Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Prominence Information in the Real-Time Comprehension of Transitive Constructions: A Cross-Linguistic Approach

Approaches to language processing have traditionally been formulated with reference to general cognitive concepts (e.g. working memory limitations) or have based their representational assumptions on concepts from generative linguistic theory (e.g. structure determines interpretation). Thus, many well-established generalisations about language that have emerged from cross-linguistic/typological research have not as yet had a major influence in shaping ideas about online processing. Here, we examine the viability of using typologically motivated concepts to account for phenomena in online language comprehension. In particular, we focus on the comprehension of simple transitive sentences (i.e. sentences involving two arguments/event participants) and cross-linguistic similarities and differences in how they are processed. We argue that incremental argument interpretation in these structures is best explained with reference to a range of cross-linguistically motivated, hierarchically ordered information types termed ‘prominence scales’ (e.g. animacy, definiteness/specificity, case marking and linear order). We show that the assumption of prominence-based argument processing can capture a wide range of recent neurocognitive findings, as well as deriving well-known behavioural results.
Assessment of Ground Reaction Force Patterns for Human Gait Malfunction Identiication

We perform a medical computing project based on gait patterns collected from patients in an Austrian gait analysis laboratory by using two ground reaction force measurement platforms. The project aims at an assessment of gait that is useful, on the one hand, as a support of diagnosis and therapy considerations. On the other hand, it is intended to give clues to a model of gait, to help developing bio-feedback systems to train patients, and to nd eeects of multiple diseases and still active compensation. As a major beneet, the proposed approach is exclusively based on observable data. Hence, we do not face the tremendous eeort to deene a biomechanical model of gait where parameters cannot be measured precisely. In this paper we report on identiication of gait malfunction with respect to the location of ailment. The employed classiication approach is learning vector quantization which proved to be highly robust in the results provided.
Population Dynamics of Wolves and Coyotes at Yellowstone National Park: Modeling Interference Competition with an Infectious Disease

Gray wolves were reintroduced to Yellowstone National Park (YNP) in 1995. The population initially flourished, but since 2003 the population has experience significant reductions due to factors that may include disease-induced mortality, illegal hunting, park control pro- grams, vehicle induced deaths and intra-species aggression. Despite facing similar conditions, and interference competition with the wolves, the coyote population at YNP has persisted. In this paper we introduce an epidemiological framework that incorporates natural, human-caused and disease-induced mortality as well as interference competition between two species of predators. The outcomes generated by this theoretical framework are used to explore the impact of competition and death-induced mechanisms on predators coexistence. It is the hope that these results on the competitive dynamics of carnivores in Yellowstone National Park will provide park management insights that result in policies that keep the reintroduction of wolves successful.
Geometry of the faithfulness assumption in causal inference

Many algorithms for inferring causality rely heavily on the faithfulness assumption. The main justification for imposing this assumption is that the set of unfaithful distributions has Lebesgue measure zero, since it can be seen as a collection of hypersurfaces in a hypercube. However, due to sampling error the faithfulness condition alone is not sufficient for statistical estimation, and strong-faithfulness has been proposed and assumed to achieve uniform or high-dimensional consistency. In contrast to the plain faithfulness assumption, the set of distributions that is not strong-faithful has nonzero Lebesgue measure and in fact, can be surprisingly large as we show in this paper. We study the strong-faithfulness condition from a geometric and combinatorial point of view and give upper and lower bounds on the Lebesgue measure of strong-faithful distributions for various classes of directed acyclic graphs. Our results imply fundamental limitations for the PC-algorithm and potentially also for other algorithms based on partial correlation testing in the Gaussian case.
Advocating Noise as an Agent for Ultra-Low Energy Computing: Probabilistic Complementary Metal–Oxide–Semiconductor Devices and Their Characteristics

Noise immunity and low-energy computing have become limiting factors in the semiconductor roadmap as transistor feature sizes shrink. The subject of our study is the probabilistic switch, implemented in the complementary metal–oxide–semiconductor (CMOS) domain, referred to as a probabilistic CMOS (PCMOS) switch, whose behavior is rendered probabilistic by noise. In conducting this study, we are motivated by the possibility of using such probabilistic switches to realize ultra-low energy computing. Based on PCMOS switches realized using 0.5 and 0.25 µm processes, we present detailed analytical models, subsequently verified through HSpice simulations. We consider the thermal noise and power supply noise as our sources for probabilistic behavior. Through one interesting aspect of the study, we characterize the effects of the noise sampling frequency and the output sampling frequency on probabilistic behavior. Finally, we briefly outline the opportunity that such probabilistic switches offer to ultra low-energy computing through the concept of a probabilistic system-on-a-chip (PSoC) architecture (that is based on PCMOS switches); such architectures can achieve significant energy savings and performance improvements at the application level.
List of Publications Faculty Opponent

This thesis is based on the following publications, which are referred to in the text by their Roman numerals. " Silhouette " scores for assessment of SNP genotype clusters. BMC Genom-ics.resolution, high-throughput SNP mapping in Drosophila melanogaster. Positional cloning by fast-track SNP-mapping in Droso-phila melanogaster. Dried reagents for multiplex genotyping by tag-array minisequencing to be used in micro-fluidic devices. Performance of microarray and liquid based capture methods for target enrichment for massively parallel sequencing and SNP discovery. Submitted manuscript. Reprints were made with permission from the respective publishers. Multiplex padlock targeted sequencing reveals human hypermutable CpG variations. Genome Research. Abbreviations bp Base pair CNV Copy number variant dNTP Deoxynucleotide triphosphates ddNTP Dideoxynucleotide triphosphates ExoI Exonuclease I GA Genome Analyzer InDel Insertion-deletion polymorphism kb Kilobase pair Mb Megabase pair MIP Molecular inversion probe MPS Massively parallel sequencing nt Nucleotide PCR Polymerase chain reaction RFLP Restriction fragment length polymorphisms SAP Shrimp alkaline phosphatase SBE Single base primer extension SBS Sequencing by synthesis SNP Single nucleotide polymorphism µ-TAS Micro-total analysis systems 13 Introduction
Building a Patient Oriented Treatment Decision System for Liver Cancer

The aim of this study is to establish a decision system to assist liver cancer patients to choose treatments, and explore whether patients' treatment preferences were concordant with their physicians' recommendations. We analyzed the patients' considerations involved in the evaluation of treatment and combined these considerations with Barcelona Clinic Liver Cancer (BCLC) clinical guidelines to design the surveys and adopted Multi-Attribute Utility Theory (MAUT) to establish a decision model for treatment selections. Without intervening the clinical processes, we interviewed 53 liver cancer patients(and their families) using this decision system to choose preferred treatments. The results showed: (1) There was a difference between liver cancer patients' treatment preferences and their physicians' recommendations, (2) Liver cancer patients with advanced stage, still prefer active treatment, (3) The most concerns on treatments were cure rate, survival rate and self-care ability. Instead of only following physicians' recommendations, this system assist liver cancer patients to evaluate treatment using various factors(considerations) including physiological, psychological and social support. For oncologists, we suggest the psychological processes of patients are taken into consideration, and this study provide an example of framework on cancer care interventions and expect to improve the care of liver cancer population in the future.
Evaluation of the performance of a p53 sequencing microarray chip using 140 previously sequenced bladder tumor samples.

BACKGROUND Testing for mutations of the TP53 gene in tumors is a valuable predictor for disease outcome in certain cancers, but the time and cost of conventional sequencing limit its use. The present study compares traditional sequencing with the much faster microarray sequencing on a commercially available chip and describes a method to increase the specificity of the chip. METHODS DNA from 140 human bladder tumors was extracted and subjected to a multiplex-PCR before loading onto the p53 GeneChip from Affymetrix. The same samples were previously sequenced by manual dideoxy sequencing. In addition, two cell lines with two different homozygous mutations at the TP53 gene locus were analyzed. RESULTS Of 1464 gene chip positions, each of which corresponded to an analyzed nucleotide in the sequence, 251 had background signals that were not attributable to mutations, causing the specificity of mutation calling without mathematical correction to be low. This problem was solved by regarding each chip position as a separate entity with its own noise and threshold characteristics. The use of background plus 2 SD as the cutoff improved the specificity from 0.34 to 0.86 at the cost of a reduced sensitivity, from 0.92 to 0.84, leading to a much better concordance (92%) with results obtained by traditional sequencing. The chip method detected as little as 1% mutated DNA. CONCLUSIONS Microarray-based sequencing is a novel option to assess TP53 mutations, representing a fast and inexpensive method compared with conventional sequencing.
Hip-Hop to Deep House : Navigating the Music Graph using Decentralized Search Group 37 :

Music is considered by many an integral part of the human experience. Indeed, most cultures and subcultures around the world are associated with specific musical tastes. In this project we are interested in exploring the properties of music graphs constructed using attributes collected from several music datasets. In particular the problem we are trying to explore is something most of us have faced: how do we pick the next song to listen to. We examine how we can generate music graphs, what the important parameters are, and whether these music graphs are navigable using decentralized search. Ultimately we hope to gain some insight that can help us build interesting applications like a system that can smoothly interpolate playlists between pairs or lists of user defined songs.
Random network peristalsis in Physarum polycephalum organizes fluid flows across an individual

Individuals can function as integrated organisms only when information and resources are shared across a body. Signals and substrates are commonly moved using fluids, often channeled through a network of tubes. Peristalsis is one mechanism for fluid transport and is caused by a wave of cross-sectional contractions along a tube. We extend the concept of peristalsis from the canonical case of one tube to a random network. Transport is maximized within the network when the wavelength of the peristaltic wave is of the order of the size of the network. The slime mold Physarum polycephalum grows as a random network of tubes, and our experiments confirm peristalsis is used by the slime mold to drive internal cytoplasmic flows. Comparisons of theoretically generated contraction patterns with the patterns exhibited by individuals of P. polycephalum demonstrate that individuals maximize internal flows by adapting patterns of contraction to size, thus optimizing transport throughout an organism. This control of fluid flow may be the key to coordinating growth and behavior, including the dynamic changes in network architecture seen over time in an individual.
PFP/ESG: automated protein function prediction servers enhanced with Gene Ontology visualization tool

UNLABELLED Protein function prediction (PFP) is an automated function prediction method that predicts Gene Ontology (GO) annotations for a protein sequence using distantly related sequences and contextual associations of GO terms. Extended similarity group (ESG) is another GO prediction algorithm that makes predictions based on iterative sequence database searches. Here, we provide interactive web servers for the PFP and ESG algorithms that are equipped with an effective visualization of the GO predictions in a hierarchical topology. AVAILABILITY PFP/ESG servers are freely available at http://kiharalab.org/web/pfp.php and http://kiharalab.org/web/esg.php, or access both at http://kiharalab.org/pfp_esg.php. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
A Multimodal Brain-arm Interface for Operation of Complex Robotic Systems and Upper Limb Motor Recovery

This work introduces the architecture of a novel brain-arm haptic interface usable to improve the operation of complex robotic systems, or to deliver a fine rehabilitation therapy to the human upper limb. The proposed control scheme combines different approaches from the areas of robotics, neuroscience and human-machine interaction in order to overcome the limitations of each single field. Via the adaptive Brain Reading Interface (aBRI) user movements are anticipated by classification of surface electroencephalographic data in a millisecond range. This information is afterwards integrated into the control strategy of a wearable exoskeleton in order to finely modulate its impedance and therefore to comply with the motion preparation of the user. Results showing the efficacy of the proposed control approach are presented for the single joint case.
An Access Control Framework for Semi-trusted Storage Using Attribute-Based Encryption with Short Ciphertext and Mediated Revocation

Cryptographic access control (CAC) is an enforcement mechanism that provides authorization in the absence of a fully trusted reference monitor, which is the case in outsourced storage systems. Attribute-based encryption can be used to represent permissions in CAC similar to traditional access control, but several limitations regarding its performance and revocation process were observed. Several schemes addressed the computational overhead from revocation but did not provide solutions for storage overhead issues. Other schemes focused on storage consumption but not on revocation. To address both issues of storage and revocation overhead, we constructed Mediated Constant Cipher text-Policy ABE (MC-CP-ABE) and a mediated revocation protocol. We implemented this and three other CP-ABE schemes together with the protocol to build an access control framework for facilitating file transfer in semi-trusted third-party servers. We evaluated the performance of our framework using these four schemes and the trade-offs in using a mediated architecture for fine-grained revocation. We show through experiments that our solution maintains a constant-length numeric ABE cipher text and reduces the time required to perform selective and partial revocation.
1.5°C accurate CMOS temperature sensor with a single point trim at 85°C

This paper presents a temperature sensor with an accuracy of 1.5°C. The paper analyzes inaccuracy of the existing temperature sensors and outlines the techinques to overcome them. The sensor is based on a CMOS current reference which is almost constant over process/corner and voltage variation. Most of the techniques known today for generating a process and voltage independent current source have very stringent constraints on sizing of the transistors. The current source proposed in the paper relaxes such constraints thus easing the portability across various technology nodes. The sensor designed in TSMC 28 nm CMOS process offers the accuracy of 1.5°C over a temperature range of −40°C to 125°C with a single point trim at 85°C. The sensor consumes a power of 90 μW of power when operating on 1.8 V supply.
Support-plane estimation for floor detection to understand regions' spatial organization

Plane fitting plays an important role in image processing and computer vision. It is challenging because of the outliers that do not follow the plane pattern. In this work, we address the problem of support-plane fitting for room floor detection from point clouds that are generated from depth image. Based on the geometric layout of data, an optimization problem is derived to estimate the support-plane. Algorithms are also proposed to deal with data noise. The floor detection is achieved by support-plane fitting, and is employed as a reference to analyze the spatial organization of room scene. A projection method is presented to form the organization map. Experiments demonstrate the proposed method is more robust, and it achieves remarkable performance in understanding the spatial organization.
Compressive Sensing Optimization for Signal Ensembles in WSNs

Compressive sensing (CS) is a new approach to simultaneous sensing and compressing that is highly promising for fully distributed compression in wireless sensor networks (WSNs). While a wide investigation has been performed about theory and practice of CS for individual signals, real and practical cases, in general, involve multiple signals, extending the problem of compression from 1-D single-sensor to 2-D multiple-sensors data. In this paper the two most prominent frameworks on sparsity and compressibility of multidimensional signals and signal ensembles, Distributed compressed sensing (DCS) and Kronecker compressive sensing (KCS), are investigated. In this paper we compare these two frameworks against a common set of artificial signals properly built to embody the main characteristics of natural signals. We further investigate how, in a real deployment, DCS can be used to reduce the power consumption and to prolong lifetime. In particular an extensive analysis is performed using real commercial off-the-shelf (COTS) hardware evaluating how different kind of compression matrices can affect the jointly reconstruction, trying to achieve the better tradeoff between quality and energy expenditure.
Species specificity and augmentation of responses to class II major histocompatibility complex molecules in human CD4 transgenic mice

Murine T cell responses to human class II major histocompatibility complex (MHC) molecules were shown to be a minimum of 20-70-fold lower than responses to allogeneic molecules. Transgenic mice expressing slightly below normal (75-95%) or very high (250-380%) cell surface levels of human CD4 were utilized to determine whether this was due to a species-specific interaction between murine CD4 and class II molecules. Human CD4 was shown to function in signal transduction events in murine T cells based on the ability of anti-human CD4 antibody to synergize with suboptimal doses of anti-murine CD3 antibody in stimulating T cell proliferation. In mice expressing lower levels of human CD4, T cell responses to human class II molecules were enhanced up to threefold, whereas allogeneic responses were unaltered. In mice expressing high levels of human CD4, responses to human class II molecules were enhanced at least 10-fold, whereas allogeneic responses were between one and three times the level of normal responses. The relatively greater enhancement of the response to human class II molecules in both lines argues for a preferential interaction between human CD4 and human class II molecules. In mice expressing lower levels of human CD4, responses to human class II molecules were blocked by antibodies to CD4 of either species, indicating participation by both molecules. In mice expressing high levels of human CD4, responses to both human and murine class II molecules were almost completely blocked with anti-human CD4 antibody, whereas anti-murine CD4 antibody had no effect. However, anti-murine CD4 continued to synergize with anti-CD3 in stimulating T cell proliferation in these mice. Thus, overexpression of human CD4 selectively impaired the ability of murine CD4 to assist in the process of antigen recognition. The ability of human CD4 to support a strong allogeneic response under these conditions indicates that this molecule can interact with murine class II molecules to a significant extent. Despite the fact that human CD4 appeared to be the only functional coreceptor in these mice, responses to human class II molecules were still much lower than those to murine class II alloantigens. This indicates that species-specific interactions between class II molecules and CD4 expressed on peripheral T cells are not sufficient to account for the low xenogeneic response and that intrinsic differences in T cell receptor structures or the need for species specificity in the interaction between CD4 and class II molecules during positive selection are also important.
Estimating the Eects of Adverse Selection in Used Car Markets

For tracing two scanning paths with a single laser beam, a laser beam scanning system comprises a laser beam source radiating a laser beam, a collimator lens unit, a PLZT element for rotating the polarized direction of the laser beam over 90 degrees, a polygonal mirror causing the laser beam to sweep in a lateral direction, a scanning lens unit for regulating the liner velocity of sweeping motion, a polarization beam splitter transmitting or deflecting the laser beam toward a first destination depending upon the polarized direction and a reflective mirror directing the laser beam transmitted from the beam splitter to a second destination, and the PLZT element is applied with a biasing voltage at every second scanning motion for the rotation of the polarized direction, so that the laser beam rapidly changes the scanning path.
Proactive predictions to handle issues in recommendations

In today's online world users are suffering with the problem of information overload. To handle this problem, recommender systems assist users in giving required information by filtering out irrelevant information. So, most of the recommender systems mainly strive to achieve only accuracy in recommendations but this is not just what users want. Users require more coverage and diversity in recommendations mainly in the case of news domain which is highly dynamic in nature. To handle the issues of coverage and diversity we have worked on proactive predictions of those user interests which could not have been predicted by just user behavior analysis. User interest has been expanded on the basis of Concepts, sub concepts, entities, properties and relationships stored in our designed news domain ontology. Ontology design is based on news industry standards and careful study of the domain. It is also semantically annotated with context sensitive knowledge, extracted from external knowledge source DBpedia.