Miracle-dz/UniFAR-FTUs huggingface dataset:
RECURRENCE QUANTIFICATION ANALYSIS FEATURES FOR AUDITORY SCENE CLASSIFICATION

This extended abstract describes our submission for the scene classification task of the IEEE AASP Challenge for Detection and Classification of Acoustic Scenes and Events. We explore the use of Recurrence Quantification Analysis (RQA) features for this task. These features are computed over a thresholded similarity matrix computed from windows of MFCC features. Added to traditional MFCC statistics, they improve accuracy when using a standard SVM classifier.
Mixtures of Deterministic-Probabilistic Networks and their AND/OR Search Space

The paper introduces mixed networks, a new framework for expressing and reasoning with probabilistic and deterministic information. The framework combines belief networks with constraint networks, defining the semantics and graphical representation. We also introduce the AND/OR search space for graphical models, and develop a new linear space search algorithm. This provides the basis for understanding the benefits of processing the constraint information separately, resulting in the pruning of the search space. When the constraint part is tractable or has a small number of solutions, using the mixed representation can be exponentially more effective than using pure belief networks which model constraints as conditional probability tables.
CDX 2 Polymorphisms , RNA Expression , and Risk of Colorectal Cancer

In adult mammals, CDX2 acts as a transcription factor and is expressed in intestinal epithelial cells. Down-regulation of CDX2 is frequently observed in colorectal cancer, suggesting its loss may cause dedifferentiation of gastrointestinal epithelial cells. However, it is not clear whether inherited variants of CDX2 are associated with risk of colorectal cancer. Using epidemiologic data and tumors from a populationbased case-control study in Israel, we identified novel single nucleotide polymorphisms (SNPs) by resequencing 35 cases, compared genotype and haplotype frequencies in 455 matched pairs, and characterized the tumor characteristics of all 455 cases by microsatellite instability analysis, in addition to a partially overlapping set of 201 frozen tumors with expression profiling data (82/201) from the same study. Nine polymorphisms were identified in the 35 cases, and none of the SNPs or haplotypes were associated with risk of colorectal cancer in the 455 matched pairs. These variants were not associated with CDX2 expression in the 83 subjects with expression data. We evaluated subject and tumor characteristics in the 201 subjects with CDX2 tumor expression data. Reduced CDX2 expression was associated with tumor location (right sided), poor differentiation, high microsatellite instability status, and a positive first-degree family history. We conclude that it is unlikely that common CDX2 variants account for a measurable fraction of susceptibility to colorectal cancer in this population. However, CDX2 expression levels were strongly associated with microsatellite instability and tumor location in the gastrointestinal tract, consistent with a possible role in the specification of gastrointestinal epithelial cell fate in humans. (Cancer Res 2005; 65(13): 5488-92)
Interference Mitigation in Turbo-Coded OFDM Systems using Robust Statistics

A robust cost function for log likelihood ratio (LLR) computation is proposed for turbo coded OFDM systems in the presence of narrowband interference (NBI) and co-channel interference (CCI). In systems employing standards such as the IEEE 802.16d/e, CCI behaves like NBI with the number of affected subcarriers ranging from 10% to 30%. The combined effect of NBI and thermal Gaussian noise leads to a contaminated Gaussian (CG) noise probability density function (pdf). Simulation results indicate that the proposed method performs very close to the optimal method where the optimal method computes the LLR using the CG pdf. While the optimal method requires knowledge of the NBI power, the fraction of subcarriers contaminated by NBI and the NBI pdf, the proposed method does not require knowledge of these parameters.
Lexical knowledge representation with contextonyms

Inter-word associations like stagger - drunken, or intra-word sense divisions (e.g. write a diary vs. write an article) are difficult to compile using a traditional lexicographic approach. As an alternative, we present a model that reflects this kind of subtle lexical knowledge. Based on the minimal sense of a word (clique), the model (1) selects contextually related words (contexonyms) and (2) classifies them in a multi-dimensional semantic space. Trained on very large corpora, the model provides relevant, organized contexonyms that reflect the fine-grained connotations and contextual usage of the target word, as well as the distinct senses of homonyms and polysemous words. Further study on the neighbor effect showed that the model can handle the data sparseness problem.
Low-cost digital implementation of proportional-resonant current controllers for PV inverter applications using delta operator

The performances of the P+Resonant controller in case of current control for a single phase grid connected inverter have been proved to be superior to the PI controller, since it is able to remove the phase error of the control at the fundamental frequency of the grid. It offers also the possibility of selective harmonic compensation. However, in case of digital implementation on a low-cost fixed-point DSP, the limited computational power and the limited numerical representation precision can restrict the utilization of it. The present paper proposes a different way of digital implementation of the P+Resonant controller with selective harmonic compensation on a low-cost fixed-point DSP. The resonant part of the P+R has been implemented as a second order filter based on delta operator. The current controller, together with harmonic compensation for the 3/sup rd/, 5/sup th/, and 7/sup th/ harmonics has been successfully tested in practice with a 1.5 KW PV inverter, achieving a 1.2% total harmonic distortion (THD) of the grid current.
Automata and Complexity in Multiple-Quantifier Sentence Verification

We study possible algorithmic models for the picture verification task with double-quantified sentences of the form ‘Some X are connected with every Y’. We show that the ordering of quantifiers, either Some ◦ Every or Every ◦ Some, influences the cognitive difficulty of the task. We discuss how computational modeling can account for the varying cognitive load in quantifier verification.
The robust tagging of unrestricted text: the BNC experience

The production of annotated machine-readable corpora has been a central activity of the UCREL team at Lancaster University, led by Geoffrey Leech, since the early 1980s. This commenced with the annotation of the LoB (Lancaster-oslo/Bergen) corpus with part-ofspeech information over the period l98l-84 (Garside, Leech and Sampson 1987). The work has continued with corpora which introduced syntactic annotation at the constituent level (Leech and Garside l99l ) and at the level of anaphora (Fligelstone 1992; Garside 1993), with corpora marked with word sense and key semantic relationship information (Wilson and Rayson 1993), and with aligned multi-lingual corpora (McEnery et al 1994). Most recently it has resulted in the development of the British National Corpus (BNC), a corpus of one hundred million words of varied written and spoken texts annotated with part-of-speech information (Leech 1993). The BNC was constructed by a team of publishers (Oxford University Press, I-ongman, and Chambers Harrap), academic institutions (Lancaster University and Oxford University Computing Senrices) and the British Library, over the period l99l-94; Lancaster was responsible for the grammatical tagging of the corpus. The various types of annotation listed above have always been inserted in the text by a mixture of automatic and manual procedures, generally making use of some form of probabilistic technique to assign an analysis to a text at the appropriate linguistic level, and this can then be manually post-edited if neressary to achieve the desired level of accuracy. Because large quantities of text are involved, the post-editing will always involve some assistance by the computer to minimize the time taken to implement the analyst's decision, and to check the validity of each change. The results of the manual correction
Identifying collaboration patterns in collaborative telelearning scenarios

Project DoCTA focuses on understanding interaction in a set of collaborative telelearning scenarios aimed at teacher training. Rooted in a sociocultural perspective, two scenarios were studied from thirteen views including ethnographic flavoured studies focused on understanding work organisation, usability studies of groupware systems, evaluations of computer logs, and questionnaire studies. These exploratory studies provide us with insight into the processes of collaboration enabling us to identify collaboration patterns and further our understanding of how geographically distributed instructors, students and other learning facilitators organise their learning and work. In this paper introduce four collaboration patterns we have identified: adaptation, coordinated desynchronization, informal language, and constructive commenting.
Supervised categorization for habitual versus episodic sentences

Thesis (M.S.)--Georgetown University, 2009. ; Includes bibliographical references. In natural language, there are commonly used sentence constructions which express a form of genericity, a general property which summarizes groups of particular episodes or behavior - such sentences are referred to as habitual sentences. The availability of such constructions in human discourse serves a specific communication function which is to provide a mechanism to convey knowledge on common or regular behavior that defines and characterizes the environment we live in. This can be contrasted with episodic sentences which express some degree of detail surrounding irregular events in time and serve more of a reporting purpose in human communication. Given the different linguistic function of habitual sentences and episodic sentences and the different nature of information communicated by them, it can be argued that there is significance in a repeatable method, based on internal and possibly external sentence characteristics, which can make a distinction between these two sentence categories where applicable. ; This research is conducted with the primary goal of category disambiguation in situations where the verbal predicate of a sentence is known to be used in both a habitual and an episodic context; sentences for which the verbal predicate provides explicit categorization are not considered to prevent undue skew on the results. A secondary objective of the research effort is to attempt to statistically study and report the individual and collective impact of lexical and syntactic features which are known to influence the categorization of a sentence as either habitual or episodic. I have focused on the influence of syntactic and lexical features such as tense, aspect, noun phrase features, temporal modifiers, specific adverb modifiers, and specific verb auxiliaries on genericity. Another secondary objective is to attempt to build and evaluate a supervised decision-tree based machine learning classifier that disambiguates between habitual and episodic sentences using selected syntactic and lexical features and a previously categorized set of sentences for the purpose of training and evaluating the classifier. Using such features I have created a machine classifier that provides 86.3% precision in disambiguating habitual and episodic sentences. This compares against a baseline of 73.1% precision where every sentence is blindly categorized as belonging to the more commonly occurring episodic category. In order to support these objectives, a representative corpus sample was hand-annotated to provide a human perspective on an appropriate category per sentence. ; The final results support a claim that a machine based classifier trained on the features discussed can out-perform the baseline model. Implications for successful markup of habitual sentences include application in building knowledge-bases that describe general world behavior. Successful markup of episodic sentences can find use in more sensitive information extraction systems.
BMVC test, an improved fluorescence assay for detection of malignant pleural effusions

The diagnosis of malignant pleural effusions is an important issue in the management of malignancy patients. Generally, cytologic examination is a routine diagnostic technique. However, morphological interpretation of cytology is sometimes inconclusive. Here an ancillary method named BMVC test is developed for rapid detection of malignant pleural effusion to improve the diagnostic accuracy at low cost. A simple assay kit is designed to collect living cells from clinical pleural effusion and a fluorescence probe, 3,6‐Bis(1‐methyl‐4‐vinylpyridinium) carbazole diiodide (BMVC), is used to illuminate malignant cells. The fluorescence intensity is quantitatively analyzed by ImageJ program. This method yields digital numbers for the test results without any grey zone or ambiguities in the current cytology tests due to intra‐observer and inter‐observer variability. Comparing with results from double‐blind cytologic examination, this simple test gives a good discrimination between malignant and benign specimens with sensitivity of 89.4% (42/47) and specificity of 93.3% (56/60) for diagnosis of malignant pleural effusion. BMVC test provides accurate results in a short time period, and the digital output could assist cytologic examination to become more objective and clear‐cut. This is a convenient ancillary tool for detection of malignant pleural effusions.
Verification architectures for complex real-time systems

In the analysis of complex real-time systems, several aspects have to be covered, e.g., behaviour that conforms to communication protocols, rich data structures, and timing constraints such that the system reacts timely to external events. In practise it turns out that to handle such systems engineers fall back on combinations of techniques. An example is the Unified Modelling Language, combining multiple graphical notations for different views of a design. Similarly, in the world of formal analysis there has been a lot of work on integrating specification techniques to condense advantages of single formalisms into combined formalisms. However, a major problem remains: these integrated techniques are designed for heterogeneous systems, and when formally verifying those systems, one has to cope with their inherent complexity. To solve this problem, we propose to verify global properties by combining local analyses using abstract, behavioural protocols. This idea originates from previous case studies, where a specification of the European Train Control System is decomposed according to a behavioural protocol. The protocol splits the system runs into several phases with local real-time properties which hold during these phases. After showing the correctness of a desired global safety property, this property is also guaranteed by all instances of the protocol that fit to the structure of the protocol and satisfy all local properties. We generalise and formalise this approach in a uniform framework for combined real-time formalisms. As several combined specification formalisms are based on Communicating Sequential Processes (CSP), we introduce a CSP extension to specify system protocols with data and unknown processes to capture a large class of systems. On the unknown processes, local real-time assumptions are specified by formulae in an arbitrary logic. By this means, a decomposition of a global property into local assumptions on protocol phases is defined. We call these protocols with local real-time assumptions Verification Architectures (VA). To establish safety properties on VAs, we embed the CSP extension into a temporal dynamic logic and introduce a sound sequent-style proof calculus. We prove that all models that structurally refine the CSP part of a VA and that satisfy the real-time assumptions inherit the desired properties. The instantiation of VAs is exemplified with a combined formalism, called CSP-OZDC. The real-time logic Duration Calculus is used to specify assumptions on protocol phases. We introduce a syntactical proof rule to show efficiently that a CSP-OZ-DC specification structurally refines a VA protocol. The correctness of the assumptions is shown by using an existing model checking approach. Furthermore, by presenting a case study from the European Train Control System, we demonstrate the verification of a complex real-time system with the VA approach.
Neuroimaging H.M.: A 10‐year follow‐up examination

In 1997, Corkin et al. described the anatomical boundaries of the amnesic patient H.M. 's surgical resection, based on a comprehensive analysis of magnetic resonance imaging (MRI) scans collected in 1992 and 1993 (Corkin et al. (1997) J Neurosci 17:3964–3979). We subsequently scanned H.M. on several occasions, employing more advanced data acquisition and analysis methods, and now describe additional details about his brain anatomy and pathology. This account combines results from high‐resolution T1‐weighted scans, which provide measures of cortical and subcortical morphometry, diffusion tensor images, which provide quantitative information about white matter microstructure and the anatomy of major fasciculi, and T2‐weighted images, which highlight damage to deep white matter. We applied new MRI analysis techniques to these scans to assess the integrity of areas throughout H.M. 's brain. We documented a number of new changes, including cortical thinning, atrophy of deep gray matter structures, and a large volume of abnormal white matter and deep gray matter signal. Most of these alterations were not apparent in his prior scans, suggesting that they are of recent origin. Advanced age and hypertension likely contributed to these new findings. © 2006 Wiley‐Liss, Inc.
Multi-object filtering from image sequence without detection

Almost every single-view visual multi-target tracking method presented in the literature includes a detection routine that maps the image data to point measurements relevant to the target states. These measurements are commonly further processed by a filter to estimate the number of targets and their states. This paper presents a novel visual tracking technique based on a multi-object filtering algorithm that operates directly on the image observations without the need for any detection. Experimental results on tracking sport players show that our proposed method can automatically track numerous interacting targets and quickly finds players entering or leaving the scene.
The Value of Privacy: Strategic Data Subjects, Incentive Mechanisms and Fundamental Limits

We study the value of data privacy in a game-theoretic model of trading private data, where a data collector purchases private data from strategic data subjects (individuals) through an incentive mechanism. The private data of each individual represents her knowledge about an underlying state, which is the information that the data collector desires to learn. Different from most of the existing work on privacy-aware surveys, our model does not assume the data collector to be trustworthy. Then, an individual takes full control of its own data privacy and reports only a privacy-preserving version of her data. In this paper, the value of ε units of privacy is measured by the minimum payment of all nonnegative payment mechanisms, under which an individual's best response at a Nash equilibrium is to report the data with a privacy level of ε. The higher ε is, the less private the reported data is. We derive lower and upper bounds on the value of privacy which are asymptotically tight as the number of data subjects becomes large. Specifically, the lower bound assures that it is impossible to use less amount of payment to buy ε units of privacy, and the upper bound is given by an achievable payment mechanism that we designed. Based on these fundamental limits, we further derive lower and upper bounds on the minimum total payment for the data collector to achieve a given learning accuracy target, and show that the total payment of the designed mechanism is at most one individual's payment away from the minimum.
Detection of Trypanosoma cruzi in blood specimens of chronic chagasic patients by polymerase chain reaction amplification of kinetoplast minicircle DNA: comparison with serology and xenodiagnosis

A panel of 114 blood samples from chronic chagasic patients and nonchagasic patients was screened for Trypanosoma cruzi by xenodiagnostic, serologic, and polymerase chain reaction (PCR) amplification tests. Blood samples were preserved in a guanidine-EDTA buffer, and total blood DNA was isolated after chemical nuclease cleavage with 1,10-phenanthroline-copper ion and used as a template for PCR amplification of the conserved and variable regions of T. cruzi minicircle molecules. The PCR products were screened by Southern blot hybridization with a digoxigenin-labeled oligonucleotide probe specific for the conserved region of the minicircle. The method showed a sensitivity of 100% compared with the serologic test. In addition, all of the serology-positive, xenodiagnosis-negative samples were positive by PCR. This demonstrates that PCR amplification of T. cruzi kinetoplast minicircle DNA could replace xenodiagnosis for evaluation of parasitemia in chronic chagasic patients and could serve as a complement for serologic testing in the screening of blood bank donors.
Video browsing for course-on-demand in distance learning

The rapid evolution of communication technologies, contributed by the advanced data networks, which enable the integration of multimedia information processing and have greatly impacted our approach to distance learning. Several new multimedia features are developed and reported in this paper. These features allow students to browse the lecture contents directly on digital video sequences while also providing access to multimedia information like lecture captions, databases or handbooks with additional information or another video sequence to explain the current contents. Using these multimedia features, students can learn the course more effectively as compared to learning from conventional analog media in the distance learning environments.
GH Mediates Exercise-Dependent Activation of SVZ Neural Precursor Cells in Aged Mice

Here we demonstrate, both in vivo and in vitro, that growth hormone (GH) mediates precursor cell activation in the subventricular zone (SVZ) of the aged (12-month-old) brain following exercise, and that GH signaling stimulates precursor activation to a similar extent to exercise. Our results reveal that both addition of GH in culture and direct intracerebroventricular infusion of GH stimulate neural precursor cells in the aged brain. In contrast, no increase in neurosphere numbers was observed in GH receptor null animals following exercise. Continuous infusion of a GH antagonist into the lateral ventricle of wild-type animals completely abolished the exercise-induced increase in neural precursor cell number. Given that the aged brain does not recover well after injury, we investigated the direct effect of exercise and GH on neural precursor cell activation following irradiation. This revealed that physical exercise as well as infusion of GH promoted repopulation of neural precursor cells in irradiated aged animals. Conversely, infusion of a GH antagonist during exercise prevented recovery of precursor cells in the SVZ following irradiation.