Miracle-dz/UniFAR-FTUs huggingface dataset:
A Formalism for Active and Informative Web Services

In our previous works, we issued a significant difference between active Web services, that help carry out an action - e.g. buying a ticket to next Saturday's representation in the theater - and informative Web services that merely search for information - e.g. querying some databases to get a list of available CD's. This paper presents a dynamic logic for modeling accurately this distinction among composite Web services. We use a logical formalism allowing a calculus on complex Web services preconditions and effects. On the one hand, this formalism enlightens that active Web services modeling does not fall back to database update, when resources are taken into account (e.g. the number of seats in the theater). On the other hand, it models active Web service as a composed one : an informative Web service gathers information, a choice function is applied and feeds the input of an updating Web service.
An Analysis of Online Twitter Sentiment Surrounding the European Refugee Crisis

Using existing natural language and sentiment analysis techniques, this study explores different dimensions of mood states of tweet content relating to the refugee crisis in Europe. The study has two main goals. The first goal is to compare the mood states of negative emotion, positive emotion, anger and anxiety across two populations (English and German speaking). The second goal is to discover if a link exists between significant real-world events relating to the refugee crisis and online sentiment on Twitter. Gaining an insight into this comparison and relationship can help us firstly, to better understand how these events shape public attitudes towards refugees and secondly, how online expressions of emotion are affected by significant events.
Gremlin-1 Induces BMP-Independent Tumor Cell Proliferation, Migration, and Invasion

Gremlin-1, a bone morphogenetic protein (BMP) antagonist, is overexpressed in various cancerous tissues but its role in carcinogenesis has not been established. Here, we report that gremlin-1 binds various cancer cell lines and this interaction is inhibited by our newly developed gremlin-1 antibody, GRE1. Gremlin-1 binding to cancer cells was unaffected by the presence of BMP-2, BMP-4, and BMP-7. In addition, the binding was independent of vascular endothelial growth factor receptor-2 (VEGFR2) expression on the cell surface. Addition of gremlin-1 to A549 cells induced a fibroblast-like morphology and decreased E-cadherin expression. In a scratch wound healing assay, A549 cells incubated with gremlin-1 or transfected with gremlin-1 showed increased migration, which was inhibited in the presence of the GRE1 antibody. Gremlin-1 transfected A549 cells also exhibited increased invasiveness as well as an increased growth rate. These effects were also inhibited by the addition of the GRE1 antibody. In conclusion, this study demonstrates that gremlin-1 directly interacts with cancer cells in a BMP- and VEGFR2-independent manner and can induce cell migration, invasion, and proliferation.
Design and implementation of a novel conical electrode for fast anodic bonding

Anodic bonding is a frequently used nonintermediate wafer-bonding technique for use in MEMS. However, it has a minimum bonding time for a 4 in silicon/glass wafer that is generally limited to the order of several minutes because of the gas-trapping problem that occurs in the bonded interface when a conventional bonding electrode is used. Therefore, the purpose of this study was to develop a novel conical bonding electrode, which shortens the bonding time and solves the gas-trapping problem of the bonded interface. The 4 in silicon/glass wafers fitted with the proposed electrode exhibited a bonding ratio of 99.89% and an average bonding strength of around 15 MPa, which was attained within 15 s, at a bonding voltage of 900 V and a bonding temperature of 400 °C. A comprehensive series of experiments was performed to validate the excellent bonding performance of the proposed conical electrode.
Embedding of Embedding (EOE): Joint Embedding for Coupled Heterogeneous Networks

Network embedding is increasingly employed to assist network analysis as it is effective to learn latent features that encode linkage information. Various network embedding methods have been proposed, but they are only designed for a single network scenario. In the era of big data, different types of related information can be fused together to form a coupled heterogeneous network, which consists of two different but related sub-networks connected by inter-network edges. In this scenario, the inter-network edges can act as comple- mentary information in the presence of intra-network ones. This complementary information is important because it can make latent features more comprehensive and accurate. And it is more important when the intra-network edges are ab- sent, which can be referred to as the cold-start problem. In this paper, we thus propose a method named embedding of embedding (EOE) for coupled heterogeneous networks. In the EOE, latent features encode not only intra-network edges, but also inter-network ones. To tackle the challenge of heterogeneities of two networks, the EOE incorporates a harmonious embedding matrix to further embed the em- beddings that only encode intra-network edges. Empirical experiments on a variety of real-world datasets demonstrate the EOE outperforms consistently single network embedding methods in applications including visualization, link prediction multi-class classification, and multi-label classification.
An H-infinity approach to stealth-resilient control design

We revisit the problem of stealth attack - a coordinated attack through several possible entry points - on a closed loop linear time invariant dynamical system. We propose a notion of the impact of such an attack on the system and consider a novel metric related to the H-infinity norm of the inverse of the system dynamics (assuming it exists) as a measure of the security of the system. We show that the problem can be cast as a linear matrix inequality optimization with the system parameters (observer gain) as the variable. This formulation allows a user to re-design the system from the perspective of minimizing the impact of any stealth attack. Numerical results on simulated data illustrate the security and performance tradeoff using the proposed approach.
Improving Pivot-Based Statistical Machine Translation by Pivoting the Co-occurrence Count of Phrase Pairs

To overcome the scarceness of bilingual corpora for some language pairs in machine translation, pivot-based SMT uses pivot language as a "bridge" to generate source-target translation from sourcepivot and pivot-target translation. One of the key issues is to estimate the probabilities for the generated phrase pairs. In this paper, we present a novel approach to calculate the translation probability by pivoting the co-occurrence count of source-pivot and pivot-target phrase pairs. Experimental results on Europarl data and web data show that our method leads to significant improvements over the baseline systems.
The GSA Difference: LGBTQ and Ally Experiences in High Schools with and without Gay-Straight Alliances

We examine the lived experiences of high-school students who participated in lesbian, gay, bisexual, transgender, and queer (LGBTQ)-centered activism of some kind, highlighting the promise of gay-straight alliance groups by comparing the experiences of students at schools with gay-straight alliances (GSA schools) with the experiences of students at schools that did not have an LGBTQ-specific group (no-GSA schools). We compare students at GSA and no-GSA schools based on their experiences of harassment, experiences of support from authority figures, and patterns of friendships. We find that students at both types of schools experienced harassment and heard negative comments about lesbian and gay people. However, students at GSA schools reported more support from teachers and administrators than students at no-GSA schools, who have stories of teachers and administrators actively opposing equality for LGBTQ people. Students at GSA schools reported a wide variety of friendships across sexual identities, while students at no-GSA schools felt more isolated and withdrawn. This much-needed qualitative comparative analysis of students’ experiences brings a human face to the improved quality of life that schools with gay-straight alliances can bring to young people.
A $W$ -band High LO-to-RF Isolation Triple Cascode Mixer With Wide IF Bandwidth

A W-band triple cascode down conversion mixer using a 0.15- μm pseudomorphic high-electron mobility transistor process is proposed in this paper. Due to the utilization of modified bias topology, resistive mixing core, and IF low-pass filter, this circuit has a very wide IF bandwidth. Moreover, the triple cascode structure is used in this mixer for high local oscillator (LO)-to-RF isolation and compact chip area. The measured results illustrate that the mixer achieves 9-13-dB upper sideband conversion loss with dc-to-26-GHz IF bandwidth, and the LO-to-IF, LO-to-RF, and RF-to-IF isolation are 38, 42, and 40 dB, respectively with 5-dBm LO power at 86 GHz. When the LO power is 7 dBm at 96 GHz, the upper sideband conversion loss is 10-14 dB with dc-to-24-GHz IF bandwidth, and LO-to-IF, LO-to-RF, and RF-to-IF isolation are 29, 41.5, and 45 dB, respectively. The power consumption is 24 mW and chip area is 1 mm2.
Redox-dependent stability, protonation, and reactivity of cysteine-bound heme proteins

Significance Metal thiolates are common components of electron transfer proteins, enzymes, and redox sensors. Reduction of ferric thiolate hemes often involves protonation of the Cys ligand and ligand loss or substitution. These reactions contribute to enzyme inactivation and form the basis of sensing functions, but their mechanistic details are not well understood, particularly in proteins. A neutral thiol is a viable ligand to the heme; however, analysis of this interaction has been challenging. Herein, we describe a series of model proteins that offer detailed spectroscopic and thermodynamic characterization of ferric thiolate and ferrous thiol species as well as their interconversions. Results have shed light on the forces that control a particular heme ligation and redox reactivity of these key bioinorganic centers. Cysteine-bound hemes are key components of many enzymes and biological sensors. Protonation (deprotonation) of the Cys ligand often accompanies redox transformations of these centers. To characterize these phenomena, we have engineered a series of Thr78Cys/Lys79Gly/Met80X mutants of yeast cytochrome c (cyt c) in which Cys78 becomes one of the axial ligands to the heme. At neutral pH, the protonation state of the coordinated Cys differs for the ferric and ferrous heme species, with Cys binding as a thiolate and a thiol, respectively. Analysis of redox-dependent stability and alkaline transitions of these model proteins, as well as comparisons to Cys binding studies with the minimalist heme peptide microperoxidase-8, demonstrate that the protein scaffold and solvent interactions play important roles in stabilizing a particular Cys–heme coordination. The increased stability of ferric thiolate compared with ferrous thiol arises mainly from entropic factors. This robust cyt c model system provides access to all four forms of Cys-bound heme, including the ferric thiol. Protein motions control the rates of heme redox reactions, and these effects are amplified at low pH, where the proteins are less stable. Thermodynamic signatures and redox reactivity of the model Cys-bound hemes highlight the critical role of the protein scaffold and its dynamics in modulating redox-linked transitions between thiols and thiolates.
How and when should interactome-derived clusters be used to predict functional modules and protein function?

Motivation: Clustering of protein–protein interaction networks is one of the most common approaches for predicting functional modules, protein complexes and protein functions. But, how well does clustering perform at these tasks? Results: We develop a general framework to assess how well computationally derived clusters in physical interactomes overlap functional modules derived via the Gene Ontology (GO). Using this framework, we evaluate six diverse network clustering algorithms using Saccharomyces cerevisiae and show that (i) the performances of these algorithms can differ substantially when run on the same network and (ii) their relative performances change depending upon the topological characteristics of the network under consideration. For the specific task of function prediction in S.cerevisiae, we demonstrate that, surprisingly, a simple non-clustering guilt-by-association approach outperforms widely used clustering-based approaches that annotate a protein with the overrepresented biological process and cellular component terms in its cluster; this is true over the range of clustering algorithms considered. Further analysis parameterizes performance based on the number of annotated proteins, and suggests when clustering approaches should be used for interactome functional analyses. Overall our results suggest a re-examination of when and how clustering approaches should be applied to physical interactomes, and establishes guidelines by which novel clustering approaches for biological networks should be justified and evaluated with respect to functional analysis. Contact: msingh@cs.princeton. edu Supplementary information: Supplementary data are available at Bioinformatics online.
Salience-adaptive Painterly Rendering Using Genetic Search

We present a new non-photorealistic rendering (NPR) algorithm for rendering photographs in an impasto painterly style. We observe that most existing image-based NPR algorithms operate in a spatially local manner, typically as non-linear image filters seeking to preserve edges and other high-frequency content. By contrast, we argue that figurative artworks are salience maps, and develop a novel painting algorithm that uses a genetic algorithm (GA) to search the space of possible paintings for a given image, so approaching an "optimal" artwork in which salient detail is conserved and non-salient detail is attenuated. Differential rendering styles are also possible by varying stroke style according to the classification of salient artifacts encountered, for example edges or ridges. We demonstrate the results of our technique on a wide range of images, illustrating both the improved control over level of detail due to our salience adaptive painting approach, and the benefits gained by subsequent relaxation of the painting using the GA.
Risk factors for developing delirium in older patients admitted to general medical wards.

BACKGROUND Delirium in older patients is common and leads to poor clinical outcomes. It is, however, preventable if its risk factors are identified and modified accordingly. OBJECTIVE To determine risk factors associated with delirium in hospitalized older patients admitted to general medical wards at Siriraj Hospital. MATERIAL AND METHOD A prospective observational study was conducted at general medical wards, Siriraj Hospital. All consecutive patients aged 70 years or older admitted during study period were assessed and followed until discharge. A diagnosis of delirium was made if patients developed symptoms which fulfilled DSM IV criteria. Information regarding demographic data, co-morbid illnesses, preexisting cognitive status and functional status was collected at admission. Factorf associated with delirium were analyzed using logistic regression models. RESULTS Risk factors associated with developing delirium identified from univariate analysis were female gender, age more than 80 years-old, having 4 or more co-morbidities, azothemia, hyponatremia, presence of infection, severe illness, preexisting dementia, depression, and impaired basic activities of daily living. After adjusted in multivariate analysis; factors those remained statistically significant were preexisting dementia (OR = 5.52, 95% CI = 2.51-12.14), severe illness (OR = 5.18, 95% CI = 2.10-12.76) presence of infection (OR = 2.54, 95% CI = 1.15-5.61) and azothemia (OR = 2.55, 95% CI = 1.205.40). CONCLUSION Pre-existing dementia and illness severity were strongly associated with developing delirium in older patients in the present study, which is concordant with previous studies. Other factors such as presence of infection and azothemia are modifiable factors that could potentially be important targets, along with other factors identified in the present study, for implementing intervention in order to prevent delirium in this population.
iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels

Conotoxins are small disulfide-rich neurotoxic peptides, which can bind to ion channels with very high specificity and modulate their activities. Over the last few decades, conotoxins have been the drug candidates for treating chronic pain, epilepsy, spasticity, and cardiovascular diseases. According to their functions and targets, conotoxins are generally categorized into three types: potassium-channel type, sodium-channel type, and calcium-channel types. With the avalanche of peptide sequences generated in the postgenomic age, it is urgent and challenging to develop an automated method for rapidly and accurately identifying the types of conotoxins based on their sequence information alone. To address this challenge, a new predictor, called iCTX-Type, was developed by incorporating the dipeptide occurrence frequencies of a conotoxin sequence into a 400-D (dimensional) general pseudoamino acid composition, followed by the feature optimization procedure to reduce the sample representation from 400-D to 50-D vector. The overall success rate achieved by iCTX-Type via a rigorous cross-validation was over 91%, outperforming its counterpart (RBF network). Besides, iCTX-Type is so far the only predictor in this area with its web-server available, and hence is particularly useful for most experimental scientists to get their desired results without the need to follow the complicated mathematics involved.
Quality Assurance of Open Source Components: Integrator Point of View

The breakthrough of open source software (OSS) is not only evident when looking at the gradually rising interest in OSS research but also when observing the field of software business. Clearly OSS provides one of many opportunities for companies to speed up their software development and lower its costs. However, there are risks involved in using open source (OS) components such as multitude of licenses and lack of liabilities and information when it comes to the quality of the components. Considering quality it is perilous to include components with questionable quality to software development project. This is particularly true in product family engineering (PFE) and component based software engineering (CBSE), since the effects of low quality are experienced on a larger scale than a single project. Therefore it is imperative to study how commercial companies today perceive and assure the quality of these components in their new context and environment and what are the conceptions of companies about QA in OS communities. The research was conducted by interviewing representatives of nine Finnish IT companies utilizing OS components
Clostridium and Bacillus Binary Enterotoxins: Bad for the Bowels, and Eukaryotic Being

Some pathogenic spore-forming bacilli employ a binary protein mechanism for intoxicating the intestinal tracts of insects, animals, and humans. These Gram-positive bacteria and their toxins include Clostridium botulinum (C2 toxin), Clostridium difficile (C. difficile toxin or CDT), Clostridium perfringens (ι-toxin and binary enterotoxin, or BEC), Clostridium spiroforme (C. spiroforme toxin or CST), as well as Bacillus cereus (vegetative insecticidal protein or VIP). These gut-acting proteins form an AB complex composed of ADP-ribosyl transferase (A) and cell-binding (B) components that intoxicate cells via receptor-mediated endocytosis and endosomal trafficking. Once inside the cytosol, the A components inhibit normal cell functions by mono-ADP-ribosylation of globular actin, which induces cytoskeletal disarray and death. Important aspects of each bacterium and binary enterotoxin will be highlighted in this review, with particular focus upon the disease process involving the biochemistry and modes of action for each toxin.
A rhenium review – from discovery to novel applications

Purpose: The article characterises rhenium in terms of its physiochemical properties, most popular methods of manufacturing and key applications. The examples of rhenium at a nanometric scales are also presented, taking into account the latest literature reports in this field. The objective of the article is also to present advanced nanocomposite materials consisting of nanostructured rhenium permanently attached to selected carbon nanomaterials Single Walled Carbon NanoTubes (SWCNTs), Double Walled Carbon NanoTubes (DWCNTs), Multi Walled Carbon NanoTubes (MWCNTs) and Single Walled Carbon Nanohorns (SWCNHs). Design/methodology/approach: The article delineates various manufacturing methods at a mass and nanometric scale. It also describes a custom fabrication method of carbonrhenium nanocomposites and the results of investigations performed in a transmission electron microscope (TEM) for nanocomposites of the following type: MWCNTs-Re, SWCNTs/DWCNTs-Re, SWCNTs-Re and SWCNHs-Re. Findings: Rhenium has been gaining growing importance in industry for years, and its applications are very diverse, including: heat resistant alloys, anti-corrosive alloys, rhenium and rhenium alloy coatings, elements of electrical equipment, radiotherapy, chemistry and analytical technology and catalysis. Carbon-metallic nanocomposites are currently enjoying strong attention of research institutions. Research limitations/implications: The development and optimisation of fabrication processes of materials containing carbon nanotubes or carbon nanotubes coated with metal nanoparticles, especially rhenium, is a weighty aspect of advanced materials engineering. Practical implications: Newly created nanocomposite materials, developed as a response to the market demand, are interesting, state-of-the-art materials dedicated to various applications, especially as gas or fluid sensors, and as materials possessing catalytic properties. Originality/value: The article describes nanocomposites of the following types: MWCNTsRe, SWCNTs/DWCNTs-Re, SWCNTs-Re, SWCNHs-Re, created as a result of hightemperature reduction of a precursor of rhenium (HReO4 or NH4ReO4) to metallic rhenium. This metal is deposited on carbon nanomaterials as nanoparticles, or inside of them as nanoparticles or nanowires whose size and dispersion are dependent upon the conditions of a technological process.