Mechanical Modeling and Analysis of Stability Deterioration of Production Well During Marine Hydrate Depressurization Production

Different from oil and gas production,hydrate reservoirs are shallow and unconsolidated,whose mechanical properties deteriorate with hydrate decomposition.Therefore,the formations will undergo significant subsidence during depressurization,which will destroy the original force state of the production well.However,existing research on the stability of oil and gas production wells assumes the formation to be stable,and lacks consideration of the force exerted on the hydrate production well by formation subsidence caused by hydrate decomposition during production.To fill this gap,this paper proposes an analytical method for the dynamic evolution of the stability of hydrate production well considering the effects of hydrate decomposition.Based on the mechanical model of the production well,the basis for stability analysis has been proposed.A multi-field coupling model of the force state of the production well considering the effect of hydrate decomposition and formation subsidence is established,and a solver is developed.The analytical approach is verified by its good agreement with the results from the numerical method.A case study found that the decomposition of hydrate will increase the pulling-down force and reduce the supporting force,which is the main reason for the stability deterioration.The higher the initial hydrate saturation,the larger the reservoir thickness,and the lower the production pressure,the worse the stability or even instability.This work can provide a theoretical reference for the stability maintaining of the production well.

Single-base editing in IGF2 improves meat production and intramuscular fat deposition in Liang Guang Small Spotted pigs

Background Chinese indigenous pigs are popular with consumers for their juiciness,flavour and meat quality,but they have lower meat production.Insulin-like growth factor 2(IGF2) is a maternally imprinted growth factor that promotes skeletal muscle growth by regulating cell proliferation and differentiation.A single nucleotide polymorphism(SNP) within intron 3 of porcine IGF2 disrupts a binding site for the repressor,zinc finger BED-type containing 6(ZBED6),leading to up-regulation of IGF2 and causing major effects on muscle growth,heart size,and backfat thickness.This favorable mutation is common in Western commercial pig populations,but absent in most Chinese indigenous pig breeds.To improve meat production of Chinese indigenous pigs,we used cytosine base editor 3(CBE3)to introduce IGF2 intron3-C3071T mutation into porcine embryonic fibroblasts(PEFs) isolated from a male Liang Guang Small Spotted pig(LGSS),and single-cell clones harboring the desired mutation were selected for somatic cell nuclear transfer(SCNT) to generate the founder line of IGF2^(T/T) pigs.Results We found the heterozygous progeny IGF2^(C/T) pigs exhibited enhanced expression of IGF2,increased lean meat by 18%-36%,enlarged loin muscle area by 3%-17%,improved intramuscular fat(IMF) content by 18%-39%,marbling score by 0.75-1,meat color score by 0.53-1.25,and reduced backfat thickness by 5%-16%.The enhanced accumulation of intramuscular fat in IGF2^(C/T) pigs was identified to be regulated by the PI3K-AKT/AMPK pathway,which activated SREBP1 to promote adipogenesis.Conclusions We demonstrated the introduction of IGF2-intron3-C3071T in Chinese LGSS can improve both meat production and quality,and first identified the regulation of IMF deposition by IGF2 through SREBP1 via the PI3KAKT/AMPK signaling pathways.Our study provides a further understanding of the biological functions of IGF2and an example for improving porcine economic traits through precise base editing.

Evolving patterns of agricultural production space in China:A network-based approach

The agricultural production space,as where and how much each agricultural product grows,plays a vital role in meeting the increasing and diverse food demands.Previous studies on agricultural production patterns have predominantly centered on individual or specific crop types,using methods such as remote sensing or statistical metrological analysis.In this study,we characterize the agricultural production space(APS)by bipartite network connecting agricultural products and provinces,to reveal the relatedness between diverse agricultural products and the spatiotemporal characteristic of provincial production capabilities in China.The results show that core products are cereal,pork,melon,and pome fruit;meanwhile the milk,grape,and fiber crop show an upward trend in centrality,which is in line with diet structure changes in China over the past decades.The little changes in community components and structures of agricultural products and provinces reveal that agricultural production patterns in China are relatively stable.Additionally,identified provincial communities closely resemble China's agricultural natural zones.Furthermore,the observed growth in production capabilities in North and Northeast China implies their potential focus areas for future agricultural production.Despite the superior production capa-bilities of southern provinces,recent years have witnessed a notable decline,warranting special attentions.The findings provide a comprehensive perspective for understanding the complex relationship of agricultural prod-ucts'relatedness,production capabilities and production patterns,which serve as a reference for the agricultural spatial optimization and agricultural sustainable development.

Optimization of Gas Production from Hydrate-Bearing Sediments with Fluctuation Characteristics

As an important source of low-carbon,clean fossil energy,natural gas hydrate plays an important role in improving the global energy consumption structure.Developing the hydrate industry in the South China Sea is important to achieving‘carbon peak and carbon neutrality’goals as soon as possible.Deep-water areas subjected to the action of long-term stress and tectonic movement have developed complex and volatile terrains,and as such,the morphologies of hydrate-bearing sediments(HBSs)fluctuate correspondingly.The key to numerically simulating HBS morphologies is the establishment of the conceptual model,which represents the objective and real description of the actual geological body.However,current numerical simulation models have characterized HBSs into horizontal strata without considering the fluctuation characteristics.Simply representing the HBS as a horizontal element reduces simulation accuracy.Therefore,the commonly used horizontal HBS model and a model considering the HBS’s fluctuation characteristics with the data of the SH2 site in the Shenhu Sea area were first constructed in this paper.Then,their production behaviors were compared,and the huge impact of the fluctuation characteristics on HBS production was determined.On this basis,the key parameters affecting the depressurization production of the fluctuating HBSs were studied and optimized.The research results show that the fluctuation characteristics have an obvious influence on the hydrate production of HBSs by affecting their temperatures and pressure distributions,as well as the transmission of the pressure drop and methane gas discharge.Furthermore,the results show that the gas productivity of fluctuating HBSs was about 5%less than that of horizontal HBSs.By optimizing the depressurization amplitude,well length,and layout location of vertical wells,the productivity of fluctuating HBSs increased by about 56.6%.

Influence of Production Factors on the Physico-Chemical Characteristics of Fermented Cassava Dough and Sensory Evaluation of Attieke

Attieke is an Ivorian semolina which obtained by fermenting, pressing and steaming cassava dough. Attieke production remains a traditional activity carried out by less literate women. However, perceived differences in measurable factors and attieke qualities require an investigation of their influence on the characteristics of the pressed dough and attieke. The aim of this study is to improve the quality of the dough in relation to that of the attieke produced. The experiment was carried out on 4 production factors, namely the type of boiled or braised ferment, the incorporation rate of the ferment between 8 and 10%, the addition of oil from 0.1 to 1% and the fermentation time from 12 to 15 hours applied to the Improved African Cassava (IAC) variety. A complete experiment design of 16 samples of fermented dough and attieke was employed. These samples underwent physic-chemical analyses for the fermented dough and sensory evaluation for the attieke. It was found that, except for titratable acidity, reducing sugar content and ash content, the physico-chemical characteristics of the dough of IAC variety were significantly influenced by all production factors and their interaction. Fermentation time significantly influences 60% of the physico-chemical characteristics of the fermented dough. The type of ferment, the oil addition and the ferment rate have a significant influence at 40% of these characteristics. At the sensory level, color, acidity and grain binding with an explained variance of 34.60% were essential for the appreciation of the attieke samples. Thus, these production factors could be considered for the improvement of the fermented dough and attieke production process.

Short Communication: Enhancing the Drying Process of Microbial-Based Products with a Dehumidifier

The development of microbial-based products requires certain criteria for them to be successfully commercialized. The product must meet the following desirable criteria: effectiveness, contamination free, stability, cost-effectiveness, and a prolonged shelf life. Controlling the drying process is crucial for ensuring the stability and durability of the product. The traditional approach, which involved mechanical and natural drying, led to decreased productivity and quality. The objective of this research endeavour was to achieve a dry process enhancement while preserving the microbial quality of Trichoderma asperellum (M103). The temperature and relative humidity during the drying period were monitored under two conditions: with and without a dehumidifier. The results demonstrate that the dehumidifier increases drying period efficiency by up to 63%.

Gas-Water Production of a Continental Tight-Sandstone Gas Reservoir under Different Fracturing Conditions

A numerical model of hydraulic fracture propagation is introduced for a representative reservoir(Yuanba continental tight sandstone gas reservoir in Northeast Sichuan).Different parameters are considered,i.e.,the interlayer stress difference,the fracturing discharge rate and the fracturing fluid viscosity.The results show that these factors affect the gas and water production by influencing the fracture size.The interlayer stress difference can effectively control the fracture height.The greater the stress difference,the smaller the dimensionless reconstruction volume of the reservoir,while the flowback rate and gas production are lower.A large displacement fracturing construction increases the fracture-forming efficiency and expands the fracture size.The larger the displacement of fracturing construction,the larger the dimensionless reconstruction volume of the reservoir,and the higher the fracture-forming efficiency of fracturing fluid,the flowback rate,and the gas production.Low viscosity fracturing fluid is suitable for long fractures,while high viscosity fracturing fluid is suitable for wide fractures.With an increase in the fracturing fluid viscosity,the dimensionless reconstruction volume and flowback rate of the reservoir display a non-monotonic behavior,however,their changes are relatively small.

Euler Product Expressions of Absolute Tensor Products of Dirichlet L-Functions

In this paper, we calculate the absolute tensor square of the Dirichlet L-functions and show that it is expressed as an Euler product over pairs of primes. The method is to construct an equation to link primes to a series which has the factors of the absolute tensor product of the Dirichlet L-functions. This study is a generalization of Akatsuka’s theorem on the Riemann zeta function, and gives a proof of Kurokawa’s prediction proposed in 1992.

Alternate cotton-peanut intercropping:a new approach to increasing productivity and minimizing environmental impact

Recent publications have highlighted the development of an alternate cotton-peanut intercropping as a novel strat-egy to enhance agricultural productivity.In this article,we provide an overview of the progress made in the alternate cotton-peanut intercropping,specifically focusing on its yield benefits,environmental impacts,and the underlying mechanisms.In addition,we advocate for future investigations into the selection or development of appropriate crop varieties and agricultural equipment,pest management options,and the mechanisms of root-canopy interactions.This review is intended to provide a valuable reference for understanding and adopting an alternate intercropping system for sustainable cotton production.

Classification and technical target of water electrolysis for hydrogen production

Continuous efforts are underway to reduce carbon emissions worldwide in response to global climate change.Water electrolysis technology,in conjunction with renewable energy,is considered the most feasible hydrogen production technology based on the viable possibility of large-scale hydrogen production and the zero-carbon-emission nature of the process.However,for hydrogen produced via water electrolysis systems to be utilized in various fields in practice,the unit cost of hydrogen production must be reduced to$1/kg H_(2).To achieve this unit cost,technical targets for water electrolysis have been suggested regarding components in the system.In this paper,the types of water electrolysis systems and the limitations of water electrolysis system components are explained.We suggest guideline with recent trend for achieving this technical target and insights for the potential utilization of water electrolysis technology.

The multiple roles of crop structural change in productivity,nutrition and environment in China:A decomposition analysis

China's crop structure has undergone significant changes in the last two decades since 2000,with an increase in the share of cereals,vegetables,and fruit,squeezing out other crops.As a result,land productivity,nutrient supply,and carbon emissions have changed.How to reallocate limited farmland among crops to achieve the multiple goals of agrifood systems becomes an important issue.This study explores the sources of land productivity and nutrition supply growth and carbon emissions reduction,and identifies the multiple roles of crop structural change from 2003 to 2020 based on a decomposition analysis.The results reveal that the growth within crops is still the primary driver in land productivity and nutrition supply and the reduction in carbon emissions.However,structural change also plays various roles at different periods.From 2003 to 2010,crop structural change increased the total calorie supply but lowered land productivity and contributed at least 70%of the total growth of carbon emissions.The crop structure was relatively stable,and their effects were modest from 2010 to 2015.From 2015 to 2020,the crop structural change began to play a greater role and generate synergistic effects in improving land productivity,micronutrient supply,and reducing carbon emissions,contributing to approximately a quarter of the growth of land productivity and 30%of total carbon emissions reduction.These results suggest that strategies for crop structural change should comprehensively consider its multiple impacts,aiming to achieve co-benefits while minimizing trade-offs.

High glucose reduces Nrf2-dependent cRAGE release and enhances inflammasome-dependent IL-1βproduction in monocytes:the modulatory effects of EGCG

Soluble receptor for advanced glycation end products(sRAGE)acts as a decoy sequestering of RAGE ligands,thus preventing the activation of the ligand-RAGE axis linking human diseases.However,the molecular mechanisms underlying sRAGE remain unclear.In this study,THP-1 monocytes were cultured in normal glucose(NG,5.5 mmol/L)and high glucose(HG,15 mmol/L)to investigate the effects of diabetesrelevant glucose concentrations on sRAGE and interleukin-1β(IL-1β)secretion.The modulatory effects of epigallocatechin gallate(EGCG)in response to HG challenge were also evaluated.HG enhanced intracellular reactive oxygen species(ROS)generation and RAGE expression.The secretion of sRAGE,including esRAGE and cRAGE,was reduced under HG conditions,together with the downregulation of a disintegrin and metallopeptidase 10(ADAM10)and nuclear factor erythroid 2-related factor 2(Nrf2)nuclear translocation.Mechanistically,the HG effects were counteracted by siRAGE and exacerbated by siNrf2.Chromatin immunoprecipitation results showed that Nrf2 binding to the ADAM10 promoter and HG interfered with this binding.Our data reinforce the notion that RAGE and Nrf2 might be sRAGE-regulating factors.Under HG conditions,the treatment of EGCG reduced ROS generation and RAGE activation.EGCG-stimulated cRAGE release was likely caused by the upregulation of the Nrf2-ADAM10 pathway.EGCG inhibited HG-mediated NLRP3 inflammasome activation at least partly by stimulating sRAGE,thereby reducing IL-1βrelease.

Better use of experience from other reservoirs for accurate production forecasting by learn-to-learn method

To assess whether a development strategy will be profitable enough,production forecasting is a crucial and difficult step in the process.The development history of other reservoirs in the same class tends to be studied to make predictions accurate.However,the permeability field,well patterns,and development regime must all be similar for two reservoirs to be considered in the same class.This results in very few available experiences from other reservoirs even though there is a lot of historical information on numerous reservoirs because it is difficult to find such similar reservoirs.This paper proposes a learn-to-learn method,which can better utilize a vast amount of historical data from various reservoirs.Intuitively,the proposed method first learns how to learn samples before directly learning rules in samples.Technically,by utilizing gradients from networks with independent parameters and copied structure in each class of reservoirs,the proposed network obtains the optimal shared initial parameters which are regarded as transferable information across different classes.Based on that,the network is able to predict future production indices for the target reservoir by only training with very limited samples collected from reservoirs in the same class.Two cases further demonstrate its superiority in accuracy to other widely-used network methods.

Impacts of information about COVID-19 on pig farmers'production willingness and behavior:Evidence from China

This paper examines the impacts of information about COVID-19 on pig farmers'production willingness by using endorsement experiments and follow-up surveys conducted in 2020 and 2021 in China.Our results show that,first,farmers were less willing to scale up production when they received information about COVID-19.The information in 2020 that the second wave of COVID-19 might occur without a vaccine reduced farmers'willingness to scale up by 13.4%,while the information in 2021 that COVID-19 might continue to spread despite the introduction of vaccine reduced farmers'willingness by 4.4%.Second,farmers whose production was affected by COVID-19 were considerably less willing to scale up,given the access to COVID-19 information.Third,farmers'production willingness can predict their actual production behavior.

Crosstalk between degradation and bioenergetics: how autophagy and endolysosomal processes regulate energy production

Cells undergo metabolic reprogramming to adapt to changes in nutrient availability, cellular activity, and transitions in cell states. The balance between glycolysis and mitochondrial respiration is crucial for energy production, and metabolic reprogramming stipulates a shift in such balance to optimize both bioenergetic efficiency and anabolic requirements. Failure in switching bioenergetic dependence can lead to maladaptation and pathogenesis. While cellular degradation is known to recycle precursor molecules for anabolism, its potential role in regulating energy production remains less explored. The bioenergetic switch between glycolysis and mitochondrial respiration involves transcription factors and organelle homeostasis, which are both regulated by the cellular degradation pathways. A growing body of studies has demonstrated that both stem cells and differentiated cells exhibit bioenergetic switch upon perturbations of autophagic activity or endolysosomal processes. Here, we highlighted the current understanding of the interplay between degradation processes, specifically autophagy and endolysosomes, transcription factors, endolysosomal signaling, and mitochondrial homeostasis in shaping cellular bioenergetics. This review aims to summarize the relationship between degradation processes and bioenergetics, providing a foundation for future research to unveil deeper mechanistic insights into bioenergetic regulation.

Spatial evolution and spatial production of traditional villages from "backward poverty villages" to "ecologically well-off villages": Experiences from the hinterland of national nature reserves in China

With the rapid urbanization process,the space of traditional villages in China is undergoing significant changes.Studying the spatial evolution of traditional villages is significant in promoting rural spatial transformation and realizing rural revitalization and sustainable rural development.Based on the traceability analysis of spatial production theory,this paper constructed an analytical framework for the spatial production evolution of traditional villages,analyzed the spatial evolution process and characteristics of traditional villages by using buffer analysis,spatial syntax,and other research methods,and revealed the characteristics of the spatial production evolution of traditional villages and the driving mechanism.The results show that:(1)The village spatial formation and development follow the village life cycle theory and usually develop from embryonic villages to diversified and integrated villages;(2)The evolution of village spatial production is characterized by the diversity of material space,the sublimation of daily life space,and the integration of social system space and generalization of emotional space;(3)The evolution of village spatial production from backward and poor village to ecologically well-off village is influenced by a combination of factors;(4)The village has formed a spatial structure of"people-land-scape-culture-industry",realized comprehensive reconstruction and spatial reproduction.The study results reflect the spatial evolution characteristics of traditional villages in mountainous areas in a more comprehensive way,which helps to promote the protection and development of traditional villages in mountainous areas and,to a certain extent,provides a reference for the development of rural revitalization.

Smart Farming for Sustainable Rice Production:An Insight into Application,Challenge,and Future Prospect

Rice has a huge impact on socio-economic growth,and ensuring its sustainability and optimal utilization is vital.This review provides an insight into the role of smart farming in enhancing rice productivity.The applications of smart farming in rice production including yield estimation,smart irrigation systems,monitoring disease and growth,and predicting rice quality and classifications are highlighted.The challenges of smart farming in sustainable rice production to enhance the understanding of researchers,policymakers,and stakeholders are discussed.Numerous efforts have been exerted to combat the issues in rice production in order to promote rice sector development.The effective implementation of smart farming in rice production has been facilitated by various technical advancements,particularly the integration of the Internet of Things and artificial intelligence.The future prospects of smart farming in transforming existing rice production practices are also elucidated.Through the utilization of smart farming,the rice industry can attain sustainable and resilient production systems that could mitigate environmental impact and safeguard food security.Thus,the rice industry holds a bright future in transforming current rice production practices into a new outlook in rice smart farming development.

Research on Risk Identification and Industrial Governance of Digital Education Products Based on Data Annotation Technology

The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.

Upcycling plastic wastes into value-added products via electrocatalysis and photoelectrocatalysis

Plastic,renowned for its versatility,durability,and cost-effectiveness,is indispensable in modern society.Nevertheless,the annual production of nearly 400 million tons of plastic,coupled with a recycling rate of only 9%,has led to a monumental environmental crisis.Plastic recycling has emerged as a vital response to this crisis,offering sustainable solutions to mitigate its environmental impact.Among these recycling efforts,plastic upcycling has garnered attention,which elevates discarded plastics into higher-value products.Here,electrocatalytic and photoelectrocatalytic treatments stand at the forefront of advanced plastic upcycling.Electrocatalytic or photoelectrocatalytic treatments involve chemical reactions that facilitate electron transfer through the electrode/electrolyte interface,driven by electrical or solar energy,respectively.These methods enable precise control of chemical reactions,harnessing potential,current density,or light to yield valuable chemical products.This review explores recent progress in plastic upcycling through electrocatalytic and photoelectrocatalytic pathways,offering promising solutions to the plastic waste crisis and advancing sustainability in the plastics industry.

Analyzing topics in social media for improving digital twinning based product development

Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product development.Previous efforts of digital twinning neglect the decisive consumer feedback in product development stages,failing to cover the gap between physical and digital spaces.This work mines real-world consumer feedbacks through social media topics,which is significant to product development.We specifically analyze the prevalent time of a product topic,giving an insight into both consumer attention and the widely-discussed time of a product.The primary body of current studies regards the prevalent time prediction as an accompanying task or assumes the existence of a preset distribution.Therefore,these proposed solutions are either biased in focused objectives and underlying patterns or weak in the capability of generalization towards diverse topics.To this end,this work combines deep learning and survival analysis to predict the prevalent time of topics.We propose a specialized deep survival model which consists of two modules.The first module enriches input covariates by incorporating latent features of the time-varying text,and the second module fully captures the temporal pattern of a rumor by a recurrent network structure.Moreover,a specific loss function different from regular survival models is proposed to achieve a more reasonable prediction.Extensive experiments on real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods.