Miracle-dz/UniFAR-FTUs huggingface dataset:
MHC–disassortative mating preferences reversed by cross–fostering

House mice (Mus musculus domesticus) avoid mating with individuals that are genetically similar at the major histocompatibility complex (MHC). Mice are able recognize MHC–similar individuals through specific odour cues. However, to mate disassortatively for MHC genes, individuals must have a referent, either themselves (self–inspection) or close kin (familial imprinting), with which to compare the MHC identity of potential mates. Although studies on MHC–dependent mating preferences often assume that individuals use self–inspection, laboratory experiments with male mice indicate that they use familial imprinting, i.e. males learn the MHC identity of their family and then avoid mating with females carrying ‘familial’ MHC alleles. To determine if female mice use familial imprinting, we cross–fostered wild–derived female mouse pups into MHC–dissimilar families, and then tested if this procedure reversed their mating preferences compared with in–fostered controls. Our observations of the female's mating behaviour in seminatural social conditions and the genetic typing of their progeny both indicated that females avoided mating with males carrying MHC genes of their foster family, supporting the familial imprinting hypothesis. We show that MHC–dependent familial imprinting potentially provides a more effective mechanism for avoiding kin matings and reducing inbreeding than self–inspection.
Automatic generation of package diagram to understand Java packages

Program comprehension is a prerequisite in most software maintenance and evolution tasks. Given an unfamiliar system, it is difficult for practitioners to determine which software artifacts are relevant to the current task. Generally, there are a variety of packages in a Java software system. These packages often have different intents and different relationships between each other. Different information of packages and the relationships between different stereotypes packages form a signature of the system. This paper proposes a novel approach to automatically generate the description of the packages and its diagram to show relationships between the packages. The generated description and diagram can allow developers to more easily understand the main intent and structure of the system.
Joint equalization and soft decoding for vector quantization over channels with intersymbol interference

An approach to joint equalization and decoding for vector quantization over a Gaussian channel with intersymbol interference is presented. The decoder is based on a Hadamard transform representation of the vector quantizer. This gives the decoder a structure that allows the decoding to be based on estimates of the transmitted bits in an efficient manner. The decoder is soft in the sense that soft channel information is used and no decisions are involved in the decoding. Simulations demonstrate that the soft decoder can outperform a scheme based on Viterbi equalization plus table look-up decoding.
Building tailorable hypermedia systems: the embedded-interpreter approach

This paper discusses an approach for developing dynamically tailorable hypermedia systems in an object-oriented environment. The approach is aimed at making applications developed in compiled languages like Beta and C++ tailorable at run-time. The approach is based on use of: 1) a hypermedia application framework (DEVISE Hyper-media), and 2) an embeddable interpreter for the framework language. A specific hypermedia system is instantiated from the framework with the interpreter embedded in the executable. The specific hypermedia system has a number of “open points” which can be filled via the interpreter at run-time. These open points and the interpreter provide sufficient support to allow tailoring at run-time as well as compile-time. Among the types of tailoring supported are: 1) adding new media-types, 2) alternating editors for supported media-types, and 3) removing a supported media-type. The paper describes the framework and illustrates how the interpreter is integrated. It describes steps involved in tailoring a specific hypermedia system with a new drawing media-type, where graphical objects can be endpoints for links. Since the hypermedia framework uses a persistent object-store, a solution for handling persistent interpreted objects is presented. Finally, the approach is compared with other environments supporting tailoring.
Latent class analysis of co-morbidity in the Adult Psychiatric Morbidity Survey in England 2007: implications for DSM-5 and ICD-11

Background Psychiatric co-morbidity is complex and ubiquitous. Our aim was to describe the extent, nature and patterning of psychiatric co-morbidity within a representative sample of the adult population of England, using latent class analysis. Method Data were used from the 2007 Adult Psychiatric Morbidity Survey, a two-phase national household survey undertaken in 2007 comprising 7325 participants aged 16 years and older living in private households in England. The presence of 15 common mental health and behavioural problems was ascertained using standardized clinical and validated self-report measures, including three anxiety disorders, depressive episode, mixed anxiety depressive disorder, psychosis, antisocial and borderline personality disorders, eating disorders, post-traumatic stress disorder, attention deficit disorder, alcohol and drug dependencies, problem gambling and attempted suicide. Results A four-class model provided the most parsimonious and informative explanation of the data. Most participants (81.6%) were assigned to a non-symptomatic or ‘Unaffected’ class. The remainder were classified into three qualitatively different symptomatic classes: ‘Co-thymia’ (12.4%), ‘Highly Co-morbid’ (5.0%) and ‘Addictions’ (1.0%). Classes differed in mean numbers of conditions and impairments in social functioning, and these dimensions were correlated. Conclusions Our findings confirm that mental disorders typically co-occur and are concentrated in a relatively small number of individuals. Conditions associated with the highest levels of disability, mortality and cost – psychosis, suicidality and personality disorders – are often co-morbid with more common conditions. This needs to be recognized when planning services and when considering aetiology.
Network meta-analysis of randomized clinical trials: Reporting the proper summaries

Background In the absence of sufficient data directly comparing multiple treatments, indirect comparisons using network meta-analyses (NMAs) can provide useful information. Under current contrast-based (CB) methods for binary outcomes, the patient-centered measures including the treatment-specific event rates and risk differences (RDs) are not provided, which may create some unnecessary obstacles for patients to comprehensively trade-off efficacy and safety measures. Purpose We aim to develop NMA to accurately estimate the treatment-specific event rates. Methods A Bayesian hierarchical model is developed to illustrate how treatment-specific event rates, RDs, and risk ratios (RRs) can be estimated. We first compare our approach to alternative methods using two hypothetical NMAs assuming a fixed RR or RD, and then use two published NMAs to illustrate the improved reporting. Results In the hypothetical NMAs, our approach outperforms current CB NMA methods in terms of bias. In the two published NMAs, noticeable differences are observed in the magnitude of relative treatment effects and several pairwise statistical significance tests from previous report. Limitations First, to facilitate the estimation, each study is assumed to hypothetically compare all treatments, with unstudied arms being missing at random. It is plausible that investigators may have selected treatment arms on purpose based on the results of previous trials, which may lead to ‘nonignorable missingness’ and potentially bias our estimates. Second, we have not considered methods to identify and account for potential inconsistency between direct and indirect comparisons. Conclusions The proposed NMA method can accurately estimate treatment-specific event rates, RDs, and RRs and is recommended.
Error-Resilient Multicasting for Multi-View 3D Videos in Wireless Networks

With the emergence of naked-eye 3D mobile devices, mobile 3D video services are becoming increasingly important for video service providers, such as Youtube and Netflix, while multi-view 3D videos have the potential to inspire a variety of innovative applications. However, enabling multi-view 3D video services may overwhelm WiFi networks when every view of a video are multicasted. In this paper, therefore, we propose to incorporate depth-image-based rendering (DIBR), which allows each mobile client to synthesize the desired view from nearby left and right views, in order to effectively reduce the bandwidth consumption. Moreover, when each client suffers from packet losses, retransmissions incur additional bandwidth consumption and excess delay, which in turn undermines the quality of experience in video applications. To address the above issue, we first discover the merit of view protection via DIBR for multi-view video multicast using a mathematical analysis and then design a new protocol, named Multi-View Group Management Protocol (MVGMP), to support the dynamic join and leave of users and the change of desired views. The simulation results demonstrate that our protocol effectively reduces bandwidth consumption and increases the probability for each client to successfully playback the desired views in a multi-view 3D video.
Arabic Script Documents Language Identifications Using Fuzzy ART

The volume of information available on the internet, intranet, digital libraries and newsgroup has increased dramatically in recent years. Therefore, there is a growing interest in helping user better find, filter, and manage these resources. Language identification is the first step of understanding text documents which is written in. It is usually a module within multilingual application. In this paper, we introduce language identification of Arabic script documents by letter frequency. Technique used for identification is fuzzy adaptive resonance theory (ART), which is belong to the neural network architectures that perform incremental unsupervised learning. Arabic script documents such as Arabic, Persian and Urdu were used for performing language identification. From the experiments, we have found that fuzzy ART is particularly promising in terms of accuracy on language identification.
The Arabidopsis irregular xylem8 Mutant Is Deficient in Glucuronoxylan and Homogalacturonan, Which Are Essential for Secondary Cell Wall Integrity[W]

The secondary cell wall in higher plants consists mainly of cellulose, lignin, and xylan and is the major component of biomass in many species. The Arabidopsis thaliana irregular xylem8 (irx8) mutant is dwarfed and has a significant reduction in secondary cell wall thickness. IRX8 belongs to a subgroup of glycosyltransferase family 8 called the GAUT1-related gene family, whose members include GAUT1, a homogalacturonan galacturonosyltransferase, and GAUT12 (IRX8). Here, we use comparative cell wall analyses to show that the irx8 mutant contains significantly reduced levels of xylan and homogalacturonan. Immunohistochemical analyses confirmed that the level of xylan was significantly reduced in the mutant. Structural fingerprinting of the cell wall polymers further revealed that irx8 is deficient in glucuronoxylan. To explore the biological function of IRX8, we crossed irx8 with irx1 (affecting cellulose synthase 8). The homozygous irx1 irx8 exhibited severely dwarfed phenotypes, suggesting that IRX8 is essential for cell wall integrity during cellulose deficiency. Taken together, the data presented show that IRX8 affects the level of glucuronoxylan and homogalacturonan in higher plants and that IRX8 provides an important link between the xylan polymer and the secondary cell wall matrix and directly affects secondary cell wall integrity.
Anorexic Subjects Underestimate the Amount of Food

Anorexic Subjects Underestimate the Amount of Food Vinai Piergiuseppe (piervinai@tin.it) “Studi Cognitivi”, Post-graduate Cognitive Psychotherapy School, 27 Montebello street, Milano, 20121 Italy. Ferrato Noemi “Studi Cognitivi”, Post-graduate Cognitive Psychotherapy School, 27 Montebello street, Milano, 20121 Italy Cardetti Silvia “Studi Cognitivi”, Post-graduate Cognitive Psychotherapy School, 27 Montebello street, Milano, 20121Italy. Vallauri Paola “Studi Cognitivi”, Post-graduate Cognitive Psychotherapy School, 27 Montebello street, Milano, 20121 Italy. Carpegna Gabriella Studi Cognitivi”, Post-graduate Cognitive Psychotherapy School, 27 Montebello street, Milano, 20121 Italy. Masante Donatella “Studi Cognitivi”, Post-graduate Cognitive Psychotherapy School, 27 Montebello street, Milano, 20121 Italy. Luxardi Gianluigi Eating Disorders Unit ASL N° 6 Western Friuli S. Vito al Tagliamento Pordenone, Italy Ostuzzi Roberto Eating Disorders Unit Villa Margherita Vicenza, Italy, Pozzato Marita Eating Disorders Unit Villa Margherita Vicenza, Italy, Todisco Patrizia Eating Disorders Unit of Spedali Riuniti Brescia Italy Ruggiero Giovanni “Studi Cognitivi”, Post-graduate Cognitive Psychotherapy School, 27 Montebello street, Milano, 20121 Italy Sassaroli Sandra “Studi Cognitivi”, Post-graduate Cognitive Psychotherapy School, 27 Montebello street, Milano, 20121 Italy. peoples and anorexic patients capability to evaluate amounts of food. We also investigated the influence of unnatural color and odor of food on the perception of the amount. A group of anorexic subjects was asked to evaluate how many biscuits were used to prepare of a certain amount of broken biscuits. Abstract People affected by eating disorders often misjudge their food intake. This misjudgement might be due to fear of eating and of the amount of food eaten. This study contrasted normal
The dBoard: A Digital Scrum Board for Distributed Software Development

In this paper we present the dBoard - a digital Scrum Board for distributed Agile software development teams. The dBoard is designed as a 'virtual window' between two Scrum team spaces. It connects two locations with live video and audio, which is overlaid with a synchronized and interactive digital Scrum board, and it adapts the fidelity of the video/audio to the presence of people in front of it. The dBoard is designed to work (i) as a passive information radiator from which it is easy to get an overview of the status of work, (ii) as a media space providing awareness about the presence of remote co-workers, and (iii) as an active meeting support tool. The paper presents a case study of distributed Scrum in a large software company that motivates the design of the dBoard, and details the design and technical implementation of the dBoard. The paper also reports on an initial user study, which shows that users found the dBoard both useful and easy to use. Based on this work, we suggest that superimposing collaborative applications onto live video is a useful way of designing collaborative meeting and awareness systems.
De retibus socialibus et legibus momenti

Online Social Networks (OSNs) are a cutting edge topic. Almost everybody —users, marketers, brands, companies, and researchers— is approaching OSNs to better understand them and take advantage of their benefits. Maybe one of the key concepts underlying OSNs is that of influence which is highly related, although not entirely identical, to those of popularity and centrality. Influence is, according to Merriam-Webster, “the capacity of causing an effect in indirect or intangible ways”. Hence, in the context of OSNs, it has been proposed to analyze the clicks received by promoted URLs in order to check for any positive correlation between the number of visits and different “influence” scores. That evaluation methodology is used in this letter to compare a number of those techniques with a new method firstly described here. That new method is a simple and rather elegant solution which tackles with influence in OSNs by applying a physical metaphor.
THUEE language modeling method for the OpenKWS 2015 evaluation

In this paper, we describe the THUEE (Department of Electronic Engineering, Tsinghua University) team's method of building language models (LMs) for the OpenKWS 2015 Evaluation held by the National Institute of Standards and Technology (NIST). Due to the very limited in-domain data provided by NIST, it takes most of our time and efforts to make good use of the out-of-domain data. There are three main steps in our work. Firstly, data cleaning has been done on the out-of-domain data. Secondly, by comparing the cross-entropy difference between the in-domain data and out-of-domain data, a part of the out-of-domain corpus which is well-matched to the in-domain one has been selected as the training corpus. Thirdly, the final n-gram LM is obtained by interpolating individual n-gram LMs according to different training corpus and all the training data is further combined to train one feed-forward neural network LM (FNNLM). In this way, we reduce the perplexity on development test data by 8.3% for n-gram LM and 1.7% for FNNLM, and the Actual Term-Weighted Value (ATWV) of the final result is 0.5391.
Online Information for “ Chiral plasmons without magnetic field ”

For a complementary view to the approach employed in the main text, here we present an alternative formulation of the plasmon equations of motion. Rather than focusing on the semiclassical equations of motion for the particle and velocity density fields, here we work with the charge density ρ(r, t) = −en(r, t), the current density j(r, t), and the conductivity tensor σ. As we will be interested in oscillatory collective (plasmon) modes, it will be useful to work in terms of Fourier modes, ρ(r, t) = ρω(r)e , j(r, t) = jω(r)e , and φ(r, t) = φω(r)e . The charge and current densities obey a continuity equation, which in terms of the Fourier modes reads:
MULTI-MODAL EMOTION RECOGNITION – MORE " COGNITIVE " MACHINES

Based on several results related to studies on emotions, we suggest that the process of emotionrecognition is assisted by some internal structure of the cognitive images of emotions, which are at different levels of knowledge representation. We concede that the main proposed in psychology models are in correspondence with these levels and in this sense complementary. We summarize the state-of-the-art of machine emotion recognition with regards of the used psychological models of emotions. In order to discover amelioration sources of multimodal machine emotion recognition, we propose a scheme of the cognitive process, based on gradual levels of representation. The proposed scheme shows several "strategic" differences with the architectures used in machine emotion recognition. We discuss the questions related to recognition, assisted by two levels of representation that we called "perceptual" and "conceptual". ACM Classification
Three dimensional rock-scene modelling using dense stereo reconstruction

A dense stereo reconstruction technique for extracting a 3D model of a rock scene from a pair of images is presented. The technique falls under the conventional approach of extracting 3D information from a calibrated stereo pair. In this work, a single camera that is under going linear motion with respect to the scene is used. As far as correspondence analysis is concerned, a simple method for reducing the search along scan lines of the input image pair is proposed. Finally, multiple view geometry is used to produce range maps of the rock-scene. Preliminary results on a limited data set show that the quality of the produced maps is acceptable.
Please Scroll down for Article International Journal of Production Research Optimising Product Configurations with a Data-mining Approach Optimising Product Configurations with a Data-mining Approach

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Customers benefit from the ability to select their desired options to configure final products. Manufacturing companies, however, struggle with the dilemma of product diversity and manufacturing complexity. It is important, therefore, for them to capture correlations among the options provided to the customers. In this paper, a data mining approach is applied to manage product diversity and complexity. Rules are extracted from historical sales data and used to form sub-assemblies as well as product configurations. Methods for discovering frequently ordered product sub-assemblies and product configurations from 'if-then' rules are discussed separately. The development of the sub-assemblies and configurations allows for effective management of enterprise resources, contributes to the innovative design of new products, and streamlines manufacturing and supply chain processes. The ideas introduced in this paper are illustrated with examples and an industrial case study.
Fast customization of geometric models

We present a technique for customization of geometric models of animals based on pictures. The object to be customized is divided into a set of hierarchically related local coordinate systems which allow for independent transformations of different body parts. A picture of the desired result is used as a visual aid to drive the customization process. We show the results of applying this technique to customize a generic three-dimensional horse model to three different horse breeds.
Wireless Broadcast with Network Coding: A Connected Dominating Sets Approach

We study network coding for multi-hop wireless networks. We focus the case of broadcasting, where one source transmits information to all the nodes in the network. Our goal is energy-efficient broadcasting, in other words, to minimize the number of transmissions for broadcasting to the entire network. To achieve this goal, we propose a family of methods that combine the use of network coding and connected dominating sets. They consists in rate selections using connected dominated sets (RAUDS: Rate Adjustment Using Dominating Sets, and an generalized version, MARAUDS). The main insight behind these methods is that their use of connected dominating sets, allows near-optimality in the core of the network, while they efficiently handle borders and non-uniformity. The main contribution is a formal proof of the performance of these families of algorithms. One main result is the comparison of performance between routing and these methods (and in general, network coding).
Optimization of power allocation with simple relay selection

In this paper, we consider a dual-hop selective decode-and-forward relay system with multiple antennas at the destination. Using a simple relay selection strategy with the knowledge of channel gain magnitudes, we explore adaptive power allocation between the source and relay to minimize the system outage probability under a power constraint. Numerical results show that optimizing the allocation of power enhances the system performance. Moreover, more destination antennas bring more improvement and less power allocation at the relay. It is also shown that more candidate relays will further improve the outage performance of relay system under both uniform and adaptive power allocation.