Miracle-dz/UniFAR-FTUs huggingface dataset:
The frequency-dependent polarization switching in nanograined BaTiO3 films under high-strength electric field

ABSTRACT The polarization reorientation in ferroelectric nanomaterials under high-strength AC electric fields is intrinsically a frequency-dependent process. However, the related study is not widely seen. We report a phase-field investigation regarding the dynamics of polarization switching and the electromechanical characteristics of a polycrystalline BaTiO3 nanofilm under applied frequency from 0.1 to 80 kHz. The grain boundaries and the in-plane strains are considered in the model. The obtained hysteresis and butterfly loops exhibit a remarkable variety of shapes with the changing frequency. The underlying mechanism for the observed frequency-dependent physical properties was discussed via domain structure-based analysis. In addition, we examined the influence of the kinetic coefficient in the Ginzburg-Landau equation as well as the influence of the electric-field amplitude to the frequency dependency. It was found that a higher value of kinetic coefficient or field amplitude tends to enhance the mobility of polarization switching and to transform high-frequency characteristics to low-frequency ones. GRAPHICAL ABSTRACT
Coherent state theory of the noncompact symplectic group

An extended coherent state theory is presented for the noncompact Sp(3,R) group which reveals a simple relationship between the Sp(3,R) algebra and its contracted u(3)‐boson limit. The relationship is used to derive a remarkably accurate analytic expression for Sp(3,R) matrix elements for the generic lowest‐weight representations. The expression is shown to be exact whenever the states involved are multiplicity free with respect to the u(3) subalgebra. It is further shown how exact matrix elements are easily calculated in general. Dyson and Holstein–Primakoff type u(3)‐boson expansions are given.
A Survey on Detecting Vandalism in Crowdsourcing Models

Crowdsourcing is a common term for collaborative environments that include a group of workers participating in the content of these platforms to create knowledge. The most important and well-known crowdsourcing platforms are Amazon's Mechanical Turk, Kaggle, Design99, and Wikipedia. Wikipedia is one of the most vital crowdsourcing models where users are contributing in creating and editing articles. Thus, leading to significant expansion in the encyclopedia that made it one of the most visited sites for getting information or using it as a knowledge base for many applications such as Chatbots. All These characteristics have come with another aspect through which users can sabotage the content of the encyclopedia that is known as vandalism. Vandalism is any attempt to modify the article in a way that negatively affects the article's quality. Vandalism is considered as one of the five layers model that constructed for cyber threads, which is known as cyber vandalism. Instead of misusing or stealing data, cyber vandalism involves all actions for damaging or destroying it. This paper presents a comprehensive survey that deals with various aspects of the vandalism detection problem in a crowdsourcing model - Wikipedia
Performance of Electrocoagulation Process Using Iron and Aluminum Electrodes with and without Perforations

Electrocoagulation process is widely used for the removal of pollutants from the industrial wastewater. In the present study, an attempt was made to investigate the performance of electrocoagulation process using alu-minum and iron electrodes to treat the metal ions present in the synthetic galvanic wastewater. The electrodes used are with and without perforations and it was observed that the efficiency of electrodes with perforation (80 %) was higher than without perforations (50 %). The removal efficiency of heavy metal ions increased with retention time and direct current. The optimized values of residence time, voltage, pH, current, electrode spacing were 160 min, 6 V, 5, 0.2 A, and 3 cm, respectively. The maximum removal percentage of nickel and copper ions using perforated iron electrodes was 90.7 % and 86.0 %, respectively, and for chromium using a combination of perforated iron and aluminum electrodes it was 93.1 %. The removal of metal ions followed pseudo second order kinetic model with current dependent parameters.
Bearing Fault Diagnosis Method Based on Fuzzy Petri Nets with Adam Optimization

To address the problem that three-phase asynchro-nous motor is difficult to maintenance support due to frequent faults and strong fuzziness of faults. A fault diagnosis method using fuzzy Petri nets (FPN) based on adaptive moment estimation (Adam) optimization is proposed. First, using fault tree analysis method, a bearing diagnosis model based on Adam-FPN is constructed. Then, adopting transition factors instead of traditional expert experience, the Adam algorithm and the Bp algorithm are combined into the Petri net to optimize the inference algorithm and achieve accurate prediction of bearing faults. Finally, the bearing fault model is used as an example for forward and reverse inference analysis and compared with other methods to verify its effectiveness and superiority.
Transfer Learning Empowered Resource Allocation for Vehicular Edge Computing

Vehicular edge computing servers as a decentralized network extension to offer distributed and proximity services for computation-intensive vehicular applications. For some complex computing tasks, when they are offloaded from smart vehicles to edge servers, computing environment needs to be established on the servers, which requires extra computing power and brings unprecedented computation delay. To address this problem, we incorporate transfer learning into vehicular edge networks, leveraging existing knowledge and experience of similar edge services to improve the agility of environment construction. Furthermore, we investigate various knowledge transfer scenarios in terms of data source selection and knowledge preprocessing. We propose joint transfer learning and resource scheduling schemes adapted to both multi-source transfer and single-source transfer scenarios, which minimize computation delay while ensuring task computation accuracy constraints. Numerical simulations are conducted to verify the effectiveness of our proposed scheme as compared to benchmark schemes.
Super resolution based face recognition: do we need training image set?

This paper is concerned with face recognition under uncontrolled condition, e.g. at a distance surveillance scenarios, and post-rioting forensic, whereby captured face images are severely degraded/blurred and of low-resolution. This is a tough challenge due to many factors including capturing conditions. We present the results of our investigations into recently developed Compressive Sensing (CS) theory to develop scalable face recognition schemes using a variety of overcomplete dictionaries that construct super-resolved face images from any input low-resolution degraded face image. We shall demonstrate that deterministic as well as non-deterministic dictionaries that do not involve the use of face image information but satisfy some form of the Restricted Isometry Property used for CS can achieve face recognition accuracy levels, as good as if not better than those achieved by dictionaries proposed in the literature, that are learned from face image databases using elaborate procedures. We shall elaborate on how this approach helps in crime fighting and terrorism.
MODAL RECONSTRUCTION ERROR OF THE HARTMANN SENSOR ON MEASURING THE ATMOSPHERE DISTURBED WAVEFRONT I

WT5”BZ]By using the Zernike and the Karhunen Loeve wavefront reconstruction algorithm,the wavefront reconstruction error of a Hartmann sensor on measuring the atmosphere disturbed wavefront was analyzed in this paper. In the condition of without measurement noise, there are two kinds of wavefront reconstruction errors: the mode coupling error causing by finite spatial frequency of sub apertures and the mode cutting error by using finite mode numbers. It is showed that the wavefront reconstruction error will be minimum while optimal mode numbers were using, and the Karhunen Loeve algorithm is somewhat better than the Zernike algorithm.
What Happens Depends on When It Happens: Copula-Based Ordered Event History Analysis of Civil War Duration and Outcome

Scholars are interested in not just what event happens but also when the event happens. If there is dependence among events or dependence between time and events, however, the currently common methods (e.g., competing risks approaches) produce biased estimates. To deal with these problems, this article proposes a new method of copula-based ordered event history analysis (COEHA). A merit of working with copulas is that, whatever marginal distributions time and event variables follow (including the Cox model), researchers can derive whatever joint distribution exists between the two. Application of the COEHA model to a dataset from civil wars supports two controversial hypotheses. First, as wars become longer, rebel victory becomes more likely but settlement does not (there is dependence between time and events at both tails). Second, stronger rebels make wars shorter but do not necessarily tend to win, as experts predict but fail to establish (rebels’ strength shortens time but has no effect on which events occur). Supplementary materials for this article are available online.
DPD and Compensation under RF Impairments in the Hardware by BiLSTM

In higher-order modulation and mmWave communications, radio frequency (RF) impairments, including amplifier nonlinearity, IQ imbalance, and phase noise are becoming serious problems in hardware devices. In this paper, we attempt to deal with RF impairments by Bi-directional Long Short-Term Memory (BiLSTM), including the improvements in digital pre-distortion (DPD) in the transmitter and compensation in the receiver. Characteristics of the RF device are considered to extract hidden laws and information in the fluctuation of RF devices, and the complexity is discussed. The simulation results show that the performance of the BiLSTM-based DPD and compensation for RF impairments are better than the traditional estimation. The data of DPD is collected from a universal software radio peripheral (USRP) with a 30 MHz bandwidth for authenticity.
Ion beta dependence on the development of Alfvénic fluctuations in reconnection jets

The generation of magneto‐hydro‐dynamic (MHD) to ion‐scale fluctuations in collisionless magnetic reconnection is discussed using a two‐dimensional electromagnetic hybrid code. It is shown that reconnection jets become turbulent specifically in low beta conditions, βi0<0.1–0.2 (where βi0 is the ion plasma beta in initial inflow regions). The fluctuations observed in reconnection jets consist of outgoing Alfvénic fluctuations. As probable candidates for the origin of Alfvénic fluctuations, this study focused on the dynamics in the plasma sheet boundary layer (PSBL) and a current sheet. We suggest that PSBL ion dynamics play an important part in excitation and suppression of waves. PSBL beam ions drive Alfvén waves in MHD to ion scale, kλi<0.5 (λi is ion inertial length), independent of βi0. On the other hand, because the beam temperature is highly correlated with that of inflowing ions, the waves decay by cyclotron damping as the value of the inflow ion beta increases. Local linear analysis suggests that this damping signature changes in βi0∼0.1–0.2 and suppresses the wave activity of Alfvén modes in high beta reconnection jets.
Inverse Problem of Oil Pipeline Dynamic Operation Based on Model-Free Adaptive Control Theory

The purpose of this paper is to solve the inverse problem of the dynamic operation of dispatchers in oil pipeline system based on the real-time system process parameters. To realize online solution of system dynamic operation inverse problem, model free adaptive control theory is introduced for the first time. In particular, the frequency domain analysis method is adopted to prove that the oil pipeline system meets assumptions of the control theory. The dynamic state model suitable for solving the control process of the pipeline system is established by using the field data, and the inverse problem of the controlled components dynamic process is solved by using the model free adaptive control method. By analyzing the characteristics of pipeline flow process and comparing different linearized models, the full from dynamic linearization method is selected to model the system state. Single-input-single-output system model and Multi-Input-Single-Output system model are adopted to solve the single station and multiple stations joint operation process respectively. This method is verified with SCADA data of a real pipeline system. The results show that the proposed method can realize the online twining of valve dynamic operation process, and improve the accurate of system state parameters estimation during dynamic operation.
Convergence Rates for Hestenes’ Gram–Schmidt Conjugate Direction Method without Derivatives in Numerical Optimization

In this work, we studied convergence rates using quotient convergence factors and root convergence factors, as described by Ortega and Rheinboldt, for Hestenes’ Gram–Schmidt conjugate direction method without derivatives. We performed computations in order to make a comparison between this conjugate direction method, for minimizing a nonquadratic function f, and Newton’s method, for solving ∇f=0. Our primary purpose was to implement Hestenes’ CGS method with no derivatives and determine convergence rates.
Ultra-Low Detection of Perfluorooctanoic Acid Using a Novel Plasmonic Sensing Approach Combined with Molecularly Imprinted Polymers

In this work, a novel optical fiber sensor system for ultra-low perfluorooctanoic acid (PFOA) detection in aqueous solutions is proposed. It is based on the connection, in series, of two different plastic optical fiber (POF) platforms: the first is a chemical chip realized by using a D-shaped POF with microholes filled with a specific molecularly imprinted polymer (MIP); the second is a typical surface plasmon resonance (SPR) sensor based on a D-shaped POF. In particular, the MIP-based chemical chip was used to launch the light inside the SPR–POF chip to change the SPR phenomenon by exploiting the PFOA–MIP interaction in the microholes. At first, experimental results were performed in water to demonstrate the applicability of the proposed sensing approach for measuring PFOA (or C8) in a concentration range of 1 ppt to 750 ppt, obtaining an ultra-low limit of detection (LOD) equal to about 0.81 ppt. Then, experimental results were carried out in simulated seawater to implement a complex matrix. The obtained results denoted a slight matrix effect, paving the way for the applicability of the proposed chemical sensing mechanism in several aqueous solutions.
Analogical Modeling and morphological change: the case of the adjectival negative prefix in English

This article examines the usefulness of Skousen's Analogical Modeling (AM) for explaining morphological change. In contrast to previous accounts of analogy, AM constitutes a general unified model of language that accounts for both sporadic and systematic changes. AM also provides explicit constraints on analogy that allow explanation of how morphological changes begin, which forms most likely serve as patterns for analogy, and which forms are most likely to change. AM is then tested on the case of the adjectival negative prefix in English (in-, un-, dis-, etc.), using the Middle and Early Modern English portions of the Helsinki corpus as a basis for prediction. AM was given the task of using forms containing negative prefixes for one time period to predict the prefixes that adjectives would take in the subsequent time period. For each of the roughly seventy-year periods in the corpus, AM was able to predict valid prefixes about 90 percent of the time.
Corners Detection Based on Improved Harris Algorithm

The traditional Harris corner detection algorithm not only has a good work,but also has a higher repetition rate.However,the whole corner detection process depends almost entirely on the corner extraction threshold during non-maxima suppression,and it's hard to achieve the rotational invariance if the parameters do not change.It presents an improved Harris algorithm,through the secondary maxima suppression to avoid setting the threshold value;at the same time,reduce the corner extraction differences around image rotation when there is not any change to the parameters.The experiment shows that this algorithm is simple and easy to operate,the corner points extracted are very effective,compared with the traditional Harris algorithm has better corner detection performance.
The Bugis People's Naming System in Bugis Ethnic Tradition

The naming system in the Bugis ethnic is part of the customary system that has been attached since the Bugis existed. The purpose of this study is to describe the system of naming the Bugis in the Bugis tradition. This research is a type of qualitative research using descriptive methods and ethnographic approaches. Verbal data are in the form of words, phrases, and expressions as well as statements obtained from the interview. The data collected were from three community groups: Tosora in Majauleng District, Lagosi in Pammana District, and Gilireng in Gilireng District. Three community groups are known as cultural villages. They are called cultural villages because these three villages are the source of the history of the Bugis people of South Sulawesi. This study uses an ethnographic approach. This is because research activities are inseparable between the activities of a community group as the object of research and their cultural system. Thus, information or data is obtained from interactions between researchers and the public who are research subjects or data sources. The results of this study are based on findings that show that the Bugis self-naming system is of three types; based on the situation and circumstances, based on natural events, and based on the child’s appearance. The results of this research provide an increase in the revitalization process of traditions that exist in Bugis society. The naming system in the Bugis ethnicity is still being preserved even though advanced technology is growing rapidly.
Studying Milky Way structure using stellar populations

Abstract With the advent of large wide-field cameras and deep, CCD-based “all-sky” surveys, the study of the structure of the Milky Way (MW) through its stellar populations has become feasible. We are developing tools to apply CMD fitting techniques for this purpose. Here we present two applications. First we constrain the properties of the old and young stellar populations of the Canis Major overdensity. Secondly, we demonstrate how CMD fitting can be used to detect faint overdensities in the halo of the MW and determine their properties, using data from the Sloan Digital Sky Survey (SDSS).
Metabolomics Analysis Reveals Metabolites and Metabolic Pathways Involved in the Growth and Quality of Water Dropwort [Oenanthe javanica (Blume) DC.] under Nutrient Solution Culture

Water dropwort (Oenanthe javanica (Blume) DC. ) is an important vegetable crop. Nutrient liquid culture has become an important cultivation method in the production of water dropwort. However, the effects of different nutrient solution cultivation methods on the growth and quality of water dropwort remains unclear. In this study, to screen the most suitable nutrient solution formula for the cultivation of water dropwort, the effects of different nutrient solution formulas (Hoagland, Cooper, Dutch greenhouse, Garden-style, Yamasaki and SCAU) on plant physiological and quality characteristics are investigated. The plant height, root length, water content (%), distribution rate of dry matter (%), chlorophyll, VC, flavonoid, total phenolic, DPPH and dietary fiber of water dropwort under different nutrient solutions were determined. According to the analytic hierarchy process (AHP) of the growth index and quality index of water dropwort under different nutrient solutions, the Yamazaki nutrient solution was considered to be the most suitable nutrient solution formula for water dropwort. To further confirm the differences of water dropwort under nutrient solution culture and soil culture, the broadly targeted metabolomics were performed. A total of 485 metabolites were detected in water dropwort under optimal nutrient solution and soil cultivation. Metabolomics analysis showed that flavonoids were the most abundant differential accumulated metabolites, and most flavonoids were up-regulated. A qRT-PCR assay indicated that the structural genes of the flavonoid biosynthesis pathway (PAL, C4H, CHS, CHI, F3H, DFR, UFGT) were significantly higher under the Yamasaki nutrient solution treatment. The current study provided a theoretical basis and technical guidance for the nutrient solution cultivation of water dropwort. Meanwhile, this study provides new insights into the study of flavonoids in water dropwort.
Innovation norms during COVID-19 and Indonesian hotel performance: Innovative energy use as a mediating variable

Abstract This study investigates the strategic effects of innovation norms—opportunity awareness and creative environment—to execute better innovative energy use and obtain better hotel performance during the COVID-19 outbreak. This exploration may shed light on the coping mechanism of hospitality business under the perspective of Resource-based Views. This study designed a survey, under the quantitative approach, to hotel managers in Makassar, Indonesia, resulting in a 204-response rate. The data was analyzed using the partial-least-square structural-equation modeling (PLS-SEM). The findings confirm the acceptance of all proposed hypotheses. Innovative norms—opportunity awareness and creative environment—are the foundation of executing energy-saving use in the organization. Finally, it mediates the relationship between innovation norms and hotel performance. This finding indicates the importance of green-innovative resources to mitigate the negative consequences of economic turbulence.
Strategies for Improving Vascularization in Kidney Organoids: A Review of Current Trends

Simple Summary Organoids are small, 3D models of organs that can help researchers study organ function and disease. Kidney organoids have the potential to treat chronic kidney disease, which affects over 800 million people. However, creating fully functioning kidney organoids is still a challenge due to functional immaturity and the lack of blood vessels and tissue organization. This article discusses the current challenges and efforts in developing matured and vascularized organoids. Abstract Kidney organoids possess the potential to revolutionize the treatment of renal diseases. However, their growth and maturation are impeded by insufficient growth of blood vessels. Through a PubMed search, we have identified 34 studies that attempted to address this challenge. Researchers are exploring various approaches including animal transplantation, organ-on-chips, and extracellular matrices (ECMs). The most prevalent method to promote the maturation and vascularization of organoids involves transplanting them into animals for in vivo culture, creating an optimal environment for organoid growth and the development of a chimeric vessel network between the host and organoids. Organ-on-chip technology permits the in vitro culture of organoids, enabling researchers to manipulate the microenvironment and investigate the key factors that influence organoid development. Lastly, ECMs have been discovered to aid the formation of blood vessels during organoid differentiation. ECMs from animal tissue have been particularly successful, although the underlying mechanisms require further research. Future research building upon these recent studies may enable the generation of functional kidney tissues for replacement therapies.