Miracle-dz/UniFAR-FTUs huggingface dataset:
Subseasonal variation of winter rainfall anomalies over South China during the mature phase of super El Niño events

ABSTRACT The authors explore the intraseasonal oscillation (ISO) of rainfall anomalies in South China, the related circulation regimes, and discuss the possible causes of the large variability of the positive rainfall anomalies over South China during the winter of the 1982/83, 1997/98 and 2015/16 super El Niño events. Case-by-case analysis shows that the 10–20-day ISO associated with the successive heavy rainfall events lead to the positive anomalies of winter rainfall in the three winters. Meanwhile, the 20–50-day ISO is relatively stronger in the winter of 1982/83 and 2015/16 but weaker in the winter of 1997/98. Except for a different speed, the anomalies of the 200-hPa wave train associated with the two ISOs both propagate eastward along the westerly jet between 20 N and 30 N. In the winter of 1982/83 and 2015/16, when the upper-level subseasonal wave trains in different periods pass through South China, the in-phase enhancement of upper-level divergences and the pumping effect could induce the persistent heavy rainfall events, which facilitate the stronger seasonal-mean rainfall. Although the 10–20-day ISO alone in the winter of 1997/98 could cause the higher-frequency rainfall events, the weaker 20–50-day ISO attenuates the anomalies of the South China winter rainfall. Therefore, the joint effects of the 10–20- and 20–50-day ISOs are critical for the larger amount of above-normal rainfall over South China during the mature phase of super El Niño events. Graphical Abstract
Decreased Thalamocortical Functional Connectivity after 36 Hours of Total Sleep Deprivation: Evidence from Resting State fMRI

Objectives The thalamus and cerebral cortex are connected via topographically organized, reciprocal connections, which hold a key function in segregating internally and externally directed awareness information. Previous task-related studies have revealed altered activities of the thalamus after total sleep deprivation (TSD). However, it is still unclear how TSD impacts on the communication between the thalamus and cerebral cortex. In this study, we examined changes of thalamocortical functional connectivity after 36 hours of total sleep deprivation by using resting state function MRI (fMRI). Materials and Methods Fourteen healthy volunteers were recruited and performed fMRI scans before and after 36 hours of TSD. Seed-based functional connectivity analysis was employed and differences of thalamocortical functional connectivity were tested between the rested wakefulness (RW) and TSD conditions. Results We found that the right thalamus showed decreased functional connectivity with the right parahippocampal gyrus, right middle temporal gyrus and right superior frontal gyrus in the resting brain after TSD when compared with that after normal sleep. As to the left thalamus, decreased connectivity was found with the right medial frontal gyrus, bilateral middle temporal gyri and left superior frontal gyrus. Conclusion These findings suggest disruptive changes of the thalamocortical functional connectivity after TSD, which may lead to the decline of the arousal level and information integration, and subsequently, influence the human cognitive functions.
Aggregation methods for efficient collocation detection

In this article we propose a rank aggregation method for the task of collocations detection. It consists of applying some well-known methods (e.g. Dice method, chi-square test, z-test and likelihood ratio) and then aggregating the resulting collocations rankings by rank distance and Borda score. These two aggregation methods are especially well suited for the task, since the results of each individual method naturally forms a ranking of collocations. Combination methods are known to usually improve the results, and indeed, the proposed aggregation method performs better then each individual method taken in isolation.
Level Set Methodology for Tamil Document Image Binarization and Segmentation

most challenging task in OCR is getting the characters segmented properly. The accuracy of segmentation depends on the quality of the binarization technique applied. Binarization is the process of setting all intensity values greater than some threshold value to "on". It converts the document image into binary image as extracting text and eliminating the background. This process also removes the noise. The output of this process is used as input to image segmentation process. Conventionally separate methods are used for binarizarion and segmentation. In this paper we investigate the use of recently introduced convex optimization methods, selective local/global segmentation (SLGS) algorithm (16) and fast global minimization (FGM) algorithm (15) for simultaneous binarization and segmentation. Out of the two methods we tried out, one of them is found to be suitable for OCR task. The FGM algorithm provides an average accuracy of 89.97% for Tamil character segmentation. Keywordsvel Set, Active Contours, Binarization, Segmentation.
Fusion and Fission of Genes Define a Metric between Fungal Genomes

Gene fusion and fission events are key mechanisms in the evolution of gene architecture, whose effects are visible in protein architecture when they occur in coding sequences. Until now, the detection of fusion and fission events has been performed at the level of protein sequences with a post facto removal of supernumerary links due to paralogy, and often did not include looking for events defined only in single genomes. We propose a method for the detection of these events, defined on groups of paralogs to compensate for the gene redundancy of eukaryotic genomes, and apply it to the proteomes of 12 fungal species. We collected an inventory of 1,680 elementary fusion and fission events. In half the cases, both composite and element genes are found in the same species. Per-species counts of events correlate with the species genome size, suggesting a random mechanism of occurrence. Some biological functions of the genes involved in fusion and fission events are slightly over- or under-represented. As already noted in previous studies, the genes involved in an event tend to belong to the same functional category. We inferred the position of each event in the evolution tree of the 12 fungal species. The event localization counts for all the segments of the tree provide a metric that depicts the “recombinational” phylogeny among fungi. A possible interpretation of this metric as distance in adaptation space is proposed.
A systematic evaluation of MBOT in statistical machine translation

Shallow local multi-bottom up tree transducers (MBOTs) have been successfully used as translation models in several settings because of their ability to model discontinuities. In this contribution, several additional settings are explored and evaluated. The ﬁrst rule extractions for tree-to-tree MBOT with non-minimal rules and for string-to-string MBOT are developed. All existing MBOT systems are systematically evaluated and compared to corresponding base-line systems in three large-scale translation tasks: English-to-German, English-to-Chinese, and English-to-Arabic. Particular emphasis is placed on the use of discontinuous rules. The developed rule extractions and analysis tools will be made publicly available.
Solving POMDPs with Continuous or Large Discrete Observation Spaces

We describe methods to solve partially observable Markov decision processes (POMDPs) with continuous or large discrete observation spaces. Realistic problems often have rich observation spaces, posing significant problems for standard POMDP algorithms that require explicit enumeration of the observations. This problem is usually approached by imposing an a priori discretisation on the observation space, which can be sub-optimal for the decision making task. However, since only those observations that would change the policy need to be distinguished, the decision problem itself induces a lossless partitioning of the observation space. This paper demonstrates how to find this partition while computing a policy, and how the resulting discretisation of the observation space reveals the relevant features of the application domain. The algorithms are demonstrated on a toy example and on a realistic assisted living task.
Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

Scatterplots remain one of the most popular and widely-used visual representations for multidimensional data due to their simplicity, familiarity and visual clarity, even if they lack some of the flexibility and visual expressiveness of newer multidimensional visualization techniques. This paper presents new interactive methods to explore multidimensional data using scatterplots. This exploration is performed using a matrix of scatterplots that gives an overview of the possible configurations, thumbnails of the scatterplots, and support for interactive navigation in the multidimensional space. Transitions between scatterplots are performed as animated rotations in 3D space, somewhat akin to rolling dice. Users can iteratively build queries using bounding volumes in the dataset, sculpting the query from different viewpoints to become more and more refined. Furthermore, the dimensions in the navigation space can be reordered, manually or automatically, to highlight salient correlations and differences among them. An example scenario presents the interaction techniques supporting smooth and effortless visual exploration of multidimensional datasets.
Nonlinear acoustic echo cancellation using adaptive orthogonalized power filters

In acoustic echo cancellation as, e.g., for mobile communication receivers, loudspeakers and their amplifiers cause significant nonlinear distortion in the echo path, resulting in a degradation of the performance of linear echo cancelers. In order to cope with this type of nonlinear echo path, we discuss an orthogonalized version of power filter that can be considered as a parallelized realization of the cascade of a memoryless polynomial followed by a linear filter. As, in the echo cancellation context, the statistics of the speech input are non-stationary and not known in advance, the orthogonalization follows the signal statistics. The performance of the resulting novel nonlinear structure is evaluated by experiments using real hardware.
Text Search of Surnames in Some Slavic and Other Morphologically Rich Languages Using Rule Based Phonetic Algorithms

Surnames play a key role as person natural identifiers, essentially in present information systems. This paper deals with the topic of optimizing a phonetic search algorithm as a string matching of surnames usable for communications service providers, person registries, social networks or genealogy databases. It describes a proposed solution for the phonetic searching of Slovak and (territorial) neighboring languages (Czech, Polish, Ukrainian, Russian, German, Hungarian, Jewish) surnames. This solution was designed to improve search precision and recall when searching for people by their surnames originating in these languages.
OsiriX: Is it really a suitable software for 3D visualization of neuroanatomical structures acquired from DICOM images?

In this paper, compatibility of OsiriX software with 3D visualization of neuroanatomical structures acquired from DICOM images was examined. OsiriX, as a multi-dimensional image navigation and display software, was designed for display and interpretation of multidimensional and multimodality images. This software was used in some new thesis on anatomy about 3D reconstruction and volume calculation of the intra-orbital part of the optic nerve successfully. Advantages and features of the software in 3D visualization, multidimensional image navigation and display were summarized in this brief technical note. © Neuroanatomy. 2008; 7: 20–21.
Towards a cultural ontology for interorganizational knowledge processes

The explication of national-specific and organizational-specific value systems of the firms involved in interorganizational knowledge management processes is the necessary condition for their success. The term cultural ontology is introduced to refer to such explication. Based on an inter-organizational knowledge-manipulating process model and on framework for studying the cultural influences on knowledge transfer process, the elements of cultural ontology are specified. The cultural ontology specification document includes its domain, purpose, level of formality, scope, possible sources of knowledge, competency questions and the possible reusable ontologies.
K-vec: A New Approach for Aligning Parallel Texts

Various methods have been proposed for aligning texts in two or more languages such as the Canadian Parliamentary Debates (Hansards). Some of these methods generate a bilingual lexicon as a by-product. We present an alternative alignment strategy which we call K-vec, that starts by estimating the lexicon. For example, it discovers that the English word fisheries is similar to the French peches by noting that the distribution of fisheries in the English text is similar to the distribution of pê'ches in the French. K-vec does not depend on sentence boundaries.
Study of air pollution using the leaves of some plant species from two cities in Delta State, Nigeria

The comparative study of air quality in two cities in the Niger Delta Region of Delta State, Nigeria was investigated. Eleven duplicates of fully matured leaves samples of Vernonia amygdalina , Magnifera indica , Citrius sinesis , Psidium guajava , Colocasia esculanta L . , Anacadium occidentale , Carica papaya L . , Elais guinensis , Bambosa Bambosa , Delonix regia and Musa paradisiacal L . cultivated in Agbarho metropolis in Ughelli North local government area and Osubi metropolis in Okpe local government area both of Delta State were randomly collected and analyzed for their ascorbic acid content, water retention capacity, chlorophyll and pH. Data from this study reveals higher relative water and chlorophyll content in experimental site as compared to the control site. This study further reveals that about 82% of plant species collected from the experimental sites showed higher ascorbic acid and pH content. While the air pollution tolerance index values were higher in experimental site as compared to those from the control site, the percentage increase in APTI values in the leaves of the plant species ranges from 5.42 to 26.49. The plant species under investigation shows increasing tolerance to air pollution in the order of Vernonia amygdalina (5.42) > Magnifera indica (6.54) > Citrius sinesis (6.69) > Psidium guajava (7.13) > Colocasia esculanta L . (7.61) > Anacadium occidentale (7.93) > Carica papaya L . (11.46) > Elais guinensis (16.20) > Bambosa bambosa (22.00) > Delonix regia (26.01) > Musa paradisiacal L . (26.49). Though, this study reveals conflicting results for the individual biochemical parameters to the tolerance of air pollution in both experimental and control sites, combining the various biochemical parameters for computing the APTI values gives more reliable results. Hence, a relationship is not only observed in the accumulation of chemical substance used in determining the extent of damage done by pollution in the leaves of all the plant species under investigation, but a gradient also exist for the individual parameters in the experimental sites as compared to those from the control sites and it is thus reflected in the APTI values recorded from both sites. Keywords: Air, APTI, Ascorbic Acid, Biochemical, Delta State, Pollution Water retention capacity
A Machine Learning Approach to Determine Semantic Dependency Structure in Chinese

In this paper, we attempt to automatically annotate the Penn Chinese Treebank with semantic dependency structure. Initially a small portion of the Penn Chinese Treebank was manually annotated with headword and semantic dependency relations. An initial investigation is then done using a Naive Bayesian Classifier and some handcrafted rules. The results show that the algorithms and proposed approach are effective at determining semantic dependency structure automatically. The Naive Bayesian Classifier makes a good baseline algorithm for future research.
Towards Automatic Addressee Identification in Multi-party Dialogues

The paper is about the issue of addressing in multi-party dialogues. Analysis of addressing behavior in face to face meetings results in the identification of several addressing mechanisms. From these we extract several utterance features and features of non-verbal communicative behavior of a speaker, like gaze and gesturing, that are relevant for observers to identify the participants the speaker is talking to. A method for the automatic prediction of the addressee of speech acts is discussed.
Efficient bundle sorting

Many data sets to be sorted consist of a limited number of distinct keys. Sorting such data sets can be thought of as bundling together identical keys and having the bundles placed in order; we therefore denote this as bundle sorting. We describe an efficient algorithm for bundle sorting in external memory, which requires at most c(N/B) logM/Bk disk accesses, where N is the number of keys, M is the size of internal memory, k is the number of distinct keys, B is the transfer block size, and 2 < c < 4. For moderately sized k, this bound circumvents the Theta((N/B) logM/B (N/B)) I/O lower bound known for general sorting. We show that our algorithm is optimal by proving a matching lower bound for bundle sorting. The improved running time of bundle sorting over general sorting can be significant in practice, as demonstrated by experimentation. An important feature of the new algorithm is that it is executed "in-place," requiring no additional disk space.
Assessing Sleep Disturbance in Low Back Pain: The Validity of Portable Instruments

Although portable instruments have been used in the assessment of sleep disturbance for patients with low back pain (LBP), the accuracy of the instruments in detecting sleep/wake episodes for this population is unknown. This study investigated the criterion validity of two portable instruments (Armband and Actiwatch) for assessing sleep disturbance in patients with LBP. 50 patients with LBP performed simultaneous overnight sleep recordings in a university sleep laboratory. All 50 participants were assessed by Polysomnography (PSG) and the Armband and a subgroup of 33 participants wore an Actiwatch. Criterion validity was determined by calculating epoch-by-epoch agreement, sensitivity, specificity and prevalence and bias- adjusted kappa (PABAK) for sleep versus wake between each instrument and PSG. The relationship between PSG and the two instruments was assessed using intraclass correlation coefficients (ICC 2, 1). The study participants showed symptoms of sub-threshold insomnia (mean ISI = 13.2, 95% CI = 6.36) and poor sleep quality (mean PSQI = 9.20, 95% CI = 4.27). Observed agreement with PSG was 85% and 88% for the Armband and Actiwatch. Sensitivity was 0.90 for both instruments and specificity was 0.54 and 0.67 and PABAK of 0.69 and 0.77 for the Armband and Actiwatch respectively. The ICC (95%CI) was 0.76 (0.61 to 0.86) and 0.80 (0.46 to 0.92) for total sleep time, 0.52 (0.29 to 0.70) and 0.55 (0.14 to 0.77) for sleep efficiency, 0.64 (0.45 to 0.78) and 0.52 (0.23 to 0.73) for wake after sleep onset and 0.13 (−0.15 to 0.39) and 0.33 (−0.05 to 0.63) for sleep onset latency, for the Armband and Actiwatch, respectively. The findings showed that both instruments have varied criterion validity across the sleep parameters from excellent validity for measures of total sleep time, good validity for measures of sleep efficiency and wake after onset to poor validity for sleep onset latency.
Histamine H4 receptor antagonist ameliorates chronic allergic contact dermatitis induced by repeated challenge

To cite this article: Seike M, Furuya K, Omura M, Hamada‐Watanabe K, Matsushita A, Ohtsu H. Histamine H4 receptor antagonist ameliorates chronic allergic contact dermatitis induced by repeated challenge. Allergy 2010; 65: 319–326.
Synthesizing cognition in neuromorphic electronic systems

Significance Neuromorphic emulations express the dynamics of neural systems in analogous electronic circuits, offering a distributed, low-power technology for constructing intelligent systems. However, neuromorphic circuits are inherently imprecise and noisy, and there has been no systematic method for configuring reliable behavioral dynamics on these substrates. We describe such a method, which is able to install simple cognitive behavior on the neuromorphic substrate. Our approach casts light on the general question of how the neuronal circuits of the brain, and also future neuromorphic technologies, could implement cognitive behavior in a principled manner. The quest to implement intelligent processing in electronic neuromorphic systems lacks methods for achieving reliable behavioral dynamics on substrates of inherently imprecise and noisy neurons. Here we report a solution to this problem that involves first mapping an unreliable hardware layer of spiking silicon neurons into an abstract computational layer composed of generic reliable subnetworks of model neurons and then composing the target behavioral dynamics as a “soft state machine” running on these reliable subnets. In the first step, the neural networks of the abstract layer are realized on the hardware substrate by mapping the neuron circuit bias voltages to the model parameters. This mapping is obtained by an automatic method in which the electronic circuit biases are calibrated against the model parameters by a series of population activity measurements. The abstract computational layer is formed by configuring neural networks as generic soft winner-take-all subnetworks that provide reliable processing by virtue of their active gain, signal restoration, and multistability. The necessary states and transitions of the desired high-level behavior are then easily embedded in the computational layer by introducing only sparse connections between some neurons of the various subnets. We demonstrate this synthesis method for a neuromorphic sensory agent that performs real-time context-dependent classification of motion patterns observed by a silicon retina.
Tremor Suppression of Elbow Joint via Functional Electrical Stimulation: A Simulation Study

In this paper, we propose a 1-DOF musculoskeletal model of the elbow joint that consists of a pair of antagonist muscles and one skeleton. Simulation based on the proposed model is performed to study the feasibility of tremor suppression via functional electrical stimulation (FES). In order to effectively attenuate pathological tremor of the movement disorder patients with minimal effect in the voluntary movement, we propose a fuzzy logical controller (FLC), a proportional-derivative (PD) controller and a compensator to regulate the stimulator. Current simulation results have shown satisfactory performance for the postural tremor suppression