Research progress and management strategies of fungal diseases in Camellia oleifera

Camellia oleifera Abel, a woody oil plant, that is endemic to China. Tea oil, also referred to as “oriental olive oil,” is a superior quality plant-based cooking oil. The production of tea oil accounts for 8% of the total edible vegetable oil production in the country. Since 2022, the annual output value of C. oleifera industry has exceeded 100 billion yuan, making it one of the major economic contributors to China’s rural revitalization development strategy. In recent years, demand and production have grown in parallel. However, this has led to an increase in the incidence levels of pest and diseases. Pests and diseases significantly reduce the quality and yield of C. oleifera. C. oleifera diseases are mainly caused by pathogenic fungi. C. oleifera anthracnose, soft rot, leaf spot, coal stain, leaf gall disease, and root rot are the most important fungal diseases affecting the C. oleifera industry. However, the same disease may be caused by different pathogenic fungi. C. oleifera can be found in half of China and is found in several climatic zones. The geographical distribution of woody plant diseases is consistent with the distribution of the tree species and the ecology of the range, which also results in a highly complex distribution of fungal diseases of C. oleifera. The management of fungal diseases in C. oleifera is extremely challenging due to the variety of pathogenic fungal species, multiple routes of transmission, the lack of resistant plants, and the environmental safety of chemical measures. The optimal strategy for addressing fungal diseases in C. oleifera is to develop and apply an integrated disease management plan. This review provides a brief overview of the pathogenic species, pathogenesis, pathogenesis, geographical distribution, current management strategies, and potentially new methods of C. oleifera fungal diseases, to provide direction for the development of comprehensive management measures for C. oleifera fungal diseases in the future

Modelling underground coal gasification: What to start with

Underground coal gasification (UCG) is widely regarded as a clean coal technology that holds enormous potential to decarbonize the world's coal industry. It converts coal underground into combustible syngas through a set of complex physiochemical events. Experimental and numerical efforts over the past century have contributed to the development of UCG around the world; however, tapping the world's deep-situated coal resources with UCG requires substantial contributions from numerous high-quality researchers. To facilitate effective engagement, this paper will provide a background on where to start if one wishes to undertake UCG modelling. First, a brief description of the fundamental phenomena involved in UCG is given. Then, a succinct introduction of the widely used modelling software is rendered, followed by a description of UCG studies to provide insight how to tune the various software packages for modelling UCG and where their strengths lie. This paper shall serve as guidance to new UCG modellers

No Banquet Can Do without Liquor: Alcohol counterfeiting in the People’s Republic of China

The illegal trade in alcohol has been an empirical manifestation of organised crime with a very long history; yet, the nature of the illegal trade in alcohol has received relatively limited academic attention in recent years despite the fact that it has been linked with significant tax evasion as well as serious health problems and even deaths. The current article focuses on a specific type associated with the illegal trade in alcohol, the counterfeiting of alcohol in China. The article pays particular attention to the counterfeiting of baijiu, Chinese liquor in mainland China. The aim of the article is to offer an account of the social organisation of alcohol counterfeiting business in China by illustrating the counterfeiting process, the actors in the business as well as its possible embeddedness in legal practices and industries/trades. The alcohol counterfeiting business is highly reflective to the market demand and consumer needs. Alcohol counterfeiting in China is characterised primarily by independent actors many of whom are subcontracted to provide commodities and services about the counterfeiting process. The business relies on personal networks – family and extended family members, friends and acquaintances. Relationships between actors in the business are very often based on a customer-supplier relationship or a ‘business-to-business market’. The alcohol counterfeiting business in China highlights the symbiotic relationship between illegal and legal businesses

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

A Novel Deep-Learning Method with Channel Attention Mechanism for Underwater Target Recognition

The core of underwater acoustic recognition is to extract the spectral features of targets. The running speed and track of the targets usually result in a Doppler shift, which poses significant challenges for recognizing targets with different Doppler frequencies. This paper proposes deep learning with a channel attention mechanism approach for underwater acoustic recognition. It is based on three crucial designs. Feature structures can obtain high-dimensional underwater acoustic data. The feature extraction model is the most important. First, we develop a ResNet to extract the deep abstraction spectral features of the targets. Then, the channel attention mechanism is introduced in the camResNet to enhance the energy of stable spectral features of residual convolution. This is conducive to subtly represent the inherent characteristics of the targets. Moreover, a feature classification approach based on one-dimensional convolution is applied to recognize targets. We evaluate our approach on challenging data containing four kinds of underwater acoustic targets with different working conditions. Our experiments show that the proposed approach achieves the best recognition accuracy (98.2%) compared with the other approaches. Moreover, the proposed approach is better than the ResNet with a widely used channel attention mechanism for data with different working conditions

Effect of Critical Illness Insurance on Household Catastrophic Health Expenditure: The Latest Evidence from the National Health Service Survey in China

Background: China fully implemented the critical illness insurance (CII) program in 2016 to alleviate the economic burden of diseases and reduce catastrophic health expenditure (CHE). With an aging society, it is necessary to analyze the extent of CHE among Chinese households and explore the effect of CII and other associated factors on CHE. Methods: Data were derived from the Sixth National Health Service Survey (NHSS, 2018) in Jiangsu Province. The incidence and intensity of CHE were calculated with a sample of 3660 households in urban and rural areas in Jiangsu Province, China. Logistic regression and multiple linear regression models were used for estimating the effect of CII and related factors on CHE. Results: The proportion of households with no one insured by CII was 50.08% (1833). At each given threshold, from 20% to 60%, the incidence and intensity were higher in rural households than in urban ones. CII implementation reduced the incidence of CHE but increased the intensity of CHE. Meanwhile, the number of household members insured by CII did not affect CHE incidence but significantly decreased CHE intensity. Socioeconomic factors, such as marital status, education, employment, registered type of household head, household income and size, chronic disease status, and health service utilization, significantly affected household CHE. Conclusions: Policy effort should further focus on appropriate adjustments, such as dynamization of CII lists, medical cost control, increasing the CII coverage rate, and improving the reimbursement level to achieve the ultimate aim of using CII to protect Chinese households against financial risk caused by illness

One-Step piggyBac Transposon-Based CRISPR/Cas9 Activation of Multiple Genes

Neural cell fate is determined by a tightly controlled transcription regulatory network during development. The ability to manipulate the expression of multiple transcription factors simultaneously is required to delineate the complex picture of neural cell development. Because of the limited carrying capacity of the commonly used viral vectors, such as lentiviral or retroviral vectors, it is often challenging to perform perturbation experiments on multiple transcription factors. Here we have developed a piggyBac (PB) transposon-based CRISPR activation (CRISPRa) all-in-one system, which allows for simultaneous and stable endogenous transactivation of multiple transcription factors and long non-coding RNAs. As a proof of principle, we showed that the PB-CRISPRa system could accelerate the differentiation of human induced pluripotent stem cells into neurons and astrocytes by triggering endogenous expression of different sets of transcription factors. The PB-CRISPRa system has the potential to become a convenient and robust tool in neuroscience, which can meet the needs of a variety of in vitro and in vivo gain-of-function applications. Keywords: CRISPR, gene activation, human induced pluripotent stem cells, piggyBac, transposo

Retrieval practice facilitates memory updating by enhancing and differentiating medial prefrontal cortex representations.

Updating old memories with new, more current information is critical for human survival, yet the neural mechanisms for memory updating in general and the effect of retrieval practice in particular are poorly understood. Using a three-day A-B/A-C memory updating paradigm, we found that compared to restudy, retrieval practice could strengthen new A-C memories and reduce old A-B memory intrusion, but did not suppress A-B memories. Neural activation pattern analysis revealed that compared to restudy, retrieval practice led to stronger target representation in the medial prefrontal cortex (MPFC) during the final test. Critically, it was only under the retrieval practice condition that the MPFC showed strong and comparable competitor evidence for both correct and incorrect trials during final test, and that the MPFC target representation during updating was predictive of subsequent memory. These results suggest that retrieval practice is able to facilitate memory updating by strongly engaging MPFC mechanisms in memory integration, differentiation and consolidation