The 2030 Geophysics Collections Project was a collaborative effort between the National Computational Infrastructure (NCI), AuScope, Terrestrial Ecosystem Research Network (TERN) and the Australian Research Data Commons (ARDC) that aimed to create a nationally transparent, online geophysics data environment suitable for programmatic access on High Performance Computing (HPC) at the NCI. Key focus areas of this project included the publication of internationally standardised geophysical data on NCI’s Gadi Tier 1 research supercomputer, as well as the development of geophysics and AI-ML related specialised software environments that allow for efficient multi-physics processing, modeling and analysis at scale on HPC systems.Raw and high-resolution versions of AuScope funded Magnetotelluric (MT), Passive Seismic (PS) and Distributed Acoustic Sensing (DAS) datasets are now accessible on HPC along with selected higher-level data products. These datasets have been structured to enable horizontal integration, allowing disparate datasets to be accessed in real-time as online web services from other repositories. Additionally, vertical integration has been established for MT data, linking the source field acquired datasets with derivative processed data products at the NCI repository, as well as linking to other derivative data products hosted by external data portals.To support next-generation geophysical research at scale, these valuable datasets and accompanying metadata need to be captured in machine-readable formats and leverage international standards, vocabularies and identifiers. For MT, automations were developed that generate different MT processing levels at scale in internationally compliant high-performant data and metadata standards. By parallelising these automated processes across HPC clusters, one can rapidly generate different processing levels for entire geophysical surveys in a matter of minutes. In parallel with these data enhancements, the NCI-geophysics software environment was developed, which compiled and containerised a wide range of geophysical and data science related packages in Python, Julia and R. In addition, the NCI-AI-ML environment bundled together popular machine learning and data science packages and configured them for HPC GPU architectures. Standalone open source geophysical applications that support parallel computation have also been added to NCI’s Gadi supercomputer. The 2030 Geophysics Collections Project has made the first strides towards enabling a new era in Australian geophysical research, opening up the potential for rapid multi-physics geophysical analysis at scale with the computational tools available within the NCI. By establishing and continuing to build on this geophysical infrastructure, the nation will be better equipped to address the various geophysical challenges and opportunities in the decades ahead.

Background:Diabetic foot ulcer (DFU) is one of the most common and complex complications of diabetes, but the underlying pathophysiology remains unclear. Single-cell RNA sequencing (scRNA-seq) has been conducted to explore novel cell types or molecular profiles of DFU from various perspectives. This study aimed to comprehensively analyze the potential mechanisms underlying impaired re-epithelization of DFU in a single-cell perspective. Methods:We conducted scRNA-seq on tissues from human normal skin, acute wound, and DFU to investigate the potential mechanisms underlying impaired epidermal differentiation and the pathological microenvironment. Pseudo-time and lineage inference analyses revealed the distinct states and transition trajectories of epidermal cells under different conditions. Transcription factor analysis revealed the potential regulatory mechanism of key subtypes of keratinocytes. Cell-cell interaction analysis revealed the regulatory network between the proinflammatory microenvironment and epidermal cells. Laser-capture microscopy coupled with RNA sequencing (LCM-seq) and multiplex immunohistochemistry were used to validate the expression and location of key subtypes of keratinocytes. Results:Our research provided a comprehensive map of the phenotypic and dynamic changes that occur during epidermal differentiation, alongside the corresponding regulatory networks in DFU. Importantly, we identified two subtypes of keratinocytes: basal cells (BC-2) and diabetes-associated keratinocytes (DAK) that might play crucial roles in the impairment of epidermal homeostasis. BC-2 and DAK showed a marked increase in DFU, with an inactive state and insufficient motivation for epidermal differentiation. BC-2 was involved in the cellular response and apoptosis processes, with high expression of TXNIP, IFITM1, and IL1R2. Additionally, the pro-differentiation transcription factors were downregulated in BC-2 in DFU, indicating that the differentiation process might be inhibited in BC-2 in DFU. DAK was associated with cellular glucose homeostasis. Furthermore, increased CCL2 + CXCL2+ fibroblasts, VWA1+ vascular endothelial cells, and GZMA+CD8+ T cells were detected in DFU. These changes in the wound microenvironment could regulate the fate of epidermal cells through the TNFSF12-TNFRSF12A, IFNG-IFNGR1/2, and IL-1B-IL1R2 pathways, which might result in persistent inflammation and impaired epidermal differentiation in DFU. Conclusions:Our findings offer novel insights into the pathophysiology of DFU and present potential therapeutic targets that could improve wound care and treatment outcomes for DFU patients.

The 2030 Geophysics Collections Project was a collaborative effort between the National Computational Infrastructure (NCI), AuScope, Terrestrial Ecosystem Research Network (TERN) and the Australian Research Data Commons (ARDC) that aimed to create a nationally transparent, online geophysics data environment suitable for programmatic access on High Performance Computing (HPC) at the NCI. Key focus areas of this project included the publication of internationally standardised geophysical data on NCI’s Gadi Tier 1 research supercomputer, as well as the development of geophysics and AI-ML related specialised software environments that allow for efficient multi-physics processing, modeling and analysis at scale on HPC systems. Raw and high-resolution versions of AuScope funded Magnetotelluric (MT), Passive Seismic (PS) and Distributed Acoustic Sensing (DAS) datasets are now accessible on HPC along with selected higher-level data products. These datasets have been structured to enable horizontal integration, allowing disparate datasets to be accessed in real-time as online web services from other repositories. Additionally, vertical integration has been established for MT data, linking the source field acquired datasets with derivative processed data products at the NCI repository, as well as linking to other derivative data products hosted by external data portals. To support next-generation geophysical research at scale, these valuable datasets and accompanying metadata need to be captured in machine-readable formats and leverage international standards, vocabularies and identifiers. For MT, automations were developed that generate different MT processing levels at scale in internationally compliant high-performant data and metadata standards. By parallelising these automated processes across HPC clusters, one can rapidly generate different processing levels for entire geophysical surveys in a matter of minutes.  In parallel with these data enhancements, the NCI-geophysics software environment was developed, which compiled and containerised a wide range of geophysical and data science related packages in Python, Julia and R. In addition, the NCI-AI-ML environment bundled together popular machine learning and data science packages and configured them for HPC GPU architectures. Standalone open source geophysical applications that support parallel computation have also been added to NCI’s Gadi supercomputer.  The 2030 Geophysics Collections Project has made the first strides towards enabling a new era in Australian geophysical research, opening up the potential for rapid multi-physics geophysical analysis at scale with the computational tools available within the NCI. By establishing and continuing to build on this geophysical infrastructure, the nation will be better equipped to address the various geophysical challenges and opportunities in the decades ahead.

Based on the era of big data, this paper first introduces the concept, connotation and function of interest balance, and then expounds the relationship between the era of big data and intellectual property rights, pointing out that big data has become an important driving force for social innovation and economic growth in the emerging stage, but it inevitably conflicts with the legal interests of intellectual property protection in the development process, which leads to the opportunities and challenges that intellectual property rights will face as private rights protection, and sums up how to protect intellectual property rights in the era of big data. On the premise of making full use of the data, we can play the role of balancing interests, so as to achieve the social public goal of promoting economic development, scientific and cultural prosperity with intellectual property rights.

At present, China's poverty alleviation efforts are entering the consolidation and expansion of poverty alleviation achievements. It is necessary to focus on "solving relative poverty", establish a long-term poverty alleviation mechanism, and prevent the occurrence of phenomena such as "returning to poverty after poverty alleviation" and "digital poverty alleviation". For impoverished areas, sustainable and stable agricultural product supply chains are the key to their current development. Rural logistics plays an important role in rural revitalization and rural economic development. Although there has been significant development in rural logistics, there are still problems such as untimely supply dispersion, high logistics costs, inconsistent supply chains, insufficient infrastructure, and the need to improve logistics service levels. This article analyzes the current situation of agricultural product logistics development and proposes optimization suggestions for rural logistics development, in order to establish a complete rural logistics system and establish a new logistics poverty alleviation system.

Laryngeal carcinoma (LC) is one of the common human cancer types. MicroRNAs (miRNAs) were reported to be the essential regulators in cancer diagnosis, treatment, and prognosis. It was reported that miR-206 expression was reduced in various neoplastic diseases. However, the role and functional mechanism of miR-206 in LC progression remain unclear. In this research, miR-206 was found to be associated with tumor-node-metastasis (TNM) staging. In addition, the area under the curve (AUC) of miR-206 was 0.902 for diagnosis of LC and 0.854 for differential diagnosis of stage I-II and stage III-IV patients. Low expression of miR-206 was associated with poor prognosis of LC patients. miR-206 expression was an independent factor affecting the prognosis of LC patients, as revealed by the Cox regression analysis. In vitro experiments demonstrated that miR-206 overexpression reduced cell multiplication, invasion, and migration and increased cell apoptosis in LC cells. Moreover, SOX9 was a target of miR206, and miR-206 negatively regulated SOX9 expression. Collectively, miR-206 might be a promising biomarker with diagnostic and prognostic value for LC, and the miR-206/SOX9 axis might be a candidate target for LC therapy.

作为茶叶生产大国,我国的茶叶生产与出口历史悠久,但随着时代的发展,茶农们为了做大做强茶叶产业,由于茶农质量安全意识淡薄,只注重经济效益.在茶叶生产中,只追求短、平、快的病虫害防治方式,普遍存在用药品种多、次数多、施用量大、安全间隔期执行情况差等问题,不仅增加了成本,也影响到了茶叶的质量安全.因此,相关部门更应以茶叶质量安全管理标准为基础,完善茶叶种植过程以提高茶叶质量,以维护茶叶产业的健康、稳定、持续的发展.

农作物种子的监管工作是农业发展的重中之重,种子质量的优异程度是监管工作的核心所在.农业中有关种子的法律则明确表达了种子检验的标准,进一步推动现代农业的进步.在政府部门的大力帮助下,种子质量监管部门开展了更加严格的监管工作,保障种子的质量,但在开展工作期间仍然面临许多困难需要相关工作人员及时纠正.

为了解遵义市的蔬菜质量安全状况,于2018年对遵义市播州区等12个县区市生产的莲花白、白菜60个抽检样品,进行了甲胺磷、乙酰甲胺磷、氧化乐果等48种农药残留检测.结果 表明:在部分样品中定量检出14种农药残留,并进行慢性和急性膳食摄入风险评估,均在可接受范围内,基本不存在膳食摄入风险.

为遵义市加速辣椒品种的更新换代,提高辣椒种植产量,对遵辣9号、遵辣10号、遵辣6号、黔辣5112、黔辣5228、艳椒425、艳椒465、686等8个朝天椒品种进行田间比较试验.结果表明:艳椒465、艳椒425、遵辣10号、686、遵辣9号和遵辣6号生长优势强,中晚熟,生育期187天,果面光滑,熟果大红,抗病抗倒性强,商品性好,亩产量在900公斤以上,其中艳椒465的亩产量最高,为1 283.8公斤.黔辣5228和黔辣5112晚熟,生育期187天,果面光滑,熟果鲜红,坐果集中,亩产量分别为1 057.9公斤和1 142.4公斤,抗病性强,但不抗倒.

Different loading rates of composite photocatalysts Fe3O4/g-C3N4 were prepared by in situ precipitation method and were characterized by IR and XRD spectroscopies. Their photocatalytic performances were evaluated by the degradation of RhB under visible light irradiation. Fe3O4/g-C3N4 composites assisted by H2O2 shows higher photocatalytic performance than that of Fe3O4 or g-C3N4. As the dosage rate of Fe3O4 increases, the degradation rate is slightly increased. The Fe3O4/g-C3N4(0.1:1) composite has the best photocatalytic performance. It is inferred that the introduction of Fe3O4 is beneficial for the separation of photogenerated electrons and holes on the surface of the catalyst.

为考查检测人员的盲样检测能力,按照NY/T 761-2008《蔬菜和水果中有机磷、有机氯、拟除虫菊酯和氨基甲酸酯类农药多残留的测定》方法,通过在辣椒样品中随机添加敌敌畏等7种农药,对检测人员进行盲样考核.结果 表明,检测人员根据添加的不同农药各自准确检出了盲样中的农药组分及其含量,各种农药组分添加回收率均在70％～120％.检测人员的检测能力均符合农产品检测计量认证要求,可承担正常的检测工作.

样品的农药残留检测种类繁多,且农残检测属于痕量检测,常由于处理上的细微差异,直接影响到检测结果的准确性.为了避免造成检测结果的差异,在样品的前处理过程中,必须对样品的制备、提取、浓缩和净化作细致处理,最大限度地减少农药的损失.本文浅谈农残前处理对检测结果的影响因素.

本试验以测土配方施肥项目实施要求为依据,更进一步验证玉米最佳施肥量在土壤应用中的效果,以验证玉米测土配方施肥的效果和经济效益,为玉米作物大面积开展施肥配方提供依据,以形成配方施肥技术在田间大面积应用和示范推广.

Background and objectives: An increasing number of studies have examined the ability of mesothelin to be a marker for the diagnosis of pancreatic cancer (PCa). The exact role of mesothelin needs to be elucidated. The aim of this study is to determine the overall accuracy of mesothelinin PCa through a meta-analysis of published studies. Materials and methods: Publications addressing the accuracy of mesothelin in the diagnosis of PCa were selected from Pubmed, Embase, Cochrane Library, Web of Science, and The Chinese Journals Full-text Database (CNKI). The following indexes of test accuracy were computed for eachstudy: sensitivity, specificity, positive likeli - hood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). The diagnostic threshold identified for each study wasused to plot a summary receiver operating characteristic (SROC) curve. Statistical analysis was performed by Meta-Disc1.4 and STATA 12.0 software. Results: 12 studies met the inclusion criteria. The summary estimates for mesothelin in the diagnosis of PCa were: sensitivity 0.71 (95% CI, 0.67-0.75), specificity 0.88 (95% CI, 0.85-0.91), positive likelihood ratio (PLR) 8.53 (95% CI, 3.42-21.27), negative likelihood ratio (NLR) 0.36 (95% CI, 0.28-0.46)and diagnostic odds ratio 33.93 (95% CI, 10.71-107.5). The SROC curveindicated that the maximum joint sensitivity and specificity (Q-value) was 0.81; the area under the curve was 0.88. Conclusion: Our findings suggest that mesothelin may be a useful diagnostic adjunctive tool for confirming PCa. However, further large scale studies are needed to confirm these findings.