gebhart/patrepeval huggingface dataset:
Psychophysiologic Assessment of Posttraumatic Stress Disorder Imagery in Vietnam Combat Veterans (1987)

This study utilized psychophysiologic techniques to assess emotional arousal during imagery of psychologically traumatic experiences. All subjects were medication-free Vietnam combat veterans, classified on the basis of DSM-III-R criteria into groups with posttraumatic stress disorder (PTSD, n = 18) and no mental disorder (control, n = 15), which did not differ in extent of combat or in the judged severity of the traumatic experiences reported. "Scripts" describing each subject's combat experiences as well as other experiences were read to them in the laboratory, and they were instructed to imagine the events the scripts portrayed, while heart rate, skin conductance, and frontalis electromyogram were recorded. The PTSD subjects' physiologic responses to their combat scripts were markedly higher than the controls'. The combined physiologic variables identified PTSD subjects with a specificity of 100% and a sensitivity of 61%. The results demonstrate exaggerated physiologic arousal during recollection of traumatic experiences in PTSD.
UMA PROPOSTA DE LEGENDAGEM PARA O ESPETÁCULO MIRALU E A LUNETA ENCANTADA (2019)

Subtitling for the Deaf and Hard of Hearing to the theater field is still little explored in our\ncountry. Aiming, therefore, to insert the deaf community in the audiovisual media, this work\nwas written with the general aim of proposing a Deaf and Hard of Hearing Subtitle for the\nchildren's theater show Miralu e a Luneta Encantada. The specific objective is to observe\nsome factors that cause the need to apply textual reduction strategies in the elaboration of the\nmentioned subtitles. The methodology applied for the elaboration of the subtitles was based\non the research and studies that have been developed by the LEAD group (Legendagem e\nAudiodescrição) from the Ceará State University (UECE), on the main considerations of\nAraújo (2004, 2006, 2008, 2012 ), Assis (2016) and Nascimento (2018, 2013), as well as the parameters brought by the Guia para Produções Audiovisuais Acessíveis (ARAÚJO;\nCHAVES, 2016). The results obtained in this research showed that factors such as the\nidentification of speakers and the speed of dialogues often lead to the need to reduce the\nlenght of the subtitles. However, tests are needed to prove the effectiveness of the textual\nreduction strategies used. We could observe with this work that the forms of reduction and\ntextual omission are important to produce appropriated subtitles to the reading time of the\ntarget viewer, thus contributing to the appreciation of audiovisual products as a whole.
AutoQ: Automated Kernel-Wise Neural Network Quantization (2019)

Network quantization is one of the most hardware friendly techniques to enable the deployment of convolutional neural networks (CNNs) on low-power mobile devices. Recent network quantization techniques quantize each weight kernel in a convolutional layer independently for higher inference accuracy, since the weight kernels in a layer exhibit different variances and hence have different amounts of redundancy. The quantization bitwidth or bit number (QBN) directly decides the inference accuracy, latency, energy and hardware overhead. To effectively reduce the redundancy and accelerate CNN inferences, various weight kernels should be quantized with different QBNs. However, prior works use only one QBN to quantize each convolutional layer or the entire CNN, because the design space of searching a QBN for each weight kernel is too large. The hand-crafted heuristic of the kernel-wise QBN search is so sophisticated that domain experts can obtain only sub-optimal results. It is difficult for even deep reinforcement learning (DRL) Deep Deterministic Policy Gradient (DDPG)-based agents to find a kernel-wise QBN configuration that can achieve reasonable inference accuracy. In this paper, we propose a hierarchical-DRL-based kernel-wise network quantization technique, AutoQ, to automatically search a QBN for each weight kernel, and choose another QBN for each activation layer. Compared to the models quantized by the state-of-the-art DRL-based schemes, on average, the same models quantized by AutoQ reduce the inference latency by 54.06\%, and decrease the inference energy consumption by 50.69\%, while achieving the same inference accuracy.
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction (2017)

Researchers have demonstrated state-of-the-art performance in sequential decision making problems (e.g., robotics control, sequential prediction) with deep neural network models. One often has access to near-optimal oracles that achieve good performance on the task during training. We demonstrate that AggreVaTeD --- a policy gradient extension of the Imitation Learning (IL) approach of (Ross & Bagnell, 2014) --- can leverage such an oracle to achieve faster and better solutions with less training data than a less-informed Reinforcement Learning (RL) technique. Using both feedforward and recurrent neural network predictors, we present stochastic gradient procedures on a sequential prediction task, dependency-parsing from raw image data, as well as on various high dimensional robotics control problems. We also provide a comprehensive theoretical study of IL that demonstrates we can expect up to exponentially lower sample complexity for learning with AggreVaTeD than with RL algorithms, which backs our empirical findings. Our results and theory indicate that the proposed approach can achieve superior performance with respect to the oracle when the demonstrator is sub-optimal.
Firm financing in India: recent trends and factors (2005)

Using balance sheet information for nearly 6,000 firms between 1994-2003, this study investigates recent firm financing patterns in India. The paper documents the overall use of debt and, in particular, the role of bank financing (short-term and long-term), trade credit, intrabusiness group borrowing and foreign financing. The study examines financing patterns over time and explores differences across firms by sector, age, ownership type, export orientation, and, in particular, size. In terms of trends, we find that while debt to asset ratios have been relatively stable, nominal debt growth has slowed down in recent years. At the same time, firms' repayment capacity, as measured by the interest coverage ratio has exhibited a U-shaped pattern falling during 1997-99 and recovering in recent years. Throughout the period of study, bank financing as a share of total debt has increased, while borrowing from non-bank financial institutions fell sharply. In terms of differences across firms, the most robust finding is that debt levels increase with firm size. Smaller firms have especially less debt relative to larger firms if they are young (below 10 years since incorporation), if they are in the manufacturing sector, and if they are located in Southern India. Furthermore, while the ratio of debt to assets has been relatively stable for large firms, we observe a significant decline for smaller firms. Overall, the findings presented in the paper provide suggestive (but not definite) evidence of stronger credit constraints for smaller firms.
Compressive Privacy Generative Adversarial Network (2020)

Machine learning as a service (MLaaS) has brought much convenience to our daily lives recently. However, the fact that the service is provided through cloud raises privacy leakage issues. In this work we propose the compressive privacy generative adversarial network (CPGAN), a data-driven adversarial learning framework for generating compressing representations that retain utility comparable to state-of-the-art, with the additional feature of defending against reconstruction attack. This is achieved by applying adversarial learning scheme to the design of compression network (privatizer), whose utility/privacy performances are evaluated by the utility classifier and the adversary reconstructor, respectively. Experimental results demonstrate that CPGAN achieves better utility/privacy trade-off in comparison with the previous work, and is applicable to real-world large datasets.
Dynamic Wireless QoS Analysis for Real-Time Control in URLLC (2018)

One of the major goals of ultra-reliable and low-latency communication (URLLC) is to enable real-time wireless control systems. However, it is challenging to use URLLC throughout the control process since a huge amount of wireless resource is needed to maintain the rigorous quality-of-service (QoS) in URLLC, i.e, ultra reliability and low latency. In this paper, our goal is to discuss that whether the extreme high QoS in URLLC leads to better control performance than low QoS during the control process. This is expected to provide a guideline on the usage of the URLLC throughout the control process dynamically. Specifically, we first investigate the relationship between the URLLC QoS and control performance. Then, we discuss the effect of different communication QoS on the control performance. Our results show that the rigorous QoS in URLLC and a low QoS can be used dynamically throughout the control process with high system performance.
3D imaging and wavefront sensing with a plenoptic objective (2011)

Plenoptic cameras have been developed over the last years as a passive method for 3d scanning. Several superresolution algorithms have been proposed in order to increase the resolution decrease associated with lightfield acquisition with a microlenses array. A number of multiview stereo algorithms have also been applied in order to extract depth information from plenoptic frames. Real time systems have been implemented using specialized hardware as Graphical Processing Units (GPUs) and Field Programmable Gates Arrays (FPGAs). In this paper, we will present our own implementations related with the aforementioned aspects but also two new developments consisting of a portable plenoptic objective to transform every conventional 2d camera in a 3D CAFADIS plenoptic camera, and the novel use of a plenoptic camera as a wavefront phase sensor for adaptive optics (OA). The terrestrial atmosphere degrades the telescope images due to the diffraction index changes associated with the turbulence. These changes require a high speed processing that justify the use of GPUs and FPGAs. Na artificial Laser Guide Stars (Na-LGS, 90km high) must be used to obtain the reference wavefront phase and the Optical Transfer Function of the system, but they are affected by defocus because of the finite distance to the telescope. Using the telescope as a plenoptic camera allows us to correct the defocus and to recover the wavefront phase tomographically. These advances significantly increase the versatility of the plenoptic camera, and provides a new contribution to relate the wave optics and computer vision fields, as many authors claim.
Hepatocyte growth factor/scatter factor: a heparan sulphate-binding pleiotropic growth factor (1994)

Conference Article| May 01 1994 Hepatocyte growth factor/scatter factor: a heparan sulphate-binding pleiotropic growth factor Malcolm Lyon; Malcolm Lyon * *To whom correspondence should be addressed Search for other works by this author on: This Site PubMed Google Scholar John T. Gallagher John T. Gallagher 1CRC and University of Manchester Department of Medical Oncology, Christie Hospital, Wilmslow Road, Manchester M20 9BX, U.K. Search for other works by this author on: This Site PubMed Google Scholar Biochem Soc Trans (1994) 22 (2): 365–370. https://doi.org/10.1042/bst0220365 Article history Received: December 24 1993 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Cite Icon Cite Get Permissions Citation Malcolm Lyon, John T. Gallagher; Hepatocyte growth factor/scatter factor: a heparan sulphate-binding pleiotropic growth factor. Biochem Soc Trans 1 May 1994; 22 (2): 365–370. doi: https://doi.org/10.1042/bst0220365 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 ContentAll JournalsBiochemical Society Transactions Search Advanced Search Keywords: AT, antithrombin, bFGF, basic FGF, EGF, epidermal growth factor, FGF, fibroblast growth factor, HexA, hexuronate, HS, heparan sulphate, HSPG, US proteoglycan, IdoA, α-l-iduronic acid, VEGF, vascular endothelial growth factor This content is only available as a PDF. © 1994 Biochemical Society1994 Article PDF first page preview Close Modal You do not currently have access to this content.
Dynamic Programming Solution for Detecting Dim Moving Targets (1985)

An on-board scanning or mosaic sensor is staring down from a satellite to a fixed ground point while producing a set of frames that contain target and background signals. Detecting dim moving targets should ideally be done by exhaustively searching over all in he maery(mached fltering), as ppoed possible trajectories in the imagery (matched filtering) as opposed to assembling trajectories from thresholded frames. The dynamic programming approach equivalently substitutes the above prohibitive exhaustive search by a feasible algorithm.
Highly efficient broadband waveguide based adiabatic polarization converter with apodization (2016)

We report the design of a highly efficient broadband electro optic waveguide polarization converter using the rapid adiabatic passage mechanism, a well-known technique in the field of quantum optics. We also introduce a novel design for apodization of electrode pattern to get a ripple free bandwidth spectrum.
Modeling the Atmospheric Concentrations of Individual Gas-Phase and Particle-Phase Organic Compounds (2000)

An Eulerian photochemical airshed model is adapted to track the concentrations of individual vapor-phase, semivolatile, and particle-phase compounds over the carbon number range from C1 to C34. The model incorporates primary emissions of organic gases and particles from sources based on recent source tests. These emissions are processed through a photochemical airshed model whose chemical mechanism has been expanded to explicitly follow the reaction or formation of 125 individual vapor-phase organic compounds plus 11 lumped vapor-phase compound groups. Primary organic compounds in the particle phase can be disaggregated at will from a lumped primary organic compound mass category; in the present model application, 31 individual primary particulate organic compounds are tracked as they are transported from sources to receptor air monitoring sites. The model is applied to study air quality relationships for organics in California's South Coast Air Basin that surrounds Los Angeles during the severe photochemical smog episode that occurred on September 8−9, 1993. The ambient concentra tions of all normal alkanes and most aromatic hydrocarbons are predicted within the correct order of magnitude over 6 orders of magnitude concentration change from most abundant gas phase to least abundant particulate species studied. A formal evaluation of model performance shows that, with the exception of a few outliers, the concentrations of over 100 organic compounds studied were reproduced with an average absolute bias of ±47% and with roughly equal numbers of compounds underpredicted (58) versus overpredicted (46). The time series of observed aromatic hydrocarbons concentrations are reproduced closely, production of methylglyoxal from aromatic precursors is tracked, and the predicted olefinic hydrocarbon concentrations decline dramatically in concentration due to chemical reaction and dilution during downwind transport as is observed in the ambient monitoring database. This ability to simultaneously account for the concentrations of individual gas-phase and particulate organic compounds lays a foundation for future calculations of secondary organic aerosol formation and gas/particle repartitioning in the atmosphere.
Ecdysone receptor expression in the CNS correlates with stage-specific responses to ecdysteroids during <i>Drosophila</i> and <i>Manduca</i> development (1994)

In insects, the ecdysteroids act to transform the CNS from its larval to its adult form. A key gene in this response is the ecdysone receptor (EcR), which has been shown in Drosophila to code for 3 protein isoforms. Two of these isoforms, EcR-A and EcR-B1, are prominently expressed in the CNS and we have used isoform-specific antibodies to examine their fluctuations through postembryonic life. EcR expression at the onset of metamorphosis is extremely diverse but specific patterns of EcR expression correlate with distinct patterns of steroid response. Most larval neurons show high levels of EcR-B1 at the start of metamorphosis, a time when they lose larval features in response to ecdysteroids. Earlier, during the larval molts, the same cells have no detectable receptors and show no response to circulating ecdysteroids; later, during the pupal-adult transformation, they switch to EcR-A expression and respond by maturing to their adult form. During the latter period, a subset of the larval neurons hyperexpress EcR-A and these cells are fated to die after the emergence of the adult. The stem cells for the imaginal neurons show prominent EcR-B1 expression during the last larval stage correlated with their main proliferative period. Most imaginal neurons, by contrast, express only EcR-A when they subsequently initiate maturation at the start of metamorphosis. The imaginal neurons of the mushroom bodies are unusual amongst imaginal neurons in expressing the B1 isoform at the start of metamorphosis but they also show regressive changes at this time as they lose their larval axons. Imaginal neurons of the optic lobe show a delayed expression of EcR-B1 through the period when cell-cell interactions are important for establishing connections within this region of the CNS. Overall, the appearance of the two receptor isoforms in cells correlates with different types of steroid responses: EcR-A predominates when cells are undergoing maturational responses whereas EcR-B1 predominates during proliferative activity or regressive responses. The heterogeneity of EcR expression at the start of metamorphosis presumably reflects the diverse origins and requirements of the neurons that nevertheless are all exposed to a common hormonal signal.
Microsampling valves of new design and their applications: generation of concentration-programmed gaseous streams (1983)

Microsampling valves of new design were developed in glass or metal forms. The valves are suitable for sampling minute quantities of gases and can be used for sampling in gas mixture streams. The valves were used to produce gas streams of a time-programmable concentration.
The Influence of Hafnium Doping on Density of States in Zinc Oxide Thin-Film Transistors Deposited via Atomic Layer Deposition (2017)

Thin-film transistors (TFTs) with atomic layer deposition (ALD) HfZnO (HZO) as channel layer and Al<sub>2</sub>O<sub>3</sub> as gate insulator were successfully fabricated. Compared with ZnO-TFT, the stability of HZO-TFT was obviously improved as Hf doping can suppress the generation of oxygen related defects. The transfer characteristics of TFTs at different temperatures were also investigated, and temperature stability enhancement was observed for the TFT with Hf doping. The density of states (DOS) was calculated based on the experimentally obtained E <sub>a</sub>, which can explain the experimental observation. A high-field effect mobility of 9.4 cm<sup>2</sup>/Vs, a suitable turn-on voltage of 0.26 V, a high on/off ratio of over 10<sup>7</sup> and a steep sub-threshold swing of 0.3 V/decade were obtained in HZO-TFT. The results showed that temperature stability enhancement in HfZnO thin-film transistors are attributed to the smaller DOS.
Graphical user interface for image acquisition and processing (2023)

An event-driven GUI-based image acquisition interface for the IDL programming environment designed for CCD camera control and image acquisition directly into the IDL environment where image manipulation and data analysis can be performed, and a toolbox of real-time analysis applications. Running the image acquisition hardware directly from IDL removes the necessity of first saving images in one program and then importing the data into IDL for analysis in a second step. Bringing the data directly into IDL creates an opportunity for the implementation of IDL image processing and display functions in real-time. program allows control over the available charge coupled device (CCD) detector parameters, data acquisition, file saving and loading, and image manipulation and processing, all from within IDL. The program is built using IDL's widget libraries to control the on-screen display and user interface.
Modulation of the Inflammatory Response in Cardiovascular Disease (2004)

There is a growing body of evidence that inflammation might play an important role in the initiation and progression of cardiovascular diseases (CVDs). The designation of CVD as a chronic inflammatory process is further supported by evidence that the risk factors for CVD cause endothelial cells throughout the vascular tree to assume an inflammatory phenotype. These activated endothelial cells characteristically exhibit oxidative stress and increased adhesiveness for circulating leukocytes. Although initial efforts to define the mechanisms underlying the inflammatory phenotype in diseased endothelial cells have focused on the linkage between oxidative stress and adhesion molecule activation/expression, recent work has implicated a variety of additional factors that can modulate the magnitude and/or nature of the inflammatory responses in CVD. Platelets, angiotensin II, and the CD40/CD40 ligand signaling system are gaining recognition as contributors to the pathogenesis of CVD. These factors appear to converge with known pathways that link oxidative stress with adhesion molecule expression and help to explain the apparent integration of coagulation with inflammation in CVD. These factors also hold the promise of offering multiple sites for therapeutic intervention in CVD.
Architecture for realizing cloud-based IT infrastructures (2012)

Traditional IT infrastructures consist of a multitude of different hardware elements, each of them consuming electrical power even in times of low usage by end users. In the BCI project the TUB is working on realization of cloud-based IT infrastructures, where physical hardware elements are migrated into the cloud.
Effect of growth conditions and substratum composition on the persistence of coliforms in mixed-population biofilms (1996)

Laboratory reactors operated under oligotrophic conditions were used to evaluate the importance of initial growth rate and substratum composition on the long-term persistence of coliforms in mixed-population biofilms. The inoculum growth rate had a dramatic effect on the ability of coliforms to remain on surfaces. The most slowly grown coliforms (mu = 0.05/h) survived at the highest cell concentration. Antibody staining revealed that Klebsiella pneumoniae existed primarily as discrete microcolonies on the surface. Both coliforms and heterotrophic plate count bacteria were supported in larger numbers on a reactive substratum, mild steel, than on polycarbonate.