gebhart/patrepeval huggingface dataset:
An optimized self-powered switching circuit for non-linear energy harvesting with low voltage output (2008)

Harvesting energy from environmental sources has been of particular interest these last few years. Microgenerators that can power electronic systems are a solution for the conception of autonomous, wireless devices. They allow the removal of bulky and costly wiring, as well as complex maintenance and environmental issues for battery-powered systems. In particular, using piezoelectric generators for converting vibrational energy to electrical energy is an intensively investigated field. In this domain, it has been shown that the harvested energy can be greatly improved by the use of an original non-linear treatment of the piezoelectric voltage called SSHI (Synchronized Switch Harvesting on Inductor), which consists in intermittently switching the piezoelectric element on a resonant electrical network for a very short time. However, the integration of miniaturized microgenerators with low voltage output (e.g. MEMS microgenerators) has not been widely studied. In the case of low voltage output, the losses introduced by voltage gaps of discrete components such as diodes or transistors can no longer be neglected. Therefore the purpose of this paper is to propose a model that takes into account such losses as well as a new architecture for the SSHI energy harvesting circuit that limits such losses in the harvesting process. While most of the study uses an externally powered microcontroller for the non-linear treatment, this circuit is fully self-powered, thus providing an enhanced autonomous microgenerator. In particular this circuit aims at limiting the effect of non-linear components with a voltage gap such as diodes. It is shown both theoretically and experimentally that the harvested power can be significantly increased using such a circuit. In particular, experimental measurements performed on a cantilever beam show that the circuit allows a 160% increase of the harvested power compared to a standard energy harvesting circuit, while the classical implementation of the SSHI shows an increase of only 100% of the output power in the classical case.
Symbolic pointer analysis (2003)

One of the bottlenecks in the recent movement of hardware synthesis from behavioral C programs is the difficulty in reasoning about runtime pointer values at compile time. The pointer analysis problem has been investigated in the compiler community for two decades, which has yielded efficient, polynomial time algorithms for context-insensitive analysis. However, at the accuracy level for which hardware synthesis is desired, namely context and flow sensitive analysis, the time and space complexity of the best algorithms reported grow exponentially with program size. In this paper, we present our first step towards a new analysis technology which potentially leads to almost-linear time complexity and sub-linear space complexity algorithm even for the most accurate analysis. The key idea that contributes to this efficiency is to implicitly encode the pointer-to relation in the Boolean domain, thereby capturing the procedure transfer function completely, compactly and canonically. This represents a wide departure from the traditional techniques, all of which explicitly capture pointer-to relation using variations of point-to graph, which have to be re-evaluated for different calling contexts. Experiments for our first flow-insensitive algorithm on common benchmarks show promising results.
New Strategies in Ovarian Cancer: Translating the Molecular Complexity of Ovarian Cancer into Treatment Advances (2014)

An improved understanding of the genomics of ovarian cancer and the separation of ovarian cancer into histologically and molecularly defined subgroups have affected drug development and clinical trial design in ovarian cancer. Active therapies that have been tested in ovarian cancer include agents that inhibit angiogenesis and poly (ADP-ribose) polymerase inhibitors (PARPi). However, no FDA drug approvals for ovarian cancer have been granted since 2006, and overall survival improvements have been difficult to achieve with new agents. The genomic complexity of ovarian cancer and modest single-agent activity of many biologic agents in this disease have led to testing of biologic agent combinations. In this article, we review recent advances in the understanding of the molecular diversity of ovarian cancer as well as emerging therapeutic strategies such as new agents and biologic combinations that attempt to target multiple aberrant pathways in this cancer.
Nano-networks communication architecture: Modeling and functions (2018)

Nano-network is a communication network at the Nano-scale between Nano-devices. Nano-devices face certain challenges in functionalities, because of limitations in their processing capabilities and power management. Hence, these devices are expected to perform simple tasks, which require different and novel approaches. In order to exploit different functionalities of Nano-machines, we need to manage and control a set of Nano-devices in a full Nano-network using an appropriate architecture. This step will enable unrivaled applications in the biomedical, environmental and industrial fields. By the arrival of Internet of Things (IoT) the use of the Internet has transformed, where various types of objects, sensors and devices can interact making our future networks connect nearly everything from traditional network devices to people. In this paper, we provide an unified architectural model of Nano-network communication with a layered approach combining Software Defined Network (SDN), Network Function Virtualization (NFV) and IoT technologies and present how this combination can help in Nano-networks’ context. Consequently, we propose a set of functions and use cases that can be implemented by Nano-devices and discuss the significant challenges in implementing these functions with Nano-technology paradigm and the open research issues that need to be addressed.
Analog Vlsi: Signal and Information Processing (1994)

CMOS analogue building blocks BiCMOS analogue building blocks sampled-data signal processing continuous-time signal processing current-mode signal processing analogue VLSI neural information processing data converters statistical modelling and simulation of analogue analogue CAD interconnects in analogue VLSI analogue VLSI design-for-test analogue integrated sensors.
An overview on the correlation of neurological disorders with cardiovascular disease (2014)

Neurological disorders (NDs) are one of the leading causes of death especially in the developed countries. Among those NDs, Alzheimer's disease (AD) and Parkinson disease (PD) are heading the table. There have been several reports in the scientific literatures which suggest the linkage between cardiovascular disorders (CVDs) and NDs. In the present communication, we have tried to compile NDs (AD and PD) association with CVDs reported in the literature. Based on the available scientific literature, we believe that further comprehensive study needs to be done to elucidate the molecular linking points associated with the above mentioned disorders.
Simplified nonlinear equalizers (1995)

Nonlinear equalization was previously shown to be beneficial for recording channels with nonlinearities and signal-dependent noise. In this work, we study two types of simplified nonlinear filter architectures that are suitable for VLSI implementation. The performance loss due to the simplifications are not significant in most cases, compared to the signal-to-noise ratio gain achieved by nonlinear equalization. In one form of simplification the need for full multiplications is eliminated and in the other the number of multiplications in the original nonlinear filter architecture is reduced significantly. Work on experimental and simulated data are presented.
Automatic detection of new words in a large vocabulary continuous speech recognition system (1989)

In practical large vocabulary speech recognition systems, it is nearly impossible for a speaker to remember which words are in the vocabulary. The probability of the speaker using words outside the vocabulary can be quite high. For the case when a speaker uses a new word, current systems will always' recognize other words within the vocabulary in place of the new word, and the speaker wouldn't know what the problem is.In this paper, we describe a preliminary investigation of techniques that automatically detect when the speaker has used a word that is not in the vocabulary. We developed a technique that uses a general model for the acoustics of any word to recognize the existence of new words. Using this general word model, we measure the correct detection of new words versus the false alarm rate.Experiments were run using the DARPA 1000-word Resource Management Database for continuous speech recognition. The recognition system used is the BBN BYBLOS continuous speech recognition system (Chow et al., 1987). The preliminary results indicate a detection rate of 74% with a false alarm rate of 3.4%.
Mental toughness among district, state and national level kabaddi players (2018)

The purpose of this study was to compare Mental Toughness among District Level, State Level and National Level Kabaddi Players. For the purpose of this study Sixty (N=60), Male subjects between the age group of 18-28 years (Mean ± SD: Age 22.01±2.31 (yrs), Body Height 168.85±4.74 (cm), Body Mass 65.8±3.53 (kg)) volunteered to participate in the study. The investigator has used the questionnaire for measuring all the dimensions of mental toughness of the subjects and their overall mental toughness. The Statistical Package for the Social Sciences (SPSS) was used for all analyses. To conclude, it is significant to mention in relation to Ability to Handle Pressure, Concentration, Motivation and Mental Toughness that results of Analysis of Variance (ANOVA) among Kabaddi Players (i.e. District Level, State Level and National Level) were found statistically insignificant (P>.05). Furthermore, in relation to Reboundability and Confidence that result of Analysis of Variance (ANOVA) among Kabaddi Players (i.e. District Level, State Level and National Level) were found statistically significant (P
Image processing tools for the enhancement of concealed weapon detection (2003)

A number of technologies are being developed for Concealed Weapon Detection (CWD). Use of appropriate processing techniques will be very important to the success of such technologies. This article describes digital image processing procedures currently being investigated to enhance the detection of weapons concealed underneath clothing.
Method to enable variable speed wind turbine primary regulation (2009)

This article proposes a method to enable variable speed wind turbine primary regulation. The method consists of adjusting the power-speed curve of the turbine to the grid frequency, thus varying the percentage of maximum power available injected to the grid. This is achieved by operating at rotational speed different from the optimal, and not controlling the pitch angle. Two practical implementations of the method are proposed and demonstrated by simulation exercises.
Who “defects”? (1968)

Share Icon Share Twitter Facebook Reddit LinkedIn Reprints and Permissions Cite Icon Cite Search Site Citation E. U. Condon; Who “defects”?. Physics Today 1 March 1968; 21 (3): 19. https://doi.org/10.1063/1.3034814 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentPhysics Today Search Advanced Search
Applications of high throughput (combinatorial) methodologies to electronic, magnetic, optical, and energy-related materials (2013)

High throughput (combinatorial) materials science methodology is a relatively new research paradigm that offers the promise of rapid and efficient materials screening, optimization, and discovery. The paradigm started in the pharmaceutical industry but was rapidly adopted to accelerate materials research in a wide variety of areas. High throughput experiments are characterized by synthesis of a “library” sample that contains the materials variation of interest (typically composition), and rapid and localized measurement schemes that result in massive data sets. Because the data are collected at the same time on the same “library” sample, they can be highly uniform with respect to fixed processing parameters. This article critically reviews the literature pertaining to applications of combinatorial materials science for electronic, magnetic, optical, and energy-related materials. It is expected that high throughput methodologies will facilitate commercialization of novel materials for these critically important applications. Despite the overwhelming evidence presented in this paper that high throughput studies can effectively inform commercial practice, in our perception, it remains an underutilized research and development tool. Part of this perception may be due to the inaccessibility of proprietary industrial research and development practices, but clearly the initial cost and availability of high throughput laboratory equipment plays a role. Combinatorial materials science has traditionally been focused on materials discovery, screening, and optimization to combat the extremely high cost and long development times for new materials and their introduction into commerce. Going forward, combinatorial materials science will also be driven by other needs such as materials substitution and experimental verification of materials properties predicted by modeling and simulation, which have recently received much attention with the advent of the Materials Genome Initiative. Thus, the challenge for combinatorial methodology will be the effective coupling of synthesis, characterization and theory, and the ability to rapidly manage large amounts of data in a variety of formats.
Genetic and biochemical evidence for a siderophore-dependent iron transport system in Corynebacterium diphtheriae (1984)

During growth under conditions of iron deprivation, Corynebacterium diphtheriae secreted a siderophore into the culture medium. This extracellular siderophore was necessary for rates of iron uptake at pH 8.0 by C. diphtheriae C7 and related strains. We isolated a mutant of C. diphtheriae C7(beta), strain HC6, which did not make the corynebacterial siderophore. Strain HC6 grew very poorly, even under high-iron conditions, and had a severe defect in iron transport. Both growth and iron uptake by strain HC6 were greatly stimulated by the corynebacterial siderophore. We used strain HC6 to develop a bioassay for the corynebacterial siderophore and to look for other potential siderophores for C. diphtheriae. Among the purified phenolate and hydroxamate siderophores tested, only aerobactin was able to stimulate the growth of strain HC6. Partial purification of the corynebacterial siderophore was achieved. The siderophore did not give positive reactions in the Arnow test for phenolates or the Csaky test for hydroxamates and may have a novel chemical structure.
A method to estimate weight and dimensions of large and small gas turbine engines (1979)

A computerized method was developed to estimate weight and envelope dimensions of large and small gas turbine engines within + or - 5% to 10%. The method is based on correlations of component weight and design features of 29 data base engines. Rotating components were estimated by a preliminary design procedure which is sensitive to blade geometry, operating conditions, material properties, shaft speed, hub tip ratio, etc. The development and justification of the method selected, and the various methods of analysis are discussed.
Geometric differential evolution (2009)

Geometric Particle Swarm Optimization (GPSO) is a recently introduced formal generalization of traditional Particle Swarm Optimization (PSO) that applies naturally to both continuous and combinatorial spaces. Differential Evolution (DE) is similar to PSO but it uses different equations governing the motion of the particles. This paper generalizes the DE algorithm to combinatorial search spaces extending its geometric interpretation to these spaces, analogously as what was done for the traditional PSO algorithm. Using this formal algorithm, Geometric Differential Evolution (GDE), we formally derive the specific GDE for the Hamming space associated with binary strings and present experimental results on a standard benchmark of problems.
Hydrolysis of suxamethonium by different types of plasma (1969)

1. A method, based on the use of the isolated frog rectus abdominis preparation, is described for studying quantitatively the hydrolysis of suxamethonium at low concentrations.2. Rates of hydrolysis of butyrylcholine, 10 mM, benzoylcholine, 0.05 mM, and suxamethonium, 0.025 mM, by plasma from different species and human plasma with genetic variants of cholinesterase were measured.3. The rates of hydrolysis of suxamethonium by different types of plasma vary widely. Human plasma with usual cholinesterase and monkey plasma hydrolyse suxamethonium more speedily than do the plasma of cats, dogs and rats, and human plasma with either atypical or fluoride resistant cholinesterase. This is only to a small extent attributable to differences in enzyme concentration and not explained by the presence of an inhibitor.4. The K(m) values for butyrylcholine are very similar for different types of plasma but the K(I) values for suxamethonium in the system plasma-butyrylcholine-suxamethonium vary greatly.5. These results and observations on the inhibition by decamethonium of the hydrolysis of butyrylcholine are consistent with the interpretation that the rates of hydrolysis of suxamethonium, 0.025 mM, obtained with different types of plasma vary because they are a function of two variables, the affinity of the ester for cholinesterase and the stability of the monosuccinyl derivative of the cholinesterase. It seems that human plasma with atypical cholinesterase hydrolyses suxamethonium much slower than does human plasma with usual cholinesterase mainly or solely because of differences in affinity of the ester for the two enzymes. On the other hand, cat plasma appears to hydrolyse suxamethonium much slower than does human plasma with usual cholinesterase mainly because the monosuccinyl derivative of cholinesterase in cat plasma is much more stable than that in human plasma. The reverse might apply for monkey plasma.6. Inhibition by dibucaine or sodium fluoride of the hydrolysis of benzoylcholine is not a general guide to rates of hydrolysis of suxamethonium by different types of plasma.
Experimental hookworm infection: a randomized placebo‐controlled trial in asthma (2010)

Experimental infection with ten hookworm larvae in asthma did not result in significant improvement in bronchial responsiveness or other measures of asthma control in this study. However, infection was well tolerated and resulted in a non-significant improvement in airway responsiveness, indicating that further studies that mimic more closely natural infection are feasible and should be undertaken.
Blackstone as Architect: Constructing the Commentaries (2003)

On January 28, 1746, as Cumberland's forces pursued the retreating Jacobite army into Scotland, a twenty-three year old newly-minted Bachelor of Civil Law and junior fellow of All Souls College sat down to write a characteristically cheerful letter to his lawyer uncle Seymour Richmond, shortly after reaching "my new Habitation (which is at Mr Stoke's a Limner in Arundel St)." In the light of what is becoming clear about William Blackstone's own accomplishments and interests in draftsmanship and the visual arts, his choice of London lodgings was perhaps not entirely accidental. Be that as it may, this report on what was seemingly Blackstone's first serious encounter with the common law (even though he had by now accumulated a full five years' standing at the Middle Temple), exudes a jaunty self-confidence, couched in topically martial language: "I have stormed one Book of Littleton, & opened my Trenches before ye 2d; and I can with Pleasure say I have met with no Difficulty of Consequence...." Having established that even the common law's notoriously arid mysteries held no terrors for a person of his intellectual precocity, William went on to muse in more general terms about the nature of the body of knowledge with which he was now becoming acquainted, as it would seem for the first time:
Apprehending joule thieves with cinder (2009)

Energy is the critical limiting resource to mobile computing devices. Correspondingly, an operating system must track, provision, and ration how applications consume energy. The emergence of third-party application stores and marketplaces makes this concern even more pressing. A third-party application must not deny service through excessive, unforeseen energy expenditure, whether accidental or malicious. Previous research has shown promise in tracking energy usage and rationing it to meet device lifetime goals, but such mechanisms and policies are still nascent, especially regarding user interaction. We argue for a new operating system, called Cinder, which builds on top of the HiStar OS. Cinder's energy awareness is based on hierarchical capacitors and task profiles. We introduce and explore these abstractions, paying particular attention to the ways in which policies could be generated and enforced in a dynamic system.
OCT Minimum Intensity as a Predictor of Geographic Atrophy Enlargement (2014)

The MI may be increased at the margins of GA lesions before enlargement, which may indicate disruption or atrophy of the photoreceptors in these areas before GA becomes apparent. Increased MI may help predict areas of enlargement of GA, and may relate to overall growth rate and be a useful screening tool for GA. (ClinicalTrials.gov number, NCT00935883.).
Exploring optimal controller parameters for complex industrial systems (2015)

Tuning controller parameters to achieve desired system performance is challenging, especially for complex systems. Many heuristic methods are proposed to solve the problem. Because there are many system performance indices, such as response time and overshoot, it is difficult for these methods to achieve desired system performance due to system complexity, noise and uncertainties etc. This paper proposes an automated parameter tuning method, Gaussian Process Regression surrogated Bayesian Optimization Algorithm (GPRBOA), based on the required system performance for complex industrial systems. Because proportional-integral-derivative (PID) controller is widely used in industry, it is used as an example to demonstrate how the proposed method works. GPRBOA is applied to optimize the PID parameters by iteratively updating the system model and optimizing the system performance. Simulations have been performed and the results demonstrate the effectiveness of the proposed method.
Reinforcement Learning Using Approximate Belief States (1999)

The problem of developing good policies for partially observable Markov decision problems (POMDPs) remains one of the most challenging areas of research in stochastic planning. One line of research in this area involves the use of reinforcement learning with belief states, probability distributions over the underlying model states. This is a promising method for small problems, but its application is limited by the intractability of computing or representing a full belief state for large problems. Recent work shows that, in many settings, we can maintain an approximate belief state, which is fairly close to the true belief state. In particular, great success has been shown with approximate belief states that marginalize out correlations between state variables. In this paper, we investigate two methods of full belief state reinforcement learning and one novel method for reinforcement learning using factored approximate belief states. We compare the performance of these alg...