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Hyperspectral image classification (HSIC) has garnered increasing attention among researchers. While classical networks like convolution neural networks (CNNs) have achieved satisfactory results with the advent of deep learning, they are confined to processing local information. Vision transformers, despite being effective at establishing long-distance dependencies, face challenges in extracting high-representation features for high-dimensional images. In this paper, we present the multiscale efficient attention with enhanced feature transformer (MEA-EFFormer), which is designed for the efficient extraction of spectral–spatial features, leading to effective classification. MEA-EFFormer employs a multiscale efficient attention feature extraction module to initially extract 3D convolution features and applies effective channel attention to refine spectral information. Following this, 2D convolution features are extracted and integrated with local binary pattern (LBP) spatial information to augment their representation. Then, the processed features are fed into a spectral–spatial enhancement attention (SSEA) module that facilitates interactive enhancement of spectral–spatial information across the three dimensions. Finally, these features undergo classification through a transformer encoder. We evaluate MEA-EFFormer against several state-of-the-art methods on three datasets and demonstrate its outstanding HSIC performance. [ABSTRACT FROM AUTHOR]

In this study, an overview of two years of research findings concerning the 2022 Hunga Tonga–Hunga Ha'apai (HTHH) volcanic eruption in the stratospheric environment is provided, focusing on water vapor, aerosols, and ozone. Additionally, the potential impacts of these changes on aviation equipment materials are discussed. The HTHH volcanic eruption released a large amount of particles (e.g., ash and ice) and gases (e.g., H2O, SO2, and HCl), significantly affecting the redistribution of stratospheric water vapor and aerosols. Stratospheric water vapor increased by approximately 140–150 Tg (8–10%), with a concentration peak observed in the height range of 22.2–27 km (38–17 hPa). Satellite measurements indicate that the HTHH volcano injected approximately 0.2–0.5 Tg of sulfur dioxide into the stratosphere, which was partially converted into sulfate aerosols. In-situ observations revealed that the volcanic aerosols exhibit hygroscopic characteristics, with particle sizes ranging from 0.22–0.42 μm under background conditions to 0.42–1.27 μm. The moist stratospheric conditions increased the aerosol surface area, inducing heterogeneous chlorine chemical reactions on the aerosol surface, resulting in stratospheric ozone depletion in the HTHH plume within one week. In addition, atmospheric disturbances and ionospheric disruptions triggered by volcanic eruptions may adversely affect aircraft and communication systems. Further research is required to understand the evolution of volcanic aerosols and the impact of volcanic activity on aviation equipment materials. [ABSTRACT FROM AUTHOR]

Despite notable advancements achieved on Hyperspectral (HS) pansharpening tasks through deep learning techniques, previous methods are inherently constrained by convolution or self-attention intrinsic defects, leading to limited performance. In this paper, we proposed an Attention-Interactive Dual-Branch Convolutional Neural Network (AIDB-Net) for HS pansharpening. Our model purely consists of convolutional layers and simultaneously inherits the strengths of both convolution and self-attention, especially the modeling of short- and long-range dependencies. Specially, we first extract, tokenize, and align the hyperspectral image (HSI) and panchromatic image (PAN) by Overlapping Patch Embedding Blocks. Then, we specialize a novel Spectral-Spatial Interactive Attention which is able to globally interact and fuse the cross-modality features. The resultant token-global similarity scores can guide the refinement and renewal of the textural details and spectral characteristics within HSI features. By deeply combined these two paradigms, our AIDB-Net significantly improve the pansharpening performance. Moreover, with the acceleration by the convolution inductive bias, our interactive attention can be trained without large scale dataset and achieves competitive time cost with its counterparts. Compared with the state-of-the-art methods, our AIDB-Net makes 5.2%, 3.1%, and 2.2% improvement on PSNR metric on three public datasets, respectively. Comprehensive experiments quantitatively and qualitatively demonstrate the effectiveness and superiority of our AIDB-Net. [ABSTRACT FROM AUTHOR]

There have been considerable efforts in generating tree crown maps from satellite images. However, tree localization in urban environments using satellite imagery remains a challenging task. One of the difficulties in complex urban tree detection tasks lies in the segmentation of dense tree crowns. Currently, methods based on semantic segmentation algorithms have made significant progress. We propose to split the tree localization problem into two parts, dense clusters and single trees, and combine the target detection method with a procedural generation method based on planting rules for the complex urban tree detection task, which improves the accuracy of single tree detection. Specifically, we propose a two-stage urban tree localization pipeline that leverages deep learning and planting strategy algorithms along with region discrimination methods. This approach ensures the precise localization of individual trees while also facilitating distribution inference within dense tree canopies. Additionally, our method estimates the radius and height of trees, which provides significant advantages for three-dimensional reconstruction tasks from remote sensing images. We compare our results with other existing methods, achieving an 82.3% accuracy in individual tree localization. This method can be seamlessly integrated with the three-dimensional reconstruction of urban trees. We visualized the three-dimensional reconstruction of urban trees generated by this method, which demonstrates the diversity of tree heights and provides a more realistic solution for tree distribution generation. [ABSTRACT FROM AUTHOR]

Simple Summary: Protozoa that parasitize within host cells can avoid direct damage from the host immune system. In this review, we have revealed some key factors and signaling pathways that inhibit host cell apoptosis, regulate cell apoptosis signal transduction, and interfere with the molecular mechanisms of cell apoptosis. These findings provide important clues to further understand the infection mechanism and pathogenesis of Apicomplexan protozoa and a theoretical basis for the development of new therapeutic strategies and preventive measures. Apicomplexan protozoa, which are a group of specialized intracellular parasitic protozoa, infect humans and other animals and cause a variety of diseases. The lack of research on the interaction mechanism between Apicomplexan protozoa and their hosts is a key factor restricting the development of new drugs and vaccines. In the early stages of infection, cell apoptosis is inhibited by Apicomplexan protozoa through their interaction with the host cells; thereby, the survival and reproduction of Apicomplexan protozoa in host cells is promoted. In this review, the key virulence proteins and pathways are introduced regarding the inhibition of cell apoptosis by the interaction between the protozoa and their host during the early stage of Apicomplexan protozoa infection. It provides a theoretical basis for the development of drugs or vaccines for protozoal diseases. [ABSTRACT FROM AUTHOR]

Online surface inspection systems have gradually found applications in industrial settings. However, the manual effort required to sift through a vast amount of data to identify defect images remains costly. This study delves into a self-supervised binary classification algorithm for addressing the task of defect image classification within ductile cast iron pipe (DCIP) images. Leveraging the CutPaste-Mix data augmentation strategy, we combine defect-free data with enhanced data to input into a deep convolutional neural network. Through Gaussian Density Estimation, we compute anomaly scores to achieve the classification of abnormal regions. Our approach has been implemented in real-world scenarios, involving equipment installation, data collection, and experimentation. The results demonstrate the robust performance of our method, in both the DCIP image dataset and practical field application, achieving an impressive 99.5 AUC (Area Under Curve). This presents a cost-effective means of providing data support for subsequent DCIP surface inspection model training. [ABSTRACT FROM AUTHOR]

Background: Psychological distress is an important mental health problem in college students. Insomnia may be a major factor contributing to psychological distress. This study aimed to explore the indirect relationship between insomnia and psychological distress through the five PERMA wellbeing variables (i.e., positive emotions, engagement, relationships, meaning in life, and achievement) among nursing college students. Methods: A cross-sectional study was conducted in China using an online survey design. Mediation analyses were examined using the PROCESS macro version 4.1 for SPSS 27.0. A total of 1741 nursing college students completed the online survey. Results: Insomnia was positively associated with psychological distress (p < 0.01, r = 0.673), while negative associations were detected between PERMA wellbeing variables and insomnia (p < 0.01, r range = −0.176 and −0.272), as well as psychological distress (p < 0.01, r range = −0.196 and −0.386). The association between insomnia and psychological distress was partially mediated by the participants' positive emotions (indirect effect = 0.137, SE = 0.024, 95% CI boot = [0.094, 0.188]), engagement (indirect effect = −0.033, SE = 0.010, 95% CI boot = [−0.054, −0.017]), and meaning in life (indirect effect = 0.027, SE = 0.014, 95% CI boot = [0.001, 0.055]) but not their relationships or achievement of the PERMA wellbeing variables. Conclusions: The findings of this study suggest that the PERMA wellbeing variables, especially positive emotions, engagement, and meaning in life, could be potential mechanisms by which insomnia is associated with psychological distress. The mediating roles of PERMA wellbeing variables between insomnia and psychological distress could be incorporated into the health management of university administrations to promote the health and wellbeing of nursing college students. [ABSTRACT FROM AUTHOR]

The preparation and application of microcapsules containing healing agents have become a crucial way to enhance the self-healing capability of bitumen. This intelligent material has become a hot topic in the field of pavement material and has greatly stimulated the development and applications of pavement engineering. However, there has been no research focused on the relationship of the multistructures from the viewpoint of molecular-size, microsize, and macrosize, which significantly limits the predictions of the self-healing efficiency and structure design of this self-healing material. The purpose of this study was to make a mathematical analysis of the influencing factors of self-healing efficiency based on the self-healing mechanism of bitumen using microcapsules, fully considering the structural dimensions, preparation conditions, and self-healing conditions. In the mathematical analysis, the cross-linking degree of the shell material molecules of the microcapsules was considered for its damage strength from the perspective of molecular structure. The final tip stress of the microcrack was believed to be equal to the puncture strength of the microcapsules in terms of microsize. From a macroscale point of view, the amount of healing agent released from the microcapsule rupture was considered more significant than or equal to the volume of the microcracks. At the same time, the time–temperature superposition principle was applied to simplify the influence factors. The above derivation based on multiscale structures found that the additive amount of the microcapsules, temperature, and time were the three main influencing factors on the self-healing features of bitumen. Finally, the experimental data was investigated considering the three factors, which thoroughly verified the feasibility of the derivation. All results will help to establish a bridge between the initial structural design of self-healing bitumen and the prediction of the final self-healing effects. [ABSTRACT FROM AUTHOR]

The oily rejuvenator acted as the healing agent in microvasculars. A tensile test was designed to evaluate the self-healing efficiency of asphalt affected by microvascular number, self-healing time and temperature. It was found that the healing agent was slowly released through the microporous channels on the inner shell of the microvascular. The release modes of the agent can work together to improve the self-healing efficiency. The self-healing values of the three samples (asphalt, asphalt/microvasculars without rejuvenator and asphalt/microvasculars with rejuvenator) are 51%, 53%, and 71%. The self-healing capability of the asphalt samples with a healing agent is much greater than that of the other two without a healing agent at the same time. More microvascular rupture at the asphalt sample interface led to a higher self-healing efficiency. The self-healing efficiency values of the three samples (asphalt samples with one, two, and three microvasculars) are 52%, 67%, and 73%, respectively. The self-healing efficiency of the same sample increased during 1–3 days from 26% to 88% in one self-healing cycle. The self-healing efficiency value indicated that increasing the temperature improved each sample's self-healing efficiency. The above trend of change also applies to the second self-healing process. A higher temperature reduces the resistance to molecular motion and accelerates the molecular action of bitumen and the healing agent. The time–temperature equivalence principle can be fully applied to comprehend asphalt self-healing. [ABSTRACT FROM AUTHOR]

Strong earthquakes can not only trigger many landslides in a short period of time but can also change the stability of slopes in the earthquake area, causing them to be active for a long time after the earthquake. Research on the variation of slow-motion slopes before and after earthquakes can help us to better understand the mechanism of earthquake-affected landslides, which is also crucial for assessing the long-term landslide risk in seismically active areas. Here, L-band ALOS-2 PALSAR-2 images are utilized with the SBAS-InSAR algorithm to monitor and assess the location and activity changes of slow-moving landslides in the Iburi region (Hokkaido, Japan) before and after an earthquake occurred on 6 September 2018. Unlike previous studies, which focused on single typical landslides, we tracked all the landslides within a 33 × 55 km region close to the epicenter. According to the results, the majority of the co-seismic landslides that quickly failed during the earthquake are now stable, and a few of them are still moving. In contrast, due to near-field seismic shaking, certain slopes that did not show substantial surface changes during the earthquake period continued to move and eventually developed into slow-moving landslides. In addition, it can be seen from the spatial distribution of slow-moving landslides after the earthquake that this distribution is not only dependent on strong earthquake seismic vibration or the hanging-wall effect. Far-field weak vibrations can also accelerate landslides. Additionally, we discovered that the earthquake made the unstable slopes move more quickly but also tended to stabilize the slopes that were already in motion before the earthquake. The various response modes of slow-moving landslides to seismic events are related not only to the intensity of seismic vibration but also to the geological conditions of the region and to the size of the landslide itself. These findings are extremely valuable for studying the mechanism of earthquake-affected landslides. [ABSTRACT FROM AUTHOR]

Since late 2019, the explosive outbreak of Coronavirus Disease 19 (COVID-19) has emerged as a global threat, necessitating a worldwide overhaul of public health systems. One critical strategy to prevent virus transmission and safeguard public health, involves deploying Nucleic Acid Testing (NAT) sites. Nevertheless, determining the optimal locations for public NAT sites presents a significant challenge, due to the varying number of sites required in different regions, and the substantial influences of population, the population heterogeneity, and daily dynamics, on the effectiveness of fixed location schemes. To address this issue, this study proposes a data-driven framework based on classical location-allocation models and bi-objective optimization models. The framework optimizes the number and location of NAT sites, while balancing various cost constraints and adapting to population dynamics during different periods of the day. The bi-objective optimization process utilizes the Knee point identification (KPI) algorithm, which is computationally efficient and does not require prior knowledge. A case study conducted in Shenzhen, China, demonstrates that the proposed framework provides a broader service coverage area and better accommodates residents' demands during different periods, compared to the actual layout of NAT sites in the city. The study's findings can facilitate the rapid planning of primary healthcare facilities, and promote the development of sustainable healthy cities. [ABSTRACT FROM AUTHOR]

The aging and damage of artificial skin materials for artificial intelligence robots are technical problems that need to be solved urgently in their application. In this work, poly (vinylidene fluoride) (PVDF) fibers containing a liquid agent were fabricated directly as biomimetic microvasculars, which were mixed in a glycol–polyvinyl alcohol–gelatin network gel to form biomimetic self-healing artificial skin composites. The self-healing agent was a uniform-viscous buffer solution composed of phosphoric acid, acetic acid, and sodium carboxymethyl cellulose (CMC-Na), which was mixed under 40 °C. Microstructure analysis showed that the fiber surface was smooth and the diameter was uniform. SEM images of the fiber cross-sections showed that there were uniformly distributed voids. With the extension of time, there was no phenomenon of interface separation after the liquid agent diffused into the matrix through the fiber cavity. The entire process of self-healing was observed and determined including fiber breakage and the agent diffusion steps. XRD and FT–IR results indicated that the self-healing agent could enter the matrix material through fiber damage or release and it chemically reacted with the matrix material, thereby changing the chemical structure of the damaged matrix. Self-healing behavior analysis of the artificial skin indicated that its self-healing efficiency increased to an impressive 97.0% with the increase in temperature to 45 °C. [ABSTRACT FROM AUTHOR]

Deformation and heat treatment are important means to strengthen aluminum alloys. However, the influence mechanism of pre-strain on aging precipitation kinetics and its effect on mechanical properties are still not clear. In this work, uniaxial isothermal tensile tests with different strains and artificial aging treatments for Al-Zn-Mg-Cu alloys have been carried out. Then, a model describing the precipitates kinetic behavior has been developed to investigate the effect of thermal pre-strain on subsequent aging precipitation kinetics and peak aging microhardness based on the microstructure characterization by TEM, SAXS and XRD tests. In addition, the role of dislocations on the aging precipitation kinetics is also explored. The experimental results show that the peak aging microhardness of the Al-Zn-Mg-Cu alloy reveals a tendency to decrease and increase and then the peak aging time firstly decreases and then keeps almost constant with the increase in the strain. The calculations demonstrate that the precipitate average size almost remains unchanged, while the precipitate volume fraction decreases and then increases with the increase in strain, which is consistent with the change in peak aging microhardness. It also indicates that dislocations can promote precipitate nucleation and growth, while the actual effect depends on the dislocation density, which is closely dependent on the pre-deformation condition, especially for the precipitate nucleation. In particular, when the dislocation density after thermal pre-deformation is not enough, it will slightly inhibit precipitate nucleation but promote precipitate growth, which could shorten the peak aging time, with the peak aging strength being guaranteed. [ABSTRACT FROM AUTHOR]

Non-renewable-resource consumption and global greenhouse-gas (GHG) emissions are critical issues that pose a significant threat to sustainable development. Solar energy is a promising source to generate renewable energy and an appealing alternative electricity source for households. The primary goal of this research is to detect the rooftops that have no solar photovoltaic (PV) system deployed on them but that receive moderate to high solar-energy radiation using the Geographic Information System (GIS) and deep-learning techniques. Although various studies have been conducted on this subject, not many addressed these two issues simultaneously at a residential level. Identifying the installed solar PV systems in a large area can be expensive and time-consuming work if performed manually. Therefore, the deep-learning algorithm is an emerging alternative method to detect objects using aerial images. We employed the Single-Shot-Detector (SSD) model with the backbone of residual neural network 34 (ResNet34) to detect the solar PV systems and used GIS software to compute solar isolation and calculate the electricity production estimate (EPE) of each rooftop. Our results show that the SSD model detected 6010 solar panels on 4150 properties with an accuracy of 78% and observed that there were 176 Statistical Area 1s (SA1s) that had no rooftops with solar PV systems installed. Moreover, the total electricity production from the suitable area was estimated at over 929.8 Giga Watt-hours (GWhs) annually. Finally, the relation between solar-PV-system density and EPE was also identified using the bivariant correlation technique. Detecting the existing solar PV systems is useful in a broad range of applications including electricity-generation prediction, power-plant-production management, uncovering patterns between regions, etc. Examination of the spatial distribution of solar-energy potential in a region and performing an overlay analysis with socio-economic factors can help policymakers to understand the explanation behind the pattern and strategize the incentives accordingly. [ABSTRACT FROM AUTHOR]

Over the past several decades, deep neural networks have been extensively applied to medical image segmentation tasks, achieving significant success. However, the effectiveness of traditional deep segmentation networks is substantially limited by the small scale of medical datasets, a limitation directly stemming from current medical data acquisition capabilities. To this end, we introduce AttEUnet, a medical cell segmentation network enhanced by edge attention, based on the Attention U-Net architecture. It incorporates a detection branch enhanced with edge attention and a learnable fusion gate unit to improve segmentation accuracy and convergence speed on small medical datasets. The AttEUnet allows for the integration of various types of prior information into the backbone network according to different tasks, offering notable flexibility and generalization ability. This method was trained and validated on two public datasets, MoNuSeg and PanNuke. The results show that AttEUnet significantly improves segmentation performance on small medical datasets, especially in capturing edge details, with F1 scores of 0.859 and 0.888 and Intersection over Union (IoU) scores of 0.758 and 0.794 on the respective datasets, outperforming both convolutional neural networks (CNNs) and transformer-based baseline networks. Furthermore, the proposed method demonstrated a convergence speed over 10.6 times faster than that of the baseline networks. The edge attention branch proposed in this study can also be added as an independent module to other classic network structures and can integrate more attention priors based on the task at hand, offering considerable scalability. [ABSTRACT FROM AUTHOR]

The aims of the present study were to optimize the operational parameters to maximize the yield of ultrasound-assisted polysaccharide extraction from Volvariella volvacea (straw mushroom) fruiting bodies by using for the first time one-factor-at-a-time and three-level Box-Behnken factorial designs. A maximum polysaccharide yield of 8.28 ± 0.23% was obtained under the optimized conditions of ultrasound power of 175 W, extraction temperature of 57 °C, extraction time of 33 min, and the ratio of liquid to raw material of 25:1, respectively. Compared to the hot-water extraction, the ultrasound-assistance favored the extraction of polysaccharides from V. volvacea for its higher polysaccharide yield and efficiency. Further preliminary polysaccharide structural characterization indicated that ultrasound treatment affected the monosaccharide compositions and ratios, and molecular weight range of polysaccharides extracted from V. volvacea. [ABSTRACT FROM AUTHOR]

A series of α-Fe2O3 nanocrystals (NCs) with fascinating morphologies, such as hollow nanoolives, nanotubes, nanospindles, and nanoplates, were prepared through a simple template-free hydrothermal synthesis process. The results showed that the morphologies could be easily controlled by SO42- and H2PO4-. Physical property analysis showed that the α-Fe2O3 NCs exhibited shape- and size-dependent ferromagnetic and optical behaviors. The absorption band peak of the α-Fe2O3 NCs could be tuned from 320 to 610 nm. Furthermore, when applied as electrode material for supercapacitor, the hollow olive-structure exhibited the highest capacitance (285.9 F•g-1) and an excellent long-term cycling stability (93% after 3000 cycles), indicating that it could serve as a candidate electrode material for a supercapacitor. [ABSTRACT FROM AUTHOR]

Simple Summary: Melanoma is a growing health issue in the 21st century. Due to early metastasis and the development of resistance, it still goes along with a poor prognosis. ADCK protein kinases have been shown to play a role during cancer development and metastasis. Here, we investigated the role of ADCK2 in melanoma. In our study, we showed that higher levels of intratumoral ADCK2 benefit patient survival, while a low expression of ADCK2 was associated with a higher motility and a dedifferentiated state of melanoma cells, which facilitates metastasis. Our results could give new insights into melanoma metastasis, and ADCK2 could qualify as a prognostic marker or a target for melanoma therapy in the future. Background: ADCK2 is a member of the AarF domain-containing kinase family, which consists of five members, and has been shown to play a role in CoQ metabolism. However, ADCKs have also been connected to cancer cell survival, proliferation and motility. In this study, we investigated the role of ADCK2 in melanoma. Methods: The effect of ADCK2 on melanoma cell motility was evaluated by a scratch assay and a transwell invasion assay upon siRNA-mediated knockdown or stable overexpression of ADCK2. Results: We found that high levels of intratumoral ADCK2 and MYL6 are associated with a higher survival rate in melanoma patients. Knocking down ADCK2 resulted in enhanced cell migration of melanoma cells. Moreover, ADCK2-knockdown cells adopted a more dedifferentiated phenotype. A gene expression array revealed that the expression of ADCK2 correlated with the expressions of MYL6 and RAB2A. Knocking down MYL6 in ADCK2-overexpressing cells could abrogate the effect of ADCK2 overexpression and thus confirm the functional connection between ADCK2 and MYL6. Conclusion: ADCK2 affects melanoma cell motility, most probably via MYL6. Our results allow the conclusion that ADCK2 could act as a tumor suppressor in melanoma. [ABSTRACT FROM AUTHOR]

Ligands plays an important role in the extraction procedures for the determination of cadmium in rice samples by using flame atomic absorption spectrometry (FAAS). In the present study, comparative evaluation of 10 commercially available ligands for formation of Cd(II)-ligand complex and determination of cadmium in rice samples by ultrasound-assisted dispersive liquid–liquid microextraction (UADLLME) combined with FAAS was developed. Sodium diethyldithiocarbamate (DDTC) provided a high distribution coefficient as well as a good absorbance signal, therefore DDTC was used as a ligand in UADLLME. A low density and less toxic solvent, 1-heptanol, was used as the extraction solvent and ethanol was used as the disperser solvent. In addition, the experimental conditions of UADLLME were optimized in standard solution first and then applied in rice, such as the type and volume of extractant and dispersant, pH, extraction time, and temperature. Under the optimal experimental conditions, the detection limit (3σ) was 0.69 μg/L for Cd(II). The proposed method was applied for the determination of Cd(II) in three different rice samples (polished rice, brown rice, and glutinous rice), the recovery test was carried out, and the results ranged between 96.7 to 113.6%. The proposed method has the advantages of simplicity, low cost, and accurate and was successfully applied to analyze Cd(II) in rice. [ABSTRACT FROM AUTHOR]

Many countries have set a goal for a carbon neutral future, and the adoption of solar energy as an alternative energy source to fossil fuel is one of the major measures planned. Yet not all locations are equally suitable for solar energy generation. This is due to uneven solar radiation distribution as well as various environmental factors. A number of studies in the literature have used multicriteria decision analysis (MCDA) to determine the most suitable places to build solar power plants. To the best of our knowledge, no study has addressed the subject of optimal solar plant site identification for the Al-Qassim region, although developing renewable energy in Saudi Arabia has been put on the agenda. This paper developed a spatial MCDA framework catering to the characteristics of the Al-Qassim region. The framework adopts several tools used in Geographic Information Systems (GIS), such as Random Forest (RF) raster classification and model builder. The framework aims to ascertain the ideal sites for solar power plants in the Al-Qassim region in terms of the amount of potential photovoltaic electricity production (PVOUT) that could be produced from solar energy. For that, a combination of GIS and Analytical Hierarchy Process (AHP) techniques were employed to determine five sub-criteria weights (Slope, Global Horizontal Irradiance (GHI), proximity to roads, proximity to residential areas, proximity to powerlines) before performing spatial MCDA. The result showed that 'the most suitable' and 'suitable' areas for the establishment of solar plants are in the south and southwest of the region, representing about 17.53% of the study area. The 'unsuitable' areas account for about 10.17% of the total study area, which is mainly concentrated in the northern part. The rest of the region is further classified into 'moderate' and 'restricted' areas, which account for 46.42% and 25.88%, respectively. The most suitable area for potential solar energy, yields approximately 1905 Kwh/Kwp in terms of PVOUT. The proposed framework also has the potential to be applied to other regions nationally and internationally. This work contributes a reproducible GIS workflow for a low-cost but accurate adoption of a solar energy plan to achieve sustainable development goals. [ABSTRACT FROM AUTHOR]

The essential trace element selenium (Se) is needed for the biosynthesis of selenocysteine-containing selenoproteins, including the secreted enzyme glutathione peroxidase 3 (GPX3) and the Se-transporter selenoprotein P (SELENOP). Both are found in blood and thyroid colloid, where they serve protective functions. Serum SELENOP derives mainly from hepatocytes, whereas the kidney contributes most serum GPX3. Studies using transgenic mice indicated that renal GPX3 biosynthesis depends on Se supply by hepatic SELENOP, which is produced in protein variants with varying Se contents. Low Se status is an established risk factor for autoimmune thyroid disease, and thyroid autoimmunity generates novel autoantigens. We hypothesized that natural autoantibodies to SELENOP are prevalent in thyroid patients, impair Se transport, and negatively affect GPX3 biosynthesis. Using a newly established quantitative immunoassay, SELENOP autoantibodies were particularly prevalent in Hashimoto's thyroiditis as compared with healthy control subjects (6.6% versus 0.3%). Serum samples rich in SELENOP autoantibodies displayed relatively high total Se and SELENOP concentrations in comparison with autoantibody-negative samples ([Se]; 85.3 vs. 77.1 µg/L, p = 0.0178, and [SELENOP]; 5.1 vs. 3.5 mg/L, p = 0.001), while GPX3 activity was low and correlated inversely to SELENOP autoantibody concentrations. In renal cells in culture, antibodies to SELENOP inhibited Se uptake. Our results indicate an impairment of SELENOP-dependent Se transport by natural SELENOP autoantibodies, suggesting that the characterization of health risk from Se deficiency may need to include autoimmunity to SELENOP as additional biomarker of Se status. [ABSTRACT FROM AUTHOR]

Perilipin5 (Plin5) is a scaffold protein that plays an important role in lipid droplets (LD) formation, but the regulatory effect of leptin on it is unclear. Our study aimed to explore the underlying mechanisms by which leptin reduces the N6-methyladenosine (m6A) methylation of Plin5 through fat mass and obesity associated genes (FTO) and regulates the lipolysis. To this end, 24 Landrace male piglets (7.73 ± 0.38 kg) were randomly sorted into two groups, either a control group (Control, n = 12) or a 1 mg/kg leptin recombinant protein treatment group (Leptin, n = 12). After 4 weeks of treatment, the results showed that leptin treatment group had lower body weight, body fat percentage and blood lipid levels, but the levels of Plin5 mRNA and protein increased significantly in adipose tissue (p < 0.05). Leptin promotes the up-regulation of FTO expression level in vitro, which in turn leads to the decrease of Plin5 M6A methylation (p < 0.05). In in vitro porcine adipocytes, overexpression of FTO aggravated the decrease of M6A methylation and increased the expression of Plin5 protein, while the interference fragment of FTO reversed the decrease of m6A methylation (p < 0.05). Finally, the overexpression in vitro of Plin5 significantly reduces the size of LD, promotes the metabolism of triglycerides and the operation of the mitochondrial respiratory chain, and increases thermogenesis. This study clarified that leptin can regulate Plin5 M6A methylation by promoting FTO to affect the lipid metabolism and energy consumption, providing a theoretical basis for treating diseases related to obesity. [ABSTRACT FROM AUTHOR]

As a by-product of Interferometric Synthetic Aperture Radar (SAR, InSAR) technique, interferometric coherence is a measure of the decorrelation noise for InSAR observation, where the lower the coherence value, the more serious the decorrelation noise. In the densely vegetated area, the coherence value could be too low to obtain any valuable signals, leading to the degradation of InSAR performance and the possible waste of expensive SAR data. Normalized Difference Vegetation Index (NDVI) value is a measure of the vegetation coverage and can be estimated from the freely available optical satellite images. In this paper, a multi-stage model is established to quantitatively estimate the decorrelation noise for vegetable areas based on Landsat-derived NDVI prior to the acquisition of SAR data. The modeling process is being investigated with the L-band ALOS-1/PALSAR-1 data and the Landsat-5 optical data acquired in the Meitanba area of Hunan Province, China. Furthermore, the reliability of the established model is verified in the Longhui area, which is situated near the Meitanba area. The results demonstrate that the established model can quantitatively estimate InSAR decorrelation associated with the vegetation coverage. [ABSTRACT FROM AUTHOR]

The excessive extraction and recharge of groundwater lead to long-time seasonal land subsidence in Los Angeles, USA, and especially in the Santa Ana basin. The rate of land subsidence in the Santa Ana basin has been rising, which could pose a danger to infrastructure and human lives. However, the most recent research on land surface deformation in the area was conducted using the traditional parameter estimation method, resulting in little understanding of the regional spatiotemporal characteristics. The parametric method consists of a least square linear inversion, using the pre-defined mathematical geometric or geophysical theoretical models to describe groundwater deformation, and it requires precise external environmental variables and accurate geophysical parameters, which are more difficult to implement. In this study, multitemporal InSAR-derived deformation time series are analyzed by using 69 descending C-band Sentinel-1A SAR scenes acquired from 2015 to 2018. A method based on independent component analysis (ICA) is applied to characterize the spatial pattern and temporal evolution of land subsidence in the Santa Ana basin. The results reveal two different spatial and temporal deformation patterns in the basin. First, a widespread seasonal deformation is identified by the first component, related to annual seasonal groundwater level changes, and the overall deformation shows a concentrated spatial pattern. The second component captures a long-term signal with a large-scale spatial pattern. For quantitative assessment, the obtained deformation time series are compared with the GNSS data, validating an accuracy of millimeters. We further calculate the cross-correlation coefficient and the elastic skeletal storage coefficient from the ICA-derived seasonal deformation and groundwater level, which reveals that the deformation responds quickly (i.e., a lag of 8 days) to the change in groundwater and the Santa Ana aquifer retains almost the same elasticity for at least 15 years. Quantifying the spatiotemporal characteristics of the deformation in the Santa Ana basin can provide a reference for the monitoring and managing of groundwater. [ABSTRACT FROM AUTHOR]

Machine-learning technologies have exhibited robust competences in solving many petroleum engineering problems. The accurate predictivity and fast computational speed enable a large volume of time-consuming engineering processes such as history-matching and field development optimization. The Southwest Regional Partnership on Carbon Sequestration (SWP) project desires rigorous history-matching and multi-objective optimization processes, which fits the superiorities of the machine-learning approaches. Although the machine-learning proxy models are trained and validated before imposing to solve practical problems, the error margin would essentially introduce uncertainties to the results. In this paper, a hybrid numerical machine-learning workflow solving various optimization problems is presented. By coupling the expert machine-learning proxies with a global optimizer, the workflow successfully solves the history-matching and CO2 water alternative gas (WAG) design problem with low computational overheads. The history-matching work considers the heterogeneities of multiphase relative characteristics, and the CO2-WAG injection design takes multiple techno-economic objective functions into accounts. This work trained an expert response surface, a support vector machine, and a multi-layer neural network as proxy models to effectively learn the high-dimensional nonlinear data structure. The proposed workflow suggests revisiting the high-fidelity numerical simulator for validation purposes. The experience gained from this work would provide valuable guiding insights to similar CO2 enhanced oil recovery (EOR) projects. [ABSTRACT FROM AUTHOR]

This paper presents an underwater high-precision line laser three-dimensional (3D) scanning (LLS) system with rotary scanning mode, which is composed of a low illumination underwater camera and a green line laser projector. The underwater 3D data acquisition can be realized in the range of field of view of 50° (vertical) × 360° (horizontal). We compensate the refraction of the 3D reconstruction system to reduce the angle error caused by the refraction of light on different media surfaces and reduce the impact of refraction on the image quality. In order to verify the reconstruction effect of the 3D reconstruction system and the effectiveness of the refraction compensation algorithm, we conducted error experiments on a standard sphere. The results show that the system's underwater reconstruction error is less than 0.6 mm within the working distance of 140 mm~2500 mm, which meets the design requirements. It can provide reference for the development of low-cost underwater 3D laser scanning system. [ABSTRACT FROM AUTHOR]

To counteract host antiviral RNA silencing, plant viruses encode numerous viral suppressors of RNA silencing (VSRs). P0 proteins have been identified as VSRs in many poleroviruses. However, their suppressor function has not been fully characterized. Here, we investigated the function of P0 from pea mild chlorosis virus (PMCV) in the suppression of local and systemic RNA silencing via green fluorescent protein (GFP) co-infiltration assays in wild-type and GFP-transgenic Nicotiana benthamiana (line 16c). Amino acid deletion analysis showed that N-terminal residues Asn 2 and Val 3, but not the C-terminus residues from 230–270 aa, were necessary for PMCV P0 (P0PM) VSR activity. P0PM acted as an F-box protein, and triple LPP mutation (62LPxx79P) at the F-box-like motif abolished its VSR activity. In addition, P0PM failed to interact with S-phase kinase-associated protein 1 (SKP1), which was consistent with previous findings of P0 from potato leafroll virus. These data further support the notion that VSR activity of P0 is independent of P0–SKP1 interaction. Furthermore, we examined the effect of P0PM on ARGONAUTE1 (AGO1) protein stability, and co-expression analysis showed that P0PM triggered AGO1 degradation. Taken together, our findings suggest that P0PM promotes degradation of AGO1 to suppress RNA silencing independent of SKP1 interaction. [ABSTRACT FROM AUTHOR]

There is a large number of outliers in the operation data of photovoltaic (PV) array, which is caused by array abnormalities and faults, communication issues, sensor failure, and array shutdown during PV power plant operation. The outlier will reduce the accuracy of PV system performance analysis and modeling, and make it difficult for fault diagnosis of PV power plant. The conventional data cleaning method is affected by the outlier data distribution. In order to solve the above problems, this paper presents a method for identifying PV array outliers based on sliding standard deviation mutation. Considering the PV array output characteristics under actual environmental conditions, the distribution of array outliers is analyzed. Then, an outlier identification method is established based on sliding standard deviation calculation. This method can identify outliers by analyzing the degree of dispersion of the operational data. The verification part is illustrated by case study and algorithm comparison. In the case study, multiple sets of actual operating data of different inverters are cleaned, which is selected from a large grid-connected power station. The cleaning results illustrate the availability of the algorithm. Then, the comparison against the quantile-algorithm-based outlier identification method explains the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This article provides a comprehensive review of the state-of-art in the area of artificial intelligence applications to solve reservoir engineering problems. Research works including proxy model development, artificial-intelligence-assisted history-matching, project design, and optimization, etc. are presented to demonstrate the robustness of the intelligence systems. The successes of the developments prove the advantages of the AI approaches in terms of high computational efficacy and strong learning capabilities. Thus, the implementation of intelligence models enables reservoir engineers to accomplish many challenging and time-intensive works more effectively. However, it is not yet astute to completely replace the conventional reservoir engineering models with intelligent systems, since the defects of the technology cannot be ignored. The trend of research and industrial practices of reservoir engineering area would be establishing a hand-shaking protocol between the conventional modeling and the intelligent systems. Taking advantages of both methods, more robust solutions could be obtained with significantly less computational overheads. [ABSTRACT FROM AUTHOR]

Glioblastoma is a highly lethal adult brain tumor with no effective treatments. In this review, we discuss the potential to target cholesterol metabolism as a new strategy for treating glioblastomas. Twenty percent of cholesterol in the body is in the brain, yet the brain is unique among organs in that it has no access to dietary cholesterol and must synthesize it de novo. This suggests that therapies targeting cholesterol synthesis in brain tumors might render their effects without compromising cell viability in other organs. We will describe cholesterol synthesis and homeostatic feedback pathways in normal brain and brain tumors, as well as various strategies for targeting these pathways for therapeutic intervention. [ABSTRACT FROM AUTHOR]

Press-hardened steels (PHS) with a 1.5-mm-thick coated Al–Si layer is welded using an IPG YLS6000 continuous fiber laser in the air atmosphere. An SU5000 scanning electron microscope (SEM) and an Oxford EDS X-Max20 energy spectrometer are used to characterize the microstructure, which consists of delta (δ)-ferrite and lath martensite. It is similar to that of the welding performed in the Ar atmosphere, but the content of δ-ferrite is less. The reason is the formation of Al2O3 inclusions in the molten pool, which reacts with oxygen from the air ambient and the Al from the molten Al–Si coating of PHS. The oxygen content is measured with an ONH-3000 analyzer. An HV-1000 microhardness tester and DNS-100 universal material test equipment are performed to test the hardness and tensile strength. Similar hardness and strength of welded joints are achieved welding in the air atmosphere compared to that of the Ar atmosphere. Fracture was initialed in the fusion line of overlapping zone and propagated along the interface of two plates and fusion line due to the Al segregation. [ABSTRACT FROM AUTHOR]

The coastline detection is one of the main applications of the Gaofen-3 satellite in the ocean field. However, the capability of Gaofen-3 SAR image in coastline detection has not yet been validated. In this paper, two Gaofen-3 SAR images, acquired in 2016, were used to extract the coastlines of the regions of Bohai and Taihu in China, respectively. The classical Fuzzy C-means (FCM) method was used in the coastline detection, but had been improved by combining the Wavelet decomposition algorithm to better suppress the inherent speckle noises of SAR image. Coastline detection results obtained from two Sentinel-1 SAR images acquired on the same regions were compared with those of the Gaofen-3 images. By using the manually delineated coastlines as the standards in the qualitative evaluations, improvements of about 12.0%, 8.3%, 23.8%, and 9.4% can be achieved by the improved FCM method with respect to the indicators of mean, RMSE, PGSD, and P90%, respectively; demonstrating that the Gaofen-3 data is superior to the Sentinel-1 data in the detection of coastline. [ABSTRACT FROM AUTHOR]

β-Ga2O3 nanostructures are attractive wide-band-gap semiconductor materials as they exhibit promising photoelectric properties and potential applications. Despite the extensive efforts on β-Ga2O3 nanowires, investigations into β-Ga2O3 nanotubes are rare since the tubular structures are hard to synthesize. In this paper, we report a facile method for fabricating β-Ga2O3 nanotubes using pre-synthesized GaSb nanowires as sacrificial templates. Through a two-step heating-treatment strategy, the GaSb nanowires are partially oxidized to form β-Ga2O3 shells, and then, the residual inner parts are removed subsequently in vacuum conditions, yielding delicate hollow β-Ga2O3 nanotubes. The length, diameter, and thickness of the nanotubes can be customized by using different GaSb nanowires and heating parameters. In situ transmission electron microscopic heating experiments are performed to reveal the transformation dynamics of the β-Ga2O3 nanotubes, while the Kirkendall effect and the sublimation process are found to be critical. Moreover, photoelectric tests are carried out on the obtained β-Ga2O3 nanotubes. A photoresponsivity of ~25.9 A/W and a detectivity of ~5.6 × 1011 Jones have been achieved with a single-β-Ga2O3-nanotube device under an excitation wavelength of 254 nm. [ABSTRACT FROM AUTHOR]

Ground deformation is the direct manifestation of the earth-rock dam's hazard potential. Therefore, it is essential to monitor deformation for dam warning and security evaluation. The Liuduzhai Dam, a clay-core dam of a large reservoir in China, was reinforced with plastic concrete cut-off walls between 13 January 2009 and 29 May 2010, as it was subject to leakage and deformation. However, the deformation development and the mechanism of the dam are still unclear. In this study, the deformation fields before and after the reinforcement of the Liuduzhai Dam were yielded by using the Interferometric Synthetic Aperture Radar (InSAR) technique. Furthermore, a numerical simulation method was employed to obtain the dynamic seepage field of the dam during the InSAR observation period. The results indicated that the average deformation velocity and maximum deformation velocity are −11.7 mm/yr and −22.5 mm/yr, respectively, and the cumulative displacement exceeds 100 mm, which shows typical continuous growth characteristics in a time series. In contrast, the dam deformation tended to be stable after reinforcement, with the average deformation velocity and maximum deformation velocity being −0.4 mm/yr and −1.2 mm/yr, respectively, behaving as cyclical deformation time series. According to the results of InSAR and seepage analysis, it is shown that: (1) dynamic seepage was the main mechanism controlling dam deformation prior to reinforcement; (2) the concentrated load caused by construction and the rapid dissipation of pore water pressure caused by the sudden drop of the infiltration line were the reasons for the acceleration of deformation during and after construction; and (3) the plastic concrete cut-off walls effectively reduced the dynamic seepage field, while the water level fluctuations were the main driving factor of elastic deformation of the dam after reinforcement. This study provides a novel approach to investigating the deformation mechanism of earth-rock dams. Furthermore, it has been confirmed that InSAR can identify the seepage deformation of dams by detecting surface movements. It is recommended that InSAR deformation monitoring should be incorporated into future dam safety programs to provide detailed deformation signals. By analyzing the temporal and spatial characteristics of the deformation signal, we can identify areas where dam performance has degraded. This crucial information aids in conducting a comprehensive dam safety assessment. [ABSTRACT FROM AUTHOR]

Unlike car navigation, where almost all vehicles can traverse every route, one route might not be optimal or even suitable for all pedestrians. Route geometry information, including tortuosity, twists and turns along roads, junctions, and road slopes, among others, matters a great deal for specific types of pedestrians, particularly those with limited mobility, such as wheelchair users and older adults. Offering practical routing services to these users requires that pedestrian navigation systems provide further information on route geometry. Therefore, this article proposes a novel method for extracting and analyzing the geometry properties of the shortest pedestrian paths, with a focus on open geospatial data across four aspects: (a) similarity, (b) route curviness, (c) road turns and intersections, and (d) road gradients. Deriving from the Hausdorff distance, a metric called the "dissimilarity ratio" was developed, allowing us to determine whether pairs of routes show any tendencies to be similar to each other. Using the "sinuosity index", a segment-based technique quantified the route curviness based on the number and degree of the road turns along the route. Moreover, relying upon open elevation data, the road gradients were extracted to identify routes offering smoother motion and better accessibility. Lastly, the road turns and intersections were investigated as pedestrian convenience and safety indicators. A local government area of Greater Sydney in Australia was chosen as the case study. The analysis was implemented on OpenStreetMap (OSM) shortest pedestrian paths against Google Maps as a benchmark for real-world commercial applications. The similarity analysis indicated that over 90% of OSM routes were identical or roughly similar to Google Maps. In addition, while Spearman's rank correlation showed a direct relationship between route curviness and route length, r S (758) = 0.92, p < 0.001, OSM, on average, witnessed more tortuous routes and, consequently, shorter straight roads between turns. However, OSM routes could be more suitable for pedestrians when the frequency of intersections and road slopes are at the center of attention. Finally, the devised metrics in this study, including the dissimilarity ratio and sinuosity index, showed their practicability in translating raw values into meaningful indicators. [ABSTRACT FROM AUTHOR]

Heteroepitaxial growth of high Al-content AlGaN often results in a high density of threading dislocations and surface hexagonal hillocks, which degrade the performance and reliability of AlGaN-based UVC light emitting diodes (LEDs). In this study, the degradation mechanism and impurity/defect behavior of UVC LEDs in relation to the hexagonal hillocks have been studied in detail. It was found that the early degradation of UVC LEDs is primarily caused by electron leakage. The prominent contribution of the hillock edges to the electron leakage is unambiguously evidenced by the transmission electron microscopy measurements, time-of-flight secondary ion mass spectrometry, and conductive atomic force microscopy. Dislocations bunching and segregation of impurities, including C, O, and Si, at the hillock edges are clearly observed, which facilitate the trap-assisted carrier tunneling in the multiple quantum wells and subsequent recombination in the p-AlGaN. This work sheds light on one possible degradation mechanism of AlGaN-based UVC LEDs. [ABSTRACT FROM AUTHOR]

Whole-genome duplication often results in a reduction in the lignin content in autopolyploid plants compared with their diploid counterparts. However, the regulatory mechanism underlying variation in the lignin content in autopolyploid plants remains unclear. Here, we characterize the molecular regulatory mechanism underlying variation in the lignin content after the doubling of homologous chromosomes in Populus hopeiensis. The results showed that the lignin content of autotetraploid stems was significantly lower than that of its isogenic diploid progenitor throughout development. Thirty-six differentially expressed genes involved in lignin biosynthesis were identified and characterized by RNA sequencing analysis. The expression of lignin monomer synthase genes, such as PAL, COMT, HCT, and POD, was significantly down-regulated in tetraploids compared with diploids. Moreover, 32 transcription factors, including MYB61, NAC043, and SCL14, were found to be involved in the regulatory network of lignin biosynthesis through weighted gene co-expression network analysis. We inferred that SCL14, a key repressor encoding the DELLA protein GAI in the gibberellin (GA) signaling pathway, might inhibit the NAC043–MYB61 signaling functions cascade in lignin biosynthesis, which results in a reduction in the lignin content. Our findings reveal a conserved mechanism in which GA regulates lignin synthesis after whole-genome duplication; these results have implications for manipulating lignin production. [ABSTRACT FROM AUTHOR]

Spermidine is a naturally occurring polyamine compound that has many biological functions, such as inducing autophagy and anti-inflammatory and anti-aging effects. Spermidine can affect follicular development and thus protect ovarian function. In this study, ICR mice were fed exogenous spermidine drinking water for three months to explore the regulation of ovarian function by spermidine. The results showed that the number of atretic follicles in the ovaries of spermidine-treated mice was significantly lower than that in the control group. Antioxidant enzyme activities (SOD, CAT, T-AOC) significantly increased, and MDA levels significantly decreased. The expression of autophagy protein (Beclin 1 and microtubule-associated protein 1 light chain 3 LC3 II/I) significantly increased, and the expression of the polyubiquitin-binding protein p62/SQSTM 1 significantly decreased. Moreover, we found 424 differentially expressed proteins (DEPs) were upregulated, and 257 were downregulated using proteomic sequencing. Gene Ontology and KEGG analyses showed that these DEPs were mainly involved in lipid metabolism, oxidative metabolism and hormone production pathways. In conclusion, spermidine protects ovarian function by reducing the number of atresia follicles and regulating the level of autophagy protein, antioxidant enzyme activity, and polyamine metabolism in mice. [ABSTRACT FROM AUTHOR]

Through excellent absorption and transformation, the macrophyte Myriophyllum (M.) aquaticum can considerably remove phosphorus from wastewater. The results of changes in growth rate, chlorophyll content, and roots number and length showed that M. aquaticum could cope better with high phosphorus stress compared with low phosphorus stress. Transcriptome and differentially expressed genes (DEGs) analyses revealed that, when exposed to phosphorus stresses at various concentrations, the roots were more active than the leaves, with more DEGs regulated. M. aquaticum also showed different gene expression and pathway regulatory patterns when exposed to low phosphorus and high phosphorus stresses. M. aquaticum's capacity to cope with phosphorus stress was maybe due to its improved ability to regulate metabolic pathways such as photosynthesis, oxidative stress reduction, phosphorus metabolism, signal transduction, secondary metabolites biosynthesis, and energy metabolism. In general, M. aquaticum has a complex and interconnected regulatory network that deals efficiently with phosphorus stress to varying degrees. This is the first time that the mechanisms of M. aquaticum in sustaining phosphorus stress have been fully examined at the transcriptome level using high-throughput sequencing analysis, which may indicate the direction of follow-up research and have some guiding value for its future applications. [ABSTRACT FROM AUTHOR]

Simple Summary: Termites are eusocial insects that live in large colonies made up of queens, kings, workers, and soldiers. Queens and kings start new colonies and continually reproduce. Workers are responsible for many crucial roles, including colony husbandry, foraging, and nest construction. Soldiers are adapted for colony defense, usually with large heads and mandibles to ward off predators, but their defensive adaptations prevent them from caring for themselves or performing tasks within the nest. The soldiers of some termite species participate in foraging, either directly by scouting food sources and recruiting workers, or indirectly by influencing worker foraging behavior through their presence. Colonies of the Formosan subterranean termite maintain relatively large soldier proportions compared to termites in their invasive range, but the potential soldier influence on foraging workers has not yet been studied. Since the soldiers of other termite species can influence food exploration, we hypothesized that soldier presence also influences foraging behavior in this species. We compared the exploratory behavior of foraging groups of 100 workers and either 0, 2, 10, or 30 soldiers to determine whether soldier concentration influenced tunnel complexity, tunnel speed, food location, or food collection. In the context of this study, soldier presence did not influence worker foraging behavior, which suggests that workers of the Formosan subterranean termite can maintain foraging efficiency regardless of fluctuations in soldier presence. Termites are eusocial insects that live in organized colonies consisting of reproductives, workers, and soldiers. Soldiers are specialized for defense but are expensive to maintain, as they are incapable of husbandry and must be fed and groomed by workers. The soldiers of several species influence foraging behavior by acting as scouts that initiate foraging or by mediating worker behavioral plasticity during food exploration. These behaviors imply that soldiers may play a keystone role in termite colony function, apart from defense. Subterranean termite workers tunnel through soil in search of food while accompanied by varying proportions of soldiers, depending on the species and colony conditions. Previous studies have shown that soldiers accelerate worker exploratory tunneling behavior in two Reticulitermes species, the colonies of which contain fewer than 2% soldiers. This effect, however, is unknown in other subterranean species with different soldier proportions. In this study, we examined the influence of soldiers on exploratory foraging behavior in the Formosan subterranean termite, Coptotermes formosanus Shiraki, which is an economically devastating invasive species that maintains a relatively high soldier proportion (about 10%). When 100 foraging workers were grouped with 0, 2, 10, or 30 soldiers in two-dimensional foraging arenas, we found no significant effect of soldiers on the tunnel length, branch pattern, food source interception, or food collected within 96 h. These results suggest that C. formosanus colonies maintain food exploration efficiency regardless of soldier proportion variation. [ABSTRACT FROM AUTHOR]

Simple Summary: Neospora caninum is an apicomplexan parasite with worldwide distribution, infecting cattle, goats and other kinds of warm-blooded animals. However, specific medicines for the prevention or treatment of Neospora caninum are still limited. This study is aimed at selecting a potential immunoprotective antigen of N. caninum and evaluating the adjuvant function of interleukin (IL)-18 in mice or goats; NcSRS2, NcSRS17 and NcSRS52 from the SRS superfamily were considered to be targets. The results reveal that the recombinant proteins NcSRS2, NcSRS17 and NcSRS52 can all induce humoral and cellular immune responses, and NcSRS17 showed itself to be a promising new antigen candidate. IL-18 had a certain immunoenhancing effect in both experimental animal mice and intermediate host goats and could be used as an adjuvant. Neosporosis is caused by Neospora caninum (N. caninum), which mainly infects cattle and goats and severely threatens the animal industry. In this study, the inhibitory effects of polyclonal antiserum anti-NcSRS17, NcSRS2 and NcSRS52 were explored. Cytokines in mice or goat serum were detected after immunization. After infection, the survival of mice was recorded. The pathological changes and parasite loads were observed and detected in tissues. The results showed that anti-NcSRS2, NcSRS17 and NcSRS52 antibodies all inhibit the invasion and proliferation of N. caninum. The IFN-γ level in the NcSRS17 group was higher than that in the NcSRS2 and NcSRS52 groups, and higher in the NcSRS2-mIL-18 group than in the NcSRS2 group. The survival rates of mice were 16% in the positive control group, 67% in the SRS52 group, 83% in the SRS2 and mIL-18 groups and 100% in the SRS17 and SRS2-mIL-18 groups. Goats immunized with NcSRS17-gIL-18 developed high levels of IL-4, IL-12 and IFN-γ compared with those immunized with NcSRS-17. Parasite loads in the brains of animals in the NcSRS17 and NcSRS17-gIL-18 groups were significantly reduced, and were significantly lower in the NcSRS17-gIL-18 group (p ≤ 0.01). This study indicates that SRS17 may be an antigen candidate for vaccine development against neosporosis, and IL-18 can enhance the immune protective efficiency of antigen candidates. [ABSTRACT FROM AUTHOR]

Pork accounts for an important proportion of livestock products. For pig farming, a lot of manpower, material resources and time are required to monitor pig health and welfare. As the number of pigs in farming increases, the continued use of traditional monitoring methods may cause stress and harm to pigs and farmers and affect pig health and welfare as well as farming economic output. In addition, the application of artificial intelligence has become a core part of smart pig farming. The precision pig farming system uses sensors such as cameras and radio frequency identification to monitor biometric information such as pig sound and pig behavior in real-time and convert them into key indicators of pig health and welfare. By analyzing the key indicators, problems in pig health and welfare can be detected early, and timely intervention and treatment can be provided, which helps to improve the production and economic efficiency of pig farming. This paper studies more than 150 papers on precision pig farming and summarizes and evaluates the application of artificial intelligence technologies to pig detection, tracking, behavior recognition and sound recognition. Finally, we summarize and discuss the opportunities and challenges of precision pig farming. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is critical in monitoring the time-lagged impacts of agrometeorological drought. In Australia and several south-west Pacific Small Island Developing States (SIDS), there are a limited number of in situ SM stations that can adequately assess soil-water availability in a near-real-time context. Satellite SM datasets provide a viable alternative for SM monitoring and agrometeorological drought provision in these regions. In this study, we investigated the performance of Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), Soil Moisture Operational Products System (SMOPS), SM from the Advanced Microwave Scanning Radiometer 2 (AMSR-2) and SM from the Advanced Scatterometer (ASCAT) over Australia and south-west Pacific SIDS. Products were first evaluated in Australia, given the presence of several in-situ SM monitoring stations and a state-of-the-art hydrological model—the Australian Water Resources Assessment Landscape modelling system (AWRA-L). We further investigated the accuracy of SM satellite datasets in Australia and the south-west Pacific through Triple Collocation analysis with two other SM reference datasets—ERA5 reanalysis SM data and model data from the Global Land Data Assimilation System (GLDAS) dataset. All datasets have differing observation periods ranging from 1911-now, with a common period of observations between 2015–2021. Results demonstrated that ASCAT and SMOS were consistently superior in their performance. Analysis in the six south-west Pacific SIDS indicated reduced performance for all products, with ASCAT and SMOS still performing better than others for most SIDS with median R values ranging between 0.3–0.9. We conducted a case study of the 2015 El Niño and Positive Indian Ocean Dipole-induced drought in Papua New Guinea. It was shown that ASCAT is a valuable dataset indicative of agrometeorological drought for the nation, highlighting the value of using satellite SM products to provide early warning of drought in data-sparse regions in the south-west Pacific. [ABSTRACT FROM AUTHOR]

Due to their high strength, high toughness, and corrosion resistance, high-strength aluminum alloys have attracted great scientific and technological attention in the fields of aerospace, navigation, high-speed railways, and automobiles. However, the fracture toughness and impact toughness of high-strength aluminum alloys decrease when their strength increases. In order to solve the above contradiction, there are currently three main control strategies: adjusting the alloying elements, developing new heat treatment processes, and using different deformation methods. This paper first analyzes the existing problems in the preparation of high-strength aluminum alloys, summarizes the strengthening and toughening mechanisms in high-strength aluminum alloys, and analyzes the feasibility of matching high-strength aluminum alloys in strength and toughness. Then, this paper summarizes the research progress towards adjusting the technology of high-strength aluminum alloys based on theoretical analysis and experimental verification, including the adjustment of process parameters and the resulting mechanical properties, as well as new ideas for research on high-strength aluminum alloys. Finally, the main unsolved problems, challenges, and future research directions for the strengthening and toughening of high-strength aluminum alloys are systematically emphasized. It is expected that this work could provide feasible new ideas for the development of high-strength and high-toughness aluminum alloys with high reliability and long service life. [ABSTRACT FROM AUTHOR]

The 8 January 2022 Mw6.7 Menyuan earthquake was generated in the transition zone between the western Lenglongling fault and the eastern Tuolaishan fault, both being part of the Qilian–Haiyuan fault system with an important role in the adjustment of the regional tectonic regime. In this study, four pairs of SAR (synthetic aperture radar) data from Sentinel-1 and ALOS-2 (Advanced Land Observation Satellite-2) satellites were used to derive the surface displacement observations along the satellite line-of-sight (LOS) and azimuth directions using the differential interferometric SAR (InSAR, DInSAR), pixel offset-tracking (POT), multiple aperture InSAR (MAI), and burst overlap InSAR (BOI) methods. An SM-VCE method (i.e., a method for measuring three-dimensional (3D) surface displacements with InSAR based on a strain model and variance component estimation) was employed to combine these derived SAR displacement observations to calculate the 3D co-seismic displacements. Results indicate that the 2022 Menyuan earthquake was dominated by left-lateral slip, and the maximum horizontal and vertical displacements were 1.9 m and 0.6 m, respectively. The relative horizontal surface displacement across the fault was as large as 2–3 m, and the fault-parallel displacement magnitude was larger on the southern side of the fault compared with the northern side. Furthermore, three co-seismic strain invariants were also investigated, revealing that the near-fault area suffered severe deformation, and two obviously expanding and compressed zones were identified. We provide displacements/strains derived in this study in the prevailing geotiff format, which will be useful for the broad community studying this earthquake; in addition, the SM-VCE code used in this study is open to the public so that readers can better understand the method. [ABSTRACT FROM AUTHOR]

Simple Summary: Insects use antennae to perceive the chemical environment, and olfaction (the sense of smell) is essential for a variety of behavioral responses. Termites are social insects that display a division of labor based on an elaborate caste system consisting of reproductive (queen and king) and non-reproductive individuals (workers and soldiers). Whether these castes have different senses of smell is poorly understood. In this study, we characterized the morphology of antennae in alates (winged reproductives), workers, and soldiers in the Formosan subterranean termite, Coptotermes formosanus, and further analyzed the diversity and abundance of the antennal sensilla (sensory receptors) in each caste. We found that both female and male alates had longer antennae and greater numbers of sensilla than workers and soldiers, but all castes possessed the same nine types of antennal sensilla. Each type of sensilla had a specific spatial distribution along the antenna. The quantitative composition of sensilla differed between the reproductive and non-reproductive castes, but few differences were found between female and male alates or between worker and soldier castes. These results suggest that the olfactory morphology is associated with the reproductive division of labor in subterranean termites. Antennae are the primary sensory organs in insects, where a variety of sensilla are distributed for the perception of the chemical environment. In eusocial insects, colony function is maintained by a division of labor between reproductive and non-reproductive castes, and chemosensation is essential for regulating their specialized social activities. Several social species in Hymenoptera display caste-specific characteristics in antennal morphology and diversity of sensilla, reflecting their differential tasks. In termites, however, little is known about how the division of labor is associated with chemosensory morphology among castes. Using light and scanning electron microscopy, we performed antennal morphometry and characterized the organization of sensilla in reproductive (female and male alates) and non-reproductive (worker and soldier) castes in the Formosan subterranean termite, Coptotermes formosanus Shiraki. Here, we show that the antennal sensilla in alates are twice as abundant as in workers and soldiers, along with the greater number of antennal segments and antennal length in alates. However, all castes exhibit the same types of antennal sensilla, including basiconicum, campaniformium, capitulum, chaeticum I, chaeticum II, chaeticum III, marginal, trichodeum I, and trichodeum I. The quantitative composition of sensilla diverges between reproductive and non-reproductive castes, but not between female and male alates or between worker and soldier castes. The sensilla display spatial-specific distribution, with basiconicum exclusively and capitulum predominantly found on the ventral side of antennae. In addition, the abundance of chemosensilla increases toward the distal end of antennae in each caste. This research provides morphological signatures of chemosensation and their implications for the division of labor, and suggests future neurophysiological and molecular studies to address the mechanisms of chemical communication in termites. [ABSTRACT FROM AUTHOR]

With the rapid increase in the costs of rural labour and the adjustment of planting structures, the phenomenon of farmland abandonment has appeared in China. It is of great significance to promptly and accurately grasp the information on dynamic temporal and spatial changes in abandoned farmland to ensure national food security and the sustainable use of cultivated land. Luquan District in Hebei, China was selected as the research area based on multispectral images from Sentinel-2A, Landsat-7, and Landsat-8 combined with methods of random forest (RF) classification and vegetation index change detection. Rules for the identification of abandoned farmland were also developed, and remote sensing monitoring of the abandonment status of the cultivated land was also carried out in the study area. We also obtained the spatial distribution of abandoned and reclaimed farmland and analysed the frequency of farmland abandonment. The results show that the overall accuracy of the land-use time-series map ranged from 90.20% to 96.92% for the study period of 2010–2020. The average rate of farmland abandonment in the study area was 10.62%, with the lowest rate (5.83%) in 2020 and the highest (14.09%) in 2012. From 2011 to 2020, the maximum farmland abandonment area was 3906.02 hm2, and the minimum area was 1618.74 hm2. The farmland abandonment area showed a trend of first increasing and then decreasing. From 2012 to 2020, the maximum area of reclaimed farmland was 291.49 hm2, and the highest rate of reclamation was 14.26%. The overall reclamation rate was low. The abandonment frequency of most of the abandoned farmland was 1–3 years, covering an area of 8193.73 hm2, which comprised 79% of the total area of abandoned farmland. The frequency of abandonment was inversely proportional to the area of abandoned farmland. Farmland abandonment mainly occurred in hilly areas. We expect that our results can provide case studies for long time series in farmland abandonment research and can provide a reference for studying the driving factors, risk assessment, and policymaking with respect to abandoned farmland. [ABSTRACT FROM AUTHOR]

Cadmium is a common environmental pollutant that causes bone damage. However, the effects of cadmium on the osteogenic differentiation of bone marrow mesenchymal stem cells (BMMSCs) and its mechanism of action in this process are unclear. Here, we determined the effects of cadmium chloride (CdCl2) on the osteogenic differentiation of BMMSCs and the potential mechanism involved in this process. As determined in the present investigation, CdCl2, in a concentration-dependent manner, affected the viability of BMMSCs and their cytoskeletons. Exposure to 0.1 or 0.2 µM CdCl2 inhibited osteogenic differentiation of BMMSCs, which was reflected in the down-regulation of osteoblast-related genes (ALP, OCN, Runx2, OSX, and OPN); in suppression of the protein expression of alkaline phosphatase (ALP) and runt-related transcription factor 2 (Runx2); and in decreased ALP activity and capacity for mineralization. Moreover, mRNA microarray was performed to determine the roles of these factors in BMMSCs treated with CdCl2 in comparison to control BMMSCs. As determined with the microarrays, the Wingless-type (Wnt), mothers against decapentaplegic and the C. elegans gene Sam (SMAD), and Janus kinase-Signal Transducers and Activators of Transcription (JAK-STAT) signaling pathways were involved in the effects caused by CdCl2. Moreover, during differentiation, the protein levels of Wnt3a, β-catenin, lymphoid enhancer factor 1 (LEF1), and T-cell factor 1 (TCF1) were reduced by CdCl2. The current research shows that CdCl2 suppresses the osteogenesis of BMMSCs via inhibiting the Wnt/β-catenin pathway. The results establish a previously unknown mechanism for bone injury induced by CdCl2. [ABSTRACT FROM AUTHOR]

GaN-on-Si resonant-cavity light-emitting diodes (RCLEDs) have been successfully fabricated through wafer bonding and Si substrate removal. By combining the chemical mechanical polishing technique, we obtained a roughness of about 0.24 nm for a scan area of 5 μm × 5 μm. The double-sided dielectric distributed Bragg reflectors could form a high-quality optical resonant cavity, and the cavity modes exhibited a linewidth of 1 nm at the peak wavelength of around 405 nm, corresponding to a quality factor of 405. High data transmission in free space with an opening in the eye diagram was exhibited at 150 Mbps, which is limited by the detection system. These results showed that GaN-based RCLEDs grown on Si are promising as a low-cost emitter for visible light communications in future. [ABSTRACT FROM AUTHOR]

Simple Summary: Subterranean termites are wood-feeding insects that construct foraging tunnels in soil to search for cellulose-based food sources. The Formosan subterranean termite is an invasive species to the United States and one of the most destructive termites in the world. Management of these termites depends on understanding termite behavior and the use of termiticides that are effective, safe, and cost-efficient. Menadione, also known as vitamin K3, is safely used in animal feeds but toxic to some insects due to disruption of energy production by interference with mitochondrial respiration. In this study, we examined how menadione affected the survival, feeding, and tunneling activity of the Formosan subterranean termite. We found that when menadione was applied to food (paper) or tunneling substrate (sand), this compound caused mortality and reduced feeding activity in termites in a dose-dependent manner. When provided with both treated and untreated sand, termites were deterred from tunneling and feeding on the side treated with menadione. Overall, our findings demonstrated strong toxicity and repellency of menadione against the Formosan subterranean termite, suggesting this compound can be potentially used as a termite control agent. The Formosan subterranean termite, Coptotermes formosanus Shiraki, is a highly destructive pest and a cosmopolitan invasive species. Sustainable termite management methods have been improving with the search for novel insecticides that are effective, safe, and cost efficient. Menadione, also known as vitamin K3, is a synthetic analogue and biosynthetic precursor of vitamin K with low mammalian toxicity. Menadione has shown insecticidal activity in several insects, presumably due to interference with mitochondrial oxidative phosphorylation. However, little is known about its effectiveness against termites. In this study, we evaluated the toxicity and repellency of menadione in C. formosanus. Our results showed that menadione affected the survival and feeding activity of termites both in filter paper and substrate (sand) treatments, and menadione influenced termite tunneling activity in treated sand. In a no-choice assay, ≥90% mortality after seven days and minimal or no food consumption were recorded when sand was treated with menadione at 6 to 600 ppm. In a two-choice assay with a combination of treated and untreated sand, termites were deterred by menadione at 6 to 600 ppm and exhibited low mortality (≤30%) over seven days, while tunneling activity was prevented with 60 to 600 ppm of menadione treatment. Overall, our study demonstrated dose-dependent toxicity and repellency of menadione in C. formosanus. The potential use of menadione as an alternative termite control agent is discussed. [ABSTRACT FROM AUTHOR]