Miracle-dz/UniFAR-FTUs huggingface dataset:
Lessons Learned from the Effort to Solve Cooperative PathFinding Optimally

This paper addresses makespan optimal solving of cooperative pathfinding problem (CPF) by translating it to propositional satisfiability (SAT). The task in CPF is to relocate a set of agents to given goal locations so that they do not collide with each other. Recent findings indicate that a simple direct encoding outperforms the more elaborate encodings based on binary encodings of multivalue state variables. The direct encoding is further improved by a hierarchical build-up that uses auxiliary variables to reduce its size in this work. The conducted experimental evaluation shown that the simple design of the encoding together with new improvements which reduced its size significantly are key enablers for faster solving of the encoded CPFs than with existing encodings. It has been also shown that the SAT based methods dominates over A* based methods in environments with high occupancy by agents.
AN LINEAR TECHNIQUE FOR POSE ESTIMATION FROM DIFFERENT GEOMETRIC FEATURES

Existing linear solutions for the pose estimation (or exterior orientation) problem suffer from a lack of robustness and accuracy partially due to the fact that the majority of the methods utilize only one type of geometric entity and t.heir frameworks do not allow simultaneous use of different types of features. Furthermore, the orthonormality constraints are weakly enforced or not enforced at all. We have developed a new analytic linear least-squares framework for determining pose from multiple types of geometric features. The technique utilizes correspondences between points, between lines and between ellipse-circle pairs. The redundancy provided by different geometric features improves the robustness and accuracy of the least-squares solution. A novel way of approximately imposing orthonormality constraints on the sought rotation matrix within the linear framework is presented. Results from experimental evaluation of the new technique using both synthetic data and real images reveal its improved robustness and accuracy over existing direct methods.
Precipitation Trends over the Indus Basin

A large population relies on water input to the Indus basin, yet basinwide precipitation amounts and trends are not well quantified. Gridded precipitation data sets covering different time periods and based on either station observations, satellite remote sensing, or reanalysis were compared with available station observations and analyzed for basinwide precipitation trends. Compared to observations, some data sets tended to greatly underestimate precipitation, while others overestimate it. Additionally, the discrepancies between data set and station precipitation showed significant time trends in such cases, suggesting that the precipitation trends of those data sets were not consistent with station data. Among the data sets considered, the station-based Global Precipitation Climatology Centre (GPCC) gridded data set showed good agreement with observations in terms of mean amount, trend, and spatial and temporal pattern. GPCC had average precipitation of about 500 mm per year over the basin and an increase in mean precipitation of about 15% between 1891 and 2016. For the more recent past, since 1958 or 1979, no significant precipitation trend was seen. Among the remote sensing based data sets, the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) compared best to station observations and, though available for a shorter time period than station-based data sets such as GPCC, may be especially valuable for parts of the basin without station data. The reanalyses tended to have substantial biases in precipitation mean amount or trend relative to the station data. This assessment of precipitation data set quality and precipitation trends over the Indus basin may be helpful for water planning and management.
Deep learning for fake news classification

This work presents the application of several Deep Learning techniques for Natural Language Processing to the classification of tweets into containing fake news or not. To validate our approach, we use an open-access dataset containing annotated tweets related to the 2016 US elections. From our experiments, we can confirm that Deep Learning techniques are indeed able to identify tweets containing fake news, and that LSTMs with pre-computed embeddings is the best performing among the tested techniques (validation AUC = 0.70), particularly in avoiding misclassification of the minority class.
Age related changes in afferent pathways and urothelial function in the male mouse

The prevalence of lower urinary tract storage disorders such as overactive bladder syndrome and urinary incontinence significantly increase with age. Previous studies have demonstrated age-related changes in detrusor function and urothelial transmitter release but few studies have investigated how the urothelium and sensory pathways are affected. The aim of this study was to investigate the effect of ageing on urothelial-afferent signalling in the mouse bladder. Three-month-old control and 24-month-old aged male mice were used. In vivo natural voiding behaviour, sensory nerve activity, urothelial cell function, muscle contractility, transmitter release and gene and protein expression were measured to identify how all three components of the bladder (neural, contractile and urothelial) are affected by ageing. In aged mice, increased voiding frequency and enhanced low threshold afferent nerve activity was observed, suggesting that ageing induces overactivity and hypersensitivity of the bladder. These changes were concurrent with altered ATP and acetylcholine bioavailability, measured as transmitter overflow into the lumen, increased purinergic receptor sensitivity and raised P2X3 receptor expression in the urothelium. Taken together, these data suggest that ageing results in aberrant urothelial function, increased afferent mechanosensitivity, increased smooth muscle contractility, and changes in gene and protein expression (including of P2X3). These data are consistent with the hypothesis that ageing evokes changes in purinergic signalling from the bladder, and further studies are now required to fully validate this idea. (Received 25 July 2013; accepted after revision 25 November 2013; first published online 2 December 2013) Corresponding author Professor D. Grundy: Department of Biomedical Science, University of Sheffield, Western Bank, Sheffield S10 2TN, UK. Email: D.Grundy@sheffield.ac. uk Abbreviations ACh, acetylcholine; DRG, dorsal root ganglia; OAB, overactive bladder syndrome; UI, urinary
Associations of CXCL 16 , miR ‐ 146 a and miR ‐ 146 b in atherosclerotic apolipoprotein E ‐ knockout mice

Atherosclerosis is the primary cause of cardiovascular and cerebrovascular diseases. Recent studies have revealed that C-X-C motif chemokine ligand 16 (CXCL16), microRNA (miR)-146a and miR-146b may have important roles in atherosclerotic diseases. However, the associations of CXCL16, miR-146a and miR-146b in atherosclerotic diseases in vivo remain unclear. Previous studies have demonstrated that miR-146a and miR-146b may negatively regulate the toll like receptor (TLR4)/nuclear factor (NF)-κB signaling pathway to repress the inflammatory response. The present study investigated the associations of CXCL16, miR-146a and miR-146b in atherosclerotic apolipoprotein E (ApoE)-/mice in vivo. The expression levels of CXCL16, TLR4/NF-κB signaling pathway, miR-146a and miR-146b in the control and atherosclerotic ApoE-/mice were investigated via reverse transcription-quantitative polymerase chain reaction and western blot analysis. The present study demonstrated that the expression of CXCL16 was significantly upregulated in atherosclerotic ApoE-/mice compared with control ApoE-/mice. The expression levels of TRL4, interleukin-1 receptor-associated kinase 1, tumor necrosis factor receptor associated factor 6, NF-κB, tumor necrosis factor-α and interleukin-1β were also significantly upregulated in atherosclerotic ApoE‐/‐ mice compared with control mice. However, the present study revealed that the expression levels of miR-146a and miR-146b were significantly downregulated in atherosclerotic ApoE‐/‐ mice compared with control ApoE-/mice. Overall, the results of the present study suggested that CXCL16 may regulate the TRL4/NF-κB/CXCL16 signaling pathway, and that miR-146a and miR-146b may negatively regulate CXCL16 via this pathway in atherosclerosis in vivo.
C 14 ORF 179 encoding IFT 43 is mutated in Sensenbrenner syndrome

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. C14ORF179 encoding IFT43 is mutated in Sensenbrenner syndrome Heleen H Arts, Ernie Bongers, Dorus Mans, Sylvia van Beersum, Machteld Oud, Emine Bolat, Liesbeth Spruijt, Elisabeth Cornelissen, Janneke Schuurs-Hoeijmakers, Nicole de Leeuw, et al.
Hardware Development and Implementation of an Object Tracking Algorithm for UAV Applications

The task of reliably detecting and tracking the moving objects in surveillance video forms a basis for higher level intelligence applications. This project aim is to develop the Hardware and to implement an object tracking algorithm. The tracking technique uses CAMSHIFT algorithm to detect moving objects and generate reliable tracks from real-time surveillance video. In mean shift algorithm there are many limitations and one of the most important is that the window remains the same size when object is farther away or very close to camera, so it is necessary to adapt the window size with target size and rotation. The solution for this problem is Continuously Adaptive Mean shift algorithm. It applies mean shift first, once mean shift converges it updates the size of the window. It also calculates the orientation of best fitting ellipse to it. Again it applies the mean shift with new scaled search window and previous window location. Window adaptation keeps continuing throughout of Tracking. This Tracking technique is implemented in arduino hardware with Pan-Tilt mechanism. Raspberry Pi is also used to implement CAMSHIFT algorithm here. Raspberry Pi is widely used for video processing and it is fit for UAV related surveillance applications as it has less weight with more functionality for video processing. Pan-Tilt mechanism is made by using two servo motors. Here, Pan-Tilt mechanism is used for real-time tracking of the target. For UAV application, overall communication for real-time tracking is also taken care by Raspberry Pi.
A survey on image description algorithms

This survey focuses on the field of computer vision. Several keypoint-detectors and descriptors are presented and a study is made to make an empirical evaluation of these. A simple key-point detector is also implemented on the OpenCV library, focused on the enabling a customized analysis to images by using several filters, thresholds and colour-analysis processes.
Automatic Microblog Summarization Based on Unsupervised Key-Bigram Extraction

Microblog summarization can save large amount of time for users in browsing. In this paper, we propose an automatic microblog summarization method based on unsupervised key-bigram extraction. Firstly, we extract a key-bigram set to discover the key aspects of posts by three unsupervised key-bigram extractor based on Hybrid TF-IDF, TextRank and Latent Dirichlet Allocation (LDA). Secondly, we rank sentences by overlap similarity and mutual information strategies based on the key-bigram set. Top ranked salient sentences with redundancy removal are selected as summaries. Compared with some other text content based summarizers, the proposed method was shown to perform superiorly in experiments on SinaWeibo and Twitter datasets.
Transpiration from canopy temperature : Implications for the assessment of crop yield in almond orchards

This paper evaluates the usefulness of the Crop Water Stress Index (CWSI) for monitoring transpiration and water status in almond trees, and proposes a methodology for assessing crop yield derived from the relation between canopy temperature and transpiration. For this purpose, a Non-Water Stress Baseline (NWSB) was developed from canopy temperature measurements taken with Infrared Thermometers (IRT) installed permanently over well-watered trees for three years. Tree transpiration was measured continuously with sap flow probes installed in the same trees than the IRT sensors. The calculated CWSI was closely related to water potential and stomatal conductance measured during kernel filling, as well as with transpiration and the ratio kT/ GC (the transpiration coefficient over the ground cover). Taking into consideration this relation and the water production function recently published, the seasonal CWSI was compared to final yield and the regression yielded good results (R= 0.80). An empirical relationship between the CWSI acquired remotely from two flights performed during the kernel filling stage and crop yield was determined for this orchard. The estimated yield from the proposed methodology was compared to ground-truth measurements of crop yield measured in 80 trees during 2014 and 2015. The result obtained a RMSE that yielded 1.54 kg/tree. This study thus demonstrates that CWSI is closely related to the transpiration and the ratio kT/GC. This relation settles the basis for the development of methodologies for estimating water-limited crop yield from thermal derived information.
Rounding 3 D meshes October 16 , 2018 Contact

Context. In most software, 3D polygonal meshes have vertices whose coordinates are represented with fixed-precision floating-point numbers, say doubles. Unfortunately, actions, such as rotations and intersections, create vertices whose coordinates cannot be exactly represented with doubles. A natural problem is thus to round the coordinates to doubles, without creating self-intersections between the faces and without changing the geometry too much; the faces can however be subdivided. This problem is of interest in academic and industrial contexts because many 3D digital models contain self intersections (45% of the 10 thousands triangle meshes in the famous Thingiverse data base) and many applications require models without self intersections.
A FULL MOTION MANUAL WHEELCHAIR SIMULATOR FOR REHABILITATION RESEARCH

Wheelchairs are the most common assistive devices for enhancing mobility with dignity [1], and are used by over 10 million users in developed countries alone [2]. Yet several major problems are still faced by manual wheelchair users today, including upper-body injuries induced by wheelchair propulsion [3], and difficulty navigating complex environments [4]. This paper describes a comprehensive manual wheelchair simulator being developed at Toronto Rehabilitation Institute’s new Challenging Environment Assessment Laboratory (CEAL) see Figure 1. The simulator is intended to enable and encourage research that can meaningfully address the challenges faced by wheelchair users, thus potentially improving the lives of millions.
Interaction between Energy Consumption and Economic Growth in Pakistan: A More Comprehensive Analysis Using ARDL Approach

Energy arguably plays a substantial part in the economic growth process. In this paper, we examine the intertemporal causal relationship between energy consumption and economic growth in Pakistan during the period of 1985? 2017. Unlike the majority of the previous studies, we employ the newly developed autoregressive distributed lag (ARDL)-bounds testing approach by Pesaran et al. (2001) to examine this association. It is an attempt to explore the long run ties for energy consumption and energy intensity with economic growth, urbanization, trade openness, and financial development. Results postulate that the trade openness has a positive impact on energy consumption while urbanization and financial development have a negative influence. As far as sectoral analysis is concerned, agriculture and manufacturing share has a positive imprint on energy while the services sector has a negative effect. Overall, the study finds that energy consumption spurs economic growth in Pakistan. The findings have practical policy implications for decision makers in the area of macroeconomic planning.
HOW UNDERSTANDING THE PATTERN OF BROILER FARM CONTAMINATION HAS SOLVED THE CAMPYLOBACTER ISSUE IN BROILERS

A small area of the broiler house, for 5 different flocks, was sectioned off using Perspex sheeting. This ‘biosecure cube’ (BC) was populated with 25 to 125 chicks (test birds), a small subset of the general population of up to 30,000 (control) birds. The BC area incorporated the water and feed-lines. The birds were routinely tested for Campylobacter (faecal and/or caecal samples). Despite the general bird population being Campylobacter positive as early as 14 days, 4 of the 5 BC sub-populations remained negative while the fifth remained negative until day 35. It was therefore concluded that preventing direct contact between the farm staff and the broilers prevents Campylobacter infection in broilers.
Semi-supervised Question Classification with Jointly Learning Question and Answer Representations

基于问题与答案共同表示学习的半监督问题分类方法  张栋,李寿山,王晶晶 (苏州大学 计算机科学与技术学院, 江苏 苏州 215006) 摘要:问题分类旨在对问题的类型进行自动分类,该任务是问答系统研究的一项基本任务。 本文提出了一 种基于问题和答案共同表示学习的问题分类方法。 该方法的特色在于,利用问题及其答案作为共同的上下 文环境,学习词的分布式表示,从而充分利用未标注样本中问题和答案隐含的分类信息。 具体而言,首先, 我们引入神经网络语言模型,利用问题与答案共同学习词向量表示,增加问题词向量的信息量;其次,加 入大量未标注的问题与答案样本参与词向量学习,进一步增强问题词向量表示能力;最后,将已标注的问 题样本以词向量形式表示作为训练样本,采用卷积神经网络建立问题分类模型。 实验结果表明,本文提出 的基于半监督问题分类方法能够充分利用词向量表示和大量未标注样本来提升性能,明显优于其他基准半 监督分类方法。 关键词:问题分类;共同表示;半监督 中图分类号:TP391 文献标识码:A Semi-supervised Question Classification with Jointly Learning Question and Answer Representations Dong Zhang, Shoushan Li, Jingjing Wang (School of Computer Science & Technology, Soochow University, Suzhou 215006, China) Abstract: Question classification aims at classifying the types of questions automatically, and this task is a basic task of question answering system. This paper proposes a method of semi-supervised question classification with jointly learning question and answer representations. The characteristic is that we consider the question and its corresponding answer as conjunct context to learn the word distributed representation. Specifically, neural network language model is introduced to learn question and answer representations jointly, so that the word vectors of question are added more information. Secondly, large numbers of unlabeled questions and answers participate in word vectors learning, which could strengthen the representation capacity of question word vectors. Finally, we represent the questions of word vectors as training samples, adopting the convolutional neural network to construct the question classifier. The experimental results demonstrate that the method of semi-supervised question classification with synergetic representations learning in this paper can make full use of word vectors and the unlabeled samples to improve the performance, and is better than other strong semi-supervised methods.
REAL-TIME PCR WITH HIGH-RESOLUTION MELTING ANALYSIS FOR DIAGNOSIS OF LYMPHATIC FILARIASIS

Lymphatic filariasis (LF), or elephantiasis, is caused by the filarial nematodes Wuchereria bancrofti, Brugia malayi, and B. timori. Over a billion people are at risk of contracting the disease, and about 40 million people suffer from severe disfigurement and disability as a result. Diagnosis is an essential element in the management of the disease, both at the individual patient care level and at the level of disease control in endemic populations. The success of LF elimination programs has lowered the levels of microfilariae in blood samples, which in turn has reduced the sensitivity of the conventional microfilariae detection method. In this study, we used real-time PCR with highresolution melting analysis (HRM) to detect and identify B. malayi and W. bancrofti in human blood samples. The assay can be performed using a single pair of primers targeting the mitochondrial partial 12S rRNA genes of these filarial parasites. Amplification and detection steps can be conducted in the same reaction, and no post-PCR processing is required. After assessing 30 blood samples, the HRM assay exhibited a specific melting temperature for each species, as well as high sensitivity and specificity compared with the microfilaria-detection method. Thus, the assay could be helpful for the diagnosis of LF.
Conference Title Amplitude Transformation-Based Blind Equalization Part II : Suitable for High-Order QAM Signals

In the digital transmission system, constant modulus algorithm (CMA) is a famous blind equalization to overcome the inter-symbol interference without the aid of training sequences. But for the non-constant modulus signals such as higher-order QAM signals, the CMA just achieve moderate steady-state mean square error (MSE) which may not be sufficient for the system to obtain adequate performance. By studying the amplitude relationship between different constellations of QAM signals, a new amplitude transformation method is proposed. According to such method the non-constant modulus signals can be changed to be constant modulus, and then using it to the CMA the zero steadystate MSE can be obtained. The efficiency of the proposed method is proved by computer simulations.