Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetic Fields in Massive Star-forming Regions (MagMaR). I. Linear Polarized Imaging of the Ultracompact H ii Region G5.89–0.39

We report 1.2 mm polarized continuum emission observations carried out with the Atacama Large Millimeter/submillimeter Array toward the high-mass star formation region G5.89–0.39. The observations show a prominent 0.2 pc north–south filamentary structure. The ultracompact H ii region in G5.89–0.39 breaks the filament into two pieces. Its millimeter emission shows a dusty belt with a mass of 55–115 M ⊙ and 4500 au in radius, surrounding an inner part comprising mostly ionized gas, with dust emission only accounting for about 30% of the total millimeter emission. We also found a lattice of convex arches that may be produced by dragged dust and gas from the explosive dispersal event involving the O5 Feldt’s star. The north–south filament has a mass between 300 and 600 M ⊙ and harbors a cluster of about 20 mm envelopes with a median size and mass of 1700 au and 1.5 M ⊙, respectively, some of which are already forming protostars. We interpret the polarized emission in the filament as mainly coming from magnetically aligned dust grains. The polarization fraction is ∼4.4% in the filaments and 2.1% at the shell. The magnetic fields are along the North Filament and perpendicular to the South Filament. In the Central Shell, the magnetic fields are roughly radial in a ring surrounding the dusty belt between 4500 and 7500 au, similar to the pattern recently found in the surroundings of Orion BN/KL. This may be an independent observational signpost of explosive dispersal outflows and should be further investigated in other regions.
Modifying mechanical properties of silicon dioxide using porous graphene: molecular dynamics simulations

Graphene or other 2D materials are often used as agents to reinforce engineering structures because they possess extremely high mechanical strength and structural flexibility. This is however not cost effective and the reported enhancement is often limited although the mechanical properties of graphene is often several orders higher than cements or concretes. Defective graphene is mechanically weaker than pristine graphene but stronger than engineering structures, moreover, it is cheaper because the synthesis condition is low. In this work we perform systematic molecular dynamics simulations to evaluate the effect of porous graphene (PG), a type of defective graphene, on reinforcing mechanical properties of silicon dioxide (SiO2) which is the key components of engineering structures. Our results show that PG is mechanically weaker than pristine graphene but stronger than SiO2, therefore, with certain amount of PG encapsulation into SiO2, the mechanical properties can be improved under tensile, shear and compressive loadings, although not as significant as the effective of pristine graphene. The modification mechanism is found to depend both on the intrinsic mechanical properties of GP and the interface induced surface stress redistribution in SiO2. The effects of defect concentration, volume fraction, loading methods and interface roughness are found to be influential on the reinforcing effect. Our findings are expected to offer new strategies for rational design of low-cost but high-strength engineering composite structures.
Incorporating Domain Knowledge into Text Classification Diagnosis in Customer Service Dialogue Field

The customer service dialogue process is an important way for consumers to communicate with manufacturers. In order to enhance the consumer experience as well as to assist the staff, we build a knowledge base that can categorize consumer questions and provide suitable answers. However, due to labeling deviations, there are some errors in the knowledge base. So we propose a domain knowledge-based text classification diagnosis method, which innovatively transforms the question and answer task into the text classification task. We use an ERNIE-based structure to match consumer questions with multivariate groups of answers from the knowledge base, judged by similarity. Also for incorrectly matched pairs, our method provides a list of suitable candidates for selection. Compared with other baselines, our model achieves competitive results. At the same time, good results are obtained on cross-province data, proving that our method has good scalability.
Simulation and Analysis of P-P-N 10T SRAM cell for IoT based devices

Ultra low power integrated circuits got the major attention due to its lower power dissipation in the era of Internet of Things (IoT) based smarter devices. In this context, a P-P-N based 10T SRAM cell has been designed and simulated on cadence virtuoso tool with GPDK 45nm technology node at supply voltage ranges from 0.6V to 1V. The various parameters such as static noise margin, read/write power, read/write delay of the 10T SRAM cell are determined out and compared with other considered topologies. It is interesting to notice that 10T SRAM cell shows commendable improvement in read static noise margin (RSNM) i.e. 36% and 46% as compared to conventional 6T and differential 8T SRAM cells respectively. The 10T SRAM cell also has reduction in read power of 38.52% and 38% as compared to conventional 6T and differential 8T SRAM cells respectively. The read delay of P-P-N based 10T SRAM cell is improved by 40% with compared to conventional 6T SRAM cell.
Comparison of Battery Models for Battery Energy Storage System Development

Battery Energy Storage System (BESS) can be utilized in various ways to improve the reliability, durability, and efficiency of grid operations. With the advancement of battery technology and rapid cost reduction, BESS has become very promising. An accurate BESS model in simulation platform is very important to design an efficient BESS-connected powered system. Battery as one of the main components that govern BESS perfomance need to be modeled. There are many battery models that has been developed. In this paper, some of battery models will be studied and the comparison of different battery models is also presented.
Numerical Investigation of the Flow Field and Aerodynamic Load on Impellers Under Radial Inlet Guide Vanes With Trailing Edge Blowing in Centrifugal Compressor

The radial inlet is a typical upstream component which is widely used in multiple-stage centrifugal compressors or blowers. Adding the guide vane in the radial inlet could improve the flow field along circumference distribution and increase the efficiency of the compressor as well. However, the guide vane in the radial inlet generates the wake which causes the Rotor-Stator-Interaction (RSI) and further raises the issue of impeller fatigue failure. In order to compensate the wake effect caused by the guide vane, the active control of trailing edge blowing (TEB) is adopted. Based on Computational Fluid Dynamics (CFD) simulation, the radial inlets with unevenly distributed guide vanes (UGV) are considered. This study investigates the guide vane wake in a radial inlet with or without TEB, and aims to figure out the flow phenomenon in radial inlet and the aerodynamic load on the downstream impellers. The simulation results show that the trailing edge blowing has effect on the compressor performance and reduces the wake intensity. By conducting unsteady simulations, the aerodynamic load on the impeller’s leading edge is obtained for the radial inlets with or without TEB. The dominant frequency and the pulse amplitude are obtained by Fast Fourier Transforms (FFT). Compared with the UGV model, the TEB shows lower excitation at the harmonics of the impeller passing frequency, and has little influence on the amplitude at the impeller rotation frequency. It means the TEB could improve. the safety of the impeller under radial inlet guide vane condition.
A Novel Method for Distribution Transformer Short-circuit Test

Short-circuit test of distribution transformer is an important test to check out the short-circuit resistance of distribution transformer. This paper presents a novel short-circuit test method of distribution transformer based on energy storage short-circuit test device, which can complete the short-circuit field test of distribution transformer. The basic principle of the device is introduced, and the feasibility of the method is verified by simulation and experiment.
Time Varied Morphology Controllable Fabrication of NiS Nanosheets Structured Thin Film and its Application as a Counter Electrode for QDSSC

A novel strategy has been successfully developed for highly efficient nanosheet-structured NiS counter electrodes. The NiS was deposited on FTO substrate with different deposition times using the simple and cost-effective chemical bath deposition technique. The NiS CEs were used to grow high quality thin films containing nanoparticles, nanosheets, or nanorods. The nanosheet-structured NiS CE in QDSSCs under one-sun illumination (AM 1.5, 100 Mw cm–2) yielded a high short circuit current density (Jsc) of 13.53 mA cm–2, open circuit voltage (Voc) of 0.570 V, fill factor (FF) of 0.450, and power conversion efficiency (η) of 3.47%. These values are much higher than those of the Pt CE (Jsc = 7.85 mA cm–2, Voc = 0.611, FF = 0.243, and η = 1.170%). The NiS was strongly adhered on the FTO substrate by acetic acid which acts as stabilizer and strong reagent in this one step preparation. The performance of NiS CE was improved by the surface morphology, which enable rapid electron transport and a lower electron recom.
Implementation Of STMCpE Textbooks On Students’ Problem Solving Skill

Problem solving is a higher level of skill than conceptual understanding. Problem solving skills require a logical process in solving a problem. Problem solving is a higher level of skill than the mastery of concepts that requires a logical process in solving a problem. The purpose of this study was to determine the effect of STMCpE textbook implementation on students’ problem solving skills. This research is a quasi-experimental design with nonequivalent control group design. Data collection was obtained from the results of problem solving skills tests conducted in the experimental class and the control class before and after learning. Pretest is used as initial data of student ability and posttest data is used as data to test the effect of learning. Test the effect of learning using ANCOVA. The result showed that the problem solving skills of students who studied with STMCPE textbooks was higher than students with conventional learning with a significance value of 0.000 <0.050. The percentage of effect of the application of the STMCpE textbook was 50.4%. This shows that the problem solving skills of students who learn with STMCpE textbooks are better than students who study using school textbooks.
Distribution and mitigation efforts for microplastic pollution in Kendari bay as the mainstay coastal tourism area of Southeast Sulawesi

Marine waste, especially plastic waste, is a complex problem faced by areas close to the beach/coastal area. This problem also occurs in Kendari Bay which has a unique character because of its position stretching in the middle of Kendari City, its shape is like a horse’s footprint and as a mainstay tourist attraction in Southeast Sulawesi. This study aims to analyze the distribution of microplastic abundance in sediments and marine biota, analyze water quality in the microplastic abundance distribution area, and determine efforts to mitigate pollution of plastic waste in Kendari Bay. A sampling of sediments and biota from 2 stations (settlement and port) using paralon pipes at depths of 0-5 cm and 5-10 cm. Seawater quality parameters are parameters related to solid waste pollution based on UNESCO-WHO-UNEP and the method for water quality analysis refers to APHA-AWWA-WEF. The results showed that the types of microplastics found were film, fragment, and fiber. The average abundance of microplastics in Station I (Mata Village, Kendari City) and Station II (Kendari Archipelago Harbor) at a depth of 0-5 cm range from 426.82-424.92 particles/kg. This value is higher than the microplastic abundance at 5-10 cm depth, which is between 276.50 to 363.74 particles/kg. The average abundance of film-type microplastics and fragments at 0-5 cm depth was higher at Station I (203.75 particles/kg and 359.90 particles/kg). The microplastic category of fragments/debris at a depth of 5-10 cm, was found at Station II (409.06 particles/kg). Biota found in Station I sediments were blood shells (AnadaraSp) With microplastic fragment type (1 particle) and fiber type (2 particles) with an average abundance of 0.12 particles/Ind. Fiber-type microplastics are found in tofu skin (Maretrixmaretrix) of 5 particles with an average abundance of 0.5 particles/Ind. and Violin Crab (Uca), 1 particle with an average abundance of 0.04 particles/Ind. Water quality in the area of microplastic abundance found NH3, BOD, Phosphate (PO43-), Nitrate (NO3−), Phenol (C6H5OH), detergent and fat oil content have exceeded the quality standard. Mitigation efforts that can be done are 6R, separating the types of waste from the beginning, encouraging the role of government through education and regulation, research and technology support as well as bay cleaning measures so as to beautify the bay and improve the comfort of the local community and visitors so that the function of Kendari Bay as a tourist area the mainstay coast of Southeast Sulawesi remains sustainable.
Classification method of carbonate reservoir welltest interpretation model based on long and short-term memory network

The development of carbonate reservoirs is inseparable from the measurement of formation parameters, and well test interpretation techniques are often used to determine these parameters. Determining the carbonate reservoir type according to the shape of the well test interpretation curve will help people better understand the reservoir situation and enable more precise well test interpretation. This research focusing on the well test interpretation of carbonate oil and gas reservoirs combined with the actual data of the mine field and uses deep learning algorithms such as feature value extraction, clustering and neural network training to classify the types of carbonate oil and gas reservoirs. Neural network training is further carried out for different types of carbonate reservoirs, so as to achieve the purpose of identifying reservoir types at the algorithm level.
An Improving Noise Immunity Algorithm for Multiple Kernel Boosting Using Noise Detection and Kernel Selection Technique

Focus on the problem that the Multiple Kernel Boosting(MKBoost) algorithm is sensitive to noise, a Multiple Kernel Boosting algorithm based on weight update and kernel selection is proposed. Firstly, the algorithm use the combined classification error rate of the previously selected classifier and the current classifier to be selected as the selection index of the kernel function in the weak classifier before the kernel of the base classifier is selected in each iteration; Secondly, in the weight update stage, a new weight update method is constructed by fusing the noise-detection and the average of weights in Multiple Kernel Boosting algorithm, which reduce the sensitivity to noise samples. Among the 8 of UCI data sets with varying levels of noise, the algorithm was compared with MKBoost-D1, MKBoost-D2, under the accuracy criteria, it performed better than traditional MKBoost algorithms. Experimental results show that the algorithm is able to effectively reduce the sensitivity of MKBoost to noise, and also has better robustness than traditional MKBoost algorithms.
Thermodynamic properties of pure and doped (B, N) graphene

Ab initio density functional perturbation theory (DFPT) has been employed to study the thermodynamical properties of pure and doped graphene sheet and the results have been compared with available theoretical and experimental data. The concentration of B and N has been varied upto 50% of the carbon atoms in graphene. Phonon frequencies are essential ingredients entering into such a calculation, which have been computed by using the dynamical matrix provided by VASP software in combination with phonopy code in the harmonic approximation. This easily provides us with the Helmholtz free energy and leads us to numerical estimates of various thermodynamical properties. The results for specific heat are in good agreement with various theoretical and experimental studies obtained earlier for pure graphene. Interesting new results have been reported for B and N substituted structures. It has been observed that the specific heat decreases with the increase in concentration of doping while the entropy increases. Furthermore, large doping concentrations result in unstable sheets leading to imaginary frequencies in the transverse directions. The instability needs to be compensated by external strains and that has been assumed while carrying out Brilluoin summations. These results will be useful for calculations of thermal conductivity of doped graphene and thus feasibility of using these for device applications. Our preliminary results for thermal expansion have indicated negative thermal expansion behavior of pure graphene at low temperatures which needs investigation on doped graphene as well.
Ballistic Target Signal Separation Based on Differential Evolution Algorithm

During the course of the ballistic target’s mid-flight, it is very important to accurately identify the target. Separating the target micro-Doppler curve is the key to accurate identification. Aiming at this problem, this paper proposes and improves a differential evolution algorithm to separate the micro-Doppler curves of the scattering points. According to the results of the simulation experiment, the signal is separated well, which verifies the effectiveness of the proposed algorithm.
Retraction Retraction: Fuzzy Techniques to Verify A Person’s Identification Using the X-Ray Images

Biometric x-rays are a means of testing the physical properties of an individual to check their identity. There are anatomical attributes, such as eyes or traits of behavior, fingerprints and a special path to authentication. In this article, the use of a deep neural network with fuzzy clustering is proposed as a new approach for forensic radiography based human authentication. A complex, convolutionary neural architecture is used to derive features of hand x-rays and for the detection of fluid clusters. Our experiment demonstrates that hand xrays provide fingerprint information to identify individuals. That laboratory analysis shows that the proposed solution is much better than previously existing authentication schemes with hand X-rays.
Experimental studies of the efficiency of incorporating green manure crops with a combined unit

In recent years, many agricultural producers have begun to take care of environmental aspects and are gradually switching to the use of organic farming elements in the cultivation of agricultural crops, which include green fertilizers - siderates. Many experts recommend cutting the green mass of green manure crops with a mower and embedding it in the surface layer of the soil as mulch. However, not all termination methods are equally effective. In particular, when passing through a field with a rotary harrow’s green manure, the disc knives have to simultaneously perform two functions: chop and embed the vegetative mass of plants, which negatively affects the depth of processing. Therefore, the goal of our research is to develop a combined unit for mowing, crushing and embedding green mass of green manure crops into the soil. To achieve this, it is proposed to attach a plant chopper to the front of the tractor, which will mow and chop the plants, and two disc batteries installed on the rear hitch of the tractor will close the chopped organic mass. To determine the efficiency of using the proposed combined unit in different regions of the Republic of Tatarstan on different soils, comparative field tests were carried out, which consisted in determining the completeness of incorporation of green mass. The value of this indicator without using the mower on the front hitch was 65%, and with mowing and chopping - 95%, this is 1.5 times more than in the variant with the compared unit, which should have a favorable effect on the decomposition of the embedded organic matter.
Utilization of wind energy in Belu District to improve community welfare and support environmental friendly development

The border area geographic of Indonesia and Timor Leste, especially Belu District, has a large potential source of natural energy. But unfortunately, the potential of wind energy cannot be explored to improve people’s welfare and to support sustainable development. This study found the potential for wind energy of 120 Megawatts which can be developed into electricity for the benefit of the people of Belu Regency, East Nusa Tenggara. The potential points are in Laktutus and Lookeu, Belu District. The research method used quantitative and qualitative participatory observations in the field study. If this wind potential can be developed by the local government of East Nusa Tenggara, it can encourage economic growth and home industries in Belu District. This finding is an important recommendation material for the East Nusa Tenggara Provincial Government in assessing development and implementing environmentally friendly and sustainable development activities.
Characterization of whole mitochondrial genome Amyda cartilaginea from Dharmasraya, West Sumatera

Previous data of the whole mitochondrial genome of soft-shelled turtle that it’s available in a public repository: Dogania subplana, Pelochelys cantorii, Chitra indica, Trionyx triunguis, Apalone spinifera, Rafetus swinhoei, and Pelodiscus sinensis. The first two species have natural distribution in Indonesia. Amyda cartilaginea is a species of soft-shelled turtle that is abundant in Indonesia. However, the whole mitochondrial genome data of A. cartilaginea is not available. This study aims to characterize the partial mitochondrial genome and analyze the phylogenetic position of A. cartilaginea. We reported almost complete mitochondrial genome of A. cartilaginea that caught from Batanghari river in Dharmasraya District, West Sumatera. The amplification of mitochondrial DNA fragments was performed using several primers designed following mitochondrial gene organization and sequence of D. subplana (Accession No AF366350). We sequenced half of the whole mitochondrial genome (7757 bp, 48%). The gene organization of the mitochondrial genome of A. cartilaginea was identic with D. subplana and P. cantorii. The phylogenetic tree analysis based on 16SrRNA revealed that the position of A. cartilaginea clustered with another soft-shelled turtle. Further study is needed to make a complete sequence of the mitochondrial genome of A. cartilaginea, with special focus on the control region to be applied to sustainable wild population management.