Miracle-dz/UniFAR-FTUs huggingface dataset:
X-ray and neutron total scattering analysis of H y ·(Bi0.2Ca0.55Sr0.25)(Ag0.25Na0.75)Nb3O10·xH2O perovskite nanosheet booklets with stacking disorder

Ion-exchanged Aurivillius materials form perovskite nanosheet booklets wherein well-defined bi-periodic sheets, with ~11.5 Å thickness, exhibit extensive stacking disorder. The perovskite layer contents were defined initially using combined synchrotron X-ray and neutron Rietveld refinement of the parent Aurivillius structure. The structure of the subsequently ion-exchanged material, which is disordered in its stacking sequence, is analyzed using both pair distribution function (PDF) analysis and recursive method simulations of the scattered intensity. Combined X-ray and neutron PDF refinement of supercell stacking models demonstrates sensitivity of the PDF to both perpendicular and transverse stacking vector components. Further, hierarchical ensembles of stacking models weighted by a standard normal distribution are demonstrated to improve PDF fit over 1–25 Å. Recursive method simulations of the X-ray scattering profile demonstrate agreement between the real space stacking analysis and more conventional reciprocal space methods. The local structure of the perovskite sheet is demonstrated to relax only slightly from the Aurivillius structure after ion exchange.
Physical Modelling of the Effect on the Wave Field of the WaveCat Wave Energy Converter

The WaveCat is a moored Wave Energy Converter design which uses wave overtopping discharge into a variable v-shaped hull, to generate electricity through low head turbines. Physical model tests of WaveCat WEC were carried out to determine the device reflection, transmission, absorption and capture coefficients based on selected wave conditions. The model scale was 1:30, with hulls of 3 m in length, 0.4 m in height and a freeboard of 0.2 m. Wave gauges monitored the surface elevation at discrete points around the experimental area, and level sensors and flowmeters recorded the amount of water captured and released by the model. Random waves of significant wave height between 0.03 m and 0.12 m and peak wave periods of 0.91 s to 2.37 s at model scale were tested. The wedge angle of the device was set to 60°. A reflection analysis was carried out using a revised three probe method and spectral analysis of the surface elevation to determine the incident, reflected and transmitted energy. The results show that the reflection coefficient is highest (0.79) at low significant wave height and low peak wave period, the transmission coefficient is highest (0.98) at low significant wave height and high peak wave period, and absorption coefficient is highest (0.78) when significant wave height is high and peak wave period is low. The model also shows the highest Capture Width Ratio (0.015) at wavelengths on the order of model length. The results have particular implications for wave energy conversion prediction potential using this design of device.
Utilization efficiency of microwave energy for granular food in continuous drying: From propagation properties to technology parameters

Abstract To elucidate the utilization efficiency of microwave energy (UEME) of granular food, germinated brown rice (GBR) as a representational material, in a continuous microwave dryer, the propagation of microwave energy inside drying cavity and the effects of technology parameters on the energy consumption of GBR material layer were investigated by using numerical simulation and bench experiments. Results indicate that the transmission loss of microwave scatter from the waveguide ports decline with the increase of thickness of grain layer in drying cavity. The total absorption of microwave energy is achieved in the thickness of material processed exceeding critical depth of microwave penetration to reduce the scatter loss of microwave transmission. In microwave cavity, the dissipation of microwave energy inside material processed alters the modes and frequency of microwave propagation and resonance, and continuous movement and ventilation process may promote UEME due to the improvement of drying uniformity of GBR. High UEME may be achieved at the temperature of GBR material layer in range of 100 ± 5 °C till final moisture content of 14.5% (w.b.). The optimal technology parameters of microwave drying for GBR is obtained as microwave intensity of 2 W/g, ventilation velocity of 1.0–1.5 m/s, drying duration for per drying pass of 6 min, and the thickness of GBR layer of 8 mm to achieve high UEME. The research results provide significant insights to evaluate the electric field distribution and design industrial microwave dryer with high utilization efficiency of microwave energy.
Sea Ice Changes in the Pacific Sector of the Southern Ocean in Austral Autumn Closely Associated With the Negative Polarity of the South Pacific Oscillation

We present an explanation for the sea ice concentration trends in the Pacific sector of the Southern Ocean (PSSO) in austral autumn (April‐June) during 1979–2018. Sea ice has decreased in the Bellingshausen Sea and increased in the Ross Sea, concurrently with a negative trend in the South Pacific Oscillation (SPO). SPO statistically explains 43% of the sea ice concentration trend averaged over PSSO. Convective activities over East Africa and the southwestern Indian Ocean, the Interdecadal Pacific Oscillation (IPO), and extratropical processes excite a wavetrain that propagates from the Indian Ocean to the Southern Ocean and South America. The wavetrain contributes to the decrease of the autumn SPO index, which influences sea ice changes over PSSO. During the negative phase of SPO, an anomalous surface anticyclonic wind field over high‐latitude South Pacific Ocean generates anomalous sea ice concentrations via heat advection and wind forcing on ice drift.
A Monotonic Smeared Truss Model to Predict the Envelope Shear Stress—Shear Strain Curve for Reinforced Concrete Panel Elements under Cyclic Shear

In previous studies, a smeared truss model based on a refinement of the rotating-angle softened truss model (RA-STM) was proposed to predict the full response of structural concrete panel elements under in-plane monotonic loading. This model, called the “efficient RA-STM procedure”, was validated against the experimental results of reinforced and prestressed concrete panels, steel fiber concrete panels, and reinforced concrete panels externally strengthened with fiber-reinforced polymers. The model incorporates equilibrium and compatibility equations, as well as appropriate smeared constitutive laws of the materials. Besides, it incorporates an efficient algorithm for the calculation procedure to compute the solution points without using the classical trial-and-error technique, providing high numerical efficiency and stability. In this study, the efficient RA-STM procedure is adapted and checked against some experimental data related to reinforced concrete (RC) panels tested under in-plane cyclic shear until failure and found in the literature. Being a monotonic model, the predictions from the model are compared with the experimental envelopes of the hysteretic shear stress–shear strain loops. It is shown that the predictions for the shape (at least until the peak load is reached) and for key shear stresses (namely, cracking, yielding, and maximum shear stresses) of the envelope shear stress–shear strain curves are in reasonably good agreement with the experimental ones. From the obtained results, the efficient RA-STM procedure can be considered as a reliable model to predict some important features of the response of RC panels under cyclic shear, at least for a precheck analysis or predesign.
Et ve et ürünlerinin üretimi ve saklanmasında antimikrobiyal ambalajlama sistemlerinin kullanımı

Many microbiological, enzymatic, physicochemical, and biochemical changes occur during the production and storage of fresh and processed meat products, which tend to deteriorate more easily by their nature. Nevertheless, consumers mainly prefer cost-effective foods that have a longer shelf life and minimally modified natural properties, can be easily prepared, and in which fewer additives are used. For these reasons, the food packaging industry has turned towards developing new applications with different functions that are not found in traditional packaging methods, such as antimicrobial packaging systems, especially for the protection and improvement of food quality and safety. In this type of packaging, in addition to improving food safety and quality, the shelf life of the product is extended by slowing down the growth rate of microorganisms. Thus, the existing growth of microorganisms during the transportation and storage of the product is also prevented. Therefore, the preservatives taken into the human body with foods are reduced, and the negative effects on health are also avoided. In these systems, the application of antimicrobial food packaging components to the packaging material can be performed by the addition of antimicrobial agents into the polymer, coating polymer surfaces with antimicrobial agents, immobilizing antimicrobial agents on the polymer, and using polymers with antimicrobial properties. In this review, antimicrobial packaging and application methods were generall
Optimizing Chinese Story Generation Based on Multi-channel Word Embedding and Frequent Pattern Tree Structure

Much space remains for generating stories in the Chinese language. In this paper, we propose a novel approach to address this issue by multi-channel word embedding and effective control of the part-of-speech structure while producing sentences to imitate the writing style. The proposed approach consists of four parts: We first preprocess the sentences to label all sentences in the data set according to the format of , where , and represent the beginning, the end of the sentence, and the separation between sentences. We then propose a multi-channel method to embed words by integrating traditional vectorization methods including Word2vec, Fasttext, LexVec, and Glove to improve the information in the input data. We next optimize the model architecture to effectively control the process of sentence generation based on the BERT (Bidirectional encoder representations from) model. Finally, we perform some optimization on performance. For example, Softmax function in the model was optimized to reduce the search time during training. In addition, the GAN (generative adversarial network) architecture for the data set was revised to improve the training performance of the model. All sentences in the data set are built into a tree structure and the part-of-speech structure of the next sentence was generated through model generation based on FP-tree. The experimental results show that the proposed method can effectively control the generation of Chinese stories.
Differential Mode Noise Estimation and Filter Design for Interleaved Boost Power Factor Correction Converters

Interleaved power factor correction (PFC) is widely used circuit topology due to good efficiency and power density for single-switch boost PFC. As the differential mode (DM) electromagnetic interference (EMI) noise magnitude depends upon the input current ripple, this research details a comprehensive study of DM EMI filter design for interleaved boost PFC with the aim of minimizing the component size. It is also demonstrated that the different numbers of interleaved stages and switching frequency influence the filter attenuation requirement and, thus, the EMI filter size. First, an analytical model is derived on the basis of the Norton equivalent circuit model for the differential mode noises of interleaved boost PFC within the frequency range of 9–500 kHz. The derived model can help identify the proper phase shifting among the interleaved boost converters in order to minimize the considered differential mode noises at the filter design frequency. So, a novel phase-shift method is developed to get a minimized attenuation required by a filter in Band B. Further, a volume optimization of the required DM filter was introduced based on the calculated filter attenuation and volumetric component parameters. Based on the obtained results, unconventional and conventional phase shifts have demonstrated a good performance in decreasing the EMI filter volume in Band B and Band A, respectively. A 2-kW interleaved PFC case study is presented to verify the theoretical analyses and the impact of phase-shifting on EMI filter size.
The Conductive Cooling of Planetesimals With Temperature‐Dependent Properties

Modeling the planetary heat transport of small bodies in the early Solar System allows us to understand the geological context of meteorite samples. Conductive cooling in planetesimals is controlled by thermal conductivity, heat capacity, and density, which are functions of temperature (T). We investigate if the incorporation of the T‐dependence of thermal properties and the introduction of a nonlinear term to the heat equation could result in different interpretations of the origin of different classes of meteorites. We have developed a finite difference code to perform numerical models of a conductively cooling planetesimal with T‐dependent properties and find that including T‐dependence produces considerable differences in thermal history, and in turn the estimated timing and depth of meteorite genesis. We interrogate the effects of varying the input parameters to this model and explore the nonlinear T‐dependence of conductivity with simple linear functions. Then we apply non‐monotonic functions for conductivity, heat capacity, and density fitted to published experimental data. For a representative calculation of a 250 km radius pallasite parent body, T‐dependent properties delay the onset of core crystallization and dynamo activity by ∼40 Myr, approximately equivalent to increasing the planetary radius by 10%, and extend core crystallization by ∼3 Myr. This affects the range of planetesimal radii and core sizes for the pallasite parent body that are compatible with paleomagnetic evidence. This approach can also be used to model the T‐evolution of other differentiated minor planets and primitive meteorite parent bodies and constrain the formation of associated meteorite samples.
Augmented Analytics and Modern Business Intelligence Adoption to Maximize Business Value

The business success is critical for any organization irrespective of its size. Understanding business value and advanced technology capabilities in Business Intelligence (BI) solutions for analysis and decision making is the need of every management, researchers and analysts. Data is available at every corner, at every platform and it is being produced all the way using digital equipment. These complex data sets for analysis and decision-making can be used on various platforms and are more accessible than ever to find insights and explanations. There is an abundance of datasets and data analysts, but organizations are still unable to leverage its potential to the fullest and this perhaps is the failure of most data analytics initiatives. This paper covers the need for Augmented Analytics adoption in companies to maximize business value with respect to added advanced analytics capabilities in BI Tools for effective, accurate and timely decision making, and business analysis.
The Role of Fluid Pressure‐Induced Aseismic Slip in Earthquake Cycle Modulation

The evolving state of fault stress during and after the perturbation of fluid pressure gives rise to an intriguing interplay of seismic and aseismic slip on the fault. A better understanding of the possible role of fluids in the triggering mechanism of seismicity is pivotal to effective seismic hazard mitigation, particularly in the context of induced seismicity. Through numerical modeling, we investigate the effect of pore pressure perturbations on the spatio‐temporal evolution of fault slip and the modulation of earthquake cycles. Pressure perturbations are imposed at different magnitudes and different times during a selected interseismic period. Results show a wide range of aseismic responses which can lead to both time advancement and delay of subsequent earthquakes. Specifically, even pressure perturbation <5% of the average event stress drop can trigger aseismic slip that leads to considerable time delay in the next earthquake even when perturbation occurs late in the interseismic period. We find that earthquakes that are delayed in time are associated with large aseismic moment release. Our study highlights the importance of close monitoring of aseismic fault slip in regions prone to the influence of pore fluids and provides physical insights into identifying critical aseismic responses associated with certain triggering outcomes.
On‐line modelling and planning for urban traffic control

Urban Traffic Control is a key problem for most big cities. Current approaches to handle the city traffic rely on controlling traffic lights. The systems in operation range from static control of traffic light phases to adaptive systems based on numeric models and traffic sensors. Recently, some planning‐based approaches have also been proposed. These approaches work at a higher level of abstraction, but have been found to work well if complemented by low‐level systems. We have identified two main difficulties for the wide use of planning techniques in this domain: generating the control models is a difficult task; and some algorithms scale poorly. In this paper we present Automated Planning for Traffic Control (APTC), a control system based on Automated Planning, that successfully overcomes these two problems. It combines techniques that continuously: learn an accurate planning model; and also divide the city for distributed reasoning in order to scale to large city networks. Experimental results show that APTC outperforms static approaches as well as other planning‐based systems. We also show that the combination of both approaches improves compared with using only one of them.
Geological Heritage of Syros Island, Cyclades Complex, Greece: An Assessment and Geotourism Perspectives

Syros Island, Cyclades complex, central Aegean Sea, Greece, is a prime locality for the study of processes active in deep levels of orogens and is world famous for its exceptionally well preserved glaucophane schist-to eclogite-facies lithologies. Glaucophane schists and eclogites are witnesses of one of the fundamental tectonic processes operating on planet Earth. Results of geological research on Syros have contributed a lot to our present understanding of why and how these processes work that make oceans disappear, how mountain ranges can start to form, how magma chambers form to feed volcanoes, how subduction mechanisms can trigger earthquakes and lead to tsunamis, and a series of other spectacular or very impressive phenomena which have been observed and studied throughout the earth’s window offered in that particular place of the world. The description, interpretation, and evaluation of the important geological heritage of Syros, in combination with a SWOT analysis, showed the geotourism potential of the region. The results of this paper are intended to constitute a valuable tool for enhancing and raising awareness of the geological heritage of the island of Syros, regarding to the added value activities to be developed on a sustainable basis.
Condition monitoring systems: a systematic literature review on machine-learning methods improving offshore-wind turbine operational management

ABSTRACT Information is key. Offshore wind farms are installed with supervisory control and data acquisition systems (SCADA) gathering valuable information. Determining the precise condition of an asset is essential on achieving the expected operational lifetime and efficiency. Equipment fault detection is necessary to achieve this. This paper presents a systematic literature review of machine learning methods applied to condition monitoring systems, using both vibration information and SCADA data together. Starting with conventional methods using vibration models, such as Fast-Fourier transforms to five prominent supervised learning regression models; Artificial neural network, support vector regression, Bayesian network, random forest and K-nearest neighbour. This review specifically looks at how conventional vibration data can be combined with SCADA data to determine the assets condition.
Potentiality of tree variables as predictors in pavement roughness progression rate modelling

ABSTRACT This paper presents statistical evidence of roadside vegetation’s contribution to pavement roughness progression rates. Detailed statistical and regression analysis of the roadside vegetation data collected via satellite imageries and road roughness data collected via high speed road profiler was performed. Elaborative investigation on interaction between roadside vegetation and waveband roughness progression has provided a clear indication of tree variable’s contribution on road deterioration. Statistical parameters such as moderate Pearson correlation coefficient (r) values, low mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE) values, high Willmott’s index of agreement (d) were obtained for training and validation datasets, that depicted the potentiality of tree variables as predictors in pavement roughness progression rate modelling. Statistical evidence showed that effect of trees on road deterioration was more noticeable on long wavelength roughness progression rates. This can be justified via prevailing soil moisture interaction in expansive soil deposits subjected to moisture withdrawal of deciduous trees in arid climate conditions. Overall, the findings of this paper exemplify on the necessity of considering the presence of roadside vegetation in road deterioration analysis, and suggesting the scope of improvement for prediction performance.
Primary frequency regulation support through deloaded offshore renewable power generators with HVDC‐link

Grid operation becomes a challenging task due to the high penetration of uncontrolled offshore renewable power generators into the mainland system through HVDC-link system. As a result, system frequency may quickly go outside the acceptable range under severe frequency events. This paper proposes a coordinated control strategy for linearized models of deloaded offshore renewable power generators with HVDC-link to make contributions in the mainland system during depressed frequency conditions to address the frequency regulation issue. Linearized models are used to obtain the power output from deloaded ORPG by adjusting droop value in proportional to frequency deviation and minimizing the frequency deviation of the mainland system. Inertia control scheme based on utilizing the different capacitors of HVDC-link is proposed to further improve frequency regulation. Adding inertia from HVDC-link helps to minimize the rate of change of frequency deviation. Finally, to improve both frequency deviation and rate of change of frequency deviation, case studies of offshore renewable power generators linking with HVDC in view of abrupt load deviations have been effectively shown on system model to validate the pro-ﬁciency of control schemes in MATLAB/SIMULINK R .