gebhart/patrepeval huggingface dataset:
Synthesis, Biological Activity, and Molecular Modeling Studies of Selective 5-HT<sub>2C/2B</sub> Receptor Antagonists (1996)

The synthesis and biological activity are reported for a series of analogues of the previously published indole urea 2 (SB-206553), designed to probe the 5-HT(2C) receptor binding site. Small molecule modeling studies have been used to define a region in space which is allowed at the 5-HT(2C) receptor but disallowed at the 5-HT(2A) receptor. In a complementary approach, docking of 2 into our model of the 5-HT(2C) receptor has allowed us to propose a novel primary binding interaction for this series of diaryl ureas, involving a potential double hydrogen-bonding interaction between the urea carbonyl oxygen of the ligand and two serine residues in the receptor. The difference of two valine residues in the 5-HT(2C) receptor for leucine residues in the 5-HT(2A) receptor is believed to account for the observed 5-HT(2C)/5-HT(2A) selectivity with 2.
Ratiometric temperature stable current reference (1993)

Current-mode integraed circuit design leads to the use of a current reference achieving good temperature compensation. A novel circuit is described, which has good performance based on a ratiometric expression that is easily reproduced. As a bonus, the circuit acts as a PTAT (proportional to absolute temperature) reference without any structural change.
Concept of a modified flywheel for megajoule storage and pulse conditioning (1991)

The concept of a flywheel with a variable moment of inertia for electromagnetic launch (EML) is introduced. The modified flywheel will further improve the energy density and efficiency. Coupled to a pulse-duty generator, it could produce a near-square pulse or other desirable pulse shapes. The amount of energy, its rate, and its switching all could be controlled prior to electric energy conversion. The modified flywheel is structured with masses movable along radial paths. Potential energy is stored with respect to mass position and kinematic energy with respect to spin. This mass positioning provides a means to control the rate of energy discharge. Control with spring-loaded weight would have near constant spin output. A servomechanism scheme can, however, provide the precise inward-moving positioning control of masses, and hence the other desirable output pulse conditioning. In the conventional flywheel, energy is always discharged in an exponential decay. In an EML system, a flywheel is the rotor of the pulse-duty generator, such as in the homopolar generator, compulsator, or the disk alternator.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
TRAF2 Exerts Its Antiapoptotic Effect by Regulating the Expression of Krüppel-Like Factor LKLF (2003)

Tumor necrosis factor receptor (TNFR)-associated factor 2 (TRAF2) is one of the key factors that mediate TNF signaling. The deletion of TRAF2 renders cells more sensitive to TNF-induced apoptosis. Although TRAF2 is known to be required for TNF-induced JNK and NF-kappaB activation, the underlying mechanism of the increased sensitivity of TRAF2 null cells (TRAF2(-/-)) to TNF-induced apoptosis is not fully understood. To study the underlying mechanism, we examined the difference in gene expression between TRAF2(-/-) and wild-type fibroblast cells by using microarray technology. We found that one of the genes whose expression was dramatically decreased in TRAF2(-/-) cells was the lung Krüppel-like factor (LKLF). Our results indicate that the expression of LKLF requires TRAF2 but is independent of TNF signaling. Although it appears that TRAF2 regulates the expression of the LKLF gene at the transcription level, TRAF2 does not function as a transcription factor itself. Our results suggest that TRAF2 regulates LKLF expression through the mitogen-activated protein kinase p38 pathway. More importantly, ectopic expression of LKLF in TRAF2(-/-) cells protected cells against TNF-induced apoptosis. These results reveal a novel aspect of TRAF2 function: by regulating the expression of genes, such as LKLF, TRAF2 controls cell sensitivity to apoptosis.
A Survey on Information and Communication Technologies for Industry 4.0: State-of-the-Art, Taxonomies, Perspectives, and Challenges (2019)

A new industrial revolution is undergoing, based on a number of technological paradigms. The will to foster and guide this phenomenon has been summarized in the expression “Industry 4.0” (I4.0). Initiatives under this term share the vision that many key technologies underlying Cyber-Physical Systems and Big Data Analytics are converging to a new distributed, highly automated, and highly dynamic production network, and that this process needs regulatory and cultural advancements to effectively and timely develop. In this work, we focus on the technological aspect only, highlighting the unprecedented complexity of I4.0 emerging from the scientific literature. While previous works have focused on one or up to four related enablers, we consider ten technological enablers, including besides the most cited Big Data, Internet of Things, and Cloud Computing, also others more rarely considered as Fog and Mobile Computing, Artificial Intelligence, Human-Computer Interaction, Robotics, down to the often overlooked, very recent, or taken for granted Open-Source Software, Blockchain, and the Internet. For each we explore the main characteristics in relation to I4.0 and its interdependencies with other enablers. Finally we provide a detailed analysis of challenges in leveraging each of the enablers in I4.0, evidencing possible roadblocks to be overcome and pointing at possible future directions of research. Our goal is to provide a reference for the experts in some of the technological fields involved, for a reconnaissance of integration and hybridization possibilities with other fields in the endeavor of I4.0, as well as for the laymen, for a high-level grasp of the variety (and often deep history) of the scientific research backing I4.0.
A new parameterizable power macro-model for datapath components (1999)

Article Free Access Share on A new parameterizable power macro-model for datapath components Authors: Gerd Jochens OFFIS Research Institute, Oldenburg OFFIS Research Institute, OldenburgView Profile , Lars Kruse OFFIS Research Institute, Oldenburg OFFIS Research Institute, OldenburgView Profile , Eike Schmidt OFFIS Research Institute, Oldenburg OFFIS Research Institute, OldenburgView Profile , Wolfgang Nebel OFFIS Research Institute, Oldenburg OFFIS Research Institute, OldenburgView Profile Authors Info & Claims DATE '99: Proceedings of the conference on Design, automation and test in EuropeJanuary 1999 Pages 8–eshttps://doi.org/10.1145/307418.307434Published:01 January 1999Publication History 15citation156DownloadsMetricsTotal Citations15Total Downloads156Last 12 Months9Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Evaluation of the computational validity of the image model in predicting the sound field in a wedge-shaped layer using acoustical reciprocity (1991)

Computer models based on the method of image were used to investigate and calculate the pressure amplitude distribution in wedge-shaped (tapered) water layer overlying a fast, absorbing bottom. The pressure amplitude of the field was generated and compared at reciprocal positions of source and receiver. The results showed that the ratio of pressure was larger when the position of source receiver was closer to the bottom and nearer the apex.
A Graph Based Methodology for Temporal Signature Identification from HER. (2015)

Data driven technology is believed to be a promising technique for transforming the current status of healthcare. Electronic Health Records (EHR) is one of the main carriers for conducting the data driven healthcare research, where the goal is to derive insights from healthcare data and utilize such insights to improve the quality of care delivery. Due to the progression nature of human disease, one important aspect for analyzing healthcare data is temporality, which suggests the temporal relationships among different healthcare events and how their values evolve over time. Sequential pattern mining is a popular tool to extract time-invariant patterns from discrete sequences and has been applied in analyzing EHR before. However, due to the complexity of EHR, those approaches usually suffers from the pattern explosion problem, which means that a huge number of patterns will be detected with improper setting of the support threshold. To address this challenge, in this paper, we develop a novel representation, namely the temporal graph, for event sequences like EHR, wherein the nodes are medical events and the edges indicate the temporal relationships among those events in patient EHRs. Based on the temporal graph representation, we further develop an approach for temporal signature identification to identify the most significant and interpretable graph bases as temporal signatures, and the expressing coefficients can be treated as the embeddings of the patients in such temporal signature space. Our temporal signature identification framework is also flexible to incorporate semi-supervised/supervised information. We validate our framework on two real-world tasks. One is predicting the onset risk of heart failure. The other is predicting the risk of heart failure related hospitalization for patients with COPD pre-condition. Our results show that the prediction performance in both tasks can be improved by the proposed approaches.
Screening for amblyopia among grade-1 students in primary school with uncorrected vision and stereopsis test in central China (2013)

Distant VA test of high cutoff alone displays a high sensitivity but a low specificity. Simultaneous testing of distant VA of low cutoff and stereoacuity is a better choice to balance between sensitivity and specificity.
Gray Matter Age Prediction as a Biomarker for Risk of Dementia (2019)

The gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as a biomarker for early-stage neurodegeneration. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link. We aimed to investigate the utility of such a gap as a risk biomarker for incident dementia using a deep learning approach for predicting brain age based on MRI-derived gray matter (GM). We built a convolutional neural network (CNN) model to predict brain age trained on 3,688 dementia-free participants of the Rotterdam Study (mean age 66 ± 11 y, 55% women). Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for age, sex, intracranial volume, GM volume, hippocampal volume, white matter hyperintensities, years of education, and <i>APOE</i> ε4 allele carriership. Additionally, we computed the attention maps, which shows which regions are important for age prediction. Logistic regression and Cox proportional hazard models showed that the age gap was significantly related to incident dementia (odds ratio [OR] = 1.11 and 95% confidence intervals [CI] = 1.05-1.16; hazard ratio [HR] = 1.11, and 95% CI = 1.06-1.15, respectively). Attention maps indicated that GM density around the amygdala and hippocampi primarily drove the age estimation. We showed that the gap between predicted and chronological brain age is a biomarker, complimentary to those that are known, associated with risk of dementia, and could possibly be used for early-stage dementia risk screening.
Effect of detector energy response on image quality of myocardial perfusion SPECT (2008)

The goal of this study was to evaluate the effect of the detector energy response on the quality of <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">99m</sup> Tc myocardial perfusion SPECT images. A Data Spectrum torso phantom was prepared to model the low-dose rest portion of a standard one-day myocardial perfusion protocol. Projection data were acquired with a recently developed Ultra-Fast Cardiac SPECT System (UFC, GE Healthcare). UFC utilizes an array of CZT detector modules and pinhole collimators. A point source in air was used to measure the <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">99m</sup> Tc spectrum in CZT. In addition to acquiring emission data, the phantom was scanned with high resolution CT and converted into a 3D model for the SimSET Monte Carlo simulation package, which was then used to generate photon history files. We developed a collimator-detector response module that operates on the SimSET photon history files. This module performs multi-pinhole collimation followed by a stochastic energy blurring operation and generates projection data. The simulated CZT detector response was derived from a measured spectrum, and ideal energy response served as reference. Simulation results were compared to actual torso phantom acquisitions. Components of the resulting projection data (amount of primary and scattered photons) and reconstructed slices were compared. For fixed energy acceptance windows, the asymmetric CZT energy response shape leads to a 30% reduction of the scatter component in measured data and contributes to superior reconstructed image quality.
Measurement of geometrical dimensions using scanning electron microscopy (1999)

In this paper, in-process measurement method of geometrical dimensions of fine patterns using the principle of stereoscopy and digital image processing techniques is presented. We have applied this measurement method to sub-micrometer patterns with variable shapes in fabrication steps. Then, we have verified that an accuracy of 0.063 μm and a repeatability of 0.14 μm in depth measurements of hole patterns with a sharp side wall angle, an accuracy of 0.75° and a repeatability of 0.53° in measurements of a taper angle of photoresist patterns were achieved.
Image Schemas and Conceptual Dependency Primitives: A Comparison (2017)

A major challenge in natural language understanding research in artificial intelligence (AI) has been and still is the grounding of symbols in a representation that allows for rich semantic interpretation, inference, and deduction. Across cognitive linguistics and other disciplines, a number of principled methods for meaning representation of natural language have been proposed that aim to emulate capacities of human cognition. However, little cross-fertilization among those methods has taken place. A joint effort of human-level meaning representation from AI research and from cognitive linguistics holds the potential of contributing new insights to this profound challenge. To this end, this paper presents a first comparison of image schemas to an AI meaning representation system called Conceptual Dependency (CD). Restricting our study to the domain of physical and spatial conceptual primitives, we find connections and mappings from a set of action primitives in CD to a remarkably similar set of image schemas. We also discuss important implications of this connection, from formalizing image schemas to improving meaning representation systems in AI.
A novel fast current - control method for the back- to-back converters (2005)

This paper presents a novel fast current-control method for the back-to-back converter. In this paper, two methods which are used to produce the reference value during the dynamic period are introduced in order to get fast dynamic response. Simulation and experiment show the feasibility and the conspicuous advantage of the methods.
Systematic dose‐extension of octreotide LAR: the importance of individual tailoring of treatment in patients with acromegaly (2004)

Individual tailoring of LAR administration maintains control of acromegaly, with reduced injection frequency and improved cost-effectiveness.
Detection and Mitigation of Spoofing Attacks on a Vector-Based Tracking GPS Receiver (2012)

Position solutions provided by GNSS receivers can be completely misled by spoofing attacks. Consequently detection and mitigation of spoofing signals have become one of the important topics within the GNSS community. Some recently published work has addressed spoofing attack on tracking receivers. The work has mostly focused on signal quality monitoring (SQM) techniques to detect spoofing and authentic signals interaction. SQM methods can effectively detect the spoofing correlation peak that is approaching the authentic signal. However, they are not applicable in cases where spoofing attack does not affect the shape of the correlation peak. This situation happens when a spoofer and authentic signals are almost aligned together. This paper provides an analytical approach to investigate the interaction between the authentic and the spoofing correlation peaks during spoofing attacks. Then, a spoofing detection technique based on amplitude analysis of different (namely very early (VE), early (E), prompt (P), late (L) and very late (VL)) correlator branches is proposed. The proposed spoofing detection technique continuously checks the distribution of each correlator output. Spoofing attack is detected if this distribution considerably deviates from that of the authentic signal. A vector based tracking receiver structure has been also employed to bridge the authentic signal outage during the spoofing attack. Data collection has been performed using the simulated spoofing attack by Spirent hardware simulator. Data processing results verify that the proposed spoofing detection and mitigation based on vector based (VB) receiver structure techniques perform well in real world scenarios.
Retinitis pigmentosa and allied conditions today: a paradigm of translational research (2010)

Monogenic human retinal dystrophies are a group of disorders characterized by progressive loss of photoreceptor cells leading to visual handicap. Retinitis pigmentosa is a type of retinal dystrophy where degeneration of rod photoreceptors occurs at the early stages. At present, there are no available effective therapies to maintain or improve vision in patients affected with retinitis pigmentosa, but post-genomic studies are allowing the development of potential therapeutic approaches. This review summarizes current knowledge on genes that have been identified to be responsible for retinitis pigmentosa, the involvement of these genes in the different forms of the disorder, the role of the proteins encoded by these genes in retinal function, the utility of genotyping, and current efforts to develop novel therapies.
An Epizootic of Vibriosis in Chinook Salmon (1969)

Vibrio anguillarum was identified as the causal organism of an epizootic of vibriosis in juvenile chinook salmon (Oncorhynchus tshawytscha) reared in a salt-water impoundment on the Oregon coast.
Evolving cellular automata to model fluid flow in porous media (2003)

Fluid flow in porous media is a dynamic process that is traditionally modeled using PDE (partial differential equations). In this approach, physical properties related to fluid flow are inferred from rock sample data. However, due to the limitations posed in the sample data (sparseness and noise), this method often yields inaccurate results. Consequently, production information is normally used to improve the accuracy of property estimation. This style of modeling is equivalent to solving inverse problems. We propose using a genetic algorithm (GA) as an inverse method to model fluid flow in a pore network cellular automaton (CA). This GA evolves the CA to produce specified flow dynamic responses. We apply this method to a rock sample data set. The results are presented and discussed. Additionally, the prospect of building the pore network CA machine is discussed.
The Costs of The Costs of Accidents (2005)

Guido Calabresi's The Costs of Accidents is unquestionably the most important book written in tort theory during the past fifty years. Much of what has been written since the book's publication either extends Calabresi's insights or reacts critically to them; some essays do a bit of both. Its lessons are by now so absorbed as to constitute part of the common understanding of the subject. The Costs of Accidents not only provides the intellectual framework within which the current debate occurs, but the language in which it is expressed as well. In time, the expression "cheapest cost avoider" will no doubt find its way into the Italian translation of the Oxford English Dictionary and may even appear someday as an entry in the Authorized Version. The Costs of Accidents has redefined both tort law and tort theory–often, but not always, for the betterment of each.
Proximity-Based Security Techniques for Mobile Users in Wireless Networks (2013)

In this paper, we propose a privacy-preserving proximity-based security system for location-based services in wireless networks, without requiring any pre-shared secret, trusted authority, or public key infrastructure. In this system, the proximity-based authentication and session key establishment are implemented based on spatial temporal location tags. Incorporating the unique physical features of the signals sent from multiple ambient radio sources, the location tags cannot be easily forged by attackers. More specifically, each radio client builds a public location tag according to the received signal strength indicators, sequence numbers, and media access control (MAC) addresses of the ambient packets. Each client also keeps a secret location tag that consists of the packet arrival time information to generate the session keys. As clients never disclose their secret location tags, this system is robust against eavesdroppers and spoofers outside the proximity range. The system improves the authentication accuracy by introducing a nonparametric Bayesian method called infinite Gaussian mixture model in the proximity test and provides flexible proximity range control by taking into account multiple physical-layer features of various ambient radio sources. Moreover, the session key establishment strategy significantly increases the key generation rate by exploiting the packet arrival time of the ambient signals. The authentication accuracy and key generation rate are evaluated via experiments using laptops in typical indoor environments.
Psorospermin, A New Antileukemic Xanthone From Psorospermum febrifugum (1980)

An ethanolic extract of Psorospermum febrifugum was fractionated with antileukemic activity in vivo in the P388 lymphocytic leukemia in mice and in vitro in the KB cell culture system used as a guide. The new antileukemic xanthone psorospermin 1 was isolated, and its structure was elucidated. The chlorohydrin of O-methylpsorospermin 2 was also isolated after treatment of the fraction containing psorospermin chlorohydrin 6 with diazomethane. Psorospermin 1 was demonstrated to have significant antitumor activity in the P388 in vivo system as well as cytotoxicity against the KB in vitro system.
The Economic Feasibility of a New Jersey Fresh Tomato Packing Facility: A Stochastic Simulation Approach (1995)

This study evaluates the economic feasibility of establishing a packing house for the New Jersey Tomato Council Cooperative Association. Several scenarios were evaluated using a comprehensive firm-level, dynamic, stochastic, multiple-year, capital-budgeting computer model. Results indicate that the packing house would have difficulty sustaining itself if it packed tomatoes only during the three months a year that local tomatoes are produced. Economic performance of the packing house improved, however, when additional tomatoes were repacked from another supplier during the months that tomatoes are not produced in New Jersey.