Conversion Method Research Articles

A hybrid network TEdgeNeXt for data-limited and resource-constrained fault diagnosis

In the field of intelligent machinery fault diagnosis, overcoming challenges arising from scarce labeled data and the demand for deployment on resource-constrained edge devices is imperative. To address these hurdles, this work aims to improve the ability of deep learning models to learn strong feature representations from limited data, while also reducing the model complexity. We presenting a novel network named TEdgeNeXt, the approach begins with a new signal-to-image conversion method, which is proved to be able to acquire less training data quantity. Structurally, the Convolutional (Conv.) Encoder initially is employed with depth-wise separable convolution to control the size of model rather than the traditional convolution, and the Split Depth-wise Transpose Attention (SDTA) encoder is consequently utilized by leveraging a multidimensional processing approach and the Multi-head Self-Attention which is across the channel dimensions instead of the spatial channel. By doing so, it effectively handles challenges such as high multiply-additions (MAdds) and increased latency through Flops and params. On the other hand, the fine-tune-based transfer learning technique is able to be extended in our approach for improving the capacity of generalizing. Ultimately, it indicates the noticeable improvements in Top-1 Accuracy (T1A), Mean Precision (MP), Mean Recall (MR), and Mean F1 score (MF1) across three distinct datasets.

Variations in soil erodibility (K-factor) for the Chernozems depending on the method of texture determination

Soil erodibility (K-factor) is an important parameter in erosion modeling, is one of five factors of the Revised Universal Soil Loss Equation (RUSLE), and generally represents the soil's response to rainfall and run-off erosivity. The erodibility could be determined based on direct measurements of soil properties and mathematical calculations. In this study, the K-factor was calculated based on a formula from RUSLE, proposed by Renard et al. (1997). All input parameters: soil organic carbon (SOC), soil structure, and permeability classes were measured by one method, but particle size distribution – in two ways by sedimentation and laser diffraction methods to assess the impact the K-factor variability and the values of soil erosion rates. The 107 soil samples of Chernozems from Kursk Oblast (Russia) were studied. The texture for the most of samples was classified as silty loam in both analyses. However, the laser diffraction underestimates the clay content by an average of 13.2% compared to the pipette method. The average K-factor estimated based on laser diffraction data was 0.050, and 0.034 t ha h ha−1 MJ−1 mm−1 – sedimentation method. Thus, depending on the method of soil texture analysis, the RUSLE calculated soil loss could underestimated/overstated by 32% (or 4 t ha-1 yr-1 on average in the study site). Therefore, we propose a regression equation-based conversion method of laser diffraction data to sedimentation method data for Chernozems.The Laska-TM laser analyzer measured on ∼ 13% less clay fraction (more on ∼ 8% silt and ∼ 5% fine sand) compared with sedimentation method data.For erosional researchers/modelers it is suggested to state the method of soil texture analysis (based on sedimentation law or laser diffraction) was used for RUSLE K-factor calculations.To convert K-factor values (for Chernozems) calculated and based on data of the sedimentation method to laser sedimentation – it suggested utilize the coefficient 1.47 (0.68 – vice versa).

The Effect of Varying the Light Spectrum of a Scene on the Localisation of Photogrammetric Features

In modern digital photogrammetry, an image is usually registered via a digital matrix with an array of colour filters. From the registration of the image until feature points are detected on the image, the image is subjected to a series of calculations, i.e., demosaicing and conversion to greyscale, among others. These algorithms respond differently to the varying light spectrum of the scene, which consequently results in the feature location changing. In this study, the effect of scene illumination on the localisation of a feature in an image is presented. The demosaicing and greyscale conversion algorithms that produce the largest and smallest deviation of the feature from the reference point were assessed. Twelve different illumination settings from polychromatic light to monochromatic light were developed and performed, and five different demosaicing algorithms and five different methods of converting a colour image to greyscale were analysed. A total of 300 different cases were examined. As the study shows, the lowest deviation in the polychromatic light domain was achieved for light with a colour temperature of 5600 K and 5000 K, while in the monochromatic light domain, it was achieved for light with a green colour. Demosaicing methods have a significant effect on the localisation of a feature, and so the smallest feature deviation was achieved for smooth hue-type demosaicing, while for greyscale conversion, it was achieved for the mean type. Demosaicing and greyscale conversion methods for monochrome light had no effect. The article discusses the problem and concludes with recommendations and suggestions in the area of illuminating the scene with artificial light and the application of the algorithms, in order to achieve the highest accuracy using photogrammetric methods.

The Research Progress of Magnesium Alloy Building Formwork.

Building formwork is a kind of temporary supporting structure consumable material used in the construction field. In recent years, building formwork has gradually developed to become lighter, more environmentally friendly, and have higher performance. This sets higher requirements for the materials used to make building formwork. There is an urgent need to find a lighter and more durable material for building formwork. Magnesium alloys possess the advantages of low density, high alkali resistance, and high strength. As a building formwork material, it can reduce the weight of formwork and improve its durability. Therefore, a magnesium alloy is considered a material with high potential for building formwork. Currently, magnesium alloy building formwork has attracted the attention of many companies and research and development institutions, with preliminary research applications and good feedback on usage effects. It is highly possible to obtain the opportunity to put it into market application. However, to be applied on a large scale, there are still some important problems that need to be solved. These problems fall into three main areas, including the relatively low processing efficiency of magnesium alloy materials, the unstable price of magnesium alloys, and the fact that the formwork is easily corroded during storage. Firstly, at present, the main processing methods for magnesium alloy building formwork are casting and extrusion, and the production efficiency of both methods needs to be improved. Secondly, high-performance magnesium alloy materials are usually more expensive, which is not conducive to the large-scale application of the formwork. The price of magnesium alloys has fluctuated greatly in recent years, which increases the difficulty of promoting magnesium alloy building formwork. Thirdly, in the atmosphere, the oxide film on the surface of the magnesium alloy cannot play an effective role in corrosion resistance. So, surface treatment is necessary for magnesium alloy building formwork. Among the various surface treatment methods for magnesium alloys, the chemical conversion method has the advantages of being easy to operate, cost-effective, and having good corrosion resistance. It may be a very suitable protective method for large-scale applications of magnesium alloy building formwork and possesses excellent potential for application. The future of magnesium alloy building formwork will focus on new low-cost materials, high-efficiency processing technology, and low-cost green anti-corrosion technology. With in-depth research and the maturation of technology, magnesium alloy formwork is expected to play a more important role in the construction industry.

Dry-gel conversion synthesis sponge-based MIL-160 monolith adsorbent at low temperature for water adsorption

The facile synthesis MOFs monolith adsorbent is highly imperative for the economically friendly development of water adsorption. Herein, metal-organic framework material MIL-160 monolith was synthesized by the dry-gel conversion method at low temperature. The effects of curing conditions, dry-gel composition and crystallization temperature on crystal structure, porosity, microstructure and water vapor adsorption/desorption properties were studied. XRD results showed that the MIL-160 powder and monolith adsorbent can be synthesized under the condition that the molar ratio of dry-gel was Al3+: FDCA: NaOH = 1:1:2 at 60 °C (FDCA is the abbreviation of 2,5-Furandicarboxylicacid). The water vapor saturation adsorption capacity and water vapor desorption activation energy of the powder and monolith adsorbent were 0.310, 0.231 g/g at 20 % RH and 72.3, 62.4 kJ/mol, respectively. The convenient dry-gel conversion synthesis of MIL-160 monolith may provide a guidance for the manufacture of high-performance water harvest device.

Taking Advantage of Potential Coincidence Region: Insights into Gas Production Behavior in Advanced Self-Activated Hydrazine-Assisted Alkaline Seawater Electrolysis.

Water electrolysis assisted by hydrazine has emerged as a prospective energy conversion method for achieving efficient hydrogen generation. Due to the potential coincidence region (PCR) between the hydrogen evolution reaction (HER) and the electro-oxidation of hydrazine, the hydrazine oxidation reaction (HzOR) offers distinct advantages in terms of strategy amalgamation, device architecture, and the broadening of application horizons. Herein, we report a bifunctional electrocatalyst of interfacial heterogeneous Fe2P/Co2P microspheres supported on Ni foam (FeCoP/NF). Benefiting from the strong interfacial coupling effect between Fe2P and Co2P and the three-dimensional microsphere structure, FeCoP/NF exhibits outstanding bifunctional electrocatalytic performance, achieving 10 mA cm-2 with low overpotentials of 10 and 203 mV for HER and HzOR, respectively. Utilizing FeCoP/NF for both electrodes in HzOR-assisted water electrolysis results in significantly reduced potentials of 820 mV for 1 A cm-2 in contrast to the electro-oxidation of alternative chemical substrates. The presence of a potential coincidence region makes the application of self-activated seawater electrolysis realistic. The gas production behavior at different current densities in this interesting hydrogen production system is discussed, and some rules that are distinguished from conventional water electrolysis are summarized. Furthermore, a new self-powered hydrogen production system with a direct hydrazine fuel cell, rechargeable Zn-hydrazine battery, and hydrazine-assisted seawater electrolysis is proposed, emphasizing the distinct benefits of HzOR and its potential role in electrochemical energy conversion technologies powered by renewable sources.

Swin-FER: Swin Transformer for Facial Expression Recognition

The ability of transformers to capture global context information is highly beneficial for recognizing subtle differences in facial expressions. However, compared to convolutional neural networks, transformers require the computation of dependencies between each element and all other elements, leading to high computational complexity. Additionally, the large number of model parameters need extensive data for training so as to avoid overfitting. In this paper, according to the characteristics of facial expression recognition tasks, we made targeted improvements to the Swin transformer network. The proposed Swin-Fer network adopts the fusion strategy from the middle layer to deeper layers and employs a method of data dimension conversion to make the network perceive more spatial dimension information. Furthermore, we also integrated a mean module, a split module, and a group convolution strategy to effectively control the number of parameters. On the Fer2013 dataset, an in-the-wild dataset, Swin-Fer achieved an accuracy of 71.11%. On the CK+ dataset, an in-the-lab dataset, the accuracy reached 100%.

Exergy analysis of direct method for conversion of natural gas to methanol

The exergy analysis of a direct method for the conversion of natural gas to methanol is reported in this work. The study is part of a process development effort to identify areas of improvement to the technology of direct conversion of natural gas to methanol. Prior to the exergy analysis, different configurations of the direct conversion process were developed and simulated. Two heat-integrated configurations designated as Case I and Case II were considered plausible. The exergy efficiency, excluding exergy of the rejected heat, of Case I and Case II were determined as 33% and 36%, respectively. The 9% increase in efficiency of Case II relative to Case I did not justify the installation of an expander and was therefore screened out. Exergy balance in Case I showed that a total of 56% of the exergy input was lost to internal consumption. The majority of exergy destruction was found to be due to the methanol synthesis reactor (36.0%), heat exchangers (30.1%) and combustion (25.0%). Further analyses of the losses across all heat exchangers indicated a nonlinear relationship between exergy destruction contribution and minimum approach temperature (ΔTmin), with a minimal at ΔTmin of 10 °C. The methanol product was determined to represent 18% of exergy input, excluding the air separation unit. The overall process efficiencies were found to be 18% (LHV) and 24% (LHV) for recycle split fractions of 90% and 98%, respectively. The results of this work would provide further insight into the exergy viability of the technology of direct conversion of natural gas to methanol.

Social responsibility of nursing in policies of health humanization

Background: new conceptions of the world have focused on restructuring health policies and designing a new healthcare model.Objective: to reflect on the humanization policy as part of health promotion with emphasis on nursing care.Content: The article mentions paradigm changes and refers to the biomedical model and the new condition of diversity in models of care practices for health promotion and co-responsibility of nursing in generating and sustaining the humanization of nursing care. It rethinks strategies and commitment to co-responsibility by nursing staff in promoting population health. Participation of nurses in promoting humanization care has shown signs of development in its acceptance, bonding healthcare service professionals and its users. An interview-conversation as a strategy for collecting information is highlighted, whether to care or to research based on a humanization framework.Conclusions: Sensitive listening, modality of dialogue, and the conversational interview method are relationship techniques and means to acquire skills for policy development in humanizing care in health promotion.

Bi4O5Br2 co-modified with oxygen vacancy and Bi metal for efficient photothermal conversion of CO2 to C2 hydrocarbons

Photothermal catalytic reduction of CO2 into high value-added C2 hydrocarbon products is a promising method for efficient CO2 conversion. However, current photocatalysts still encounter obstacles including limited photoabsorption range, rapid recombination of photogenerated carriers, and inadequate surface active sites. Herein, Bi4O5Br2 co-modified with oxygen vacancy (OV) and metal bismuth (Bi) (Bi4O5Br2-OV@Bi) has been prepared to optimize these crucial issues. Bi4O5Br2-OV@Bi delivers a remarkably improvement in CO2 photothermal conversion, reflecting by the notable increase in C1 (CO and CH4) and newly generated C2 (C2H4 and C2H6) products compared to pristine Bi4O5Br2. In situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) spectrometry reveals that OC−COH* intermediate promotes the C–C coupling for produce C2 hydrocarbons. This study strengthens the understanding of metal modification and defect engineering for forming C2 hydrocarbons on bismuth-based photocatalysts.

Research Progress of Functional Materials for Conversion of Agricultural Biomass Wastes

Excess agricultural biomass waste is increasing rapidly, leading to many environmental and governance issues. Therefore, increased attention has been paid to the recycling and value-added application of agricultural biomass waste. In recent years, the research of agricultural biomass waste utilization and derived functional materials has mainly included the following two aspects： ① the extraction of natural polymers and value-added applications and ② the direct preparation of new carbon-based materials, including adsorption, catalysis, energy storage electrode, and composite functional materials. The conversion of agricultural biomass waste into functional materials has been gradually realized and widely used. To enable industrial-scale production and the quality and safety of agricultural biomass waste derivatives and to develop highly feasible and cost-effective biomass waste conversion methods should be the focus of future studies.

Program Design to Improve Punctual Graduates of Students in the Unsika Industrial Engineering Study Program by Using the 5C-4C Knowledge Conversion Method

The Faculty of Engineering, University of Singaperbangsa Karawang (Unsika) was established in 1995, one of which is the S1 Industrial Engineering (IT) Study Program, officially registered in 1996. Currently, the faculty is trying to achieve Superior Accreditation or A. The number of applicants for the Industrial Engineering Study Program will increase in 2023, reaching 891 prospective students through the SNBT route, but the capacity can only accommodate 56 people. However, it is in demand as the 4th out of 29 study programs at Unsika. The increase in the number of students is not in line with the on-time graduation rate. This study aims to identify the results of grouping students of the Industrial Engineering Study Program (S1) using the 5C-4C (Knowledge Conversion) process and then implement the relationship with learning activities for the 2017, 2018 and 2019 batches. Next, the data is transformed into information by using the 5C knowledge conversion method: contextualization, categorization, calculation, correction, and condensing. In order to build a program that increases the percentage of students who graduate on time, this information is transformed into knowledge utilizing the 4C knowledge conversion method: comparison, consequence, connections, and conversation. In this study, the population focus is on students of the Industrial Engineering Study Program from three batches, namely 2014, 2015, and 2016. The results of grouping Industrial Engineering students using the 5C process provide a deep understanding of the characteristics and factors that affect learning achievement. This provides a solid foundation for designing appropriate programs to increase the on-time graduation rate.

Gesture Recognition of Filipino Sign Language Using Convolutional and Long Short-Term Memory Deep Neural Networks

In response to the recent formalization of Filipino Sign Language (FSL) and the lack of comprehensive studies, this paper introduces a real-time FSL gesture recognition system. Unlike existing systems, which are often limited to static signs and asynchronous recognition, it offers dynamic gesture capturing and recognition of 10 common expressions and five transactional inquiries. To this end, the system sequentially employs cropping, contrast adjustment, grayscale conversion, resizing, and normalization of input image streams. These steps serve to extract the region of interest, reduce the computational load, ensure uniform input size, and maintain consistent pixel value distribution. Subsequently, a Convolutional Neural Network and Long-Short Term Memory (CNN-LSTM) model was employed to recognize nuances of real-time FSL gestures. The results demonstrate the superiority of the proposed technique over existing FSL recognition systems, achieving an impressive average accuracy, recall, and precision rate of 98%, marking an 11.3% improvement in accuracy. Furthermore, this article also explores lightweight conversion methods, including post-quantization and quantization-aware training, to facilitate the deployment of the model on resource-constrained platforms. The lightweight models show a significant reduction in model size and memory utilization with respect to the base model when executed in a Raspberry Pi minicomputer. Lastly, the lightweight model trained with the quantization-aware technique (99%) outperforms the post-quantization approach (97%), showing a notable 2% improvement in accuracy.

Selective Conversion of Glycerol to Lactic Acid in Water via Acceptorless Dehydrogenation Catalyzed by a Water-Soluble Metal-Ligand Bifunctional Iridium Catalyst.

An efficient method for the selective conversion of glycerol, the major byproduct of the biodiesel manufacturing process, to lactic acid in water via acceptorless dehydrogenation has been developed. In the presence of a water-soluble [Cp*Ir(6,6'-(OH)2-2,2'-bpy)(H2O)][OTf]2 (0.1 mol %) and KOH (1.1 equiv), the reaction proceeded at 120 °C for 24 h to afford the desired product in >99% yield with >99% selectivity. It was confirmed that OH functional groups in the ligand were crucial for the activity of the iridium complex. Furthermore, density functional theory calculations and mechanistic experiments were also undertaken.

The use of venous blood gas in assessing arterial acid−base and oxygenation status – an analysis of aggregated data from multiple studies evaluating the venous to arterial conversion (v-TAC) method

ABSTRACT Background Several methods exist to reduce the number of arterial blood gases (ABGs). One method, Roche v-TAC, has been evaluated in different patient groups. This paper aggregates data from these studies, in different patient categories using common analysis criteria. Research design and methods We included studies evaluating v-TAC based on paired arterial and peripheral venous blood samples. Bland-Altman analysis compared measured and calculated arterial values of pH, PCO2, and PO2. Subgroup analyses were performed for normal, chronic hypercapnia and chronic base excess, acute hyper- and hypocapnia, and acute and chronic base deficits. Results 811 samples from 12 studies were included. Bias and limits of agreement for measured and calculated values: pH 0.001 (−0.029 to 0.031), PCO2 −0.08 (−0.65 to 0.49) kPa, and PO2 0.04 (−1.71 to 1.78) kPa, with similar values for all sub-group analyses. Conclusion These data suggest that v-TAC analysis may have a role in replacing ABGs, avoiding arterial puncture. Substantial data exist in patients with chronic hypercapnia and chronic base excess, acute hyper- and hypocapnia, and in patients with relatively normal acid−base status, with similar bias and precision across groups and across study data. Limited data exist for patients with acute and chronic base deficits.

Wideband coherent microwave conversion via magnon nonlinearity in a hybrid quantum system

Frequency conversion is a widely realized physical process in nonlinear systems of optics and electronics. As an emerging nonlinear platform, spintronic devices have the potential to achieve stronger frequency conversion. Here, we demonstrated a microwave frequency conversion method in a hybrid quantum system, integrating nitrogen-vacancy centers in diamond with magnetic thin film CoFeB. We achieve a conversion bandwidth ranging from 0.1 to 12 GHz, presenting an up to 25th order frequency conversion and further display the application of this method for frequency detection and qubits coherent control. Distinct from traditional frequency conversion techniques based on nonlinear electric response, our approach employs nonlinear magnetic response in spintronic devices. The nonlinearity, originating from the symmetry breaking such as domain walls in magnetic films, presents that our method can be adapted to hybrid systems of other spintronic devices and spin qubits, expanding the application scope of spintronic devices and providing a promising on-chip platform for coupling quantum systems.

Hydrothermally fabricated MoTe2/rGO as a proficient electrocatalyst for robust oxygen evolution reaction

The faster depletion of fossil fuels owing to overconsumption has encouraged the invention of eco-friendly energy conversion methods, resulting in an intensifying energy shortage and sustainability issues. The increasing energy demand compels researchers to investigate novel strategies for water electrolysis and energy conversion. However, fabricating a catalyst with minimal overpotential (η) for water oxidation is a difficult task. The recent research investigate the production of MoTe2 nanoparticles imbedded in rGO nanosheet to generate MoTe2/rGO composite using a hydrothermal technique. Various physical procedures were assessed to analyze the structure, vibrational modes, shape and elemental analysis of the prepared composite. The BET calculated surface area for the MoTe2/rGO composite is (62.3 m2 g−1), which is preferable for the OER procedure. The electrochemical results show that the composite exhibits a Tafel value (36 mV dec−1) with η of 201 mV at 10 mA cm−2 current density (j). Chronoamperometric analysis and cyclic endurance of the composite show stability for 42 h. The electrochemical outcomes show that incorporating rGO into MoTe2 increases electrocatalytic surface area, resulting in the greater adsorption of the electrolyte ions and active areas, allowing for rapid adsorption of electrolyte ions and lower resistance. The present study demonstrates a novel way for producing highly efficient rGO-based electrocatalysts, which improve OER efficiency and open up new paths for their widespread use in various applications.

Elephant Grass (Pennisetum purpureum): A Bioenergy Resource Overview

Elephant grass (EG), or Pennisetum purpureum, is gaining attention as a robust renewable biomass source for energy production amidst growing global energy demands and the push for alternatives to fossil fuels. This review paper explores the status of EG as a sustainable bioenergy resource, integrating various studies to present a comprehensive analysis of its potential in renewable energy markets. Methods employed include assessing the efficiency and yield of biomass conversion methods such as pretreatment for bioethanol production, biomethane yields, direct combustion, and pyrolysis. The analysis also encompasses a technoeconomic evaluation of the economic viability and scalability of using EG for energy production, along with an examination of its environmental impacts, focusing on its water and carbon footprint. Results demonstrate that EG has considerable potential for sustainable energy practices due to its high biomass production and ecological benefits such as carbon sequestration. Despite challenges in cost competitiveness with traditional energy sources, specific applications like small-scale combined heat and power (CHP) systems and charcoal production show economic promise. Conclusively, EG presents a viable option for biomass energy, potentially playing a pivotal role in the biomass sector as the energy landscape shifts towards more sustainable solutions; although, technological and economic barriers need further addressing.

SDS-assisted solar evaporation on floating carbon-based hybrid porous evaporator

Solar evaporation systems represent a green and sustainable strategy for obtaining fresh water. However, traditional evaporation processes depend on the heating of bulk water. Recently, floating solar absorbers have demonstrated excellent evaporation efficiency via localized heating at the device–water interface. In this work, a floating carbon-based hybrid porous evaporator was prepared through simple and inexpensive phase conversion methods, effectively improving the water evaporation efficiency two-fold compared to pure water. The evaporators and evaporation process were characterized by mercury porosimeter, scanning electron microscope, near-infrared spectrometer, infrared thermography, and differential scanning calorimetry. Furthermore, by introducing sodium dodecyl sulfate to regulate the surface hydrophobicity and hydrogen bond structure of water at the device–water interface, the evaporation rate was further improved to 1.27 kg·m−2·h−1 (three times that of pure water) at the optimal sodium dodecyl sulfate concentration of 0.3–1 mmol·L−1. The system also demonstrated excellent practical performance and durability in the evaporation of seawater, salt solutions, and under natural sunlight conditions. This work creates a new avenue for the evaporation applications of hydrophobic carbon-based materials and provides a strategy to regulate solar evaporation systems from the perspective of bulk water by introduction of a surfactant.

Numerical heat transfer analysis of bio convective flow of non-Newtonian nanofluid with Darcy-Forchheimer effect over a curved stretching surface

The main aim of this study is to investigate the behavior of bio-convective flow of 2nd grade micropolar nanofluid with Darcy-Forchheimer law over a curved porous stretching surface. The fluid flow analysis includes novel aspects such as the nonuniform heat source/sink, Joule heating, magnetic field, chemical reaction, and thermal radiation. Furthermore, the boundary of the stretching surface is acquired the stratification conditions. A suitable conversion method is employed to transform the flow model into a collection of ordinary differential equations, characterized by their nonlinearity. The bvp4c technique on the MATLAB is utilized to acquire numerical solutions for this set of nonlinear equations. The characteristics of various influential parameters on the velocity, temperature, concentration, and microorganism density profiles are observed and discussed. In the present problem, it is observed that by the growth of micropolar parameter enhances the angular fluid velocity. Moreover, larger values of the magnetic parameter, Darcy number, and porosity parameter result in a decrease in the fluid’s linear velocity. The temperature profile exhibits a decreasing pattern with the elevation thermal stratification parameter, while the opposite trend shows by the increment of the radiation parameter and Eckert number. Additionally, the concentration of nanoparticles decreases as the Schmidt number and Brownian motion parameter increases.