Miracle-dz/UniFAR-FTUs huggingface dataset:
What is Aromaphilicity?

Proteins and peptides have the ability to interact with various substances such as biological molecules and artificial objects. In principle, these interactions are attributed to the interplays of amino acid residues and peptide bonds with target substances and are often described in physical terms, including electrostatic interaction, hydrogen bond, and van der Waals interaction. However, in some practical cases, conceptual scales and indices for describing the nature of amino acids, such as the hydrophilicity scale and the hydropathy index, are more useful for understanding the interactions. In recent years, I have investigated the affinity of proteins and peptides for aromatic carbon materials, such as carbon nanotubes (CNTs) and graphene, and realized that this affinity is barely described by conventional scales and indices. After speculating whether a more suitable index for describing the affinity of amino acids for aromatic carbon materials is available in such a situation, I recognized the need for a new concept that describes such an affinity. Upon establishing this concept, I named the affinity for aromatic carbon material surfaces “aromaphilicity,” meaning an aromatic-loving nature. In this Commentary and Perspective, I summarized my recent works with my collaborators regarding physical interactions between amino acids (or amino acid residues) and aromatic carbon material surfaces and introduced a new index— aromaphilicity index—of amino acids. The aromaphilicity index is unique and distinct from conventional indices for amino acids, offering prospective applications as a universal index for describing the properties of amino acids.
BEHAVIOR OF PILES SUBJECTED TO EXCAVATION-INDUCED SOIL MOVEMENT

Two neighbor tall buildings are constructed on soft soil ground.The piles of the buildings are subject to deflection due to excavation-induced soil movement.Based on the project,three-dimensional finite-difference program is applied to calculate the deflection of piles due to the soil lateral movements.The effects of pit excavation on pile deflection have also been studied.
Spreadsheet Simulation

"Spreadsheet simulation" refers to the use of a spreadsheet as a platform for representing simulation models and performing simulation experiments. This tutorial explains the reasons for using this platform for simulation, discusses why this is frequently an efficient way to build simulation models and execute them, describes how to setup a spreadsheet simulation, and finally examines some limitations on the use of spreadsheets for simulation.
University of New Hampshire Scholars' Repository University of New Hampshire Scholars

Various approaches to computational metaphor interpretation are based on pre-existing similarities between source and target domains and/or are based on metaphors already observed to be prevalent in the language. This paper addresses similarity-creating cross-modal metaphoric expressions. It is shown how the “abstract concept as object” (or reiﬁcation) metaphor plays a central role in a large class of metaphoric extensions. The described approach depends on the imposition of abstract ontological components, which represent source concepts, onto target concepts. The challenge of such a system is to represent both denotative and connotative components which are extensible, together with a framework of general domains between which such extensions can conceivably occur. An existing ontology of this kind, consistent with some mathematic concepts and widely held linguistic notions, is outlined. It is suggested that the use of such an abstract representation system is well adapted to the interpretation of both conventional and unconventional metaphor that is similarity-creating.
Classification of Highway Lane Change Behavior to Detect Dangerous Cut-in Maneuvers

Recognizing dangerous driver behavior is an essential part of predicting accurate vehicle trajectories in vehicle active safety systems. This paper proposes a lane change behavior classification approach to detect dangerous cut-in behaviors on highways. First, a probabilistic lane change behavior classifier is proposed based on Hidden Markov Models (HMMs). Then, time series data of lane changing vehicles from both normal and dangerous driving data sets are analyzed and compared to extract decisive features that are more likely to appear in dangerous lane change processes. A feature detection module is proposed specifically considering decisive features correlated to dangerous lane change. Furthermore, the feature detection module is integrated into the HMM classifier to enhance classification ability. The proposed classifier is verified with a separate test data set, and shows satisfactory results in reducing false negative rate of misclassification.
A synthetic study to evaluate the utility of hydrological signatures for calibrating a base flow separation filter

Estimation of base flow from streamflow hydrographs has been a major challenge in hydrology for decades, leading to developments of base flow separation filters. When without tracer or groundwater data to calibrate the filters, the standard approach to apply these filters in practice involves some degrees of subjectivity in choosing the filter parameters. This paper investigates the use of signature‐based calibration in implementing base flow filtering by testing seven possible hydrological signatures of base flow against modeled daily base flow produced by Li et al. (2014) for a range of synthetic catchments simulated with HydroGeoSphere. Our evaluation demonstrates that such a calibration method with few selected signatures as objectives is capable of calibrating a filter–Eckhardt filter–to yield satisfactory base flow estimates at daily, monthly and long‐term time scales, outperforming the standard approach. The best performing signatures can be readily derived from streamflow time series. While their performance depends on the catchment characteristics, the catchments where the signature method performs can be distinguished using commonly‐used descriptors of flow dynamics.
Sentient Sketchbook: Computer-Assisted Game Level Authoring

This paper introduces Sentient Sketchbook, a tool which supports a designer in the creation of game levels. Using map sketches to alleviate designer effort, the tool automates playability checks and evaluations and visualizes significant gameplay properties. Most importantly, this paper introduces constrained novelty search via a two-population paradigm for generating, in real-time, alternatives to the author’s design and evaluates its potential against current approaches. The paper concludes with a small-scale user survey during which industry experts interact with Sentient Sketchbook to design game levels. Results demonstrate the tool’s potential and provide directions for its improvement.
Analyzing Spread of Influence in Social Networks for Transportation Applications Analyzing Spread of Influence in Social Networks for Transportation Applications

For individuals with sensory disabilities, this is available in alternate ABSTRACT Using Twitter data, we developed a tool for generating a list of potential influential individuals and/or organizations for particular transportation-related topics by counting the number of mentions of a specific Twitter user and retweets of a particular tweet. Their locations are indicated in Google Maps. Although papers in the current literature propose different measures of influence using both contrived and real data, mentions and retweets are the most reliable measures of influence. To date, our work is the only work in the study of influence that is transportation-related. We believe our tool will advance the state of the practice. We have listed many purposes that can be addressed by using our tool including limiting misinformation and encouraging acceptance of a new transportation product or service. Caltrans hashtag on reviewed a of posts with the Caltrans hashtag and for a variety of including numbers of likes, positive negative posts and numbers of followers, and frequency of irrelevant posts with the hashtag non-associated individuals
Harnessing Immunoinformatics for developing a multiple-epitope peptide-based vaccination approach against SARS-CoV-2 Spike Protein

Harnessing Immunoinformatics for developing a multiple-epitope peptide-based vaccination approach against SARS-CoV-2 Spike Protein Abstract COVID-19 has spread to over 200 countries with variable severity and mortality rates. Computational analysis is a valuable tool for developing B-cell and T-cell epitope-based vaccines. In this study, by harnessing immunoinformatics tools, we designed a multiple-epitope
Building machines that learn and think about morality

Lake et al. [30] propose three criteria which, they argue, will bring artiﬁcial intelligence (AI) systems closer to human cognitive abilities. In this paper, we explore the application of these criteria to a particular domain of human cognition: our capacity for moral reasoning. In doing so, we explore a set of considerations relevant to the development of AI moral decision-making. Our main focus is on the relation between dual-process accounts of moral reasoning and model-free/model-based forms of machine learning. We also discuss how work in embodied and situated cognition could provide a valuable perspective on future research.
Old growth in northwestern California national forests.

Summary Beardsley, Debby; Warbington, Ralph. 1996. Old growth in northwestern California National Forests. Res. Pap. PNW-RP-491. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 47 p. This report estimates old-growth forest area and summarizes stand characteristics of old growth in northwestern California National Forests by forest type. Old-growth definitions for each forest type are used.
ATPG For Scan Chain Latches and Flip-Flops

A new approach for testing the bistable elements (latches and flip-flops) in scan chain circuits is presented. In this approach, we generate test patterns that apply a checking experiment to each bistable element in the circuit while checking their response. Such tests guarantee the detection of all detectable combinational defects inside the bistable el ments. The algorithm is implemented by modifying an existing stuck-at combinational test pattern generator. The number of test patterns generated by the new program is comparable to the number of traditional stuck-at patterns. This shows that this approach is practical for large circuits.
Word Frequencies in Written and Spoken English: based on the British National Corpus

Resulting from inter-disciplinary research with Linguistics, this book addressed limitations of earlier word frequency dictionaries of English, that of sample size and breadth. It supercedes previous landmark volumes from the 1930s and 1960s. We used a large representative corpus (100 million words) of up-to-date written, and importantly, spoken language. The book has been cited within the computational and corpus linguistics communities as well as making impact more widely (ontology literature, psychology, language teaching and HCI). The publication led directly to a new series of frequency dictionaries for major world languages published by Routledge, also co-edited by Rayson.
PATTERN RECOGNITION BASED SPEED FORECASTING METHODOLOGY FOR URBAN TRAFFIC NETWORK

A full methodology of short-term traffic prediction is proposed for urban road traffic network via artificial neural network. The goal of the forecasting is to provide speed estimation forward by 5, 15, and 30 minutes. Unlike similar research results in this field, the investigated method aims to predict traffic speed for signalized urban road links and not for highway or arterial roads. The methodology contains an efficient feature selection algorithm in order to determine the appropriate input parameters required for neural network training. As another contribution of the paper, a built-in incomplete data handling is provided as input data (originating from traffic sensors or floating car data) might be absent or biased in practice. Therefore, input data handling can assure a robust operation of speed forecasting also in case of missing data. The proposed algorithm is trained, tested and analysed in a test network built-up in a microscopic traffic simulator by using daily course of real-world traffic.
Scalable Computing: Practice and Experience

We investigate the use of the multistep successive preconditioning strategies (MSP) to construct a class of parallel multilevel sparse approximate inverse (SAI) preconditioners. We do not use independent set ordering, but a diagonal dominance based matrix permutation to build a multilevel structure. The purpose of introducing multilevel structure into SAI is to enhance the robustness of SAI for solving difficult problems. Forward and backward preconditioning iteration and two Schur complement preconditioning strategies are proposed to improve the performance and to reduce the storage cost of the multilevel preconditioners. One version of the parallel multilevel SAI preconditioner based on the MSP strategy is implemented. Numerical experiments for solving a few sparse matrices on a distributed memory parallel computer are reported.
MapReduce Online

MapReduce is a popular framework for data-intensive distributed computing of batch jobs. To simplify fault tolerance, many implementations of MapReduce materialize the entire output of each map and reduce task before it can be consumed. In this paper, we propose a modified MapReduce architecture that allows data to be pipelined between operators. This extends the MapReduce programming model beyond batch processing, and can reduce completion times and improve system utilization for batch jobs as well. We present a modified version of the Hadoop MapReduce framework that supports online aggregation, which allows users to see "early returns" from a job as it is being computed. Our Hadoop Online Prototype (HOP) also supports continuous queries, which enable MapReduce programs to be written for applications such as event monitoring and stream processing. HOP retains the fault tolerance properties of Hadoop and can run unmodified user-defined MapReduce programs.
High performance N-body simulation on computational grids

Een N-bodysimulatie is een simulatie van een dynamisch systeem van deeltjes, meestal onder invloed van natuurkundige krachten zoals zwaartekracht. Gravitationele N-bodysimulaties zijn essentiele instrumenten om inzicht te krijgen in de vorming van sterrenhopen, sterrenstelsels en het universum als geheel. Ze worden echter veelvuldig uitgevoerd op een enkele supercomputer, terwijl er wereldwijd vele honderden supercomputers zijn. Het gebruik van meerdere supercomputers tegelijk maakt het mogelijk om bijvoorbeeld sterrenstelsels in groter detail na te bootsen. Derek Groen voerde simulaties uit die maximaal vier supercomputers tegelijk gebruiken. Deze machines zijn met elkaar verbonden via een intercontinentaal netwerk. De kosmologische N-bodysimulaties blijken heel geschikt om over meerdere supercomputers uit te voeren, en het gebruik van een intercontinentaal netwerk blijkt weinig effect te hebben op de algehele prestaties van de simulaties (ongeveer10% overhead voor de meest grootschalige simulaties). Groen verwacht op basis van zijn modellen dat kosmologische simulaties efficient uitgevoerd kunnen worden over tientallen supercomputers, mits deze machines tegelijkertijd benut kunnen worden.
Thermal conductivity of geosynthetic clay liners

The thermal conductivities of powdered and granular bentonite based needle punched geosynthetic clay liners (GCLs) were investigated at different gravimetric water contents under 25, 50, 75, and 100 kPa vertical stresses. Both types of GCLs exhibited an increase in thermal conductivity with increasing vertical stress at all water contents. The effect of vertical stresses was more pronounced for the specimens hydrated at lower gravimetric water contents and this was attributed to their high initial volumetric air content. The variability of water distribution in partially hydrated GCLs has been identified as a factor that may affect their thermal conductivity. The forms of bentonites (i.e., powder or granular) affected their thermal conductivities; however, this effect was less apparent at higher gravimetric water contents due to the reduced air content and gel formation in the bentonites. Finally, the GCL thermal conductivity calculated from the measured thermal conductivities of its various constituents .
CoSy Cognitive Systems for Cognitive Assistants Integrated Project Information Society Technologies Deliverable 8 . 8 Spatio-temporal and Functional Aspects of Spatial Cognition for Spatial Language Comprehension

The article presents an approach to modeling spatio-temporal comprehension in situated dialogue. The approach combines linguistic reasoning with reasoning about intentions and plans during incremental interpretation of dialogue moves. The article explores how intention-directed planning can prime selectional attention in utterance comprehension by disambiguating linguistic analyses on the basis of plan availability, and by raising expectations what action(s) may be mentioned next. Also, planning can complement linguistic analyses with details on spatiotemporal-causal structure established in planning inferences. This makes such inferences available for future referencing in the discourse context.
Facial feature tracking and expression recognition for sign language

Facial expressions play a vital role in sign language by changing the meaning of the performed sign. In this work, we propose a system composed of a facial feature tracker based on Active Shape Models and a classifier based on Hidden Markov Models to recognize common facial expressions used in sign language. Face tracker works in multi-resolution and multi-view to track faces in different poses fast and effectively. Detailed tests are prepared to report the accuracy of the tracker and classifier, and it is seen that the system works in high accuracy and robustly.
A ray tracing solution for diffuse interreflection

An efficient ray tracing method is presented for calculating interreflections between surfaces with both diffuse and specular components. A Monte Carlo technique computes the indirect contributions to illuminance at locations chosen by the rendering process. The indirect illuminance values are averaged over surfaces and used in place of a constant "ambient. " term. Illuminance calculations are made only for those areas participating in the selected view, and the results are stored so that subsequent views can reuse common values. The density of the calculation is adjusted to maintain a constant accuracy, permitting less populated portions of the scene to be computed quickly. Successive reflections use proportionally fewer samples, which speeds the process and provides a natural limit to recursion. The technique can also model diffuse transmission and illumination from large area sources, such as the sky.
Precise memory leak detection for java software using container profiling

A memory leak in a Java program occurs when object references that are no longer needed are unnecessarily maintained. Such leaks are difficult to detect because static analysis typically cannot precisely identify these redundant references, and existing dynamic leak detection tools track and report fine-grained information about individual objects, producing results that are usually hard to interpret and lack precision. In this article we introduce a novel container-based heap-tracking technique, based on the fact that many memory leaks in Java programs occur due to incorrect uses of containers, leading to containers that keep references to unused data entries. The novelty of the described work is twofold: (1) instead of tracking arbitrary objects and finding leaks by analyzing references to unused objects, the technique tracks only containers and directly identifies the source of the leak, and (2) the technique computes a confidence value for each container based on a combination of its memory consumption and its elements' staleness (time since last retrieval), while previous approaches do not consider such combined metrics. Our experimental results show that the reports generated by the proposed technique can be very precise: for two bugs reported by Sun, a known bug in SPECjbb 2000, and an example bug from IBM developerWorks, the top containers in the reports include the containers that leak memory.
PowerBookmarks: A System for Personalizable Web Information Organization, Sharing, and Management

We extend the notion of bookmark management by introducing the functionalities of hypermedia databases. PowerBookmarks is a Web information organization, sharing, and management tool, which parses metadata from bookmarked URLs and uses it to index and classify the URLs. PowerBookmarks supports advanced query, classi(cid:12)cation, and navigation functionalities on collections of bookmarks. Power-Bookmarks monitors and utilizes users’ access patterns to provide many useful personalized services, such as automated URL bookmarking, document refreshing, and bookmark expiration. It also allows users to specify their preference in bookmark management, such as ranking schemes and classi(cid:12)cation tree structures. Subscrip-tion services for new or updated documents of users’ interests are also supported.
Linear Zero-knowledge -a Note on Eecient Zero-knowledge Proofs and Arguments

We present a 4-move zero-knowledge proof system 21] for any NP language L, which allows showing that x 2 L with error probability less than 2 ? k using communication corresponding to O(jxj c)+O(k) bit commitments , where c is a constant depending only on L. We also present a 4-move perfect zero knowledge interactive argument for any NP-language L. On input x 2 L, the communication complexity is O(jxj c)max(k; l) bits, where l is the security parameter for the prover 1. The protocols can be based on any bit commitment scheme with a particular set of properties. We suggest eecient implementations based on discrete logarithms or factoring. As a function of the security parameters, our protocols have the smallest known asymptotic communication complexity among general proofs or arguments for NP. Moreover, the constants involved are small enough for the protocols to be practical in a realistic situation: our protocols allows proving/arguing satissabil-ity of a Boolean formula (containing and-, or-and not-operators) with communication complexity at most 6n + 2 commitments for the interactive proof and at most 5nl + 10l bits for the argument (assuming k l), where n is the number of times reads an input vari-1 The meaning of l is that if the prover is unable to solve an instance of a hard problem of size l before the protocol is nished, he can cheat with probability at most 2 ? k able. Thus, if we use k = n, the number of commitments required for the proof is linear in n. Finally, we present an application of our results that results in a protocol for oblivious transfer requiring O(1) commitments of size O(k) bits for a maximal cheating probability of 2 ? k. Corresponding results for multiparty computations follow from this.