bluuebunny/crossref_metadata_2025 huggingface dataset:
A Method of Laser Frequency Stabilization Based on the Effect of Linear Dichroism in Alkali Metal Vapors in a Modulated Transverse Magnetic Field
Authors: Petrenko Mikhail V. , Pazgalev Anatoly S. , Vershovskii Anton K.
Published: September 2024

We present a method of laser frequency stabilization based on the linear dichroism signal in a transverse magnetic field. This method is similar to the DAVLL (Dichroic Atomic Vapor Laser Lock) method. It differs from DAVLL and from its existing modifications primarily by the fact that it uses signals of linearly polarized light caused by alignment, rather than circular refraction caused by orientation, and therefore allows us to obtain error signals at the magnetic field modulation frequency (or its second harmonic) by extremely simple means. The method allows the laser frequency to be stabilized in the vicinity of the low-frequency transition in the D1 line of Cs; it does not require strong magnetic fields or careful shielding of cells containing cesium atoms. Although the absorption line in a gas-filled cell is typically gigahertz wide, the achievable resolution, limited by the signal-to-noise ratio of photon shot noise, can reach units or tens of kilohertz in a one hertz bandwidth.
Alginate Spheres: Influence of Agar and Xanthan Gum Incorporation on Membrane Stability and Permeability
Authors: Bevan Pascal , Codina-Torrella Idoia , Xydia Christina , Hammadi Nisserine El , Almajano María Pilar
Published: September 2024

Calcium alginate spheres with a volume of about 5 mL can be used for important purposes. Those that incorporate oolong tea give, in addition to the recreational aspect, the possibility of drinking small quantities of this tea, because oolong tea can be used as a compound with antioxidant properties. This incorporation can be achieved by reverse spherification (5 mL). Six types of spheres have been made, all of them with calcium alginate and the presence or absence of agar-agar and xanthan gum—XG—in two concentrations. The weight loss of the spheres, the release of bioactive compounds over time (a total of 48 h), the surface (internal and external) of the membranes, and the physical characteristics of these membranes have been analyzed. The data obtained indicate that the presence of XG prevents the formation of precipitates inside the spheres and slows down weight loss. It also provides opacity to the spheres. However, the incorporation of agar-agar does not have a significant influence on the different parameters analyzed. The release of catechins reaches a maximum of 80% of what could be achieved under ideal conditions, and it reaches 90% in the first 3 h. The incorporation of XG increases the shelf life of the spheres, slows down the release of chelate, and decreases weight loss over time, allowing for a new perspective on the spherification process.
Compression Behavior of 3D Printed Composite Isogrid Structures
Authors: Andreozzi Marina , Bruni Carlo , Forcellese Archimede , Gentili Serena , Vita Alessio
Published: September 2024

Composite materials, particularly carbon fiber-reinforced polymers (CFRPs), have become a cornerstone in industries requiring high-performance materials due to their exceptional mechanical properties, such as high strength-to-weight ratios, and their inherent lightweight nature. These attributes make CFRPs highly desirable in aerospace, automotive, and other advanced engineering applications. However, the compressive behavior of CFRP structures remains a challenge, primarily due to the material sensitivity to structural instability, leading to matrix cracking and premature failure under compressive loads. Isogrid structures, characterized by their unique geometric patterns, have shown promise in enhancing the compressive behavior of CFRP panels by providing additional support that mitigates these issues. Traditionally, these structures are manufactured using automated techniques like automated fiber placement (AFP) and automated tape laying (ATL), which, despite their efficacy, are often cost-prohibitive for small-scale or custom applications. Recent advancements in 3D-printing technology, particularly those involving continuous fiber reinforcement, present a cost-effective and flexible alternative for producing complex CFRP structures. This study investigates the compressive behavior of 3D-printed isogrid structures, fabricated using continuous carbon fiber reinforcement via an Anisoprint Composer A3 printer equipped with towpreg coextrusion technology. A total of eight isogrid panels with varying infill percentages were produced and subjected to buckling tests to assess their performance. The experimental results indicate a direct correlation between infill density and buckling resistance, with higher infill densities leading to increased buckling loads. Additionally, the failure modes were observed to shift from local to global buckling as the infill density increased, suggesting a more uniform distribution of compressive stresses. Post-test analyses using optical microscopy and scanning electron microscopy (SEM) revealed the presence of voids within the 3D-printed structures, which were found to negatively impact the mechanical performance of the isogrid panels. The findings of this study demonstrate that 3D-printed isogrid CFRP structures can achieve significant buckling resistance, making them a viable option for high-performance applications. However, the presence of voids remains a critical issue, highlighting the need for process optimizations in 3D-printing techniques to enhance the overall performance and reliability of these structures.
Vacuum Chamber Infusion for Fiber-Reinforced Composites
Authors: Grisin Benjamin , Carosella Stefan , Middendorf Peter
Published: September 2024

A new approach to an automatable fiber impregnation and consolidation process for the manufacturing of fiber-reinforced composite parts is presented in this article. Therefore, a vacuum chamber sealing machine classically used in food packaging is modified for this approach—Vacuum Chamber Infusion (VCI). Dry fiber placement (DFP) preforms, made from 30 k carbon fiber tape, with different layer amounts and fiber orientations, are infused with the VCI and with the state-of-the-art process—Vacuum Assisted Process (VAP)—as the reference. VCI uses a closed system that is evacuated once, while VAP uses a permanently evacuated open system. Since process management greatly influences material properties, the mechanical properties, void content, and fiber volume fraction (FVF) are analyzed. In addition, the study aims to identify how the complexity of a resin infusion process can be reduced, the automation potential can be increased, and the number of consumables can be reduced. Comparable material characteristics and a reduction in consumables, setup complexity, and manufacturing time by a factor of four could be approved for VCI. A void content of less than 2% is measured for both processes and an FVF of 39% for VCI and 45% for VAP is achieved.
Polyester Adhesives via One-Pot, One-Step Copolymerization of Cyclic Anhydride, Epoxide, and Lactide
Authors: Suzuki Ryota , Miwa Toshiki , Nunokawa Ryosuke , Sumi Ayaka , Ando Masaru , Takahashi Katsuaki , Takagi Akira , Yamamoto Takuya , Tajima Kenji , Li Feng , Isono Takuya , Satoh Toshifumi
Published: September 2024

Polyesters (PEs) are sustainable alternatives for conventional polymers owing to their potential degradability, recyclability, and the wide availability of bio-based monomers for their synthesis. Herein, we used a one-pot, one-step self-switchable polymerization linking the ring-opening alternating copolymerization (ROAC) of epoxides/cyclic anhydrides with the ring-opening polymerization (ROP) of L-lactide (LLA) to synthesize PE-based hot-melt adhesives with a high bio-based content. In the cesium pivalate-catalyzed self-switchable polymerization of glutaric anhydride (GA), butylene oxide (BO), and LLA using a diol initiator, the ROAC of GA and BO proceeded whereas the ROP of LLA simultaneously proceeded very slowly, resulting in a copolyester consisting of poly(GA-alt-BO) and poly(L-lactide) (PLLA) segments with tapered regions, that is, PLLA-tapered block-poly(GA-alt-BO)-tapered block-PLLA (PLLA-tb-poly(GA-alt-BO)-tb-PLLA). Additionally, a series of tapered-block or real-block copolyesters consisting of poly(anhydride-alt-epoxide) (A segment) and PLLA (B segment) with AB-, BAB-, (AB)3-, and (AB)4-type architectures of different compositions and molecular weights were synthesized by varying the monomer combinations, alcohol initiators, and initial feed ratios. The lap shear tests of these copolyesters revealed an excellent relationship between the adhesive strength and polymer structural parameters. The (AB)4-type star-block copolyester (poly(GA-alt-BO)-tb-PLLA)4 exhibited the best adhesive strength (6.74 ± 0.64 MPa), comparable to that of commercial products, such as PE-based and poly(vinyl acetate)-based hot-melt adhesives.
Synergistic Effects of Liquid Rubber and Thermoplastic Particles for Toughening Epoxy Resin
Authors: Wang Zhaodi , Lai Yuanchang , Xu Peiwen , Ma Junchi , Xu Yahong , Yang Xin
Published: September 2024

This study aims to investigate the toughening effects of rubber and thermoplastic particles on epoxy resin (EP), and to understand the mechanism underlying their synergistic effect. For this purpose, three EP systems were prepared using diglycidyl ether of bisphenol-A (DGEBA) epoxy resin (E-54) and 4,4-Diamino diphenyl methane (Ag-80) as matrix resin, 4,4-diaminodiphenyl sulfone (DDS) as a curing agent, and phenolphthalein poly (aryl ether ketone) particles (PEK-C) and carboxyl-terminated butyl liquid rubber (CTBN) as toughening agents. These systems are classified as an EP/PEK-C toughening system, EP/CTBN toughening system, and EP/PEK-C/CTBN synergistic toughening system. The curing behavior, thermal properties, mechanical properties, and phase structure of the synergistic-toughened EP systems were comprehensively investigated. The results showed that PEK-C did not react with EP, while CTBN reacted with EP to form a flexible block polymer. The impact toughness of EP toughened by PEK-C/CTBN was improved obviously without significantly increasing viscosity or decreasing thermal stability, flexural strength, and modulus, and the synergistic toughening effect was significantly higher than that of the single toughening system. The notable improvement in toughness is believed to be due to the synergistic energy dissipation effect of PEK-C/CTBN.
Particle Dynamics Study on Influencing Factors of Ice Slurry Flow Characteristics in District Cooling Systems
Authors: Yang Di , Hong Wenpeng
Published: September 2024

In district cooling systems, substituting the conventional cooling medium with ice slurry represents an ideal approach to achieve economical operation. During pipeline transportation, ice slurry exhibits heterogeneous flow characteristics distinct from those of pure fluids. Consequently, investigating the flow field characteristics of non-homogeneous ice slurry, quantitatively analyzing the rheological variations and flow resistance laws due to the uneven distribution of ice particles, and standardizing the comprehension and depiction of flow patterns within ice slurry pipes hold significant theoretical importance and practical value. This study analyzes the heterogeneous isothermal flow characteristics of ice slurry in a straight pipe by employing particle dynamics and the Euler–Euler dual-fluid model. Taking into account the impact of ice particles’ non-uniform distribution on the rheological properties of ice slurry, a particle concentration diffusion equation is incorporated to develop an isothermal flow resistance model for ice slurry. The flow behavior of ice slurry with initial average ice particle fractions (IPFs) ranging from 0% to 20% in DN20 horizontal straight and elbow pipes is examined. The findings reveal that the degree of heterogeneous flow in ice slurry is inversely proportional to the initial velocity and directly proportional to the initial concentration of ice particles. When the flow velocity is close to 0.5 m/s, the flow resistance of ice particles exhibits a linear positive correlation with changes in flow velocity, whereas the flow resistance of the fluid-carrying phase displays a linear negative correlation. As the flow rate increases to 1 m/s, the contribution of each phase to the total flow resistance becomes independent of the initial velocity parameter. Additionally, the drag fraction of the ice particle phase is positively associated with the initial concentration of ice particles. Furthermore, the phenomenon of “secondary flow” arises when ice slurry flows through an elbow, enhancing the mixing of ice particles with the carrier fluid. The extent of this mixing intensifies with a decrease in the turning radius and an increase in the initial velocity.
Factors Influencing Radiation Sound Fields in Logging While Drilling Using an Acoustic Dipole Source
Authors: Cao Jingji , Qin Ruibao , Li Xiongyan , Ye Xinyu , Hei Chuang , Yin Zhongxu , Wang Peng
Published: September 2024

With the increasing number of complex well types in the development stage of oil and gas fields, it is becoming increasingly urgent to use remote detection logging while drilling (LWD) to explore the geological structures in a formation. In this paper, the feasibility and reliability of the dipole remote detection of logging while drilling are demonstrated theoretically. For this purpose, we use an asymptotic solution of elastic wave far-field displacement to derive the calculation formula for the radiation pattern and energy flux of an LWD dipole source. The effects of influencing factors, including the source frequency, formation property, drill collar size, and mud parameter, on the radiation pattern and energy flux are analyzed. The results show that the horizontally polarized shear wave (SH-wave) has a greater advantage in imaging the reflector compared with the cases of the compressive wave (P-wave) and vertically polarized shear wave (SV-wave), which indicates the dominance of the SH-wave in dipole remote detection while drilling. The optimal source excitation frequency of 2.5 kHz and inner and outer radii of the drill collar of 0.02 and 0.1 m, respectively, should be considered in the design of an LWD dipole shear wave reflection tool. However, the heavy drilling mud is not conducive to remote detection during logging while drilling. In addition, the reflection of the SH-wave for the LWD condition is simulated. Under the conditions of optimal source frequency, drill collar size, and mud parameters, the reflection of the SH-wave signal is still detected under the fast formation.
Fault Diagnosis of Pumped Storage Units—A Novel Data-Model Hybrid-Driven Strategy
Authors: Bai Jie , Che Chuanqiang , Liu Xuan , Wang Lixin , He Zhiqiang , Xie Fucai , Dou Bingjie , Guo Haonan , Ma Ruida , Zou Hongbo
Published: September 2024

Pumped storage units serve as a crucial support for power systems to adapt to large-scale and high-proportion renewable energy sources by providing a stable and flexible energy supply. However, due to the coupling effects of electric power load demands and the complex multi-source factors within the water–mechanical–electrical system, the interrelationship between unit parameters becomes more intricate, posing significant threats to the operational reliability and health status of the units. The complexity of fault diagnosis is further aggravated by the intricate and varied nature of fault characteristics, as well as the challenges in signal extraction under conditions of strong electromagnetic interference and high noise levels. To address these issues, this paper proposes a novel data-model hybrid-driven strategy that analyzes vibration signals to achieve rapid and accurate fault diagnosis of the units. Firstly, the spectral kurtosis theory is employed to enhance the traditional empirical mode decomposition, achieving optimal decomposition and noise reduction effects for vibration signals. Secondly, the intrinsic mode functions (IMFs) obtained from the decomposition are reconstructed, and the entropy values of effective IMFs are calculated as fault feature vectors. Subsequently, the CNN-LSTM model is utilized for fault diagnosis. The effectiveness and feasibility of the proposed method are verified through actual operational data from pumped storage units in a specific region. Through analysis, the fault diagnosis accuracy of the method proposed in this paper can be maintained above 95%, demonstrating robustness in complex engineering environments and effectively ensuring the safe and stable operation of pumped storage units.
Advanced Processes in Water Treatment: Synergistic Effects of Hydrodynamic Cavitation and Cold Plasma on Rhodamine B Dye Degradation
Authors: Verdini Federico , Crudo Daniele , Bosco Valentina , Kamler Anna V. , Cravotto Giancarlo , Calcio Gaudino Emanuela
Published: September 2024

The increasing pollution of water bodies, due to the constant release of highly toxic and non-biodegradable organic pollutants, requires innovative solutions for environmental remediation and wastewater treatment. In this study, the effectiveness of different Advanced Oxidation Processes (AOPs) for the purification of water contaminated with Rhodamine B (RhB) dye at a concentration of 5 mg/L were investigated and compared. Using the classical ozonation strategy as a benchmark treatment, the research showed over 99% degradation of RhB within 4 min in a laboratory-scale batch setup with a capacity of 0.2 L. In contrast, a “chemical-free” process exploiting ultrasound (US) technology achieved a 72% degradation rate within 60 min. Further experiments were conducted using a pilot-scale rotor-stator hydrodynamic cavitation (HC) reactor on a 15 L solution leading to 33% of RhB removal in the presence of hydrogen peroxide (H2O2) at 75 mg/L. However, the use of an innovative cavitational reactor, which hybridizes HC with cold plasma, showed remarkable efficiency and achieved 97% degradation of RhB in just 5 min when treating a 5 L solution at an inlet pressure of 20 bar in a loop configuration. In addition, a degradation rate of 58% was observed in a flow-through configuration, emphasising the robustness and scalability of the HC/electrical discharge (ED) plasma technology. These results underline the potential of hybrid HC/ED plasma technology as an intensified and scalable process for the purification of water, as it offers a catalyst- and oxidant-free protocol.
Simulation Research and Practical Application of Cutting Teeth for Drill Bits in Life-Support Holes
Authors: Zhu Zebin , Feng Jian , Kang Yuguo , Zhang Biao , Ling Xue
Published: September 2024

This study aims to achieve rapid drilling of life-support holes, regarding the optimization design of drill bits as the key, among which the simulation analysis of drill bit cutting teeth is an important technical means. Firstly, based on the rock mechanics test results in the study area combined with the corresponding logging information, the analysis and evaluation of the geological conditions in the study area were completed, a complete rock mechanics characteristic profile was established, and the drillability of the rock was calculated to be relatively good. Then, a numerical simulation of parallel cutting of rock with conical teeth was established by experimentally testing rock mechanics parameters and using the discrete element method (PFC2D). The simulation study of the drill bit cutting teeth was completed by parameter calibration, analysis of rock cutting morphology, analysis of the number of rock cutting cracks, and analysis of the specific work of rock cutting and breaking. It was determined that the optimal rock-entering angle of the drill bit cutting teeth in the Shouyang mining area is 14°. Finally, verified by field practice, the optimized drill bit has stable performance, strong cutting ability, and good wear resistance; the maximum instantaneous mechanical drilling speed reaches 58.14 m/h, and it shows a slightly worn state after continuously drilling 582 m in the stratum, meeting the requirements of one-trip drilling and hole formation for life-support holes. This research provides a scientific basis and practical techniques for the construction of life-support holes in the Shouyang mining area and under similar geological conditions. It can provide more effective emergency plans and rescue strategies for possible mine disasters in the future, which is crucial for improving the technical system of emergency rescue for mine accidents and enhancing the emergency rescue capability of surface drilling.
Psychological Improvement of People with Substance Addiction through a Self-Esteem Workshop
Authors: Fernández-Alarcón Santiago Manuel , Adame Manuel , Antona César Jesús , Antón-Sancho Álvaro , Vergara Diego
Published: September 2024

Addictions undermine the quality of life of individuals and their families. They generally lead to misadjustment that affects many areas (psychological, family, social, and occupational) and, in the most severe cases, can end in helplessness, loneliness, or early death. The self-esteem of the person with addictions tends to be reduced and this limits their chances of recovery. Through this research, we tried to test the effect of a self-esteem workshop on 58 people with addictions to different substances. A self-esteem workshop was carried out with people who were part of a therapeutic community belonging to the province of Pontevedra (Spain). Several working groups were established and received sessions over a period of two and a half months. Participation was voluntary and the anonymity and confidentiality of the participants were guaranteed. To assess self-esteem, the Coopersmith Self-Esteem Scale Short Form, or Form B, was used at the beginning and at the end of the workshop. The results confirm the existence of statistically significant differences in the Self-Esteem Scale in relation to the pre-treatment and post-treatment assessments: F(1) = 106.44, p = 0.000, η2 = 0.655. The self-esteem workshop resulted in a significant change in this construct and contributed to the psychological improvement of people with addictions.
Quantum-Enhanced Generalized Pattern Search Optimization
Authors: Mikes Colton , Gutman David Huckleberry , Howle Victoria E.
Published: September 2024

While the development of quantum computers promises a myriad of advantages over their classical counterparts, care must be taken when designing algorithms that substitute a classical technique with a potentially advantageous quantum method. The probabilistic nature of many quantum algorithms may result in new behavior that could negatively impact the performance of the larger algorithm. The purpose of this work is to preserve the advantages of applying quantum search methods for generalized pattern search algorithms (GPSs) without violating the convergence criteria. It is well known that quantum search methods are able to reduce the expected number of oracle calls needed for finding the solution to a search problem from O(N) to O(N) However, the number of oracle calls needed to determine that no solution exists with certainty is exceedingly high and potentially infinite. In the case of GPS, this is a significant problem since overlooking a solution during an iteration will violate a needed assumption for convergence. Here, we overcome this problem by introducing the quantum improved point search (QIPS), a classical–quantum hybrid variant of the quantum search algorithm QSearch. QIPS retains the O(N) oracle query complexity of QSearch when a solution exists. However, it is able to determine when no solution exists, with certainty, using only O(N) oracle calls.
Academic Degrees for Monks: Sera Je and the Challenges of Integrating Tibetan Buddhist Monastic Education into the Indian University System
Authors: Hobhouse Nicholas S.
Published: September 2024

Although there have been concerted efforts to integrate Tibetan Buddhist monastic education into the Indian university system since the 1960s, the attainment of academic accreditation has tended to require significant curricular trade-offs. The majority of Tibetan Buddhist monastic colleges have therefore eschewed the potential advantages of academic accreditation—including greater opportunities for monastic graduates in universities and other secular contexts—in order to preserve the rigour of traditional scholastic programmes. However, through its affiliation to the University of Mysore in 2022, the Geluk monastery of Sera Je is now able to award accredited Bachelor of Arts (BA) degrees even without making significant changes in practice to its traditional curriculum and pedagogy. This article examines the structure and content of Sera Je’s new programmes and contextualises what may prove to be a landmark development against the backdrop of previous attempts to negotiate the boundary between Tibetan Buddhist monastic education and university education in India. It suggests that the accreditation of research programmes raises further challenges in addition to those associated with the accreditation of taught programmes. Nonetheless, the urgency of solving these longstanding issues appears to have been heightened by a developing crisis in Tibetan Buddhist monastic recruitment. In investigating the topic of academic accreditation, this article throws light on an issue that has driven notable evolutions in Tibetan Buddhist monastic education in India but has previously received little scholarly attention.
Weituo Statue in Temple Space: Worshipping Weituo as a Patron Deity of the Chinese Saṅgha
Authors: Zhu Tianshu
Published: September 2024

Weituo 韦驮 is one of the most frequently represented protective deities in Chinese Buddhist temples. The statue of Weituo is enshrined virtually in every standard Buddhist temple in China today, and at a unique location—in the entrance hall for the four Heavenly Kings and facing inward. Why is the Weituo statue placed at this place and looking inward? The Chinese Weituo can be traced back to the Hindu god Skanda. However, his iconography and functions in China were completely reshaped by master Daoxuan’s 道宣 (596–667) account of this deity. Actually, Weituo is just one of the many Buddhist protective deities for general protection and prosperity. In China, as I demonstrate in this study, Weituo has been known as the most diligent Dharma-protector and is associated in particular with the saṅgha, as a patron guardian and inspector of monks and nuns. Thus, Weituo’s images are shrined in Buddhist temples. The locations of these images reflect the importance of Weituo and his special role in Chinese Buddhism. In the past, there have been a few studies, but they mainly focus on his origin. The functions of Weituo and the worship of Weituo in the Chinese saṅgha have not been well examined. Going beyond his identities, iconography, and style, this study aims to contextualize Weituo images in temple space and religious practice.
Change in Fractional Vegetation Cover and Its Prediction during the Growing Season Based on Machine Learning in Southwest China
Authors: Li Xiehui , Liu Yuting , Wang Lei
Published: September 2024

Fractional vegetation cover (FVC) is a crucial indicator for measuring the growth of surface vegetation. The changes and predictions of FVC significantly impact biodiversity conservation, ecosystem health and stability, and climate change response and prediction. Southwest China (SWC) is characterized by complex topography, diverse climate types, and rich vegetation types. This study first analyzed the spatiotemporal variation of FVC at various timescales in SWC from 2000 to 2020 using FVC values derived from pixel dichotomy model. Next, we constructed four machine learning models—light gradient boosting machine (LightGBM), support vector regression (SVR), k-nearest neighbor (KNN), and ridge regression (RR)—along with a weighted average heterogeneous ensemble model (WAHEM) to predict growing-season FVC in SWC from 2000 to 2023. Finally, the performance of the different ML models was comprehensively evaluated using tenfold cross-validation and multiple performance metrics. The results indicated that the overall FVC in SWC predominantly increased from 2000 to 2020. Over the 21 years, the FVC spatial distribution in SWC generally showed a high east and low west pattern, with extremely low FVC in the western plateau of Tibet and higher FVC in parts of eastern Sichuan, Chongqing, Guizhou, and Yunnan. The determination coefficient R2 scores from tenfold cross-validation for the four ML models indicated that LightGBM had the strongest predictive ability whereas RR had the weakest. WAHEM and LightGBM models performed the best overall in the training, validation, and test sets, with RR performing the worst. The predicted spatial change trends were consistent with the MODIS-MOD13A3-FVC and FY3D-MERSI-FVC, although the predicted FVC values were slightly higher but closer to the MODIS-MOD13A3-FVC. The feature importance scores from the LightGBM model indicated that digital elevation model (DEM) had the most significant influence on FVC among the six input features. In contrast, soil surface water retention capacity (SSWRC) was the most influential climate factor. The results of this study provided valuable insights and references for monitoring and predicting the vegetation cover in regions with complex topography, diverse climate types, and rich vegetation. Additionally, they offered guidance for selecting remote sensing products for vegetation cover and optimizing different ML models.
Investigation and Validation of Split-Window Algorithms for Estimating Land Surface Temperature from Landsat 9 TIRS-2 Data
Authors: Su Qinghua , Meng Xiangchen , Sun Lin
Published: September 2024

Land surface temperature (LST) is important in a variety of applications, such as urban thermal environment monitoring and water resource management. In this paper, eleven candidate split-window (SW) algorithms were adapted to Thermal Infrared Sensor-2 (TIRS-2) data of the Landsat 9 satellite for estimating the LST. The simulated dataset produced by extensive radiative transfer modeling and five global atmospheric profile databases was used to determine the SW algorithm coefficients. Ground measurements gathered at Surface Radiation Budget Network sites were used to confirm the efficiency of the SW algorithms after their performance was initially examined using the independent simulation dataset. Five atmospheric profile databases perform similarly in training accuracy under various subranges of total water vapor. The candidate SW algorithms demonstrate superior performance compared to the radiative transfer equation algorithm, exhibiting a reduction in overall bias and RMSE by 1.30 K and 1.0 K, respectively. It is expected to provide guidance for the generation of the Landsat 9 LST using the SW algorithms.
Impact of Long-Term Drought on Surface Water and Water Balance Variations in Iran: Insights from Highland and Lowland Regions
Authors: Kazemi Garajeh Mohammad , Abdoli Nastaran , Seyedebrahimi Ebrahim , Naboureh Amin , Kurdpour Iman , Bakhshi Lomer Amir Reza , Sadeqi Amin , Mirzaei Saham
Published: September 2024

Droughts have a significant impact on surface water resources, especially in arid and semi-arid regions. Computational and data handling limitations have constrained previous time-series analyses. However, advances in cloud computing services and remote sensing technology allow for a more detailed examination. This study integrates multi-source satellite-derived data with a cloud computing platform to assess the impact of long-term drought on surface water and water balance in Iran from 2000 to 2021. Given the varying effects of drought on highlands and lowlands, the analysis was conducted at three levels: the entire country, the highlands, and the lowlands. The results of this study reveal imbalances between water balance from 2000 to 2021, with notable disparities observed during 2000–2007, 2009–2014, and 2016–2019. The results also show varying drought trends (e.g., −1.22 in 2000 and −0.73 in 2021), with severe conditions captured in 2008 (SPI: −1.92). Additionally, our analysis illustrated that lowlands were more impacted by droughts compared to highlands. Long-term drought and permanent surface water had correlation values of 0.33 across the country, 0.33 in the highlands, and 0.31 in the lowlands. For seasonal surface water, coefficients were 0.18 for the entire country, 0.16 for the highlands, and 0.18 for the lowlands. Overall, long-term drought had minimal effect on reducing surface water. These findings show that drought is only part of the explanation for the decrease in surface water resources.
Autonomous Single-Image Dehazing: Enhancing Local Texture with Haze Density-Aware Image Blending
Authors: Han Siyeon , Ngo Dat , Choi Yeonggyu , Kang Bongsoon
Published: September 2024

Single-image dehazing is an ill-posed problem that has attracted a myriad of research efforts. However, virtually all methods proposed thus far assume that input images are already affected by haze. Little effort has been spent on autonomous single-image dehazing. Even though deep learning dehazing models, with their widely claimed attribute of generalizability, do not exhibit satisfactory performance on images with various haze conditions. In this paper, we present a novel approach for autonomous single-image dehazing. Our approach consists of four major steps: sharpness enhancement, adaptive dehazing, image blending, and adaptive tone remapping. A global haze density weight drives the adaptive dehazing and tone remapping to handle images with various haze conditions, including those that are haze-free or affected by mild, moderate, and dense haze. Meanwhile, the proposed approach adopts patch-based haze density weights to guide the image blending, resulting in enhanced local texture. Comparative performance analysis with state-of-the-art methods demonstrates the efficacy of our proposed approach.
Siamese InternImage for Change Detection
Authors: Shen Jing , Huo Chunlei , Xiang Shiming
Published: September 2024

For some time, CNN was the de facto state-of-the-art method in remote sensing image change detection. Although transformer-based models have surpassed CNN-based models due to their larger receptive fields, CNNs still retain their value for their efficiency and ability to extract precise local features. To overcome the limitations of the restricted receptive fields in standard CNNs, deformable convolution allows for dynamic adjustment of sampling locations in convolutional kernels, improving the network’s ability to model global contexts. InternImage is an architecture built upon deformable convolution as its foundational operation. Motivated by InternImage, in this paper, a CNN-based change detection vision foundation model is proposed. By introducing deformable convolution into Siamese InternImage architecture, the proposed CNN-based change detection vision foundation model is capable of capturing long-range dependencies and global information. A refinement block is utilized to merge local detail, where channel attention is incorporated. The proposed approach achieved excellent performance on the LEVIR-CD and WHU-CD datasets.
A Multiple Targets ISAR Imaging Method with Removal of Micro-Motion Connection Based on Joint Constraints
Authors: Li Hongxu , Guo Qinglang , Xu Zihan , Jin Xinfei , Su Fulin , Li Xiaodi
Published: September 2024

Combining multiple data sources, Digital Earth is an integrated observation platform based on air–space–ground–sea monitoring systems. Among these data sources, the Inverse Synthetic Aperture Radar (ISAR) is a crucial observation method. ISAR is typically utilized to monitor both military and civilian ships due to its all-day and all-weather superiority. However, in complex scenarios, multiple targets may exist within the same radar antenna beam, resulting in severe defocusing due to different motion conditions. Therefore, this paper proposes a multiple-target ISAR imaging method with the removal of micro-motion connections based on the integration of joint constraints. The fully motion-compensated targets exhibit low rank and local similarity in the high-resolution range profile (HRRP) domain, while the micro-motion components possess sparsity. Additionally, targets display sparsity in the image domain. Inspired by this, we formulate a novel optimization by promoting the low-rank, the Laplacian, and the sparsity constraints of targets and the sparsity constraints of the micro-motion components. This optimization problem is solved by the linearized alternative direction method with adaptive penalty (LADMAP). Furthermore, the different motions of various targets degrade their inherent characteristics. Therefore, we integrate motion compensation transformation into the optimization, accordingly achieving the separation of rigid bodies and the micro-motion components of different targets. Experiments based on simulated data demonstrate the effectiveness of the proposed method.
Local Weather and Global Climate Data-Driven Long-Term Runoff Forecasting Based on Local–Global–Temporal Attention Mechanisms and Graph Attention Networks
Authors: Yang Binlin , Chen Lu , Yi Bin , Li Siming , Leng Zhiyuan
Published: September 2024

The accuracy of long-term runoff models can be increased through the input of local weather variables and global climate indices. However, existing methods do not effectively extract important information from complex input factors across various temporal and spatial dimensions, thereby contributing to inaccurate predictions of long-term runoff. In this study, local–global–temporal attention mechanisms (LGTA) were proposed for capturing crucial information on global climate indices on monthly, annual, and interannual time scales. The graph attention network (GAT) was employed to extract geographical topological information of meteorological stations, based on remotely sensed elevation data. A long-term runoff prediction model was established based on long-short-term memory (LSTM) integrated with GAT and LGTA, referred to as GAT–LGTA–LSTM. The proposed model was compared to five comparative models (LGTA–LSTM, GAT–GTA–LSTM, GTA–LSTM, GAT–GA–LSTM, GA–LSTM). The models were applied to forecast the long-term runoff at Luning and Pingshan stations in China. The results indicated that the GAT–LGTA–LSTM model demonstrated the best forecasting performance among the comparative models. The Nash–Sutcliffe Efficiency (NSE) of GAT–LGTA–LSTM at the Luning and Pingshan stations reached 0.87 and 0.89, respectively. Compared to the GA–LSTM benchmark model, the GAT–LGTA–LSTM model demonstrated an average increase in NSE of 0.07, an average increase in Kling–Gupta Efficiency (KGE) of 0.08, and an average reduction in mean absolute percent error (MAPE) of 0.12. The excellent performance of the proposed model is attributed to the following: (1) local attention mechanism assigns a higher weight to key global climate indices at a monthly scale, enhancing the ability of global and temporal attention mechanisms to capture the critical information at annual and interannual scales and (2) the global attention mechanism integrated with GAT effectively extracts crucial temporal and spatial information from precipitation and remotely-sensed elevation data. Furthermore, attention visualization reveals that various global climate indices contribute differently to runoff predictions across distinct months. The global climate indices corresponding to specific seasons or months should be selected to forecast the respective monthly runoff.
Design of Differential Loudspeaker Line Array for Steerable Frequency-Invariant Beamforming
Authors: Zhang Yankai , Xiang Qian , Zhu Qiaoxi
Published: September 2024

Differential beamforming has attracted much research since it can utilize an array with a small aperture size to form frequency-invariant beampatterns and achieve high directional gains. It has recently been applied to the loudspeaker line array to produce a broadside frequency-invariant radiation pattern. However, designing steerable frequency-invariant beampatterns for the loudspeaker line array has yet to be explored. This paper proposes a method to design a steerable differential beamformer with a loudspeaker line array. We first determine the target differential beampatterns according to the desired direction, the main lobe width, and the beampattern order. Then, we transform the target beampattern into the modal domain for representation. The Jacobi-Anger expansion is subsequently used to design the beamformer so that the resulting beampattern matches the target differential beampattern. Furthermore, based on the criterion of minimizing the mean square error between the synthesized beampattern and the ideal one, a multi-constraint optimization problem, which compromises between the robustness and the mean square error, is formulated to calculate the optimal desired weighting vector. Simulations and experimental results show that the proposed method can achieve steerable frequency-invariant beamforming from 300 Hz–4 kHz.
Enhancing Coffee Agroforestry Systems Suitability Using Geospatial Analysis and Sentinel Satellite Data in Gedeo Zone, Ethiopia
Authors: Nigussie Wondifraw , Al-Najjar Husam , Zhang Wanchang , Yirsaw Eshetu , Nega Worku , Zhang Zhijie , Kalantar Bahareh
Published: September 2024

The Gedeo zone agroforestry systems are the main source of Ethiopia’s coffee beans. However, land-use and suitability analyses are not well documented due to complex topography, heterogeneous agroforestry, and lack of information. This research aimed to map the coffee coverage and identify land suitability for coffee plantations using remote sensing, Geographic Information Systems (GIS), and the Analytical Hierarchy Process (AHP) in the Gedeo zone, Southern Ethiopia. Remote sensing classifiers often confuse agroforestry and plantations like coffee cover with forest cover because of their similar spectral signatures. Mapping shaded coffee in Gedeo agroforestry using optical or multispectral remote sensing is challenging. To address this, the study identified and mapped coffee coverage from Sentinel-1 data with a decibel (dB) value matched to actual coffee coverage. The actual field data were overlaid on Sentinel-1, which was used to extract the raster value. Pre-processing, classification, standardization, and reclassification of thematic layers were performed to find potential areas for coffee plantation. Hierarchy levels of the main criteria were formed based on climatological, edaphological, physiographic, and socioeconomic factors. These criteria were divided into 14 sub-criteria, reclassified based on their impact on coffee growing, with their relative weights derived using AHP. From the total study area of 1356.2 km2, the mapped coffee coverage is 583 km2. The outcome of the final computed factor weight indicated that average annual temperature and mean annual rainfall are the primary factors, followed by annual mean maximum temperature, elevation, annual mean minimum temperature, soil pH, Land Use/Land Cover (LULC), soil texture, Cation Exchange Capacity (CEC), slope, Soil Organic Matter (SOM), aspect, distance to roads, and distance to water, respectively. The identified coffee plantation potential land suitability reveals unsuitable (413 km2), sub-suitable (596.1 km2), and suitable (347.1 km2) areas. This study provides comprehensive spatial details for Ethiopian cultivators, government officials, and agricultural extension specialists to select optimal coffee farming locations, enhancing food security and economic prosperity.
A Real-Time Global Re-Localization Framework for a 3D LiDAR-Based Navigation System
Authors: Chai Ziqi , Liu Chao , Xiong Zhenhua
Published: September 2024

Place recognition is widely used to re-localize robots in pre-built point cloud maps for navigation. However, current place recognition methods can only be used to recognize previously visited places. Moreover, these methods are limited by the requirement of using the same types of sensors in the re-localization process and the process is time consuming. In this paper, a template-matching-based global re-localization framework is proposed to address these challenges. The proposed framework includes an offline building stage and an online matching stage. In the offline stage, virtual LiDAR scans are densely resampled in the map and rotation-invariant descriptors can be extracted as templates. These templates are hierarchically clustered to build a template library. The map used to collect virtual LiDAR scans can be built either by the robot itself previously, or by other heterogeneous sensors. So, an important feature of the proposed framework is that it can be used in environments that have never been visited by the robot before. In the online stage, a cascade coarse-to-fine template matching method is proposed for efficient matching, considering both computational efficiency and accuracy. In the simulation with 100 K templates, the proposed framework achieves a 99% success rate and around 11 Hz matching speed when the re-localization error threshold is 1.0 m. In the validation on The Newer College Dataset with 40 K templates, it achieves a 94.67% success rate and around 7 Hz matching speed when the re-localization error threshold is 1.0 m. All the results show that the proposed framework has high accuracy, excellent efficiency, and the capability to achieve global re-localization in heterogeneous maps.
Geo-Sensing-Based Analysis of Urban Heat Island in the Metropolitan Area of Merida, Mexico
Authors: Sánchez-Sánchez Francisco A. , Vega-De-Lille Marisela , Castillo-Atoche Alejandro A. , López-Maldonado José T. , Cruz-Fernandez Mayra , Camacho-Pérez Enrique , Rodríguez-Reséndiz Juvenal
Published: September 2024

Urban Heat Islands are a major environmental and public health concern, causing temperature increase in urban areas. This study used satellite imagery and machine learning to analyze the spatial and temporal patterns of land surface temperature distribution in the Metropolitan Area of Merida (MAM), Mexico, from 2001 to 2021. The results show that land surface temperature has increased in the MAM over the study period, while the urban footprint has expanded. The study also found a high correlation (r> 0.8) between changes in land surface temperature and land cover classes (urbanization/deforestation). If the current urbanization trend continues, the difference between the land surface temperature of the MAM and its surroundings is expected to reach 3.12 °C ± 1.11 °C by the year 2030. Hence, the findings of this study suggest that the Urban Heat Island effect is a growing problem in the MAM and highlight the importance of satellite imagery and machine learning for monitoring and developing mitigation strategies.