Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrasound-based subject-specific parameters improve fascicle behaviour estimation in Hill-type muscle model

The estimation of muscle fascicle behaviour is decisive in a Hill-type model as they are related to muscle force by the force–length–velocity relationship and the tendon force–strain relationship. This study was aimed at investigating the influence of subject-specific tendon force–strain relationship and initial fascicle geometry (IFG) on the estimation of muscle forces and fascicle behaviour during isometric contractions. Ultrasonography was used to estimate the in vivo muscle fascicle behaviour and compare the muscle fascicle length and pennation angle estimated from the Hill-type model. The calibration–prediction process of the electromyography-driven model was performed using generic or subject-specific tendon definition with or without IFG as constraint. The combination of subject-specific tendon definition and IFG led to muscle fascicle behaviour closer to ultrasound data and significant lower forces of the ankle dorsiflexor and plantarflexor muscles compared to the other conditions. Thus, subject-specific ultrasound measurements improve the accuracy of Hill-type models on muscle fascicle behaviour.
CLONING OF PORCINE INTERCELLULAR ADHESION MOLECULE-1 AND CHARACTERIZATION OF ITS INDUCTION ON ENDOTHELIAL CELLS BY CYTOKINES1

Background. The transplantation of pig organs into humans requires a detailed knowledge of similarities and differences between the two species in the molecular physiology of host defense mechanisms. We therefore set out to identify porcine intercellular adhesion molecule (ICAM)-1 and to characterize its expression by endothelial cells. Methods. Porcine ICAM-1 cDNA was isolated from an endothelial cell cDNA library. An anti-pig ICAM-1 monoclonal antibody was generated and used to investigate the regulation by cytokines of ICAM-1 expression by porcine aortic endothelial cells (PAEC), using flow cytometry. Results. We found that porcine ICAM-1 was similar in primary structure to human ICAM-1, with five Ig-like domains. COS-7 cells transfected with porcine ICAM-1 supported &bgr;2 but not &agr;4 integrin-dependent adhesion of human T lymphoblasts. There was a low-level surface expression of ICAM-1 on unstimulated PAEC and increased expression after stimulation with tumor necrosis factor (TNF)-&agr;. However expression of ICAM-1 seemed to be significantly lower than that of vascular cell adhesion molecule-1, both on unstimulated and TNF-&agr;-activated PAEC. Recombinant porcine interferon-&ggr; weakly stimulated ICAM-1 expression when incubated alone with PAEC but had an inhibitory effect on the increase in ICAM-1 due to TNF-&agr;, both at 8 and 24 hr. Conclusions. Our observations confirm the existence of ICAM-1 in the pig and provide novel insights into how porcine and human endothelial cells differ in terms of adhesion molecule expression and cytokine responsiveness. Such differences are potentially important in interpreting models of inflammation in the pig and also in understanding the process of rejection of porcine xenografts.
Schema covering: a step towards enabling reuse in information integration

We introduce schema covering, the problem of identifying easily understandable common objects for describing large and complex schemas. Defining transformations between schemas is a key objective in information integration. However, this process often becomes cumbersome when the schemas are large and structurally complex. If such complex schemas can be broken into smaller and simpler objects, then simple transformations defined over these smaller objects can be reused to define suitable transformations among the complex schemas. Schema covering performs this vital task by identifying a collection of common concepts from a repository and creating a cover of the complex schema by these concepts. In this paper, we formulate the problem of schema covering, show that it is NP-Complete, and give efficient approximation algorithms for it. A performance evaluation with real business schemas confirms the effectiveness of our approach.
A Multidisciplinary Model of Dynamic and Semantic Social Networks Analysis for Institutions

Social networks of the Web 2.0 have become global (e.g. FaceBook, MSN). In 1977, L. C. FREEMAN published the first generic metrics for Social Networks Analysis (SNA), mainly based on static graph-mining models. The objective of our work is to introduce new dynamic SNA models dedicated to SNA and to take the conceptual aspects of enterprises and institutions social graph into account. Our work is based on the definition of new multidimensional measures in SNA for new decision-making functions in Human Resource Management (HRM). The presented contributions makes it original. They are: (1) a measure of tension of a social network, (2) an electrodynamic and predictive system for semantic recommendations on social graphs evolutions and (3) a measure of reactance of a social network used to evaluate the individual stress of its members.
Comparison and validation of the recent freely available ASTER-GDEM ver1, SRTM ver4.1 and GEODATA DEM-9S ver3 digital elevation models over Australia

This study investigates the quality (in terms of elevation accuracy and systematic errors) of three recent publicly available elevation model datasets over Australia: (i) the 9 arc second national GEODATA DEM-9S ver3 from Geoscience Australia and the Australian National University; (ii) the 3 arc second SRTM ver4.1 from CGIAR-CSI; and (iii) the 1 arc second ASTER-GDEM ver1 from NASA/METI. The main features of these datasets are reported from a geodetic point of view. Comparison at about 1 billion locations identifies artefacts (e.g. residual cloud patterns and stripe effects) in ASTER. For DEM-9S, the comparisons against the space-collected SRTM and ASTER models demonstrate that signal omission (due to the ∼270 m spacing) may cause errors of the order of 100–200 m in some rugged areas of Australia. Based on a set of geodetic ground control points over Western Australia, the vertical accuracy of DEM-9S is ∼9 m, SRTM ∼6 m and ASTER ∼15 m. However, these values vary as a function of the terrain type and shape. Thus, CGIAR-CSI SRTM ver4.1 may represent a viable alternative to DEM-9S for some applications. While ASTER GDEM has an unprecedented horizontal resolution of ∼30 m, systematic errors present in this research-grade version of the ASTER GDEM ver1 will impede its immediate use for some applications.
Specialist Experts for Prediction with Side Information

The paper proposes the vicinities merging algorithm for prediction with side information. The algorithm is based on specialist experts techniques. We use vicinities in the side information domain to identify relevant past examples, apply standard learning techniques to them, and then use prediction with expert advice tools to merge those predictions. Guarantees from the theory of prediction with expert advice ensure that helpful vicinities are selected dynamically. The algorithm automatically converges on the right vicinities from an initial broad selection. We apply the resulting algorithms to two problems, prediction of implied volatility of options and prediction of students' performance at tests. On the problem of predicting implied volatility, the algorithm consistently outperforms naive competitors and a highly-tuned proprietary method used in the industry. When applied to the students' performance, the algorithm never falls behind the baseline and outperforms it when the side information is beneficial.
Unsupervised Discovery of Nonlinear Structure Using Contrastive Backpropagation

We describe a way of modeling high-dimensional data vectors by using an unsupervised, nonlinear, multilayer neural network in which the activity of each neuron-like unit makes an additive contribution to a global energy score that indicates how surprised the network is by the data vector. The connection weights that determine how the activity of each unit depends on the activities in earlier layers are learned by minimizing the energy assigned to data vectors that are actually observed and maximizing the energy assigned to "confabulations" that are generated by perturbing an observed data vector in a direction that decreases its energy under the current model.
Long-lasting Disease Stabilization in the Absence of Toxicity in Metastatic Lung Cancer Patients Vaccinated with an Epitope Derived from Indoleamine 2,3 Dioxygenase

Purpose: To investigate targeting of indoleamine 2,3 dioxygenase (IDO) enzyme using a synthetic peptide vaccine administered to patients with metastatic non–small cell lung cancer (NSCLC). Experimental Design: In a clinical phase I study, we treated 15 HLA-A2–positive patients with stage III–IV NSCLC in disease stabilization after standard chemotherapy. Patients were treated with imiquimod ointment and subcutaneous vaccinations (100 μg IDO5 peptide, sequence ALLEIASCL, formulated in 900 μL Montanide). Primary endpoint was toxicity. Clinical benefit and immunity were assessed as secondary endpoints. Results: No severe toxicity was observed. One patient developed a partial response (PR) after one year of vaccine treatment, whereas long-lasting stable disease (SD) ≥ 8.5 months was demonstrated in another six patients. The median overall survival (OS) was 25.9 months. Patients demonstrated significant improved OS (P = 0.03) when compared with the group of patients excluded because of HLA-A2 negativity. IDO-specific CD8+ T-cell immunity was demonstrated by IFN-γ Elispot and Tetramer staining. Fluorescence-activated cell sorting analyses demonstrated a significant reduction of the Treg population (P = 0.03) after the sixth vaccine (2.5 months) compared with pretreatment levels. Furthermore, expression of IDO was detected in nine of ten tumor biopsies by immunohistochemistry. High-performance liquid chromatography analyses of kynurenine/tryptophan (Kyn/Trp) ratio in sera were performed. In long-term analyses of two clinical responding patients, the ratio of Kyn/Trp remained stable. Conclusions: The vaccine was well tolerated with no severe toxicity occurring. A median OS of 25.9 months was demonstrated and long-lasting PR+SD was seen in 47% of the patients. Clin Cancer Res; 20(1); 221–32. ©2013 AACR.
Probabilistic Verifiers: Evaluating Constrained Nearest-Neighbor Queries over Uncertain Data

In applications like location-based services, sensor monitoring and biological databases, the values of the database items are inherently uncertain in nature. An important query for uncertain objects is the probabilistic nearest-neighbor query (PNN), which computes the probability of each object for being the nearest neighbor of a query point. Evaluating this query is computationally expensive, since it needs to consider the relationship among uncertain objects, and requires the use of numerical integration or Monte-Carlo methods. Sometimes, a query user may not be concerned about the exact probability values. For example, he may only need answers that have sufficiently high confidence. We thus propose the constrained nearest-neighbor query (C-PNN), which returns the IDs of objects whose probabilities are higher than some threshold, with a given error bound in the answers. The C-PNN can be answered efficiently with probabilistic verifiers. These are methods that derive the lower and upper bounds of answer probabilities, so that an object can be quickly decided on whether it should be included in the answer. We have developed three probabilistic verifiers, which can be used on uncertain data with arbitrary probability density functions. Extensive experiments were performed to examine the effectiveness of these approaches.
Multi-task co-clustering via nonnegative matrix factorization

Recent results have empirically proved that, given several related tasks with different data distributions and an algorithm that can utilize both the task-specific and cross-task knowledge, clustering performance of each task can be significantly enhanced. This kind of unsupervised learning method is called multi-task clustering. We focus on tackling the multi-task clustering problem via a 3-factor nonnegative matrix factorization. The object of our approach consists of two parts: (1) Within-task co-clustering: co-cluster the data in the input space individually. (2) Cross-task regularization: Learn and refine the relations of feature spaces among different tasks. We show that our approach has a sound information theoretic background and the experimental evaluation shows that it outperforms many state-of-the-art single-task or multi-task clustering methods.
In Vitro Cytotoxicity of Fluorescent Silica Nanoparticles Hybridized with Aggregation-Induced Emission Luminogens for Living Cell Imaging

Fluorescent silica nanoparticles (FSNPs) can provide high-intensity and photostable fluorescent signals as a probe for biomedical analysis. In this study, FSNPs hybridized with aggregation-induced emission (AIE) luminogens (namely FSNP-SD) were successfully fabricated by a surfactant-free sol-gel method. The FSNP-SD were spherical, monodisperse and uniform in size, with an average diameter of approximately 100 nm, and emitted strong fluorescence at the peak of 490 nm. The FSNP-SD selectively stained the cytoplasmic regions and were distributed in the cytoplasm. Moreover, they can stay inside cells, enabling the tacking of cells over a long period of time. The intracellular vesicles and multinucleated cells were increase gradually with the rise of FSNP-SD concentration. Both cell viability and survival only lost less than 20% when the cells were exposed to the high concentration of 100 μg/mL FSNP-SD. Additionally, the cell apoptosis and intracellular ROS assay indicated that FSNP-SD had no significant toxic effects at the maximum working concentration of 80 μg/mL. This study demonstrated that the FSNP-SD are promising biocompatible fluorescent probes for living cell imaging.
The deer from the early Middle Pleistocene site of Isernia la Pineta (Molise, Italy): revised identifications and new remains from the last 15 years of excavation

The deer remains from the renowned Palaeolithic site of Isernia la Pineta (southern Italy) are revised. Both material already published, and new specimens from the last 15 years of excavation, is taken into account and some identifications are revised. The published assemblage consists of Megaceroides solilhacus, Cervus sp. cf. C. elaphus acoronatus, Dama sp. cf. D. clactoniana and Capreolus sp. The literature dealing with these species is discussed and the problems still unresolved are outlined. The giant deer, now assigned by most authors to the genus Praemegaceros as P. solilhacus, is the largest and most common deer species at the site, represented by numerous antler fragments plus a few isolated teeth and fragmentary postcranial elements. The retrieval of new, well‐preserved specimens, namely one nearly complete antler, plus a distal portion of palmation, two neural skulls and one premaxillary bone, allows a better characterization of this otherwise still poorly understood species. The sub‐specific attribution of the red deer, in the lack of more complete antler specimens, is still dubious. The fallow deer remains probably belong to Dama roberti, a recently described species from the early Middle Pleistocene of Western Europe. The morphology of the lower portion of the only preserved antler fits better with this species rather than with D. clactoniana, to which it was previously tentatively assigned. At last, the specific identity of the few roe deer remains from Isernia is discussed, but the problem remains unanswered because of lack of agreement, in the literature, about the taxonomy of the Pleistocene species. Copyright © 2015 John Wiley & Sons, Ltd.
Developmental toxicity of in ovo exposure to polychlorinated biphenyls: I. Immediate and subsequent effects on first‐generation nestling American kestrels (Falco sparverius)

We determined that in ovo exposure to polychlorinated biphenyls (PCBs) alters growth off first‐generation nestlings during and one year after parental exposure. Captive American kestrels (Falco sparverius) laid eggs with environmentally relevant total PCB levels (34.1 μg/g whole‐egg wet wt) when fed PCB‐spiked (Aroclor® 1248, 1254, and 1260) food (7 mg/kg body wt/d) for 100 d in 1998. In 1999, the same adults laid eggs with estimated total PCBs of 29.0 μg/g. Nonsurviving PCB‐exposed chicks were small (mass, bones) in 1998. Survivors showed a strong sex‐specific growth response (mass, bones) compared to respective sex controls: Only female hatchlings were larger, and only male nestlings had longer feathers (1998); maximal growth and bone growth rates also differed (males were advanced, faster; females delayed, slower) (1999); and male nestlings fledged earlier and were smaller, while females were larger (1998, 1999). However, regardless of sex, PCB‐exposed nestlings generally grew at faster rates in both years. In 1998, greater contaminant burdens and toxic equivalent concentrations in sibling eggs were associated with nestlings being lighter, having longer bones and feathers, and growing at faster rates (mass, bone) for females but slower rates (mass) for males. Both physiological‐biochemical and behavioral changes are likely mechanisms. This study supports and expands on the Great Lakes embryo mortality, edema, and deformities syndrome: While PCB exposure alters nestling size, maximal growth and growth rates also change immediately, are sustained, and are sex specific.
A signal transducer for aerotaxis in Escherichia coli

The newly discovered aer locus of Escherichia coli encodes a 506-residue protein with an N terminus that resembles the NifL aerosensor and a C terminus that resembles the flagellar signaling domain of methyl-accepting chemoreceptors. Deletion mutants lacking a functional Aer protein failed to congregate around air bubbles or follow oxygen gradients in soft agar plates. Membranes with overexpressed Aer protein also contained high levels of noncovalently associated flavin adenine dinucleotide (FAD). We propose that Aer is a flavoprotein that mediates positive aerotactic responses in E. coli. Aer may use its FAD prosthetic group as a cellular redox sensor to monitor environmental oxygen levels.
Response-Dependent Contributions of Human Primary Motor Cortex and Angular Gyrus to Manual and Perceptual Sequence Learning

Motor sequence learning on the serial reaction time task involves the integration of response-, stimulus-, and effector-based information. Human primary motor cortex (M1) and the inferior parietal lobule (IPL) have been identified with supporting the learning of effector-dependent and -independent information, respectively. Current neurocognitive data are, however, exclusively based on learning complex sequence information via perceptual-motor responses. Here, we investigated the effects of continuous theta-burst transcranial magnetic stimulation (cTBS)-induced disruption of M1 and the angular gyrus (AG) of the IPL on learning a probabilistic sequence via sequential perceptual-motor responses (experiment 1) or covert orienting of visuospatial attention (experiment 2). Functional effects on manual sequence learning were evident during 75% of training trials in the cTBS M1 condition, whereas cTBS over the AG resulted in interference confined to a midpoint during the training phase. Posttraining direct (declarative) tests of sequence knowledge revealed that cTBS over M1 modulated the availability of newly acquired sequence knowledge, whereby sequence knowledge was implicit in the cTBS M1 condition but was available to conscious awareness in the cTBS AG and control conditions. In contrast, perceptual sequence learning was abolished in the perceptual cTBS AG condition, whereas learning was intact and available to conscious awareness in the cTBS M1 and control conditions. These results show that the right AG had a critical role in perceptual sequence learning, whereas M1 had a causal role in developing experience-dependent functional attributes relevant to conscious knowledge on manual but not perceptual sequence learning.
Predicting Vulnerable Components: Software Metrics vs Text Mining

Building secure software is difficult, time-consuming, and expensive. Prediction models that identify vulnerability prone software components can be used to focus security efforts, thus helping to reduce the time and effort required to secure software. Several kinds of vulnerability prediction models have been proposed over the course of the past decade. However, these models were evaluated with differing methodologies and datasets, making it difficult to determine the relative strengths and weaknesses of different modeling techniques. In this paper, we provide a high-quality, public dataset, containing 223 vulnerabilities found in three web applications, to help address this issue. We used this dataset to compare vulnerability prediction models based on text mining with models using software metrics as predictors. We found that text mining models had higher recall than software metrics based models for all three applications.
Haptic Wave: A Cross-Modal Interface for Visually Impaired Audio Producers

We present the Haptic Wave, a device that allows cross-modal mapping of digital audio to the haptic domain, intended for use by audio producers/engineers with visual impairments. We describe a series of participatory design activities adapted to non-sighted users where the act of prototyping facilitates dialog. A series of workshops scoping user needs, and testing a technology mock up and lo-fidelity prototype fed into the design of a final high-spec prototype. The Haptic Wave was tested in the laboratory, then deployed in real world settings in recording studios and audio production facilities. The cross-modal mapping is kinesthetic and allows the direct manipulation of sound without the translation of an existing visual interface. The research gleans insight into working with users with visual impairments, and transforms perspective to think of them as experts in non-visual interfaces for all users.
Crowd Experience and Performance: An Empirical Analysis of Crowdsourced New Product Development

Crowdsourcing has widely been used as a strategy for sourcing ideas and efforts to facilitate innovation and new product development. However, research into to the value creation of crowdsourcing and the efficacy of the crowd is still limited. In this study, we investigate a crowdsourced new product development context and apply the framework of collective intelligence to understand the crowd co-creation process. Based on the theory of diversity about generalists vs. specialists, we examine the role of prior experience in affecting crowd performance. Our empirical analysis shows that participants with both diverse and specialized experience are helpful in enhancing crowd performance in terms of efficient product development. We also find participants with T-shaped experience in non-focal tasks are beneficial. Contrary to other group contexts, generalists do not seem to be a valuable type in our study context. The findings provide insights for understanding collaboration and value co-creation in crowdsourcing communities.