LLukas22/scidocs huggingface dataset:
Technology roadmapping in review : A tool for making sustainable new product development decisions

Typically, firms decide whether or not to develop a new product based on their resources, capabilities and the return on investment that the product is estimated to generate. We propose that firms adopt a broader heuristic for making new product development choices. Our heuristic approach requires moving beyond traditional finance-based thinking, and suggests that firms concentrate on technological trajectories by combining technology roadmapping, information technology (IT) and supply chain management to make more sustainable new product development decisions. Using the proposed holistic heuristic methods, versus relying on traditional finance-based decision-making tools (e.g., emphasizing net present value or internal rate of return projections), enables firms to plan beyond the short-term and immediate set of technologies at hand. Our proposed heuristic approach enables firms to forecast technologies and markets, and hence, new product priorities in the longer term. Investments in new products should, as a result, generate returns over a longer period than traditionally expected, giving firms more sustainable investments. New products are costly and need to have a 0040-1625/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0040-1625(03)00064-7 * Corresponding author. Tel.: +1-814-863-7133. E-mail addresses: ijpetrick@psu.edu (I.J. Petrick), aie1@psu.edu (A.E. Echols). 1 Tel.: +1-814-863-0642. I.J. Petrick, A.E. Echols / Technological Forecasting & Social Change 71 (2004) 81–100 82 durable presence in the market. Transaction costs and resources will be saved, as firms make new product development decisions less frequently. D 2003 Elsevier Inc. All rights reserved.
Randomized, comparative study of interferon beta-1a treatment regimens in MS: The EVIDENCE Trial.

BACKGROUND
Interferon beta (IFNbeta) reduces relapses and MRI activity in relapsing-remitting MS (RRMS), with variable effects on disability. The most effective dose regimen remains controversial.


METHODS
This randomized, controlled, multicenter trial compared the efficacy and safety of IFNbeta-1a (Rebif) 44 micro g subcutaneously three times weekly (tiw), and IFNbeta-1a (Avonex) 30 micro g IM once weekly (qw) in 677 patients with RRMS. Assessors blinded to treatment performed neurologic and MRI evaluations. The primary endpoint was the proportion of patients who were relapse free at 24 weeks; the principal MRI endpoint was the number of active lesions per patient per scan at 24 weeks.


RESULTS
After 24 weeks, 74.9% (254/339) of patients receiving IFNbeta-1a 44 micro g tiw remained relapse free compared with 63.3% (214/338) of those given 30 micro g qw. The odds ratio for remaining relapse free was 1.9 (95% CI, 1.3 to 2.6; p = 0.0005) at 24 weeks and 1.5 (95% CI, 1.1 to 2.1; p = 0.009) at 48 weeks, favoring 44 micro g tiw. Patients receiving 44 micro g tiw had fewer active MRI lesions (p < 0.001 at 24 and 48 weeks) compared with those receiving 30 micro g qw. Injection-site reactions were more frequent with 44 micro g tiw (83% vs 28%, p < 0.001), as were asymptomatic abnormalities of liver enzymes (18% vs 9%, p = 0.002) and altered leukocyte counts (11% vs 5%, p = 0.003) compared with the 30 micro g qw dosage. Neutralizing antibodies developed in 25% of 44 micro g tiw patients and in 2% of patients receiving 30 micro g qw.


CONCLUSIONS
IFNbeta-1a 44 micro g subcutaneously tiw was more effective than IFNbeta-1a 30 micro g IM qw on all primary and secondary outcomes investigated after 24 and 48 weeks of treatment.
Zero Knowledge in the Random Oracle Model, Revisited

We revisit previous formulations of zero knowledge in the random oracle model due to Bellare and Rogaway (CCS ’93) and Pass (Crypto ’03), and present a hierarchy for zero knowledge that includes both of these formulations. The hierarchy relates to the programmability of the random oracle, previously studied by Nielsen (Crypto ’02). – We establish a subtle separation between the Bellare-Rogaway formulation and a weaker formulation, which yields a finer distinction than the separation in Nielsen’s work. – We show that zero-knowledge according to each of these formulations is not preserved under sequential composition. We introduce stronger definitions wherein the adversary may receive auxiliary input that depends on the random oracle (as in Unruh (Crypto ’07)) and establish closure under sequential composition for these definitions. We also present round-optimal protocols for NP satisfying the stronger requirements. – Motivated by our study of zero knowledge, we introduce a new definition of proof of knowledge in the random oracle model that accounts for oracledependent auxiliary input. We show that two rounds of interaction are necessary and sufficient to achieve zero-knowledge proofs of knowledge according to this new definition, whereas one round of interaction is sufficient in previous definitions. – Extending our work on zero knowledge, we present a hierarchy for circuit obfuscation in the random oracle model, the weakest being that achieved in the work of Lynn, Prabhakaran and Sahai (Eurocrypt ’04). We show that the stronger notions capture precisely the class of circuits that is efficiently and exactly learnable under membership queries.
High-dose cyclophosphamide with or without etoposide for mobilization of peripheral blood progenitor cells in patients with multiple myeloma: efficacy and toxicity

Summary:The purpose of the study was to examine the yield of CD34+ cells, response rates, and toxicity of high-dose cyclophosphamide with or without etoposide in patients with multiple myeloma. In total, 77 myeloma patients received either cyclophosphamide 4.5 g/m2 (n=28) alone or with etoposide 2 g/m2 (n=49) in a nonrandomized manner, followed by G-CSF 10 μg/kg/day for the purpose of stem cell mobilization. The effects of various factors on CD34+ cell yield, response rate and engraftment were explored. A median of 22.39 × 106 CD34+ cells/kg were collected on the first day of leukapheresis (range 0.59–114.71 × 106/kg) in 71 (92%) of patients. Greater marrow plasma cell infiltration (P=0.02) or prior radiation therapy (P=0.02) adversely affected CD34+ cell yield. In total, 45% of patients receiving cyclophosphamide and 56% of those receiving cyclophosphamide/etoposide had at least a minimum response by EBMT criteria. In all, 25% of patients who received cyclophosphamide alone vs 75.5% of patients who received combined chemotherapy required hospitalization mainly for treatment of neutropenic fever. Cyclophosphamide alone is associated with impressive CD34+ cell yields and clear antimyeloma activity. The addition of etoposide resulted in increased toxicity without significant improvement in CD34+ cell yield or response rates.
Satellite-based vessel Automatic Identification System: A feasibility and performance analysis

The Automatic Identification System (AIS) is a VHF communication system that provides identification/ location information to vessels and shore stations by exchanging data such as position, identification, course, speed, etc. Recently, the interest in detecting and tracking ships at distances from coastlines larger than what can be accomplished by normal terrestrial VHF communications has grown, driven by requirements of long-range applications such as better handling of hazardous cargo, improved security and countering illegal operations. This paper presents an extension of AIS to a long-range positioning reporting through a constellation of LEO satellites. It outlines technical challenges like the high rate of message collisions from ships in the field of view of a satellite. Technical solutions are proposed at system and subsystem level to address these challenges. A computer-based system simulator is used to assess the system performance and carry out a high-level system sizing. Results show that a relatively small constellation of LEO satellites can guarantee good ship position detection probability as well as a reporting time interval of a few hours. System performance aspects to be addressed in future work are the possible impact of terrestrial mobile communications interference as well as variations of the estimated traffic data. Copyright r 2009 John Wiley & Sons, Ltd.
Four Switch Buck-Boost Converter for Photovoltaic DC-DC power applications

Photovoltaic energy is a wide kind of green energy. A high performance on these systems is needed to make the most of energy produced by solar cells. Also, there must be a constant adaptation due to the continuous variation of power production. Control techniques for Power Converters like the MPPT algorithm (Maximum Power Point Tracking) present very good results on photovoltaic chains. Nevertheless, losses on power elements reduce global performance and the voltage/current adaptation is not always possible. In this paper, the use of the high efficiency structure Four Switch Buck-Boost for Photovoltaic systems is addressed. FSBB Converters present some advantages regarding other Power Converter structures: it has few electrical components, output voltage can be higher or lower than input voltage, and it presents a non-inverted output voltage as happens with others Buck-Boost Converters. A prototype of FSBB has been developed in order to exploit these new capabilities for a Photovoltaic DC-DC power application (solar module: 0V to 20V input voltage and different resistive loads). The implemented MPPT digital control chooses between a Buck or Boost mode, depending on the working conditions. Firstly, an introduction and the FSBB operating mode are addressed. Then, the adaptive MPPT control algorithm is detailed. And finally, the experimental results and conclusion are presented.
Category independent object discovery via background modeling

Traditional approaches for object discovery assume that there are common characteristics among objects, and then attempt to extract features specific to objects in order to discriminate objects from background. However, the assumption “common features” may not hold, considering different variations between and within objects. Instead, we look at this problem from a different angle: if we can identify background regions, then the rest should belong to foreground. In this paper, we propose to model background to localize possible object regions. Our method is based on the observations: (1) background has limited categories, such as sky, tree, water, ground, etc., and can be easier to recognize, while there are millions of objects in our world with different shapes, colors and textures; (2) background is occluded because of foreground objects. Thus, we can localize objects based on voting from fore/background occlusion boundary. Our contribution lies: (1) we use graph-based image segmentation to yield high quality segments, which effectively leverages both flat segmentation and hierarchical segmentation approaches; (2) we model background to infer and rank object hypotheses. More specifically, we use background appearance and discriminative patches around fore/background boundary to build the background model. The experimental results show that our method can generate good quality object proposals and rank them where objects are covered highly within a small pool of proposed regions. © 2016 Elsevier B.V. All rights reserved.
Improvement of clustal-derived sequence alignments with evolutionary algorithms

Multiple sequence alignment (MSA) is a central problem in bioinformatics. In this study, we extended previous efforts using evolutionary algorithms (EAs) for MSA. Candidate solutions in the initial population were derived from the well-known alignment program Clustal X. Evolutionary computation was then used to evolve increasingly appropriate solutions. Three new alignment operators were introduced and tested within the framework of protein sequence alignment. Statistics on alignment quality were generated with respect to selected alignment benchmarks from the BAliBASE database using the BLOSUM 62 substitution matrix. Our results indicate the degree to which EAs can enhance the results of Clustal X. Moreover, the experimental results show that the commonly used sum-ofpairs scoring scheme sometimes fails to correlate higher scoring alignments with increase in alignment quality in terms of the BAliBASE sum-of-pairs score.
Evolution of development in closely related species of flies and worms

Key PointsThe extensive knowledge of the genetic basis for development of the model organisms Drosophila melanogaster and Caenorhabditis elegans, together with their complete genome sequences, provides a useful tool for comparing their development with that of other closely related species. To identify the genetic changes that underlie small morphological differences, recent studies have used either a candidate-gene approach or, where hybrids are viable, direct classical genetics. This approach can allow the rapid identification of genes that contribute to phenotypic change. Evolution of cis-regulatory sequences that alters gene expression might contribute to phenotypic change. Regulatory modules of developmental genes are subject to continuous sequence change and to stabilizing selection in the absence of morphological change. Co-evolution of transcription factors and their binding sequences can be readily shown using comparisons between closely related species. The redundant cellular interactions that underlie the development of a structure and that contribute to its robustness are also subject to continuous change. Studies of satellite species should help to bridge the gap between evolutionary genetics and comparative embryology.AbstractOne of the main challenges in evolutionary biology is to identify the molecular changes that underlie phenotypic differences that are of evolutionary significance. Comparative studies of early development have shown that changes in the spatio-temporal use of regulatory genes, as well as changes in the specificity of regulatory proteins, are correlated with important differences in morphology between phylogenetically distant species. However, it is not known how such changes take place in natural populations, and whether they result from a single, or many small, additive events. Extending this approach to the study of development of closely related species promises to enrich this debate.
Multimodal theater: extending low fidelity paper prototyping to multimodal applications

Low-fidelity paper prototyping has proven to be a useful technique for designing graphical user interfaces [1]. Wizard of Oz prototyping for other input modalities, such as speech, also has a long history [2]. Yet to surface are guidelines for low-fidelity prototyping of multimodal applications, those that use multiple and sometimes simultaneous combination of different input types. This paper describes our recent research in low fidelity, multimodal, paper prototyping and suggest guidelines to be used by future designers of multimodal applications.
Building Efficient Query Engines in a High-Level Language

Abstraction without regret refers to the vision of using high-level programming languages for systems development without experiencing a negative impact on performance. A database system designed according to this vision offers both increased productivity and high performance instead of sacrificing the former for the latter as is the case with existing, monolithic implementations that are hard to maintain and extend.
 In this article, we realize this vision in the domain of analytical query processing. We present LegoBase, a query engine written in the high-level programming language Scala. The key technique to regain efficiency is to apply generative programming: LegoBase performs source-to-source compilation and optimizes database systems code by converting the high-level Scala code to specialized, low-level C code. We show how generative programming allows to easily implement a wide spectrum of optimizations, such as introducing data partitioning or switching from a row to a column data layout, which are difficult to achieve with existing low-level query compilers that handle only queries. We demonstrate that sufficiently powerful abstractions are essential for dealing with the complexity of the optimization effort, shielding developers from compiler internals and decoupling individual optimizations from each other.
 We evaluate our approach with the TPC-H benchmark and show that (a) with all optimizations enabled, our architecture significantly outperforms a commercial in-memory database as well as an existing query compiler. (b) Programmers need to provide just a few hundred lines of high-level code for implementing the optimizations, instead of complicated low-level code that is required by existing query compilation approaches. (c) These optimizations may potentially come at the cost of using more system memory for improved performance. (d) The compilation overhead is low compared to the overall execution time, thus making our approach usable in practice for compiling query engines.
Feature-Selected Tree-Based Classification

Feature selection can decrease classifier size and improve accuracy by removing noisy and/or redundant features. However, it is possible for feature selection to yield features that are only partially informative about the classes in the set. These features are beneficial for distinguishing between some classes but not others. In these cases, it is beneficial to divide the large classification problem into a set of smaller problems, where a more specific set of features can be used to classify different classes. Dividing a problem this way is also common when the base classifier is binary, and the problem needs to be reformulated as a set of two-class problems so it can be handled by the classifier. This paper presents a method for multiclass classification that simultaneously formulates a binary tree of simpler classification subproblems and performs feature selection for the individual classifiers. The feature selected hierarchical classifier (FSHC) is tested against several well-known techniques for multiclass division. Tests are run on nine different real data sets and one artificial data set using a support vector machine (SVM) classifier. The results show that the accuracy obtained by the FSHC is comparable with other common multiclass SVM methods. Furthermore, the results demonstrate that the algorithm creates solutions with fewer classifiers, fewer features, and a shorter testing time than the other SVM multiclass extensions.
Research Guides: Soil Science: Professional Networks & Resources

This Guide is designed to support the research needs of Environmental Soil and Water Science students at West Virginia University.
Estimation of global sensitivity indices for models with dependent variables

Article history: Received 15 March 2011 Received in revised form 28 November 2011 Accepted 23 December 2011 Available online 29 December 2011
The Land of Whose Father? the Politics of Indigenous Peoples' Claims

The Land of Whose Father? The Politics of Indigenous Peoples’ Claims by Anne Frances Boxberger Flaherty Department of Political Science Duke University Date:_______________________ Approved: ___________________________ Dr. Margaret McKean, Supervisor ___________________________ Dr. Michael Munger ___________________________ Dr. Paula McClain ___________________________ Dr. Evan Charney An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Political Science in the Graduate School of Duke University 2009 Copyright by Anne Frances Boxberger Flaherty 2009
Lactic acid production from lime-treated wheat straw by Bacillus coagulans: neutralization of acid by fed-batch addition of alkaline substrate

Conventional processes for lignocellulose-to-organic acid conversion requires pretreatment, enzymatic hydrolysis, and microbial fermentation. In this study, lime-treated wheat straw was hydrolyzed and fermented simultaneously to lactic acid by an enzyme preparation and Bacillus coagulans DSM 2314. Decrease in pH because of lactic acid formation was partially adjusted by automatic addition of the alkaline substrate. After 55 h of incubation, the polymeric glucan, xylan, and arabinan present in the lime-treated straw were hydrolyzed for 55%, 75%, and 80%, respectively. Lactic acid (40.7 g/l) indicated a fermentation efficiency of 81% and a chiral l(+)-lactic acid purity of 97.2%. In total, 711 g lactic acid was produced out of 2,706 g lime-treated straw, representing 43% of the overall theoretical maximum yield. Approximately half of the lactic acid produced was neutralized by fed-batch feeding of lime-treated straw, whereas the remaining half was neutralized during the batch phase with a Ca(OH)2 suspension. Of the lime added during the pretreatment of straw, 61% was used for the neutralization of lactic acid. This is the first demonstration of a process having a combined alkaline pretreatment of lignocellulosic biomass and pH control in fermentation resulting in a significant saving of lime consumption and avoiding the necessity to recycle lime.
Full-Capacity Unitary Recurrent Neural Networks

Recurrent neural networks are powerful models for processing sequential data, but they are generally plagued by vanishing and exploding gradient problems. Unitary recurrent neural networks (uRNNs), which use unitary recurrence matrices, have recently been proposed as a means to avoid these issues. However, in previous experiments, the recurrence matrices were restricted to be a product of parameterized unitary matrices, and an open question remains: when does such a parameterization fail to represent all unitary matrices, and how does this restricted representational capacity limit what can be learned? To address this question, we propose full-capacity uRNNs that optimize their recurrence matrix over all unitary matrices, leading to significantly improved performance over uRNNs that use a restricted-capacity recurrence matrix. Our contribution consists of two main components. First, we provide a theoretical argument to determine if a unitary parameterization has restricted capacity. Using this argument, we show that a recently proposed unitary parameterization has restricted capacity for hidden state dimension greater than 7. Second, we show how a complete, fullcapacity unitary recurrence matrix can be optimized over the differentiable manifold of unitary matrices. The resulting multiplicative gradient step is very simple and does not require gradient clipping or learning rate adaptation. We confirm the utility of our claims by empirically evaluating our new full-capacity uRNNs on both synthetic and natural data, achieving superior performance compared to both LSTMs and the original restricted-capacity uRNNs. Advances in Neural Information Processing Systems (NIPS) This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c © Mitsubishi Electric Research Laboratories, Inc., 2016 201 Broadway, Cambridge, Massachusetts 02139