Miracle-dz/UniFAR-FTUs huggingface dataset:
microRNA as a Potential Vector for the Propagation of Robustness in Protein Expression and Oscillatory Dynamics within a ceRNA Network

microRNAs (miRNAs) are small noncoding RNAs that are important post-transcriptional regulators of gene expression. miRNAs can induce thresholds in protein synthesis. Such thresholds in protein output can be also achieved by oligomerization of transcription factors (TF) for the control of gene expression. First, we propose a minimal model for protein expression regulated by miRNA and by oligomerization of TF. We show that miRNA and oligomerization of TF generate a buffer, which increases the robustness of protein output towards molecular noise as well as towards random variation of kinetics parameters. Next, we extend the model by considering that the same miRNA can bind to multiple messenger RNAs, which accounts for the dynamics of a minimal competing endogenous RNAs (ceRNAs) network. The model shows that, through common miRNA regulation, TF can control the expression of all proteins formed by the ceRNA network, even if it drives the expression of only one gene in the network. The model further suggests that the threshold in protein synthesis mediated by the oligomerization of TF can be propagated to the other genes, which can increase the robustness of the expression of all genes in such ceRNA network. Furthermore, we show that a miRNA could increase the time delay of a “Goodwin-like” oscillator model, which may favor the occurrence of oscillations of large amplitude. This result predicts important roles of miRNAs in the control of the molecular mechanisms leading to the emergence of biological rhythms. Moreover, a model for the latter oscillator embedded in a ceRNA network indicates that the oscillatory behavior can be propagated, via the shared miRNA, to all proteins formed by such ceRNA network. Thus, by means of computational models, we show that miRNAs could act as vectors allowing the propagation of robustness in protein synthesis as well as oscillatory behaviors within ceRNA networks.
Identifying Image Authenticity by Detecting Inconsistency in Light Source Direction

Inconsistency in light source direction resulted from image forgery is one of the traces which cannot be removed. Hereby, a blind identification to distinguish the image authenticity by detecting inconsistency in light source direction was proposed. The search means and least-squares method were used to calculate the light source direction for local and infinite light source images respectively, in accordance with the error function between the actual intensity and calculated intensity, as well as the constraint function suitable for different light source models. And, by analyzing if the light source directions between different objects and background in one image are consistent to determine whether the image had been altered. Experimental results showed that the correct detection rates of blind identification for local and infinite light source images were 87.31% and 85.47% respectively. Keywordsimage tampering; inconsistency in light source direction; blind identification; local light source; infinite light source
Analysis of certificated mobile application for medical education purposes

Background. The evolution and the growth of mobile application in our society is a reality. This evolution has been spread in the Medical Schools as well, being part of the self-learning of the students and a tool for medical teachers. However, there is a lot of unawareness of the use of mobile applications, as the medical professionals do not know the most suitable applications for their educational purposes. The aim of this research is to analyze, design and implement a quality protocol that can be validated with different mobile applications already developed. The methodology was based on two phases. The first one included a Technological Acceptance model (TAM) survey and the second one is based on a practical implementation of the quality protocol. The first results of the research are presented in this study. The participants of the first approach were 124 and these results reveal the attitude toward the new technologies by medical professionals and undergraduate students and the necessity of a certification for mobile application in the medical education. Conclusions. The mobile applications are a potential tool to use in Medical Schools. The medical professionals are open-minded to introduce them in their curriculum. However, they have to be provided with the needed resources and a certification of mobile applications that allows them to trust on them.
Enhancement of Medical Ultrasound Images using Non-Linear Filtering Based on Rational-Dilation Wavelet Transform

 Abstract— Feature preserved enhancement is of great interest in medical ultrasound images. Speckle is a main factor which affects the quality, contrast resolution and most important texture information present in ultrasound images and can make the post-processing difficult. This paper presents a new computationally efficient enhancement approach which is based on the rational-dilation wavelet transform (RADWT) and non-linear bilateral filter. RADWT, a new family of the discrete wavelet transform for which frequency resolution can be varied, is employed to provide effective representation of the noisy coefficient. Bilateral filter and different thresholding schemes are applied to the noisy RADWT coefficient to improve the denoising efficiency and preserve the edge features effectively with this consideration that blurring associated with speckle reduction should be less and fine details are enhanced properly for the visual enhancement of ultrasound images. The proposed approach helps also to improve the visual quality of the ultrasound images. Experimental results demonstrate the ability of proposed method for noise suppression, feature and edge preservation in terms of different performance measures.
Public Opinion in State Politics

Contents List of Tables and Figures Preface Acknowledgments Contributors 1. "Introduction: Studying Public Opinion in the American States" by Jeffrey E. Cohen 2. "Does Familiarity Breed Contempt? Examining the Correlates of State-level Confidence in the Federal Government" by Paul Brace and Martin Johnson 3. "State Residency, State Laws, and Public Opinion" by Barbara Norrander and Clyde Wilcox 4. "Mexican-American and Cuban-American Public Opinion: Differences at the State Level? " by David L. Leal 5. "Public Opinion in the States: Determinants of Legislative Job Performance" by John A. Hamman 6. "The State Economy, the National Economy, and Gubernatorial Popularity" by Jeffrey E. Cohen and James D. King 7. "Ideological Cleavage, Political Competition, and Policy Making in the American States" by Charles J. Barrilleaux 8. "The Civil State: Trust, Polarization, and the Quality of State Government" by Eric M. Uslaner 9. "Public Opinion and Policymaking in the Culture Wars: Is there a Connection between Opinion and State Policy on Gay and Lesbian Issues? " by Donald Haider-Markel and Matthew S. Kaufman 10. "Citizen Influences on State Policy Priorities: The Interplay of Public Opinion and Interest Groups" by Saundra K. Schneider and William G. Jacoby 11. "State Level Opinions From National Surveys: Post-Stratification Using Multilevel Logistic Regression" David K. Park, Andrew Gelman, and Joseph Bafumi 12. "Public Opinion in the States: A Quarter Century of Change and Stability" by Robert Erikson, Gerald Wright, and John McIver 13. "Conclusions: Where We Have Been, Where Should We Go" by Jeffrey E. Cohen Index
Comments on the NOAA Scientific Panel Report by:

The report describes discrepancies between current and historical carrying capacity for the SRKW, but fails to discuss options for increasing current carrying capacity. The report also appears to be overwhelmingly focused on broad demographic associations between annual SRKW population growth and fish abundance that occur over a relatively long time scale. Too little attention is paid to changes occurring over shorter time scales, including key transitional pinch-points of salmon runs and availability facing the SRKW population over each year. The panel rightly recommended the need to focus on more sensitive tools to monitor nutritional and associated impacts on SRKW population growth. However, again, their only specific recommendation was for photogrammetric measures, which occur over a relatively long time scale. They dismissed the use of more short-term physiological analyses from scat, arguing that hormones are confounded because they have multiple functions. However, as argued below, the multiple functions of these hormones should instead be viewed as strengths; their measurement in properly designed studies allows investigators to observe how physiological levels change over the short-term with the various environmental pressures the SRKW are responding to. Such short-term temporal changes are particularly conducive for designing and evaluating mitigation.
Feature Matches Filtering Using Geometric Invariants in Image Registration Tasks

Filtering of feature matches is heuristic method aimed to reduce the number of feasible matches and is widely employed in different image registration algorithms based on local features. In this paper we propose to interpret the filtering process as an optimal classification of the matches into the correct or incorrect match classes. The statistics, according to which the filtering is per- formed, uses differences of the geometrical invariants obtained from ordered sets of local features (composite features) of proper cardinality. Further, we examine some computationally efficient im- plementation schemes of the classification. Under the assumption of Gaussian measurement error, the conditional distribution densities of invariants can be approximated by well-known linearization approach. Experimental evidences obtained from fingerprint identification, which confirm viability of the proposed approach, are presented.
Partitioning Trust in Network Testbeds

Traditionally, test beds for networking and systems research have been designed as monolithic facilities: they contain a single root of trust. The resources in the facility are assumed to be administered by a single entity or a set of mutually-trusting entities. All user management, including vouching for users' identities and taking responsibility for their actions, is done using a flat trust structure or a simple hierarchy with the facility itself as the root. This design is not a good match for test beds that are composed of multiple autonomous facilities, or in which different parts of the test bed operate under different trust models. In this paper, we argue that partitioned trust is increasingly important in large scale and security-sensitive test beds. We present a design that accomplishes this partitioning by using multiple trust roots. The trust domains created by these roots may decide, independently, how much trust to place in each other, and can apply policies based on the domain or principal that originates a request. The domains could represent separately administered facilities (as in a federated test bed), or they could represent sections within a single facility that run with different trust models (for example, with differing levels of security.) We have implemented this design in ProtoGENI, a control framework for federated test beds, we include details of this implementation and share experiences from using it in an active deployment with hundreds of users.
Feature selection for pose invariant face recognition

One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In this work, we have designed a feature based pose estimation and face recognition system using 2D Gabor wavelets as local feature information. The difference of our system from the existing ones lies in its simplicity and its intelligent sampling of local features. Intelligent feature selection can be carried out by learning a set of parameters where the aim is the optimal performance of the overall system. In this paper we give comparative analysis of the performance of our system with the standard modular eigenfaces approach and show that local feature based approach improved the performance of both pose estimation and face recognition. For efficient coding, we have employed principal component analysis to the outputs of local feature vectors. Intelligent feature selection also reduced the space and time complexity of the system while retaining almost the same estimation and recognition accuracy.
Evaluation of manipulators based on a force accuracy index considering task-directions

Some manipulation tasks have directions of forces required at a manipulator's endpoint and directions for which force accuracy is required. This paper proposes a new index (FAIT: Force Accuracy Index for Task-directions) that allows us to evaluate the force accuracy of manipulators considering the task-directions. Firstly, we derive the FAIT. Secondly, we evaluate some postures of a 2-degrees of freedom (DOF) planar manipulator on the basis of some indices that have been proposed (condition number, manipulability measure and task compatibility) and the FAIT, respectively. Finally, from the evaluation results, we discuss the usefulness of the FAIT.
Constraint-Based and Sensorless Force Control With an Application to a Lightweight Dual-Arm Robot

The increasing demand for flexible robotized solutions in SMEs motivates the research on innovative and general control algorithms suitable for a large variety of applications. Particularly suited for this are constraint-based trajectory generation and control methods, which have been deeply investigated in the last decade. In this letter, we present an application of such a control framework for sensorless execution of a force control task as applied to a dual-arm redundant manipulator. Experiments and simulations confirm the effectiveness of the approach, even in the case of parametric uncertainties.
IMPLEMENTATION AND VALIDATION OF OBJECT-ORIENTED DESIGN-LEVEL COHESION METRICS

_______________________________ Date iii DEDICATION This thesis is dedicated to my parent: Late Alhaji Adamu and Hajiya Titi Yusuf. & To my wonderful stepmother: Hajiya Habiba Adamu iv ACKNOWLEDGEMENT I would like to begin by thanking Allah, Lord of the worlds, for His infinite mercy, blessing and forgiveness. I thank King Fahd University of Petroleum and Minerals for supporting this research. My deepest appreciation goes to my thesis advisor, Dr. Jarallah Al-Ghamdi, who has an attitude and the substance of being a good scholar and a good advisor. His continual support and constructive criticism is highly appreciated; I do not know what would have become of this thesis without his support. I am very thankful to the members of my thesis committee: Dr. Krishna Rao and Dr. Moataz Ahmed for their valuable contributions. In particular Dr. Moataz's contributions have been invaluable for this research. My thank goes to the Software Metrics Research Group (SMRG); I found the weekly meetings highly informative. I would like to thank my friends and colleagues in KFUPM for their companionship especially Rufai, Sohel and Abid for their concern and brotherly support in the course of this research. Immense appreciation goes to Yushau Balarabe, Yau Garba and Hamisu Shehu for their assistance; and to Hassan (Abu Hamza) for helping with some of the statistical analysis. Finally, I thank the members of my family for their care, love and prayers I believe this is what kept me going.
Antihistaminic effect of Bauhinia racemosa leaves

Bauhinia racemosa Lam. (Caesalpiniaceae) leaves have been used in the treatment of asthma traditionally and we therefore undertook this study to scientifically validate its benefit in asthma using suitable animal models. Antihistaminic principles are known to be useful in the treatment of asthma; hence, in the present work, the antihistaminic activity of an ethanol extract of B. racemosa (at a dose of 50 mg/kg, i.p.) was assessed using clonidine-induced catalepsy and haloperidol-induced catalepsy in Swiss albino mice. The results showed that the ethanol extract inhibits clonidine-induced catalepsy but there is no effect on haloperidol-induced catalepsy. This suggests that the inhibition is through an antihistaminic action and that there is no role of dopamine. Hence, we concluded that the ethanol extract has significant antihistaminic activity. The polar constituents in the ethanol extract of leaves of B. racemosa may be responsible for the antihistaminic activity and B. racemosa may therefore have a role in the treatment of asthma.
Robust Inferences from Random Clustered Samples: Applications Using Data from the Panel Survey of Income Dynamics

Many large data sets are created using clustered, rather than random sampling schemes. Clustered data arise when multiple observations exist on the same respondent, as in panel data, and when respondents share a common factor, such as a neighborhood or family. In the presence of clustered data, methods that rely on random sampling to measure the precision of an estimator may be incorrect. Many researchers, however, continue to treat respondents from the same sampling cluster as independent observations and thus implicitly ignore the potential intracluster correlation. In this paper, I use a robust method for drawing inferences and data from the Panel Survey of Income Dynamics, to examine the implications of clustered samples on inference. Consistent with the previous survey sampling literature, important differences are revealed in comparisons between the estimated asymptotic variances derived assuming random and clustered sampling, even when there are only a few observations per cluster. The estimates derived under random sampling are generally biased downward.
HRD in the Age of Globalization: A Practical Guide To Workplace Learning In The Third Millennium

The pro- and anti-globalization forces may be logically at odds, but there's little dispute on the inevitability of globalization's forward march. And as Michael Marquardt, Nancy Berger, and Peter Loan explain, the real issue is not stopping or promoting globalization, but rather how to minimize the negative effects of globalization and leverage its powerful, positive effects. Human Resource Development will play a key role in determining this transformation. At no time in history has HRD been more critical in solving urgent economic and social problems faced by a wide array of groups, communities, organizations, and nations. HRD in the Age of Globalization explores the best HRD programs in twelve geographic regions and their impact on culture, the global environment, and other geopolitical and demographic elements. This book not only answers all the questions that exist concerning this burgeoning field-it tells us what questions we should be asking.
EncephalomyelitisDevelopment of Spontaneous Autoimmune CD28 Costimulation Is Crucial for the

Multiple sclerosis (MS) is a severe central nervous system disease. Experimental autoimmune encephalomyelitis (EAE) mimics MS in mice. We report that spontaneous development of EAE in RAG-1-deﬁcient mice transgenic for a myelin basic protein (MBP)-speciﬁc TCR (TgMBP 1 /RAG-1 2 / 2 ) requires expression of the T cell costimulatory molecule CD28. Surprisingly, T cells from CD28 2 / 2 TgMBP 1 /RAG-1 2 / 2 mice proliferate and produce IL-2 in response to MBP 1–17 peptide in vitro, excluding clonal anergy as the mechanism of CD28-regulated pathogenesis. Proliferation of autoaggressive T cells was dependent on the concentration of the MBP peptide, as was the development of MBP-induced EAE in CD28-deﬁcient PL/J mice. These results provide the ﬁrst genetic evidence that CD28 costimulation is crucial for MBP-speciﬁc T cell activation in vivo and the initiation of spontaneous EAE. The Journal of Immunology, 1999, 162: 4490–4495. concentration-dependent (Fig. 3 b ). These results indicate that CD28 plays a role in controlling the activation of autoaggressive TgMBP 1 T cells, depending on the concentration of the autoantigen.
A Decentral, Adaptive Load Sharing Approach for Workstation Clusters Using Fuzzy Logic

This paper presents a load sharing heuristic for distributed computing on workstation clusters. The approach is novel in that it combines the use of predicted resource requirements of processes (CPU-time, memory requirements, density of the I/O-stream) and a fuzzy logic controller which makes the placement decision. The heuristic is distributed, i.e. each node runs a copy of the prediction and load sharing code, and its implementation is based on PVM. Using a benchmark program (Choleski factorization) experiments were conducted to compare the proposed heuristic against standard PVM and an older version of the presented heuristic without the fuzzy logic controller.
Why are Capital Flows so Much More Volatile in Emerging than in Developed Countries?

The standard deviations of capital flows to emerging countries are 80 percent higher than those to developed countries. First, we show that very little of this difference can be explained by more volatile fundamentals or by higher sensitivity to fundamentals. Second, we show that most of the difference in volatility can be accounted for by three characteristics of capital flows: (i) capital flows to emerging countries are more subject to occasional large negative shocks (“crises”) than those to developed countries, (ii) shocks are subject to contagion, and (iii) – the most important one – shocks to capital flows to emerging countries are more persistent than those to developed countries. Finally, we study a number of country characteristics to determine which are most associated with capital flow volatility. Our results suggest that underdevelopment of domestic financial markets, weak institutions, and low income per capita, are all associated with capital flow volatility.
A price prediction model for online auctions using fuzzy reasoning techniques

E-consumers are urged to opt for the best bidding strategies to excel in the competitive environment of multiple and simultaneous online auctions for same or similar items. It becomes very complicated for the bidders to make the decisions of selecting which auction to participate in, place single or multiple bids, early or late bidding and how much to bid. In this paper, we present the design of an autonomous dynamic bidding agent (ADBA) that makes these decisions on behalf of the buyers according to their bidding behaviors. The agent develops a comprehensive methodology for initial price estimation and an integrated model for final price prediction. The initial price estimation methodology selects an auction to participate in and assesses the value (initial price) of the auctioned item. Then the final price prediction model forecasts the bid amount by designing different bidding strategies using fuzzy reasoning techniques. The experimental results demonstrated improved initial price prediction outcomes by proposing a clustering based approach. Also, the results show the proficiency of the fuzzy bidding strategies in terms of their success rate and expected utility.