Using Artificial Neural Networks to Produce High-Resolution Soil Property Maps

High-resolution maps of soil property are considered as the most important inputs for decision support and policy-making in agriculture, forestry, flood control, and environmental protection. Commonly, soil properties are mainly obtained from field surveys. Field soil surveys are generally time-consuming and expensive, with a limitation of application throughout a large area. As such, high-resolution soil property maps are only available for small areas, very often, being obtained for research purposes. In the chapter, artificial neural network (ANN) models were introduced to produce high-resolution maps of soil property. It was found that ANNs can be used to predict high-resolution soil texture, soil drainage classes, and soil organic content across landscape with reasonable accuracy and low cost. Expanding applications of the ANNs were also presented

An Updated Genome Assembly Improves Understanding of the Transcriptional Regulation of Coloration in Midas Cichlid

Midas cichlid (Amphilophus citrinellus), a popular aquarium fish, attracts extensive attention from worldwide biologists mainly due to its morphological polymorphism (dark versus gold). Continuous efforts have therefore been paid to address mechanisms of its coloration variants, while it is far away from the detailed illustration of a clear regulatory network. Some limits may come from the absence of a high-quality genome assembly and a relatively accurate gene set. In this study, we sequenced about 149 Gb of nucleotide sequences of Midas cichlid, generating a genome assembly with a total size of 933.5 Mb, which exhibits a good genome continuity with a contig N50 of 10.5 Mb. A total of 25,911 protein-coding genes were annotated and about 90% completeness was achieved, which helps to build a good gene pool for understanding expressional differences of color variation. With the assistance of the final gene set, we identified a total of 277 differential expressional genes (DEGs), of which 97 up- and 180 downregulated were determined in dark-vs-gold comparisons. Two protein-protein interaction (PPI) networks were constructed from these DEGs, and three key functional modules were classified. Hub genes within each module were evaluated, and we found that the third key module contains tyrp1b, oca2, pmela, tyr, and slc24a5, which were previously proven to be associated with melanin formation. Two downregulated DEGs (myl1 and pgam2) in the first key module may be involved in muscle movement and spermatogenesis, implying that certain side effects could result from the morphological polymorphism. The first key module, consisting of proteins encoded by upregulated DEGs that were associated with MAPK signaling, Toll-like receptor signaling, and gonadotropin-releasing hormone pathways, may contribute to a negative upstream regulation or downstream influence on melanin biosynthesis. Taken together, our new genome assembly and gene annotation of Midas cichlid provide a high-quality genetic resource for biological studies on this species, and the newly identified key networks and hub genes in dark-vs-gold comparisons enhance our understanding of the transcriptional regulatory mechanisms underlying coloration changes not only in Midas cichlid but also in other fishes from freshwater to marine ecosystems

ISA-Net: Improved spatial attention network for PET-CT tumor segmentation

Achieving accurate and automated tumor segmentation plays an important role in both clinical practice and radiomics research. Segmentation in medicine is now often performed manually by experts, which is a laborious, expensive and error-prone task. Manual annotation relies heavily on the experience and knowledge of these experts. In addition, there is much intra- and interobserver variation. Therefore, it is of great significance to develop a method that can automatically segment tumor target regions. In this paper, we propose a deep learning segmentation method based on multimodal positron emission tomography-computed tomography (PET-CT), which combines the high sensitivity of PET and the precise anatomical information of CT. We design an improved spatial attention network(ISA-Net) to increase the accuracy of PET or CT in detecting tumors, which uses multi-scale convolution operation to extract feature information and can highlight the tumor region location information and suppress the non-tumor region location information. In addition, our network uses dual-channel inputs in the coding stage and fuses them in the decoding stage, which can take advantage of the differences and complementarities between PET and CT. We validated the proposed ISA-Net method on two clinical datasets, a soft tissue sarcoma(STS) and a head and neck tumor(HECKTOR) dataset, and compared with other attention methods for tumor segmentation. The DSC score of 0.8378 on STS dataset and 0.8076 on HECKTOR dataset show that ISA-Net method achieves better segmentation performance and has better generalization. Conclusions: The method proposed in this paper is based on multi-modal medical image tumor segmentation, which can effectively utilize the difference and complementarity of different modes. The method can also be applied to other multi-modal data or single-modal data by proper adjustment

Evaluation of the green development efficiency of marine fish culture in China

Green development efficiency (GDE) is an important criterion for measuring the level of green development. GDE considers not only economic development efficiency but also environmental costs. In China, marine fish culture, as one of the pillar industries of mariculture, promotes green development and industrial transformation and upgradation. Based on data from the field surveys of marine fish farmers (2017–2019) and the China Fishery Statistical Yearbook (2018–2020), this study establishes an evaluation index system and uses the super-slack-based measure model (Super-SBM) to evaluate the GDE of marine fish culture. The results show that the average GDE of marine fish culture in China was 0.9529, which was in an inefficient state. As for culture species, golden pompano (Trachinotus ovatus) and cobia (Rachycentron canadum) were the two species farmed in an efficient state, with a GDE of 1.2107 and 1.0659, respectively. Regarding culture modes, green modes (offshore cage aquaculture, industrial recirculating aquaculture, and engineering pond aquaculture) were in an efficient state, with a GDE of 1.2310, 1.0827, and 1.0401, respectively. Traditional modes (industrial flow-through aquaculture, ordinary cage aquaculture, and ordinary pond aquaculture) were in an inefficient state, with their GDE being 0.9884, 0.8746, and 0.8248, respectively. Green modes have higher GDE than traditional modes. In contrast, the production and culture areas of green modes were less than those of traditional modes because the profits of the same species in green modes were lower than those in traditional modes. The results of this study present an objective assessment of the GDE of marine fish culture in China and provide valuable insights for analyzing the mechanisms to improve the GDE of marine fish culture

Genome wide identification and functional characterization of two LC-PUFA biosynthesis elongase (elovl8) genes in rabbitfish (Siganus canaliculatus)

Elongases of very long-chain fatty acids (Elovls) catalyze the rate-limiting step of the elongation pathway that results in net 2‑carbon elongation of pre-existing fatty acyl chains. As a set of crucial enzymes involved in the long-chain polyunsaturated fatty acids (LC-PUFA) biosynthesis, Elovls of fish have been investigated extensively in recent years. In the present study, we first identified two novel fish-specific elovl genes (named as elovl8a and elovl8b) from the herbivorous marine teleost rabbitfish (Siganus canaliculatus) by genomic survey and molecular cloning methods. Subsequently, their functional characteristics, tissue distribution patterns and transcriptional changes in response to different nutritional states were investigated. Full-length coding sequences of the elovl8a and elovl8b genes were 804 and 792 bp, encoding 267 and 263 amino acids, respectively. Multiple alignment, genomic synteny and phylogenetic analyses further suggested that elovl8 genes were unique to teleosts. Functional characterization by heterologous expression in yeast showed that Elovl8b could elongate C18 (18:2n-6, 18:3n-3 and 18:4n-3) and C20 (20:4n-6 and 20:5n-3) polyunsaturated fatty acids (PUFA) to longer-chain polyunsaturated fatty acids (LC-PUFA) whereas Elovl8a lacked this ability. In vitro, the expression of elovl8b but not elovl8a in rabbitfish hepatocytes was significantly up-regulated by incubation with 18:2n-6, 18:3n-3, 20:4n-6 and 20:5n-3, respectively. In vivo, compared with fish oil, dietary vegetable oil enriched in C18 PUFA enhanced the expression of elovl8b in rabbitfish brain, liver, intestine and gill. These findings suggest that elovl8b but not elovl8a is a novel active member of the Elovl protein family involved in the LC-PUFA biosynthesis pathway in rabbitfish, and provide novel insight into the mechanisms of LC-PUFA biosynthesis in teleost

Effect of storage time on the silage quality and microbial community of mixed maize and faba bean in the Qinghai-Tibet Plateau

Tibetan Plateau is facing serious shortage of forage in winter and spring season due to its special geographical location. Utilization of forages is useful to alleviate the forage shortage in winter and spring season. Consequently, the current study was aimed to evaluate the influence of storage time on the silage quality and microbial community of the maize (Zea mays L.) and faba bean (Vicia faba L.) mixed silage at Qinghai-Tibet Plateau. Maize and faba bean were ensiled with a fresh weight ratio of 7:3, followed by 30, 60, 90, and 120 days of ensiling. The results showed the pH value of mixed silage was below 4.2 at all fermentation days. The LA (lactic acid) content slightly fluctuated with the extension of fermentation time, with 33.76 g/kg DM at 90 days of ensiling. The AA (acetic acid) and NH3-N/TN (ammonium nitrogen/total nitrogen) contents increased with the extension of fermentation time and no significantly different between 90 and 120 days. The CP (crude protein) and WSC (water soluble carbohydrate) contents of mixed silage decreased significantly (P < 0.05) with ensiling time, but the WSC content remained stable at 90 days. The Proteobacteria was the predominant phyla in fresh maize and faba bean, and Pseudomonas and Sphingomonas were the predominant genera. After ensiling, Lactobacillus was the prevalent genus at all ensiling days. The relative abundance of Lactococcus increased rapidly at 90 days of ensiling until 120 days of fermentation. Overall, the storage time significant influenced the silage fermentation quality, nutrient content, and microbial environment, and it remained stable for 90 days of ensiling at Qinghai-Tibet Plateau. Therefore, the recommended storage time of forage is 90 days in Qinghai-Tibet Plateau and other cool areas

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

The competitiveness of China's seaweed products in the international market from 2002 to 2017

China is the most productive seaweed farming country in the world and her seaweed imports and exports have a significant impact on global seaweed trade commodities and food security. Nevertheless, few studies had delved into the main characteristics and development of China's seaweed farming industry. This paper aims to narrow this research gap by analyzing trade patterns in China's seaweed products and the international competitiveness of seaweed product by using the international market share index (IMS), the trade competitiveness index (TC), and revealed comparative advantage index (RCA) from 2002 to 2017. The results showed that Japan, the Association of Southeast Asian Nations (ASEAN), Chile, Peru, and the Republic of Korea are China's main trade partners, the total trade value of China's seaweed products has grown rapidly, its imports have gradually exceeded exports, the trade deficit continues to expand, and its competitiveness keeps decreasing. The reasons for this trend may include the changing seaweed trade commodity structure, product differentiation, increased government support in competing countries, and trade barriers among the trade partners. We propose actively expanding international trade markets, establishing a strong seaweed product processing industry to develop high value-added seaweed products, optimizing the trade commodity structure, and differentiating of seaweed products to improve the competitiveness of China's seaweed products