Miracle-dz/UniFAR-FTUs huggingface dataset:
Cianfriglia Targeting MDR 1P-glycoprotein ( MDR 1-Pgp ) in immunochemotherapy of acute myeloid leukemia ( AML )

Background. Monoclonal antibodies represent the fastest growing sector of pharmaceutical biotechnology and a number of antibody-based biopharmaceuticals have been approved for cancer treatment. However, in many cases the antibodies used for the treatment of tumors offer only a modest survival benefit to cancer patients. Aims. In the present review-article we intend to analyze: i) the curative regimen gemtuzumab ozogamicin (GO) -mediate characterized by the absence of cytotoxic drugs MDR1-Pgp substrates to overcome the mechanism of action of this multidrug transporter, ii) the safety and efficacy of MDR reversing strategy in AML outcome and, iii) chemical and biological MDR modulators playing a dual relevant medical role as a therapeutic and MDR reversing agents but not yet entered in the clinical setting of AML. Since the similar multidrug transporter protein MDR1-Pgp and its down modulation factors may affect safety and efficacy of already generated antibody drug conjugates (ADCs) a comprehensive overview of the most clinically representative immunoconjugates is reported. Discussion. ADCs represent one of the most promising strategies to enhance the antitumor activity of antibodies. ADCs comprise an antibody (or an antibody fragment) conjugated to a cytotoxic drug via a chemical linker. The therapeutic concept of ADCs is to use an antibody as a vehicle to selectively delivering a cytotoxic drug specifically to a tumor cell, in most cases by means of binding to target cell surface antigen. As a consequence, ADCs have significant potential for enhancing the antitumor activity of “naked” antibodies and reducing the systemic toxicity of the conjugated drugs. Maurizio Cianfriglia Targeting MDR1-P-glycoprotein (MDR1-Pgp) in immunochemotherapy of acute myeloid leukemia (AML) Dipartimento del Farmaco, Istituto Superiore di Sanità, Rome, Italy Ann Ist Super Sanità 2013 | Vol. 49, No. 2: 190-208 DOI: 10.4415/ANN_13_02_11
Programmable clustering

We initiate a novel study of clustering problems. Rather than specifying an explicit objective function to optimize, our framework allows the user of clustering algorithm to specify, via a first-order formula, what constitutes an acceptable clustering to them. While the resulting genre of problems includes, in general, NP-complete problems, we highlight three specific first-order formulae, and provide efficient algorithms for the resulting clustering problems.
The Characterisation of (Quantitative) Structure-Activity Relationships: Preliminary Guidance

In November 2004, the OECD Member Countries and the European Commission adopted five principles for the validation of (quantitative) structure-activity relationships ([Q]SARs) intended for use in the regulatory assessment of chemicals. International agreement on a set of valdation principles was important, not only to provide regulatory bodies with a scientific basis for making decisions on the acceptability of data generated by (Q)SARs, but also to promote the mutual acceptance of (Q)SAR models by improving the transparency and consistency of (Q)SAR reporting. According to the OECD Principles for (Q)SAR validation, a (Q)SAR model that is proposed for regulatory use should be associated with five types of information: 1) a defined endpoint; 2) an unambiguous algorithm; 3) a defined domain of applicability; 4) appropriate measures of goodness-of-fit, robustness and predictivity; and 5) a mechanistic interpretation, if possible. Taken together, these five principles form the basis of a conceptual framework for characterising (Q)SAR models, and of reporting formats for describing the model characteristics in a transparent manner. Under the proposed REACH legislation in the EU, there are provisions for the use of estimated data generated by (Q)SARs, both as a substitute for experimental data, and as a supplement to experimental data in weight-of-evidence approaches. It is foreseen that (Q)SARs will be used for the three main regulatory goals of hazard assessment, risk assessment and PBT/vPvB assessment. In the Registration process under REACH, the registrant will be able to use (Q)SAR data in the registration dossier provided that adequate documentation is provided to argue for the validity of the model(s) used. This report provides preliminary guidance on how to characterise (Q)SARs according to the OECD validation principles. It is emphasised that the understanding of how to characterise (Q)SAR models is evolving, and that the content of the current report reflects the understanding and perspectives of the authors at the time of writing (November 2005). It is therefore likely that an update will be produced in the future for the benefit of those who need to submit (Industry) or evaluate (Authorities) chemical information based (partly) on (Q)SARs. It is also noted that this document does not provide guidance on the use of (Q)SAR reporting formats, or on criteria for the acceptance of (Q)SAR estimates, since EU guidance on these topics stills need to be developed.
A Relaxation Scheme for TSP-Based 3D Printing Path Optimizer

Additive-layered manufacturing has gained attentionin recent years as it has many advantages over conventionalinjection moulding methods. The optimization of printing trajectoriescan be formulated as a travelling salesman problem (TSP) and solved accordingly. However, computational complexities ofordinary TSP solvers can increase tremendously with the scaleof the problem, which make them impractical. In this work, arelaxation scheme for TSP-based 3D printing path optimizer isproposed. Simulation results show that the proposed scheme cansignificantly shorten the computational time of the optimizationprocess with insignificant impact on solution quality.
Whole Genome Association Study to Detect Single Nucleotide Polymorphisms for Behavior in Sapsaree Dog (Canis familiaris)

The purpose of this study was to characterize genetic architecture of behavior patterns in Sapsaree dogs. The breed population (n = 8,256) has been constructed since 1990 over 12 generations and managed at the Sapsaree Breeding Research Institute, Gyeongsan, Korea. Seven behavioral traits were investigated for 882 individuals. The traits were classified as a quantitative or a categorical group, and heritabilities (h2) and variance components were estimated under the Animal model using ASREML 2.0 software program. In general, the h2 estimates of the traits ranged between 0.00 and 0.16. Strong genetic (rG) and phenotypic (rP) correlations were observed between nerve stability, affability and adaptability, i.e. 0.9 to 0.94 and 0.46 to 0.68, respectively. To detect significant single nucleotide polymorphism (SNP) for the behavioral traits, a total of 134 and 60 samples were genotyped using the Illumina 22K CanineSNP20 and 170K CanineHD bead chips, respectively. Two datasets comprising 60 (Sap60) and 183 (Sap183) samples were analyzed, respectively, of which the latter was based on the SNPs that were embedded on both the 22K and 170K chips. To perform genome-wide association analysis, each SNP was considered with the residuals of each phenotype that were adjusted for sex and year of birth as fixed effects. A least squares based single marker regression analysis was followed by a stepwise regression procedure for the significant SNPs (p<0.01), to determine a best set of SNPs for each trait. A total of 41 SNPs were detected with the Sap183 samples for the behavior traits. The significant SNPs need to be verified using other samples, so as to be utilized to improve behavior traits via marker-assisted selection in the Sapsaree population.
A distributed polling service‐based MAC protocol testbed

Medium access control (MAC) protocols play a vital role in wireless networking. It is well‐known that the high control overhead of IEEE 802.11 MAC is the limiting factor on the throughput and delay performance of wireless networks. In our prior work, three polling service‐based medium access control protocols (PSMACs) are developed to amortize the high control overhead over multiple frame transmissions, thus achieving higher efficiency. Both analysis and simulations are conducted to validate the efficacy of the proposed protocols. In this paper, we extend this work by implementing the distributed version of PSMAC, i.e., PSMAC 2, on the GNU Radio and universal software radio peripheral (GNU Radio/USRP) platform. We discuss various design considerations and challenges of prototyping PSMAC 2 and carry out extensive experimental studies with the GNU Radio/USRP PSMAC testbed. Our experimental results are found to be consistent with the theoretical study reported in our prior work and validate the advantages of PSMAC under a realistic wireless channels. Copyright © 2013 John Wiley & Sons, Ltd.
Applications of targeted proteomics in systems biology and translational medicine

Biological systems are composed of numerous components of which proteins are of particularly high functional significance. Network models are useful abstractions for studying these components in context. Network representations display molecules as nodes and their interactions as edges. Because they are difficult to directly measure, functional edges are frequently inferred from suitably structured datasets consisting of the accurate and consistent quantification of network nodes under a multitude of perturbed conditions. For the precise quantification of a finite list of proteins across a wide range of samples, targeted proteomics exemplified by selected/multiple reaction monitoring (SRM, MRM) mass spectrometry has proven useful and has been applied to a variety of questions in systems biology and clinical studies. Here, we survey the literature of studies using SRM‐MS in systems biology and clinical proteomics. Systems biology studies frequently examine fundamental questions in network biology, whereas clinical studies frequently focus on biomarker discovery and validation in a variety of diseases including cardiovascular disease and cancer. Targeted proteomics promises to advance our understanding of biological networks and the phenotypic significance of specific network states and to advance biomarkers into clinical use.
Mid-Infrared Diagnostics of Starburst Galaxies: Clumpy, Dense Structures in Star-Forming Regions in the Antennae (NGC 4038/4039)

Recently, mid-infrared instruments have become available on several large ground-based telescopes, resulting in data sets with unprecedented spatial resolution at these long wavelengths. In this paper we examine "ground-based-only" diagnostics, which can be used in the study of star-forming regions in starburst galaxies. By combining output from the stellar population synthesis code Starburst99 with the photoionization code Mappings, we model stellar clusters and their surrounding interstellar medium, focusing on the evolution of emission lines in the N- and Q-band atmospheric windows (8-13 and 16.5-24.5 μm, respectively) and those in the near-infrared. We address the detailed sensitivity of various emission-line diagnostics to stellar population age, metallicity, nebular density, and ionization parameter. Using our model results, we analyze observations of two stellar clusters in the overlap region of the Antennae galaxies obtained with VLT Imager and Spectrometer for Mid-Infrared (VISIR). We find evidence for clumpy, high-density, ionized gas. The two clusters are young (younger than 2.5 and 3 Myr, respectively), the surrounding interstellar matter is dense (≥104 cm-3) and can be characterized by a high ionization parameter (log U ≥ -1.53). Detailed analysis of the mid-infrared spectral features shows that a (near-)homogeneous medium cannot account for the observations, and that complex structure on scales below the resolution limit, containing several young stellar clusters embedded in clumpy gas, is more likely.
Multi-channel Data Collection for Throughput Maximization in Wireless Sensor Networks

We present the design and implementation of Multi-Channel Collection (MCC) protocol , a high-rate multi-channel time-scheduled protocol for fair, real-time data collection in Wireless Sensor Networks (WSN). MCC incorporates sophisticated mechanisms for balanced routing tree formation, multiple frequency channel allocation and globally synchronized TDMA scheduling. Through systematic experiments with real WSN hardware (Tmote Sky), we identify the maximum possible throughput for many-to-one (convergecast) data collection as a function of key communication parameters such as packet size, use of acknowledgements, and network topology. Then, we demonstrate that the maximum achievable network throughput can in fact be attained in practice using a carefully designed mix of routing, frequency allocation and time scheduling. Compared to state of the art collection protocols for WSN, we show that MCC offers 33-155% improvement in throughput. We also show how to exploit the time-scheduled nature of this approach for reducing the number of required frequency channels. MCC presents an algorithmic approach for time-frequency scheduling and routing that could be adapted and used in conjunction with relevant emerging standards such as WirelessHART, ISA 100.11a and IEEE 802.15. 4e TSCH.
Multilevel logic synthesis

A survey of logic synthesis techniques for multilevel combinational logic is presented. The goal is to provide more in-depth background and perspective for people interested in pursuing or assessing some of the topics in this emerging field. Introductions, capsule summaries, and, in some cases, detailed analysis of the synthesis methods that have become established as practically significant are provided. Also included are some methods that have theoretical interest and potential for future impact. The discussion covers notation and definitions, representation of the network and nodes, logic decomposition/restructuring, logic optimization/minimization, logic synthesis and testing, and technology mapping. >
Interactive volume rendering

Volume rendering is the display of data sampled in three dimensions. Traditionally, visualization of such data has been through conventional computer graphics line or surface drawing methods preceded by processes that coerce the sampled data into a form suitable for display. This approach is being replaced by new techniques which operate directly on the three dimensional samples to avoid the artifacts introduced by the use of conventional graphics primitives. Volume rendering is a compute-intensive operation. This paper discusses an approach for volume rendering in which interactive speed is achieved through a parallelizable forward mapping algorithm, successive refinement, table driven mappings for shading and filtering, and the avoidance of complex machine classification of the data. Since the renderer is interactive, users are able to specify application specific mapping functions on-thefly. Current applications include molecular modeling, geology, computed tomography, and astronomy.
Frequent itemset mining algorithms: A literature survey

Data mining is used for mining useful data from huge datasets and finding out meaningful patterns from the data. Many organizations are now using data mining techniques. Frequent pattern mining has become an important data mining technique and has been a focused area in research field. Frequent patterns are patterns that appear in a data set most frequently. Various methods have been proposed to improve the performance of frequent pattern mining algorithms. In this paper, we provide the preliminaries of basic concepts about frequent pattern tree(fp-tree) and present a survey of the recent developments in this area that is receiving increasing attention from the Data Mining community. Experimental results show that fp- Tree based approach achieves better performance than Apriori. So here we concentrate on recent fp-tree modifications and some other new techniques other than Apriori. A single paper cannot be a complete review of all the algorithms, here we have included only four relevant papers which are recent and directly using the basic concept of fp-tree. A brief description of each technique has been provided. This detailed literature survey is a preliminary to the proposed research which is to be further carried on.
Computationally Efficient Music Synthesis – Methods and Sound Design

In this thesis, the design of a music synthesizer for systems suffering from limitations in computing power and memory capacity is presented. First, different possible synthesis techniques are reviewed and their applicability in computationally efficient music synthesis is discussed. In practice, the applicable techniques are limited to additive and source-filter synthesis, and, in special cases, to frequency modulation, wavetable and sampling synthesis. Next, the design of the structures of the applicable techniques are presented in detail, and properties and design issues of these structures are discussed. A major implementation problem is raised in digital source-filter synthesis, where the use of classic wave-forms, such as sawtooth wave, as the source signal is challenging due to aliasing caused by waveform discontinuities. Methods for existing bandlimited waveform synthesis are reviewed, and a new approach using polynomial bandlimited step function is presented in detail with design rules for the applicable polynomials. The approach is also tested with two different third-order polynomials. They reduce aliasing more at high frequencies, but at low frequencies their performance is worse than with the first-order polynomial. In addition, some commonly used sound effect algorithms are reviewed with respect to their applicability in computationally efficient music synthesis. In many cases the sound synthesis system must be capable of producing music consisting of various different sounds ranging from real acoustic instruments to electronic instruments and sounds from nature. Therefore, the music synthesis system requires careful sound design. In this thesis, sound design rules for imitation of various sounds using the computationally efficient synthesis techniques are presented. In addition, the effects of the parameter variation for the design of sound variants are presented.
CS 270 Project-Comparing and Clustering Human Motion

There are a number of usefull things that can be done with measurements of the similarity between a pair of motions. In this project I will first present methods used in two different papers to obtain a comparison of motions. The methods feature several common themes but vary widely as the input data differ significantly, specifically motion capture data vs. noisy video images. Next, I draw upon methods from both algorithms to compare motions from a database of motion capture data and cluster them into groups of related motions.
Insulin Resistance of Protein Metabolism in Type 2 Diabetes

OBJECTIVE—We previously demonstrated that 1) obesity impairs and 2) sex influences insulin sensitivity of protein metabolism, while 3) poor glycemic control in type 2 diabetes accelerates protein turnover in daily fed-fasted states. We hypothesized that type 2 diabetes alters the insulin sensitivity of protein metabolism and that sex modulates it. RESEARCH DESIGN AND METHODS—Hyperinsulinemic (∼570 pmol/l), euglycemic (5.5 mmol/l), and isoaminoacidemic (kept at postabsorptive concentrations) clamps were performed in 17 hyperglycemic type 2 diabetic subjects and 23 subjects without diabetes matched for age and body composition, after 7 days on a inpatient, protein-controlled, isoenergetic diet. Glucose and leucine kinetics were determined using tracers. RESULTS—In type 2 diabetes, postabsorptive (baseline) glycemia was 8–9 mmol/l, glucose production (Ra) and disposal (Rd) were elevated, and once clamped, endogenous glucose Ra remained greater and Rd was less (P < 0.05) than in control subjects. Baseline leucine kinetics did not differ despite higher insulin levels. The latter was an independent predictor of leucine flux within each sex. With clamp, total flux increased less (P = 0.016) in type 2 diabetic men, although protein breakdown decreased equally (∼20%) in male groups but less in female groups. Whereas protein synthesis increased in male control subjects and in both female groups, it did not in male subjects with type 2 diabetes. In men, homeostasis model assessment of insulin resistance predicted 44%, and, in women, waist-to-hip ratio predicted 40% of the change in synthesis. CONCLUSIONS—During our clamp, men with type 2 diabetes have greater insulin resistance of protein metabolism than that conferred by excess adiposity itself, whereas women do not. These results may have implications for dietary protein requirements.
Measuring Testability of Object Oriented Design: A Systematic Review

Testability is an important quality factor of object oriented software. Its correct measurement or evaluation always facilitates and improves the test process. A lack of testability contributes to a higher level test cost and changeable effort. However testability has always been an indefinable concept and its absolute estimation (measurement) or evaluation is a tough job. Researchers and practioners have always claimed that testability should be considered as key factors which have positive impact on software development in order to ensure the software quality customer satisfaction especially at design face. (29). The purpose of this review report is to proposing a conceptual comparative evaluation considering the testability issues, limitation and to investigate the general testability factors and commonly accepted minimal set of testability factors with the help of the systematic literature review. In this paper initially we conduct a literature review to have broad knowledge of testability and its quality factors and associated measurements that are found exhibiting the number of different testability factors that are presented by different researchers in different perspective. Next we do a comparative analysis on software testability proposed by various experts/researchers including their contribution and limitation.
Developments in forecast combination and portfolio choice

Contributors About the Contributors. Series Preface Preface THEME I MODEL AND FORECAST COMBINATIONS What Exactly Should We Be Optimising? Criterion Risk in Multicomponent and Multimodel Forecasting (A. Neil Burgess) A Meta-parameter Approach to the Construction of Forecasting Models for Trading Systems (Neville Towers and A. Neil Burgess) The Use of Market Data and Model Combination to Improve Forecast Accuracy (Christian L. Dunis, Jason Laws and Sti phane Chauvin) 21 Nonlinear Ways to Beat the Market (George T. Albanis and Roy A. Batchelor) Predcting High Performance Stocks Using Dimensionality Reduction Techniques Based on Neural Networks (George T. Albanis and Roy A. Batchelor) THEME II STRUCTURAL CHANGE AND LONG MEMEOR Structural Change and Long Memory in Volatility: New Evidence from Daily Exchange Rates (Michel Beine and Si bastien Laurent) Long-run Volatility Dependencies in Intraday Data and Mixture of Normal Distributions (Auri lie Boubel and Si bastien Laurent) Comparison of Parameter Esitmation Methods in Cyclical Long Memory Time Series (Laurent Ferrara and Dominique Guegan) THEME III CONTROLLING DOWNSIDE RISK AND INVESTMENT STRATEGIES Building a Mean Downside Risk Portfolio Frontier (Gustavo M. de Athayde) Implementing Discrete-Time Dynamic Investment Strategies with Downside Risk: A Comparison of Returns and Investment Policies (Mattias Persson) Portfolio Optimisation in a Downside Risk Framework (Riccardo Bramante and Barbara Cazzaniga) The Three-moment CAPM: Theoretical Foundations and an Asset Pricing Model Comparison in a Unified Framework (Emmanuel Jurczwnko and Bertrand Maillet) Stress-testing Correlations: An Application to Portfolio Risk Management (Frederick Bourgoin.) Index.