Miracle-dz/UniFAR-FTUs huggingface dataset:
A neural networks application for the study of the influence of transport conditions on the working performance

This paper presents a study about the factors that influence the working performances of workers in the automotive industry. These factors regard mainly the transportations conditions, taking into account the fact that a large number of workers live in places that are far away of the enterprise. The quantitative data obtained from this study will be generalized by using a neural network, software simulated. The neural network is able to estimate the performance of workers even for the combinations of input factors that had been not recorded by the study. The experimental data obtained from the study will be divided in two classes. The first class that contains approximately 80% of data will be used by the Java software for the training of the neural network. The weights resulted from the training process will be saved in a text file. The other class that contains the rest of the 20% of experimental data will be used to validate the neural network. The training and the validation of the networks are performed in a Java software (TrainAndValidate java class). We designed another java class, Test.java that will be used with new input data, for new situations. The experimental data collected from the study. The software that simulated the neural network. The software that estimates the working performance, when new situations are met. This application is useful for human resources department of an enterprise. The output results are not quantitative. They are qualitative (from low performance to high performance, divided in five classes).
New Distributional Records of Four Indo-Pacific Species from Astypalaia Island , South Aegean Sea , Greece

During in situ investigation carried out in July and August 2016 and 2017 successively by the authors in Astypalaia (South Aegean, Greece) the following alien species were recorded: (1) a colony of epibyssal pteriid Isognomon australica (Reeve, 1858) in shallow water under rocks, (2) two specimens of Isognomon legumen (Gmelin, 1791), (3) a live group of Indo-Pacific triphorid Viriola cf. bayani (Jousseaume, 1884), trawled at a depth of 35-50 m, and (4) a freshly dead specimen of Euthymella colzumensis (Jousseaume, 1898) also trawled at a depth of 35-50 m. A comparative study of collected material using type data, resulted in their identification and recording as Indo-Pacific newcomers to Greek waters. Moreover, it led to a first Mediterranean record for I. australica and E. colzumensis. These occurrences considerably far from the mouth of the Suez Canal support the assumption that a combination of conditions consisting an “Invasion window” converge in Astypalaia and favour the successful establishment of alien species not necessarily following the patterns of Lessepsian Migration. Introduction The main island of Astypalaia, with a number of adjacent islets form a small complex positioned between the Dodecanese and the Cyclades in the centre of the Southern Aegean Sea. The island’s lace-like coastline with coves and canals and its subtropical waters, though far from the mainland seem to favour the establishment of alien species expected to spread westwards to the rest of the Mediterranean. The present rather unexpected records draw interest to the study of conditions and vectors that make possible alien invasions (Carlton, 1996) in the east Mediterranean basin that are not explained by the Lessepsian Migration pattern alone. Four new alien species are recorded and described in this paper; their identification was quite difficult involving examination of original descriptions in old literature and type material of Indo-Pacific mollusc genera that are not yet adequately studied. A morphological approach for their identification was only possible because existing type material is not biologically described. Nevertheless, we managed to make three new taxonomic identifications recorded for the first time from Mediterranean waters and a fourth one which is a first record for Greek waters. First Mediterranean record of the epibyssal pteriid Isognomon australica (Reeve, 1858). Systematics Family: Pteriidae Gray, (1847-1820) Genus: Isognomon (Lightfoot, 1786) Isognomon australica (Reeve, 1858) Fig. 1
Multi-legged Joint Kinematic Analysis of an Insect Tethered over a Slippery Surface

5 INTRODUCTION . 6 INSECT LOCOMOTION . 6 LEG SEGMENTS AND JOINTS . 7 JOINT CONTROL RULES . 10 NEURAL CONTROL . 14 Head Ganglia . 14 Thoracic Ganglia . 16 CENTRAL PATTERN GENERATORS . 17 JOINT COORDINATION . 18 SENSORY STRUCTURES AND REFLEXES . 19 External Receptors . 19 Receptors Associated with Legs . 20 REFLEX MODEL OF LEG CONTROL . 24 INTER-LEG CONTROL . 25 COCKROACH TURNING . 27 PURPOSE OF PROJECT . 29 METHODS . 30 RESULTS . 39 DISCUSSION . 59 CONCLUSION . 68 APPENDIX . 69 References . 81
MAGNETIC FIELD IN THE VICINITY OF DISTRIBUTION TRANSFORMERS

A quasi-static analysis of an oil-type distribution transformer was described to determine the ambient magnetic field in the surrounding region. Windings and terminals were assumed to be primary sources of the magnetic field. Core and tank of the transformer were modeled by secondary sources (surface current density, surface charge density and eddy current density). In order to find these sources, the system of integral equations was transformed into linear system. Magnetic field was calculated by evaluating volume and surface integrals. The calculated and measured results of the magnetic induction were compared on a 630 kVA transformer. Evaluation of the magnetic induction was made for distribution transformers in the range 50-2500 kVA.
Breaking Up : Experimental insights into international economic ( dis ) integration ∗

Trade theory suggests that people should embrace economic integration because it promises large gains. But recent events such as “Brexit” suggest a desire for economic disintegration. Here we report results of a laboratory investigation of how size and distribution of potential gains from integration influences the actual economic outcomes, and individuals’ inclination to belong to an “integrated” economy. The experiment documents the existence of several behavioral challenges to the process of economic integration, which prevent individuals from fully realizing the gains promised by trade theory.
Modeling and Development of a Geographic Database : Application to the Elaboration of Oil-spill Environmental Sensitivity Maps in Coastal Areas of the Rio Grande do Norte State

The study area is located between Galinhos and São Bento do Norte beaches, northern coast of the Rio Grande do Norte State. This area is characterized by natural factors and the human interference huge in the surroundings due to the Guamaré Petroliferous Pole nearby, the greater terrestrial oil producing in Brazil. The first part of this work consisted to elaborate a Geographic Database to store all the data collected on this study. This dataset was stored as a virtual library to assist men decisions from the results presented as digital thematic maps, tables and reports. The second stage of this work consisted on elaborate the Oil-Spill Environmental Sensitivity Maps. These maps are cartographic products that supply full information to the decision making, contingency planning and assessment in case of an oil spilling incident in any area. They represent the sensitivity of the areas related to oil spilling, through basic data such as geology, geomorphology, oceanographic, social-economic and biology. Thus using the available data were possible to develop sensitivity maps of the study area on different dates (June/2000 and December/2000) and to perceive that there was a difference on the sensitivity index generated. The area on December presented more sensible indices to the oil than June presents because hydrodynamic data (wave and tide energy) allowed a faster natural cleaning on June. This presented a medium index (3 to 4) to the long shore and a high index (10) to the mangrove areas highly vulnerable to oil spill.
Predictive Maintenance Using Machine Learning Methods in Petrochemical Refineries

This research project evaluates the suitability of machine learning methods for early fault prediction and predictive maintenance in petrochemical refineries based on real- life use cases at Shell Pernis. Refineries are mature industrial installations, however, unplanned shutdowns still occur due to equipment failures. Refineries have petabytes of process control data available from the past years, however, all of that data is unla- belled. The goal of this research project was to evaluate, whether useful information can be extracted from the process control data. The resulting approach had to be compatible with Shell IT, scalable to larger sections of the refinery, reusable in other parts of the refinery and capable of detecting the components that cause the potential faults. During this research project, multiple solutions based on artificial neural net- works and statistical approaches were implemented to model the normal behaviour of the monitored systems. Abnormal predictions for the modelled systems were then used to predict failures in advance, where the prediction horizon reached more than a month for some use cases. 4-layer GRUs with tanh activation functions and an input sequence length of 4 samples provided the best results. GRUs were 7% faster to train than LSTMs while reducing the prediction error by 15%. Furthermore, the predic- tion error was less than 3% for the normal operating conditions while reaching more than 15% prior to failures. Therefore, machine learning models can predict failures in petrochemical refineries without any industry-specific knowledge, if the model is trained with clean data that does not contain abnormal time series.
Public Spending and Economic Activity : Quasi-Experimental Evidence from Brazilian Municipalities

According to Brazilian law, federal transfers to municipal governments vary discontinuously at numerous pre-determined population thresholds. Using changes in local population around these thresholds as an instrument for actual public spending in a ‘fuzzy’ regression discontinuity set-up, we identify the causal effect of fiscal policy on economic activity. Our baseline estimates point to an average local multiplier between 1.6 and 2 across a range of empirical specifications that control for fixed municipal characteristics, national business cycle, monetary policy, and federal fiscal policy. The average effect, however, masks significant heterogeneity. An exogenous increase in government spending of 1% of municipal GDP tends to generate an insignificant boost in local activity, with point estimates of 0.9% to 1.3%. In contrast, the multiplier associated with a public spending cut appears highly significant, with central values between 2.5 and 3. Contractions in government spending on transportation, housing and, to a lesser extent, health and education appear the most detrimental for the local economy. JEL codes: E62, H72, C26.
Effects of sorbitol on essential oil of Carum copticum L . under in vitro culture

Drought is the most limiting factor for the plant growth and crop productivity in the agriculture industry; however, its effect on the medicinal plants under in vitro culture has seen rather from different point of views. Due to use of Carum copticum as a voluble medical plant as well as dry climate in most parts of the world, the present study was conducted to evaluate the effect of drought stress on the physiology and essential oil production of seedlings and callus of C. copticum. In this study, seedlings of C. copticum were cultured in MS medium containing 0, 3 and 6% sorbitol and calli were cultured in MS medium containing 0.25 mg.L 2,4-D, 2 mg.L BAP and different levels of sorbitol (0, 3 and 6%). After 4 weeks, the highest amount of proline and carbohydrate was observed at 6% sorbitol. Protein content showed a significant difference in leaves, roots and callus under the drought stress. Evaluation of contents of essential oils using GC–MS showed the components of the essential oils at high stress condition increased. Thirty-five compounds were identified in both of the essences of C. copticum, which thymol, gamatherpinen and parasimen in each treatment were changed.
Aging and the Welfare State : The Politico-Economic Conflict between Young and Old , and between Rich and Poor

An income tax is generally levied on both labor and capital. The working young bear mostly the tax on labor income, whereas the retired old, who already accumulated savings, bear the brunt of the capital tax. Therefore, there arise two types of conicts in the determination of the income tax: the standard intra-generational conict between the poor and rich, and an intergenerational conict between the young and the old. The paper studies how aging a¤ects the resolution of these conicts, and the politicoeconomic forces that are of play: the changes in the voting pivots and the scal leakages from taxpayers to transfer recipients. JEL classi cation: H1, H2
EXPLORATION METHOD IMPROVEMENTS OF AUTONOMOUS ROBOT FOR EXPLORATION METHOD IMPROVEMENTS OF AUTONOMOUS ROBOT FOR A 2-D ENVIRONMENT NAVIGATION A 2-D ENVIRONMENT NAVIGATION

This paper presents a method for integrating different algorithms for building an autonomous robot. The developed robot has the ability to construct the 2-D map of an unknown environment, localize itself in the map, explore undiscovered area, and path finding. In order to efficiently explore a map, we propose an exploration method. Additionally, improvements of conventional A* algorithm are proposed. Experimental results show that the developed robot is capable of navigating an unknown indoor environment with random obstacles
32 Assessing the control of fermentative free-energy metabolism in yeast : a modelling exploration

Free-energy metabolism (i.e., the synthesis and utilisation of ATP) is pivotal to all living systems. Its efficient regulation is important for living cells to survive and to adapt to changing circumstances such as reduced availability of nutrients. This means that ATP should be synthesised when needed by the cell, but that ATP synthesis should be inhibited under conditions of free-energy excess (high concentrations of ATP). In the parlance of control analysis, if the pathway fulfils its functional criterion to supply free energy when needed, the demand for ATP should control the glycolytic flux [1]. An experimental analysis of the control of fermentative free-energy metabolism is sorely needed because to this day textbook dogma pertains that the glycolytic flux is controlled by glycolytic enzymes themselves, with the irreversible steps of hexokinase, phosphofructokinase and pyruvate kinase being identified as “pacemakers” and regulatory enzymes owing to their allosteric effects (cf. [2]). However, single or pairwise overexpression of most of the glycolytic enzymes did not affect the glycolytic flux to any significant extent [3]. To explain this result, Hofmeyr argued that “steady-state glycolytic flux is controlled by reactions outside of what has traditionally been regarded as glycolysis; more specifically, it is controlled by those cellular processes that consume the key product of glycolysis, ATP” [1]. Baker’s yeast (Saccharomyces cerevisiae) is a good model organism for performing a control analysis of fermentative free-energy metabolism, for two reasons: (i) Yeast is able to grow fermentatively in the absence of oxygen, converting
Ju n 20 19 BERE : A N ACCURATE DISTANTLY SUPERVISED BIOMEDICAL ENTITY RELATION EXTRACTION NETWORK

Automated entity relation extraction (RE) from literature provides an important source for constructing biomedical database, which is more efficient and extensible than manual curation. However, existing RE models usually ignore the information contained in sentence structures and target entities. In this paper, we propose BERE, a deep learning based model which uses Gumbel Tree-GRU to learn sentence structures and joint embedding to incorporate entity information. It also employs word-level attention for improved relation extraction and sentence-level attention to suit the distantly supervised dataset. Because the existing dataset are relatively small, we further construct a much larger drug-target interaction extraction (DTIE) dataset by distant supervision. Experiments conducted on both DDIExtraction 2013 task and DTIE dataset show our model’s effectiveness over state-of-the-art baselines in terms of F1 measures and PR curves.
A Framework for Discovering Variable-length Motifs in Medical Data Streams

In this paper, we explore two key problems in time series motif discovery: releasing the constraints of trivial matching between subsequence with different lengths and improving the time and space efficiency. The purpose of avoiding trivial matching is to avoid too much repetition between subsequence in calculating their similarities. We describe a limited-length enhanced suffix array based framework (LiSAM) to resolve the two problems. We first convert the continuous time series to the discrete time series using the Symbolic Aggregate approXimation procedure, and then introduce two covering relations of the discrete subsequence: α-covering between the instances of LCP (Longest Common Prefix) intervals and β-covering between LCP intervals to support the motif discovery: if an LCP interval is βuncovered, its instances form a motif. The βUncover algorithm of LiSAM identifies the β-uncovered l-intervals, in which we introduce two LCP tabs: presuf and nextsuf to support the identification of the αuncovered instances of an l-interval. Experimental results on Electrocardiogram signals indicate the accuracy of LiSAM on finding motifs with different lengths.
Piezoresistive NanoComposites : Characterization and Applications

Piezoresistive Nano-Composites: Characterization and Applications Tommy Hyatt Department of Mechanical Engineering Master of Science Innovative multifunctional materials are essential to many new sensor applications. Piezoresistive nano-composites make up a promising class of such materials that have the potential to provide a measurable response to strain over a much wider range than typical strain gages. Commercial strain gages are currently dominated by metallic sensors with a useable range of a few percent strain at most [1]. There are, however, many applications that would benefit from a reliable wide-range sensor. These might include the study of explosive behavior, instrumentation of flexible components, motion detection for compliant mechanisms and hinges, human-technology interfaces, and a wide variety of bio-mechanical applications where structural materials may often be approximated as elastomeric. In order to quantify large strains, researchers often use optical methods which are tedious and difficult. This thesis proposes a new material and technique for quantifying large strain (up to 40%) by use of piezoresistive nano-composite strain gages. The nano-composite strain gage material is manufactured by suspending nickel nano-strands within a biocompatible silicone matrix. Study and design iteration on the strain gage material requires an improved understanding of the electrical behavior and conduction path within the material when strained. A percolation model has been suggested for numerical approximations, but has only provided marginal results for lack of data. Critical missing information in the percolation model is the nano-strand cluster size, and how that size changes in response to strain. These data are gathered using a dynamic technique in the scanning electron microscope called voltage contrast. Cluster sizes were found to vary in size by approximately 6% upon being strained to 10%. A feasibility study is also conducted on the nano-composite to show its usability as a strain gage. High Displacement Strain Gages (HDSGs) were manufactured from the nanocomposite. HDSGs measured the strain of bovine ligament under prescribed loading conditions. Results demonstrate that HDSGs are an accurate means for measuring ligament strains across a broad spectrum of applied deformations.
Enactment of Face Recognition Algorithm for Attendance System

The reason for this program is to guarantee that the administrations gave is gotten to just by authentic clients, not by others. By utilizing biometrics, you can distinguish or set up the natural character of your own personality and condense some of its qualities, shortcomings, qualities, impediments, and related security issues. Biometrics-based frameworks likewise have a few confinements that may antagonistically influence the security of the framework. Albeit a portion of the confinements of biometrics can be overwhelmed by the advancement of biometrics and cautious framework outline.
Mini is beautiful : Playing serious mini-games to facilitate collective learning on complex urban processes

Spatial planning projects can be conceived as processes of collective learning. Planners have been looking at games and playful approaches to support these processes. Considering that planning projects are long and complex, we propose to not reason for single, full-fledged and all-encompassing games, but instead work with strings of, so-called, serious mini-games that each addresses a specific learning goal, guided by a collective learning model. This paper conceptualizes a toolbox to support the development and contextualization of such strings of serious mini-games.
Strategies for Integrating Digital Technology in Classrooms to support English Language Learners’ Learning and Engagements

Toronto is one of the most multicultural cities in Canada, and as a result, the population of English Language Learners (ELLs) only continues to grow in its classrooms. In a recent survey done by People for Education on Ontario’s Publicly Funded Schools, 73% of elementary schools reported they have ELLs who require language support (People for Education, 2015). Technology is the mechanism through which current generations of students are growing up and learning, and can be used as a tool for levelling the playing field for ELLs, allowing them to showcase their knowledge through a familiar medium. This research study focused on learning the different strategies teachers use to integrate digital technology to support ELLs’ learning and engagement in the classrooms. Data was collected through semi-structured interviews with two elementary teachers currently working in a publicly funded school board in Ontario. Participants used technology to differentiate instruction for ELLs in terms of the delivery of material, more time to process information and complete work at their own pace, and offering a different way to demonstrate understanding and learning. Teachers observed increased student engagement as digital technology provided students with opportunities to express themselves in different ways. Recommendations include creating a community network, e-platform, where teachers can mentor each other, share instructional practices, technological implementations, and questions and concerns.