Miracle-dz/UniFAR-FTUs huggingface dataset:
Capture-recapture method in the epidemiology of type 2 diabetes: a contribution from the Verona Diabetes Study.

OBJECTIVE The present investigation used data from the Verona Diabetes Study to verify a main assumption of the capture-recapture method (source independence) and to characterize the subgroup of known diabetic patients missed by all sources whose number is estimated by the capture-recapture method. RESEARCH DESIGN AND METHODS The Verona Diabetes Study identified 7,148 type 2 diabetic patients on 31 December 1986 using 3 different sources: family physicians, a diabetes center, and a drug prescription database. Completeness of ascertainment was estimated with traditional methods based on the hypergeometric distribution and with a log-linear model. RESULTS Identification sources were not independent because the drug prescription database was positively related to family physicians and negatively related to the diabetes center (P < 0.001). Thus, completeness of ascertainment was overestimated (87.5% [95% CI 86.3-88.8]) when using only family physicians and the drug prescription database and underestimated (45.9% [43.9-48.1]) when using only the diabetes center and the drug prescription database. Because of characteristics contributing to variable "catchability" (probability of ascertainment), the estimated proportion of ascertainment increased with increasing time since diagnosis from 65.6% in the first tertile (<6 years) to 91.5% in the third tertile (>12 years); moreover, the ascertainment was estimated to be nearly complete (97.9%) for insulin-treated patients and scanty (28.9%) for diet-treated patients. CONCLUSIONS Because identification sources are likely to be dependent, the capture-recapture method should be used with caution in diabetes epidemiology and possibly when at least 3 sources are available. The subgroup of diabetic patients whose existence is inferred by this technique likely consists of newly diagnosed patients with mild disease severity.
RRAM Reliability/Performance Characterization through Array Architectures Investigations

The reliability and performance characterization of each non-volatile memory technology requires the thorough investigation of dedicated array test structures that mimic the real operations of a fully functional integrated product. This makes no exception also for emerging non-volatile memories like the Resistive Random Access Memory (RRAM) concept. An extensive electrical characterization activity performed on test vehicles manufactured in a CMOS backend-of-line process allowed the first glance estimation of operation modes and reliability threats typical of this technology. In this paper, it is provided a review of the most important issues like forming instabilities, optimal set/reset operation finding, and read disturb to provide a guideline either for a further technology optimization or an efficient algorithms co-design to handle these reliability/performance threats.
Adaptive Ensemble Construction based on Progressive Interactive Training of Neural Networks

The goal of an ensemble construction with several neural networks (NNs) is to achieve better generalization ability over a single neural network. In a Neural Network Ensemble (NNE), component networks solve the desired problem independently and combine their outputs for NNE's output. Therefore, the size of an NNE plays an important role in determining the performance for a particular problem. Although there has been much work for constructing ensembles, most of the works trains predefined number of NNs for an NNE. This study presents a problem dependent adaptive NNE construction method based on Progressive Interactive Training Scheme (PITS) of NNs. In PITS, a predefined number of NNs are trained one by one in a progressive manner, where each NN is concerned with a specific task that has not been solved by any previously trained NN. Proposed Adaptive PITS (APITS) is an extension of PITS utilizing inherited benefit of its sequential style training. APITS employs a simple overhead in PITS while training NNs one after another sequentially. The overhead determines more NNs training will be beneficial or not for a given problem and therefore, return different number of NNs for different problems. The proposed method has been evaluated on several benchmark problems, and the method (with concise NNE) is shown competitive generalization ability with the popular NNE methods.
A review in feature extraction approach in question classification using Support Vector Machine

Text classification which is an integral part of text mining has caught much attention in various industries and fields recently. The ability is in assigning text documents to one or more pre-defined categories based on content similarity. While most of application of text classification focuses on document level, question classification works at much granular level such as sentence and phrase. There have been numerous studies on question classification in accordance to Bloom taxonomy in assessments to measure cognitive level of learners in higher learning institutions. But it has not been effective yet to resolve overlapping issue of Bloom taxonomy verb keywords being assigned to more than one category of Bloom taxonomy. The presence of this poses a problem in respect of classifying a particular question into a right category of Bloom taxonomy. And feature extraction plays an important role in improving the accuracy of classifier such as Support Vector Machine in question classification. Much of the past related research work focus on feature extraction methods such as bag of word (BOW) and syntactic analysis to classify questions and to address the issue, an improvement in feature extraction is needed. In view of this, this study proposes an integrated approach in feature extraction involving semantic aspect in classifying questions in accordance to Bloom taxonomy. Support Vector Machine classifier is used as it is well known for its high accuracy in text classification. With all this in place, an improved accuracy in classifying questions in accordance to Bloom taxonomy can be expected.
The PI3-Kinase Delta Inhibitor Idelalisib (GS-1101) Targets Integrin-Mediated Adhesion of Chronic Lymphocytic Leukemia (CLL) Cell to Endothelial and Marrow Stromal Cells

CLL cell trafficking between blood and tissue compartments is an integral part of the disease process. Idelalisib, a phosphoinositide 3-kinase delta (PI3Kδ) inhibitor causes rapid lymph node shrinkage, along with an increase in lymphocytosis, prior to inducing objective responses in CLL patients. This characteristic activity presumably is due to CLL cell redistribution from tissues into the blood, but the underlying mechanisms are not fully understood. We therefore analyzed idelalisib effects on CLL cell adhesion to endothelial and bone marrow stromal cells (EC, BMSC). We found that idelalisib inhibited CLL cell adhesion to EC and BMSC under static and shear flow conditions. TNFα-induced VCAM-1 (CD106) expression in supporting layers increased CLL cell adhesion and accentuated the inhibitory effect of idelalisib. Co-culture with EC and BMSC also protected CLL from undergoing apoptosis, and this EC- and BMSC-mediated protection was antagonized by idelalisib. Furthermore, we demonstrate that CLL cell adhesion to EC and VLA-4 (CD49d) resulted in the phosphorylation of Akt, which was sensitive to inhibition by idelalisib. These findings demonstrate that idelalisib interferes with integrin-mediated CLL cell adhesion to EC and BMSC, providing a novel mechanism to explain idelalisib-induced redistribution of CLL cells from tissues into the blood.
PDM: A New Strong Password-Based Protocol

In this paper we present PDM (Password Derived Moduli), a new approach to strong password-based protocols usable either for mutual authentication or for downloading security information such as the user's private key. We describe how the properties desirable for strong password mutual authentication differ from the properties desirable for credentials download. In particular, a protocol used solely for credentials download can be simpler and less expensive than one used for mutual authentication since some properties (such as authentication of the server) are not necessary for credentials download. The features necessary for mutual authentication can be easily added to a credentials download protocol, but many of the protocols designed for mutual authentication are not as desirable for use in credentials download as protocols like PDM and basic EKE and SPEKE because they are unnecessarily expensive when used for that purpose. PDM's performance is vastly more expensive at the client than any of the protocols in the literature, but it is more efficient at the server. We claim that performance at the server, since a server must handle a large and potentially unpredictable number of clients, is more important than performance at the client, assuming that client performance is "good enough". We describe PDM for credentials download, and then show how to enhance it to have the properties desirable for mutual authentication. In particular, the enhancement we advocate for allowing PDM to avoid storing a password-equivalent at the server is less expensive than existing schemes, and our approach can be used as a more efficient (at the server) variant of augmented EKE and SPEKE than the currently published schemes. PDM is important because it is a very different approach to the problem than any in the literature, we believe it to be unencumbered by patents, and because it can be a lot less expensive at the server than existing schemes.
“It’s Scary but It’s Also Exciting”: Evidence of Meta-Affective Learning in Science

Abstract We study the case of Marya, a freshman engineering major who showed and spoke of a drastic shift in her feelings and approach to learning physics during an introductory course. For the first several weeks, she was anxiously manipulating equations without considering physical meaning, and she was terribly worried about being correct. By the end of the semester, however, she was sense-making and taking pleasure in it, showing and expressing an enjoyment of challenges and uncertainty. In this paper, we illustrate Marya’s transformation using data from her interview and coursework, and we propose it as an example of meta-affective learning. We argue that meta-affective learning was an important part of Marya’s physics learning and that it was deeply entangled with her developing epistemology.
A three-axial body force sensor for flexible manipulators

This paper introduces an optical based three axis force sensor which can be integrated with the robot arm of the EU project STIFF-FLOP (STIFFness controllable Flexible and Learnable Manipulator for Surgical Operations) in order to measure applied external forces. The structure of the STIFF-FLOP arm is free of metal components and electric circuits and, hence, is inherently safe near patients during surgical operations. In addition, this feature makes the performance of this sensing system immune against strong magnetic fields inside magnetic resonance (MR) imaging scanners. The hollow structure of the sensor allows the implementation of distributed actuation and sensing along the body of the manipulator. In this paper, we describe the design and calibration procedure of the proposed three axis optics-based force sensor. The experimental results confirm the effectiveness of our optical sensing approach and its applicability to determine the force and momentum components during the physical interaction of the robot arm with its environment.
Influence Landscapes-From Spatial to Conceptual Representations

In this paper we will present the concept of the ”Influence Landscape”, an extension to the current ”Influence Map” or ”A rtificial Potential Field” that is commonly used in AI for Games. I nfluence Maps have previously only been used purely in relation t o a spatial representation of the world and have been used to gui de the movement of agents, avoiding dangerous areas and being draw n to rewarding areas. We will describe an extension to this princ iple that allows the computationally efficient process to be applied a cross a conceptual space, allowing the agent to perform basic reaso ning in this efficient manner.
A Benchmark for Graphics Recognition Systems

Abstract This paper presents a benchmark for evaluating graphics recognition systems. The benchmarkis designed for evaluating the performance of graphics recognition systems on images that containstraight lines (solid or dashed), circles (solid or dashed), circular arcs (solid or dashed), and textblocks. This benchmark enables an objective assessment and comparison of vectorization software.It uses practical performance evaluation methods that can be applied to complete vectorizationsystems. At a recent graphics recognition contest, three systems were evaluated using this bench-mark. The results of the contest are summarized in this paper. We hope that this benchmark willhelp assess the state of the art in graphics recognition, and highlight the strengths and weaknessesof current vectorization technology and evaluation methods. 1: Introduction Performance evaluation and benchmarking have been gaining acceptance in all areas of com-puter vision. An overview of this area is available at [1]. However, the performance evaluationof graphics recognition is still a very young ﬁeld. Although graphics recognition systems haveexisted for several years (e.g., [2, 3, 4, 5]), there has been no way to compare their performancequantitatively (some qualitative and subjective comparisons do exist, e.g., [6]). Objective and quan-titative methods for evaluation of graphics recognition systems have been proposed very recently[7,8,9,10]. Kong et al. [7] propose a quantitative method for evaluating the recognition of dashed lines. Horiand Doermann [8] propose a quantitative performance measurement methodology for task-speciﬁcraster to vector conversion. Wenyin and Dori [9] present a protocol for evaluating the recognitionof straight and circular lines. These methods do not lend themselves to an objective evaluationof a complete graphics recognition system. Some of the methods evaluate low level algorithmsand not complete systems. Other methods, although quite comprehensive, use performance metricsthat favor good recognition algorithms over good recognition systems. For instance, often the most
MIST, a Novel Approach to Reveal Hidden Substrate Specificity in Aminoacyl-tRNA Synthetases

Aminoacyl-tRNA synthetases (AARSs) constitute a family of RNA-binding proteins, that participate in the translation of the genetic code, by covalently linking amino acids to appropriate tRNAs. Due to their fundamental importance for cell life, AARSs are likely to be one of the most ancient families of enzymes and have therefore been characterized extensively. Paradoxically, little is known about their capacity to discriminate tRNAs mainly because of the practical challenges that represent precise and systematic tRNA identification. This work describes a new technical and conceptual approach named MIST (Microarray Identification of Shifted tRNAs) designed to study the formation of tRNA/AARS complexes independently from the aminoacylation reaction. MIST combines electrophoretic mobility shift assays with microarray analyses. Although MIST is a non-cellular assay, it fully integrates the notion of tRNA competition. In this study we focus on yeast cytoplasmic Arginyl-tRNA synthetase (yArgRS) and investigate in depth its ability to discriminate cellular tRNAs. We report that yArgRS in submicromolar concentrations binds cognate and non-cognate tRNAs with a wide range of apparent affinities. In particular, we demonstrate that yArgRS binds preferentially to type II tRNAs but does not support their misaminoacylation. Our results reveal important new trends in tRNA/AARS complex formation and potential deep physiological implications.
Multigrid Algorithms for Nonconforming and Mixed Methods for Nonsymmetric and Indefinite Problems

In this paper we consider multigrid algorithms for nonconforming and mixed finite element methods for nonsymmetric and/or indefinite elliptic problems. We show that a simple $\cal V$-cycle multigrid iteration using conforming coarse-grid corrections converges at a uniform rate provided that the coarsest level in the multilevel iteration is sufficiently fine (but independent of the number of multigrid levels). Various types of smoothers for the nonsymmetric and indefinite problems are discussed. Extensive numerical results are presented.
The Biochemistry and Regulation of S100A10: A Multifunctional Plasminogen Receptor Involved in Oncogenesis

The plasminogen receptors mediate the production and localization to the cell surface of the broad spectrum proteinase, plasmin. S100A10 is a key regulator of cellular plasmin production and may account for as much as 50% of cellular plasmin generation. In parallel to plasminogen, the plasminogen-binding site on S100A10 is highly conserved from mammals to fish. S100A10 is constitutively expressed in many cells and is also induced by many diverse factors and physiological stimuli including dexamethasone, epidermal growth factor, transforming growth factor-α, interferon-γ, nerve growth factor, keratinocyte growth factor, retinoic acid, and thrombin. Therefore, S100A10 is utilized by cells to regulate plasmin proteolytic activity in response to a wide diversity of physiological stimuli. The expression of the oncogenes, PML-RARα and KRas, also stimulates the levels of S100A10, suggesting a role for S100A10 in pathophysiological processes such as in the oncogenic-mediated increases in plasmin production. The S100A10-null mouse model system has established the critical role that S100A10 plays as a regulator of fibrinolysis and oncogenesis. S100A10 plays two major roles in oncogenesis, first as a regulator of cancer cell invasion and metastasis and secondly as a regulator of the recruitment of tumor-associated cells, such as macrophages, to the tumor site.
Peer victimization and child physical health: the moderating role of pessimism.

OBJECTIVE Involvement in peer victimization has been associated with numerous negative consequences, including poor physical health. The purpose of this study is to improve on previous research evaluating the victimization-health relationship by examining the health (i.e., health-related quality of life [HRQoL], medical service utilization) of both victims and aggressors and examining individual variation in this relationship through the moderating effect of pessimism. METHOD The sample included 125 ethnically diverse youth aged 8-11 years recruited from a low-income medical practice. Child-report of involvement in peer victimization and pessimism was assessed along with parent-report of HRQoL. 2-year medical service utilization was extracted from medical records. RESULTS Although not all hypotheses were supported, victims and aggressors were found to be at increased risk for certain poor health outcomes, which were exacerbated by high levels of pessimism. CONCLUSION Findings expand on research into peer victimization and health and provide important implications for identification, prevention, and intervention strategies with at-risk youth.
On-Line Data Stream Query Processing Using Finite State Automata

In data stream systems, data does not appear in form of persistent relations, but rather arrives in multiple, continuous, rapid, time-varying streams. Although, the nature of data streams is on-line, the well-known data stream models don't consider on-line query processing. This is a major deficit in these environments. In this paper an on-line query processing model for data streams is presented in which finite state automata is used. Architecture of the proposed query processing model, structure of the finite state automata, and relevant algorithms for on-line data stream query processing are presented. It is tested using an on-line auction environment and its performance in term of response time, tuple latency, number of operations and required memory space is evaluated and compared with the existing system via simulation
Even Keel and the Great Inflation

Using IV-GMM techniques and real-time data, we estimate a forward looking, Taylor-type reaction function incorporating dummy variables for even-keel operations and a variable for foreign official pressures on the U.S. gold stock during the Great Inflation.We show that when the Federal Reserve undertook even-keel operations to assist U.S. Treasury security sales, the FOMC tended to delay monetary-policy adjustments and to inject small amounts of reserves into the banking system.The operations, however, did not contribute significantly to the Great Inflation, because they occurred during periods of both monetary ease and monetary tightness, at least in the FOMC’s view.Consequently, the average federal funds rate during months containing even-keel events was no different than the average federal funds rate in other months, suggesting that even keel had no effect on the thrust of monetary policy.We also show that prospective gold losses had no effect on the FOMC’s monetary-policy decisions in the 1960s and early 1970s.
Reduced intensity conditioning allogeneic stem cell transplantation for adult patients with acute lymphoblastic leukemia: a retrospective study from the European Group for Blood and Marrow Transplantation

Reduced intensity conditioning allogeneic stem cell transplantation may be a feasible therapeutic option for adult patients with acute lymphoblastic leukemia. This retrospective study reported the outcome of 97 adult acute lymphoblastic leukemia patients who received a reduced-intensity conditioning allogeneic stem cell transplantation. With a median follow-up of 2.8 years, two year overall-survival, leukemia-free survival and non-relapse mortality were significantly better in patients transplanted in first complete remission (CR1, 52±9%; 42±10%; and 18±7% respectively) compared with those transplanted in more advanced phase (p=0.003, p=0.002 and p=0.01 respectively). In multivariate analysis, disease status (CR1 vs. advanced; p=0.001) and chronic graft-vs-host disease (p=0.01) were associated with an improved overall-survival, suggesting that reduced-intensity conditioning allogeneic stem cell transplantation is feasible in patients with high risk lymphoblastic leukemia in remission at transplantation.
A blind watermarking scheme for depth-image-based rendered 3D video using the dual-tree complex wavelet transform

The amount of unauthorized distribution of 3D video is increasing day by day due to the availability of high speed Internet and low cost 3D TV. Note that, not only both left and right views generated using depth-image-based rendering can be distributed as 3D content but also the centre, left or right view individually as 2D content. Video watermarking is a possible way to protect this type of illegal distribution. In this paper, we propose a digital watermarking method for depth-image-based rendered 3D video to protect each centre, left, and right view. In this method, the watermark is embedded into the centre view using the dual-tree complex wavelet transform. At the receiver, the left and the right views are generated from the centre view and the depth map using depth-image-based rendering. Finally, we extract the watermark from the centre, left and right views in a blind fashion. This scheme is robust to the most common video distortions which include geometric attacks such as scaling, rotation and cropping as well as lossy JPEG compression and additive noise.