PEG4000/聚苯胺形状稳定复合相变材料的制备及其储热性能

以聚苯胺气凝胶(PANI)为支撑骨架,聚乙二醇4000(PEG4000)为相变材料,银纳米线(AgNWs)为导热增强填料,采用低温氧化聚合法和真空浸渍法制备得到具有良好形状和循环稳定性的定形相变复合材料PEG4000@Ag/PANI.聚苯胺气凝胶的高孔隙率及PEG4000与基体材料间的氢键作用和毛细作用,使得相变复合材料的最高负载率能够达到94.17%(熔融焓为165.17 J·g^(–1),凝固焓为152.77 J·g^(–1));加入AgNWs与PANI气凝胶共同搭建导热通路,提高了相变复合材料的导热性能(热导率最高为0.45 W·m^(–1)·K^(–1),比纯PEG4000提高80%);借助Ag NWs和聚苯胺优异的光吸收能力,相变复合材料的光–热转换效率达到90.61%.高储能密度、高光热转换能力和高热导率定形相变复合材料的成功制备为新型相变复合材料的合成提供了新思路,为太阳能光–热转换和储能应用提供了新材料,实现对太阳能的高效利用.

考虑相含量的TC17钛合金线性摩擦焊中的残余应力

为了获得准确的TC17钛合金线性摩擦焊中的残余应力,建立TC17钛合金弹性常数与相分数之间的数值关系。结合焊接区域的相分数,获得呈梯度分布的弹性常数,并将其引入轮廓法进行计算。结果表明,TC17钛合金的弹性常数与α相分数呈正相关,在宽度约4 mm的焊接区域呈现明显的梯度分布特征;若忽略相分数的梯度分布,计算残余应力时相对误差可达36.06%;修正后的残余应力呈双峰分布,在热影响区边缘处达到峰值,约为442 MPa。这说明考虑相分数的梯度分布是必要的。

基于多性状模型内蒙古绒山羊早期生长性状基因组预测准确性研究

内蒙古绒山羊是经过长期自然选择和人工选育后形成的优良家畜品种,是目前世界一流的绒肉兼用山羊。多性状动物模型被认为可以显著提高畜禽遗传评估的准确性,实现性状间的间接选择。本文基于内蒙古绒山羊个体的系谱、基因型、环境以及早期生长性状的表型记录,建立多性状动物模型,利用ABLUP、GBLUP、ssGBLUP三种方法进行早期生长性状(初生重、断乳重、断乳前平均日增重、周岁重)遗传参数及基因组育种值的估计,进一步利用五倍交叉验证方法评价基因组育种值估计准确性和可靠性。结果显示,3种方法估计的初生重遗传力为0.13~0.15,断乳重遗传力为0.13~0.20,日增重遗传力为0.11~0.14,周岁重遗传力为0.09~0.14,均属于中等偏低遗传力;断乳重和日增重、日增重和周岁重之间存在强的正遗传相关,相关系数分别为0.77~0.79和0.56~0.67,表型相关发现同样的规律;ABLUP、GBLUP和ssGBLUP法估计的初生重育种值准确性分别为0.5047、0.6694、0.7156,断乳重分别为0.6207、0.6456、0.7254;日增重分别为0.6110、0.6855、0.7357,周岁重分别为0.6209、0.7155、0.7756。综上所述,内蒙古绒山羊早期生长性状属于中等偏低遗传力,对其进行遗传选育改良速度相对较慢;通过对断乳重的选择可以实现其他生长性状的遗传改良;ssGBLUP方法估计内蒙古绒山羊早期生长性状基因组育种值的准确性和可靠性均最高,且显著高于ABLUP法,说明该方法是内蒙古绒山羊早期性状基因组选育的最佳方法。

Epidemiological and clinical features,treatment status,and economic burden of traumatic spinal cord injury in China:a hospital-based retrospective study

Traumatic spinal cord injury is potentially catastrophic and can lead to permanent disability or even death.China has the largest population of patients with traumatic spinal cord injury.Previous studies of traumatic spinal cord injury in China have mostly been regional in scope;national-level studies have been rare.To the best of our knowledge,no national-level study of treatment status and economic burden has been performed.This retrospective study aimed to examine the epidemiological and clinical features,treatment status,and economic burden of traumatic spinal cord injury in China at the national level.We included 13,465 traumatic spinal cord injury patients who were injured between January 2013 and December 2018 and treated in 30 hospitals in 11 provinces/municipalities representing all geographical divisions of China.Patient epidemiological and clinical features,treatment status,and total and daily costs were recorded.Trends in the percentage of traumatic spinal cord injuries among all hospitalized patients and among patients hospitalized in the orthopedic department and cost of care were assessed by annual percentage change using the Joinpoint Regression Program.The percentage of traumatic spinal cord injuries among all hospitalized patients and among patients hospitalized in the orthopedic department did not significantly change overall(annual percentage change,-0.5%and 2.1%,respectively).A total of 10,053(74.7%)patients underwent surgery.Only 2.8%of patients who underwent surgery did so within 24 hours of injury.A total of 2005(14.9%)patients were treated with high-dose(≥500 mg)methylprednisolone sodium succinate/methylprednisolone(MPSS/MP);615(4.6%)received it within 8 hours.The total cost for acute traumatic spinal cord injury decreased over the study period(-4.7%),while daily cost did not significantly change(1.0%increase).Our findings indicate that public health initiatives should aim at improving hospitals’ability to complete early surgery within 24 hours,which is associated with improved sensorimotor recovery,increasing the awareness rate of clinical guidelines related to high-dose MPSS/MP to reduce the use of the treatment with insufficient evidence.

Distinct molecular targets of ProEGCG from EGCG and superior inhibition of angiogenesis signaling pathways for treatment of endometriosis

Endometriosis is a common chronic gynecological disease with endometrial cell implantation outside the uterus.Angiogenesis is a major pathophysiology in endometriosis.Our previous studies have demonstrated that the prodrug of epigallocatechin gallate(ProEGCG)exhibits superior anti-endometriotic and anti-angiogenic effects compared to epigallocatechin gallate(EGCG).However,their direct binding targets and underlying mechanisms for the differential effects remain unknown.In this study,we demonstrated that oral ProEGCG can be effective in preventing and treating endometriosis.Additionally,1D and 2D Proteome Integral Solubility Alteration assay-based chemical proteomics identified metadherin(MTDH)and PX domain containing serine/threonine kinase-like(PXK)as novel binding targets of EGCG and ProEGCG,respectively.Computational simulation and BioLayer interferometry were used to confirm their binding affinity.Our results showed that MTDH-EGCG inhibited protein kinase B(Akt)-mediated angiogenesis,while PXK-ProEGCG inhibited epidermal growth factor(EGF)-mediated angiogenesis via the EGF/hypoxia-inducible factor(HIF-1a)/vascular endothelial growth factor(VEGF)pathway.In vitro and in vivo knockdown assays and microvascular network imaging further confirmed the involvement of these signaling pathways.Moreover,our study demonstrated that ProEGCG has superior therapeutic effects than EGCG by targeting distinct signal transduction pathways and may act as a novel antiangiogenic therapy for endometriosis.

Comparative analysis of thermodynamic and mechanical responses between underground hydrogen storage and compressed air energy storage in lined rock caverns

Underground hydrogen storage(UHS)and compressed air energy storage(CAES)are two viable largescale energy storage technologies for mitigating the intermittency of wind and solar power.Therefore,it is meaningful to compare the properties of hydrogen and air with typical thermodynamic storage processes.This study employs a multi-physical coupling model to compare the operations of CAES and UHS,integrating gas thermodynamics within caverns,thermal conduction,and mechanical deformation around rock caverns.Gas thermodynamic responses are validated using additional simulations and the field test data.Temperature and pressure variations of air and hydrogen within rock caverns exhibit similarities under both adiabatic and diabatic simulation modes.Hydrogen reaches higher temperature and pressure following gas charging stage compared to air,and the ideal gas assumption may lead to overestimation of gas temperature and pressure.Unlike steel lining of CAES,the sealing layer(fibre-reinforced plastic FRP)in UHS is prone to deformation but can effectively mitigates stress in the sealing layer.In CAES,the first principal stress on the surface of the sealing layer and concrete lining is tensile stress,whereas UHS exhibits compressive stress in the same areas.Our present research can provide references for the selection of energy storage methods.

Engineering of geometrical configurations in dual-atom catalysts for electrocatalytic applications

Geometrical configurations play a crucial role in dual-atom catalysts(DACs)for electrocatalytic applications.Significant progress has been made to design DACs electrocatalysts with various geometri-cal configurations,but in-depth understanding the relationship between geometrical configurations and metal-metal interaction mechanisms for designing targeted DACs is still required.In this review,the recent progress in engineering of geometrical configurations of DACs is systematically summarized.Based on the polarity of geometrical configuration,DACs can be classified into two different types that are homonuclear and heteronuclear DACs.Furthermore,with regard to the geometrical configurations of the active sites,homonuclear DACs are identified into adjacent and bridged configurations,and heteronuclear DACs can be classified into adjacent,bridged,and separated configurations.Subsequently,metal-metal interactions in DACs with different geometrical configurations are introduced.Additionally,the applications of DACs in different electrocatalytic reactions are discussed,including the oxygen reduction reaction(ORR),oxygen evolution reaction(OER),hydrogen evolution reaction(HER),and other catalysis.Finally,the future challenges and perspectives for advancements in DACs are high-lighted.This review aims to provide inspiration for the design of highly effcient DACs towards energy relatedapplications.

A Self-Healing Optoacoustic Patch with High Damage Threshold and Conversion Efficiency for Biomedical Applications

Compared with traditional piezoelectric ultrasonic devices,optoacoustic devices have unique advantages such as a simple preparation process,anti-electromagnetic interference,and wireless long-distance power supply.However,current optoacoustic devices remain limited due to a low damage threshold and energy conversion efficiency,which seriously hinder their widespread applications.In this study,using a self-healing polydimethylsiloxane(PDMS,Fe-Hpdca-PDMS)and carbon nanotube composite,a flexible optoacoustic patch is developed,which possesses the self-healing capability at room temperature,and can even recover from damage induced by cutting or laser irradiation.Moreover,this patch can generate high-intensity ultrasound(>25 MPa)without the focusing structure.The laser damage threshold is greater than 183.44 mJ cm^(-2),and the optoacoustic energy conversion efficiency reaches a major achievement at 10.66×10^(-3),compared with other carbon-based nanomaterials and PDMS composites.This patch is also been successfully examined in the application of acoustic flow,thrombolysis,and wireless energy harvesting.All findings in this study provides new insight into designing and fabricating of novel ultrasound devices for biomedical applications.

A novel live attenuated vaccine candidate protects chickens against subtype B avian metapneumovirus

Avian metapneumovirus(aMPV) is a highly contagious pathogen that causes acute upper respiratory tract diseases in chickens and turkeys, resulting in serious economic losses. Subtype B aMPV has recently become the dominant epidemic strain in China. We developed an attenuated aMPV subtype B strain by serial passaging in Vero cells and evaluated its safety and efficacy as a vaccine candidate. The safety test showed that after the 30th passage, the LN16-A strain was fully attenuated, as clinical signs of infection and histological lesions were absent after inoculation.The LN16-A strain did not revert to a virulent strain after five serial passages in chickens. The genomic sequence of LN16-A differed from that of the parent wild-type LN16(wtLN16) strain and had nine amino acid mutations. In chickens, a single immunization with LN16-A induced robust humoral and cellular immune responses, including the abundant production of neutralizing antibodies, CD4^(+) T lymphocytes, and the Th1(IFN-γ) and Th2(IL-4 and IL-6)cytokines. We also confirmed that LN16-A provided 100% protection against subtype B aMPV and significantly reduced viral shedding and turbinate inflammation. Our findings suggest that the LN16-A strain is a promising live attenuated vaccine candidate that can prevent infection with subtype B aMPV.

Energy beam-based direct and assisted polishing techniques for diamond:A review

Diamond is a highly valuable material with diverse industrial applications,particularly in the fields of semiconductor,optics,and high-power electronics.However,its high hardness and chemical stability make it difficult to realize high-efficiency and ultra-low damage machining of diamond.To address these challenges,several polishing methods have been developed for both single crystal diamond(SCD)and polycrystalline diamond(PCD),including mechanical,chemical,laser,and ion beam processing methods.In this review,the characteristics and application scope of various polishing technologies for SCD and PCD are highlighted.Specifically,various energy beam-based direct and assisted polishing technologies,such as laser polishing,ion beam polishing,plasma-assisted polishing,and laser-assisted polishing,are summarized.The current research progress,material removal mechanism,and infuencing factors of each polishing technology are analyzed.Although some of these methods can achieve high material removal rates or reduce surface roughness,no single method can meet all the requirements.Finally,the future development prospects and application directions of different polishing technologies are presented.

Assimilating FY-4A AGRI Radiances with a Channel-Sensitive Cloud Detection Scheme for the Analysis and Forecasting of Multiple Typhoons

This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager(AGRI)radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West Pacific Ocean using the 3DVar data assimilation(DA)method along with the WRF model.A channel-sensitive cloud detection scheme based on the particle filter(PF)algorithm is developed and examined against a cloud detection scheme using the multivariate and minimum residual(MMR)algorithm and another traditional cloud mask–dependent cloud detection scheme.Results show that both channel-sensitive cloud detection schemes are effective,while the PF scheme is able to reserve more pixels than the MMR scheme for the same channel.In general,the added value of AGRI radiances is confirmed when comparing with the control experiment without AGRI radiances.Moreover,it is found that the analysis fields of the PF experiment are mostly improved in terms of better depicting the typhoon,including the temperature,moisture,and dynamical conditions.The typhoon track forecast skill is improved with AGRI radiance DA,which could be explained by better simulating the upper trough.The impact of assimilating AGRI radiances on typhoon intensity forecasts is small.On the other hand,improved rainfall forecasts from AGRI DA experiments are found along with reduced errors for both the thermodynamic and moisture fields,albeit the improvements are limited.

The nitrogen transformation behavior based on the pyrolysis products of wheat stra

In order to provide basic design parameters for the industrial pyrolysis process,the transformation behavior of nitrogen was investigated using wheat straw as raw material.The distributions of nitrogen in pyrolysis char,oil,and gas were obtained and the nitrogenous components in the products were analyzed systematically by X-ray photoelectron spectroscopy(XPS),pyrolysis-gas chromatography/mass spectrometry(Py-GC/MS)and thermogravimetric-Fourier transform infrared spectrometry(TG-FTIR).The nitrogen distribution ranges of the pyrolysis char,oil,and gas were 37.34%–54.82%,32.87%–40.94%and 10.20%–28.83%,respectively.More nitrogen was retained in char at lower pyrolysis temperature and the nitrogen distribution of oil was from rise to decline with increasing temperature.The most abundant N-containing compounds in three-phase products were pyrrole-N,amines,and HCN,respectively.In addition,the transformation mechanism of nitrogen from wheat straw to pyrolysis products was concluded.

Evaluating two stages of silicone-containing arylene resin oxidation via experiment and molecular simulation

Silicon-containing aryl acetylene resin(PSA)is a new type of high-temperature resistant resin with excellent oxidation resistance,whereas antioxidant reaction mechanism of PSA resin under ultra-high temperatures still remains unclear.Herein,the oxidation behavior and mechanisms of PSA resin are systematically investigated combining kinetic analysis and Reax FF molecular dynamics(MD)simulations.Thermogravimetric analysis indicates that the oxidation process of PSA resin undergoes two main steps:oxidative mass gain and oxidative degradation.The distributed activation energy model(DAEM)is employed for describing oxidation processes and the best-fit one is obtained using genetic algorithms and differential evolution.DAEM model demonstrates that the oxidative weight gain stage is dominated by two virtual reactants and the oxidative degradation stage consists of three virtual reactants.Correspondingly,the observation of MD reaction pathways indicates that oxygen oxidation of unsaturated structures occurs in the initial stage,which results in the formation of PSA resin oxides.Furthermore,cracked pieces react with O_(2)to generate CO and other chemicals in the second step.The resin matrix's great antioxidation resilience is illustrated by the formation of SiO_(2).The analysis based on MD simulations exhibits an efficient computational proof with the experiments and DAEM methods.Based on the results,a two-stage reaction mechanism is proposed,which provides important theoretical support for the subsequent study of the oxidation behavior of silica-based resins.

Effectiveness and safety of combined nimotuzumab and S-1 chemotherapy with concurrent radiotherapy for locally advanced esophageal cancer in malnourished and elderly patients:A prospective phaseⅡstudy

Objective:Definitive chemoradiotherapy(dCRT)is the standard treatment for unresectable locally advanced esophageal cancer.However,this treatment is associated with substantial toxicity,and most malnourished or elderly patients are unable to complete this therapy.Therefore,there is a need for a more suitable radiotherapy combination regimen for this population.This study was aimed to evaluate the efficacy and safety of a combination regimen comprising chemotherapy with nimotuzumab and S-1 and concurrent radiotherapy for patients with fragile locally advanced esophageal cancer with a high Nutritional Risk Screening 2002(NRS-2002)score.Methods:Eligible patients with unresectable esophageal carcinoma who had an NRS-2002 score of 2 or higher were enrolled.They were treated with S-1 and nimotuzumab with concurrent radiotherapy,followed by surgery or definitive radiotherapy.The primary endpoint was the locoregional control(LRC)rate.Results:A total of 55 patients who met the study criteria were enrolled.After completion of treatment,surgery was performed in 15 patients and radiotherapy was continued in 40 patients.The median follow-up period was 33.3[95%confidence interval(95%CI,31.4−35.1)]months.The LRC rate was 77.2%(95%CI,66.6%−89.4%)at 1 year in the entire population.The overall survival(OS)rate and event-free survival(EFS)rate were 57.5%and 51.5%at 3 years,respectively.Surgery was associated with better LRC[hazard ratio(HR)=0.16;95%CI,0.04−0.70;P=0.015],OS(HR=0.19;95%CI,0.04−0.80;P=0.024),and EFS(HR=0.25;95%CI,0.08−0.75;P=0.013).Most adverse events were of grade 1 or 2,and no severe adverse events occurred.Conclusions:For malnourished or elderly patients with locally advanced esophageal cancer,radiotherapy combined with nimotuzumab and S-1 is effective and has a good safety profile.

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex problems.Given the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

Multiframe-integrated, in-sensor computing using persistent photoconductivity

The utilization of processing capabilities within the detector holds significant promise in addressing energy consumption and latency challenges. Especially in the context of dynamic motion recognition tasks, where substantial data transfers are necessitated by the generation of extensive information and the need for frame-by-frame analysis. Herein, we present a novel approach for dynamic motion recognition, leveraging a spatial-temporal in-sensor computing system rooted in multiframe integration by employing photodetector. Our approach introduced a retinomorphic MoS_(2) photodetector device for motion detection and analysis. The device enables the generation of informative final states, nonlinearly embedding both past and present frames. Subsequent multiply-accumulate (MAC) calculations are efficiently performed as the classifier. When evaluating our devices for target detection and direction classification, we achieved an impressive recognition accuracy of 93.5%. By eliminating the need for frame-by-frame analysis, our system not only achieves high precision but also facilitates energy-efficient in-sensor computing.

Experimental study of core MHD behavior and a novel algorithm for rational surface detection based on profile reflectometry in EAST

Microwave reflectometry is a powerful diagnostic that can measure the density profile and localized turbulence with high spatial and temporal resolution and will be used in ITER,so understanding the influence of plasma perturbations on the reflect signal is important.The characteristics of the reflect signal from profile reflectometry,the time-of-flight(TOF)signal associated with the MHD instabilities,are investigated in EAST.Using a 1D full-wave simulation code by the Finite-DifferenceTime-Domain(FDTD)method,it is well validated that the local density flattening could induce the discontinuity of the simulated TOF signal and an obvious change of reflect amplitude.Experimental TOF signals under different types of MHD instabilities(sawtooth,sawtooth precursors and tearing mode)are studied in detail and show agreement with the simulation.Two new improved algorithms for detecting and localizing the radial positions of the low-order rational surface,the cross-correlation and gradient threshold(CGT)method and the 2D convolutional neural network approach(CNN)are presented for the first time.It is concluded that TOF signal analysis from profile reflectometry can provide a straightforward and localized measurement of the plasma perturbation from the edge to the core simultaneously and may be a complement or correction to the q-profile control,which will be beneficial for the advanced tokamak operation.

Wetting-drying effect on the strength and microstructure of cementphosphogypsum stabilized soils

Phosphogypsum has often been used as an effective and environmentally friendly binder for partial replacement of cement,improving the engineering properties of slurries with high water content.However,the influence of phosphogypsum on the physicomechnical properties of stabilized soil subjected to wettingedrying cycles is not well understood to date.In this study,the effect of phosphogypsum on the durability of stabilized soil was studied by conducting a series of laboratory experiments,illustrating the changes in mass loss,pH value and unconfined compressive strength(qu)with wettingdrying cycles.The test results showed that the presence of phosphogypsum significantly restrained the mass loss in the early stage(lower than the 4th cycle),which in turn led to a higher qu of stabilized soil than that without phosphogypsum.After the 4th cycle,a sudden increase in mass loss was observed for stabilized soil with phosphogypsum,resulting in a significant drop in qu to a value lower than those without phosphogypsum at the 6th cycle.In addition,the qu of stabilized soils correlated well with the measured soil pH irrespective of phosphogypsum content for all wettingedrying tests.According to the microstructure observation via scanning electron microscope(SEM)and X-ray diffraction(XRD)tests,the mechanisms relating the sudden loss of qu for the stabilized soils with phosphogypsum after the 4th wetting-drying cycle are summarized as follows:(i)the disappearance of ettringite weakening the cementation bonding effect,(ii)the generation of a larger extent of microcrack,and(iii)a lower pH value,in comparison with the stabilized soil without phosphogypsum.

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges.