Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Domestic Savings and Investments on Nigeria’s Economy: 1981-2020

This study assessed effect of gross domestic savings and investments on Nigeria’s economy. The poor economic well-being in Nigeria seems to be caused by poor savings and consequent poor investment. There seems to be weak links among domestic savings, domestic investment and economic growth in Nigeria possibly due to low income, policy inconsistencies, low productivity among others. The general objective of the study was to examine the effect of gross domestic savings and investments on the Nigerian economy for the period 1981-2020. The data used were extracted from the data base of World Development Indicators. Harrod-Domar growth Model and neoclassical growth theory of savings and investments explained the conceptual framework of this study. The unit root test, co-integration test and regression analysis were used for data analysis. Using regression techniques the results showed that there is positive and significant relationship between gross domestic savings and gross domestic product per capita; there is negative but significant relationship between gross domestic investment and gross domestic product growth rate per capita; there is positive and significant relationship between gross domestic savings and adjusted net national income per capita; and there is negative but significant relationship between gross domestic investments and adjusted net national income per capita in Nigeria. Thus, gross domestic savings and investments contributed to economic growth and development in Nigeria. The work recommended that the Nigerian monetary authority should sustain the monetary policy rate between 11% and 12% and encourage savings deposit rate to be between 1.5% and 2.5%; and investment environment should be conducive through policy consistency from the Government; and that capital flight need to be curbed by improving ease of doing business in Nigeria by streamlining business registration process, and ensuring enforcement of national digital policy.
Fluid-Phase Endocytosis and Lysosomal Degradation of Bovine Lactoferrin in Lung Cells

The iron-binding protein lactoferrin and the cell-penetrating peptides derived from its sequence utilise endocytosis to enter different cell types. The full-length protein has been extensively investigated as a potential therapeutic against a range of pathogenic bacteria, fungi, and viruses, including SARS-CoV-2. As a respiratory antiviral agent, several activity mechanisms have been demonstrated for lactoferrin, at the extracellular and plasma membrane levels, but as a protein that enters cells it may also have intracellular antiviral activity. Characterisation of lactoferrin’s binding, endocytic traffic to lysosomes, or recycling endosomes for exocytosis is lacking, especially in lung cell models. Here, we use confocal microscopy, flow cytometry, and degradation assays to evaluate binding, internalisation, endocytic trafficking, and the intracellular fate of bovine lactoferrin in human lung A549 cells. In comparative studies with endocytic probes transferrin and dextran, we show that lactoferrin binds to negative charges on the cell surface and actively enters cells via fluid-phase endocytosis, in a receptor-independent manner. Once inside the cell, we show that it is trafficked to lysosomes where it undergoes degradation within two hours. These findings provide opportunities for investigating both lactoferrin and derived cell-penetrating peptides activities of targeting intracellular pathogens.
Reconstructing Saliency Effect in 12/10 DC Vernier Reluctance Machine for Position-Sensorless Drive Aerospace Starter Generator Application

DC-Excited vernier reluctance machine (DC-VRM) using a 12-slot/10-pole-pair design, exhibits the advantages of small torque ripple and low cogging torque due to the inherent commentary characteristic. However, the inherent saliency is canceled out by a 12/10 pole combination of machine design driven by a traditional three-phase inverter. As a result, the sensorless operation in zero/low-speed regions becomes difficult because the position estimation methods using self-inductance detection cannot be applied. To tackle this problem, we first analyzed the saliency annihilation phenomenon through Fourier analysis that the odd-order harmonics in self-inductance are canceled. Moreover, reconstructing saliency method is proposed by splitting a phase winding into two sub-phase coils and using parallel H-bridge converters to supply sub-phase coils and achieve sensorless drive. Through this method, the saliency effect is recovered in self-inductance, thereby pulse injection sensorless drive can be applied. The constructed 12/10 DC-VRM sensorless drive shows good fault-tolerant ability and can be applied in safety-critical industry applications such as aerospace propulsion. Analysis and experiments are performed in the initial position detection, start-up and free-running stages to verify the feasibility of the proposed solution. A sector estimation accurate to 6° can be achieved.
The Lubrication Effect of Micro-Pits on Parallel Sliding Faces of SiC in Water

Silicon carbide is regarded as a promising material for sliding bearings and mechanical seals working in water. In order to improve its load carrying capacity (or anti-seizure ability) in water, micro-pits were formed on one of the contact surfaces by ion reaction etching. The effect of micro-pits on the critical load for the transition from EHL to mixed lubrication was studied experimentally in the cases of bearing type contact (with relatively rich water supply) and seal type contact (with relatively poor water supply). In order to understand the mechanisms of the lubrication effect of micro-pits, the experimental results obtained from bearing type contact and seal type contact were compared, and a theoretical analysis was carried out. Presented at the 57th Annual Meeting Houston, Texas May 19–23, 2002
A Flow-based Generative Network for Photo-Realistic Virtual Try-On

Image-based virtual try-on systems aim at transferring the try-on clothes onto a target person. Despite making considerable progress recently, such systems are still highly challenging for real-world applications because of occlusion and drastic spatial deformation. To address the issues, we propose a novel Flow-based Virtual Try-on Network (FVTN). It consists of three modules. Firstly, the Parsing Alignment Module (PAM) aligns the source clothing to the target person at the semantic level by predicting a semantic parsing map. Secondly, the Flow Estimation Module (FEM) learns a robust clothing deformation model by estimating multi-scale dense flow fields in an unsupervised fashion. Thirdly, the Fusion and Rendering Module (FRM) synthesizes the final try-on image by effectively integrating the warped clothing features and human body features. Extensive experiments on a public fashion dataset demonstrate that our FVTN qualitatively and quantitatively outperforms the state-of-the-art approaches. The source code and trained models are available at https://github.com/gxl-groups/GFGN.
Stripes Matter: Integrative Systematics of Coryphellina rubrolineata Species Complex (Gastropoda: Nudibranchia) from Vietnam

Coryphellina rubrolineata (Gastropoda: Nudibranchia: Flabellinidae) was believed to be a widespread tropical species demonstrating high diversity in external and internal morphological traits. In this paper, we perform an integrative analysis of the C. rubrolineata species complex based on samples collected in Vietnam waters, combined with available data from other localities of the Indo-West Pacific. The methods of the study include morphological analysis of external and internal traits using light and scanning electron microscopy and the molecular analysis of four markers (COI, 16S, H3, and 28S). The phylogenetic hypothesis was performed using Bayesian and maximum likelihood approaches, and the species delimitation analyses included ASAP, GMYC, and bPTP. Our results support the validity of the genus Coryphellina as a distinct taxon and confirm that Coryphellina rubrolineata is restricted to the type locality and adjacent waters, while in the Indo-West Pacific, it represents a complex of pseudocryptic species. Based on our integrative analysis, we describe four new species: Coryphellina pseudolotos sp. nov., Coryphellina pannae sp. nov., Coryphellina flamma sp. nov., and Coryphellina aurora sp. nov. For the first time, Coryphellina lotos is reported in Vietnam waters. All five species differ in combination of coloration and other external traits and show minor differences in internal morphology.
Robust orthogonal iterative monocular pose estimation algorithm based on point features

Monocular pose estimation is a basic element in computer vision, and monocular pose estimation based on point features, as one of the important branches of monocular pose estimation, is widely used in many fields such as robot positioning, virtual reality, and image precision measurement. When solving the monocular pose based on point features, the number of point features and image noise has a great influence on the estimation accuracy. Therefore, this paper proposes a robust orthogonal iterative pose measurement algorithm that introduces an intermediate coordinate system between the camera coordinate system and the world coordinate system to optimize estimation constraints. Then, the method that uses the least square method to solve the error problem is applied to solving the distance between the characteristic point and the camera's optical center. Moreover, the calculation of the initial value of the camera pose is simplified through the intermediate coordinate system. Finally, the camera pose is optimized by orthogonal iteration. Experiments show that, compared with existing algorithms, the algorithm proposed in this paper is more robust to the number of point features and image noise, and the overall solution accuracy is better.
A four port DC-DC converter for renewable energy systems

Multiport converters can be used for relatively high-power applications. Three port Full-bridge-based topologies utilize a lot of switches with complicated driving and control circuitry. Due to this reason overall cost and size are high. This paper presents the control strategy and power management for an integrated Fourport converter, which interfaces one wind energy port ,one solar input port, one battery port and an isolated output port. A competitive method is used to realize smooth and seamless mode transition. Multiport converter has plenty of interacting control loops due to integrated power trains. The integrated system will have a lower overall mass and more compact packaging. And also has lower cost, improved reliability and enhanced dynamic performance due to power stage integration and centralized control. The circuit is simulated using MATLAB. The simulation results are presented in this paper. Key Terms: Multiport Converter, DC-DC converter, Renewable Energy Sources, Four Port Converter.
Development of a measure for technological capability in the information and communications technology industry in Nigeria

1.1 Introduction Information and Communications Technology (ICT) has proved to be a catalyst to fundamental changes in the world's economies and societies. It creates more avenues to earn income, allows access to useful information, enhances the world of work and makes the world a global village (Aderemi, 2006). The ICT industry spans broadcast, electronics and print media, computers, telecommunications and e-commerce activities. As put forward by Oyelaran-Oyeyinka, Adelaja & Abiola (2007), ICT infrastructure is made up of all physical facilities and technologies engaged in delivering and disseminating information and communication services in telecommunications, broadcasting, cable television service, postal service, publishing, printing, computer networks, and a wide range of terminal equipment. The minimum composition of an ICT infrastructure that would bring about social and industrial development include: a functional telecommunications network with voice, data and video transmission to enable an information base that is adequately networked; local production of ICT equipment and materials; a pool of human resources with capacity in 2 telecommunications and other related aspects of the rapidly growing ICT industry; and software development and production of information technology (IT) applications (Oyelaran-oyeyinka, Adelaja & Abiola, 2007). In Nigeria today, telecommunication activities continues to play a lead role as a central component of the ICT sector. The industry is competitive with a mix of service providers in the private and public sectors in their respective domains. This is consequent upon the deregulation in the industry. The recognition of the pivotal role of Information Technology (IT) for development became eminent in Nigeria with the formulation and approval of the IT policy was a consultative process that brought together major IT stakeholders such as Computer Association of Nigeria (COAN) now known as Computer Society of Nigeria, National Information Technology Professional Associations (NITPAs) now known as Computer Professionals of Nigeria (CPN), Association of Licensed Telecommunication Companies in Nigeria (ALTCON) as well as the Nigerians in the Diaspora. The IT policy has very clear-cut policy goals on the development of the national information backbone. This was to engender seamless interconnectivity in ICT infrastructure development in Nigeria. The policy document stipulated that the government, through the National Information Technology Development Agency (NITDA), shall establish and develop a National Information Infrastructure (NII) backbone as the gateway to the Global Information Infrastructure (GII) interconnecting it with State Information Infrastructure (SII) and the Local Information Infrastructure (LII). The policy also has the objective to promote technological capability in …
Exploring the influence of work values on millennial hospitality employees’ turnover intentions: an empirical assessment

ABSTRACT The millennial generation has gradually become a major employee segment of the hotel industry. Using organizational identification and job satisfaction as mediators, this paper develops a dual path model regarding the influence of work values on millennial employees’ turnover intentions. Panel data were obtained in two waves from two high-class hotel millennial employees with a time lag of ten weeks. The results showed that the intrinsic preference and long-term development dimensions of their work values lower millennial employees’ turnover intentions by the partial mediation of their organizational identification and job satisfaction. At the same time, the utilitarian orientation, interpersonal harmony and innovative orientation only decrease their turnover intentions through organizational identification or job satisfaction. This paper makes theoretical contributions by finding that millennial employees have some distinctive behavioural characteristics by clarifying the relationship between the millennial employees’ work values and turnover intentions.
Research on Inter-Turn Short Circuit Fault Diagnosis of Electromechanical Actuator Based on Transfer Learning and VGG16

In this paper, an inter-turn short-circuit fault of a permanent magnet synchronous motor in an electromechanical actuator is analyzed, and a fault diagnosis method based on transfer learning with a VGG16 convolution network is proposed. First, a 2D finite element model of an inter-turn short circuit fault of a permanent magnet synchronous motor was established in ANSOFT Maxwell, and then a simulation experiment analysis was completed. A three-phase current was chosen as a fault characteristic signal. Second, a fault diagnosis method with a VGG16 deep convolutional neural network and based on transfer learning was designed, and the fine tuning of the hyperparameters of the fault diagnosis model was completed by using grid search and cross verification methods. Finally, based on the transfer learning VGG16 model established in this paper, the inter-turn short circuit fault of a permanent magnetic synchronous machine (PMSM) was diagnosed and verified. The experimental results showed that the proposed convolutional network model based on transfer learning can identify faults effectively and accurately, and has a good engineering guidance significance.
Perspectives for the implementation of blockchain technology in the supply chain: research, trends and future

The rise of new technologies is pushing companies to a new digital era. Among all technologies, one that has been gaining prominence is blockchain, which has potential for improving processes and enhance business models in supply chain. The implementation of blockchain technology in the supply chain is promising as it can bring benefits to everyone involved in the chain, among them, highlight for reliability, security, transparency, traceability and authenticity of information. Nonetheless, its application is still in the initial phase and this paper aims to shed light on the current research, trends and future related in the literature. Through an RSL (Systematic Literature Review) is identified how recent and innovative are studies published about the subject, as well as how researchers and universities are working on that around the world. The conclusion is that the issue has been attracting attention from academics, with researches dispersed in several countries and universities around the world, with growth potential. It was also identified a few papers with a high impact factor or citied many times, while these usually brings features as security, transparency and sustainability. Despite the advantages and potential, there is still a lack of empirical studies, characterizing a good gap for potential future research.
The Added Value of Atrial Strain Assessment in Clinical Practice

Speckle tracking echocardiography has emerged as a sensitive tool to analyze myocardial function with improved diagnostic accuracy and prognostic value. Left atrial strain assessment has become a novel imaging method in cardiology with superior prognostic value compared to conventional left atrial volume indices. Left atrial function is divided into three phases, reservoir function being the most important. This review summarizes the added value of speckle tracking echocardiography derived left atrial strain assessment in clinical practice. Recently published data suggest the prognostic value of left atrial reservoir function in heart failure, atrial fibrillation, stroke and valvular heart disease. Furthermore, left atrial reservoir strain proved to be a predictor of cardiovascular morbidity and mortality in the general population. Thus, routine assessment of left atrial function can be an optimal strategy to improve cardiovascular risk prediction and supplement the current risk prediction models.
Adaptive Instrument Module - A Reconfigurable Processor for Spacecraft Applications

A reconfigurable computer optimized for spacecraft instrument use called the Adaptive Instrument Module (AIM) is under development and scheduled for launch in November 2000 on the Australian Fedsat spacecraft. The advent of RAM-based FPGAs whose configuration can be changed at any time has enabled the development of a low cost reconfigurable computer for space use. Reconfigurable computers provide solutions to problems that are uniquely found in spacecraft applications, but difficulties in using RAM-based FPGAs in the space environment must be overcome. The development of the AIM will allow future satellite programs to avoid the large costs associated with new builds by reconfiguring standardized processing hardware.
Accelerated Generation of Extra-Islet Insulin-Producing Cells in Diabetic Rats, Treated with Sodium Phthalhydrazide

β-cells dysfunction plays an important role in the pathogenesis of type 2 diabetes (T2D), partially may be compensated by the generation of extra-islet insulin-producing cells (IPCs) in pancreatic acini and ducts. Pdx1 expression and inflammatory level are suggested to be involved in the generation of extra-islet IPCs, but the exact reasons and mechanisms of it are unclear. Macrophages are key inflammatory mediators in T2D. We studied changes in mass and characteristics of extra-islet IPCs in rats with a streptozotocin-nicotinamide model of T2D and after i.m. administration of 20 daily doses of 2 mg/kg b.w. sodium aminophthalhydrazide (APH). Previously, we found that APH modulates macrophage production and increases the proliferative activity of pancreatic β-cells. Expressions of insulin and Pdx1, as well as F4/80 (macrophage marker), were detected at the protein level by immunohistochemistry analysis, the concentration of pro- and anti-inflammatory cytokines in blood and pancreas—by ELISA. Diabetic rats treated with APH showed an increasing mass of extra-islet IPCs and the content of insulin in them. The presence of Pdx1+ cells in the exocrine pancreas also increased. F4/80+ cell reduction was accompanied by increasing TGF-β1 content. Interestingly, during the development of diabetes, the mass of β-cells decreased faster than the mass of extra-islet IPCs, and extra-islet IPCs reacted to experimental T2D differently depending on their acinar or ductal location.
Decreased cognition is associated with altered cardiovascular autonomic functions and decreased baroreflex sensitivity in women with premenstrual syndrome

Premenstrual syndrome (PMS) is a clinical entity of concern in women of reproductive age group with its onset during the late luteal phase of the menstrual cycle that typically resolves within a few days after the onset of menstruation. Female reproductive hormones stimulate the gene promotor region of Gonadal steroids, which are modulators of the hypothalamic-pituitary axis, in association with the autonomic nervous system (ANS), form the stress system, which regulates the homeostatic mechanisms of the body. Disruption of this mechanism can lead to sympathovagal imbalance and cognitive deficits. Objectives: This study was aimed to compare the autonomic functions and cognition between PMS and control group. Methodology: This cross-sectional study was conducted as a pilot study with 20 subjects in each group. Autonomic function test and P300 were recorded. Study participants were also asked to answer Montreal cognitive assessment (MOCA) questionnaire. Results: On comparison of the test results between the two groups, individuals in PMS group were found to have increased sympathetic activity and reduced cognition when compared to the no PMS (control) group. Conclusion: The findings from this study proves a detrimental effect of gonadal steroids on autonomic nervous system and cognition.
A New Model for Brain Tumor Detection Using Ensemble Transfer Learning and Quantum Variational Classifier

A brain tumor is an abnormal enlargement of cells if not properly diagnosed. Early detection of a brain tumor is critical for clinical practice and survival rates. Brain tumors arise in a variety of shapes, sizes, and features, with variable treatment options. Manual detection of tumors is difficult, time-consuming, and error-prone. Therefore, a significant requirement for computerized diagnostics systems for accurate brain tumor detection is present. In this research, deep features are extracted from the inceptionv3 model, in which score vector is acquired from softmax and supplied to the quantum variational classifier (QVR) for discrimination between glioma, meningioma, no tumor, and pituitary tumor. The classified tumor images have been passed to the proposed Seg-network where the actual infected region is segmented to analyze the tumor severity level. The outcomes of the reported research have been evaluated on three benchmark datasets such as Kaggle, 2020-BRATS, and local collected images. The model achieved greater than 90% detection scores to prove the proposed model's effectiveness.