bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of High-Pressure Homogenization Conditions on the Physicochemical Properties and Stability of Designed Fluconazole-Loaded Ocular Nanoemulsions
Authors: Gawin-Mikołajewicz Agnieszka , Nawrot Urszula , Malec Katarzyna Hanna , Krajewska Karolina , Nartowski Karol Przemysław , Karolewicz Bożena Lucyna
Published: December 2023

The growing interest in high-energy emulsification is a result of its scalability, which is important from an industrial perspective and allows for a more reproducible and efficient production of pharmaceutical formulations. The aim of this study was to evaluate the effect of composition, mainly a fixed surfactant/cosurfactant (Smix) ratio, their concentration, and the parameters of high-pressure homogenization (HPH) processing on the quality and stability of ophthalmic fluconazole-loaded nanoemulsions. After a physicochemical analysis of nanoemulsions containing 20% w/w of oil, as optimal conditions for the HPH process, three cycles at a pressure of 1000 bar were established, obtaining formulations with an average droplet diameter size in the range of 80.63–129.68 nm and PDI values below 0.25. While it was expected that an increasing cosurfactant concentration decreased the droplet size, in the case of formulations containing Tween 20 and 10% w/w of cosurfactants, “over-processing” was observed, identified by the droplet size and polydispersity index increase. Consecutively, the selected formulations were evaluated for in vitro drug release in Franz’s cell, antifungal activity, and 30-day stability using NMR spectroscopy. An antifungal activity test showed no significant difference in the antifungal activity between optimal fluconazole-loaded nanoemulsions and a 0.3% aqueous drug solution, but previously, research showed that prepared formulations were characterized by a higher viscosity and satisfactory prolonged release compared to a control. In a 30-day stability study, it was observed that higher HLB values of the used surfactants decreased the stability of the formulations in the following order: Kolliphor EL, Tween 80, Tween 20. The NMR spectra confirmed that Kolliphor EL-based formulations ensured the higher stability of the nanoemulsion composition in comparison to Tween 80 and a better stabilizing effect of propylene glycol as a cosurfactant in comparison to PEG 200. Therefore, the optimization of HPH technology should be focused on the selection of Smix and the Smix:oil ratio in order to prepare stable formulations of high quality.
Head-to-Head Comparison of Novel Vaccine Technologies Comes with a Minefield of Challenges
Authors: Christensen Dennis
Published: December 2023

Modern vaccine development is having a golden period, with a variety of novel subunit technologies being introduced into clinical development in recent years. This opens the opportunity to find the best platform to use for novel vaccine antigen candidates through head-to-head comparative studies. Seldom appreciated is, however, the fact that these different technologies often do not have the same optimal antigen dose ratio, prime-boost regime and peak timepoint for measuring immunity. Instead, the preclinical studies that make the basis for platform selection use standard protocols not optimized for individual vaccines and fail to make selection on an informed basis. Here, I discuss the opportunities we have to optimize vaccine platform technologies through a better understanding of vaccine priming kinetics, the optimal antigen dose and sampling time and location.
Phenotypic Plasticity of Yield and Yield-Related Traits Contributing to the Wheat Yield in a Doubled Haploid Population
Authors: Saieed Md Atik Us , Zhao Yun , Chen Kefei , Rahman Shanjida , Zhang Jingjuan , Islam Shahidul , Ma Wujun
Published: December 2023

Phenotypic plasticity is the ability of an individual genotype to express phenotype variably in different environments. This study investigated the plasticity of yield-related traits of bread wheat by utilising 225 doubled haploid (DH) lines developed from cv. Westonia and cv. Kauz, through two field trials in Western Australia. Plasticity was quantified via two previously published methods: responsiveness to varying ecological conditions and slopes of reaction norms. The spikelets/spike was the most plastic trait, with an overall plasticity of 1.62. The least plastic trait was grain protein content, with an overall plasticity of 0.79. The trait hierarchy based on phenotypic plasticity was spikelets/spike > thousand kernel weight > seed number > seed length > grain yield > grain protein content. An increase in yield plasticity of 0.1 was associated with an increase in maximum yield of 4.45 kg ha−1. The plasticity of seed number and grain protein content were significantly associated with yield plasticity. The maximal yield was positively associated with spikelets/spike and grain yield, whereas it negatively associated with grain protein content. In contrast, the minimal yield was found to be negatively related to the plasticity of spikelets/spike and the plasticity of grain yield, whereas it was not related to grain protein content plasticity. Seed number and seed length exhibited plastic responses at the higher fertilisation state while remaining relatively stable at the lower fertilisation state for the wheat DH population. The finding of the current study will play a key role in wheat improvement under the changing climate. Seed length and seed number should be the breeding target for achieving stable yield in adverse environmental conditions.
Energy Partitioning and Latent Heat Flux Driving Factors of the CAM Plant Pineapple (Ananas comosus (L.) Merril) Grown in the South Subtropical China
Authors: Liu Zhigang , Zhao Baoshan , Yan Haofang , Su Junbo
Published: December 2023

Elucidation of different vegetation energy partitioning and environmental control factors at the agro-ecosystem levels is critical for better understanding and scientific management of farmland. Pineapple (Ananas comosus (L.) Merril) is a tropical plant widely cultivated in the southern subtropical region of China; however, the energy partitioning of crassulacean acid metabolism (CAM) plants like pineapple and their interactions with the environment remain not well understood. In this study, we investigated the energy partitioning patterns of pineapple fields and latent heat flux (LET) response to environmental factors using the Bowen ratio energy balance system and meteorological observation field data. The results showed that the CAM plant pineapple energy partitioning was significantly different from the common C3 and C4 crops during the study period, which was mainly attributed to the complex interactions between CAM plant transpiration and the environment. Specifically, sensible heat flux was the main component of net radiation (Rn), followed by the LET, accounting for 65.0% and 30.8% of the Rn, respectively. Soil heat flux accounts for a very small fraction (4.2%). The mean values of the Bowen ratio were 2.09 and 1.41 for sunny and cloudy days during the daytime and 0.74 and 0.46 at night, respectively. LET is a key factor in responding to crop growth status and agricultural water management, and the path analysis indicates that its variation is mainly influenced directly by Rn with a direct path coefficient of 0.94 on sunny days, followed by vapor pressure deficit, air temperature and relative humidity, which indirectly affect LET through the Rn pathway, whereas soil moisture and wind speed have a low effect on LET. On cloudy days, the effect of Rn on LET was overwhelmingly dominant, with a direct path coefficient of 0.91. The direct path coefficients of the remaining factors on LET were very small and negative. Overall, this study is an important reference for enhancing the impact of pineapple as well as CAM plants on the surface energy balance and regional climate.
Origin and Function of Amino Acids in Nectar and Nectaries of Pitcairnia Species with Particular Emphasis on Alanine and Glutamine
Authors: Göttlinger Thomas , Lohaus Gertrud
Published: December 2023

Floral nectar contains sugars and numerous other compounds, including amino acids, but little is known about their function and origin in nectar. Therefore, the amino acid, sugar, and inorganic ion concentrations, as well as the activity of alanine aminotransferase (AlaAT) and glutamine synthetase (GS) in nectar, nectaries, and leaves were analyzed in 30 Pitcairnia species. These data were compared with various floral traits, the pollinator type, and the phylogenetic relationships of the species to find possible causes for the high amino acid concentrations in the nectar of some species. The highest concentrations of amino acids (especially alanine) in nectar were found in species with reddish flowers. Furthermore, the concentration of amino acids in nectar and nectaries is determined through analyzing flower color/pollination type rather than phylogenetic relations. This study provides new insights into the origin of amino acids in nectar. The presence of almost all amino acids in nectar is mainly due to their transport in the phloem to the nectaries, with the exception of alanine, which is partially produced in nectaries. In addition, active regulatory mechanisms are required in nectaries that retain most of the amino acids and allow the selective secretion of specific amino acids, such as alanine.
Strengthened Decellularized Porcine Valves via Polyvinyl Alcohol as a Template Improving Processability
Authors: Chen Qingqing , Wang Chaorong , Wang Han , Xiao Jinfeng , Zhou Yingshan , Gu Shaojin , Xu Weilin , Yang Hongjun
Published: December 2023

The heart valve is crucial for the human body, which directly affects the efficiency of blood transport and the normal functioning of all organs. Generally, decellularization is one method of tissue-engineered heart valve (TEHV), which can deteriorate the mechanical properties and eliminate allograft immunogenicity. In this study, removable polyvinyl alcohol (PVA) is used to encapsulate decellularized porcine heart valves (DHVs) as a dynamic template to improve the processability of DHVs, such as suturing. Mechanical tests show that the strength and elastic modulus of DHVs treated with different concentrations of PVA significantly improve. Without the PVA layer, the valve would shift during suture puncture and not achieve the desired suture result. The in vitro results indicate that decellularized valves treated with PVA can sustain the adhesion and growth of human umbilical vein endothelial cells (HUVECs). All results above show that the DHVs treated with water-soluble PVA have good mechanical properties and cytocompatibility to ensure post-treatment. On this basis, the improved processability of DHV treated with PVA enables a new paradigm for the manufacturing of scaffolds, making it easy to apply.
Citryl-Imino-Chitosan Xerogels as Promising Materials for Mercury Recovery from Waste Waters
Authors: Ailincai Daniela , Andreica Bianca Iustina
Published: December 2023

The present study reported the obtention of xerogels based on chitosan and citral and their use as materials for mercury ion recovery from aqueous solutions, this being a serious problem related to the environment. The systems were prepared by the acid condensation of chitosan with citral, followed by the lyophilization of the resulting hydrogels, in order to obtain highly porous solid materials. The structural, morphological and supramolecular characterization of the systems was performed using 1H-NMR and FTIR spectroscopy, scanning electron microscopy and wide-angle X-ray diffraction. The ability of the obtained materials to be used for the recovery of mercury from aqueous solutions revealed the high potential of the xerogels to be used in this sense, the analysis of the materials post mercury absorption experiments revealing that this ability is predominantly conferred by the imine linkages which act as coordinating moieties for mercury ions.
Long-Term Viscoelastic Behavior of Polyisobutylene Sealants before and after Thermal Stabilization
Authors: Centa Urška Gradišar , Oseli Alen , Mihelčič Mohor , Kralj Aleš , Žnidaršič Matjaž , Halilovič Miroslav , Perše Lidija Slemenik
Published: December 2023

Polyisobutylene (PIB) is commonly used as a primary sealant in multi-layer insulating glazing elements, where temperatures often exceed 100 °C. At such conditions, PIB undergoes structural changes, causing different relaxation dynamics and leading to decreased lifetime of the material. Understanding thermal behavior is therefore imperative for achieving effective insulation of these materials for long-term use in insulating application. The present study was focused on the temperature dependence of viscoelastic behavior of two commercially available polyisobutylene (PIB) materials, which are commonly used as primary sealants for energy-efficient multi-layer glazing units. The long-term viscoelastic behavior of the materials before and after thermal treatment at high temperatures was studied by using time–temperature superposition (tTS). Van-Gurp–Palmen plots were obtained directly from experimental data and enabled the study of thermally induced changes, while the relaxation time spectra were calculated from master curves and enabled the calculation of molecular weight distribution. The results showed that, after thermal treatment, the structure of PIB materials changes from linear to branched, while the molecular weight distributions transition from monomodal to bimodal. The untreated samples exhibited viscous-like behavior, while the thermally stabilized samples exhibited solid-like behavior, extending the material response for ~6 decades towards a longer timescale. Moreover, the presented results can be directly used to simulate the mechanical responses of the sealants using currently available FEM software packages to predict their functional and structural lifetime.
Resolved Simulation of the Clarification and Dewatering in Decanter Centrifuges
Authors: Baust Helene Katharina , Hammerich Simon , König Hartmut , Nirschl Hermann , Gleiß Marco
Published: December 2023

Solid–liquid separation is a fundamental operation in process engineering and thus an important part of many process chains in the preparation of slurries in the chemical industry and other parts of the industrial environment. For the separation of micron-sized particles which, due to their size, do not settle or settle very slowly in the earth’s gravity field, centrifuges are often used. The preferred choice are often decanter centrifuges because they work continuously and stabilize the process against product fluctuations due to their adjustment possibilities. The design of the apparatus is complex: The main components of the apparatus are the cylindrical-conical bowl, which rotates at a high speed, and a screw located inside the bowl, which rotates in the same direction at a low differential speed to transport the separated solids out of the apparatus. Geometrical properties of the apparatus, as well as the adjustable operating parameters, such as rotational speed or differential speed, have a significant influence on the separation. In practice, analytical models and the experience of the manufacturers form the basis for the design. Characteristics of the disperse phase, interactions with the liquid, as well as the influence of the flow on the separation, are not taken into account. As a consequence, the transfer to industrial scale always requires a large number of pilot-scale experiments, which are time-consuming and expensive. Due to the increasing computational power, computational fluid dynamics (CFD) provides one possibility to minimize the experimental effort in centrifuge design. In this work, the open-source software OpenFOAM is used to simulate the multi-phase flow in a laboratory decanter centrifuge. For validation, experiments were carried out on a laboratory scale and the main operating parameters, such as speed, differential speed, and volume flow rate, were varied. The simulation results show a good agreement with the experimental data. Furthermore, the numerical investigations show the influence of the flow on the separation of the particles. To evaluate the transportability of a material, the transport efficiency was introduced as a dimensionless parameter. In addition, the simulation allows the consideration of the individual velocity components, making it possible to generate an impression of the complex three-dimensional flow in the apparatus for the first time.
Calibration and Experimental Study of a Self-Developed Particle-Number Measurement Instrument
Authors: Li Guangze , Luo Weixian , Zhang Chenglin , Cui Boxuan , Chang Liuyong , Chen Longfei
Published: December 2023

To accurately evaluate the size and distribution characteristics of the emission particles exhausted from in-use motor vehicle engines, we independently developed a condensation particle counter (CPC) known as BHCPC. It was calibrated by conducting the calibration procedures stated in the International Standard ISO 27981. After calibration, we conducted on-site measurements and offline sampling analysis of soot particles exhausted from different engines at a motor vehicle inspection center. The calibration results show that the detection efficiency is 90% when the particle diameter is 20.6 nm and the startup response time of the instrument is 3.53 s. The experiment results show that the self-developed BHCPC demonstrates good consistency in measuring particle-number concentration (PNC) in motor vehicle exhaust, with significant count fluctuations only occurring when PNC is higher than 25,000 P/cc. Under idle conditions, motor vehicles compliant with China VI emission regulations exhibit markedly lower exhaust emission PNC compared to those adhering to China IV emission regulations. Moreover, the results obtained from the offline electron microscope analysis show that fuel content in particle samples significantly decreases as engine speed increases, and a similar variation was also found in particle size. The micro-characteristics of the particle can give potential support to the combustion diagnostics.
Research on the Real-Time Detection of Red Fruit Based on the You Only Look Once Algorithm
Authors: Mei Song , Ding Wenqin , Wang Jinpeng
Published: December 2023

The real-time and accurate recognition of fruits and vegetables is crucial for the intelligent control of fruit and vegetable robots. In this research, apple picking is selected. This study proposed a lightweight, coupon-product, neural-net terminal YOLO algorithm for apple image recognition. Compared with the YOLO series algorithm, the tiny algorithm shows a strong relationship with the calculation speed. In traditional red fruit detection, the recognition time is generally several seconds, which is unacceptable in the real-time system. In this research, a total of 2000 apple images from different environments are used as a dataset for training and testing. The YOLOv4-tiny model is detailed, instructed, and used for the identification. The indicators, such as F1Score (0.92) and mAP (95.5% average), are analyzed by calculating the loss rate, accuracy rate (96.21%), and recall rate (95.47%). Finally, the algorithm shows good accuracy and high speed (no more than 5 ms) in online real-time detection.
Spatialization of Imperial Power: Spatial Reconstruction and Power Operation of Jinshan Temple during the Southern Inspection Tours of Emperor Kangxi
Authors: Yan Aibin , Zhu Shiyi
Published: December 2023

The Kangxi Southern Inspection Tours strengthened the Qing Dynasty’s control over Jiangnan Buddhism, thereby promoting the standardization and officialization of Jiangnan temples and externalizing imperial power through images and physical space. Taking Jinshan Temple as an example, this study combines spatial analysis of architecture and image analysis used by art historians to examine the transformation between physical and pictorial spaces in Jinshan Temple, revealing the spatial operation of imperial power. The intervention of imperial power sparked the space reconstruction of Jinshan Temple through a process of “merger-occupation-infiltration-adjustment”. Thus, the control measures of Kangxi are revealed, including the emphasis on the geographical significance of the temple, space occupation of royal buildings, change in landscape, and the adaptation of monks by adjusting their imagination of the sacred space. By determining the spatial reconstruction, we observe that the spatial strategy of power reflects Kangxi’s religious attitude toward Buddhism of “neither promoting nor suppressing, but treating it reasonably” 朕惟置之焉能有無之間, which may enrich our understanding of the influence of Kangxi’s Southern Inspection Tours on Jiangnan’s religious space.
When Does Psychotherapy Encourage Selfishness?
Authors: Park Deborah Y. , Peteet John R.
Published: December 2023

This paper explores how psychotherapy, with its inherent focus on the self, may inadvertently contribute to problematic selfishness. By comparison with religious traditions which have encouraged humility and dedication to serving others, psychotherapeutic schools have historically emphasized ways to meet one’s own needs. We review here the evolution of ego-centric approaches toward more relational and growth- and virtue-oriented ones, before considering four clinical contexts which risk fostering undue absorption with oneself and one’s therapy. A greater awareness of these risks can help clinicians and patients appreciate the role of moral values, world views, and religious commitments in shaping the direction of their work.
I Am What I Do—Negative Work as a Lens for the Study of Movement Chaplaincy
Authors: Wolff Edda Stephanie
Published: December 2023

This article explores the application of the concept of negative work within Movement Chaplaincy, contending that this framework facilitates engagement with negative spirituality in this sphere of ministry. Using the lens of the ‘work of the negative’, it examines the interplay between spirituality and political activism in Movement Chaplaincy, addressing potential resistance and inquiries surrounding the fusion of ‘negative spirituality’—focused on the apophatic and mystical-paradoxical aspects—and practical collective activism. This approach emphasizes the practical and theoretical aspects of challenging prevailing narratives, investigating self-subverting methods, and unearthing layers of non-identical elements within this process. It suggests that the evolving interest in the role of spirituality within social movements, coupled with initiatives like the Daring Compassion project, signifies a synergy between academic exploration and practical spiritual care provision. Ultimately, this article seeks to interpret activist work through the lens of spiritual accompaniment, creating space for an expanded understanding of activism across diverse identities and power dynamics. It proposes that the concept of ‘negative work’ serves as a tool for interpreting and deepening comprehension of the intrinsic dynamics within Movement Chaplaincy, fostering an inclusive and transformative approach to social and political change.
Spatiotemporal Characteristics of Actual Evapotranspiration Changes and Their Climatic Causes in China
Authors: Dai Qin , Chen Hong , Cui Chenfeng , Li Jie , Sun Jun , Ma Yuxin , Peng Xuelian , Wang Yakun , Hu Xiaotao
Published: December 2023

As the main expenditure item in water balance, evapotranspiration has an important impact on the surface ecosystem. Assessing the impact of changes in meteorological elements on evapotranspiration is essential to identify the spatiotemporal heterogeneity of hydrographic responses to climate changes. Based on the actual evapotranspiration (ETa) product (GPR-ET) generated by Gaussian process regression (GPR), as well as temperature and precipitation datasets, our study employed various statistical analysis methods, including geographic detector, the center of gravity migration model, spatial variation coefficients, and partial differential models, to investigate the spatiotemporal variation in ETa in China from 2000 to 2018. The analysis covered future trends in ETa changes and the contribution of meteorological factors. Our results showed that the ETa in northwest China had stronger spatial heterogeneity and the mean value was generally lower than that in the southeast. But the center of gravity of ETa was shifting towards the northwest. In most areas, the future trend was expected to be inconsistent with the current stage. ETa in the regions of north and west was mainly driven by precipitation, while its increase in southeast China was largely attributed to temperature. In addition to spatial variations, the joint enhancement effect of temperature and precipitation on ETa exists. According to the contribution analysis, precipitation contributed more to the change in ETa than temperature. These findings have enhanced our comprehension of the contribution of climate variability to ETa changes, providing scientific proof for the optimization apportion of future water resources.
A Method for Extracting Photovoltaic Panels from High-Resolution Optical Remote Sensing Images Guided by Prior Knowledge
Authors: Liu Wenqing , Huo Hongtao , Ji Luyan , Zhao Yongchao , Liu Xiaowen , Li Jing
Published: December 2023

The extraction of photovoltaic (PV) panels from remote sensing images is of great significance for estimating the power generation of solar photovoltaic systems and informing government decisions. The implementation of existing methods often struggles with complex background interference and confusion between the background and the PV panels. As a result, the completeness and edge clarity of PV panel extraction results are compromised. Moreover, most previous studies have overlooked the unique color characteristics of PV panels. To alleviate these deficiencies and limitations, a method for extracting photovoltaic panels from high-resolution optical remote sensing images guided by prior knowledge (PKGPVN) is proposed. Firstly, aiming to address the problems related to missed extractions and background misjudgments, a Photovoltaic Index (PVI) based on visible images in the three-band is constructed to serve as prior knowledge to differentiate between PV panels and non-PV panels. Secondly, in order to strengthen information interaction between shallow features and deep features and enhance the accuracy and integrity of results, a Residual Convolution Hybrid Attention Module (RCHAM) is introduced into the skip-connection of the encoding–decoding structure. Finally, for the purpose of reducing the phenomenon of blurred edges, a multilevel Feature Loss (FL) function is designed to monitor the prediction results at different scales. Comparative experiments are conducted with seven methods, including U-Net, on publicly available datasets. The experimental results show that our PKGPVN achieves superior performance in terms of evaluation metrics such as IoU (above 82%), Precision (above 91%), Recall (above 89%), and F1-score (above 90%) on the AIR-PV dataset. Additionally, the ablation experiments illustrate the effectiveness of our key parts. The proposed method reduces the phenomena of missed extractions and background misjudgments effectively while producing highly accurate results with clear boundaries.
An Improved Hybrid Beamforming Algorithm for Fast Target Tracking in Satellite and V2X Communication
Authors: Zorkun Aral Ertug , Salas-Natera Miguel A. , Rodríguez-Osorio Ramón Martínez
Published: December 2023

Autonomous remote sensing systems establish communication links between nodes. Ensuring coverage and seamless communication in highly dense environments is not a trivial task as localization, separation, and tracking of targets, as well as interference suppression, are challenging. Therefore, smart antenna systems fulfill these requirements by employing beamforming algorithms and are considered a key technology for autonomous remote sensing applications. Among many beamforming algorithms, the recursive least square (RLS) algorithm has proven superior convergence and convergence rate performances. However, the tracking performance of RLS degrades in the case of dynamic targets. The forgetting factor in RLS needs to be updated constantly for fast target tracking. Additionally, multiple beamforming algorithms can be combined to increase tracking performance. An improved hybrid constant modulus RLS beamforming algorithm with an adaptive forgetting factor and a variable regularization factor is proposed. The forgetting factor is updated using the low-complexity yet robust adaptive moment estimation method (ADAM). The sliding-window technique is applied to the proposed algorithm to mitigate the steady-state noise. The proposed algorithm is compared with existing RLS-based algorithms in terms of convergence, convergence rate, and computational complexity. Based on the results, the proposed algorithm has at least 10 times better convergence (accuracy) and a convergence rate two times faster than the compared RLS-based algorithms.
The Responses of Ozone to the Solar Eclipse on the 21st of June 2020 in the Mesosphere and Upper Stratosphere
Authors: Li Jingyuan , Jiang Shuwen , Yao Jingrui , Cui Jingqi , Lu Jianyong , Tian Yufeng , Yang Chaolei , Xiong Shiping , Wei Guanchun , Zhang Xiaoping , Fu Shuai , Zhu Zhixin , Wang Jingye , Li Zheng , Zhang Hua
Published: December 2023

Microwave Limb Sounder (MLS) observations showed an obvious variation of ozone concentration during the annular solar eclipse on 21 June 2020 in the mesosphere and upper stratosphere. Ozone concentration slightly reduced near 40 km in the regions of 24°N–36°N, and increased in low latitudes at 40 km. In the heights of 45–60 km, the increase in ozone concentration in most of the regions was obvious. The ozone increases and decreases were more obvious between 60–65 km, where enhancement took the leading role. The nighttime ozone variation was weaker than the daytime in most of the heights of 30–65 km. The variation of HO2 and CO is investigated to study the photochemical and dynamical causes of ozone variation. As HO2 decreased at 1 hPa and increased at 60–65 km, ozone variation shows a mostly reversed relationship to HO2 variation. CO increased at 32–39 km and decreased at 52–60 km, which was related to the upwelling at these heights. The dynamic processes also contributed to the decrease in ozone concentration at 40 km and increase at 50–60 km.
AI for Marine, Ocean and Climate Change Monitoring
Authors: Nieves Veronica , Ruescas Ana , Sauzède Raphaëlle
Published: December 2023

In the ever-evolving landscape of marine, oceanic, and climate change monitoring, the intersection of cutting-edge artificial intelligence (AI), machine learning (ML), and data analytics has emerged as a pivotal catalyst for transformative advancements [...]
Infrared Small Dim Target Detection Using Group Regularized Principle Component Pursuit
Authors: Li Meihui , Wei Yuxing , Dan Bingbing , Liu Dongxu , Zhang Jianlin
Published: December 2023

The detection of an infrared small target faces the problems of background interference and non-obvious target features, which have yet to be efficiently solved. By employing the non-local self-correlation characteristic of the infrared images, the principle component pursuit (PCP)-based methods are demonstrated to be applicable to infrared small target detection in a complex scene. However, existing PCP-based methods heavily depend on the uniform distribution of the background pixels and are prone to generating a high number of false alarms under strong clutter situations. In this paper, we propose a group low-rank regularized principle component pursuit model (GPCP) to solve this problem. First, the local image patches are clustered into several groups that correspond to different grayscale distributions. These patch groups are regularized with a group low-rank constraint, enabling an independent recovery of different background regions. Then, GPCP model integrates the group low-rank components with a global sparse component to extract small targets from the background. Different singular value thresholds can be exploited for image groups corresponding to different brightness and grayscale variance, boosting the recovery of background clutters and also enhancing the detection of small targets. Finally, a customized optimization approach based on alternating direction method of multipliers is proposed to solve this model. We set three representative detection scenes, including the ground background, sea background and sky background for experiment analysis and model comparison. The evaluation results show the proposed model has superiority in background suppression and achieves better adaptability for different scenes compared with various state-of-the-art methods.
Sensitivities of Vegetation Gross Primary Production to Precipitation Frequency in the Northern Hemisphere from 1982 to 2015
Authors: Xue Shouye , Wu Guocan
Published: December 2023

Vegetation of the Northern Hemisphere plays a vital role in global ecosystems and the carbon cycle. Variations in precipitation profoundly affect vegetation productivity, plant growth, and species communities. Precipitation frequency directly controls soil moisture availability, which has an impact on the vegetation carbon sink. However, it is unclear how precipitation frequency affects the vegetation productivity of different land cover types in different seasons. In this study, the sensitivities of the gross primary production (GPP) of six vegetation types (forest, cropland, grassland, shrubland, tundra and barren land) in response to the frequency of five categories of precipitation (trace: 0.1–5 mm/day, small: 5–10 mm/day, moderate: 10–15 mm/day, heavy: 15–20 mm/day, and very heavy: >20 mm/day) were analyzed based on the XGBoost model. The results showed that, between 1982 and 2015, precipitation frequency declined in most land cover types but increased significantly in the pan-Arctic. Differences in the sensitivity to precipitation frequency were observed between seasons and precipitation categories in northern latitudes. The GPP values of forest and barren land vegetation were less sensitive to precipitation frequency than grassland, shrubland and tundra. This may be related to different vegetation community structures and underlying surfaces and gradually increasing drought resistance capability. The sensitivity to precipitation frequency declined for moderate and heavy precipitation in cropland, but it increased in winter. As the frequency of trace precipitation diminishes in winter, the sensitivity of each vegetation type reduces by an average of 0.03%/decade. Conversely, the sensitivities to small and moderate rain increase by 0.01%/decade and 0.02%/decade, respectively, for ecosystems such as cultivated land, forests, and shrubs. However, shrubs and tundra exhibit distinct behaviors, where shifts in precipitation frequency align directly with trends in sensitivity. These results show that the frequency of precipitation significantly affects vegetation productivity and has different sensitivities, and vegetation shows different feedback mechanisms in the face of environmental changes.
Self-Adaptive-Filling Deep Convolutional Neural Network Classification Method for Mountain Vegetation Type Based on High Spatial Resolution Aerial Images
Authors: Li Shiou , Fei Xianyun , Chen Peilong , Wang Zhen , Gao Yajun , Cheng Kai , Wang Huilong , Zhang Yuanzhi
Published: December 2023

The composition and structure of mountain vegetation are complex and changeable, and thus urgently require the integration of Object-Based Image Analysis (OBIA) and Deep Convolutional Neural Networks (DCNNs). However, while integration technology studies are continuing to increase, there have been few studies that have carried out the classification of mountain vegetation by combining OBIA and DCNNs, for it is difficult to obtain enough samples to trigger the potential of DCNNs for mountain vegetation type classification, especially using high-spatial-resolution remote sensing images. To address this issue, we propose a self-adaptive-filling method (SAF) to incorporate the OBIA method to improve the performance of DCNNs in mountain vegetation type classification using high-spatial-resolution aerial images. Using this method, SAF technology was employed to produce enough regular sample data for DCNNs by filling the irregular objects created by image segmenting using interior adaptive pixel blocks. Meanwhile, non-sample segmented image objects were shaped into different regular rectangular blocks via SAF. Then, the classification result was defined by voting combining the DCNN performance. Compared to traditional OBIA methods, SAF generates more samples for the DCNN and fully utilizes every single pixel of the DCNN input. We design experiments to compare them with traditional OBIA and semantic segmentation methods, such as U-net, MACU-net, and SegNeXt. The results show that our SAF-DCNN outperforms traditional OBIA in terms of accuracy and it is similar to the accuracy of the best performing method in semantic segmentation. However, it reduces the common pretzel phenomenon of semantic segmentation (black and white noise generated in classification). Overall, the SAF-based OBIA using DCNNs, which is proposed in this paper, is superior to other commonly used methods for vegetation classification in mountainous areas.
Basin Scale Soil Moisture Estimation with Grid SWAT and LESTKF Based on WSN
Authors: Zhang Ying , Hou Jinliang , Huang Chunlin
Published: December 2023

This research utilized in situ soil moisture observations in a coupled grid Soil and Water Assessment Tool (SWAT) and Parallel Data Assimilation Framework (PDAF) data assimilation system, resulting in significant enhancements in soil moisture estimation. By incorporating Wireless Sensor Network (WSN) data (WATERNET), the method captured and integrated local soil moisture characteristics, thereby improving regional model state estimations. The use of varying observation search radii with the Local Error-subspace Transform Kalman Filter (LESTKF) resulted in improved spatial and temporal assimilation performance, while also considering the impact of observation data uncertainties. The best performance (improvement of 0.006 m3/m3) of LESTKF was achieved with a 20 km observation search radii and 0.01 m3/m3 observation standard error. This study assimilated wireless sensor network data into a distributed model, presenting a departure from traditional methods. The high accuracy and resolution capabilities of WATERNET’s regional soil moisture observations were crucial, and its provision of multi-layered soil temperature and moisture observations presented new opportunities for integration into the data assimilation framework, further enhancing hydrological state estimations. This study’s implications are broad and relevant to regional-scale water resource research and management, particularly for freshwater resource scheduling at small basin scales.
Altitudinal Genetic Variation of Pinus oocarpa Seedling Emergence in the Southern Mountains, Oaxaca, Mexico
Authors: Velasco-García Mario Valerio , Hernández-Hernández Adán
Published: December 2023

Pinus oocarpa is the most important conifer for resin production in Mexico, so superior resin trees were selected in the Southern Mountains of Oaxaca, Mexico. The objective was to determine the variation and differences among provenances and among trees according to the parameters of seedling emergence and the number of cotyledons, and their relationship with elevation and climatic variables. The seedling emergence of four replicates of 20 seeds from 80 trees was counted daily. For the emergence parameters, provenance contributed 42.02% to the total variance, tree 29.19% and error 28.79%. Only tree (11.71%) and error (88.29%) contributed to the total variance of the cotyledon number. The effect of provenance (p ≤ 0.0006) and tree (p ≤ 0.0001) was significant for all variables evaluated. Higher-elevation provenances and trees had higher emergence values. The emergence parameters were positively associated with tree elevation. Climatic variables related to precipitation and temperature were negatively related to the emergence parameters. The results allow for the selection of phenotypes without emergence problems to establish seed orchards.
Investigation of a Hydraulic Channel for Plastic Particles Sorting via Experimental and Numerical Tools
Authors: Moroni Monica
Published: December 2023

In recent decades, the versatility of fossil-based polymers has led them to become one of the most used materials for the production of several consumer goods. The destiny of post-consumer plastics is crucial for environmental sustainability. Two are the alternatives to landfilling: (i) energy recovery, i.e., replacement of traditional fuel with plastic litter, and (ii) recycling, i.e., processing of plastic wastes to produce secondary raw materials that may substitute primary raw materials. This work presents the investigation of a device for the hydraulic separation of heterogeneous plastic wastes, which, when properly upscaled, may be efficiently used within recycling plants. This apparatus is suitable for the separation of granules or flakes of plastics with a density higher than 1000 Kg/m3 and may replace existing technologies for mechanical recycling. The purpose of the device is to separate the useful fraction from a mixture of plastics and water introduced inside. The separation procedure efficacy relies on the difference in density, dimension, and shape of the processed plastic particles and on the flow features within the device. Experiments were carried out to test the efficacy of the device as a function of those factors. To increase the range of variation in the key parameters influencing the apparatus’s working principles, Computational Fluid Dynamics was employed to build a numerical model of the device. The validated numerical model suitable to fully characterize the apparatus performance features a hybrid grid with an inner mesh of 3·10−3 m size, a careful modeling of the near-wall region, and the k-ω SST turbulent model.
The Impact Factors and Spatial Spillover of Industrial Green Development: Based on Cities in the Northwest Segment of the Silk Road Economic Belt
Authors: Li Chendi , Wang Lei , Liu Yang
Published: December 2023

With the increasing global emphasis on green development, industrial green development (IGD) has gradually gained attention as a crucial component of sustainable development. However, there is limited research evaluating and analyzing the IGD of cities with slow economic development and a high resource endowment. Utilizing empirical data gathered from cities in the northwest segment of the Silk Road Economic Belt spanning from 2009 to 2018, this research employs the entropy-weighted TOPSIS model to establish an indicator framework for evaluating IGD. Subsequently, this paper analyzes the impact of factors such as the economic foundation, innovation capacity and crucial guarantee on IGD, as well as the spatial spillover effects in cities of the northwest segment of the Silk Road Economic Belt using spatial panel data and the spatial Durbin model. The results indicate that the IGD levels of urban clusters exhibit the characteristics of plate-ladder-type difference, being “excellent in the southeast, good in the middle, and inferior in the northwest” displaying fluctuating upward trends and spatial clustering over time. Additionally, the degree of opening up also positively impacts IGD, while the level of economic development has a detrimental effect on IGD. Human capital and environmental regulations demonstrate notable spatial spillover effects on IGD. Our study enriches the evaluation system for IGD and provides recommendations for the industrial green transformation of cities along the Silk Road Economic Belt.
Sustainability-Driven Green Innovation: Revolutionising Aerospace Decision-Making with an Intelligent Decision Support System
Authors: Mutanov Galimkair , Omirbekova Zhanar , Shaikh Aijaz A. , Issayeva Zhansaya
Published: December 2023

Green innovation refers to developing and implementing new technologies, practices, products, and processes that promote sustainability and reduce environmental impacts. This article postulates the conceptualisation and implementation of an intelligent decision support system (IDSS) tailored to the aerospace technology sector. The data were collected from open sources such as social media and analyzed using the natural language processing tool. The envisaged IDSS is a comprehensive and seamlessly integrated platform designed to undergird decision-making, problem-solving, and research initiatives within the aerospace industry. Catering to the sector’s engineers, technicians, and managerial cadres, it aims to unravel complex datasets, proffer incisive analyses, and furnish prudent advice and recommendations. Its multifaceted capabilities range from data search and optimisation to modelling and forecasting. With an emphasis on harmonious integration with extant aerospace systems, it strives to provide engineers and technicians with enriched data insights. Moreover, its design ethos is centred on user-friendliness, underscored by an intuitive graphical interface that expedites seamless access and utilisation. Ultimately, the envisioned IDSS will augment the aerospace industry’s analytical prowess and will serve as a potent instrument for effective decision-making.
A Multi-Hazard Climate, Displacement and Socio-Vulnerability Score for New York City
Authors: Tedesco Marco , Foster Sheila , Baptista Ana , Zuzak Casey
Published: December 2023

Understanding and quantifying the compounding effects of climate change, displacement and socio-vulnerability is crucial for the development and implementation of timely mitigation and adaptation policies. Here, we present a new Climate Displacement and Socio-Vulnerability (CDSV) score over NYC that accounts for several climate hazards (coastal and riverine flooding, heatwaves, hurricanes and winter weather), displacement and social vulnerability metrics with the ultimate goal of identifying those areas where risk of the combination of the three factors is the highest (e.g., hotspots due to compounding effects). To our knowledge, this is the first time that multiple climate hazards have been studied in conjunction with displacement and socio-vulnerability for NYC. We discuss those areas that are exposed to high CDSV values for the different hazards, where multiple hazards show overlapping high values of CDSV and analyze how socio-demographic characteristics have changed over the past two decades. We find that Black and Latin/Hispanic people are exposed to the compounding effects of multiple hazards, especially in areas located in the south Bronx, south Brooklyn and Queens, with maximum CDSV scores reaching values close to ~80 over a scale of 100, and with the increased exposure of Black, Latinx/Hispanix and Asians since the beginning of the century. We find that, except for the case of coastal flooding, the percentage of White people living in areas characterized by CDSV values decreases as CDSV scores increase where the percentage of Black people and Latin/Hispanic people increases, with the latter showing the strongest correlation. We also find a statistically significant relationship between the number of people with asthma and diabetes and the CDSV score in the case of heatwaves.
Influence of Depth on CO2/CH4 Sorption Ratio in Deep Coal Seams
Authors: Dutka Barbara
Published: December 2023

The present work aims to analyse the influence of present-day burial depths of coal seams on the sorption properties towards CH4 and CO2, respectively. For medium-rank coals located in the southwestern area of the Upper Silesian Coal Basin (USCB), the gravimetric sorption measurements were carried out with pure gases at a temperature of 30 °C. The variability of CO2/CH4 exchange sorption and diffusivity ratios was determined. It was revealed that in coal seams located at a depth above 700 m, for which the sorption exchange ratio was the greatest, the process of CO2 injection for permanent storage was more beneficial. In the coal seams lying deeper than 700 m with a lower CO2/CH4 sorption ratio, the CH4 displacement induced by the injection of CO2 (CO2-ECBM recovery) became more favourable.