Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-Based Systems Engineering Tool-Chain for Automated Parameter Value Selection

Cyber-physical systems (CPSs) integrate heterogeneous systems and process sensor data using digital services. As the complexity of CPS increases, it becomes more challenging to efficiently formalize the integrated multidomain views with flexible automated verification across the entire lifecycle. This article illustrates a model-based systems engineering tool-chain to support CPS development with an emphasis on automated parameter value selection for co-simulation. First, a domain-specific modeling approach is introduced to support the formalizations of CPS artifacts, development processes, and simulation configurations. The domain-specific models are used as the basis to generate a Web-based process management system for automated parameter value selections, which coordinates Open Services for Lifecycle Collaboration services of development information and technical resources (models, data, and tools) in order to support automated co-simulation. The services are deployed by a service orchestrator based on a decision-making algorithm for parameter value selection. Finally, developers make use of the WPMS to implement simulations and to select system parameter values for co-simulation automatically. The approach is illustrated by a case study on auto-braking system development and we evaluate the efficiency of this tool-chain by both qualitative and quantitative methods. The results show that parameter values are selected more efficiently and effectively when implementing co-simulations using our tool-chain.
Effective and Efficient Similarity Measures for Purchase Histories Considering Product Taxonomy

In an online shopping site or offline store, products purchased by each customer over time form the purchase history of the customer. Also, in most retailers, products have a product taxonomy, which represents a hierarchical classification of products. Considering the product taxonomy, the lower the level of the category to which two products both belong, the more similar the two products. However, there has been little work on similarity measures for sequences considering a hierarchical classification of elements. In this paper, we propose new similarity measures for purchase histories considering not only the purchase order of products but also the hierarchical classification of products. Unlike the existing methods, where the similarity between two elements in sequences is only 0 or 1 depending on whether two elements are the same or not, the proposed method can assign any real number between 0 and 1 considering the hierarchical classification of elements. We apply this idea to extend three existing representative similarity measures for sequences. We also propose an efficient computation method for the proposed similarity measures. Through various experiments, we show that the proposed method can measure the similarity between purchase histories very effectively and efficiently.
Integrating Dilated Convolution into DenseLSTM for Audio Source Separation

Herein, we proposed a multi-scale multi-band dilated time-frequency densely connected convolutional network (DenseNet) with long short-term memory (LSTM) for audio source separation. Because the spectrogram of the acoustic signal can be thought of as images as well as time series data, it is suitable for convolutional recurrent neural network (CRNN) architecture. We improved the audio source separation performance by applying the dilated block with a dilated convolution to CRNN architecture. The dilated block has the role of effectively increasing the receptive field in the spectrogram. In addition, it was designed in consideration of the acoustic characteristics that the frequency axis and the time axis in the spectrogram are changed by independent influences such as speech rate and pitch. In speech enhancement experiments, we estimated the speech signal using various deep learning architectures from a signal in which the music, noise, and speech were mixed. We conducted the subjective evaluation on the estimated speech signal. In addition, speech quality, intelligibility, separation, and speech recognition performance were also measured. In music signal separation, we estimated the music signal using several deep learning architectures from the mixture of the music and speech signal. After that, the separation performance and music identification accuracy were measured using the estimated music signal. Overall, the proposed architecture shows the best performance compared to other deep learning architectures not only in speech experiments but also in music experiments.
Responsibility and Organization Science: Integrating Micro and Macro Perspectives

Responsibility is an important issue in organizations and society. Employees, managers, and owners can behave responsibly in the workplace and beyond. In addition, these individuals can be influenced by the propensity of the organization to behave responsibly. Organizations can pursue strategies that take into account responsibility at the product, firm, industry, and societal levels. This virtual special issue examines 19 articles published in Organization Science that consider responsibility at multiple levels of analysis. An important theme that emerges is that although some studies have crossed levels of analysis, future research would benefit from cross-level or more meso-based approaches.
Graphene Oxide–Carbon Nanotubes Hybrids: Preparation, Characterization, and Application in Phenol Formaldehyde Resin

Graphene oxide–carbon nanotubes hybrids were prepared by using methylene diphenyl diisocyanate as a bridging agent. The as-prepared hybrids were introduced in phenol formaldehyde resin to fabricate polymer-based composites. Fourier transform infrared spectroscopy, transmission electrical microscopy, and X-ray diffraction were performed to characterize the functional groups, morphologies, and crystal structure of the as-prepared hybrids, respectively. The experimental results showed that the carbon nanotubes were loaded on the surfaces of the graphene oxide and they were held together through chemical bonds. Moreover, the as-prepared hybrids could improve the mechanical properties of the matrix. When the as-prepared hybrids loading was 0.6 wt%, the tensile strength, Young's modulus, and elongation at break of the composites were 31.3%, 97.0%, and 75.0% more than the pure sample; in addition, the compression strength and modulus of the composites were 19.7% and 21.3% more than the pure sample, respectively.
Market orientation and behavioural intentions of tourists in Ghana’s tourist destinations: the mediation role of tourist satisfaction

ABSTRACT The study investigates the relationship between market orientation and behavioural intentions in Ghana’s tourism industry using tourist satisfaction as a mediator. A sample of 226 respondents of 18 tourist destinations was drawn using a purposive sampling technique. Structural Equation Modelling (SEM) of Partial Least Squares (PLS) was employed to test the hypothesised relationships in the research model. The study found a significant positive relationship between market orientation and behavioural intentions and that tourist satisfaction mediates the relationship between market orientation and behavioural intentions. The study recommends that tourist destinations need to implement market orientation to improve their competitive advantage through tourist satisfaction and ultimately behavioural intentions. The study has practical implication on tourist destination marketing performance.
Bayesian Analysis of the Joint Risk of Malaria and Anemia Among Under-age Ve Children in Nigeria

-BackgroundA life-threatening malaria parasites are known to have a substantial causative effect with the occurrences of frequent episodes of other diseases causing rapid progression to death. The parasites feed on iron molecules present in the red blood cells, therefore, resulting in low functional hemoglobin concentration causing anemia in children, and preventing rapid recovery. This study quantifies the impact of malaria on under-age five anemic children in Nigeria. -MethodThe joint risk and disease specific risks factors of malaria and anemia were estimated using a generalized linear mixed model in a Bayesian framework and a Besag-York-Mollie spatial prior model to account for spatial heterogeneity. Data were sourced from the Demographic and Health Survey conducted by the National Population Commission. -ResultsMalaria significantly places anemic children at a higher risk, which signifies a significant correlation between these diseases with regards to risk factors such as the place or region of residence, family wealth index, and use of a mosquito-preventive net. -ConclusionA high proportion of parents that live in the rural region is non-educated and low-income earners engaging in subsistence farming places children at severe risk of malaria and anemia.
An Efficient Artificial Neural Network Model for Inverse Design of Metasurfaces

To expedite the design process of metasurface, an improved transfer function (TF)-based artificial neural network (ANN) model is proposed, which can directly generate structure parameters to match the customer-expected electromagnetic (EM) response. Compared with the existing inverse design techniques, poles and residues of TF instead of the EM responses at discrete points are input into the proposed model. To identify the solution to circumvent the nonuniqueness problem, which is the major challenge of inverse design, a novel network structure and a new training error function are proposed. An electromagnetically induced transparency-like metasurface is selected as an example to verify the effectiveness and efficiency of the proposed inverse design model.
Cell immobilization of Streptomyces griseobrunneus by microcrystalline cellulose for production of cyclodextrin glucanotransferase enzyme

Abstract The cyclodextrin glucanotransferase are extracellular enzymes that can hydrolysis starch as a substrate to cyclodextrin. Encapsulation and immobilization technique of microbial cells within the polymeric network have widespread applications in the production of enzyme. Bacterial cells were isolated from soil by serial dilution method. The molecular identity was established using 16S rDNA sequence analysis, and the identified strain was immobilized in the synthesized composites. Physicochemical characteristics of the synthesized composites were determined by using field emission scanning electron microscopy, Malvern Zetasizer Nano ZS and FT-IR analyses. Enzyme activity was measured by phenolphthalein assay. Streptomyces griseobrunneus was identified according to the 16S rDNA sequence. FT-IR analyses indicated that there was an interaction between all of the elements. Scanning electron microscopy analysis showed a cross-section of composites without cells and cells attached to composites. Enzyme activity was 1109, 948 and 606 U/ml in alginate/chitosan/microcrystalline cellulose (MCC) sheets, agar/gelatin/MCC beads and free cells, respectively. It could be concluded that the polymeric immobilization was effective in improving enzyme production because of its excellent properties such as guarding the bacterial cells against inhibitors and toxins.
Torque Ripple Suppression of PMSM Using Fractional-Order Vector Resonant and Robust Internal Model Control

Periodic torque ripples caused by current harmonics seriously affect the control accuracy of the Permanent magnet synchronous motors (PMSMs). A conventional approach to reducing current harmonics is the use of a proportional–integral resonant controller in the current loop. Nonetheless, harmonics can still cause steady-state errors. Furthermore, the PI-based control structure is sensitive to parameter mismatches and uncertain disturbances, which will decrease the tracking performance of the current loop. To overcome the drawbacks of the traditional control method, a hybrid robust resonant control strategy was developed in this study. First, a vector resonant controller was enhanced by introducing fractional-order calculus (denoted as the fractional-order vector resonant (FOVR) controller in this article) so that it can suppress harmonic components more effectively. Then, a robust internal mode controller (Robust-IMC) was designed to improve the robustness and dynamic response and further reduce the current harmonics. Finally, by combining the FOVR controller and Robust-IMC, a control method—FOVR-Robust-IMC was designed as the robust control law to ensure satisfactory robustness and harmonics suppression performance. Meanwhile, the stability and robust stability of the developed control strategy were also analyzed. The results demonstrated that the proposed FOVR-Robust-IMC effectively reduced the harmonic components and improved the robustness to parameter mismatch.
Using Computed Tomography Data for Finite Element Models of Wood Boards

A procedure is presented to generate 3D FE models of timber boards based on CT scans. The boards were tested in four-point bending tests until failure and the local displacement in the pure bending zone was recorded. The CT scans were treated as 3D images and image processing methods were used to reconstruct the board, the knots and the pith. A new procedure to reconstruct the ﬁbre deviations around knots by accounting for image gradient information was used. A quadratic tetrahedral mesh was generated for the region of the board which was under pure bending in the tests. The ﬁbre directions and the stiffness tensor, scaled by the local density, were transferred into each integration point of the mesh and the bending test was replicated. Preliminary results show that the procedure is able to realistically predict the observed local stiffness of the boards. Further development of the procedure is required to account for dead knots and to extend the procedure for indicating strength and predicting failure.
Negatively Charged N-Heterocyclic Carbene-Stabilized Pd and Au Nanoparticles and Efficient Catalysis in Water

Herein we describe the synthesis of negatively charged N-heterocyclic carbene (NHC)-functionalized palladium and gold nanoparticles (NPs), which are stable in water for over 3 months. The formation of these NHC–NPs proceeds via an efficient ligand exchange procedure. This method was successfully applied to different negatively charged NHCs bearing sulfonate and carboxylate groups. The obtained PdNPs were investigated as catalysts in hydrogenation reactions and showed high catalytic activity (TON up to 2500 and TOF up to 2000 h–1).
Geothermal heat use to eliminate hydrate formations in oil deposit injection wells

The article is devoted to an actual issue: the development of internal downhole heat exchangers technology to combat hydration in injection wells. Purpose: development of conceptual solutions for the use of geothermal coolant in the internal well heat exchanger of the injection well. A scheme of an internal downhole heat exchanger with a geothermal heat carrier has been developed, and includes a supply line of a geothermal carrier through the heat exchange surface of the injection well into the productive reservoir of the oil field. The scheme provides targeted utilization of thermobaric energy of a geothermal source to combat hydration in the injection well. A mathematical apparatus for describing the process of heat utilization and heat exchange in injection well is proposed. It is established that the capacity of one geothermal well discovered at the oil depths in the Dnipro-Donetsk basin is sufficient to eliminate hydration in 1-3 injection wells, and determines the feasibility of their joint work.
Impact of seabed slope on steel catenary riser touchdown zone response

Several factors can affect the response of steel catenary risers (SCR) around its touch down zone (TDZ). These include the stiffness of the soil, the soil suction force on the riser TDZ, the soil degradation with cyclic TDZ loading, etc. Riser strength and fatigue response computation are usually performed considering flat seabed and with the use of rigid or linear (spring) riser soil interaction model. However, bathymetric information obtained for the SCR lay path on the seabed reveal complex seabed profile variation, indicating that the seabed is far from being flat around the SCR TDZ. This paper presents findings from an investigation conducted on the influence of seabed slopes on the strength and fatigue response of SCRs, using a non-linear (NL) riser soil interaction model. The responses of SCRs on positively and negatively sloped seabed (rotated about the static touch down point on flat seabed) are compared with responses of SCRs on flat seabed. From the results, it can be deduced that the SCR dynamic and fatigue responses may be overpredicted or underpredicted in magnitudes dependent on the slope deviation of actual seabed from a flat seabed.
Social Media Exposure of Students in Relation to Academic Performance

This study aimed to determine the level of academic performance of college students in relation to their level of social media exposure. The descriptive-correlational research design was used. The study was conducted during the First Semester of 2018-2019 in CapSU Dayao Satellite College utilizing the 186 randomly selected 4-year college students from the four curricular (4) programs. A researcher-made questionnaire was utilized. Gathered data were analyzed and interpreted using mean, standard deviation, t-test, One-way ANOVA, and Pearson r. Results revealed that the respondents were 18-20 years old age, females, and with family income below the poverty threshold level. Respondents’ level of social media exposure is “sometimes” and their academic performance is “good. ” Further, no significant difference was found in the level of social media exposure when grouped according to sex and monthly income, however, a significant difference was found when grouped according to age. On the other hand, no significant difference was found in the respondents’ academic performance when grouped according to age, sex, and monthly family income. Further, no significant association or relationship was found between the level of social media exposure and the academic performance of the respondents. This implies that even though the respondents were exposed to social media they were able to maintain a good academic performance. Therefore, the time spent by students on the different social media platforms or the number of gadgets used is not indicative and determinant of how they will perform in their academics as a whole. Keywords— academic performance, social media exposure, social media platforms.
Effects of applying a training program on basketball shooting in young players

The main aim of this study was to determine the effects of the application of a strength program in the accuracy of basketball shooting in young female players. Twenty female basketball players, (mean ± standard deviation: 12.08 ± 0.42 years; 1.55 ± 0.08 height; 44.4 ± 5.54 body mass) participated in the study. The participants were divided into two groups, the Control Group (GC) and the Experimental Group (GE), and were evaluated in 4 throwing exercises before (Pre-Test), after the application of a 6-week strength program (Post-Test), as well as after 4 weeks of detraining. The applied training program includes four exercises: i) Jump with Counter-Movement; ii) Throwing of the Medicinal Ball; iii) Sit-ups; iv) Push-ups. The results suggest that application of the 6-week training program had a positive effect on performance in two the four throwing exercises. In addiction 4 weeks of detraining, did not cause significant changes in the performance of the different throwing exercises compared to the Post-test period. It was concluded that a strength training program with a duration of 6 weeks was sufficient to obtain positive effects in the effectiveness of 2 Point throwing exercises in young female basketball players.
Application of the classical Payout Ratio Model and determination of the limitations of the Lintner Model demonstrated on the example of Komerční banka, PLC

Initial determination of the payout ratio should be an integral part of each company strategy; it is a cornerstone of a long-term operation of any company. The aim of this contribution is to analyse the possibilities of determining the payout ratio of the company using dividend models and to design the most optimal application of the dividend model, and to define the limitations for the application. The data required for the application of the dividend models are obtained from the annual reports of Komerční banka, PLC. for the years of 2006-2018. The obtained data are used to calculate the classical payout ratio model, and subsequently to determine the payout ratio according to the Lintner model. Using the method of comparison, the obtained results for the application of the pay ratio are contrasted. The classic payout ratio model coincided directly with the results of the payout ratios of Komerční banka, PLC. and therefore turned out to be optimal for the application. The Lintner model is considered in literature to be very well functioning. However, this research confirmed that the resulting values of payout ratios after the application of the Lintner model are unacceptable in the long run.
Wind energy potential analysis for Thailand: Uncertainty from wind maps and sensitivity to turbine technology

ABSTRACT Rapid development of wind energy has been witnessed in Thailand. However, different wind resource maps (over land) have brought great uncertainty to wind energy planning. Here, four important mesoscale wind maps were considered: DEDP (2001), World Bank (2001), Manomaiphiboon et al. (2010) of JGSEE, and DEDE (2010). The wind maps were first harmonized to a common grid at 100 m and then compared. The earlier wind maps (DEDP and World Bank) are shown to represent the lower and upper limits of predicted speed, respectively, while JGSEE and DEDE tend to be more moderate with predictions statistically closer to observations. A consolidated wind map was constructed based on their median and shown to have the best prediction performance. It was then used for the technical potential analysis, in which three large (2-MW) turbine models (two conventional and one designed for low wind speed) were considered. By GIS techniques, any land areas not feasible for large wind turbines were excluded, and the corresponding overall onshore technical potential ranges between 50 and 250 GW, depending on map and turbine model. Considering only economically feasible turbines (with capacity factors of 20%) and the median-based map, the final technical potential equals 17 GW when using the low-wind-speed model but is reduced to 5 GW with the conventional models, adequately meeting the national wind energy target of 3 GW by the year 2036. The results suggest a strong sensitivity of estimated technical potential to turbine technology and a suitability of low-wind-speed turbines for wind conditions in Thailand.