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Machine learning is a promising method to model production processes and predict product quality. It is challenging to accurately model complex systems due to data scarcity, as mass customisation leads to various high-variety low-volume products. This study conceptualised knowledge accumulation, extraction, and transfer (KAET) to exploit the knowledge embedded in similar entities to address data scarcity. A sequential cross-product KAET (SeqTrans) is proposed to conduct KAET, integrating data preparation and preprocessing, feature selection (FS), feature learning (FL), and transfer learning (TL). The FS and FL modules conduct knowledge extraction and help address various practical challenges such as changing operating conditions and unbalanced datasets. In this paper, sequential TL is introduced to production modelling to conduct knowledge transfer among multiple entities. The first case study of auxetic material performance prediction demonstrates the effectiveness of sequential TL. Compared with conventional TL, sequential TL can achieve the same test mean square errors with 300 fewer training examples when facing data scarcity. In the second case study, balancing anomaly detection models were constructed for two gas turbines in the same series using real-world production data. With SeqTrans, the F1-score of the anomaly detection model of the data-poor engine was improved from 0.769 to 0.909. [ABSTRACT FROM AUTHOR]

Asynchronous online discussion is a learning activity commonly used in online teaching. The way instructors participate in asynchronous online discussions significantly impacts students' learning outcomes. This systematic review aims to determine the effects of instructor participation in asynchronous online discussions on student performance by analysing 25 relevant studies in the past twelve years (2011–22). The findings show that the research was focused on the presence, frequency and type of instructor participation. The effects of instructor participation on student performance were mixed and concentrated in five main aspects: the quantity of student participation, the quality of student participation, student achievements, student emotions and student learning time. Not only the teaching experience of instructors but also course content, learning objectives, class sizes and learner characteristics influenced the effects. Based on the findings, several recommendations were made to help instructors effectively participate in asynchronous online discussions, thereby contributing to improving the quality of online education. Practitioner notesWhat is already known about this topic Asynchronous online discussion is a learning activity commonly used in online teaching.The way instructors participate in asynchronous online discussions significantly impacts students' learning outcomes.What this paper adds Previous research on instructor participation in asynchronous online discussions and student performance primarily focuses on the presence, frequency and type of instructor participation.The impact of instructor participation on student performance is mixed and concentrated in the following main areas: Quantity of student participationQuality of student participationStudent achievementsStudent emotionsStudent learning timeThe effects of instructor participation are influenced not only by the teaching experience of instructors but also by: Course contentLearning objectivesClass sizesLearner characteristicsImplications for practice and/or policy Instructors should participate in asynchronous online discussions based on the class sizes, more in small classes (within 15 students) and less in large classes (more than 30 students). If it is possible, divide the large classes into small discussion groups.Instructors should initiate discussions with heuristic and interesting open‐ended questions, gradually release control and give the central position to students and intervene only when necessary (eg, keep discussions on track, provide correct information, extend discussions, mediate conflicts, etc).Instructors should apply appropriate facilitation strategies (eg, establish detailed discussion rubrics, grade student posts and provide regular individual feedback).Instructors should use more instructional comments and supplement them with sincere rather than perfunctory social comments. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) techniques are maturing and penetrating every aspect of the industry. With more and more design, process, structure, and property data collected, machine learning (ML) models are found to be useful to analyze the patterns in the data. The quality of datasets and the handling methods are important to the performance of these ML models. This work reviews recent publications on the topic, focusing on the data types along with the data handling methods and the implemented ML algorithms. The examples of ML applications in AM are then categorized based on the lifecycle stages, and research focuses. In terms of data management, the existing public database and data management methods are introduced. Finally, the limitations of the current data processing methods are discussed and suggestions on perspectives are given. [ABSTRACT FROM AUTHOR]

Tibet orbivirus (TIBOV), a new candidate of Orbivirus genus, was initially isolated from mosquitoes in Tibet in 2009 and subsequently from both Culicoides and mosquitoes in several provinces of China and Japan. Little is known about the origin, genetic diversity, dissemination and pathogenicity of TIBOV, although its potential threat to animal health has been acknowledged. In this study, two viruses, V290/YNSZ and V298/YNJH, were isolated from the Culicoides and sentinel cattle in Yunnan Province. Their genome sequences, cell tropism in mammalian and insect cell lines along with pathogenicity in suckling mice were determined. Genome phylogenetic analyses confirmed their classification as TIBOV species; however, OC1 proteins of the V290/YNSZ and V298/YNJH shared maximum sequence identities of 31.5% and 33.9% with other recognized TIBOV serotypes (TIBOV‐1 to TIBOV‐4) and formed two monophyletic branches in phylogenetic tree, indicating they represented two novel TIBOV serotypes which were tentatively designated as TIBOV‐5 and TIBOV‐6. The viruses replicated robustly in BHK, Vero and C6/36 cells and triggered overt clinical symptoms in suckling mice after intracerebral inoculation, causing mortality of 100% and 25%. Cross‐sectional epidemiology analysis revealed silent circulation of TIBOV in Yunnan Province with overall prevalence of 16.4% (18/110) in cattle, 10.8% (13/120) in goats and 5.5% (6/110) in swine. The prevalence patterns of four investigated TIBOV serotypes (TIBOV‐1, ‐2, ‐5 and 6) differed from each one another, with their positive rates ranging from 8.2% (9/110) for TIBOV‐2 in cattle to 0.9% (1/110) for TIBOV‐1 and TIBOV‐5 in cattle and swine. Our findings provided new insights for diversity, pathogenicity and epidemiology of TIBOV and formed a basis for future studies addressing the geographical distribution and the zoonotic potential of TIBOV. [ABSTRACT FROM AUTHOR]

The Triassic Yanchang Formation in the Pengyang area of Ordos Tianhuan depression is an important oil and gas formation. However, most of the oil pays in the study formations are low-resistivity or low-contrast reservoirs with low permeability, bringing challenges to the reservoir identification and evaluation by well logs. In this paper, we first measured the nuclear magnetic resonance (NMR), phase permeability, cation exchange capacity (CEC), and X-ray diffraction for core samples. Then, the genetic types for the low-resistivity pays were analyzed based on the experiment results, water analysis, and well log data collected. It was found that large variations of formation water salinity, high irreducible water saturation, and clay conductivity are the primary genetic types. Further, the random forest (RF) algorithm with sensitive parameter inputs was used to identify the oil, oil and water, and water layers. The anomaly of spontaneous potential (∆SP) that characterizes water salinity, the relative value of gamma ray log (∆GR) that describes the bound water content, resistivity, density, and acoustic logs were taken as sensitive logs according to the genetic analysis. Finally, this identification method was verified by comparison with the traditional crossplot method and oil test results. The identification accuracy of the RF is 90%, far higher than that by the crossplot method. [ABSTRACT FROM AUTHOR]

Defects such as warping, which are introduced during additive manufacturing, severely compromise the quality of parts and could even damage the 3D printer. This paper proposes automated feature extraction and hyperparameter optimization in a closed-loop in-process system to monitor warping in fused filament fabrication (FFF). The feature extraction is based on G-code analysis, and map matching between the build platform and the captured image. This allows the warping detection algorithm to be applied to different camera angles, part locations, and corner geometries. Bayesian optimization is adopted to determine the best hyperparameters for the classification model. This model, based on a convolutional neural network (CNN), is executed in a Raspberry Pi pre-configured with OctoPrint, with plugins coordinating and controlling the camera, 3D printer, and microcomputer. Based on 16 tests carried out, the warping monitoring system was determined to be 99.2% accurate. [ABSTRACT FROM AUTHOR]

Renewable energy units led by wind power participate in diversified control primary frequency modulation, making the frequency response modes and the setting of frequency modulation parameters more complex. This paper proposes a frequency response model of the power system which is highly penetrated by wind power based on the two mainstream control strategies of wind power that participate in primary frequency modulation. The model considers the influence of wind capture devices, maximum power point tracking (MPPT), and other complex control strategies on system frequency response. Based on this model, the calculation formulas of the maximum change rate of dynamic frequency, the lowest point of dynamic frequency, and the maximum steady-state frequency deviation of the system after fault disturbance are derived in the frequency domain. The influences of wind power permeability and two typical frequency response control strategies on system frequency stability are analyzed. On the one hand, it is found that the proposed model can fit the system frequency response better than the traditional system frequency response model. Beyond that, two control strategies are mainly aimed at the different frequency stability requirements. On the other hand, under the condition of meeting the system's stability requirements, the paper calculates the control parameters of frequency response of the doubly-fed induction generator (DFIG). The time-domain simulation model of the improved IEEE three-machine nine-node system and IEEE 39-node system with high permeability of wind power are built. Through the different fault scenarios, the simulation results verify the effectiveness of the proposed model and the accuracy of control strategy parameter calculation. [ABSTRACT FROM AUTHOR]

Sedoreoviridae is a family of viruses belonging to the order Reovirales and comprises six genera, two of which, Orbivirus and Seadornavirus, contain arboviruses that cause disease in humans and livestock. Areas such as Yunnan Province in southwestern China, have high arboviral activity due in part to warm and wet summers, which support high populations of biting flies such as mosquitoes and Culicoides. Three viral isolates previously obtained from Culicoides collected at cattle farms in Shizong County of Yunnan Province, China, between 2019 and 2020 were completely sequenced and identified as Banna virus (BAV) genotype A of Seadornavirus and serotypes 1 and 7 of epizootic hemorrhagic disease virus (EHDV) of Orbivirus. These results suggest that Culicoidestainanus and C. orientalis are potential vectors of BAV and EHDV, respectively, and represent the first association of a BAV with C. tainanus and of an arbovirus with C. orientalis. Analysis using VP9 generally agreed with the current groupings within this genus based on VP12, although the classification for some strains should be corrected. Furthermore, the placement of Kadipiro virus (KDV) and Liao ning virus (LNV) in Seadornavirus may need confirmation as phylogenetic analysis placed these viruses as sister to other species in the genus. [ABSTRACT FROM AUTHOR]

In recent years, the prevalence of pseudorabies virus (PRV) has caused huge economic losses to the Chinese pig industry. Meanwhile, PRV infection in humans also sounded the alarm about its cross-species transmission from pigs to humans. To study the regional PRV epidemic, serological and epidemiological investigations of PRV in pig populations from Yunnan Province during 2017–2021 were performed. The results showed that 31.37% (6324/20,158, 95% CI 30.73–32.01) of serum samples were positive for PRV glycoprotein E (gE)-specific antibodies via enzyme-linked immunosorbent assay (ELISA). The risk factors, including the breeding scale and development stage, were significantly associated with PRV seroprevalence among pigs in Yunnan Province. Of the 416 tissue samples collected from PRV-suspected pigs in Yunnan Province, 43 (10.33%, 95% CI 7.41–13.26) samples were positive for PRV-gE nucleic acid in which 15 novel PRV strains from these PRV-positive samples were isolated, whose gC and gE sequences were analyzed. Phylogenetic analysis showed that all 15 isolates obtained in this study belonged to the genotype II. Additionally, the gC gene of one isolate (YuN-YL-2017) was genetically closer to variant PRV strains compared with others, while the gE gene was in the same clade with other classical PRV strains, indicating that this isolate might be a recombinant strain generated from the classical and variant strains. The results revealed the severe PRV epidemic in Yunnan Province and indicated that PRV variants are the major genotypes threatening the pig industry development. [ABSTRACT FROM AUTHOR]

The tumor microenvironment is a complex ecosystem formed by distinct and interacting cell populations, and its composition is related to cancer prognosis and response to clinical treatment. In this study, we have taken the advantage of two single‐cell RNA sequencing technologies (Smart‐seq2 and DNBelab C4) to generate an atlas of 15,115 immune and nonimmune cells from primary tumors and hepatic metastases of 18 colorectal cancer (CRC) patients. We observed extensive changes in the proportions and functional states of T cells and B cells in tumor tissues, compared to those of paired non‐tumor tissues. Importantly, we found that B cells from early CRC tumor were identified to be pre‐B like expressing tumor suppressors, whereas B cells from advanced CRC tumors tended to be developed into plasma cells. We also identified the association of IgA+IGLC2+ plasma cells with poor CRC prognosis, and demonstrated a significant interaction between B‐cell and myeloid‐cell signaling, and found CCL8+ cycling B cells/CCR5+ T‐cell interactions as a potential antitumoral mechanism in advanced CRC tumors. Our results provide deeper insights into the immune infiltration within CRC, and a new perspective for the future research in immunotherapies for CRC. [ABSTRACT FROM AUTHOR]

• BTV utilizes NS3 and NS4 to antagonize IFN-Ⅰ signaling in the JAK-STAT pathway. • NS3 and NS4 inhibit phosphorylation of STAT1 in a dose-dependent manner. • NS3 and NS4 target the SH2 domain of STAT1. Previous studies have pointed out that bluetongue virus (BTV) down-regulates the expression levels of type Ⅰ interferon (IFN-Ⅰ) and inhibits IFN-Ⅰ signaling by targeting on the Janus tyrosine kinase (JAK)-signal transducer and activator of transcription protein (STAT) pathway. However, individual viral protein could not effectively block IFN-Ⅰ signaling. There is a need to explore the underlying mechanisms by which viral proteins of BTV coordinate to antagonize the IFN-Ⅰ signaling. We investigated the coordinative role of BTV-1 nonstructural protein 3 (NS3) and NS4 in counteracting IFN-Ⅰ signaling in the JAK-STAT pathway by directly interacting with STAT1. The NS3 and NS4 targeted the SH2 domain of STAT1 to inhibit its phosphorylation, heterodimerization, nuclear translocation, as well as activation of downstream genes of the JAK-STAT pathway. NS3 and NS4 impaired STAT1 phosphorylation induced by IFN-Ⅰ in a dose dependent manner. Overall, this study confirmed that NS3 and NS4 of BTV participate in interfering with IFN-Ⅰ signaling process. Also, a new mechanism employed by BTV to evade host innate immune responses was revealed. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) has high relapse and low 5-year survival rates. Single-cell profiling in relapsed HCC may aid in the design of effective anticancer therapies, including immunotherapies. We profiled the transcriptomes of ∼17,000 cells from 18 primary or early-relapse HCC cases. Early-relapse tumors have reduced levels of regulatory T cells, increased dendritic cells (DCs), and increased infiltrated CD8+ T cells, compared with primary tumors, in two independent cohorts. Remarkably, CD8+ T cells in recurrent tumors overexpressed KLRB1 (CD161) and displayed an innate-like low cytotoxic state, with low clonal expansion, unlike the classical exhausted state observed in primary HCC. The enrichment of these cells was associated with a worse prognosis. Differential gene expression and interaction analyses revealed potential immune evasion mechanisms in recurrent tumor cells that dampen DC antigen presentation and recruit innate-like CD8+ T cells. Our comprehensive picture of the HCC ecosystem provides deeper insights into immune evasion mechanisms associated with tumor relapse. • ScRNA-seq reveals a distinct immune ecosystem in early-relapse HCC • Decreased Tregs, increased DCs, and CD8+ T cells were observed in early-relapse HCC • CD8+ T cells have an innate-like, low cytotoxic, and low clonal expansion phenotype • Recurrent malignant cells mediate the compromised antitumor immune response Single-cell analysis of primary and relapsed hepatocellular carcinoma tumors from patients reveal innate-like CD8+ T cells with low cytotoxicity and clonal expansion in the latter that may explain the compromised antitumor immunity and poor prognosis associated with liver cancer. [ABSTRACT FROM AUTHOR]