gebhart/patrepeval huggingface dataset:
Synapsins: Mosaics of Shared and Individual Domains in a Family of Synaptic Vesicle Phosphoproteins (1989)

Synapsins are neuronal phosphoproteins that coat synaptic vesicles, bind to the cytoskeleton, and are believed to function in the regulation of neurotransmitter release. Molecular cloning reveals that the synapsins comprise a family of four homologous proteins whose messenger RNA's are generated by differential splicing of transcripts from two genes. Each synapsin is a mosaic composed of homologous amino-terminal domains common to all synapsins and different combinations of distinct carboxyl-terminal domains. Immunocytochemical studies demonstrate that all four synapsins are widely distributed in nerve terminals, but that their relative amounts vary among different kinds of synapses. The structural diversity and differential distribution of the four synapsins suggest common and different roles of each in the integration of distinct signal transduction pathways that modulate neurotransmitter release in various types of neurons.
Recruiting for Diversity in Law Enforcement: An Evaluation of Practices Used by State and Local Agencies (2013)

Abstract This study analyzes several law enforcement agencies to (a) determine levels of representation of racial minorities in the law enforcement profession and (b) identify the marketing strategies being used during recruitment campaigns to locate, attract, and hire racial minorities to sworn positions. Responders answered questions regarding levels and areas of marketing techniques, sources of community outreach, recruit eligibility requirements, and other factors considered during recruiting campaigns. Results indicate low levels of informational distribution to, and contact with, critical core constituencies and institutions in minority communities. These findings may have implications for the numbers of minorities who are eventually hired for law enforcement positions. KEYTERMS: Minority recruitmentpolice–community relationspolice recruitmentracial profiling
An Analog Memory Circuit for Spiking Silicon Neurons (1997)

A simple circuit is described that functions as an analog memory whose state and dynamics are directly controlled by pulsatile inputs. The circuit has been incorporated into a silicon neuron with a spatially extensive dendritic tree as a means of controlling the spike firing threshold of an integrate-and-fire soma. Spiking activity generated by the neuron itself and by other units in a network can thereby regulate the neuron's excitability over time periods ranging from milliseconds to many minutes. Experimental results are presented showing applications to temporal edge sharpening, bistable behavior, and a network that learns in the manner of classical conditioning.
A Simple Method for the Analysis of Particle Sizes of Forage and Total Mixed Rations (1996)

A simple separator was developed to determine the particle sizes of forage and TMR that allows for easy separation of wet forage into three fractions and also allows plotting of the particle size distribution. The device was designed to mimic the laboratory-scale separator for forage particle sizes that was specified by Standard S424 of the American Society of Agricultural Engineers. A comparison of results using the standard device and the newly developed separator indicated no difference in ability to predict fractions of particles with maximum length of less than 8 and 19 mm. The separator requires a small quantity of sample (1.4 L) and is manually operated. The materials on the screens and bottom pan were weighed to obtain the cumulative percentage of sample that was undersize for the two fractions. The results were then plotted using the Weibull distribution, which proved to be the best fit for the data. Convenience samples of haycrop silage, corn silage, and TMR from farms in the northeastern US were analyzed using the forage and TMR separator, and the range of observed values are given.
Dynamic response for motion capture animation (2005)

Human motion capture embeds rich detail and style which is difficult to generate with competing animation synthesis technologies. However, such recorded data requires principled means for creating responses in unpredicted situations, for example reactions immediately following impact. This paper introduces a novel technique for incorporating unexpected impacts into a motion capture-driven animation system through the combination of a physical simulation which responds to contact forces and a specialized search routine which determines the best plausible re-entry into motion library playback following the impact. Using an actuated dynamic model, our system generates a physics-based response while connecting motion capture segments. Our method allows characters to respond to unexpected changes in the environment based on the specific dynamic effects of a given contact while also taking advantage of the realistic movement made available through motion capture. We show the results of our system under various conditions and with varying responses using martial arts motion capture as a testbed.
Incidence of invasive aspergillosis following hematopoietic stem cell and solid organ transplantation: interim results of a prospective multicenter surveillance program (2005)

The incidence of invasive aspergillosis was estimated among 4621 hematopoietic stem cell transplants (HSCT) and 4110 solid organ transplants (SOT) at 19 sites dispersed throughout the United States, during a 22 month period from 1 March 2001 through 31 December 2002. Cases were identified using the consensus definitions for proven and probable infection developed by the Invasive Fungal Infections Cooperative Group of the European Organization for Research and Treatment of Cancer and the Mycoses Study Group of the National Institute of Allergy and Infectious Diseases. The cumulative incidence (CI) of aspergillosis was calculated for the first episode of the infection that occurred within the specified time period after transplantation. To obtain an aggregate CI for each type of transplant, data from participating sites were weighted according to the proportion of transplants followed-up for specified time periods (four and 12 months for HSCT; six and 12 months for SOT). The aggregate CI of aspergillosis at 12 months was 0.5% after autologous HSCT, 2.3% after allogeneic HSCT from an HLA-matched related donor, 3.2% after transplantation from an HLA-mismatched related donor, and 3.9% after transplantation from an unrelated donor. The aggregate CI at 12 months was similar following myeloablative or non-myeloablative conditioning before allogeneic HSCT (3.1 vs. 3.3%). After HSCT, mortality at 3 months following diagnosis of aspergillosis ranged from 53.8% of autologous transplants to 84.6% of unrelated-donor transplants. The aggregate CI of aspergillosis at 12 months was 2.4% after lung transplantation, 0.8% after heart transplantation, 0.3% after liver transplantation, and 0.1% after kidney transplantation. After SOT, mortality at three months after diagnosis of aspergillosis ranged from 20% for lung transplants to 66.7% for heart and kidney transplants. The Aspergillus spp. associated with infections after HSCT included A. fumigatus (56%), A. flavus (18.7%), A. terreus (16%), A. niger (8%), and A. versicolor (1.3%). Those associated with infections after SOT included A. fumigatus (76.4%), A. flavus (11.8%), and A. terreus (11.8%). In conclusion, we found that invasive aspergillosis is an uncommon complication of HSCT and SOT, but one that continues to be associated with poor outcomes. Our CI figures are lower compared to those of previous reports. The reasons for this are unclear, but may be related to changes in transplantation practices, diagnostic methods, and supportive care.
Continuous and Energy-Efficient Transportation Behavior Monitoring (2012)

In this thesis we present and evaluate a novel approach for energy-efficient and continuous transportation behavior monitoring for smartphones. Our work builds on a novel adaptive hierarchical sensor management scheme (HASMET), which decomposes the classification task into smaller subtasks. In comparison to previous work, our approach improves the task of transportation behavior monitoring on three aspects. First, by employing only the minimal set of necessary sensors for each subtask, we are able to significantly reduce power consumption of the detection task. Second, using the hierarchical decomposition, we are able to tailor features and classifiers for each subtask, improving the accuracy and robustness of the detection task. Third, we are able to extend the detectable motorised modalities to cover most common public transportation vehicles. All of these attributes are highly desirable for real-time transportation behavior monitoring and serve as important steps toward implementing the first truly practical transportation behavior monitoring on mobile phones.\n\nIn the course of the research, we have developed an Android application for sensor data collection and utilized it to collect over 200 hours of transportation data, along with 2.5 hours of energy consumption data of the sensors. We apply our method on the data to demonstrate that compared to current state-of-art, our method offers higher detection accuracy, provides more robust transportation behavior monitoring and achieves significant reduction in power consumption.\n\nFor evaluating results with respect to the continuous nature of the transportation behavior monitoring, we use event and frame-based metrics presented by Ward et al.
Effective and precise face detection based on color and depth data (2014)

In this work an effective face detector based on the well-known Viola–Jones algorithm is proposed. A common issue in face detection is that for maximizing the face detection rate a low threshold is used for classifying as face an input image, but at the same time using a low threshold drastically increases the number of false positives. In this paper several criteria are proposed for reducing false positives: (i) a skin detection step is used to reject a candidate face region that does not contain the skin color, (ii) the size of the candidate face region is calculated according to the depth data, removing the too small or the too large faces, (iii) images of flat objects (e.g. candidate face found in a wall) or uneven objects (e.g. candidate face found in the leaves of a tree) are removed using the depth map and a segmentation approach based both on color and depth data. The above criteria permit to drastically reduce the number of false positives without decreasing the detection rate. The proposed approach has been validated on three datasets composed of 180 samples including both 2D and depth images. The face position inside samples has been manually labeled for testing. A Matlab version of the system for face detection and the full testing dataset will be freely available from http://www.dei.unipd.it/node/2357.
Learning a distance function with a Siamese network to localize anomalies in videos (2020)

This work introduces a new approach to localize anomalies in surveillance video. The main novelty is the idea of using a Siamese convolutional neural network (CNN) to learn a distance function between a pair of video patches (spatio-temporal regions of video). The learned distance function, which is not specific to the target video, is used to measure the distance between each video patch in the testing video and the video patches found in normal training video. If a testing video patch is not similar to any normal video patch then it must be anomalous. We compare our approach to previously published algorithms using 4 evaluation measures and 3 challenging target benchmark datasets. Experiments show that our approach either surpasses or performs comparably to current state-of-the-art methods.
Protein kinase C mediates caspase 3 activation: A role for erythrocyte morphology changes (2015)

We have previously showed that morphological alterations in Red Blood Cells (RBCs) are correlated to an impaired eNOS enzymatic activity and a concomitant reduced NO derived metabolites formation. Here we extend our previous observations, reporting that RBC morphology is regulated by a series of specific cell signaling events linked to Protein Kinase C (PKC)-mediated activation of caspase 3. Pretreatment of RBCs with the PKC inhibitor chelerythrine, prior to the addition of phorbol-12-myristate-13-acetate (PMA), an activator of PKC, blocks the appearance of the morphology alterations and the sustained decrease in nitrates and nitrites levels induced by PMA. Inhibition of PKC also completely inhibits PMA mediated caspase-3 activation. On the other hand, caspase 3 inhibition, lessens the PMA induced-effects on the appearance of RBC morphology alterations, although it enhances PMA-mediated effects on nitric oxide (NO) derived metabolites levels. These data demonstrate that PKC-mediated activation of caspase 3 is an integral and essential part of signaling pathway in RBCs, that may be a regulatory factor of RBC mechanical properties, through regulation of NO metabolism.
Trabecular cells of the eye express messenger RNA for transforming growth factor-beta 1 and secrete this cytokine. (1993)

These investigations show that the trabecular meshwork, iris, and ciliary body in vivo express the messenger RNA transcript for TGF-beta 1, and that trabecular cells in vitro synthesize and secrete this cytokine. The TGF-beta 1 present in normal aqueous humor may be derived locally, at least in part, from the cells of the trabecular meshwork, iris, and ciliary body. Abnormal synthesis, secretion, activation, and clearance of TGF-beta 1 may contribute to the pathogenesis of many ocular disorders, including primary open-angle glaucoma.
Spatial Dynamics of DNA Damage Response Protein Foci along the Ion Trajectory of High-LET Particles (2011)

High-linear energy transfer (LET) ion irradiation of cell nuclei induces complex and severe DNA lesions, and foci of repair proteins are formed densely along the ion trajectory. To efficiently discriminate the densely distributed/overlapping foci along the ion trajectory, a focus recognition algorithm called FociPicker3D based on a local fraction thresholding technique was developed. We analyzed high-resolution 3D immunofluorescence microscopic focus images and obtained the kinetics and spatial development of γ-H2AX, 53BP1 and phospho-NBS1 foci in BJ1-hTERT cells irradiated with 55 MeV carbon ions and compared the results with the dynamics of double-strand break (DSB) distributions simulated using the PARTRAC model. Clusters consisting of several foci were observed along the ion trajectory after irradiation. The spatial dynamics of the protein foci supports that the foci clusters are not formed by neighboring foci but instead originate from the DSB cluster damage induced by high-LET radiations.
AN N-terminal peptide from link protein stimulates proteoglycan biosynthesis in human articular cartilage in vitro (1998)

This N-terminal peptide, which can be liberated from proteoglycan aggregates by proteolysis, potently stimulated the synthesis of proteoglycans with normal glycosaminoglycan chains. The results suggest that the N-terminal peptide may have a regulatory role in maintaining the integrity of human cartilage matrix.
UAV-Assisted Heterogeneous Networks for Capacity Enhancement (2016)

Modern day wireless networks have tremendously evolved driven by a sharp increase in user demands, continuously requesting more data and services. This puts significant strain on infrastructure-based macro cellular networks due to the inefficiency in handling these traffic demands, cost effectively. A viable solution is the use of unmanned aerial vehicles (UAVs) as intermediate aerial nodes between the macro and small cell tiers for improving coverage and boosting capacity. This letter investigates the problem of user-demand-based UAV assignment over geographical areas subject to high traffic demands. A neural-based cost function approach is formulated, in which UAVs are matched to a particular geographical area. It is shown that leveraging multiple UAVs not only provides long-range connectivity but also better load balancing and traffic offload. Simulation study demonstrates that the proposed approach yields significant improvements in terms of fifth percentile spectral efficiency up to 38% and reduced delays up to 37.5% compared with a ground-based network baseline without UAVs.
A Simple Sequential Spectrum Sensing Scheme for Cognitive Radio (2009)

Cognitive radio that supports a secondary and opportunistic access to licensed spectrum shows great potential to dramatically improve spectrum utilization. Spectrum sensing performed by secondary users to detect unoccupied spectrum bands, is a key enabling technique for cognitive radio. This paper proposes a truncated sequential spectrum sensing scheme, namely the sequential shifted chi-square test (SSCT). The SSCT has a simple test statistic and does not rely on any deterministic knowledge about primary signals. As figures of merit, the exact false-alarm probability is derived, and the miss-detection probability as well as the average sample number (ASN) are evaluated by using a numerical integration algorithm. Corroborating numerical examples show that, in comparison with fixed-sample size detection schemes such as energy detection, the SSCT delivers considerable reduction on the ASN while maintaining a comparable detection performance.
Compact Models Based on Transmission-Line Concept for Integrated Capacitors and Inductors (2006)

This paper presents a compact modeling methodology for inductors and capacitors based on transmission-line theory. Using continued fractions approximation, second- and third-order intrinsic inductor and capacitor models are demonstrated. With the second-order model, one can accurately predict inductor and capacitor behavior up to their first resonance frequencies. With the third-order model, one can match the measured inductor or capacitor response beyond the first resonance frequency. Wideband accurate passive models developed here are essential for transient and harmonic-balance analysis where out-of-band frequencies are important. The model parameters are extracted directly from S-parameter measurement without a need for optimization. Furthermore, the frequency-dependent nonlinear effects of spiral inductors and metal-insulator-metal capacitors are expressed based on simple models without resorting to frequency-dependent parameters
Behavioral fault modeling and simulation of phase-locked loops using a VHDL-A like language (2002)

A new methodology called induced behavioral fault modeling is presented for fault simulation and testing of analog and mixed-signal circuits, and demonstrated using voltage controlled oscillators and phase-locked loops. The key of this methodology is to use actual layout and process defect information to derive a set of realistic faults at the transistor level, and to generate a small set of behavioral fault models-in a mixed-signal hardware description language-that abstracts the derived transistor-level faults. While ensuring the same fault coverage as transistor-level fault modeling, induced behavioral fault modeling offers significant advantage in simulation efficiency and modeling capacity.
Unravelling Intratumoral Heterogeneity through High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing (2019)

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for resolving transcriptional heterogeneity. However, its application to studying cancerous tissues is currently hampered by the lack of coverage across key mutation hotspots in the vast majority of cells; this lack of coverage prevents the correlation of genetic and transcriptional readouts from the same single cell. To overcome this, we developed TARGET-seq, a method for the high-sensitivity detection of multiple mutations within single cells from both genomic and coding DNA, in parallel with unbiased whole-transcriptome analysis. Applying TARGET-seq to 4,559 single cells, we demonstrate how this technique uniquely resolves transcriptional and genetic tumor heterogeneity in myeloproliferative neoplasms (MPN) stem and progenitor cells, providing insights into deregulated pathways of mutant and non-mutant cells. TARGET-seq is a powerful tool for resolving the molecular signatures of genetically distinct subclones of cancer cells.
Hot-Carrier-induced Circuit Degradation In Actual DRAM (1995)

The hot-carrier effects on DRAM have been evaluated thoroughly by investigating the performance degradation of each constituent circuit as component transistor aging in a 64 Mb DRAM. The mechanism of how the overall circuit performance is affected by unit transistor aging and which transistors cause most critical circuit performance failures is discussed. It was found that hot-carrier-induced transistor aging in the circuit block did not directly affect the speed degradation, but instead, seriously reduced the design margin of the analog circuit. The circuit performance degradation caused by hot-carrier stress depended more on the circuit structure including output loading rather than the voltage level. In addition, on-chip hot-carrier stress/test patterns were also used to investigate the influence of different output loads of inverter on the dynamic hot-carrier degradation. It was found that the inverter with heavy output load showed less degradation in comparison to the inverter with small load.
The Type 1 growth factor receptors and their ligands considered as a complex system. (2001)

The Type 1 family of growth factors and their receptors play an important role in normal development, wound healing and in diseases such as cancer. The products of the four receptor genes and the ten genes specifying ligands interact in a complex pattern. Such systems may develop emergent properties which cannot be predicted from a reductionist analysis of the interactions of individual components. New methods of determining these higher level properties are, however, being developed. These include microscopic analysis of live cells expressing fluorescently tagged ligands, receptors and second messengers which can provide positional information on components of the system. Computational simulations of the complex interactions are being developed which can help to predict the properties of the system.
Measuring differential gene expression with RNA-seq: challenges and strategies for data analysis (2014)

RNA-seq is a methodology for RNA profiling based on next-generation sequencing that enables to measure and compare gene expression patterns at unprecedented resolution. Although the appealing features of this technique have promoted its application to a wide panel of transcriptomics studies, the fast-evolving nature of experimental protocols and computational tools challenges the definition of a unified RNA-seq analysis pipeline. In this review, focused on the study of differential gene expression with RNA-seq, we go through the main steps of data processing and discuss open challenges and possible solutions.
Analysis of macro-strain transfer and complete strain state measurement with embedded fiber-optic sensors (1993)

Summarizes the normal strain coupling from an isotropic material into an embedded optical fiber which serves as a sensor. The sensor is based on single-mode polarization-maintaining fibers and is sensitive to all three normal strains. It is shown analytically that six such sensors can monitor the complete strain state of the host material provided that the sensor direction and polarization axes are properly orientated.