Miracle-dz/UniFAR-FTUs huggingface dataset:
Students' Evaluation of a MOODLE Resource in the Federal University of Technology, Akure, Nigeria

The new knowledge technologies have maximized teaching and learning opportunities and have been used to configure patterns of social interactions in the classroom. Bill Gates (cited in Ker, 2006) rightly concludes that the information superhighway will transform education in the first quarter of the twenty-first century. The global, expansive nature of online resources allows for simultaneous delivery of peda-gogic content to learners in all parts of the world and enhances widespread use of web-based instruction and e-learning opportunities. The new media have been responsible for rapid technological advancement and development in this age and they have remained at the centre spread of global socio-economic change. More importantly, they have been used to maximize both teaching and learning opportunities in both first and second language situations and in the teaching of EAP which is the major concern in this work. ABSTRACT This chapter presents an exploratory study on students’ evaluation of a MOODLE teaching and learn - ing resource (the Wiki in this case) in the Federal University of Technology, Akure, Nigeria. 85 students (11 female and 74 male) were guided in the use of a wiki website for language learning in a context of English for Academic Purposes (EAP). Data on their opinions on the resource was collected through questionnaires and feedback on the wiki. T-test was employed in data analysis and the results revealed that in spite of the challenges encountered in using the website, the students’ attitude towards using it was positive as they were enthused about using the novel approach for research and learning purposes. The results also indicated that there was no significant difference between the opinions of male and female respondents. Challenges associated with the use of the resource are highlighted and recommendations presented.
Taxonomic and thematic semantic relationships in picture naming as revealed by Laplacian‐transformed event‐related potentials

Abstract Semantically related concepts co‐activate when we speak. Prior research reported both behavioral interference and facilitation due to co‐activation during picture naming. Different word relationships may account for some of this discrepancy. Taxonomically related words (e.g., WOLF‐DOG) have been associated with semantic interference; thematically related words (e.g., BONE‐DOG) have been associated with facilitation. Although these different semantic relationships have been associated with opposite behavioral outcomes, electrophysiological studies have found inconsistent effects on event‐related potentials. We conducted a picture‐word interference electroencephalography experiment to examine word retrieval dynamics in these different semantic relationships. Importantly, we used traditional monopolar analysis as well as Laplacian transformation allowing us to examine spatially deblurred event‐related components. Both analyses revealed greater negativity (150–250 ms) for unrelated than related taxonomic pairs, though more restricted in space for thematic pairs. Critically, Laplacian analyses revealed a larger negative‐going component in the 300 to 500 ms time window in taxonomically related versus unrelated pairs which were restricted to a left frontal recording site. In parallel, an opposite effect was found in the same time window but localized to a left parietal site. Finding these opposite effects in the same time window was feasible thanks to the use of the Laplacian transformation and suggests that frontal control processes are concurrently engaged with cascading effects of the spread of activation through semantically related representations.
Imagens multiespectrais para discriminar fontes de adubo no cafeeiro

Multispectral images to discriminate sources of in Coffee fertilization is key for the entire plant development and must be managed according to the phenological stage of the crop. The source and dose of the fertilizer to be used is an important choice, as it affects not only productivity but also the chemical and biological properties of the soil. Remote monitoring of the management of coffee crops is necessary as the demand in decision-making, where the aim is to rise production based on sustainable management is in a constant growth. In this work, we evaluated the potential of images obtained by low-cost sensors in the discrimination of sources of mineral and organomineral fertilizers in coffee. The experimental design was in randomized blocks, with five blocks and six treatments, as follows: (TI) - 100% of the organomineral treatment; (T2) - 70% of the organomineral treatment; (T3) - 50% of the organomineral treatment; (T4) - 100% of mineral fertilization; (T5) - 70% of mineral fertilization (T6) - standard treatment of the farm. After management, we used the Mapir 3 Survey3W camera coupled to an ARP drone – Phantom4 to take images of the experiment over a 12-month vegetative period. Combined with image taking, we collected agronomic parameters of coffee growth and productivity for two crops and concluded that different fertilization doses did not significantly affect the analyzed characteristics. Based on the supervised classification of multispectral images, it was possible to discriminate treatments with a higher degree of accuracy (86.66% accuracy) than when analyzing coffee growth parameters.
Detection and Classification of Transformer Winding Mechanical Faults Using UWB Sensors and Bayesian Classifier

Abstract In this paper, the Bayesian classifier is used to detect and classify the radial deformation and axial displacement of transformer windings. The proposed method is tested on a model of transformer for different volumes of radial deformation and axial displacement. In this method, ultra-wideband (UWB) signal is sent to the simplified model of the transformer winding. The received signal from the winding model is recorded and used for training and testing of Bayesian classifier in different axial displacement and radial deformation states of the winding. It is shown that the proposed method has a good accuracy to detect and classify the axial displacement and radial deformation of the winding.
Binary polymer systems for biomedical applications

Binary polymer systems provide significant advantages in the preparation of materials used in biomedical applications. To highlight the importance and need of binary polymer systems in biomedical applications; utilisations of nano-carrier and fibre are discussed in detail in terms of their use as biomaterial, and their potential for further development with focus on dual and sequential drug delivery applications. On the other hand, in fibre technology, creation of binary polymer systems have been investigated using spinning processes such as electrospinning and even more recently innovated pressurised gyration. How these methods can be used to promote the mass production of binary polymer systems with various morphologies and characteristics are elucidated. The effects of different polymer materials, including solvents, mechanical properties, and the rate of degradation of polymers, are discussed. Current polymer blending systems and manufacturing processes are analysed, and technologies for biomaterials are carefully considered with up to date details.
UI Management System on Multi-User Interactive Tabletop

Interactive tabletop is now receiving wide publicity for its natural setting for collaboration. However, few works have carefully studied the user interface management on tabletop, and many problems are still to be resolved. In this paper, we carry out a systematic research on tabletop UI management, and develop a system to facilitate user interaction on tabletop. Firstly, based on the analysis of tabletop's horizontal display, multi-user usage and natural input features, we identify four fundamental requirements for tabletop UI management: input management, layout management, conflict management and authority management, which are significantly different from UI management on desktops. Secondly, we design a model for tabletop UI management. It contains a hierarchical structure for organizing surface elements, Object Manager for multi-user interface controlling, and Input Manager for processing concurrent multimodal inputs. Thirdly, we implement a system, uTablePlatform based on our model, and an SDK for users developing applications on uTablePlatform. At last, we carry out a user study, where four groups carry out a travel planning task using uTablePlatform. Results suggest that the UI management technique we present can help people complete individual or collaborative tasks effectively on tabletop.
Stability and bifurcation analysis of robots subject to digital position control

Summary. Precision and stability in position control of robots are critical parameters in many industrial applications where high accuracy is needed. It is well known that digital effect is destabilizing and can cause instabilities. In this paper, the stability limits are presented in the parameter space of the control gains, furthermore the bifurcations occurring at the stability border are analytically defined and numerically verified. These analytical results explain some of the typical instabilities occurring in industrial applications.
Semi-supervised multi-scale dense based encoder-decoder architecture for lung computed tomography image segmentation

Covid-19 pandemic continues to threaten health of the global population, an efficient way to restrain the Covid-19 outbreak is timely screening suspected cases for quarantine and treatment. Despite of pathogenic laboratory testing is the gold standard to screen suspected cases, but it may obtain false negative results and consuming a lot of time. Computed tomography of chest can be an alternative diagnostic method to screen suspected cases that is based on radio graphical changes in lung area of Covid-19 confirmed case. Precisely delineate the lung area that is first and critical step for screening computed tomography image of chest by using deep learning method. In this paper, several related previous works will be introduced at first. Then, an improved encoder-decoder based segmentation framework is proposed, which is integrated with multi-scale densely connection-based convolution block and skip connection path. Moreover, in model training process, a semi-supervised manner is applied to train model which can reduce the demand of labeled training data. Finally, the proposed method is tested with a dataset of public X-ray image of chest. The experiment test proposed model in this paper with varieties of segmentation methods and result demonstrates promising performance of proposed model that against several other deep learning models.
Effect of Concurrent Engineering on Benefits of Product Development in Two Wheeler Automobiles

In today's highly competitive business environment, introducing a new product with expectation of high level of customer satisfaction is an intricate and immense challenge to the companies. Concurrent Engineering has a great deal of importance in design and development of new products in Indian automobile industry and is posing a big challenge to Indian firms in the wake of global ization. Success of concurrent engineering demands that major areas of product design and development of an organization are kept in focus concomitantly. The aim of the paper is to assess and establish the benefits of concurrent engineering in the new product desi gn and development. The survey presents its evaluation based on the data analysis using cumulative weighed average with the help of primary data which was collected through a pre-tested questionnaire. The findings reveal that the two wheeler manufacturing companies in India are realizing maximum benefits with the implementation of the concurrent engineering in new product design and development. The research further recommends that companies must focus on weak areas of design and development in order to enhance the productivity.
Molecular Pathology of Skin Melanoma: Epidemiology, Differential Diagnostics, Prognosis and Therapy Prediction

Similar to other malignancies, TCGA network efforts identified the detailed genomic picture of skin melanoma, laying down the basis of molecular classification. On the other hand, genome-wide association studies discovered the genetic background of the hereditary melanomas and the susceptibility genes. These genetic studies helped to fine-tune the differential diagnostics of malignant melanocytic lesions, using either FISH tests or the myPath gene expression signature. Although the original genomic studies on skin melanoma were mostly based on primary tumors, data started to accumulate on the genetic diversity of the progressing disease. The prognostication of skin melanoma is still based on staging but can be completed with gene expression analysis (DecisionDx). Meanwhile, this genetic knowledge base of skin melanoma did not turn to the expected wide array of target therapies, except the BRAF inhibitors. The major breakthrough of melanoma therapy was the introduction of immune checkpoint inhibitors, which showed outstanding efficacy in skin melanoma, probably due to their high immunogenicity. Unfortunately, beyond BRAF, KIT mutations and tumor mutation burden, no clinically validated predictive markers exist in melanoma, although several promising biomarkers have been described, such as the expression of immune-related genes or mutations in the IFN-signaling pathway. After the initial success of either target or immunotherapies, sooner or later, relapses occur in the majority of patients, due to various induced genetic alterations, the diagnosis of which could be developed to novel predictive genetic markers.
KESERIUSAN KECURANGAN AKUNTANSI DAN NIAT MENJADI WHISTLEBLOWER INTERNAL ANALISIS MODERASI EDUKASI

Kecurangan merupakan bencana besar bagi organisasi. Partisipasi karyawan untuk bersedia untuk mengungkapkan kecurangan merupakan harapan bagi setiap organisasi. Penelitian ini bertujuan untuk menguji pengaruh keseriusan kecurangan akuntansi terhadap niat menjadi whistleblower internal serta pengaruh moderasi edukasi terhadap niat menjadi whistleblower internal. Objek penelitian ini adalah ASN bagian keuangan Pemerintah Kota Banjarmasin. Teknik penyampelan yang digunakan adalah teknik jenuh yakni menggunakan keseluruhan populasi sebagai sampel penelitian. Terdapat 100 responden yang diperoleh sebagai sampel. Data kuesioner dianalisis menggunakan alat analisis Partial Least Squares (PLS). Hasil penelitian menunjukkan bahwa keseriusan kecurangan akuntansi berpengaruh terhadap niat ASN menjadi whistleblower internal. Namun, edukasi tidak mampu memoderasi pengaruh keseriusan kecurangan akuntansi terhadap niat ASN menjadi whistleblower internal. Hasil ini memberikan kontribusi untuk memberikan wawasan baru terkait dengan kebijakan yang mampu mendorong ASN menjadi whistleblower internal. Kata kunci: keseriusan pelanggaran akuntansi; edukasi; niat melaporkan kecurangan
Radiation hardness of InWZnO thin film as resistive switching layer

In this study, the effect of radiation on an amorphous semiconductor InWZnO (IWZO) thin film has been investigated. From the x-ray photoelectron spectroscopy in-depth analysis, most of the oxygen vacancies in pristine IWZO films are located at the bottom of the film. As the radiation dose increases, the proportion of oxygen vacancies at the bottom of the film increases. However, the top of the IWZO film is hardly affected by the radiation dose. In addition, the resistive switching behavior of an IWZO memristor under irradiation has also been investigated. A forming process and a bipolar I–V curve of the IWZO memristor vary with the radiation dose. The high resistance state of the memristor is significantly degraded at a radiation dose of 1000 krad, which is due to the more defects in the IWZO film. The retention time of the IWZO memristor is up to 104 s at 85 °C with 100 krad. The damaged site in the IWZO film is observed and fabricated into memristors under radiation. The IWZO film as the resistive switching layer exhibits great potential in harsh environments such as polar regions, space technology, nuclear military, and medical imaging.
Enhancing enterprise competitiveness and sustainability using eWOM: The case of Egypt

The digital marketing transformation of the Internet has significantly experienced a paradigm shift, i.e., a transformation from a passive source of information to an interactive and engaging participatory web. This study demonstrates the ability of electronic word-of-mouth (eWOM) as a participatory web tool that enables enterprises to achieve profitable growth, resilience, business sustainability, and competitiveness, through developing operational strategy. This study adopts a conclusive descriptive cross-sectional survey research design, which allows the collection of quantitative data through structured questionnaires. The data were obtained from Egyptian social media users through a convenience sampling method. To test the hypotheses regression analysis was conducted. Results indicate that eWOM positively influences the brand image and purchase intention, which consequently enables the enterprises to achieve business sustainability. Accordingly, enterprises wanting to achieve strategic competitiveness must integrate social media into their marketing mix which would generate positive eWOM. Using convenience sampling might result in the inability to generalize the findings. This study is designed to study the effect of eWOM using social media platforms in general, however, future studies should replicate this study to specified types of different social media platforms, to identify which platform generates the highest impact. The proposed conceptual model tests a relationship that connects eWOM dimensions, namely, credibility, quality, and quantity, to purchase intention and brand image. There is lack of research in the Egyptian context on the implications of eWOM on enterprise competitiveness and sustainability
Neuroprotective Effects of Cranberry Juice Treatment in a Rat Model of Parkinson’s Disease

Rich in polyphenols, cranberry juice (CJ) with high antioxidant activity is believed to contribute to various health benefits. However, our knowledge of the neuroprotective potential of cranberries is limited. Previously, we have demonstrated that CJ treatment controls oxidative stress in several organs, with the most evident effect in the brain. In this study, we examined the capability of CJ for protection against Parkinson’s disease (PD) in a rotenone (ROT) rat model. Wistar rats were administered with CJ in a dose of 500 mg/kg b.w. /day (i.g.) and subcutaneously injected with ROT (1.3 mg/kg b.w./day). The experiment lasted 45 days, including 10 days pre-treatment with CJ and 35 days combined treatment with CJ and ROT. We quantified the expression of α-synuclein and apoptosis markers in the midbrain, performed microscopic examination, and assessed postural instability to evaluate the CJ neuroprotective effect. Our results indicate that the juice treatment provided neuroprotection, as evidenced by declined α-synuclein accumulation, Bax and cleaved/active caspase-9 expression, and normalized cytochrome c level that was accompanied by the enhancement of neuronal activity survival and improved postural instability. Importantly, we also found that long-term administration of CJ alone in a relatively high dose may exert a deleterious effect on cell survival in the midbrain.
Dynamics and control in power grids and complex oscillator networks

Dynamics and Control in Power Grids and Complex Oscillator Networks Florian Anton Dorfler The efficient production, transmission and distribution of electrical power underpins our technological civilization. Public policy and environmental concerns are leading to an increasing adoption of renewable energy sources and the deregulation of energy markets. These trends, together with an ever-growing power demand, are causing power networks to operate increasingly closer to their stability margins. Recent scientific advances in complex networks and cyber-physical systems along with the technological re-instrumentation of the grid provide promising opportunities to handle the challenges facing our future energy supply. In this thesis, we discuss the synchronization problem in power networks, which is central to their operation and functionality. We identify and exploit a close connection between the mathematical models for power networks and complex oscillator networks. Our main contributions are concise, sharp, and purely-algebraic conditions that relate synchronization in a power grid to graph-theoretical properties of the underlying electric network. Our novel conditions hold for arbitrary interconnection topologies and network parameters, and they significantly improve upon
Research on trajectory tracking of unmanned vehicle based on intelligent humanoid control

Trajectory tracking technology is one of the key technologies of unmanned vehicles, and accurate trajectory tracking control is also the primary premise for unmanned vehicles to complete various military tasks. At present, the trajectory tracking research of unmanned vehicle mostly relies on the research results of mobile robot. The traditional trajectory tracking control methods mainly include PID control, neural network control, optimal control, sliding mode control and predictive control. They have their own advantages and limitations. By studying the control behavior of vehicle drivers, using intelligent control method, this paper establishes a nonlinear time-varying dynamic model suitable for unmanned vehicles, breaks through the key technologies such as accurate trajectory tracking control of unmanned vehicles, and provides technical support for the development of new unmanned vehicles in practical environment and the unmanned transformation of active vehicles.
Incorporating Quantum Effects in Ultralow Power (ULP) Subthreshold Logic Design With Junctionless Nanowire Transistor

This article proposes a ultralow-power (ULP) subthreshold model for short-channel nanowire underlap junctionless transistor (JLT-U) incorporating quantum confinement effect. Considering JLT-U as a confined quantum harmonic oscillator, consistent values of subband energies are obtained for wide ranges of nanowire diameter and channel doping. The subband energy, electron line density, drain current, and threshold voltage of JLT-U are determined and validated with TCAD simulations. DC figures of merit (voltage swing, switching threshold, voltage gain, and noise margin) of ULP subthreshold inverter are investigated using a simplified circuit model. The approach presented in this article is of utmost benefit for device/circuit designers aiming for ULP subthreshold logic technology.
Vibration-based experimental damage detection of a small-scale wind turbine blade

Structural health monitoring offers an attractive tool for condition assessment, fault prognosis and life-cycle management of wind turbine components. However, owing to the intense loading conditions, geometrical nonlinearities, complex material properties and the lack of real-time information on induced structural response, damage detection and characterization of structural components comprise a challenging task. This study is focused on the problem of damage detection for a small-scale wind turbine (Sonkyo Energy Windspot 3.5 kW) experimental blade. To this end, the blade is dynamically tested in both its nominal (healthy) condition and for artificially induced damage of varying types and intensities. The response is monitored via a set of accelerometers; the acquired signals serve for damage detection via the use of appropriate statistical and modal damage detection methods. The former rely on extraction of a characteristic statistical quantity and establishment of an associated statistical hypothesis test, while the latter rely on tracking of damage-sensitive variations of modal properties. The results indicate that statistical-based methods outperform modal-based ones, succeeding in the detection of induced damage, even at low levels.