A Sharding Scheme Based on Graph Partitioning Algorithm for Public Blockchain

Blockchain technology,with its attributes of decentralization,immutability,and traceability,has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business processes.However,transaction performance and scalability has become the main challenges hindering the widespread adoption of blockchain.Due to its inability to meet the demands of high-frequency trading,blockchain cannot be adopted in many scenarios.To improve the transaction capacity,researchers have proposed some on-chain scaling technologies,including lightning networks,directed acyclic graph technology,state channels,and shardingmechanisms,inwhich sharding emerges as a potential scaling technology.Nevertheless,excessive cross-shard transactions and uneven shard workloads prevent the sharding mechanism from achieving the expected aim.This paper proposes a graphbased sharding scheme for public blockchain to efficiently balance the transaction distribution.Bymitigating crossshard transactions and evening-out workloads among shards,the scheme reduces transaction confirmation latency and enhances the transaction capacity of the blockchain.Therefore,the scheme can achieve a high-frequency transaction as well as a better blockchain scalability.Experiments results show that the scheme effectively reduces the cross-shard transaction ratio to a range of 35%-56%and significantly decreases the transaction confirmation latency to 6 s in a blockchain with no more than 25 shards.

A Monte Carlo-based framework for risk-return analysis in mineral prospectivity mapping

Quantification of a mineral prospectivity mapping(MPM)heavily relies on geological,geophysical and geochemical analysis,which combines various evidence layers into a single map.However,MPM is subject to considerable uncertainty due to lack of understanding of the metallogenesis and limited spatial data samples.In this paper,we provide a framework that addresses how uncertainty in the evidence layers can be quantified and how such uncertainty is propagated to the prediction of mineral potential.More specifically,we use Monte Carlo simulation to jointly quantify uncertainties on all uncertain evidence variables,categorized into geological,geochemical and geophysical.On stochastically simulated sets of the multiple input layers,logistic regression is employed to produce different quantifications of the mineral potential in terms of probability.Uncertainties we address lie in the downscaling of magnetic data to a scale that makes such data comparable with known mineral deposits.Additionally,we deal with the limited spatial sampling of geochemistry that leads to spatial uncertainty.Next,we deal with the conceptual geological uncertainty related to how the spatial extent of the influence of evidential geological features such as faults,granite intrusions and sedimentary formations.Finally,we provide a novel way to interpret the established uncertainty in a risk-return analysis to decide areas with high potential but at the same time low uncertainty on that potential.Our methods are illustrated and compared with traditional deterministic MPM on a real case study of prospecting skarn Fe deposition in southwestern Fujian,China.

疫情期间线上学习效果评价分析

2020年初突发的新冠疫情,使在线教学成为完成教学任务的必然选择,也促使众多高校开启在线教学新模式。然而在线学习的效果如何,一直是大家持续关注的问题。文章通过定量定性的分析,对学生在线学习的效果进行评价。首先,对比线下和线上教学的期末笔试成绩,评价在线学习的效果。结果显示,线下学习成绩服从正态分布,但线上学习成绩不服从正态分布,出现双峰的分布。这反映了线上学习效果两极分化比较严重。其次,通过问卷调查,分析学生参与在线教学与学习成绩的关系。结果显示,部分学生对突如其来的在线学习不适应,有抵触心理,导致部分学生松懈。最后,针对上述存在的问题,进行分析与总结,为未来的在线学习提供一些建议。

Construction and Research of Formative Evaluation System in Fine Arts Classroom Teaching in Rural Primary Schools

With the popularization of quality education,the teaching evaluation of fine arts class in rural primary schools has become an important part of the new curriculum reform,which tests whether the teaching goals are effectively achieved.This paper takes the formative evaluation system of fine arts classroom teaching in rural primary schools as the research object,analyzes the research status of the formative evaluation system in rural primary schools,and expounds the theoretical basis and construction principles of the formative evaluation system.This paper constructs a formative evaluation system of fine arts classroom teaching in rural primary schools from the aspects of teachers and students inside and outside the classroom,teaching process and teaching effect,in order to effectively stimulate students'interest in learning and improve their aesthetic literacy.

Leucogranite mapping via convolutional recurrent neural networks and geochemical survey data in the Himalayan orogen

Geochemical survey data analysis is recognized as an implemented and feasible way for lithological mapping to assist mineral exploration.With respect to available approaches,recent methodological advances have focused on deep learning algorithms which provide access to learn and extract information directly from geochemical survey data through multi-level networks and outputting end-to-end classification.Accordingly,this study developed a lithological mapping framework with the joint application of a convolutional neural network(CNN)and a long short-term memory(LSTM).The CNN-LSTM model is dominant in correlation extraction from CNN layers and coupling interaction learning from LSTM layers.This hybrid approach was demonstrated by mapping leucogranites in the Himalayan orogen based on stream sediment geochemical survey data,where the targeted leucogranite was expected to be potential resources of rare metals such as Li,Be,and W mineralization.Three comparative case studies were carried out from both visual and quantitative perspectives to illustrate the superiority of the proposed model.A guided spatial distribution map of leucogranites in the Himalayan orogen,divided into high-,moderate-,and low-potential areas,was delineated by the success rate curve,which further improves the efficiency for identifying unmapped leucogranites through geological mapping.In light of these results,this study provides an alternative solution for lithologic mapping using geochemical survey data at a regional scale and reduces the risk for decision making associated with mineral exploration.

Insulin peptides and their receptors regulate ovarian development and oviposition behavior in Diaphorina citri

Diaphorina citri is an important vector of Citrus Huanglongbing(HLB)disease.After feeding on young host plant shoots,the population of D.citri can increase significantly.Females also only lay eggs on young shoots.However,there are few studies on the mechanism of this phenomenon.Exogenous nutrient signals can affect the insulin signaling system of D.citri after feeding on young shoots.In this study,the expression of upstreamfactors DclLPl,DclLP2,and DclR in the insulin signaling system of D.citri was upregulated after feeding on young shoots.After being silenced by RNA interference technology,the results showed that the number of oviposited eggs of D.citri was significantly decreased and the ovarian development was inhibited with severe vacuolation.In addition,detection using quantitative reverse transcription-polymerase chain reaction showed that the upstream regulatory gene DcRheb of the target of rapamycin(TOR)pathway and the downstream reproduction-related DcVg gene were also significantly downregulated.These results suggest that feeding upon young shoots may upregulate the expression levels of upstream factors DclLPl,DclLP2,and DclR in the insulin signaling system.The signal will be through upregulating the expression of DcRheb,an upstream gene of the TOR signaling pathway.This in turn influences yolk metabolism,which eventually causes the ovaries of female D.citri to mature and therefore initiate oviposition behavior.

Spatial Analysis of Fe Deposits in Fujian Province, China: Implications for Mineral Exploration

Spatial point pattern statistics, fractal analysis and Fry analysis in support of GIS were applied to explore the spatial distribution characteristics of mineral deposits and the spatial relationships between mineralization and geological features in Fujian Province(China). The results of Ripley's K(r) revealed a clustered distribution of Fe deposits in space with a fractal dimension of 1.38. Fry analysis showed that Fe deposits distributed mainly along a NNE-NE trend. Buffer analysis showed that most of the known Fe deposits developed within 4 km buffer zones of the NNE-NE-trending faults, Yanshanian intrusions, and Late Paleozoic marine sedimentary rocks and the carbonate formations(C–P Formation), indicating that they possibly control the spatial distribution of Fe mineralization. This is possibly because the NNE-NE-trending faults, Yanshanian intrusions, and C–P Formation provided pathways of fluids, energy and a part of metal, and zones of deposition for the Fe mineralization, respectively. The fractal relation of the number of Fe deposits occurring within the buffer zones of geological features was observed. The fractal dimension suggested that the significance of Yanshanian intrusions and C–P Formation are greater than that of NNE-NE-trending faults in controlling the formation of Fe mineralization. These findings are useful for better understanding the formation of the mineralization and provide significant information for further mineral exploration.

Continuous-wave operation of 1550 nm low-threshold triple-lattice photonic-crystal surface-emitting lasers

Benefitting from narrow beam divergence,photonic crystal surface-emitting lasers are expected to play an essential role in the ever-growing fields of optical communication and light detection and ranging.Lasers operating with 1.55μm wavelengths have attracted particular attention due to their minimum fiber loss and high eye-safe threshold.However,high interband absorption significantly decreases their performance at this 1.55μm wavelength.Therefore,stronger optical feedback is needed to reduce their threshold and thus improve the output power.Toward this goal,photonic-crystal resonators with deep holes and high dielectric contrast are often used.Nevertheless,the relevant techniques for high-contrast photonic crystals inevitably complicate fabrication and reduce the final yield.In this paper,we demonstrate the first continuous-wave operation of 1.55μm photonic-crystal surface-emitting lasers by using a‘triple-lattice photonic-crystal resonator’,which superimposes three lattice point groups to increase the strength of in-plane optical feedback.Using this geometry,the in-plane 180°coupling can be enhanced threefold compared to the normal single-lattice structure.Detailed theoretical and experimental investigations demonstrate the much lower threshold current density of this structure compared to‘single-lattice’and‘double-lattice’photonic-crystal resonators,verifying our design principles.Our findings provide a new strategy for photonic crystal laser miniaturization,which is crucial for realizing their use in future high-speed applications.