gebhart/patrepeval huggingface dataset:
Towards a Driver Monitoring System for Estimating Driver Situational Awareness (2019)

Autonomous vehicle technology is rapidly developing but the current state-of-the-art still has limitations and requires frequent human intervention. However, handovers from an autonomous vehicle to a human driver are challenging because a human operator may be unaware of the vehicle surroundings during a handover which can lead to dangerous driving outcomes. There is presently an urgent need to develop advanced driver-assistance systems capable of monitoring driver situational awareness within an autonomous vehicle and intelligently handing-over control to a human driver in emergency situations. Towards this goal, in this paper we present the development and evaluation of a vision-based system that identifies visual cues of a driver's situational awareness including their: head pose, eye pupil position, average head movement rate and visual focus of attention.
CHRONIC BLOCKADE OF CD28-B7-MEDIATED T-CELL COSTIMULATION BY CTLA4Ig REDUCES INTIMAL THICKENING IN MHC CLASS I AND II INCOMPATIBLE MOUSE HEART ALLOGRAFTS1,2 (1997)

In this model with MHC class I and II disparities, day 2 murine CTLA4Ig treatment improved survival and function but did not ameliorate vascular thickening. However, ongoing blockade of CD28-B7 costimulation conferred protection against vascular thickening.
Block based Rate-Distortion analysis for quality improvement of synthesized views (2010)

We present a preliminary study on the Rate-Distortion (RD) gain that can be achieved applying RD optimization techniques in a multiview plus depth encoder. We consider the use of Multiview Video Coding (MVC) for both, color and depth sequences, and evaluate the improvement that can be obtained allowing a quantization parameter (QP) assignment on a macroblock basis compared to the use of a fixed QP for the whole sequence. The optimization criterion is the minimization of the distortion of the synthesized views generated at the receiver. Our motivation for this criterion is to capture the impact of depth coding according to its final purpose: the generation of virtual views. Since a unique objective quality metric for view synthesis artifacts evaluation has not been set yet, the performance of several algorithms for quality evaluation of the target synthesized view have been compared. Beyond obtaining a better RD performance, as could be expected, results also show that optimized synthesized views achieve absolute lower distortion values than the best result of the approach that uses a fixed QP for the whole sequence.
Abstract PL01-01: Advances in functional cancer genomics (2011)

Abstract Recent advances in genomics now make it possible to consider enumerating all of the genetic lesions in specific cancers. While these approaches will yield critical information regarding the identify, number, and types of alterations found in human tumors, a complementary approach to decipher the molecular basis of malignant transformation depends upon the application of genome scale tools to annotate the function of genes involved in cancer initiation and progression. Over the past several years, we have developed genome scale RNAi libraries and open reading frame expression libraries that permit a systematic evaluation of genes involved in cancer initiation and maintenance. Using these libraries, we have now performed screens in a panel of human cancer cell lines to systematically identify cancer vulnerabilities. By combining these functional approaches with information derived from mapping the structural abnormalities present in cancer genomes, we have identified several new oncogenes that contribute to cancer development. The ability to systematically manipulate gene expression at genome scale now provides opportunities to investigate the function of genes involved in cancer initiation and maintenance, which will provide a framework for therapeutic and prevention strategies. Citation Information: Cancer Prev Res 2011;4(10 Suppl):PL01-01.
Effects of Time and Compression on the Interactions of Adsorbed Polystyrene Layers in a Near-ϑ Solvent (1997)

We have investigated the effects of molecular weight, adsorption time, force-measuring rate, and repeated compression−decompression cycles (previous history) on the interactions between high molecular weight polystyrenes adsorbed on mica from dilute cyclopentane solutions under near-ϑ solvent conditions. On the first slow approach, a long-range bridging attraction, which needs several minutes to fully develop for each incremental movement of the surfaces, is found at separations below 6Rg. The interaction becomes a steep hard-wall repulsion at separations below 0.5Rg. With increasing molecular weight the thickness of the adsorbed layers increases, and the attractive bridging force on approach and adhesion on separation decreases. Self-consistent field theory underestimates the onset location and depth of the attractive minima but accurately predicts the location of the hard-wall repulsion. For shorter (nonequilibrium) adsorption times, the bridging attraction and adhesion are stronger and occur at smaller separations, consistent with incomplete coverage. If the first approach and compression are done slowly, the layers become “irreversibly” compressed and no long-range bridging attraction is observed on subsequent approaches, even after allowing the polymer layers to relax for several days.
Engineering a Metal–Organic Framework Catalyst by Using Postsynthetic Modification (2009)

MOF+PSM=Kat.: Ein hochporöses Metall-organisches Gerüst (MOF) wird mithilfe einer Postsynthesemodifikation (PSM) metalliert und in einen aktiven, robusten, wiederverwendbaren Katalysator (Kat.) überführt. Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores (2016)

To identify computer extracted imaging features for estrogen receptor (ER)-positive breast cancers on dynamic contrast enhanced (DCE)-MRI that are correlated with the low and high OncotypeDX risk categories. We collected 96 ER-positive breast lesions with low (< 18, N = 55) and high (> 30, N = 41) OncotypeDX recurrence scores. Each lesion was quantitatively characterize via 6 shape features, 3 pharmacokinetics, 4 enhancement kinetics, 4 intensity kinetics, 148 textural kinetics, 5 dynamic histogram of oriented gradient (DHoG), and 6 dynamic local binary pattern (DLBP) features. The extracted features were evaluated by a linear discriminant analysis (LDA) classifier in terms of their ability to distinguish low and high OncotypeDX risk categories. Classification performance was evaluated by area under the receiver operator characteristic curve (Az). The DHoG and DLBP achieved Az values of 0.84 and 0.80, respectively. The 6 top features identified via feature selection were subsequently combined with the LDA classifier to yield an Az of 0.87. The correlation analysis showed that DHoG (ρ = 0.85, P < 0.001) and DLBP (ρ = 0.83, P < 0.01) were significantly associated with the low and high risk classifications from the OncotypeDX assay. Our results indicated that computer extracted texture features of DCE-MRI were highly correlated with the high and low OncotypeDX risk categories for ER-positive cancers.
Markov Channel-Based Performance Analysis for Millimeter Wave Mobile Networks (2017)

A critical issue facing millimeter wave (mmWave) cellular systems is channel dynamics. MmWave signals are extremely susceptible to blocking and thus may vary rapidly with motion, orientation of the handset and local blockages. In this work, we derive a Finite State Markov Channel (FSMC) model of the mmWave channel from the statistics of ray tracing simulation data, which are based on channel measurements in an urban environment. The FSMC tracks the mutual information effective SINR (MI-ESNR), which can then be used in network simulations. The FSMC model is applied to analyze queue behavior and obtain the latency, throughput, packet error and droppage statistics for mmWave links at the MAC layer, making it useful for higher-layer analysis, as well. We evaluate the accuracy of the channel model for various model complexities and packet arrival rates and show that the model performance closely matches the empirical ray tracing data.
An accurate compensation method of distributed capacitance current in differential protection of UHV transmission line (2005)

The distributed capacitance current of UHV transmission line has a negative impact on differential current protection. Aiming at this problem, a novel accurate compensation method of capacitance current is proposed in this paper. All the factors that affect the capacitance current are taken into account by the variation of the capacitance value. The capacitance value can be calculated on line, based on which the capacitance current can be compensated accurately. Simulation results demonstrate that the proposed method is superior to the fixed compensation method.
Testing the Goodness of Model Fit in Tunable Diode Laser Absorption Tomography (2021)

Tunable diode laser absorption tomography (TDLAT) has emerged as a popular nonintrusive technique for simultaneous sensing of gas concentration and temperature by making light absorbance measurements. Major challenge of TDLAT imaging is that the measurement data is very sparse. Therefore, precise models are required to describe the measurement process (forward model) and the behavior of the gas flow properites (prior model) to get accurate reconstructions. The sparsity of the measurement data makes TDLAT very sensitive to the accuracy of the models and makes it prone to overfitting. Both the forward and prior models can have systematic errors due to several reasons. So far, substantial amount of work has been done by researchers on developing reconstruction methods and formulating models, forward and prior. Yet, there has not been significant research work done on constructing a metric for goodness of the model fit that can indicate when there is an inaccuracy in the forward or the prior model. In this paper, we present a metric for goodness of model fit that can be used to indicate if the models used in the reconstruction are inaccurate. Results show that our metric can reliably quantify the goodness of model fit for sparese data reconstruction problems such as TDLAT.
Performance Evaluation of Relay Deployment Strategies in Multi-Cell Single Frequency Networks (2010)

We investigate the impact of fixed relay station deployment in a single frequency network (SFN) using orthogonal frequency-division multiplexing (OFDM). We provide semi-analytical methods for relay-based SFN performance evaluation. Monte Carlo simulations are performed to provide numerical calculation of multi-cell network performance. The performance metric is the cumulative distribution function of the signal-to-interference-plus-noise-ratio (SINR) for different user positions in the network. Common relaying methods for two-hop amplify-and-forward (A&F) relay networks are evaluated. The impact on the SINR is compared for different relaying gains, locations and densities of relays, as well as different transmission protocols, such as full-duplex (FD) and half-duplex (HD). Overall, taking into account their different rates and physical layer performances, FD appears to outperform HD. In addition to showing the benefit of relay deployment for enhancing network performance, our simulations show that the fixed and variable gains perform equally well.
GLI2 inhibition abrogates human leukemia stem cell dormancy (2015)

In summary, while GLI2, forms part of a core HH pathway transcriptional regulatory network that promotes human myeloid leukemic progression and dormant LSC generation, selective inhibition with PF-04449913 reduces the dormant LSC burden thereby providing a strong rationale for clinical trials predicated on SMO inhibition in combination with TKIs or chemotherapeutic agents with the ultimate aim of obviating leukemic therapeutic resistance, persistence and progression.
Localized Supervised Metric Learning on Temporal Physiological Data (2010)

Effective patient similarity assessment is important for clinical decision support. It enables the capture of past experience as manifested in the collective longitudinal medical records of patients to help clinicians assess the likely outcomes resulting from their decisions and actions. However, it is challenging to devise a patient similarity metric that is clinically relevant and semantically sound. Patient similarity is highly context sensitive: it depends on factors such as the disease, the particular stage of the disease, and co-morbidities. One way to discern the semantics in a particular context is to take advantage of physicians' expert knowledge as reflected in labels assigned to some patients. In this paper we present a method that leverages localized supervised metric learning to effectively incorporate such expert knowledge to arrive at semantically sound patient similarity measures. Experiments using data obtained from the MIMIC II database demonstrate the effectiveness of this approach.
Angle–of–Arrival (AoA) Factorization in Multipath Channels (2021)

This paper considers the problem of estimating K angle of arrivals (AoA) using an array of M > K microphones. We assume the source signal is human voice, hence unknown to the receiver. Moreover, the signal components that arrive over K spatial paths are strongly correlated since they are delayed copies of the same source signal. Past works have successfully extracted the AoA of the direct path, or have assumed specific types of signals/channels to derive the subsequent (multipath) AoAs. Our method builds on the core observation that signals from multiple AoAs embed predictable delay-structures in them, which can be factorized through iterative alignment and cancellation. Simulation results show median AoA errors of < 4° for the first 3 AoAs. Real-world measurements, from a circular microphone array similar to Amazon Echo, show modest degradations. We believe the ability to infer even K = 3 AoAs can be helpful to various sensing and localization applications.
2,6,9-Trioxabicyclo[3.3.1]nona-3,7-dienes and 2,4,6,8-Tetraoxaadamantanes: Novel Chiral Spacer Units in Macrocyclic Polyethers (2002)

The unusual chiral heterocyclic systems, trioxabicyclo[3.3.1]nona-3,7-dienes ("bridged bisdioxines"), are incorporated as novel spacer molecules into macrocyclic polyether ring systems of various sizes (8, 9 as well as 11-15) by cyclocondensation reaction of the bisacid chloride 4b or bisesters 6,7 and 10, with several ethylene glycols. The 2:2 macrocycles 12-14 are obtained in approximately 50:50 mixtures of diastereomers. These conclusions are mainly based on HPLC data presented in Table I as well as X-ray analyses of (1R,5R)-8c (space group Pbca, a =10.163(3) Å, b =18.999(4) Å, c =36.187(10) Å, V =6987(3) Å3 , Z =8, d calc =1.218 g cmm 3, 6974 reflections, R =0.0553), meso/rac-11 (space group P1 ¥ , a =10.472(5) Å, b=16.390(5) Å, c =17.211(5) Å, f =98.69(2)°, g =93.04(2)°, n =98.52(2)°, V =2879.3(18) Å 3 , Z =2, d calc =1.173 g cm m 3 , 11,162 reflections, R =0.0945) and meso-12 (space group P21/c, a =9.927(2), b =18.166(3), c =17.820(3) Å, g =96.590(10)°, V =3192.3(10) Å 3 , Z =4, D c =1.109 g cmm 3, 3490 reflections, R =0.0646). The 1:1 macrocycles 8b,c are also formed by intramolecular transesterification of the open-chain bisesters 7b,c and their formation is favored by the use of metal ions as templates. The bridged bisdioxine moieties in 8b and 12 are converted into the corresponding chiral tetraoxaadamantane spacers to afford macrocycles 16 and 17. Preliminary metal ion complexation studies with selected species (8c, 11-14) were also performed.
High-Performance Row Pattern Recognition Using Joins (2023)

The SQL standard introduced MATCH_RECOGNIZE in 2016 for row pattern recognition. Since then, MATCH_RECOGNIZE has been supported by several leading relation systems, they implemented this function using Non-Deterministic Finite Automaton (NFA). While NFA is suitable for pattern recognition in streaming scenarios, the current uses of NFA by the relational systems for historical data analysis scenarios overlook important optimization opportunities. We propose a new approach to use Join to speed up row pattern recognition in historical analysis scenarios for relational systems. Implemented as a logical plan rewrite rule, the new approach first filters the input relation to MATCH_RECOGNIZE using Joins constructed based on a subset of symbols taken from the PATTERN expression, then run the NFA-based MATCH_RECOGNIZE on the filtered rows, reducing the net cost. The rule also includes a specialized cardinality model for the Joins and a cost model for the NFA-based MATCH_RECOGNIZE operator for choosing an appropriate symbol set. The rewrite rule is applicable when the query pattern's definition is self-contained and either the input table has no duplicates or there is a window condition. Applying the rewrite rule to a query benchmark with 1,800 queries spanning over 6 patterns and 3 pattern definitions, we observed median speedups of 5.4X on Trino (v373 with ORC files on Hive), 57.5X on SQL Server (2019) using column store and 41.6X on row store.
Characterization of Three Amino-Functionalized Surfaces and Evaluation of Antibody Immobilization for the Multiplex Detection of Tumor Markers Involved in Colorectal Cancer (2013)

Antibody microarrays are powerful and high-throughput tools for screening and identifying tumor markers from small sample volumes of only a few microliters. Optimization of surface chemistry and spotting conditions are crucial parameters to enhance antibodies' immobilization efficiency and to maintain their biological activity. Here, we report the implementation of an antibody microarray for the detection of tumor markers involved in colorectal cancer. Three-dimensional microstructured glass slides were functionalized with three different aminated molecules ((3-aminopropyl)dimethylethoxysilane (APDMES), Jeffamine, and chitosan) varying in their chain length, their amine density, and their hydrophilic/hydrophobic balance. The physicochemical properties of the resulting surfaces were characterized. Antibody immobilization efficiency through physical interaction was studied as a function of surface properties as well as a function of the immobilization conditions. The results show that surface energy, steric hindrance, and pH of spotting buffer have great effects on protein immobilization. Under optimal conditions, biological activities of four immobilized antitumor marker antibodies were evaluated in multiplex immunoassay for the detection of the corresponding tumor markers. Results indicated that the chitosan functionalized surface displayed the highest binding capacity and allowed to retain maximal biological activity of the four tested antibody/antigen systems. Thus, we successfully demonstrated the application of amino-based surface modification for antibody microarrays to efficiently detect tumor markers.
Spatial analyses of glaucomatous visual fields; a comparison with traditional visual field indices (1992)

Interpretation of numeric automated threshold visual field results is often difficult. A large amount of data is obtained for every single field tested. Various approaches to summarize this data have been suggested, most commonly the mean and standard deviation of departures from age-corrected normal threshold values. These visual field indices differ substantially from subjective field interpretation where spatial relationships are important. We have previously devised two methods for automated field interpretation which take spatial information into account--regional up-down comparisons and arcuate cluster analysis. We now studied the merits of using these new spatial methods and compared them to traditional visual field indices for discrimination between normal and glaucomatous field results. Central static 30 degree field results in 101 eyes of 101 normal subjects and 101 eyes of 101 patients with glaucoma were discriminated using logistic regression analysis. The best field classification was obtained with a spatial visual field model combining up-down differences and arcuate clusters. The advantages of the spatial model were confirmed in an independent material of 163 eyes of 163 normal subjects and 76 eyes of 76 patients with glaucoma where eyes with large field defects had been removed. In this material the spatial model gave 87% sensitivity and 83% specificity while the best non-spatial model gave 82% sensitivity and 80% specificity. Visual field interpretation in glaucoma may be significantly enhanced if detection is focused on circumscribed field loss rather than on averages of differential light sensitivities and similar indices which do not take spatial relationships into consideration.
Estimating Multiple Frequency-Hopping Signal Parameters via Sparse Linear Regression (2010)

Frequency hopping (FH) signals have well-documented merits for commercial and military applications due to their near-far resistance and robustness to jamming. Estimating FH signal parameters (e.g., hopping instants, carriers, and amplitudes) is an important and challenging task, but optimum estimation incurs an unrealistic computational burden. The spectrogram has long been the starting non-parametric estimator in this context, followed by line spectra refinements. The problem is that hop timing estimates derived from the spectrogram are coarse and unreliable, thus severely limiting performance. A novel approach is developed in this paper, based on sparse linear regression (SLR). Using a dense frequency grid, the problem is formulated as one of under-determined linear regression with a dual sparsity penalty, and its exact solution is obtained using the alternating direction method of multipliers (ADMoM). The SLR-based approach is further broadened to encompass polynomial-phase hopping (PPH) signals, encountered in chirp spread spectrum modulation. Simulations demonstrate that the developed estimator outperforms spectrogram-based alternatives, especially with regard to hop timing estimation, which is the crux of the problem.
When new needs for satellite payloads meet with new filters architecture and technologies (2009)

To cope with the economical and technical demands of the market and to compete with terrestrial networks, satellite operators and manufacturers will need to upgrade their satellites and services. Nowadays, most of commercial satellite payloads are designed for a predetermined service and lack flexibility. Future communication satellites have to become more flexible and shall provide capacity at the lowest cost. The upcoming new needs lead to a major impact on the architecture at satellite payload level. RF and microwave filters are one of the most affected by the derived equipment specifications. The required out-of-band rejection close to the useful bandwidth will become more stringent (better than 40 dBc) while saving size and mass by more than 30% compared to the heavy mechanical cavities used today. Advanced technologies, like ceramic 3D stereolithography or Surface Integrated Waveguide technology presented in this paper are very promising solutions to overcome these requirements. Moreover, tunable filters could be a relevant option to simplify payload architectures by giving more flexibility on the frequency plan and/or bandwidth. Today, agile filters are not available in space equipments but some new technologies presented in this paper, such as MEMS technologies or ceramic based flexible filters, have now the capability to comply with space environment constraints. Finally, new synthesis method techniques could help saving mass (by 30% or more) of future OMUX equipments.