gebhart/patrepeval huggingface dataset:
Discriminative Relational Topic Models (2013)

Many scientific and engineering fields involve analyzing network data. For document networks, relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents, and they have shown promise on predicting network structures and discovering latent topic representations. However, existing RTMs have limitations in both the restricted model expressiveness and incapability of dealing with imbalanced network data. To expand the scope and improve the inference accuracy of RTMs, this paper presents three extensions: 1) unlike the common link likelihood with a diagonal weight matrix that allows the-same-topic interactions only, we generalize it to use a full weight matrix that captures all pairwise topic interactions and is applicable to asymmetric networks; 2) instead of doing standard Bayesian inference, we perform regularized Bayesian inference (RegBayes) with a regularization parameter to deal with the imbalanced link structure issue in common real networks and improve the discriminative ability of learned latent representations; and 3) instead of doing variational approximation with strict mean-field assumptions, we present collapsed Gibbs sampling algorithms for the generalized relational topic models by exploring data augmentation without making restricting assumptions. Under the generic RegBayes framework, we carefully investigate two popular discriminative loss functions, namely, the logistic log-loss and the max-margin hinge loss. Experimental results on several real network datasets demonstrate the significance of these extensions on improving the prediction performance, and the time efficiency can be dramatically improved with a simple fast approximation method.
Introduction to the new Standards - IEEE STD 844.1™-2017 /CSA C22.2 No. 293.1-17 and IEEE STD 844.2™-2017/CSA C293.2-17 for Skin Effect Trace Heating of Pipelines, Vessels, Equipment, and Structures: Copyright Material IEEE, Paper No. PCIC-2018-20 (2018)

Through a joint standards development process between the Institute of Electrical and Electronic Engineers (IEEE) and the Canadian Standards Association (CSA), two new standards are now completed. These new standards include a certification standard, IEEE Std 844.1 ™-2017/CSA C22.2 No. 293.1-17 (Standard for Skin Effect Trace Heating of Pipelines, Vessels, Equipment, and Structures-General, Testing, Marking, and Documentation), and an application guide standard, IEEE Std 844.2™-2017/CSA C22.2 No. C293.2-17 (Standard for Skin Effect Trace Heating of Pipelines, Vessels, Equipment, and Structures-Application Guide for Design, Installation, Testing, Commissioning, and Maintenance). Requirements are detailed that have been added or clarified in the skin effect trace heating system certification process. This paper summarizes new applications as well as new recommended installation practices in the application guide. Reflections on the path taken in this joint standard development as well as a look forward at future developments are shared.
Experience with concurrent aggregates (CA): implementation and programming (1995)

Programming languages for massively parallel concurrent computers need multi-access data abstraction tools. Most concurrent object-oriented languages serialize hierarchical abstractions. Thus multiple levels of abstraction can result in greatly diminished concurrency, even if each level only causes a tiny amount of serialization. This leaves programmers with the choice of reduced concurrency or working without useful levels of abstraction. Going without these levels of abstraction makes programs more difficult to write, understand, and debug.
Multi-channel source separation by beamforming trained with factorial HMMs (2004)

Speaker separation has conventionally been treated as a problem of blind source separation (BSS). This approach does not utilize any knowledge of the statistical characteristics of the signals to be separated, relying mainly on the independence between the various signals to separate them. Maximum-likelihood techniques, on the other hand, utilize knowledge of the a priori probability distributions of the signals from the speakers, in order to effect separation. Previously (Reyes-Gomez, M.J. et al., Proc. ICASSP, 2003), we presented a maximum-likelihood speaker separation technique that utilizes detailed statistical information about the signals to be separated, represented in the form of hidden Markov models (HMMs), to estimate the parameters of a filter-and-sum processor for signal separation. We show that the filters that are estimated for a particular utterance by a speaker generalize well to other utterances by the same speaker, provided the location of the various speakers remains constant. Thus, filters that have been estimated using a "training" utterance of a known transcript can be used to separate all future signals by the speaker from mixtures of speech signals in an unsupervised manner. On the other hand, the filters are ineffective for other speakers, even at the same locations, indicating that they capture the spatio-frequency characteristics of the speaker.
Relationship between human T cell leukemia virus-II and atypical hairy cell leukemia: a serologic study of hairy cell leukemia patients. (1987)

Human T cell leukemia virus (HTLV-II) is an infrequently encountered human T cell leukemia virus first isolated from a patient with atypical hairy cell leukemia. Recently, we identified a second patient infected with HTLV-II who had a similar clinical syndrome of atypical hairy cell leukemia associated with peripheral T cell lymphocytosis. HTLV-II was detected by molecular hybridization studies, and more recently, by electron microscopy, in cell lines derived from the patient. Both patients came from the Los Angeles area and had spent several years in Alaska. As opposed to our two patients, 21 patients with more typical cases of hairy cell leukemia were seronegative for HTLV-II. Two additional cases of unusual T cell malignancy linked to HTLV-II have been described by other investigators and bear limited similarity to our index cases. Further studies are necessary to define the spectrum of malignancies linked to HTLV-II and to identify infected individuals for prospective study.
Abstract 5660: Vaccinia virus GLV-1h153 in combination with 131I-iodine shows increased efficiency in treating triple-negative breast cancer in vivo (2012)

Abstract BACKGROUND: Triple-negative breast cancers (TNBC) are aggressive tumors due to their inherent biology and the lack of receptors for hormonal/targeted therapy, namely estrogen, progesterone, and Her2/neu. The human sodium iodide symporter (hNIS) is a naturally occurring protein in some human breast and thyroid tissue which enables cells to concentrate iodine, including radioiodide. In this study, we investigated the therapeutic efficacy of a new oncolytic vaccinia virus, GLV-1h153 carrying the hNIS, in combination with radioiodine in a TNBC murine model. METHODS: GLV-1h153, a replication-competent vaccinia virus, was tested against the TNBC cell lines MDA-MB-231, MDA-MB-468, HCC-1937, and HCC-1143 at multiplicities of infections (MOI) of 0.1, 1.0, and 5. Cytotoxicity and viral replication were determined. Mammary fat pad tumors were generated in athymic nude mice with MDA-MB-231 cells. A subset of xenografts were infected with GLV-1h153 and ∼150 μCi of 124I-iodine was administered. Serial Focus 120 microPET were obtained for 131I dosimetry calculations. For the combination therapy study, 14 days after cell implantation, xenografts were treated with intratumoral injection of GLV-1h153 or PBS. One week after viral injection (day 21), xenografts were further randomized into 4 treatments groups: GLV-1h153 alone, GLV-1h153 and iodine (∼5 mCi of 131I), iodine alone, or PBS and followed for tumor growth. RESULTS: Greater than 90% cell kill was achieved in all cell lines within 5 days at an MOI of 5.0. GLV-1h153 replicated efficiently in all cell lines with a peak titer of 2.6 x107 viral plaque forming units per ml (&amp;gt;1300-fold increase from the initial viral dose) by day 4 in cell line MDA-MB-468. Only infected tumors were identified via PET scanning compared to controls. In vivo, administration of systemic radioiodine in combination with GLV-1h153 resulted in greater tumor regression, 24 mm3 compared to 146 mm3 for the viral-treated group only (p&amp;lt;0.05; days 21-40), a six-fold difference. CONCLUSION: GLV-1h153 infected, replicated in, and killed all TNBC cell lines effectively. This study is the first to our knowledege to demonstrate killing of TNBC by a novel vaccinia virus in combination with radioactive 131I-iodine in an in vivo xenograft model. Our results suggest that GLV-1h153 is a promising therapeutic agent in combination with 131I and merits further testing in the clinical setting. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5660. doi:1538-7445.AM2012-5660
Synthesis of 8-oxa analogues of norcocaine endowed with interesting cocaine-like activity (1999)

In order to further explore the importance of cocaine's bridge nitrogen atom in binding to the dopamine transporter (DAT), we have synthesized the previously known racemic 8-oxa-norcocaines 3-6 in which the nitrogen atom has been replaced by oxygen. Additionally, to avoid incorrect interpretations of biological data that may stem from the use of racemic materials, several of these analogues were synthesized and tested in non-racemic form. (-)-8-Oxa-norcocaine (3) was found to bind to the cocaine recognition site and to inhibit the dopamine transporter with potencies only about 8-fold and 4-fold, respectively, less than those of norcocaine (2). (-)-8-Oxa-pseudonorcocaine (4) as well as (+)-8-oxa-norcocaine (3) were found to be comparable in activity to (-)-oxa-norcocaine. These pharmacological findings support our earlier suggestion that cocaine is likely to bind in its neutral form to the DAT.
Fatty acid desaturase 1 knockout mice are lean with improved glycemic control and decreased development of atheromatous plaque (2016)

Delta-5 desaturase (D5D) and delta-6 desaturase (D6D), encoded by fatty acid desaturase 1 (FADS1) and FADS2 genes, respectively, are enzymes in the synthetic pathways for ω3, ω6, and ω9 polyunsaturated fatty acids (PUFAs). Although PUFAs appear to be involved in mammalian metabolic pathways, the physiologic effect of isolated D5D deficiency on these pathways is unclear. After generating >4,650 knockouts (KOs) of independent mouse genes and analyzing them in our high-throughput phenotypic screen, we found that Fads1 KO mice were among the leanest of 3,651 chow-fed KO lines analyzed for body composition and were among the most glucose tolerant of 2,489 high-fat-diet-fed KO lines analyzed by oral glucose tolerance test. In confirmatory studies, chow- or high-fat-diet-fed Fads1 KO mice were leaner than wild-type (WT) littermates; when data from multiple cohorts of adult mice were combined, body fat was 38% and 31% lower in Fads1 male and female KO mice, respectively. Fads1 KO mice also had lower glucose and insulin excursions during oral glucose tolerance tests along with lower fasting glucose, insulin, triglyceride, and total cholesterol levels. In additional studies using a vascular injury model, Fads1 KO mice had significantly decreased femoral artery intima/media ratios consistent with a decreased inflammatory response in their arterial wall. Based on this result, we bred Fads1 KO and WT mice onto an ApoE KO background and fed them a Western diet for 14 weeks; in this atherogenic environment, aortic trees of Fads1 KO mice had 40% less atheromatous plaque compared to WT littermates. Importantly, PUFA levels measured in brain and liver phospholipid fractions of Fads1 KO mice were consistent with decreased D5D activity and normal D6D activity. The beneficial metabolic phenotype demonstrated in Fads1 KO mice suggests that selective D5D inhibitors may be useful in the treatment of human obesity, diabetes, and atherosclerotic cardiovascular disease.
Fundamental Approaches to Robust Differential Beamforming With High Directivity Factors (2022)

Differential beamforming, which measures the spatial derivatives of the acoustic pressure field, can be used in a wide range of small devices that require high-fidelity sound and speech acquisition as it can achieve frequency-invariant spatial responses with high directivity factors (DFs). Since a differential process is inherently sensitive to sensors' self noise and other array imperfections, the most challenging problem in the design of any differential beamformer is how to achieve the maximum possible DF while maintaining a proper level of robustness for practical usage. While significant efforts have been made on this topic, the problem remains unsolved and further study is indispensable. This paper is devoted to dealing with this challenging problem. It presents a study on theory and methods to achieve the optimal and fundamental compromise between the white noise gain (WNG), which quantifies how robust is the beamformer, and the DF in differential beamforming. The major contributions of this work are as follows. 1) We show and prove that any null constrained fixed beamformer can be decomposed as the sum of two orthogonal filters, i.e., the maximum WNG (MWNG) beamformer and a reduced-rank one. Based on this decomposition, we develop three kinds of differential beamformers from the WNG perspective, which can achieve a flexible and optimal compromise between DF and WNG. 2) We show that a transformed null constrained beamformer can also be decomposed as the sum of two orthogonal filters, i.e., the transformed maximum DF (MDF) beamformer and another reduced-rank one. Based on this decomposition, we also develop three kinds of differential beamformers, which can obtain the desired level of DF while using the rest of the degrees of freedom to maximize the WNG. Simulations are performed to validate the theoretical analysis and developed differential beamformers.
ChemInform Abstract: SYNTHESIS, ABSOLUTE CONFIGURATION, AND CIRCULAR DICHROISM OF THE ENANTIOMERS OF FLUOROSUCCINIC ACID (1980)

Abstract Mit Diethylaminoschwefeltrifluorid wird die Hydroxygruppe des Äpfelsäurediesters (I)stereospezifisch unter Inversion durch Fluor zum Diester (II) substituiert, der nach saurer Hydrolyse zur Disäure (III) in das Lacton (IV) übergeführt wird.
3D Numerical Analysis of Two-Phase Immersion Cooling for Electronic Components (2018)

This paper presents a three-dimensional numerical analysis, using ANSYS Fluent, of a two-phase immersion cooling solution for high-powered processor designs. The primary electronic component, a CPU package, is modeled as a bare 5cm × 5cm flat plate heat source. The remainder of the model is based on the structure of typical two-phase immersion-cooled servers. Two arrangements are investigated, both fully immersing the heat-producing components in liquid coolant. The first has two vertically mounted heat sources to achieve higher packing density of the server, while the second only has a single heat source. This study considers 3M Novec7000 as the phase change coolant, which is a dielectric with a low (34°C) boiling temperature. We validate our numerical model against published results. Our simulations show: (1) when the two heat sources are in series, the upper source runs significantly hotter than the lower source because bubbles from lower source reduce the coolant contact area on the upper source. (2) Novec7000 can support cooling a 5cm × 5cm heat source in a vertical orientation with power as high as 225W (heat flux 9W/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ). However, if two such sockets are thermally coupled, the power of the upper socket must be lower than 185W. If socket power exceeds that limit, a heat transfer enhancement layer should be applied to the coupled sockets to increase cooling area and reduce heat flux.
Nitrate versus oxygen respiration in the activated sludge process (2016)

In this study biokinetic and microbial growth coefficients for nitrate versus oxygen respiration in the activated sludge process were evaluated and compared. Two bench-scale activated sludge units were operated over a range of mean cell residence times and under the same conditions except that one unit was aerobic and the other was anoxic. The maximum mi crobial yield coefficient, Ymax, and the endogenous decay coeffi cient, k<i, were lower and the maximum substrate utilization rate, k, was higher for nitrate respiration versus oxygen respiration. COD removal efficiencies were nearly equal at corresponding mean cell residence times. Sludge production was approximately 40% smaller for anoxic conditions when compared to aerobic conditions for similar mean cell residence times less than 10 days. J. Water Pollut. Control Fed., 60, 342 (1988).
Comparison of CpG s-ODNs, chromatin immune complexes, and dsDNA fragment immune complexes in the TLR9-dependent activation of rheumatoid factor B cells (2004)

Synthetic single-stranded oligodeoxynucleotides (15—30 bp) containing CpG motifs and phosphorothioate backbones (CpG s-ODN), immune complexes consisting of anti-nucleosome mAbs and mammalian chromatin (chromatin IC), and immune complexes consisting of anti-hapten mAbs and haptenated-double stranded DNA fragments (~600 bp) can all effectively stimulate transgenic B cells expressing a rheumatoid factor receptor by a TLR9-dependent process. However, differential sensitivity to both s-ODN and small molecule inhibitors suggests that stimulatory CpG sODN and chromatin IC may either access TLR9 via different routes or depend on discrete activation parameters. These data have important implications regarding the therapeutic application of TLR9 inhibitors to the treatment of systemic autoimmune diseases.
Implications of Experiment Set-Ups for Residential Water End-Use Classification (2020)

With the increased population in urban areas worldwide, the security of water supply is gaining in importance. Water scarcity accelerated by climate change poses additional stress to water supply infrastructures. Water consumption data transmitted by smart water meters form the foundation of advanced data analysis, such as water end-use classification, with which the resilience of water supply can be improved. Especially with large amounts of high-resolution data, the accurate categorization of data from smart water meters into different end-uses such as toilets, showers or dishwashers is challenging and cannot be performed by humans. To this end, machine-learning (ML) approaches provide several benefits, such as real-time capability, scalability and generalizability. State-of-the-art methods to identify residential water end-uses include both unsupervised methods and supervised approaches. However, a comprehensive comparison of unsupervised and supervised techniques is still missing. In this study, we are aiming at a quantitative evaluation of various ML techniques for water end-use classification. Furthermore, we focus on deriving general implications on the setting and conduction of ML-based experiments for water end-use classification. For these purposes, a stochastic water consumption simulation tool with high capability to model the real-world water consumption pattern is applied to generate residential data. Subsequently, unsupervised clustering methods, such as dynamic time warping, k-means, DBSCAN, OPTICS and Hough transform, are compared to supervised methods based on SVM. The quantitative results demonstrate that supervised approaches are capable to classify common residential end-uses (toilet, shower, faucet, dishwasher, washing machine, bathtub and mixed water-uses) with accuracies up to 0.99, whereas unsupervised methods fail to detect those consumption categories. The major implications drawn from the quantitative results are two-fold: clustering is not suitable to separate end-use categories. Hence, accurate labels are essential for the end-use classification of water events, where crowdsourcing and citizen science approaches pose feasible solutions for this purpose.
CFTR-rich ionocytes mediate chloride absorption across airway epithelia (2023)

The volume and composition of a thin layer of liquid covering the airway surface defend the lung from inhaled pathogens and debris. Airway epithelia secrete Cl- into the airway surface liquid through cystic fibrosis transmembrane conductance regulator (CFTR) channels, thereby increasing the volume of airway surface liquid. The discovery that pulmonary ionocytes contain high levels of CFTR led us to predict that ionocytes drive secretion. However, we found the opposite. Elevating ionocyte abundance increased liquid absorption, whereas reducing ionocyte abundance increased secretion. In contrast to other airway epithelial cells, ionocytes contained barttin/Cl- channels in their basolateral membrane. Disrupting barttin/Cl- channel function impaired liquid absorption, and overexpressing barttin/Cl- channels increased absorption. Together, apical CFTR and basolateral barttin/Cl- channels provide an electrically conductive pathway for Cl- flow through ionocytes, and the transepithelial voltage generated by apical Na+ channels drives absorption. These findings indicate that ionocytes mediate liquid absorption, and secretory cells mediate liquid secretion. Segregating these counteracting activities to distinct cell types enables epithelia to precisely control the airway surface. Moreover, the divergent role of CFTR in ionocytes and secretory cells suggests that cystic fibrosis disrupts both liquid secretion and absorption.
VLSI design for real-time signal processing based on biologically realistic neural models (2002)

The hippocampus region of the brain system performs cognitive functions of learning and memory. A VLSI design of a hippocampal model has been proposed and two mixed analog-digital chips which use analog circuits for parallel computing and digital circuits for interconnection were designed and fabricated by the MOSIS service. The objectives of this research effort is to incorporate adequate biological constraints into the microelectronic chips and systems. (i) to provide a basis for realizing a massively parallel, hardware model with which to study the dynamics of biological neural networks, and (ii) so that the well-known signal processing capabilities of the nervous system can be more readily applied to the solution of real-world problems.
Steering Control of Autonomous Vehicles by Neural Networks (1991)

This paper describes how neural networks can be used to control the steering of an autonomous vehicle. It is assumed that the vehicle is equipped with passive or active sensors providing the range and heading angle information. Most of the developed autonomous vehicles rely on a path planning module to obtain appropriate steering commands. In contrast to path planning, a human driver bypasses the computation of a path trajectory and turns the steering wheel in direct reaction to an observed heading angle and range. In this paper, we present a neural network scheme to emulate human driving in order to eliminate the difficulties associated with path planning. Backpropogation and functional-link networks have been studied in terms of training and recall capabilities. The networks are trained by real data obtained from vehicle-tracking live test runs.