Hybrid model based on K-means++ algorithm, optimal similar day approach, and long short-term memory neural network for short-term photovoltaic power prediction

Photovoltaic(PV) power generation is characterized by randomness and intermittency due to weather changes.Consequently, large-scale PV power connections to the grid can threaten the stable operation of the power system. An effective method to resolve this problem is to accurately predict PV power. In this study, an innovative short-term hybrid prediction model(i.e., HKSL) of PV power is established. The model combines K-means++, optimal similar day approach,and long short-term memory(LSTM) network. Historical power data and meteorological factors are utilized. This model searches for the best similar day based on the results of classifying weather types. Then, the data of similar day are inputted into the LSTM network to predict PV power. The validity of the hybrid model is verified based on the datasets from a PV power station in Shandong Province, China. Four evaluation indices, mean absolute error, root mean square error(RMSE),normalized RMSE, and mean absolute deviation, are employed to assess the performance of the HKSL model. The RMSE of the proposed model compared with those of Elman, LSTM, HSE(hybrid model combining similar day approach and Elman), HSL(hybrid model combining similar day approach and LSTM), and HKSE(hybrid model combining K-means++,similar day approach, and LSTM) decreases by 66.73%, 70.22%, 65.59%, 70.51%, and 18.40%, respectively. This proves the reliability and excellent performance of the proposed hybrid model in predicting power.

颈椎前路Hybrid手术和颈椎后路单开门椎管扩大成形术治疗多节段脊髓型颈椎病临床疗效分析

目的:分析颈椎前路Hybrid手术和颈椎后路单开门椎管扩大成形术(EODL)治疗多节段脊髓型颈椎病的疗效,探讨多节段脊髓型颈椎病患者手术方式的选择。方法:对2017年7月—2020年7月在首都医科大学附属北京中医医院手术治疗的70例多节段脊髓型颈椎病患者进行回顾性分析,根据手术方式不同,分为前路组35例和后路组35例,前路组患者行Hybrid手术[颈椎前路椎间盘切除融合术(ACDF)联合人工颈椎间盘置换术(ACDR)],后路组患者行EODL。记录2组患者住院时间、手术时间、术中出血量和术后引流量,通过日本骨科协会(JOA)评分、JOA改善率、颈椎残障功能指数(NDI)、疼痛视觉模拟评分(VAS)和术后满意度评分进行疗效评价,统计2组患者术后并发症发生情况。结果:与后路组比较,前路组患者术中出血量、术后引流量、住院时间和手术时间均明显减少(P<0.01),术前各项评分差异无统计学意义(P>0.05)。末次随访时,与后路组比较,前路组患者JOA评分和JOA改善率明显升高(P<0.01),NDI评分和VAS评分明显降低(P<0.01)。与术前比较,末次随访时2组患者JOA评分明显升高(P<0.01),NDI和VAS评分均明显降低(P<0.01)。按术后满意度评分评价,2组患者术后满意度均较高。2组患者术后并发症发生率比较差异无统计学意义(P>0.05)。结论:颈椎前路Hybrid手术和EODL在治疗多节段脊髓型颈椎病方面均取得了较为满意的疗效。Hybrid手术具有出血量少和手术时间短等优点,临床上应根据患者实际情况选择最适宜的术式。

Multilevel optoelectronic hybrid memory based on N-doped Ge_(2)Sb_(2)Te_(5)film with low resistance drift and ultrafast speed

Multilevel phase-change memory is an attractive technology to increase storage capacity and density owing to its high-speed,scalable and non-volatile characteristics.However,the contradiction between thermal stability and operation speed is one of key factors to restrain the development of phase-change memory.Here,N-doped Ge_(2)Sb_(2)Te_(5)-based optoelectronic hybrid memory is proposed to simultaneously implement high thermal stability and ultrafast operation speed.The picosecond laser is adopted to write/erase information based on reversible phase transition characteristics whereas the resistance is detected to perform information readout.Results show that when N content is 27.4 at.%,N-doped Ge_(2)Sb_(2)Te_(5)film possesses high ten-year data retention temperature of 175℃and low resistance drift coefficient of 0.00024 at 85℃,0.00170 at 120℃,and 0.00249 at 150℃,respectively,owing to the formation of Ge–N,Sb–N,and Te–N bonds.The SET/RESET operation speeds of the film reach 520 ps/13 ps.In parallel,the reversible switching cycle of the corresponding device is realized with the resistance ratio of three orders of magnitude.Four-level reversible resistance states induced by various crystallization degrees are also obtained together with low resistance drift coefficients.Therefore,the N-doped Ge_(2)Sb_(2)Te_(5)thin film is a promising phase-change material for ultrafast multilevel optoelectronic hybrid storage.

Activation Redistribution Based Hybrid Asymmetric Quantization Method of Neural Networks

The demand for adopting neural networks in resource-constrained embedded devices is continuously increasing.Quantization is one of the most promising solutions to reduce computational cost and memory storage on embedded devices.In order to reduce the complexity and overhead of deploying neural networks on Integeronly hardware,most current quantization methods use a symmetric quantization mapping strategy to quantize a floating-point neural network into an integer network.However,although symmetric quantization has the advantage of easier implementation,it is sub-optimal for cases where the range could be skewed and not symmetric.This often comes at the cost of lower accuracy.This paper proposed an activation redistribution-based hybrid asymmetric quantizationmethod for neural networks.The proposedmethod takes data distribution into consideration and can resolve the contradiction between the quantization accuracy and the ease of implementation,balance the trade-off between clipping range and quantization resolution,and thus improve the accuracy of the quantized neural network.The experimental results indicate that the accuracy of the proposed method is 2.02%and 5.52%higher than the traditional symmetric quantization method for classification and detection tasks,respectively.The proposed method paves the way for computationally intensive neural network models to be deployed on devices with limited computing resources.Codes will be available on https://github.com/ycjcy/Hybrid-Asymmetric-Quantization.

基于Hybrid A^(*)算法的变压器声级巡检系统研究与设计

随着国内变电站数目逐步增加,采用固定式声级监测终端对变压器声级检测的方式已经满足不了日常检测的需求。为解决固定式声级监测终端方式成本高、维护复杂、设备利用率低等问题,该文率先提出了一种变压器声级巡检系统,并设计了最优声级巡检路径。通过场地定位传感器生成变压器场地栅格图信息,采用Hybrid A^(*)算法将场地栅格图信息生成符合国标所要求的最优声级巡检路径检测点;针对所开发的变压器声级巡检装置,采用生成的巡检路径对变压器进行声级测定作业,对测定的声级数据进行分析处理。测试结果表明,该文开发的系统与设计算法的变压器声级巡检时间、检测效率以及数据的采集准确性都优于固定式声级监测终端方式,系统完成变压器声级巡检全过程的成功率可达95%。

复杂建设环境下基于Hybrid A^(*)算法的铁路平面线形绿色优化设计

随着“双碳经济下绿色铁路”理念的兴起,将“绿色生态”融入到铁路平面线路优化已成为近年来的研究热点。本文以铁路建设成本与生态破坏成本的协同优化为目标,引入并改进了一种自动驾驶导航算法(Hybrid A^(*)算法),以适应复杂的铁路设计问题,同时考虑最小曲线半径、最大曲线半径、最短曲线长度、最短夹直线长度、缓和曲线长度等铁路线形约束。研究结果表明:(1)改进后算法以离散网格方式整合外部环境因素,实现渐进式全局探索,获取接近全局最优的铁路线路设计结果;(2)该方法在复杂外部环境约束下,无需预设水平交点位置和数量,可自动生成符合线路-环境耦合约束的优化平面线路方案。

p-d Orbital Hybridization Engineered Single-Atom Catalyst for Electrocatalytic Ammonia Synthesis

The rational design of metal single-atom catalysts(SACs)for electrochemical nitrogen reduction reaction(NRR)is challenging.Two-dimensional metal-organic frameworks(2DMOFs)is a unique class of promising SACs.Up to now,the roles of individual metals,coordination atoms,and their synergy effect on the electroanalytic performance remain unclear.Therefore,in this work,a series of 2DMOFs with different metals and coordinating atoms are systematically investigated as electrocatalysts for ammonia synthesis using density functional theory calculations.For a specific metal,a proper metal-intermediate atoms p-d orbital hybridization interaction strength is found to be a key indicator for their NRR catalytic activities.The hybridization interaction strength can be quantitatively described with the p-/d-band center energy difference(Δd-p),which is found to be a sufficient descriptor for both the p-d hybridization strength and the NRR performance.The maximum free energy change(ΔG_(max))andΔd-p have a volcanic relationship with OsC_(4)(Se)_(4)located at the apex of the volcanic curve,showing the best NRR performance.The asymmetrical coordination environment could regulate the band structure subtly in terms of band overlap and positions.This work may shed new light on the application of orbital engineering in electrocatalytic NRR activity and especially promotes the rational design for SACs.

Machine learning-assisted efficient design of Cu-based shape memory alloy with specific phase transition temperature

The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance.In this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored data.Component modeling and feature modeling were used to predict the phase transition temperature of the shape memory alloys.The experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)model.The results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition temperature.On this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between atoms.This work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.

Enhancing rock fragmentation prediction in mining operations:A hybrid GWO-RF model with SHAP interpretability

In the mining industry,precise forecasting of rock fragmentation is critical for optimising blasting processes.In this study,we address the challenge of enhancing rock fragmentation assessment by developing a novel hybrid predictive model named GWO-RF.This model combines the grey wolf optimization(GWO)algorithm with the random forest(RF)technique to predict the D_(80)value,a critical parameter in evaluating rock fragmentation quality.The study is conducted using a dataset from Sarcheshmeh Copper Mine,employing six different swarm sizes for the GWO-RF hybrid model construction.The GWO-RF model’s hyperparameters are systematically optimized within established bounds,and its performance is rigorously evaluated using multiple evaluation metrics.The results show that the GWO-RF hybrid model has higher predictive skills,exceeding traditional models in terms of accuracy.Furthermore,the interpretability of the GWO-RF model is enhanced through the utilization of SHapley Additive exPlanations(SHAP)values.The insights gained from this research contribute to optimizing blasting operations and rock fragmentation outcomes in the mining industry.

Electrostatic Interaction-directed Construction of Hierarchical Nanostructured Carbon Composite with Dual Electrical Conductive Networks for Zinc-ion Hybrid Capacitors with Ultrastability

Metal-organic framework(MOF)-derived carbon composites have been considered as the promising materials for energy storage.However,the construction of MOF-based composites with highly controllable mode via the liquid-liquid synthesis method has a great challenge because of the simultaneous heterogeneous nucleation on substrates and the self-nucleation of individual MOF nanocrystals in the liquid phase.Herein,we report a bidirectional electrostatic generated self-assembly strategy to achieve the precisely controlled coatings of single-layer nanoscale MOFs on a range of substrates,including carbon nanotubes(CNTs),graphene oxide(GO),MXene,layered double hydroxides(LDHs),MOFs,and SiO_(2).The obtained MOF-based nanostructured carbon composite exhibits the hierarchical porosity(V_(meso)/V_(micro)∶2.4),ultrahigh N content of 12.4 at.%and"dual electrical conductive networks."The assembled aqueous zinc-ion hybrid capacitor(ZIC)with the prepared nanocarbon composite as a cathode shows a high specific capacitance of 236 F g^(-1)at 0.5 A g^(-1),great rate performance of 98 F g^(-1)at 100 A g^(-1),and especially,an ultralong cycling stability up to 230000 cycles with the capacitance retention of 90.1%.This work develops a repeatable and general method for the controlled construction of MOF coatings on various functional substrates and further fabricates carbon composites for ZICs with ultrastability.

Astrocytic endothelin-1 overexpression impairs learning and memory ability in ischemic stroke via altered hippocampal neurogenesis and lipid metabolism

Vascular etiology is the second most prevalent cause of cognitive impairment globally.Endothelin-1,which is produced and secreted by endothelial cells and astrocytes,is implicated in the pathogenesis of stroke.However,the way in which changes in astrocytic endothelin-1 lead to poststroke cognitive deficits following transient middle cerebral artery occlusion is not well understood.Here,using mice in which astrocytic endothelin-1 was overexpressed,we found that the selective overexpression of endothelin-1 by astrocytic cells led to ischemic stroke-related dementia(1 hour of ischemia;7 days,28 days,or 3 months of reperfusion).We also revealed that astrocytic endothelin-1 overexpression contributed to the role of neural stem cell proliferation but impaired neurogenesis in the dentate gyrus of the hippocampus after middle cerebral artery occlusion.Comprehensive proteome profiles and western blot analysis confirmed that levels of glial fibrillary acidic protein and peroxiredoxin 6,which were differentially expressed in the brain,were significantly increased in mice with astrocytic endothelin-1 overexpression in comparison with wild-type mice 28 days after ischemic stroke.Moreover,the levels of the enriched differentially expressed proteins were closely related to lipid metabolism,as indicated by Kyoto Encyclopedia of Genes and Genomes pathway analysis.Liquid chromatography-mass spectrometry nontargeted metabolite profiling of brain tissues showed that astrocytic endothelin-1 overexpression altered lipid metabolism products such as glycerol phosphatidylcholine,sphingomyelin,and phosphatidic acid.Overall,this study demonstrates that astrocytic endothelin-1 overexpression can impair hippocampal neurogenesis and that it is correlated with lipid metabolism in poststroke cognitive dysfunction.

Hybrid model for BOF oxygen blowing time prediction based on oxygen balance mechanism and deep neural network

The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.

Promotion of structural plasticity in area V2 of visual cortex prevents against object recognition memory deficits in aging and Alzheimer's disease rodents

Memory deficit,which is often associated with aging and many psychiatric,neurological,and neurodegenerative diseases,has been a challenging issue for treatment.Up till now,all potential drug candidates have failed to produce satisfa ctory effects.Therefore,in the search for a solution,we found that a treatment with the gene corresponding to the RGS14414protein in visual area V2,a brain area connected with brain circuits of the ventral stream and the medial temporal lobe,which is crucial for object recognition memory(ORM),can induce enhancement of ORM.In this study,we demonstrated that the same treatment with RGS14414in visual area V2,which is relatively unaffected in neurodegenerative diseases such as Alzheimer s disease,produced longlasting enhancement of ORM in young animals and prevent ORM deficits in rodent models of aging and Alzheimer’s disease.Furthermore,we found that the prevention of memory deficits was mediated through the upregulation of neuronal arbo rization and spine density,as well as an increase in brain-derived neurotrophic factor(BDNF).A knockdown of BDNF gene in RGS14414-treated aging rats and Alzheimer s disease model mice caused complete loss in the upregulation of neuronal structural plasticity and in the prevention of ORM deficits.These findings suggest that BDNF-mediated neuronal structural plasticity in area V2 is crucial in the prevention of memory deficits in RGS14414-treated rodent models of aging and Alzheimer’s disease.Therefore,our findings of RGS14414gene-mediated activation of neuronal circuits in visual area V2 have therapeutic relevance in the treatment of memory deficits.

Between the City and Images:An Analysis of Mainstream Media’s Paths of Constructing the Cultural Memory of a City:Taking Chengdu Radio and Television’s“Hi Chengdu”as an Example

Mainstream media play a crucial role in constructing the cultural memory of a city.This study used 319 short videos released by“Hi Chengdu,”a new media product of Chengdu Radio and Television,as samples.Based on the grounded theory,a research framework encompassing“content,technology,and discourse”was established to explore the paths through which mainstream media construct the cultural memory.Regarding content,this paper emphasized temporal and spatial contexts and urban spaces,delving deep into the themes of the cultural memory and vehicles for it.In terms of technology,this paper discussed the practice of leveraging audio/visual-mode discourse to stitch together the impressions of a city and evoke emotional resonance to create a“flow”of memory.As for discourse,this paper looked at the performance of a communication ritual to frame concepts and shape urban identity.It is essential to break free from conventional thinking and leverage local culture as the primary driving force to further boost a city’s productivity,in order to excel in cultural communication.

Production traits and fertility of reciprocal hybrids between Argopecten irradians irradians and A.i.concentricus

The two bay scallop subspecies,Argopecten irradians irradians(NN)and A.i.concentricus(SS),are fast growing and major cultured bivalves in China.However,their relatively small sizes and decreasing production traits caused by long-term inbreeding have been major concerns to the industry in the last two decades.Hybridization between the two bay scallop subspecies may provide a new approach to breed a new variety with superior production traits for the industry.For this end,in this study,we hybridized the two bay scallop subspecies in order to obtain a new strain that incorporates the genes of both subspecies.No significant difference was found in fertilization rate,hatching rate and metamorphosis rate between the purebred and crossbred cohorts(NN♀×SS♂,denoted as NS;SS♀×NN♂,denoted as SN).Both mating strategy(intra-vs.inter-population crosses)and egg origin had significant effects on growth and survival at the larval stage.Heterosis was observed in the crossbred and was more pronounced in older stages.Genetic diversity of the reciprocal hybrids,especially that of SN,was increased compared with the purebred cohorts.Almost all hybrids were completely fertile and able to reproduce by selffertilization or by backcrossing with either parent.Apparently,male sterile individuals whose gonads were fully occupied by the ovary part at mature stage were found in the hybrids for the first time.The hybrids,especially SN,may provide precious germplasm resources for the production of ternary hybrids with the Peruvian scallop,A.purpuratus.

Total Fat, Fatty Acid Composition, Tocopherol and Tocotrienol Profiles in Fermented Beans of Ten Controlled Pollinated Cocoa (Theobroma cacao L.) Hybrids from Cameroon

This study aimed to discriminate ten Cameroonian cocoa hybrids according to their total fat, fatty acid composition, tocopherol and tocotrienol profiles. Six cocoa clones from the gene banks of the Cameroon Cocoa Development Corporation were used to create hybrids. The determination of fatty acid composition was carried out by using a gas chromatography (GC) apparatus coupled by a flame ion detector (FID). Tocopherol and tocotrienol analysis was performed by upper high-performance liquid chromatography (UHPLC). Information on the impact of the genotype on the cocoa fat composition was provided. The major fatty acids (FA) in fermented samples are stearic (34.57%), palmitic (26.13%), oleic (34.13%) and linoleic (3.16%) acids. (35.05% to 35.6%). SCA12 × ICS40, SCA12 × SNK13, SNK13 × T79/501 have the least hard cocoa butters. Tocopherols analysis showed a predominance of γ-tocopherols (94.64 ± 1.51 to 292.16 ± 3.17 µg∙g−1), whereas only a small amount of β and δ-tocopherol (from 0.46 to 2.78 µg∙g−1 and 0.12 to 5.82 respectively) was observed. No γ-tocotrienol was found in fermented samples. A differentiation in terms of total fat and tocopherol content was observed amongst hybrids with the same mother-clone, suggesting an impact of pollen on these compounds.

Integrating HPWS and Organisational Memory for Enhanced Employee Performance

This research paper investigates the relationship between high-performance work systems(HPWS),organisational memory,and employee in-role performance,focus-ing on the direct impact of HPWS on different dimensions of organisational memory and employee in-role performance,as well as the mediating role of organisational memory in this relationship.Utilizing a sample of employees working in the tele-communications industry,the study employed structural equation modelling to ana-lyse the relationships among HPWS,organisational memory,and employee in-role performance.The findings revealed that HPWS positively influence all three dimen-sions of organisational memory and employee in-role performance,with organisa-tional memory partially mediating the relationship between HPWS and employee in-role performance.However,the study was limited to the telecommunications industry and Dhofar region and did not examine the potential moderating effects of individual-level or contextual factors on the relationships among HPWS,organisa-tional memory,and employee in-role performance.The study offers practical impli-cations for organizations seeking to improve employee performance and overall effectiveness by highlighting the importance of implementing high-performance work systems and managing organisational memory effectively.This study contrib-utes to the literature on the relationships among HPWS,organisational memory,and employee in-role performance,providing valuable insights into the dynamics of organisational effectiveness.

Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

Recent progress of hybrid cathode interface layer for organic solar cells

Organic solar cells(OSCs)have gained conspicuous progress during the past few decades due to the development of materials and upgrading of the device structure.The power conversion efficiency(PCE)of the single-junction device had surpassed 19%.The cathode interface layer(CIL),by optimizing the connection between the active layer and the cathode electrode,has become a momentous part to strengthen the performances of the OSCs.Simultaneously,CIL is also indispensable to illustrating the working mechanism of OSCs and enhancing the stability of the OSCs.In this essay,hybrid CILs in OSCs have been summarized.Firstly,the advancement and operating mechanism of OSCs,and the effects and relevant design rules of CIL are briefly concluded;secondly,the significant influence of CIL on enhancing the stability and PCE of OSCs is presented;thirdly,the characteristics of organic hybrid CIL and organic-inorganic hybrid CIL are introduced.Finally,the conclusion and outlook of CIL are summarized.

Hybrid Skin-Topological Effect Induced by Eight-Site Cells and Arbitrary Adjustment of the Localization of Topological Edge States

Hybrid skin-topological effect(HSTE)in non-Hermitian systems exhibits both the skin effect and topological protection,offering a novel mechanism for localization of topological edge states(TESs)in electrons,circuits,and photons.However,it remains unclear whether the HSTE can be realized in quasicrystals.