Optimization Control of Multi-Mode Coupling All-Wheel Drive System for Hybrid Vehicle

The all-wheel drive(AWD)hybrid system is a research focus on high-performance new energy vehicles that can meet the demands of dynamic performance and passing ability.Simultaneous optimization of the power and economy of hybrid vehicles becomes an issue.A unique multi-mode coupling(MMC)AWD hybrid system is presented to realize the distributed and centralized driving of the front and rear axles to achieve vectored distribution and full utilization of the system power between the axles of vehicles.Based on the parameters of the benchmarking model of a hybrid vehicle,the best model-predictive control-based energy management strategy is proposed.First,the drive system model was built after the analysis of the MMC-AWD’s drive modes.Next,three fundamental strategies were established to address power distribution adjustment and battery SOC maintenance when the SOC changed,which was followed by the design of a road driving force observer.Then,the energy consumption rate in the average time domain was processed before designing the minimum fuel consumption controller based on the equivalent fuel consumption coefficient.Finally,the advantage of the MMC-AWD was confirmed by comparison with the dynamic performance and economy of the BYD Song PLUS DMI-AWD.The findings indicate that,in comparison to the comparative hybrid system at road adhesion coefficients of 0.8 and 0.6,the MMC-AWD’s capacity to accelerate increases by 5.26%and 7.92%,respectively.When the road adhesion coefficient is 0.8,0.6,and 0.4,the maximum climbing ability increases by 14.22%,12.88%,and 4.55%,respectively.As a result,the dynamic performance is greatly enhanced,and the fuel savings rate per 100 km of mileage reaches 12.06%,which is also very economical.The proposed control strategies for the new hybrid AWD vehicle can optimize the power and economy simultaneously.

不同EMS处理时间对大豆诱变后代主要品质含量变化影响分析

为探究不同EMS处理时间对大豆诱变后代主要品质含量变化的影响,文章利用0.5%EMS溶液处理大豆高蛋白品系公交1057-1,分别浸泡4、7和10 h(清水冲洗处理为对照),对播种后获得的连续4代诱变后代主要品质含量变化进行分析。结果表明,与对照相较,经EMS处理后的植株成活率随处理时间延长而降低。其中,经EMS-4处理后的植株成活率最高,为43.5%;经EMS-10处理后的植株成活率最低,仅为16.0%。不同EMS处理时间对大豆诱变后代的蛋白质含量影响显著,对脂肪含量影响不明显。其中经EMS-4处理的诱变后代蛋白质含量高于其他3组处理;经EMS-4处理后的M2代蛋白质含量发生显著分离,并出现超亲个体,脂肪含量变化不显著。

甲基磺酸乙酯(EMS)对谷子种子及幼苗活力的影响

为了探明甲基磺酸乙酯(EMS)诱变嫩选18种子构建突变体库的最适条件,加快品种选育进程,本研究对嫩选18种子进行了3种处理时间、3种EMS处理浓度的化学诱导,并对M1种子发芽及幼苗生长的诱变效应进行研究。结果表明:与对照相比,EMS处理在浓度0.4%下浸种6 h对嫩选18的发芽率及幼苗生长影响差异不显著,随着EMS浸种浓度、时间增加,种子萌发及幼苗生长逐渐受到抑制,在1.2%浓度下浸种14 h对种子萌发及幼苗生长抑制作用最强,极大降低了嫩选18的发芽势、发芽率、成苗率,并且导致幼苗生长缓慢。以存活率达到50%为标准,通过回归方程计算出在6 h、10 h、14 h浸种时间下,EMS浓度的半致死剂量分别为0.99%、0.72%、0.38%,可作为嫩选18 EMS诱变建立突变体库的适合条件。

达乌里胡枝子愈伤组织及种子EMS诱变研究

为优化达乌里胡枝子愈伤诱导培养基的激素含量及比例,明确甲基磺酸乙酯(EMS)诱变愈伤组织及种子的最佳条件,本研究以达乌里胡枝子种子为外植体,探究了不同激素配比对愈伤诱导的影响,并针对愈伤组织和种子处理分别设置了两时间两浓度(2 h和6 h,0.3%和0.9%)及三时间两浓度(6 h、8 h、10 h,0.4%、0.8%)的EMS处理时间和浓度的组合,研究各处理对愈伤分化系数和后期植株成活率以及种子发芽率、发芽势和幼苗表型变异的影响。结果表明,达乌里胡枝子种子愈伤的最佳激素配比为0.25 mg/L NAA+0.5 mg/L 6-BA+0.5 mg/L 2,4-D,此时达乌里胡枝子愈伤诱导率为94.9%。EMS诱变达乌里胡枝子愈伤组织的适宜浓度为0.3%,处理时间为6 h,分化系数和植株相对成活率分别为46.31%和47.78%,接近半致死范围,且生根数、根长和平均株高等指标与高浓度EMS处理相比受到的负面影响较小。EMS诱变达乌里胡枝子种子的适宜浓度为0.8%,处理时间10 h,发芽率、出苗率、成苗率分别为53.61%、51.06%和53.28%,均接近半致死量,同时发现多株幼苗叶片出现了明显的形态变异。本试验在达乌里胡枝子原有种质资源基础上,丰富了达乌里胡枝子突变体库,也为后续开展达乌里胡枝子诱变育种研究提供理论依据。

EMS诱变对鹰嘴紫云英种子萌发及幼苗表型特征的影响

【目的】筛选适宜鹰嘴紫云英的EMS诱变条件。【方法】以鹰嘴紫云英品种甘绿2号种子为试验材料,采用不同浓度(0、0.2%、0.4%、0.6%、0.8%)的甲基磺酸乙酯(EMS)进行不同时间(2、4、6、8 h)的诱变处理,探究EMS对鹰嘴紫云英种子萌发特征及表型变化的影响。【结果】低浓度和短时间EMS处理促进鹰嘴紫云英种子的萌发,随EMS浓度升高和诱变时间的增加,对鹰嘴紫云英种子萌发产生抑制作用。种子浸出液电导率随诱变条件的加深呈上升趋势,在2~6 h时,萌发期发芽率、发芽势、幼苗苗长和根长均随处理时间和诱变浓度的增加呈先升高后降低的趋势,在8 h处理下,随EMS浓度的增加呈逐渐降低趋势,EMS浓度在0.8%时,种子发芽率和发芽势均达到最低,较对照分别降低了54.45%和56.67%;经形态学筛选,发现有鹰嘴紫云英幼苗表现出幼苗矮小、停滞生长、叶片黄化、宽叶、窄叶、叶片发紫、诸多病斑等特殊变异性状。【结论】0.8%EMS处理6 h可作为最佳诱变组合;幼苗的生长随诱变时间和浓度增加而明显受到抑制,且表型变异类型也逐步增多。

芒果^(60)Co-γ、EMS诱变及SC-SSR分子标记遗传多样性分析

诱变育种是短时间内增加物种遗传多样性和表型变异的最有效方法之一。为探明诱变创制芒果突变体基因库可行性,本研究以凯特芒果为试验材料,通过^(60)Co-γ射线辐射枝条和EMS溶液浸泡种子创制诱变群体材料,利用SC-SSR分子标记进行遗传多样性分析。结果表明:^(60)Co-γ射线辐射半致死剂量为31.37 Gy,0.2%EMS溶液浸泡半致死时间为5.9 h;利用16对SC-SSR引物分析100份诱变材料和1份凯特材料的遗传多样性,共检测出117个多态性位点,引物多态性条带百分比、多态性信息含量(PIC)、观测等位基因数(Na)、有效等位基因数(Ne)、Nei’s基因多样性指数(H)和Shannon’s信息指数(I)平均值分别为93.18%、0.610、1.923、1.583、0.334和0.493;试验材料间遗传相似系数在0.373~0.984之间,平均为0.779。诱变增加了芒果遗传信息,其中EMS诱变种子变异更大,本研究结果为芒果诱变育种提供了理论依据。

基于EMS管理模式的延续性护理在学龄前喘息性疾病儿童中的应用观察

目的·探讨基于EMS[环境管理(environment management,E)、用药指导(medicine direction,M)与自我监测(self monitoring,S)]管理模式的延续性护理在学龄前喘息性疾病儿童中的应用效果。方法·选取2019年12月至2020年11月,在上海交通大学医学院附属儿童医院呼吸科收治的67例0~6岁喘息性疾病患儿,按照随机数字表分为观察组33例和对照组34例,其中失访3例,最终每组32例。观察组采用基于EMS管理模式的延续性护理,对照组给予常规护理和出院电话随访。2组患儿出院后1、3、6个月随访评估儿童呼吸和哮喘测试(Test for Respiratory and Asthma Control in Kids,TRACK)结果、喘息复发情况;出院后6个月随访采用支气管哮喘用药依从性评分表(Medication Adherence Report Scale for Asthma,MARS-A)和护理工作满意度调查表评估用药依从性及护理工作满意度。结果·2组患儿人口学特征及临床基线特征差异无统计学意义。重复测量方差分析结果显示,时间、组别、组别×时间的交互作用对TRACK总分的影响均有统计学意义;出院后1、3、6个月,观察组TRACK总分均显著高于对照组(均P=0.000);2组患儿TRACK总分均随时间推移逐渐上升(P=0.000)。观察组1、3、6个月随访发现喘息复发率分别为25.0%、18.7%、9.4%,均显著低于对照组(分别为50.0%、43.7%、31.3%,均P<0.05);广义估计方程分析显示组间比较差异有统计学意义(P=0.013),观察组干预效果优于对照组(OR=0.292)。出院后6个月观察组MARS-A得分为(4.519±0.395)分,显著高于对照组[(3.994±0.739)分,P=0.001]。护理工作满意度调查结果显示,观察组显著高于对照组(P=0.000)。患儿MARS-A得分与护理工作满意度呈中度正相关(r=0.389,P=0.001)。结论·基于EMS管理模式的延续性护理可显著提高学龄前喘息性疾病儿童的用药依从性和喘息控制水平,明显降低喘息复发率,以及提高护理工作满意度。

籽用美洲南瓜EMS诱变突变体库的构建及表型分析

【目的】构建籽用美洲南瓜突变体库,加快籽用美洲南瓜种质资源创新进程,对南瓜品种选育、品种改良以及遗传基础的拓宽具有重要的意义。【方法】利用1.8%诱变剂甲基磺酸乙酯(EMS)处理籽用美洲南瓜ZHL4种子15 h,然后对M_(1)和M_(2)代群体单株进行表型变异观察,同时对M_(2)群体变异株系ZHL4-33进行显微组织结构观察。【结果】(1)M_(2)群体中共筛选到242个突变植株,45种表型变异,变异类型涵盖了突变株的各个生长时期以及各植物器官,总的突变频率达到25.17%。(2)突变体叶片栅栏组织厚度显著高于野生型,排列紧凑,维管形成层痕迹明显;突变体茎维管束多而密集,导管直径小于野生型,髓部发达,细胞间隙较小,细胞数目有所增加。【结论】初步构建了由425个M_(2)家系所组成的籽用美洲南瓜突变体库,为籽用美洲南瓜功能基因组研究和新品种选育奠定了材料基础。

EMS诱变对大麦种子萌发及M_(1)代植株成熟期主要性状的影响

为探究甲基磺酸乙酯(EMS)对大麦种子萌发及M_(1)代植株成熟期主要表型性状突变的影响,以啤酒大麦品种新啤6号为材料,分别用0.00%、0.05%、0.10%、0.15%和0.20%的EMS浸种10 h,分析各浓度EMS处理对种子发芽势、发芽率、致死率、畸变率、幼苗叶绿素含量、根系活力和形态指标的影响,记录0.10%EMS诱变后M_(1)代成熟期植株主要性状的突变类型和突变频率。结果表明,EMS明显抑制种子萌发和幼苗生长,并产生了大量的性状突变。与对照相比,0.10%EMS浸种显著降低了种子发芽势、发芽率、幼苗叶绿素含量和根系活力,致死率和畸变率显著提高;0.15%和0.20%EMS浸种显著降低了幼苗根和芽的长度、鲜重和干重,胚芽鞘干重显著提高。田间统计发现,0.10%EMS处理的M_(1)代植株主要突变性状集中在茎秆、叶片、穗形和育性等方面,产生了红秆、矮秆、红叶、芒卷、穗畸形、结实率低和分蘖少等性状,突变频率分别20.17%、4.87%、1.08%、16.67%、0.94%、14.00%和6.02%。因此,通过EMS诱变构建大麦突变体库和创制种质资源。

不同浓度EMS诱变不结球白菜的效果分析

为创制不结球白菜新种质,发掘新基因,探索不同浓度甲基磺酸乙酯(ethyl methane sulfonate,EMS)对不结球白菜的诱变效应。采用浓度为0.4%、0.6%和0.8%的EMS溶液对4个不结球白菜品种[黑塌菜(HTC)、香青菜(XQC)、JP241、XWZ]进行种子诱变处理,调查种子发芽情况与田间植株农艺性状表现。结果表明:4个不结球白菜品种的种子发芽势、发芽率和相对成苗率均随着EMS浓度的升高而逐渐降低,且处理间差异显著。EMS诱变可以引起不结球白菜叶色、叶形、株型、花器官等性状发生变异。不同品种不结球白菜的EMS诱变半致死剂量有所不同,产生的变异种类和变异频率也有所不同,HTC的半致死剂量为0.8%,相对变异频率为23.83%;XQC的半致死剂量为0.8%,相对变异频率为17.61%;JP241的半致死剂量为0.6%,相对变异频率为38.45%;XWZ的半致死剂量为0.6%,相对变异频率16.69%。EMS的浓度越高,诱变的不结球白菜始花开放时间越晚,莲座叶叶片数越少,雄性不育率越高。

EMS诱变的水稻不同位点突变体对ALS抑制剂类除草剂抗性差异

稻田杂草严重威胁水稻生长,培育抗除草剂水稻新品种,是高效解决稻田杂草危害的重要途径之一。本研究利用甲基磺酸乙酯(EMS)对华占水稻进行化学诱变,创建突变体,利用乙酰乳酸合成酶(ALS)抑制剂类除草剂甲咪唑烟酸(20 g/hm 2,有效成分)对突变体进行筛选,获得抗甲咪唑烟酸突变体材料,并对上述突变体的OsALS基因序列进行分析,明确其突变类型。最后对不同突变类型对甲氧咪草烟和甲基二磺隆的交互抗性进行分析。结果表明,华占水稻经EMS诱变和甲咪唑烟酸筛选后共获得11株抗甲咪唑烟酸突变体材料,其突变类型为Pro171Leu、Ser627Cys、Ser627Asn和Gly628Glu 4种。其中,Ser627Cys为首次发现的突变类型。4种突变类型对甲咪唑烟酸的抗性水平存在一定的差异,Ser627Asn、Ser627Cys、Pro171Leu、Gly628Glu突变类型的抗性指数分别为8.71、5.16、3.28和3.69。4种突变类型对甲氧咪草烟和甲基二磺隆的抗性亦存在显著差异。其中,Ser627Asn突变类型对甲氧咪草烟的抗性最高,抗性指数为20.57,Gly628Glu对甲基二磺隆抗性最高,抗性指数为5.11。综上,本研究通过EMS诱变获得了4种抗ALS抑制剂类除草剂的华占水稻突变类型,并鉴定了其对甲咪唑烟酸的抗性差异及对甲氧咪草烟和甲基二磺隆的交互抗性,为进一步的抗除草剂水稻品种培育和除草剂轮换使用提供依据。

EMS诱变菜豆子叶节定向筛选耐羟脯氨酸(HYP)突变体

以双丰一号菜豆子叶节为外植体,利用化学诱变剂EMS处理引发基因突变,进行突变体定向筛选抗逆突变细胞系。以0.17%EMS诱变处理2 h,子叶节的不再生率接近50%;以羟脯氨酸最大致死量3.5 mmol/L为筛选压力,定向筛选抗逆突变体。结果显示,在羟脯氨酸筛选培养基上,经EMS诱变的子叶节存活31个,突变率为8.61%,存活的子叶节再生率为74.19%,成功获得耐羟脯氨酸的突变株系。

上海某院EMS转运急性缺血性脑卒中患者院前延误的回顾性研究

目的 探究启动EMS(emergency medical service,紧急医疗服务)转运的急性缺血性脑卒中患者院前延误的影响因素,为急性缺血性脑卒中患者减少延误提高策略。方法 对132例启动EMS的急性缺血性脑卒中患者进行相关影响因素分析,包括年龄、性别、呼救时天气情况、脑卒中知识认知度,首发症状等,分为延误组(n=29)和及时组(n=103),通过多因素Logistics回归分析确定造成院前延误的影响因素。结果 两组患者在不同天气情况、卒中知识认知度、首发症状上存在差异(P<0.05)。多因素Logistics回归分析显示天气情况(OR=0.581,95%CI:0.358~0.943),卒中知识认知度(OR=0.238,95%CI:0.098~0.578)及首发症状为意识障碍(OR=0.076,95%CI:0.008~0.717)是减少院前延误的独立影响因素(P<0.05)。结论 较高卒中知识认知度、首发症状有意识障碍、天气情况良好有利于减少启动EMS转运的急性缺血性脑卒中患者的院前延误。因此,加强公众卒中知识普及培训,提高公众卒中意识,尽快启动EMS系统,可减少院前延误,改善患者预后。

EMS诱变处理对洋葱种子萌发的影响及其变异表型的观察

以中原地区洋葱主要品种“钻石红N3”种子为试材,采用不同浓度(0%~1.7%)的甲基磺酸乙酯(EMS)和不同浸泡时长(6、9、12、14、15、16、18 h)进行诱变处理,分析EMS处理对洋葱种子发芽势、相对发芽势、发芽率及相对发芽率的影响,以确定洋葱EMS处理的最优条件,以期为选育具有自主知识产权的洋葱新品种提供参考依据。结果表明:随着EMS浓度(0%~1.7%)的提高,种子的发芽势、相对发芽势、发芽率和相对发芽率均呈逐渐降低趋势,与对照相比,差异均达极显著水平;在相同EMS浓度下,随着浸泡时间的延长(9、12、14、15、16、18 h),种子的发芽势和发芽率均显著降低;但当EMS处理时间为6 h、浓度为0.5%~1.7%和EMS处理时间为15 h、浓度为0.5%~0.8%时,洋葱种子的发芽率和相对发芽率与对照相比均有所提高,但差异均未达显著水平,说明在该范围内EMS处理起到促进作用,即低浓度或短时间的EMS处理对种子发芽有轻微促进作用。以半致死浓度作为诱变标准,洋葱诱变育种时,最终确定浓度1.7%、浸泡16 h为EMS诱变洋葱品种“钻石红N3”及构建突变体库的最佳条件。EMS诱变处理可导致洋葱幼苗发生变异,主要表现有幼苗黄化、叶管皱缩、茎基部不规则膨大等。

保护装置交流回路EMS测试对源影响的研究

在继电保护电磁兼容标准中,对于保护装置交流回路端口有严格的电磁兼容抗扰度试验要求。作为一种辅助设备或回路——给保护装置交流采样回路加激励量的“源”,必须保持“干净”,这是抗干扰性能测试的重要影响因素。“源”干净与否,会对测试结果本身产生重要影响。本文旨在分析这些影响原因,并对如何消除影响提出了一些建议。

Generative Multi-Modal Mutual Enhancement Video Semantic Communications

Recently,there have been significant advancements in the study of semantic communication in single-modal scenarios.However,the ability to process information in multi-modal environments remains limited.Inspired by the research and applications of natural language processing across different modalities,our goal is to accurately extract frame-level semantic information from videos and ultimately transmit high-quality videos.Specifically,we propose a deep learning-basedMulti-ModalMutual Enhancement Video Semantic Communication system,called M3E-VSC.Built upon a VectorQuantized Generative AdversarialNetwork(VQGAN),our systemaims to leverage mutual enhancement among different modalities by using text as the main carrier of transmission.With it,the semantic information can be extracted fromkey-frame images and audio of the video and performdifferential value to ensure that the extracted text conveys accurate semantic information with fewer bits,thus improving the capacity of the system.Furthermore,a multi-frame semantic detection module is designed to facilitate semantic transitions during video generation.Simulation results demonstrate that our proposed model maintains high robustness in complex noise environments,particularly in low signal-to-noise ratio conditions,significantly improving the accuracy and speed of semantic transmission in video communication by approximately 50 percent.

Fake News Detection Based on Text-Modal Dominance and Fusing Multiple Multi-Model Clues

In recent years,how to efficiently and accurately identify multi-model fake news has become more challenging.First,multi-model data provides more evidence but not all are equally important.Secondly,social structure information has proven to be effective in fake news detection and how to combine it while reducing the noise information is critical.Unfortunately,existing approaches fail to handle these problems.This paper proposes a multi-model fake news detection framework based on Tex-modal Dominance and fusing Multiple Multi-model Cues(TD-MMC),which utilizes three valuable multi-model clues:text-model importance,text-image complementary,and text-image inconsistency.TD-MMC is dominated by textural content and assisted by image information while using social network information to enhance text representation.To reduce the irrelevant social structure’s information interference,we use a unidirectional cross-modal attention mechanism to selectively learn the social structure’s features.A cross-modal attention mechanism is adopted to obtain text-image cross-modal features while retaining textual features to reduce the loss of important information.In addition,TD-MMC employs a new multi-model loss to improve the model’s generalization ability.Extensive experiments have been conducted on two public real-world English and Chinese datasets,and the results show that our proposed model outperforms the state-of-the-art methods on classification evaluation metrics.

Artificial-intelligent-powered safety and efficiency improvement for controlling and scheduling in integrated railway systems

The multi-mode integrated railway system,anchored by the high-speed railway,caters to the diverse travel requirements both within and between cities,offering safe,comfortable,punctual,and eco-friendly transportation services.With the expansion of the railway networks,enhancing the efficiency and safety of the comprehensive system has become a crucial issue in the advanced development of railway transportation.In light of the prevailing application of artificial intelligence technologies within railway systems,this study leverages large model technology characterized by robust learning capabilities,efficient associative abilities,and linkage analysis to propose an Artificial-intelligent(AI)-powered railway control and dispatching system.This system is elaborately designed with four core functions,including global optimum unattended dispatching,synergetic transportation in multiple modes,high-speed automatic control,and precise maintenance decision and execution.The deployment pathway and essential tasks of the system are further delineated,alongside the challenges and obstacles encountered.The AI-powered system promises a significant enhancement in the operational efficiency and safety of the composite railway system,ensuring a more effective alignment between transportation services and passenger demands.

Modeling the Physical Parameters of Solenoids for MEMS Applications

The paper is devoted to study of the electrical parameters of the motion parts of the MEMS such as solenoids. The analytical background is given in order to describe the influence of the electrical field components on the forces, which are result of interaction of the electromagnetic (EM) field components with the parts of motion devices of MEMS. The given analytical formulas open the ability to calculate the self-inductance of the microsolenoids of the different kind, as well as the stored energy of such motion devices, that could be used for the modeling and optimization of parameters of running devices of MEMS such as actuators, sensors etc.

监控画面信号自动巡视技术在电化学储能EMS中的应用

电化学储能电站普遍采用组态型EMS,通过查看监控画面实现对储能电站电池、BMS、PCS、消防等设备运行状态的监视。提出一种在锂离子电化学储能电站EMS系统中自动巡视监控画面数据的方法,通过周期性自动扫描监控画面上的设备运行数据,识别信号点的数据品质类型,将设备的实时状态数据与健康特征值做对比,主动发现画面上遥测越限、数据不刷新、封锁、遥测遥信不匹配等异常数据,识别异常设备,生成异常数据报告。通过采用这种画面自动巡视技术,可以减轻储能电站监控员的画面监盘工作压力,提高储能电站的运行效率和安全性。