LLukas22/scidocs huggingface dataset:
Circuit for Reversible Quantum Multiplier Based on Binary Tree Optimizing Ancilla and Garbage Bits

Reversible logic has emerged as a promising computing paradigm having applications in quantum computing, optical computing, dissipation less computing and low power computing etc. In reversible logic there exists a one to one mapping between the input and output vectors. Reversible circuits require constant ancilla inputs for reconfiguration of gate functions and garbage outputs that help in keeping reversibility. Quantum circuits of many qubits are extremely difficult to realize thus reduction in the number of ancilla inputs and the garbage outputs is the primary goal of optimization. In existing literature researchers have proposed several designs of reversible quantum multipliers based on reversible full adders and reversible half adders. The use of reversible full adders and the half adders for the addition of partial products increases the overhead in terms of number of ancilla inputs and number of garbage outputs. This paper presents a binary tree based design methodology for a NxN reversible quantum multiplier. The proposed binary tree based design methodology for NxN reversible quantum multiplier performs the addition of partial products in parallel using the reversible ripple quantum adders with no garbage output and ancilla bit, thereby minimizing the number of ancilla and garbage bits used in the design. The proposed design methodology shows the improvement of 17.86% to 60.34% in terms of ancilla inputs; and 21.43% to 52.17% in terms of garbage outputs compared to all the existing reversible quantum multiplier designs.
MalDozer: Automatic framework for android malware detection using deep learning

Android OS experiences a blazing popularity since the last few years. This predominant platform has established itself not only in the mobile world but also in the Internet of Things (IoT) devices. This popularity, however, comes at the expense of security, as it has become a tempting target of malicious apps. Hence, there is an increasing need for sophisticated, automatic, and portable malware detection solutions. In this paper, we propose MalDozer, an automatic Android malware detection and family attribution framework that relies on sequences classification using deep learning techniques. Starting from the raw sequence of the app's API method calls, MalDozer automatically extracts and learns the malicious and the benign patterns from the actual samples to detect Android malware. MalDozer can serve as a ubiquitous malware detection system that is not only deployed on servers, but also on mobile and even IoT devices. We evaluate MalDozer on multiple Android malware datasets ranging from 1 K to 33 K malware apps, and 38 K benign apps. The results show that MalDozer can correctly detect malware and attribute them to their actual families with an F1-Score of 96%e99% and a false positive rate of 0.06% e2%, under all tested datasets and settings. © 2018 The Author(s). Published by Elsevier Ltd on behalf of DFRWS. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Interaction design gone wild: striving for wild theory

bricolage, they can rapidly combine, customize, and embed a whole range of innovative technologies in real-world environments in ways that were unimaginable a decade ago. Armies of computer scientists and engineers are no longer needed. Interaction designers, with less technical expertise and modest resources, can conjure, create, and deploy a diversity of prototypes in all manner of places in the everyday world.
Research Paper: A Randomized Trial Comparing Telemedicine Case Management with Usual Care in Older, Ethnically Diverse, Medically Underserved Patients with Diabetes Mellitus

BACKGROUND
Telemedicine is a promising but largely unproven technology for providing case management services to patients with chronic conditions who experience barriers to access to care or a high burden of illness.


METHODS
The authors conducted a randomized, controlled trial comparing telemedicine case management to usual care, with blinding of those obtaining outcome data, in 1,665 Medicare recipients with diabetes, aged 55 years or greater, and living in federally designated medically underserved areas of New York State. The primary endpoints were HgbA1c, blood pressure, and low-density lipoprotein (LDL) cholesterol levels.


RESULTS
In the intervention group (n = 844), mean HgbA1c improved over one year from 7.35% to 6.97% and from 8.35% to 7.42% in the subgroup with baseline HgbA1c > or =7% (n = 353). In the usual care group (n = 821) mean HgbA1c improved over one year from 7.42% to 7.17%. Adjusted net reductions (one-year minus baseline mean values in each group, compared between groups) favoring the intervention were as follows: HgbA1c, 0.18% (p = 0.006), systolic and diastolic blood pressure, 3.4 (p = 0.001) and 1.9 mm Hg (p < 0.001), and LDL cholesterol, 9.5 mg/dL (p < 0.001). In the subgroup with baseline HgbA1c > or =7%, net adjusted reduction in HgbA1c favoring the intervention group was 0.32% (p = 0.002). Mean LDL cholesterol level in the intervention group at one year was 95.7 mg/dL. The intervention effects were similar in magnitude in the subgroups living in New York City and upstate New York.


CONCLUSION
Telemedicine case management improved glycemic control, blood pressure levels, and total and LDL cholesterol levels at one year of follow-up.
An Ontology of Architectural Design Decisions in Software-Intensive Systems

Architectural design decisions deserve to be first class entities in the process of developing complex software-intensive systems. Preserving the graphs of decisions and all their interdependencies will support the evolution and maintenance of such systems. In this paper we present a possible ontology of architectural design decisions, their attributes and relationships, for complex, software-intensive systems.
Phases in development of an interactive mobile phone-based system to support self-management of hypertension

Hypertension is a significant risk factor for heart disease and stroke worldwide. Effective treatment regimens exist; however, treatment adherence rates are poor (30%-50%). Improving self-management may be a way to increase adherence to treatment. The purpose of this paper is to describe the phases in the development and preliminary evaluation of an interactive mobile phone-based system aimed at supporting patients in self-managing their hypertension. A person-centered and participatory framework emphasizing patient involvement was used. An interdisciplinary group of researchers, patients with hypertension, and health care professionals who were specialized in hypertension care designed and developed a set of questions and motivational messages for use in an interactive mobile phone-based system. Guided by the US Food and Drug Administration framework for the development of patient-reported outcome measures, the development and evaluation process comprised three major development phases (1, defining; 2, adjusting; 3, confirming the conceptual framework and delivery system) and two evaluation and refinement phases (4, collecting, analyzing, interpreting data; 5, evaluating the self-management system in clinical practice). Evaluation of new mobile health systems in a structured manner is important to understand how various factors affect the development process from both a technical and human perspective. Forthcoming analyses will evaluate the effectiveness and utility of the mobile phone-based system in supporting the self-management of hypertension.
Data mining : past present and future - a typical survey on data streams

Data Stream Mining is one of the area gaining lot of practical significance and is progressing at a brisk pace with new methods, methodologies and findings in various applications related to medicine, computer science, bioinformatics and stock market prediction, weather forecast, text, audio and video processing to name a few. Data happens to be the key concern in data mining. With the huge online data generated from several sensors, Internet Relay Chats, Twitter, Face book, Online Bank or ATM Transactions, the concept of dynamically changing data is becoming a key challenge, what we call as data streams. In this paper, we give the algorithm for finding frequent patterns from data streams with a case study and identify the research issues in handling data streams. © 2013 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of Department of Electrical and Computer Engineering, Faculty of Engineering, “Petru Maior” University of Tîrgu Mureș.
On the performance of telemedicine system using 17-GHz orthogonally polarized microwave links under the influence of heavy rainfall

This paper describes the design of a telemedicine system based on next-generation wireless local area networks (WLANs) operating at 17 GHz. Seventeen gigahertz is proposed for next-generation WLAN services offering numerous advantages over traditional IEEE 802.11 networks that operate in the range of 2.4-5 GHz. Orthogonal polarization is often used to increase spectrum efficiency by utilizing signal paths of horizontal and vertical polarization. Radio waves exceeding 10 GHz are particularly vulnerable to signal degradation under the influence of rain which causes an effective reduction in isolation between polarized signal paths. This paper investigates the influence of heavy rain in a tropical region on wide-band microwave signals at 17 GHz using two links provided by a fixed broad-band wireless access system for two-way data exchange between paramedics attending an accident scene and the hospital via microwave equipment installed in the ambulance. We also study the effects of cross polarization and phase rotation due to persistent heavy rainfall in tropical regions.
E-government adoption in public administration organizations: integrating institutional theory perspective and resource-based view

Received: 27 June 2010 Revised: 25 April 2011 2nd Revision: 5 March 2012 Accepted: 5 April 2012 Abstract We develop and test a theoretical model to investigate the adoption of government-to-government (G2G) information systems in public administration organizations. Specifically, this model explains how top management commitment (TMC) mediates the impact of external institutional pressures on internal organizational resource allocation, which finally leads to the adoption decision. The hypotheses were tested using survey data from public administration organizations in China. Results from partial least squares analyses suggest that coercive and normative pressures positively affect TMC, which then positively affects financial and information technology (IT) human resources in the G2G adoption process. In turn, financial and IT human resources are confirmed to positively affect the intention to adopt G2G. Surprisingly, we do not find support for our hypothesis that mimetic pressures directly influence TMC. Rather, a post hoc analysis implies that mimetic pressures indirectly influence TMC via the influence of coercive pressures. Our findings provide important managerial implications for public administration organizations. European Journal of Information Systems (2013) 22, 221–234. doi:10.1057/ejis.2012.28; published online 19 June 2012
Constructing support vector machine ensemble

Even the support vector machine (SVM) has been proposed to provide a good generalization performance, the classi6cation result of the practically implemented SVM is often far from the theoretically expected level because their implementations are based on the approximated algorithms due to the high complexity of time and space. To improve the limited classi6cation performance of the real SVM, we propose to use the SVM ensemble with bagging (bootstrap aggregating) or boosting. In bagging, each individual SVM is trained independently using the randomly chosen training samples via a bootstrap technique. In boosting, each individual SVM is trained using the training samples chosen according to the sample’s probability distribution that is updated in proportional to the errorness of the sample. In both bagging and boosting, the trained individual SVMs are aggregated to make a collective decision in several ways such as the majority voting, least-squares estimation-based weighting, and the double-layer hierarchical combining. Various simulation results for the IRIS data classi6cation and the hand-written digit recognition, and the fraud detection show that the proposed SVM ensemble with bagging or boosting outperforms a single SVM in terms of classi6cation accuracy greatly. ? 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Large‐scale Correlation of Accounts across Social Networks

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors or originators and do not necessarily reflect the views of the National Science Foundation. Abstract Organizations are increasingly mining the personal data users generate as they carry out much of their day‐to‐day activities online. A range of new business models specifically exploit what users publish on their social network profiles, including services performing background checks and analytics providers who, e.g., associate demographics with consumer behavior. In this work we set out to understand the capabilities of machine learning techniques for linking independent accounts that users maintain on different social networks, based solely on the information people explicitly and publicly provide in their profiles. We perform a large scale study that assesses a range of correlation approaches for matching accounts between five popular social networks: Twitter, Facebook, Google+, Myspace, and Flickr. Our results show for instance that by exploiting usernames, real names, locations, and photos, we can robustly identify about 80% of the matching pairs of user accounts between any combination of two social networks among Twitter, Facebook and Google+. Our work is the first to demonstrate the feasibility of such conceptually simple privacy attacks at large scale, across several major networks, and with such efficiency.
Service Function Chaining: Creating a Service Plane via Network Service Headers

As service chaining matures, interoperability is a must. Network service headers provide the required data-plane information needed to construct topologically independent service paths as well as to pass opaque metadata between classification and service functions.
A systematic review of approaches to assessing cybersecurity awareness

Purpose – The purpose of this paper is to survey, explore and inform researchers about the previous methodologies applied, target audience and coverage of previous assessment of cybersecurity awareness by capturing, summarizing, synthesizing and critically comment on it. It is also conducted to identify the gaps in the cybersecurity awareness assessment research which warrants the future work. Design/methodology/approach – The authors used a systematic literature review technique to search the relevant online databases by using pre-defined keywords. The authors limited the search to retrieve only English language academic articles published from 2005 to 2014. Relevant information was extracted from the retrieved articles, and the ensuing discussion centres on providing the answers to the research questions. Findings – From the online searches, 23 studies that matched the search criteria were retrieved, and the information extracted from each study includes the authors, publication year, assessment method used, target audiences, coverage of assessment and assessment goals. Originality/value – The review of the retrieved articles indicates that no previous research was conducted in the assessment of the cybersecurity awareness using a programme evaluation technique. It was also found that few studies focused on youngsters and on the issue of safeguarding personal information.
New Dromaeosaurids (Dinosauria: Theropoda) from the Lower Cretaceous of Utah, and the Evolution of the Dromaeosaurid Tail

BACKGROUND
The Yellow Cat Member of the Cedar Mountain Formation (Early Cretaceous, Barremian?--Aptian) of Utah has yielded a rich theropod fauna, including the coelurosaur Nedcolbertia justinhofmanni, the therizinosauroid Falcarius utahensis, the troodontid Geminiraptor suarezarum, and the dromaeosaurid Utahraptor ostrommaysorum. Recent excavation has uncovered three new dromaeosaurid specimens. One specimen, which we designate the holotype of the new genus and species Yurgovuchia doellingi, is represented by a partial axial skeleton and a partial left pubis. A second specimen consists of a right pubis and a possibly associated radius. The third specimen consists of a tail skeleton that is unique among known Cedar Mountain dromaeosaurids.


METHODOLOGY/PRINCIPAL FINDINGS
Y. doellingi resembles Utahraptor ostrommaysorum in that its caudal prezygapophyses are elongated but not to the degree present in most dromaeosaurids. The specimen represented by the right pubis exhibits a pronounced pubic tubercle, a velociraptorine trait that is absent in Y. doellingi. The specimen represented by the tail skeleton exhibits the extreme elongation of the caudal prezygapophyses that is typical of most dromaeosaurids. Here we perform a phylogenetic analysis to determine the phylogenetic position of Y. doellingi. Using the resulting phylogeny as a framework, we trace changes in character states of the tail across Coelurosauria to elucidate the evolution of the dromaeosaurid tail.


CONCLUSIONS/SIGNIFICANCE
The new specimens add to the known diversity of Dromaeosauridae and to the known diversity within the Yellow Cat paleofauna. Phylogenetic analysis places Y. doellingi in a clade with Utahraptor, Achillobator, and Dromaeosaurus. Character state distribution indicates that the presence of intermediate-length caudal prezygapophyses in that clade is not an evolutionarily precursor to extreme prezygapophyseal elongation but represents a secondary shortening of caudal prezygapophyses. It appears to represent part of a trend within Dromaeosauridae that couples an increase in tail flexibility with increasing size.
Glycemic control among patients in China with type 2 diabetes mellitus receiving oral drugs or injectables

BACKGROUND
The prevalence of type 2 diabetes mellitus (T2DM) is increasing rapidly among Chinese adults, and limited data are available on T2DM management and the status of glycemic control in China. We assessed the efficacy of oral antidiabetes drugs (OADs), glucagon-like peptide-1 (GLP-1) receptor agonists, and insulin for treatment of T2DM across multiple regions in China.


METHODS
This was a multicenter, cross-sectional survey of outpatients conducted in 606 hospitals across China. Data from all the patients were collected between April and June, 2011.


RESULTS
A total of 238,639 patients were included in the survey. Eligible patients were treated with either OADs alone (n=157,212 [65.88%]), OADs plus insulin (n=80,973 [33.93%]), or OADs plus GLP-1 receptor agonists (n=454 [0.19%]). The OAD monotherapy, OAD + insulin, and OAD + GLP-1 receptor agonist groups had mean glycosylated hemoglobin (HbA1c) levels (±SD) of 7.67% (±1.58%), 8.21% (±1.91%), and 7.80% (±1.76%), respectively. Among those three groups, 34.63%, 26.21%, and 36.12% met the goal of HbA1c <7.0%, respectively. Mean HbA1c and achievement of A1c <7.0% was related to the duration of T2DM.


CONCLUSIONS
Less than one third of the patients had achieved the goal of HbA1c <7.0%. Glycemic control decreased and insulin use increased with the duration of diabetes.
155 Omalizumab Improves Asthma but not Nasal Symptoms in Japanese Patients With Severe Allergic Asthma and Rhinitis

BACKGROUND
Statins are the most commonly prescribed drugs for the treatment of hypercholesterolemia. Statins exert not only lipid-lowering but also other cellular effects, including antifibrotic properties. The purpose of this study was to determine the effect of simvastatin on transforming growth factor (TGF)-beta-1-induced myofibroblast differentiation and collagen production in nasal polyp-derived fibroblasts (NPDFs) and to verify the mechanism of the effect of simvastatin in TGF-beta-1-induced myofibroblast differentiation in NPDFs.


METHODS
NPDFs were pretreated with simvastatin with or without mevalonate or Y-27643 for 2 hours before induction by TGF-beta-1. The expression of alpha-smooth muscle actin (SMA) and collagen type IV mRNA was determined by a reverse transcription-polymerase chain reaction, and the expression of alpha-SMA protein was determined by immunofluorescent cytochemical staining. Total soluble collagen production was analyzed by the SirCol collagen dye-binding assay (Biocolor, Belfast, U.K.). Phosphorylation of Smad 2/3 was evaluated by Western blot analysis.


RESULTS
In TGF-beta-1-induced NPDFs, simvastatin significantly inhibited the expressions of α-SMA and collagen type IV mRNA and reduced alpha-SMA and collagen protein levels. Pretreatment with mevalonate reversed the effect of simvastatin. The expression of alpha-SMA mRNA and protein was significantly decreased by pretreatment with Y-27632. The TGF-beta-1-induced expression of pSmad 2/3 protein was notably decreased by pretreatment with simvastatin.


CONCLUSION
We showed that simvastatin inhibits TGF-beta-1-induced myofibroblast differentiation (expression of alpha-SMA) and collagen production in NPDFs and Rho/Rock and TGF-β/Smad signaling is involved as an underlying mechanism. The results of our study suggest that simvastatin is a possible candidate for the suppression of nasal polyp formation.
Effectiveness of COOP Advertising Programs in Competitive Distribution Channels

We propose a model of retail promotions for competitive distribution channels and investigate whether cooperative advertising programs are profitable for such channels. While previous studies showed that coop programs increase total channel profits in bilateral monopolies, no evidence of such a result has been provided for channels where competition is present at the manufacturing and the retailing levels. In this paper, we consider a distribution channel formed by two manufacturers and two retailers and propose a model that accounts for brand and store substitution effects generated by the retailer’s promotional efforts. The efficiency of the coop plan is investigated by comparing equilibria of four non-cooperative games; one where manufacturers do not offer any promotional support to the retailers, one where manufacturers do offer such a support and two scenarios where in turn only one manufacturer is offering such program. We show that when competition is introduced, coop ad programs may be due to a prisonner’s dilemma situation for the manufacturers. The benefit for retailers and consumers is also assessed.