A Comprehensive Survey on Joint Resource Allocation Strategies in Federated Edge Learning

Federated Edge Learning(FEL),an emerging distributed Machine Learning(ML)paradigm,enables model training in a distributed environment while ensuring user privacy by using physical separation for each user’s data.However,with the development of complex application scenarios such as the Internet of Things(IoT)and Smart Earth,the conventional resource allocation schemes can no longer effectively support these growing computational and communication demands.Therefore,joint resource optimization may be the key solution to the scaling problem.This paper simultaneously addresses the multifaceted challenges of computation and communication,with the growing multiple resource demands.We systematically review the joint allocation strategies for different resources(computation,data,communication,and network topology)in FEL,and summarize the advantages in improving system efficiency,reducing latency,enhancing resource utilization,and enhancing robustness.In addition,we present the potential ability of joint optimization to enhance privacy preservation by reducing communication requirements,indirectly.This work not only provides theoretical support for resource management in federated learning(FL)systems,but also provides ideas for potential optimal deployment in multiple real-world scenarios.By thoroughly discussing the current challenges and future research directions,it also provides some important insights into multi-resource optimization in complex application environments.

Energy release characteristics of PTFE/Al/TiH_(2) reactive jet with different TiH_2 content

Titanium hydride(TiH_(2)), a promising high-energy additive, is doped into PTFE/Al to optimize the energy output structure of the reactive jet and strive for better aftereffect damage ability to the target. Six types of PTFE/Al/TiH_(2) reactive liners with different TiH_(2) content are prepared by the molding and sintering method. The energy release characteristics of PTFE/Al/TiH_(2) reactive jet are tested by the transient explosion energy test, and are characterized from pressure and temperature. The reaction delay time,pressure history, and temperature history of the energy release process are obtained, then the actual value of released energy and reaction efficiency of the reactive jet are calculated. The results show that the peak pressure and temperature of the PTFE/Al/TiH_(2) jet initially increase and then decrease with increasing TiH_(2) content. When the TiH_(2) content is 10%, the actual value of released energy and reaction efficiency increased by 24% and 6.4%, respectively, compared to the PTFE/Al jet. The reaction duration of the reactive material is significantly prolonged as the TiH_(2) content increased from 0% to 30%. Finally,combined with the energy release behaviors of PAT material and the dynamic deformation process of liner, the enhancement mechanism of TiH_(2) on energy release of the reactive jet is expounded.

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

Shock-induced chemical reaction characteristics of PTFE-Al-Bi_(2)O_(3)reactive materials

A ternary system of PTFE/Al/Bi_(2)O_(3)is constructed by incorporating PTFE-based reactive material and thermite for enhancing the energy release of the PTFE-based reactive material.The effects of Bi_(2)O_(3)in the PTFE/Al/Bi_(2)O_(3)on both mechanical properties and the energy release were investigated through various tests such as thermogravimetry-differential scanning calorimetry,adiabatic oxygen bomb test and split Hopkinson pressure bar test.The microstructure observed through scanning electron microscope and Xray diffraction results are used to analyze the ignition and reaction mechanism of PTFE/Al/Bi_(2)O_(3).The results indicate that the PTFE/Al/Bi_(2)O_(3)are capable of triggering the exothermic reaction of molten PTFE/Bi_(2)O_(3)and Al/Bi_(2)O_(3)over the PTFE/Al reactive materials,thereby promoting reactions.The excessive aluminum in the ternary system is beneficial for increasing energy release.The ignition of shock-induced chemical reactions in PTFE/Al/Bi_(2)O_(3)is closely related to the material fracture.The dominant mechanism for hot-spot generation under Split Hopkinson Pressure Bar test is the frictional temperature rise at the microcrack after failure.

A High-Quality Adaptive Video Reconstruction Optimization Method Based on Compressed Sensing

The video compression sensing method based onmulti hypothesis has attracted extensive attention in the research of video codec with limited resources.However,the formation of high-quality prediction blocks in the multi hypothesis prediction stage is a challenging task.To resolve this problem,this paper constructs a novel compressed sensing-based high-quality adaptive video reconstruction optimizationmethod.Itmainly includes the optimization of prediction blocks(OPBS),the selection of searchwindows and the use of neighborhood information.Specifically,the OPBS consists of two parts:the selection of blocks and the optimization of prediction blocks.We combine the high-quality optimization reconstruction of foreground block with the residual reconstruction of the background block to improve the overall reconstruction effect of the video sequence.In addition,most of the existing methods based on predictive residual reconstruction ignore the impact of search windows and reference frames on performance.Therefore,Block-level search window(BSW)is constructed to cover the position of the optimal hypothesis block as much as possible.To maximize the availability of reference frames,Nearby reference frame information(NRFI)is designed to reconstruct the current block.The proposed method effectively suppresses the influence of the fluctuation of the prediction block on reconstruction and improves the reconstruction performance.Experimental results showthat the proposed compressed sensing-based high-quality adaptive video reconstruction optimization method significantly improves the reconstruction performance in both objective and supervisor quality.

Three-Stages Hyperspectral Image Compression Sensing with Band Selection

Compressed sensing(CS),as an efficient data transmission method,has achieved great success in the field of data transmission such as image,video and text.It can robustly recover signals from fewer Measurements,effectively alleviating the bandwidth pressure during data transmission.However,CS has many shortcomings in the transmission of hyperspectral image(HSI)data.This work aims to consider the application of CS in the transmission of hyperspectral image(HSI)data,and provides a feasible research scheme for CS of HSI data.HSI has rich spectral information and spatial information in bands,which can reflect the physical properties of the target.Most of the hyperspectral image compressed sensing(HSICS)algorithms cannot effectively use the inter-band information of HSI,resulting in poor reconstruction effects.In this paper,A three-stage hyperspectral image compression sensing algorithm(Three-stages HSICS)is proposed to obtain intra-band and inter-band characteristics of HSI,which can improve the reconstruction accuracy of HSI.Here,we establish a multi-objective band selection(Mop-BS)model,amulti-hypothesis prediction(MHP)model and a residual sparse(ReWSR)model for HSI,and use a staged reconstruction method to restore the compressed HSI.The simulation results show that the three-stage HSICS successfully improves the reconstruction accuracy of HSICS,and it performs best among all comparison algorithms.

蛋白降解靶向嵌合体在非小细胞肺癌治疗中的研究进展

蛋白降解靶向嵌合体(proteolysis targeting chimeria,PROTAC)通过利用泛素蛋白酶体途径实现对靶蛋白降解,颠覆了传统小分子抑制剂的理念。在非小细胞肺癌(non-small cell lung cancer,NSCLC)常见的突变靶点中,PROTAC技术在临床前研究中已经成功实现了鼠类肉瘤病毒癌基因(kirsten rat sarcoma viral oncogene homolog,KRAS)、表皮生长因子受体(epidermal growth factor receptor,EGFR)和间变性淋巴瘤激酶(anaplastic lymphoma kinase,ALK)等蛋白的有效降解。PROTAC药物以其事件驱动的独特优势,有望克服小分子抑制剂产生的获得性耐药的问题,并对难成药靶点展现出良好的治疗潜力,有望成为NSCLC治疗的新策略。

A Rough Set Based Optimization Method for Elderly Evaluation

In order to improve the efficiency of elderly evaluation, an optimization method based on rough set is proposed. Compared with the traditional rough set attribute reduction, the redundant evaluation items are eliminated by items’ correlation. It avoids a big overhead of calculating the core of rough sets that have many attributes. A novel rule reduction method is proposed based on reliability and coverage, in order to solve the problem of rarely appeared rules and conflict rules in traditional rough set. A sorting algorithm based on coverage is used to optimize the traditional flat evaluation questionnaire model with a hierarchical order. By these optimizations, the number of items that need to evaluate is greatly reduced. The proposed approach is deployed in an elderly service company named Lime family. Real-life result shows that the method can reduce more than 40% items with over 90% accuracy prediction rate. Compared with decision tree and the method based on expert knowledge in reduction rate and accuracy rate, the method has same performance in one index, and 20% improvement on average in the other one.

The English Corner:an Effective Way to TBLT

本文探讨了任务型教学法在中国实施的现状以及英语教学中存在的问题, 并将课堂英语教学与英语角加以比较。研究表明英语角更有利于任务型教学的开展并且在发展学生口语交际技能及提高口语水平方面有其独到的优势。本文还就英语角的设计提出了一些可行的方法与建议。本论文的案例研究建立在天津财经大学英语学习俱乐部英语角活动的基础之上。

Integrative regulatory mechanisms of stomatal movements under changing climate

Global climate change-caused drought stress,high temperatures and other extreme weather profoundly impact plant growth and development,restricting sustainable crop production.To cope with various environmental stimuli,plants can optimize the opening and closing of stomata to balance CO_(2)uptake for photosynthesis and water loss from leaves.Guard cells perceive and integrate various signals to adjust stomatal pores through turgor pressure regulation.Molecular mechanisms and signaling networks underlying the stomatal movements in response to environmental stresses have been extensively studied and elucidated.This review focuses on the molecular mechanisms of stomatal movements mediated by abscisic acid,light,CO_(2),reactive oxygen species,pathogens,temperature,and other phytohormones.We discussed the significance of elucidating the integrative mechanisms that regulate stomatal movements in helping design smart crops with enhanced water use efficiency and resilience in a climate-changing world.

Regulation of the pore structure of carbon nanosheets based electrocatalyst for efficient polysulfides phase conversions

The practical applications of lithium-sulfur(Li-S)batteries are hampered by the sluggish redox kinetics and polysulfides shuttle in the cyclic process,which leads to a series of problems including the loss of active materials and poor cycling efficiency.In this paper,the pore structures of carbon nanosheets based electrocatalysts were precisely controlled by regulating the content of water-soluble KCl template.The relationship between pore structures and Li-S electrochemical behavior was studied,which demonstrates a key influence of pore structure in polysulfides phase conversions.In the liquid-sloid redox reaction of polysulfides,the micropores and small mesopores(d<20 nm)exhibited little impact,while the meso-pores(d>20 nm)and macropores played a decisive role.As a typical exhibition,the nickel-embedded carbon nanosheets(Ni-CNS)with a high content of large mesopores and macropores can aid Li-S batteries in exhibiting stable cycling performance(760.1 mAh g^(-1)at 1 C after 300 cycles)and superior rate capac-ity(847.8 mAh g^(-1)at 2 C).Furthermore,even with high sulfur loading(8 mg cm^(−2))and low electrolyte(E/S is around 6μL mg^(-1)),the high area capacity of 7.7 mAh cm^(−2)at 0.05 C could be achieved.This work can provide a guideline for the design of the pore structure of carbon-based electrocatalysts toward high-efficiency sulfur species redox reactions,and afford a general,controllable,and simple approach to constructing high performance Li-S batteries.

Cytokinin signaling promotes salt tolerance by modulating shoot chloride exclusion in maize

Excessive accumulation of chloride(Cl^(-))in the aboveground tissues under saline conditions is harmful to crops.Increasing the exclusion of Cl^(-) from shoots promotes salt tolerance in various crops.However,the underlying molecular mechanisms remain largely unknown.In this study,we demonstrated that a type A response regulator(ZmRR1)modulates Cl^(-) exclusion from shoots and underlies natural variation of salt tolerance in maize.ZmRR1 negatively regulates cytokinin signaling and salt tolerance,likely by interacting with and inhibiting His phosphotransfer(HP)proteins that are key mediators of cytokinin signaling.A naturally occurring non-synonymous SNP variant enhances the interaction between ZmRR1 and ZmHP2,conferring maize plants with a salt-hypersensitive phenotype.We found that ZmRR1 undergoes degradation under saline conditions,leading to the release of ZmHP2 from ZmRR1 inhibition,and subsequently ZmHP2-mediated signaling improves salt tolerance primarily by promoting Cl^(-) exclusion from shoots.Furthermore,we showed that ZmMATE29 is transcriptionally upregulated by ZmHP2-mediated signaling under highly saline conditions and encodes a tonoplast-located Cl^(-) transporter that promotes Cl^(-) exclusion from shoots by compartmentalizing Cl^(-) into the vacuoles of root cortex cells.Collectively,our study provides an important mechanistic understanding of the cytokinin signaling-mediated promotion of Cl^(-) exclusion from shoots and salt tolerance and suggests that genetic modification to promote Cl^(-) exclusion from shoots is a promising route for developing salt-tolerant maize.

双功能双位点单原子催化剂在可充电锌-空气电池氧电催化中的研究进展

可充电锌空气电池以其低成本和高能量密度而受到广泛关注.然而,其空气电极上发生的氧还原反应和氧析出反应的动力学缓慢且过程复杂,涉及四电子转移过程,这严重制约了可充电锌空气电池的大规模应用.碳载单原子催化剂在氧电催化领域展现出巨大的潜力,但其双功能氧电催化性能仍有待提高,这与活性位点的配位环境密切相关.相较于单位点单原子催化剂,双位点单原子催化剂可在原子水平上调整活性位点的配位环境,从而提高催化剂的双功能氧电催化性能.本文系统地总结了近年来双功能双位点碳载单原子催化剂在可充电锌-空气电池领域的研究进展.首先,阐述了氧电催化剂的催化机理和设计原则;随后讨论了金属-非金属原子协同策略和双金属原子协同策略在制备高性能双位点碳载单原子催化剂中的应用;最后,提出了双位点碳载单原子催化剂的发展前景和挑战,为合理设计高效双功能氧电催化剂提供了新思路.

Establishment and validation of a multigene model to predict the risk of relapse in hormone receptor-positive early-stage Chinese breast cancer patients

Background: Breast cancer patients who are positive for hormone receptor typically exhibit a favorable prognosis. It is controversial whether chemotherapy is necessary for them after surgery. Our study aimed to establish a multigene model to predict the relapse of hormone receptor-positive early-stage Chinese breast cancer after surgery and direct individualized application of chemotherapy in breast cancer patients after surgery. Methods: In this study, differentially expressed genes (DEGs) were identified between relapse and nonrelapse breast cancer groups based on RNA sequencing. Gene set enrichment analysis (GSEA) was performed to identify potential relapse-relevant pathways. CIBERSORT and Microenvironment Cell Populations-counter algorithms were used to analyze immune infiltration. The least absolute shrinkage and selection operator (LASSO) regression, log-rank tests, and multiple Cox regression were performed to identify prognostic signatures. A predictive model was developed and validated based on Kaplan-Meier analysis, receiver operating characteristic curve (ROC). Results: A total of 234 out of 487 patients were enrolled in this study, and 1588 DEGs were identified between the relapse and nonrelapse groups. GSEA results showed that immune-related pathways were enriched in the nonrelapse group, whereas cell cycle- and metabolism-relevant pathways were enriched in the relapse group. A predictive model was developed using three genes ( CKMT1B , SMR3B , and OR11M1P ) generated from the LASSO regression. The model stratified breast cancer patients into high- and low-risk subgroups with significantly different prognostic statuses, and our model was independent of other clinical factors. Time-dependent ROC showed high predictive performance of the model. Conclusions: A multigene model was established from RNA-sequencing data to direct risk classification and predict relapse of hormone receptor-positive breast cancer in Chinese patients. Utilization of the model could provide individualized evaluation of chemotherapy after surgery for breast cancer patients.

A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples

Background:Microsatellite instability(MSI)is a key biomarker for cancer immunotherapy and prognosis.Integration of MSI testing into a next-generation-sequencing(NGS)panel could save tissue sample,reduce turn-around time and cost,and provide MSI status and comprehensive genomic profiling in single test.We aimed to develop an MSI calling model to detect MSI status along with the NGS panel-based profiling test using tumor-only samples.Methods:From January 2019 to December 2020,a total of 174 colorectal cancer(CRC)patients were enrolled,including 31 MSI-high(MSI-H)and 143 microsatellite stability(MSS)cases.Among them,56 paired tumor and normal samples(10 MSI-H and 46 MSS)were used for modeling,and another 118 tumor-only samples were used for validation.MSI polymerase chain reaction(MSI-PCR)was performed as the gold standard.A baseline was built for the selected microsatellite loci using the NGS data of 56 normal blood samples.An MSI detection model was constructed by analyzing the NGS data of tissue samples.The performance of the model was compared with the results of MSI-PCR.Results:We first intersected the target genomic regions of the NGS panels used in this study to select common microsatellite loci.A total of 42 loci including 23 mononucleotide repeat sites and 19 longer repeat sites were candidates for modeling.As mononucleotide repeat sites are more sensitive and specific for detecting MSI status than sites with longer length motif and the mononucleotide repeat sites performed even better than the total sites,a model containing 23 mononucleotide repeat sites was constructed and named Colorectal Cancer Microsatellite Instability test(CRC-MSI).The model achieved 100%sensitivity and 100%specificity when compared with MSI-PCR in both training and validation sets.Furthermore,the CRC-MSI model was robust with the tumor content as low as 6%.In addition,8 out of 10 MSI-H samples showed alternations in the four mismatch repair genes(MLH1,MSH2,MSH6,and PMS2).Conclusion:MSI status can be accurately determined along the targeted NGS panels using only tumor samples.The performance of mononucleotide repeat sites surpasses loci with longer repeat motif in MSI calling.

JUNO sensitivity on proton decay p→νK^(+)searches

The Jiangmen Underground Neutrino Observatory(JUNO)is a large liquid scintillator detector designed to explore many topics in fundamental physics.In this study,the potential of searching for proton decay in the p→νK^(+)mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification.Moreover,the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals.Based on these advantages,the detection efficiency for the proton decay via p→νK^(+)is 36.9%±4.9%with a background level of 0.2±0.05(syst)±0.2(stat)events after 10 years of data collection.The estimated sensitivity based on 200 kton-years of exposure is 9.6×1033 years,which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies.

Developing Thick Cardiac Tissue with a Multilayer Fiber Sheet for Treating Myocardial Infarction

Human-induced pluripotent stem cell (hiPSC)-derived cardiac patches have been extensively used for treating myocardialinfarction and have shown potential for clinical application. However, the limited patch thickness can hamper its therapeuticeffect. We previously developed a fibrous scaffold that allowed the formation of well-organized cardiac tissue constructs. Inthe present study, based on the above technology, we developed a three-dimensional multilayer fibrous scaffold with dynamicperfusion, on which approximately 20 million hiPSC-derived cardiomyocytes (CMs) could be seeded in a single step andorganized into 1 mm thick and viable tissue. The multilayer cardiac tissue demonstrated enhanced contractile properties andupregulated cytokine secretion compared with the control group. Notably, when used on the myocardial infarction model,the multilayer group showed improved functional recovery and less fibrosis. These results indicated that the appropriatehiPSC-CM dose requires careful evaluation in developing clinical therapy. The multilayer cardiac tissue group demonstratedsignificant improvement than the control group, indicating that higher doses of transplanted cells may have improvedtherapeutic effects in treating myocardial infarction.

健康管理服务模式的发展趋势

健康管理经历了多年的发展,在国外已经成为医疗服务体系中不可或缺的一部分。我国的健康管理正处于创新发展阶段,近年来,无论在理论研究还是实践探索等方面都有了很大进步,但也存在一些问题。健康管理服务主要包括健康教育、健康体检、健康评估和健康干预。健康教育主要是被动的宣传教育,缺乏系统性健康教育;健康体检提供的服务产品单一,缺乏学术支撑;健康评估模型的研究处于起步阶段,多数为单病种风险预测模型;运动、营养和心理干预是健康干预的主要手段,但除了运动外,营养和心理干预与健康管理的融合目前不是很普遍。健康管理服务的收费标准依然不明确,一些保险机构设置的健康险尚未真正服务百姓,制约了健康管理服务的推广应用。随着信息化技术和健康保险行业的快速发展,健康医疗信息化和健康医疗大数据将出现有序整合,健康管理服务将以健康医疗大数据为基础,由商业健康保险推动和促进。未来,个体碎片化的健康医疗数据将被整合为人体全生命周期健康数据库,商业健康保险驱动的预防式健康管理将成为主要的健康管理服务模式。通过分析健康管理发生发展及现状,旨在探索健康管理服务模式的发展趋势。

Isolation and characterization of a novel mouse erythroid differentiation-denucleation related gene(MEDDF)

Using subtractive cDNA cloning method, a series of cDNA fragments have been isolated. One of them has been selected, that expressed differentially in the mouse intermediatelate erythroblasts, as a probe for the screening of mouse erythroid differentiation related gene from a cDNA library constructed from mouse mid-late erythroids. A positive cDNA clone has been obtained using phage in situ hybridization coupled with PCR technique. Sequencing of this cDNA by utilizing the Bluescript-SK( + ) phage vector system demonstrates that it has a full length of 505 bp with an open reading frame of 309 bp (from 53 to 359 bp) encoded a protein of 102 amino acids. There is a tailing signal AATAA at 462 bp and a 26-bp long poly A tail terminal at the 3′UTR. Searches of GenBank databases failed to find any homologous sequences (GenBank Accession Number: Banklt 180846 AF 060220) and it was proved to be a novel gene designated mouse erythroid differentiation-denucleation related gene (MEDDF). Northern blot analysis

Fabrication of Cr-doped SrTiO3/Ti-dopedα-Fe_(2)O_(3) photoanodes with enhanced photoelectrochemical properties

Cr-doped Sr TiO_(3)/Ti-dopedα-Fe_(2)O_(3) heterojunction has been constructed by an ingenious way,i.e.using segregation titanium oxide on the surface of the Ti-dopedα-Fe_(2)O_(3) electrode to in situ prepare Cr-doped SrTiO_(3).After construction of the heterojunction,the photocurrent onset potential for water oxidation on a Ti4+dopedα-Fe_(2)O_(3) cathodically shifts by about 100 mV.Moreover,the cathodic shift of the onset potential can be preserved well even after a long time running.The results indicate the effectiveness and credibility of the fabricated heterojunction.In order to make clear the reason for the onset potential shift,the asprepared Ti-dopedα-Fe_(2)O_(3) and Cr-doped SrTiO_(3)/Ti-dopedα-Fe_(2)O_(3) samples were investigated by X-ray photoelectron spectroscopy,electrochemical impedance spectroscopy,X-ray diffraction spectroscopy,etc.Based on the experimental evidences,it is proposed that cathodic shift of the onset potential is mainly due to the enhanced charge separation at the photoanode surface.This strategy can offer a reference to construct heterojunction on other films especially for those with surface segregation.