bluuebunny/crossref_metadata_2025 huggingface dataset:
Protocrystallinity of Monodispersed Ultra-Small Templated Mesoporous Silica Nanoparticles
Authors: Bonneviot Laurent , Albela Belén , Gao Feifei , Perriat Pascal , Epicier Thierry , El Eter Mohamad
Published: June 2024

Monodisperse and semi-faceted ultra-small templated mesoporous silica nanoparticles (US-MSNs) of 20–25 nm were synthesized using short-time hydrolysis of tetraethoxysilane (TEOS) at room temperature, followed by a dilution for nucleation quenching. According to dynamic light scattering (DLS), a two-step pH adjustment was necessary for growth termination and colloidal stabilization. The pore size was controlled by cetyltrimethylammonium bromide (CTAB), and a tiny amount of neutral surfactant F127 was added to minimize the coalescence between US-MSNs and to favor the transition towards internal ordering. Flocculation eventually occurred, allowing us to harvest a powder by centrifugation (~60% silica yield after one month). Scanning transmission electron microscopy (STEM) and 3D high-resolution transmission electron microscopy (3D HR-TEM) images revealed that the US-MSNs are partially ordered. The 2D FT transform images provide evidence for the coexistence of four-, five-, and sixfold patterns characterizing an “on-the-edge” crystallization step between amorphous raspberry and hexagonal pore array morphologies, typical of a protocrystalline state. Calcination preserved this state and yielded a powder characterized by packing, developing a hierarchical porosity centered at 3.9 ± 0.2 (internal pores) and 68 ± 7 nm (packing voids) of high potential for support for separation and catalysis.
The Effect of Surface Oxygen Coverage on the Oxygen Evolution Reaction over a CoFeNiCr High-Entropy Alloy
Authors: Yuan Geng , Ruiz Pestana Luis
Published: June 2024

Developing cost-effective and highly active electrocatalysts for the oxygen evolution reaction (OER) is crucial for advancing sustainable energy applications. High-entropy alloys (HEAs) made from earth-abundant transition metals, thanks to their remarkable stability and electrocatalytic performance, provide a promising alternative to expensive electrocatalysts typically derived from noble metals. While pristine HEA surfaces have been theoretically investigated, and the effect of oxygen coverage on conventional metal electrocatalysts has been examined, the impact of surface oxygen coverage on the electrocatalytic performance of HEAs remains poorly understood. To bridge this gap, we employ density functional theory (DFT) calculations to reconstruct the free energy diagram of OER intermediates on CoFeNiCr HEA surfaces with varying oxygen coverages, evaluating their impact on the rate-limiting step and theoretical overpotential. Our findings reveal that increased oxygen coverage weakens the adsorption of HO* and O*, but not HOO*. As a result, the theoretical overpotential for the OER decreases with higher oxygen coverage, and the rate-limiting step shifts from the third oxidation step (HOO* formation) at low coverage to the first oxidation step (HO* formation) at higher coverage.
The Detection of Vaccine Virus and Protection of a Modified Live, Intranasal, Trivalent Vaccine in Neonatal, Colostrum-Fed Calves with an Experimental Bovine Respiratory Syncytial Virus Challenge
Authors: Perkins-Oines Stephanie , Senevirathne Nirosh D. , Krafsur Greta M. , Abdelsalam Karim , Renter David , Meyer Brent , Chase Christopher C. L.
Published: June 2024

The efficacy of an intranasal (IN) bovine respiratory syncytial virus (BRSV) vaccine administered in the presence of passive immunity was assessed. Pooled colostrum was administered by intubation to 50 beef-dairy crossbred calves the day they were born. The calves were transported to a research facility and were blocked by age and sex, and randomly assigned into two groups: sham-vaccinated intranasally with a placebo (sterile water) or vaccinated with a trivalent (BRSV, bovine herpesvirus 1 and bovine parainfluenza 3) modified live viral (MLV) vaccine. The calves were 9 ± 2 days old when vaccinated (day 0). The calves were challenged by aerosolized BRSV on days 80 and 81 as a respiratory challenge. The study was terminated on day 88. Lung lesion scores (LLS) were significantly lower for calves vaccinated with trivalent MLV vaccine than those for calves that were sham-vaccinated. Serum neutralization (SN) antibody against BRSV in calves vaccinated with the trivalent MLV vaccine demonstrated an anamnestic response on day 88. After challenge, the calves sham-vaccinated with the placebo lost weight, while those vaccinated with the trivalent MLV vaccine gained weight. In this study, colostrum-derived antibodies did not interfere with the immune response or protection provided by one dose of the trivalent MLV vaccine.
Few ns Pulse Duration of Gain-Switched Ho:YAG Laser Pumped by an Active Q-Switched Tm:YLF Laser
Authors: Golan Shaul Avichai , Nahear Rotem , Bach Yechiel , Noach Salman
Published: June 2024

This paper describes a gain-switched Ho:YAG laser that emitted at 2089 nm, driven by an actively Q-switched Tm:YLF laser as the pumping source. The laser attained few ns short pulse durations with high energies at controlled repetition rates due to the active Q-switch pump source. Using the gain-switch method, stable short pulse durations ranging from 3.5 to 7.2 ns, with an energy per pulse of 0.4 to 0.52 mJ, were achieved at repetition rates of up to 2.5 kHz. This design can have significant advantages in various fields, where accuracy in the repetition rate is essential and a passive Q-switch cannot be implemented due to its accuracy limitations, including sensing, LIDAR, medical procedures, and material processing.
Angular Deviations, Lateral Displacements, and Transversal Symmetry Breaking: An Analytical Tutorial
Authors: De Leo Stefano , Mazzeo Marco
Published: June 2024

The study of a Gaussian laser beam interacting with an optical prism, both through reflection and transmission, provides a technical tool to examine deviations from the optical path as dictated by geometric optics principles. These deviations encompass alterations in the reflection and refraction angles, as predicted by the reflection and Snell laws, along with lateral displacements in the case of total internal reflection. The analysis of the angular distributions of both the reflected and transmitted beams allows us to understand the underlying causes of these deviations and displacements, and it aids in formulating analytic expressions that are capable of characterizing these optical phenomena. The study also extends to the examination of transverse symmetry breaking, which is a phenomenon observed in the laser beam as it traverses the oblique interface of the prism. It is essential to underscore that this analytical overview does not strive to function as an exhaustive literature review of these optical phenomena. Instead, its primary objective is to provide a comprehensive and self-referential treatment, as well as give universal analytical formulas intended to facilitate experimental validations or applications in various technological contexts.
Impact of Grating Duty-Cycle Randomness on DFB Laser Performance
Authors: Yang Manpo , Kong Xiangpeng , Li Xun
Published: June 2024

The duty-cycle randomness (DCR) of the Bragg grating of the distributed feedback (DFB) lasers introduced by the fabrication process is inevitable, even with state-of-the-art technologies such as electron beam lithography and dry or wet etching.This work investigates the impact of grating DCR on DFB laser performance through numerical simulations. The result reveals that such randomness causes a reduction in the side mode suppression ratio (SMSR), and deteriorates the noise characteristics, i.e., broadens the linewidth and increases the relative intensity noise (RIN). With the grating DCR, the effective grating coupling coefficient decreases as evidenced by the reduced Bragg stopband width. However, the longitudinal spatial hole burning (LSHB) effect in the DFB lasers can somewhat be diminished by the grating DCR. The seriousness of these effects depends on different grating structures and their coupling strengths. Our simulation shows that a degradation of 17 dB can be brought to the SMSR of the uniform grating DFB lasers with their duty cycles taking a deviation of ±25% in a uniformly distributed random fashion. It also broadens the linewidth of the quarter-wavelength phase-shifted DFB lasers by more than 2.5 folds. The impact of this effect on the RIN is moderate—less than 2%. All the performance deteriorations can partially be attributed to the effective reduction in the grating coupling coefficient of around 20% by such a DCR.
Advances in Lensless Fluorescence Microscopy Design
Authors: Khoubafarin Somaiyeh , Dadson Edmond Kwesi , Ray Aniruddha
Published: June 2024

Lensless fluorescence microscopy (LLFM) has emerged as a promising approach for biological imaging, offering a simplified, high-throughput, portable, and cost-effective substitute for conventional microscopy techniques by removing lenses in favor of directly recording fluorescent light on a digital sensor. However, there are several obstacles that this novel approach must overcome, such as restrictions on the resolution, field-of-view (FOV), signal-to-noise ratio (SNR), and multicolor-imaging capabilities. This review looks at the most current developments aimed at addressing these challenges and enhancing the performance of LLFM systems. To address these issues, computational techniques, such as deconvolution and compressive sensing, hardware modifications and structured illumination, customized filters, and the utilization of fiber-optic plates, have been implemented. Finally, this review emphasizes the numerous applications of LLFM in tissue analysis, pathogen detection, and cellular imaging, highlighting its adaptability and potential influence in a range of biomedical research and clinical diagnostic areas.
Influence of Time-Lag Effects between Winter-Wheat Canopy Temperature and Atmospheric Temperature on the Accuracy of CWSI Inversion of Photosynthetic Parameters
Authors: Wang Yujin , Lu Yule , Yang Ning , Wang Jiankun , Huang Zugui , Chen Junying , Zhang Zhitao
Published: June 2024

When calculating the CWSI, previous researchers usually used canopy temperature and atmospheric temperature at the same time. However, it takes some time for the canopy temperature (Tc) to respond to atmospheric temperature (Ta), suggesting the time-lag effects between Ta and Tc. In order to investigate time-lag effects between Ta and Tc on the accuracy of the CWSI inversion of photosynthetic parameters in winter wheat, we conducted an experiment. In this study, four moisture treatments were set up: T1 (95% of field water holding capacity), T2 (80% of field water holding capacity), T3 (65% of field water holding capacity), and T4 (50% of field water holding capacity). We quantified the time-lag parameter in winter wheat using time-lag peak-seeking, time-lag cross-correlation, time-lag mutual information, and gray time-lag correlation analysis. Based on the time-lag parameter, we modified the CWSI theoretical and empirical models and assessed the impact of time-lag effects on the accuracy of the CWSI inversion of photosynthesis parameters. Finally, we applied several machine learning algorithms to predict the daily variation in the CWSI after time-lag correction. The results show that: (1) The time-lag parameter calculated using time-lag peak-seeking, time-lag cross-correlation, time-lag mutual information, and gray time-lag correlation analysis are 44–70, 32–44, 42–58, and 76–97 min, respectively. (2) The CWSI empirical model corrected by the time-lag mutual information method has the highest correlation with photosynthetic parameters. (3) GA-SVM has the highest prediction accuracy for the CWSI empirical model corrected by the time-lag mutual information method. Considering time lag effects between Ta and Tc effectively enhanced the correlation between CWSI and photosynthetic parameters, which can provide theoretical support for thermal infrared remote sensing to diagnose crop water stress conditions.
Preparation and Evaluation of PVDF-HFP-Based Gel Electrolyte for Ge-Sensitized Thermal Cell
Authors: Chai Yadong , Matsushita Sachiko
Published: June 2024

The semiconductor-sensitized thermal cell (STC) is a new thermoelectric conversion technology. The development of nonliquid electrolytes is the top priority for the practical application of the STC. In this study, a novel gel polymer electrolyte (PH-based GPE) composed of poly(vinylidenefluoride-co-hexafluoropropylene) (PH), 1-Methyl-2-pyrrolidone (NMP), and Cu ions was synthesized and applied to the STC system. The PH-based GPE synthesized at 45 °C showed higher open-circuit voltage (−0.3 V), short-circuit current density (59 μA cm−2) and diffusion coefficient (7.82 × 10−12 m2 s−1), indicating that a well-balanced structure among the NMP molecules was formed to generate a high-efficiency conduction path of the Cu ions. Moreover, the ion diffusion lengths decreased with decreasing content rates of NMP for the PH-based GPEs, indicating that the NMP plays an important role in the diffusion of Cu ions. Furthermore, the activation energy was calculated to be 107 kJ mol−1, and that was smaller compared to 150 kJ mol−1 for the poly(ethylene glycol)-based liquid electrolyte. These results play an important reference role in the development of electrolytes for STC systems. At the same time, they also provide a new avenue and reference indicator for the synthesis of high-performance and safe GPEs.
Substrate Neutrality for Obtaining Block Copolymer Vertical Orientation
Authors: Hillery Kaitlyn , Hendeniya Nayanathara , Abtahi Shaghayegh , Chittick Caden , Chang Boyce
Published: June 2024

Nanopatterning methods utilizing block copolymer (BCP) self-assembly are attractive for semiconductor fabrication due to their molecular precision and high resolution. Grafted polymer brushes play a crucial role in providing a neutral surface conducive for the orientational control of BCPs. These brushes create a non-preferential substrate, allowing wetting of the distinct chemistries from each block of the BCP. This vertically aligns the BCP self-assembled lattice to create patterns that are useful for semiconductor nanofabrication. In this review, we aim to explore various methods used to tune the substrate and BCP interface toward a neutral template. This review takes a historical perspective on the polymer brush methods developed to achieve substrate neutrality. We divide the approaches into copolymer and blended homopolymer methods. Early attempts to obtain neutral substrates utilized end-grafted random copolymers that consisted of monomers from each block. This evolved into side-group-grafted chains, cross-linked mats, and block cooligomer brushes. Amidst the augmentation of the chain architecture, homopolymer blends were developed as a facile method where polymer chains with each chemistry were mixed and grafted onto the substrate. This was largely believed to be challenging due to the macrophase separation of the chemically incompatible chains. However, innovative methods such as sequential grafting and BCP compatibilizers were utilized to circumvent this problem. The advantages and challenges of each method are discussed in the context of neutrality and feasibility.
Hydrophobic Deep Eutectic Solvents for Ethanol, Propan-1-ol, and Propan-2-ol Recovery from Aqueous Solutions
Authors: Audeh Dalal J. S. A. , Carniel Adriano , Borges Cristiano Piacsek , Coelho Maria Alice Zarur , Buarque Filipe Smith , Ribeiro Bernardo Dias
Published: June 2024

Separating hydroalcoholic mixtures remains a significant challenge in engineering. Liquid–liquid extraction has emerged as an appealing alternative method, because it avoids the need for the large energy inputs, volatile organic compounds, and high pressures that are typically required by other separation processes. This study explores the use of hydrophobic deep eutectic solvents (HDESs) composed of terpenes and 10-undecenoic acid as extraction agents for the liquid–liquid separation of hydroalcoholic mixtures composed of alcohols (ethanol, propan-1-ol, and propan-2-ol) and water. The water content in the solvents studied was notably low, reflecting their hydrophobic nature. For the dried HDES samples, the water content ranged from 553 to 4901 ppm. In contrast, the water-saturated samples exhibited higher water contents, ranging from 7250 to 20,864 ppm. The HDES based on thymol, DL-menthol, and L-menthol displayed a eutectic point at an xterpenes of approximately 0.67. These mixtures maintained a liquid state up to a mole fraction of terpenes around 0.75. In contrast, the HDES composed of carvacrol, fenchyl alcohol, and α-terpineol exhibited their eutectic point at an xterpenes near 0.5. Notably, these mixtures remained in a liquid state across the entire composition range studied. The 2:1 molar ratio (HBA:HBD) presented the best values for extracting alcohols, reaching 34.04%, 36.59%, and 39.78% for ethanol, propan-2-ol, and propan-1-ol, respectively. These results show that HDES can be applied to overcome issues with existing extraction solvents, increasing the separation efficiency and making the process eco-friendly.
Advancing Wastewater Treatment: A Comparative Study of Photocatalysis, Sonophotolysis, and Sonophotocatalysis for Organics Removal
Authors: Bognár Szabolcs , Jovanović Dušica , Despotović Vesna , Finčur Nina , Putnik Predrag , Šojić Merkulov Daniela
Published: June 2024

Clear and sanitarily adequate water scarcity is one of the greatest problems of modern society. Continuous population growth, rising organics concentrations, and common non-efficient wastewater treatment technologies add to the seriousness of this issue. The employment of various advanced oxidation processes (AOPs) in water treatment is becoming more widespread. In this review, the state-of-the-art application of three AOPs is discussed in detail: photocatalysis, sonophotolysis, and sonophotocatalysis. Photocatalysis utilizes semiconductor photocatalysts to degrade organic pollutants under light irradiation. Sonophotolysis combines ultrasound and photolysis to generate reactive radicals, enhancing the degradation of organic pollutants. Sonophotocatalysis synergistically combines ultrasound with photocatalysis, resulting in improved degradation efficiency compared to individual processes. By studying this paper, readers will get an insight into the latest published data regarding the above-mentioned processes from the last 10 years. Different factors are compared and discussed, such as degradation efficiency, reaction kinetics, catalyst type, ultrasound frequency, or water matrix effects on process performance. In addition, the economic aspects of sonophotolysis, photocatalysis, and sonophotocatalysis will be also analyzed and compared to other processes. Also, the future research directions and potential applications of these AOPs in wastewater treatment will be highlighted. This review offers invaluable insights into the selection and optimization of AOPs.
Image Analysis Techniques Applied in the Drilling of a Carbon Fibre Reinforced Polymer and Aluminium Multi-Material to Assess the Delamination Damage
Authors: Sousa Costa Rúben D. F. , Barbosa Marta L. S. , Silva Filipe G. A. , Silva Tiago E. F. , de Jesus Abílio M. P. , Silva Francisco J. G. , Durão Luís M. P. , Tavares João Manuel R. S.
Published: June 2024

Due to the high abrasiveness and anisotropic nature of composites, along with the need to machine different materials at the same time, drilling multi-materials is a difficult task, and usually results in material damage, such as uncut fibres and delamination, hindering hole functionality and reliability. Image processing and analysis algorithms can be developed to effectively assess such damage, allowing for the calculation of delamination factors essential to the quality control of hole inspection in composite materials. In this study, a digital image processing and analysis algorithm was developed in Python to perform the delamination evaluation of drilled holes on a carbon fibre reinforced polymer (CFRP) and aluminium (Al) multi-material. This algorithm was designed to overcome several limitations often found in other algorithms developed with similar purposes, which frequently lead to user mistakes and incorrect results. The new algorithm is easy to use and, without requiring manual pre-editing of the input images, is fully automatic, provides more complete and reliable results (such as the delamination factor), and is a free-of-charge software. For example, the delamination factors of two drilled holes were calculated using the new algorithm and one previously developed in Matlab. Using the previous Matlab algorithm, the delamination factors of the two holes were 1.380 and 2.563, respectively, and using the new Python algorithm, the results were equal to 3.957 and 3.383, respectively. The Python results were more trustworthy, as the first hole had a higher delamination area, so its factor should be higher than that of the second one.
Dynamic Numerical Simulation and Transfer Learning-Based Rapid Rock Identification during Measurement While Drilling (MWD)
Authors: Fang Yuwei , Wu Zhenjun , Jiang Lianghua , Tang Hua , Fu Xiaodong , Shen Junxin
Published: June 2024

In constructing rapid rock identification models for measurement while drilling (MWD) via neural network methods, collecting actual drilling data to train the model is extremely time-consuming and labor-intensive. This requires extensive drilling experiments in various rock types, resulting in limited neural network training data for rock identification that covers a limited range of rock types. To suitably address this issue, a dynamic numerical simulation model for rock drilling is established that generates extensive drilling data. The input parameters for the simulations include torque, drill bit rotation speed, and drilling speed. A neural network model is then developed for rock classification using large datasets from dynamic numerical simulations, specifically those of granite, limestone, and sandstone. Building upon this model, transfer learning is appropriately applied to store the knowledge obtained in the rock identification based on the neural network model. Further training through transfer learning is conducted with smaller datasets obtained during actual drilling, making the model suitable for practical rock identification and prediction in the drilling processes. The neural network rock classification model, incorporating dynamic numerical simulation and transfer learning, achieves a prediction accuracy of 99.36% for granite, 99.53% for sandstone, and 99.82% for limestone. This reveals an enhancement in prediction accuracy of up to 22.94% compared to the models without transfer learning.
Primary-Side Indirect Control of the Battery Charging Current in a Wireless Power Transfer Charger Using Adaptive Hill-Climbing Control Technique
Authors: Lassioui Abdellah , El Ancary Marouane , El Idrissi Zakariae , El Fadil Hassan , Rachid Kamal , Rachid Aziz
Published: June 2024

This paper addresses the control task of a wireless power transfer (WPT) charger designed for electric vehicles (EVs). The challenge is to maintain a constant battery charging current when the WPT is controlled on the ground side. Indeed, the intermittent latency involved in the wireless data communication between the ground and vehicle sides leads to system instability. To overcome this issue, a new control approach has been proposed in this paper. The proposed technique ensures indirect control of the battery charging current through control of the current on the ground side. The control technique relies on an adaptive hill-climbing algorithm in conjunction with a PI-based controller. The adaptive parameter is adjusted online, during the operation of the charger, only when a new measure of the battery charging current is received on the primary side. This makes it possible to avoid the need for real-time wireless data communication. It should be noted that this aspect is crucial in ensuring the controller’s robustness and stability of the system regardless of potential delays in wireless communication and large misalignments between the coils. The validity of the proposed control technique has been confirmed through simulation. In addition, experimental validation, using a laboratory test bed, demonstrated satisfactory results.
Mineral Water as a Sustainable Raw Material for Skincare Products and Protective Natural Antioxidant from Solar Irradiation: Stability of Vitamin C and In Vitro Antioxidant Assessments
Authors: Bognár Szabolcs , Šojić Merkulov Daniela , Finčur Nina , Putnik Predrag , Katona Gabor , Vojvodić Slađana , Kalić Marina , Nastić Nataša , Jovanović Lješković Nataša
Published: June 2024

Oxygen is crucial for life, but its reactive species, like free radicals, can damage health and accelerate aging. Antioxidants from natural and synthetic sources mitigate these effects. Kanjiža Spa’s mineral-rich thermal water is renowned for its therapeutic benefits and potential in eco-friendly pharmaceuticals and cosmetics. Hence, the utilization of mineral water in pharmaceutical and cosmetic applications when exposed to artificially generated free radicals under simulated solar irradiation and different experimental conditions (pH values and mineral concentrations in the thermal water) was researched. Three different dermocosmetic products designed with raw minerals and water from Kanjiža Spa were tested. Our findings confirmed the protective effect of mineral water, as evidenced by the higher stability of vitamin C in thermal water. The degradation of vitamin C was significantly reduced in the presence of mineral water, with the least degradation occurring at pH = 7, which closely matches human skin pH. These results were further validated using 2,2-diphenyl-1-picrylhydrazyl and ABTS tests. Overall, the obtained results underscore the therapeutic and commercial potential of Kanjiža Spa’s mineral water, suggesting that it could be a valuable ingredient in next-generation skincare and pharmaceutical products.
Mathematical Models for Estimating Diffusion Coefficients in Concentrated Polymer Solutions from Experimental Data
Authors: Asoltanei Adriana Mariana , Iacob-Tudose Eugenia Teodora , Secula Marius Sebastian , Mamaliga Ioan
Published: June 2024

Diffusion processes in operations involving polymeric materials are of significant interest. Determining experimental values for diffusion coefficients is often challenging. Estimating these coefficients in concentrated polymer solution, polymer films, and membranes relies on experimental tests where the polymer is brought into contact with certain components/solvents. The diffusion coefficient values depend on the diffusion type, which is affected mainly by the nature of the polymer, concentration, and temperature. The literature presents an extensive amount of information regarding the diffusion phenomenon. This paper makes a particular contribution by showing how experimental data obtained from different applications can be processed to determine diffusion coefficients. The manuscript addresses some aspects regarding solvent diffusion in polymers, and illustrates how to determine the diffusion coefficients from experimental data. For specific cases of diffusion, several models for the predictive estimation of diffusion coefficients are also presented. Polymer–solvent systems such as polyvinyl alcohol (PVA)–water, cellulose acetate (CA)–tetrahydrofuran (THF) and cellulose triacetate (CTA)–dichloromethane (DCM) are investigated, with their diffusion mechanisms influenced by changes in structure caused by variations in concentration and temperature. The experimental data obtained through a gravitational technique allow for the highlighting of the diffusion mechanism and the selection of an appropriate mathematical model. A change in the structure of the polymer during the experiment leads to diffusion anomalies. Modeling the experimental data yielded diffusion coefficient values that vary based on the type of system investigated, composition and temperature. Thus, in the case of the CTA-DCM system, the diffusion coefficient at 303 K, at various concentration values, is in the range of 4.5 and 8·10−11 m2/s; for the PVA-H2O system, D = 4.1·10−12 m2/s at 303 K, and D = 6.5·10−12 m2/s at 333 K; while for the CA-THF system, the solvent–polymer diffusion coefficient has a value of 2.5∙10−12 m2/s at 303 K, and D = 1.75∙10−11 m2/s at 323 K. Mathematical models can be useful in studies regarding the drying of polymer films with complex structures, providing knowledge for designing or selecting suitable equipment.
High-Density Polyethylene Pipe Butt-Fusion Joint Detection via Total Focusing Method and Spatiotemporal Singular Value Decomposition
Authors: Zhang Haowen , Wang Qiang , Zhou Juan , Wu Linlin , Xu Weirong , Wang Hong
Published: June 2024

High-density polyethylene (HDPE) pipes are widely used for urban natural gas transportation. Pipes are usually welded using the technique of thermal butt fusion, which is prone to manufacturing defects that are detrimental to safe operation. This paper proposes a spatiotemporal singular value decomposition preprocessing improved total focusing method (STSVD-ITFM) imaging algorithm combined with ultrasonic phased array technology for non-destructive testing. That is, the ultrasonic real-value signal data are first processed using STSVD filtering, enhancing the spatiotemporal singular values corresponding to the defective signal components. The TFM algorithm is then improved by establishing a composite modification factor based on the directivity function and the corrected energy attenuation factor by adding angle variable. Finally, the filtered signal data are utilized for imaging. Experiments are conducted by examining specimen blocks of HDPE materials with through-hole defects. The results show the following: the STSVD-ITFM algorithm proposed in this paper can better suppress static clutter in the near-field region, and the average signal-to-noise ratios are all higher than the TFM algorithm. Moreover, the STSVD-ITFM algorithm has the smallest average error among all defect depth quantification results.
Dynamic Monitoring and Change Analysis of Lake Area on the Inner-Mongolian Plateau over the Past 22 Years
Authors: Xing Naichen , Gan Fuping , Yan Bokun , Bai Juan , Guo Yi , Zhuo Yue , Li Ruoyi
Published: June 2024

Lakes are essential components of the terrestrial water cycle. Their size and quantity reflect natural climate change and anthropogenic activities in time. Lakes on the Inner-Mongolian Plateau (IMP) have experienced significant changes in recent decades, but the current situation remains elusive. In this study, we conducted multi-decadal intensive monitoring of lake area and performed comprehensive variation analysis on the IMP. The study involved pre-processing, lake area extraction, post-processing, and lake area analysis procedures using multi-source satellite images. The results reveal the detailed variation in the lake from various aspects. The temporal analysis indicates that the lake area has undergone two distinct periods of decline followed by subsequent increase, and the variation pattern from January to December was diverse. The spatial analysis suggests that the lake area expanded slightly in the western and southern parts, while the area shrank in the other two. Variations in lakes of different sizes exhibited spatial heterogeneity. To some extent, effective actions have led to lake rehabilitation, but it has not yet reached or surpassed the level of 2000. This study provides a substantial data basis and technological guidance for conducting lacustrine surveys. The results can play important roles in fostering further analyses of the water cycle and the carbon cycle.
Landsat-8/9 Atmospheric Correction Reliability Using Scene Statistics
Authors: Groeneveld David , Ruggles Tim , Gao Bo-Cai
Published: June 2024

Landsat data correction using the Land Surface Reflectance Code (LaSRC) has been proposed as the basis for the atmospheric correction of smallsats. While atmospheric correction can enhance smallsat data, the Landsat/LaSRC pathway delays output and may constrain accuracy and utility. The alternative, the Closed-form Method for Atmospheric Correction (CMAC), developed for smallsat application, provides surface reflectance derived solely from scene statistics. In a prior paper, CMAC closely agreed with LaSRC software for correction of the four VNIR bands of Landsat-8/9 images for conditions of low to moderate atmospheric effect over quasi-invariant warehouse-industrial targets. Those results were accepted as surrogate surface reflectance to support analysis of CMAC and LaSRC reliability for surface reflectance retrieval in two contrasting environments: shortgrass prairie and barren desert. Reliability was defined and tested through a null hypothesis: the same top-of-atmosphere reflectance under the same atmospheric condition will provide the same estimate of surface reflectance. Evaluated against the prior surrogate surface reflectance, the results found decreasing error with increasing wavelength for both methods. From 58 comparisons across the four bands, the LaSRC average absolute error ranged from 0.59% (NIR) to 50.30% (blue). CMAC provided reliable results: error was well constrained from 0.01% (NIR) to 0.98% (blue).
A Robust Target Detection Algorithm Based on the Fusion of Frequency-Modulated Continuous Wave Radar and a Monocular Camera
Authors: Yang Yanqiu , Wang Xianpeng , Wu Xiaoqin , Lan Xiang , Su Ting , Guo Yuehao
Published: June 2024

Decision-level information fusion methods using radar and vision usually suffer from low target matching success rates and imprecise multi-target detection accuracy. Therefore, a robust target detection algorithm based on the fusion of frequency-modulated continuous wave (FMCW) radar and a monocular camera is proposed to address these issues in this paper. Firstly, a lane detection algorithm is used to process the image to obtain lane information. Then, two-dimensional fast Fourier transform (2D-FFT), constant false alarm rate (CFAR), and density-based spatial clustering of applications with noise (DBSCAN) are used to process the radar data. Furthermore, the YOLOv5 algorithm is used to process the image. In addition, the lane lines are utilized to filter out the interference targets from outside lanes. Finally, multi-sensor information fusion is performed for targets in the same lane. Experiments show that the balanced score of the proposed algorithm can reach 0.98, which indicates that it has low false and missed detections. Additionally, the balanced score is almost unchanged in different environments, proving that the algorithm is robust.
Quantifying the Impact of Aerosols on Geostationary Satellite Infrared Radiance Simulations: A Study with Himawari-8 AHI
Authors: Sun Haofei , Wang Deying , Han Wei , Yang Yunfan
Published: June 2024

Aerosols exert a significant influence on the brightness temperature observed in the thermal infrared (IR) channels, yet the specific contributions of various aerosol types remain underexplored. This study integrated the Copernicus Atmosphere Monitoring Service (CAMS) atmospheric composition reanalysis data into the Radiative Transfer for TOVS (RTTOV) model to quantify the aerosol effects on brightness temperature (BT) simulations for the Advanced Himawari Imager (AHI) aboard the Himawari-8 geostationary satellite. Two distinct experiments were conducted: the aerosol-aware experiment (AER), which accounted for aerosol radiative effects, and the control experiment (CTL), in which aerosol radiative effects were omitted. The CTL experiment results reveal uniform negative bias (observation minus background (O-B)) across all six IR channels of the AHI, with a maximum deviation of approximately −1 K. Conversely, the AER experiment showed a pronounced reduction in innovation, which was especially notable in the 10.4 μm channel, where the bias decreased by 0.7 K. The study evaluated the radiative effects of eleven aerosol species, all of which demonstrated cooling effects in the AHI’s six IR channels, with dust aerosols contributing the most significantly (approximately 86%). In scenarios dominated by dust, incorporating the radiative effect of dust aerosols could correct the brightness temperature bias by up to 2 K, underscoring the substantial enhancement in the BT simulation for the 10.4 μm channel during dust events. Jacobians were calculated to further examine the RTTOV simulations’ sensitivity to aerosol presence. A clear temporal and spatial correlation between the dust concentration and BT simulation bias corroborated the critical role of the infrared channel data assimilation on geostationary satellites in capturing small-scale, rapidly developing pollution processes.
Harmonic Source Depth Estimation by a Single Hydrophone under Unknown Seabed Geoacoustic Property
Authors: Li Xiaolei , Xu Yangjin , Gao Wei , Wang Haozhong , Wang Liang
Published: June 2024

The passive estimation of harmonic sound source depth is of great significance for underwater target localization and identification. Passive source depth estimation using a single hydrophone with an unknown seabed geoacoustic property is a crucial challenge. To address this issue, a harmonic sound source depth estimation algorithm, seabed independent depth estimation (SIDE) algorithm, is proposed. This algorithm combines the estimated mode depth functions, modal amplitudes, and the sign of each modal to estimate the sound source depth. The performance of the SIDE algorithm is analyzed by simulations. Results show that the SIDE is insensitive to the initial range of the sound source, the source depth, the hydrophone depth, the source velocity, and the type of the seabed. Finally, the effectiveness of the SIDE algorithm is verified by the SWellEX-96 data.
Performance Assessment of Two Low-Cost PM2.5 and PM10 Monitoring Networks in the Padana Plain (Italy)
Authors: Gualtieri Giovanni , Brilli Lorenzo , Carotenuto Federico , Cavaliere Alice , Giordano Tommaso , Putzolu Simone , Vagnoli Carolina , Zaldei Alessandro , Gioli Beniamino
Published: June 2024

Two low-cost (LC) monitoring networks, PurpleAir (instrumented by Plantower PMS5003 sensors) and AirQino (Novasense SDS011), were assessed in monitoring PM2.5 and PM10 daily concentrations in the Padana Plain (Northern Italy). A total of 19 LC stations for PM2.5 and 20 for PM10 concentrations were compared vs. regulatory-grade stations during a full “heating season” (15 October 2022–15 April 2023). Both LC sensor networks showed higher accuracy in fitting the magnitude of PM10 than PM2.5 reference observations, while lower accuracy was shown in terms of RMSE, MAE and R2. AirQino stations under-estimated both PM2.5 and PM10 reference concentrations (MB = −4.8 and −2.9 μg/m3, respectively), while PurpleAir stations over-estimated PM2.5 concentrations (MB = +5.4 μg/m3) and slightly under-estimated PM10 concentrations (MB = −0.4 μg/m3). PurpleAir stations were finer than AirQino at capturing the time variation of both PM2.5 and PM10 daily concentrations (R2 = 0.68–0.75 vs. 0.59–0.61). LC sensors from both monitoring networks failed to capture the magnitude and dynamics of the PM2.5/PM10 ratio, confirming their well-known issues in correctly discriminating the size of individual particles. These findings suggest the need for further efforts in the implementation of mass conversion algorithms within LC units to improve the tuning of PM2.5 vs. PM10 outputs.
Infrared and Visible Image Fusion Algorithm Based on Double-Domain Transform Filter and Contrast Transform Feature Extraction
Authors: Ma Xu , Li Tianqi , Deng Jun , Li Tong , Li Jiahao , Chang Chi , Wang Rui , Li Guoliang , Qi Tianrui , Hao Shuai
Published: June 2024

Current challenges in visible and infrared image fusion include color information distortion, texture detail loss, and target edge blur. To address these issues, a fusion algorithm based on double-domain transform filter and nonlinear contrast transform feature extraction (DDCTFuse) is proposed. First, for the problem of incomplete detail extraction that exists in the traditional transform domain image decomposition, an adaptive high-pass filter is proposed to decompose images into high-frequency and low-frequency portions. Second, in order to address the issue of fuzzy fusion target caused by contrast loss during the fusion process, a novel feature extraction algorithm is devised based on a novel nonlinear transform function. Finally, the fusion results are optimized and color-corrected by our proposed spatial-domain logical filter, in order to solve the color loss and edge blur generated in the fusion process. To validate the benefits of the proposed algorithm, nine classical algorithms are compared on the LLVIP, MSRS, INO, and Roadscene datasets. The results of these experiments indicate that the proposed fusion algorithm exhibits distinct targets, provides comprehensive scene information, and offers significant image contrast.
Experimental Validation of Two Types of Force Actuators: A Performance Comparison
Authors: Jiang Xishan , Wang Ning , Zheng Jing , Pan Jie
Published: June 2024

This paper experimentally investigates the performance of piezoelectric force actuators. Using the same encapsulated piezoelectric stack, an inertial-type actuator and a frame-type actuator are constructed for performance comparison. The experimental results are also used to validate the recently established actuator models, whilst the mechanical and piezoelectrical parameters of the models are experimentally identified. The performance of the actuators is described by the transmitted force(s) and input power flow from the actuators to the base structure with reference to the same electrical input voltage to the stack. The validation is deemed successful due to the strong agreement observed between the measured and predicted actuator performances. Additionally, it is discovered that the frame-type actuator has the capacity to produce significantly higher transmitted forces and input power flow to the base structure compared to the inertial-type actuator. The mechanism underlying the performance disparity between these two types of actuators is also examined. This paper clarifies the mechanism, shedding light on the design and optimization of piezoelectric actuators.
Robot Learning Method for Human-like Arm Skills Based on the Hybrid Primitive Framework
Authors: Li Jiaxin , Han Hasiaoqier , Hu Jinxin , Lin Junwei , Li Peiyi
Published: June 2024

This paper addresses the issue of how to endow robots with motion skills, flexibility, and adaptability similar to human arms. It innovatively proposes a hybrid-primitive-frame-based robot skill learning algorithm and utilizes the policy improvement with a path integral algorithm to optimize the parameters of the hybrid primitive framework, enabling robots to possess skills similar to human arms. Firstly, the end of the robot is dynamically modeled using an admittance control model to give the robot flexibility. Secondly, the dynamic movement primitives are employed to model the robot’s motion trajectory. Additionally, novel stiffness primitives and damping primitives are introduced to model the stiffness and damping parameters in the impedance model. The combination of the dynamic movement primitives, stiffness primitives, and damping primitives is called the hybrid primitive framework. Simulated experiments are designed to validate the effectiveness of the hybrid-primitive-frame-based robot skill learning algorithm, including point-to-point motion under external force disturbance and trajectory tracking under variable stiffness conditions.
Enhancing the Efficiency of Resilient Multipath-Routed Elastic Optical Networks: A Novel Approach for Coexisting Protected and Unprotected Services with Idle Slot Reuse
Authors: Cavalcanti Michael M. L. , Teixeira Gabriela W. , Dinarte Henrique A. , Almeida Raul C. , Boutaba Raouf , Chaves Daniel A. R.
Published: June 2024

In this paper, we investigate a scenario in which protected and unprotected services coexist in an elastic optical network under dynamic traffic. In the investigated scenario, unprotected services can reuse the reserved idle bandwidth to provide protection to the protected services. Under this scenario, we propose a new heuristic algorithm that enables such reuse as well as define and introduce a new assignment problem in elastic optical networks, named a Transmission Spectrum Assignment (T-SA) problem. In this paper, we consider a scenario in which services may be routed using the multipath routing approach. Additionally, protection using bandwidth squeezing is also considered. We assess our proposal through simulations on three different network topologies and compare our proposal against the classical protection approach, in which bandwidth reuse is not allowed. For the simulated range of network loads, the maximum (minimum) blocking probability reduction obtained by our proposal is approximately 48% (10%) in the European topology, 46% (7%) in the NSFNET topology, and 32% (6%) in the German topology.
SnowMotion: A Wearable Sensor-Based Mobile Platform for Alpine Skiing Technique Assistance
Authors: Tang Weidi , Suo Xiang , Wang Xi , Shan Bo , Li Lu , Liu Yu
Published: June 2024

Skiing technique and performance improvements are crucial for athletes and enthusiasts alike. This study presents SnowMotion, a digital human motion training assistance platform that addresses the key challenges of reliability, real-time analysis, usability, and cost in current motion monitoring techniques for skiing. SnowMotion utilizes wearable sensors fixed at five key positions on the skier’s body to achieve high-precision kinematic data monitoring. The monitored data are processed and analyzed in real time through the SnowMotion app, generating a panoramic digital human image and reproducing the skiing motion. Validation tests demonstrated high motion capture accuracy (cc > 0.95) and reliability compared to the Vicon system, with a mean error of 5.033 and a root-mean-square error of less than 12.50 for typical skiing movements. SnowMotion provides new ideas for technical advancement and training innovation in alpine skiing, enabling coaches and athletes to analyze movement details, identify deficiencies, and develop targeted training plans. The system is expected to contribute to popularization, training, and competition in alpine skiing, injecting new vitality into this challenging sport.
A Dynamic Traffic Light Control Algorithm to Mitigate Traffic Congestion in Metropolitan Areas
Authors: Kumar Bharathi Ramesh , Kumaran Narayanan , Prakash Jayavelu Udaya , Salunkhe Sachin , Venkatesan Raja , Shanmugam Ragavanantham , Abouel Nasr Emad S.
Published: June 2024

This paper proposes a convolutional neural network (CNN) model of the signal distribution control algorithm (SDCA) to maximize the dynamic vehicular traffic signal flow for each junction phase. The aim of the proposed algorithm is to determine the reward value and new state. It deconstructs the routing components of the current multi-directional queuing system (MDQS) architecture to identify optimal policies for every traffic scenario. Initially, the state value is divided into a function value and a parameter value. Combining these two scenarios updates the resulting optimized state value. Ultimately, an analogous criterion is developed for the current dataset. Next, the error or loss value for the present scenario is computed. Furthermore, utilizing the Deep Q-learning methodology with a quad agent enhances previous study discoveries. The recommended method outperforms all other traditional approaches in effectively optimizing traffic signal timing.