Eco-Physic: Eco-Physical design initiative for very large databases

In the Big Data Era, the management of energy consumption by servers and data centers has become a challenging issue for companies, institutions, and countries. In data-centric applications, Database Management Systems are one of the major energy consumers when executing complex queries involving very large databases. Several initiatives have been proposed to deal with this issue, covering both the hardware and software dimensions. They can be classified in two main approaches assuming that either (a) the database is already deployed on a given platform, or (b) it is not yet deployed. In this study, we focus on the first set of initiatives with a particular interest in physical design, where optimization structures (e.g., indexes, materialized views) are selected to satisfy a given set of non-functional requirements such as query performance for a given workload. In this paper, we first propose an initiative, called Eco-Physic, which integrates the energy dimension into the physical design when selecting materialized views, one of the redundant optimization structures. Secondly, we provide a multi-objective formalization of the materialized view selection problem, considering two non-functional requirements: query performance and energy consumption while executing a given workload. Thirdly, an evolutionary algorithm is developed to solve the problem. This algorithm differs from the existing ones by being interactive, so that database administrators can adjust some energy sensitive parameters at the final stage of the algorithm execution according to their specifications. Finally, intensive experiments are conducted using our mathematical cost model and a real device for energy measurements. Results underscore the value of our approach as an effective way to save energy while optimizing queries through materialized views structures.     

An overview of utilizing water-in-diesel emulsion fuel in diesel engine and its potential research study

The need for more efficient energy usage and a less polluted environment are the prominent research areas that are currently being investigated by many researchers worldwide. Water-in-diesel emulsion fuel (W/D) is a promising alternative fuel that could fulfills such requests in that it can improve the combustion efficiency of a diesel engine and reduce harmful exhaust emission, especially nitrogen oxides (NO_x) and particulate matter (PM). To date, there have been many W/D emulsion fuel studies, especially regarding performance, emissions and micro-explosion phenomena. This review paper gathers and discusses the recent advances in emulsion fuel studies in respect of the impact of W/D emulsion fuel on the performance and emission of diesel engines, micro-explosion phenomena especially the factors that affecting the onset and strength of micro-explosion process, and proposed potential research area in W/D emulsion fuel study. There is an inconsistency in the results reported from previous studies especially for the thermal efficiency, brake power, torque and specific fuel consumption. However, it is agreed by most of the studies that W/D does result in an improvement in these measurements when the total amount of diesel fuel in the emulsion is compared with that of the neat diesel fuel. NO_x and PM exhaust gas emissions are greatly reduced by using the W/D emulsion fuel. Unburnt hydrocarbon (UHC) and carbon monoxide (CO) exhaust emissions are found to be increased by using the W/D emulsion fuel. The inconsistency of the experimental result can be related to the effects of the onset and the strength of the micro-explosion process. The factors that affect these measurements consist of the size of the dispersed water particle, droplet size of the emulsion, water-content in the emulsion, ambient temperature, ambient pressure, type and percentage of surfactant, type of diesel engine and engine operating conditions. Durability testing and developing the fuel production device that requires no/less surfactant are the potential research area that can be explored in future.     

VCR采矿法在武山铜矿应用展望

为进一步提高武山铜矿综合采矿效益，根据武山铜矿地质条件、采矿经验，并结合安全、成本、效益等因素，浅述后期生产建设过程中如何发挥现有采矿方法的优势，并针对 VCR 采矿法在武山铜矿应用现状，分析了改进提升的方法。     

Participatory system dynamics modelling for housing,energy and wellbeing interactions

The built environment is a key target of decarbonization policies. However, such policies often have a narrow objective and narrow focus, resulting in ‘policy-resistance’ and unintended consequences. The literature attributes these unintended consequences to a narrow financial focus, adverse incentives, and inadequate handling of knowledge, skills, communication and feedback gaps, but it provides little advice on how these complex interactions can be captured. This paper illustrates the development and application of an integrated approach to address these complex interactions with regard to housing performance, energy, communal spaces and wellbeing. In particular, it explores the dynamics created by these relationships with simulation modelling in participatory settings, and with a diverse group of stakeholders. The simulation results suggest that monitoring is key to improve the performance of the housing stock besides energy efficiency; and investments in communal spaces positively affect the adoption of energy-efficiency measures and the wellbeing of residents. The evaluation results for participatory workshops show this approach was found useful by the stakeholders for supporting more integrated decision-making about housing. In future research, this approach can be implemented for policy problems in specific contexts.     

Breeding goal traits accounting for feed intake capacity and roughage or concentrate intake separately

Current breeding tools aiming to improve feed efficiency use definitions based on total dry matter intake (DMI); for example, residual feed intake or feed saved. This research aimed to define alternative traits using existing data that differentiate between feed intake capacity and roughage or concentrate intake, and to investigate the phenotypic and genetic relationships among these traits. The data set contained 39,017 weekly milk yield, live weight, and DMI records of 3,164 cows. The 4 defined traits were as follows: (1) Feed intake capacity (FIC), defined as the difference between how much a cow ate and how much she was expected to eat based on diet satiety value and status of the cow (parity and lactation stage); (2) feed saved (FS), defined as the difference between the measured and the predicted DMI, based on the regression of DMI on milk components within experiment; (3) residual roughage intake (RRI), defined as the difference between the measured and the predicted roughage intake, based on the regression of roughage intake on milk components and concentrate intake within experiment; and (4) residual concentrate intake (RCI), defined as the difference between the measured and the predicted concentrate intake, based on the regression of concentrate intake on milk components and roughage intake within experiment. The phenotypic correlations were ?0.72 between FIC and FS, ?0.84 between FS and RRI, and ?0.53 between FS and RCI. Heritability of FIC, FS, RRI, and RCI were estimated to be 0.21, 0.12, 0.15, and 0.03, respectively. The genetic correlations were ?0.81 between FS and FIC, ?0.96 between FS and RRI, and ?0.25 between FS and RCI. Concentrate intake and RCI had low heritability. Genetic correlation between DMI and FIC was 0.98. Although the defined traits had moderate phenotypic correlations, the genetic correlations between DMI, FS, FIC, and RRI were above 0.79 (in absolute terms), suggesting that these traits are genetically similar. Therefore, selecting for FIC is expected to simply increase DMI and RRI, and there seems to be little advantage in separating concentrate and roughage intake in the genetic evaluation, because measured concentrate intake was determined by the feeding system in our data and not by the genetics of the cow.     

Rapid Hormetic Responses of Photosystem II Photochemistry of Clary Sage to Cadmium Exposure

Five-day exposure of clary sage (Salvia sclarea L.) to 100 μM cadmium (Cd) in hydroponics was sufficient to increase Cd concentrations significantly in roots and aboveground parts and affect negatively whole plant levels of calcium (Ca) and magnesium (Mg), since Cd competes for Ca channels, while reduced Mg concentrations are associated with increased Cd tolerance. Total zinc (Zn), copper (Cu), and iron (Fe) uptake increased but their translocation to the aboveground parts decreased. Despite the substantial levels of Cd in leaves, without any observed defects on chloroplast ultrastructure, an enhanced photosystem II (PSII) efficiency was observed, with a higher fraction of absorbed light energy to be directed to photochemistry (Φ_PSΙΙ). The concomitant increase in the photoprotective mechanism of non-photochemical quenching of photosynthesis (NPQ) resulted in an important decrease in the dissipated non-regulated energy (Φ_NO), modifying the homeostasis of reactive oxygen species (ROS), through a decreased singlet oxygen (¹O₂) formation. A basal ROS level was detected in control plant leaves for optimal growth, while a low increased level of ROS under 5 days Cd exposure seemed to be beneficial for triggering defense responses, and a high level of ROS out of the boundaries (8 days Cd exposure), was harmful to plants. Thus, when clary sage was exposed to Cd for a short period, tolerance mechanisms were triggered. However, exposure to a combination of Cd and high light or to Cd alone (8 days) resulted in an inhibition of PSII functionality, indicating Cd toxicity. Thus, the rapid activation of PSII functionality at short time exposure and the inhibition at longer duration suggests a hormetic response and describes these effects in terms of “adaptive response” and “toxicity”, respectively.     

隧洞开挖典型掏槽设计方法

针对目前隧洞开挖爆破施工中缺少具体、详细的掏槽设计方法的现状,提出了最常用的2种典型掏槽方式,并详细论述了其设计方法。这些掏槽方式及设计方法均在实际施工中得到了推广应用,并且取得了良好的爆破效果。实际应用表明:这些典型掏槽方式及设计方法能有效提高硬质岩石开挖的钻孔利用率,能将钻孔利用率提高到98%～100%,实现掌子面基本无残孔,从而有效提高单循环进尺,加快开挖进度,降低开挖成本。     

Towards efficient device-to-device multicast content delivery with social awareness

Frequent content retrieval leads to significant energy consumption in cellular networks. Thereby, device-to-device (D2D) communication is used for proximal content delivery. Be aware that social friends may have common content interests, D2D content delivery is further improved by considering social network. However, how to implement efficient D2D multicast with the aid of social relationship needs further consideration. In this paper, with a proposed architecture on combined networks, the cooperation range of content sharing is investigated for D2D multicast to minimize the average energy consumption of serving a content request. Based on combined networks, a cooperation group formation scheme is proposed. Simulation results verify our analyzes and the advantage of proposed scheme.     

Performance improvement of microbial fuel cell through artificial intelligence

The current work introduces an enhancement in the performance of the microbial fuel cell through estimating the optimal set of controlling parameters. The maximization of both power density (PD) and the percentage of chemical oxygen demand (COD) removal were considered as the enhancement in the cell's performance. Three main parameters in terms of performance as well as commercialization are the system's inputs; the Pt which takes the range of 0.1‐0.5 mg/cm², the degree of sulphonation in sulfonated‐poly‐ether‐ether‐ketone that changes in the range of 20‐80%, and the rate of aeration of cathode which varies between 10 and 150 mL/min. From the experimental dataset, two robust adaptive neuro‐fuzzy inference system models based on the fuzzy logic technique have been constructed. The comparisons between the models' outputs and the experimental data showed well‐fitting in both training and testing datasets. The mean squared errors of the PD model, for testing and whole datasets, were found 2.575 and 0.909 while for the COD model it showed 19.242 and 6.791, respectively. Then, based on the two fuzzy models, a Particle Swarm Optimization algorithm has been used to determine the best parameters that maximize both of the PD and the COD removal of the cell. The optimization process was utilized for single and multi‐object optimization processes. In the single optimization, the resulting maximums of the PD and the COD removal were found 62.844 (mW/m²) and 99.99 (%), respectively. Whereas, in the multi‐object optimization, the values of 61.787 (mW/m²) and 96.21 (%) were reached as the maximums for the PD and COD, respectively. This implies that, in both cases of optimization processes, the adopted methodology can efficiently enhance the microbial fuel cell performances than the previous work.     

真空热处理炉布料矩阵优化仿真分析

为了获得更高的加热效率和更好的温度均匀性,采用有限元软件建立了真空热处理炉加热过程仿真模型,并耦合PID算法用于温度控制。通过与实测温度对比,验证了仿真模型的准确性。借助该模型,模拟研究了布料矩阵对两种典型形状零件在真空热处理炉内加热特性的影响。模拟装炉时基于零件几何形状特征,对圆棒形工件采用顺排、叉排和环形排列3种形式,对圆盘形工件采用横排式和竖排式。研究结果表明:尽管零件形状和数量相同,但是随着布料矩阵的变化,加热效率和温度均匀性都会改变。对于圆棒形工件,采用环形排列不仅可以提高内部工件的加热速率,而且相较于叉排式可以将最大温差减小36 ℃;对于圆盘形工件,由水平式改为竖直式布料可以将最大温差由248 ℃减小至171 ℃。