Miracle-dz/UniFAR-FTUs huggingface dataset:
The Long-Run Dynamics of Green Technology, Ecological Footprint, and Health Vulnerability in Developed and Developing Countries

Human activities have contributed to environmental degradation for decades, and ecological footprint is considered an effective tool for measuring natural resource consumption. The present study explores the moderating role of green technology to determine the impact of the ecological footprint on the health vulnerability of developed and developing countries from 1990 to 2020. The long-run results are estimated by using the Panel Quantile Regression model at lower, middle, and higher health vulnerability groups. The empirical results show a U-shaped relationship exists between ecological footprint and health vulnerability in all groups. The green technology is used as the moderator term, which shifts the turning point of the U-shaped curve at higher quantile groups of developed countries and middle quantile groups at middle quantiles. Which shows that green technology moderates health vulnerability by reducing the ecological footprint. Furthermore, this study shows that most developing countries fall in the lower health vulnerability group while most developed countries fall in the middle health vulnerability group. This study recommends that these selected countries' governments increase green technologies, reducing the ecological footprint and improving the health sector.
Equatorially trapped nonlinear water waves in a $\unicode[STIX]{x1D6FD}$ -plane approximation with centripetal forces

In this paper we present an exact and explicit nonlinear solution of a $\unicode[STIX]{x1D6FD}$ -plane approximation to the governing equations which retains all Coriolis terms. The solution represents an equatorially trapped wave propagating in the presence of a constant underlying background current. In particular, we show that retention of the (relatively) small-scale centripetal forces in the governing equations enables us to admit currents of any physically plausible magnitude in the background flow.
Advances in the synthesis and applications of porous carbon materials

The progress of human civilization depends on the development of all kinds of materials. The establishment of modern science has led to the rapid development of synthetic materials. However, increasing energy demand and environmental pollution urgently require the search for new materials to solve the energy and environmental crisis. Carbon is an extremely abundant element in nature and provides the basis for all life on Earth (Li et al., 2008; Toth et al., 2016). The carbon atom has six electrons outside the nucleus, and its outermost electron arrangement is 2s2p, which shows a strong ability to form covalent bonds (Krueger, 2010). Porous carbon materials have advantages such as chemical stability, low density, high thermal conductivity, high electrical conductivity, and high mechanical strength (Gallo, 2017). Porous carbon materials also have a large specific surface area, adjustable pore size, and functional groups and can be prepared from a wide range of precursors at relatively low cost. In recent years, a large number of researchers have been devoted to the synthesis and application of porous carbon (Ang, 2019; Liu, 2019; Liu, 2020a; Hwang, 2020; Raj, 2021). Depending on the pore size distribution, the pore structure of carbon materials can be divided into three categories, namely, micropores (pore size <2 nm), mesopores (2 nm < pore size <50 nm), and macropores (pore size >50 nm) (Vu, 2012). The size of the pore structure of porous carbonmaterials has a significant impact on their performance in practical applications. Due to these advantages, carbonmaterials are widely used in the fields of adsorption (He, 2019), catalysis (Dong et al., 2020), and energy storage (Peng, 2019). This paper mainly introduces the synthesis and application of carbon materials and describes the main improvement ideas for current carbon materials (Figure 1). Importantly, the future direction of carbon materials is further discussed.
A group III patatin-like phospholipase gene pPLAIIIδ regulates lignin biosynthesis and influences the rate of seed germination in Arabidopsis thaliana

The lignification of plant secondary walls is an important process that provides plants with mechanical support. However, the presence of lignin in the secondary walls affects the readily availability of cellulose required in various industries, including the biofuel, paper, and textile industries. Thus, plants with less lignin are ideal for usage in such industries. Molecular studies have identified genes that regulate plant lignification, including group III plant-specific patatin-related phospholipase genes. Recent studies have reported decreased lignin content when pPLAIIIα, pPLAIIIγ (from Arabidopsis thaliana), and pPLAIIIβ (from Panax ginseng) were overexpressed in Arabidopsis. However, the role played by a closely related gene pPLAIIIδ in lignin biosynthesis has not yet been reported. In this study, we found that overexpression of the pPLAIIIδ significantly reduced the lignin content in secondary cell walls, whereas the silencing of the gene increased secondary walls lignification. Transcript level analysis showed that the key structural and regulatory genes involved in the lignin biosynthesis pathway decreased in overexpression, and increased in plants with silenced pPLAIIIδ. Further analysis revealed that pPLAIIIδ played an influential role in several physiological processes including seed germination, and chlorophyll accumulation. Moreover, the gene also influenced the size of plants and plant organs, including leaves, seeds, and root hairs. Generally, our study provides important insights toward the use of genetic engineering for lignin reduction in plants and provides information about the agronomical and physiological suitability of pPLAIIIδ transgenic plants for utilization in biomass processing industries.
Chaotic Signal De-Noising Based on Threshold Selection Rules with SNR Evaluations of Wavelet

In nature, the observed Chaos phenomenas were often mixed with noise, the existence of noise made the prediction of chaotic time series generate large errors. Chaotic time series had the characteristic of broadband, which liked noise. So there were some limitations with the traditional method of de-noising. But the wavelet threshold de-noising method had the characteristic of the multi-resolution analysis, and its computational quantity was smaller and the noise filtering effect was better. On the other hand, for different types of signals, with different wavelet base functions and threshold rules, it might have a different effect on the de-noising effect. In order to search for the optimal selection of those parameters, firstly this paper constructed a simulated Lorenz noisy signal, and used this signal to do the de-noising experiment, used the SNR and RMSE as the evaluating indicator, and finally obtained the matching combination of those parameters. At the end of this paper, the de-noising simulation was carried out using China's Shijiao station runoff time series data from 1960 to 1970 in China, and the final results showed the effectiveness of the proposed method in this paper.
Hypoellipticité des équations paraboliques

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Factors Associated with Depression in Infertile Couples: A Study in Thailand

Background: Infertility can affect a couple’s mental health and marital and social relationships. The study aimed to investigate the prevalence of depression among infertile couples and their relationships with other factors. Methods: This study employed a cross-sectional survey. Validated tools were used to assess anxiety and depression, marital satisfaction, personality traits and sufficiency economy. The actor–partner interdependence model (APIM) was used for dyadic analysis. Results: The prevalence of depression in infertile couples was 6.7%. Aggression, extraversion and neuroticism were significantly correlated with depression, whereas the expectation of having children, marital satisfaction and sufficiency economy were negatively correlated with depression. The APIM model suggested that neuroticism and marital satisfaction were significant predictors of depression. Partner effect between the expectation of having children and depression was observed (p = 0.039). Conclusions: Like other populations, depression in infertile couples seems to be associated with aggression, extraversion and neuroticism. However, there are specific variables related to infertility that impact the depression levels of these couples. For instance, the expectation of having children can affect the partners of infertile couples, while the role of the sufficiency economy is a new factor that has been examined for depression in this sample and requires further exploration.
Convergence analysis of time-domain PMLs for 2D electromagnetic wave propagation in dispersive waveguides

This work is dedicated to the analysis of generalized perfectly matched layers (PMLs) for 2D electromagnetic wave propagation in dispersive waveguides. Under quite general assumptions on frequency-dependent dielectric permittivity and magnetic permeability we prove convergence estimates in homogeneous waveguides and show that the PML error decreases exponentially with respect to the absorption parameter and the length of the absorbing layer. The optimality of this error estimate is studied both numerically and analytically. Finally, we demonstrate that in the case when the waveguide contains a heterogeneity supported away from the absorbing layer, instabilities may occur, even in the case of the non-dispersive media. Our findings are illustrated by numerical experiments.
The Weierstrass Approximation Theorem on Linear Varieties: Poly- nomial Lyapunov Functionals for Delayed Systems

In 1885, Weierstrass first published a result [16] showing that real-valued polynomials can be used to approximate any continuous function on a compact interval to arbitrary accuracy with respect to the supremum norm. Various generalizations of the Weierstrass approximation theorem have focused on generalized mappings [15] and alternate topologies [4]. More recently, the Weierstrass theorem has found applications in numerical computation due to the ease with which polynomial functions are parameterized and evaluated. In this paper, we reexamine the Weierstrass theorem from the relatively new perspective of polynomial optimization. These problems consider optimization over C(X), the Banach space of continuous functions on X where X ⊂ R is compact. The structure of the problem is often a special case of
Maritime Patrol Collaboration with Indonesian Maritime Law Enforcement Agencies

With so many agencies patrolling separately, the patrol becomes ineffective and inefficient. Each agency needs a budget and conducts repeated ship inspections. The expected condition is when all agencies can collaborate in carrying out patrols. Researchers used qualitative methods with exploratory designs. Interviews were conducted with informants from Bakamla, TNI AL, Polair, Bea Cukai, PSDKP, and KPLP. The results of the research show that collaboration is needed to combine various elements of patrols from various authorities in the sea. Researchers suggest collaboration between agencies with joint base assets and create a ship inspection information system in real-time.
Intelligent Diagnosis of Rolling Bearings Fault Based on Multisignal Fusion and MTF-ResNet

Existing diagnosis methods for bearing faults often neglect the temporal correlation of signals, resulting in easy loss of crucial information. Moreover, these methods struggle to adapt to complex working conditions for bearing fault feature extraction. To address these issues, this paper proposes an intelligent diagnosis method for compound faults in metro traction motor bearings. This method combines multisignal fusion, Markov transition field (MTF), and an optimized deep residual network (ResNet) to enhance the accuracy and effectiveness of diagnosis in the presence of complex working conditions. At the outset, the acquired vibration and acoustic emission signals are encoded into two-dimensional color feature images with temporal relevance by Markov transition field. Subsequently, the image features are extracted and fused into a set of comprehensive feature images with the aid of the image fusion framework based on a convolutional neural network (IFCNN). Afterwards, samples representing different fault types are presented as inputs to the optimized ResNet model during the training phase. Through this process, the model’s ability to achieve intelligent diagnosis of compound faults in variable working conditions is realized. The results of the experimental analysis verify that the proposed method can effectively extract comprehensive fault features while working in complex conditions, enhancing the efficiency of the detection process and achieving a high accuracy rate for the diagnosis of compound faults.
Quantum Optics with Semiconductor Double Quantum Dots

There has been a lot of interest in solid state quantum devices such as electron spins, superconductor islands or nitrogen-vacancy centers for quantum information processing. Semiconductor double quantum dots (DQDs) have been proposed as one platform for quantum bit (qubit) implementations due to the potentially long coherence time of electron spins in materials such as silicon. Strong coupling between microwave photons and these solid state quantum devices has been achieved in circuit quantum electrodynamics (cQED) architectures. This provides one scheme for long range quantum entanglement which is important for scaling up these qubit systems. This thesis will examine hybrid cQED devices consisting of indium arsenide (InAs) DQDs that are coupled to microwave cavities. The photon emission from the DQDs, which is the main topic of the thesis, demonstrates the opportunity to study the environment such as phonons and photons that interact with this qubit candidate as well as the potential in applications such as generating quantum optics states in cavities. We first discuss our observation of photon emission from single electron tunneling events driven by a voltage biased DQD. Later we demonstrate maser action when the photon emission rate overcomes the cavity loss rate. We first examine the emission from two DQDs that are coupled to the same cavity. We verify maser action by comparing the statistics of the emitted microwave field above and below the maser threshold. By increasing the charge-cavity coupling rate and suppressing the cavity loss channels, we achieve the maser action with only one DQD. We then study the threshold behavior of this single atom maser which reveals the contribution from tunneling between the DQD and the source-drain electrodes. Finally, we show that the emission can be stabilized by an external cavity drive. A frequency comb can be generated by modulating the DQD gain medium. Finally, we utilize the single atom maser as an on-chip microwave source for state readout of other quantum devices. iii
Self-Training Intelligent Predictive Control for Grid-Tied Transformerless Multilevel Converters

Literature reviews affirm the constructive influence of the intelligent predictive multiobjective control (IPMOC) on the power quality, power ancillary services, efficiency, and reliability expected from grid-tied transformerless multilevel converters. Regarding, this article contributes to developing the IPMOC concept in terms of training, autonomous power management, and real-time harmonic mitigation. In the proposed IPMOC, model predictive control (MPC) adjusts the power, regulates the dc-link capacitors’ voltages, reduces the switching transitions, suppresses CMV, and alleviates harmonics using a novel real-time selective-predictive harmonic mitigation objective. As the intelligent part, two artificial neural networks trained by a novel data-free, fast, self-training strategy reinforce the MPC to handle the multiobjective task. The first one adapts the weighting factors of the MPC dynamically, while the second one as a model-free controller autonomously adjusts the active and reactive power references of the MPC to assure the unity power factor of the grid in the presence of unknown loads. The proposed IPMOC has been applied to a three-phase neutral point clamped converter and evaluated via various test scenarios run by dSPACE 1202 and MATLAB to verify its effectiveness and feasibility.
Thermal plasmas

Although many thermal plasma processes have been developed for industrial applications, the wide acceptance as a manufacturing technology is prevented due to economical and competitive reasons, and/or reproducibility and reliability aspects. This paper is devoted to an assessment of the present knowledge in the following topics: (1) plasma torch and performance of blown arc (dc or ac), transferred arc and radio frequency torches; (2) established industrial applications with special emphasis on cutting, welding, spraying, transferred arc reclamation, reheating and purification, reheating metal melts, smelting reduction, chemical operations, and waste destruction; (3) recent developments in the knowledge of fundamental processes in plasma torches with power sources, cathodes (hot and cold), anodes (static and dynamic behavior), and torch components; (4) modeling-thermodynamic and transport properties, plasma flow with and without the Maxwell's equations; (5) measurement techniques including emission and absorption spectroscopy, laser scattering, enthalpy probes, video cameras, spectral analysis, shadowgraphy, and particle diagnostics either in flight with statistical measurements and those giving characteristics of a single particle upon flattening on a substrate; and (6) plasma-processing development in the presently used industrial processes and also in prospective processes with surface hardening, ultrafine powder production, plasma-assisted CVD, and plasma-fluidized or spouted bed reactors.
A Magnetic-Enhanced Reflectarray Antenna for High-Power Microwave Applications

A magnetic-enhanced reflectarray antenna (MERA) based on <inline-formula> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula>-negative (ENG) metamaterial is proposed in this communication. By utilizing the variable-rotation technique (VRT), the MERA achieves the first-ever application of the ENG metamaterial in a high-power microwave (HPM) reflectarray antenna (RA) under passive conditions. The antenna element of the MERA is a tri-layer structure composed of an ENG layer sandwiched by two high-<inline-formula> <tex-math notation="LaTeX">$\varepsilon _{\text {r}}$ </tex-math></inline-formula> dielectric slabs, with a metal sheet situated at the bottom of the sandwich structure to reflect incident waves. Operating in X-band (8.6–9.8 GHz), the MERA element exhibits a continuous 360° phase coverage with negligible element loss and robustness against the incident angle, with an estimated power handling capacity (PHC) exceeding 1 GW/m2. Using the proposed element, a prototype focused in the direction of (<inline-formula> <tex-math notation="LaTeX">$\theta _{0}= 20^{\circ }$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\varphi _{0}=0^{\circ }$ </tex-math></inline-formula>) was fabricated and experimented, and the simulation results were found to be in good agreement with the measured results. The measured results indicate that the MERA has an aperture efficiency greater than 53.4% within the operation bandwidth, with the maximum value reaching 64.33%, while achieving sidelobe levels of less than −20 dB.
An 89.3% Current Efficiency, Sub 0.1% THD Current Driver for Electrical Impedance Tomography

Accurate electrical impedance tomography (EIT) measurements require a current driver with low total harmonic distortion (THD) and high output impedance. Conventional EIT current drivers attain good performance for these parameters but at the expense of low current efficiency. This Brief presents a differential current driver based on a current feedback structure with isolated common-mode feedback, achieving very low THD, high output impedance and high current efficiency. In addition, it uses current DACs to remove any dc offsets at the output nodes. The current driver was fabricated in a 65-nm CMOS technology with 3.3 V supply. Measured results demonstrate a THD of 0.05% and 0.1% at 80 kHz, for <inline-formula> <tex-math notation="LaTeX">$1\,\,{\mathrm{ mA}}_{\mathrm{ p-p}}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$1.375\,\,\rm mA_{\mathrm{ p-p}}$ </tex-math></inline-formula> output current, respectively. The total current consumption is 1.54 mA, resulting in a maximum current efficiency of 89.3%. The measured output impedance is 1.023 <inline-formula> <tex-math notation="LaTeX">$\text{M}\Omega $ </tex-math></inline-formula> at 500 kHz and 568 <inline-formula> <tex-math notation="LaTeX">$\text{k}\Omega $ </tex-math></inline-formula> at 1 MHz.
Fault Diagnosis of Realistic Arrays From a Reduced Number of Phaseless Near-Field Measurements

We present a new approach to the problem of detecting element failures in any kind of array antenna. The proposed method requires only phaseless information on the generated field and reduces as much as possible the number of needed measurements by exploiting the compressed sensing (CS) theory. The solution procedure works regardless of whether the probes are located in the near-field or in far-field region of the antenna under test, and it is the first and only CS-based technique able to perform the diagnostics by exploiting only phaseless measurements taken exclusively in the near-field zone. It is also simple and fast as it requires a single measurement surface and reduces, in most practical instances, to the solution of a convex programming problem. The given theory is supported by very many numerical experiments involving full-wave electromagnetic simulations of realistic arrays and considering both scalar and vector fields with different types of scanning surfaces and different noise levels. Both ON-OFF and phase faults are dealt with. An experimental validation of a fabricated array is also presented.
Pricing dynamic fund protections for a hyperexponential jump diffusion process

ABSTRACT This article deals with the valuation of dynamic fund protections (DFPs) under a jump diffusion model, where the jump size follows a hyperexponential distribution. The closed-form solution of the value of DFP is obtained in terms of Laplace transform. A numerical example is provided to show that the explicit solution is easy to implement by using the Gaver–Stehfest algorithm. Effects of key parameters are analyzed at last. The valuation method developed in this work can be used in pricing various variable annuities and path-dependent financial products.