Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamics of generalized Caputo type delay fractional differential equations using a modified Predictor-Corrector scheme

In this paper, we modified the Predictor-Corrector scheme to simulate the delay differential equations in new generalised Caputo-type non-classical derivatives sense. We provided some numerical illustrations to exhibit availability of the algorithm. From the graphical simulations, we observed some periodic and chaotic natures of the given systems for different fractional order values. We believe that the presented scheme is expected to be further used to solve delay fractional differential equations in generalized Caputo type fractional-order sense. The original contribution of this research is to provide a generalised numerical algorithm to solve different fractional-order delay-type systems.
Broadband piezoelectric energy harvesting induced by mixed resonant modes under magnetic plucking

A piezoelectric device connected to the standard interface circuit is proposed for harvesting energy by inducing the mixed resonant modes of vibration under the two-point rotary magnetic plucking. It consists of a piezoelectric cantilever beam attached to a tip magnet and a second magnet placed on the middle of the beam. Both magnets are excited by another two magnets aligned radically and attached to a rotating host. The two impulsive forces from these magnets are made in opposite directions for the ease of inducing the second resonant mode. As a result, the harvester device exhibits the pronounced broadband energy harvesting which can not be achieved by the conventional design based on the one-point magnetic plucking for exciting a single resonant mode. The analysis is based on the Fourier decomposition of magnetic impulsive forces for realizing the phenomenon of frequency up-conversion. In addition, the estimate of harvested power is analytically derived based on using the equivalent load impedance which is originally proposed for analyzing harvester arrays. The result shows that the theoretical prediction agrees well with the experimental observation. Further, the rotary frequency response exhibits the remarkable feature of broadband energy harvesting as the output power is increased up to 2500% higher than that in the off-resonance region of the setup allowing plucking only on the tip magnet.
Intelligent rotating machinery fault diagnosis based on super-resolution enhancement using data augmentation under large speed fluctuation

In the real production of industry, in order to solve the problem that it is usually difficult to obtain correctly labeled samples, data augmentation algorithms have received more and more attention. Many efficient deep learning models have been successfully applied to the intelligent fault diagnosis of rotating machinery. However, the premise of the above method is the working conditions of the machinery are constant. It is inevitable that the equipment runs under large speed fluctuation in real industries. To achieve data augmentation under the condition of variable speed, an efficient sub-pixel deep residual neural network (ESPDRN) is proposed. The ESPDRN framework is implemented as follows: utilize low resolution (LR) samples as input to the network, to effectively learn high-level and extract feature maps by constructing a deep residual network. Through sub-pixel convolution layers to arrange the LR features of multi-channels periodically and get a set of ultra high resolution features, and the data points are augmented 16 times compared to raw data. Statistical indicators and experimental results demonstrate that the proposed ESPDRN model can effectively generate data under the condition of variable speed.
Similarity evaluation of 3D surface topography measurements

With the recent advances in three-dimensional (3D) optical scanning technologies, 3D surface topography measurement plays an increasingly important role in many fields, such as product quality inspection in additive manufacturing (AM), gauge capability analysis, and firearm identification in forensic science. In this paper, we establish a thorough and flexible new framework of surface topography data comparison that generates a scaled similarity score for a pair of measurements, and distinguishes matched and non-matched pairs based on the score. If two measurements are portraying the same surface, they are defined as a matched pair. If not, they are defined as a non-matched pair. This similarity evaluation framework can be very useful in comparing optical scanning systems, quantifying different sources of variation in a process, and monitoring the stability and uniformity of a process, thus has a great potential to improve the quality assurance cycle of AM processes in the long run. We illustrate the framework and statistically evaluate the binary classification performance on data measured from additive manufactured parts on a large scale. We also examine how different systems, repeated measurements, and operators affect the similarity score and classification performance. We compare our work with a baseline method using the surface roughness average parameter Ra. The results show that the methodology can distinguish matched and non-matched pairs with high accuracy, and it outperforms the baseline method greatly. The framework serves as a benchmark method and can be generalized to be used in other fields where surface topography plays a critical role.
Non-invasive deformation metrology using subspace analysis in digital holographic interferometry

For non-invasive precision measurement of deformation using digital holographic interferometry (DHI), reliable estimation of interference phase from complex fringe signal is required. This article introduces a method for estimation of interference phase in DHI. The proposed method is based on computing roots of a frequency estimation function obtained from noise subspace of the fringe signal. The main advantage of the proposed method is robustness against severe noise. In addition, the method also offers the capability of direct phase derivative estimation. The performance of the proposed method is validated using numerical simulations. Our simulation results show that even for signal to noise ratio as low as −5 dB, the proposed method offers root mean square errors of less than 1 radian for phase retrieval. The practical utility of the method for non-invasive deformation analysis is demonstrated using experimental results in DHI.
Positioning, transfer, and rotation movements of particles manipulated by a novel piezoelectric acoustofluidic device with multiple vibration modes

Acoustic-based manipulation platforms are the preferred device to manipulate particles in analytical chemistry and biomedicine due to their label-free and high biocompatibility. As a significant wave mode of the acoustic manipulation method, bulk acoustic waves (BAWs) have been wildly concerned by academia and industry. To realize the high-precise multi-mode manipulation of particles with a simple structure, a BAWs-based piezoelectric acoustofluidic device is proposed. It is composed of a Langevin transducer and a disk with a circular groove. Two vibration modes of the disk with three and five node circles, respectively, are used to manipulate particles to position, transfer, and rotate. A non-nodal acoustic trap is induced in the disk center by producing its first out-of-plane bending vibration mode. In this acoustic trap, the spherical particles and irregularly shaped particles can be fixed entirely and rotated, respectively. Simultaneously, the disk center is an antinode of the acoustic field induced by the second disk out-of-plane bending vibration mode, leading to that the trapped particles can be equidistantly transferred from the disk center to the nearest node. The effectiveness of the proposed device is verified by simulations and experiments. With appropriate control parameters, the minimum position fluctuation of the submillimeter-hollow-glass sphere (SHGS) after being positioned is 0.32% of its diameter. Moreover, the maximum transfer speed of the SHGS and maximum rotation speed of the cylindrical metal wire are 130.8 mm s−1 and 23.51 rad s−1, respectively. This proposed device is capable of multiple manipulation modes for particles with simple control strategy, providing a novel method for designing a BAWs-based device to achieve the manipulation of particles.
Recognition of Station Topology Based on Power Conservation

Aiming at the problems of the confusion of user meter data in the distribution network and the difficulty in identifying the relationship, a creative method of identifying the topological structure of the station based on the conservation of current and energy is proposed. Through the calculation of the current data relationship, a mathematical relationship model based on energy conservation is established for the topological scene of the station. After constructing the mathematical model, through a series of transformation methods, the model is transformed into a convex optimization problem. By solving the model, the topological relationship of the station is finally obtained. Through the experimental verification and analysis of real data, the model algorithm proposed in this paper has higher accuracy and higher efficiency than manual screening, and has deeper research value.
Nucleotides to Rorquals: Delineating humpback whale distribution with environmental DNA

The assessment of species distribution is integral to understanding biodiversity in aquatic systems but remains difficult for rare or cryptic species such as whales. Environmental DNA (eDNA) has become a powerful non-invasive approach for genetic monitoring of species presence in marine ecosystems, providing further insight towards the ecological and spatial processes of difficult-to-sample taxa. This study examines eDNA metabarcoding data amplified with universal MiFish primers that target the mitochondrial 12S rRNA gene to characterize cetacean communities in Monterey Bay, California. Water samples were collected monthly from a nearshore location (C1) during the years of 200819. Cetacean communities detected with eDNA were analyzed to determine species abundance and distribution to show community structural differences over time. Megaptera novaeangilae (humpback whale) showed to be the most prominent in all datasets, with 8 different ASVs identified, encompassing 30,816 high quality Illumina sequence reads. The presence of humpback ASVs was found to be correlated with the presence of anchovies and upwelling status in the system, as well as following known fall feeding migration trends. Results suggest accurate portrayal of humpback presence in
Effect of Gender Diversity on the Association between Corporate Sustainability Practices and Financial Performance of Firms

Purpose: The objective of this research is to examine the effect of corporate sustainability practices (CSP) on financial performance (FP) as well as the moderating effect of gender diversity (GENDIV) in the board on the relationship between CSP and FP of firms in Malaysia. Methods: The sample of the study is 312 firm-year observations from 2015 to 2017 of 104 firms listed in Bursa Malaysia. The theoretical framework of the study is underpinned by the Stakeholder theory and the Agency theory. To test the hypotheses, with the help of STATA software, the panel corrected standard errors (PCSE) estimator model and the hierarchical moderated multiple regression model have been used. Results: The findings of the study reveal that CSP significantly and positively affects the FP of firms. The empirical results also show that gender diversity in boards significantly moderates the relationship between CSP and FP of Firms in Malaysia. Implications: Based on the empirical findings, the study recommends that the policymakers and regulatory bodies should follow up the mandatory corporate sustainability practices of the firms as well as revise the codes of corporate governance regarding gender diversity of the boards to ensure their longterm sustainability as well as to reduce the risk of financial distress, or bankruptcies in the future.
New perspectives for the isomerization of light n-alkanes

Isomerization of light n-alkanes into the high-octane number branched alkanes is an important challenge for petroleum refining industry. According to the literature, such a transformation needs two different active centres: one having a hydrogenating/dehydrogenating ability and another, a protonic acid function. From this point of view, heteropolyacids (HPAs) in mixing with one or more transition metal appear promising. Mechanical mixtures of alumina-supported platinum or of mixed palladium (or nickel) -cerium oxides and silica-supported HPAs have been tested for the isomerization of n-hexane. The catalysts were characterized before and after tests. Although pure silica-supported HPAs have an initial activity, they are very easily to deactivate by coke deposition. Presence of Pt, Pd, and Ni gives rise to a better activity and a higher selectivity for di-branched isomers, and is really beneficial for retaining the Keggin structure of silica-supported HPAs. The catalytic performances are strongly depending on the composition of the mechanical mixtures. Roughly, the activity is in the same order as the acid strength. 1H and 31P solid-state NMR studies of trimethyl phosphine adsorbed on heteropolytungstate put in the evidence of the acidic sites. It is noteworthy that the presence of metallic Pt, Pd, or Ni metal after the reduction, instead of the original metallic ions, reinforces the generally admitted mechanism with an activation of the alkane. The activation is difficult to obtain by direct attack by an acid (proton), but it can be achieved by the metallic species to the corresponding alkene before formation of a carbenium intermediate on the acid site. However, the formation of alkenes directly by the HPAs and the participation of metallic species for limiting the alkenes concentration are not excluded.
Systematic treatment and prevention of cardiac digoxin toxicity

Digoxin has a narrow therapeutic index, such as complicated pharmacokinetics and dynamics. Many drug interactions may occur when the administration of one drug alters the clinical effects of another. As a result, digoxin toxicity can be a common condition within clinical settings that might lead to the development of many morbidities and even mortality. Many studies were published to investigate the efficacy and safety of different management modalities to enhance the outcomes that follow digoxin administration. The aim of the study was to discuss the approaches to systematically treat and prevent the development of cardiac digoxin toxicity. The findings are based on evidence from previous studies in the literature. To be specific, Fab fragments are the most effective modalities that can be used to treat severe cases within ideal periods. However, evidence regarding their administration for asymptomatic or mild cases is still poor regarding the cost-efficacy and the development of serious adverse events. Physicians should primarily care for a better intervention as it is usually associated with a significantly more enhanced prognosis and clinical outcomes. Nevertheless, adequate monitoring of the patients and evaluation of their personal and medical history are important steps in the process, and further approaches are still needed. Also, detailed information about our intended outcomes is furtherly discussed within the manuscript.
Lipolytic Activities of Bacteria and Fungi Isolated from Soil Samples

This study was carried out at the Department of Microbiology, Microbiology Laboratory, Ado-Ekiti State University, Ekiti State, Nigeria between July, 2018 to March, 2019. Due to the diverse biotechnological importance of lipases as a biocatalytic enzyme, extracellular production of microbial lipases has to gain lots of interest. This study, therefore, focused on the physicochemical parameters of lipase producing microorganisms from different soil samples. Microorganisms were isolated from four different soil samples using Nutrient Agar (NA) and Potato Dextrose Agar (PDA). The isolates were identified and characterized. Production, an assay for Lipase enzymes, purification, the effect of pH, Temperature and metal ion was investigated. The isolates were culturally, morphologically and biochemically characterized. Two of the bacteria strains (Bacillus sp. and Staphylococcus sp.) and four fungi (Fusarium sp., Aspergillus fumigatus, Aspergillus niger, and Trichophyton sp.) isolates were able to produce lipid using Sudan Black B Fat staining techniques. Fusarium sp. isolated from dumpsite soil had the highest specific lipase activity (21.16 Original Research Article Fashogbon et al.; MRJI, 31(5): 27-43, 2021; Article no.MRJI. 69500 28 μmol/min/ml) while Bacillus sp. isolated from red oil spill soil had the highest lipase activity (0.59 μmol/min/mg). The specific activity of partially purified lipase for Fusarium sp. was 2.39 μmol/min/mg while Bacillus sp. had a specific activity of 2.46 μmol/min/mg. 30C 50C, pH 7.0 to 9.0 and KCl2 (139.672%) supported the highest production of lipase by the Bacillus sp. and Fusarium sp. This study demonstrated that the Bacillus sp. produced a high amount of lipase activity followed by Fusarium sp. Extensive and persistent screening for new microorganisms and their lipolytic activities will help to provide faster ways to solve most environmental soil pollution.
In vitro anthelmintic activity of pineapple peel juice (Ananas comosus (L.) Merr.) against Paramphistomum sp.

Pineapple peel (Ananas comosus (L.) Merr. ) has a potential natural-based anthelmintic agent. This study aimed to determine the effective concentration of pineapple peel juice against Paramphistomum sp. in vitro. Adults Paramphistomum sp. were divided into 5 test groups, the control group contained Albendazole 10% w/v, the nontreatment group contained NaCl 0.9% w/v and the treatment group contained pineapple peel juice with concentration of 12.5, 20, and 25% w/v. The number of live flukes and the motility scores were recorded every 15 minutes for 5 hours of incubation. The Survival Index (SI) and Relative Motility (RM) of flukes were calculated and statically analyzed using SPSS version 23 software. SI values of flukes in the 12.5, 20, and 25% w/v concentration of treatment group were 46.3, 50.0, and 38.9% respectively. RM values of flukes in the 12.5, 20 and 25% w/v concentration of treatment groups were 39.1, 42.0, and 34.1 respectively. RM values of flukes in the 12.5, 20 and 25% w/v concentration of treatment groups were 39.1359, 42.0249, and 34.1174 respectively. This research showed that, pineapple peel juice 25% w/v was effective against Paramphistomum sp. with survival index and relative motility values comparable to Albendazole 10% w/v (p <0.05).
Trichoderma harzianum antagonism against chickpea fusariosis and its biofertilizing effect

Chickpea is a legume, which is grown in two regions of Mexico mainly, Northwest (Sonora, Sinaloa and Baja California) and El Bajío region (Guanajuato, Michoacán and Jalisco); however, each year the production of the culture is compromised with vascular fusariosis, one of the main diseases that affect the culture and that is associated with the fungal complex Fusarium oxysporum, Fusarium solani, Rhizoctonia solani, Macrophomina phaseolina and Sclerotium rolfsii. An alternative of biological control is the application of Trichoderma, which also has an indirect effect on the nutrition of the plant. The objective of this study was to determine the in vitro antagonism of two strains of Trichoderma harzianum (T1 and T2) and its effect as a biofertilizer. In vitro confrontations were carried out against strains of the Fusarium oxysporum f. sp. ciceris (Foc 0, 1B/C, 5 and 6), Fusarium solani, Macrophomina phaseolina (M-Sonora and M-GTO) and Sclerotium rolfsii. The effect of T2 as a biofertilizer (TB) was evaluated by measuring the variables: number of flowers, pods, plant height, stem diameter, root length and grain yield. The two strains of T. harzianum showed antagonism on different scales against pathogens. Additionally, with the treatment where T. harzianum (TB) was applied, there were increases in the number of flowers (30%), pods (24%), height (3%), plant diameter (3.5%), as well as root length (13%) and grain yield (23%).
Spoken language identification using i-vectors, x-vectors, PLDA and logistic regression

Received Feb 19, 2021 Revised May 20, 2021 Accepted Jun 22, 2021 In this paper, i-vector and x-vector is used to extract the features from speech signal from local Indonesia languages, namely Javanese, Sundanese and Minang languages to help classifier identify the language spoken by the speaker. Probabilistic linear discriminant analysis (PLDA) are used as the baseline classifier and logistic regression technique are used because of prior studies showing logistic regression has better performance than PLDA for classifying speech data. Once these features are extracted. The feature is going to be classified using the classifier mentioned before. In the experiment, we tried to segment the test data to three segment such as 3, 10, and 30 seconds. This study is expanded by testing multiple parameters on the i-vector and xvector method then comparing PLDA and logistic regression performance as its classifier. The x-vector has better score than i-vector for every segmented data while using PLDA as its classifier, except where the i-vector and x-vector is using logistic regression, i-vector still has better accuracy compared to xvector.
Smart-adaptive Learning Systems: Systematic Survey on the Ubiquitous Computing Environment

Smart-adaptive learning is a model of technology-based learning that aware of the students' individual learning needs and style, situation, context, also the state of their learning process and acts according to them dynamically. This system can be applied to various fields such as education and training. One of the benefits of Smart-adaptive Learning is the ability of the system to realize and collect context-based information from students or students to then adapt to the student's learning characteristics and needs. Moreover, another essential feature of Ubicomp Smart-adaptive is its ability to provide access to learning resources that are digitally flexible, anytime, anywhere, and multi-wares. Most academic communities think that this scenario is still rare. Therefore, this article proposes to investigate the smart-adaptive ubicomp environment and its potential application in higher education. This study aims to examine the smart-adaptive ubicomp environments and to introduce these systems in the literature of the educational services and the recent research in this topic through a systematic survey study.
How Home Contexts of South African University Students Shape their Experiences of Emergency Remote Teaching and Learning

The shift to Emergency Remote Teaching and Learning (ERTL) in response to the COVID-19 pandemic has necessitated online learning at home for South African (and other) students. Using a critical paradigm, qualitative approach and case study design, this study, underpinned by critical theory, used interviews, voice notes and text messages to generate data to explore how South African university students’ home contexts shape their experiences of ERTL. Using thematic analysis, the findings indicated that student learning at home was negatively impacted by poor internet connectivity, home responsibilities, cramped living conditions, lack of safety, and financial and psycho-social stresses. The findings exposed the lived realities of students’ home contexts, made more difficult through the pandemic. This study adds to the literature on student adaptation to learning in the pandemic within home contexts characterised by resource poverty and challenging psycho-social conditions.