gebhart/patrepeval huggingface dataset:
Structure of a regulatory complex involving the Abl SH3 domain, the Crk SH2 domain, and a Crk-derived phosphopeptide (2002)

On phosphorylation of Y221 by Abelson (Abl) kinase, the Crk-II adapter protein undergoes an intramolecular reorganization initiated by the binding of its own Src homology 2 (SH2) domain to the pY221 site. Conformational changes induced by phosphotyrosine recognition promote the binding of the Src homology 3 (SH3) domain of the Abl tyrosine kinase to a proline-rich loop located between the betaD and betaE strands of the SH2 domain (DE loop). We have determined the NMR solution structure of the ternary complex of the Abl SH3 domain with the Crk SH2 domain bound to a Crk pY221 phosphopeptide. The SH2 domain bridges two ligands that bind at distinct sites. The interaction between the Abl SH3 domain and the Crk SH2 domain is localized to a canonical eight-residue site within the DE loop. From (15)N relaxation experiments, the DE loop of the SH2 domain in the complex displays a significant degree of conformational freedom. The structural and dynamic data therefore indicate that these SH2 and SH3 domains do not assume a unique orientation with respect to one another; rather, they appear to be only tethered via the DE loop. Thus, SH2 domain-SH3 domain interactions do not require additional tertiary contacts or restriction of domain orientation when a recognition motif is presented in a mobile loop. This complex between the Abl SH3 domain, Crk SH2 domain, and Crk phosphopeptide is an example of the extremely modular nature of regulatory proteins that provides a rich repertoire of mechanisms for control of biological function.
Localized positioning in ad hoc networks (2003)

Position centric approaches, such as Cartesian routing, geographic routing, and the recently proposed trajectory based forwarding (TBF), address scalability issues in large ad hoc networks by using Euclidean space as a complementary name space. These approaches require. that nodes know their position in a common coordinate system. While a GPS receiver in each node would be ideal, in many cases an approximation algorithm is necessary for networks with only a few GPS enabled nodes. These algorithms however require collaboration of large portions of the network, thus imposing an overhead for nodes which do not need positioning, or are mobile. We propose Local Positioning System (LPS), a method that makes use of local node capabilities-angle of arrival, range estimations, compasses and accelerometers, in order to internally position only the groups of nodes involved in particular conversations. Localized positioning enables position centric uses, like discovery, flooding and routing in networks where global positioning is not available.
KAJAOLALIDDONG, THE INTELLECTUAL OF BUGIS BONE : From The Historical Perspective (2018)

Kajaolaliddong was well known as a scholar and advisor to the King of Bone in term life mainly related to basic values of state (kingdom), law, and/or political culture. The thoughts of Kajaolaliddong cover the aspects of customs, justice, jurisprudence, and complete governmental systems. Kajaolaliddong was an ambassador to assist the King in overcoming the problems which occurred with the neighboring kingdoms. Besides, this appointment aimed to grow and develop the Kingdom of Bone. The methods used were the library research referring to the ancients documents, such as lontaraq (Buginese ancient manuscript), oral and previous studies. The study shows that the basic pattern called pangadereng (customs) later becomes references of the King and other officials in their activities. The main narrations of Kajaolaliddong thoughts were lempue nasibawai tau (honesty and religiosity), ada tongeng nasibawa tike (true words with vigilance), siri nasibawai getting (shame or self esteem with determination), awaraningeng nasibawai nyameng kininnawa (courage with love), appesona ri Dewata seuwwae (surrender to One God). Of these five components, Kajaolaliddong thoughts emphasized three major components, namely honesty, intelligence, and courage.
Accurate and Efficient Traffic Monitoring Using Adaptive Non-Linear Sampling Method (2008)

Sampling technology has been widely deployed in measurement systems to control memory consumption and processing overhead. However, most of the existing sampling methods suffer from large estimation errors in analyzing small-size flows. To address the problem, we propose a novel adaptive non-linear sampling (ANLS) method for passive measurement. Instead of statically configuring the sampling rate, ANLS dynamically adjusts the sampling rate for a flow depending on the number of packets having been counted. We provide the generic principles guiding the selection of sampling function for sampling rate adjustment. Moreover, we derive the unbiased flow size estimation, the bound of the relative error, and the bound of required counter size for ANLS. The performance of ANLS is thoroughly studied through theoretic analysis and experiments under synthetic/real network data traces, with comparison to several related sampling methods. The results demonstrate that the proposed ANLS can significantly improve the estimation accuracy, particularly for small-size flows, while maintain a memory and processing overhead comparable to existing methods.
A variable transverse stiffness sandwich structure using fluidic flexible matrix composites (F<sup>2</sup>MC) (2008)

Presented in this paper is the development of a novel honeycomb sandwich panel with variable transverse stiffness. In this structure, the traditional sandwich face sheets are replaced by the fluidic flexible matrix composite (F<sup>2</sup>MC) tube layers developed in recent studies. The F<sup>2</sup>MC layers, combined with the anisotropic honeycomb core material properties, provide a new sandwich structure with variable stiffness properties for transverse loading. In this research, an analytical model is derived based on Lekhitskii's anisotropic pressurized tube solution and Timoshenko beam theory. Experimental investigations are also conducted to verify the analytical findings. A segmented multiple-F<sup>2</sup>MC-tube configuration is synthesized to increase the variable stiffness range. The analysis shows that the new honeycomb sandwich structure using F<sup>2</sup>MC tubes of 10 segments can provide a high/low transverse stiffness ratio of 60. Segmentation and stiffness control can be realized by an embedded valve network, granting a fast response time.
Biparametric Potentiometric Analytical Microsystem Based on the Green Tape Technology (2010)

Abstract The construction and evaluation of a Low Temperature Co‐fired Ceramics (LTCC)‐based microsystem prototype as a possible on‐site microanalyzer to monitor the presence of two ions in water simultaneously is presented. The approach has been assayed to detect nitrate and chloride ions as model analytes by means of integrating in the same single substrate an ion selective polymeric membrane to nitrate and two screen‐printed Ag/AgCl electrodes. One supplies the chloride ion concentration and the other is to complete the potentiometric detection system as the reference electrode. The results obtained by the full characterization of the microanalyzer prove the relevance of the proposal and the possibility to be transferred to real‐world samples and environmental monitoring.
Interactive solving of vehicle routing and scheduling problems: basic concepts and qualification of tabu search approaches (2003)

This paper introduces a framework for the interactive solving of optimization problems and presents an interactive tabu search algorithm for the pick-up-and-delivery problem with time windows (PDPTW). The framework for the development of interactive algorithms is based on the idea of activating and deactivating constraints in the model of the problem under consideration. We start with an introduction to interactive problem solving and suggest an algorithmic framework. Next we focus on vehicle routing and scheduling applications. There we discuss the demand for interactive approaches, since established local search methods fail to produce reasonable solutions. Our idea is to support them by interactive manipulations. Therefore, we present a recent tabu search algorithm for the PDPTW We demonstrate several possibilities for human interactions by means of an additional tabu list.
Stabilizing Exposure of Conserved Epitopes by Structure Guided Insertion of Disulfide Bond in HIV-1 Envelope Glycoprotein (2013)

Entry of HIV-1 into target cells requires binding of the viral envelope glycoprotein (Env) to cellular receptors and subsequent conformational changes that culminates in fusion of viral and target cell membranes. Recent structural information has revealed that these conformational transitions are regulated by three conserved but potentially flexible layers stacked between the receptor-binding domain (gp120) and the fusion arm (gp41) of Env. We hypothesized that artificial insertion of a covalent bond will 'snap' Env into a conformation that is less mobile and stably expose conserved sites. Therefore, we analyzed the interface between these gp120 layers (layers 1, 2 and 3) and identified residues that may form disulfide bonds when substituted with cysteines. We subsequently probed the structures of the resultant mutant gp120 proteins by assaying their binding to a variety of ligands using Surface Plasmon Resonance (SPR) assay. We found that a single disulfide bond strategically inserted between the highly conserved layers 1 and 2 (C65-C115) is able to 'lock' gp120 in a CD4 receptor bound conformation (in the absence of CD4), as indicated by the lower dissociation constant (Kd) for the CD4-induced (CD4i) epitope binding 17b antibody. When disulfide-stabilized monomeric (gp120) and trimeric (gp140) Envs were used to immunize rabbits, they were found to elicit a higher proportion of antibodies directed against both CD4i and CD4 binding site epitopes than the wild-type proteins. These results demonstrate that structure-guided stabilization of inter-layer interactions within HIV-1 Env can be used to expose conserved epitopes and potentially overcome the sequence diversity of these molecules.
Classification of Cape Gooseberry Fruit According to its Level of Ripeness Using Machine Learning Techniques and Different Color Spaces (2019)

The classification of fresh fruits according to their visual ripeness is typically a subjective and tedious task; consequently, there is a growing interest in the use of non-contact techniques to automate this process. Machine learning techniques, such as artificial neural networks, support vector machines (SVMs), decision trees, and K-nearest neighbor algorithms, have been successfully applied for classification problems in the literature, particularly for images of fruit. However, the particularities of each classification problem make it difficult, if not impossible, to select a general technique that is applicable to all types of fruit. In this paper, the combinations of four machine learning techniques and three color spaces ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RGB</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HSV</i> , and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L*a*b*</i> ) were evaluated with regard to their ability to classify Cape gooseberry fruits. To this end, 925 Cape gooseberry fruit samples were collected, and each fruit was manually classified into one of seven different classes according to its level of ripeness. The color values of each fruit image in the three color spaces and their corresponding ripening stages were organized for training and validation following a fivefold cross-validation strategy in an iterative process repeated 100 times. According to the results, the classification of Cape gooseberry fruits by their ripeness level was sensitive to both the color space and the classification technique used. The models based on the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L*a*b*</i> color space and the SVM classifier showed the highest f-measure regardless of the color space, and the principal component analysis combination of color spaces improved the performance of the models at the expense of increased complexity.
Retinoblastoma protein and simian virus 40-dependent immortalization of human fibroblasts (1991)

Transformation and immortalization of human diploid fibroblasts by simian virus 40 (SV40) is at least a two-stage process, since transformants have a limited lifespan in culture. We have isolated immortalized derivatives (AR5 and HAL) from transformants generated with an origin-defective SV40 genome encoding a heat-labile large T protein (T antigen) and reported that both preimmortal and immortal transformants are continuously dependent on T antigen function for growth as determined by temperature shift experiments. In this study, we demonstrate complex formation between T antigen and the retinoblastoma susceptibility gene product (Rb) at 35 degrees C and observed a reduction in complexes under conditions of loss of T antigen function and growth inhibition at 39 degrees C. Viral oncogenes (polyomavirus large T protein and adenovirus E1A 12S protein) known to bind Rb were introduced into AR5 and HAL cells, both stably by gene transfer and transiently by virus vectors. Such double transformants are still unable to proliferate at 39 degrees C, although complex formation with the newly introduced oncogenes was demonstrated. We suggest that T antigen interacts with other cellular processes in addition to Rb to transform and immortalize human cells in culture. Our finding that p53-T antigen complexes are also temperature dependent in AR5 and HAL cells could provide such an additional mechanism.
Genomic Profiling Uncovers a Molecular Pattern for Toxicological Characterization of Mutagens and Promutagens In Vitro (2011)

The aim of this study was to evaluate the suitability of global gene expression profiling for the characterization and identification of mutagens and promutagens in vitro. To enable detection of both mutagenic and promutagenic compounds, we cotreated HepG2 cells with a rat liver S9 fraction as metabolic activation system (MAS), supplementing the limited drug metabolic capability of HepG2 cells. Illumina BeadChip arrays were used to quantify gene expression changes after treatment with three well-known mutagenic, three promutagenic, as well as two nongenotoxic reference compounds for a period of 24 or 48 h. Statistical data analysis revealed 91 genes being most representative for the (pro-)genotoxic response. Several processes such as cellular differentiation and the complex interactive regulation of the stress and DNA damage response via the transcriptional modulators STAT1, SP1, and P53 were differentially regulated. The gene set evaluated was further used to predict the genotoxic characteristics of N-nitrosodiethylamine (DEN) after its metabolic activation. Although no clear response could be established in P53 activation experiments, DEN was classified correctly as nongenotoxic without S9 and genotoxic in the presence of the MAS by means of its transcriptomic pattern. Our data support that mechanistic profiling in vitro is a useful tool compared with single endpoint detections to predict genotoxicity.
Geometric modeling and recognition of elongated regions in aerial images (1989)

The authors present a curve-fitting method for the recovery of elongated regions in aerial images by analyzing the local image features that constitute these regions. Elongation is defined in terms of an axial model that describes a broad class of objects found in aerial scenes. The authors fit the model using a perceptual strip clustering that maintains constraints on feature connectivity and curvilinear alignment. Connectivity is obtained from internal representations of closest-point properties, specifically, a thresholded version of the Gabriel graph. This is shown to offer the advantages of both the minimum spanning tree and the Delauney triangulation, while being easily computable from finite neighborhood operations. An iterative curve fitting is used for the clustering of maximally elongated partitions, incorporating the perceptual constraints. This has the ability to interpolate across missing elements with a smooth curve, while ignoring nearby complicating structures and systematic gross noise. The general parametric strip model is described, with specific algorithms and examples given for lines and circles. A complete analysis of linear shape in low-level region segmentations is presented, with results for a suburban road network.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Multidirectional Routing in Wavelength Selective Switches (2015)

We present a novel configuration of bidirectionally-utilized WSSs, which enables routing of wavelengths between tributary ports. The proposed configuration enables realization of OXCs and ROADMs with fewer numbers of WSSs than would conventionally be required.
3D Human Pose Machines with Self-supervised Learning (2019)

Driven by recent computer vision and robotic applications, recovering 3D human poses has become increasingly important and attracted growing interests. In fact, completing this task is quite challenging due to the diverse appearances, viewpoints, occlusions and inherently geometric ambiguities inside monocular images. Most of the existing methods focus on designing some elaborate priors /constraints to directly regress 3D human poses based on the corresponding 2D human pose-aware features or 2D pose predictions. However, due to the insufficient 3D pose data for training and the domain gap between 2D space and 3D space, these methods have limited scalabilities for all practical scenarios (e.g., outdoor scene). Attempt to address this issue, this paper proposes a simple yet effective self-supervised correction mechanism to learn all intrinsic structures of human poses from abundant images. Specifically, the proposed mechanism involves two dual learning tasks, i.e., the 2D-to-3D pose transformation and 3D-to-2D pose projection, to serve as a bridge between 3D and 2D human poses in a type of "free" self-supervision for accurate 3D human pose estimation. The 2D-to-3D pose implies to sequentially regress intermediate 3D poses by transforming the pose representation from the 2D domain to the 3D domain under the sequence-dependent temporal context, while the 3D-to-2D pose projection contributes to refining the intermediate 3D poses by maintaining geometric consistency between the 2D projections of 3D poses and the estimated 2D poses. Therefore, these two dual learning tasks enable our model to adaptively learn from 3D human pose data and external large-scale 2D human pose data. We further apply our self-supervised correction mechanism to develop a 3D human pose machine, which jointly integrates the 2D spatial relationship, temporal smoothness of predictions and 3D geometric knowledge. Extensive evaluations on the Human3.6M and HumanEva-I benchmarks demonstrate the superior performance and efficiency of our framework over all the compared competing methods.
Absorption measurements of doped thin film InP for solar cell modeling (2003)

The first direct transmission measurement of above bandedge absorption coefficients in InP are reported. A novel technique for fabricating high-quality single crystal InP thin films is used to fabricate the thin films for transmission measurements. Two InP thin films were fabricated in this manner, one with a doping concentration of 1.4*10/sup 17/ cm/sup -3/ and the other with a doping concentration of 32*10/sup 18/ cm/sup -3/. Absorption coefficients were obtained from transmission measurements made on these two films, and were used to calculate the cell performance and quantum efficiency of an InP solar cell. These results were then compared with similar calculations made on the same cell using absorption coefficients for undoped InP, which are commonly used due to the lack of absorption coefficient data for doped InP. Model calculations with the directly measured absorption coefficients resulted in a cell efficiency which was significantly different from the efficiency of the cell with undoped InP absorption coefficients. This demonstrates that correct absorption coefficients are necessary to accurately model InP devices which utilize highly doped regions.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
An Online Defense Framework against Cyber Attacks on Automatic Generation Control. (2017)

We propose an online framework to defend against cyber attacks on Automatic Generation Control (AGC). A cyber attack detection algorithm is designed based on the approach of Dynamic Watermarking. The detection algorithm provides a theoretical guarantee of detection of cyber attacks launched by sophisticated attackers possessing extensive knowledge of the physical and statistical models of targeted power systems. The proposed framework is practically implementable, as it needs no hardware update on generation units. The efficacy of the proposed framework is validated by a four-area synthetic power system.
A novel Monte Carlo simulation procedure for modelling COVID-19 spread over time (2020)

The coronavirus disease 2019 (COVID-19) has now spread throughout most countries in the world causing heavy life losses and damaging social-economic impacts. Following a stochastic point process modelling approach, a Monte Carlo simulation model was developed to represent the COVID-19 spread dynamics. First, we examined various expected performances (theoretical properties) of the simulation model assuming a number of arbitrarily defined scenarios. Simulation studies were then performed on the real COVID-19 data reported (over the period of 1 March to 1 May) for Australia and United Kingdom (UK). Given the initial number of COVID-19 infection active cases were around 10 for both countries, the model estimated that the number of active cases would peak around 29 March in Australia (≈ 1,700 cases) and around 22 April in UK (≈ 22,860 cases); ultimately the total confirmed cases could sum to 6,790 for Australia in about 75 days and 206,480 for UK in about 105 days. The results of the estimated COVID-19 reproduction numbers were consistent with what was reported in the literature. This simulation model was considered an effective and adaptable decision making/what-if analysis tool in battling COVID-19 in the immediate need, and for modelling any other infectious diseases in the future.
Seismic signal detection by fractal dimension analysis (1999)

Abstract We introduce a new detection algorithm with improved local and regional seismic signal recognition. The method is based on the difference between seismic signals and background random noise in terms of fractal dimension D. We compare the new method extensively with standard methods currently in use at the Seismic Network of the Istituto Nazionale di Geofisica. Results from the comparisons show that the new method recognizes seismic phases detected by existing procedures, and in addition, it features a greater sensitivity to smaller signals, without an increase in the number of false alarms. The new method was tested on real continuous data and artificially simulated high-noise conditions and demonstrated a capability to recognize seismic signals in the presence of high noise. The efficiency of the method is due to a radically different approach to the topic, in that the assertion that a signal is fractal implies a relationship between the spectral amplitude of different frequencies. This relationship allows, for the fractal detector, a complete analysis of the entire frequency range under consideration.