Miracle-dz/UniFAR-FTUs huggingface dataset:
The Power of Parallelism in Membrane Computing

: Maximal parallelism has been an important feature of membrane systems from the beginning, i.e., only non-extendable multisets of rules are applied to the underlying conﬁguration. During the last two decades many new variants of parallel derivation modes have been investigated, for example, non-extendable sets of rules are used instead of non-extendable multisets of rules. In many cases, computational completeness can be obtained. Recently, derivation modes applying multisets of rules affecting or generating the maximal number of objects or yielding the maximal difference between the objects in the current and the derived conﬁguration have been shown to allow for computational completeness even when using only very restricted variants of rules.
Bayesian-Inference-based Inverse Estimation of Small Angle Scattering

As an application of machine-learning algorithms, we improved SAS (Small Angle Scattering), which is common experiment in material science, by developing a Bayesian inference and deriving the confidence-level contour. In the SAS experiment, the grain-size of the sample material has to be estimated from the distribution of the scattered beam. A stochastic model and maximum-likelihood inference with EM-algorithm are often used, but the result is noisy due to data noise. With the proposed method, the grain-size distribution can be estimated similarly to the maximum-likelihood inference method and the confidence levels can be visualized. Thus, researchers can determine estimation reliability and decide whether there are sufficient data. Simulation-generated datasets were processed with the proposed method to evaluate its effectiveness, and it was confirmed that it is useful for automatic SAS data analysis.
Anomaly Detection in Text Documents using HTM Networks

: Anomalies in texts can be caused mainly by various interventions in texts, such as, by supplementing parts of a text from different authors. Such a type of anomalies can disrupt text that would otherwise be consistent. In order to ﬁnd anomalies we have combined multiple algorithms, including a non-traditional neural network model - the Hierarchical Temporal Memory (HTM) network. HTM networks are spatiotemporal predictors based on the neocortex that combine the ability to retain memories of time sequences like recurrent neural networks with the spatial representations of convolutional neural networks. To represent the text inputs for the HTM algortihm we use semantic folding, which encodes text differently than other embedding method: as a collection of contexts they occur in. Alongside such a predictor we use numerous other, more well known metrics, and combine them into a two step algorithm. In the ﬁrst step we ﬁnd the division points between the anomalous and non-anomalous parts. In the second step we determine which sections located between two division points are actually anomalous. The algorithm was tested on 40 benchmark texts from PAN plagiarism corpus PAN-PC-11 and the results of determining whether the text contains anomalies or not are 100 %. The percentage of fully detected anomalies is 70.15 %.
Machine Learning Application for Permeability Estimation of Three-Dimensional Rock Images

Estimation of permeability in porous media is fundamental to understanding coupled multi-physics processes critical to various geoscience and environmental applications. Recent emerging machine learning methods with physics-based constraints and/or physical properties can provide a new means to improve computational efficiency while improving machine learning-based prediction by accounting for physical information during training. Here we first used three-dimensional (3D) real rock images to estimate permeability of fractured and porous media using 3D convolutional neural networks (CNNs) coupled with physics-informed pore topology characteristics (e.g., porosity, surface area, connectivity) during the training stage. Training data of permeability were generated using lattice Boltzmann simulations of segmented real rock 3D images. Our preliminary results show that neural network architecture and usage of physical properties strongly impact the accuracy of permeability predictions. In the future we can adjust our methodology to other rock types by choosing the appropriate architecture and proper physical properties, and optimizing the hyperparameters.
S1759078720001567jra 921..936

In this paper, a stacked microstrip patch antenna with polarization reconfigurable property has been proposed for worldwide interoperability for microwave access (WiMAX) application. The proposed antenna has two substrate layers: upper and lower layers with two radiating patches connected with the coaxial probe. Without the upper layer the lower square-shaped substrate layer having regular hexagonal radiating patch with probe fed acts as a linear polarized antenna with impedance bandwidth for (S11≤−10 dB) is 370MHz 10.56% (3.32–3.69 GHz) cover WiMAX (3.4–3.69 GHz) application band. The hexagonal radiating patch is perturbed with an optimum rectangular slot to enhance the impedance bandwidth of the antenna. The lower substrate layer having hexagonal patch with the same probe position is stacked with the upper square-shaped substrate layer with same sized square patch and the upper patch soldered with the coaxial probe. The overall stacked antenna generates a circularly polarized band when the opposite corner of the top square radiating patch of the upper layer is truncated with optimum size. In order to generate another circularly polarized band and to improve the input impedance matching of the stacked antenna, the top radiating patch is perturbed with two slots and a slit. The stacked circularly polarized antenna generates impedance bandwidth of 12.75% (3.23–3.67 GHz) for (S11≤−10 dB) with two circularly polarized bands (3.34–3.37 GHz) and (3.66–3.70 GHz) as per (axial ratio≤ 3 dB) for WiMAX application. Therefore, the proposed antenna can be used as linearly polarized or dual band circularly polarized according to requirement.
Extraction Methods for Pipeline Weld Defect Features

This paper introduced weld defect features based on a digital X-ray image using texture and geometric feature parameters. An improved complete local ternary pattern (CLTP) algorithm was proposed according to these parameters to extract the texture features from the image, while the geometric feature values were obtained using the contour tracking method. Furthermore, the practicability of this method was demonstrated with an example.
Influence of bentonite as partial replacement of cement in basalt fiber concrete

Concrete is commonly accepted construction material in the construction field. Concrete is second in terms of per-capita consumption in the world that is about approximately 500 kilograms. This leads to increase in consumption of Ordinary Portland Cement(OPC). The environment is at risk in terms of damage caused by Carbon dioxide(CO2) emission during OPC manufacturing process. Hence this is the hour to reduce consumption of OPC by partial replacement. The present study focuses on finding of optimum percentage substitution of OPCwith bentonite. As the concrete is weak in tension, basalt fiber is used in concrete to add the tensile properties to concrete. The investigation is carried out using cube, cylinders, and beams specimens with varying percentages of bentonite and basalt fiber by cement weight. The workability and mechanical properties like slump cone, compression, split tensile, flexure strengthis measuredfor different combinations of fiber and bentonitein conventional and trial mix concrete.Specimens are casted, cured, and tested for 3, 7 and 28 days as per Indian standards. The test results of conventional concrete and trial mix concrete are compared,and it is observed that 10% bentonite replacement and 1.5% basalt fiber replacement given optimum results.From the study benefit of bentonite as partial replacement material to cementis recommended.
Application of Structural Equation Model in Electric Vehicles User Evaluation of Charging Infrastructure Determines

On the basis of the user satisfaction questionnaire survey of charging infrastructure, a user satisfaction evaluation model of charging infrastructure based on structural model is constructed. According to the calculated weights of the first-and second-level indicators, the overall satisfaction score is calculated, and the optimization direction for the charging infrastructure is proposed. The results show that users’ satisfaction with the charging infrastructure is acceptable, and the development of all aspects of the charging infrastructure is relatively balanced. Besides, the hardware facilities of the charging station are the priority optimization indicators in the future.
Qnet: Convolutional Network and Semantic segmentation with Attention for Computer Cells Image Processing Technology

The semantic segmentation of tumor cells in glioma is for clinical diagnosis and judgment of tumor location. However, there are many problems with this task in testing, such as high cost, excessive expenditure of human resources, and insufficient detection accuracy. The data extracted in brain CT can accurately segment and often fail to meet the requirements. For further fine segmentation of tumor cell positions, we propose a new semantic segmentation method: QNet. Through network training, the location of active tumors can be segmented more accurately, which is more helpful for doctors to judge the location of tumors. Evaluate our model and classic semantic segmentation model on 2420 brain CT data sets. The experimental results show that the newly proposed QNet can realize the detailed recognition of the cavity in the tumor, the PA is as high as 0.975, and the CPA is as high as [0.986,0.507], mlou is as high as 0.698, which is better than other classic semantic segmentation models. This model can be used to segment the tumor more accurately, and meets.
Research on Fault early Warning Technology of Wind Turbine Main Bearing by Stacked Auto Encoder

With the rise of new energy power generation technology, the installed capacity of wind turbines continues to increase. At the same time, the potential faults of wind turbines have also increased with the increase of wind turbines. Therefore, early prediction of potential faults of wind turbines and ensuring the safe and stable operation of wind turbines is of great significance for improving power generation efficiency and reducing maintenance costs. In order to realize the fault early warning of the main bearing of the wind turbine, an early warning method of the main bearing of the wind turbine based on Stacked Auto encoder (SAE) is proposed.
Antifriction effect of 316L stainless steel textured surface with superhydrophilic properties in brain tissue insertion

To reduce the tissue damage caused by the cannula electrodes during the operation of deep brain stimulation, laser matching micro texture on the surface of the electrodes was proposed to reduce the friction force. Different grooves and pit arrays were fabricated on the 316L stainless steel surface using an ultra-violet nanosecond laser. The wettability of textured surfaces with different morphologies was measured by distilled water and artificial cerebrospinal fluid. Insertion experiments were carried out on porcine brains using textured steel needles. The results showed that textured steel needles have an obvious antifriction effect under the condition of the lubricant. The elliptical pit texture has the best effect of reducing friction, and the friction force can be reduced by 37.6% on average.
An Air Network Risk Control Method Based on Airport Location and Throughput*

An aviation network risk control measure considering airport location and throughput is proposed to reduce the risk loss. Firstly, the relationship between cost input and risk residual rate is determined, and then the importance of airport node is determined by combining kernel degree and importance evaluation matrix. Then, based on the linear programming method, the minimum residual risk loss is used as the objective function to obtain the residual risk loss minimization deployment scheme, and the minimum control cost is taken as the objective function by controlling the cost minimization operation. Comparative experiments show that ALTRCM method has great advantages in risk control efficiency and cost control.
Robust Speech Recognition Model Using Multi-Source Federal Learning after Distillation and Deep Edge Intelligence

In order to further explore and solve the problem of distributed training edge intelligent application in edge devices close to the data side, a joint training method of multi-source federated learning is proposed for the robust speech recognition model. The joint training is performed directly on the edge computing device close to the data supply side. Under the open source Chinese speech recognition data set, the recognition accuracy is 95%. Compared with federated learning, there is only 2% performance reduction, but the communication load is reduced by 90%.
Spinodal Decomposition in Nanoparticles - Experiments and Simulation

For revealing internal atomic processes in bimetallic nanoparticles, individual hemispherical Ag-Cu alloy particles were grown by direct current (DC) magnetron sputtering. Phase separation of particles was found to be size- and composition-dependent. Particles smaller than 5 nm in diameter remained as a solid solution of the components for all tested compositions (15-80 at.% Ag). At 15 and 30 at. % Ag compositions phase separation was observed only for particles above 5 nm in diameter. Computer simulations by Stochastic Kinetic Mean Field model reproduced the size-dependence of the decomposition and the internal structure of two-phase particles. Theoretical explanation is given for the composition dependence of the phase separation tendency.
Atomistic Insight into the Correlation among Oxygen Vacancies, Protonic Defects, and the Acceptor Dopants in Sc-Doped BaZrO3 Using First-Principles Calculations

It is necessary to elucidate the correlation between hydration properties and proton distributions in electrolytes as proton conductors to allow for further improvements in solid oxide fuel cells. In this study, the hydration properties of Sc-doped BaZrO3 (BZO) were investigated by means of density functional theory calculations capable of taking both the local structural configurations and the hydration levels into account. At a low hydration level, Sc-doped BZOs gained a negatively larger hydration energy, that is, more exothermic reaction, by incorporating an H2O molecule with unstable oxygen vacancies adjacent to Zr. At a high hydration level, the configuration of ScO4(OH)2, which has a positive net charge as a local structure, was formed with a smaller but negative hydration energy by the reaction of H2O with oxygen vacancies adjacent to Sc. This indicates that the stability of the whole system, and not only the local electrostatic interactions of point defects, needs to be taken into account when co.
Investigation of the influence of the composition on mechanical properties poly(glycolide-DL-lactide)

In this paper we describe the creation of films from poly (glycolide-DL-lactide). Studied the mechanical properties of developed polymer films of poly (glycolide-DL-lactide). The effect of the molecular weight of poly (glycolide-DL-lactide) on the mechanical properties of the resulting polymer films is shown. The dependence of the mechanical properties of poly (glycolide-DL-lactide) films on the polymer concentration in chloroform was studied. The possibility of creating biodegradable films with specified mechanical properties is shown.
A vario-scale approach that improves integration of point clouds with different point densities

Point clouds are becoming one of the most common ways to represent geographical data. The scale of acquisition of point clouds is growing steadily. However, point clouds are often very large in storage size and require computationally intensive operations. The integration of point clouds nowadays still face a lot of challenges. This project focuses on one of these challenges; integrating point clouds of different scales and granularity. Solving this challenge enables appealing visualisation, usability for low and high computation powers and geometrical consistency for analysis. The following question is researched: 'To what extent can a vario-scale approach improve integration of point clouds with varying point densities? '. A data model is created that uses importance as an additional dimension. This dimension contains an importance value which is calculated using two methods. Firstly random assignment of values to the points and secondly exact computed values. To compute this value the smallest distances to its nearest neighbour is assigned as importance value. A web application shows the results. Both random and exact methods show an exponential decay in distribution of the importance value. Though the random methods run much faster, the exact methods preserve much more edges and other details.
NIR-Absorbing Dye Functionalized Supramolecular Vesicles for Chemo-photothermal Synergistic Therapy

Developing multifunctional supramolecular nanoplatforms for effective tumor therapy is a challenging task. In this contribution, a NIR-absorbing perylene diimide dye G has been prepared, which not only acted as a photothermal agent, but also served as a guest. Multifunctional supramolecular vesicles were efficiently constructed by the recognition of dye G and water-soluble pillar[5]arene, which showed high-loading capacity for hydrophobic chemotherapy drug doxorubicin. What’s more, the resulting drug-loaded vesicles had high stability in simulated normal physiological condition but showed rapid drug release in the acidic microenvironment. Additionally, the drug-loaded vesicles exhibited more remarkable antitumor efficacy than chemotherapy or photothermal treatment alone through chemo-photothermal synergistic therapy. Furthermore, such supramolecular drug nanocarriers could efficiently get inside the tumor cells mainly via endocytosis to obtain excellent accumulation of drug in tumor sites. Overall, this s.
Preparation and characterization of electrically semi-conductive polyfuran-coated poly(ethylene terephthalate) fibers

Abstract One of the most important textile materials, poly(ethylene terephthalate) (PET) fiber, was coated with a semi-conductive polyfuran (PFu) by in situ oxidative polymerization using FeCl3 oxidant in solvent mixture of acetonitrile–chloroform. The effects of polymerization conditions such as volume ratios of acetonitrile/chloroform, monomer concentration, and oxidant/monomer mol ratio were investigated on PFu content (%) of the composites. It was observed that pretreatment of PET in dichloromethane increased PFu content and its coating continuity before polymerization. The highest PFu content (12.0%) was obtained using FeCl3/furan mol ratios of 3.5 in acetonitrile/chloroform mixture (5/1). The density values of the composites with different PFu contents were measured. Composite fibers were also subjected to doping processes with HCl and I2 vapors, separately, and it was observed that the surface resistivity of PFu/PET (1012 Ω/cm2) reached to 53 Ω/cm2 after doping with I2. The structural, thermal, and morphological characterization was performed with FTIR, XRD, TGA, and SEM, respectively.
GENİŞLEMİŞ SPEKTRUMLU BETA-LAKTAMAZ POZİTİF ESCHERICHIA COLI İLE OLUŞAN KOMPLİKE OLMAYAN ÜRİNER SİSTEM İNFEKSİYONLARININ TEDAVİSİNDE ORAL ANTİBİYOTİKLER KARBAPENEMLERE ALTERNATİF OLABİLİR Mİ?

Üriner sistem infeksiyonları etkenleri arasında genişlemiş spektrumlu beta-laktamaz (GSBL) üreten Escherichia coli izolatlarının artışı ve antimikrobiyal direnç önemli bir sorundur. Bu nedenle tedavide zorluklar gözlenmektedir. Karbapenemler, GSBL üreten E.coli suşlarının tedavisinde etkin bir seçenek olmakla beraber, çok geniş spektrum, yüksek maliyet, intravenöz/ intramusküler kullanım, hasta yatışı gerekliliği gibi özelliklere sahiptir. Komplike olmayan üriner infeksiyonların tedavisinde daha dar spektrumlu antibiyotiklerin yeri tartışılmaktadır. Çalışmamızda; üriner GSBL pozitif E.coli suşlarında başlıca nitrofurantoin, fosfomisin ve alternatif oral seçeneklerden siprofloksasin ve trimetoprim/sülfametoksazol (SMX/TMP) duyarlılığı saptanması amaçlanmıştır. İdrar kültürlerinde üreyen E.coli suşları konvansiyonel yöntemlerle identifiye edilmiştir. Antibiyotik duyarlılıkları Clinical and Laboratory Standarts Institute (CLSI) standartlarına göre belirlenmiştir. İzolatların GSBL üretimi çift disk sinerji testi ile çalışılmıştır. Duyarlılık oranları şu şekildedir: fosfomisin % 96, nitrofurantoin % 84, siprofloksasin % 24 ve SMX/TMP % 22. Üriner infeksiyonlarda özellikle nitrofurantoin ve fosfomisinin etkinliği bilinmektedir. Çalışmamızda da, üriner infeksiyon etkeni GSBL pozitif E.coli izolatlarında fosfomisin ve nitrofurantoine yüksek duyarlılık oranları saptanmıştır. Komplike olmayan üriner sistem infeksiyonlarının tedavisinde karbapenemlere alternatif olarak kullanılmasının kolay, noninvazif, maliyet etkin ve karbapenem direnci gelişiminin önlenmesi açısından yararlı olabileceği sonucuna varılmıştır.
Transparency helps in balancing the environment, society and economy: lessons from the world’s largest public works program​

Sustainable development depends on the complex set of interactions between the natural environment, the society we live and economic conditions. The relationship between humans and the environment is like 'one will give and other will take', during which equilibrium may get distracted. Economics leverages the growth potential of the society and society is influenced by the natural environment. To maintain the equilibrium between these three pillars of sustainable development there is a need to link them. Transparency during the execution of large-scale projects plays a pivotal role in achieving sustainable development and enables the balance between the environment, society, and economy. In recent times, the governments of many countries have adopted programs for improving the living standards, food security and improved nutrition, health, clean water and sanitation, education, and other aspects of sustainable development goals. This article reports the transparency methods that are implemented for MGNREGA project and articulates the role of transparency in linking between the three dimensions of sustainable development: environment, society, and economics. The paper emphasizes that the mechanism of transparency should reside in all sides of
Safe and high-rate supercapacitors based on an “acetonitrile/water in salt” hybrid electrolyte

The properties of the electrolyte are the dominant factors for the overall performance and safety of electrical energy storage devices. Highly concentrated “water in salt” (WIS) electrolytes are inherently non-flammable, moisture-tolerant, and exhibit wide electrochemical stability windows, making them promising electrolytes for high-performance energy storage devices. However, WIS electrolytes possess intrinsically low conductivity and high viscosity, which usually impair the high-rate performance of many energy storage devices, especially supercapacitors (SCs). Additionally, the inevitable salt precipitation at low temperature for WIS electrolytes narrows down their applicable temperature range. Here, we introduce acetonitrile as a co-solvent to a typical “water in salt” electrolyte to formulate an “acetonitrile/water in salt” (AWIS) hybrid electrolyte that provides significantly improved conductivity, reduced viscosity and an expanded applicable temperature range while maintaining the aforementioned important physicochemical properties of WIS electrolytes. Using the AWIS electrolyte for a model SC remarkably enhances the high-rate performance, accompanied by a 2.4 times capacitance increase at 10 A g−1 with respect to the original WIS electrolyte. This AWIS electrolyte also enables a stable long-term cycling capability of the model SC for over 14 000 cycles at a high operation voltage of 2.2 V.