Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated frequency tracking system for efficient mid‐range magnetic resonance wireless power transfer

An automated frequency tracking system is implemented for an efficient mid‐range magnetic resonance wireless power transfer based on an analysis of a wireless power link consisting of transmitting and receiving resonators placed in a strong coupling region.The proposed tracking system is designed to maintain a power transfer efficiency of more than 70% for any transfer distance range by directly monitoring the efficiency via out‐band communication. The advantage of the proposed system over other frequency tracking schemes is that the performance of the resonators and power amplifier can be applied to the tracking algorithm. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:1423–1426, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26858
Extending the Diffusion of Innovation Theory to Predict Smartphone Adoption Behaviour Among Higher Education Institutions’ Lecturers in Nigeria

With the rise in the number of ICT-enabled devices in Nigeria and considering the relevance and importance of these devices in effective teaching, it becomes legitimate and inevitable to understand the key predictors of smartphone adoption among lecturers in the higher education institutions (HEIs). While extant literatures are gorged with such investigations, the majority of Sub-Saharan African contexts are grossly under-researched. Using this as a point of departure, this paper seeks to answer these questions: what are the predictors of smartphone adoption among the university lecturers? And how do these identified predictors influence smartphone adoption among university lecturers? Since smartphone is a new technological device and its adoption as a teaching-enabled device is different from its traditional adoption for communication, the main objective of this paper is to empirically investigate the predictors of smartphone adoption among Nigerian university lecturers. The study was based on the lecturers of Nnamdi Azikiwe University, Awka, Anambra State, Nigeria. Data were collected using questionnaire based on multistage sampling technique of 284 respondents. Factor analysis and multiple regressions were used for data reduction and hypotheses testing respectively. Analyses of data reveal that personal experience, relative advantage, job relevance, triability, complexity and price were the predicators of smartphone adoption. The findings have serious implications for smartphone retail management among others.
Bandwidth enhancement techniques for planar inverted-F antenna

The planar inverted-F antenna (PIFA) is widely used in mobile radio systems because of its excellent performance. However, it is not yet employed as an ultra wide band (UWB) antenna because of its perceived narrowband characteristics. This study introduces three techniques for enhancing the impedance bandwidth of PIFA, which are (i) changes in the widths of feed plate and shorting plate, (ii) addition of an inverted-L-shaped parasitic element and (iii) addition of a rectangular parasitic element. It is shown that PIFAs with a very wide fractional bandwidths (up to 110%) can be achieved. Using these techniques, an UWB PIFA antenna is designed, manufactured and tested. Simulated and measured results are provided to verify the conclusion.
ASSESSING PATHOLOGIES ON VILLAMAYOR STONE (SALAMANCA, SPAIN) BY TERRESTRIAL LASER SCANNER INTENSITY DATA

This paper deals with the assessing of pathologies in facades using a variety of intensity data provided by different terrestrial laser scanner. In particular, a complex building built in the Villamayor Stone that is to be candidate as a Global Heritage Stone Resource has been chosen as study case. The Villamayor Stone were quarrying for the construction and ornamentation of monuments in Salamanca, declared World Heritage City by UNESCO in 1988. The objective of this paper is to assess the pathologies of Villamayor Stone and compare the results obtained through the laser techniques with the classical techniques of mapped pathologies (i.e. visual inspection). For that intensity data coming from laser scanners will be used as non-destructive techniques applied to the facades and several retired plaques (after of building restoration) of Villamayor Stone with pathologies (fissures, scales, loss of matter, humidity/biological colonization) carried to the laboratory. Subsequently it will perform different comparisons between the accuracy reached with the different sensors and a high precision model setup on laboratory which performs as “ground truth”. In particular, the following objectives will be pursued: i) accuracy assessment of the results obtained in in situ and laboratory; ii) an automation or semi-automation of the detection of pathologies in Villamayor Stone; iii) discriminate the different types of Villamayor Stone used in the facades in function of the radiometric response; iv) establish a methodology for detection and assessing of pathologies based on laser scanner intensity data applied to monuments and modern buildings built in Villamayor Stone.
Identification of Hub Genes in Diabetic Nephropathy by an Integrated Bioinformatic Analysis

BackgroundDiabetic nephropathy (DN) is a progressive kidney disease caused by damage to the capillaries in the kidneys' glomeruli. The dysregulation of genes plays a significant role in the progression of DN. MethodsIn the present study, gene expression profiles were analyzed to identify the key genes and pathways involved in DN. Gene expression profiles of 9 patients with DN and 11 normal subjects were downloaded from the Gene Expression Omnibus (GEO) database. Subsequently, differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. In addition, protein-protein interaction (PPI) networks were established and hub genes were identified. ResultsAs a result, a total of 424 DEGs were identified (113 were upregulated and 311 were downregulated). In the protein-protein interaction network, four hub modules and 30 hub genes were identified. To explore potential associations between gene and DN clinical features and to identify hub genes, the top 25% of genes with the greatest variance in the gene expression profiles were extracted for weighted correlation network analysis (WGCNA). There were ten genes (RNASE6, CD1C, SASH3, COL1A2, MS4A6A, CD163, CLEC10A, MOXD1, IQGAP2, GHR) identified as significant DN‐associated genes. Furthermore, the expression level of these hub genes was confirmed in the GSE96804 dataset. ConclusionsThese findings provide new insight into DN pathogenesis, which may enhance our fundamental knowledge of the molecular mechanisms underlying this disease.
Broadband vibration energy harvesting using triboelectric mechanism

This paper demonstrates an approach to vibration energy harvesting using contact electrification or triboelectric mechanism. The device uses a cantilever to realize the contact electrification process when subjected to external vibrations. The device utilizes stiffening in the cantilever beam introduced by contact between two triboelectric layers to broaden the bandwidth of the vibrational energy harvester. The operating bandwidth of the energy harvester is shown to increase from 4.4 Hz to 17.8 Hz at RMS output voltage level of 60mV. The device was also observed to demonstrate continuous improvement in bandwidth as the acceleration level increased.
Integration of clustering analysis and reward/penalty mechanisms for regulating service reliability in distribution systems

This study proposes an approach for improving service reliability in the distribution network based on establishing competition among electric distribution utilities. The idea behind this approach is to categorise the utilities and compare the performance of utilities located in one cluster with the other members of the same cluster. The reward/penalty mechanism (RPM) as a quality regulating instrument is designed for each cluster and used to penalise the utilities with a performance worse than the benchmark and to reward them for providing a performance better than the benchmark. Based on the RPM, utilities located in one cluster compete to make more profit by serving customers in better reliability level. The setting of a RPM in an ex-post manner is also proposed to provide incentives for utilities to improve their reliability in an active manner. The system reliability indices are utilised to measure the utilities performance. The proposed method is applied to 39 electric distribution utilities in Iran. The results show the effectiveness of combining clustering analysis with a reward/penalty instrument in reliability improvement.
Multi-Hierarchy Variable Fuzzy Evaluation Method of Planning Design Scheme of Urban Traffic Facilities

Based on variable fuzzy evaluation method and model, which is suitable for evaluation with the characteristics of multi-hierarchy, multi-indexes, dynamic variable and fuzzy though, this paper assesses the planning design schemes of urban traffic facilities to rich the evaluation research of this field, and that will provide references for more widespread application of variable fuzzy evaluation method and model in future. Key words: variable fuzzy, evaluation, urban traffic, planning design scheme
Capsule Network on Social Media Text: An Application to Automatic Detection of Clickbaits

The advent of groundbreaking deep learning techniques like Capsule Network has changed the way of approaching a problem in data science research. Initially, Capsule Networks were built and tested on image data and found to be of great use. Their usage on textual data is still very limited. In this paper, we try to investigate whether Capsule Network can be used to address a research problem where the classification heavily depends on the textual data. In various classification task involving social networks and online sources, words and sentences across classes do not vary that much. But, the context and representation of those words play a significant role. One such problem is to correctly identify clickbaits. State of the art solutions either take into account various handcrafted features from the data or use efficient text classification techniques like LSTM. Our work is a stepping stone towards examining whether the need of network properties and feature engineering can be omitted while using Capsule Network. It relaxes the effort of manual feature construction from the data and looks beyond the sequence to sequence modelling of an LSTM based approach. Our proposed approach of clickbait detection using a Capsule Network outperforms various existing methods in terms of multiple performance metric.
The Effects of Corporate Social Responsibility on Overseas Mergers and Acquisitions

This survey studies the effects of corporate social responsibility (CSR) on overseas mergers and acquisitions (overseas M&As) on acquirers’ corporate social responsibility (CSR) using a sample of Ghana multinational firms and MBA students. This study reveals that firms with overseas M&A activities experience an improvement in CSR performance during the post-acquisition period, and this positive effect is more distinctive when the acquisition of targets is from developed markets than from emerging or low-quality markets. Besides, acquirers significantly improve CSR performance following their overseas acquisitions, suggesting that acquirers initiate efforts to improve CSR performance to gain legitimacy in host countries. The study equally finds that host country legal origins, social norms, and the acquirers’ exposure to multiple jurisdictions hold the keys to improving the CSR performance of acquirers. The results appear robust and valid to various measures of CSR and are effective when endogeneity concerns are addressed. Further analyses disclose that overseas M&A firms with high CSR performance show greater CSR initiatives. Overall, our findings add to the field of literature on the influence of legal and social norm origins on shaping stakeholder-oriented practices by showing how overseas M&As may aid as a critical channel through which overseas acquirers bond themselves to the better CSR practices of the host countries.
Modified Multi-scale Feature Extraction for Copy-Move Forgery Detection Based on CMD-SIFT

The copy-move attack is a more common method in digital tampering. When copy-move forgery image occur, many important objects add or remove from the image. In order to implement forensic of the images, In the literatures many methods of copy-move forgery detection (CMFD) have been improved. The different approaches of CMFD feature-based was proposed in recent years. but, still more place to enhancement performance further. the problem of Many methods are suffering insufficient matched key points, but forgeries performance on the mirror transformed, then many feature-based methods when the forged region is of uniform texture it might hardly expose the tempering. In this paper we proposed a now scheme. In this scheme the criteria of block and keypoint features will integrate to gather in a new scheme, then multiple copy-move regions or objects will be work very well and especially when regions and objects are different sizes and contain both detailed textures and smooth.
Free Energy Landscapes for RBD Opening in SARS-CoV-2 Spike Glycoprotein Simulations Suggest Key Interactions and a Potentially Druggable Allosteric Pocket

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) an enveloped, positive-sense single-stranded RNA virus that is responsible for the COVID-19 pandemic. The viral spike is a class I viral fusion glycoprotein that extends from the viral surface and is responsible for viral entry into the host cell, and is the primary target of neutralizing antibodies. However, antibody recognition often involves variable surface epitopes on the spike, and the receptor binding domain (RBD) of the spike hides from immune recognition underneath a glycan shield aside from brief dynamic excursions to search for the host-cell surface receptor ACE2. Using an atomistic model of the glycosylated wild-type spike in the closed and 1-up RBD conformations, we identified specific interactions that stabilize the closed RBD, and mapped the free energy landscape for RBD opening. We characterized a transient pocket associated with a hinge motion during opening of the RBD, suggesting the possibility of allosteric control of the RBD via this region. Substitution of a conserved alanine to bulkier leucine in the pocket shifted the RBD equilibrium to favor the open, exposed state, as did removal of a conserved lysine that forms a critical salt-bridge in the closed, hidden state. Results from our virtual screening, MD simulations and free energy landscape calculations for wild-type spike suggest that small molecules can spontaneously bind to the highly conserved hinge pocket, and that such binding can shift the RBD equilibrium to favor the open state. Stabilizing the open state may facilitate antibody recognition by forcing the spike to expose critical RBD epitopes, and also could increase the likelihood of premature triggering of the spike fusion machinery via S1 shedding, neutralizing the infectious ability of the virus.
Development of a baseline model for a steel girder bridge using remote sensing and load tests

A new skewed two span continuous steel girder bridge was constructed and opened to traffic recently. This bridge uses high performance steel (HPS 100W) in the flanges of the negative moment region over the intermediate pier. For construction verification and long-term structural health monitoring purposes, a finite element (FE) model was developed for the bridge superstructure. Various field tests were performed to verify the model: 1) LiDAR scan, 2) static truck load tests, and 3) Laser doppler vibrometer testing. LiDAR scanner was introduced to gain geometrical information of the bridge in the real world. It was also used to measure girder deflections during load tests. The fundamental frequency of the bridge vibration was obtained by using a Laser doppler vibrometer. Both dynamic and static measurements are then used to update the FE model. This valid bridge superstructure FE model was provided to local DOT bridge engineers with the completion of this study.
Variable Window Stereo Matching Based on Phase Congruency

The major challenge in area stereo matching algorithms is to find appropriate window size and shape. Phase congruency is robust to noise and can reflects the gray changes. With these benefits, the paper first detects image and determines pixels characteristics according to phase congruency. Then, different window will be used to matching according to different feature pixels. After using cost function which combined with non-parametric measure and gray value, the final disparity map will be obtained. The result of experiment indicates that the algorithm can generates more accurate disparity map.
Synovial Sarcoma on Magnetic Resonance Imaging: a Retrospective Study on Tumor Configuration and Postoperative Surveillance

Background: To assess the configuration of primary and recurrent synovial sarcoma on MRI. Additionally, to evaluate postoperative MRI regarding diagnostic performance and locoregional post-treatment changes.Methods: Twenty-five patients with histologically proven synovial sarcomas underwent 1.5-T MRI follow-up between 2012 and 2018. In all, 258 pre- and postoperative MRIs with available radiological and pathological were screened for primary/recurrent synovial sarcoma, diagnostic performance (false-positive/-negative and true-positive/-negative values) and post-treatment changes.Results: The median age of the patients was 40±15.2 years. The median volumes of primary and recurrent synovial sarcomas were 603 cm3 and 806 cm3, respectively. Of the patients 24% presented recurrences (n=6). In two patients false-positive diagnosis was made . There was one false-negative diagnosis of synovial sarcoma. Primary synovial sarcomas were significantly most often polycyclic/multilobulated (p=0.01) and heterogeneous in appearance with marked contrast enhancement. Recurrent synovial sarcomas showed two appearances: ovoid/nodular/homogeneous and polycyclic/multilobulated/heterogeneous, both with marked contrast enhancement. The most common post-treatment changes were subcutaneous (92%; p<0.001) and muscular edema (72%; p<0.001-0.003). Conclusion: While the configuration of primary synovial sarcomas was mainly polycyclic/multilobulated/heterogeneous, recurrent synovial sarcomas showed two shapes: ovoid/homogeneous and polycyclic/multilobulated/heterogeneous. MRI is still a highly valuable imaging modality for the postoperative surveillance of synovial sarcomas. Subcutaneous and muscular edema are common post-treatment changes.
Development of a product audit tool

Abstract The creation of new products that satisfy both the needs of customers and of the company is widely acknowledged as an important contributor to a firm's ongoing success. In principle, the design process, as part of the wider new product development (NPD) process, should result in products that are ‘well designed’, but what does a well-designed product look like? This paper presents a tool to enable a design team to evaluate their products against a range of criteria, with a view to targeting design improvements. This ‘product audit’ tool is based on literature and has been iteratively developed using a mixed research approach, including detailed exploratory cases and application in action research mode. Previous assessment tools have tackled a narrow set of product issues, such as usability. This tool addresses the ‘whole product’ and captures aspects of product design in a concise and usable form. The product audit does not seek to be a benchmarking tool. Aspects such as novelty, desirability, usability, and producibility are expanded as simple checklists, to enable perceptions towards product characteristics to be assessed. This novel assessment tool encourages greater consideration of design issues within the wider context of NPD. By focusing attention on the tangible output of the design process ’ the product ’ practitioners are better able to understand the way in which design decisions influence product usability, desirability, and producibility. Case evidence confirms both the value and originality of this tool.
Minimally invasive beating heart technique for redo mitral valve surgery in patients with giant left ventricle

Purpose: To analyze the feasibility and efficacy of minimally invasive beating heart technique for redo mitral valve surgery in the cardiac patients with giant left ventricle.Methods: Eighty cardiac patients with giant left ventricle according to the diagnostic criteria that left ventricular end diastolic diameter (LVEDD) was ≥70 mm,who underwent redo mitral valve surgery at our center from January 2006 to January 2019 were analyzed. We divided all patients into minimally invasive beating heart technique group (n=30) and conventional median thoracotomy arrested heart technique group (n=50) according to the surgical methods. Preoperative, intraoperative, and postoperative variables were compared between two groups.Results: Minimally invasive beating heart technique compared to the conventional median thoracotomy arrested heart technique for redo mitral valve surgery in the cardiac patients with giant left ventricle had significant differences in operation time(P=0.002), cardiopulmonary bypass (CPB) time(P<0.001), intraoperative blood loss(P<0.001), postoperative transfusion ratio(P=0.01), postoperative transfusion amount(P<0.001), postoperative drainage volume(P=0.001), extubation time(P=0.04), intensive care unit (ICU) stay time(P=0.04) and postoperative hospital stay time(P<0.001), but no significant differences in re-exploration for bleeding, postoperative 30-day mortality, postoperative complications, and six months postoperative echocardiographic parameters.Conclusions: Using the method of minimally invasive beating heart technique for redo mitral valve surgery in the cardiac patients with giant left ventricle is feasible, effective, reliable and cosmetic, meanwhile reduce the operation time and CPB time, decrease the transfusion ratio and transfusion amount, shorten postoperative ICU stay and hospital stay time, promote the early extubation so that accelerate the patients’ early recovery.
Construction of a 3C Product Mold Manufacturing Process Predictive Optimization Model

Mold trials are critical in the mold development process; therefore, it is necessary to develop predictive models that can control processing results and solve problems in processing parameter optimization to ensure manufacturing efficiency and processing quality. Using the six sigma method, this research constructed an optimized 3C (Computer, Communication, and Consumer electronic) product mold manufacturing process predictive model, and conducted an empirical study on the largest electronic products foundry. The Taguchi parameter design method, the back propagation network (BPN) prediction method, and genetic algorithms (GAs) were used to establish an optimization search module. The surface quality was inferred by the network predictive model as a limiting condition for acquiring the maximized material removal rate in milling. The optimized milling processing parameters of the maximum fitness degree can be determined by GA. The findings can serve as a practical reference for quality improvements and decision planning.