Miracle-dz/UniFAR-FTUs huggingface dataset:
An Analysis of the Immersed Perspective Flight Path Display Benefit: Benefits of Preview, Prediction, and Frame of Reference

A theoretical explanation for an immersed perspective flight path display is investigated in this current study. Past research suggests that the immersed perspective flight path display (" tunnel-in-the-sky ") can improve flight path tracking when compared to more conventional flight navigation instruments but at present the specific sources of this benefit have not adequately been explained. On the basis of past research, four properties of the tunnel were investigated. These are egocentric frame of reference, preview of the flight path, prediction of future aircraft location, and a high display gain. The four variables of frame of reference, preview, prediction, and display gain were experimentally contrasted in a partially crossed factorial design to investigate the relative contributions of each variable to the tunnel benefit. A quickened display condition was also included. Twenty-four subjects were asked to fly an aircraft through a series of vertically and laterally changing flight paths on a PC based simulation using eleven different displays incorporating the variables of interest. The dependent measures of root mean squared error in lateral and vertical tracking, mean number of resets, and mean number of control inputs were collected. The results showed that preview benefits were greater than those of prediction. An interaction of prediction and preview was found, with the benefits of prediction sometimes being contingent on the presence of preview. Explanations of control order account for the finding that prediction and preview benefited lateral tracking more than vertical tracking. The egocentric frame of reference was found to play a large role in the tunnel benefit. This was especially true in conjunction with preview such that performance without a tunnel was benefited by an egocentric viewpoint. The large cost of an exocentric frame of reference was mediated by the paired presence of prediction and preview in the altitude data. The larger display gain appears to account for no portion of the egocentric frame of reference benefit.
Advanced techniques for designing stealthy hardware trojans

The necessity of detecting malicious modifications in hardware designs has led to the development of various detection tools. Trojan detection approaches aim to reveal compromised designs using several methods such as static code analysis, side-channel dynamic signal analysis, design for testing, verification, and monitoring architectures etc. This paper demonstrates new approaches for circumventing some of the latest Trojan detection techniques. We introduce and implement stealthy Trojans designs that do not violate the functional specifications of the corresponding original models. The designs chosen to demonstrate the effectiveness of our techniques correspond to encryption algorithms and a pseudo random number generator. The proposed Trojans are inserted into the original RTL, and decrease the overall security of the designs, minimizing detection probability by state-of-the-art static analysis tools.
Reinforced Tabu Search for Graph Coloring

Tabu search (TS) [21] was first applied to graph coloring by Hertz and de Werra in 1987 [23]. Even today, the original Tabucol algorithm as well as its variants are among the best reference algorithms for general graph coloring. In this paper, we describe a Reinforced TS (RTS) coloring algorithm and show improved results on the well-established Dimacs challenge graphs. The improvement is essentially achieved by employing more informative evaluation functions as well as an adaptive technique for tuning the tabu list. We show that RTS can equal the best-known results for many of the Dimacs graphs while remaining quite simple.
Human video textures

This paper describes a data-driven approach for generating photorealistic animations of human motion. Each animation sequence follows a user-choreographed path and plays continuously by seamlessly transitioning between different segments of the captured data. To produce these animations, we capitalize on the complementary characteristics of motion capture data and video. We customize our capture system to record motion capture data that are synchronized with our video source. Candidate transition points in video clips are identified using a new similarity metric based on 3-D marker trajectories and their 2-D projections into video. Once the transitions have been identified, a video-based motion graph is constructed. We further exploit hybrid motion and video data to ensure that the transitions are seamless when generating animations. Motion capture marker projections serve as control points for segmentation of layers and nonrigid transformation of regions. This allows warping and blending to generate seamless in-between frames for animation. We show a series of choreographed animations of walks and martial arts scenes as validation of our approach.
Scant Collinearity in Gene Order Shows Arabidopsis Comparative Genomics Between Rice and Material Supplemental

Material Supplemental http://genome.cshlp. org/content/suppl/2001/12/03/11.12. 2020.DC1. html References http://genome.cshlp. org/content/11/12/2020.full. html#ref-list-1 This article cites 18 articles, 9 of which can be accessed free at: License Commons Creative http://creativecommons.org/licenses/by-nc/3.0/. described at a Creative Commons License (Attribution-NonCommercial 3.0 Unported License), as ). After six months, it is available under http://genome.cshlp. org/site/misc/terms.xhtml first six months after the full-issue publication date (see This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the
Is Quantum Mechanics Falsifiable? A computational perspective on the foundations of Quantum Mechanics

Quantum computation teaches us that quantum mechanics exhibits exponential complexity. We argue that the standard scientific paradigm of "predict and verify" cannot be applied to testing quantum mechanics in this limit of high complexity. We describe how QM can be tested in this regime by extending the usual scientific paradigm to include {\it interactive experiments}.
Rethinking Storage for Discard-Based Search

The workload characteristics of content-based image retrieval are poorly suited to existing storage architectures. This is particularly true for discard-based search, where images are filtered on-demand, potentially at the storage devices themselves (an active disk technique referred to as early discard). In general, discard-based search is a highly concurrent, sequential, and read-only workload, making it ideally suited for JBOD (“just a bunch of disks”), as opposed to a more familiar RAID configuration. Further, as with most image databases, no specific order is imposed on the retrieved images. In the context of discard-based search, such any-order semantics introduce a variety of opportunities to the storage system designer (e.g., an I/O coalescing technique called “bandwagon synchronization”). This paper examines the storage workloads of discard-based search, and discusses the implications for a new storage system specifically designed for content-based image retrieval. In addition, representative synthetic workloads are used to demonstrate the efficiency of JBOD over RAID, and to quantify the benefits of bandwagon synchronization. We show that JBOD achieves 80–90% of an array’s bandwidth (depending on the level of I/O concurrency and the average object size), compared to 40–80% for RAID-0. This research was partly supported by the National Science Foundation (NSF) under grant number CNS-0614679. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF, Carnegie Mellon University, or Intel Corp.
Do Managers Influence Their Pay? Evidence from Stock Price Reversals Around Executive Option Grants

Using a database of 605,106 option grant filings by insiders between 1992 and 2002, we find significant abnormal stock return reversals around the grant date. Consistent with the hypothesis that managers influence their pay, the reversals are positively related to grant size and the seniority of the manager, and negatively related to the firm size. The reversals are also more pronounced for grants that are not awarded on a regular schedule. The returns following the grant date are negatively correlated to the returns prior to the grant date, indicating that some firms are attempting to influence the grant date stock price by more than just timing the grant date or timing information releases around the grant date. We find that the extent of reversals are positively related to the magnitude of the time interval between the grant date and the date the grants are reported to the SEC, suggesting that some firms are setting the grant date on a back-date basis, i.e., picking a date in the past with a lower stock price compared to that on the decision date.
Artificial Selection Reveals High Genetic Variation in Phenology at the Trailing Edge of a Species Range

Species responses to climate change depend on the interplay of migration and adaptation, yet we know relatively little about the potential for adaptation. Genetic adaptations to climate change often involve shifts in the timing of phenological events, such as flowering. If populations at the edge of a species range have lower genetic variation in phenological traits than central populations, then their persistence under climate change could be threatened. To test this hypothesis, we performed artificial selection experiments using the scarlet monkeyflower (Mimulus cardinalis) and compared genetic variation in flowering time among populations at the latitudinal center, northern edge, and southern edge of the species range. We also assessed whether selection on flowering time yielded correlated responses in functional traits, potentially representing a cost associated with early or late flowering. Contrary to prediction, southern populations exhibited greater responses to selection on flowering time than central or northern populations. Further, selection for early flowering resulted in correlated increases in specific leaf area and leaf nitrogen, whereas selection for late flowering led to decreases in these traits. These results provide critical insights about how spatial variation in the potential for adaptation may affect population persistence under changing climates.
DICOM image size reduction and data embedding using randomization technique

With the development of Internet technologies, digital media can be transmitted conveniently over the Internet. However, medical information transmissions over the Internet still have to face all kinds of problem such as network bandwidth, integrity of data, image quality and security. Normally Medical images are in DICOM (Digital Imagine in Communication and Medicine) format. The DICOM technology is suitable when sending images between different departments within hospitals or/and other hospitals, and consultant. However, the header file to DICOM image adds additional size to the image. We have proposed new techniques of transforming DICOM format in to BMP(Bitmap Image file) format and divide data into two parts and embedding a patient data in an image in odd, number memory location of image pixel values. Fix length Huffman compression is applied to get lossless compressed image. This investigation mainly focuses on computing the data hiding capacity, Compression Ratio, Mean Square Error (MSE) and Peak to Signal Noise Ratio (PSNR) of medical images.
Semiconductor Quantum Dots in Chemical Sensors and Biosensors

Quantum dots are nanometre-scale semiconductor crystals with unique optical properties that are advantageous for the development of novel chemical sensors and biosensors. The surface chemistry of luminescent quantum dots has encouraged the development of multiple probes based on linked recognition molecules such as peptides, nucleic acids or small-molecule ligands. This review overviews the design of sensitive and selective nanoprobes, ranging from the type of target molecules to the optical transduction scheme. Representative examples of quantum dot-based optical sensors from this fast-moving field have been selected and are discussed towards the most promising directions for future research.
Advertising to boost energy efficiency: the Power of One campaign and natural gas consumption

In this paper we study the recent awareness and persuasion campaign launched by the Irish government to increase energy efficiency and we assess its effect on residential natural gas consumption. We first analyse changes in the daily consumption of natural gas and find that advertising leaflets had a significant effect on natural gas consumption. We then study three surveys administered to 1000 consumers prior to and during the campaign. This repeated cross-section allows us to determine that the efficiency campaign has increased self-reported interest in energy efficiency and awareness of behaviours that curb natural gas consumption. However we do not find any positive effect of the campaign on self-reported energy-saving behaviours.
Configuration and data processing over a heterogeneous wireless sensor networks

Whereas software adaptation has been identified as an effective approach for addressing context-aware applications, the existing work on WSNs fails to support context-awareness and mostly focuses on developing techniques to reprogram the whole sensor node rather than reconfiguring a particular portion of the sensor application software. Therefore, enabling adaptively in the higher layers of the network architecture such as the middleware and application layers, beside the consideration in the lower layers, becomes of high importance. In this paper we propose an approach to hide heterogeneity and offer a single common configuration and processing component for all nodes of that heterogeneous system. This advances the current state-of-the-art, by providing a lego-like model whereby a single simple but powerful component is deployed in any node regardless of its underlying differences and the system is able to remotely configure and process data in any node in a most flexible way, since every node has the same uniform API, processing and access functionalities.
Mechanical stress and glucose concentration modulate glucose transport in cultured rat podocytes.

BACKGROUND Recent studies show that mechanical stress modifies both morphology and protein expression in podocytes. Ambient glucose is another factor modulating protein synthesis in these cells. In diabetes, podocytes experience elevated glucose concentrations as well as mechanical strain generated by high intracapillary pressures. Both these factors are responsible for podocyte injury, leading to impairment of kidney glomerular function. In the present study, we examined the effects of glucose concentration and mechanical stress on glucose uptake in podocytes. METHODS Following a 24 h pre-incubation in low (2.5 mM, LG), normal (5.6 mM, NG) or high (30 mM, HG) glucose media, cultured rat podocytes were exposed to 4 h mechanical stress. We used the labelled glucose analogue, [3H]2-deoxy-D-glucose, to measure glucose uptake. The distribution of facilitative glucose transporters GLUT2 and GLUT4 was assessed by flow cytometry. RESULTS In the control (static) cells, glucose uptake was similar in the three glucose groups. In mechanically stressed podocytes, glucose uptake increased 2-fold in the LG and NG groups but increased 3-fold in the HG group. In the NG cells, mechanical load increased the membrane expression of GLUT2 and reduced the membrane-bound GLUT4. In stretched HG cells, the membrane expression of both GLUT2 and GLUT4 was decreased. High glucose decreased the plasma membrane GLUT2 content in the stretched cells, whereas both static and stretched podocytes showed an elevation in GLUT4. CONCLUSION Mechanical stress potentiated glucose uptake in podocytes and this effect was enhanced by high ambient glucose. The decreased expression of GLUT2 and GLUT4 on the surface of stretched cells suggests that the activity of other glucose transporters may be regulated by mechanical stress in podocytes.
IJESRT INTERNATIONAL JOURNA Cryptographic Key Generation from Finger Vein

Bio-cryptography is a progressive technology that combines biometrics with cryptography. The use of biometric data for security purposes has become increasingly popular, but the use of biometric data in cryptography is a new, growing and promising area of research. One of the most important problems of bio generation of a stable encryption key. This pape vein pattern. The approach is based on the established finger vein image pre proposed Contour-tracing algorithm.
Digital Image Forensics Through the Use of Noise Reference Patterns

As result of the growing use of digital cameras, methods to identify an image's origin quickly, reliably, and inexpensively are needed. By designing and implementing methods for mitigating or "attacking" forensic features in the images, the robustness of various forensic identification techniques have been analyzed. The objective of this research was to see if drastically modified images could still be identified using a camera’s defects in the form of a reference noise pattern. Experimental data has been gathered using several digital cameras and has been placed in an image database to organize and manage the gathered experimental data. Various types of filters, including blurring, weighted blurring, sharpening, median, histogram equalization, and pseudo-random noise filters, have been programmed and implemented on the various images. These images have then been used to see if the image's source camera is still identifiable after attacking the image. A reference pattern is being found by averaging the noise pattern found in multiple pictures obtained from the same camera. This intrinsic signature of the camera can be used to correlate with a noise pattern of an image with an unknown origin. If the patterns are similar, and the correlation is above a certain threshold, the camera containing that particular reference pattern is the source camera. All images’ source camera were identified correctly, and except for a few exceptions, most correlation values for attacked images were lower, and therefore had less similar noise patterns than the original images’.
Data link requirements for air-to-air collision avoidance

One of the key technologies in future air traffic management is air-to-air communication. Especially data links, that is, direct wireless transmission of digital data will play a major role for air traffic applications like ad-hoc integration into air spaces, separation assurance, collision avoidance and landing. Recently, the avionics engineering center of Ohio University has developed a high-precision air-to-air surveillance solution for use in these areas, especially collision avoidance. The prerequisite for this air-to-air surveillance solution is the availability of a reliable data link. DLR deals with the development and simulation of future data links within the project Air2Air. Working together, Ohio University and DLR have carried out a series of flight experiments in late 2012 and early 2013, during which data exchange was recorded and evaluated with a special emphasis on the requirements of transmission of high-framerate, high-precision navigational information. In this paper we will present some results from these recordings together with considerations concerning future applications of data links for collision avoidance methods.
Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays

We propose a new method for class prediction in DNA microarray studies based on an enhancement of the nearest prototype classifier. Our technique uses "shrunken" centroids as prototypes for each class to identify the subsets of the genes that best characterize each class. The method is general and can be applied to other high-dimensional classification problems. The method is illustrated on data from two gene expression studies: lymphoma and cancer cell lines.
Investigation of a Preemptive Network Architecture by Christopher

by Christopher James Lefelhocz B.S, Computer Engineering, Carnegie Mellon University (Pittsburgh, Pennsylvania), 1992 Submitted to the Department of Electrical Engineering and Computer Science In Partial Fulfillment of the Requirements for the Degree of Master of Science in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology May, 1994 © Massachusetts Institute of Technology, 1994
Drivers for Household Electricity Prices in the EU: A System-GMM Panel Data Approach

Electricity as well as gas or refined petroleum products exemplify a significant part of the consumer basket of European households and companies. As energy products are important inputs of nearly all final goods and services, any change of energy prices has a direct impact of the general price level. In this context, the main purpose of this study is to assess the main drivers of household electricity prices in the European Union (EU), throughout a period of deep sector transformation. Relying on Eurostat up to date data, not only we analyze the long-term evolution of household electricity prices across the EU, but also we provide the latest empirical evidence on their determinants while confronting the results with the EU energy policy path. For this purpose a new approach is herein developed based on a dynamic model with panel data through GMM proposal method by Blundell and Bond (1998) with the Windermeijer correction (2005). The data analysis provides grounds for a relation between the variable of household electricity prices with variables related to sector liberalization, renewable energy sources which support the EU policy to boost liberalization. This study offers evidence that the sector liberalization, herein assumed via the market share of the largest electricity producer, is accompanied by a decreasing trend in prices, which is consistent with the European Commission’s objectives to liberalize.
Payoff-based Inhomogeneous Partially Irrational Play for Potential Game Theoretic Cooperative Control of Multi-agent Systems

This paper handles a kind of strategic game called potential games and develops a novel learning algorithm Payoff-based Inhomogeneous Partially Irrational Play (PIPIP). The present algorithm is based on Distributed Inhomogeneous Synchronous Learning (DISL) presented in an existing work but, unlike DISL, PIPIP allows agents to make irrational decisions with a specified probability, i.e. agents can choose an action with a low utility from the past actions stored in th e memory. Due to the irrational decisions, we can prove convergence in probability of collective actions to potential function maximizers. Finally, we demonstrate the effectiveness of the present algorithm through experiments on a sensor coverage problem. It is revealed through the demonstration that the present learning algorithm successfully leads agents to around potential function maximizers even in the presence of undesirable Nash equilibria. We also see through the experiment with a moving density function that PIPIP has adaptability to environmental changes.