Dispersion and nonlinearity properties of small solid-core photonic fibers with As2Se3 substrate

Characteristics of As2Se3 photonic crystal fibers (PCFs) with a solid-core and small-core diameter are numerically investigated in the long-wavelength range (from 2 to 10 μm). A full modal analysis and optical properties of designed photonic crystal fibers with lattice constant Λ and filling factor d/Λ are presented in terms of chromatic dispersion, effective refractive index, nonlinear coefficients, and confinement loss. The simulation results show that a high nonlinear coefficient of 4410.303 W–1·km–1 and a low confinement loss of 10−20 dB·km–1 can simultaneously be achieved in the proposed PCFs at a 4.5 μm wavelength. Chromatic dispersions are flat. The values of dispersion increase with increasing filling factor d/Λ and decrease with the increase in lattice constant Λ. In particular, some chromatic dispersion curves also cut the zero-dispersion line at two points. The flat dispersion feature, high nonlinearity, and small confinement loss of the proposed photonic crystal fiber structure make it suitable for supercontinuum

DESIGN OF A HIGH-SENSITIVITY DEVICE FOR DETECTING WEAK MAGNETIC FIELDS

An anti-serial fluxgate sensor configuration is proposed in this report. The design comprises two identical bilayer-rod fluxgate sensors connected anti-serially in a straight line. Each bilayer-rod sensor is constructed of an excitation coil and a pick-up coil wrapped around a core. The core material consists of Metglas ribbon, an amorphous alloy with high permeability, negligible hysteresis, and a high saturated magnetic field. The core is cut into a bar shape and uses double layers to enhance modulated flux density. A high sensitivity of 10 mV/Oe (with excitation of 45 kHz and 250 mA) is obtained experimentally with low noise of 1´10-5 Oe/Ö Hz at 1 Hz. In measurements of weak magnetic fields, the azimuth response indicates its vector feature. The proposed design is suitable for electronic compass and displacement applications

DEVELOPMENT OF A SIMPLE TECHNOLOGY TO REMOVE ARSENIC IN GROUND WATER BASED ON USING "LATERITE"-ADSORBENT, A COMMON NATURAL IRON ORE IN VIETNAM

Joint Research on Environmental Science and Technology for the Eart

NONLINEAR CHARACTERISTICS OF SQUARE SOLID-CORE PHOTONIC CRYSTAL FIBERS WITH VARIOUS LATTICE PARAMETERS IN THE CLADDING

Nonlinear characteristics of fused silica, solid-core photonic crystal fibers (PCFs) with a square array of air holes are studied numerically. We present a novel design that emphasizes the difference in air hole diameters in the photonic cladding. These PCFs have the advantages of flat dispersion, high nonlinearity, and low attenuation. Based on simulation results, three optimal structures, denoted #F1, #F2, and #F3, having anomalous and all-normal dispersions in the near-infrared range are selected to investigate characteristic properties at the pump wavelength. Such PCFs open up many possibilities for nonlinear optical applications, especially supercontinuum generation

Effect of loading paths on hydroforming ability of stepped hollow shaft components from double layer pipes

The step hollow shaft components are composed of two layers of different materials, they are formed using tube hydroforming process due to its high strength and rigidity, low weight and flexible profiles, compared to traditional casting, welding, and forming methods. These products are effectively used in industries such as the automotive, shipbuilding, aerospace and defense, and oil and gas sectors. The success of various double layer pipe hydroforming process depends on several factors, with the most important being the internal pressure path and axial loading path. This paper presents research on the effect of input loading paths on the hydroforming ability of a different two-layer metal structure - an outer layer of SUS304 stainless steel and an inner layer of CDA110 copper - using 3D numerical simulations on Abaqus/CAE software. Output criteria were used to evaluate the forming ability of the formed components, including Von Mises stress, Plastic strain component (PEmax), wall thinning, and pipe profile, based on which the input loading paths were combined during the forming process. These output criteria allow for more accurate predictions of material behavior during the hydroforming process, as well as deformation and stress distribution. This can support the design process, improve product quality, reduce errors, and increase production efficiency. The research results can be applied as a basis for optimizing load paths for the next experimental step in the near future, for undergraduate and graduate training, as well as allowing designers and engineers to optimize the process of hydroforming of different 2-layer tubes, reducing costs, improving accuracy, flexible design, minimizing risks, and increasing efficienc

INFLUENCE OF STRUCTURAL PARAMETERS ON OPTICAL CHARACTERISTICS OF PHOTONIC CRYSTAL FIBERS WITH CIRCULAR LATTICE

We demonstrate in this study that near-zero, ultra-flattened chromatic dispersion can be achieved over a wide range of wavelengths in photonic crystal fibers (PCFs) by means of slight variations in the geometrical parameters of the cladding. To do that, a new solid-core circular PCF design with various air hole diameters and lattice constants is presented, and the design features are numerically analyzed in detail. After 40 simulations, we determined three structures that possess optimal dispersion with the following lattice constants (Ʌ) and filling factors for the first ring (d1/Ʌ): Ʌ = 0.8 µm, d1/Ʌ = 0.45 for #F1, Ʌ = 0.9 µm, d1/Ʌ = 0.45 for #F2, and Ʌ = 1.0 µm, d1/Ʌ = 0.45 for #F3. High nonlinearity and low attenuation are outstanding features of our model. With these advantages, the proposed fibers are targeted for smooth flat broadband supercontinuum generation for near-infrared applications

Characterization of pig farms in Hung Yen, Hai Duong and Bac Ninh provinces

peer reviewedIn order to characterization of pig farms in the Red River Delta, a study was conducted on 90 pig farms in Hung Yen, Hai Duong and Bac Ninh provinces from June to December 2006. Results show that most of the pig farms had been built for five years with a small size (0.5 hectare per farm). The invested capital was about 300-400 millions VND per farm. Four main sow groups used in the farms included crossbred exotic sows (51.1%), crossbred sow between local and exotic breeds (14.4%), purebred Landrace and Yorkshire breeds (15.6 and 18.9%, respectively). The boars were various (Duroc 30%, Yorkshire 21%, Landrace 13%, PiÐtrain × Duroc 36% and others). The pigs farms were faced with several difficulties such as limited land, lack of invested capital, uncontrolled quality of breeding pigs, high costs of feed, poor hygiene condition and diseases

Comparison of dispersion characteristics of hollow-core photonic crystal fibers filled with aromatic compounds

In this paper, hollow-core photonic crystal fibers (PCFs) infiltrated with benzene and nitrobenzene are designed and investigated. Their dispersion characteristics are numerically simulated. The results show that using the aromatic-compounds-filled hollow core of PCFs makes dispersion curves flat. In addition, the dispersion curves approach the zero-dispersion line closer than previously published dispersion curves of PCFs with toluene, thus significantly improving the supercontinuum generation to create the ultra-flat spectrum expansion

ViCGCN: Graph Convolutional Network with Contextualized Language Models for Social Media Mining in Vietnamese

Social media processing is a fundamental task in natural language processing with numerous applications. As Vietnamese social media and information science have grown rapidly, the necessity of information-based mining on Vietnamese social media has become crucial. However, state-of-the-art research faces several significant drawbacks, including imbalanced data and noisy data on social media platforms. Imbalanced and noisy are two essential issues that need to be addressed in Vietnamese social media texts. Graph Convolutional Networks can address the problems of imbalanced and noisy data in text classification on social media by taking advantage of the graph structure of the data. This study presents a novel approach based on contextualized language model (PhoBERT) and graph-based method (Graph Convolutional Networks). In particular, the proposed approach, ViCGCN, jointly trained the power of Contextualized embeddings with the ability of Graph Convolutional Networks, GCN, to capture more syntactic and semantic dependencies to address those drawbacks. Extensive experiments on various Vietnamese benchmark datasets were conducted to verify our approach. The observation shows that applying GCN to BERTology models as the final layer significantly improves performance. Moreover, the experiments demonstrate that ViCGCN outperforms 13 powerful baseline models, including BERTology models, fusion BERTology and GCN models, other baselines, and SOTA on three benchmark social media datasets. Our proposed ViCGCN approach demonstrates a significant improvement of up to 6.21%, 4.61%, and 2.63% over the best Contextualized Language Models, including multilingual and monolingual, on three benchmark datasets, UIT-VSMEC, UIT-ViCTSD, and UIT-VSFC, respectively. Additionally, our integrated model ViCGCN achieves the best performance compared to other BERTology integrated with GCN models

EVALUATION OF THE VULNERABILITY OF THE COASTAL SOCIO-NATURAL SYSTEMS (EXAMPLE FROM KHANH HOA COASTAL ZONE)

Joint Research on Environmental Science and Technology for the Eart