Miracle-dz/UniFAR-FTUs huggingface dataset:
Power efficiency optimisation of a three‐coil wireless power transfer using compensatory reactance

Magnetic coupling resonant-wireless power transfer (MCR-WPT) has attracted considerable attention in recent decades. A relay-coil structure is utilised to extend the transfer distance between the transmitter side (Tx) and receiver side (Rx). This structure increases the complexity of analysing and optimising the operation of the system. The optimal compensatory capacitors of a three-coil wireless power transfer (WPT) system with a relay coil were investigated based on the transfer efficiency. The WPT system is modelled according to the circuit theory using the magnetic coupling between the Tx and the Rx. The condition to derive the optimal efficiency is deduced into a polynomial equation using only the compensatory reactance of the relay coil. These real solutions are theoretically compared to determine the global optimum. An experimental prototype is implemented, and the experimental results agree well with the calculations.
Identifying blue ocean leadership items

The purposes of this paper are to identify the reliability and validity of the blue ocean leadership items. Blue ocean leadership (BOL) focuses on what leaders need to do, not on who they need to be, which is far easier to change and has a direct impact on performance. Stratified sampling is use to select the sample. Data is collected using survey method. Total of 500 questionnaire are distributed to middle to top level manager from the Government Link Companies (GLCs) and Multinational Companies (MNCs). Two type of analysis are used in this study in order to analyze the data which is exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Base from the analysis, 63 items could be used to measure BOL variable. These findings contribute to new knowledge in leadership study.
Uniﬁed Models for Multiwinding Coupled Magnetics

—Circuit models for multiwinding coupled magnetics are summarized, compared, and uniﬁed. Multiwinding coupled magnetics are classiﬁed into parallel coupled structure and series coupled structure. For parallel coupled structure, the relationships between a) inductance matrix model, b) extended cantilever model, c) magentic circuit model, d) multiwinding transformer model, e) gyrator-capacitor model, and f) inductance dual model are investigated and discussed. These models represent identical physical relationships in the multiphase coupled magnetics, but show different fundamental principles and offer distinct design insights. The circuit duality between the series coupled structure and parallel coupled structure is revealed. Design equations linking these models are compared and uniﬁed. The models and design equations are veriﬁed through theoretical derivation, SPICE simulation, and experimental measurements.
First principles study of structural, electronic and magnetic properties of SnGen(0, ±1) (n = 1–17) clusters

The structures, relative stability and magnetic properties of pure Gen+1, neutral cationic and anionic SnGen (n = 1–17) clusters have been investigated by using the first principles density functional theory implemented in SIESTA packages. We find that with the increasing of cluster size, the Gen+1 and SnGen(0, ±1) clusters tend to adopt compact structures. It has been also found that the Sn atom occupied a peripheral position for SnGen clusters when n < 12 and occupied a core position for n > 12. The structural and electronic properties such as optimized geometries, fragmentation energy, binding energy per atom, HOMO–LUMO gaps and second-order differences in energy of the pure Ge n+1 and SnGen clusters in their ground state are calculated and analyzed. All isomers of neutral SnGen clusters are generally nonmagnetic except for n = 1 and 4, where the total spin magnetic moments is 2μb. The total (DOS) and partial density of states of these clusters have been calculated to understand the origin of peculiar magnetic properties. The cluster size dependence of vertical ionization potentials, vertical electronic affinities, chemical hardness, adiabatic electron affinities and adiabatic ionization potentials have been calculated and discussed.
IMU-Assisted 2D SLAM Method for Low-Texture and Dynamic Environments

Generally, the key issues of 2D LiDAR-based simultaneous localization and mapping (SLAM) for indoor application include data association (DA) and closed-loop detection. Particularly, a low-texture environment, which refers to no obvious changes between two consecutive scanning outputs, with moving objects existing in the environment will bring great challenges on DA and the closed-loop detection, and the accuracy and consistency of SLAM may be badly affected. There is not much literature that addresses this issue. In this paper, a mapping strategy is firstly exploited to improve the performance of the 2D SLAM in dynamic environments. Secondly, a fusion method which combines the IMU sensor with a 2D LiDAR, based on framework of extended Kalman Filter (EKF), is proposed to enhance the performance under low-texture environments. In the front-end of the proposed SLAM method, initial motion estimation is obtained from the output of EKF, and it can be taken as the initial pose for the scan matching problem. Then the scan matching problem can be optimized by the Levenberg–Marquardt (LM) algorithm. For the back-end optimization, a sparse pose adjustment (SPA) method is employed. To improve the accuracy, the grid map is updated with the bicubic interpolation method for derivative computing. With the improvements both in the DA process and the back-end optimization stage, the accuracy and consistency of SLAM results in low-texture environments is enhanced. Qualitative and quantitative experiments with open-loop and closed-loop cases have been conducted and the results are analyzed, confirming that the proposed method is effective in low-texture and dynamic indoor environments.
Institutional Knowledge at Singapore Management University Institutional Knowledge at Singapore Management University Optimal Collusion with Internal Contracting Optimal Collusion with Internal Contracting

In this paper, two ﬁ rms play an in ﬁ nitely-repeated Bertrand game, and each ﬁ rm has an agent who produces the ﬁ rm’s output and holds private information about production costs. The colluding ﬁ rms ﬁ x prices and allocate market shares based on their agents’ information. We develop a model of collusion in which ﬁ rms use the presence of agents as a strategic opportunity to restrict their incentives to distort private information. We show that such ﬁ rm behavior may expand the scope of optimal collusion whether market-allocation schemes are asymmetric or symmetric.
The (Fuzzy) Digital Divide: Universal Broadband Access and Firm Performance

Providing “universal” broadband access to firms in rural and semi-urban areas is a key tenet of government policy. This paper exploits a unique geographical discontinuity in the availability of broadband to study the causal effect of broadband on the performance of firms located outside of major urban localities. Firms in towns and villages on one side of the divide had access to broadband services that those on the other side did not. The discontinuity stems from an historical accident, whereby the telecommunications in one area of the North East of England is delivered by a separate company to the national monopoly provider. We study the discontinuity at the boundary between these two telecommunications providers, which rolled out broadband infrastructure 5 years apart. Contrary to the belief underlying universal broadband policies, we consistently find that broadband has no statistically significant effect on the performance of firms. JEL classification: J23; J24; J31; O3
Urbanization and depressive symptoms among middle-aged and older adults in China

Aims Urbanization plays an important role in individuals' health. However, it is difficult to isolate healthy migrant effect between urbanization and health. This study examined the effects of urbanization on depressive symptoms and its possible pathways among Chinese middle-aged and older adults independent of the influence of health-selective migration. Methods Using the baseline survey of the China Health and Retirement Longitudinal Study, this study compared the depressive symptoms among three groups (urbanized rural residents, rural non-migrants and urban non-migrants). The 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) short form was used to measure depressive symptoms. Logistic regression models and Structural Equation Model (SEM) were applied to examine the association between urbanization and depressive symptoms and the corresponding potential mechanisms. Results Our final sample contained 11,156 respondents with an average age of 58.91 (SD = 9.48), with 5,142 males (46.09%) and 6,014 females (53.91%). Compared with urbanized rural residents, rural residents were more likely to have depressive symptoms (OR = 1.19, 95% CI = 1.07, 1.32), and urban residents were associated with a decreased risk of depressive symptoms (OR = 0.81, 95% CI: 0.70, 0.94). A large proportion of the association between urbanization and depressive symptoms were mainly mediated by social participation, income and living conditions. Conclusions Planned urbanization had an independent impact on decreased depressive symptoms. Improvements in social participation, income and living conditions are the main drivers behind this relationship. Additionally, urbanization compensates for the negative impact of depressive symptoms from disadvantaged early life conditions, but it cannot eliminate the gap between urbanized rural people and urban non-migrants.
DevelopmentSAP-1 Is Required for Regulatory T Cell Raf Signaling but not the ERK Effector

Regulatory T cells (T reg ) play an important role in immune regulation. Their development in the thymus requires TCR activation and recognition of peptide-MHC, although the downstream signals controlling commitment to the lineage are unclear. To compare the requirements for positive selection and T reg development, we studied knockout and transgenic mice defective in Raf signaling and the ERK effector SRF accessory protein 1 (SAP-1), a member of the ternary complex factor family of Ets domain transcription factors. Although SAP-1 deﬁcient mice display a severe defect in thymocyte positive selection, T reg development was unimpaired as assessed by expression of Foxp3 and the activation markers CD25, GITR, CTLA4, and CD103 in the CD4 (cid:1) cell population. In contrast, inhibition of Raf signaling by the interfering dominant negative Raf derivative reduced both Foxp3 (cid:1) and Foxp3 (cid:2) CD4 (cid:1) populations. In SAP-1-deﬁcient CD4 (cid:1) CD25 (cid:1) T reg cells, TCR crosslinking efﬁciently induced ERK activation, but transcriptional induction of the immediate early gene Egr-1 was impaired. Nevertheless, neither deletion of SAP-1 nor expression of a dominant negative Raf derivative affected the ability of CD4 (cid:1) CD25 (cid:1) T reg cells to suppress CD4 (cid:1) CD25 (cid:2) cell proliferation in vitro. Finally the suppressive activity of CD4 (cid:1) CD25 (cid:1) T reg cells lacking SAP-1 in an in vivo colitis model was not signiﬁcantly impaired. The signaling requirements for development of T reg cells in the thymus are thus distinct from those required for “conventional” T cell positive selection, and ERK signaling to SAP-1 is not required for the suppressive activity of T reg cells. The Journal of Immunology, 2007, 179: 6836–6844.
Implementation of Web usage Mining tool using Efficient Algorithm

: In this paper,The World Wide Web (WWW) continues to grow at an astounding rate in both the sheer volume of traffic and the size and complexity of Web sites. An important input to website design is the analysis of how a Web site is being used by the users. Usage analysis includes straightforward statistics, such as page access frequency, as well as sophisticated forms of analysis, such as finding the common traversal paths through a Web site. Web Usage Mining is usually done using data mining techniques to determine frequent access patterns of the users. There are two phases in the Web Usage Mining. The first phase is Data Preprocessing. There are several preprocessing tasks i.e. Data Cleaning, User Identification, Session Identification and Transaction Identification. These tasks are computationally intensive and time consuming. Which need to be performed on the data, this data collected from web server logs. The work initially develops on usage data preparation techniques in order to identify users and the user sessions. There after groups the user sessions of the users based on semantically meaningful access paths of the users. These access paths help to generate the frequent access patterns of the user that can be used for effective web page design. The second phase is Mining the frequent patterns. This phase generate the frequent patterns from the access paths of the users.
Pacifying Babel’s Tower: A scientometric analysis of polycentricity in urban research

It is sometimes claimed that the degree of polycentricity of an urban region influences that region’s competitiveness. However, because of widespread use and policy relevance, the underlying concept of polycentricity has become a ‘stretched concept’ in urban studies. As a result, academic debate on the topic leads to situations reminiscent of Babel’s Tower. This meta-study of the scientific literature in urban studies traces the conceptual stretching of polycentricity using scientometric methods and content analysis. All published studies that either apply the concept directly or cite a work that does, were collected from the Scopus bibliographic database. This resulted in a citation network with over 9,000 works and more than 20,000 citations between them. Network analysis and clustering algorithms were used to define the most influential papers in different citation clusters within the network. Subsequently, we employed content analysis to systematically assess the mechanisms associated with the formation of polycentric urban systems in each of these papers. Based on this meta-analysis, we argue that the common categorization of polycentricity research in intra-urban, inter-urban and inter-regional polycentricity is somewhat misleading. More apt categorizations to understand the origins of polycentricity’s conceptual ambiguity relate to different methodological traditions and geographical contexts in which the research is conducted. Nonetheless, we observe a firm relation across clusters between assessments of polycentricity and different kinds of agglomeration economies. We conclude by proposing a re-conceptualisation of polycentricity based on explicitly acknowledging the variable spatial impact of these different kinds of agglomeration economies. Polycentric and balanced territorial development of the EU is key element of achieving territorial cohesion [sic]. Where the most developed cities and regions within Europe cooperate as parts of a polycentric pattern they add value and act as centers contributing to the development of their wider regions. Urban development policies also have a significant role in this regard. Polycentric territorial development policy should foster the territorial competitiveness of the EU territory also outside the core ‘Pentagon area’.
Extracting bb Higgs Decay Signals using Multivariate Techniques

For low-mass Higgs boson production at ATLAS at {radical}s = 7 TeV, the hard subprocess gg {yields} h{sup 0} {yields} b{bar b} dominates but is in turn drowned out by background. We seek to exploit the intrinsic few-MeV mass width of the Higgs boson to observe it above the background in b{bar b}-dijet mass plots. The mass resolution of existing mass-reconstruction algorithms is insufficient for this purpose due to jet combinatorics, that is, the algorithms cannot identify every jet that results from b{bar b} Higgs decay. We combine these algorithms using the neural net (NN) and boosted regression tree (BDT) multivariate methods in attempt to improve the mass resolution. Events involving gg {yields} h{sup 0} {yields} b{bar b} are generated using Monte Carlo methods with Pythia and then the Toolkit for Multivariate Analysis (TMVA) is used to train and test NNs and BDTs. For a 120 GeV Standard Model Higgs boson, the m{sub h{sup 0}}-reconstruction width is reduced from 8.6 to 6.5 GeV. Most importantly, however, the methods used here allow for more advanced m{sub h{sup 0}}-reconstructions to be created in the future using multivariate methods.
Acromegalic arthropathy in various stages of the disease: a Magnetic Resonance Imaging (MRI) study

BACKGROUND: Arthropathy is a prevalent and invalidating complication of acromegaly with a characteristic radiographic phenotype. We aimed to further characterize cartilage and bone abnormalities associated with acromegalic arthropathy using Magnetic Resonance (MR) imaging. METHODS: Twenty-six patients (23% women, mean age 56.8±13.4 years), with active (N=10) and controlled acromegaly (N=16) underwent a 3.0T MRI of the right knee. Osteophytes, cartilage defects, bone marrow laesions, and subchondral cysts were assessed by KOSS (Knee Osteoarthritis Scoring System). Cartilage thickness and cartilage T2 relaxation times, in which higher values reflect increased water content, were measured. Fifty-nine controls (80% women, mean age 61.9±6.8 years) with primary knee OA were included for comparison. RESULTS: In active acromegaly, structural OA defects were already highly prevalent. Active acromegaly patients had thicker cartilage and higher cartilage T2 relaxation times than controlled patients. When compared to primary OA subjects, acromegaly patients seem to have less cysts, but comparable prevalence of osteophytosis, cartilage defects and bone marrow laesions. Acromegalic patients had thicker joint cartilage with higher cartilage T2 relaxation times than primary OA subjects. CONCLUSIONS: In active acromegaly, prevalence of structural OA fat (TR/TE 1900/18ms, TSE 150x150x115, PDW DRIVE sagittal and (TR/TE 2225/25ms, 150x150x86, matrix 432x336, slice thickness 3mm), and a 3D gradient fat-suppressed sagittal scan (details below). In addition, a sagittal T2-mapping scan ( vide infra ) performed.
Collagen-Induced Arthritis in Mice Complement Deficiency Ameliorates

Collagen-induced arthritis (CIA) is an experimental animal model of human rheumatoid arthritis being characterized by synovitis and progressive destruction of cartilage and bone. CIA is induced by injection of heterologous or homologous collagen type II in a susceptible murine strain. DBA/1J mice deﬁcient of complement factors C3 (C3 (cid:1) / (cid:1) ) and factor B (FB (cid:1) / (cid:1) ) were generated to elucidate the role of the complement system in CIA. When immunized with bovine collagen type II emulsiﬁed in CFA, control mice developed severe arthritis and high CII-speciﬁc IgG Ab titers. In contrast, the C3 (cid:1) / (cid:1) and FB (cid:1) / (cid:1) were highly resistant to CIA and displayed decreased CII-speciﬁc IgG Ab response. A repeated bovine collagen type II exposure 3 wk after the initial immunization led to an increase in the Ab response in all mice and triggered arthritis also in the complement-deﬁcient mice. Although the arthritic score of the C3 (cid:1) / (cid:1) mice was low, the arthritis in FB (cid:1) / (cid:1) mice ranked intermediate with regard to C3 (cid:1) / (cid:1) and control mice. We conclude that complement activation by both the classical and the alternative pathway plays a deleterious role in CIA. The Journal of Immunology, 2002, 169: 454–459. were immunized with bovine CII and arthritis was evaluated both clinically and histopathologically. We show that the Ab response in C3 (cid:1) / (cid:1) and FB (cid:1) / (cid:1) mice is impaired but can be boosted by repeated immunization. Regardless of the speciﬁc anti-CII Ab levels, the complement-deﬁcient mice display reduction or almost complete absence of clinically or histologically veriﬁable arthritis. These results show that the classical pathway and possibly also the alternative pathway are involved in the pathogenesis of CIA.
Machine Learning techniques and visualization tools for STM images at CNR-IOM labs

This thesis reports the activities carried out on a scientific archive of scanning tunneling microscopy images with the objective of organizing it in a more structured and convenient dataset. The work, performed in strict cooperation with scientists, is framed within the urgent and relevant issue of a correct data management approach in the scientific research activity. The solutions developed in this thesis are designed around the European Commission guidelines on research data management, which follow a concise set of principles, known as the FAIR Data Principles. The problem was addressed using different tools and techniques, addressing several shortcomings of the original dataset, meeting the needs of the data producers from one side, and giving the dataset a broader audience perspective on the other. In particular, the achievements of this work involve the creation of a database to store the scientific images metadata and the development of a web service to visually explore these metadata through interactive tools. Moreover, an analysis of the images and their representation led to the implementation of a novel technique to automatically detect and solve a particular type of image artifact. Finally, the focus of this thesis was dedicated to the development of a workflow for the labeling of the images based on the material composition of the measured samples. This goal was achieved using machine learning techniques, such as feature learning, to retrieve relevant images to help researchers in the manual labeling process. The complete source code used to reach the objectives of this thesis is open-source and publicly accessible (Rodani, 2020). The thesis is organized as follows: chapter one shortly introduces the problem of scientific data management, frames the specific challenges faced in this work within the data management activities of CNR-IOM, and illustrates the necessary technical elements of STM images. The second chapter introduces the original dataset, de-
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