A Hybrid Deep Learning Approach for Green Energy Forecasting in Asian Countries

Electricity is essential for keeping power networks balanced between supply and demand,especially since it costs a lot to store.The article talks about different deep learning methods that are used to guess how much green energy different Asian countries will produce.The main goal is to make reliable and accurate predictions that can help with the planning of new power plants to meet rising demand.There is a new deep learning model called the Green-electrical Production Ensemble(GP-Ensemble).It combines three types of neural networks:convolutional neural networks(CNNs),gated recurrent units(GRUs),and feedforward neural networks(FNNs).The model promises to improve prediction accuracy.The 1965–2023 dataset covers green energy generation statistics from ten Asian countries.Due to the rising energy supply-demand mismatch,the primary goal is to develop the best model for predicting future power production.The GP-Ensemble deep learning model outperforms individual models(GRU,FNN,and CNN)and alternative approaches such as fully convolutional networks(FCN)and other ensemble models in mean squared error(MSE),mean absolute error(MAE)and root mean squared error(RMSE)metrics.This study enhances our ability to predict green electricity production over time,with MSE of 0.0631,MAE of 0.1754,and RMSE of 0.2383.It may influence laws and enhance energy management.

基于Deep Forest算法的对虾急性肝胰腺坏死病(AHPND)预警数学模型构建

为预报池塘养殖凡纳对虾(Penaeus vannamei)急性肝胰腺坏死病(AHPND)的发生,自2020年开始,笔者对凡纳对虾养殖区开展了连续监测工作,包括与疾病发生相关的环境理化因子、微生物因子、虾体自身健康状况等18个候选预警因子指标,通过数据标准化处理后分析病原、宿主与环境之间的相关性,对候选预警因子进行筛选,基于Python语言编程结合Deep Forest、Light GBM、XGBoost算法进行数据建模和预测性能评判,仿真环境为Python2.7,以预警因子指标作为输入样本(即警兆),以对虾是否发病指标作为输出结果(即警情),根据输入样本和输出结果各自建立输入数据矩阵和目标数据矩阵,利用原始数据矩阵对输入样本进行初始化,结合函数方程进行拟合,拟合的源代码能利用已知环境、病原及对虾免疫指标数据对目标警情进行预测。最终建立了基于Deep Forest算法的虾体(肝胰腺内)细菌总数、虾体弧菌(Vibrio)占比、水体细菌总数和盐度的4维向量预警预报模型,准确率达89.00%。本研究将人工智能算法应用到对虾AHPND发生的预测预报,相关研究结果为对虾AHPND疾病预警预报建立了预警数学模型,并为对虾健康养殖和疾病防控提供了技术支撑和有力保障。

Responses of vegetation cover to the Grain for Green Program and their driving forces in the He-Long region of the middle reaches of the Yellow River

The implementation of the Grain for Green Program is a great breakthrough in the history of China＇s ecological environment construction,which can control soil erosion effectively,increase land productivity and improve the ecological environment.To investigate the eco-environmental benefits brought by the Grain for Green Program,the spatiotemporal variations of vegetation cover in the growing season from 2000 to 2010 across the Hekou-Longmen （He-Long） region were analyzed by using remote sensing information,meteorological data and land use data.Moreover,the impacts of climate and human activities on vegetation change were evaluated objectively.Annual vegetation cover in the growing season increased very significantly.Increased vegetation cover occurred in 98.7％ of the region,of which the area for vegetation cover improved slightly constituted 79.8％ of the whole area.Vegetation moderately improved was mainly distributed in the south of the He-Long region,covering 9.6％ of the area,and the area for vegetation basically unchanged concentrated in the middle and upper reaches of the Wuding River.Precipitation was found to be an important natural factor influencing vegetation cover change.The area of vegetation cover showing a significantly positive correlation with precipitation occupied 22.14％ of the region.As driven by policies from the Grain for Green Program,forestland increased significantly and land use structure became more intensive.Human activities played a positive and effective role in the protection,restoration and improvement of vegetation in the places where vegetation cover was basically unchanged,even though precipitation declined greatly,and vegetation improved moderately with massive increases of forestland and grassland.

Changes in Land Use and Agricultural Production Structure Before and After the Implementation of Grain for Green Program in Western China–Taking Two Typical Counties as Examples

Soil erosion becomes a serious environmental problem in the world, especially in western China. An effective management practice called the Grain for Green Program(GGP), which was launched in 1999, aims to reduce soil and water loss and alleviate the ecological environment problem in western China. Two typical counties in western China, the Zhongxian(in Chongqing Municipality) and Ansai(in Shaanxi Province) were chosen to evaluate the dynamic changes of land use and agricultural production structure before and after the implementation of the Program in this paper. The results showed that the cultivated land area was reduced by 7.08% from 1989 to 2003. The cultivated land per person was decreased by 8.42% during 1999-2003. Moreover, the stability index of the secondary sector of the economy was increased from 0.91 in the period 1990-1999 to 0.94 in the following ten years. In addition, the stability index of tertiary economic sector increased from 0.88 to 0.92 in Zhongxian county. Meanwhile, the cultivated land area was reduced by 15.48% from 1990 to 1999. The soil erosion modulus was decreased by 33.33% from 1999 to 2006. Also, the stability index of secondary and tertiary economic sectors was 0.86 in the period 1998-2002. However, it decreased by 77% during 2002 to 2007 in Ansai County. These results imply that the Grain for Green Program had different impact on the two regions. Several effective strategies of soil and water conservation have been carried out to ameliorate the sustainable development of ecological environment and economy in these two counties of western China.

Increasing the greenness of an organic acid through deep eutectic solvation and further polymerisation

Acrylic acid(AA)is an important and widely used industrial chemical,but its high toxicity renders its use incompatible with the concept of green development.By leveraging its terminal carboxyl group and unsaturated bond,we designed and explored a new strategy to increase the greenness of AA via its eutectic melting using a quaternary ammonium salt(choline chloride)to form a deep eutectic solvent(DES),followed by polymerisation of the DES to form a polymer(poly(DES)).The greenness of AA,DES,and poly(DES)was evaluated via an in vitro test using MGC80-3 cells and an in vivo test using Kunming mice.The toxicity improved from Grade 2(moderately toxic)for AA to Grade 1(slightly toxic)for DESs and Grade 0(non-toxic)for poly(DES)in the in vitro test.Moreover,the poly(DES)s showed a lower toxicity in mice than the DESs in the in vivo test.Thus,greenness enhancement was successfully achieved,with the greenness following the order AA<DES<poly(DES).Furthermore,the mechanisms underlying the change in toxicity were explored through microscopy and flow cytometry,which revealed that the DES can permeate the MGC80-3 cell membrane during the G_(0)/G_(1) phase to adversely affect DNA synthesis in the S phase,but the poly(DES)cannot.Finally,the green poly(DES),which showed good adsorption properties and flexible functionality,was successfully applied as a carrier or excipient of drugs.Through the novel strategy reported herein,greenness enhancement and the broadening of the application scope of a toxic organic acid were achieved,making such acids applicable for green development.

Coupling between the Grain for Green Program and a household level-based agricultural eco-economic system in Ansai,Shaanxi Province of China

The implementation of the Grain for Green Program(GGP)has changed the development track of the agricultural eco-economic system in China.In response to the results of a lag study that investigated the coupling between the GGP and the agricultural eco-economic system in a loess hilly region,we used a structural equation model to analyze the survey data from 494 households in Ansai,a district of Yan’an City in Shaanxi Province of China in 2015.The model clarified the direction and intensity of the coupling between the GGP and the agricultural eco-economic system.The coupling benefits were derived through linkages between the program and various chains in the agricultural eco-economic system.The GGP,the agroecosystem of Ansai and their potential coupling effects were in a state of general coordination.The agroecosystem directly affected the coupling effect,with the standardized path coefficient of 0.87,indicating that the agroecosystem in Ansai at this stage provided basic material support for the coupling between the GGP and the agricultural eco-economic system.The direct path coefficient of agroeconomic system impacted on the coupling effect was-0.76,indicating that partial contradictions occurred between the agroeconomic system and the coupling effect.Therefore,although the current agroecosystem in Ansai should be provided sufficient agroecological resources for the benign coupling between the program and the agricultural eco-economic system,agricultural development failed to effectively transform agroecological resources into agricultural economic advantages in this region,which resulted in a relative lag in the development of the agricultural economic system.Thus,the coupling between the GGP and the agricultural eco-economic system was poor.To improve the coupling and the sustainable development of the agricultural eco-economic system in cropland retirement areas,the industrial structure needs to be diversified,the agricultural resources(including agroecological resources,agricultural economic resources and agricultural social resources)need to be rationally allocated,and the chain structure of the agricultural eco-economic system needs to be continuously improved.

Issues and Challenges in Implementing China’sGreen Public Procurement Program

Sustainable development and environmental protection are the themes of the day. One popular policy tool that government uses to promote sustainable development and to protect the environment is green public procurement. Chinese government established its public procurement system in the late 1990s. It has moved to implement green procurement since 2004. In this paper, the authors will first trace the development of Chinese green public procurement program. The authors will then examine the issues involved in its implementation and make suggestions as to how to make green public procurement program more effective. This is one of the first papers examining China’s green public procurement program.

Industrial Poverty Alleviation Model in Deep Poverty-stricken Villages in the Dry-hot Valley of Jinsha River: A Case Study of Poverty Alleviation in the Green Prickleyash Planting Industry in Laopingzi Village,Luquan County

Industrial poverty alleviation is the core of poverty alleviation in rural areas of China,and it is the fundamental way for the rural poor to achieve stable income and poverty alleviation. Laopingzi Village,Jiaopingdu Town,Luquan County,Kunming County,Yunnan Province,located in the dry-hot valley area of Jinsha River,has become a typical deep poverty-stricken village due to its special natural conditions.In recent years,in the battle to win the fight against poverty,the people of Laopingzi Village have achieved a virtuous cycle of the ecological environment and an access to get rid of poverty and get rich through vigorously developing green prickleyash planting industry. By the end of 2018,the incidence of poverty in Laopingzi Village Committee dropped from 45. 62% in 2014 to 1. 11%,and the green prickleyash planting industry had achieved remarkable results in poverty alleviation. This article summarizes the specific practices of developing the green prickleyash planting industry in the village,analyzes the main results and successful experiences of the mode and discusses the inspiration of the implementation of green prickleyash cultivation on industrial poverty alleviation,so as to provide an effective practical example for the development and poverty alleviation of poverty-stricken areas.

Impacts of Drought and Human Activity on Vegetation Growth in the Grain for Green Program Region,China

The Chinese government adopted six ecological restoration programs to improve its natural environments. Although these programs have proven successful in improving local environments, some studies have questioned their performance when regions suffer from drought. Whether we should consider the effects of drought on vegetation change in assessments of the benefits of ecological restoration programs is unclear. Therefore, taking the Grain for Green Program(GGP) region as a study area, we estimated vegetation growth in the region from 2000–2010 to clarify the trends in vegetation and their driving forces. Results showed that: 1) vegetation growth increased in the GGP region during 2000–2010, with 59.4% of the area showing an increase in the Normalized Difference Vegetation Index(NDVI). This confirmed the benefits of the ecological restoration program. 2) Drought can affect the vegetation change trend, but human activity plays a significant role in altering vegetation growth, and the slight downward trend in the NDVI was not consistent with the severity of the drought. Positive human activity led to increased NDVI in 89.13% of areas. Of these, 22.52% suffered drought, but positive human activity offset the damage in part. 3) Results of this research suggest that appropriate human activity can maximize the benefits of ecological restoration programs and minimize the effects of extreme weather. We therefore recommend incorporating eco-risk assessment and scientific management mechanisms in the design and management of ecosystem restoration programs.

Trade-offs and Synergies of Ecosystem Services in Karst Area of China Driven by Grain-for-Green Program

As an important means regulating the relationship between human and natural ecosystem,ecological restoration program plays a key role in restoring ecosystem functions.The Grain-for-Green Program(GFGP,One of the world’s most ambitious ecosystem conservation set-aside programs aims to transfer farmland on steep slopes to forestland or grassland to increase vegetation coverage)has been widely implemented from 1999 to 2015 and exerted significant influence on land use and ecosystem services(ESs).In this study,three ecological models(In VEST,RUSLE,and CASA)were used to accurately calculate the three key types of ESs,water yield(WY),soil conservation(SC),and net primary production(NPP)in Karst area of southwestern China from 1982 to 2015.The impact of GFGP on ESs and trade-offs was analyzed.It provides practical guidance in carrying out ecological regulation in Karst area of China under global climate change.Results showed that ESs and trade-offs had changed dramatically driven by GFGP.In detail,temporally,SC and NPP exhibited an increasing trend,while WY exhibited a decreasing trend.Spatially,SC basically decreased from west to east;NPP basically increased from north to south;WY basically increased from west to east;NPP and SC,SC and WY developed in the direction of trade-offs driven by the GFGP,while NPP and WY developed in the direction of synergy.Therefore,future ecosystem management and restoration policy-making should consider trade-offs of ESs so as to achieve sustainable provision of ESs.

Degradation of malachite green dye by Tenacibaculum sp. HMG1isolated from Pacific deep-sea sediments

A deep-sea bacterium from the Pacific Ocean identified as Tenacibaculum sp. HMG1 was found to have strong malachite green（MG） degradation activity. The MG tolerance and decolorizing activities of strain HMG1 were confirmed by bacterial growth and high-performance liquid chromatography（HPLC） analyses. Strain HMG1 was capable of removing 98.8% of the MG in cultures within 12 h and was able to grow vigorously at 20 mg/L MG. A peroxidase gene detected in the genome of strain HMG1 was found to be involved in the MG biodegradation process. The corresponding recombinant peroxidase（r POD） demonstrated high degradative activity at 1 000 mg/L MG. Based on the common candidate intermediates, strain HMG1 was inferred to have one primary MG degradation pathway containing r POD. In addition, five other candidate intermediates of the r POD-MG degradative process were detected. The optimal conditions for MG degradation were determined and showed that strain HMG1 and the r POD enzyme could maintain high bioactivity at a low temperature（20℃）, variable p H values（6.0–9.0）, higher salinities（100 mmol/L） and other factors, such as multiple metal ions, H2O2 and EDTA.MG-tolerant strain Tenacibaculum sp. HMG1 and its peroxidase have prospective applications as environmental amendments for MG degradation during coastal remediation.

Decomposition dynamics and ecological stoichiometry of Quercus acutissima and Pinus densiflora litter in the Grain to Green Program Area of northern China

Litter decomposition and ecological stoichiometry of nutrient release is an important part of material cycling and energy flow in forest ecosystems.In a study of the ecological stoichiometry and nutrient release during litter decomposition in a pine–oak forest ecosystem of the Grain to Green Program(GTGP)area of northern China,a typical pine and oak species(PDS:Pinus densiflora Sieb.,QAC:Quercus acutissima Carr.)were selected in the Taiyi Mountain study area.The ecological stoichiometry characteristics of carbon(C),nitrogen(N)and phosphorus(P)and litter decomposition dynamics were studied by field sampling and quantitative analyses.The results showed the following.(1)The decomposition dynamics of both litters was slow-fast-slow.The most important climatic factor affecting the litter decomposition rate from May to October was precipitation and temperature from November to April of the following year.(2)Throughout the 300-day study,in both litters,C of the two litters was released,N first accumulated and was then released,and P exhibited a release-accumulate-release pattern.(3)C:P was significantly higher than C:N and N:P(p<0.05);the C:N of PSD litter was higher than that of QAC(p<0.05),but the N:P of QAC litter was higher than that of PSD litter(p<0.05).The C:N of both litters was very high in the study area,indicating that the nutrient release ability during litter decomposition in the two typical pine–oak forest ecosystems was relatively weak;therefore,more attention should be paid to nitrogen-fixing species and mixed forests in the GTGP area of northern China.

Improving Sensor-free Detection of Programming Difficulties Using Deep Learning

Programming difficulties are one of the common problems faced by software engineering students,which can lead to a rapid decline in motivation and even drop out.Probing students’programming difficulties is a crucial step in understanding their current programming situation and implementing appropriate instructional interventions.However,how to detect students’programming difficulties accurately without students’awareness remains a big challenge.Address the issues above;this paper adopts a sensor-free difficulties detecting method based on a deep neural network which employs a recurrent neural network(RNN)model and uses the sequential timing data from programming behaviour.The method can detect students’programming difficulties in real-time with 93%accuracy without interference in the programming process.In the long term,this method is the first step for establishing an automated intelligent programming environment.At the same time,it can assist teachers in noticing the difficulties that students encounter.Then,teachers can adjust their teaching plans and provide manual tutoring intervention more quickly.

Development of green urbanization under the guidance of deep ecology

At present, green urbanization process is in the initial state in China. In the process of development, how to promote urban development and urbanization will highly integrated. And the ecological environment protection and economic development is an urgent problem to be solved. Based on the guidance of deep ecology, this paper studies the development process of green urbanization; and literature review method and exemplification method are adopted. Firstly, the concept of green urbanization is demonstrated. Secondly, combined with the current situation of green urbanization in China, guided by analysis of deep ecology, the challenge for the development of urbanization is analysed. Finally, based on the deep ecology guided by revelation, the green urbanization path is put forward.

Using Deep Learning to Improve Automated Program Static Assessment

Evaluation is an essential part of the teaching process,especially in the programming course.Both students and teachers can benefit significantly from automatic program evaluation.It shortens the time required for assessment so that students can get immediate feedback.At the same time,it can also significantly reduce the workload of teachers.Currently,the automated program assessment system mainly uses a combination of static and dynamic analysis methods.The system is faced with two crucial problems of the unfinished code evaluation and the template code construction.This paper proposes a method of combining deep learning with static analysis.The syntax tree repair is used to solve the problem that the code with compiling errors cannot generate the correct syntax tree.Moreover,the target code is converted to a subset of solution space through the syntax tree standardization,which reduces the number of template code needed.Based on deep learning,the embedded token vector keeps the code’s context all the time,which ensures that the lexical-semantic remains unchanged as much as possible after the syntax tree changes.Finally,the standardized tree is represented as a vector by the recursive neural network.Cosine similarity between target and template code vectors is used as an evaluation score.The experiment shows that the similarity scores obtained by this method are consistent with the expert scores.This method can provide support for future research,such as difficult feedback and has great significance.

利用DeepLabv3+模型提取分析街景图像绿视率——以北京三环内为例

基于语义分割模型的绿视率提取缺乏适用性研究,本文首先基于DeepLabv3+语义分割预训练模型和自主标注样本,采用迁移学习策略,构建街景图像语义分割模型,并对其进行精度验证。然后基于构建的街景图像语义分割模型提取计算北京三环内绿视率(GVI),分析点、线尺度下绿视率空间分布特征。结果表明:①相比DeepLabv3+语义分割预训练模型,迁移学习后模型F1值和mIoU值分别提高了7%和3%;②点状尺度上北京三环内绿视率整体呈“西高东低,北高南低”聚类式分布特征,0~0.15区间内街景采样点GVI约占58.1%;③线状尺度上整体呈“环线低环内高”且中心发散式特征分布,0~0.15区间内研究区道路GVI约占59.8%。该研究对于提升城市街道绿化感知程度和城市空间规划具有重要的参考意义。

Partnership in the Community“Going Green”Program

On the lawns and central garden of a community in the Haidian District of Beijing, called ＂Enjili＂, one can see a number of signs with the ＂Michelin＂ logo standing as tall as a man.

多尺度特征增强的街景绿色景观分割方法

针对街景图像中景观复杂多样且多种景观相互遮挡,绿色景观分割效果存在相似景观错分、边界分割模糊、细节丢失等问题,提出一种多尺度特征增强的城市绿色景观分割网络。在编码部分改进多尺度残差网络提取上下文信息以区分相似景观,同时构建多级特征聚合增强模块增强目标特征的边缘细节信息。增加双注意力机制,在局部特征上建模丰富的上下文联系。最后,将多级特征聚合增强模块同样引入解码器,并融合多层级特征来提高目标信息的恢复能力完善边缘信息。在公共街景数据集Cityscapes与自制数据集StreetData的消融实验表明,该网络与基础网络相比,平均交并比分别提高2.96%和5.57%。此外,在两个数据集上进行对比实验,该网络较对比模型平均交并比分别高1.25%~5.29%和1.52%~6.95%。定量分析与实验结果表明,该方法能够有效识别街景的绿色景观,实现高精度的城市绿色景观数据提取。

共同富裕的空间分层与推进乡村振兴的系统逻辑——基于浙江“千万工程”实践中的农村综合改革经验

共同富裕是社会主义的本质要求,以共同富裕为目标推动乡村全面振兴,已经成为破解城乡发展不平衡、实现中国式现代化的重要内容。共同富裕在不同的社会情境和研究视角中具有不同的内涵。既有研究从经济、社会与文化等不同视角来讨论共同富裕的理论意义,虽展现了共同富裕的内涵多重性和实践复杂性,但也导致关于共同富裕的研究更多停留在理念的阐释上,而缺乏实践体系的建构。基于空间视角认识共同富裕的差异化内涵,为破解这一理论和实践难题提供了新思路,因为只有在区域、城乡、社区等不同层次的空间单元内,才能体现出经济发展、社会关系以及价值引领的同步性和一致性,也才能够真正建立作为共同体的社会系统、明确共同富裕的具体目标。浙江“千万工程”实践中的农村综合改革经验表明,不同空间层次的共富目标和政策实践具有一定的差异,构成了推动当地乡村全面振兴的系统逻辑。更有利于发挥市场作用、实现经济高质量发展的“区域共富”构成了推动乡村全面振兴的外部社会环境;更有利于发挥城乡互补优势与联动优势的“城乡共富”,为推动乡村全面振兴提供了实现跨越式发展的纽带和机制;更有利于发挥地方社会文化优势和情感价值的“社区共富”,为构建乡村社会治理共同体、推动乡村文化振兴创造了条件。共同富裕的空间分层具有整体性和系统性。浙江的农村综合改革体现了区域、县域、村域多重空间视角下系统性推进乡村振兴的经验,实现了经济高质量发展、新型城镇化、乡村振兴等重大战略与地方发展实际的有机融合,体现了国家政策的地方化统筹,从而内生性推动了当地的高质量发展和乡村振兴,进而实现了区域经济与县域经济的有效衔接,推动了城乡工农关系的内生性重构,激活和发挥了集体经济优势,推动乡村治理现代化,促进了乡村物质与精神的共同富裕,为全国其他地区系统性推进乡村全面振兴提供了启示。

四步法消除SYBR GreenⅠ实时定量RT-PCR中引物二聚体的影响

为建立一种新的SYBRgreenⅠ实时定量RT PCR方法 ,使之能够有效消除引物二聚体 (PDs)对实时定量结果的影响 .对RT PCR特异性扩增产物和PDs分别进行了凝胶电泳检测和熔解曲线分析 .依据PDs和扩增产物的熔解温度 (Tm)特点 ,在通用的三步法的延伸步骤之后 ,增加一个短暂的 (5s)恒温和荧光检测步骤 ,使这个步骤的温度高于PDs的Tm,但低于扩增产物的Tm,简称该法为四步法 .PDs的Tm 通常高于 72℃ ,但低于扩增产物的Tm .将四步法第四步的温度设置在高于PDs的Tm ,但低于扩增产物的Tm 时 ,四步法能够有效地消除PDs的影响 .对三步法和四步法SYBRgreenⅠ实时定量RT PCR进行了比较 ,发现三步法根本不能用于RNA的实时定量 ,而四步法能够实现包括低丰度RNA在内的RNA的定量 .选择Tm 值尽可能小的引物 ,使PDs与扩增产物Tm 值之间有足够的差距 ,将更有利于四步法的应用 。