commutators of BMO functions and Marcinkiewicz integrals are also given.
Real‐time architecture for advanced quality monitoring in manufacturing

Explains that the rapid growth of artificial intelligence techniques, especially neural networks and knowledge‐based systems, have paved the way for the development of an intelligent and real‐time manufacturing information system. By efficiently utilizing the specific domain representation in a production cell, an intelligent system can manage the complex issues concerning the structure and character of the product, goals of the manufacturing unit and provide production guidance accordingly. Addresses issues in manufacturing intelligence through two case studies that demonstrate the feasibility of a real‐time quality control in changing environmental conditions. The quality and the factor of acceptability are determined by the intelligent agent. These intelligent agents involve the use of an artificial neural network system and, in some cases, a knowledge‐based system to control and operate, in real‐time, the functions of an inspection process in manufacturing. Addresses the design issues of interest, especially setting up global routines which can be used in a common platform to control a machine tool, interpret the sensor inputs, monitor the quality of products, and take corrective actions on a real‐time basis.
Protection performance testing in IEC 61850 based systems

IEC 61850 offers significant advantages when compared against other substation communication protocols; in particular the replacement of analogue and binary signals with Ethernet messages reduces the cost of the system and improves flexibility and functionality. However, it also requires a new type of test bench suitable for the functional and performance testing of IEC 61850 compatible protection relays and systems. Test sets used in such applications need to have the functionality to perform coordinated and precisely synchronised tasks as a part of a distributed, system wide test facility. Methods for testing conventional protection relays will be reviewed and some of the issues that affect how we test the next generation of relays will be discussed; the paper will also investigate new approaches for testing IEC 61850 compatible relays based on the Real Time Digital Simulator (RTDS) and the OMICRON test set. The structure and implementation of a new RTDS system based on IEC 61850 standard are proposed. A test model connecting the RTDS system and the secondary digital devices will be presented. (5 pages)
ANALIZA KOLIČINE FEDINGA SSC PRIJEMA U KANALU SA KORELISANIM α-μ FEDINGOM AMOUNT OF FADING ANALYSIS FOR SSC RECEIVERS IN CORRELATED α-μ FADING CHANNELS

In this letter, the analysis of amount of fading (AoF) as a part of the performance analysis of switch and stay combining (SSC) scheme is presented. The proposed system is analysed over correlated α-μ fading channels. Using required mathematical evaluations, infinite series expressions for the probability density function (pdf) and the moments of the output envelope are derived. The proposed analysis is used for evaluating AoF as an important performance criterion. The effects of fading severity and branch correlation are considered and numerically presented.
PIPELINE AND DEEP LEARNING APPROACH FOR NLIDB: A COMPARATIVE STUDY

Databases are integral part of current world’s scenario of rich technology. Greater amount of the data in the world is stored in the databases. That amount of data storages can be utilized for various purposes in data science world. Besides potential usage and benefits of available data amounts, the requirement of formal language to access the databases is a huge hurdle. Structured Query language (SQL) is one of such formal languages to access the database. Besides its impact and powerful as a language it is not a common knowledge. Therefore, domain experts of some particular databases cannot access their data freely and easily. Web interfaces to access that data has their own limitation and do not fulfil the purpose to the maximum of the potential of data. Natural Language Interface to Database (NLIDB) system is natural solution for such problems. Text to SQL task in NLIDB system is being experimented with since 70s. Previously it was based on integrated methods and techniques from Natural Language Processing (NLP) and Data Science areas, those integrated frameworks generally known as pipeline methods. Recently, machine learning showed promising performance for the solutions to semantic problems. Which is why, deep learning had been adopted for text to SQL task as well. Currently NLIDB systems research is going on with both of the approaches of pipeline methods and deep learning methods in parallel. It is important at this time to analyze the latest work with both approaches and compare and identify their unique challenges and issues as well as findings and potential of both approaches for the NLIDB systems. In this paper, a comparative analysis is presented to find out the achievements and issues of NLIDB with pipeline methods and with deep learning methods regarding each of them.
Analytical design and analysis procedure for a transverse flux machine

A transverse flux machine (TFM) offers a higher specific torque and power density than a conventional radial flux machine, though at a cost of a poorer power factor. This paper provides an analytical approach to dimension an application-specific TFM and analyse its performance for first order calculations. Important features of TFMs are also outlined to facilitate an understanding of its operation and design. The design is explained with reference to an arbitrarily chosen application; a TFM wind generator. Only a surface mounted, single sided, outer rotor TFM generator design is treated. The method can however be equally applied to other types of TFMs, with proper adjustments of the analytical models.
Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks

Sampling-based motion planning is a popular approach in robotics for finding paths in continuous configuration spaces. Checking collision with obstacles is the major computational bottleneck in this process. We propose new learning-based methods for reducing collision checking to accelerate motion planning by training graph neural networks (GNNs) that perform path exploration and path smoothing. Given random geometric graphs (RGGs) generated from batch sampling, the path exploration component iteratively predicts collision-free edges to prioritize their exploration. The path smoothing component then optimizes paths obtained from the exploration stage. The methods benefit from the ability of GNNs of capturing geometric patterns from RGGs through batch sampling and generalize better to unseen environments. Experimental results show that the learned components can significantly reduce collision checking and improve overall planning efficiency in challenging high-dimensional motion planning tasks.
DAS VENTRIKULÄRE AKTIONSPOTENTIAL (LUO-RUDY-MODEL) - EINE COMPUTERSIMULATIONSSTUDIE

Die Modellierung der elektrischen Aktivität der Herzmuskelzellen ist seit den fünfziger Jahren [1], [3J, [4J, [5] Gegenstand zahlreicher Untersuchungen, insbesondere als hiermit die komplexen mikroskopischen Vorgänge im Herzmuskelgewebe untersucht werden können. Neben einem Modell für die Zelle der Purkinje-Faser [3] wurde in den siebziger und neunziger Jahren ein Membranmodell für die Zelle des ventrikulären Myokardialgewebes [1], [4] entwickelt. Diese Modelle basieren weitgehend auf dem Hodgkin-Huxley-Mechanismus [5] der potentialund zeitabhängigen Torvariablen, wobei in [3] und [4] zusätzlich der Einfluß ionischer Konzentrationsänderungen berücksichtigt wird. Das von uns verwendete Modell [4] stützt sich sowohl auf single-cell-recordings als auch auf single-channel-recordings\ da die Änderung der extrazellulären Kaliumkonzentration [K]Q den zeitlichen Verlauf der Repolarisation stark beeinflußt, wird in diesem Modell die Abhängigkeit der Kaliumströme von der [K]Q berücksichtigt; außerdem wird der dynamische Verlauf der intrazellulären Calciumkonzentration [Ca^ durch eine zusätzliche Differentialgleichung in Betracht gezogen. Das die dynamischen Zellmembranvorgänge beschreibende System setzt sich aus acht gekoppelten nichtlinearen Differentialgleichungen zusammen. In dieser Studie wird sowohl das Verhalten der Einzelzelle, u.a. die supernormale Erregbarkeit (superncrmal excitability) und die Wenckebachmuster, als auch die eindimensionale Erregungsausbreitung unter dem Einfluß eines entlang der Faser variierenden spezifischen intrazellulären longitudinalen Widerstandes Rj und unter dem Einfluß einer variierenden [K]Q untersucht. Als Integrationsalgorithmus wird die Hybrid-Integration-Method verwendet [6], Die Algorithmen für die Simulation der Erregungsabläufe in einer Einzelzelle als auch für die Ausbreitung der Erregung entlang einer Faser wurden auf einer DECstation 5000/240 unter Verwendung von MATLAB implementiert.
Using Unlabeled Out-Of-Domain Data to Improve Question Answering

Our goal is to use unsupervised learning to improve the baseline of question-answering on the BioASQ dataset. We train our model on labeled training data from BioASQ, as well as unlabeled data from SQuAD (a significantly larger dataset), and we use a form of data augmentation by applying Gaussian noise to the word embedding input vectors to have the model obtain a more generalizable, domain-invariant underlying feature representation that is smooth over changes in the input space. Using this unsupervised loss term and optimizing only hyperparameters relevant to this loss term, we were able to get an approximate 6 point boost for EM and a 5.5 point boost for the F1 score on average on the BioASQ development set, although the models tend not to generalize very well to the unlabeled SQuAD examples used in unsupervised training, and can actually degrade performance on SQuAD if too much noise is used.
Deep Reinforcement Learning of the Inverse Pushing Model in Robotics

—This thesis presents a Deep Reinforcement Learning Framework approach to learn inverse models for robotic push manipulation of single objects, based on available forward pushing models. The introduced framework has the ability to learn the inverse pushing model of an object for which a point cloud can be acquired at run time. This work illustrates the application of the proposed approach on a box shaped object. Planar pushes being quasi-static processes are considered and only 2-Dimensions are taken into account. The inverse models are learned for a discrete set of actions. The aim of these models is to push the object as close as possible to a target pose in a single action. The push actions are parametrized by contacts sampled on the object surface and by motion models encoding possible robot actions. Pushing goals are sampled from a Gaussian probability distribution function based on the forward models outcomes. In the considered environment, the proposed approach achieves success rates over 0,8 at the given task.
AI Gone Rogue: Exterminating Deep Fakes Before They Cause Menace

The face: A crucial aspect of identity. But what if this crucial part of one’s identity is stolen from an individual? Yes, this now happens and is termed “Deep Fake. ” Deep fake technology is an artificial intelligence (AI)-based human image blending method used in different ways, such as when creating revenge pornography and fake celebrity pornographic videos, or even in cyber propaganda. Videos are altered using Generative Adversarial Networks (GANs) in which the face of the speaker is manipulated by a network by swapping it with someone else's face. These videos can sometimes be identified as fake by the human eye; however, as neural networks get rigorously trained on more resources, it will become difficult for the human eye to identify fake videos. Such videos can cause chaos and bring economic and emotional damages to one's reputation. Videos targeted against politicians in the form of cyber propaganda can prove to be catastrophic to a country's government. In the bigger picture, it has the potential to undermine democracies. In this study, we have discussed the many tentacles of Deep Fake and the extent of damage it can cause. Additionally, we share our progress on our proposed solution: to identify complex Deep fake videos using deep learning. We used a pre-trained Facenet model. The model was trained on the image data of people of importance or concern. After training, the output of the final layer was stored in a database. A set of sampled images from a video was passed through the same model and the output of the final layer from the neural network was compared with values stored in the database. A simple Euclidean distance measure between the encodings can recognize the actor in the video, which can in turn help us in finding out if the video is fake. In 2018, we believe that Deep Fakes have already progressed to a different level. We also discuss other defensive measures against Deep Fakes.
Microbial Characterization of Carbonate Surface Sediments from the Bahamas and Turks and Caicos Platforms

Microorganisms are abundant and ubiquotous components of carbonate sediments where their metabolisms can modify the geochemical conditions of their surroundings. The consortia of microorganisms along with their vast metabolic diversity allow these communities to efficiently cycle major elements and mediate the degree of carbonate saturation (González-Muñoz 2010; Dittrich and Sibler 2005; Baskar et al 2006) Heterotrophic and autotrophic bacteria are known to play a role in carbonate precipitation (Dupraz et al 2009). These microbes contribute to the formation of carbonates deposits that potentially form reservoir rocks, such as stromatolites (Dupraz and Visccher 2005), dolomites; (Wright and Wacey 2005) and ooid shoals (Kahle 2007). The primary role of bacteria in the precipitation process has been attributed to their metabolic activity (sulfate reduction, denitrification, ammonification, anaerobic sulphide oxidation, and photosynthesis) creating an alkaline environment that induces mineral precipitation (Douglas and Beveridge 1998, Castanier et al. 2000). In addition, the negatively charged nature of their cell wall and extracellular polymeric secretions (EPS), which is influenced by specific functional groups, can further trigger precipitation as they create an ideal microenvironment for crystal nucleation sites of divalent cations, Ca and Mg (Rivadeneyra et al. 1998). Gerdes et al. (1994) observed that patterns of calcification in biogenic carbonates emphasize both ecological situations and conditions of early diagenesis.
How to get started: Three tips from Quality Action

A good starting point for introducing participation and at the same time practicing a method from the tool kit is Circles of Influence. As a stakeholder mapping exercise it introduces the ‘levels of participation’. Applying Circles of Influence to the project (or the work of the organisation as a whole), gives you a snapshot of where you stand with participation. It makes it easier to decide as a team where you want to increase (or decrease) the level of stakeholder participation. For example, if your team decides to increase the participation of the target group in the planning of an intervention, you can then select a PQD method to achieve it (e.g. Rapid Assessment or Project Advisory Group).
Special events travel surveys and model development

Abstract The travel associated with special events in any metropolitan region is often under-represented in regional travel demand models owing to the lack of travel data to and from these events. This paper presents a comprehensive data collection effort aimed at capturing travel data related to special events and development of a standalone special events model for the Phoenix metropolitan area. The importance of this study was highlighted by the success of the introduction of light rail transit in the region. Special event patrons constitute a significant portion of the light rail ridership and overall regional travel demand. Therefore, the need to better understand and forecast transit markets served as the impetus to conduct an in-depth study and modeling of planned special events in the region. This paper focuses on all aspects of data collection and model development including survey design and sampling plan, collection of special events travel data, expansion of survey data, model design, estimation and development of the special events model, calibration and validation, integration with the four step trip based model, and the impact on light rail transit ridership due to special event travel.
Aging-as-Leveler, Persistent Health Inequality, Cumulative Disadvantage, or All Three? Race/Ethnicity, Life Course Capital and Health Trajectories*

Racial/ethnic disparities in health levels are well-documented, yet less is known about racial/ethnic differences in age-trajectories of health. This study integrates demographic and developmental perspectives by utilizing life course theory, panel data from the Health and Retirement Study, and multilevel growth curves to investigate racial/ethnic differences in trajectories of chronic conditions and functional limitations. We empirically test three hypotheses on the nature of racial/ethnic inequalities in health across the life course (i.e., aging-as-leveler, persistent inequality, and cumulative disadvantage hypotheses), and the extent to which racial/ethnic inequalities in life course capital account for health disparities. While aging-asleveler, persistent inequality, and cumulative disadvantage theories are often framed as competing perspectives, we find evidence to support each of them, suggesting that the underlying mechanisms are contingent upon the life stage and health outcome being analyzed. Controlling for measures of life course capital reduces but does not eliminate racial/ethnic disparities in health trajectories.
Recent spruce (Picea abies) treeline ecotonal progression since the late1980s in the Swedish Scandes-a repeat photographic narration and analysis

This study reports a case of climate-mediated transformation and physiognomic progression of the Norway spruce (Picea abies) treeline ecotone since the mid-1990s in the Swedish Scandes. The methods include repeat photography and foliation estimates of old-established clonal spruces. An air and soil temperature nadir by the 1980s had caused extensive needle and shoot mortality, evident at the landscape-scale. Subsequent winter and summer temperature rises induced a striking canopy recovery, including densification and vertical growth. Release from low soil temperature stress appears as instrumental for canopy progression and shift from stunted growth to erect tree forms. Seed-based regeneration of new individuals has been virtually nil and the ecotone appears to be spatially stable. Ongoing ecotonal shifts has the character of growth form transformations in accordance with climatic conjunctures.
Maternal and Child Undernutrition 1 Maternal and child undernutrition: global and regional exposures and health consequences

Maternal and child undernutrition is highly prevalent in low-income and middle-income countries, resulting in substantial increases in mortality and overall disease burden. In this paper, we present new analyses to estimate the effects of the risks related to measures of undernutrition, as well as to suboptimum breastfeeding practices on mortality and disease. We estimated that stunting, severe wasting, and intrauterine growth restriction together were responsible for 2·2 million deaths and 21% of disability-adjusted life-years (DALYs) for children younger than 5 years. Deficiencies of vitamin A and zinc were estimated to be responsible for 0·6 million and 0·4 million deaths, respectively, and a combined 9% of global childhood DALYs. Iron and iodine deficiencies resulted in few child deaths, and combined were responsible for about 0·2% of global childhood DALYs. Iron deficiency as a risk factor for maternal mortality added 115 000 deaths and 0·4% of global total DALYs. Suboptimum breastfeeding was estimated to be responsible for 1·4 million child deaths and 44 million DALYs (10% of DALYs in children younger than 5 years). In an analysis that accounted for co-exposure of these nutrition-related factors, they were together responsible for about 35% of child deaths and 11% of the total global disease burden. The high mortality and disease burden resulting from these nutrition-related factors make a compelling case for the urgent implementation of interventions to reduce their occurrence or ameliorate their consequences.