Miracle-dz/UniFAR-FTUs huggingface dataset:
Observations on the Circulation in the Alboran Sea Using ERS1 Altimetry and Sea Surface Temperature Data

Abstract Data from the altimeter onboard the European Remote Sensing Satellite (ERSI) was used to Study the circulation of the Alboran Sea between 35° and 38°N, 0° and 6°W. This region is dominated by two anticyclonic gyres that are quasi-stationary in space but at times collapse over periods as short as 9 days. Maps of sea level residual, between February 1992 and December 1993, were created from the ERSI data with high correlation between sea surface temperature and residual sea level in the eastern part of the Alboran Sea. The spatially coherent signal was then extracted using the technique of complex empirical orthogonal analysis with the first three modes statistically significant. The variability of the first complex empirical orthogonal function mode appears to be associated with the incoming jet through the straits of Gibraltar with three time periods of high amplitude during the 1992–93 time frame. The second and third modes appear to be associated with the variability of both the western and eas.
Video stylization by single image example

In this paper, we propose a novel method for transferring artistic styles from a single image to a video clip. This new method can be considered as an extension of the image analogies technique in the domain of video processing. The method is built upon a previous fast texture transfer algorithm. The main contribution of our work lies in an extra constraint added to the original formulation, which preserves temporal coherence during frame-wise texture transfer. The experimental results show that this new constraint successfully helps suppress the artifacts of flickering, “stained-glass” and dragging, which are the main causes of temporal incoherence.
Protein Arginine Methyltransferase 1 and 8 Interact with FUS to Modify Its Sub-Cellular Distribution and Toxicity In Vitro and In Vivo

Amyotrophic lateral sclerosis (ALS) is a late onset and progressive motor neuron disease. Mutations in the gene coding for fused in sarcoma/translocated in liposarcoma (FUS) are responsible for some cases of both familial and sporadic forms of ALS. The mechanism through which mutations of FUS result in motor neuron degeneration and loss is not known. FUS belongs to the family of TET proteins, which are regulated at the post-translational level by arginine methylation. Here, we investigated the impact of arginine methylation in the pathogenesis of FUS-related ALS. We found that wild type FUS (FUS-WT) specifically interacts with protein arginine methyltransferases 1 and 8 (PRMT1 and PRMT8) and undergoes asymmetric dimethylation in cultured cells. ALS-causing FUS mutants retained the ability to interact with both PRMT1 and PRMT8 and undergo asymmetric dimethylation similar to FUS-WT. Importantly, PRMT1 and PRMT8 localized to mutant FUS-positive inclusion bodies. Pharmacologic inhibition of PRMT1 and PRMT8 activity reduced both the nuclear and cytoplasmic accumulation of FUS-WT and ALS-associated FUS mutants in motor neuron-derived cells and in cells obtained from an ALS patient carrying the R518G mutation. Genetic ablation of the fly homologue of human PRMT1 (DART1) exacerbated the neurodegeneration induced by overexpression of FUS-WT and R521H FUS mutant in a Drosophila model of FUS-related ALS. These results support a role for arginine methylation in the pathogenesis of FUS-related ALS.
Applications of Resampling Methods in Dynamic Financial Analysis May 13 , 1998

Dynmnic Financial Analysis can be viewed as the process of studying profitability and solvency of an ilmurance firm under a realistic and integrated nmdel of key input random variables such as loss frequency and severity, expenses, reinsurance, interest and inflation rates, and asset defaults. Traditional nmdels of input variables have generally fitted parameters for a predetermined family of probability distributiotm. In this paper we discuss applications of some modern methods of non-parametric statistics to modeling loss distributions, and possibilities of using them for modeling other input variables for tile purpose of arriving at an integrated company model. Several examples of inference about the severity of loss, loss distributions percentiles and other related quantities based on data smoothing, bootstrap estimates of standard error and bootstrap confidence intervals are presented. The examples are based on real-life auto injury claim data and the accuracy of our methods is compared with that of standard techniques. Model ndju~tment for inflation and bootstrap techniques based on the Kaplan-Meier estimator, useful in the presence of policies limits (censored losses), are also considered.
Employing Bootstrapping Methods to Examine the Need for Pulse Triggering In Diffusion-Weighted Imaging

Z. Nagy, C. Hutton, D. C. Alexander, R. Deichmann, and N. Weiskopf Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, London, United Kingdom, Centre for Medical Image Computing, Department of Computer Science, University College London, London, London, United Kingdom, University Hospital Brain Imgaging Centre, University of Frankfurt, Frankfurt, Germany
Simulation of line-edge roughness effects in silicon nanowire MOSFETs

In this paper, the effects of nanowire (NW) line-edge roughness (LER) in gate-all-around (GAA) silicon nanowire MOSFETs (SNWTs) are investigated by 3-D statistical simulation in terms of both performance variation and mean value degradation. A physical model is developed for NW LER induced performance degradation in SNWTs for the first time. The results indicate large performance mean value degradations due to NW LER in SNWTs. However, the LER induced parameter variation is still acceptable. In addition, as the LER correlation length (Λ) scales beyond the gate length, new distribution of performance parameters is observed, which has dual-peaks rather than single in conventional Gaussian distribution. The optimization for NW LER parameters is given for SNWT design as well.
A Maximum Entropy-Based Bio-Molecular Event Extraction Model that Considers Event Generation

In this paper, we propose a maximum entropy-based model, which can mathematically explain the bio-molecular event extraction problem. The proposed model generates an event table, which can represent the relationship between an event trigger and its arguments. The complex sentences with distinctive event structures can be also represented by the event table. Previous approaches intuitively designed a pipeline system, which sequentially performs trigger detection and arguments recognition, and thus, did not clearly explain the relationship between identified triggers and arguments. On the other hand, the proposed model generates an event table that can represent triggers, their arguments, and their relationships. The desired events can be easily extracted from the event table. Experimental results show that the proposed model can cover 91.36% of events in the training dataset and that it can achieve a 50.44% recall in the test dataset by using the event table.
A robust skew detection method based on Maximum Gradient Difference and R-signature

In this paper we study the detection of skewed text lines in scanned document images. The aim of our work is to develop a new automatic approach able to estimate precisely the skew angle of text in document images. Our new method is based on Maximum Gradient Difference (MGD) and R-signature. It detects zones that have high variations of gray values in different directions using the MGD transform. We consider these zones as being text regions. R-signature which is a shape descriptor based on Radon transform is then applied in order to approximate the skew angle. The accuracy of the proposed algorithm is evaluated on an open dataset by comparing error rates.
Using affective knowledge to generate and validate a set of emotion-related, action words

Emotion concepts are built through situated experience. Abstract word meaning is grounded in this affective knowledge, giving words the potential to evoke emotional feelings and reactions (e.g., Vigliocco et al., 2009). In the present work we explore whether words differ in the extent to which they evoke ‘specific’ emotional knowledge. Using a categorical approach, in which an affective ‘context’ is created, it is possible to assess whether words proportionally activate knowledge relevant to different emotional states (e.g., ‘sadness’, ‘anger’, Stevenson, Mikels & James, 2007a). We argue that this method may be particularly effective when assessing the emotional meaning of action words (e.g., Schacht & Sommer, 2009). In study 1 we use a constrained feature generation task to derive a set of action words that participants associated with six, basic emotional states (see full list in Appendix S1). Generation frequencies were taken to indicate the likelihood that the word would evoke emotional knowledge relevant to the state to which it had been paired. In study 2 a rating task was used to assess the strength of association between the six most frequently generated, or ‘typical’, action words and corresponding emotion labels. Participants were presented with a series of sentences, in which action words (typical and atypical) and labels were paired e.g., “If you are feeling ‘sad’ how likely would you be to act in the following way? ” … ‘cry. ’ Findings suggest that typical associations were robust. Participants always gave higher ratings to typical vs. atypical action word and label pairings, even when (a) rating direction was manipulated (the label or verb appeared first in the sentence), and (b) the typical behaviours were to be performed by the rater themselves, or others. Our findings suggest that emotion-related action words vary in the extent to which they evoke knowledge relevant for different emotional states. When measuring affective grounding, it may then be appropriate to use categorical ratings in conjunction with unimodal measures, which assess the ‘magnitude’ to which words evoke feelings (e.g., Newcombe et al., 2012). Towards this aim we provide a set of emotion-related action words, accompanied by generation frequency and rating data, which show how strongly each word evokes knowledge relevant to basic emotional states.
Prevalence of generalised osteoarthritis in patients with advanced hip and knee osteoarthritis: The Ulm Osteoarthritis Study

OBJECTIVES Different prevalences of generalised osteoarthritis (GOA) in patients with knee and hip OA have been reported. The aim of this investigation was to evaluate radiographic and clinical patterns of disease in a hospital based population of patient subgroups with advanced hip and knee OA and to compare the prevalence of GOA in patients with hip or knee OA, taking potential confounding factors into account. METHODS 420 patients with hip OA and 389 patients with knee OA scheduled for unilateral total joint replacement in four hospitals underwent radiographic analysis of ipsilateral and contralateral hip or knee joint and both hands in addition to a standardised interview and clinical examination. According to the severity of radiographic changes in the contralateral joints (using Kellgren-Lawrence ⩾ grade 2 as case definition) participants were classified as having either unilateral or bilateral OA. If radiographic changes of two joint groups of the hands (first carpometacarpal joint and proximal/distal interphalangeal joints defined as two separate joint groups) were present, patients were categorised as having GOA. RESULTS Patients with hip OA were younger (mean age 60.4 years) and less likely to be female (52.4%) than patients with knee OA (66.3 years and 72.5% respectively). Intensity of pain and functional impairment at hospital admission was similar in both groups, while patients with knee OA had a longer symptom duration (median 10 years) compared with patients with hip OA (5 years). In 41.7% of patients with hip OA and 33.4% of patients with knee OA an underlying pathological condition could be observed in the replaced joint, which allowed a classification as secondary OA. Some 82.1% of patients with hip and 87.4% of patients with knee OA had radiographic changes in their contralateral joints (bilateral disease). The prevalence of GOA increased with age and was higher in female patients. GOA was observed more often in patients with knee OA than in patients with hip OA (34.9% versus 19.3%; OR=2.24; 95% CI: 1.56, 3.21). Adjustment for the different age and sex distribution in both patient groups, however, takes away most of the difference (OR=1.32; 95% CI: 0.89, 1.96). CONCLUSION The crude results confirm previous reports as well as the clinical impression of GOA being more prevalent in patients with advanced knee OA than in patients with advanced hip OA. However, these different patterns might be attributed to a large part to a different distribution of age and sex in these hospital based populations.
A Novel Sidelobe Suppression Technique for OFDM-Based Cognitive Radio Transmission

In this paper, we propose a novel two-step sidelobe suppression technique for OFDM-based cognitive radios designed to minimize the amount of out-of-band emissions that could potentially interfere with incumbent licensed transmissions in adjacent frequency bands. The proposed technique combines both constellation expansion (CE) and cancellation subcarrier (CC) sidelobe reduction approaches in order to achieve lower out- of-band interference levels relative to their individual application. Being a two-step process, the first step of the proposed technique consists of performing CE, which exploits the combination of different random symbol sequences across the subcarriers in order to yield lower sidelobe levels. The second step is to insert several CCs on either side of contiguous blocks of data-bearing subcarriers such that they combine destructively with the data- bearing subcarrier sidelobe levels, yielding a reduction in out- of-band emissions. Simulation results show that with the CE of four symbols mapped to an 8-PSK signal constellation and with one CC employed on each side of a 32 subcarrier OFDM spectrum, there is a reduction of as much as 16 dB on the peak- interference causing sidelobe. From a probabilistic point of view, this translates to reducing 99.9% of the sidelobe power levels from around -5 dB to around -22 dB.
A Practical System for Human-like Parsing Content Areas: Natural Language Processing, Applications, Cognitive Modelling

In this paper I describe a human-like natural language parser called Plink. It works by parsing left-to-right through a sentence and keeping a complete representation of the partially read sentence. It does this by combining a sophisticated uniication-based grammar and grammar rule selection heuristics. Like humans, it parses in linear time, and generates one interpretation that is both syntactic and semantic. Plink also functions in real world applications. To do this, it must process texts that are not grammatical and does this by combining a general grammar and taking advantage of preference levels in the rule selection heuristics. Since it is a real world parser it has been evaluated on two parsing metrics: Parseval Black et al., 1991] and a dependency based metric Lin, 1996]. Plink performs in the area of 60 to 75is among the best parsers that do not use semantics for parsing decisions. The Plink mechanism forces the grammar developer to concentrate on the constituents that have the information that is needed for parsing decisions. This is psycholinguistically inspired, but also simpli-es development.
Traffic sign representation using sparse-representations

Automatic Traffic Sign Recognition has gained significant impetus among the research community in recent times. Increasing demands in the arenas of Autonomous Vehicle Navigation and Driver Assistance Systems is making this field of research more attractive. In this paper, we developed a technique which uses Sparse Representation based Classification coupled with Boundary Discriminative Factor (BDF) for recognizing traffic signs. The performance of this system is compared with one of the existing classifiers, Convolutional Neural Networks (CNNs) which has been employed in many real-time systems. This method also helps in reducing the enormous training time required for CNNs.
Multiconverter System Design for Fuel Cell Buffering and Diagnostics Under UAV Load Profiles

This paper presents a multisource, multiconverter power system for electrically propelled unmanned aerial vehicles (UAVs) with a focus on promoting fuel cell health. Linearized multiconverter system analysis and the two extra element theorem (2EET) inform a system design for fuel cell current buffering and integral diagnostics. Integral diagnostics is in situ impedance spectroscopy achieved by controlling the power system to superpose a frequency-swept excitation current at the fuel cell terminals. An experimental system demonstrates hybridization of a solid-oxide fuel cell (SOFC) with a lead-acid battery having suitable current buffering and integral diagnostics performance under UAV load profiles. Experimental behavior is demonstrated with an electrically emulated SOFC stack or “reference simulator. ” Impedance spectroscopy data measured during run-time clearly indicate both degradation and recovery phenomena in the SOFC.
Volumetric reconstruction of craniofacial structures from 2D lateral cephalograms by regression forest

The 3D reconstruction is an essential step to measure the craniofacial morphological changes from the historical growth database with only 2D cephalograms. In this paper, we propose a novel regression-forest-based method to estimate the volumetric intensity images from a lateral cephalogram. The regression forest can produce a prediction of the volumetric craniofacial structure as a mixture of Gaussian by weighted aggregating the distributions from trees. The dense anatomical structure can be reconstructed with no time-consuming digitally-reconstructed-radiographs (DRR) in the online testing process. The experiments demonstrate the proposed method can reconstruct volumetric intensity images from the lateral cephalograms effectively.
XCCS - Graphical Extension of CCS Language

A graphical extension of CCS process calculus called XCCS (extended CCS) is proposed in the paper. In the modified process calculus most operators were moved to a graphical layer to eliminate problems typical for CCS language, e.g. elimination of undesirable connections among agents. An XCCS model consists of two layers: a textual and a graphical one. The former is used to define behaviour of single agents, while the latter is used to define interconnections among them in concurrent systems. XCCS calculus is compatible with the CCS one and it is possible to transform an XCCS model into an equivalent CCS script. The paper presents a survey of main features of XCCS language.
The Development of Multi-Point Laser Doppler Anemometry ( MPLDA ) : A New Method to Estimate Fluid Flow Statistics

In this paper we describe a method to measure fluid flow fields that we call Multi-Point Laser Doppler Anemometry (MPLDA). Like Doppler Global Velocimetry (DGV) and single point Laser Doppler Anemometry (LDA), the technique derives information from the Doppler shift observed when light is scattered from a moving particle and exploits the advantages of these techniques. The method retains the elegant simplicity of DGV, but uses coherent heterodyne detection as in LDA rather than applying an absorption edge to demodulate the Doppler signal (as in DGV). This makes MPLDA suitable for the measurement of flow fields throughout the velocity range. In contrast with pulsed laser imaging techniques, such as Particle Image Velocimetry (PIV) and its derivatives, MPLDA does not require individual seeding particles to be resolved as is the case with LDA and DGV. We believe that this makes MPLDA unique in its ability to gain whole field measurements in large scale, low speed wind tunnel facilities. In essence MPLDA utilises a streak camera and coherent detection to record a short segments of the Doppler signals collected from many points within a seeded flow field. The streak image is then analysed to estimate the Doppler frequency at each point in the flow. In our original studies we used reflection from a galvanometer mirror to implement streak imaging. Using this technology we were able to prove the principles of MPLDA by measuring the surface velocity of a spinning disk. In this case the disk velocity was low (1/20 rev/sec) and consequently the measured Doppler frequencies were in the range of 0-10kHz. These initial results clearly demonstrated the potential of MPLDA, however, the scale and speed of the experiment are several orders of magnitude less than that which would be expected in a wind tunnel. In addition the reference beam necessary for coherent detection did not include a frequency shift and as such the measurements were subject to directional ambiguity. More recently we have conducted investigations into the use of electronic vacuum tube technology as a means to implement the streak imaging requirement of MPLDA. A streak tube of this kind is similar in principle to an image intensifier and uses deflection plates to displace electrons en route to an output phosphor screen. In this way pico second resolution is possible. In what follows, a streak tube in conjunction with a Peltier cooled CCD camera is used to provide a flexible MPLDA streak system for both low and high speed wind tunnel facilities. We demonstrate the use of this system as a means to measure the velocity of spray particles within the measurement volume of a basic, single component, LDA system.
GAME THEORY BASED TASK PLANNING IN MULTI ROBOT SYSTEMS

In the paper we discuss a problem of planning and coordination in a multi robot system. We consider a team of robots that performs a global task in a humanmade workspace of complex structure. A hybrid architecture of the team motion control system is considered. The system can be split into two layers: the planner module and the behavior based collision free motion controller, that is designed to perform several elementary navigation tasks. The role of the planner is to plan and coordinate execution of elementary tasks by individual agents to obtain performance of global task. We presents the method of elementary tasks planning based on N-person game. The Nash equilibrium concept of the game solution is applied. An algorithm of multi robot workspace exploration is presented as an example of application of the proposed method. Simulation of the algorithm was carried out, and its result is presented and discussed in the paper.
Detailed analysis and evaluation of keypoint extraction methods

In this paper, some existing keypoint extraction algorithms, including Harris, SIFT, SURF and CenSurE, are analyzed and evaluated based on images containing view, scale and rotation changes. After these algorithms are introduced, analysis on Harris and SIFT detectors has been carried out, which can lead to better understanding about their performances. Comparative experiments have been conducted to investigate repeatability, matching ratio, accuracy, characteristic distribution and computational efficiency. At last, the advantage and disadvantage of each method are summarized and the future works to improve their performances is also suggested.