Miracle-dz/UniFAR-FTUs huggingface dataset:
Design a mobile game for home computer users to prevent from “phishing attacks”

This research aims to design an educational mobile game for home computer users to protect against phishing attacks. Phishing is an online identity theft which aims to steal sensitive information such as username, password and online banking details from victims. To prevent this, phishing education needs to be considered. Mobile games could facilitate to embed learning in a natural environment. The paper introduces a mobile game design based on a story which is simplifying and exaggerating real life. We use a theoretical model derived from Technology Threat Avoidance Theory (TTAT) to address the game design issues and game design principles were used as a set of guidelines for structuring and presenting information. The overall mobile game design was aimed to enhance avoidance motivation and behaviour of home computer users to protect against phishing threats. The prototype game design is presented on Google App Inventor Emulator. We believe by training home computer users to protect against phishing attacks, would be an aid to enable the cyberspace as a secure environment.
An Interactive Tool for Learning Linear and Differential Cryptanalysis of SPNs

Introduction Linear and differential cryptanalysis have existed for years as a set of tools to establish a metric of resiliency for cryptographic ciphers utilizing the substitution-permutation network (SPN) design, a category of cryptographic cipher in which many popular ciphers, such as the Advanced Encryption Standard (AES). This is typically an involved process with many manual steps, often written specifically for the SPN being analyzed, with minimal reusable or generalized code. As of this writing, there do not exist any tools to make the process interactive for an arbitrary SPN; the few interactive, automated tools that do exist are designed around a particular predefined cipher. The goal of this project is to create Maledict [1] , a Java application inspired and influenced by the tutorial by Howard Heys [4] , with a user interface in Swing in order to provide an interactive experience in the linear and differential cryptanalysis of arbitrary, user-designed substitution-permutation networks. As a part of the interactive process I seek to provide visualizations of various features, such as the pseudo-linear " path " followed through the network by a given bit. I also intend to report meaningful results obtained using the tool, such as linear approximation/difference distribution tables or subkey biases from experimental results. It is my intention that this project provide a foundation for an effective academic tool, which can be used by students to better understand and observe the processes of linear and differential cryptanalysis.
A Hybrid Data and Knowledge Driven Approach for Gene Clustering and Network Reconstruction

Many methods have been developed for reverse engineering gene networks from time series expression data. However, when the number of genes and the complexity of regulation increase, it becomes increasingly difficult to infer gene networks. To tackle this scalability problem, this study presents an approach with two phases: gene clustering and network reconstruction. To perform gene clustering, a hybrid data and knowledge-driven method is developed to calculate both data and semantic similarity between genes. In the network reconstruction procedure, a Boolean network model is inferred from the gene clusters. A series of experiments are conducted to investigate the effect of the hybrid similarity measure in gene clustering and network reconstruction. The results prove the feasibility and effectiveness of the proposed approach.
Salsolinol Facilitates Glutamatergic Transmission to Dopamine Neurons in the Posterior Ventral Tegmental Area of Rats

Although in vivo evidence indicates that salsolinol, the condensation product of acetaldehyde and dopamine, has properties that may contribute to alcohol abuse, the underlying mechanisms have not been fully elucidated. We have reported previously that salsolinol stimulates dopamine neurons in the posterior ventral tegmental area (p-VTA) partly by reducing inhibitory GABAergic transmission, and that ethanol increases glutamatergic transmission to VTA-dopamine neurons via the activation of dopamine D1 receptors (D1Rs). In this study, we tested the hypothesis that salsolinol stimulates dopamine neurons involving activation of D1Rs. By using whole-cell recordings on p-VTA-dopamine neurons in acute brain slices of rats, we found that salsolinol-induced increase in spike frequency of dopamine neurons was substantially attenuated by DL-2-amino-5-phosphono-valeric acid and 6, 7-dinitroquinoxaline-2, 3-dione, the antagonists of glutamatergic N-Methyl-D-aspartic acid and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors. Moreover, salsolinol increased the amplitude of evoked excitatory postsynaptic currents (EPSCs) and the frequency but not the amplitude of spontaneous EPSCs. Additionally, SKF83566, a D1R antagonist attenuated the salsolinol-induced facilitation of EPSCs and of spontaneous firing of dopamine neurons. Our data reveal that salsolinol enhances glutamatergic transmission onto dopamine neurons via activation of D1Rs at the glutamatergic afferents in dopamine neurons, which contributes to salsolinol's stimulating effect on p-VTA dopamine neurons. This appears to be a novel mechanism which contributes toward rewarding properties of salsolinol.
Polyphenol-Rich Fraction of Brown Alga Ecklonia cava Collected from Gijang, Korea, Reduces Obesity and Glucose Levels in High-Fat Diet-Induced Obese Mice

Ecklonia cava (E. cava) is a brown alga that has beneficial effects in models of type 1 and type 2 diabetes. However, the effects of E. cava extracts on diet-induced obesity and type 2 diabetes have not been specifically examined. We investigated the effects of E. cava on body weight, fat content, and hyperglycemia in high-fat diet- (HFD) induced obese mice and sought the mechanisms involved. C57BL/6 male mice were fed a HFD (60% fat) diet or normal chow. After 3 weeks, the HFD diet group was given extracts (200 mg/kg) of E. cava harvested from Jeju (CA) or Gijang (G-CA), Korea or PBS by oral intubation for 8 weeks. Body weights were measured weekly. Blood glucose and glucose tolerance were measured at 7 weeks, and fat pad content and mRNA expression of adipogenic genes and inflammatory cytokines were measured after 8 weeks of treatment. G-CA was effective in reducing body weight gain, body fat, and hyperglycemia and improving glucose tolerance as compared with PBS-HFD mice. The mRNA expression of adipogenic genes was increased, and mRNA expression of inflammatory cytokines and macrophage marker gene was decreased in G-CA-treated obese mice. We suggest that G-CA reduces obesity and glucose levels by anti-inflammatory actions and improvement of lipid metabolism.
Video caching in Radio Access Network: Impact on delay and capacity

In this paper, we introduce distributed caching of videos at the base-stations of the Radio Access Network (RAN) as a way to reduce the need to bring requested videos from Internet CDNs, thereby reducing backhaul transmission, improving video quality of experience - delay and video stalling - and increasing overall network capacity to support more number of simultaneous video requests. Unlike Internet CDNs that can store millions of videos in a relatively few large sized caches, our proposed caching architecture consists of a very large number of micro-caches, with each base-station micro-cache being able to store only 1000s of videos, and hence may not be able to have high cache hit ratio. To address this challenge, we propose two new caching policies based on the User Preference Profile (UPP) of users in a cell: R-UPP (Reactive UPP) and P-UPP (Proactive UPP). Further, for videos that result in cache misses and need to be fetched from Internet CDNs, we develop a video scheduling approach that allocates the RAN backhaul resources to the video requests so as to reduce video latency and increase network capacity. We develop a discrete event statistical simulation framework using MATLAB to study the performance of RAN caching. Our simulation results show that RAN micro-caches with the proposed UPP-based caching policies, together with the proposed scheduling approach, can improve the probability of video requests that can meet initial delay requirements by almost 60%, and the number of concurrent video requests that can be served by up to 100%. The results also show that UPP based policies can enhance network capacity by up to 30% compared to conventional caching policies.
Top-down design flow for application specific printed electronics circuits (ASPECs)

This paper presents a top-down approach for the design process of digital Application Specific Printed Electronics (PE) Circuits (ASPECs); from functionality specification at circuit level (i.e. HDL), through the optimization of combinational circuitry (represented by their logical equations), according to the PMOS-based technology that will be used to build a set of Standard Cells (SC) or use a predesign Inkjet Gate Array (IGA), down to the Place and Route to get the final circuit layout. This process will use the technology coming from the Centre for Process Innovation (CPI). This methodology maps the existing ASIC one by updating design styles and cost functions. Thus, it is portable to different Printed Electronics processes, using state-of-the-art logic synthesis EDA/software tools being the main optimization goal the transistor count. Main reason is that printed electronics technologies show low density and not such high yield compared to traditional Silicon-based microelectronics. To illustrate this methodology, we use the design and implementation of the TicTacToe game to be implemented together with flexible textile pressure sensor and lighting.
Automatic indexing of multimedia documents as a starting point to annotation process

Automatic text analysis widened the perspective of work on document contents by opening up the studies on the linguistic productions. In this case, we are using annotation as a case study. In our approach, annotation is defined as textual, graphic or sound information, attached to document source (text, photo, audio sequence or video sequence : multimedia). The source of our corpus is from INA databases (ie. Institut National de l'Audiovisuel, Paris). Our research task consisted of identifying what are the appropriate characteristics of a multimedia document, its context and information retrieval in the context of natural language processing (NLP), automatic indexing and knowledge representation. We discuss the crucial role of annotation process in the Knowledge Extraction tools and Management as well as in the design of Information Retrieval Systems. Our focus is more specifically on the new approach in information system design dedicated to “economic intelligence”.
Analysis of Climate Model Outputs Using Linear and Nonlinear Statistical Techniques

Regional climate models (RCMs) are currently one of regularly applied tools for localization of global climate models (GCMs) outcomes. This study is focused on analyses of mean daily temperature and precipitation using linear and nonlinear statistical techniques. 48 grid points of the regional climate models HIRHAM and RCAO and 29 meteorological stations of the Czech Republic were compared in the period 1961-1990. Mean annual courses of mean daily temperature and precipitation in the period 2071- 2100 were analyzed at selected HIRHAM and RCAO grid points for A2 and B2 emission scenarios (IPCC, 2007). Furthermore, time-delayed average mutual information (AMI) and autocorrelation function were analyzed. AMI and autocorrelation function were calculated for one selected time series of each grid point of the Czech Republic and Europe with a time lag varying from 1 to 10 days. The values of average mutual information were compared with values of autocorrelation function.
The impact of supervisor-subordinate work-value congruency on the development of leader-member exchange

THE IMPACT OF SUPERVISOR-SUBORDINATE WORK-VALUE CONGRUENCY ON THE DEVELOPMENT OF LEADER-MEMBER EXCAHNGE BY GREGORY R. THRASHER August 2015 Advisor: Marcus Dickson, PhD Major: Psychology (Industrial/Organizational) Degree: Master of Arts This study evaluates the antecedents and dynamic interplay between leader and follower levels of leader-member exchange (LMX). Value congruence and dyad contact are specifically looked at as predictors of both levels of and agreement of LMX. Social work students taking part in a work placement along with their supervisors composed 34 matched dyad pairs and 268 unmatched individuals. Results suggest that both value congruency and dyad contact predict LMX, with dyad contact predicting LMX differentiation. Value congruence displayed incremental validity in predicting LMC beyond dyad contact. Interestingly, these relationships were moderated by leader-follower status, suggesting that followers are much more sensitive to the effects of individual and environmental dyad characteristics.
Improvement of route lifetime of LAR protocol for VANET in highway scenario

Vehicular Ad-hoc networks (VANETs) are an emerging class of wireless networks for data exchange between vehicles or between vehicles and infrastructure. They attract interest both from the point of view of the automobile industry as operators of networks and services, in order to provide new technologies that improve the safety and efficiency of road transport. Following this vision, we seek in this paper to adapt the protocol Location-Aided Routing (LAR) for inter-vehicle communications in a highway environment. We improved the stability of paths between sources and destinations. When a node receives a route request message, it will not forward the message unconditionally but according to the direction of motion of source, the time of neighbor to stay in communication range and the location information to determine whether it needs to receive and forward the message. The performance metrics such as average delay of stability path between source and destination, packet delivery ratio (PDR), throughput, and normalized routing load are measured using ns2. The Intelligent Driver Model with Lane Changing (IDM_LC) based on VanetMobiSim tool is used to generate realistic mobility traces in highway.
Exploring potential new floral organ morphogenesis genes of Arabidopsis thaliana using systems biology approach

Flowering is one of the important defining features of angiosperms. The initiation of flower development and the formation of different floral organs are the results of the interplays among numerous genes. But until now, just fewer genes have been found linked with flower development. And the functions of lots of genes of Arabidopsis thaliana are still unknown. Although, the quartet model successfully simplified the ABCDE model to elaborate the molecular mechanism by introducing protein-protein interactions (PPIs). We still don't know much about several important aspects of flower development. So we need to discriminate even more genes involving in the flower development. In this study, we identified seven differentially modules through integrating the weighted gene co-expression network analysis (WGCNA) and Support Vector Machine (SVM) method to analyze co-expression network and PPIs using the public floral and non-floral expression profiles data of Arabidopsis thaliana. Gene set enrichment analysis was used for the functional annotation of the related genes, and some of the hub genes were identified in each module. The potential floral organ morphogenesis genes of two significant modules were integrated with PPI information in order to detail the inherent regulation mechanisms. Finally, the functions of the floral patterning genes were elucidated by combining the PPI and evolutionary information. It was indicated that the sub-networks or complexes, rather than the genes, were the regulation unit of flower development. We found that the most possible potential new genes underlining the floral pattern formation in A. thaliana were FY, CBL2, ZFN3, and AT1G77370; among them, FY, CBL2 acted as an upstream regulator of AP2; ZFN3 activated the flower primordial determining gene AP1 and AP2 by HY5/HYH gene via photo induction possibly. And AT1G77370 exhibited similar function in floral morphogenesis, same as ELF3. It possibly formed a complex between RFC3 and RPS15 in cytoplasm, which regulated TSO1 and CPSF160 in the nucleus, to control the floral organ morphogenesis. This process might also be fine tuning by AT5G53360 in the nucleus.
Postnatal maturation of somatostatin-expressing inhibitory cells in the somatosensory cortex of GIN mice

Postnatal inhibitory neuron development affects mammalian brain function, and failure of this maturation process may underlie pathological conditions such as epilepsy, schizophrenia, and depression. Furthermore, understanding how physiological properties of inhibitory neurons change throughout development is critical to understanding the role(s) these cells play in cortical processing. One subset of inhibitory neurons that may be affected during postnatal development is somatostatin-expressing (SOM) cells. A subset of these cells is labeled with green-fluorescent protein (GFP) in a line of mice known as the GFP-positive inhibitory neurons (GIN) line. Here, we studied how intrinsic electrophysiological properties of these cells changed in the somatosensory cortex of GIN mice between postnatal ages P11 and P32+. GIN cells were targeted for whole-cell current-clamp recordings and ranges of positive and negative current steps were presented to each cell. The results showed that as the neocortical circuitry matured during this critical time period multiple intrinsic and firing properties of GIN inhibitory neurons, as well as those of excitatory (regular-spiking [RS]) cells, were altered. Furthermore, these changes were such that the output of GIN cells, but not RS cells, increased over this developmental period. We quantified changes in excitability by examining the input–output relationship of both GIN and RS cells. We found that the firing frequency of GIN cells increased with age, while the rheobase current remained constant across development. This created a multiplicative increase in the input–output relationship of the GIN cells, leading to increases in gain with age. The input–output relationship of the RS cells, on the other hand, showed primarily a subtractive shift with age, but no substantial change in gain. These results suggest that as the neocortex matures, inhibition coming from GIN cells may become more influential in the circuit and play a greater role in the modulation of neocortical activity.
Graph-based Word Clustering Applied to Question Answering and Reading Comprehension Tests

This paper describes our participation in the QA4MRE 2011 task, targeted at reading comprehension tests and multiple choice ques- tion answering. Our system constructs a co-occurrence graph with words that are common or proper nouns and verbs extracted from each docu- ment. The documents are pre-selected through an information retrieval process for recovering only those that are most relevant to a particular question. An algorithm to detect communities of words with signicant co-occurrence is applied to the co-occurrence graph. Each of the detected communities are treated as dierent contexts of a question in the cor- pus, and these contexts are used to nd the most suitable answer. Our evaluation results suggest that, the number of retrieved documents is an important factor in the results.
Limits to Electronic Sourcing Adoption in Chinese Healthcare Sector: A Contextualist Perspective

The adoption of electronic sourcing promises to bring in free-market competition so as to achieve significant cost reduction. However, this promise has not been realized in the healthcare industry in China after years of e-sourcing adoption. Instead, adoption of e-sourcing has steadily increased the cost of pharmaceutical products that hospitals charged to patients. Our study indicates that this paradox was caused neither by the lack of market control mechanism nor the resistance to market process reengineering. Taking a contextualist perspective, this paper examines three embedded levels of context so as to appreciate the internalization problem underlying e-sourcing adoption in Chinese healthcare sector. The findings indicate that technology is unable to be internalized effectively if the alignment of context at three levels – societal (society), industrial (industry) and organizational (organization) – is not given due consideration during adoption and implementation.
Online Coloring Co-interval Graphs ∗

We study the problem of online coloring co-interval graphs. In this problem, a set of intervals on the real line is presented to the algorithm one at a time, and upon receiving each interval I, the algorithm must assign I a color different from the colors of all previously presented intervals not intersecting I. The objective is to use as few colors as possible. It is known that the competitive ratio of the simple FirstFit algorithm on the class of co-interval graphs is at most 2. We show that for the class of unit co-interval graphs, where all intervals have equal length, the 2-bound on the competitive ratio of First-Fit is tight. On the other hand, we show that no deterministic online algorithm for coloring unit co-interval graphs can be better than 3/2-competitive. We then study the effect of randomization on our problem, and show a lower bound of 4/3 on the competitive ratio of any randomized algorithm for the unit co-interval coloring problem. We also prove that for the class of general co-interval graphs no randomized algorithm has competitive ratio better than 3/2.
VLSI implementation of a lossless ECG encoder design with fuzzy decision and two-stage Huffman coding for wireless body sensor network

An efficient VLSI design of lossless electrocardiogram (ECG) encoder is proposed for wireless body sensor networks. To save wireless transmission power, a novel lossless encoding algorithm has been created for ECG signal compression. The proposed algorithm consists of an adaptive predictor based on the fuzzy decision control, and an entropy encoder including a two-stage Huffman coding. The VLSI architecture contains only 2.78 K gates and its core area is 34,411 μm2 synthesized by a 0.18 μm CMOS process. Moreover, this design can be operated at 100 MHz processing rate by consuming only 28.3 μW. It achieves an average compression rate of 2.53 for the MIT-BIH arrhythmia database. To compare with the previous low-complexity and high performance lossless ECG encoder studies, it is performed higher compression rate, lower power consumption and lower hardware cost than VLSI design.