gebhart/patrepeval huggingface dataset:
Intelligible description language and its rapid verification method for design support of distributed sequential control systems (2002)

In distributed control systems (DCS), designed distributed controllers, which interact with each other operate plants. Therefore, in the development of the system, verification of whether the controllers satisfy given specification is important. However, the existing description languages, for example, temporal interval, are too complicated to formulize the specification. In this paper, first, Sequence Oriented Language (SOL), which is intelligible language in order to describe specification for distributed sequential control systems, is proposed. Secondly, we developed a tool for it. In this method, the tool automatically verifies that behavior of models satisfies specifications which is described using SOL.
Tire classification from still images and video (2012)

The use of different types of tires (e.g., all-season, snow, studded, summer) is regulated by law in several states and countries. Violation of tire usage laws typically results in substantial fines for infringers. In this paper, we propose an automated method to classify tires into snow, all-season and summer tires from still images or from a sequence of video frames. Our method first trains a Support Vector Machine (SVM) classifier on features extracted from a set of training images. Classification of test tire images is a two-stage process that entails feature extraction and tire classification based on the processing of the extracted features by the previously trained SVM classifier. The principle underlying the feature extraction stage is the representation of tire images via a low-dimensional approximation obtained from Principal Component Analysis (PCA). In order to improve robustness to changes in illumination and perspective, the features are extracted from the frequency representation of the binary edge map of the tire tread image. Our experimental results show that the proposed method achieves high classification accuracy.
ChemInform Abstract: PREPARATION AND REACTIONS OF A TITANIUM(IV) METALLOCYCLE, FORMATION OF CYCLOPENTANONE FROM ETHYLENE AND CARBON MONOXIDE (1974)

Abstract Die Umsetzung der Titanverbindung (I) mit der Di‐Li‐Verbindung (II) in der Kälte in Diäthyläther unter Stickstoff‐ oder Argonatmosphäre führt zu dem nur unter ‐30°C stabilen Tetramethylen‐Ti‐Produkt (III), dessen Thermolyse Buten‐(l) und Äthylen ergibt.
On the optimality of tree-reweighted max-product message-passing (2012)

Tree-reweighted max-product (TRW) message passing [9] is a modified form of the ordinary max-product algorithm for attempting to find minimal energy configurations in Markov random field with cycles. For a TRW fixed point satisfying the strong tree agreement condition, the algorithm outputs a configuration that is provably optimal. In this paper, we focus on the case of binary variables with pairwise couplings, and establish stronger properties of TRW fixed points that satisfy only the milder condition of weak tree agreement (WTA). First, we demonstrate how it is possible to identify part of the optimal solution—i.e., a provably optimal solution for a subset of nodes — without knowing a complete solution. Second, we show that for submodular functions, a WTA fixed point always yields a globally optimal solution. We establish that for binary variables, any WTA fixed point always achieves the global maximum of the linear programming relaxation underlying the TRW method. 1
Perceived risks, role, and objectified trustworthiness information in the sharing economy (2017)

Trust plays a central role of the sharing economy because there exist potential risks in P2P transactions. To mitigate those risks, both host and guest can utilize the Objectified trustworthiness information (OTI), which is not identical to reputation because higher reputation does not always mean he is trustworthy. This study aims at analyzing factors influencing the adoption intention of OTI with regard to various factors of perceived risk, role (host versus guest), usage experience, gender, and age. The regression analysis results reveal that young guests are likely to adopt OTI to mitigate perceived risk than aged hosts.
ChemInform Abstract: Study of the Kulinkovich Synthesis of 1‐Methylcyclopropanol and Its Conversion into 1‐Methylcyclopropyl 4‐Nitrophenyl Carbonate. (2014)

Abstract A carefully designed process for the scalable synthesis of 1‐methylcyclopropanol (III) is developed as well as the optimized conversion to the mixed carbonate (V).
Supplementary Figure 5 from Chk2 Phosphorylation of Survivin-ΔEx3 Contributes to a DNA Damage–Sensing Checkpoint in Cancer (2023)

&lt;p&gt;PDF file - 59K, Expression of Aurora B during DNA damage. HCT116 cells on glass coverslips were transfected with the indicated cDNAs, treated with etoposide for 16 h and fixed in 1% paraformaldehyde for 15 min and 70% ethanol for 30 min. After permeabilization in 0.2% Triton X-100 in 1% BSA in PBS, pH 7.4, for 10 min, cells were incubated with primary antibody to Aurora B (1:500) followed by secondary antibody (Alexa Fluor� 594) and analyzed by fluorescence microscopy. DNA was stained with DAPI.&lt;/p&gt;
Provably minimal energy using coordinated DVS and power gating (2014)

Both energy and execution speed can be greatly impacted by clock and power gating, nonlinear voltage scaling, and leakage energy. We address the problem of coordinated power gating and dynamic voltage scaling (DVS) to minimize the overall energy consumption of an application under user-specified timing constraints. We prove that a solution provided by our convex programming formulation that uses at most two versions of hardware, where each version uses its own constant voltages, is optimal. Comprehensive evaluation of the new approach demonstrates energy improvements over traditional DVS and DVS and power gating techniques by factors of 1.44X-2.97X and 1.44X-2.82X, respectively.
Novel α-L-Fucosidases from a Soil Metagenome for Production of Fucosylated Human Milk Oligosaccharides (2016)

This paper describes the discovery of novel α-L-fucosidases and evaluation of their potential to catalyse the transglycosylation reaction leading to production of fucosylated human milk oligosaccharides. Seven novel α-L-fucosidase-encoding genes were identified by functional screening of a soil-derived metagenome library and expressed in E. coli as recombinant 6xHis-tagged proteins. All seven fucosidases belong to glycosyl hydrolase family 29 (GH 29). Six of the seven α-L-fucosidases were substrate-inhibited, moderately thermostable and most hydrolytically active in the pH range 6-7, when tested with para-nitrophenyl-α-L-fucopyranoside (pNP-Fuc) as the substrate. In contrast, one fucosidase (Mfuc6) exhibited a high pH optimum and an unusual sigmoidal kinetics towards pNP-Fuc substrate. When tested for trans-fucosylation activity using pNP-Fuc as donor, most of the enzymes were able to transfer fucose to pNP-Fuc (self-condensation) or to lactose. With the α-L-fucosidase from Thermotoga maritima and the metagenome-derived Mfuc5, different fucosyllactose variants including the principal fucosylated HMO 2'-fucosyllactose were synthesised in yields of up to ~6.4%. Mfuc5 was able to release fucose from xyloglucan and could also use it as a fucosyl-donor for synthesis of fucosyllactose. This is the first study describing the use of glycosyl hydrolases for the synthesis of genuine fucosylated human milk oligosaccharides.
SLIP (2015)

Wire energy has become the major contributor to energy in large lower level caches. While wire energy is related to wire latency its costs are exposed differently in the memory hierarchy. We propose Sub-Level Insertion Policy (SLIP), a cache management policy which improves cache energy consumption by increasing the number of accesses from energy efficient locations while simultaneously decreasing intra-level data movement. In SLIP, each cache level is partitioned into several cache sublevels of differing sizes. Then, the recent reuse distance distribution of a line is used to choose an energy-optimized insertion and movement policy for the line. The policy choice is made by a hardware unit that predicts the number of accesses and inter-level movements. Using a full-system simulation including OS interactions and hardware overheads, we show that SLIP saves 35% energy at the L2 and 22% energy at the L3 level and performs 0.75% better than a regular cache hierarchy in a single core system. When configured to include a bypassing policy, SLIP reduces traffic to DRAM by 2.2%. This is achieved at the cost of storing 12b metadata per cache line (2.3% overhead), a 6b policy in the PTE, and 32b distribution metadata for each page in the DRAM (a overhead of 0.1%). Using SLIP in a multiprogrammed system saves 47% LLC energy, and reduces traffic to DRAM by 5.5%.
Multilingual Data Selection for Low Resource Speech Recognition (2016)

Abstract : Feature representations extracted from deep neural network-based multilingual frontends provide significant improvements to speech recognition systems in low resource settings. To effectively train these frontends, we introduce a data selection technique that discovers language groups from an available set of training languages. This data selection method reduces the required amount of training data and training time by approximately 40 , with minimal performance degradation. We present speech recognition results on 7 very limited language pack (VLLP) languages from the second option period of the IARPA Babel program using multilingual features trained on up to 10 languages. The proposed multilingual features provide up to 15 relative improvement over baseline acoustic features on the VLLP languages.
Physically-Based Editing of Indoor Scene Lighting from a Single Image (2022)

We present a method to edit complex indoor lighting from a single image with its predicted depth and light source segmentation masks. This is an extremely challenging problem that requires modeling complex light transport, and disentangling HDR lighting from material and geometry with only a partial LDR observation of the scene. We tackle this problem using two novel components: 1) a holistic scene reconstruction method that estimates scene reflectance and parametric 3D lighting, and 2) a neural rendering framework that re-renders the scene from our predictions. We use physically-based indoor light representations that allow for intuitive editing, and infer both visible and invisible light sources. Our neural rendering framework combines physically-based direct illumination and shadow rendering with deep networks to approximate global illumination. It can capture challenging lighting effects, such as soft shadows, directional lighting, specular materials, and interreflections. Previous single image inverse rendering methods usually entangle scene lighting and geometry and only support applications like object insertion. Instead, by combining parametric 3D lighting estimation with neural scene rendering, we demonstrate the first automatic method to achieve full scene relighting, including light source insertion, removal, and replacement, from a single image. All source code and data will be publicly released.
Latent semantic mapping: dimensionality reduction via globally optimal continuous parameter modeling (2005)

Originally formulated in the context of information retrieval, latent semantic analysis exhibits three main characteristics: (i) discrete entities (namely words and documents) are mapped onto a continuous vector space; (ii) this mapping is determined by global correlation patterns; and (iii) dimensionality reduction is an integral part of the process. Such fairly generic properties may be advantageous in a variety of different contexts, which motivates a broader interpretation of the underlying paradigm. The outcome is latent semantic mapping, a data-driven framework for modeling global relationships implicit in large volumes of (not necessarily textual) data. This paper gives a general overview of the framework, and underscores the multi-faceted benefits it can bring to a number of problems in natural language understanding and spoken language processing. It concludes with a discussion of the inherent trade-offs associated with the approach, and some perspectives on its general applicability to unsupervised information extraction
A MAGNETICALLY ENHANCED WIRELESS MICRO-GEIGER COUNTER (2006)

This paper reports a micromachined Geiger counter with integrated permanent magnets that enhance the RF transmission from the discharges initiated by incident beta particles. With the intent of wireless sensing within the ultra wideband (UWB) spectrum, the transmission in the 2.0-2.8 GHz frequency range is investigated. The device consists of a 1x2 cm 2 micromachined glass/Si cavity sandwiched between two miniaturized NdFeB rare earth magnets. Several different magnet orientations as well as two different shapes of magnets (square and ring) are investigated. The square and ring magnets have a maximum flux density of 2.40 and 0.91 kG, respectively. Preliminary results show that the RF spectra in the presence of 90 Sr and 204 Tl sources of 0.1-1.0 Ci increased by ~8 relative dBV (compared to non-magnetic devices) at a distance of 5 cm from the device. The radiation pattern emitted by the microdischarges is measured in the plane of the device. Wireless spectra from electrostatic discharges are also reported.
Abstract 88: Single Nucleotide Polymorphisms of the Dopamine D2 Receptor Increase Inflammation and Fibrosis in Human Renal Proximal Tubule Cells (2013)

We have reported that lack or downregulation of dopamine D(2) receptor (D 2 R) function in mice increases the vulnerability to renal inflammation independent of blood pressure and that the D 2 R negatively regulates inflammation and prevents injury in mouse renal proximal tubule cells (RPTCs). Some common single nucleotide polymorphisms (SNPs; rs 6276, 6277 and 1800497) in the human DRD2 gene are associated with decreased D 2 R expression and function, as well as high blood pressure. We tested the hypothesis that human RPTCs expressing these SNPs have increased expression of inflammatory markers and injury. We studied immortalized human RPTCs isolated from normal tissue of nephrectomies which were genotyped for the D 2 R SNPs; 10 cell lines were selected: wild type (WT) n=5; heterozygous for both rs6276 and 6277 n=3; heterozygous for both rs6276 and 1800497 n=2. All 5 cell lines expressing SNPs (hRPTC-SNP) had decreased D 2 R mRNA (0.52±0.03 vs. 1±0.02 (WT) fold; P&lt;0.02 ) and protein (62±4 vs. 100±6%; P&lt;0.04) and were pooled together for analysis. D 2 R function was also decreased as determined by the decreased ability of a D 2 R agonist to increase PMA-induced cAMP accumulation (hRPTC-SNP: 201±16; hRPTC-WT 270 ±5 %; n=4; P&lt;0.05). The expression of the pro-inflammatory cytokines TNFα (2.5 ± 0.3 fold; P&lt;0.04) and CD40L (2.3 ± 0.5 fold; P&lt;0.05), as well as the inflammation marker CRP (1.5 ± 0.2 fold; P&lt;0.04) was increased in hRPTC-SNP. The expression of the pro-fibrotic TGFβ1 (1.8 ± 0.4 fold; P&lt;0.04) and its signaling targets PAI-1 (6.3± 0.5 fold; P&lt;0.01), SMAD3 (2.8± 0.4 fold; P&lt;0.02) and VEGFa (2.3± 0.6 fold; P&lt;0.04) were also increased. Furthermore hRPTC-SNP showed induction of epithelial mesenchymal transition and production of extracellular matrix proteins as shown by increased fibronectin -1 (3.1± 0.7 fold; P&lt;0.03), col 1a (1.6± 0.2 fold; P&lt;0.05), col 3a (2.2± 0.5 fold; P&lt;0.05), MMP3 (5.6± 0.8 fold; P&lt;0.04), and MMP9 (3.5± 0.5 fold; P&lt;0.04). These data support the hypothesis that D 2 R function has protective effects in human RPTCs and suggest that carriers of these SNPs may be prone to chronic renal disease and high blood pressure.
Leptospiral TlyC is an extracellular matrix‐binding protein and does not present hemolysin activity (2009)

The role of TlyA, TlyB and TlyC proteins in the biology of Leptospira is still uncertain. Although these proteins have been considered as putative hemolysins, we demonstrate that leptospiral recombinant TlyB and TlyC do not possess hemolytic activity. However, further experiments showed that TlyC is a surface-exposed protein that seems to bind to laminin, collagen IV and fibronectin. The expression of both proteins was detected both in vitro and in vivo. Our findings suggest that TlyB and TlyC are not directly involved in hemolysis, and that TlyC may contribute to Leptospira binding to extracellular matrix (ECM) during host infection.
Suppl Figure S1 from Efficacy of Nivolumab in Pediatric Cancers with High Mutation Burden and Mismatch Repair Deficiency (2023)

&lt;p&gt;Pathological complete remission in metastatic colorectal adenocarcinoma. (A) Baseline (hematoxylin-eosin, CD8 and PD-L1). (B) Post-nivolumab: no detectable tumor cells, increased inflammation, and increase in CD8 and PD-L1 expression. All IHC images are 100X.&lt;/p&gt;
Critical Evaluation of Organic Thin-Film Transistor Models (2018)

Thin-film transistors (TFTs) represent a wide-spread tool to determine the charge-carrier mobility of materials. Mobilities and further transistor parameters like contact resistances are commonly extracted from the electrical characteristics. However, the trust in such extracted parameters is limited, because their values depend on the extraction technique and on the underlying transistor model. We propose a technique to establish whether a chosen model is adequate to represent the transistor operation. This two-step technique analyzes the electrical measurements of a series of TFTs with different channel lengths. The first step extracts the parameters for each individual transistor by fitting the full output and transfer characteristics to the transistor model. The second step checks whether the channel-length dependence of the extracted parameters is consistent with the model. We demonstrate the merit of the technique for distinct sets of organic TFTs that differ in the semiconductor, the contacts, and the geometry. Independent of the transistor set, our technique consistently reveals that state-of-the-art transistor models fail to reproduce the correct channel-length dependence. Our technique suggests that contemporary transistor models require improvements in terms of charge-carrier-density dependence of the mobility and/or the consideration of uncompensated charges in the transistor channel.
UAS-based tracking of the Santiaguito Lava Dome, Guatemala (2020)

Imaging growing lava domes has remained a great challenge in volcanology due to their inaccessibility and the severe hazard of collapse or explosion. Changes in surface movement, temperature, or lava viscosity are considered crucial data for hazard assessments at active lava domes and thus valuable study targets. Here, we present results from a series of repeated survey flights with both optical and thermal cameras at the Caliente lava dome, part of the Santiaguito complex at Santa Maria volcano, Guatemala, using an Unoccupied Aircraft System (UAS) to create topography data and orthophotos of the lava dome. This enabled us to track pixel-offsets and delineate the 2D displacement field, strain components, extrusion rate, and apparent lava viscosity. We find that the lava dome displays motions on two separate timescales, (i) slow radial expansion and growth of the dome and (ii) a narrow and fast-moving lava extrusion. Both processes also produced distinctive fracture sets detectable with surface motion, and high strain zones associated with thermal anomalies. Our results highlight that motion patterns at lava domes control the structural and thermal architecture, and different timescales should be considered to better characterize surface motions during dome growth to improve the assessment of volcanic hazards.
Intelligent Reconciliation of Well Logs – A Pathway Towards 4IR Assisted Log Interpretation (2020)

Abstract Reservoir characterization, well log analysis and interpretation are key enablers for the optimization of field development and the maximization of recovery. Key challenges in well log analysis are that the current interpretation practices could be subjective, discrete and demanding. Additionally, comparing and analyzing well log data from multiple wells requires constraints to the geological setting. Leveraging on big data well log availability in developed areas, we present an innovative fourth industry revolution (4IR) method for the reconciliation of well logs to automatically assist the process of well log interpretation. The training set of the method consists of reconciled sonic, resistivity and density well logs together with their target set of saturation and porosity. A multi-layer neural network was trained on selected data sets and validated on a synthetic reservoir case as well as on a reservoir box model. The results are very promising, paving the way towards an innovative approach for the artificial intelligence assisted interpretation of well logs.
Robust non-linear controllers for automotive vehicle handling (2009)

The main goal of this paper is to compute high performance controllers that will allow an automotive vehicle to follow longitudinal speed and yaw rate references. Three non-linear control techniques are explored: ℋ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> Quasi-LPV, non-linear feedback linearization with ℋ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> “outer” loop and non-linear feedback linearization with two optimal PIs “outer” loop. MIMO stability margins and most significant singular values plots are computed. Controllers are then discretized for implementation within an advanced non-linear simulator jointly developed by the INRETS (French institute of safe transportation research) and RENAULT. Time domain responses in closed-loop, obtained in this environment, validate the proposed control schemes.
FDTD/K-DWM simulation of 3D room acoustics on general purpose graphics hardware using compute unified device architecture (CUDA) (2010)

The growing demand for reliable prediction of sound fields in rooms have resulted in adaptation of various approaches for physical modeling, including the Finite Difference Time Domain (FDTD) and the Digital Waveguide Mesh (DWM). Whilst considered versatile and attractive methods, they suffer from dispersion errors that increase with frequency and vary with direction of propagation, thus imposing a high frequency calculation limit. Attempts have been made to reduce such errors by considering different mesh topologies, by spatial interpolation, or by simply oversampling the grid. As the latter approach is computationally expensive, its application to three-dimensional problems has often been avoided. In this paper, we propose an implementation of the FDTD on general purpose graphics hardware, allowing for high sampling rates whilst maintaining reasonable calculation times. Dispersion errors are consequently reduced and the high frequency limit is increased. A range of graphics processors are evaluated and compared with traditional CPUs in terms of accuracy, calculation time and memory requirements.