Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-foreground objects segmentation based on RGB-D image

Silhouette extraction of foreground objects appears frequently in various real-world applications, such as Advanced Driving Assistant System, Intelligent Monitoring System, and movie production. Plenty of solutions have been developed to extract silhouette in RGB image with only color information. Since those color based silhouette extraction methods still have dif-ﬁculties to separate overlapping foreground objects and eliminate excessive segmentation, this paper proposes a novel object segmentation method using color and depth information in RGB-D images. Firstly, we remove the ground plane using the normal map of depth image. Sec-ondly, to separate foreground objects at different distances completely and correctly, the deep Residual Network (ResNets) and Otsu’s multi-thresholding method are combined to divide the depth image into multiple layers. Each depth layer contains only one foreground object or objects at same distance. Finally the outline of foreground object is extracted directly from its depth layer, and reﬁned with color information. Experimental results demonstrate that our method has a better performance than those using color or depth information only, and extracts more types of objects than neural networks.
Considerations and guidelines

Studies have shown that foster children encounter many problems in everyday life. Three of these major problems are access to information, communication and integration. Studies have also shown that digital services such as mobile application can assist this particular type of user with their needs. However, when designing such a service, it is important that the right user experience design process which is suitable for the user will be implemented. For this reason, the goal of this study is to answer the following questions: “Which UX design guidelines are considered more efficient when designing a digital service, especially eHealth services, aimed for adolescent foster children? ” In general, this study aims to identify which factors inside user experience design will lead to a more efficient experience for adolescent foster children from the age of 15 to 18. In order to accomplish this, the user centered design and design science research methodology were adopted for this study. Other methods such as literature study, interviews, usability test and heuristic evaluation test were also conducted. Furthermore, to evaluate the identified design guidelines, a mobile prototype which included the design guidelines were created. Based on the results from the usability test and heuristic evaluation test, it can be argued that the design features that would benefit adolescent foster children in a digital service are social features, accessing the right information at the right time, rewards and challenges. Other design features such positive color palates, clear navigation features and minimum use of instructional text should also be used. More importantly, when it came to understanding the needs of the focus group and the context specifics surrounding them, it was realized that designers should create trust with the user, including experts in the area, identifying ethical issues and the exact limitations that the focus group faces. It should be noted that at the beginning of this study, the main plan was to test the concept on actual foster children. Unfortunately, due to certain circumstances, this was not possible. Instead, a usability test and heuristic evaluation test for the prototype was conducted with participants that were experts in the areas related to this study.
Systolic Versus Diastolic Determinants

Background. Experimental studies indicate that in addition to diastolic dysfunction, hypertrophied myocardium can display depressed contractile responses, particularly at rapid heart rates, compounding reserve limitations. This study tests whether such abnormalities exist in intact human subjects at physiological paced rates and, if so, whether they are linked to simultaneous rate-dependent deterioration in diastolic function. Methods and Results. Ten subjects with left ventricular hypertrophy (LVH) and 8 normal control subjects were studied. Most LVH patients presented with dyspnea and/or pulmonary edema and had concentric hypertrophy. Since rapid pacing simultaneously alters cardiac filling volumes and pressures, pressurevolume relation analysis was used to better define changes in contractile response. Patients were instrumented with a conductance catheter and micromanometer for pressure-volume data recording and a balloon occluder at the right atrial-inferior vena caval junction to vary filling and thus generate function relations. Data were obtained at baseline and at three atrial pacing rates (100, 120, 150 min'1). In addition, single-beat force-interval data were used to indirectly examine calcium cycling kinetics. LVH subjects demonstrated baseline diastolic abnormalities, including prolonged relaxation, elevated end-diastolic pressure, and reduced chamber compliance. However, systolic function was similar to that in control subjects. With rapid pacing, normal subjects displayed a positive contractile response, whereas this was markedly diminished in LVH subjects. With abrupt termination of pacing and return to slower sinus rhythm, LVH subjects displayed greater initial potentiation followed by a more rapid decline than control subjects, suggesting abnormalities of calcium handling. Despite contractile abnormalities, diastolic function did not further deteriorate with rapid pacing and thus did not appear to be tightly linked to the systolic changes. Conclusions. Pacing stress in intact human LVII can result in systolic impairment superimposed on preexisting but not worsened diastolic dysfunction. Abnormal calcium handling probably contributes prominently to this response. (Circulation. 1993;88[part 11:1893-1906.)
Isolation and characterization of fungi isolated from Nigerian cocoa samples

Ten fungal isolates were cultured from 40 samples of powdered cocoa by plating on Potato Dextrose Agar and incubation at 25 C for 7 days. They were subjected to macroand micro-morphological examination to determine their genus and species. Some of the identified fungal species have been reported to produce industrially important enzymes, which they utilize to degrade a wide variety of substrates, while others have been reported to produce mycotoxins and also incite diseases in humans and animals. For the fungi identified, those that had the potential to produce mycotoxins were then analyzed using thin layer chromatography as well as ultra-pure liquid chromatography. Finally, we performed molecular analyses for our fungal isolates, to confirm or refute their morphological identifications, by amplifying and sequencing a portion of their respective ITS regions. Our findin gs supported most of the morphological identifications , but there were some observed inconsistencies based on mycotoxin and molecular examinations. Our findings underscore the importance of a multifaceted approach to fungal identification. The following six genera or species were distinctly identified from the isolates: Aspergillus flavus, A. niger, A. tamarii, A. violaceofuscus, Neocosmospora ramosa and Syncephalastrum racemosum. The availability of these fungal isolates will serv as a reference point for researchers in southwestern Nigeria, thereby improving the quality and integrit y of cocoa research in this region.
MODELLING OF GENE EXPRESSION DATA USING EVOLVING SPIKING NEURAL NETWORK-A CASE STUDY ON NUTRIGENOMICS PROBLEM

The work presents a methodology to assess the problems behind static gene expression data modelling and analysis with machine learning techniques. As a case study, transcriptomic data collected during a longitudinal study on the effects of diet on the expression of oxidative phosphorylation genes was used. Data were collected from 60 abdominally overweight men and women after an observation period of eight weeks, whilst they were following three different diets. Real-valued static gene expression data were encoded into spike trains using Gaussian receptive fields for multinomial classification using an evolving spiking neural network (eSNN) model. Results demonstrated that the proposed methodology can be used for predictive modelling of static gene expression data and future works are proposed regarding the application of eSNNs for personalised modelling.
Fuzzy Clustering with Particle Swarm Intelligence for Large Dataset Classification

– The most challenging problem in data mining is deriving knowledge from large dataset. Existing methods have better performance in medium – scale dataset but the level of performance degrades in large datasets. Swarm intelligence (SI) is a computational method to solve complex problems inspired from biological phenomena like flock of birds, shoal of fish, herd of sheep and swarm of bees. The ant colony optimization is the multi-agent system solving of problems through cooperation like ants. Particle swarm optimization (PSO) is one of the methods successfully implemented with fuzzy concepts and solved complex problems. The objective of the research is to classify the large dataset using fuzzy clustering with PSO. The experiment results proved that the proposed method is more effective and produces optimum accuracy.
Non-uniform sediment transport estimation in non-equilibrium situations: case studies

Quantitative estimate of sediment transport in alluvial channels is one of the most important task in river engineering. Even today, numerical models of sediment transport processes are confronted with some difficulties, often of conceptual nature. One of these difficulties is the simulation of non-uniform sediment transport in non-equilibrium situations, which requires the characterization of the ability of the alluvial system to immediately overcome the variations of the sediment boundary conditions. In this work a 1-D numerical model, which includes a new expression of the so-called “adaptation coefficient”, has been applied to test its capability to simulate the transient bed profiles. Specifically, the model has been applied to predict bedlevel changes due to sediment overloading and sediment cut-off. The model’s application to literature study cases (used by other researchers to assess coupled models) has shown that it gives reasonable results and, thus, it appears suitable for practical applications © 2013 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the CCWI2013 Committee.
The impact of test positivity on surveillance with asymptomatic carriers

Abstract Objectives Recent studies show that Test Positivity Rate (TPR) gains a better correlation than incidence with the number of hospitalized patients in COVID-19 pandemic. Nevertheless, epidemiologists remain sceptical concerning the widespread use of this metric for surveillance, and indicators based on known cases like incidence rate are still preferred despite the large number of asymptomatic carriers, which remain unknown. Our aim is to compare TPR and incidence rate, to determine which of the two has the best characteristics to predict the trend of hospitalized patients in the COVID-19 pandemic. Methods We perform a retrospective study considering 60 outbreak cases, using global and local data from Italy in different waves of the pandemic, in order to detect peaks in TPR time series, and peaks in incidence rate, finding which of the two indicators has the best ability to anticipate peaks in patients admitted in hospitals. Results On average, the best TPR-based approach anticipates the incidence rate of about 4.6 days (95 % CI 2.8, 6.4), more precisely the average distance between TPR peaks and hospitalized peaks is 17.6 days (95 % CI 15.0, 20.4) with respect to 13.0 days (95 % CI 10.4, 15.8) obtained for incidence. Moreover, the average difference between TPR and incidence rate increased to more than 6 days in the Delta outbreak during summer 2021, where presumably the percentage of asymptomatic carriers was larger. Conclusions We conclude that TPR should be used as the primary indicator to enable early intervention, and for predicting hospital admissions in infectious diseases with asymptomatic carriers.
Dual‐end opened slot antenna design for dual‐band WLAN uses on handsets

A novel slot antenna configuration is proposed for applications on mobile terminals. The slot has both ends opened and can be placed on circuit board edges or incorporated with a handset's metal body. The antenna is loaded with one capacitor at the slot's opening and an inductor right next to the feed. Functions of loadings include size reduction, band broadening, and matching improvement. A compact design of 15 mm × 5 mm is devised for dual‐band WLAN uses. Simulated and measured results validate that good matching and radiation efficiency are achieved with moderately directive patterns in both bands. A two‐antenna scheme is also provided for MIMO uses. A mobile device can take advantage of the proposed antenna's compact volume and directive pattern to achieve good isolation and diversity performances.
Image quality assessment employing joint structure-colour histograms as quality-aware features

Image quality assessment is of fundamental importance for various image processing applications. A novel method is presented in which the joint occurrences of statistical local representation by log-Gabor filters and texture analysis by local tetra patterns and histograms of colour are considered as quality-aware features. Then the dissimilarities of these features between the distorted and reference images are quantified and mapped into quality score prediction by utilising a support vector regression. Extensive experiments on LIVE, CSIQ and TID databases show that the proposed method is remarkably consistent with human perception and outperforms many state-of-the-art methods, and also it is robust across different distortion types and different databases.
Th e Clues of Th e Discovery of New Pathogens Eventuated by the Horizontal Gene Transfer Among the Bacillus cereus Group Members

Genes, which constitute the biological basis of heredity, are DNA segments that give various structural and functional properties to the organism they are found in. Genes have become diff erentiated and highly conserved among microorganisms that have completed their evolutionary development and completely distanced from each other. However, horizontal gene transfers (HGT) can occur between microorganisms even though they have high structural similarities in the environment, especially in soil. An example, HGT can occur between the members of the Bacillus cereus group, and thus other species can develop into new life-threatening pathotypes by taking some virulence structures of the most pathogenic species-Bacillus anthracis. Th is study aimed to investigate some virulence genes (protective antigen-PA and capsule-cap) of B. anthracis in B. cereus group members isolated from soil, which is known as the reservoir of this group of bacteria and can easily trigger the genetic material exchange. Th e study material has consisted of 15 soil samples taken from 5 diff erent locations in the Kars region (Turkey) contaminated with cattle carcasses that died with suspected anthrax. B. cereus group bacteria were obtained from the soil by in vitro cultural method, and the agent identification was performed by phenotypic and molecular methods (PCR). As a result, a total of 1350 Bacillus species was identified from the soil, including 123 B. anthracis, 303 B. mycoides, 348 B. thuringiensis and 576 B. cereus. DNAs obtained from all isolates other than B. anthracis were pooled at a final concentration of 4 ng/mL and as an average of 10 extracts and analyzed by PCR for the relevant virulence genes (PA and cap). While the PA gene was found in 6 (4.88%) of 123 DNA pools, the cap gene was not detected in any of the pooled DNA. All B. anthracis isolates were evaluated as fully virulent strains as they did not lose the PA and cap genes. Th e DNA pooling method has been an obstacle to the selection of gene positivity individually, however, it roughly off ered some clues indicating the HGT. Th us, further studies with sampling and methodological diversities are needed that will enable the proof of HGT, which mediates the emergence of new pathotypes among the B. cereus group members.
IJBM-08-2021-0397_proof 886..917

Purpose – This study aims to identify key factors driving consumers’ adoption of Open Banking. It extends the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating perceived risk, initial trust and financial literacy into an overarching conceptual model. Design/methodology/approach – Measurement items of the theoretical constructs included in the conceptual model were adapted from related literature and a set of hypotheses was developed. The hypotheses of the conceptual model were subsequently assessed with partial least squares structural equation modeling using a dataset of 456 Australian survey respondents. Findings – The model has strong explanatory power with an R of 69.5%. Performance expectancy, effort expectancy, social influence and perceived risk are direct antecedents of consumers’ usage intention of Open Banking. Social influence has a strong mediating effect on usage intention through performance expectancy. The effect of perceived risk is alleviated by effort expectancy and initial trust, while initial trust positively affects the effects of performance expectancy and effort expectancy on consumers’ usage intention of Open Banking. Finally, financial literacy lowers initial trust towards Open Banking, possibly inducing consumer skepticism. Practical implications – The results suggest that practitioners should focus on performance expectancy as a primary driver of Open Banking adoption, while understanding the role of other drivers, such as social influence and perceived risk in developing marketing strategies. Policy makers are recommended to adopt a governance approach to build initial trust amongst consumers. Originality/value – This research contributes by providing an integrated and comprehensive model for explaining consumers’FinTech adoptions by extending the existing technology adoptionmodel UTAUT to the Open Banking domain and integrating perceived risk, initial trust and financial literacy, thereby advancing and enriching the conceptual horizon of the extant literature.
Recent Advances in Cardiovascular

Cardiovascular diseases (CVD) are one among the most common causes of death worldwide. There are plethora’s of events leading to cardiovascular pathophysiology. Despite, recent advancements in the treatment of cardiovascular diseases, it remains the number one cause of death in the world. While traditional risk factors partially account for the development of CVD, other novel risk factors have recently been implicated. Specifically chronic inflammation has been postulated to play a role in the development and propagation of this disease. Reactive oxygen species (ROS) generated during excessive oxidative stress are the one among responsible for the various inflammatory events in cardiovascular disorders including atherosclerosis, cardiac hypertrophy, cardiomyopathy heart failure, ventricular remodelling, ischemia/reperfusion injury and myocardial infarction. In the last decade, significant advancements in CVD treatment have been made and achieved some curative effects as well. The existing treatment is medical, surgical or a combination of both depending on the extent if severity and clinical presentation of CVD. The collaboration of different science disciplines likely biotechnology and tissue engineering has led to the development of novel therapeutic strategies: Stem cells therapy, Nanotechnology, Robotic surgery and Drugs. These treatment modalities show promising effects in management of CVD and associated conditions to larger extent.
Effects of Inventory Management Practices on the Performance of Small and Medium Scale Enterprises SMES in Akure

This study investigates the effect of inventory management practices on the organizational performance of Small and Medium Scale Enterprises (SMEs) in Akure Metropolis, Ondo State, Nigeria. The specific objectives of the study are to: identify the inventory management techniques used in the selected SMEs; assess the factors affecting the nature of inventory management practices adopted by the selected enterprise and evaluate the effects of inventory management practices on the profitability of the selected enterprise. The study was designed to combine primary surveybased data with secondary information from SMEs in Akure Metropolis. The population of the study area comprised 966 registered SMEs in Akure Metropolis, Ondo State Nigeria. 400 sample sizes were obtained in this study using a multi-stage sampling technique. Primary and Secondary data were quantitatively obtained respectively using a well-structured questionnaire and also profit data from the selected SMEs in the study area where implemented as well. The data collected were analysed with descriptive and inferential statistical tools respectively. The analysis of the result showed that, the perception of the respondents towards planning and procurement were favourable. The hypothesis testing result of (r = 0.225 and P ≤ 0.05) obtained with Pearson Product moment correlation revealed that there is a positive and significant relationship between the inventory management techniques and the profitability level of the selected SMEs in the study area.
Offloading Elastic Transfers to Opportunistic Vehicular Networks Based on Imperfect Trajectory Prediction

Due to the high cost of cellular networks, vehicle users would like to offload elastic traffic through vehicular networks as much as possible. This demand prompts researchers to consider how to make the vehicular network system achieve better performance for requests coming online, such as maximizing throughput. The traffic in vehicular networks is transferred through opportunistic contacts between vehicles and infrastructures. When making scheduling decisions, the scheduler must be aware of vehicles’ future trajectories. Vehicles’ future trajectories are usually predicted by trajectory prediction algorithms when users are unwilling to report their future trips. Unfortunately, no trajectory prediction algorithm can be completely accurate, and these inaccurate prediction results will degrade the throughput achieved by scheduling algorithms. In this paper, we focus on reducing the negative impact of inaccurate predictions. Specifically, we measure two data-driven trajectory prediction algorithms that have been widely used for trajectory predictions and understand the characteristics of the accuracy of predicted contacts. Based on the enlightenment from the measurement, we design a system, i.e., i-Offload, to offload elastic traffic under imperfect trajectory predictions. The experimental results show that our system has good throughput and high scheduling efficiency even under imperfect trajectory predictions. Compared with existing scheduling algorithms, our method improves the throughput by about one time.