Miracle-dz/UniFAR-FTUs huggingface dataset:
SAR speckle filtering and automatic feature extraction: An innovative integrated algorithm

Filtering processes are necessary in order to extract automatically useful information from Synthetic Aperture Radar (SAR) data. Galileian Plus S r.l. (GPLUS) developed an innovative proprietary procedure (European Patent EP2146315 of 2009), which takes off from the demand of maintaining high spatial details of nowadays SAR sensors during the filtering process, while at the same time improving the data radiometric resolution. In this article, the innovative filtering procedure is described in details, by giving particular importance to mathematical definition of the non-linear transfer function Gα,β. Comparisons with the state-of-the-art of speckle filters show the enhancement and benefits of GPLUS filter, not only for visual interpretation of the data but mainly for automatic classification and feature extraction purposes. The two applications described in the paper show the potentiality and the step ahead performed with this algorithm: automated classification and extraction processes based on SAR imagery move straight towards a wider range of applications.
Rapid fluorescence imaging of spinal cord following epidural administration of a nerve-highlighting fluorophore

Iatrogenic spinal cord injury (SCI) is the most devastating complication of spine surgery, which usually results in permanent and serious disabilities of patients. Improvement of the visualization and discrimination of the spinal cord is critical for accuracy and safety during surgery; however, to date, there is no suitable technology to fulfill this clinical need. Here, we first show an efficient and rapid fluorescence imaging of the spinal cord in rabbit by epidural administration of a nerve-highlighting fluorophore, i.e. (E, E)-1,4-bis(p-aminostryl)-2-methoxy benzene (BMB). The BMB is firstly encapsulated into polymeric micelles to form a BMB-micelle (BMB-m) formulation with well-dispersion in normal saline solution. After epidural administration of BMB-m, BMB is transported by the flow of cerebrospinal fluid (CSF) and binds to the peripheral region of the white matter thus facilitating rapid staining of the spinal cord. Furthermore, this BMB imaging technology also holds great potential for visually monitoring the integrity of the spinal cord in real time and promptly identifying acute SCI during spine surgery.
High Dielectric Constant of Silver Nanowires–Epoxy Composites

Silver nanowires–epoxy composites were prepared via cryomilling dispersion and hot-press forming process. The microstructure of the silver nanowires was studied by SEM. Dependence of dielectric properties of the composites on volume fraction of silver nanowires and frequency was investigated RF impedance material analyzer. The percolation threshold of the composites was 0.16, the value of the dielectric constant of the composite was as high as 100.
GCPred: a web tool for guanylyl cyclase functional centre prediction from amino acid sequence

Summary GCPred is a webserver for the prediction of guanylyl cyclase (GC) functional centres from amino acid sequence. GCs are enzymes that generate the signalling molecule cyclic guanosine 3', 5'-monophosphate from guanosine-5'-triphosphate. A novel class of GC centres (GCCs) has been identified in complex plant proteins. Using currently available experimental data, GCPred is created to automate and facilitate the identification of similar GCCs. The server features GCC values that consider in its calculation, the physicochemical properties of amino acids constituting the GCC and the conserved amino acids within the centre. From user input amino acid sequence, the server returns a table of GCC values and graphs depicting deviations from mean values. The utility of this server is demonstrated using plant proteins and the human interleukin-1 receptor-associated kinase family of proteins as example. Availability and implementation The GCPred server is available at http://gcpred.com. Supplementary information Supplementary data are available at Bioinformatics online.
Feasibility of Homomorphic Encryption for Sharing I2B2 Aggregate-Level Data in the Cloud

The biomedical community is lagging in the adoption of cloud computing for the management of medical data. The primary obstacles are concerns about privacy and security. In this paper, we explore the feasibility of using advanced privacy-enhancing technologies in order to enable the sharing of sensitive clinical data in a public cloud. Our goal is to facilitate sharing of clinical data in the cloud by minimizing the risk of unintended leakage of sensitive clinical information. In particular, we focus on homomorphic encryption, a specific type of encryption that offers the ability to run computation on the data while the data remains encrypted. This paper demonstrates that homomorphic encryption can be used efficiently to compute aggregating queries on the ciphertexts, along with providing end-to-end confidentiality of aggregate-level data from the i2b2 data model.
Generic Modelling with Graph Rewriting Systems

One of the main goals of the software engineering discipline is the provision of appropriate tools for the construction of complex and interactive software systems. A large number of tools, languages, and methods exist to cope with the problems of administering the documents, information, and processes of creating large software systems. Specification languages and methods have been developed to describe formal aspects of these complex and interactive systems. At the Department of Computer Science III at Aachen University of Technology, the specification language PROGRES (PROgrammed Graph REwriting System) has been developed in the context of the IPSEN (Interactive/Integrated/Incremental Project Support ENvironment) research project. With PROGRES it is possible to formally describe complex graph-based structures and operations on these structures. Furthermore, it is possible to generate rapid prototypes of the specified software systems as stand-alone applications. In this thesis we have used the PROGRES specification system together with the rapid prototyping framework to build tools for editing, analysing, and interpreting visual languages. During a collaborative research with the Department for Process Control Engineering we have built such tools for an IEC-61131/3 compliant language which is widely used in the automation and process control industry. We have detected shortcomings of the PROGRES language for the specification of such large systems. The identified problems of the PROGRES language are mainly dealing with reusability of specified code. Many modern programming languages offer genericity for modelling reusable software units, often together with an object-oriented programming methodology which also gives users support in an easy adaption of real-world problems to formal models. In this thesis we have examined those programming and modelling languages and improved the PROGRES language by corresponding concepts. As being a statically typed specification language, PROGRES already has an elaborate two-level typing system. We have extended this typing system to allow for generic modelling of specification units.
Loss of CtIP disturbs homologous recombination repair and sensitizes breast cancer cells to PARP inhibitors

Breast cancer is one of the leading causes of death worldwide, and therefore, new and improved approaches for the treatment of breast cancer are desperately needed. CtIP (RBBP8) is a multifunctional protein that is involved in various cellular functions, including transcription, DNA replication, DNA repair and the G1 and G2 cell cycle checkpoints. CtIP plays an important role in homologous recombination repair by interacting with tumor suppressor protein BRCA1. Here, we analyzed the expression profile of CtIP by data mining using published microarray data sets. We found that CtIP expression is frequently decreased in breast cancer patients, and the patient group with low-expressing CtIP mRNA is associated with a significantly lower survival rate. The knockdown of CtIP in breast cancer MCF7 cells reduced Rad51 foci numbers and enhanced f H2AX foci formation after f-irradiation, suggesting that deficiency of CtIP decreases homologous recombination repair and delays DNA double strand break repair. To explore the effect of CtIP on PARP inhibitor therapy for breast cancer, CtIP-depleted MCF7 cells were treated with PARP inhibitor olaparib (AZD2281) or veliparib (ABT-888). As in BRCA mutated cells, PARP inhibitors showed cytotoxicity to CtIP-depleted cells by preventing cells from repairing DNA damage, leading to decreased cell viability. Further, a xenograft tumor model in mice with MCF7 cells demonstrated significantly increased sensitivity towards PARP inhibition under CtIP deficiency. In summary, this study shows that low level of CtIP expression is associated with poor prognosis in breast cancer, and provides a rationale for establishing CtIP expression as a biomarker of PARP inhibitor response, and consequently offers novel therapeutic options for a significant subset of patients.
Understanding the Differences between Proprietary & Free and Open Source Software

Proprietary software is the one which is owned by an individual or a company. They are almost always major restrictions on its use, and its source code is always kept secret. Examples include the products delivered by Microsoft, the Windows family of operating systems and Microsoft office. On the other hand Open source software has recently become a major interest in the software industry. Open source software includes free software and public domain software. Open source software generally same as free software is available at no or with limited cost to everyone along with the source code, and it can be used by any one for any purpose and with minimal restrictions. In this paper we would like to focus some of the differences between the Proprietary and Open source software in general terms and in particular in terms of their evolution, verifiability of Lehman laws of software evolution, Style of development, the participants in the development and evolution and the differences in the users’ perspective.
Transport Control Strategies in Named Data Networking: A Survey

Different from traditional IP networks, named data networking (NDN) based on the named content can realize fast content retrieval and delivery. As one of the most important architectures for the future Internet, NDN needs flexible, effective, and efficient transport control strategies, which are crucial for widely development of NDN. In this paper, we present a comprehensive survey and research challenges on transport control of NDN for the first of time. We first provide an introduction of NDN and its data transport process. Then, the essential differences of NDN transport control compared with IP transport control are analyzed and compared from three perspectives: users side, routers, and network provider. Next, an in-depth taxonomy and classification of NDN recent transport control proposals is given. Finally, we present some research challenges and broader perspectives.
A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression

Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction, or network inference problems. During the past decade, kernel methods have played a dominant role in pairwise learning. They still obtain a state-of-the-art predictive performance, but a theoretical analysis of their behavior has been underexplored in the machine learning literature. In this work we review and unify kernel-based algorithms that are commonly used in different pairwise learning settings, ranging from matrix filtering to zero-shot learning. To this end, we focus on closed-form efficient instantiations of Kronecker kernel ridge regression. We show that independent task kernel ridge regression, two-step kernel ridge regression, and a linear matrix filter arise naturally as a special case of Kronecker kernel ridge regression, implying that all these methods implicitly minimize a squared loss. In addition, we analyze universality, consistency, and spectral filtering properties. Our theoretical results provide valuable insights into assessing the advantages and limitations of existing pairwise learning methods.
Sex‐antagonistic genes, XY recombination and feminized Y chromosomes

The canonical model of sex‐chromosome evolution predicts that sex‐antagonistic (SA) genes play an instrumental role in the arrest of XY recombination and ensuing Y chromosome degeneration. Although this model might account for the highly differentiated sex chromosomes of birds and mammals, it does not fit the situation of many lineages of fish, amphibians or nonavian reptiles, where sex chromosomes are maintained homomorphic through occasional XY recombination and/or high turnover rates. Such situations call for alternative explanatory frameworks. A crucial issue at stake is the effect of XY recombination on the dynamics of SA genes and deleterious mutations. Using individual‐based simulations, we show that a complete arrest of XY recombination actually benefits females, not males. Male fitness is maximized at different XY recombination rates depending on SA selection, but never at zero XY recombination. This should consistently favour some level of XY recombination, which in turn generates a recombination load at sex‐linked SA genes. Hill–Robertson interferences with deleterious mutations also impede the differentiation of sex‐linked SA genes, to the point that males may actually fix feminized phenotypes when SA selection and XY recombination are low. We argue that sex chromosomes might not be a good localization for SA genes, and sex conflicts seem better solved through the differential expression of autosomal genes.
Impact of Exercise on Cardiometabolic Component Risks in Spinal Cord–injured Humans

Purpose Spinal cord injury (SCI) creates a complex pathology, characterized by low levels of habitual physical activity and an increased risk of cardiometabolic disease. This study aimed to assess the effect of a moderate-intensity upper-body exercise training intervention on biomarkers of cardiometabolic component risks, adipose tissue metabolism, and cardiorespiratory fitness in persons with SCI. Methods Twenty-one inactive men and women with chronic (>1 yr) SCI (all paraplegic injuries) 47 ± 8 yr of age (mean ± SD) were randomly allocated to either a 6-wk prescribed home-based exercise intervention (INT; n = 13) or control group (CON; n = 8). Participants assigned to the exercise group completed 4 × 45-min moderate-intensity (60%–65% peak oxygen uptake (V˙O2peak)) arm-crank exercise sessions per week. At baseline and follow-up, fasted and postload blood samples (collected during oral glucose tolerance tests) were obtained to measure metabolic regulation and biomarkers of cardiovascular disease. Abdominal subcutaneous adipose tissue biopsies were also obtained, and cardiorespiratory fitness was assessed. Results Compared with CON, INT significantly decreased (P = 0.04) serum fasting insulin (&Dgr;, 3.1 ± 10.7 pmol·L−1 for CON and −12.7 ± 18.7 pmol·L−1 for INT) and homeostasis model assessment of insulin resistance (HOMA2-IR; &Dgr;, 0.06 ± 0.20 for CON and −0.23 ± 0.36 for INT). The exercise group also increased V˙O2peak (&Dgr;, 3.4 mL·kg−1·min−1; P ⩽ 0.001). Adipose tissue metabolism, composite insulin sensitivity index (C-ISIMatsuda), and other cardiovascular disease risk biomarkers were not different between groups. Conclusions Moderate-intensity upper-body exercise improved aspects of metabolic regulation and cardiorespiratory fitness. Changes in fasting insulin and HOMA2-IR, but not C-ISIMatsuda, suggest improved hepatic but not peripheral insulin sensitivity after 6 wk of exercise training in persons with chronic paraplegia.
Global brain dynamics during social exclusion predict subsequent behavioral conformity

Abstract Individuals react differently to social experiences; for example, people who are more sensitive to negative social experiences, such as being excluded, may be more likely to adapt their behavior to fit in with others. We examined whether functional brain connectivity during social exclusion in the fMRI scanner can be used to predict subsequent conformity to peer norms. Adolescent males (n = 57) completed a two-part study on teen driving risk: a social exclusion task (Cyberball) during an fMRI session and a subsequent driving simulator session in which they drove alone and in the presence of a peer who expressed risk-averse or risk-accepting driving norms. We computed the difference in functional connectivity between social exclusion and social inclusion from each node in the brain to nodes in two brain networks, one previously associated with mentalizing (medial prefrontal cortex, temporoparietal junction, precuneus, temporal poles) and another with social pain (dorsal anterior cingulate cortex, anterior insula). Using predictive modeling, this measure of global connectivity during exclusion predicted the extent of conformity to peer pressure during driving in the subsequent experimental session. These findings extend our understanding of how global neural dynamics guide social behavior, revealing functional network activity that captures individual differences.
Key Components in eHealth Interventions Combining Self-Tracking and Persuasive eCoaching to Promote a Healthier Lifestyle: A Scoping Review

Background The combination of self-tracking and persuasive eCoaching in automated interventions is a new and promising approach for healthy lifestyle management. Objective The aim of this study was to identify key components of self-tracking and persuasive eCoaching in automated healthy lifestyle interventions that contribute to their effectiveness on health outcomes, usability, and adherence. A secondary aim was to identify the way in which these key components should be designed to contribute to improved health outcomes, usability, and adherence. Methods The scoping review methodology proposed by Arskey and O’Malley was applied. Scopus, EMBASE, PsycINFO, and PubMed were searched for publications dated from January 1, 2013 to January 31, 2016 that included (1) self-tracking, (2) persuasive eCoaching, and (3) healthy lifestyle intervention. Results The search resulted in 32 publications, 17 of which provided results regarding the effect on health outcomes, 27 of which provided results regarding usability, and 13 of which provided results regarding adherence. Among the 32 publications, 27 described an intervention. The most commonly applied persuasive eCoaching components in the described interventions were personalization (n=24), suggestion (n=19), goal-setting (n=17), simulation (n=17), and reminders (n=15). As for self-tracking components, most interventions utilized an accelerometer to measure steps (n=11). Furthermore, the medium through which the user could access the intervention was usually a mobile phone (n=10). The following key components and their specific design seem to influence both health outcomes and usability in a positive way: reduction by setting short-term goals to eventually reach long-term goals, personalization of goals, praise messages, reminders to input self-tracking data into the technology, use of validity-tested devices, integration of self-tracking and persuasive eCoaching, and provision of face-to-face instructions during implementation. In addition, health outcomes or usability were not negatively affected when more effort was requested from participants to input data into the technology. The data extracted from the included publications provided limited ability to identify key components for adherence. However, one key component was identified for both usability and adherence, namely the provision of personalized content. Conclusions This scoping review provides a first overview of the key components in automated healthy lifestyle interventions combining self-tracking and persuasive eCoaching that can be utilized during the development of such interventions. Future studies should focus on the identification of key components for effects on adherence, as adherence is a prerequisite for an intervention to be effective.
A biomolecular proportional integral controller based on feedback regulations of protein level and activity

Homeostasis is the capacity of living organisms to keep internal conditions regulated at a constant level, despite environmental fluctuations. Integral feedback control is known to play a key role in this behaviour. Here, I show that a feedback system involving transcriptional and post-translational regulations of the same executor protein acts as a proportional integral (PI) controller, leading to enhanced transient performances in comparison with a classical integral loop. Such a biomolecular controller—which I call a level and activity-PI controller (LA-PI)—is involved in the regulation of ammonium uptake by Escherichia coli through the transporter AmtB. The PII molecules, which reflect the nitrogen status of the cell, inhibit both the production of AmtB and its activity (via the NtrB-NtrC system and the formation of a complex with GlnK, respectively). Other examples of LA-PI controller include copper and zinc transporters, and the redox regulation in photosynthesis. This scheme has thus emerged through evolution in many biological systems, surely because of the benefits it offers in terms of performances (rapid and perfect adaptation) and economy (protein production according to needs).
Mouse Dux is myotoxic and shares partial functional homology with its human paralog DUX4

Abstract D4Z4 repeats are present in at least 11 different mammalian species, including humans and mice. Each repeat contains an open reading frame encoding a double homeodomain (DUX) family transcription factor. Aberrant expression of the D4Z4 ORF called DUX4 is associated with the pathogenesis of Facioscapulohumeral muscular dystrophy (FSHD). DUX4 is toxic to numerous cell types of different species, and over-expression caused dysmorphism and developmental arrest in frogs and zebrafish, embryonic lethality in transgenic mice, and lesions in mouse muscle. Because DUX4 is a primate-specific gene, questions have been raised about the biological relevance of over-expressing it in non-primate models, as DUX4 toxicity could be related to non-specific cellular stress induced by over-expressing a DUX family transcription factor in organisms that did not co-evolve its regulated transcriptional networks. We assessed toxic phenotypes of DUX family genes, including DUX4, DUX1, DUX5, DUXA, DUX4-s, Dux-bl and mouse Dux. We found that DUX proteins were not universally toxic, and only the mouse Dux gene caused similar toxic phenotypes as human DUX4. Using RNA-seq, we found that 80% of genes upregulated by Dux were similarly increased in DUX4-expressing cells. Moreover, 43% of Dux-responsive genes contained ChIP-seq binding sites for both Dux and DUX4, and both proteins had similar consensus binding site sequences. These results suggested DUX4 and Dux may regulate some common pathways, and despite diverging from a common progenitor under different selective pressures for millions of years, the two genes maintain partial functional homology.
Fiber-based Fracture Model for Simulating Soft Tissue Tearing

In this paper, we propose a novel approach for simulating soft tissue tearing, using a model that takes into account the existence of fibers within the tissue. These fibers influence the deformation by introducing anisotropy, and impact the direction of propagation for the fracture during tearing. We describe our approach for simulating, in real-time, the deformation and fracture of anisotropic membranes, and we illustrate our method with the simulation of capsulorhexis, one of the critical steps of cataract surgery.