gebhart/patrepeval huggingface dataset:
Secure sensor network SUM aggregation with detection of malicious nodes (2012)

In-network aggregation is an essential operation which reduces communication overhead and power consumption of resource-constrained sensor network nodes. Sensor nodes are typically organized into an aggregation tree, whereby aggregator nodes collect data from multiple data source nodes, and perform a reduction operation such as sum, average, minimum, etc. The result is then forwarded to other aggregators higher in the hierarchy toward a base station (or sink node) that receives the final outcome of the in-network computation. However, despite its performance benefits, aggregation introduces several difficult security challenges with respect to data confidentiality, integrity and authenticity. In today's outsource-centric computing environments, the aggregation task may be delegated to a third party that is not fully trusted. In addition, even in the absence of outsourcing, nodes may be compromised by a malicious adversary with the purpose of altering aggregation results. To defend against such threats, several mechanisms have been proposed, most of which devise aggregation schemes that rely on cryptography to detect that an attack has occurred. Although they prevent the sink from accepting an incorrect result, such techniques are vulnerable to denial-of-service if a compromised node alters the aggregation result in each round. Several more recent approaches also identify the malicious nodes and exclude them from future computation rounds. However, these incur high communication overhead as they require flooding or other expensive communication models to connect individual nodes with the base station. We propose a flexible aggregation structure (FAS) and an advanced ring structure (ARS) topology that allow secure aggregation and efficient identification of malicious aggregator nodes for the SUM operation. Our scheme uses only symmetric key cryptography, outperforms existing solutions in terms of performance, and guarantees that the aggregate result is correct and that malicious nodes are identified.
Rational Design of Manganese Cobalt Phosphide with Yolk–Shell Structure for Overall Water Splitting (2019)

The development of low‐cost, earth‐abundant, and efficient catalysts for overall water splitting, involving the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), attracts tremendous attention in recent years. Herein, this work reports the preparation of Mn‐Co phosphide (Mn‐Co‐P) bifunctional catalysts with a yolk–shell structure by a facile hydrothermal route. The as‐prepared catalysts exhibit an excellent catalytic activity with the low overpotentials of 66 mV at 10 mA cm −2 for HER and 355 mV at 50 mA cm −2 for OER in 1 m KOH, along with an outstanding stability. More importantly, the cell voltage of 1.74 V can achieve a current density of 10 mA cm −2 when assembled as an electrolyzer for overall water splitting. Such superior performance makes the Mn‐Co‐P a promising candidate to replace Pt‐based noble metal catalysts for electrocatalytic applications.
<em>Salmonella enterica serovar senftenberg</em> infection in the neonatal intensive care unit (1998)

Salmonella senftenberg (Group E Salmonella) was first isolated in India in 1963. It became a serovar of concern after ) 985 when it caused outbreak in paediatric wards and neotxates in India. This study shows gut colonisation of preterm neonates by group E Salmo- nella sp in Neonatal Intensive Care Unit (NICU) at AIIMS, N. Delhi. A total of 58 preterm babies admitted to the NICU were exanined for microbialflora in stool samples on day 3't , Vh, I4'h,21't and 28th. Organisms were identified by methods based on culture, conven- tional biochemical and rapid identification kits (BioMerieta). Polymerase chain reaction (PCR) technique for detecting flagellin gene for all Salmonella sp using previously standardised primers detect prese,xce o/Salmonella sp in stool. Five (8.6Vo) out of 58 babies grew group E Salmonella sp and were also PCR positive. These were further identified as S, senftenberg havhg antibiotic resista,xt prortb AGKT (AmpiciLlin, Gentamicin, Kanamycin & Tetracyclin). S. senftenberg coul.d not be identffied in any satnple from the envirorunent, medical and paramedical staff.
Pitfalls in outcome prediction of breast cancer (2013)

Breast cancer represents a heterogeneous group of diseases with varied presentation, morphological and biological features, behaviour, and response to therapy. Management of breast cancer relies on availability of robust predictive and prognostic factors to support decision making. Identifying and validating the prognostic and predictive value of a given marker is based on studying its association with clinical outcome with or without consideration for therapy, respectively. In the field of cancer research, clinical outcome is determined by assessing certain time-dependent events: 'endpoints' such as tumour progression, recurrence and patient mortality. Guidelines for reporting tumour markers have been published and there is a perception that outcome determination in breast cancer is well documented. However, reviewing the literature has highlighted the varied use of definitions used in clinical outcome measures and there are pitfalls in outcome analysis. This may have contributed to the discrepancies in the literature and to the inconsistent conclusions seen in published studies assessing the same markers. Identification of these pitfalls is expected to improve prognostic and predictive marker assessment. Here issues related to outcome determination in breast cancer including definitions and pitfalls and some critical views are presented.
Model independent eigenaxis maneuvers using quaternion feedback (2001)

The main contribution of the paper is the derivation of a model independent feedback control law that causes a rigid body to execute a near eigenaxis maneuver. The degree of approximation is a function of the control gains and the initial attitude error. Using passivity techniques, the dependence of the control strategy on velocity information is eliminated. The technique used to derive the control strategy is a novel orthogonal decomposition of the unit quaternion into a component along the direction of the eigenaxis and a component that is orthogonal to that direction.
Photomodification of a poly(acrylonitrile‐co‐butadiene‐co‐styrene) containing diaryltetrazolyl groups (1994)

Abstract A new type of membrane polymer, containing a photosensitive moiety, was synthesized. The photochemically induced functionalization and crosslinking of poly [acrylonitrile‐co‐butadiene‐co‐styrene‐co‐2‐(4‐ethenyl) phenyl‐5‐phenyl‐2H‐tetrazole], ABSV, has been studied. A variety of dipolarophiles and phenolic compounds were applied to alter the polarity of the membrane surface. The functionalization and crosslinking were initiated by photoirradiation. DSC and contact angle measurements were used to characterize the modified polymer. Pervaporation experiments with a cyclohexane/benzene mixture (5 wt% benzene) were carried out, with the results showing, that the photochemical treatment significantly effects both permselectivity and flux. Solubility parameters were found to be useful to interpret the pervaporation data. In general, the selectivity towards benzene increases with the polarity of the membrane surface, i.e., with increasing polarity of the modifier. A mechanism to explain the influence of both functionalization and crosslinking on the membrane performance, is proposed. © 1994 John Wiley &amp; Sons, Inc.
A Polymer-Based, Paclitaxel-Eluting Stent in Patients with Coronary Artery Disease (2004)

As compared with bare-metal stents, the slow-release, polymer-based, paclitaxel-eluting stent is safe and markedly reduces the rates of clinical and angiographic restenosis at nine months.
Parallelizable Synthesis of Arbitrary Single-Qubit Gates with Linear Optics and Time-Frequency Encoding (2022)

We propose novel methods for the exact synthesis of single-qubit unitaries with high success probability and gate fidelity, considering both time-bin and frequency-bin encodings. The proposed schemes are experimentally implementable with a spectral linear-optical quantum computation (S- LOQC) platform, composed of electro-optic phase modulators and phase-only programmable filters (pulse shapers). We assess the performances in terms of fidelity and probability of the two simplest 3-components configurations for arbitrary gate generation in both encodings and give an exact analytical solution for the synthesis of an arbitrary single-qubit unitary in the time-bin encoding, using a single-tone Radio Frequency (RF) driving of the EOMs. We further investigate the parallelization of arbitrary single-qubit gates over multiple qubits with a compact experimental setup, both for spectral and temporal encodings. We systematically evaluate and discuss the impact of the RF bandwidth - that conditions the number of tones driving the modulators - and of the choice of encoding for different targeted gates. We moreover quantify the number of high fidelity Hadamard gates that can be synthesized in parallel, with minimal and increasing resources in terms of driving RF tones in a realistic system. Our analysis positions spectral S-LOQC as a promising platform to conduct massively parallel single qubit operations, with potential applications to quantum metrology and quantum tomography.
Procedural Patterns and Safety of Atrial Fibrillation Ablation (2020)

More than 98% of AF ablations among participating sites are performed for class I or class IIA indications. Contact force-guided radiofrequency ablation is the dominant technique and pulmonary vein isolation the principal lesion set. In-hospital complications are uncommon and rarely life-threatening.
Gene Screening for Prognosis of Non-Muscle-Invasive Bladder Carcinoma under Competing Risks Endpoints (2023)

Background: Discovering clinically useful molecular markers for predicting the survival of patients diagnosed with non−muscle-invasive bladder cancer can provide insights into cancer dynamics and improve treatment outcomes. However, the presence of competing risks (CR) endpoints complicates the estimation and inferential framework. There is also a lack of statistical analysis tools and software for coping with the high-throughput nature of these data, in terms of marker screening and selection. Aims: To propose a gene screening procedure for proportional subdistribution hazards regression under a CR framework, and illustrate its application in using molecular profiling to predict survival for non-muscle invasive bladder carcinoma. Methods: Tumors from 300 patients diagnosed with bladder cancer were analyzed for genomic abnormalities while controlling for clinically important covariates. Genes with expression patterns that were associated with survival were identified through a screening procedure based on proportional subdistribution hazards regression. A molecular predictor of risk was constructed and examined for prediction accuracy. Results: A six-gene signature was found to be a significant predictor associated with survival of non−muscle-invasive bladder cancer, subject to competing risks after adjusting for age, gender, reevaluated WHO grade, stage and BCG/MMC treatment (p-value < 0.001). Conclusion: The proposed gene screening procedure can be used to discover molecular determinants of survival for non−muscle-invasive bladder cancer and in general facilitate high-throughput competing risks data analysis with easy implementation.
Edgeworth-Expanded Gaussian Mixture Density Modeling (2005)

Instead of increasing the order of the Edgeworth expansion of a single gaussian kernel, we suggest using mixtures of Edgeworth-expanded gaussian kernels of moderate order. We introduce a simple closed-form solution for estimating the kernel parameters based on weighted moment matching. Furthermore, we formulate the extension to the multivariate case, which is not always feasible with algebraic density approximation procedures.
Safety considerations for the operation of bipolar DC-grids (2017)

DC microgrids can offer many advantages for an installation in commercial applications like data centers or in private homes. In this paper, future expansion of such grids towards a bipolar architecture (e.g. ±380 V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DC</sub> ) is evaluated. The focus lies on various fault situations, their effects on the grid and possible solutions to maintain grid safety. For this purpose, a laboratory scale bipolar test grid is set up and subjected to ground faults, loss of neutral and load shedding.
On accuracy estimation and comparison of results in biometric research (2016)

The estimated accuracy of an algorithm is the most important element of the typical biometrics research publication. Comparisons between algorithms are commonly made based on estimated accuracies reported in different publications. However, even when the same dataset is used in two publications, there is a very low frequency of the publications using the same protocol for estimating algorithm accuracy. Using the example problems of face recognition, expression recognition and gender classification, we show that the variation in estimated performance on the same dataset across different protocols can be enormous. Based on these results, we make recommendations for how to obtain performance estimates that allow reliable comparison between algorithms.
Polyploid genome of Camelina sativarevealed by isolation of fatty acid synthesis genes (2010)

There is compelling evidence for triplication of the C. sativa genome, including a larger chromosome number and three-fold larger measured genome size than other Camelina relatives, three isolated copies of FAD2, FAE1, and the KCS17-FAE1 intergenic region, and three expressed haplotypes observed for six predicted single-copy genes. Based on these results, we propose that C. sativa be considered an allohexaploid. The characterization of fatty acid synthesis pathway genes will allow for the future manipulation of oil composition of this emerging biofuel crop; however, targeted manipulations of oil composition and general development of C. sativa should consider and, when possible take advantage of, the implications of polyploidy.
Effects of an Exercise Programme on Functional Capacity, Body Composition and Risk of Falls in Patients with Cirrhosis: A Randomized Clinical Trial (2016)

ClinicalTrials.gov NCT01447537.
Clustering of Distributed Word Representations and its Applicability for Enterprise Search (2016)

Machine learning of distributed word representations with neural embeddings is a state-of-the-art approach to modelling semantic relationships hidden in natural language. The thesis “Clustering of Distributed Word Representations and its Applicability for Enterprise Search” covers different aspects of how such a model can be applied to knowledge management in enterprises. A review of distributed word representations and related language modelling techniques, combined with an overview of applicable clustering algorithms, constitutes the basis for practical studies. The latter have two goals: firstly, they examine the quality of German embedding models trained with gensim and a selected choice of parameter configurations. Secondly, clusterings conducted on the resulting word representations are evaluated against the objective of retrieving immediate semantic relations for a given term. The application of the final results to company-wide knowledge management is subsequently outlined by the example of the platform intergator and conceptual extensions.":1 Introduction 1.1 Motivation 1.2 Thesis Structure 2 Related Work 3 Distributed Word Representations 3.1 History 3.2 Parallels to Biological Neurons 3.3 Feedforward and Recurrent Neural Networks 3.4 Learning Representations via Backpropagation and Stochastic Gradient Descent 3.5 Word2Vec 3.5.1 Neural Network Architectures and Update Frequency 3.5.2 Hierarchical Softmax 3.5.3 Negative Sampling 3.5.4 Parallelisation 3.5.5 Exploration of Linguistic Regularities 4 Clustering Techniques 4.1 Categorisation 4.2 The Curse of Dimensionality 5 Training and Evaluation of Neural Embedding Models 5.1 Technical Setup 5.2 Model Training 5.2.1 Corpus 5.2.2 Data Segmentation and Ordering 5.2.3 Stopword Removal 5.2.4 Morphological Reduction 5.2.5 Extraction of Multi-Word Concepts 5.2.6 Parameter Selection 5.3 Evaluation Datasets 5.3.1 Measurement Quality Concerns 5.3.2 Semantic Similarities 5.3.3 Regularities Expressed by Analogies 5.3.4 Construction of a Representative Test Set for Evaluation of Paradigmatic Relations 5.3.5 Metrics 5.4 Discussion 6 Evaluation of Semantic Clustering on Word Embeddings 6.1 Qualitative Evaluation 6.2 Discussion 6.3 Summary 7 Conceptual Integration with an Enterprise Search Platform 7.1 The intergator Search Platform 7.2 Deployment Concepts of Distributed Word Representations 7.2.1 Improved Document Retrieval 7.2.2 Improved Query Suggestions 7.2.3 Additional Support in Explorative Search 8 Conclusion 8.1 Summary 8.2 Further Work Bibliography List of Figures List of Tables Appendix
Dynamics of geometrically reconfigurable one dimensional and two dimensional magneto-elastic metamaterials (2014)

Periodic structures are presented as metamaterials that exhibit multistability due to the nonlinearities of magneto-elastic interactions and structure geometry. The multistability of these structures affords them the ability to adapt their properties though geometric reconfiguration, bringing about changes in stiffness and Poisson's ratio, and introducing anisotropy. These changes in structural properties cause drastic changes in wave propagation, which is of interest for wave control. The dynamic transformation of one-dimensional (1D) and two-dimensional (2D) lattices between stable states are studied through nonlinear numerical simulations. The analysis is conducted using a lumped mass system of magnetic particles. The structures studied include hexagonal, re-entrant, and kagome lattices. Changes in plane wave propagation properties are predicted by applying Bloch theorem to lattice unit cells with linearized interactions. Results from Bloch analysis are then verified through direct numerical simulations. The propagation of plane waves in these lattices before and after topological changes is compared, and large differences are evident.
Mechanism of action of Lactobacillus reuteri ATCC PTA 6475 in colon epithelial cells (2016)

Lactobacillus reuteri ATCC PTA 6475 (LR) is a well‐known probiotic that has been shown to be beneficial to the gastrointestinal (GI) system. In addition, LR has been shown to secrete beneficial immunomodulatory factors. In previous studies, we demonstrated that LR can modulate inflammatory genes in the GI tract in mice in vivo. However, the mechanisms of action of LR in the GI system during inflammatory conditions are still poorly understood. In the present study, we investigated the potential role of LR on tumor necrosis factor a (TNFa)‐induced colon epithelial cell biology, including expression of inflammatory genes. For this, we pre‐treated colon epithelial cells (SW480) with live LR, LR conditioned medium (CM), CM fractions (ranging from &lt; 3, 3–10, 10–30, 30–50, 50–100 and &gt;100kD) and heat inactivated CM. Subsequently, we treated the cells with TNFa (10ng/ml) for 6 or 24 hours and examined expression of inflammatory genes. We found that live LR induced IL‐8 mRNA expression in a dose dependent manner. We further identified that the less than 3KD fraction of the CM produced by LR is sufficient to induce IL‐8 at both the mRNA and proteins levels. While we observed similar effects on MIP2a, TNFa gene expression was not regulated by LR. We further found that the factors that induce IL‐8 expression are heat labile. These effects on gene expression were also observed in other intestinal epithelial cell lines including HT29 and CaCo2. The effect on gene expression was not accompanied by cell proliferation. Preliminary examination of signaling pathway activation indicated that LR‐CM small factors do not regulate IL‐8 production by activation of the MAPK or NF‐κB pathways, suggesting other mechanisms. Together, our results confirm that live LR and its secreted factors induce inflammatory genes in epithelial cells that could potentially affect intestinal inflammation without affecting cell growth.
An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles (2020)

Energy-efficient navigation constitutes an important challenge in electric vehicles, due to their limited battery capacity. We employ a Bayesian approach to model the energy consumption at road segments for efficient navigation. In order to learn the model parameters, we develop an online learning framework and investigate several exploration strategies such as Thompson Sampling and Upper Confidence Bound. We then extend our online learning framework to multi-agent setting, where multiple vehicles adaptively navigate and learn the parameters of the energy model. We analyze Thompson Sampling and establish rigorous regret bounds on its performance. Finally, we demonstrate the performance of our methods via several real-world experiments on Luxembourg SUMO Traffic dataset.
Specific Mesothelial Signature Marks the Heterogeneity of Mesenchymal Stem Cells From High-Grade Serous Ovarian Cancer (2014)

Mesenchymal stem/stromal cells (MSCs) are the precursors of various cell types that compose both normal and cancer tissue microenvironments. In order to support the widely diversified parenchymal cells and tissue organization, MSCs are characterized by a large degree of heterogeneity, although available analyses of molecular and transcriptional data do not provide clear evidence. We have isolated MSCs from high-grade serous ovarian cancers (HG-SOCs) and various normal tissues (N-MSCs), demonstrated their normal genotype and analyzed their transcriptional activity with respect to the large comprehensive FANTOM5 sample dataset. Our integrative analysis conducted against the extensive panel of primary cells and tissues of the FANTOM5 project allowed us to mark the HG-SOC-MSCs CAGE-seq transcriptional heterogeneity and to identify a cell-type-specific transcriptional activity showing a significant relationship with primary mesothelial cells. Our analysis shows that MSCs isolated from different tissues are highly heterogeneous. The mesothelial-related gene signature identified in this study supports the hypothesis that HG-SOC-MSCs are bona fide representatives of the ovarian district. This finding indicates that HG-SOC-MSCs could actually derive from the coelomic mesothelium, suggesting that they might be linked to the epithelial tumor through common embryological precursors.