Miracle-dz/UniFAR-FTUs huggingface dataset:
An Algorithm of Micromouse Maze Solving

This paper proposes a maze exploring algorithm named “Partition-central Algorithm”, which is used to find the shortest path in a micromouse competition maze. A standard 16*16 units maze is divided into 12 partitions in this algorithm. Depending on the absolute direction of the micromouse and the locations of each partition, exploring rules alter when the micromouse walks to optimize the maze exploring process. A simulation program is developed to verify the algorithm. The test result shows that Partition-central algorithm has higher average efficiency when compared with other algorithms.
Effects of unilateral, isometric resistance training on strength development and the Hoffmann-reflex response in the trained and untrained limb

The purpose of this study was to determine the effects of a 5-week unilateral, isometric strength-training program on presynaptic inhibition (PSI) and alterations in the H-reflex in both the trained and untrained limbs. Thirteen subjects, aged 23-42 years old were assigned to either a control group (n=6) or an exercise group (n=7). Both groups were tested at the beginning and end of a 5-week interval on both limbs for maximal voluntary isometric contractions (MVIC) of the plantar flexors as well as three different conditioning protocols of the Soleus Hoffmann (H) reflex. Experimental group participants significantly increased MVIC in both legs following training (p<0.05) while control group participants showed no increase for either leg. Experimental subjects displayed increased normalized H-reflex values at M=5% (HA) (p<0.05) in the trained leg only. Adaptations in HA for the trained limb in the presence of a substantial strength increase suggests that spinal mechanisms may partly explain the increase in strength, possibly due to increased a-motoneuronal excitability. However, the lack of HA increase in contralateral limb in the presence of a substantial strength increase, points to different neural mechanisms responsible for the cross education effect.
Convolutional Neural Network Based Transient Earth Voltage Detection

Partial Discharge Detection is an important method to find hidden dangers and safety problems of power equipment. The traditional Transient Earth Voltages (TEV) methods of the switchgear and GIS usually consist of four steps, i.e. data gathering, filtering, feature extraction and pattern recognition. These methods generate features using statistical analysis or waveform analysis of the signals, and then conduct the recognition and classification operations. In recent years, the increasingly developing deep learning methods have a huge effect on the pattern recognition, due to its outstanding abilities of recognition and feature extraction, which greatly offset the poor recognition performance of the traditional TEV methods. A novel Convolutional Neural Network (CNN) based TEV detection method is proposed in the paper, which needs no signal feature prepared by human and overcomes the detection problems resulted from an inappropriately selected feature. A CNN model is designed to train and classify the spectral image of the TEV. Although no sophisticated denoising method is adopted in the preprocessing, the proposed method approaches an extraordinary detection performance, which demonstrates the effectiveness of our CNN based TEV detection method.
Detection of Autism using Magnetic Resonance Imaging data and Graph Convolutional Neural Networks

Autism or Autism Spectrum Disorder (ASD) is a development disability which generally begins during childhood and may last throughout the lifetime of an individual. It is generally associated with difficulty in communication and social interaction along with repetitive behavior. One out of every 59 children in the United States is diagnosed with ASD [11] and almost 1% of the world population has ASD [12]. ASD can be difficult to diagnose as there is no definite medical test to diagnose this disorder. The aim of this thesis is to extract features from resting state functional Magnetic Resonance Imaging (rsfMRI) data as well as some personal information provided about each subject to train variations of a Graph Convolutional Neural Network to detect if a subject is Autistic or Neurotypical. The time series information as well as the connectivity information of specific parts of the brain are the features used for analysis. The thesis converts fMRI data into a graphical representation where the vertex represents a part of the brain and the edge represents the connectivity between two parts of the brain. New adjacency matrix filters were added to the Graph CNN model and the model was altered to add a time dimension.
EU-ACP Economic Partnership Agreements - Empirical Evidence for Sub-Saharan Africa

Since early 2008 interim trade agreements between the EU and six regions of ACP countries (respectively sub-groups within the region) are in force. These agreements could be stepping stones towards full Economic Partnership Agreements between the EU and all ACP countries. We estimate the welfare effects of the interim agreements for nine African countries: Botswana, Cameroon, Cote d'Ivoire, Ghana, Kenya, Mozambique, Namibia, Tanzania, and Uganda. Our analysis is based on highly disaggregated data for trade and tariffs (HS six digit level) and follows a simple analytical model by Milner et al. (2006) to quantify the welfare effects of trade liberalization. We extend the literature in two principal ways: First, we estimate elasticities of import demand for the nine African countries importing from the EU and Sub-Saharan Africa respectively. Second, we apply the actual tariff reduction rates recently negotiated between the EU and the African countries to estimate the agreement's welfare effects of trade liberalization for the African countries. Results indicate that Botswana, Cameroon, Mozambique, and Namibia will significantly profit from the interim agreements, while the trade effects for Cote d'Ivoire, Ghana, Kenya, Tanzania, and Uganda are close to zero. However, Tanzania and Uganda also have the potential to experience positive welfare effects, but predicted results of the liberalization based on the interim agreement's reduction rates fall short of the potential of a full liberalization.
Modulation of microrna expression by volatile organic compounds in mouse lung

Volatile organic compounds (VOCs) are one of main pollutants indoors. Exposure to VOCs is associated with cancer, asthma disease, and multiple chemical allergies. Despite the adverse health effects of VOCs, the molecular mechanisms underlying VOCs‐induced disease remain largely unknown. MicroRNAs (miRNAs), as key post‐transcriptional regulators of gene expression, may influence cellular disease state. To investigate whether lung miRNA expression profiles in mice are modified by VOCs mixture exposure, 44 male Kunming mice were exposed in 4 similar static chambers, 0 (control) and 3 different doses of VOCs mixture (groups 1–3). The concentrations of VOCs mixture were as follows: formaldehyde, benzene, toluene, and xylene 3.0 + 3.3 + 6.0 + 6.0 mg/m3, 5.0 + 5.5 + 10.0 + 10.0 mg/m3, 10.0 + 11.0 + 20.0 + 20.0 mg/m3, respectively, which corresponded to 30, 50, and 100 times of indoor air quality standard in China, after exposure to 2 weeks (2 h/day, 5 days/week). Small RNAs in lung and protein isolated from bronchoalveolar lavage fluid (BALF) were collected and analyzed for miRNA expression using microarray analysis and for interleukin‐8 (IL‐8) protein levels by enzyme‐linked immunosorbent assay, respectively. VOCs exposure altered the miRNA expression profiles in lung in mice. Specifically, 69 miRNAs were significantly differentially expressed in VOCs‐exposed samples versus controls. Functional annotation analysis of the predicted miRNA transcript targets revealed that VOCs exposure potentially alters signaling pathways associated with cancer, chemokine signaling, Wnt signaling, neuroactive ligand‐receptor interaction, and cell adhesion molecules. IL‐8 isolated from BALF and nitric oxide synthase of lung increased significantly, whereas GSH of lung decreased significantly in mice exposed to VOCs. These results indicate that inhalation of VOCs alters miRNA patterns that regulate gene expression, potentially leading to the initiation of cancer and inflammatory diseases. © 2012 Wiley Periodicals, Inc. Environ Toxicol 29: 679–689, 2014.
Likelihood Gradient Evaluation Using Square-Root Covariance Filters

Using the array form of numerically stable square-root implementation methods for Kalman filtering formulas, we construct a new square-root algorithm for the log-likelihood gradient (score) evaluation. This avoids the use of the conventional Kalman filter with its inherent numerical instabilities and improves the robustness of computations against roundoff errors. The new algorithm is developed in terms of covariance quantities and based on the ldquocondensed formrdquo of the array square-root filter.
A global maximum power point tracking method based on interval short-circuit current

A photovoltaic (PV) array show multi local maximum power points mode under partially shaded conditions, where the operating point of the PV system tends to converge to a local maximum power point (LMPP) which is not the real maximum power point. A novel MPPT method is proposed in this paper to achieve global maximum power point tracking (GMPPT) under partially shaded conditions. The behavior of I-V characteristics is discussed and interval short-circuit current is applied to locate global maximum power point interval. A state-space based PV array model and simulation results are presented to validate the proposed method.
Ciphertext Policy Attribute Based Encryption with Efficient Revocation

Revocation is a vital open problem in almost every cryptosystem dealing with malicious behaviors. In ciphertext policy attribute based encryption, unlike traditional public key cryptosystem, different users may hold the same functional secret keys related with the same attribute set leading to additional difficulties in designing revocation mechanism. In this paper, we propose the ciphertext policy attribute based encryption scheme with efficient revocation which can be proved secure in the standard model. Our construction uses linear secret sharing and binary tree techniques as the underlying tools. In addition to assigned attribute set, each user is also assigned with a unique identifier. Therefore, a user can be easily revoked by using his/her unique identifier; on the other hand, the encryption and decryption algorithms of ABE (Attribute Based Encryption) can be done without any involvement of these unique identifiers. Then, we prove the chosen plaintext security of our construction based on Decisional Bilinear Diffie-Hellman (DBDH) assumption in the standard model. Finally, we provide some discussion on the efficiency of our scheme and the extensions including delegation capability and chosen ciphertext security.
A Named Entity Labeler for German: Exploiting Wikipedia and Distributional Clusters

Named Entity Recognition is a relatively well-understood NLP task, with many publicly available training resources and software for processing English data. Other languages tend to be underserved in this area. For German, CoNLL-2003 Shared Task provided training data, but there are no publicly available, ready-to-use tools. We fill this gap and develop a German NER system with state-of-the-art performance. In addition to CoNLL 2003 labeled training data, we use two additional resources: (i) 32 million words of unlabeled news article text and (ii) infobox labels from German Wikipedia articles. From the unlabeled text we derive distributional word clusters. Then we use cluster membership features and Wikipedia infobox label features to train a supervised model on the labeled training data. This approach allows us to deal better with word-types unseen in the training data and achieve good performance on German with little engineering effort.
Multifunctional catheters combining intracardiac ultrasound imaging and electrophysiology sensing

A family of 3 multifunctional intracardiac imaging and electrophysiology (EP) mapping catheters has been in development to help guide diagnostic and therapeutic intracardiac EP procedures. The catheter tip on the first device includes a 7.5 MHz, 64-element, side-looking phased array for high resolution sector scanning. The second device is a forward-looking catheter with a 24-element 14 MHz phased array. Both of these catheters operate on a commercial imaging system with standard software. Multiple EP mapping sensors were mounted as ring electrodes near the arrays for electrocardiographic synchronization of ultrasound images and used for unique integration with EP mapping technologies. To help establish the catheters' ability for integration with EP interventional procedures, tests were performed in vivo in a porcine animal model to demonstrate both useful intracardiac echocardiographic (ICE) visualization and simultaneous 3-D positional information using integrated electroanatomical mapping techniques. The catheters also performed well in high frame rate imaging, color flow imaging, and strain rate imaging of atrial and ventricular structures. The companion paper of this work discusses the catheter design of the side-looking catheter with special attention to acoustic lens design. The third device in development is a 10 MHz forward-looking ring array that is to be mounted at the distal tip of a 9F catheter to permit use of the available catheter lumen for adjunctive therapy tools.
Bioinformatics Applications Note Genetics and Population Analysis Msms: a Coalescent Simulation Program including Recombination, Demographic Structure and Selection at a Single Locus

Motivation: We have implemented a coalescent simulation program for a structured population with selection at a single diploid locus. The program includes the functionality of the simulator ms to model population structure and demography, but adds a model for deme-and time-dependent selection using forward simulations. The program can be used, e.g. to study hard and soft selective sweeps in structured populations or the genetic footprint of local adaptation. The implementation is designed to be easily extendable and widely deployable. The interface and output format are compatible with ms. Performance is comparable even with selection included. Availability: The program is freely available from http://www.mabs . at/ewing/msms/ along with manuals and examples. The source is freely available under a GPL type license.
A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning

We propose two transductive bounds on the risk of majority votes that are estimated over partially labeled training sets. The first one involves the margin distribution of the classifier and a risk bound on its associate Gibbs classifier. The bound is tight when so is the Gibbs's bound and when the errors of the majority vote classifier is concentrated on a zone of low margin. In semi-supervised learning, considering the margin as an indicator of confidence constitutes the working hypothesis of algorithms which search the decision boundary on low density regions. Following this assumption, we propose to bound the error probability of the voted classifier on the examples for whose margins are above a fixed threshold. As an application, we propose a self-learning algorithm which iteratively assigns pseudo-labels to the set of unlabeled training examples that have their margin above a threshold obtained from this bound. Empirical results on different datasets show the effectiveness of our approach compared to the same algorithm and the TSVM in which the threshold is fixed manually.
Gene silencing and a novel monoallelic expression pattern in distinct CD177 neutrophil subsets

CD177 presents antigens in allo- and autoimmune diseases on the neutrophil surface. Individuals can be either CD177-deficient or harbor distinct CD177neg and CD177pos neutrophil subsets. We studied mechanisms controlling subset-restricted CD177 expression in bimodal individuals. CD177pos, but not CD177neg neutrophils, produced CD177 protein and mRNA. Haplotype analysis indicated a unique monoallelic CD177 expression pattern, where the offspring stably transcribed either the maternal or paternal allele. Hematopoietic stem cells expressed both CD177 alleles and silenced one copy during neutrophil differentiation. ChIP and reporter assays in HeLa cells with monoallelic CD177 expression showed that methylation reduced reporter activity, whereas demethylation caused biallelic CD177 expression. HeLa cell transfection with c-Jun and c-Fos increased CD177 mRNA. Importantly, CD177pos human neutrophils, but not CD177neg neutrophils, showed a euchromatic CD177 promoter, unmethylated CpGs, and c-Jun and c-Fos binding. We describe epigenetic mechanisms explaining the two distinct CD177 neutrophil subsets and a novel monoallelic CD177 expression pattern that does not follow classical random monoallelic expression or imprinting.
Subthreshold membrane currents confer distinct tuning properties that enable neurons to encode the integral or derivative of their input

Neurons rely on action potentials, or spikes, to encode information. But spikes can encode different stimulus features in different neurons. We show here through simulations and experiments how neurons encode the integral or derivative of their input based on the distinct tuning properties conferred upon them by subthreshold currents. Slow-activating subthreshold inward (depolarizing) current mediates positive feedback control of subthreshold voltage, sustaining depolarization and allowing the neuron to spike on the basis of its integrated stimulus waveform. Slow-activating subthreshold outward (hyperpolarizing) current mediates negative feedback control of subthreshold voltage, truncating depolarization and forcing the neuron to spike on the basis of its differentiated stimulus waveform. Depending on its direction, slow-activating subthreshold current cooperates or competes with fast-activating inward current during spike initiation. This explanation predicts that sensitivity to the rate of change of stimulus intensity differs qualitatively between integrators and differentiators. This was confirmed experimentally in spinal sensory neurons that naturally behave as specialized integrators or differentiators. Predicted sensitivity to different stimulus features was confirmed by covariance analysis. Integration and differentiation, which are themselves inverse operations, are thus shown to be implemented by the slow feedback mediated by oppositely directed subthreshold currents expressed in different neurons.
Academic Orientation Supported by Hybrid Intelligent Decision Support System

It is common that in all academic systems the students must make decisions about the future by choosing among different alternatives that include professional profiles or modalities, elective subjects or optional, etc. These decisions can have a very important influence in the academic journey of the students because sometimes a wrong decision can lead to academic failure or its correction implies a time cost for the students. It is remarkable that in many academic systems these important decisions have to be made in early stages in which the students do not have enough maturity or knowledge to be conscious about the consequences in their future if a wrong decision is made. Ideally these multiple choices, offered to the students, want to facilitate the acquirement of some professional and valuable competences to obtain a job. Taking into account that the suitability of people in jobs or studies is not only restricted to their taste or preferences, but also other factors involved in the process of acquiring maturity as an adult who develops any function. These factors such as capacities, skills, attitudes concerning the task, social attitudes, taste, preferences, etc. (Brinol 2007, Robertson 1993, Salgado 1996, Shevin 2004), must be taken into account in such processes. Initially these decision making processes were made by the students themselves or with their parents support according to different criteria such as, preferences, future job market, even randomly, etc. Therefore, in order to improve this situation different countries introduced one figure, so-called advisor, whose role is to guide the students in their decision making situations regarding their academic future. The academic orientation process carried out by these advisors imply the review of different information regarding the students in order to report which academic alternatives suits better their skills, competences and needs. In most of academic institutions the advisor deals yearly with several hundreds of students with different skills, personalities, etc. To make an idea, in Spain, and depending on the high school, advisors can manage from 200 to 800 students. This number of students implies a big search space to find the relevant information that can facilitate the orientation for each one in a right way, making very hard to perform successfully the academic orientation process. Hence it seems suitable the development of automated tools that support the accomplishment of the different processes of academic orientation to improve the success of advisors’ tasks. An overview of different problems in the real world that deal with search spaces drove us to pay attention to the situation raised some years ago with the advent of Internet and the
Pen and touch gestural environment for document editing on interactive tabletops

Combined pen and touch input is an interaction paradigm attracting increasing interest both in the research community and recently in industry. In this paper, we illustrate how pen and touch interaction techniques can be leveraged for editing and authoring of presentational documents on digital tabletops. Our system exploits the rich interactional vocabulary afforded by the simultaneous availability of the two modalities to provide gesture-driven document editing functionality as an expert alternative to widgets. For our bimanual gestures, we make use of non-dominant hand postures to set pen modes in which the dominant hand articulates a variety of transactions. We draw an analogy between such modifier postures and modifier keys on a keyboard to construct command shortcuts. Based on this model, we implement a number of common document editing operations, including several page and element manipulations, shape and text input with styling, clipart retrieval and insertion as well as undo/redo. The results of a lab study provide in-sights as to the strengths and limitations of our approach.
Temporal consistent stereo matching approach for road applications

In this paper, we present a fast approach for matching stereo images acquired by a stereo sensor embedded in a moving vehicle. The proposed approach exploits the disparity map already computed at the preceding frame to improve the matching results at the current one. An edge association method is used to track the edge curves over time. Local disparity constraints are computed for all the edge points that belong to the tracked edge curves. For the rest of edge points, we use a global disparity constraint, which is computed for each image line based on the preceding v-disparity. We integrate these constraints in the dynamic programming algorithm, which increases the matching results and speeds up the matching process.