Miracle-dz/UniFAR-FTUs huggingface dataset:
Engagement of STEM and Non-STEM Students: A Comparison between International and American Undergraduate Students.

iv ACKNOWLEDGMENTS . v DEDICATION. vii LIST OF TABLES . x LIST OF FIGURES . xi CHAPTER 1 – INTRODUCTION . 1 Problem Statement . 2 Student Engagement . 5 Research Questions . 10 Significance of the Study . 11 CHAPTER 2 – LITERATURE REVIEW . 15 Defining & Measuring Student Engagement . 16 Review of Theories Guiding Student Engagement Research . 21 Review of Literature on International Status and Student Engagement . 27 Review of Literature on STEM & Non-STEM Major and Student Engagement . 30 Review of Literature on Other Determinants of Student Engagement . 33 Proposed Conceptual Framework . 40 Conclusion . 42 CHAPTER 3 – RESEARCH DESIGN . 43 Data Source . 43 Why NSSE Data? 45 Data Reliability & Validity . 46 Data Variables . 47 Missing Value Analysis . 53 Research Method . 53 Limitations . 55 CHAPTER 4 – RESULTS . 57 Descriptive Statistics . 57 Research Question 1 . 61 Independent T-Test . 62 Multiple Imputation . 67
VCP/p97, Down-Regulated by microRNA-129-5p, Could Regulate the Progression of Hepatocellular Carcinoma

Valosin containing protein (VCP)/p97 plays various important roles in cells. Moreover, elevated expression of VCP in hepatocellular carcinoma (HCC) is correlated with increased incidence of recurrence. But the role of VCP in HCC progression in vitro and in vivo is unclear. And there are few reports about the regulation mechanism on the expression of VCP in HCC. In this study, it was identified that the level of VCP was frequently increased in human HCC tissues. In addition, down-regulation of VCP with siRNAs could dramatically suppress the genesis and progression of tumor in vivo. It was found that miR-129-5p directly inhibited the expression of VCP in several HCC cell lines. Meanwhile, the level of VCP in HCC tissues was negatively associated with the level of miR-129-5p. Our further investigation showed that the enhanced expression of miR-129-5p also suppressed tumor growth in vivo. Moreover, it was revealed that miR-129-5p could inhibit the degradation of IκBα and increase the apoptosis and reduce the migration of HCC cells by suppressing the expression of VCP. Our results revealed that the expression of VCP was directly regulated by miR-129-5p and this regulation played an important role in the progression of HCC.
Advanced modulation formats and digital signal processing for next generation fiber optics networks

Advanced modulation formats are proposed and analysed for next generation optical networks. The new evolving optical networks data rates of 100G and above require real time analog-to-digital conversion followed by real time digital signal processing. This is in order to allow increased spectral efficiency and full compensation of amplitude and phase distortion imposed by the optical channel in such high bitrates. Various approaches are presented, including discrete multi-tone and optical OFDM.
Perceptual quality metric for digitally coded color images

In this paper, a computational metric that incorporates many aspects of human vision and color perception to predict the quality of color coded images is presented. The proposed distortion measure is built on opponent-colors theory and on a multi-channel model of spatial vision. The metric has been validated by psychophysical data on 400 images and two human observers.
Comparison of AODV and R-AODV Routing Protocols by varying Network Mobility, Network Area and Network Density

A Mobile Ad hoc Network (MANET) is a temporary network with increased flexibility and mobility and lack of fixed infrastructure. Factors such as network mobility, network area and network density play an important role while evaluating the overall network performance of various on-demand MANET routing protocols. In this paper a comparative study between one of the most widely studied on- demand routing protocol, AODV (Ad hoc On-Demand Distance Vector) and a modified version of AODV, namely Reverse-AODV (R-AODV) has been presented by varying the above mentioned factors. Basically this paper evaluates the impact of these factors based on performance metrics such as packet delivery fraction and average end-to-end delay. A NS-2 based simulation study shows that R-AODV provides a reasonably good result as compared to AODV for almost all types of network scenarios.
Development of Analytical Model for Data Trustworthiness in Sensor Networks

The security and trustworthiness of data transmitted by sensors within the wireless sensor networks (WSN) are highly crucial, since the sensors' data can be easily accessed and manipulated by intruders or malfunctions. Data security within WSN can be viewed as how the data is protected during transmission, whereas the data trustworthiness represents the confidence of the sensed data. The unfriendly operational environment, insufficient energy, and hardware malfunction may be the cause of sensors' erratic behaviors, thereby making the sensed and collected data unreliable. Thus, data trustworthiness should ensure the confidence of the sensed data. In this work, we have developed an analytical model to represent the data trustworthiness of WSN, which is a first-order polynomial combining two trust factors. The trust factors are derived based on the average value of the previously transmitted data from the sensor, and the average value of the similar sensing data reported by its neighboring sensors. We have developed an algorithm to find the sensible subspace to operate on ensuring the maximum trust, where Simulated Annealing is utilized as a search tool to select the best weighted combination of trust factors. The experimental outcomes with varying deviation of sensing parameters reveal that 67% of the estimated trust-scores are in acceptable region.
Dual multiple change-point model leads to more accurate recombination detection

MOTIVATION We introduce a dual multiple change-point (MCP) model for recombination detection among aligned nucleotide sequences. The dual MCP model is an extension of the model introduced previously by Suchard and co-workers. In the original single MCP model, one change-point process is used to model spatial phylogenetic variation. Here, we show that using two change-point processes, one for spatial variation of tree topologies and the other for spatial variation of substitution process parameters, increases recombination detection accuracy. Statistical analysis is done in a Bayesian framework using reversible jump Markov chain Monte Carlo sampling to approximate the joint posterior distribution of all model parameters. RESULTS We use primate mitochondrial DNA data with simulated recombination break-points at specific locations to compare the two models. We also analyze two real HIV sequences to identify recombination break-points using the dual MCP model.
Question recommender with ML business logic

Advising the learner regarding the resources he needs to access in order to obtain best learning proficiency is one of the main issues in learning management systems. This paper presents an original method of recommending questions that need to be taken into consideration for answering by learner. The business logic that decides what questions are displayed to student is based on machine learning algorithms, more exactly on Naive Bayes classifier.
Design of Optimal Linear Phase FIR High Pass Filter using Improved Particle Swarm Optimization

This paper presents a novel approach for designing a linear phase digital high pass FIR filter using Improved Particle Swarm Optimization (IPSO) algorithm. Design of FIR filter is a multi-modal optimization problem. The conservative gradient based optimization techniques are not efficient for digital filter design. Given the specifications for the filters to be realized, IPSO algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristics. This paper presents the realization of the optimal FIR high pass filter of filter order 20 as per given problem statements. The simulation results have been compared to those obtained from well accepted classical algorithms like Park and McClellan algorithm (PM), and evolutionary algorithms like genetic algorithm (GA) and particle swarm optimization (PSO). The results rationalize that the proposed optimal filter design approach using IPSO outperforms PM, RGA, PSO in the accuracy of the designed filter, as well as in the convergence speed and solution quality.
RSS-based spoofing detection and localization algorithm in IEEE 802.11 wireless networks

Wireless networks have gained immense popularity in recent years. Though wireless networks have innumerous advantages over conventional wired networks, the borderless nature of wireless networks makes it prone to various felonious activities. In the context of network security, one of the most crucial vulnerabilities which have caused a serious global concern is the MAC Address Spoofing. MAC address spoofing facilitates launching of other attacks such as Denial-of-service, Man-in-the-middle, SYN flooding etc. In this paper we propose a methodology for the detection of spoofing attacks in IEEE 802.11 networks that involve performance of cluster analysis on RSS patterns of 802.11 transmitters which not only detect presence of a spoofing attack but also determine number of attackers. Further for localizing the adversaries, we propose a discriminant-adaptive neural network (DANN) based localization system.
Applying RFID Technology to construct an Elegant Hospital Environment

Radio frequency identification (RFID) technology has seen increasing adoption rates in applications that range from supply chain management, asset tracking, Medical/Health Care applications, People tracking, Manufacturing, Retail, Warehouses, and Livestock Timing. Of these, Medical/Health care applications are of more importance because minute errors in it can cost heavy financial and personal losses. The success of these applications depends heavily on the quality of the data stream generated by the RFID readers. Efficient and accurate data cleaning is an essential task for the successful deployment of RFID systems. Hence this paper gives the brief
A systematic review of protocol studies on conceptual design cognition: Design as search and exploration

This paper reports findings from the first systematic review of protocol studies focusing specifically on conceptual design cognition, aiming to answer the following research question: What is our current understanding of the cognitive processes involved in conceptual design tasks carried out by individual designers? We reviewed 47 studies on architectural design, engineering design and product design engineering. This paper reports 24 cognitive processes investigated in a subset of 33 studies aligning with two viewpoints on the nature of designing: (V1) design as search (10 processes, 41.7%); and (V2) design as exploration (14 processes, 58.3%). Studies on search focused on solution search and problem structuring, involving: long-term memory retrieval; working memory; operators and reasoning processes. Studies on exploration investigated: co-evolutionary design; visual reasoning; cognitive actions; and unexpected discovery and situated requirements invention. Overall, considerable conceptual and terminological differences were observed among the studies. Nonetheless, a common focus on memory, semantic, associative, visual perceptual and mental imagery processes was observed to an extent. We suggest three challenges for future research to advance the field: (i) developing general models/theories; (ii) testing protocol study findings using objective methods conducive to larger samples and (iii) developing a shared ontology of cognitive processes in design.
Towards the human, after the child of Man: Seeing the child differently in teacher education

Abstract Sylvia Wynter’s wide-ranging intellectual contributions contain a poetics of being and becoming human that serve to counter the hegemony of developmental psychology and its articulation of the child in teacher education. In this article, I use Wynter’s insights to unsettle the universality of this child figure to reveal the child of Man, a genre-specific formulation of the not-yet-fully-human white modal child. In the first part of the article, I demonstrate how the origins of the developing child are conjoined with purely biocentric nineteenth century views of the human as formulated within the context of asserting the hegemony of the Western bourgeois subject. In the second part, I consider how the genre-specific trope of the child of Man persists in teacher education and the kind of subjectivities it compels for teaching candidates. I explore materials relating to the developmental psychology course (i.e. standards, syllabi and textbook), an important site where teacher candidates confront notions of the child. I argue that the white Western bourgeois child masquerading as universal child is key to reproducing our current hierarchical order by inciting the violence of continual measurement, evaluation and ranking, thereby legitimizing and depoliticizing the “achievement gap”, and condemning Black, brown and poor children. In conclusion, I suggest ways to use Wynter’s poetics of being and becoming human in the constructive sense to inspire other ways of thinking about the child, teaching and learning for a project of re-enchanting humanism.
Artificial Neural Network Model for Alkali-Surfactant-Polymer Flooding in Viscous Oil Reservoirs: Generation and Application

Chemical flooding has been widely utilized to recover a large portion of the oil remaining in light and viscous oil reservoirs after the primary and secondary production processes. As core-flood tests and reservoir simulations take time to accurately estimate the recovery performances as well as analyzing the feasibility of an injection project, it is necessary to find a powerful tool to quickly predict the results with a level of acceptable accuracy. An approach involving the use of an artificial neural network to generate a representative model for estimating the alkali-surfactant-polymer flooding performance and evaluating the economic feasibility of viscous oil reservoirs from simulation is proposed in this study. A typical chemical flooding project was referenced for this numerical study. A number of simulations have been made for training on the basis of a base case from the design of 13 parameters. After training, the network scheme generated from a ratio data set of 50%-20%-30% corresponding to the number of samples used for training-validation-testing was selected for estimation with the total coefficient of determination of 0.986 and a root mean square error of 1.63%. In terms of model application, the chemical concentration and injection strategy were optimized to maximize the net present value (NPV) of the project at a specific oil price from the just created ANN model. To evaluate the feasibility of the project comprehensively in terms of market variations, a range of oil prices from 30 $/bbl to 60 $/bbl referenced from a real market situation was considered in conjunction with its probability following a statistical distribution on the NPV computation. Feasibility analysis of the optimal chemical injection scheme revealed a variation of profit from 0.42 $MM to 1.0 $MM, corresponding to the changes in oil price. In particular, at the highest possible oil prices, the project can earn approximately 0.61 $MM to 0.87 $MM for a quarter five-spot scale. Basically, the ANN model generated by this work can be flexibly applied in different economic conditions and extended to a larger reservoir scale for similar chemical flooding projects that demand a quick prediction rather than a simulation process.
Serum Calprotectin: A Potential Biomarker for Neonatal Sepsis

Introduction. The correct diagnosis of neonatal sepsis is a relevant problem because sepsis is one of the most important causes of neonatal morbidity, mortality, and prolonged hospital stay. Calprotectin is an antimicrobial, calcium and zinc binding heterocomplex protein that could be used as a nonspecific marker for activation of granulocytes and mononuclear phagocytes. Calprotectin has been proposed for the diagnosis of inflammatory conditions. Our aim is to study serum calprotectin as a biomarker for neonatal sepsis diagnosis. Methods. 41 (20 females, 21 males) infants who underwent blood culture due to suspected sepsis were enrolled in the study. Serum calprotectin was measured by a commercial ELISA assay (Calprest, Eurospital, Trieste, Italy). Statistical analysis was performed using the statistical software package Stata 13.1 (Stata Corporation, College Station, Texas, USA). Results. 8 neonates (19.51%) showed sepsis with positive culture and 33 (80.49%) showed suspected sepsis. The optimal cut-off for calprotectin is 2.2 μg/mL with a sensitivity of 62.5% and a specificity of 69.7%. Conclusions. Calprotectin may be considered a promising early, sensitive, specific marker of sepsis thanks to the importance of calprotectin in defense mechanisms and physiological functions of the immune system.
Phytoplankton growth and stoichiometry under multiple nutrient limitation

Phytoplankton growth and stoichiometry depend on the availability of multiple nutrients. We use a mathematical model of phytoplankton with flexible stoichiometry to explain patterns of phytoplankton composition in chemostat experiments and nutrient drawdown dynamics that are found in the field. Exponential growth and equilibrium represent two distinct phases, each amenable to mathematical analysis. In a chemostat at a fixed dilution (growth) rate, phytoplankton stoichiometry matches the nutrient supply stoichiometry over a wide range at low growth rates and over a narrow range at high growth rates. In a chemostat with a fixed nutrient supply stoichiometry, phytoplankton stoichiometry varies with dilution rate nonlinearly, between the supply stoichiometry at low dilution rates and a species‐specific optimal ratio at high dilution rates. The flexible‐stoichiometry model we study predicts low equilibrium concentrations of two nutrients over a wide range of supply ratios, contrary to the predictions of a traditional fixed‐stoichiometry model. The model is in quantitative agreement with experimental data, except at extreme nutrient supply ratios, which require a negative feedback from quota to uptake to fit the data. Our analysis points to the importance of better understanding the regulation of uptake rates in determining phytoplankton stoichiometry and incorporating this knowledge into phytoplankton models.
An integrated environment for designing object-oriented enterprise models

The paper presents an integrated environment fo r designing object-oriented enterprise models.The conceptual framework it is based on recommends a multi-perspective approach. For thispurpose three main views on the enterprise are proposed: a static view that focuses on the rep-resentation of structural aspects, a dynamic view that serves to represent office procedures anda strategic view. The environment that is introdu ced is intended to encourage the design of en-terprise models on these three levels as well as interconnecting them. The paper however willonly focus on two levels - the strategic view will be neglected. Two tools of the environmentwill be described in detail. The Object Model Designer guides conceptualisation of an enter-prise wide object model. Object models are repr esented using a graphical notation that is com-pleted by a structured description of classes and associations. In order to facilitate user feed-back fast prototyping is supported by generating code from class descriptions. The object mod-el´s implementation demonstrates the automatic control of semantically rich integrity con-strains as well as the benefits of inter-application communication using domain concepts ascommon references rather than technical ones. The Office Procedure Designer guides the de-scription of office procedures which are conceptualised as ordered graphs of activity blocks.It provides means to analyse th e effectiveness of business procedures and generates prototyp-ical user-interface as a representation of a virtual procedure document. Beside describing the tools listed above the pape r presents a conceptual framework for the de-sign of multi-perspective enterprise models. Furthermore it is demonstrated how the tools andthe related methods interact during analysis and design and how the partial models managedby the tools are integrated.
Prostacyclin mediates endothelial COX-2-dependent neuroprotective effects during excitotoxic brain injury

In a previous study, we found that intracerebral administration of excitotoxin (RS)-(tetrazole-5yl) glycine caused increased neural damage in the brain in an endothelial COX-2 deleted mouse line (Tie2Cre COX-2flox/flox). In this study, we investigated whether prostacyclin might mediate this endothelial COX-2-dependent neuroprotection. Administration of excitotoxin into the striatum induced the production of prostacyclin (PGI2) in wild type, but not in endothelial COX-2 deleted mice. Inhibition of PGI2 synthase exacerbated brain lesions induced by the excitotoxin in wild type, but not in endothelial COX-2 deleted mice. Administration of a PGI2 agonist reduced neural damage in both wild type and endothelial COX-2 deleted mice. Increased PGI2 synthase expression was found in infiltrating neutrophils. In an ex vivo assay, PGI2 reduced the excitotoxin-induced calcium influx into neurons, suggesting a cellular mechanism for PGI2 mediated neuroprotection. These results reveal that PGI2 mediates endothelial COX-2 dependent neuroprotection.
Resilience of North Sea phytoplankton spring bloom dynamics: An analysis of long‐term data at Helgoland Roads

Analyzing one of the most extensive long‐term data series in the North Sea, the Helgoland Roads time series, we investigated the changes in the factors that potentially drive phytoplankton bloom dynamics in the German Bight. We compared the changes in these factors with the changes in the spring bloom phenology. We combined zooplankton, nutrient, weather, and phytoplankton data to analyze whether there has been a shift in trophic interactions in the North Sea affecting the spring bloom timing. The potential influence of temperature, with a mean increase of 1.5°C, was investigated. We showed that the German Bight around Helgoland is a highly dynamic system and has undergone considerable change in the last 30 yr. Nutrient levels, temperature, underwater light climate and wind speed have all changed. However, the spring bloom dynamics have hardly changed at all. We showed that the spring bloom tends to come later in warmer years but that this is not directly correlated with the overall warming trend. The known regime shift of the late 1980s is clearly visible in our data in terms of average phytoplankton winter densities and average cell size, but even so the start of the spring bloom has not changed.
Container-based unified testbed for information-centric networking

To develop and evaluate diverse ICN protocols and applications, large-scale and extensible testbeds that facilitate realistic evaluations must be designed and deployed. We propose a container-based unified testbed for ICN, called CUTEi, which employs the Linux container lightweight virtualization mechanism to build testbed nodes. CUTEi enables testbed users to run applications and protocols for ICN in two experimentation modes using two different container designs: application- level experimentation using a "common container," and network-level experimentation using a "user container. " CUTEi also implements an "on-filesystem cache" to allocate caching data on a UNIX filesystem and share the cached data with multiple containers. Thus far we have deployed the CUTEi testbed on nine sites and performed experiments using CCNx components on the testbed. Consequently, we have found that it is easy to coordinate experiments on CUTEi; further, a comparison of its data fetch performance with that of PlanetLab indicates that CUTEi is more stable for ICN experiments than PlanetLab.