Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Early and Late Mild Cognitive Impairment Using Functional Brain Network of Resting-State fMRI

Using the Pearson correlation coefficient to constructing functional brain network has been evidenced to be an effective means to diagnose different stages of mild cognitive impairment (MCI) disease. In this study, we investigated the efficacy of a classification framework to distinguish early mild cognitive impairment (EMCI) from late mild cognitive impairment (LMCI) by using the effective features derived from functional brain network of three frequency bands (full-band: 0.01–0.08 Hz; slow-4: 0.027–0.08 Hz; slow-5: 0.01–0.027 Hz) at Rest. Graphic theory was performed to calculate and analyze the relationship between changes in network connectivity. Subsequently, three different algorithms [minimal redundancy maximal relevance (mRMR), sparse linear regression feature selection algorithm based on stationary selection (SS-LR), and Fisher Score (FS)] were applied to select the features of network attributes, respectively. Finally, we used the support vector machine (SVM) with nested cross validation to classify the samples into two categories to obtain unbiased results. Our results showed that the global efficiency, the local efficiency, and the average clustering coefficient were significantly higher in the slow-5 band for the LMCI–EMCI comparison, while the characteristic path length was significantly longer under most threshold values. The classification results showed that the features selected by the mRMR algorithm have higher classification performance than those selected by the SS-LR and FS algorithms. The classification results obtained by using mRMR algorithm in slow-5 band are the best, with 83.87% accuracy (ACC), 86.21% sensitivity (SEN), 81.21% specificity (SPE), and the area under receiver operating characteristic curve (AUC) of 0.905. The present results suggest that the method we proposed could effectively help diagnose MCI disease in clinic and predict its conversion to Alzheimer’s disease at an early stage.
Backward sequential approach for dynamic parameter identification of robot manipulators

This article proposes a sequential optimization approach to efficiently identify non-minimal dynamic parameters of robot manipulators, possibly having large degrees of freedom. A back-substitution-based parameter identification from the last link to inward links is enabled due to the block upper triangular form of inherent regressor matrix. Starting with the dynamic model using the non-minimal parameters, we derive a generic compact formulation for the linear regression equation. We then establish a sequential optimization procedure taking into account physical feasibility of parameters. Numerical case examples demonstrate the validity of the proposed approach.
Comparing Deep Neural Networks, Ensemble Classifiers, and Support Vector Machine Algorithms for Object-Based Urban Land Use/Land Cover Classification

With the advent of high-spatial resolution (HSR) satellite imagery, urban land use/land cover (LULC) mapping has become one of the most popular applications in remote sensing. Due to the importance of context information (e.g., size/shape/texture) for classifying urban LULC features, Geographic Object-Based Image Analysis (GEOBIA) techniques are commonly employed for mapping urban areas. Regardless of adopting a pixel- or object-based framework, the selection of a suitable classifier is of critical importance for urban mapping. The popularity of deep learning (DL) (or deep neural networks (DNNs)) for image classification has recently skyrocketed, but it is still arguable if, or to what extent, DL methods can outperform other state-of-the art ensemble and/or Support Vector Machines (SVM) algorithms in the context of urban LULC classification using GEOBIA. In this study, we carried out an experimental comparison among different architectures of DNNs (i.e., regular deep multilayer perceptron (MLP), regular autoencoder (RAE), sparse, autoencoder (SAE), variational autoencoder (AE), convolutional neural networks (CNN)), common ensemble algorithms (Random Forests (RF), Bagging Trees (BT), Gradient Boosting Trees (GB), and Extreme Gradient Boosting (XGB)), and SVM to investigate their potential for urban mapping using a GEOBIA approach. We tested the classifiers on two RS images (with spatial resolutions of 30 cm and 50 cm). Based on our experiments, we drew three main conclusions: First, we found that the MLP model was the most accurate classifier. Second, unsupervised pretraining with the use of autoencoders led to no improvement in the classification result. In addition, the small difference in the classification accuracies of MLP from those of other models like SVM, GB, and XGB classifiers demonstrated that other state-of-the-art machine learning classifiers are still versatile enough to handle mapping of complex landscapes. Finally, the experiments showed that the integration of CNN and GEOBIA could not lead to more accurate results than the other classifiers applied.
Investigating the Fast Response of Precipitation Intensity and Boundary Layer Temperature to Atmospheric Heating Using a Cloud‐Resolving Model

Coarse‐resolution global climate models cannot explicitly resolve the intensity distribution of tropical precipitation and how it responds to a forcing. We use a cloud‐resolving model to study how imposed atmospheric radiative heating (such as that caused by greenhouse gases or absorbing aerosols) may alter precipitation intensity in the setting of radiative‐convective equilibrium. It is found that the decrease in total precipitation is realized through preferentially reducing weak events. The intensity of strong precipitation events is maintained by a cancellation between the moistening of air parcels and weakening of updrafts. A boundary layer energy budget analysis suggests that free‐tropospheric heating raises boundary layer temperatures mainly through a reduction in rain reevaporation. This insight leads to a predictive scaling for the surface sensible and latent flux changes. The results imply that cloud microphysical processes play a key role in shaping the temperature and precipitation responses to atmospheric heating.
Research Online Research Online Financial liberalisation, bank ownership type and performance in a Financial liberalisation, bank ownership type and performance in a transition economy: The case of Vietnam transition economy: The case of Vietnam

Abstract Employing a sample of Vietnamese banks covering the period 2005 to 2015, this study investigates the influence of partial, and selective, financial liberalisation on bank efficiency by ownership type in a transition economy. The key findings are: (1) state-owned banks outperformed all other ownership types; (2) selective privatisation of state-owned banks exerted a positive influence on bank efficiency; (3) rural-to-urban private bank transformation decreased banking system efficiency; (4) minority foreign ownership exerted an insignificant impact on bank efficiency; (5) business group ownership improved the provision of intermediation services but deteriorated overall bank operating efficiency. Overall, the findings suggest that the post-WTO partial-liberalisation of the banking system in Vietnam impacted banks' efficiency differently subject to ownership type, with potentially adverse implications for long term economic growth and development. Abstract 3 Employing a sample of Vietnamese banks covering the period 2005 to 2015, this study 4 investigates the influence of partial, and selective, financial liberalisation on bank efficiency 5 by ownership type in a transition economy. The key findings are: (1) state-owned banks 6 outperformed all other ownership types; (2) selective privatisation of state-owned banks 7 exerted a positive influence on bank efficiency; (3) rural-to-urban private bank 8 transformation decreased banking system efficiency; (4) minority foreign ownership exerted 9 an insignificant impact on bank efficiency; (5) business group ownership improved the 10 provision of intermediation services but deteriorated overall bank operating efficiency. 11 Overall, the findings suggest that the post-WTO partial-liberalisation of the banking system 12 in Vietnam impacted banks’ efficiency differently subject to ownership type, with potentially 13 adverse implications for long term economic growth and development. 14
Research on the Correlation between Psychological Content Parameters of Social Expectations and the Indexes of Study Progress of Future Physical Education Teachers

Popovych, I. S. Research on the Correlation between Psychological Content Parameters of Social Expectations and the Indexes of Study Progress of Future Physical Education Teachers / I. S. Popovych, O. Ye. Blynova // Journal of Physical Education and Sport. - 2019. - № 19(3). - 847-853. - DOI :10.7752/jpes. - 2019. - S. 312.
Job Flows, Demographics and the Great Recession

The recession the United States economy entered in December of 2007 is considered to be the most severe downturn the country has experienced since the Great Depression. The unemployment rate reached as high as 10.1 percent in October 2009 - the highest we have seen since the 1982 recession. In this paper we examine the severity of this recession compared to those in the past by examining worker flows into and out of unemployment taking into account changes in the demographic structure of the population. We identify the most vulnerable groups of this recession by dissagregating the workforce by age, gender and race. We find that adjusting for the aging of the U.S. labor force increases the severity of this recession. Our results indicate that the increase in the unemployment rate is driven to a larger extent by the lack of hiring (low outflows), but flows into unemployment are still important for understanding unemployment rate dynamics (they are not as acyclical as some literature suggests) and differences in unemployment rates across demographic groups. We find that this is indeed a "mancession," as men face higher job separation probabilities, lower job finding probabilities and, as a result, higher unemployment rates than women. Lastly, there is some evidence that blacks suffered more than whites (again, this difference is particularly pronounced for men).
The Microphysics of Stratiform Precipitation During OLYMPEX: Compatibility Between Triple‐Frequency Radar and Airborne In Situ Observations

The link between stratiform precipitation microphysics and multifrequency radar observables is thoroughly investigated by exploiting simultaneous airborne radar and in situ observations collected from two aircraft during the OLYMPEX/RADEX (Olympic Mountain Experiment/Radar Definition Experiment 2015) field campaign. Above the melting level, in situ images and triple‐frequency radar signatures both indicate the presence of moderately rimed aggregates. Various mass‐size relationships of ice particles and snow scattering databases are used to compute the radar reflectivity from the in situ particle size distribution. At Ku and Ka band, the best agreement with radar observations is found when using the self‐similar Rayleigh‐Gans approximation for moderately rimed aggregates. At W band, a direct comparison is challenging because of the non‐Rayleigh effects and of the probable attenuation due to ice aggregates and supercooled liquid water between the two aircraft. A variational method enables the retrieval of the full precipitation profile above and below the melting layer, by combining the observations from the three radars. Even with three radar frequencies, the retrieval of rain properties is challenging over land, where the integrated attenuation is not available. Otherwise, retrieved mean volume diameters and water contents of both solid and liquid precipitation are in agreement with in situ observations and indicate local changes of the degree of riming of ice aggregates, on the scale of 5 km. Finally, retrieval results are analyzed to explore the validity of using continuity constraints on the water mass flux and diameter within the melting layer in order to improve retrievals of ice properties.
Managing academic identity tensions in a Canadian public university: the role of identity work in coping with managerialism

ABSTRACT Research shows that the ascendency of managerialism in the higher education sector and its fundamental contradictions with the professional values has placed misaligning identity claims upon academics. However, the identity tension that arises from the misfit between the professional ethos and the organisations’ market-driven requirements, and the ways in which academics cope with it has received insufficient attention. In this article, grounded on a conception of identity that describes it as in-progress narratives available to people, I analyse the routine work of academics in a Canadian public university. The results reveal that they reflexively and situationally construct different versions of their professional selves to minimise the tensions between the co-existing yet contradictory identity claims. In so doing, I found that the academics undertake two discursive strategies of embracing and distancing. I explain how these ‘identity work’ mechanisms help to strike a balance between the two contradictory discourses and suggest some directions for future research.
Determinants of social expenditures in post-socialist countries

DOI: 10.14254/2071789X.2019/12-2/15 ABSTRACT. This study compares the development of the welfare state between Western capitalist countries and a selection of post-socialist countries of both Asia and Europe by examining the determinants of social expenditures in those. A pooled time-series, cross-sectional analysis with panel-corrected standard errors was conducted on the determinants of social expenditures in 21 post-socialist countries: Albania, Azerbaijan, Belarus, Bulgaria, Croatia, Czech, Estonia, Georgia, Hungary, Kazakhstan, Latvia, Lithuania, Moldova, Poland, Romania, Russia, Serbia, Slovakia, Slovenia, Ukraine, and Uzbekistan, using 2005 to 2017 data. It was found that, as in Western societies, democratic and welfare systems are more developed in post-socialist states than in welfare states. However, the effects of socialist heritage and globalization differ, depending on the degree of economic development of the country concerned. While in the OECD countries, globalization leads to the development of the welfare state, in non-OECD countries, socialist heritage is an enabling condition for development of the welfare state.
Canyon topography effects on ground motion: Assessment of different soil stiffness profiles

David Solans, Evangelia Skiada, Stavroula Kontoe and David M. Potts Department of Civil and Environmental Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom, david.solans16@imperial.ac. uk, evangelia.skiada11@imperial.ac. uk, stavroula.kontoe@imperial.ac. uk, d.potts@imperial.ac. uk Efectos de topografía de cañón en movimientos sísmicos: Evaluación de diferentes perfiles de rigidez del suelo
Integration of information and communication technology in nursing education in Southeast Asia: A systematic literature review

BACKGROUND: The integration of information and communication technology (ICT) in education has been a major agenda of the Association of Southeast Asian Nations and its adoption has been found effective in nursing education. OBJECTIVE: This study aims to identify and review existing literature on ICT integration in nursing education within the context of Southeast Asia and to identify the themes of these studies, ICT tools of concern and the research methods adopted. METHODOLOGY: A systematic review of six eligible literatures was conducted with thematic analysis. The data for this systematic review of literature are from published studies based on the formulated research question. Electronic databases of Medline, Scopus, PubMed, CINAHL, Mendeley, and Google Scholar were searched and literatures retrieved and screened for eligibility. No date limit was considered in the literature search. This systematic review utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. RESULTS: The studies originated from the Philippines (n = 3), Malaysia (n = 2), and Singapore (n = 1). One study originated from both the Philippines and Thailand. Four themes emerged from the thematic analysis which include: (1) use of ICT to enhance teaching and learning in nursing, (2) challenges with ICT integration in nursing education, (3) attitude and perceptions toward ICT integration in nursing education, and (4) suggestions for improvement. The most important ICT tools were computers, projectors, and internet. Majority of the studies were descriptive quantitative studies. CONCLUSION: Despite increasing concern on the use of ICT in Southeast Asia, ICT integration in nursing education has not been given significant attention. Governments of the Southeast Asian countries should provide sufficient support for ICT integration in the various nursing institutions. Institutional administrators are encouraged to key into the ICT trend and render their support when and where necessary.
Policy Implementation, Principal Agency, and Strategic Action: Improving Teaching Effectiveness in New York City Middle Schools

Ten years ago, the reform of teacher evaluation was touted as a mechanism to improve teacher effectiveness. In response, virtually every state redesigned its teacher evaluation system. Recently, a growing narrative suggests these reforms failed and should be abandoned. This response may be overly simplistic. We explore the variability of New York City principals’ implementation of policies intended to promote teaching effectiveness. Drawing on survey, interview, and administrative data, we analyze whether principals believe they can use teacher evaluation and tenure policies to improve teaching effectiveness and how such perceptions influence policy implementation. We find that principals with greater perceived agency are more likely to strategically use tenure and evaluation policies. Results have important implications for principal training and policy implementation.
Cloud Based Small Cell Networks: System Model, Performance Analysis and Resource Allocation

Cloud-based small cell networks (C-SCNs) have recently been proposed as new wireless cellular architecture. In cloud-based networks, optimisation of radio resources at the base station (BSs) is moved to a cloud data centre for centralised optimisation. In the centre, multiple processors referred to as the cloud computational unit (CCU), is used for the optimisation. As the cell size and networks become respectively smaller and denser, the number of BSs to be optimised grows exponentially, resulting in high computational complexity and latency at CCUs. In this thesis, we propose belief propagation (BP) based power allocation schemes for C-SCNs that can be used for any network optimisation objectives such as energy consumption minimisation at the data centre and BSs; and spectral efficiency. The computation for the schemes is done in parallel, leading to very low latency and computational complexity with increasing number of BSs. We prove mathematically that the messages of the proposed algorithms converge to a fixed point and show via simulation that their performances regarding spectral and energy efficiency are close to an exhaustive search solution in finding the best configuration. All the proposed power optimisation above is based on the assumption that an unconstrained system latencies between multiple remote radio head (RRH) and the central unit (CU). The system latencies in cloud-based radio access networks (C-RANs) depend on the number of bits that are used to quantise the uplink signals at the RRH and the computational latency of the CU. In this thesis, we further investigate the reduction in transmission and computational latencies that are critical for low latency wireless communications. The former depends on the number of bits used to quantise the received signal from terminals at the RRH. The latter depends on the speed of resource allocation procedure at the CU. We propose a jointly uplink spectral efficiency and a latency optimisation scheme that compute the optimum terminal’s uplink power and number of quantisation bits for each RRHs in parallel by using a belief propagation technique. Our simulation results indicate a significant reduction in the transmission and computational
Application of Scanning Kelvin Probe in the Study of Protective Paints

Industrial coatings are composed of layers of different polymers (top coats, primers) containing pigments, corrosion inhibitors, and fillers as well as additives. For corrosion protection, it is vitally important to preserve the strong adhesion and long-term stability of the metal-polymer interface in corrosive environments. In recent decades, the performance of painted materials increased, which requires the application of advanced methods for quick assessing, ranking and predicting corrosion stability. Scanning Kelvin probe (SKP) is a highly sensitive and non-invasive technique to analyze in situ the metal-polymer interface of high-performance industrial coatings. SKP is able to monitor the adhesion and corrosion underneath different kinds of paints without the need for long-term corrosion tests. SKP is a localized electrochemical technique with a spatial resolution in the range of 70-100 µm. Hence, it is possible to obtain information about the intact and corroding portions of the interface at defect sites, corrosion blisters, contaminants and intermetallics, quality of pretreatments, and the development of galvanic couples that lead to corrosion de-adhesion of the polymeric coatings. This article reviews the application of SKP to the determination of the mechanisms of corrosion de-adhesion of model paints, thick marine paints, coatings with zinc rich primers, automotive paints and coil coatings applied on galvanized steel substrates.
Performance Appraisal Politics in the Public Sector: The Effects of Political Skill and Social Similarity on Performance Rating

This study investigated the main effects of a subordinate’s (ratee) political skill dimensions (social astuteness, apparent sincerity, interpersonal influence, and networking ability) on supervisor (rater) performance rating and further analyzed the interactive effects of social similarity in the subordinate–supervisor dyad on the relationship between political skill dimension and performance rating. To test these relationships, hierarchical linear modeling (HLM) was used on a matched sample of 337 subordinate–supervisor dyads who worked in South Korea’s central government. Findings showed that subordinates with higher social astuteness, interpersonal influence, and networking abilities (but not apparent sincerity) will likely achieve more positive supervisor ratings. More importantly, the relationship between these political skill dimensions and performance ratings is stronger when there is greater social similarity between a subordinate (ratee) and his or her supervisor (rater). The findings’ practical and academic implications and future research directions are discussed.