Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Inflation on Economic Growth in Qatar An Empirical Investigation : 1980-2011 1

1 College of Business Administration American University in the Emirates,United Arab Emirates 2 Algonquin College, Ottawa, Ontario, Canada. Corresponding Author: Majeed Ali Hussain _______________________________________________________________________________________ Abstract This paper explores the relationship between inflation and economic growth for sustainable economic development in Qatar. Using annual data on Economic growth and inflation rate for the period of 1980 to 2011, co-integration and error correction models are estimated. The empirical evidence demonstrates that there exists a statistically significant long-run negative relationship between inflation and economic growth in Qatar. This result has important implications for both domestic policy makers and the development partners working for the country. Specifically, our conclusion is of direct relevance to the conduct of the monetary policy by the Qatar Bank. __________________________________________________________________________________________
Using Co-Expression Analysis and Stress-Based Screens to Uncover Arabidopsis Peroxisomal Proteins Involved in Drought Response

Peroxisomes are essential organelles that house a wide array of metabolic reactions important for plant growth and development. However, our knowledge regarding the role of peroxisomal proteins in various biological processes, including plant stress response, is still incomplete. Recent proteomic studies of plant peroxisomes significantly increased the number of known peroxisomal proteins and greatly facilitated the study of peroxisomes at the systems level. The objectives of this study were to determine whether genes that encode peroxisomal proteins with related functions are co-expressed in Arabidopsis and identify peroxisomal proteins involved in stress response using in silico analysis and mutant screens. Using microarray data from online databases, we performed hierarchical clustering analysis to generate a comprehensive view of transcript level changes for Arabidopsis peroxisomal genes during development and under abiotic and biotic stress conditions. Many genes involved in the same metabolic pathways exhibited co-expression, some genes known to be involved in stress response are regulated by the corresponding stress conditions, and function of some peroxisomal proteins could be predicted based on their co-expression pattern. Since drought caused expression changes to the highest number of genes that encode peroxisomal proteins, we subjected a subset of Arabidopsis peroxisomal mutants to a drought stress assay. Mutants of the LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) showed enhanced susceptibility to drought, suggesting the involvement of peroxisomal quality control and photorespiration in drought resistance. Our study provided a global view of how genes that encode peroxisomal proteins respond to developmental and environmental cues and began to reveal additional peroxisomal proteins involved in stress response, thus opening up new avenues to investigate the role of peroxisomes in plant adaptation to environmental stresses.
Dose Optimization Studies by Selecting Kilovoltage in Oncologic Chest CT

In this work we have studied the adequacy of dose levels of irradiation in oncologic chest CT obtained in our daily practice. The secondary objective was to evaluate the effect on radiation dose of individual adjustment of kilovoltage in thoracic multidetector row computed tomography (MDCT) images acquired with both single and dual-source technology. The impact of lowering the kilovoltage in the diagnostic quality of these studies was also evaluated. 161 patients were included in the study. CT examinations were performed using two different equipments: a conventional CT scanner and a dual-source computed tomography. The average values of dose length product (DLP) obtained in our daily practice meet the recommendations of the existing referral guidelines. Lower values can be achieved through individual adjustment of kilovoltage and with dual-source CT technology, maintaining the diagnostic quality of these studies.
Mislaid character analysis using 2-dimensional discrete wavelet transform for edge refinement

: Character recognition is an important tool used for many purposes limited only by imagination, some of them being automatic number plate recognition and digital conversion of texts. In the present methods, edge detection techniques perform well but they are time consuming and have errors if the data provided is not up to the mark. In this paper, a novel method is proposed to minimize those errors and perform the edge detection of characters using 2-dimensional wavelet transform pre-processing.
Detecting Web Attacks Using Multi-stage Log Analysis

Web-based applications have gained universal acceptance in every sector of lives, including social, commercial, government, and academic communities. Even with the recent emergence of cloud technology, most of cloud applications are accessed and controlled through web interfaces. Web security has therefore continued to be fundamentally important and extremely challenging. One major security issue of web applications is SQL-injection attacks. Most existing solutions for detecting these attacks use log analysis, and employ either pattern matching or machine learning methods. Pattern matching methods can be effective, dynamic, they however cannot detect new kinds of attacks. Supervised machine learning methods can detect new attacks, yet they need to rely on an off-line training phase. This work proposes a multi-stage log analysis architecture, which combines both pattern matching and supervised machine learning methods. It uses logs generated by the application during attacks to effectively detect attacks and to help preventing future attacks. The architecture is described in detail, a proof-of-concept prototype is implemented and hosted on Amazon AWS, using Kibana for pattern matching and Bayes Net for machine learning. It is evaluated on 10,000 logs for detecting SQL injection attacks. Experiment results show that the two-stage system has combined the advantages of both systems, and has substantially improved the detection accuracy. The proposed work is significant in advancing web securities, while the multi-stage log analysis concept would be highly applicable to many intrusion detection applications.
Exploring Corporate Practices in Management Accounting for Sustainability

business with COnFiDenCe icaew.com/academic iCAew promotes and funds, through its charitable trusts, high-quality independent academic research of interest to the accountancy profession and the wider business community. this publication was produced with the help of a grant from iCAew's charitable trusts. these trusts support educational projects in accountancy and related subjects. All research reports and briefings published under the iCAew's charitable trusts imprint are independently refereed before publication. the kind permission of edward elgar Publishing. table 1 is reproduced from burritt, R.L. , hahn, t. and schaltegger, s. (2002), 'towards a comprehensive framework for environmental management accounting. Links between business actors and environmental management accounting tools', Australian Accounting Review, 12(2), 39–50, with the kind permission of AAR and wiley-blackwell. All rights reserved. if you want to reproduce or redistribute any of the material in this publication, you should first request get iCAew's permission in writing. the views expressed in this publication are those of the authors. iCAew does not necessarily share their views. iCAew will not be liable for any reliance you placed on information in this publication.
GazeTorch: Enabling Gaze Awareness in Collaborative Physical Tasks

We present GazeTorch, a novel interface that provides gaze awareness during remote collaboration on physical tasks. GazeTorch uses a spotlight to display gaze information of the remote helper on the physical task space of the worker. We conducted a preliminary user study to evaluate user's subjective opinion on the quality of collaboration, using GazeTorch and a camera-only setup. Our preliminary results suggest that the participants felt GazeTorch made collaboration easier, made referencing and identifying of objects effortless, and improved the worker's confidence that the task was completed accurately. We conclude by presenting some novel application scenarios for the concept of augmenting real-time gaze information in the physical world.
Deficiencies in Current Software Protection Mechanisms and Alternatives for Securing Computer Integrity

The most widely spread operating system today, Microsoft Windows 2000, does not have enough built-in protection against malicious code, malware. Windows 2000, like many other operating systems, cannot detect malware and stop it from executing. This has lead to the situation that Windows need to be “patched” with additional protection mechanisms, such as antivirus programs and personal firewalls. This thesis shows that the protection software used today is not sufficient and that new solutions are needed to protect computer integrity. Today we have an unacceptable situation where the antivirus manufacturers always are one step behind the virus producers. The damage is already done by some new malware before the antivirus manufacturers can start producing a response to the new threat. The tests conducted in this thesis shows that the protection offered by most antivirus programs are limited to known threats. They cannot discover malicious code that they do not have signatures for in their definition files. The test also shows that personal firewalls cannot function without human interaction. They will ask the user if certain programs are allowed to connect to the Internet. This is not a good idea since there are trojans that can appear as other programs, such as the Internet Explorer. To show that the current protection software, antivirus programs and personal firewalls, is insufficient we used so-called “anti-protection trojans”. The purpose of these trojans is to disable the installed protection and to let the attacker gain control. When the trojans were tested against computers with antivirus programs and personal firewalls they could in most cases disable the protection. Alternative solutions, such as computerized digital immune defence systems and Microsoft’s criticized project Next Generation Secure Computing Base (NGSCB), where Digital Rights Management (DRM) is one part, are discussed as potential cures against the problem with malware. Fausi Qattan holds B.Sc. degree in Systems Analysis from Lund University – Sweden. He has been working in the IT field since 1987. Fredrik Thernelius holds M.Sc. in Electrical Engineering from the Royal Institute of Technology, Stockholm. He has worked with system development since 1999.
Investigating the Impact of Metric Aggregation Techniques on Defect Prediction

Code metrics collected at the method level are often aggregated using summation to capture system properties at higher levels (e.g., file- or package-level). Since defect data is often available at these higher levels, this aggregation allows researchers to build defect prediction models. Recent findings by Landman et al. indicate that aggregation is likely to inflate the correlation between size and complexity metrics. In this paper, we explore the effect of nine aggregation techniques on the correlation between three types of code metrics, namely Lines of Code, McCabe, and Halstead metrics. In addition to summation, we study aggregation techniques that are measures of: (1) central tendency (average and median), (2) dispersion (standard deviation and inter-quartile range), (3) shape (skewness and kurtosis), and (4) income inequality (Theil index and Gini coefficient). Our results show that defect prediction models built using summation outperform those built using other aggregation techniques. We also find that more complex aggregations are no different than much simpler ones and that incorporating all aggregation types in the same model does not provide a significant improvement over using summation alone.
2-level FIFO architecture design for switch fabrics in network-on-chip

The network-on-chip (NoC) architecture provides the integrated solution for system-on-chip (SoC) design. The buffer architecture and sizes, however, dominate the performance of NoC and influence on the design of arbiters in the switch fabrics. The 2-level FIFO architecture is proposed. It simplifies the design of the arbitration algorithm and gets better performance than other buffer architectures without increasing the buffer sizes. The concept of the shared memory mechanism and multiple accesses for the buffers are developed. The FIFO architecture is implemented and simulated with TSMC 0.13mum network-on-chip by HSPICE and Verilog. The operation frequency of the 2-level FIFO reaches 400MHz
The Differential Effects of Transformational Leadership on Multiple Identifications at Work: A Meta‐Analytic Model

Employees’ identifications are a valuable asset for modern organizations, and identification research has stressed the necessity to distinguish identifications according to their focus (i.e. organizational, team, or leader identification). Interestingly, transformational leadership (TFL) has been proposed to unfold its effects by transforming followers’ identifications and could thus be a powerful way to actively manage identification. However, it remains unclear whether TFL affects identifications with different foci similarly or whether it predominantly influences a specific focus. To resolve this puzzle, the authors conducted a meta-analysis (k = 73; N = 20,543) and found that TFL (and each TFL sub-dimension) is more strongly associated with leader identification than with organizational identification or team identification. By presenting a comprehensive model of TFL's effects on identifications, we show that leader identification mediates the relationships between TFL and collective identifications (i.e. organizational identification or team identification), illustrating that relational identification plays a crucial role in subsequently shaping collective identifications. Implications for research and practice are discussed.
An Econometric Model of Retail Rents in the United Kingdom

The present study constructs a model of retail rent determination at the aggregate level in the United Kingdom. While recognising the influence of very localised factors in the determination of retail rents, this paper explores the importance of broad economic forces and trends in the retail property market as determinants of retail rental values. A dynamic specification based on GDP, consumer expenditure and past values of retail rents in the U.K. This model provides satisfactory results and it is subsequently used to produce dynamic forecasts four quarters ahead. The forecasts suggested that U.K. retail rents would exhibit a slight recovery in the second half of 1994 terminating the downward trend since the first quarter of 1990. However, a small drop again was forecast for the first half of 1995.
Income Concentration and Market Demand

We analyze the effects of income concentration and income dispersion on market demand and its elasticity. We show that, following an increase in income concentration towards the middle (measured by variations in mean preserving spread), the increase in demand faced by firms which serve at the margin middle income consumers, is associated with an increase in price elasticity--accordingly, the positive effects of the size of the market becoming wider are amplified by a higher degree of competition. Our results hold for a large number of possible income distributions. Copyright 2002, Oxford University Press.
Interface Character Distributions in WC–Co Composites

The geometric and crystallographic characteristics of interfaces in WC–Co composites with a range of grain sizes and carbide volume fractions have been comprehensively characterized. The carbide crystals are most frequently terminated by (0001) and ð10 10Þ surfaces. The average number of carbide vertices per grain and the basal-to-prismatic face area ratio of the WC–Co interfaces increase with the carbide volume fraction. The three most frequently occurring WC/WC grain boundaries are 901 twist boundaries about ½10 10� ,3 01 twist boundaries about [0001], and asymmetric 901 boundaries about ½ 2110� . T he boundary populations do not vary with grain size or carbide volume fraction, suggesting that they are determined by the grain boundary energy anisotropy.
The impact of data quality dimensions on business process improvement

Guaranteeing high data quality level is an important issue to increase the efficiency of the business processes. In fact, poor data quality produces wrong information, which leads to the failure of the business process improvement. Identifying data quality problems has positive impact on overall effectiveness and efficiency of the process improvement. In fact, improving data quality often requires modifying business process enriching them with the most improvement activities. Such activities depend and change based on the data quality dimensions. In this paper, we focus on review of the impact of data quality dimensions on business process improvement in order to support managers to facilitate the implementation of process improvement. The evaluations of this research will use to refine and extend knowledge of relationship between data quality dimensions and business process improvement.
Low Serum Potassium Levels Associated with Disease Severity in Children with Nonalcoholic Fatty Liver Disease

Purpose Recent studies have suggested that decreased serum potassium level may contribute to various metabolic disorders in adult patients including nonalcoholic fatty liver disease (NAFLD). We aimed to study the correlation between serum potassium levels and the histologic severity of NAFLD in children. Methods Pediatric patients with biopsy-proven NAFLD were included in this study. Demographic, clinical, and histopathological data were obtained. Multivariable logistic regression analysis was used to assess whether potassium levels are associated with the presence of nonalcoholic steatohepatitis (NASH) or fibrosis after adjusting for possible confounders. A p-value <0.05 was considered statistically significant. Results Among 125 biopsies, 49.6% (62) had evidence of NASH while 66.4% (83) had some degree of fibrosis (stage 1-3). Mean serum potassium was significantly lower in NASH group as compared to non-NASH group (4.4±0.42 mmoL/L vs. 4.8±0.21, p<0.001). Higher potassium level had negative correlation with presence of steatosis, ballooning, lobular inflammation, fibrosis and NAFLD activity score (p<0.05). On multivariable analysis and after adjusting for the metabolic syndrome and insulin resistance, higher potassium level was significantly associated with lower likelihood of having a histological diagnosis of NASH on biopsy (odds ratio [OR], 0.12; 95% confidence interval [95% CI], 0.05-0.28; p<0.001). Similarly, the likelihood of having fibrosis decreases by 76% for every 0.5 mmoL/L increase in potassium (OR ,0.24; 95% CI, 0.11-0.54; p<0.001). Conclusion Our study shows an inverse relationship between serum potassium levels and the presence of aggressive disease (NASH and fibrosis) in children with NAFLD.
Salient object detection in SfM point cloud

In this paper we present a max-flow min-cut based salient object detection in 3D point cloud that results from Structure from Motion (SfM) pipeline. The SfM pipeline generates noisy point cloud due to the unwanted scenes captured along with the object in the image dataset of SfM. The background points being sparse and not meaningful, it becomes necessary to remove them. Hence, any further processes (like surface reconstruction) utilizing the cleaned up model will have no hinderance from the noise removed. We present a novel approach where the camera centers are used to segment out the salient object. The algorithm is completely autonomous and does not need any user input. We test our proposed method on Indian historical models reconstructed through SfM. We evaluate the results in terms of selectivity and specificity.
Facets of the set theoretic representation of categorical data

There are three basic notions in Data Analysis : object, category and descriptive attribute. Two description cases are of concern ; describing an object set O or describing a category set C. For the former case the set theoretic representation of a given attribute is defined with respect to O and for the latter, it is defined within each category of C. For these representations a given descriptive attribute is interpreted in terms of a relation with a given arity defined on the described set. We propose in this work a unique principle for the set theoretic representation of a descriptive attribute of different types : boolean, numerical, nominal categorical, ordinal categorical, preordonance categorical, taxonomic categorical and taxonomic preordonance categorical. The formal representations of these different types are explicited and compared in both cases : for an object set description and for a category set description. Then these representations are applied in interesting real examples.
Basic Perforator Flap Hemodynamic Mathematical Model

Background: A mathematical model to help explain the hemodynamic characteristics of perforator flaps based on blood flow resistance systems within the flap will serve as a theoretical guide for the future study and clinical applications of these flaps. Methods: There are 3 major blood flow resistance network systems of a perforator flap. These were defined as the blood flow resistance of an anastomosis between artery and artery of adjacent perforasomes, between artery and vein within a perforasome, and then between vein and vein corresponding to the outflow of that perforasome. From this, a calculation could be made of the number of such blood flow resistance network systems that must be crossed for all perforasomes within a perforator flap to predict whether that arrangement would be viable. Results: The summation of blood flow resistance networks from each perforasome in a given perforator flap could predict which portions would likely survive. This mathematical model shows how this is directly dependent on the location of the vascular pedicle to the flap and whether supercharging or superdrainage maneuvers have been added. These configurations will give an estimate of the hemodynamic characteristics for the given flap design. Conclusions: This basic mathematical model can (1) conveniently determine the degree of difficulty for each perforasome within a perforator flap to survive; (2) semiquantitatively allow the calculation of basic hemodynamic parameters; and (3) allow the assessment of the pros and cons expected for each pattern of perforasomes encountered clinically based on predictable hemodynamic observations.
Performance Analysis of Orthogonal Space-Time Block Code over Rayleigh Fading Channels for Various Modulation Techniques

use of multiple antennas at both transmitter and receiver has been shown to be an effective way to improve capacity and reliability over those achievable with single antenna wireless systems. Orthogonal Space-Time Block Code (OSTBC) is space-time coding techniques in which data is split into n streams which are simultaneously transmitted using n transmit antennas which can be received by single or multiple antennas. The performance of OSTBC technique can be analyzed for different modulation techniques using multiple transmitting and receiving antennas in terms of BER & SNR.