Miracle-dz/UniFAR-FTUs huggingface dataset:
A cybernetics paradigm for research and development in accountancy education and training

Summary The need for systematic, continuous, intra- and inter-national, monitoring of accountancy education and training systems is pointed out. The accountancy education and training system is viewed as a human resources development system, which processes a primary input of accountancy students into output of qualified accountants. The characteristics of the students, and of some other inputs, processes, and outputs are taken into consideration. The whole system is related to its environment which consists of the state of technology, economic system, political system, social values, national educational system, and so on. The proposed paradigm provides a framework for iterative search for the answers to the present and the future questions in accountancy education and training, as well as for interrelating research findings and ideas in the cognate areas, in other disciplines, or in accountancy education in other countries of the world.
Solution and performance analysis of geolocation by TDOA

One method of geolocation is based on measuring the time difference of arrivals (TDOAs) of a signal received by three or four geostationary satellites. The received signals are cross-correlated to determine the TDOAs and a set of nonlinear equations are solved to produce the location estimate. An exact solution for the transmitter position is derived for the three or four receiver cases. Extension of the solution method to more receivers is straightforward. An analysis of the performance of the system is given, together with expressions for predicting the localization mean-square errors (MSEs) and bias, and the Cramer-Rao bound. Both precision in TDOA measurements and the relative geometry between receivers and transmitter affect the localization accuracy. The geometric factors act as multipliers to the TDOA variance in the bias and MSE formulae. A study of the dependency of the geometric factors on transmitter position and satellite spacings are provided, as well as simulation results. >
Electromagnetic scattering by partially buried PEC cylinder at the dielectric rough surface interface: TM case

The Gaussian rough surface with the Gaussian correlation function is used to represent the statistical rough surface. Electromagnetic scattering from a partially buried perfectly electrically conducting (PEC) cylinder at the rough surface interface between two dielectric media is solved for the case of TM wave incidence using the method of moments with point matching. The effects of surface roughness and moisture content of the soil on the bistatic scattering cross section of the partially buried PEC objects at the rough surface interface are investigated using the Monte Carlo procedure.
Organic Semiconductor Devices with Enhanced Field and Environmental Responses for Novel Applications

We discuss some recent advances in the use of organic semiconductor devices with additional or enhanced functionality beyond simple electrical switching. These include diodes that act as local temperature sensors or that filter reverse-bias currents at tens of megahertz frequency. Transistors are described with a range of sensing and reporting functions, for such properties as pressure, magnetic field, and chemical vapor. Because these devices will likely be employed in arrays and assemblies, we also present concepts of some larger, integrated components such as artificial skin, sensor arrays, and wireless power systems. The common theme of these devices is that they build on an extensive and growing understanding of the parent transistors and diodes, but represent a departure into new physical phenomena and application areas.
Physical and practical limits of a biomolecular control system using nanoparticles and electromagnetic field irradiation

Many nanometer length scale engineering applications of mechanics and biology including computation, sensing, self-assembly, transport, and molecular machine design take advantage of natural biomolecular machinery. Further development of these technologies requires direct, external biomolecular control. This thesis proposes a simple control technique: a biomolecular “on/off” activity switch in which metallic nanoparticles (NPs) are conjugated to target biomolecules and irradiated with an electromagnetic field. Due to their unique physical properties, the NPs specifically absorb the field’s energy. They convert the energy to heat, and then they transport it to the conjugated target biomolecules. The heat affects a change in the targeted biomolecules, selectively actuating their activity. This thesis is on the mechanisms by which both ultrafast pulsed laser irradiation and radio frequency alternating magnetic fields (RFMFs) can be used as energy sources for the proposed biomolecular activity switch. The thesis reports on the quantification of a fs-pulsed laser triggered release mechanism that actuates activity of the molecules released from NPs. The release mechanism is governed by NP surface chemistry. The operating window for the critical parameters governing release including NP properties and laser fluence is defined. The thesis also reports on transmission pump-probe experiments that show the thermal interface conductance (G) of NPs is critical to nanoscale thermal transport, and that G is a strong function of the NP’s surface chemistry. The thesis concludes that an ultrafast pulsed laser actuated biomolecular activity switch is feasible if the critical parameters are carefully controlled. However, experimental studies revealed that using RFMFs in this biomolecular activity switching technique is not feasible. These results are validated by theoretical and analytical studies of nanoscale heat generation and transport in the system. The results presented in this thesis have implications on the design of the biomolecular activity switch, and many of the results are also applicable to other nanoscale
Family eJournal as an Online Relationship Enhancement Tool: A Preliminary Investigation

The use of online social networking sites (SNS) has become increasingly popular during the past decade. While motivation to use SNS varies, the current pilot study examines the usefulness of a specific SNS, Family eJournal, as a therapeutic tool. Specifically, use of this online Q & A website was evaluated as a mechanism for improving connections with family and friends. Qualitative responses were overwhelmingly favorable from a sample of college students during a 14-week trial. While a more in- depth quantitative analysis is warranted, current results suggest SNS platforms such as Family eJournal may be a convenient tool for enhancing relationship quality and overall well-being.
Reduction of rework the Six Sigma way: case study of an Indian small scale industry

To respond to the fast changing economic conditions and customer needs various industrial engineering and quality management strategic such as ISO 9000, TQM, KAIZEN, JIT manufacturing, enterprises resources planning, lean management, business process reengineering (BPR), etc., have been developed. A new paradigm in this area of manufacturing strategies is Six Sigma. From last many years, the Six Sigma define–measure–analyse–improvecontrol (DMAIC) methodology is being used in many manufacturing industries to solve the problems related to the quality and productivity. The paper discusses the real life case where Six Sigma has been successfully applied at one of the Indian small–scale units to improve rejection rate in manufacturing of components in batch production. This paper explains phase wise application of all the phases of define–measure–analyse–improvecontrol (DMAIC), and ultimately shows how Six Sigma can help improving quality and profitability.
Therapeutic Effects of Punica granatum (Pomegranate): An Updated Review of Clinical Trials

Punica granatum L. belongs to the Punicaceae family which is distributed around the world. Different parts of pomegranate like seed, peel, juice, and leaves are rich in potential bioactive compounds. These plants have found application in traditional medicine such as in treatment of gastrointestinal, cardiovascular, and endocrine diseases, among others. The present review aimed to summarize the current research on the traditional and scientific applications of P. granatum with regard to the phytochemical content and clinical applications that may be useful for future drug development. Information about P. granatum was obtained from local classic herbal literature and electronic databases, such as PubMed, Scopus, and ScienceDirect. Several phytochemical constituents including polyphenolics, flavonoids, anthocyanosides, alkaloids, lignans, and triterpenes have been reported from the plant. Randomized clinical trials have provided evidence as to the pharmacological activities of pomegranate in several diseases including diabetes, cardiovascular disease, oral cavity disorders, endocrine disorders, and cancer. The present review has provided an insight into the traditional applications of the plants, and some of them have been validated by scientific evidence, particularly their applications as treatment of cardiovascular and endocrine diseases.
Content-based user classifier to uncover information exchange in disaster-motivated networks

Disasters strike communities around the world, with a reduced time-frame for warning and action leaving behind high rates of damage, mortality, and years in rebuilding efforts. For the past decade, social media has indicated a positive role in communicating before, during, and after disasters. One important question that remained un-investigated is that whether social media efficiently connect affected individuals to disaster relief agencies, and if not, how AI models can use historical data from previous disasters to facilitate information exchange between the two groups. In this study, the BERT model is first fine-tuned using historical data and then it is used to classify the tweets associated with hurricanes Dorian and Harvey based on the type of information provided; and alongside, the network between users is constructed based on the retweets and replies on Twitter. Afterwards, some network metrics are used to measure the diffusion rate of each type of disaster-motivated information. The results show that the messages by disaster eyewitnesses get the least spread while the posts by governments and media have the highest diffusion rates through the network. Additionally, the “cautions and advice” messages get the most spread among other information types while “infrastructure and utilities” and “affected individuals” messages get the least diffusion even compared with “sympathy and support”. The analysis suggests that facilitating the propagation of information provided by affected individuals, using AI models, will be a valuable strategy to pursue in order to accelerate communication between affected individuals and survival groups during the disaster and aftermath.
Cutting Force Monitoring based on the Frequency Analysis of Feed Motor Torques

Cutting force monitoring without any additional sensors will be an important technology to achieve autonomous machine tools which can control the cutting conditions and failure detections. The purpose of this study is to develop a cutting force estimation method based on servo information in ball screw drive machine tool. In this method, the cutting force is estimated by frequency analysis of servo motor torque of feed drive systems. A frequency component depended on the cutting force is extracted from the analyzed data, and the cutting force is estimated by inverse transformation from the frequency domain to time domain. The motor torque is strongly influenced by the friction force especially in case of the axis stopped. In the proposed method, the estimated cutting force is calibrated based on the identified friction force when the force is detected along the stopped axis. In order to confirm the effectiveness of the proposed method, actual cutting tests and simulations are carried out. As the results, it is confirmed that the proposed method can estimated cutting forces accurately in case of the cutting force becomes larger than the friction force of stopped axis.
Atrial fibrillation detection in outpatient electrocardiogram monitoring: An algorithmic crowdsourcing approach

Background Atrial fibrillation (AFib) is the most common cardiac arrhythmia associated with stroke, blood clots, heart failure, coronary artery disease, and/or death. Multiple methods have been proposed for AFib detection, with varying performances, but no single approach appears to be optimal. We hypothesized that each state-of-the-art algorithm is appropriate for different subsets of patients and provides some independent information. Therefore, a set of suitably chosen algorithms, combined in a weighted voting framework, will provide a superior performance to any single algorithm. Methods We investigate and modify 38 state-of-the-art AFib classification algorithms for a single-lead ambulatory electrocardiogram (ECG) monitoring device. All algorithms are ranked using a random forest classifier and an expert-labeled training dataset of 2,532 recordings. The seven top-ranked algorithms are combined by using an optimized weighting approach. Results The proposed fusion algorithm, when validated on a separate test dataset consisting of 4,644 recordings, resulted in an area under the receiver operating characteristic (ROC) curve of 0.99. The sensitivity, specificity, positive-predictive-value (PPV), negative-predictive-value (NPV), and F1-score of the proposed algorithm were 0.93, 0.97, 0.87, 0.99, and 0.90, respectively, which were all superior to any single algorithm or any previously published. Conclusion This study demonstrates how a set of well-chosen independent algorithms and a voting mechanism to fuse the outputs of the algorithms, outperforms any single state-of-the-art algorithm for AFib detection. The proposed framework is a case study for the general notion of crowdsourcing between open-source algorithms in healthcare applications. The extension of this framework to similar applications may significantly save time, effort, and resources, by combining readily existing algorithms. It is also a step toward the democratization of artificial intelligence and its application in healthcare.
Salmonella chitosan nanoparticle vaccine administration is protective against Salmonella Enteritidis in broiler birds

Salmonella control strategies include vaccines that help reduce the spread of Salmonella in poultry flocks. In this study we evaluated the efficacy of administering a live Salmonella vaccine followed by a killed Salmonella chitosan nanoparticle (CNP) vaccine booster on the cellular and humoral immunity of broilers. The CNP vaccine was synthesized with Salmonella Enteritidis (S. Enteritidis) outer-membrane-proteins (OMPs) and flagellin-proteins. At d1-of-age, one-hundred-sixty-eight chicks were allocated into treatments: 1) No vaccine, 2) Live vaccine (Poulvac®ST), 3) CNP vaccine, 4) Live+CNP vaccine. At d1-of-age, birds were orally vaccinated with PBS, Live vaccine, or CNP. At d7-of-age, the No vaccine, Live vaccine and CNP vaccine groups were boosted with PBS and the Live+CNP vaccine group was boosted with CNP. At d14-of-age, birds were challenged with 1×109 CFU/bird S. Enteritidis. There were no significant differences in body-weight-gain (BWG) or feed-conversion-ratio (FCR). At 8h-post-challenge, CNP and Live+CNP-vaccinated birds had 17% and 24% greater levels (P<0.05) of anti-Salmonella OMPs IgA in bile, respectively, compared to control. At d28-of-age, CNP, Live, and Live+CNP-vaccinated birds had 33%, 18%, and 24% greater levels (P<0.05) of anti-Salmonella OMPs IgA in bile, respectively, compared to control. At d14-of-age, Live+CNP-vaccinated birds had 46% greater levels (P<0.05) of anti-Salmonella OMPs IgY in serum, compared to control. At d21-of-age, splenocytes from CNP and Live-vaccinated birds had increased (P<0.05) T-lymphocyte proliferation at 0.02 mg/mL OMPs stimulation compared to the control. At d28-of-age, CNP and Live+CNP-vaccinated birds had 0.9 Log10 CFU/g and 1 Log10 CFU/g decreased S. Enteritidis cecal loads (P<0.05), respectively, compared to control. The CNP vaccine does not have adverse effects on bird’s BWG and FCR or IL-1β, IL-10, IFN-γ, or iNOS mRNA expression levels. It can be concluded that the CNP vaccine, as a first dose or as a booster vaccination, is an alternative vaccine candidate against S. Enteritidis in broilers.
Chitosan/β-TCP composites scaffolds coated with silk fibroin: a bone tissue engineering approach

Bone regeneration and natural repair are long-standing processes that can lead to uneven new tissue growth. By introducing scaffolds that can be autografts and/or allografts, tissue engineering provides new approaches to manage the major burdens involved in this process. Polymeric scaffolds allow the incorporation of bioactive agents that improve their biological and mechanical performance, making them suitable materials for bone regeneration solutions. The present work aimed to create chitosan/beta-tricalcium phosphate-based scaffolds coated with silk fibroin and evaluate their potential for bone tissue engineering. Results showed that the obtained scaffolds have porosities up to 86%, interconnectivity up to 96%, pore sizes in the range of 60–170 μm, and a stiffness ranging from 1 to 2 MPa. Furthermore, when cultured with MC3T3 cells, the scaffolds were able to form apatite crystals after 21 d; and they were able to support cell growth and proliferation up to 14 d of culture. Besides, cellular proliferation was higher on the scaffolds coated with silk. These outcomes further demonstrate that the developed structures are suitable candidates to enhance bone tissue engineering.
Robust Detection of Abandoned Objects Based on Modified Dual Background Segmentation

A robust real-time method for detection of abandoned objects in complex outdoor environments is presented. The system introduces a dual background segmentation method based on feedback modification. One background updates fast and the other updates slow. The slow background is then modified by the detection result to exclude the static foreground. They contribute to build the static foreground region masks which are used to update a counter. Static foreground regions are then extracted from the counter and further filtered by a light and shadow eliminator. The filtered regions are then classified into abandoned or removed objects by comparing the feature of its surroundings and the interior boundary vicinity of the fast background and slow background. The algorithm is simple and computationally less intensive. Experimental results on public video datasets and real image sequences acquired outdoor show its practicality and robustness to moving vegetation, shaking camera, illumination change and crowed scenes.
Pregnant and breastfeeding women’s prospective acceptability of two biomedical HIV prevention approaches in Sub Saharan Africa: A multisite qualitative analysis using the Theoretical Framework of Acceptability

HIV infection during pregnancy and breastfeeding has implications for maternal health. Between May- November 2018, we explored prospective acceptability of two novel HIV Pre-exposure Prophylaxis (PrEP) products, oral pills and vaginal rings, through focus group discussions with 65 pregnant and breastfeeding women in Malawi, South Africa, Uganda, Zimbabwe. Qualitative analysis was completed, guided by the Theoretical Framework of Acceptability (TFA). First, a deductive thematic analysis was applied to relevant coded data, into the seven TFA constructs (Affective Attitude; Burden; Ethicality, Intervention Coherence; Opportunity Costs; Perceived Effectiveness; Self-efficacy). Next, an iterative analysis was completed to generate themes within each of the TFA constructs. Women’s positive attitudes towards daily oral PrEP highlighted the familiarity of taking pills, understanding the purpose of taking pills, and the perception that it is an effective method to protect mothers and babies from HIV during pregnancy and breastfeeding. Women emphasized the ease of using the ring given its monthly duration that lowers burden on the user, its discreetness and invisibility once in place. The TFA analysis highlighted how acceptability of both methods could be enhanced by focusing on perceptions of the end users (i.e. the women) and not just the products themselves. This approach provided insights into how to refine the intervention materials and plans for implementation.
A Calibrated Force-based Model for Mixed Traffic Simulation

Virtual traffic benefits a variety of applications, including video games, traffic engineering, autonomous driving, and virtual reality. To date, traffic visualization via different simulation models can reconstruct detailed traffic flows. However, each specific behavior of vehicles is always described by establishing an independent control model. Moreover, mutual interactions between vehicles and other road users are rarely modeled in existing simulators. An all-in-one simulator that considers the complex behaviors of all potential road users in a realistic urban environment is urgently needed. In this work, we propose a novel, extensible, and microscopic method to build heterogeneous traffic simulation using the force-based concept. This force-based approach can accurately replicate the sophisticated behaviors of various road users and their interactions in a simple and unified manner. We calibrate the model parameters using real-world traffic trajectory data. The effectiveness of this approach is demonstrated through many simulation experiments, as well as comparisons to real-world traffic data and popular microscopic simulators for traffic animation.
Plant neighbours can make or break the disease transmission chain of a fungal root pathogen

Summary Biodiversity can reduce or increase disease transmission. These divergent effects suggest that community composition rather than diversity per se determines disease transmission. In natural plant communities, little is known about the functional roles of neighbouring plant species in belowground disease transmission. Here, we experimentally investigated disease transmission of a fungal root pathogen (Rhizoctonia solani) in two focal plant species in combinations with four neighbour species of two ages. We developed stochastic models to test the relative importance of two transmission‐modifying mechanisms: (1) infected hosts serve as nutrient supply to increase hyphal growth, so that successful disease transmission is self‐reinforcing; and (2) plant resistance increases during plant development. Neighbouring plants either reduced or increased disease transmission in the focal plants. These effects depended on neighbour age, but could not be explained by a simple dichotomy between hosts and nonhost neighbours. Model selection revealed that both transmission‐modifying mechanisms are relevant and that focal host–neighbour interactions changed which mechanisms steered disease transmission rate. Our work shows that neighbour‐induced shifts in the importance of these mechanisms across root networks either make or break disease transmission chains. Understanding how diversity affects disease transmission thus requires integrating interactions between focal and neighbour species and their pathogens.
An OFDM Channel Estimation Method with Radial Basis Function Neural Network

For OFDM system, we proposed a channel estimation method based on radial basis function neural network (RBFNN). The neural network with Gaussian basis function is established according to the pilot pattern, where the network parameters are obtained by training channel response of pilot subcarriers as objective values for input samples. With the established network, channel coefficients of non-pilot subcarriers can be predicted. The simulation results indicate that the proposed algorithm performs well in OFDM systems under Rayleigh multipath fading channel.