Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Mean-Field-Type Filters for Big Data Assimilation

The combination of observed data and dynamical models of mean-field type over networked systems is a challenging problem because of non-linearity, high dimensionality and partial observations. In many networked systems, the effective extraction and utilization of the information contained in observed data should be accomplished by exploiting the availability of accurate predictive, proactive tools of mean-field type dynamical systems. Incorporating observed big data into dynamical models of mean-field type has two problems. One is the curse of dimensionality, and the other is the control of error accumulation. This paper presents a distributed mean-field filter (DMF) framework for large scale networked systems. The proposed filter exploits the topology of the network and decomposes it into highly independent components with respect to the marginal mean-field correlations. The upper bound of global filtering error can be estimated using mean-field-type game theory. Numerical experiments in two object tracking scenarios are carried out to illustrate the performance of our algorithm. Evaluation results show that DMF significantly outperforms the existing filtering algorithms.
Neural memories and search engines

In this article, we show the existence of a formal convergence between the matrix models of biological memories and the vector space models designed to extract information from large collections of documents. We first show that, formally, the term-by-document matrix (a mathematical representation of a set of codified documents) can be interpreted as an associative memory. In this framework, the dimensionality reduction of the term-by-document matrices produced by the latent semantic analysis (LSA) has a common factor with the matrix biological memories. This factor consists in the generation of a statistical ‘conceptualisation’ of data using little dispersed weighted averages. Then, we present a class of matrix memory that built up thematic blocks using multiplicative contexts. The thematic memories define modular networks that can be acceded using contexts as passwords. This mathematical structure emphasises the contacts between LSA and matrix memory models and invites to interpret LSA, and similar procedures, as a reverse engineering applied on context-deprived cognitive products, or on biological objects (e.g. genomes) selected during large evolutionary processes.
Automatic Classification and Relationship Extraction for Multi-Lingual and Multi-Granular Events from Wikipedia

Wikipedia is a rich data source for knowledge from all domains. As part of this knowledge, historical and daily events (news) are collected for different languages on special pages and in event portals. As only a small amount of events is available in structured form in DBpedia, we extract these events with a rule-based approach from Wikipedia pages. In this paper we focus on three aspects: (1) extending our prior method for extracting events for a daily granularity, (2) the automatic classification of events and (3) finding relationships between events. As a result, we have extracted a data set of about 170,000 events covering different languages and granularities. On the basis of one language set, we have automatically built categories for about 70% of the events of another language set. For nearly every event, we have been able to find related events.
Pneumatic Control of Robots for Rehabilitation

Pneumatic actuators are attractive for robotic rehabilitation applications because they are lightweight, powerful, and compliant, but their control has historically been difficult, limiting their use. In this paper we present the pneumatic control system developed for Pneu-WREX: a pneumatically actuated, upper extremity orthosis for rehabilitation after stroke. The developed pneumatic control system combines several novel components to make the entire system stable, reliable, and backdrivable. These components, which are described in this paper, include: (1) a unique two-valve force control subsystem that keeps chamber pressure low (to reduce friction and energy consumption) and adaptively compensates for leakage; (2) a new servovalve characterization approach that uses experimentally measured data in a combined non-linear and least-squares regression to obtain a linear relationship between mass flow and valve voltage; and (3) a new approach to state estimation using accelerometers and a Kalman filter to obtain clean signals for use in a non-linear adaptive feedback control law. Experimental testing of the device demonstrates the efficacy of the developed pneumatic control system.
Clinal Variation at Phenology-Related Genes in Spruce: Parallel Evolution in FTL2 and Gigantea?

Parallel clines in different species, or in different geographical regions of the same species, are an important source of information on the genetic basis of local adaptation. We recently detected latitudinal clines in SNPs frequencies and gene expression of candidate genes for growth cessation in Scandinavian populations of Norway spruce (Picea abies). Here we test whether the same clines are also present in Siberian spruce (P. obovata), a close relative of Norway spruce with a different Quaternary history. We sequenced nine candidate genes and 27 control loci and genotyped 14 SSR loci in six populations of P. obovata located along the Yenisei river from latitude 56°N to latitude 67°N. In contrast to Scandinavian Norway spruce that both departs from the standard neutral model (SNM) and shows a clear population structure, Siberian spruce populations along the Yenisei do not depart from the SNM and are genetically unstructured. Nonetheless, as in Norway spruce, growth cessation is significantly clinal. Polymorphisms in photoperiodic (FTL2) and circadian clock (Gigantea, GI, PRR3) genes also show significant clinal variation and/or evidence of local selection. In GI, one of the variants is the same as in Norway spruce. Finally, a strong cline in gene expression is observed for FTL2, but not for GI. These results, together with recent physiological studies, confirm the key role played by FTL2 and circadian clock genes in the control of growth cessation in spruce species and suggest the presence of parallel adaptation in these two species.
Designing a Novel System to Classify Traditional Chinese Calligraphy Images

As traditional Chinese calligraphic (TCC) occupies an important place in the life of modern Chinese, there are a lot of TCC images digitalized and exhibited on the Internet. However, effective classification in them is an imperative problem need to be addressed. The paper proposes a content-based classification system that represents the visual content of TCC images by a textural feature set. Four kinds of classifier implemented in the scheme learn the characteristics of fundamental TCC style, art movements and calligraphic artists. The experimental results show that the scheme is capable of classifying the TCC image based on calligraphic artists as well as art movements with an accuracy of greater than 80%.
The state of CASC

The CADE ATP System Competition (CASC) is an annual evaluation of fully automatic, first order Automated Theorem Proving systems - the world championship for such systems. This paper captures the state of CASC after CASC-20, the tenth CASC, held in 2005. It provides a summarized history of CASC, details of the current design of the competition, observations and discussion of the effects of CASC on ATP, lessons learnt during CASC, and remarks regarding the past, present, and future of CASC.
Distinct Gamma-Band Evoked Responses to Speech and Non-Speech Sounds in Humans

To understand spoken language, the human brain must have fast mechanisms for the representation and identification of speech sounds. Stimulus-induced synchronization of neural activity at gamma frequencies (20-80 Hz), occurring in humans at 200-300 msec from stimulus onset, has been suggested to be a possible mechanism for neural object representation. Auditory and visual stimuli also evoke an earlier (peak <100 msec) gamma oscillation, but its dependence on high-level stimulus parameters and, thereby, its involvement in object representation has remained unclear. Using whole-scalp magnetoencephalography, we show here that responses evoked by speech and non-speech sounds differed in the gamma-frequency but not in the low-frequency (0.1-20 Hz) band as early as 40-60 msec from stimulus onset. The gamma-band responses to the speech sound peaked earlier in the left than in the right hemisphere, whereas those to the non-speech sound peaked earlier in the right hemisphere. For the speech sound, there was no difference in the response amplitude between the hemispheres at low (20-45 Hz) gamma frequencies, whereas for the non-speech sound, the amplitude was larger in the right hemisphere. These results suggest that evoked gamma-band activity may indeed be sensitive to high-level stimulus properties and may hence reflect the neural representation of speech sounds. Consequently, speech-specific neuronal processing may commence no later than 40-60 msec from stimulus onset, possibly in the form of activation of language-specific memory traces.
Density Based Outlier Mining Algorithm with Application to Intrusion Detection

Presently, outlier mining is used for many areas such as telecommunication, finance and intrusion detection. However, finding outliers needs amounts of computation with most traditional algorithms. Thus, we propose a modified density based outlier mining algorithm in this paper. For every object in dataset, our algorithm need not judge whether there are core objects within the epsiv-neighborhood of it. In addition, the module information of data object is introduced in our algorithm and it can avoid large numbers of unnecessary computation to finding all outliers. The algorithm is applied on the intrusion dataset and experimental results show it obtains efficient performance for outlier mining while maintaining stable detection rates.
Estimating the size, cost, and types of Technical Debt

This study summarizes results of a study of Technical Debt across 745 business applications comprising 365 million lines of code collected from 160 companies in 10 industry segments. These applications were submitted to a static analysis that evaluates quality within and across application layers that may be coded in different languages. The analysis consists of evaluating the application against a repository of over 1200 rules of good architectural and coding practice. A formula for estimating Technical Debt with adjustable parameters is presented. Results are presented for Technical Debt across the entire sample as well as for different programming languages and quality factors.
Implicit bias in letters of recommendation for an undergraduate research internship

Abstract Letters of recommendation are commonly used to assess the potential of undergraduate students to be successful undergraduate research assistants/interns or their potential as graduate students. However, there is evidence to suggest that reference letters can include unconscious (or implicit) bias that can affect decisions and limit opportunities for under-represented minorities and students from non-research institutions. This study uses a text analysis software program to examine 457 letters of recommendation for undergraduate students applying to undertake international research experience to determine whether there is a statistically significant difference in the language used to describe the students accepted into the programme (n = 36 letters) compared to those who were not accepted (n = 421 letters). Results suggest that letters of recommendation for the accepted students describe the productivity of the students with greater certainty and include a greater number of quotes from student work. In comparison, the letters for those students who were not accepted into the programme include more positive emotion and describe the insight of the student, but include more words associated with discrepancy and tentative statements. Despite no statistically significant differences in grade point averages, a similar pattern was observed between male and female applicants, white and non-white applicants, and applicants from research and non-research institutions. Results suggest a need to standardise letters of recommendation to ensure that the biases are minimised and do not present a barrier to increasing diversity in undergraduate research.
Symmetric Squares of Elliptic Curves: Rational Points and Selmer Groups

We consider the Bloch-Kato conjecture applied to the symmetric square L-function of an elliptic curve over Q, at s = 2. In particular, we use a construction of elements of order l in a generalised Shafarevich-Tate group, which works when E has a rational point of infinite order and a rational point of order l. The existence of the latter places us in a situation where the recent theorem of Diamond, Flach, and Guo does not apply, but we find that the numerical evidence is quite convincing.
Is EQ-5D a valid quality of life instrument in patients with Parkinson's disease? A study in Singapore.

INTRODUCTION The purpose of the present study was to evaluate the validity of the EQ-5D in patients with Parkinson's disease (PD) in Singapore. MATERIALS AND METHODS In a cross-sectional survey, patients with PD completed English or Chinese version of the EQ-5D, the 8-item Parkinson's disease questionnaire (PDQ-8), and questions assessing socio-demographic and health characteristics. Clinical data were retrieved from patients' medical records. The validity of the EQ-5D was assessed by testing a-priori hypotheses relating the EQ-5D to the PDQ-8 and clinical data. RESULTS Two hundred and eight PD patients (English speaking: 135) participated in the study. Spearman correlation coefficients between the EQ-5D and PDQ-8 ranged from 0.25 to 0.75 for English-speaking patients and from 0.16 to 0.67 for Chinese-speaking patients. By and large, the EQ-5D scores were weakly or moderately correlated with Hoehn and Yahr stage (correlation coefficients: 0.05 to 0.43), Schwab and England Activities of Daily Living score (correlation coefficients: 0.10 to 0.60), and duration of PD (correlation coefficients: 0.16 to 0.43). The EQ-5D index scores for patients with dyskinesia or "wearing off" periods were significantly lower than those without these problems. The EQ-5D Visual Analog Scale (EQ-VAS) scores also differed for English-speaking patients with deferring dyskinesia, "wearing off" periods, or health transition status; however, such differences were not observed in patients who completed the survey in Chinese. CONCLUSIONS The EQ-5D questionnaire appears valid for measuring quality of life in patients with PD in Singapore. However, the validity of EQ-VAS in Chinese-speaking patients with PD should be further assessed.
Boundary management in action: A diary study of students’ school-home conflict.

Contemporary technologies enable students to be "connected" with friends, family, student peers, and their study materials 24/7. This study aimed to examine how college students' boundary management enactment (BME; ranging from segmentation to integration) related to school-to-home conflict and home-to-school conflict and, subsequently, to school performance, satisfaction with home life, and home-school balance. Moreover, this study aimed to establish whether these relationships depended on students' boundary management preferences for segmenting school from home, and home from school. A diary study was conducted among 122 students from a major university in the Netherlands. Students completed an online questionnaire and online daily surveys over a period of 5 consecutive days of study. Results supported that students experienced more school-home and home-school conflict when they integrated rather than segmented school and home. Also as predicted, integration related to lower school performance, lower home life satisfaction, and lower balance, and these relationships were mediated by increased conflict between home and school life. Students' preferences did not moderate these relationships. This indicates that segmenting school and home life roles seems to be the advisable strategy for students, irrespective of their preference for segmentation. Students would benefit from increased awareness of the advantages of segmentation and 'how to' training sessions that teach them how to set boundaries between school and home. (PsycINFO Database Record
The N-linked oligosaccharide at FcγRIIIa Asn-45: an inhibitory element for high FcγRIIIa binding affinity to IgG glycoforms lacking core fucosylation

Human leukocyte receptor IIIa (FcγRIIIa) plays an important role in mediating therapeutic antibodies’ antibody-dependent cellular cytotoxicity (ADCC), which is closely related to the clinical efficacy of anticancer processes in humans in vivo. The removal of the core fucose from oligosaccharides attached to the Fc region of antibodies improves FcγRIIIa binding, allowing the antibodies to enhance dramatically the antibody effector functions of ADCC. In this study, the contribution of FcγRIIIa oligosaccharides to the strength of the FcγRIIIa/antibody complex was analyzed using a serial set of soluble human recombinant FcγRIIIa lacking the oligosaccharides. A nonfucosylated antibody IgG1 appeared to have a significantly higher affinity to the wild-type FcγRIIIa fully glycosylated at its five N-linked oligosaccharide sites than did the fucosylated IgG1, and this increased binding was almost abolished once all of the FcγRIIIa glycosylation was removed. Our gain-of-function analysis in the FcγRIIIa oligosaccharide at Asn-162 (N-162) confirmed that N-162 is the element required for the high binding affinity to nonfucosylated antibodies, as previously revealed by loss-of-function analyses. Interestingly, beyond our expectation, the FcγRIIIa modified by N-162 alone showed a significantly higher binding affinity to nonfucosylated IgG1 than did the wild-type FcγRIIIa. Attachment of the other four oligosaccharides, especially the FcγRIIIa oligosaccharide at Asn-45 (N-45), hindered the high binding affinity of FcγRIIIa to nonfucosylated IgG1. Our data clearly demonstrated that N-45 is an inhibitory element for the high FcγRIIIa binding affinity mediated by N-162 to nonfucosylated antibodies. This information can be exploited for the structural-based functional study of FcγRIIIa.
Solving Fuzzy QoS Constraint Satisfaction Technique for Web Service Selection

In global Web services selection, it involves to multi-objectives optimization and tradeoffs of diversified QoS criteria, therefore a suitable genetic algorithm is proposed to tackle the service selection problem. Since the QoS criteria are not always explicit and usually containing of fuzzy element, So this paper focuses on the relation between constraint satisfaction of fuzzy QoS criteria optimization and fitness evolution in multi-objective Web services selection and how to adjust the fuzzy QoS criteria of individual to fit for the evolution of population.
Velocity similarity anonymization for continuous query Location based services

In this paper, we introduced a novel query privacy algorithm called the direction speed dynamic cloaking algorithm (DSDCA) for continuous query Location based services (LBS) that considered users with similar direction, similar speed, and travelling with the same transport mode for cloaking. Experimental evaluation of the algorithm on a real world map showed that our model protects privacy of users during the entire query period whiles allowing users' choice of privacy requirements. It significantly improved quality of service (QoS), exhibited a good success rate and achieved an excellent performance measure as compared to other algorithms.
Cost optimal planning with LP-based multi-valued landmark heuristic

Landmark based heuristics are among the most accurate current known admissible heuristics for cost optimal planning. Disjunctive action landmarks can be considered as at-least-one constraints on the actions they contains. In many planning domains, there are many critical propositions which have to be established for a number of times. Previous landmarks fail to express this kind of general cardinality constraints. In this paper, we propose to generalize landmarks to multi-valued landmarks to model general cardinality constraints in cost optimal planning. We show existence of complete multi-valued landmark sets by explicitly constructing complete multi-valued action landmark sets for general planning tasks. However, it's computationally intractable to extract and exploit exact lower bounds of general multi-valued action landmarks. We devise a linear programming based multi-valued landmark heuristic hlpml which extracts and exploits multi-valued landmarks using a linear programming solver. The heuristic hlpml is guaranteed to be admissible and can be computed in polynomial time. Experimental evaluation on benchmark domains shows hlpml beats state-of-the-art admissible heuristic in terms of heuristic accuracy and achieves better overall coverage performance at the cost of using more CPU time.
Introducing active learning on Text to Emotion Analyzer

Now-a-days, online interpersonal communications have become more preferable than face-to-face interactions. However, emotions play a significant role in online communication. Automatic extraction of emotions from the text is a hot research issue because it minimizes the communication gap and misunderstanding between users. To become emotionally more intelligent, our previous text to emotion analyzing system should communicate with experts for suggestions of possible emotional state if it fails to analyze the text. In this research, we augment our previous system by introducing active learning approach which allows to query experts for emotional label of the given text. It makes our training dataset enriched. To build a classification model by analyzing the training dataset, we employ Naive Bayes classification technique. Our classifier updates the emotional database automatically. We also develop a prototype of our system named TEA: Text-to-Emotion-Analyzer. Our experiment and evaluation section exhibits satisfactory results in terms of recall-precision over our previous system as well as other method namely Vector Space Model (VSM).
Medical students’ perceptions, awareness, societal attitudes and knowledge of autism spectrum disorder: an exploratory study in Malaysia

Objectives: This study aimed to investigate the perception, awareness, societal attitude, and knowledge about Autism Spectrum Disorder (ASD) in Malaysian medical students. Methods: An exploratory survey was conducted with 83 medical students in Malaysia. In the survey, the medical students were required to rate their perception, awareness, societal attitude, and their recognition of ASD symptoms. Results: The results showed the senior medical students had increased knowledge about ASD symptoms compared to the juniors, but there was no clear indicator that they had obtained the knowledge through formal training. Specifically, the medical students could better identify symptoms related to restrictive and fixation behavioral patterns than social communicative deficits. While considering the effects of societal attitude, year of study, perception about ASD course and other demographic variables, the year of study emerged as the sole predictor of the medical students’ knowledge about ASD. Conclusion: The findings from this study provided evidence for the need of compulsory training on ASD in medical schools in improve the knowledge and skills of prospective medical practitioners to identify individuals with ASD. Such effort is fundamental for the early identification and intervention of ASD in developing countries such as Malaysia.