Miracle-dz/UniFAR-FTUs huggingface dataset:
Direct numerical simulation of turbulent flow in a channel with transverse ribs

Surface roughness is of great relevance in most engineering applications, as very few surfaces can be regarded as perfectly smooth. Investigation of the effects on the mean flow, as well as the near wall turbulence is therefore of interest. In the present study, all scales of the turbulent motions are resolved using Direct Numerical Simulation (DNS). Transverse square ribs are introduced as a surface roughness model in a pressure driven channel flow at Reynolds number Reτ = 395 to establish a streamwise inhomogeneity. The principal aim of the study is to see whether a specific in-house pseudo-spectral DNS-code developed for plane channel flow performs, even though it is, in principle, not suited for this specific application. The results from the rough channel simulation are compared to both a smooth and rough channel reference case. The results are found to be almost identical to that of the rough channel reference. For the mean velocity profile, the logarithmic shape is maintaned, but the profile has a downwards shift due to the increased drag. Streamwise dependency for the mean velocity, as well as turbulence quantities, is found to be limited to the roughness sublayer, stretching out to z ≈ 5r, where r is the non-dimensionalized height of the roughness elements, indicating that the flow is unaware of the surface conditions in the outer region. Compared to the smooth channel data, roughness effects are mainly found to affect the flow inside the roughness sublayer. It is proven that the pseudo-spectral DNS-code works well with the relatively small roughness elements, and despite the fact that streamwise homogeneity is removed, the results suggests that the quasi-homogeneity of the velocity field is sufficient for the pseudo-spectral code to deliver accurate results. Further, when accounting for reduced domain size, the grid point resolution is 43% less than in the reference case of Ashrafian [4]. This is motivated by reduced computational cost, but also serves as a check on the spectral-method’s superior accuracy and reduced demand for grid point resolution. The results indicates that a relatively high level of accuracy is still delivered.
Data Augmentation Method by Applying Color Perturbation of Inverse PSNR and Geometric Transformations for Object Recognition Based on Deep Learning

Deep learning is applied in various manufacturing domains. To train a deep learning network, we must collect a sufficient amount of training data. However, it is difficult to collect image datasets required to train the networks to perform object recognition, especially because target items that are to be classified are generally excluded from existing databases, and the manual collection of images poses certain limitations. Therefore, to overcome the data deficiency that is present in many domains including manufacturing, we propose a method of generating new training images via image pre-processing steps, background elimination, target extraction while maintaining the ratio of the object size in the original image, color perturbation considering the predefined similarity between the original and generated images, geometric transformations, and transfer learning. Specifically, to demonstrate color perturbation and geometric transformations, we compare and analyze the experiments of each color space and each geometric transformation. The experimental results show that the proposed method can effectively augment the original data, correctly classify similar items, and improve the image classification accuracy. In addition, it also demonstrates that the effective data augmentation method is crucial when the amount of training data is small.
CMIP5-Based Spatiotemporal Changes of Extreme Temperature Events during 2021–2100 in Mainland China

The increasing number of extreme climate events is having a great impact on the terrestrial ecosystem. In this study, we applied a Taylor diagram to evaluate the 7 extreme temperature indices (ETI) of 12 models and the multi-model ensemble (MME) mean from phase 5 of the Coupled Model Intercomparison Project (CMIP5) during 1961–2005, and found that the MME has the best simulation effect. Warm indices and warm duration indices increase slowly, rapidly, and extremely under the representative concentration pathway 2.6 (RCP2.6), RCP4.5, and RCP8.5 scenarios, respectively. In contrast, the decrease in cold indices and cold duration indices are slow, rapid and extreme, respectively. The ETI from 2021–2100 under the RCP2.6 and RCP4.5 scenarios have primary periods ranging from 1–16 years. Under the RCP2.6 and RCP4.5 scenarios, the changes of warm indices are relatively largest in the basin of the central, and southeastern, while, under the RCP8.5 scenario, the changes are relatively significant, except for basin of northeast. The cold indices have the most significant decreasing trend in the Tibetan Plateau and its surrounding areas, under the three RCP scenarios. The findings from this study can provide reference for the risk management and prevention of climate disasters in the context of climate change in mainland China.
Perfluorocarbon nanoemulsions containing fluorinated photosensitizer for photodynamic cancer therapy

The composition of the photosensitizer and fluorocarbons with high oxygen capacity allows to increase the effectiveness of photodynamic therapy, which is shown on tumor cells. To achieve the solubility of photosensitizers in fluorocarbons, a number of fluorinated porphyrins were synthesized and their spectral characteristics were obtained. Fluorocarbon emulsions without a photosensitizer are inert for tumor cells of human colon adenocarcinoma. Fluorocarbon nanoemulsion with leader fluorinated porphyrin with fluoroaliphatic substituents accumulates in tumor cells and causes photoinduced necrosis due to peroxidation of membrane lipids. Perfluorocarbon nanoemulsions in combination with a dissolved fluorine phase photosensitizer are promising compositions for the photodynamic therapy of cancer.
The role of Hfq and sRNAs in regulation of Pasteurella multocida gene expression

The bacterium Pasteurella multocida is the cause of numerous economically important animal diseases, including avian fowl cholera. Little is known about the regulation of genes involved in P. multocida virulence. Hfq is a bacterial chaperone protein that can facilitate important RNA-RNA regulatory functions, usually via small RNA (sRNA) molecules. In this study, we aimed to unravel the role of the Hfq protein and sRNAs in the P. multocida regulatory network specifically focusing on functions that impact P. multocida pathogenesis. By increasing our understanding of the regulation of P. multocida virulence, we can develop therapeutic agents to treat P. multocida infections.
COST-BENEFIT ANALYSIS OF ESTABLISHMENT OF SCOTS PINE, AUSTRIAN PINE AND SPRUCE FOREST PLANTATIONS

The cost-benefit analysis, which contributes to finding best solutions and helps in making decision on acceptability of treatment, has been used as an instrument in the assessment of afforestation impact on the environment. It has been established that a cost-effective investment into Scots pine, Austrian pine and Spruce afforestation is viable solely on the basis of wood production. Wood production, depending on tree species and soil quality, can bear even slightly higher interest rates in the areas of good soil quality in comparison to previous estimates, which mostly ranged around 3%. In the areas of poor soil quality, the interest rates can drop even below the 3% rate. At lower discount rates, the breakeven point is extended in time, whereas at higher discount rates, it is shortened. The length of production cycle performs an important role in determining the costeffectiveness of an investment, particularly from the aspect of the relation between the length of production cycle and production purposes (type and quality of wood assortments that are produced). Based on the analysis of non-quantifiable benefits and costs, it has been established that the benefits surpass the costs, therefore, afforestation projects can be acceptable.
A Note On the Hadamard Kth Root of a Rational Function

Abstract Suppose the sequence of Taylor coefficients of a rational function f consists of kth powers of elements all belonging to some finitely generated extension field F of Q. Then it is a generalisation of a conjecture of Pisot that there is a rational function with Taylor coefficients term-by-term kth roots of those of f. The authors show that it suffices to prove the conjecture in the case that the field of definition is a number field and prove the conjecture in that case subject to the constraint that f has a dominant pole, that is, that there is a valuation with respect to which f has a unique pole either of maximal or of minimal absolute value.
Isolation and characterization of EST-SSRs in the Ramie

In order to develop the more EST-SSRs, 320 ESTs of ramie from NCBI were analyzed. 76 SSR primer-pairs developed from 320 ESTs were tested among 62 ramie individuals, and 27 SSR loci were polymorphic. Among the 27 primers, the numbers of alleles per locus ranged from two to five, in which 19 primers amplify two alleles, seven primers amplify three alleles, and only one primer amplifies five alleles. Observed heterozygosity (HO) of overall loci among the 27 primer pairs ranged from 0.16 to 0.93 and expected heterozygosity(HE) ranged from 0.21 to 0.66. Of the 27 loci, 14 displayed significant deviations from Hardy–Weinberg expectations (P < 0.05). No significant linkage disequilibrium (LD) was detected among the 27 loci. The 27 primers have been used in the ramie molecular linkage map and genetic diversity analysis successfully. Key words: Microsatellite marker, ramie, EST, EST-SSR.
IN VITRO DETERMINATION OF SUN PROTECTION FACTORS ON ETHANOL EXTRACT AND NANOSTRUCTURED LIPID CARRIER-BASED GEL EXTRACT OF MULBERRY ROOT (MORUS ALBA L.)

Objective: The purpose of this study was to determine the potential of sun protection factors on extract and nanostructured lipid carrier (NLC) gel of mulberry root extract. Methods: In this study, the root mulberry ( Morus alba L.) was extracted using 96% ethanol and tested its sun protective factor (SPF) values. Mulberry root extract made into NLC with solvent evaporation method. The NLC was evaluated and dispersed into the gel, NLC gel was tested SPF value by petro method. Results: The result shows that the SPF value extracts of mulberry root at the concentration 300 ppm, 400 ppm, and 500 ppm were 10.84, 28.17, and 66.65, respectively. While the SPF values of NLC gel extract of mulberry root at the concentration of 300 ppm, 400 ppm, and 500 ppm were 9.11, 22.87, and 45.76, respectively. Conclusion: It could be concluded that extract and NLC gel of mulberry root extract have potential in ultraviolet protection against the skin.
Advances in Thermochemical Synthesis and Characterization of the Prepared Copper/Alumina Nanocomposites

This paper presents thermochemical synthesis of copper/alumina nanocomposites in a Cu-Al2O3 system with 1–2.5 wt. % of alumina and their characterization, which included: transmission electron microscopy: focused ion beam (FIB), analytical electron microscopy (AEM) and high resolution transmission electron microscopy (HRTEM). Thermodynamic analysis was used to study the formation mechanism of desirable products during drying, thermal decomposition and reduction processes. Upon synthesis of powders, samples were cold pressed (2 GPa) in tools dimension 8 × 32 × 2 mm and sintered at temperatures within the range 800–1000 °C for 15 to 120 min in a hydrogen atmosphere. Results of characterization showed that dispersion-strengthened compacts could be produced by sintering of thermo-chemically prepared Cu-Al2O3 powders with properties suitable for material application, such as a contact material exhibiting high strength and high electrical conductivity at the same time. Additional research was carried out in order to analyze the application of the obtained nanocomposite powders for the synthesis of copper/alumina nanocomposites by a new method, which is a combination of a thermochemical procedure and mechanical alloying. The measured values of an electric conductivity and hardness were compared with ones in literature, confirming an advantage of the proposed combined strategy.
Machine Learning Education for Artists, Musicians, and Other Creative Practitioners

This article aims to lay a foundation for the research and practice of machine learning education for creative practitioners. It begins by arguing that it is important to teach machine learning to creative practitioners and to conduct research about this teaching, drawing on related work in creative machine learning, creative computing education, and machine learning education. It then draws on research about design processes in engineering and creative practice to motivate a set of learning objectives for students who wish to design new creative artifacts with machine learning. The article then draws on education research and knowledge of creative computing practices to propose a set of teaching strategies that can be used to support creative computing students in achieving these objectives. Explanations of these strategies are accompanied by concrete descriptions of how they have been employed to develop new lectures and activities, and to design new experiential learning and scaffolding technologies, for teaching some of the first courses in the world focused on teaching machine learning to creative practitioners. The article subsequently draws on data collected from these courses—an online course as well as undergraduate and masters-level courses taught at a university—to begin to understand how this curriculum supported student learning, to understand learners’ challenges and mistakes, and to inform future teaching and research.
Design of a S Band Circularly Polarized Microstrip Patch Antenna Using Ferrite Disk

The design of a microstrip patch antenna in the S band for nano-satellite application is presented. Two self biased ferrite disks are inserted in the resonant region of the patch to obtain circular polarization. The addition of ferrite disks results in gain enhancement, increase in bandwidth and decrease in axial ratio. Experimental results show that the antenna has a gain of 6.159 dB, an impedance bandwidth of 140 MHz at a resonant frequency of 2.455 GHz and an axial ratio of 1.016 which is in concurrence with the simulated results.
DSTC7 Task 1: Noetic End-to-End Response Selection

Goal-oriented dialogue in complex domains is an extremely challenging problem and there are relatively few datasets. This task provided two new resources that presented different challenges: one was focused but small, while the other was large but diverse. We also considered several new variations on the next utterance selection problem: (1) increasing the number of candidates, (2) including paraphrases, and (3) not including a correct option in the candidate set. Twenty teams participated, developing a range of neural network models, including some that successfully incorporated external data to boost performance. Both datasets have been publicly released, enabling future work to build on these results, working towards robust goal-oriented dialogue systems.
Testing the Validity of the J-curve Hypothesis between Brazil and the USA

espanolEste trabajo tiene como objetivo investigar la validez de la hipotesis de la curva J entre Brasil y EE.UU Utilizando datos trimestrales para el periodo 1981Q1-2015Q1. Para lograr este objetivo, los modelos vectoriales de correccion de errores (VEC) con cointegracion, NARX (exogeno autoregresivo no lineal) y ANFIS (sistema de inferencia neuro-difusa adaptativa) se aplican por separado para fortalecer esta investigacion. NARX y ANFIS, como modelos de redes neuronales artificiales (ANN), se utilizaron por primera vez en este estudio para probar la validez de la hipotesis de la curva J. Se encontro que el tipo de cambio real y el ingreso, como variables independientes, y la balanza comercial entre Brasil y EE.UU, como la variable dependiente, estan cointegrados en el largo plazo. Los resultados empiricos de todos los modelos de prueba examinados en este estudio indican que la hipotesis de la curva J no es valida entre Brasil y EE. UU. Las depreciaciones reales de la moneda brasilena no contribuyen positivamente a la balanza comercial de Brasil. EnglishThis paper aims to investigate the validity of the J-curve hypothesis between Brazil and the USA using quarterly data for the period of 1981Q1- 2015Q1. To achieve this aim, the vector error correction (VEC) with cointegration, NARX (non-linear autoregressive exogenous) and ANFIS (adaptive neuro-fuzzy inference system) models are separately applied to strengthen this investigation. NARX and ANFIS, as artificial neural networks (ANN) models, were used for the first time in this study to test the validity of the J-curve hypothesis. It was found that the real exchange rate and income, as the independent variables, and the trade balance between Brazil and the USA, as the dependent variable, are cointegrated in the long-run. The empirical findings of all testing models examined in this study indicate that the J-curve hypothesis is not valid between Brazil and the USA. The real depreciations of the Brazilian currency do not make a positive contribution to the trade balance for Brazil.
Exploiting OpenMP Efficiency for Multiphase Flow Simulation in Heterogeneous Porous Media

This paper presents an efficient OpenMP implementation base d on an operator splitting algorithm for the numerical simulation of multi-dimension al three-phase convection-diffusion transport problems in heterogeneous rock. The nonlinear pa rtial differential equations modelling such a three-phase flow through porous media takes int o account variable porosity and permeability fields. In our numerical procedure a locally co nservative central difference scheme is used for the approximation of the nonlinear system of hype rbolic conservation laws modelling the convective transport of the fluid phases. This scheme is c ombined with locally conservative mixed finite elements for the numerical solution of paraboli c and elliptic problems associated with the diffusive transport of fluid phases and the pressurevelocity problem. Numerical experiments indicate that the use of large time-splitting rel ations with OpenMP implementation might translates into a significant reduced computational e ffort to produce numerical results within a given accuracy requirement.
The cryoprotective effects of soybean lecithin on boar spermatozoa quality

the extender supplemented with 6% soybean lecithin, with values of 59.7% for the percentage of total motile sperm (TM%), 44.3% for motility, 45.3% for plasma membrane integrity and 61.9% for acrosome integrity. TM%, motility, acrosome integrity and plasma membrane integrity in the extender containing 6% soybean lecithin were significantly higher than that of other concentrations of soybean lecithin and 20% egg yolk (P < 0.05). However, the percentages of TM, acrosome integrity and plasma membrane integrity decreased with the increasing concentration of soybean lecithin in extender. In summary, the effect of soybean lecithin on spermatozoa quality was superior and the effective concentration of soybean lecithin in extender was 6% (w/v). Soybean lecithin might replace egg yolk in extender in the cryopreservation of boar semen.
Reference evapotranspiration in São Paulo State : Empirical methods and machine learning techniques

Reference evapotranspiration (ETo) is a key factor for water management and irrigation scheduling. In this paper, eight empirical methods, including four temperature-based (Benevides-Lopez, Hamon, Blaney-Criddle Original and Hargreaves-Samani: HS), four radiation-based (Abtew: AB, Jensen and Haise, Makkink and Irmak) and machine learning techniques (MLT) were tested against Penman Monteith FAO 56 method. The MLT comprised six architectures for artificial neural networks (ANN) as well as support vector machine (SVM). The results of the empirical methods showed that AB method performed best with Mean Bias Error (MBE) = -0.17 mm day -1 ; Root Mean Square Error (RMSE) = 0.45 mm day -1 and R 2 = 0.89. However, in case of missing data of solar radiation (Rs), HS method can be a perfect alternative (MBE = 0.51 mm day -1 ; RMSE = 0.82 mm day -1 and R 2 = 0.87). Afterwards, performance of AB and HS methods was compared to performance resulting from MLT. In MLT, 70% of data was used for training and the remaining 30% was used for validation. The used ANNs were of multilayer perceptron type, with backpropagation algorithm; in support vector machine, Kernel’s radial basic function was used with regression sequential minimal optimization algorithm. The results obtained with MLT is as follows: MBE = 0.07 mm day -1 ; RMSE = 0.20 mm day -1 ; R 2 = 0.96 for A6 (ANN) and MBE = 0.00 mm day -1 ; RMSE = 0.18 mm day -1 ; R 2 = 0.95 for S6 (SVM). A6 and S6 architectures were composed of maximum temperature (T max.), minimum (Tmin.), average temperature (T), extraterrestrial radiation (Ra) and Rs. The HS method was the worst method in terms of performance, while AB method had the best results than A1 and S1, which only used T.
PRIORITISING THE PRACTICES THAT INFLUENCE THE OPERATIONAL PERFORMANCE OF MANUFACTURING ORGANISATIONS USING HYBRID AHP-TOPSIS ANALYSIS

Organisations cannot put their efforts equally into all the best practices that impact operational performance, due to their limited resources, their ineffective usage, government policies, and inadequate strategic planning. In this contribution, we aim to identify and prioritise the practices with the most impact on operational performance. Twelve practices that steer operational performance were identified through a literature survey. Second, the identified practices were prioritised and evaluated, based on improving operational performance by using a hybrid approach. The analytical hierarchy process (AHP) and the technique for order performance by similarity to ideal solution (TOPSIS) method were used such that AHP was applied to determine the relative weights of alternatives, and then the final ranking was obtained by conducting a TOPSIS analysis. Empirical data were collected from eight experts and 417 users at operational-level. The results suggest that lean management, total quality management, six sigma, and supply chain management practices rank 1st, 2nd, 3rd, and 4th respectively, signifying the practices with the most influence and making the greatest contribution. This strategic understanding will help researchers and practitioners to frame competitive strategies in order to pay more attention to those practices that have a greater influence on operational performance.
Exploratory data structure comparisons: three new visual tools based on principal component analysis

Datasets are sometimes divided into distinct subsets, e.g. due to multi-center sampling, or to variations in instruments, questionnaire item ordering or mode of administration, and the data analyst then needs to assess whether a joint analysis is meaningful. The Principal Component Analysis-based Data Structure Comparisons (PCADSC) tools are three new non-parametric, visual diagnostic tools for investigating differences in structure for two subsets of a dataset through covariance matrix comparisons by use of principal component analysis. The PCADCS tools are demonstrated in a data example using European Social Survey data on psychological well-being in three countries, Denmark, Sweden, and Bulgaria. The data structures are found to be different in Denmark and Bulgaria, and thus a comparison of for example mean psychological well-being scores is not meaningful. However, when comparing Denmark and Sweden, very similar data structures, and thus comparable concepts of well-being, are found. Therefore, inter-country comparisons are warranted for these countries.