车联网基于信任度的RSU识别及资源分配算法

在车联网中,由于部分路侧单元（RSU）的位置比较偏远,无法得到网络管理员的及时维护,可能遭到攻击,变为不可信任的路侧单元,降低了车辆的通信质量和网络能效.为了有效地识别RSU的可靠性,提出了一种基于信任度的路侧单元识别及资源分配算法,将路侧单元识别、传输模式的选择和功率分配联合建模为网络能效的优化问题,并分成3个子优化问题,分别求解.首先,采用基于信任度的RSU识别算法,识别出可信任和不可信任的路侧单元;其次,优化车辆资源块配置和链路选择;最后,通过次梯度算法优化传输功率,最大化网络能效.理论分析和仿真结果表明,所提算法具备较低的复杂度,可以达到较高的路侧单元识别准确度,并有效地提升网络总能效.     

多孔纤维型重整微反应器的等效电阻网络建模

针对应用于重整制氢微反应器的复杂多孔金属纤维载体（PFS）的流速场高效分析难题,建立载体中随机微通道的等效电阻网络分析模型. 基于复杂随机纤维结构的统计网络模型,将纤维载体中三维联通的随机微通道结构及与之相连的进出口腔简化为规则的网络通道结构.借鉴基尔霍夫定律,建立纤维载体的等效电阻网络模型,并确定求解方法. 纤维载体流速场实例分析的结果表明,基于等效电阻网络模型求解的纤维载体流速场与计算流体力学(CFD)方法的结果之间的皮尔森相关系数约为98%,且求解效率约为CFD方法的2.9×10⁴倍. 研究成果为多孔纤维型重整制氢微反应器的设计制造提供了新的支撑方案.     

振荡翼改进运动模型的能量捕获性能分析

为了提高振荡水翼的水动力性能和能量捕获效率,基于传统简谐运动模型提出改进运动模型,通过引入俯仰运动系数k,推导改进后俯仰运动规律的一般形式,利用Fluent软件建立水翼的二维模型,综合分析半主动振荡模型下不同俯仰运动系数、折算频率和俯仰振幅等运动参数对水翼能量捕获性能的影响。结果表明:与传统简谐运动模型相比,改进运动模型能够使水翼升力系数在较长时间段内维持较大数值,提高水翼的升力系数和捕能效率;在相同的折算频率和俯仰振幅下,减小俯仰运动系数会增大俯仰角转动的角速度,进而增大俯仰运动所消耗的能量;不同俯仰振幅下对应不同的最优折算频率,折算频率越低水翼的捕能性能越不稳定,俯仰振幅越大,转动俯仰角所消耗的能量越多。在给定参数条件下,水翼的能量转化效率可超过40%。     

Future energy goals for Maryland: Greenhouse gas reductions

Legislative requirements in Maryland set very robust goals for the implementation of energy efficiency by utilities. Significant energy savings has been achieved in all customer sectors and efficiency gains have been made over time in equipment and building construction. Looking forward, utilities should implement programs to promote energy efficiency with a greater emphasis on GHG reductions. Feasibility studies need to occur, but flexibility is key given changing codes and standards and market transformation.     

Interpretable modeling of metallurgical responses for an industrial coal column flotation circuit by XGBoost and SHAP-A “conscious-lab” development

Surprisingly, no investigation has been explored relationships between operating variables and metallurgical responses of coal column flotation (CF) circuits based on industrial databases for under operation plants. As a novel approach, this study implemented a conscious-lab “CL” for filling this gap. In this approach, for developing the CL dedicated to an industrial CF circuit, SHapley Additive exPlanations (SHAP) and extreme gradient boosting (XGBoost) were powerful unique machine learning systems for the first time considered. These explainable artificial intelligence models could effectively convert the dataset to a basis that improves human capabilities for better understanding, reasoning, and planning the unit. SHAP could provide precise multivariable correlation assessments between the CF dataset by using the Tabas Parvadeh coal plant (Kerman, Iran), and showed the importance of solid percentage and washing water on the metallurgical responses of the coal CF circuit. XGBoost could predict metallurgical responses (R-square > 0.88) based on operating variables that showed quite higher accuracy than typical modeling methods (Random Forest and support vector regression).     

Environmental and climate justice and technological carbon removal

Environmental justice (EJ) and climate justice are becoming central foci of climate policy. Awareness is also growing on the need for some amount of carbon dioxide removal (CDR) to curb warming to 1.5 °C. In this paper we map dimensions of environmental and climate justice that stakeholders and communities will need to consider -- from local to global scales. Mapping issues is a step towards developing frameworks to undertake CDR in an environmentally just way.     

A combo technology of autotrophic and heterotrophic denitrification processes for groundwater treatment

In this study,a sequential process (heterotrophic up-flow column and completely mixed membrane bioreactors) was proposed combining advantages of the both processes.The system was operated for 249 days with simulated and real groundwater for nitrate removal at concentrations varying from 25 to 145 mg·L-1 NO3-N.The contribution of heterotrophic process to total nitrate removal in the system was controlled by dozing the ethanol considering the nitrate concentration.By this way,sulfur based autotrophic denitrification rate was decreased and the effluent sulfate concentrations were controlled.The alkalinity requirement in the autotrophic process was produced in the heterotrophic reactor,and the system was operated without alkalinity supplementation.Throughout the study,the chemical oxygen demand in the heterotrophic reactor effluent was (23.7 ± 22) mg·L-1 and it was further decreased to(7.5 ± 7.2) mg·L-1 in the system effluent,corresponding to a 70％ reduction.In the last period of the study,the real groundwater containing 145 mg·L-1 NO3-N was completely removed.Membrane was operated without chemical washing in the first 114 days.Between days 115-249 weekly chemical washing was required.     

Formation of Proto-Kranz in C3 Rice Induced by Spike-Stalk Injection Method

Introduction of C4 photosynthetic traits into C3 crops is an important strategy for improving photosynthetic capacity and productivity. Here, we report the research results of a variant line of sorghum–rice (SR) plant with big panicle and high spikelet density by introducing sorghum genome DNA into rice by spike-stalk injection. The whole-genome resequencing showed that a few sorghum genes could be integrated into the rice genome. Gene expression was confirmed for two C4 photosynthetic enzymes containing pyruvate, orthophosphate dikinase and phosphoenolpyruvate carboxykinase. Exogenous sorghum DNA integration induced a series of key traits associated with the C4 pathway called “proto-Kranz” anatomy, including leaf thickness, bundle sheath number and size, and chloroplast size in bundle sheath cells. Significantly, transgenic plants exhibited enhanced photosynthetic capacity resulting from both photosynthetic CO₂-concentrating effect and improved energy balance, which led to an increase in carbohydrate levels and productivity. Furthermore, such rice plant exhibited delayed leaf senescence. In summary, this study provides a proof for the feasibility of inducing the transition from C3 leaf anatomy to proto-Kranz by spike-stalk injection to achieve efficient photosynthesis and increase productivity.     

An electrochemical method for the preparation of Mg–Li alloys at low temperature molten salt system

Mg–Li alloys have been prepared by electrolysis in a molten salt electrolyte of 50% LiCl–50% KCl (mass%) at low temperature of 420–510 °C. The effects of electrolytic temperature and cathodic current density on alloy formation rate and current efficiency were studied. For the deposition of metallic lithium on the cathode consisting of solid Mg and liquid Mg–Li, both electrolytic temperature and cathodic current density have no obvious influence on current efficiency; while for the deposition of metallic lithium on the solid magnesium cathode, both electrolytic temperature and cathodic current density greatly affect alloy formation rate and current efficiency. The optimum electrolysis condition is—molten salt mixture, LiCl:KCl = 1:1 (mass%), electrolytic temperature: 480 °C, cathode current density: 1.13 A cm⁻². Mg–Li alloys with low lithium content (about 25 wt% Li) were prepared via electrolysis at low temperature following by thermal treatment at higher temperature.     

高温熔融-电感耦合等离子体原子发射光谱法测定含铁尘泥中5种有害元素

准确、快速地测定含铁尘泥中有害元素,对含铁尘泥节能降废项目研究及综合利用有着重要的指导意义。实验针对含铁尘泥试样因含碳量高,导致常规酸溶解方法如果不增加除碳步骤则很难完全分解试样的问题,采用高温熔融法将试样制成熔融液后倾倒于稀酸中溶解的方法,解决了碳含量高难溶解的问题。采用四硼酸锂-碳酸锂混合熔剂在高温下将试样熔融,熔融液高温倾倒于稀酸中制成澄清溶液,由于骤冷,试样炸裂成微小玻璃珠,无迸溅,操作简单,使得后续溶解过程快速完成,从而建立了电感耦合等离子体原子发射光谱(ICP-AES)测定P、Pb、K、Na、Zn共5种有害元素的方法。按照实验方法测定含铁尘泥中P、Pb、K、Na、Zn,测定值的相对标准偏差(RSD,n=9)在1.4%～5.7%之间,加标回收率在96%～110%之间。研究结果表明方法能够满足含铁尘泥样品中5种元素的定量分析要求。