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C. perfringens type D strains are the leading cause of enterotoxaemia in ruminants such as goats, sheep, and cattle. However, there has been no prior research on the genomic characteristics of C. perfringens type D strains from various regions in China. Here, we investigated the antibiotic resistance, genomic characteristics, and phylogenetic relationship of C. perfringens type D isolates recovered from goat farms in Shaanxi, Gansu, and Ningxia provinces. The antibiotic resistance test indicated that the isolates displayed high minimum inhibitory concentration (MIC) values to sulfafurazole, whereas the other antibiotics tested, such as penicillin, enrofloxacin, and florfenicol, worked well on them. Additionally, only tetracycline resistance genes [ tetA (P) and tetB (P)] were identified from the isolates. A collective of 13 toxin genes, including etx and cpe were detected among the isolates. Sequence comparison revealed that the etx and cpe genes shared high sequence identities, and they could coexist on a pCW3-like plasmid, representing a potential risk to both animal breeding and public health. Phylogenetic analysis using core genome multi-locus sequence typing (cgMLST) and core genome single nucleotide polymorphisms (SNPs) revealed the close genetic relationship and potential regional/transregional transmission of the C. perfringens type D isolates in Shaanxi and Gansu provinces. Furthermore, pan-genomic analysis suggested the functional differences at the protein-coding gene level, although isolates from the same source shared a close genetic relationship. In conclusion, this study indicated the antibiotic resistance, virulence markers, potential transregional transmission, and genomic diversity of C. perfringens type D strains from various regions in China, which could provide references for the prevention of C. perfringens foodborne diseases and further research. • This study investigated genomic features of C. perfringens type D. • etx and cpe could co-exist on pCW3-like plasmids. • Genomic analysis indicated the potential transregional transmission of C. perfringens type D. [ABSTRACT FROM AUTHOR]

The reverse distribution of renewable energy resources and load centers makes exploring the optimal transmission mode of long-distance and large-scale renewable hydrogen the key to solving the bottleneck of renewable hydrogen development. This study incorporates hydrogen pipeline (HGP), natural gas pipeline (NGP), and Ultra High Voltage (UHV) into an optimal planning model framework and analyzes the optimal transmission mode, quantity, network, and cost of large-scale renewable hydrogen in China. Constructing a sensitivity analysis framework, this study also investigates the optimal transmission mode changes under different scenarios. The results show that the optimal mode of large-scale renewable hydrogen transmission in the province is NGP, and 5.4% of supply level is the critical point to export renewable hydrogen inter-provincially. It switches to the combination of NGP and HGP when the unit transmission costs of these elements decrease to a certain proportion simultaneously or switches to HGP when the unit transmission cost of HGP decreases more than that of NGP. The complementary transmission mode of NGP and UHV is the optimal mode for inter-provincial transmission, and the HGP can be put into use for inter-provincial transmission only when the unit transmission cost of which is reduced to less than 25%. Jilin is the key node in the NGP network, and Tibet and Gansu are the key nodes in UHV network, and the participation or absence of which will have significant impact on the renewable hydrogen transmission system. Only minor adjustments to the transmission technical parameters of NGP or HGP can promote the qualitative overflight of the optimal transmission volume of them so as to achieve the target optimization at the minimum cost. • Optimal planning model framework for renewable hydrogen transmission is proposed. • The optimal transmission mode, network, and cost of renewable hydrogen are analyzed. • Thresholds and spatial features of the optimal plan vary with hydrogen supply level. • Renewable hydrogen will be transmitted inter-provincially at 5.4% of supply level. • Multiple equilibria for modes selection are observed by cost sensitivity analysis. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the prevalence and antimicrobial resistance of Clostridium perfringens from sheep (intensive husbandry) in Gansu and Tibetan sheep (extensive husbandry) in Qinghai, China. 400 fecal samples (sheep, n = 320, Tibetan sheep, n = 80) were collected from Gansu and Qinghai for C. perfringens isolation. Toxin genes were detected by PCR, antimicrobial susceptibility testing was carried out by broth microdilution method, and whole genome was sequenced using Illumina HiSeq. 83 strains of C. perfringens (sheep, n = 47; Tibetan sheep, n = 36) were isolated from the samples. 44.5% (37/83) of the isolates were positive for cpb2 , while 34.9% (29/83) of the isolates were positive for cna. 95.2% isolates were resistant to sulfonamides, followed by tetracycline (22.9%), ampicillin (14.5%), penicillin (10.8%), doxycycline (4.8%), and amoxicillin (1.2%). The isolates from same source shared similar allelic profile and closer genetic relationship. A total of 14 toxin genes and 11 antimicrobial resistance genes were detected among the sequenced isolates, and 10 sequenced C. perfringens isolates carried multiple (n ≥ 3) antimicrobial-resistance genes. Moreover, oxazolidinone-resistant gene optrA was detected in one isolate from Tibetan sheep, which co-harbored tetA (P), aac(6′)-aph(2″) , ant(6)-Ib , erm (Q), fexA , tet (44), erm (A) and erm (B). C. perfringens from sheep and Tibetan sheep shared different prevalence rates and antimicrobial-resistance, and the isolates from same source shared closer genetic relationship. • C. perfringens was isolated from 14.7% of sheep and 45% of Tibetan sheep. • Detection rate of beta-2 coding gene cpb2 was higher in the isolates from sheep. • 11 antimicrobial-resistance genes were detected in the sequenced isolates. • C. perfringens isolates from same source shared closer genetic relationship. [ABSTRACT FROM AUTHOR]

In recent decades, lithological mapping techniques using hyperspectral remotely sensed imagery have developed rapidly. The processing chains using visible-near infrared (VNIR) and shortwave infrared (SWIR) hyperspectral data are proven to be available in practice. The thermal infrared (TIR) portion of the electromagnetic spectrum has considerable potential for mineral and lithology mapping. In particular, the abovementioned rocks at wavelengths of 8–12 μm were found to be discriminative, which can be seen as a characteristic to apply to lithology classification. Moreover, it was found that most of the lithology mapping and classification for hyperspectral thermal infrared data are still carried out by traditional spectral matching methods, which are not very reliable due to the complex diversity of geological lithology. In recent years, deep learning has made great achievements in hyperspectral imagery classification feature extraction. It usually captures abstract features through a multilayer network, especially convolutional neural networks (CNNs), which have received more attention due to their unique advantages. Hence, in this paper, lithology classification with CNNs was tested on thermal infrared hyperspectral data using a Thermal Airborne Spectrographic Imager (TASI) at three small sites in Liuyuan, Gansu Province, China. Three different CNN algorithms, including one-dimensional CNN (1-D CNN), two-dimensional CNN (2-D CNN) and three-dimensional CNN (3-D CNN), were implemented and compared to the six relevant state-of-the-art methods. At the three sites, the maximum overall accuracy (OA) based on CNNs was 94.70%, 96.47% and 98.56%, representing improvements of 22.58%, 25.93% and 16.88% over the worst OA. Meanwhile, the average accuracy of all classes (AA) and kappa coefficient (kappa) value were consistent with the OA, which confirmed that the focal method effectively improved accuracy and outperformed other methods. [ABSTRACT FROM AUTHOR]