Miracle-dz/UniFAR-FTUs huggingface dataset:
Software for Computing the Tetrachoric Correlation Coefficient Software

Tetrachoric correlation is a special case of analysis of the statistical covariation between two variables measured on a dichotomous scale, but assuming an underlying bivariate normal distribution. Computation of tetrachoric correlation is not straightforward and is usually not available in standard statistical packages. This paper introduces ViSta-Tetrachor, a plug-in for the statistical package ViSta that computes the tetrachoric correlation using an approximation that has shown to be both accurate and simpler to compute than the original algorithm. Additionally, ViSta-Tetrachor provides point and interval estimates for this statistic. Such feature is very uncommonly found in standard statistical packages. ViSta-Tetrachor also allows for computing tetrachoric correlation matrices that can subsequently be analyzed with the ViSta’s Factor Analysis module. A brief description of the software is presented with several worked examples.
Efficacy of periodontal plastic surgery procedures in the treatment of localized facial gingival recessions. A systematic review.

BACKGROUND The aim of this Systematic Review (SR) was to assess the clinical efficacy of periodontal plastic surgery procedures in the treatment of localized gingival recessions (Rec) with or without inter-dental clinical attachment loss (iCAL). MATERIAL AND METHODS Electronic and hand searches were performed to identify randomized clinical trials (RCTs) on treatment of single gingival recessions with at least 6 months of follow-up. Primary outcome variable was complete root coverage (CRC). Secondary outcome variables were recession reduction (RecRed) and keratinized tissue (KT) gain. To evaluate treatment effect, Odds Ratios were combined for dichotomous data and mean differences in continuous data using a random-effect model. RESULTS Fifty-one RCTs (53 articles) with a total of 1574 treated patients (1744 recessions) were included in this SR. Finally, 30 groups of comparisons were identified and a total of 80 meta-analyses were performed. Coronally Advanced Flap (CAF) was associated with higher probability of CRC and higher amount of RecRed than Semilunar Coronal Positioned Flap (SCPF). The combination CAF plus Connective Tissue Graft (CAF+CTG) or CAF plus Enamel Matrix Derivative (CAF+EMD) was more effective than CAF alone in terms of CRC and RecRed. The combination CAF plus Collagen Matrix (CAF+CM) achieved higher RecRed than CAF alone. In addition, CAF+CTG achieved CRC more frequently than CAF+EMD, SCPF, Free Gingival Graft (FGG) and Laterally Positioned Flap (LPS). CAF+CTG was also associated with higher RecRed than Barrier Membranes (CAF+GTR), CAF+EMD and CAF+CM. GTR was not able to improve the clinical efficacy of CAF. Studies adding Acellular Dermal Matrix (ADM) under CAF showed a large heterogeneity and not significant benefits compared with CAF alone. Multiple combinations, using more than a single graft/biomaterial under the flap, usually provide similar or less benefits than simpler, control procedures in term of root coverage outcomes. CONCLUSIONS CAF procedures alone or with CTG, EMD are supported by large evidence in modern periodontal plastic surgery. CAF+CTG achieved the best clinical outcomes in single gingival recessions with or without iCAL.
Prebaked µVMs: Scalable, Instant VM Startup for IaaS Clouds

IaaS clouds promise instantaneously available resources to elastic applications. In practice, however, virtual machine (VM) start up times are in the order of several minutes, or at best, several tens of seconds, negatively impacting the elasticity of applications like Web servers that need to scale out to handle dynamically increasing load. VM start up time is strongly influenced by booting the VM's operating system. In this work, we propose using so-called prebaked uVMs to speed up VM start up. Uvms are snapshots of minimal VMs that can be quickly resumed and then configured to application needs by hot-plugging resources. To serve uVMs, we extend our VM boot cache service, Squirrel, allowing to store uVMs for large numbers of VM images on the hosts of a data center. Our experiments show that uVMs can start up in less than one second on a standard file system. Using 1000+ VM images from a production cloud, we show that the respective uVMs can be stored in a compressed and deduplicated file system within 50GB storage per host, while starting up within 2 -- 3 seconds on average.
Scenarios, goals, and state machines: a win-win partnership for model synthesis

Models are increasingly recognized as an effective means for elaborating requirements and exploring designs. For complex systems, model building is far from an easy task. Efforts were therefore recently made to automate parts of this process, notably, by synthesizing behavior models from scenarios of interactions between the software-to-be and its environment. In particular, our previous interactive synthesizer generates labelled transition systems (LTS) from simple message sequence charts (MSC) provided by end-users. Compared with others, the synthesizer requires no additional input such as state or flowcharting information. User interactions consist in simple scenarios generated by the synthesizer that the user has to classify as example or counterexample of desired behavior.Experience with this approach showed that the number of such scenario questions may become fairly large in interaction-intensive applications such as web applications. In this paper, we extend our model synthesis technique by injecting additional information into the synthesizer, when available, in order to constrain induction and prune the inductive search space. Additional information may include global definitions of fluents that link interaction events and atomic assertions; declarative properties of the domain; behavior models of external components; and goals that the software system is expected to satisfy. We provide comparative data on increasingly complex examples to show how effective such constraints are in reducing the number of scenario questions and in increasing the adequacy of the synthesized model. As goals and domain properties might not be easily provided by users, the paper also shows how our synthesizer generates a significant class of them automatically from the available scenarios. As a side-effect, our work provides additional evidence on the synergistic links between scenarios, goals, and state machines for model-driven engineering of requirements and designs.
Generating a 3 D shape template of a moving and deforming object from an RGB-D image sequence

Automatically reconstructing a 3D shape model of a nonrigid object using a sequence from a single commodity RGB-D sensor is a challenging problem. Some techniques use a 3D shape template of a target object; however, in order to generate the template automatically, the target object required to be stationary. Otherwise, a non-rigid ICP algorithm, which registers a pair of point clouds, can be used for reconstructing 3D geometry of a non-rigid object directly, but it often fails due to the ambiguity in point correspondences. This paper presents a method for generating a 3D shape template from a single RGB-D sequence. In order to reduce the ambiguity in point correspondences, our method leverages point trajectories obtained in the RGB images, which can be used for associating points in different point clouds. We demonstrate the capability of our method using deforming human bodies. Introduction Recently, various applications that present a moving and deforming object to users, such as virtual fitting room [1] and virtual pets [2], have become available to ordinary users. These applications render objects based on 3D geometry of their entire shapes (which we refer to as full-body shape models) and their non-rigid motion, both of which are usually handcrafted. Automatic techniques for reconstructing full-body shape models at each frame can drastically reduce the cost for creating a 3D shape model and motion (e.g., [3, 4]). They use multiple sensors (e.g., RGB or RGB-D sensors), whose relative poses are known, to capture the object from different viewpoints simultaneously. It then applies an existing 3D reconstruction technique for rigid objects, such as [5, 6, 7]. However, the use of multiple sensors may be still cumbersome for some applications in which ordinary users need their own shape models and motions. Reconstructing 3D shape and motion from a single sensor is a challenging problem. Two approaches have been proposed: one uses 3D shape templates of the target object and the other does not. Former approach [8, 9] generates a 3D shape template using a 3D shape reconstruction technique for rigid objects [5, 6, 7], assuming the object is almost stationary. They then fit the 3D shape template to a 3D point cloud at each frame of a single depth map sequence. One major limitation of this approach is that it requires an extra burden to capture the target object while it is stationary, which is practically infeasible, especially for objects like animals. Latter approach [10, 11] registers 3D point clouds in all frame of a single depth map sequence to any other frames using non-rigid iterative closest point (ICP) [12, 13]; however, it often 3D shape template
A Refined Methodology for Automatic Keyphrase Assignment to Digital Documents

AbstrAct: Keyphrases precisely express the primary topics and themes of documents and are valuable for cataloging and classification. Manually assigning keyphrases to existing documents is a tedious task; therefore, automatic keyphrase generation has been extensively used to classify digital documents. Existing automatic keyphrase generation algorithms are limited in assigning semantically relevant keyphrases to documents. In this paper we have proposed a methodology to refine the result set of automatically generated keyphrases by Keyphrase Extraction Algorithm (KEA++), so that the key-phrases accurately and precisely represent the content of the document. Our approach is an additional layer at the top of KEA++ and exploits semantic relationships and hierarchical structure of the controlled vocabulary to filter out irrelevant keyphrases from the result set generated by KEA++. The methodology was applied on different sets of academic publications for evaluation. Evaluation demonstrates that the proposed refinement methodology improves the quality of generated keyphrases.
Optimization of an individual re-identification modeling process using biometric features

We present results from the optimization of a reidentification process using two sets of biometric data obtained from the Civilian American and European Surface Anthropometry Resource Project (CAESAR) database. The datasets contain real measurements of features for 2378 individuals in a standing (43 features) and seated (16 features) position. A genetic algorithm (GA) was used to search a large combinatorial space where different features are available between the probe (seated) and gallery (standing) datasets. Multiple linear regression models are employed to estimate one set of features from the other. Results show that optimized model predictions obtained using less than half of the 43 gallery features and data from roughly 16% of the individuals available produce better reidentification rates than two other approaches that use all 43 gallery set features and information from all 2378 individuals.
On the Effectiveness of Social Tagging for Resource Discovery

Social tagging is the process of assigning and sharing among users freely selected terms of resources. This approach enables users to annotate/describe resources, and also allows users to locate new resources through the collective intelligence of other users. Social tagging offers a new avenue for resource discovery as compared to taxonomies and subject directories created by experts. This chapter investigates the effectiveness of tags as resource descriptors and is achieved using text categorization via support vector machines (SVM). Two text categorization experiments were done for this research, and tags and Web pages from del.icio. us were used. The first study concentrated on the use of terms as its features while the second used both terms and its tags as part of its feature set. The experiments yielded a macroaveraged precision, recall, and F-measure scores of 52.66%, 54.86%, and 52.05%, respectively. In terms of microaveraged values, the experiments obtained 64.76% for precision, 54.40% for recall, and 59.14% for F-measure. The results suggest that the tags were not always reliable indicators of the resource contents. At the same time, the results from the terms-only experiment were better compared to the experiment with both terms and tags. Implications of our work and opportunities for future work are also discussed. Dion Hoe-Lian Goh Nanyang Technological University, Singapore
Advances in the proteomic discovery of novel therapeutic targets in cancer

Proteomic approaches are continuing to make headways in cancer research by helping to elucidate complex signaling networks that underlie tumorigenesis and disease progression. This review describes recent advances made in the proteomic discovery of drug targets for therapeutic development. A variety of technical and methodological advances are overviewed with a critical assessment of challenges and potentials. A number of potential drug targets, such as baculoviral inhibitor of apoptosis protein repeat-containing protein 6, macrophage inhibitory cytokine 1, phosphoglycerate mutase 1, prohibitin 1, fascin, and pyruvate kinase isozyme 2 were identified in the proteomic analysis of drug-resistant cancer cells, drug action, and differential disease state tissues. Future directions for proteomics-based target identification and validation to be more translation efficient are also discussed.
Uniform ergodicity of the iterated conditional SMC and geometric ergodicity of particle Gibbs samplers

We establish quantitative bounds for rates of convergence and asymptotic variances for iterated conditional sequential Monte Carlo (i-cSMC) Markov chains and associated particle Gibbs samplers [J. R. Stat. Soc. Ser. B. Stat. Methodol. 72 (2010) 269–342]. Our main findings are that the essential boundedness of potential functions associated with the i-cSMC algorithm provide necessary and sufficient conditions for the uniform ergodicity of the i-cSMC Markov chain, as well as quantitative bounds on its (uniformly geometric) rate of convergence. Furthermore, we show that the i-cSMC Markov chain cannot even be geometrically ergodic if this essential boundedness does not hold in many applications of interest. Our sufficiency and quantitative bounds rely on a novel non-asymptotic analysis of the expectation of a standard normalizing constant estimate with respect to a “doubly conditional” SMC algorithm. In addition, our results for i-cSMC imply that the rate of convergence can be improved arbitrarily by increasing NN, the number of particles in the algorithm, and that in the presence of mixing assumptions, the rate of convergence can be kept constant by increasing NN linearly with the time horizon. We translate the sufficiency of the boundedness condition for i-cSMC into sufficient conditions for the particle Gibbs Markov chain to be geometrically ergodic and quantitative bounds on its geometric rate of convergence, which imply convergence of properties of the particle Gibbs Markov chain to those of its corresponding Gibbs sampler. These results complement recently discovered, and related, conditions for the particle marginal Metropolis–Hastings (PMMH) Markov chain.
Thermal Cycle Consideration in Applying Lead-Free TFBGA Simulation to a Design

Three-dimensional (3D) stacked die packaging has become the trend to improve efficiency for transmitting signals, reduce the volume of the package, and help with functions integration. It is more and more applied popularly in telecommunications. Solder joints, interconnections in the packaging structure, are more easily damaged by critical stress from thermal cycle loading when the component is operating, because the coefficient of the thermal expansion of various materials mismatch. People have studied the common single die during the thermal cycle loading for a long time, but the researches for the stacked die BGA are not as complete. In addition, to protect the environment and comply with legislation, the semiconductor industry wants to find a lead-free material to replace the lead solder joints. Therefore, most extant or new types of packaging started using lead-free material to do thermal cycle testing. The critical solder ball location is not the same as in a single die package where at the die corn.
Effects of Version Control System on the Efficiency of Refused Bequest Code

Refused bequest is a code smell that originates from introduction of inappropriate class hierarchies where subclasses do not specialize or use the functionalities provided by the parent class. The existing refused bequest code smell identification algorithms use either static analysis or a combination of static and dynamic analysis based technique. However, those algorithms do not consider version control history. If the parts that have been changed from a previous version can be considered for refused bequest identification, the identification time may be reduced. An approach is proposed here employing the version control history to reduce identification time in refused bequest code smell identification. The proposed approach has four components namely Change Collector, Source Code Parser, Error Injector and Smell Calculator. Change Collector identifies source codes that have been changed from the previous version. Source Code Parser then parses the source codes to identify metrics such as inherited method, overridden method, super classs method invocation etc. After parsing the source codes, Error Injector introduces intentional errors in the non-overridden inherited methods of the subclasses. Smell Calculator then calculates smell for each of the subclasses based on metrics identified in Source Code Parser and Error Injector. The comparative analysis of the results shows a significant improvement in execution time. The proposed approach is found to be 16.2% more time efficient than the existing approach for the sample projects. This is because the approach incorporates version control history in the identification process. Moreover, the proposed approach is able to identify code smells as accurately as the existing approach.
Online Astroturfing: A Theoretical Perspective

Online astroturfing refers to coordinated campaigns where messages supporting a specific agenda are distributed via the Internet. These messages employ deception to create the appearance of being generated by an independent entity. In other words, astroturfing occurs when people are hired to present certain beliefs or opinions on behalf of their employer through various communication channels. The key component of astroturfing is the creation of false impressions that a particular idea or opinion has widespread support. Although the concept of astroturfing in traditional media outlets has been studied, online astroturfing has not been investigated intensively by IS scholars. This study develops a theoretically-based definition of online astroturfing from an IS perspective and discusses its key attributes. Online astroturfing campaigns may ultimately have a substantial influence on both Internet users and society. Thus a clear understanding of its characteristics, techniques and usage can provide valuable insights for both practitioners and scholars.
The Total Variation Regularized L1 Model for Multiscale Decomposition

Abstract : This paper studies the total variation regularization model with an L1 fidelity term (TV-L1) for decomposing an image into features of different scales. We first show that the images produced by this model can be formed from the minimizers of a sequence of decoupled geometry sub-problems. Using this result we show that the TV-L1 model is able to separate image features according to their scales, where the scale is analytically defined by the G-value. A number of other properties including the geometric and morphological invariance of the TV-L1 model are also proved and their applications discussed.
Impact of age on excess risk of coronary heart disease in patients with familial hypercholesterolaemia

Objective The primary objective was to study the risk of acute myocardial infarction (AMI) and coronary heart disease (CHD) in patients with familial hypercholesterolaemia (FH) and compare with the risk in the general population. Methods Patients with an FH mutation but without prior AMI (n=3071) and without prior CHD (n=2795) were included in the study sample during 2001–2009. We obtained data on all AMI and CHD hospitalisations in Norway. We defined incident cases as first time hospitalisation or out-of-hospital death due to AMI or CHD. We estimated standardised incidence ratios (SIRs) with 95% CIs with indirect standardisation using incidence rates for the total Norwegian population stratified by sex, calendar year and 1 year age groups as reference rates. Results SIRs for AMI (95% CIs) were highest in the age group 25–39 years; 7.5 (3.7 to 14.9) in men and 13.6 (5.1 to 36.2) in women and decreased with age to 0.9 (0.4 to 2.1) in men and 1.8 (0.9 to 3.7) in women aged 70–79 years. Similarly, SIRs for CHD were highest among patients 25–39 years old; 11.1 (7.1–17.5) in men and 17.3 (9.6–31.2) in women and decreased 2.4 (1.4–4.2) in men and 3.2 (1.5–7.2) in women at age 70–79. For all age groups, combined SIRs for CHD were 4.2 (3.6–5.0) in men and 4.7 (3.9–5.7) in women. Conclusion Patients with FH are at severely increased risk of AMI and CHD compared with the general population. The highest excess risk was in the youngest group aged 25–39 years, in both sexes.
Epidemiology, outcome, and risk factors for infectious complications in myelofibrosis patients receiving ruxolitinib: A multicenter study on 446 patients

Infections represent one of the major concerns regarding the utilization of ruxolitinib (RUX) in patients with myelofibrosis. With the aim to investigate epidemiology, outcome and risk factors for infections in RUX‐exposed patients, we collected clinical and laboratory data of 446 myelofibrosis patients treated with RUX between June 2011 and November 2016 in 23 European Hematology Centers. After a median RUX exposure of 23.5 months (range, 1‐56), 123 patients (28%) experienced 161 infectious events (grades 3‐4 32%, fatal 9%), for an incidence rate of 17 cases per 100 pts/y. The rate of infections tended to decrease over time: 14% of patients developed the first infection within 6 months, 5% between 6 and 12 months, 3.7% between 12 and 18 months, 3.4% between 18 and 24 months, and 7.9% thereafter (P < .0001). Respiratory tract infections were more frequently observed (81 events, 50%), and bacteria were the most frequent etiological agents (68.9%). However, also viral (14.9%) and fungal infections (2.5%) were observed. In multivariate analysis, previous infectious event (HR 2.54; 95% CI, 1.51‐4.28; P = .0005) and high international prognostic score system category (IPSS) (HR 1.53; 95% CI, 1.07‐2.20; P = .021) significantly correlated with higher infectious risk. On the contrary, spleen reduction ≥50% from baseline after 3 months of treatment (P = .02) was associated with better infection‐free survival. Taken together, these findings reinforce the concept of disease severity as the most important risk factor for infections, and describe, for the first time, that a positive therapeutic effect in reducing splenomegaly may also reduce subsequent infectious complications.