Conventional Methods Research Articles

Effect of Ca doping on Li ion conductivity of Ge and Ta doped garnet LLZO

The series Li6.55+xGe0.05La3-xCaxZr1.75Ta0.25O12 (x = 0, 0.05, 0.10, 0.15, 0.20) was prepared by conventional solid state reaction method with the sintering temperature of 1050 °C for 7.30 h by substituting Ca at the La site to increase the Li ion conductivity. The synergistic effects of Ca incorporation on Li6.55Ge0.05La3Zr1.75Ta0.25O12 were studied using various structural and electrochemical analyses. X-ray diffraction, scanning electron microscopy, and Impedance analysis were used to determine the crystal structure, morphology, and AC conductivity of the prepared ceramic samples, respectively. The highest conductivity of 9.95 x 10−4 S/cm was obtained for a 0.05 Ca ceramic sample with minimum activation energy of 0.23 eV. The DC polarization measurements confirmed the dominance of ionic conduction in 0.05 Ca ceramic. The results obtained make the 0.05 Ca ceramic sample a promising candidate as solid electrolytes for all solid state Li-ion batteries (ASSLIBs).

Calculation and Analysis of Equilibrium Position of Aerostatic Bearings Based on Bivariate Interpolation Method

The solution of equilibrium positions is a critical component in the calculation of the dynamic characteristic coefficients of aerostatic bearings. The movement of the rotor in one direction leads to bidirectional variations in the air film force, resulting in low efficiency when using conventional calculation methods. It can even lead to iterative divergence if the initial value is improperly selected. This study concentrates on the orifice throttling aerostatic bearings and proposes a novel method called the bivariate interpolation method (BIM) to calculate the equilibrium position. The equilibrium equation for the rotor under the combined influence of air film forces, gravity, and external loads is established. A calculation program based on the finite difference method is developed to determine the equilibrium position. The process of solving the equilibrium position and the convergence is compared with the secant method and the search method. Furthermore, the variation trend of the equilibrium position and stiffness when the external loads changes are studied based on the BIM. Finally, the correctness of the BIM to solve the equilibrium position is proved by comparing it with the experiment results. The calculation results indicate that the BIM successfully resolves the problem of initial value selection and exhibits superior computational efficiency and accuracy. The equilibrium position initially moves away from the direction of the external load as the load increases, and then this gradually approaches the load direction. The main stiffness increases with increases in the external load, while the variation in cross stiffness depends on the direction of the external load.

Fog Hand Wash Machine to Save Water

The global challenge of water scarcity calls for innovative solutions to conserve this precious resource. In response, the fog hand wash machine emerges as a promising technology aimed at revolutionizing hand hygiene practices while minimizing water consumption. This paper presents a comprehensive overview of the fog hand wash machine, detailing its design, functionality, and potential impact on water conservation efforts. By utilizing a fine mist of water droplets, this machine effectively cleans hands with significantly less water compared to conventional hand washing methods. Moreover, its compact size and user-friendly interface make it suitable for various settings, including homes, public facilities, and healthcare environments. The fog hand wash machine not only addresses water scarcity concerns but also contributes to promoting hygiene practices, thereby enhancing public health outcomes. This abstract highlights the significance of integrating innovative technologies like the fog hand wash machine into sustainable water management strategies for a more resilient and water-efficient future. Keywords: Fog hand wash machine, Water-saving technology, Hand hygiene, Water conservation, Sustainability, Public health, Innovation, Environmental impact, Hygiene practices, Water scarcity.

Development of a machine‐learning model for microplastic analysis in an FT‐IR microscopy image

AbstractThe escalating concern regarding microplastics (MPs) in the environment has recently accentuated the need for comprehensive analyses across various matrices. Fourier Transfrom Infrared (FT‐IR) microscopy is widely used method for MP identification, but challenges arise due to the presence of secondary materials on real samples, causing inaccuracies in spectral matching. To tackle this issue, we propose a solution: a 1D‐convolution neural network (1D‐CNN) machine‐learning model classifying FT‐IR spectra into 16 polymer species. Using a dataset of 5413 spectra, with 80% (4330) for training and 20% (1083) for external testing, our method achieved 98.59% accuracy for cross‐validation and 92.34% for external validation. This study underscores the efficacy of machine learning in discerning polymer types among MPs, even in real samples tainted by secondary materials. The implementation of our 1D‐CNN model marks a significant leap in overcoming conventional method limitations, providing a robust tool for accurately unraveling MPs intricacies in environmental matrices.

Nanopore Sequencing Technology as an Emerging Tool for Diversity Studies of Plant Organellar Genomes

In this comprehensive review, we explore the significant role that nanopore sequencing technology plays in the study of plant organellar genomes, particularly mitochondrial and chloroplast DNA. To date, the application of nanopore sequencing has led to the successful sequencing of over 100 plant mitochondrial genomes and around 80 chloroplast genomes. These figures not only demonstrate the technology’s robustness but also mark a substantial advancement in the field, highlighting its efficacy in decoding the complex and dynamic nature of these genomes. Nanopore sequencing, known for its long-read capabilities, significantly surpasses traditional sequencing techniques, especially in addressing challenges like structural complexity and sequence repetitiveness in organellar DNA. This review delves into the nuances of nanopore sequencing, elaborating on its benefits compared to conventional methods and the groundbreaking applications it has fostered in plant organellar genomics. While its transformative impact is clear, the technology’s limitations, including error rates and computational requirements, are discussed, alongside potential solutions and prospects for technological refinement.

Prediction of Corrosion Inhibition Efficiency Based on Machine Learning for Pyrimidine Compounds: A Comparative Study of Linear and Non-linear Algorithms

The corrosion of materials poses a significant challenge in various industries, leading to substantial economic impacts. In this context, pyrimidine compounds emerge as promising, non-toxic, cost-effective, and versatile corrosion inhibitors. However, conventional methods for identifying such inhibitors are typically time-consuming, expensive, and labor-intensive. Addressing this challenge, our study leverages machine learning (ML) to predict pyrimidine compounds corrosion inhibition efficiency (CIE). Using a quantitative structure-property relationship (QSPR) model, we compared 14 linear and 12 non-linear ML algorithms to identify the most accurate predictor of CIE. The bagging regressor model demonstrated superior performance, achieving a root mean square error (RMSE) of 5.38, a mean square error (MSE) of 28.93, a mean absolute error (MAE) of 4.23, and a mean absolute percentage error (MAPE) of 0.05 in predicting the CIE values for pyrimidine compounds. This research marks a significant advancement in corrosion science, offering a novel and efficient ML-based approach as an alternative to traditional experimental methods. It shows that machine learning can quickly and accurately determine how well organic chemical inhibitors like pyrimidine stop material corrosion. This method gives the industry a new perspective and a workable solution to a problem that has existed for a long time.
 Keywords: machine learning, corrosion inhibition, pyrimidine, QSPR model, predictive analysis

Awareness of Gig Economy in Malaysia: Study At International University of Malaya-Wales

Digitalization has transformed the world of business tremendously. The world of employment has shifted from a conventional method to a more flexible and seamless way. A gig economy has opened secondary careers that have created more opportunities that consequently have boosted the country’s economy. This secondary career is referred to as “freelancing”, or work on a job basis. In Malaysia, awareness and knowledge on this matter is still lacking and needs more studies and investigation. Past studies in Malaysia found that the gig economy faces challenges in terms of job security and safety, protection policies, proper platforms and dissemination, etc. Due to this, more studies are required to examine better development and implementation for gig communities. The findings will facilitate the development of better platforms and communities for a gig economy. Thus, this study aims to understand the awareness and knowledge of Malaysian private higher education staff and students on the gig economy. As such, this study specifically gathers data at the International University of Malaya-Wales. The findings will provide insights to lecturers, students, even alumni on how this kind of economy will benefit them and other stakeholders. These findings will also enrich the current data and information for policymakers, employers, and practitioners.
 Keywords: gig economy, private university, human resource, awareness, knowledge

Optimization Method of Multi-Mode Model Predictive Control for Wind Farm Reactive Power

This paper presents a novel approach for optimizing wind farm control through the utilization of a combined model predictive control method. In contrast to conventional methods of controlling active and reactive power in wind farms, the suggested approach integrates a wind power prediction model driven by a neural network and a state-space model for wind turbines. This combination facilitates a more precise forecast of active power, thereby enabling the dynamic prediction of the range of reactive power output from the wind turbines. When combined with the equation of state in wind farm space, it is possible to accurately optimize the reactive power of a wind farm. Furthermore, the impact of active power on voltage fluctuations in the wind farm collector system was examined. The utilization of model predictive control enhances voltage regulation, optimizes system redundancy, and increases the reactive capacity. Sensitivity coefficients were calculated using analytical methods to enhance computational efficiency and to resolve issues related to convergence. In order to validate the proposed methodology and control scheme, a wind farm simulation model comprising 20 turbines was developed to assess the feasibility of the scheme.

ANALISIS PERHITUNGAN UNIT COST PELAYANAN SIRKUMSISI DENGAN PENDEKATAN ABC DI KLINIK SETIA BUDI JAMBI

Circumcision costing couter and conventional methods in Setia Budi Clinic Jambi using traditional accounting systems, so the services offered to be cheaper (under costing) or more expensive (over costing) of the costs that should be consumed on these services. It would be fatal to the hospital, especially in a highly competitive market conditions. Thus researchers need to review the unit cost in the circumcision services costing more accurate in the details of the cost and accuracy of charging better, then a decision will be taken by the management would be better and appropriate. Research performed using a qualitative descriptive design. Instruments used were documentation guidelines owned by hospital and stopwatch. Cost analysis method used is based on ABC (Activity Based Costing) system. The results of this study show units of cost to perform circumcision services at Setia Budi Clinic Jambi which is calculated using the Activity Based Costing (ABC) system is Rp 240.242,59 for the M conventional services and Rp 385.200,57 for M couter services. From the calculation of unit cost pelayananan circumcision in Clinical Setia Budi Jambi is calculated using the ABC method gives results smaller M convenstional service. While in service M couter, ABC calculation gives greater results.

Application of Blockchain Technology in the Management of Legal Documents

Blockchain technology has emerged as a transformative solution for securely managing legal documents, offering unparalleled benefits such as transparency, immutability, and enhanced security. This paper provides a comprehensive exploration of the application of blockchain in the management of legal documents, aiming to revolutionize traditional document management practices. The paper commences with an in-depth overview of blockchain technology, elucidating its decentralized nature, cryptographic security, and consensus mechanisms. It delves into the critical importance of managing legal documents securely, citing examples of the sensitive information encapsulated within legal documents and the vulnerabilities of traditional document management systems. A thorough literature review is conducted to analyse the utilization of blockchain in document management, juxtaposing blockchain-based solutions with conventional methods and underscoring the advantages of employing blockchain for legal document management. The review also scrutinizes the challenges and limitations of integrating blockchain in this context, such as scalability issues and regulatory complexities. The paper further presents illuminating case studies of real-world applications of blockchain in managing legal documents, offering insightful perspectives into the benefits and hurdles encountered in each scenario. Additionally, it outlines potential future developments in blockchain technology for legal document management, advocating for continued research to fully harness the transformative potential of blockchain in revolutionizing legal document management practices

Horizontal transverse isotropy anisotropic parameter inversion via azimuthal seismic velocity anisotropy and its application to anisotropic 3D in-situ stress estimation

Anisotropic parameter inversion in horizontal transverse isotropy (HTI) media plays an important role in predicting the fracture density and the anisotropic in-situ stress for unconventional reservoirs. The current industry practice is to use the azimuthal PP-wave reflection coefficient to estimate the HTI anisotropic parameters. Based on the linear slip theory, we develop an innovative approach that uses azimuthal P-wave phase velocity to calculate HTI anisotropic parameters, which presents superiority over the conventional azimuthal PP-wave reflection coefficient inversion. Specifically, we first verify that the azimuthal P-wave phase velocity is for the HTI elliptical fitting than the azimuthal PP-wave reflection coefficient using the analytical formulations. Second, we sort the prestack wide-azimuth data into offset vector tile sectors and perform amplitude-variation-with-offset inversion at each azimuth. Third, we apply an elliptical fitting to the obtained azimuthal P-wave phase velocities to estimate the HTI anisotropic parameters, fracture density, and fracture direction. Fourth, based on the HTI mechanical earth model, we formulate a cost-effective 3D in-situ stress estimation method using the obtained elastic parameters and fracture compliance. Finally, field examples from the Zhaotong area, China, demonstrate that the estimated fracture density and anisotropic in-situ stress are more accurate and have higher resolution compared with conventional methods. The dominant stress regime in the study area is a strike-slip faulting regime with a governing orientation of northeast–southwest and presents good alignments with well logs, which demonstrates the reliability and accuracy of our method for predicting fracture density and anisotropic in-situ stress.

New calculation method of the mechanical tensile behaviour of lumen biofibres using statistical comparison with two conventional methods

New calculation method of the mechanical tensile behaviour of lumen biofibres using statistical comparison with two conventional methods

Recent advances in SERS-based bioanalytical applications: live cell imaging

Abstract Raman scattering can provide information on molecular fingerprints, which have been widely applied in various fields of material science and nanobiotechnology. Notably, low interference with water molecules in obtaining the Raman spectra between 500 and 2000 cm−1 made it a powerful spectroscopic tool in biology, such as imaging and signaling for a living cell. To be a robust tool for cell biology, the performance of obtaining molecular-specific information with high sensitivity, high resolution in real time, and without inducing cell damage is strongly required. The conventional fluorescence-based method has been suffered from the rapid photobleaching of organic fluorophores and the lack of molecular information. In contrast, Raman scattering is a promising spectroscopic tool to acquire cellular information, and the extremely low signal intensity of Raman scattering could be amplified by incorporating the plasmonic nanomaterials. Along with the fundamental research focus on surface-enhanced Raman scattering (SERS), the practical approaches of SERS for cellular imaging as a new tool for drug screening and monitoring cellular signals have been extensively explored based on new optical setups and new designing strategies for the nanostructures. Diverse nanostructure and surface chemistry for targeting or sensing have been played pivotal roles in acquiring cellular information and high resolution cell imaging. In this regard, this review focused on the recent advances of SERS-based technologies for a live cell imaging investigated such as potential drug screening, signaling for chemicals or biomolecules in cell, in situ sensing, and high spatiotemporal resolution.

Big Data Review of the Influence of Agricultural Sector Development on Economic Resilience

The agricultural sector in the East Java's GDP structure has been stable at around 11% over the past 5 years, despite disruptions caused by the Covid pandemic. The stable development of the agricultural sector has contributed to the region's increased resilience. This study aims to identify the relationship between factors influencing agricultural development and resilience in East Java and to formulate related development strategies. The method used in this study is Correlation and Regression. Regional resilience is viewed as the output of changes in the rate of GDP growth. Factors in agricultural development are viewed from Agricultural Production, Land Factors using Big data, including LST, NDVI, and NDWI, Internet User Farmers and Farmer Populations. The results of the study indicate that significant influential factors in agricultural development are found in NDVI, NDWI, and Farmer Population. The study shows that for East Java, development strategies through digital farming have not yet been able to increase regional resilience, and conventional agricultural development methods still dominate.

A semi-analytical procedure to determine the ion recombination correction factor in high dose-per-pulse beams.

The conventional theories and methods of determining the ion recombination correction factor, such as Boag theory and the related two voltage method and Jaffé plot extrapolation, do not seem to yield accurate results in FLASH /high dose per pulse (DPP) beams ( 10 mGy DPP). This is due to the presence of a large free electron fraction that distorts the electric field inside the chamber sensitive volume. To understand the influence of these effects on the ion recombination correction factor and to develop new expressions for it, it is necessary to re-visit the underlyingphysics. To present a mathematical procedure to develop an analytical expression for the ion recombination correction factor. The expression is the basis for an extrapolation method so the correction factor can be determined in a clinical setting. A semi-analytical solution method, the homotopy perturbation method (HPM), is used to solve the partial differential equations(PDEs) describing the charge carrier physics, including space charge and free electrons. The electron velocity and attachment rate are modeled as functions of the electric field strength. An expression for the charge collection efficiency and ion recombination correction factor are developed. A fit procedure based on this expression is used to compare it to measured data from previously published articles. Another fit procedure using a general equationis also proposed and compared to the data. The series obtained for the charge collection efficiency and the ion recombination correction factor are determined to be asymptotic series and the optimal truncation established. The ion recombination correction factor exhibits a dependency due to the free electron presence. The fit using this expression agrees well with measured data as long as (1) the DPP is below 1 Gy for chambers with a 1 mm plate separation and (2) when the DPP is below 3 Gy for chambers with a 0.5 mm plate separation. In these DPP ranges, the deviation between measured and fit value did not exceed 6%. In both chamber cases the voltage range where the fit applies decreases as DPP increases. The general equationyielded comparable results. The HPM was shown to be applicable to a complex system of PDEs and generate meaningful and novel solutions, as they include both space charge and free electrons. The HPM also lends itself to other chamber geometries. The fit procedure was also shown to yield accurate results for the ion recombination correction up to the 1 Gy DPPlevel.

Impact of Dipole Effect on Perovskite Solar Cells.

Interface modification and bulk doping are two major strategies to improve the photovoltaic performance of perovskite solar cells (PSCs). Dipolar molecules are highly favored due to their unique dipolarity. This review discusses the basic concepts and characteristics of dipoles. In addition, the role of dipoles in PSCs and the corresponding conventional characterization methods for dipoles are introduced. Then, we systematically summarize the latest progress in achieving efficient and stable PSCs in dipole materials at several key interfaces. Finally, we look forward to the future application directions of dipole molecules in PSCs, aiming at providing deep insight and inspiration for developing efficient and stable PSCs.

Weakly Supervised Depth Estimation for 3D Imaging with Single Camera Fringe Projection Profilometry.

Fringe projection profilometry (FPP) is widely used for high-accuracy 3D imaging. However, employing multiple sets of fringe patterns ensures 3D reconstruction accuracy while inevitably constraining the measurement speed. Conventional dual-frequency FPP reduces the number of fringe patterns for one reconstruction to six or fewer, but the highest period-number of fringe patterns generally is limited because of phase errors. Deep learning makes depth estimation from fringe images possible. Inspired by unsupervised monocular depth estimation, this paper proposes a novel, weakly supervised method of depth estimation for single-camera FPP. The trained network can estimate the depth from three frames of 64-period fringe images. The proposed method is more efficient in terms of fringe pattern efficiency by at least 50% compared to conventional FPP. The experimental results show that the method achieves competitive accuracy compared to the supervised method and is significantly superior to the conventional dual-frequency methods.

Accelerating the Phase Formation Kinetics of Alluaudite Sodium Iron Sulfate Cathodes via Ultrafast Thermal Shock.

Alluaudite sodium iron sulfate (NFS) exhibits great potential for use in sodium-ion battery cathodes due to its elevated operating potential and abundant element reserves. However, conventional solid-state methods demonstrate a low heating/cooling rate and sluggish reaction kinetics, requiring a long thermal treatment to effectively fabricate NFS cathodes. Herein, we propose a thermal shock (TS) strategy to synthesize alluaudite sodium iron sulfate cathodes using either hydrous or anhydrous raw materials. The analysis of the phase formation process reveals that TS treatment can significantly facilitate the removal of crystal water and decomposition of the intermediate phase Na2Fe(SO4)2 in the hydrous precursor. In the case of the anhydrous precursor, the kinetics of the combination reaction between Na2SO4 and FeSO4 can be also accelerated by TS treatment. Consequently, pure NFS phase formation can be completed after a substantially shorter time of post-sintering, thereby saving significant time and energy. The TS-treated NFS cathode derived from hydrous precursor exhibits higher retention after 200 cycles at 1C and better rate capability than the counterpart prepared by conventional long-term tube furnace sintering, demonstrating the great potential of this novel strategy.

Synthesis and characterization of (Pb1−x Sr x )MnBO4: a structural and spectroscopic study

Abstract The presence of ns 2 stereo-chemical active lone electron pairs (LEPs) causes asymmetric atomic environments around a given p-block cation, leading to change the crystal chemistry of a respective system. Here we report a series of mullite-type compounds to understand at what extend Sr2+ replaces the stereochemical active Pb2+ cation in (Pb1−x Sr x )MnBO4. Each member of the solid solution has been synthesized by conventional solid-state method. The polycrystalline samples are characterized using X-ray powder diffraction followed by Rietveld refinement. Substitution of Pb2+ with Sr2+ leads to contraction of the a lattice parameter with slight elongation in the b and c direction. For a difference of 1 pm of the ionic radius between Sr2+ and Pb2+, the cell volume contracts about 4 % between the end members as the spatial requirement of the LEP activity in the MBO4 2− channels significantly decreases. Within the solid solution, two distinct Pb/Sr–O2 bond distances significantly differ, which gradually decreases with increasing strontium content leading to a more symmetric coordination around strontium. The calculated BVS of Pb2+/Sr2+ exhibits a linear correlation with the Wang–Liebau eccentricity parameter, indicating to an increased bonding ability cation. The vibrational properties are characterized by both Raman and FTIR spectroscopy, complementing the XPRD results. Electronic band gaps of selected (Pb1−x Sr x )MnBO4 samples were obtained from diffuse reflectance spectroscopy data. Additionally, the Sr containing samples show higher thermal stability than the Pb containing counterparts.

Effect of PVP Molecular Weights on the Synthesis of Ultrasmall Cus Nanoflakes: Synthesis, Properties, and Potential Application for Phototheranostics.

Copper sulfide nanoparticles (CuS) hold tremendous potential for applications in photothermal therapy (PTT) and photoacoustic imaging (PAI). However, the conventional chemical coprecipitation method often leads to particle agglomeration issues. To overcome this challenge, we utilized polyvinylpyrrolidone (PVP) as a stabilizing agent, resulting in the synthesis of small PVP-CuS nanoparticles named PC10, PCK30, and PC40. Our study aimed to investigate how different molecular weights of PVP influence the nanoparticles' crystalline characteristics and essential properties, especially their photoacoustic and photothermal responses. While prior research on PVP-assisted CuS nanoparticles has been conducted, our study delves deeper into this area, providing insights into optical properties. Remarkably, all synthesized nanoparticles exhibited a crystalline structure, were smaller than 10 nm, and featured an absorbance peak at 1020 nm, indicating their robust photoacoustic and photothermal capabilities. Among these nanoparticles, PC10 emerged as the standout performer, displaying superior photoacoustic properties. Our photothermal experiments demonstrated significant temperature increases in all cases, with PC10 achieving an impressive efficiency of 51%. Moreover, cytotoxicity assays revealed the nanoparticles' compatibility with cells, coupled with an enhanced incidence of apoptosis compared to necrosis. These findings underscore the promising potential of PVP-stabilized CuS nanoparticles for advanced cancer theranostics.