gebhart/patrepeval huggingface dataset:
Applications of Artificial Intelligence Paradigms to Decision Support in Real-Time Traffic Management (2006)

Decision support for real-time traffic management is a critical component for the success of intelligent transportation systems. Theoretically, microscopic simulation models can be used to evaluate traffic management strategies in real time before a course of action is recommended. However, the problem is that the strategies would have to be evaluated in real time; this might not be computationally feasible for large-scale networks and complex simulation models. To address this problem, two artificial intelligence (AI) paradigms—support vector regression (SVR) and case-based reasoning (CBR)—are presented as alternatives to the simulation models as a decision support tool. Specifically, prototype SVR and CBR decision support tools are developed and used to evaluate the likely impacts of implementing diversion strategies in response to incidents on a highway network in Anderson, South Carolina. The performances of the two prototypes are then evaluated by a comparison of their predictions of traffic conditions with those obtained from VISSIM, a microscopic simulation model. Although the prototype systems’ predictions were comparable to those obtained by simulation, their run times were only fractions of the time required by the simulation model. Moreover, SVR performance is superior to that of CBR for most cases considered. The study results provide motivation for consideration of the proposed AI paradigms as potential decision support tools for real-time transportation management applications.
Spherical Triboelectric Nanogenerators Based on Spring‐Assisted Multilayered Structure for Efficient Water Wave Energy Harvesting (2018)

Abstract Making use of water wave energy at large is one of the most attractive, low‐carbon, and renewable ways to generate electric power. The emergence of triboelectric nanogenerator (TENG) provides a new approach for effectively harvesting such low‐frequency, irregular, and “random” energy. In this work, a TENG array consisting of spherical TENG units based on spring‐assisted multilayered structure is devised to scavenge water wave energy. The introduction of spring structure enhances the output performance of the spherical TENG by transforming low‐frequency water wave motions into high‐frequency vibrations, while the multilayered structure increases the space utilization, leading to a higher output of a spherical unit. Owing to its unique structure, the output current of one spherical TENG unit could reach 120 µA, which is two orders of magnitude larger than that of previous rolling spherical TENG, and a maximum output power up to 7.96 mW is realized as triggered by the water waves. The TENG array fabricated by integrating four units is demonstrated to successfully drive dozens of light‐emitting diodes and power an electronic thermometer. This study provides a new type of TENG device with improved performance toward large‐scale blue energy harvesting from the water waves.
Improving deception in honeynet: Through data manipulation (2014)

Emergence of honeynet, which is a network of honeypots, has changed the phase of internet security and information gathering about intruders. In improving deception of the honeynet which in turn increases the workload of attackers, most honeynet deployments are geared towards improving on the deception deal by using MAC addresses, IP addresses and protocols on host machine. Attackers gain access to networks with different motives, this work focuses on attackers who aim for data theft, data insertion, data deletion and data modification This paper also includes data manipulation, a new component introduced by the users of these hosts. This data content contributes to improving deception by dynamically sorting, shuffling, updating, manipulating and mapping each last modified state of the data to a unique MAC/IP addresses of an intruder machine that modified the system.
Possible Role of Dimethylarsinous Acid in Dimethylarsinic Acid-Induced Urothelial Toxicity and Regeneration in the Rat (2002)

Dimethylarsinic acid (DMA(V)) is carcinogenic to the rat urinary bladder when administered at high doses in the diet or drinking water. At a dietary dose of 100 ppm (microg/g), it produces cytotoxicity within 6 h and increased proliferation (hyperplasia) by 7 days of administration. We hypothesize that formation of the reactive organic intermediate dimethylarsinous acid (DMA(III)) is involved in the induction of the cytotoxicity. To evaluate the possibility that DMA(V) administration produces urothelial toxicity and regeneration by the formation of trivalent arsenicals, 2,3-dimercaptopropane-1-sulfonic acid (DMPS, 5600 ppm), a chelator of trivalent arsenicals, was co-administered with DMA(V) (100 ppm) for 2 weeks to groups of female Fischer F344 rats. Based on light and scanning electron microscopy, and bromodeoxyuridine labeling index, DMA(V) produced cytotoxicity and regenerative hyperplasia of the urothelium which was inhibited by co-administration with DMPS. The major forms of arsenic in the 24-h urine of rats administered DMA(V) were high concentrations of DMA(V) (66.4 +/- 2.7 microM) itself and the pentavalent organic arsenical trimethylarsine oxide (TMAO) (73.2 +/- 9.5 microM). Co-administration with DMPS led to an increase in DMA(V) (507 +/- 31 microM) with a decrease in TMAO (2.8 +/- 0.4 microM) excretion. The formation of TMAO from DMA(V) mechanistically suggests formation of the intermediate trivalent metabolite, DMA(III). In a second experiment evaluating fresh void urines collected on study days 1, 71, and 175, we detected DMA(III) in the urine of DMA(V) and DMA(V) plus DMPS-treated rats at approximately micromolar concentrations. Using rat (MYP3) and human (1T1) urothelial cells, cytotoxicity for trivalent arsenicals, sodium arsenite, monomethylarsonous acid (MMA(III)), and DMA(III) was demonstrated at 0.4-4.8 microM concentrations, whereas MMA(V), DMA(V), and TMAO were cytotoxic at millimolar concentrations. The presence of DMA(III) at micromolar concentrations in the urine of rats fed 100 ppm DMA(V) suggests that DMA(III) produced in vivo may be involved in the toxic effects in the rat urinary bladder after dietary administration of DMA(V).
Characterization of Kupffer cells in livers of developing mice (2011)

Kupffer cells of the developing mouse liver appear quite similar to those of other mammalian species, confirming that the mouse presents a useful animal model for studies of liver macrophage developmental structure and function.
HEXID2: A Low-Power, Low-Noise Pixel Readout ASIC for Hyperspectral Energy-Resolving X-Ray Imaging Detectors (2017)

We present a low-power, low-noise prototype pixel readout application specific integrated circuit (ASIC) for hyperspectral energy-resolving X-ray imaging detectors. The ASIC provides 16-by-16 channels to read out positive and negative charges from 16-by-16 hexagonal silicon or CZT detector arrays, at a pitch size of 250 μm, to achieve good spatial resolution and the ability to record the energy of a detected photon as well as its position. The readout is done by bumpbonding the anodes to the inputs of the ASIC. Each channel of the ASIC provides low-noise charge amplification, high-order shaping with baseline stabilization, discrimination, extraction of amplitude (with neighbour channels), multiplexing, and dissipates ~0.6 mW. A smart readout of the triggered pixel and its adjacent six pixels in the hexagonal configuration allows reconstruction of events with charge sharing correction, and can be used to estimate the depth of the photon interaction and to suppress background events. The target equivalent noise charge (ENC) is ~10 electrons for silicon detector pixel and ~15 electrons for CZT detector pixel.
RedTell: an AI tool for interpretable analysis of red blood cell morphology (2023)

<b>Introduction:</b> Hematologists analyze microscopic images of red blood cells to study their morphology and functionality, detect disorders and search for drugs. However, accurate analysis of a large number of red blood cells needs automated computational approaches that rely on annotated datasets, expensive computational resources, and computer science expertise. We introduce RedTell, an AI tool for the interpretable analysis of red blood cell morphology comprising four single-cell modules: segmentation, feature extraction, assistance in data annotation, and classification. <b>Methods:</b> Cell segmentation is performed by a trained Mask R-CNN working robustly on a wide range of datasets requiring no or minimum fine-tuning. Over 130 features that are regularly used in research are extracted for every detected red blood cell. If required, users can train task-specific, highly accurate decision tree-based classifiers to categorize cells, requiring a minimal number of annotations and providing interpretable feature importance. <b>Results:</b> We demonstrate RedTell's applicability and power in three case studies. In the first case study we analyze the difference of the extracted features between the cells coming from patients suffering from different diseases, in the second study we use RedTell to analyze the control samples and use the extracted features to classify cells into echinocytes, discocytes and stomatocytes and finally in the last use case we distinguish sickle cells in sickle cell disease patients. <b>Discussion:</b> We believe that RedTell can accelerate and standardize red blood cell research and help gain new insights into mechanisms, diagnosis, and treatment of red blood cell associated disorders.
Self-organized Cell Assembly Sequences in the Hippocampus (2008)

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The isoengine: realisation of a high-efficiency power cycle based on isothermal compression (2005)

A novel high-efficiency internal combustion engine for power generation and direct-drive applications is being developed. Distillate-fuelled power plants in units of 7 MW electrical output are predicted to reach a net electrical efficiency of 60%. An efficiency of 58% is targeted for the gas-fired version. This compares with a net electrical efficiency of about 45% for advanced reciprocating engines of similar output but conventional design, and represents a step change in the efficiency of distributed power plant. Besides distillate oil and natural gas, the engine will be able to use suitable biofuels for efficient power generation. A 3 MW prototype engine using the full-scale engine geometry has been built to confirm the performance of the isoengine cycle. A partnership agreement has been signed by RWE Innogy and Mitsui Engineering and Shipbuilding for the future testing and development of the engine.
Influence of the R22H variant of macrophage inflammatory protein 1β/Lag-1 in HIV-1 survival (2005)

The chemokine macrophage inflammatory protein 1beta/CCL4, ligand of the major HIV co-receptor CCR5, is encoded by two genes, Act-2 and Lag-1. Our work focused on R22H, a variant of Lag-1 located near the N-loop, in the 310 turn, a domain essential for interacting with CCR5. We observed that HIV-1-infected patients from the SEROCO cohort, bearing the R22H variant either at the homozygous or heterozygous state, exhibit a worse global survival compared with wild-type homozygous individuals.
An efficient detection of flooding attacks to Internet Threat Monitors (ITM) using entropy variations under low traffic (2012)

The Internet Threat Monitoring (ITM),is a globally scoped Internet monitoring system whose goal is to measure, detect, characterize, and track threats such as distribute denial of service(DDoS) attacks and worms. To block the monitoring system in the internet the attackers are targeted the ITM system. In this paper we address flooding attack against ITM system in which the attacker attempt to exhaust the network and ITM's resources, such as network bandwidth, computing power, or operating system data structures by sending the malicious traffic. We propose an information-theoretic frame work that models the flooding attacks using Botnet on ITM. Based on this model we generalize the flooding attacks and propose an effective attack detection and Traceback using Entropy by calculating the entropy variations between normal and attack traffic.
Crushing Analysis of Square Tube With Fluid and Foam-Filled Cellular Core (2022)

Abstract Passenger vehicles are constantly being redesigned to maximize occupant safety in the event of a collision. Changes and improvements to automobiles have resulted in a significant amount of energy absorption capability through the vehicle chassis. Axial crushing members are often deployed in vehicle front end and side chassis structures and are designed to absorb a maximum amount of energy before complete deformation. These structures experience a series of progressive folding during axial deformation resulting in moderate and relatively constant force throughout the crushing behavior. To increase the performance of these structures, different cross-sectional shapes and core materials have been investigated. The present study investigates the addition of graded cellular core structure with zones of crushable foam and fluid inserts within the cell voids. The addition of crushable foam material aimed to provide stability to the crushing behavior of the structure. The incompressible nature of the fluid insert provided sections of increased structural strength and a more global crushing response. The finite element approach was conducted using ABAQUS dynamic environment and the square crush tubes were subjected to dynamic axial crushing. Foam and fluid addition provided additional energy absorption while creating a more global deformation response.
Abstract WP8: Blood Pressure And EVT Outcomes By The Baseline Perfusion And Recanalization Timing (2022)

Introduction: Leptomeningeal collaterals help maintain cerebral perfusion after the large vessel occlusion (LVO), potentially regulated by systemic blood pressure (BP). We hypothesized that the association between BP and endovascular treatment (EVT) outcomes would differ by the baseline perfusions status and before and after recanalization. Method: From a prospective registry, we identified anterior circulation LVO patients who received EVT ≤24 hours after their onset, had baseline perfusion, and achieved post-EVT mTICI ≥2b. BPs were measured from arrival at 5-minute intervals in the ER and during the procedure. Systolic BPs (SBP) up to 24 hours after EVT were summarized as dropmax (the maximal decrement over two consecutive measurements), incmax (the maximal increment), mean, coefficient of variation, and standard deviation. Baseline perfusion images were quantified using Olea Sphere. Infarct proportion was defined as the volume of final infarct on DWI within the volume of Tmax&gt;6 sec. Significant hemorrhage included PH2 or HBC class 3. 3-month mRS was prospectively collected. Result: A total of 388 LVO patients were included. Mean SBP at arrival was 153 ± 42 mm Hg; the average count of BP measurements was 47 ± 17 per patient.In the adequate baseline perfusion group, i.e., hypoperfusion intensity ratio (HIR) &lt;0.5, SBP parameters were better associated with infarct proportion and functional outcome before the recanalization period; weaker associations were noted after recanalization. In the poor baseline perfusion group, i.e., HIR ≥0.5, SBP parameters before recanalization were partially associated with the infarct proportion but not functional status. No association between SBP parameters and significant hemorrhage was noted. (estimates in Table) Conclusion: Association between BP and patient outcomes differs by baseline perfusion status and before and after recanalization. BP management during the peri-EVT period may therefore need to be individualized.
Excessive vascular smooth muscle and macrophage proliferation underlies impaired coronary collateral growth in the metabolic syndrome (2013)

Rationale Coronary collateral growth (CCG) is impaired in the metabolic syndrome. It is thought that inadequate cell proliferation is a causative factor. Pro‐angiogenic growth factors (GFs) stimulate cell proliferation. Metabolic syndrome patients and animal models exhibit elevated GF levels, but administration of GFs does not promote CCG in the metabolic syndrome. Objective To determine whether temporally inappropriate excessive cell proliferation underlies impaired CCG in the metabolic syndrome. Methods and Results Normal (SD) and metabolic syndrome (JCR) rats underwent transient, repetitive coronary artery occlusion (RI). We have previously shown that CCG was maximal at day 9 of RI in SD rats but did not occur in JCR rats. Cell proliferation was evaluated by immunohistochemistry (PCNA, Ki‐67) and Western blotting (PCNA). The increase in cell proliferation was transient in SD but greater and sustained in JCR rats. Assessment of cell cycle progression confirmed early and transient cell proliferation in SD vs. sustained proliferation in JCR rats. This was associated with accumulation of proliferating cells in the lumen of small arterioles in JCR rats, which failed to undergo outward expansion. Conclusions Excessive cell proliferation in the later stages of collateral remodeling underlies impaired CCG in the metabolic syndrome. R01 HL093052
Mitigation of wing flexure for airborne direction-finding applications (2002)

Calibration errors are the dominant error source for direction finding (DF) from airborne platforms. Calibration of the array manifold is done with the wings in an unknown position. Wing movements during flight perturbs the array manifold from its calibrated value, causing errors in the direction finding. We present a direction finding algorithm that compensates for variations in wing flexure. The algorithm relies on a physically motivated model that captures the gross behavior of the manifold perturbations. The model has been validated using experiments on a model aircraft in an anechoic chamber. The structure of the model can be exploited in estimation schemes such as weighted subspace fitting (WSF), leading to improved DF accuracy. With the correct model parameters, the effect of the manifold perturbation is, in fact, fully neutralized. The properties of the new scheme are demonstrated through analysis and simulation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Physics-based methods for studying protein-ligand interactions. (2007)

The accurate prediction of relative or absolute ligand-binding affinities is challenging in both theoretical and practical aspects. However, with the aid of advanced computing power and sophisticated methodology development, physics-based free-energy calculations, which can be used to predict ligand-binding affinities, have become increasingly utilized in the field of structure-based drug design. This review summarizes recent progress made in developing and applying physics-based methods to studying protein-ligand interactions, focusing on methods using molecular mechanics force fields. Applications of these methods include predicting ligand binding poses, enriching binders in virtual screening, and calculating relative and absolute binding free energies. Future directions for further improving current physics-based methods are also discussed.
Bluetooth and sensor networks (2003)

The current generation of sensor nodes rely on commodity components. The choice of the radio is particularly important as it impacts not only energy consumption but also software design (e.g., network self-assembly, multihop routing and in-network processing). Bluetooth is one of the most popular commodity radios for wireless devices. As a representative of the frequency hopping spread spectrum radios, it is a natural alternative to broadcast radios in the context of sensor networks. The question is whether Bluetooth can be a viable alternative in practice. In this paper, we report our experience using Bluetooth for the sensor network regime. We describe our tiny Bluetooth stack that allows TinyOS applications to run on Bluetooth-based sensor nodes, we present a multihop network assembly procedure that leverages Bluetooth's device discovery protocol, and we discuss how Bluetooth favorably impacts in-network query processing. Our results show that despite obvious limitations the Bluetooth sensor nodes we studied exhibit interesting properties, such as a good energy per bit sent ratio. This reality check underlies the limitations and some promises of Bluetooth for the sensor network regime.
A Novel Hybrid Systems Framework For Leader-Following Consensus of Multi-Agent Systems (2019)

In this paper, leader-following consensus problem is addressed for general linear multi-agent systems with communication delays. A novel hybrid event-triggering mechanism is developed without requiring continuous communication among follower agents. The multi-agent systems are firstly described as a closed-loop system with both flow dynamics and jump dynamics. Then, by introducing several auxiliary variables, a hybrid model of the multi-agent systems is constructed under hybrid systems framework. Based on this hybrid model, we present how to construct Lypaunov function, and the decentralized event-triggering conditions design is also developed. An application example is provided to show the effectiveness of the proposed approach.
Auction mechanism for spectrum allocation and profit sharing (2009)

We examine the problem of designing an auction mechanism for dynamic spectrum sharing when there are multiple sellers and multiple buyers. First, we study the interaction among homogeneous buyers of spectrum as a noncooperative game and show the existence of a symmetric mixed-strategy Nash equilibrium (SMSNE). Second, we prove that there exists an incentive for risk neutral sellers of the spectrum to cooperate to maximize their expected profits at the SMSNEs of buyers' noncooperative game. Finally, we model the interaction among the sellers as a cooperative game and demonstrate that the core of the cooperative game is nonempty. This indicates that there exists a way for the sellers to share the profits in a such manner that no subset of sellers will deviate from cooperating with the remaining sellers.
ChemInform Abstract: Interactions of Chemical Species with Acid Sites in Zeolites (1997)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
Multiobjective Optimization of SAR Reconstruction on Hybrid Multicore Systems (2020)

Hybrid multicore processors (HMPs) are poised to dominate the landscape of the next generation of computing on the desktop as well as on exascale systems. HMPs consist of general purpose CPU cores along with specialized coprocessors and can provide high performance for a wide spectrum of applications at significantly lower energy requirements per floating-point operations per second (FLOP). In this article, we develop parallel algorithms and software for constructing multiresolution synthetic aperture radar images on HMPs. We develop several load balancing algorithms for optimizing time performance and energy on HMPs. We also present a systematic approach for deriving the energy-time performance tradeoffs on HMPs in the presence of dynamic voltage frequency scaling. Pareto-optimal curves are presented on a system consisting of 24 traditional cores and a GPU.