Miracle-dz/UniFAR-FTUs huggingface dataset:
Personality and Fear Conditioning: Effects of Neuroticism

Fear conditioning is an associative learning paradigm that can be used to examine the acquisition and extinction of learned fear in various populations. Unusual patterns in fear conditioning are known to be associated with different types of psychopathology, and anxiety in particular has been studied extensively in relation to fear conditioning. However, far less is known about fear conditioning in nonclinical samples, particularly with regards to personality. The aim of the current study is to examine the acquisition and extinction of conditioned fear as it relates to neuroticism. The study utilized both physiological and subjective measures of learned fear, allowing for comparison across domains of fear expression. Eyeblink startle responses indicated that fear conditioning did not take place, with no significant differences in startle response magnitude in the presence of the conditioned and the unconditioned stimulus. Neuroticism was not found to be associated with greater eyeblink startle to either stimulus type. However, subjective fear ratings revealed an increase in fear of the conditioned stimulus following the acquisition phase, and a decrease in fear of the conditioned stimulus following the extinction phase, indicating that fear conditioning did in fact take place. Neuroticism was positively correlated with fear of the conditioned stimulus in the acquisition phase, indicating that more neurotic individuals may in fact acquire fear more readily than less neurotic individuals. Neuroticism was also associated with greater fear of the conditioned stimulus following extinction, suggesting that neurotic individuals may have difficulty learning when a stimulus no longer predicts threat. These findings indicate that neuroticism does impact both acquisition and extinction of conditioned fear, and there is a need for further replication in order to better understand the discrepancies between physiological and subjective measures in assessing fear conditioning. FEAR CONDITIONING: EFFECTS OF NEUROTICISM 3 Personality and Fear Conditioning: Effects of Neuroticism
A Novel Image Steganography Based on Contourlet Transform and Hill Cipher

In this paper, a novel image steganography is proposed, which is based on contourlet transform and hill cipher. Firstly, cover image is decomposed with contourlet transform. Contourlet transform provides a multi-scale and multi-directional representation of an image. One of the subbands is selected to embed secret data. Then hill cipher is applied to encrypt the secret message. In this approach, it’s important to ﬁnd a proper cipher matrix. The selected matrix should be inevitable and relatively primary to the number of alphabets. The skill of 2 k correction is applied to ease the diﬀerence between cover and stego image. The experiment results show that both stego image and retrieved image have better quality in the proposed approach than other methods.
CONCENTRATED FORCE ACTING ON THE BOUNDARY OF AN ELASTIC HALF-PLANE WITH CIRCULAR HOLE

This paper deals with analytical determination of stresses which occur in an elastic half-plane that contains a hole and is loaded by normal and tangential point forces on its straight boundary. The expansions of elastic potentials expressed in bipolar co-ordinates in Fourier series, deduced by Barjansky and Evan-Iwanowski, are corrected and then the shear stresses are derived. The analysis of the stress state reveals the zone in which important stress riser effects occur and the values of this riser dependent on hole depth. It is found that if the hole is placed under a specified depth, its effect can by assessed by considering it to be placed in an elastic plane.
Internal Corporate Restructuring and Firm Value : the Japanese Case

We analyze the impact of corporate restructuring on firm value using 132 Japanese corporate restructurings created between the years of 2001 and 2003 (since the establishment of the new Japanese “spin-in” law in 2001). This Japanese restructuring is unique in that a division becomes a new independent subsidiary but still remains under the control of the parent company. This unique feature enables us to examine whether corporate internal restructuring affects firm value and efficiency of internal capital markets, while keeping the scope and scale of the internal capital market intact. We find significant positive average cumulative abnormal returns around the announcements. Also, we find that both excess value and investment sensitivity have increased after spin-in transactions. We provide further evidence that changes in firm value and efficiency of internal capital markets are related to the different corporate structures – keiretsu affiliation and bank relationships. Our results are consistent with the hypothesis that the recent Japanese restructurings reduce information asymmetries and agency problems, thus improving firm value and internal capital markets‟ efficiency.
Using Hybrid MOOCs to Improve Teachers’ Academic Discourse Practices

Author(s): Hasser, Neil Ericson | Advisor(s): Pearson, P. David; Friesen, Amber | Abstract: Curricular and demographic changes in our schools have created significant shifts in the instructional needs of our classrooms. Inservice professional development (PD) through Massive Open Online Courses (MOOCs) has been posed as a scalable approach to meet the professional needs our teachers need to respond to instructional challenges. But what we know about MOOC PD is limited by our lack of knowledge of how teachers respond to this online mode, and by the shifting of MOOCs from simply online modes to hybrids using face-to-face interaction. This study is a multiple, embedded case study of the professional learning of 7 teachers participating in a hybrid MOOC. The MOOC was a multidimensional and adaptive platform to introduce current practices of engagement, the information gap, and an increased attention to language for teaching instructional strategies to elementary level teachers to support students’ development of academic uses of English. The research questions focused on how teachers processed PD features emphasized in the MOOC across 3 time points using a socio-cultural theoretical frame of developing teacher expertise (Snow, Griffin a Burns, 2005). Data sources included interviews, observations, surveys, and participants’ work assignment submissions. Findings suggest that teacher expertise was a mediator variable in response to the PD content and modes of delivery. The findings from this study have implications in research, policy, and practice. At a research level, multiple measures support analysis of modal interactions across different settings. Policy implications include specific suggestions to strengthen the collaborative nature of the PD. Implications for practice include providing additional instruction to teachers beyond the MOOC. Moreover, there is a need to develop teacher capacity for scaffolding authentic instructional interactions within context and based on ongoing formative assessment.
Multi-GNSS Precise Point Positioning Using GPS, GLONASS and Galileo

ii Acknowledgments. v Vita . vi List of Tables . xii List of Figures . xix List of Abbreviations . xxx CHAPTER 1: INTRODUCTION . 1 1.1 Background . 1 1.2 Thesis Objectives . 6 CHAPTER 2: GLOBAL NAVIGATION SATELLITE SYSTEMS. 10 2.1 Global Positioning System (GPS) . 10 2.2 GLONASS . 13 2.3 Galileo . 15 2.4 BeiDou . 17 2.5 QZSS . 18 CHAPTER 3: GPS OBSERVABLES AND ERRORS . 20 viii 3.1 GPS Measurements and Observables . 20 3.2 Common Error Sources . 25 3.2.1 Satellite Orbit and Clock Errors . 25 3.2.1.1 IGS Organization . 26 3.2.2 Ionospheric Delay . 30 3.2.3 Tropospheric Delay . 32 3.2.4 Receiver Clock Error . 37 3.2.5 Multipath and Noise . 38 3.3 Special Error Sources . 39 3.3.1 Satellite Antenna Phase Center Offset . 39 3.3.2 Phase Wind-Up . 41 3.3.3 Solid Earth Tide . 44 3.3. 4 Ocean Tide Loading . 45 3.3. 5 Relativistic Effect. 48 CHAPTER 4: DIFFERENTIAL GLOBAL POSITIONING SYSTEM AND PRECISE POINT POSITIONING METHODS . 53 4.1 Kalman Filter. 53 4.2 Extended Kalman Filter . 55 4.3 Differential Global Positioning System . 56
The Case Study for Evaluation of Landslides Volume and Moving Paths of Single Falling Rock

Landslides are natural evolution of topography. Since human behavior started reaching to mountain area, landslide disasters often occur and threaten people. The study uses the case of typhoon-Merantiinduced Hongye landslide in Taiwan on September 15th, 2016 to determine the landslide terrain feature, geological conditions, and disaster impact area by surveying the site for investigate and using the unmanned aerial vehicle (UAV) for monitoring. The UAV’s aerial photos are used to build the 3D model, orthophoto and digital surface model (DSM). The landslide area can be drawn with the area orthophoto. Compare the digital terrain model before and after the landslide to evaluate the terrain change of slope and landslide volume. While surveying the site of Hongye landslide, we found there is a risk of rock fall. To assess the motion track and form of the rock on slope, this study uses RocScience Rocfall 5.0 to conduct stability analysis to analyze the potential path and risk of the rock.
Reduction and Decomposition Optimizations in Quantum Computing Simulation Applied to the Shor’s Algorithm

Due to the expansion of transformations and read/write memory states by tensor products in multidimensional quantum applications, the exponential increase in temporal and spatial complexities constitutes one of the main challenges for quantum computing simulations. Simulation of these systems is important in order to develop and test new quantum algorithms. This work presents reduction and decomposition optimizations for the Distributed Geometric Machine environment. By exploring properties as the sparsity of the Identity operator and partiality of dense unitary transformations, better storage and distribution of quantum information are achieved. The main improvements are implemented by decreasing replication and void elements inherited from quantum operators. In the evaluation of this proposal, Shor’s algorithm considering 2n+3 qubits in the order-finding quantum algorithm was simulated up to 25 qubits over CPU, sequentially and in parallel, and over GPU. Results confirm that temporal complexity is reduced. When comparing our implementations running on the same hardware with LIQUi|i, academic release version, our new simulator was faster and allowed for the simulation of more qubits.
The 9 th International Conference on Mobile Web Information Systems ( MobiWIS ) Collective Discovery of Geographic Locations of Frequently Photographed Objects Only using the Metadata of Digital Photographs

In this paper, we propose an algorithm to classify a set of digital photographs by location of frequently photographed objects. The location is estimated by collective intelligence approach based on a collection of intersections of camera vectors of the metadata which a photograph records. In emergency, a rescue team needs information about the road to its disaster area as quick as possible. One of the best solutions for this purpose is an information sharing system between the refugees and the rescue team who share images taken by the refugees. For building this system, the following 2 difficulties are known. Firstly, this system should not inhibit refugee’s evacuation behavior while it engages in this sharing system. Secondly, the huge amount of disorganized images received is useless for the rescue team who has not enough time and other resources. The images should be categorized quick and adequately. In this paper, we propose a new classification method of images by geographic location of objects taken by them by collective intelligence. We only use metadata of digital image for this quick classification, namely, time to shoot, the latitude, the longitude and the bearing of its camera. Our method can accept consumer’s digital camera and smartphone which has a low end GPS unit and digital compass. Also, refugees need not to input any more information about objects taken than the photograph while name or location of objects taken have to be inputed in traditional works. In our method, the location of objects taken is estimated by an algorithm based on intersections of camera vectors automatically. The algorithm is confirmed by a series of experiments which use actual photographs taken by a broadly using smartphone. c © 2011 Published by Elsevier Ltd.
Comparative Study on Load Balancing Techniques in Cloud Computing

load balancing is often to provide repetition in the applications. If one server in a cluster of servers fails, the load balancer can temporal remove that server from the cluster, and partition the load onto the functioning servers. Multiple servers help each other in this way is called "redundancy". Whenever an error happens and the task is to move from the failing server to a functioning server, this is generally called "failover". A set of servers running the same application in cooperation is commonly referred to as a "cluster" of servers. Load balancing is one of the cloud environment based on how cloud developers demanded for the cloud provider. This paper explains load balancing and its types, particularly static and dynamic load balancing and performance parameter also compared.
The Potential of Graphic Nonfiction for Teaching and Learning Earth Science

Our comparative analysis demonstrates the utility of graphic nonfiction for teaching and learning scientific concepts. This study supports including graphic nonfiction along with other types of trade books as a supplement to textbooks in a multiple-text approach that allows for constructing knowledge through a cross-text comparison. Graphic nonfiction, through its visuals and conversational style, can assist in deepening understandings of content concepts and serve as an appropriate resource for science instruction, research, and enrichment.
Messages from the first International Conference on Clinical Metagenomics ( ICCMg )

Metagenomics is recently entering in the clinical microbiology and an increasing number of diagnostic laboratories are now proposing the sequencing & annotation of bacterial genomes and/or the analysis of clinical samples by direct or PCR-based metagenomics with short time to results. In this context, the first International Conference on Clinical Metagenomics (ICCMg) was held in Geneva in October 2016 and several key aspects have been discussed including: i) the need for improved resolution, ii) the importance of interpretation given the common occurrence of sequence contaminants, iii) the need for improved bioinformatic pipelines, iv) the bottleneck of DNA extraction, v) the importance of gold standards, vi) the need to further reduce time to results, vii) how to improve data sharing, viii) the applications of bacterial genomics and clinical metagenomics in better adapting therapeutics and ix) the impact of metagenomics and new sequencing technologies in discovering new microbes. Further efforts in term of reduced turnaround time, improved quality and lower costs are however warranted to fully translate metagenomics in [. ] RUPPE, Etienne, GREUB, Gilbert Daniel, SCHRENZEL, Jacques. Messages from the first International Conference on Clinical Metagenomics (ICCMg). Microbes and Infection, 2017, vol. 19, no. 4-5, p. 223-228 DOI : 10.1016/j.micinf. 2017.01. 005
Match Finalizing TestingRipping Structural Matching GUI Model Raw Match Interactive Application Test Reports AIF Recognition Full Match Reification Concrete Match

Testing software applications by interacting with their graphical user interface (GUI) is an expensive and complex process. Current automatic test case generation techniques implement explorative approaches that, although producing useful test cases, have a limited capability of covering semantically relevant interactions, thus frequently missing important testing scenarios. These techniques typically interact with the available widgets following the structure of the GUI, without any guess about the functions that are executed. In this paper we propose Augusto, a test case generation technique that exploits a built-in knowledge of the semantics associated with popular and well-known functionalities, such as CRUD operations, to automatically generate effective test cases with automated functional oracles. Empirical results indicate that Augusto can reveal faults that cannot be revealed with state of the art techniques.
LITERATURE-BASED KNOWLEDGE DISCOVERY

Literature-based knowledge discovery process identifies the important but implicit relations among information embedded in published literature. Existing techniques from Information Retrieval and Natural Language Processing attempt to identify the hidden or unpublished connections between information concepts within published literature, however, these techniques undermine the concept of predicting the future and emerging relations among scientific knowledge components encapsulated within the literature. Keyword Co-occurrence Network (KCN), built upon author selected keywords (i.e., knowledge entities), is considered as a knowledge graph that focuses both on these knowledge components and knowledge structure of a scientific domain by examining the relationships between knowledge entities. Using data from two multidisciplinary research domains other than the medical domain, capitalizing on bibliometrics, the dynamicity of temporal KCNs, and a Long Short Term Memory recurrent neural network, this study proposed a framework to successfully predict the future literature-based discoveries the emerging connections among knowledge units. Framing the problem as a dynamic supervised link prediction task, the proposed framework integrates some novel node and edge-level features. Temporal importance of keywords computed from both bipartite and unipartite networks, communities of keywords, built upon genealogical relations, and relative importance of temporal citation counts used in the feature construction process. Both node and edge-level features were input into an LSTM network to forecast the feature values for positive and negatively labeled non-connected keyword pairs and classify them accurately. High classification performance rates suggest that these features are supportive both in predicting the emerging connections between scientific knowledge units and emerging trend analysis.
RAZOR: A Framework for Post-deployment Software Debloating

Commodity software typically includes a large number of functionalities for a broad user population. However, each individual user usually only needs a small subset of all supported functionalities. The bloated code not only hinders optimal execution, but also leads to a larger attack surface. Recent works have explored program debloating as an emerging solution to this problem. Unfortunately, these works require program source code, limiting their real-world deployability. In this paper, we propose a practical debloating framework, RAZOR, that performs code reduction for deployed binaries. Based on users’ specifications, our tool customizes the binary to generate a functional program with minimal code size. Instead of only supporting given test cases, RAZOR takes several control-flow heuristics to infer complementary code that is necessary to support user-expected functionalities. We evaluated RAZOR on commonly used benchmarks and realworld applications, including the web browser FireFox and the close-sourced PDF reader FoxitReader. The result shows that RAZOR is able to reduce over 70% of the code from the bloated binary. It produces functional programs and does not introduce any security issues. RAZOR is thus a practical framework for debloating real-world programs.
Impact of Multi-User Scheduling on Distributed Antenna Small-Cell Network using STBC Transmit Diversity

Abstract— Cooperative distributed antenna transmission (CDAT) in small-cell network significantly improves the spectrum and energy efficiencies simultaneously. In any mobile communications networks, co-channel interference (CCI) from adjacent macro-cells limits the link capacity. A powerful method to effectively utilize the available bandwidth while ensuring the fairness of each user equipment (UE) is a combined use of the single-user spacetime block coded transmit diversity (STBC-TD) and the multi-user scheduling. In this paper, we evaluate the link capacity and fairness for three types of the scheduling: proportional fair (PF), the maximum signal-to-noise power ratio (max-SNR), and the round-robin (RR). It is shown that the simple RR scheduling can replace the PF scheduling. Also shown is that by increasing the number of distributed antennas deployed in a macro-cell, the link capacity and the fairness can be improved even in the presence of strong CCI from adjacent macro-cells.
perspective taking , and inhibitory control during adolescence

Structural and functional brain development is thought to lead to different developmental progressions of cognitive control, risk/reward processing and social cognition during adolescence. We compared these abilities in a cross-sectional sample of 90 adolescents aged 12, 15 or 17 years old, using computerised measures of inhibitory control (Go/No-go task), risk-taking (Balloon Analogue Risk Task), and social perspective-taking (Director task). Fifteen-year-olds exhibited better inhibitory control than 12-year-olds, while 17-year-olds exhibited greater perspective-taking than younger adolescents. Risk-taking was greater in older adolescents than 12-year-olds when controlling for inhibitory control. These findings are consistent with earlier findings obtained in separate samples.
R & D Intensity and Firm Size Revisited

Even if technology and innovations are the engines of growth, the US’s effort to create an environment that fosters innovation has not been very successful. Moreover, data shows that the US has been losing its competitive edge in the global race for innovation. Between 1999 and 2007, US’s share of global R&D has fallen from 39% to 33% while China’s R&D share has increased and is now second only to that to Japan. Current US policies intended to encourage innovation tax credit/subsidies, patent laws, etc. do not recognize the difference in funding ability between large firms and small ones. As a result, these policies benefit larger firms and sometimes discourage innovations coming from small entrepreneurs. One of the reasons why the US does not have R&D policies dependent on size might be found in the lack of empirical evidence proving the existence of a systematic relationship between firm size and R&D intensity. In this paper, I closely examine the relationship between the size of a firm and its efforts for innovation, measured in R&D expenditure. I use the US firm level data (Compustat), which provides empirical evidence in contrast with those historical studies that showed R&D intensity to be constant across all firm sizes. By looking at the way in which small firms are funded through venture capital market, this study shows that smaller firms are a very important driving force of the US innovation, and therefore, it argues in favor of size dependent R&D tax credit programs and patent policies. Such measures would lessen the burden on small firms thus helping the US economy to sustain growth and create more jobs. ∗I’m deeply grateful for all the help and encouragement I received from Lee Ohanian, Mark Wright, Pierre-Olivier Weil, Connan Snider and Venkateswaran Vaidyanathan. I also want to thank Josh Lerner and Sam Kortum for the help with venture capital data and advice on working with Compustat data and Gary Dushnitsky for providing the concordance file related to venture capital investment industry identification. Special thanks to Gianluca Rizzo, Giang Ho, David Kang, Jessica Roldan, Gitanjali Kumar for emotional support. Preliminary and Subject to Change 1