Miracle-dz/UniFAR-FTUs huggingface dataset:
Engineering Problem Solving And Sustained Learning: A Mixed Methods Study To Explore The Dynamics Of Engineering Knowledge Creation

ENGINEERING PROBLEM SOLVING AND SUSTAINED LEARNING: A MIXED METHODS STUDY TO EXPLORE THE DYNAMICS OF ENGINEERING KNOWLEDGE CREATION by RACHEL RIE ITABASHI-CAMPBELL August 2013 Advisor: Dr. Ratna Babu Chinnam Co-Advisor: Dr. Julia Gluesing Major: Industrial Engineering Degree: Doctor of Philosophy This dissertation research explores processes by which engineering problem solving (EPS) results in sustained organizational learning. Approaching from a constructionist perspective, the study empirically examines the knowledge creation dynamics instigated by product-related problems using a mixed methods research approach. The research has identified the Japanese concept of ba, defined in this study as “shared experiential space,” as a key construct that explains the phenomena of interest. A new framework that the study has developed, which interprets EPS as an epistemic journey to attain system-wide improvements, is highly complementary to the traditional structured routine based approaches to engineering operations and management. Operational sustainability is an important issue for every enterprise’s survival, to which engineering contributes by managing product and customer requirements. Effective product management is made possible by seamless feedback of lessons learned, which are generated by problem solving. While the literature offers ample evidence of the relationship
Music Training and Semantic Clustering in College Students

College students with 5 or more years of music training recalled significantly more words from a 16-item word list than did students with 0-4 years of training. The superior recall of the extensively trained students linked to better application of a semantic-clustering strategy across a series of 3 test trials. Music education and language experience may have similar influences on the development of verbal memory.
Application of Monoclonal Antibodies for Endothelin to Hypertensive Research

We developed six kinds of monoclonal antibodies against endothelin (ET)-l recognizing different epitopes with high affinities (5×1010 M−1 to 5×1011 M−1). Using these monoclonal antibodies, we developed radioimmunoassays for ET-1 with different specificities. Crossreactivities with ET-2 ranged from 80% to 100%, and those with ET-3 ranged from 3% to 60%. Patients with essential hypertension (n=20) showed a significant elevation in the plasma ET-l-LI level compared with age-matched control subjects (/i=12) (30.1 ± 1.4 pg/ml versus 18.5 ± 0.9 pg/ml, p<0.01). The plasma ET-l-LI level in hypertensive patients in stages II and III (World Health Organization classification) was significantly higher than that in those patients in stage I. There was no significant correlation between the plasma ET-l-LI level and systolic blood pressure (r=0.11), diastolic blood pressure (r=−0.13), or age (r=0.24) in all patients studied who had essential hypertension. In the neutralization experiment, monoclonal antibodies attenuated ET-1-induced contraction of rat aortic rings and the pressor action of ET-1 in pithed rats in vivo. The present study demonstrates the elevated plasma ET-l-LI level in patients with essential hypertension. Monoclonal antibodies developed in this study can become powerful tools to investigate the pathophysiological significance of ET in essential hypertension.
Understanding the Inputs into Innovation: Do Cities Substitute for Internal Firm Resources?

We examine whether there is a trade-off between employing internal (firm) resources and purchased external (local) resources in process innovation. We draw on a rich dataset of Internet investments by 86,879 US establishments to examine decisions to invest in advanced Internet technology. We show that the marginal contribution of internal resources is greater outside of a major urban area than inside one. Agglomeration is less important for firms with highly capable IT workers. When firms invest in innovative processes they act as if resources available in cities are partial substitutes for both establishment-level and firm-level internal resources.
Cooperative Environment Scans Based on a Multi-Robot System

This paper proposes a cooperative environment scan system (CESS) using multiple robots, where each robot has low-cost range finders and low processing power. To organize and maintain the CESS, a base robot monitors the positions of the child robots, controls them, and builds a map of the unknown environment, while the child robots with low performance range finders provide obstacle information. Even though each child robot provides approximated and limited information of the obstacles, CESS replaces the single LRF, which has a high cost, because much of the information is acquired and accumulated by a number of the child robots. Moreover, the proposed CESS extends the measurement boundaries and detects obstacles hidden behind others. To show the performance of the proposed system and compare this with the numerical models of the commercialized 2D and 3D laser scanners, simulation results are included.
SVMS, SCORE-SPACES AND MAXIMUM MARGIN STATISTICAL MODELS

There has been significant interest in developing new forms of acoustic model, in particular models which allow additional dependencies to be represented than allowed within a standard hidden Markov model (HMM). This paper discusses one such class of models, augmented statistical models. Here a locally exponential approximation is made about some point on a base distribution. This allows additional dependencies within the data to be modelled than are represented in the base distribution. Augmented models based on Gaussian mixture models (GMMs) and HMMs are briefly described. These augmented models are then related to generative kernels, one approach used for allowing support vector machines (SVMs) to be applied to variable length data. The training of augmented statistical models within an SVM, generative kernel, framework is then discussed. This may be viewed as using maximum margin training to estimate statistical models. Augmented Gaussian mixture models are then evaluated using rescoring on a large vocabulary speech recognition task.
Reproducing Material Appearance of Real Objects Using Mobile Augmented Reality

In this paper, we propose a system that can reproduce the material appearance of real objects using mobile augmented reality (AR). Our proposed system allows a user to manipulate a virtual object, whose model is generated from the shape and reflectance of a real object, using the user's own hand. The shape of the real object is reconstructed by integrating depth images of the object, which are captured using an RGB-D camera from different directions. The reflectance of the object is obtained by estimating the parameters of a reflectance model from the reconstructed shape and color images, assuming that a single light source is attached to the camera. We measured the shape and reflectance of some real objects and presented the material appearance of the objects using mobile AR. It was confirmed that users were able to obtain the perception of materials from changes in gloss and burnish of the objects by rotating the objects using their own hand.
PRIMA: passive reduced-order interconnect macromodeling algorithm

This paper describes PRIMA, an algorithm for generating provably passive reduced order N-port models for RLC interconnect circuits. It is demonstrated that, in addition to requiring macromodel stability, macromodel passivity is needed to guarantee the overall circuit stability once the active and passive driver/load models are connected. PRIMA extends the block Arnoldi technique to include guaranteed passivity. Moreover, it is empirically observed that the accuracy is superior to existing block Arnoldi methods. While the same passivity extension is not possible for MPVL, we observed comparable accuracy in the frequency domain for all examples considered. Additionally a path tracing algorithm is used to calculate the reduced order macromodel with the utmost efficiency for generalized RLC interconnects.
RPSL meets lightning: A model-based approach to design space exploration of robot perception systems

The design space of a robotic application defines at a meta level what are all of its possible implementations. Those possibilities are called design alternatives and differ on many different aspects, one being preferred to the other depending on how, where, when or what the application should do. Design Space Exploration (DSE) is the process of reviewing those design alternatives, prior to their implementation, with intention to verify that the set of all design alternatives to be implemented covers all the possible scenarios in which the application is to be executed. In this paper we address two challenges related to DSE, namely, (1) the formal definitions of design spaces, a non-trivial task due to the many dimensions to be taken into consideration, and (2) the automatisation of DSE, that is, enabling a domain expert to review design alternatives corresponding to a given design space effortlessly. In this paper, we address those challenges in the context of robot perception software systems by combining two already existing technologies, namely RPSL for the specification of robot perception system's design spaces and Lightning, a language workbench that we use to formalise RPSL and obtain, from RPSL specifications, corresponding design alternatives.
Extensible kernels are leading OS research astray

Argues that ongoing research in extensible kernels largely fails to address the real challenges facing the operating systems (OS) community. Instead, these efforts have become entangled in trying to solve the safety problems that extensibility itself introduces into OS design. We propose a pragmatic approach to extensibility, where kernel extensions are used in experimental settings to evaluate and develop OS enhancements for demanding applications. Once developed and well understood, these enhancements are then migrated into the base OS for production use. This approach obviates the need for guaranteeing the safety of kernel extensions, allowing the OS research community to re-focus on the real challenges in OS design and implementation. To provide a concrete example of this approach, we analyze the techniques used in experimental HTTP servers to show how proper application design combined with generic enhancements to OSs can provide the same benefits without requiring application-specific kernel extensions.
A Review of Mechanical Adjuncts in Wound Healing: Hydrotherapy, Ultrasound, Negative Pressure Therapy, Hyperbaric Oxygen, and Electrostimulation

Chronic or non-healing wounds may develop in the setting of many diseases and are the source of considerable morbidity as well as health costs. These wounds demand an aggressive, multifactorial approach including surgical debridement, revascularization, antibiotics and dressings. In addition serveral adjuvant treatment methods have been developed to further stimulate healing. Whirlpool, although used frequently, has not been proven to be of benefit. However, pulsed lavage does show a promising future. Ultrasound has demonstrated beneficial effects but further controlled studies are needed. Subatmospheric pressure therapy is associated with few complications and is fast becoming a mainstay of adjuvant therapy. Hyperbaric oxygen therapy has been shown to be effective for many types of wounds. Unfortunately, cost and access to chambers may prohibit its use on a routine basis. Finally, electrostimulation may be one of the up and coming therapies for the future. Though, more studies are needed to determine the mode of delivery for various types of wounds.
A New Canonical Model of Virtual Human Head

In this paper, a new canonical model of virtual human head is presented. By using a uniform two-step refinement operator, the canonical model has a natural multiresolution structure. In the coarsest level, the canonical model is represented by a control mesh M0 which serves as the anatomical structure of the head. To achieve fine geometric details over M0, a multi-level detail set is assigned to the corresponding control vertices in M0, with the aid of a uniquely defined local frame field. Compared to the previously work, the proposed canonical model not only captures the physical characteristics of the head, but also is optimal in the geometric sense. Diverse examples are presented, showing that the deformed model is smooth and the presented canonical model is easy to use.
Quality control in the initiation of eukaryotic DNA replication

Origins of DNA replication must be regulated to ensure that the entire genome is replicated precisely once in each cell cycle. In human cells, this requires that tens of thousands of replication origins are activated exactly once per cell cycle. Failure to do so can lead to cell death or genome rearrangements such as those associated with cancer. Systems ensuring efficient initiation of replication, while also providing a robust block to re-initiation, play a crucial role in genome stability. In this review, I will discuss some of the strategies used by cells to ensure once per cell cycle replication and provide a quantitative framework to evaluate the relative importance and efficiency of individual pathways involved in this regulation.
on Emerging

The evolution of satellite image technology is enabling the manipulation of a greater range of data contained in increasing types of satellite images. Efficient and effective utilization of transmission bandwidth and storage capacity have been a core area of research for remote sensing images. Hence image compression is required for multi-band satellite imagery. In addition, image quality is also an important factor after compression and reconstruction. The wavelet transform is anticipated to provide economical and informative mathematical representation of many objects of interest. In the proposed system, Kekres wavelet transform is used for compression of multispectral satellite image based on compressive sampling
Interferon treatment markedly inhibits the development of tumor metastases in the liver and spleen and increases survival time of mice after intravenous inoculation of friend erythroleukemia cells

To investigate the effect of interferon treatment on the development of tumor metastases, DBA/2 mice were injected i.v. with 2 × 106 Friend erythroleukemia cells (FLC) (equivalent to about 5 × 105 LD50). FLC multiplied rapidly in the liver and spleen and all untreated or control treated mice died between 7 and 12 days. Daily treatment of mice with potent preparations of mouse interferon α/β was initiated 3 to 72 he after i.v. inoculation of tumor cells, at times when FLC were already present in the liver and spleen. Interferon treatment resulted in a 100 to 1,000‐fold inhibition of the multiplication of FLC in the liver and spleen and a marked increase in mean survival time. Small numbers of tumor cells persisted in the liver and spleen in some interferon‐treated mice and could be recovered by bioassay several weeks after tumor inoculation‐Most interferon‐treated mice died with tumor in the ensuing months. Three of 34 Interferon‐treated mice were considered cured as they were alive at 386, 325 and 284 days after tumor inoculation. Daily treatment of tumor‐inoculated mice with human recotnbinant interferons αD and αBDDD, which had antiviral activity on mouse cells in culture, also increased the survival time of mice injected i.v. with FLC. The use of the interferon‐resistant 3C 18 line of FLC suggests that the marked inhibition of development of established liver and spleen metastases was not due to a direct effect of Interferon on the tumor cells, but was host‐mediated.
The Hour of Birth

Whether variations with respect to frequency of births from hour to hour within the course of the day are such as we might expect in any situation in which an immensely complex congeries of cir cumstances conspires to reproduce the characteristic features of a random sampling system, or whether there is a systematic trend indicative of some predominant agency contributory to a manifest diurnal cycle, are questions of interest both at the administrative level, and from the viewpoint of the biologist in quest of a deeper understanding of the mechanism of labour. The issue has provoked not a few descriptive statistical inquiries of which the outcome has been inconclusive up to date. For reasons which follow, this is not surprising.
Luminal Ca2+ controls activation of the cardiac ryanodine receptor by ATP

The synergic effect of luminal Ca2+, cytosolic Ca2+, and cytosolic adenosine triphosphate (ATP) on activation of cardiac ryanodine receptor (RYR2) channels was examined in planar lipid bilayers. The dose–response of RYR2 gating activity to ATP was characterized at a diastolic cytosolic Ca2+ concentration of 100 nM over a range of luminal Ca2+ concentrations and, vice versa, at a diastolic luminal Ca2+ concentration of 1 mM over a range of cytosolic Ca2+ concentrations. Low level of luminal Ca2+ (1 mM) significantly increased the affinity of the RYR2 channel for ATP but without substantial activation of the channel. Higher levels of luminal Ca2+ (8–53 mM) markedly amplified the effects of ATP on the RYR2 activity by selectively increasing the maximal RYR2 activation by ATP, without affecting the affinity of the channel to ATP. Near-diastolic cytosolic Ca2+ levels (<500 nM) greatly amplified the effects of luminal Ca2+. Fractional inhibition by cytosolic Mg2+ was not affected by luminal Ca2+. In models, the effects of luminal and cytosolic Ca2+ could be explained by modulation of the allosteric effect of ATP on the RYR2 channel. Our results suggest that luminal Ca2+ ions potentiate the RYR2 gating activity in the presence of ATP predominantly by binding to a luminal site with an apparent affinity in the millimolar range, over which local luminal Ca2+ likely varies in cardiac myocytes.
Custody: Towards Data-Aware Resource Sharing in Cloud-Based Big Data Processing

With the advent of big data processing frameworks, the performance of data-parallel applications is heavily affected by the time it takes to read input data, making it important to improve data locality. Existing methods in achieving data locality have primarily focused on selecting machines to place tasks of applications. Nevertheless, the set of machines that an application can choose from is determined by a cluster manager, which is oblivious to the location of data in existing resource sharing frameworks. In this paper, we design, implement and evaluate Custody, a new cluster management framework that helps to maximize data locality by allocating the executor processes with local access to data to those applications in need. Custody achieves this objective by dynamically collecting runtime information of an application's input data and by effectively allocating executors among and within applications through theoretic analyses of the data-aware resource sharing problem. With significantly better data locality, Custody avoids unnecessary network transfers and thus expedites job completion times. Our experimental results on a 100-node cluster demonstrate that Custody can improve the data locality for input tasks by 36.9% in comparison with Spark's default cluster manager. Meanwhile, it reduces the job completion times by 14.9% due to fewer network transfers.
Quantitative languages

Quantitative generalizations of classical languages, which assign to each word a real number instead of a Boolean value, have applications in modeling resource-constrained computation. We use weighted automata (finite automata with transition weights) to define several natural classes of quantitative languages over finite and infinite words; in particular, the real value of an infinite run is computed as the maximum, limsup, liminf, limit average, or discounted sum of the transition weights. We define the classical decision problems of automata theory (emptiness, universality, language inclusion, and language equivalence) in the quantitative setting and study their computational complexity. As the decidability of the language-inclusion problem remains open for some classes of weighted automata, we introduce a notion of quantitative simulation that is decidable and implies language inclusion. We also give a complete characterization of the expressive power of the various classes of weighted automata. In particular, we show that most classes of weighted automata cannot be determinized.
On a classification of finite statistical tests

Statistical tests of random sequences are often used in cryptography in order to perform some routine checks for random and pseudo-random number generators. Most of the test suites available are based on the theory of hypothesis testing which allows one to decide whether a sample has been drawn following a certain distribution. In this article, we develop a theoretical foundation of statistical tests of random sequences and hypothesis testing with a focus on cryptographic applications and we draw some interesting practical consequences.
A Robot-Based Platform to Measure Multiple Enzyme Activities in Arabidopsis Using a Set of Cycling Assays: Comparison of Changes of Enzyme Activities and Transcript Levels during Diurnal Cycles and in Prolonged Darknessw⃞

A platform has been developed to measure the activity of 23 enzymes that are involved in central carbon and nitrogen metabolism in Arabidopsis thaliana. Activities are assayed in optimized stopped assays and the product then determined using a suite of enzyme cycling assays. The platform requires inexpensive equipment, is organized in a modular manner to optimize logistics, calculates results automatically, combines high sensitivity with throughput, can be robotized, and has a throughput of three to four activities in 100 samples per person/day. Several of the assays, including those for sucrose phosphate synthase, ADP glucose pyrophosphorylase (AGPase), ferredoxin-dependent glutamate synthase, glycerokinase, and shikimate dehydrogenase, provide large advantages over previous approaches. This platform was used to analyze the diurnal changes of enzyme activities in wild-type Columbia-0 (Col-0) and the starchless plastid phosphoglucomutase (pgm) mutant, and in Col-0 during a prolongation of the night. The changes of enzyme activities were compared with the changes of transcript levels determined with the Affymetrix ATH1 array. Changes of transcript levels typically led to strongly damped changes of enzyme activity. There was no relation between the amplitudes of the diurnal changes of transcript and enzyme activity. The largest diurnal changes in activity were found for AGPase and nitrate reductase. Examination of the data and comparison with the literature indicated that these are mainly because of posttranslational regulation. The changes of enzyme activity are also strongly delayed, with the delay varying from enzyme to enzyme. It is proposed that enzyme activities provide a quasi-stable integration of regulation at several levels and provide useful data for the characterization and diagnosis of different physiological states. As an illustration, a decision tree constructed using data from Col-0 during diurnal changes and a prolonged dark treatment was used to show that, irrespective of the time of harvest during the diurnal cycle, the pgm mutant resembles a wild-type plant that has been exposed to a 3 d prolongation of the night.