Miracle-dz/UniFAR-FTUs huggingface dataset:
Break on through ( to the other side ) : market innovations by environmental innovative firms

The identification and development of existing or new markets for environmental friendly products are essential if we are to move towards a more sustainable consumption pattern. Most research on environmental innovation has focused on the technological aspects of innovation, thereby ignoring how environmental innovative firms can enter and develop existing and/or new markets. This study draws together the literature on environmental innovation, the resource based view of the firm and signalling theory to uncover linkages between environmental innovative firms? resource profile and their ability to introduce successful market innovations. With regard to 812 environmental innovative firms, a Heckman two stage regression analysis detected that those environmental innovative firms that engaged in R&D and marketing activities or cooperated with costumers were more likely to report market innovations that improved their access to existing or new markets. However, those environmental innovative firms that cooperated with academic research institutions were found to be less likely to report market innovations that improved their access to existing and/or new markets Implications and limitations are discussed.
Chapter 1 Elements of Information Theory for Networked Control Systems

Next generation cyber-physical systems [35] will integrate computing, communication, and control technologies, to respond to the increased societal need to build large-scale systems using digital technology and interacting with the physical world. These include energy systems where the generation, transmission, and distribution of energy is made more efficient through the integration of information technologies; transportation systems that integrate intelligent vehicles and intelligent infrastructures; and health care systems where medical devices have high degree of intelligence and interoperability, integrating wireless networking and sensing capabilities. One of the fundamental characteristics of cyber-physical systems is that communication among computing and physical entities occurs over communication channels of limited bandwidth and is subject to interference and noise. This challenges the standard assumption of classical control theory that communication can be performed instantaneously, reliably, and with infinite precision, and leads to the development of a new theory of networked control systems (NCS) [7, 8, 24, 30]. This chapter complements the surveys [2, 50] that focus on the communication constraints imposed by the network on the ability to estimate and control dynamical systems. We describe in a tutorial style the main ideas and techniques that contributed shaping the field, with particular attention to the connections with Shannon’s information theory. A compendium of additional related results can be found in the recent monograph [44], relating results to Kolmogorov’s approach to information theory via the concept of topological entropy [1].
Pre-isolation, isolation and regeneration protoplasts from leaf mesophyll of in vivo Malus domestica ‘Anna’ cv.

Abstract To isolate protoplast, a pre-treatment was completed with the order to reduce and identify the phenolic contents round the year to encourage the isolation of protoplasts. Protoplasts from in vivo mesophyll leaves of apple cultivar “Anna” was isolated from 15 days old leaves by plasmolying in medium containing 90 g L-1 mannitol for half hour, then 130 g L-1 mannitol for half hour. Then using enzymatic mixture involving (1.5% cellulase + 0.5% pectianase + 1.5% Macrozyme) Prior to isolation. Anyhow, diverse factors, for example, Osmotic pressure, incubation period, sieve pore size, centrifugation period and hormonal balance was estimated using the techniques for isolation. The quantity of cells was computed as the quantity of cells per square on haemocytometer. A considerable higher yield of protoplast formation was noted in the CPW medium using a pore size of 25 µm with using incubation period for 20 hours. Moreover, the best protoplast regeneration with using of protoplast density of 2.0 x 105 in MS medium supplemented by 1.0 mg L-1NAA and 0.3 mg L-1BAP. We believed that our protocol might encourage the plant recovery using in apple somatic hybridization programs.
Bachelor of Science in Medicine Degree Program End of Term Final Report

Sponsorship if different than above: CancerCare MB and the June Helen Coulter Memorial Scholarship SCLC is the most aggressive subtype of lung cancer and accounts for 13% of lung cancer diagnoses. Median survival, even with treatment, is under 10 months and 5-year survival is <5%. Most patients are treated with chemotherapy and radiation. The limited role of surgery means few biological specimens are available for research.
DERLEME / REWIEW AN OVERVIEW OF GENETIC ALGORITHMS

In this paper, general knowledge about Genetic Algorithms (GAs), which have received much attention the past few years because of the fact that they have been successfully applied in several different fields of study, is given. The basic principles of GAs, such as representation, selection and genetic operators are summarized and the fundamental theorem of GAs, the so-called schema theorem, is discussed. A simple example is given in order to explain how they work. Finally, a literature survey for the applications of GAs to Operational Research (OR) problems is also provided.
NUMERICAL MODELLING OF THE DYNAMICS OF ISOLATED RED BLOOD CELLS FLOWING IN A CYTOMETER

Research in numerical simulations of red blood cells (RBCs) under flow has been a very active field for the last decade. Numerous studies have focused on in vivo micro-circulation, but additional questions are raised in non-physiological flows. In biomedical devices, for instance, flows of RBCs interact with complex manufactured geometries. Moreover, high Reynolds number flows can be encountered, where inertial effects are non negligible even at the cellular scale. This is notably the case in industrial cytometers. The goal of this study is to investigate the dynamics of RBCs within a Horiba cytometer.
ongenital dislocation of the knee at birth – Part I : Clinical signs and lassification

Introduction: Congenital dislocation of the knee (CDK) is rare, and clinical semiology at birth is not always suitably analyzed. Existing classifications fail to guide treatment. The aim of the present study was to develop a CDK classification for the neonatal period. Hypothesis: A classification based on neonatal severity of clinical signs is easy to implement on simple criteria. Material and methods: Fifty-one CDKs (40 patients) seen neonatally were included. Three types could be distinguished in terms of reduction and stability: type I, easily reducible CDK, with reduction snap when the femoral condyles pass in flexion, remaining stable in flexion; type II, “recalcitrant” dislocation, reducible by posteroanterior “piston” but unstable, with iterative dislocation once posteroanterior pressure on the condyles is relaxed; and type III, irreducible. The number of anterior skin grooves, global range of motion, flexion deficit and reduction stability were noted for each type. Results: Mean age at first consultation was 5.6 days (range: 0–30). CDK was type I, II and III in respectively 28, 16 and 7 cases. Number of skin grooves, flexion and baseline range of motion were greater in type I than types II and III. Conclusion: The present neonatal clinical classification is original, logical and simple. It may be useful for prognosis and guiding treatment. Level of evidence: IV, single-center retrospective series. © 2016 Elsevier Masson SAS. All rights reserved.
Financial Reporting and Disclosure Practices in China *

We provide survey-based evidence on financial reporting and disclosure practices in China. We use the survey items used in prior studies based on U.S. CFOs (Graham et al., 2005; Dichev et al., 2013) as a benchmark to compare our results. We find some similarities between the U.S. and Chinese firms, but highlight some major differences in the perceptions on financial reporting and disclosure at Chinese firms. For example, Chinese firms do not consider analyst consensus forecasts as important earnings benchmarks, do not believe that voluntary disclosures reduce the cost of capital, and do not exhibit incentives to disclose bad news faster than good news. We provide additional evidence from follow-up questionnaires and on-site interviews that corroborate our main findings and explore the potential explanations. Taken together, our findings suggest that institutional differences at the country-level impose challenges on international studies that rely on theoretically-motivated empirical proxies or research questions from the U.S. setting.
Analysis of Emotion : An approach from Artificial Intelligence perspective

Modeling emotions can contribute to understand human emotions, to add emotional capacities to machines, and to improve appraisals on emotional state. In this work, five models, using fuzzy logic, artificial neural networks, and a hybrid of both, are presented, developed and evaluated, with the aim to infer the emotional state of children from external physiological measurements. Measurements took from a picture and compared to the canon’s proportion fed the models as inputs, finding that fuzzy logic is a good tool to work with the blurry nature of emotions.
Learning Non-Parametric Models with Guarantees: A Smooth Lipschitz Interpolation Approach

We propose a non-parametric regression method that does not rely on the structure of the ground-truth, but only on its regularity properties. The methodology can be readily used for learning surrogate models of nonlinear dynamical systems from data, while providing bounds on the prediction error. In contrast with the well known Set Membership and Kinky Inference techniques that yield non-differentiable functions, the approach presented herein produces a smooth regressor. Consequently, it is more suitable to optimizationbased controllers that heavily rely on gradient computations. A numerical example is provided to show the effectiveness of the method we call Smooth Lipschitz Interpolation (SLI) when compared to the aforementioned alternatives in a Model Predictive Control problem.
Determining the accuracy of a Markov Chain Monte Carlo output

This is a lively thesis providing different methods for analyzing Markov Chain Monte Carlo output. Written as a series of short chapters and by including a lot of background, students with no prior knowledge in Markov Chain Monte Carlo will be able to read this thesis as well. In the first part, more general statistical definitions and methods such as regression, Bayesian estimation, time series and Monte Carlo simulation are discussed. After a short chapter which includes more information about the use of simulation as a solution for statistical problems, more detailed derivations and proofs are provided for methods which estimate or describe asymptotic variance. The methods for estimating asymptotic variance which are included are: estimation by window estimators, the batch means method and the blocked means method. Furthermore by using historical data, the methods are brought to life in order to get some more feeling about the subjects.
Adaptive Item Calibration : A Process for Estimating Item Parameters Within a Computerized Adaptive Test

The characteristics of an adaptive test change the characteristics of the field testing that is necessary to add items to an existing measurement scale. The process used to add field-test items to the adaptive test might lead to scale drift or disrupt the test by administering items of inappropriate difficulty. The current study makes use of the transitivity of examinee and item in item response theory to describe a process for adaptive item calibration. In this process an item is successively administered to examinees whose ability levels match the performance of a given field-test item. By treating the item as if it were taking an adaptive test, examinees can be selected who provide the most information about the item at its momentary difficulty level. This should provide a more efficient procedure for estimating item parameters. The process is described within the context of the one-parameter logistic IRT model. The process is then simulated to identify whether it can be more accurate and efficient than random presentation of field-test items to examinees. Results indicated that adaptive item calibration might provide a viable approach to item calibration within the context of an adaptive test. It might be most useful for expanding item pools in settings with small sample sizes or needs for large numbers of items.
18 Cellular Immunotherapy for Malignant Brain Tumors

Glioblastoma multiforme (GBM) is the most common and most aggressive adult brain tumor with a patient median survival of 15 months from the time of diagnosis, and less than 20 weeks for patients with recurrent tumors. Current standard of care consists of multimodality therapy including image-guided tumor resection, fractionated radiotherapy, and chemotherapy. This aggressive therapy is non-specific and highly toxic, leaving collateral damage to surrounding normal brain and systemic tissue, and is often debilitating to patients. Thus, there is a dire need for a more effective therapy that more specifically targets tumor cells while minimizing damage to surrounding eloquent cerebral cortex. Immunotherapy is based on the premise that the inherent sensitivity and specificity of immunologic reactivity could deliver tumor cell-specific therapy. Cellular immunotherapy aims to utilize the patient’s own immune cells that are harvested, expanded ex vivo, primed against tumor antigens, and returned to the host, in order to direct an anti-tumor immune response with specificity and efficiency. During early efforts in immunotherapy, tumor specific antigens were unknown and it was unclear whether tumor antigens could be recognized and targeted by the immune system. The identification of tumor antigens began with those expressed in malignant melanoma, and soon there was an explosion in the development of antigen specific immunologic treatments against solid tumors. In the past several years, pre-clinical models of cancer have reliably demonstrated that the immune system is capable of targeting tumor antigens and eradicating malignancies. It has also been demonstrated clinically that the human immune system is capable of recognizing antigens within malignant tumor cells with precision, and current immunotherapy research aims to induce potent antitumor immune responses to prolong patient survival. It was initially unclear if a potent immune response was inducible against brain tumors because of the immunoprivileged nature of the nervous system, but studies have demonstrated that immune effector cells can infiltrate the central nervous system (CNS) and induce efficient immune responses against intracranial tumors. Current research in cellular immunotherapy against cancer is directed at eliciting a specific immune response against tumor antigens using active immunization with cellular vaccines or adoptive transfer of ex vivo activated lymphocytes. Clinical studies testing the safety and efficacy of cellular vaccines in patients with grade III or grade IV gliomas include the
AM Sourcing and Screening High-Tech Workers

Using a unique database reflecting the details of technical job interviews, we study how high-tech employers source and evaluate candidates in tight labor markets. We show that for jobs involving new technologies, employers rely more heavily on recruiters and referrals to access a pool of employed workers who may have already acquired these skills on-the-job at competitor firms. Second, by text-mining interview questions, we show that employers trying to fill such positions are more likely to ask interview questions that indicate how quickly prospective IT hires can learn on the job, rather than asking about prior experience. Employers ask such questions 39% more frequently for these jobs than for jobs involving mature technologies. These effects are robust to including employer, job title, and labor market fixed effects. Our findings are consistent with the argument that employers design technical HR strategies to complement their technology choices.
Modeling performance differences on cognitive tests using LSTMs and skip-thought vectors trained on reported media consumption.

Cognitive tests have traditionally resorted to standardizing testing materials in the name of equality and because of the onerous nature of creating test items. This approach ignores participants’ diverse language experiences that potentially significantly affect testing outcomes. Here, we seek to explain our prior finding of significant performance differences on two cognitive tests (reading span and SPiN) between clusters of participants based on their media consumption. Here, we model the language contained in these media sources using an LSTM trained on corpora of each cluster’s media sources to predict target words. We also model semantic similarity of test items with each cluster’s corpus using skip-thought vectors. We find robust, significant correlations between performance on the SPiN test and the LSTMs and skip-thought models we present here, but not the reading span test.
Evaluation of an Industrial Robotic Assistant in an Ecological Environment

Social robotic assistants have been widely studied and deployed as telepresence tools or caregivers. Evaluating their design and impact on the people interacting with them is of prime importance. In this research, we evaluate the usability and impact of ARMAR-6, an industrial robotic assistant for maintenance tasks. For this evaluation, we have used a modified System Usability Scale (SUS) to assess the general usability of the robotic system and the Godspeed questionnaire series for the subjective perception of the coworker. We have also recorded the subjects’ gaze fixation patterns and analyzed how they differ when working with the robot compared to a human partner.
Enriching input in Statistical Machine Translation

Statistical Machine Translation has problems dealing with morphologically rich languages; translating from English into these gives a significantly worse quality. We make an effort to address this problem by adding per-word linguistic information into the source language of the translation task. We use the syntax of the source sentence so as to extract information for noun cases, verb persons and attribute genders and annotate these words accordingly. The solution is tested on factored phrase-based models, giving indications that the methods proposed are useful. Manual error analysis shows that the translation of the words annotated (nouns and verbs) improves, but a problem of sparse data is caused. Experiments managed to get a small improvement on NIST metric while human evaluation showed that a model combining both noun cases and verb persons has increased the adequacy (meaning) and deteriorated the fluency of the generated translation.
Knowledge sharing and innovation capabilities: The moderating role of organizational learning

The main purpose of this research is to analyze those factors that affect the knowledge sharing and can lead the conventional banking sector towards enhancing the innovation capabilities by creating the culture of organizational learning. The model of this research paper is tested using a sample of 300 employees occupying the position of officer grade I, II and III in conventional banking sector of Bahawalpur. Researchers have used the simple random sampling technique for the collection of data with the help of questionnaire. SPSS version 21 is used to analyze data collected for this research paper. The result shows that out of nine factors, seven factors namely individual personality, individual attitude, reward and recognition, competence based trust, benevolence based trust, ICT infrastructure and availability and ICT know how are all significantly and positively related with the innovation capabilities as well as knowledge sharing and thus knowledge sharing also mediates between them. But the two factors centralization and formalization have an insignificant relationship with the innovation capabilities and knowledge sharing. Hence, no mediation takes place between them. Moderator; organizational learning also plays a significant role between knowledge sharing and innovation capabilities. This research paper has a significant managerial implication that it helps the managing bodies of conventional banks to pay an attention on these factors like individual personality, individual attitude, reward and recognition, competence based trust, benevolence based trust, ICT infrastructure and availability and ICT know how in order to enhance the innovation capabilities. The incorporation of individual personality, individual attitude, reward and recognition, competence based trust, benevolence based trust, ICT infrastructure and availability and ICT know how in order to enhance the Knowledge Sharing and Innovation Capabilities 456 innovation capabilities. Model offers a new theoretical lens and an alternative explanation for the determinants influencing the knowledge sharing that leads to innovation capabilities.
Subsistence Consumption , Investment , and Poverty

This paper develops an endogenous growth model in which the extent and depth of poverty influence the aggregate outcomes of the economy. Individuals are bound by a subsistence consumption requirement and their risk aversion depends negatively on their distance from the constraint. Agents divide their time between farming and working for a wage. Farm productivity can be improved stochastically through household investment. The impact that subsistence consumption has on household investment and economic growth is decomposed into constraints on disposable income and increased risk aversion. Constraints on disposable income determine the household’s innovation decision when they are extremely poor. However, as incomes rise to levels similar to that of India in the 1980s increased risk aversions starts to dominate household choices. Quantitative work suggests that the subsistence constraint can reduce the annualized growth rate by as much as 65 basis points. Consistent with recent empirical studies, conditional cash transfers outperform unconditional cash transfers in terms of growth outcomes, due to their creation of incentives to invest in higher risk activities. JEL Codes: O11, O14, O21, O33, O41
LES SOFTWARE FOR THE DESIGN OF LOW EMISSION COMBUSTION SYSTEMS FOR VISION 21 PLANTS

Application and testing of the new combustion Large Eddy Simulation (LES) code for the design of advanced gaseous combustion systems is described in this 12th quarterly report. In this quarter, continued validation and testing of the combustion LES code was performed for the DOE-SimVal combustor. Also, beta testing by six consortium members was performed for various burner and combustor configurations. A list of suggested code improvements by the beta testers was itemized. Work will continue in FY04. A conditional modification to the contract will be granted. The additional work will focus on modeling/analyzing the SimVal experiments.
Pliocene and Eocene provide best analogs for near-future climates

Nelson Institute for Environmental Studies, University of Wisconsin–Madison, Madison, WI 53706; Department of Geography and Center for Climatic Research, University of Wisconsin–Madison, Madison, WI 53706; Center for Climate Systems Research, Columbia University, New York, NY 10025; Goddard Institute for Space Studies, National Aeronautics and Space Administration (NASA), New York, NY 10025; School of Earth and Environment, University of Leeds, LS2 9JT Leeds, United Kingdom; School of Geographical Sciences, University of Bristol, BS8 1SS Bristol, United Kingdom; and Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO 80305