Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey Of Mobile Health System Infusion Among Healthcare Practitioners

In recent years, clinicians are beginning to utilise Mobile Health Systems (mobile devices with clinical applications) when delivering healthcare services to patients at the point-of-care. For Mobile Health Systems (MHS) to be truly valuable, it is argued that the technological artefact be utilised post-adoption and embedded within the clinicians’ work practices. Infusion is a post-adoptive phase of the Cooper and Zmud (1990) model whereby potential benefits can be obtained by the user through exhaustive use of the IT. Yet, there is a dearth of research focusing on the benefits derived from MHS infusion. In response, an exploratory study is undertaken in this paper whereby a conceptual model with eleven hypotheses is presented and examined. The empirical findings of the developed infusion model reveal key factors which positively impacts MHS infusion (availability, self-efficacy, timecriticality, habit, technology trust and task behaviour). More specifically, it provides empirical evidence surrounding the benefits which can be obtained through the infusion of MHS by clinicians. This study illustrates that infusion leads to improvements in (1) individual effectiveness in terms of clinical care, (2) efficiency in terms of individuals’ workflow, and (3) learning. As a result, this research study contributes to both theory and practice.
Power, Rationality, and the Art of Living Through Socio-Technical Change

Most information systems research takes for granted the assumption that IS practice and associated organizational change can be effectively understood as a process of technical reasoning and acting governed by a mix of concerns about software construction, administrative control, and economic gain. Its mission has been to empower managers, IS engineers, and information and communication technology users with knowledge and techniques for effective decision making. However, empirical research frequently encounters human activity that is at odds with the assumed pattern of rational behavior. Recent work tries to explain behavior in IS and organizational change in terms of social processes rather than as a consideration of rational techniques of professional practice. In this paper we address this ambivalence of the IS field with regard to technical/rational knowledge and practice. We draw from the theoretical work of Michel Foucault on power/knowledge and the aesthetics of existence to argue that the rational techniques of IS practice and the power dynamics of an organization and its social context are closely intertwined, requiring each other to be sustained. Furthermore, we develop a context-specific notion of rationality in IS innovation, through which interested parties judge the value of an innovation for their lives and consequently support or subvert its course. We demonstrate these ideas with a case study of a social security organization in Greece.
cPLC — A cryptographic programming language and compiler

Cryptographic two-party protocols are used ubiquitously in everyday life. While some of these protocols are easy to understand and implement (e.g., key exchange or transmission of encrypted data), many of them are much more complex (e.g., e-banking and e-voting applications, or anonymous authentication and credential systems). For a software engineer without appropriate cryptographic skills the implementation of such protocols is often difficult, time consuming and error-prone. For this reason, a number of compilers supporting programmers have been published in recent years. However, they are either designed for very specific cryptographic primitives (e.g., zero-knowledge proofs of knowledge), or they only offer a very low level of abstraction and thus again demand substantial mathematical and cryptographic skills from the programmer. Finally, some of the existing compilers do not produce executable code, but only metacode which has to be instantiated with mathematical libraries, encryption routines, etc. before it can actually be used. In this paper we present a cryptographically aware compiler which is equally useful to cryptographers who want to benchmark protocols designed on paper, and to programmers who want to implement complex security sensitive protocols without having to understand all subtleties. Our tool offers a high level of abstraction and outputs well-structured and documented Java code. We believe that our compiler can contribute to shortening the development cycles of cryptographic applications and to reducing their error-proneness.
A new approach to array interpolation by generation of artificial shift invariances: interpolated ESPRIT

We address the problem of data independent robust array interpolation over large angular sectors. Previous interpolation methods apply the root-MUSIC principle to interpolation data of a predefined virtual ULA manifold. These methods either suffer from severely biased direction-of-arrival estimates due to interpolation errors or rely on data dependent interpolation matrix design. In this paper a new interpolation approach is proposed. Instead of transforming the original array geometry to the rather restrictive ULA structure, here interpolation is performed with the objective to create a virtual array manifold which is a shifted version of the real array manifold. This artificial shift-invariance can be exploited by the well-known ESPRIT algorithm. A joint design of virtual array geometry and interpolation matrix yields additional degrees of freedom which reduce interpolation errors and allow us to increase the interpolation sector. The new algorithm enjoys both simple design procedure and fast implementation and offers reliable DOA estimation for a wide range of different scenarios.
Characterization of a periplasmic protein involved in iron utilization of Actinobacillus actinomycetemcomitans

The periodontopathic bacterium Actinobacillus actinomycetemcomitans possesses a 35-kDa periplasmic iron-repressible protein. Its regulation is mediated by the Fur protein, as was inferred from the Fur-binding consensus sequence at the -35 position of the gene for the 35-kDa protein and from the relaxed expression of the gene in a mutant with an altered Fur-binding sequence. The 35-kDa protein, designated AfuA, has strong homology to HitA and FbpA of Haemophilus influenzae and Neisseria meningitidis, respectively, which serve as periplasmic iron transport proteins.
Delivering Mobile Cloud Services to the User: Description, Discovery, and Consumption

The mobile cloud computing paradigm can offer relevant and useful services to the users of smart mobile devices. Such public services already exist on the web and in cloud deployments, by implementing common web service standards. However, these services are described by mark-up languages, such as XML, that cannot be comprehended by non-specialists. Furthermore, the lack of common interfaces for related services makes discovery and consumption difficult for both users and software. The problem of service description, discovery, and consumption for the mobile cloud must be addressed to allow users to benefit from these services on mobile devices. This paper introduces our work on a mobile cloud service discovery solution, which is utilised by our mobile cloud middleware, Context Aware Mobile Cloud Services (CAMCS). The aim of our approach is to remove complex mark-up languages from the description and discovery process. By means of the Cloud Personal Assistant (CPA) assigned to each user of CAMCS, relevant mobile cloud services can be discovered and consumed easily by the end user from the mobile device. We present the discovery process, the architecture of our own service registry, and service description structure. CAMCS allows services to be used from the mobile device through a user's CPA, by means of user defined tasks. We present the task model of the CPA enabled by our solution, including automatic tasks, which can perform work for the user without an explicit request.
Evaluating software clustering using multiple simulated authoritative decompositions

Evaluation of software clustering algorithms is typically done by comparing the clustering results to an authoritative decomposition prepared manually by a system expert. A well-known drawback of this approach is the fact that there are many, equally valid ways to decompose a software system, since different clustering objectives create different decompositions. Evaluating all clustering algorithms against a single authoritative decomposition can lead to biased results. In this paper, we introduce LimSim, a novel approach for software clustering evaluation that utilizes multiple simulated authoritative decompositions. We also present experimental results of applying the new approach to evaluate various software clustering algorithms. The results demonstrate the usefulness of LimSim.
Thioredoxin‐interacting protein deficiency induces Akt/Bcl‐xL signaling and pancreatic beta‐cell mass and protects against diabetes

Pancreatic beta‐cell loss through apoptosis represents a key factor in the pathogenesis of diabetes;however, no effective approaches to block this process and preserve endogenous beta‐cell mass are currently available. To study the role of thioredoxin‐interacting protein (TXNIP), a proapoptotic beta‐cell factor we recently identified, we used HcB‐19 (TXNIP nonsense mutation) and beta‐cell‐specific TXNIP knockout (bTKO) mice. Interestingly, HcB‐19 mice demonstrate increased adiposity, but have lower blood glucose levels and increased pancreatic beta‐cell mass (as assessed by morphometry). Moreover, HcB‐19 mice are resistant to streptozotocin‐induced diabetes. When intercrossed with obese, insulin‐resistant, and diabetic mice, double‐mutant BTBRlepob/obtxniphcb/hcb are even more obese, but are protected against diabetes and beta‐cell apoptosis, resulting in a 3‐fold increase in beta‐cell mass. Beta‐cell‐specific TXNIP deletion also enhanced beta‐cell mass (P< 0.005) and protected against diabetes, and terminal deoxynucleotidyl transferase‐mediated nick end labeling (TUNEL) revealed a ~50‐fold reduction in beta‐cell apoptosis in streptozotocin‐treated bTKO mice. We further discovered that TXNIP deficiency induces Akt/Bcl‐xL signaling and inhibits mitochondrial beta‐cell death, suggesting that these mechanisms may mediate the beta‐cell protective effects of TXNIP deficiency. These results suggest that lowering beta‐cell TXNIP expression could serve as a novel strategy for the treatment of type 1 and type 2 diabetes by promoting endogenous beta‐cell survival. —Chen, J., Hui, S. T. , Couto, F. M. , Mungrue, I. N. , Davis, D. B. , Attie, A. D. , Lusis, A. J., Davis, R. A. , Shalev, A. Thioredoxin‐interacting protein deficiency induces Akt/ Bcl‐xL signaling and pancreatic beta‐cell mass and protects against diabetes. FASEB J. 22, 3581–3594 (2008)
Intersecting Two-Dimensional Fractals with Lines

The Twin Dragon and Rauzy fractals are intersected with the real axis. In the Twin Dragon case, unexpectedly from its fractal nature, the intersection is an interval characterized by a finite automaton. For the case of the Rauzy fractal, it is proved that the intersection has infinitely many components.
The non-thermal superbubble in IC 10: the generation of cosmic ray electrons caught in the act

Superbubbles are crucial for stellar feedback, with supposedly high (of the order of 10 per cent) thermalization rates. We combined multiband radio continuum observations from the Very Large Array (VLA) with Effelsberg data to study the non-thermal superbubble (NSB) in IC 10, a starburst dwarf irregular galaxy in the Local Group. Thermal emission was subtracted using a combination of Balmer Hα and VLA 32 GHz continuum maps. The bubble’s nonthermal spectrum between 1.5 and 8.8 GHz displays curvature and can be well fitted with a standard model of an ageing cosmic ray electron population. With a derived equipartition magnetic field strength of 44± 8µG, and measuring the radiation energy density from Spitzer MIPS maps as 5±1×10 −11 erg cm −3 , we determine, based on the spectral curvature, a spectral age of the bubble of 1.0± 0.3 Myr. Analysis of the LITTLE THINGS HI data cube shows an expanding H I hole with 100 pc diameter and a dynamical age of 3.8± 0.3 Myr, centred to within 16 pc on IC 10 X-1, a massive stellar mass black hole (M> 23 M⊙). The results are consistent with the expected evolution for a superbubble with a few massive stars, where a very energetic event like a Type Ic supernova/hypernova has taken place about 1 Myr ago. We discuss alternatives to this interpretation.
Novel Detection of Image Forgery for Exchanged Foreground and Background Using Image Watermarking Based on Alpha Matte

This paper proposes an novel method to detect image forgery for exchanged foreground and background by using image watermarking based on alpha matte. in the proposed method, the DWT-DCT-SVD-based image watermarking is used and applied on the alpha mattes obtained using image matting algorithms. the difference of singular values is used to determine the exchanged foreground or exchanged background. Experimental results show that the proposed method can obtain accurate detection of image forgery for exchanged foreground or background. Therefore, the proposed method is a high-value tool of the image forgery detection.
Active Learning for Information Retrieval : Using 3 D Models As An Example

In this paper, we propose a general approach to content-based information retrieval. We use active learning to produce hidden annotations to improve the retrieval performance. We apply the proposed algorithm to designing a 3D model retrieval system. Our database is composed of approximately 1750 3D models having among 53 attributes that form a complex attribute tree. For each model in the database, we maintain a list of probabilities, each indicating the probability of this model having one of the attributes. During training, the learning algorithm samples models in the database and presents them to the annotator to assign attributes to. For each sampled model, each probability is set to be one or zero depending on whether or not the corresponding attribute is assigned by the annotator. For models that have not been annotated, the learning algorithm estimates their probabilities based on a potential function. Specifically, models close to an annotated model are likely to have the same attributes as the annotated model, so similar probabilities from the annotated model are given to these models. At each stage of the learning, the algorithm is able to determine, among the models that have not been annotated, which model the system is the most uncertain of, and presents it as the next sample to the annotator to assign attributes to. During retrieval, the list of probabilities works as a feature vector for us to calculate the semantic distance between two models, or between the user query and a model in the database. The overall distance between two models is determined by a weighted sum of the semantic distance and the low-level feature distance. We show that with the proposed algorithm, the retrieval performance of the system improves rapidly with the number of annotated samples. Furthermore, we show that active learning outperforms learning based on random sampling.
Crc Is Involved in Catabolite Repression Control of the bkd Operons of Pseudomonas putida andPseudomonas aeruginosa

ABSTRACT Crc (catabolite repression control) protein of Pseudomonas aeruginosa has shown to be involved in carbon regulation of several pathways. In this study, the role of Crc in catabolite repression control has been studied in Pseudomonas putida. The bkd operons of P. putida and P. aeruginosa encode the inducible multienzyme complex branched-chain keto acid dehydrogenase, which is regulated in both species by catabolite repression. We report here that this effect is mediated in both species by Crc. A 13-kb cloned DNA fragment containing the P. putida crc gene region was sequenced. Crc regulates the expression of branched-chain keto acid dehydrogenase, glucose-6-phosphate dehydrogenase, and amidase in both species but not urocanase, although the carbon sources responsible for catabolite repression in the two species differ. Transposon mutants affected in their expression of BkdR, the transcriptional activator of thebkd operon, were isolated and identified as crcand vacB (rnr) mutants. These mutants suggested that catabolite repression in pseudomonads might, in part, involve control of BkdR levels.
Improving Statistical Machine Translation with a Multilingual Paraphrase Database

The multilingual Paraphrase Database (PPDB) is a freely available automatically created resource of paraphrases in multiple languages. In statistical machine translation, paraphrases can be used to provide translation for out-of-vocabulary (OOV) phrases. In this paper, we show that a graph propagation approach that uses PPDB paraphrases can be used to improve overall translation quality. We provide an extensive comparison with previous work and show that our PPDB-based method improves the BLEU score by up to 1.79 percent points. We show that our approach improves on the state of the art in three different settings: when faced with limited amount of parallel training data; a domain shift between training and test data; and handling a morphologically complex source language. Our PPDB-based method outperforms the use of distributional profiles from monolingual source data.
Dynamic Capacity Resizing for Fair Bandwidth Sharing in Virtual Private Networks

A virtual private network (VPN) service is likely to be used by customers as a replacement for networks constructed using private lines, and thus its functionality should include the performance guarantee provided to those customers. To provide guaranteed services, the network provider allocates appropriate capacities to multiple virtual backbone networks such that the underlying network can be shared among them. As VPN users are demanding reliable and dynamic allocation of capacities, recently the capacity resizing approach has been considered as a cost efficient way of providing virtual network services. We propose a new scheme for dynamic allocation of virtual link capacities. The allocated capacities are adjusted dynamically according to the users’ requests such that their capacities are increased in a fair manner and the total reservation does not overwhelm the underlying network. Depending on the network’s status and allocation policy, a virtual link may increase or decrease its capacity, for example, for a monetary incentive. VPN users send control packets whenever they want to resize their capacities, and the network handles them in an efficient and fair way. The simulation and analytic results in this paper show that our scheme is simple and robust such that the users and the network communicate using simple control packets and the link capacities are allocated efficiently. key words: capacity resizing, virtual private network, bandwidth sharing, dynamic allocation
Value-Aware low-power register file architecture

In this paper, we propose a low power register file architecture for embedded processors. The proposed architecture, ”Value-Aware Partitioned Register File (VAP-RF)”, employs a partitioning technique that divides the register file into two partitions such that the most frequently accessed registers are stored in the smaller register partition. In our partitioning algorithm, we introduce an aggressive clock-gating scheme based on narrow-value registers to furthermore reduce power. Experimental results on an ARM processor for selected MiBench workloads show that the proposed architecture has an average power saving of 70% over generic register file structure.
Fast adaptive variational sparse Bayesian learning with automatic relevance determination

In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization approach to SBL. It allows one to adaptively construct a sparse regression or classification function as a linear combination of a few basis functions by minimizing the variational free energy. In the case of non-informative hyperpriors, also referred to as automatic relevance determination, the minimization of the free energy can be efficiently realized by computing the fixed points of the update expressions for the variational distribution of the sparsity parameters. The criteria that establish convergence to these fixed points, termed pruning conditions, allow an efficient addition or removal of basis functions; they also have a simple and intuitive interpretation in terms of a component's signal-to-noise ratio. It has been demonstrated that this interpretation allows a simple empirical adjustment of the pruning conditions, which in turn improves sparsity of SBL and drastically accelerates the convergence rate of the algorithm. The experimental evidence collected with synthetic data demonstrates the effectiveness of the proposed learning scheme.
FIVE MORE MASSIVE BINARIES IN THE CYGNUS OB2 ASSOCIATION

We present the orbital solutions for four OB spectroscopic binaries, MT145, GSC 03161 − 00815, 2MASS J20294666+4105083, and Schulte 73, and the partial orbital solution to the B spectroscopic binary, MT372, as part of an ongoing study to determine the distribution of orbital parameters for massive binaries in the Cygnus OB2 Association. MT145 is a new, single-lined, moderately eccentric (e = 0.291 ± 0.009) spectroscopic binary with period of 25.140 ± 0.008 days. GSC 03161 − 00815 is a slightly eccentric (e = 0.10 ± 0.01), eclipsing, interacting and double-lined spectroscopic binary with a period of 4.674 ± 0.004 days. 2MASS J20294666+4105083 is a moderately eccentric (e = 0.273 ± 0.002) double-lined spectroscopic binary with a period of 2.884 ± 0.001 days. Schulte 73 is a slightly eccentric (e = 0.169 ± 0.009), double-lined spectroscopic binary with a period of 17.28 ± 0.03 days and the first “twin” in our survey with a mass ratio of q = 0.99 ± 0.02. MT372 is a single-lined, eclipsing system with a period of 2.228 days and low eccentricity (e ∼ 0). Of the now 18 known OB binaries in Cyg OB2, 14 have periods and mass ratios. Emerging evidence also shows that the distribution of log(P) is flat and consistent with “Öpik's Law. ”
Mining twitterspace for information: Classifying sentiments programmatically using Java

People increasingly use Twitter to share advice, opinions, news, moods, concerns, facts, rumors, and everything else imaginable. Much of that data is public and available for mining. However, classifying automatically the sentiment of the Twitter messages into either positive or negative with respect to a query term represents a new research challenge. Variety of approaches that use natural language and statistical techniques failed to report high accuracy of tweets classification due to the nature of these tweets containing large number of abbreviations, emoticons and ill structured grammar. In this article we are presenting a programming approach that uses the Weka data mining APIs to classify tweets. Using this programming approach we can experiment on how to train the classifiers and determine which one is more effective than the others. In our experiments, the K* classifier is found to report a high degree of accuracy in tweets classification.