可信联邦学习进化优化算法综述

With the development of edge devices and cloud computing,the question of how to accomplish machine learning and optimization tasks in a privacy-preserving and secure way has attracted increased attention over the past decade.As a privacy-preserving distributed machine learning method,federated learning(FL)has become popular in the last few years.However,the data privacy issue also occurs when solving optimization problems,which has received little attention so far.This survey paper is concerned with privacy-preserving optimization,with a focus on privacy-preserving data-driven evolutionary optimization.It aims to provide a roadmap from secure privacy-preserving learning to secure privacy-preserving optimization by summarizing security mechanisms and privacy-preserving approaches that can be employed in machine learning and optimization.We provide a formal definition of security and privacy in learning,followed by a comprehensive review of FL schemes and cryptographic privacy-preserving techniques.Then,we present ideas on the emerging area of privacy-preserving optimization,ranging from privacy-preserving distributed optimization to privacy-preserving evolutionary optimization and privacy-preserving Bayesian optimization(BO).We further provide a thorough security analysis of BO and evolutionary optimization methods from the perspective of inferring attacks and active attacks.On the basis of the above,an in-depth discussion is given to analyze what FL and distributed optimization strategies can be used for the design of federated optimization and what additional requirements are needed for achieving these strategies.Finally,we conclude the survey by outlining open questions and remaining challenges in federated data-driven optimization.We hope this survey can provide insights into the relationship between FL and federated optimization and will promote research interest in secure federated optimization.

Genetic and environmental control of rice tillering

Increasing tiller number is a target of high-yield rice breeding. Identification of tiller-defect mutants and their corresponding genes is helpful for clarifying the molecular mechanism of rice tillering. Summarizing research progress on the two processes of rice tiller formation, namely the formation and growth of axillary meristem, this paper reviews the effects of genetic factors, endogenous hormones, and exogenous environment on rice tillering, finding that multiple molecular mechanisms and signal pathways regulating rice tillering cooperate rice tillering, and discusses future research objectives and application of its regulatory mechanism. Elucidation of theis mechanism will be helpful for breeding high-yielding rice cultivars with ideal plant type via molecular design breeding.

Effects of Common Mineral Trace Elements on Immune Function of Livestock and Poultry

The effects of zinc(Zn), iron(Fe), selenium(Se), copper(Cu), manganese(Mn), chromium(Cr) and germanium(Ge) on immune function of livestock and poultry are discussed, in order to provide the reference for safe and reasonable use of trace elements.

Experiment on the Fattening Effects of Mixed Silage of Wolfberry Branches on Hybrid

[Objectives] This study was conducted to use the feeding value of wolfberry branches and to provide a basis for the rational use of its active ingredients and nutrients and the development of new feed resources. [Methods] Wolfberry branches and whole-plant corn were used to make mixed silage of wolfberry branches, which replaced different proportions of whole-plant corn silage for feeding hybrid mutton sheep, and the feeding effect of the mixed silage of wolfberry branches on hybrid mutton sheep was analyzed, which provides a technical basis for rational utilization of mulberry resources to ruminants. A single factor feeding comparison experiment was carried out. 32 hybrid mutton sheep of 8 months old with conform gender, age, body weight, physiological state and feeding management level were selected and divided into two groups, 16 in each group. [Results] The gross output value of weight gain of the experimental group was 18.06 yuan, which was higher than the CK(12.97 yuan) by 5.09 yuan. [Conclusions] The addition of the mixed silage of wolfberry branches to the diet had a positive effect on the increase of the weight gain of the hybrid mutton sheep and the reduction of the feed conversion ratio compared with the single whole-plant corn silage.

Experiment on the Fattening Effects of Mixed Silage of Mulberry Branches and Leaves on Hybrid Mutton Sheep

[Objectives] This study was conducted to investigate the effect of mixed silage of mulberry branches and leaves on the production performance of Tan Han hybrid mutton sheep and explore the feasibility in production. [Methods] Twenty-six Tan Han hybrid mutton sheep were selected and divided into two groups, 13 in each group. The experimental group was fed with the mixed silage and the control group(CK) was fed with whole-plant corn silage. [Results] The average daily weight gain per sheep of the experimental group was 9.2% higher than that of the CK(P<0.05), and the feed conversion ratio was decreased by 6.98%(P<0.05). The average daily weight gain per sheep in the 30 d improved the gross profit by 7.75 yuan, which meant an increase of 16.32%. [Conclusions] The mulberry mixed silage is feasible in the production, and it could significantly improve the production performance of the hybrid mutton sheep.

Power Incomplete Data Clustering Based on Fuzzy Fusion Algorithm

With the rapid development of the economy,the scale of the power grid is expanding.The number of power equipment that constitutes the power grid has been very large,which makes the state data of power equipment grow explosively.These multi-source heterogeneous data have data differences,which lead to data variation in the process of transmission and preservation,thus forming the bad information of incomplete data.Therefore,the research on data integrity has become an urgent task.This paper is based on the characteristics of random chance and the Spatio-temporal difference of the system.According to the characteristics and data sources of the massive data generated by power equipment,the fuzzy mining model of power equipment data is established,and the data is divided into numerical and non-numerical data based on numerical data.Take the text data of power equipment defects as the mining material.Then,the Apriori algorithm based on an array is used to mine deeply.The strong association rules in incomplete data of power equipment are obtained and analyzed.From the change trend of NRMSE metrics and classification accuracy,most of the filling methods combined with the two frameworks in this method usually show a relatively stable filling trend,and will not fluctuate greatly with the growth of the missing rate.The experimental results show that the proposed algorithm model can effectively improve the filling effect of the existing filling methods on most data sets,and the filling effect fluctuates greatly with the increase of the missing rate,that is,with the increase of the missing rate,the improvement effect of the model for the existing filling methods is higher than 4.3%.Through the incomplete data clustering technology studied in this paper,a more innovative state assessment of smart grid reliability operation is carried out,which has good research value and reference significance.

Study on Addition Amount of Lactic Acid Bacteria and Cellulase in Mixed Silage of Potato Plants

[Objectives]This study was conducted to investigate the appropriate addition amounts of lactic acid bacteria and cellulase in the mixed silage of potato plants,so as to provide a basis for the rational use of potato plants.[Methods]Fresh potato(Solanum tuberosum)seedling plants,watermelon(Citrullus lanatus)plants,and melon(Cucumis melo)plants were selected as raw materials for silage,each of which was added at a ratio of 32%,and 4%of brown flour was added additionally.On this basis,an L 9(32)orthogonal experiment was designed to investigate the effects of the amount of lactic acid bacteria(10,20,30 g/kg)and the amount of cellulase(5,10,15 g/kg)on the experimental results with sensory evaluation score as an investigation index.[Results]With the increase of the amount of lactic acid bacteria and the amount of cellulase,the sensory evaluation score of silage increased,and it was the highest when the amount of lactic acid bacteria added was 20 g/kg and the amount of cellulose was 10 g/kg.With the increase of the amounts of lactic acid bacteria and cellulase added,ammonia nitrogen showed a decreasing trend,and the pH and ammonia nitrogen were the lowest when the amount of lactic acid bacteria added was 20 g/kg and the amount of cellulose was 10 g/kg.[Conclusions]This study provides a theoretical basis for the rational use of effective ingredients and nutrients in potato plants and the development of new feed resources.

Development of Microbial Fermented Feed and Its Effect on the Production Performance of Holstein Cows

[Objectives]This study was conducted to investigate the development method of microbial fermented feed and its effect on the production performance of Holstein cows.[Methods]Thirty Holstein cows were selected and randomly divided into 2 groups,15 cows in each group.The diet composition of the experimental group was:concentrate supplement added with 30% microbial fermented feed+silage+alfalfa hay,and the diet composition of the control group was:concentrate supplement added with 30% flax cake+silage+alfalfa hay.The experimental period was 60 d.[Results]Compared with the control group,the experimental group increased the average daily milk yield per cow by 2.25%(P>0.05)and the total increase in average milk yield per cow in the experimental period by 43.51%(P<0.01),and reduced the average feed-to-milk ratio by 9.20%(P<0.05).The average gross profit per cow of the experimental group was 40.34 yuan higher than that of the control group,showing an increase of 3.53% in the economic benefit.[Conclusions]Feeding a diet supplemented with the microbial fermented feed could improve the efficiency of Holstein cow farming and is recommended to be promoted.

Effect of Wolfberry Polysaccharide Additive Premixed Feed on Fattening Effect of Tan Sheep

[Objectives]This study was conducted to explore and rationally use the effective value and nutritional components of wolfberry polysaccharide to provide a basis for the use of new feed resources.[Methods]The premixed feed prepared with the wolfberry polysaccharide additive was applied to fattening Tan sheep in Ningxia,and the effect of the wolfberry polysaccharide additive on the fattening Tan sheep was analyzed,so as to provide technical support for the rational utilization of the wolfberry polysaccharide resources.The study adopted a single-factor comparison method,selecting 84 tan sheep in the fattening period with conform gender,feeding management,weight,age,and physiological status,which were divided into 2 test groups and 1 control group,28 in each group.[Results]Within 90 d,the weight gain of the group with 0.1%wolfberry polysaccharide additive increased by 6.98%,showing a significant difference(P<0.05),and the feed conversion ratio decreased by 9.66%,which was significant as well(P<0.05).The gross profit of this group was 125.76 yuan,which was higher than the control group by 57.52 yuan.The group with 0.2%wolfberry polysaccharide additive increased the weight gain by 8.63%,which was significant(P<0.05),and the feed conversion ratio decreased by 10.80%,which was significant as well(P<0.05).The gross profit of group 2 was 125.76 yuan,which was higher than the control group by 63.41 yuan.There were no significant differences in weight gain,feed conversion ratio and gross profit between the groups with 0.1%and 0.2%of wolfberry polysaccharide additive.The results showed that the use of wolfberry polysaccharide additive premixed feed has a positive effect on increasing the weight gain of fattening Tan sheep,reducing the feed conversion ratio,and improving the feed conversion efficiency.The addition of 0.1%and 0.2%of the wolfberry polysaccharide additive premixed feed had no significant differences.[Conclusions]The wolfberry polysaccharide additive has a positive effect on increasing the weight gain of fattening Tan sheep,reducing the feed conversion ratio,and improving the feed conversion efficiency.

Carotenoid isomerase regulates rice tillering and grain productivity by its biosynthesis pathway

Tillers are unique inflorescence-like branches in grasses,and their number determines the panicle number,plant architecture,and yield(Shang et al.,2021).Tiller formation mainly undergoes axillary meristem(AM)initiation and tiller bud outgrowth(Wang et al.,2018;Yan et al.,2023).The rice(Oryza sativa)KNOX gene OSH1 is expressed in AMs,and an osh1 mutant produces fewer tillers(Tanaka et al.,2015).

波罗的海希瓦氏菌AI-2/LuxS对生物被膜和致腐的调控

【目的】波罗的海希瓦氏菌(Shewanella baltica)是冷藏海产鱼类的特定腐败菌。研究群体感应信号AI-2/Lux S对鱼源S.baltica生物被膜和致腐的调控作用。【方法】扩增SB11分离株的lux S基因,用自杀性质粒构建lux S基因缺失株,通过结晶紫染色、珠涡流法、显微镜观察和HPLC,比较分析野生株与缺失株△lux S在4°C和28°C下生物被膜形成、粘附能力、泳动性和致腐产物的差异。【结果】S.baltica SB11中扩增获得lux S基因,生物信息学分析显示Lux S蛋白由169个氨基酸构成,含有保守的His-Thr-Leu-Glu-His(HTLEH)模体和关键氨基酸位点,蛋白三维空间结构与其他细菌相似。与野生株相比,△lux S缺失株上清荧光信号散失,但不影响生长,生物被膜形成期和成熟期的含量显著低于野生株,在4°C培养96 h和28°C培养24 h被膜分别减少20.1%和27.9%。缺失株在不锈钢片的粘附能力明显减弱,其中在4°C培养72 h和28°C培养24 h后的粘附量比野生株分别减少6.48%和6.57%。荧光显微镜观察发现,野生株能快速粘附于玻璃片,聚集形成大量生物被膜,而△lux S仅形成平坦稀疏的被膜,粘附细菌降低,CLSM证实野生株和△lux S的成熟被膜厚度分别为68.95μm和36.44μm。并且,△lux S株在4°C和28°C下泳动性均显著强于野生株。然而,野生株和△lux S株三甲胺和腐胺积累无差异。【结论】鱼源S.baltica中Lux S蛋白保守,AI-2/Lux S参与被膜、粘附能力及泳动性等多种生物被膜形成相关的调控作用,然而不是该菌致腐能力的功能性群体感应信号。

水稻穗粒数遗传机制与育种利用

作为影响产量的关键因素之一,水稻(Oryza sativa)每穗粒数始终备受育种家关注。穗粒数形成是复杂的生物学过程,受多基因调控。根据对表型的影响,这些基因大致包括枝梗数、穗型和小穗确定性相关基因3类。该文综述了穗粒数相关基因的遗传调控机制,并提出在水稻育种中利用的策略,以期为水稻高产育种提供理论依据。

Prediction of Primary Climate Variability Modes at the Beijing Climate Center

Climate variability modes, usually known as primary climate phenomena, are well recognized as the most impor- tant predictability sources in subseasonal-interarmual climate prediction. This paper begins by reviewing the re- search and development carried out, and the recent progress made, at the Beijing Climate Center （BCC） in predicting some primary climate variability modes. These include the El Nifio-Southern Oscillation （ENSO）, Madden-Julian Oscillation （MJO）, and Arctic Oscillation （AO）, on global scales, as well as the sea surface temperature （SST） modes in the Indian Ocean and North Atlantic, western Pacific subtropical high （WPSH）, and the East Asian winter and summer monsoons （EAWM and EASM, respectively）, on regional scales. Based on its latest climate and statistical models, the BCC has established a climate phenomenon prediction system （CPPS） and completed a hindcast experi- ment for the period 1991-2014. The performance of the CPPS in predicting such climate variability modes is system- atically evaluated. The results show that skillful predictions have been made for ENSO, MJO, the Indian Ocean basin mode, the WPSH, and partly for the EASM, whereas less skillful predictions were made for the Indian Ocean Dipole （IOD） and North Atlantic SST Tripole, and no clear skill at all for the AO, subtropical IOD, and EAWM. Improve- ments in the prediction of these climate variability modes with low skill need to be achieved by improving the BCC＇s climate models, developing physically based statistical models as well as correction methods for model predictions. Some of the monitoring/prediction products of the BCC-CPPS are also introduced in this paper.