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.

Long-range electron synergy over Pt_(1)-Co_(1)/CN bimetallic single-atom catalyst in enhancing charge separation for photocatalytic hydrogen production

The development of novel single-atom catalysts with optimal electron configuration and economical noble-metal cocatalyst for efficient photocatalytic hydrogen production is of great importance,but still challenging.Herein,we fabricate Pt and Co single-atom sites successively on polymeric carbon nitride(CN).In this Pt_(1)-Co_(1)/CN bimetallic single-atom catalyst,the noble-metal active sites are maximized,and the single-atomic Co_(1)N_4sites are tuned to Co_(1)N_3sites by photogenerated electrons arising from the introduced single-atomic Pt_(1)N_4sites.Mechanism studies and density functional theory(DFT)calculations reveal that the 3d orbitals of Co_(1)N_3single sites are filled with unpaired d-electrons,which lead to the improved visible-light response,carrier separation and charge migration for CN photocatalysts.Thereafter,the protons adsorption and activation are promoted.Taking this advantage of long-range electron synergy in bimetallic single atomic sites,the photocatalytic hydrogen evolution activity over Pt_(1)-Co_(1)/CN achieves 915.8 mmol g^(-1)Pt h^(-1),which is 19.8 times higher than Co_(1)/CN and 3.5 times higher to Pt_(1)/CN.While this electron-synergistic effect is not so efficient for Pt nanoclusters.These results demonstrate the synergistic effect at electron-level and provide electron-level guidance for the design of efficient photocatalysts.

Rationally construction of atomic-precise interfacial charge transfer channel and strong build-in electric field in nanocluster-based Zscheme heterojunctions with enhanced photocatalytic hydrogen production

The lack of effective charge transfer driving force and channel limits the electron directional migration in nanoclusters(NC)-based heterostructures,resulting in poor photocatalytic performance.Herein,a Z-scheme NC-based heterojunction(Pt1Ag28-BTT/CoP,BTT=1,3,5-benzenetrithiol)with strong internal electric field is constructed via interfacial Co-S bond,which exhibits an absolutely superiority in photocatalytic performance with 24.89 mmol·h^(−1)·g−1 H_(2)production rate,25.77%apparent quantum yield at 420 nm,and~100%activity retention in stability,compared with Pt1Ag28-BDT/CoP(BDT=1,3-benzenedithiol),Ag29-BDT/CoP,and CoP.The enhanced catalytic performance is contributed by the dual modulation strategy of inner core and outer shell of NC,wherein,the center Pt single atom doping regulates the band structure of NC to match well with CoP,builds internal electric field,and then drives photogenerated electrons steering;the accurate surface S modification promotes the formation of Co-S atomic-precise interface channel for further high-efficient Z-scheme charge directional migration.This work opens a new avenue for designing NC-based heterojunction with matchable band structure and valid interfacial charge transfer.

Nanoheterostructured photocatalysts for improving photocatalytic hydrogen production

Rapid industrialization has accordingly increased the demand for energy.This has resulted in the increasingly severe energy and environmental crises.Hydrogen production,based on the photocatalytic water splitting driven by sunlight,is able to directly convert solar energy into a usable or storable energy resource,which is considered to be an ideal alternative energy source to assist in solving the energy crisis and environmental pollution.Unfortunately,the hydrogen production efficiency of single phase photocatalysts is too low to meet the practical requirements.The construction of heterostructured photocatalyst systems,which are comprised of multiple components or multiple phases,is an efficient method to facilitate the separation of electron‐hole pairs to minimize the energy‐waste,provide more electrons,enhance their redox ability,and hence improve the photocatalytic activity.We summarize the recent progress in the rational design and fabrication of nanoheterostructured photocatalysts.The heterojunction photocatalytic hydrogen generation systems can be divided into type‐I,type‐II,pn‐junction and Z‐scheme junction,according to the differences in the transfer of the photogenerated electrons and holes.Finally,a summary and some of the challenges and prospects for the future development of heterojunction photocatalytic systems are discussed.

Ni-P cluster modified carbon nitride toward efficient photocatalytic hydrogen production

Exploring low-cost cocatalyst to take over noble metal cocatalyst is still challenging in the field of photocatalytic proton reduction.Herein,Ni-P alloy clusters are anchored onto the surface of polymeric carbon nitride through a chemical plating method and serve as highly efficient and stable cocatalyst toward photocatalytic proton reduction.An effective role in promoting the charge separation and migration of the photocatalytic system is demonstrated for Ni-P clusters,which essentially enhance the photocatalytic H2-production rate to a value of 1506μmol h^–1 g^–1.This performance is comparable to that of the benchmark of Pt-modified carbon nitride.This work highlights that the Ni-P alloy could be a potential alternative to noble metal cocatalyst in the photocatalytic reactions.

Reproductive fluids,used for the in vitro production of pig embryos,result in healthy offspring and avoid aberrant placental expression of PEG3 and LUM

Background:In vitro embryo production(IVP)and embryo transfer(ET)are two very common assisted reproductive technologies(ART)in human and cattle.However,in pig,the combination of either procedures,or even their use separately,is still considered suboptimal due to the low efficiency of IVP plus the difficulty of performing ET in the long and contorted uterus of the sow.In addition,the potential impact of these two ART on the health of the offspring is unknown.We investigated here if the use of a modified IVP system,with natural reproductive fluids(RF)as supplements to the culture media,combined with a minimally invasive surgery to perform ET,affects the output of the own IVP system as well as the reproductive performance of the mother and placental molecular traits.Results:The blastocyst rates obtained by both in vitro systems,conventional(C-IVP)and modified(RF-IVP),were similar.Pregnancy and farrowing rates were also similar.However,when compared to in vivo control(artificial insemination,AI),litter sizes of both IVP groups were lower,while placental efficiency was higher in AI than in RF-IVP.Gene expression studies revealed aberrant expression levels for PEG3 and LUM in placental tissue for C-IVP group when compared to AI,but not for RF-IVP group.Conclusions:The use of reproductive fluids as additives for the culture media in pig IVP does not improve reproductive performance of recipient mothers but could mitigate the impact of artificial procedures in the offspring.

Application of In-Flight Melting Technology by RF Induction Thermal Plasmas to Glass Production

An innovative in-flight glass melting technology with induced thermal plasmas was developed for the purpose of energy conservation and environmental protection. Two-dimensional modeling was used to simulate the thermofluid fields in the plasma torch. The in-flight melting behavior of glass raw material was investigated by various analysis methods. Results showed that the plasma temperature was up to 10000 K with a maximum velocity over 30 m/s, which made it possible to melt the granulated glass raw material within milliseconds. The carbonates in the raw material decomposed completely and the compounds in the raw material attainted 100% vitrification during the in-flight time from the nozzle exit to substrate. The particle melting process is similar to the unreacted-core shrinking model.

Positioning Temperature Sensors for Frost Protection in Northern Cranberry Production

Frost can cause serious economic losses in cranberry fields, particularly in northern regions. When the air temperature reaches a low critical threshold, sprinklers are operated to protect vines, to insure crop production and profitability. To avoid frost injury, proper positioning of temperature sensors is critical. A field experiment was designed and conducted to determine the optimal installation height of sensors above soil surface. Temperature data was used to investigate the spatial temperature gradient in the section of a cranberry field. A computer simulation of the temperature profile was performed to simulate the effect of wind velocity on the prediction of air temperature. For optimal use, sensors should be installed at the height of the canopy and several meters away from a dike. On nights with low wind velocities, the canopy air temperature was 2.7°C below that of 500 cm above the ground. The sensors should be put at least five m away from a dike to avoid the transfer of heat from the dike to the sensor. Also, multiple sensors should be installed because of the large variations in air temperature that were measured across the experiment. The simulated temperature indicated that wind velocity strongly influenced the temperature estimation;the effect of the wind on temperatures gradients was greater when the wind velocity was low (<2.3 m/s).

Research on customer knowledge transferring mode and mechanism in internet-based new product development

With the development of internet technology, customers play more and more important roles in new product development. The paper defines customer knowledge; then analyses the modes of customer knowledge transferring based on SECI model and information emission model. Finally customer knowledge transferring mechanism is discussed.

Cartesian Product Based Transfer Learning Implementation for Brain Tumor Classification

Knowledge-based transfer learning techniques have shown good performance for brain tumor classification,especially with small datasets.However,to obtain an optimized model for targeted brain tumor classification,it is challenging to select a pre-trained deep learning(DL)model,optimal values of hyperparameters,and optimization algorithm(solver).This paper first presents a brief review of recent literature related to brain tumor classification.Secondly,a robust framework for implementing the transfer learning technique is proposed.In the proposed framework,a Cartesian product matrix is generated to determine the optimal values of the two important hyperparameters:batch size and learning rate.An extensive exercise consisting of 435 simulations for 11 state-of-the-art pre-trained DL models was performed using 16 paired hyperparameters from the Cartesian product matrix to input the model with the three most popular solvers(stochastic gradient descent with momentum(SGDM),adaptive moment estimation(ADAM),and root mean squared propagation(RMSProp)).The 16 pairs were formed using individual hyperparameter values taken from literature,which generally addressed only one hyperparameter for optimization,rather than making a grid for a particular range.The proposed framework was assessed using a multi-class publicly available dataset consisting of glioma,meningioma,and pituitary tumors.Performance assessment shows that ResNet18 outperforms all other models in terms of accuracy,precision,specificity,and recall(sensitivity).The results are also compared with existing state-of-the-art research work that used the same dataset.The comparison was mainly based on performance metric“accuracy”with support of three other parameters“precision,”“recall,”and“specificity.”The comparison shows that the transfer learning technique,implemented through our proposed framework for brain tumor classification,outperformed all existing approaches.To the best of our knowledge,the proposed framework is an efficient framework that helped reduce the computational complexity and the time to attain optimal values of two important hyperparameters and consequently the optimized model with an accuracy of 99.56%.

Calcium Carbonate Lab Scale Continuous Carbon Dioxide-jet Controlled Production Following Fuzzy Logic Model

In this paper, lab scale production carried out of calcium carbonate in 400 mL open cylindrical beaker reactor following fuzzy logic approach is reported. 10 grams of Calcium hydroxide is mixed in 250 mL deionized water. Continuous jet supply of carbon dioxide is maintained at controlled flow rate. Reaction histories are noted for different reaction temperatures. Continuous constant magnetic stirring is applied to maintain homogeneity. The data obtained is fuzzified by constructing universe of discourse of temperature, reaction time, and amounts of reactants with reaction conversion. Rule based model is tabulated and results show that fuzzy logic approach is promising to set on data to plan and scale up the process. It is also found that a jump can not be made at this time with few studies of fuzzy logic applications to physiochemical processes unless otherwise amassing and storing up plentiful deduced explorations.

The Effects of Cells Density Arrangement in Chlorella vulgaris Culture to C02 Fixation and Essential Substances Production

Global warming that triggered the climate change is largely due to increased CO2 concentrations. Utilization of Chlorella sp. to reduce CO2 gas is a promising potential. Chlorella can efficiently reduce CO2 and easily be adapted into the photobioreactor system engineering. In this research, the type of microalgae which is used is Chlorella vulgaris in Benneck medium. The system of used reactor is mid-scale bubble column photobioreactor flowed by air which contains 5% CO2. Chlorella vulgaris biomass production will be increased by adjusting the cell density in the photobioreactor. These arrangements will be implemented through a continuous treatment of cell entrapment. The arrangement of cell density in continuous reactor has been proven to increase production of Chlorella vulgaris biomass about 1.25 times more than cultivation without arrangement of cell density by using the same number of inoculums. The results also have shown that the average rate of CO2 fixation and Carbon Transfer Rate （CTR） are obtained at cell entrapment condition about 17 times larger. Continuous cellular entrapment method is very potential to be developed as a method for the production of biomass. Lipids and carotene that have been produced from Ch. vulgaris respectively are 18.24% and 9.42 ppm.

Promoting and controlling electron transfer of furfural oxidation efficiently harvest electricity,furoic acid,hydrogen gas and hydrogen peroxide

Conventional chemical oxidation of aldehydes such as furfural to corresponding acids by molecular oxygen usually needs high pressure to increase the solubility of oxygen in aqueous phase,while electrochemical oxidation needs input of external electric energy.Herein,we developed a liquid flow fuel cell(LFFC)system to achieve oxidation of furfural in anode for furoic acid production with co-production of hydrogen gas.By controlling the electron transfer in cathode for reduction of oxygen,efficient generation of electricity or production of H_(2)O_(2)were achieved.Metal oxides especially Ag_(2)O have been screened as the efficient catalyst to promote the oxidation of aldehydes,while liquid redox couples were used for promoting the kinetics of oxygen reduction.A novel alkaline-acidic asymmetric design was also used for anolyte and catholyte,respectively,to promote the efficiency of electron transfer.Such an LFFC system achieves efficient conversion of chemical energy of aldehyde oxidation to electric energy and makes full use the transferred electrons for high-value added products without input of external energy.With(VO_(2))_(2)SO_(4)as the electron carrier in catholyte for four-electron reduction of oxygen,the peak output power density(Pmax)at room temperature reached 261 mW/cm^(2)with furoic acid and H_(2)yields of 90%and 0.10 mol/mol furfural,respectively.With anthraquinone-2-sulfonate(AQS)as the cathodic electron carrier,Pmaxof 60 mW/cm^(2)and furoic acid,H_(2)and H_(2)O_(2)yields of 0.88,0.15 and 0.41 mol/mol furfural were achieved,respectively.A new reaction mechanism on furfural oxidation on Ag_(2)O anode was proposed,referring to one-electron and two-electron reaction pathways depending on the fate of adsorbed hydrogen atom transferred from furfural aldehyde group.

Research on the Industrial Transfer and Restructuring Path of the Energy-Intensive Manufacturing Industry in Western China

The orderly transfer of the manufacturing industry is a major action in China’s industrial restructuring.From the perspective of industrial transfer,we used the concentration ratio to depict the trend of the industrial transfer of energy-intensive manufacturing in the eastern,central,and western regions since the policy of large-scale development of western China was implemented.We measured the total factor productivity(TFP)of western China using the DEAMalmquist index method.We conducted a regression analysis to measure the effect of western China’s undertaking of the transfer of the energy-intensive manufacturing industry.The findings of this study show that during 2000–2019,eleven provinces(as well as autonomous regions and municipalities)in western China undertook the transfer of the energy-intensive manufacturing industry from the eastern and central regions to varying degrees,exhibiting significant phase features regarding the rate and scale of transfers.Further investigation also demonstrated that the transfer of energy-intensive manufacturing industries has a U-shaped enabling effect on TFP in western China with the scale effect greater than the technology effect.Therefore,it is necessary to transition from“extensive industrial transfer”at the cost of the labor force,land,and resources to“modern industrial transfer”featured by technology and efficiency improvements to contribute to industrial restructuring in western China effectively.

农地流转提升了农业绿色全要素生产率吗?

在2006-2021年中国30个省份的面板数据基础上,本文通过SBM-GML超效率模型测算中国各省份农业绿色全要素生产率。采用双向固定效应模型和工具变量模型等方法,实证分析农地流转和农业绿色TFP之间的内在联系,并分析其影响路径机制。研究发现,中国农业绿色全要素生产率能够持续增长的主要原因在于技术进步。而农地流转能够推动农业绿色全要素生产率增长则是得益于技术效率改进。从异质性分析来看,农地流转对农业绿色全要素生产率增长的促进作用最显著的是东部地区和非粮食主产区,但在西部地区却正好相反。因此,中国应当加快推进农地流转工作进展,促进农业生产和经营管理模式变革,加快研发、推广和应用农业绿色生产技术,构建区域协作互助机制促进地区交流,进而促进农业绿色全要素生产率的提高。

基于SMOTE-IKPCA-SeNet深度迁移学习的小批量生产质量预测研究

随着智能制造技术的发展和客户个性化需求的增加,多品种小批量生产方式逐渐成为制造业的主流。面向大批量生产、以统计过程控制为核心的质量管理方式并不适用于小批量生产。针对复杂生产过程存在参数多、非线性和交互作用的问题,提出利用深度迁移学习的方式将历史生产数据作为源域迁移至小样本目标产品数据进行质量预测。首先,通过合成少数类过采样技术(synthetic minority over-sampling technique,SMOTE)和改进的核主成分分析(improved kernel principal component analysis,IKPCA)算法筛选源域和目标域的可迁移特征,这不仅兼顾了特征重要性和可迁移性,还减少了“负迁移”,提高了模型泛化能力;然后,采用结合通道注意力机制的卷积神经网络SeNet构建基于深度迁移学习的质量预测模型。仿真结果表明,随着目标域样本的增加,所提方法的预测准确性明显优于广泛采用的支持向量机建模方法。同时,所提可迁移特征筛选方法显著提高了深度迁移学习的质量预测效果,为复杂的小批量生产过程质量保证提供了新方法。

永续发展视角下土地流转对农户消费行为的影响

随着城镇化进程的持续推进,土地流转面积不断扩大,土地资源的重新配置会引起农户消费行为的变化,进而影响农村居民的永续发展。基于2010—2020年6年的中国家庭追踪调查数据,采用固定效应模型并考虑了内生性问题的回归结果表明,土地流转对农户的消费存在显著的促进作用,土地转入显著提高了农户发展型消费。从作用机制来看,土地转出租金的心理账户效应提高了农户的暂时性消费;土地转入的收入效应提高了农户消费性支出、耐用品支出和发展型支出;土地转入显著提高农户总劳动生产率,进而提高农户收入,影响农户发展型消费。此外,最高收入群体的土地租金心理账户效应显著高于最低收入群体,土地转入对非老年户的发展型消费影响更明显,但土地流转对是否领取养老金的农户消费行为影响不存在显著差异。因此,要实现农户的永续发展还需要进一步优化农地流转政策,同时发展农业生产托管服务,提高农村社会养老保障水平。

利用转移矩阵模型研究江苏省长江岸线变化

开展长江生态环境监测,推动长江经济带发展是关系国家发展全局的重大战略,是加快推进生态文明建设的客观需要。以2015-2021年江苏省沿江2 km岸线范围内土地利用数据为研究对象,利用转移矩阵模型计算研究区域内各时间节点的转移矩阵表,分析生态、生活和生产空间用地的转入转出以及增减情况;再采用高斯-赛德尔迭代法绘制三生空间流转的桑基图,对江苏省长江岸线变化进行定量分析,为长江经济带(江苏段)的生态监测提供技术支持。

三维变形管MVR蒸发器用于纤维素生产末端废水零排放项目

蒸发器的换热性能对机械蒸汽再压缩(MVR)系统投资及运行均有着重要影响。MVR蒸发器的管内传热与压降性能在基于三维变形管和直圆管的情况下存在明显差异。建立了考虑盐水浓度修正的三维变形管MVR蒸发器性能准则关联式,设计一套用于纤维素生产末端废水零排放项目的新型蒸发器。应用实践表明,相对于传统直圆管的MVR蒸发器,基于三维变形管的新型MVR蒸发器节材节能效果显著,其在节省29%换热面积的情形下仍能完全满足工程实际需要。在现场调研期间MVR系统处理每吨废水的压缩机耗电量在18.81~23.78 kW∙h之间,体现出新型蒸发器高能效的技术特性,极具应用推广价值。