Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational Statistics and Data Analysis Simultaneous Cancer Classification and Gene Selection with Bayesian Nearest Neighbor Method: an Integrated Approach

Since most cancer treatments come with a certain degree of toxicity it is very essential to identify a cancer type correctly and then administer the relevant therapy. With the arrival of powerful tools such as gene expression microarrays the cancer classification basis is slowly changing from morphological properties to molecular signatures. Several recent studies have demonstrated a marked improvement in prediction accuracy of tumor types based on gene expression microarray measurements over clinical markers. The main challenge in working with gene expression microarrays is that there is a huge number of genes to work with. Out of them only a small fraction are actually relevant for differentiating between different types of cancer. A Bayesian nearest neighbor model equipped with an integrated variable selection technique is proposed to overcome this challenge. This classification and gene selection model is able to classify different cancer types accurately and simultaneously identify the relevant or important genes. The proposed model is completely automatic in the sense that it adaptively picks up the neighborhood size and the important covariates. The method is successfully applied to three simulated data sets and four well known real data sets. To demonstrate the competitiveness of the method a comparative study is also done with several other ''off the shelf'' popular classification methods. For all the simulated data sets and real life data sets, the proposed method produced highly competitive if not better results. While the standard approach is two step model building for gene selection and then tumor prediction, this novel adaptive gene selection technique automatically selects the relevant genes along with tumor class prediction in one go. The biological relevance of the selected genes are also discussed to validate the claim.
Learning Data Trend Regularities From Databases in a Dynamic Environment

Knowledge discovery in databases has attracted a lot of attention from the AI and databases community because of the huge information stored in the databases. There are a lot of algorithms developed to find rules from databases directly, but all these algorithms assume that the data and the data scheme are stable and most of the algorithm focus on discovering the regularities about the current data in the databases. In this paper we present a method which can learn rules from the current data in the database to predict the data trend in the future. Our method combines the techniques of attribute-oriented induction, object-oriented databases and transition network. In our model, both the database contents and the database structure may evolve over the lifetime of a database.
Lagrangian Visualization of Flow‐Embedded Surface Structures

The notions of Finite‐Time Lyapunov Exponent (FTLE) and Lagrangian Coherent Structures provide a strong framework for the analysis and visualization of complex technical flows. Their definition is simple and intuitive, and they are built on a deep theoretical foundation. We apply these concepts to enable the analysis of flows in the immediate vicinity of the boundaries of flow‐embedded objects by limiting the Lagrangian analysis to surfaces closely neighboring these boundaries. To this purpose, we present an approach to approximate FTLE fields over such surfaces. Furthermore, we achieve an effective depiction of boundary‐related flow structures such as separation and attachment over object boundaries and specific insight into the surrounding flow using several specifically chosen visualization techniques. We document the applicability of our methods by presenting a number of application examples.
Body Iron Stores Are Associated With Serum Insulin and Blood Glucose Concentrations: Population study in 1,013 eastern Finnish men

OBJECTIVE To study if there is an association between mildly elevated body iron and glucose homeostasis indexes. RESEARCH DESIGN AND METHODS A cross-sectional population study was conducted in 1,013 middle-aged men, and an association of serum ferritin with concentrations of serum insulin, blood glucose, and serum fructosamine was tested. RESULTS The mean concentration of fasting serum insulin was 21.6% higher (95% CI 7.3–37.9%, P < 0.001) in the 5th quintile of serum ferritin compared with the 1st quintile. The elevation in blood glucose was 6.1% (95% CI 2.3–9.9%, P < 0.001) and in serum fructosamine 3.9% (1.5–6.9%, P < 0.01). CONCLUSIONS Mildly elevated body iron stores are associated with statistically significant elevations in glucose homeostasis indexes.
Stacked Multilayer Self-Organizing Map for Background Modeling

In this paper, a new background modeling method called stacked multilayer self-organizing map background model (SMSOM-BM) is proposed, which presents several merits such as strong representative ability for complex scenarios, easy to use, and so on. In order to enhance the representative ability of the background model and make the parameters learned automatically, the recently developed idea of representative learning (or deep learning) is elegantly employed to extend the existing single-layer self-organizing map background model to a multilayer one (namely, the proposed SMSOM-BM). As a consequence, the SMSOM-BM gains several merits including strong representative ability to learn background model of challenging scenarios, and automatic determination for most network parameters. More specifically, every pixel is modeled by a SMSOM, and spatial consistency is considered at each layer. By introducing a novel over-layer filtering process, we can train the background model layer by layer in an efficient manner. Furthermore, for real-time performance consideration, we have implemented the proposed method using NVIDIA CUDA platform. Comparative experimental results show superior performance of the proposed approach.
Applying resource sharing algorithms to ADL-driven automatic ASIP implementation

Presently, architecture description languages (ADLs) are widely used to raise the abstraction level of the design space exploration of application specific instruction-set processors (ASIPs), benefiting from automatically generated software tool suite and RTL implementation. The increase of abstraction level and automated implementation traditionally comes at the cost of low area, delay or power efficiency. The standard synthesis flow starting at RTL abstraction fails to compensate for this loss of performance. Thus, high level optimizations during RTL synthesis from ADLs are obligatory. Currently, ADL-based optimization schemes do not perform resource sharing. In this paper, we present an iterative algorithm for performing resource sharing on the basis of global dataflow graph matching criteria. This ADL-based resource sharing optimization is performed over a RISC and a VLIW architecture and two industrial embedded processors. The results indicate a significant improvement in overall performance. A comparative study with manually written RTL code is presented, too.
Effects of 4-aminopyridine on action potentials generation in mouse sinoauricular node strips

The physiological role of Ito has yet to be clarified. The goal of this study is to investigate the possible contribution of the transient outward current (Ito) on the generation of transmembrane action potentials (APs) and the sensitivity of mouse sinoauricular node (SAN) cells to a 4‐aminopyridine (4AP) as Ito blocker. The electrophysiological identification of cells was performed in the sinoauricular node artery area (nstrips = 38) of the subendocardial surface using microelectrode technique. In this study, for the first time, it was observed that dependence duration of action potential at the level of 20% repolarization (APD20) level under a 4AP concentration in the pacemaker SAN and auricular cells corresponds to a curve predicted by Hill's equation. APD20 raised by 70% and spike duration of AP increased by 15–25%, when 4AP concentration was increased from 0.1 to 5.0 mmol/L. Auricular cells were found to be more sensitive to 4AP than true pacemaker cells. This was accompanied by a decrease in the upstroke velocity as compared to the control. Our data and previous findings in the literature lead us to hypothesize that the 4AP‐sensitive current participates in the repolarization formation of pacemaker and auricular type cells. Thus, study concerning the inhibitory effects of lidocaine and TTX on APD20 can explain the phenomenon of the decrease in upstroke velocity, which, for the first time, was observed after exposure to 4AP. Duration of AP at the level of 20% repolarization (APD20) under a 4‐AP concentration 0.5 mmol/L in the true pacemaker cells lengthen by 60–70% with a control.
People help people: A pattern-matching localization with inputs from user community

Location-based services are regarded as a killer application of mobile networks. Among all RF-based localization techniques, the pattern-matching scheme is probably the most widely accepted approach. A key factor to its success is the accuracy concern and the calibration efforts to collect its training data. In this paper, we propose a community-based approach to reduce the calibration effort. We show how to get some volunteers (called co-trainers) to help add more training data to our location database. We also show how to rate the credit level of a co-trainer and the trust level of a piece of training data contributed by a co-trainer. We believe that our framework can greatly reduce the calibration effort of the pattern-matching localization scheme.
Adjuvant administration of 17-α-hydroxy-progesterone caproate in women with three or more second trimester pregnancy losses undergoing cervical cerclage is no more effective than cerclage alone

Abstract Objective: To investigate the role of adjuvant 17-α-hydroxy-progesterone caproate (17OHP-C) in reducing the risk of preterm delivery <34 weeks and adverse perinatal outcomes in women with ≥3 second trimester pregnancy losses attributed to cervical insufficiency undergoing prophylactic cerclage. Material and methods: Retrospective cohort study of women with prophylactic cerclage placed between 2006 and 2014 divided into a cohort of (i) those receiving adjuvant 17OHP-C (n=43), and (ii) controls with cerclage alone (n=59). Results: Demographic characteristics were comparable in both groups. There was no significant difference in gestational age at delivery between the cerclage-17OHP-C group (33.4±5.6 weeks) and the cerclage-alone group (34.4±4.6 weeks); P=0.33. We noted a non-significant increase for deliveries <34 weeks in the cerclage-17OHP-C group (44.2%) compared to controls (28.8%) which remained non-significant after adjusting for confounders; P=0.46. There was no statistically significant difference in the rate of delivery <37, 32, 28 and 24 weeks. Adverse neonatal outcomes were comparable in both groups (cerclage-17OHP-C 48.8% vs. cerclage-alone 39%); P=0.43. Conclusion: Intramuscular 17OHP-C in combination with prophylactic cerclage in women with cervical insufficiency and ≥3 second trimester pregnancy losses had no synergistic effect in reducing the rate of recurrent preterm birth or improving perinatal outcomes.
The ToolFinger: supporting complex direct manipulation in virtual environments

Virtual environments (VEs) such as the Responsive Workbench were designed to support interactive, complex applications. The possibility of direct manual interaction with virtual objects, using both hands in a natural, intuitive way is one of the great advantages of such configurations. The related work on interaction techniques for these environments is mainly concentrated on hand-oriented, spatial manipulation. With increasing complexity of applications, application control issues become more relevant, including the problem of tool selection. In this paper, we propose a new interaction technique, optimized for handling tool selection tasks comfortably, called the ToolFinger. The ToolFinger is a hand held 3D widget, resembling a pen, to which a set of tools is assigned in a way that selecting and applying a tool are no longer two separated tasks. The ToolFinger concept allows a fluent integration of tool selections and tool switches with the workflow of geometry editing. It benefits complex manipulation tasks in applications such as immersive geometric modelling, or interactive visualisation.
Precipitation from vertical motion: a statistical diagnostic scheme

The relationship between precipitation and atmospheric vertical motion is investigated over the globe. By combining and averaging precipitation rates within small ranges of vertical motion, the mean precipitation rate is found to vary smoothly with vertical motion. The relationship is modelled with a simple function that assumes zero precipitation for subsidence and linearly increasing precipitation for ascending motion. Function parameters are computed from National Centers for Environmental Prediction reanalysis data individually for every grid point and calendar month. Variations in the slope account for geographical and seasonal variations in moisture and other precipitation factors. At each grid point, the scheme diagnoses precipitation rate from a single concurrent value of vertical motion. It is shown to have moderate skill over climatology in predicting mean monthly precipitation. The midlatitudes, oceans and the winter season are favoured. The scheme is designed to extract precipitation fields from a dry general circulation model, based on the simulated vertical motion. Application to climate modelling is discussed. Copyright © 2003 Royal Meteorological Society
MIST: PVM with Transparent Migration and Checkpointing

We are currently involved in research to enable PVM to take advantage of shared networks of wOT'kstations (NOWs) more effectively. In such a computing environment, it is important to utilize workstations unobtrusively and recover from machine failures. Towards this goal, we have enhanced PVM with transparent task migration, checkpointing, and global scheduling. These enhancements are parl of the MIST project which takes an open systems approach in developing a cohesive, distributed parallel computing environment. This open systems approach promotes plug-and-play integration of independently developed modules, such as Condor, DQS, A VS, Prospero, XPVM, PIOUS,
Evaluation of a Novel Technique for Determining Near Optimal Task Granularity in Parallel Programs

The evolution of computers is moving more and more towards multi-core processors and parallel programs. For parallel programs to perform effciently the task granularity has to be near optimal for that specific problem. The aim of this thesis is to evaluate a novel technique, called Control of the Critical Path Delay (CCPD), for determining a near optimal granularity for parallel programs, and determine when the technique succeeds, why it performs as it does and if there is a way to improve the technique. The CCPD-technique showed promising on problems where non-optimal scheduling did not play any part. Where the non-optimal scheduling affected the problem the CCPD-technique did not perform well. To deal with potentially poor scheduling a method to improve the technique by incorporating more information from the critical path curve is proposed. Experimental results on a shared memory system as well as theoretical analysis are presented.
Recovery of Salmonella enterica serovars Typhimurium and Tennessee in peanut butter after electron beam exposure.

UNLABELLED The effect of electron beam (e-beam) radiation on the recovery of Salmonella serotypes Tennessee (ATCC 10722) and Typhimurium (ATCC 14028) in creamy peanut butter over a 14-d storage period at 22 °C was studied. Each Salmonella type was independently inoculated into peanut butter and subjected to e-beam doses that ranged from 0 to 3.1 kGy, confirmed by film dosimetry. After 2-, 4-, 6-, 8-, and 14-d of storage, microbial analyses were conducted. Survivors were recovered on growth and selective media using standard spread-plating methods. Microbial counts (CFU/g) were log-converted and differences were determined by ANOVA and Tukey's Honestly Significant Differences test. When samples were not e-beam-treated, there were no significant changes (P > 0.05) in microbial numbers over time. In e-beamed samples, microbial numbers decreased over time; however, reductions were not always significant. Initial recovery rates (R-rates) 2 d after e-beam treatment were significantly different for the 2 strains of Salmonella and between recovery media (P < 0.05); however, these differences did not persist for the remainder of the storage period (P > 0.05) indicating that injured cells were not able to survive in the high-fat, low-water activity peanut butter environment. R-rates for both strains of Salmonella were maintained until day 14 when there were significant reductions in Salmonella Typhimurium (P < 0.05). These results indicate that Salmonella Tennessee and Salmonella Typhimurium will survive in peanut butter when exposed to nonlethal doses of e-beam irradiation. PRACTICAL APPLICATION Electron beam (e-beam) irradiation is an alternative to thermal processing; this technique inactivates microorganisms and insects that might be present in a food by generating radiation by accelerated electrons that inactivate organisms directly because of interaction with cell components and indirectly by producing free radicals that disrupt integrity of the cell membrane. E-beam radiation will reduce the number of probable microbiological hazards that could be present while the food remains generally unaffected in texture, taste, and nutritional value. A recent study showed e-beam irradiation to be effective at reducing both Salmonella Tennessee and Typhimurium in peanut butter by one log after exposure to less than 1 kGy, highlighting the need to explore this process further.
Reactive synthesizing of human locomotion combining nonholonomic and holonomic behaviors

The trajectories of walking humans can be divided into two major classes: first, nonholonomic trajectories during which the orientation of the human body and the one of the motion are aligned (e.g., straight walking), and second, holonomic ones during which lateral velocities are observed (e.g., side-steps). The major contribution of this work is a general locomotion synthesis method for digital actors which enables combining nonholonomic and holonomic walk behaviors. Our motion synthesis technique is based on a motion capture blending method. Such a method is able to transform a low-dimensional trajectory describing the global displacement of a digital actor into a high-dimensional motion which involves all the degrees of freedom of the digital actor body. We extend previously existing motion blending techniques [12] to reach this goal. More precisely, we consider lateral velocity as a new input of the motion synthesis problem, whereas only tangential and angular were initially considered. Thus, the digital actor locomotion is controlled from 3 inputs in our approach: the tangential velocity, the angular velocity and the lateral velocity. The paper describes the major steps of our approach. At pre-processing, we analyze some motion captured locomotion cycles to build a Motion Library. The content of the library is projected into the Control Space. Then, at runtime, input (i.e., desired walk velocities) is also projected into the Control Space. We deduce a selection of motion captured locomotion cycles from the library, which are finally interpolated to generate a locomotion animation for digital actors. The newly generated locomotion cycle exhibit the desired input velocities.
On the dimension of the Hilbert scheme of curves

Consider a component of the Hilbert scheme whose general point corresponds to a degree d genus g smooth irreducible and nondegenerate curve in a projective variety X. We give lower bounds for the dimension of such a component when X is P^3, P^4 or a smooth quadric threefold in P^4 respectively. Those bounds make sense from the asymptotic viewpoint if we fix d and let g vary. Some examples are constructed using determinantal varieties to show the sharpness of the bounds for d and g in a certain range. The results can also be applied to study rigid curves.
C-kit positive interstitial cells of Cajal network in primary obstructive megaureter.

AIM Recent reports have shown an altered density of interstitial cells of Cajal (ICCs) and peripherin immunoreactive nerve fibres in uretopelvic junction obstruction. The aim was to investigate ICCs immunoexpression and ureteral innervation in primary obstructive megaureter (POM). METHODS Eight specimens of POM were obtained during tailoring. Restricted segments of ureters were divided from dilated segments. C-kit and peripherin immunohistochemistry were performed. RESULTS A normal distribution of ICCs was observed in both the circular and longitudinal muscle layers of the dilated segments. Marked muscle hypoplasia and sparse or no ICCs occurred in the longitudinal muscle layer of the restricted ureteral segments. A normal distribution of peripherin positive fibres was present in both the dilated and restricted segments. CONCLUSIONS Our data confirm defective muscularization in restricted aperistaltic POM. The lack of ICCs in the longitudinal muscular layer is probably due to the absence of c-kit positive muscle embryological precursors. No alteration in the peripherin immunoreactive nerve fibres network was observed in either the dilated or the restricted ureteral segments.
From Information to Experience: Place-Based Augmented Reality Games as a Model for Learning in a Globally Networked Society

Background/Context New information technologies make information available just-in-time and on demand and are reshaping how we interact with information, but schools remain in a print-based culture, and a growing number of students are disaffiliating from traditional school. New methods of instruction are needed that are suited to the digital age. Purpose/Objective/Research Question/Focus of Study The purpose of this study is to explore how curricula that are designed to capitalize on the affordances of mobile media might be employed in schools. Population/Participants/Subjects The study took place during a 2-week unit in a poor urban school district with roughly 50 at-risk middle school students. The partnering teacher adapted the model curriculum, which involved students investigating a rash of illnesses originating from a popular local beach. This qualitative case study, derived from field notes, videotapes, interviews, and document analyses, describes the practices that emerged and the strengths and limitations of the curriculum. From a classroom management perspective, the narrative elements of the unit enabled teachers to create a dramatically different classroom culture, one that was built around students performing as scientists. Students’ performance was heavily dependent on the kinds of inscriptions that they made to organize data, suggesting the importance of designers developing tools to scaffold learning, but also suggesting trade-offs in having students struggle to organize information versus doing it for them. Most noteworthy to teachers was how the technology-enhanced curriculum enacted students’ identities as problem solvers and knowledge builders rather than as compliant consumers of information, reinforcing for them the schism between what is expected of students in school and how they interact outside of school. Teachers and students lamented the lack of opportunities to actually participate in community issues beyond the classroom, suggesting that the future of such curricula may reside in building community-school-home partnerships.