Miracle-dz/UniFAR-FTUs huggingface dataset:
Enabling Global Price Comparison through Semantic Integration of Web Data

"Sell and shop globally" has been seen as a potential benefit of electronic business. A step toward realising this benefit is to know how things are selling worldwide. Global price comparison services would address this need. But there have not been many such services. We use a global price dispersion case study to illustrate the value of such services. Then we identify technology challenges, including semantic heterogeneity, in providing such services. We propose a mediation architecture to address the semantic heterogeneity problem, and demonstrate its feasibility with a prototype that enables global price comparison using web sources in several countries.
The Fusarium graminearum Genome Reveals More Secondary Metabolite Gene Clusters and Hints of Horizontal Gene Transfer

Fungal secondary metabolite biosynthesis genes are of major interest due to the pharmacological properties of their products (like mycotoxins and antibiotics). The genome of the plant pathogenic fungus Fusarium graminearum codes for a large number of candidate enzymes involved in secondary metabolite biosynthesis. However, the chemical nature of most enzymatic products of proteins encoded by putative secondary metabolism biosynthetic genes is largely unknown. Based on our analysis we present 67 gene clusters with significant enrichment of predicted secondary metabolism related enzymatic functions. 20 gene clusters with unknown metabolites exhibit strong gene expression correlation in planta and presumably play a role in virulence. Furthermore, the identification of conserved and over-represented putative transcription factor binding sites serves as additional evidence for cluster co-regulation. Orthologous cluster search provided insight into the evolution of secondary metabolism clusters. Some clusters are characteristic for the Fusarium phylum while others show evidence of horizontal gene transfer as orthologs can be found in representatives of the Botrytis or Cochliobolus lineage. The presented candidate clusters provide valuable targets for experimental examination.
A language for specifying type contracts in erlang and its interaction with success typings

We propose a small extension of the Erlang language that allows programmers to specify contracts with type information at the level of individual functions. Such contracts are optional and they document the intended uses of functions. Contracts allow automatic documentation tools such as Edoc to generate better documentation and defect detection tools such as Dialyzer to detect more type clashes. Since the Erlang/OTP system already contains components which perform automatic type inference of success typings, we also describe how contracts interact with success typings and can often provide some key information to the inference process.
Efficient Model Learning Methods for Actor–Critic Control

We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm.
Face Recognition using Hough Peaks extracted from the significant blocks of the Gradient Image

This paper proposes a new technique for automatic face recognition using integrated peaks of the Hough transformed significant blocks of the binary gradient image. In this approach firstly the gradient of an image is calculated and a threshold is set to obtain a binary gradient image, which is less sensitive to noise and illumination changes. Secondly, significant blocks are extracted from the absolute gradient image, to extract pertinent information with the idea of dimension reduction. Finally the best fitted Hough peaks are extracted from the Hough transformed significant blocks for efficient face recognition. Then these Hough peaks are concatenated together, which are used as feature in classification process. The efficiency of the proposed method is demonstrated by the experiment on 1100 images from the FRAV2D face database, 2200 images from the FERET database, where the images vary in pose, expression, illumination and scale and 400 images from the ORL face database, where the images slightly vary in pose. Our method has shown 93.3%, 88.5% and 99% recognition accuracy for the FRAV2D, FERET and the ORL database respectively.
Preoperative gastric emptying and patterns of reflux as predictors of outcome after laparoscopic fundoplication

Some studies have suggested that patients with predominantly upright reflux have a poor outcome after laparoscopic antireflux surgery. It has been proposed that this might be related to gastric emptying. The aim of this study was to evaluate the relationship between preoperative upright reflux pattern, gastric emptying rate and outcome after laparoscopic fundoplication.
The Amyloid Cascade Hypothesis in Alzheimer’s Disease: It’s Time to Change Our Mind

Since its discovery in 1984, the beta amyloid peptide has treaded the boards of neurosciences as the star molecule in Alzheimer’s disease pathogenesis. In the last decade, however, this vision has been challenged by evidence-based medicine showing the almost complete failure of clinical trials that experimented anti-amyloid therapies with great hopes. Moreover, data have accumulated which clearly indicate that this small peptide plays a key role in the physiological processes of memory formation. In the present review, we will discuss the different aspects of the amyloid cascade hypothesis, highlighting its pros and cons, and we will analyse the results of the therapeutic approaches attempted to date that should change the direction of Alzheimer’s disease research in the future.
Algorithm 919: A Krylov Subspace Algorithm for Evaluating the ϕ-Functions Appearing in Exponential Integrators

We develop an algorithm for computing the solution of a large system of linear ordinary differential equations (ODEs) with polynomial inhomogeneity. This is equivalent to computing the action of a certain matrix function on the vector representing the initial condition. The matrix function is a linear combination of the matrix exponential and other functions related to the exponential (the so-called ϕ-functions). Such computations are the major computational burden in the implementation of exponential integrators, which can solve general ODEs. Our approach is to compute the action of the matrix function by constructing a Krylov subspace using Arnoldi or Lanczos iteration and projecting the function on this subspace. This is combined with time-stepping to prevent the Krylov subspace from growing too large. The algorithm is fully adaptive: it varies both the size of the time steps and the dimension of the Krylov subspace to reach the required accuracy. We implement this algorithm in the matlab function phipm and we give instructions on how to obtain and use this function. Various numerical experiments show that the phipm function is often significantly more efficient than the state-of-the-art.
Functional assessment: Free thin anterolateral thigh flap versus free radial forearm reconstruction for hemiglossectomy defects

Background To compare free thin anterolateral thigh (ALT) flap with free radial forearm (FRF) flap in the reconstruction of hemiglossectomy defects, and to introduce our methods and experience in the tongue reconstruction with free thin ALT flap. Material and Methods The clinicopathologic data of 46 tongue carcinoma cases hospitalized from December 2009 to April 2014 were obtained from Nangjing Stomatological Hospital, Medical School of Nanjing University. All the subjects were evaluated for the articulation and the swallowing function 3 months after the surgery. Results Among these 46 patients, 12 patients underwent tongue reconstruction after hemiglossectomy with ALT flap; 34 patients underwent tongue reconstruction with FRF flap. The differences in the incidence of vascular crisis, the speech and the swallowing function between two groups were not significant (P>0.05). Conclusions Thin ALT flap could be one of the ideal flaps for hemiglossectomy defect reconstruction with its versatility in design, long pedicle with a suitable vessel diameter, and the neglectable donor site morbidity. Key words:Free thin anterolateral thigh flap, free radial forearm flap, hemiglossectomy, reconstruction, morbidity.
Selected Knee Osteotomies and Meniscal Replacement: Effects on Dynamic Intra-Joint Loading

Through the use of pressure-sensitive color film under static loading conditions, intra-joint loads, contact area, and contact pressure have been determined. Intra-joint loads have also been elucidated through the use of computationally intensive computer simulations. We present an experimental technique and loading mechanism that can provide dynamic intra-joint loads during range of motion. The goal of the study was to establish a dynamic range-of-motion testing protocol encompassing measurement of intra-joint loads while retaining the characteristics of joint compressive loads under minimal constraints to motion. ### Materials and Methods Cadaveric knee specimens were mounted in a testing frame as shown in Figure 1. The quadriceps muscle was fastened to the hydraulic actuator of a materials testing machine (MTS Systems, Eden Prairie, Minnesota) through the proximal insertion site of the patellar tendon. The vastus lateralis and medialis and hamstrings muscles were each loaded with 45 N of tensile load at angles of 17°, 50°, and 0°, respectively, in relation to the femoral axis as described by Lieb and Perry1. A knee flexion moment was generated by a 90-N force equally distributed on both sides of the tibial fixture. All pulleys were terminated and mounted with free rotating swivel joints to reduce external bending moments (Fig. 1). Fig. 1: Apparatus for dynamic testing. MTS = materials testing machine, VL = vastus lateralis, and VMO = vastus medialis oblique. To account for the varied stiffness of the knee during range of motion, an external goniometer mounted at the approximate center of knee rotation was used by the servohydraulic controller as control feedback for the actuator motion. This feedback provided reduced actuator displacement rates at increased flexion angles, at which increased resistance to knee motion was encountered as a result of muscle forces. For all of the specimens tested, knee range of motion was from 15° to …
EVENTS PLANNING IN INTRUSION DETECTION SYSTEMS 1

The goal of this paper is to present designed architecture of intrusion detection system based on events planning and intrusion signature. The article describes problematic of the variation of intrusions and intrusion detection systems. The core of the proposed architecture is intrusion signature matching through petri nets that clasify system behaviour and determine potential intrusion of monitored computer system. The result is a new method of intrusions signature detection.
Pedestrian inertial navigation with gait phase detection assisted zero velocity updating

An inertial navigation system for pedestrian position tracking is proposed, where the position is computed using inertial and magnetic sensors on shoes. Using the fact that there is a zero velocity interval in each stride, estimation errors are reduced. When implementing this zero velocity updating algorithm, it is important to know when is the zero velocity interval. The gait states are modeled as a Markov process and gait state is estimated using the hidden Markov model filter. With this gait estimation, the zero velocity interval is more accurately estimated, which helps to reduce the position estimation error.
A method to integrate, assess and characterize the protein-protein interactions

Recently, large-scale protein-protein interactions were recovered using the similar two-hybrid system for the model systems. This information allows us to investigate the protein interaction network from a systematic point of view. However, experimentally determined interactions are susceptible to errors. A previous assessment estimated that only ~10% of the interactions can be supported by more than one independent experiment, and about half of the interactions may be false positives. These false positives might unnecessarily link unrelated proteins, resulting in huge apparent interaction clusters, which complicate elucidation for the biological importance of these interactions. Address this problem, we present an approach to integrate, assess and characterize all available protein-protein interactions in model organisms yeast and fly. We first integrate all available protein-protein interaction databases of yeast and fly, and merge all the datasets. We then use machine learning techniques to score the reliability for each interaction, and to rigorously validate the scoring scheme of yeast protein-protein interactions from different aspects. Our results show that this scoring scheme provides a good basis for selecting reliable protein-protein interaction dataset
Modeling Affect in Socially Interactive Robots

Humans use expressions of emotion in a very social manner, to convey messages such as "I'm happy to see you" or "I want to be comforted," and people's long-term relationships depend heavily on shared emotional experiences. We believe that for robots to interact naturally with humans in social situations they should also be able to express emotions in both short-term and long-term relationships. To this end, we have developed an affective model for social robots. This generative model attempts to create natural, human-like affect and includes distinctions between immediate emotional responses, the overall mood of the robot, and long-term attitudes toward each visitor to the robot. This paper presents the general affect model as well as particular details of our implementation of the model on one robot, the Roboceptionist
Dynamic Character Recognition Using Hidden Markov Models

Hidden Markov Model theory is an extension of the Markov Model process. It has found uses in such areas as speech recognition, target tracking and word recognition. One area which has received little in the way of research interest, is the use of Hidden Markov Models in character recognition. In this paper the application of Hidden Markov Model theory to dynamic character recognition is investigated. The basic Hidden Markov Model theory is reviewed, and so are the algorithms associated with it. A quick overview of the dynamic character recognition process is considered. Then three types of describing characters are considered, position, inclination angle of small vectors and stroke directional encoding using a Freeman code. A system using each of these descriptions, using Hidden Markov Models in the comparison stage, is described. It is recognised that experiments using the different encoding systems have to be carried out to check the validity of this chosen method.
Set-Difference Range Queries

We introduce the problem of performing set-difference range queries, where answers to queries are set-theoretic symmetric differences between sets of items in two geometric ranges. We describe a general framework for answering such queries based on a novel use of data-streaming sketches we call signed symmetric-difference sketches. We show that such sketches can be realized using invertible Bloom filters (IBFs), which can be composed, differenced, and searched so as to solve set-difference range queries in a wide range of scenarios.
Ribonuclease Activity of Rat Liver Perchloric Acid-soluble Protein, a Potent Inhibitor of Protein Synthesis*

Rat liver perchloric acid-soluble protein (L-PSP) is a potent inhibitor of cell-free protein synthesis; however, its mechanism of action is not known. Here we show that the protein is a unique ribonuclease and that this activity is responsible for the inhibition of translation. The addition of perchloric acid-soluble protein to a rabbit reticulocyte cell-free system at a concentration of 6.2 μm led to an almost complete inhibition of protein synthesis. The kinetics are unlike those of hemin-controlled inhibitor, a protein that acts at the initiation step. The inhibition appears to be due to an endoribonucleolytic activity of perchloric acid-soluble protein because L-PSP directly affects mRNA template activity and induces disaggregation of the reticulocyte polysomes into 80 S ribosomes, even in the presence of cycloheximide. These effects were observed with authentic as well as recombinant L-PSP. Analysis by thin-layer chromatography of [α-32P]UTP-labeled mRNA incubated with the protein showed production of the ribonucleoside 3′-monophosphates Ap, Gp, Up, and Cp, providing direct evidence that the protein is an endoribonuclease. When either 5′- or 3′-32P-labeled 5 S rRNA was the substrate, L-PSP cleaved phosphodiester bonds only in the single-stranded regions of the molecule.
Synthesis of All-Digital Delay Lines

The synthesis of delay lines (DLs) is a core task during the generation of matched delays, ring oscillator clocks or delay monitors. The main figure of merit of a DL is the fidelity to track variability. Unfortunately, complex systems have a great diversity of timing paths that exhibit different sensitivities to static and dynamic variations. Designing DLs that capture this diversity is an ardous task. This paper proposes an algorithmic approach for the synthesis of DLs that can be integrated in a conventional design flow. The algorithm uses heuristics to perform a combinatorial search in a vast space of solutions that combine different types of gates and wire lengths. The synthesized DLs are (1) all digital, i.e., built of conventional standard cells, (2) accurate in tracking variability and (3) configurable at runtime. Experimental results with a commercial standard cell library confirm the quality of the DLs that only exhibit delay mismatches of about 1% on average over all PVT corners.
The effect of operating a virtual doppleganger in a 3D simulation

Recent advances in scanning technology have enabled the widespread capture of 3D character models based on human subjects. Intuition suggests that, with these new capabilities to create avatars that look like their users, every player should have his or her own avatar to play video games or simulations. We explicitly test the impact of having one's own avatar (vs. a yoked control avatar) in a simulation (i.e., maze running task with mines). We test the impact of avatar identity on both subjective (e.g., feeling connected and engaged, liking avatar's appearance, feeling upset when avatar's injured, enjoying the game) and behavioral variables (e.g., time to complete task, speed, number of mines triggered, riskiness of maze path chosen). Results indicate that having an avatar that looks like the user improves their subjective experience, but there is no significant effect on how users perform in the simulation.
Interprofessional learning and higher education structural barriers

Structural changes need to be made within universities such that interprofessional education1 for patient-centred collaborative practice becomes a responsibility that crosses faculty jurisdictions and is accepted as the responsibility of all associated health and human service programs. In communities, the patient or client is the centre of professional attention requiring care that goes beyond the skill and scope of any one profession. Notions about collaboration inform and drive interprofessional education and should lead to sustainable system changes within centres of advanced education that ensure a permanent place for interprofessional education in all health and human service programs. This chapter explores the many barriers to achieving this goal, and offers insights into their removal from one university's experience.
Recognition of Dialogue Acts in Multiparty Meetings Using a Switching DBN

This paper is concerned with the automatic recognition of dialogue acts (DAs) in multiparty conversational speech. We present a joint generative model for DA recognition in which segmentation and classification of DAs are carried out in parallel. Our approach to DA recognition is based on a switching dynamic Bayesian network (DBN) architecture. This generative approach models a set of features, related to lexical content and prosody, and incorporates a weighted interpolated factored language model. The switching DBN coordinates the recognition process by integrating the component models. The factored language model, which is estimated from multiple conversational data corpora, is used in conjunction with additional task-specific language models. In conjunction with this joint generative model, we have also investigated the use of a discriminative approach, based on conditional random fields, to perform a reclassification of the segmented DAs. We have carried out experiments on the AMI corpus of multimodal meeting recordings, using both manually transcribed speech, and the output of an automatic speech recognizer, and using different configurations of the generative model. Our results indicate that the system performs well both on reference and fully automatic transcriptions. A further significant improvement in recognition accuracy is obtained by the application of the discriminative reranking approach based on conditional random fields.
Calibration of an Outdoor Distributed Camera Network with a 3D Point Cloud

Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC).