Miracle-dz/UniFAR-FTUs huggingface dataset:
An evaluation of writeprint matching method to identify the authors of Thai online messages

This research studies the author identification of Thai online messages, based on 54 writing attributes. The method in focus is writeprint matching, which employs frequent pattern mining to create the writeprint of each suspect and computes a similarity score between this writeprint and the pattern found in an anonymous message. It achieved an average accuracy of 82%, while other well-known methods, support vector machine (SVM) and C4.5 decision tree, achieved average accuracies of 89% and 81%, respectively. As for the identification of individual author, all three methods were as good as each other in most cases. The writeprint matching method had potential in reducing Type I error or the chance of dismissing real offenders. However, its performance was still limited when the suspects had too similar writing styles.
Hybrid multivariate morphology using lattice auto-associative memories for resting-state fMRI network discovery

Analysis of fMRI data, specifically resting-state fMRI data, is performed here from the point of view of a hybrid Multivariate Mathematical Morphology induced by a supervised h-ordering defined on the fMRI time series by the response of Lattice Auto-associative Memories built from specific fMRI voxels. The supervised h-ordering values and the results of morphological filters, i.e. a morphological top-hat, allow to identify some brain networks depending on the seed voxel value. Results on a set of resting state fMRI images of schizophrenia patients and healthy controls show that these networks can be dependent on the subject class, thus providing discriminant findings that may be useful for machine learning approaches.
Accelerated Ambient Occlusion Using Spatial Subdivision Structures

Ambient Occlusion is a relatively new method that gives global illumination like results. This paper presents a method to accelerate ambient occlusion using the form factor method in Bunnel [2005] as well as utilizing the fact that ambient occlusion is a function of nearby geometry only. The proposed method combines existing ideas in order to accelerate ambient occlusion calculations by using a spatial subdivision structure (an octree) and selective sampling.
Antisperm antibodies modify plasma membrane functional integrity and inhibit osmosensitive calcium influx in human sperm.

BACKGROUND The hypo-osmotic swelling (HOS) test evaluates the ability of the functional sperm plasma membrane to stretch following cell swelling when exposed to hypo-osmotic solutions. Sperm samples with low HOS scores show low fertilization and pregnancy rates during assisted reproductive techniques, though data are controversial. The aim of this study was to compare the results of the HOS test in a group of normozoospermic men with those in a group of subjects affected by autoimmune infertility due to the presence of antisperm antibodies (ASA) bound to the sperm surface. METHODS Sperm from normozoospermic and from infertile subjects affected by autoimmune infertility were exposed to hypo-osmolar conditions to verify the effects on intracellular calcium concentrations and acrosome reaction. RESULTS Sperm samples from infertile men with ASA showed HOS test scores that were significantly lower than those of normozoospermic subjects despite similar sperm viability percentages. Sperm with ASA bound to their plasma membrane showed a reduced rise in intracellular calcium concentrations and acrosome reaction after hypo-osmotic challenge with respect to sperm from normozoospermic subjects without ASA. CONCLUSIONS Infertile subjects with ASA have a reduced sperm plasma membrane functional integrity that could explain, at least in part, the low fertilization and pregnancy rates observed in these subjects during assisted reproductive procedures. Evaluation for the presence of ASA in all sperm samples showing low HOS test scores in the presence of normal sperm viability percentages is suggested.
Hot-carrier induced degradations on RF power characteristics of SiGe heterojunction bipolar transistors

Hot-carrier (HC) effects on high-frequency and RF power characteristics of Si/SiGe HBTs are investigated in this paper. By using the two-tone load-pull measurement, we find that not only the cutoff frequency, but also the output power performances of Si/SiGe HBTs are suffered by the HC stress. In this work, S-parameters and intrinsic elements of an equivalent hybrid-/spl pi/ model were used to validate the HC effects on high-frequency characteristics. With different bias conditions, the degradations of cutoff frequency, power gain, and linearity are found to be worse under constant base-current measurement than that under constant collector-current measurement. The HC-induced degradations on the current gain, transconductance, and ideality-factor of base and collector currents are analyzed to explain the experimental observations.
Toxicity of three selected pesticides (Alachlor, Atrazine and Diuron) to the marine fish (turbot Psetta maxima)

The present study aimed to evaluate acute toxicity tests for three selected herbicides: Alachlor, Atrazine and Diuron using turbot flatfish. Larvae were more sensitive than turbot embryos to all pesticides. Median lethal concentrations of the selected pesticides during a 48 h and 96 h exposure for turbot embryos and larvae were, respectively: alachlor, 2177 and 2233; diuron, 10076 and 7826 and atrazine, 11873 and 9957 μg/L. On the basis of the obtained acute toxicity data, all compounds were included among substances highly toxic to fish, in the following order: alachlor> atrazine> diuron. At higher concentrations, pesticides caused a significant increase in embryo mortality. Surviving organisms suffered a significant decrease in hatching success, malformations (embryos), pericardial oedema and skeletal deformation (larvae). All herbicides appear to be teratogenic to the turbot early life stage. Furthermore, the three selected pesticides differed in their toxicity to the fish. Keywords: Turbot, early life stage, acute toxicity, sublethal effects, herbicides
Federal Reserve Bank of Dallas Globalization and Monetary Policy Institute Intra-safe Haven Currency Behavior during the Global Financial Crisis

We investigate intra-safe haven currency behavior during the recent global financial crisis. The currencies we consider are the USD, the JPY, the CHF, the EUR, the GBP, the SEK, and the CAD. We first assess which safe haven currency appreciates the most as market uncertainty increases, i.e. we assess which safe haven currency is the " safest ". We then use non-temporal threshold analysis to investigate whether intra-safe haven currency behavior changes, e.g. accelerates or decelerates, as market uncertainty increases. We find that the JPY is the " safest " of safe haven currencies and that only the JPY appreciates as market uncertainty increases regardless of the prevailing level of uncertainty. For all other currencies under study we find significant market uncertainty threshold effects. We extend our analysis to also consider intra-safe haven currency behavior before and after the global financial crisis. for very helpful comments. The views in this paper are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Dallas or the Federal Reserve System.
RACAI: Meaning Affinity Models

This article introduces an unsupervised word sense disambiguation algorithm that is inspired by the lexical attraction models of Yuret (1998). It is based on the assumption that the meanings of the words that form a sentence can be best assigned by constructing an interpretation of the whole sentence. This interpretation is facilitated by a dependency-like context specification of a content word within the sentence. Thus, finding the context words of a target word is a matter of finding a pseudo-syntactic dependency analysis of the sentence, called a linkage.
Identification and Classification of Differentially Expressed Genes in Renal Cell Carcinoma by Expression Profiling on a Global Human 31 , 500-Element cDNA Array

Judith M. Boer, Wolfgang K. Huber, Holger Sültmann, Friederike Wilmer, Anja von Heydebreck, Stefan Haas, Bernhard Korn, Bastian Gunawan, Andreas Vente, Laszlo Füzesi, Martin Vingron, and Annemarie Poustka Departments of Molecular Genome Analysis and Theoretical Bioinformatics, German Cancer Research Center, Heidelberg, Germany; Institute of Pathology, Georg-August-Universität, Göttingen, Germany; Resource Center Primary Database, Berlin/Heidelberg, Germany
Selecting features for domain-independent named entity recognition

We propose a domain adaptation method for supervised named entity recognition (NER). Our NER uses conditional random fields and we rank and filter out features of a new unknown domain based on the means of weights learned on known domains. We perform experiments on English texts from OntoNotes version 4 benchmark and see a statistically significant better performance on a small number of features and a convergence of performance to the maximum F1-measure faster than conventional feature selection (information gain). We also compare with using the weights learned on a mixture of known domains.
Deployment of Private Crowdsourcing System with Quality Control Methods

Current crowdsourcing platforms such as Amazon Mechanical Turk provide an attractive solution for processing of high-volume tasks at low cost. However, problems of quality control remain a major concern. In the present work, we developed a private crowdsourcing system(PCSS) running in a intranetwork, that allow us to devise for quality control methods. For quality control, we introduce four worker selection methods: preprocessing filtering, real-time filtering, post-processing filtering, and guess processing filtering. In addition to a basic approach involving initial training or the use of gold standard data, these methods include a novel approach, utilizing collaborative filtering techniques. Furthermore, we collected a large amount of vocabulary data for natural language processing, such as voice recognition and text to speech using PCSS. The quality control methods increased accuracy by 32.4% in collecting vocabulary task. Then, we got 138 thousand vocabulary data. We found that PCSS is a practical system to collect data, and used for three years since 2011.
Characterizing mild cognitive impairment in Parkinson's disease

There is growing interest in identifying Parkinson's disease (PD) patients with mild cognitive impairment (PD‐MCI), but widely disparate criteria have been used. We assessed 143 PD patients and 50 matched controls on 20 measures across 4 cognitive domains (executive function, attention and working memory, learning and memory, visuoperception). Twenty‐four patients met criteria for dementia (PD‐D); nondementia patients were classified as either with normal cognition or MCI for 12 neuropsychological criteria. We compared the influence of these criteria on the distribution of global cognitive performance in the resulting PD‐MCI groups relative to the control and PD‐D groups. Different criteria produced substantial variation in the proportion of PD‐MCI cases identified. Fourteen percent PD‐MCI was found when using 2 scores in 1 domain at 2 standard deviations (SD) below normative scores, with no controls identified as MCI, through to 89% PD‐MCI with 1 score in 1 domain at 1 SD below normative scores, when 70% of controls were identified as MCI. The balance of cases with impaired cognition but not those with generally intact cognition was better served by using criteria that required 2 specific deficit scores or deficits across 2 domains. As comparisons with external normative data may have greater applicability across centers, we suggest that 2 scores at −1.5 SD within any single domain (30% PD‐MCI) or 1 score at −1.5 SD in each of 2 domains (37% PD‐MCI) provide suitable criteria to minimize the inclusion of cognitively well patients. Clinical dementia rating did not improve the relative identification of cognitively impaired and unimpaired nondementia PD patients. © 2011 Movement Disorder Society
Transcription Factor SomA Is Required for Adhesion, Development and Virulence of the Human Pathogen Aspergillus fumigatus

The transcription factor Flo8/Som1 controls filamentous growth in Saccharomyces cerevisiae and virulence in the plant pathogen Magnaporthe oryzae. Flo8/Som1 includes a characteristic N-terminal LUG/LUH-Flo8-single-stranded DNA binding (LUFS) domain and is activated by the cAMP dependent protein kinase A signaling pathway. Heterologous SomA from Aspergillus fumigatus rescued in yeast flo8 mutant strains several phenotypes including adhesion or flocculation in haploids and pseudohyphal growth in diploids, respectively. A. fumigatus SomA acts similarly to yeast Flo8 on the promoter of FLO11 fused with reporter gene (LacZ) in S. cerevisiae. FLO11 expression in yeast requires an activator complex including Flo8 and Mfg1. Furthermore, SomA physically interacts with PtaB, which is related to yeast Mfg1. Loss of the somA gene in A. fumigatus resulted in a slow growth phenotype and a block in asexual development. Only aerial hyphae without further differentiation could be formed. The deletion phenotype was verified by a conditional expression of somA using the inducible Tet-on system. A adherence assay with the conditional somA expression strain indicated that SomA is required for biofilm formation. A ptaB deletion strain showed a similar phenotype supporting that the SomA/PtaB complex controls A. fumigatus biofilm formation. Transcriptional analysis showed that SomA regulates expression of genes for several transcription factors which control conidiation or adhesion of A. fumigatus. Infection assays with fertilized chicken eggs as well as with mice revealed that SomA is required for pathogenicity. These data corroborate a complex control function of SomA acting as a central factor of the transcriptional network, which connects adhesion, spore formation and virulence in the opportunistic human pathogen A. fumigatus.
Selective Control of Attention Supports the Positivity Effect in Aging

There is emerging evidence for a positivity effect in healthy aging, which describes an age-specific increased focus on positive compared to negative information. Life-span researchers have attributed this effect to the selective allocation of cognitive resources in the service of prioritized emotional goals. We explored the basic principles of this assumption by assessing selective attention and memory for visual stimuli, differing in emotional content and self-relevance, in young and old participants. To specifically address the impact of cognitive control, voluntary attentional selection during the presentation of multiple-item displays was analyzed and linked to participants' general ability of cognitive control. Results revealed a positivity effect in older adults' selective attention and memory, which was particularly pronounced for self-relevant stimuli. Focusing on positive and ignoring negative information was most evident in older participants with a generally higher ability to exert top-down control during visual search. Our findings highlight the role of controlled selectivity in the occurrence of a positivity effect in aging. Since the effect has been related to well-being in later life, we suggest that the ability to selectively allocate top-down control might represent a resilience factor for emotional health in aging.
Query-Regression Networks for Machine Comprehension

We present Query-Regression Network (QRN), a variant of Recurrent Neural Network (RNN) that is suitable for end-to-end machine comprehension. While previous work largely relied on external memory and global softmax attention mechanism, QRN is a single recurrent unit with internal memory and local sigmoid attention. Unlike most RNN-based models, QRN is able to effectively handle long-term dependencies and is highly parallelizable. In our experiments we show that QRN obtains the state-of-the-art result in end-to-end bAbI QA tasks.
An event-driven control to achieve adaptive walking assist with gait primitives

This paper presents a control method for walking assist with hip-mounted exoskeleton robots. For modeling a user's current walking motion, a novel finite state machine is first constructed. We divide a walking cycle uniformly using the inevitable zero crossing events. When state transitions occur, we capture the current walking spatio-temporal sensor data as discrete form. By using the sensed hip data as boundary conditions, we also develop a gait primitives based motion reconstruction method. Gait primitives are a form of basis trajectories to represent various joint motions. From those methods we estimate the moment of heel landing with interpolated knee joint motions. Utilizing the user's previous opposite step motion, we predict the positive or negative work intervals of the current step motion. This makes it possible to achieve natural `one shot' assist by driving adapted torques fast. This assist strategy is also effective to enhance gait regularity. The measures of stride time variability are improved by over 30% for the simulated experiment. Various real experimentations demonstrate the feasibility of our approach.
The Case for a General and Interaction-based Third-party Cookie Policy

The privacy implications of third-party tracking is a well-studied problem. Recent research has shown that besides data aggregators and behavioral advertisers, online social networks also act as trackers via social widgets. Existing cookie policies are not enough to solve these problems, pushing users to employ blacklist-based browser extensions to prevent such tracking. Unfortunately, such approaches require maintaining and distributing blacklists, which are often too general and adversely affect non-tracking services for advertisements and analytics. In this paper, we propose and advocate for a general third-party cookie policy that prevents third-party tracking with cookies and preserves the functionality of social widgets without requiring a blacklist and adversely affecting non-tracking services. We implemented a proof-of-concept of our policy as browser extensions for Mozilla Firefox and Google Chrome. To date, our extensions have been downloaded about 11.8K times and have over 2.8K daily users combined.
Bidirectional Background Modeling for Video Surveillance

Traditional background model methods often require complicated computations, and are sensitive to illumination and shadow. In this paper, we propose a block-based background modeling method, and use our proposed method to combine color and texture characteristics. Suppression and relaxation are the two key strategies to resist illumination changes and shadow disturbance. The proposed method is quite efficient and is capable of resisting illumination changes. Experimental results show that our method is suitable for real-word scenes and real-time applications.
Affine Invariant Point-Set Matching Using Convex Hull Bisection

Affine invariant point-set matching is an important issue in computer vision and pattern recognition. Using reference points derived from the convex hull of the point-set is an existing idea to solve this problem. However, how to choose proper and enough reference points for extracting affine invariant and powerful discriminative descriptors is an open problem. In this paper, a novel method termed convex hull bisection (CHB) is proposed for affine invariant point-set matching. In CHB, for each point in the point-set, two reference points are derived by bisecting the convex hull using the line connecting the point and the centroid of the convex hull. The resulting reference points and other reference points, such as the centroid point of the convex hull and the mean point of the point-set, are utilised to yield an 11-dimensional affine invariant feature vector associated with any point within the point-set. The obtained point based descriptors are used for point-set matching. The proposed method works well even in the case that reference points are overlapping or collinear, which overcomes the limitations of the existing convex hull based methods. The effectiveness of the proposed method is validated by an extensive experimental investigation.
An Ontology-Based Archive for Historical Research

The digitalization of cultural materials is doubtless a key-enabler for increasing accessibility of cultural heritage documents, e.g., historical texts. In the last decade Semantic Digital Libraries (see, e.g., [1]) have attracted the attention of research communities coming from different research areas, such as Cultural Heritage, History, and Knowledge Engineering. In order to find more innovative methods to improve search and retrieval operations, recently portals and digital libraries concerning Cultural Heritage have been enhanced with Semantic Web [2] technologies. Such technologies can offer effective solutions about design and implementation of user-friendly ways to access and query content and metadata [1]. In this context, a prominent example is the Europeana project [3]. Particularly, cultural heritage documents are characterized by being syntactically and semantically heterogeneous, multilingual, semantically rich, and highly interlinked. They are produced in a distributed, open fashion by organizations like museums, libraries, and archives, using their own established standards and best practices [4]. Historical documents represent an important component of the cultural heritage field, and they have been digitized and published on the web by means of several applications. In this extended abstract we present stole, an ontology-based digital archive collecting some of the most relevant journal articles published between 1848 and 1946 concerning the legislative history of public administration in Italy. In stole we leverage ontologies for describing domain knowledge and providing semantic information integration among data in order to support historians’ research. The documents stored in stole are regarded as a valuable source of information for historical research since through the study of these texts it is possible to trace the course of Italian history and often to find out some unexplored but useful aspects about a particular event or person. Currently, these historical sources