Women’s empowerment and food consumption:Evidence from female-headed households in Tanzania

Despite the growing recognition of women’s increasing role in the household and corresponding empowerment programs in sub-Saharan Africa,intensive research on the relationship between women’s influence and household food consumption is minimal.Using the most recent(2017-2018)national household survey data from Tanzania,this study examined the influence of women’s empowerment on household food consumption.First,we compared the monthly consumption of eight food categories between female-headed households(FHHs)and male-headed households(MHHs)using both descriptive statistics and the propensity score matching(PSM)method.Furthermore,we adopted the two-stage Linear Expenditure System and Almost Ideal Demand System model(LES-AIDS)to estimate income and price elasticities for the two household types.The results show that FHHs consume bread and cereals,fish,oils and fats,vegetables,and confectionery(sugar,jam,honey,chocolate,etc.)more than MHHs.Moreover,FHHs have a significantly higher income elasticity of demand for all food groups than MHHs.They are also more price elastic than MHHs in meat,fish,oils,fats,sugar,jam,honey,chocolate,etc.

Effect of bubble morphology and behavior on power consumption in non-Newtonian fluids’aeration process

Due to a prolonged operation time and low mass transfer efficiency, the primary challenge in the aeration process of non-Newtonian fluids is the high energy consumption, which is closely related to the form and rate of impeller, ventilation, rheological properties and bubble morphology in the reactor. In this perspective, through optimal computational fluid dynamics models and experiments, the relationship between power consumption, volumetric mass transfer rate(kLa) and initial bubble size(d0) was constructed to establish an efficient operation mode for the aeration process of non-Newtonian fluids. It was found that reducing the d0could significantly increase the oxygen mass transfer rate, resulting in an obvious decrease in the ventilation volume and impeller speed. When d0was regulated within 2-5 mm,an optimal kLa could be achieved, and 21% of power consumption could be saved, compared to the case of bubbles with a diameter of 10 mm.

Biodegradable and flexible i-carrageenan based RRAM with ultralow power consumption

Transient memories,which can physically disappear without leaving traceable remains over a period of normal operation,are attracting increasing attention for potential applications in the fields of data security and green electronics.Resistive random access memory(RRAM)is a promising candidate for next-generation memory.In this context,biocompatible l-carrageenan(l-car),extracted from natural seaweed,is introduced for the fabrication of RRAM devices(Ag/l-car/Pt).Taking advantage of the complexation processes between the functional groups(C–O–C,C–O–H,et al.)and Ag metal ions,a lower migration barrier of Ag ions and a high-speed switching(22.2 ns for SET operation/26 ns for RESET operation)were achieved,resulting in an ultralow power consumption of 56 fJ.And the prepared Ag/l-car/Pt RRAM devices also revealed the capacities of multilevel storage and flexibility.In addition,thanks to the hydrophilic groups of l-car molecule,the RRAM devices can be rapidly dissolved in deionized(DI)water within 13 minutes,showing excellent transient characteristics.This work demonstrates that l-car based RRAM devices have great potential for applications in secure storage applications,flexible electronics and transient electronics.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

Virginia Tech Comprehensive Power-based Fuel Consumption Model(VT-CPFM):Model Validation and Calibration Considerations

A power-based vehicle fuel consumption model,entitled the Virginia Tech Comprehensive Power-based Fuel Consumption Model(VT-CPFM)that was developed in an earlier publication is validated against in-field fuel consumption measurements.The study demonstrates that the VT-CPFMs calibrated using the EPA city and highway fuel economy ratings generally provide reliable fuel consumption estimates with a coefficient of determination in the range of 0.96.More importantly,both estimates and measurements produce very similar behavioral changes depending on engine load conditions.The VT-CPFMs are demonstrated to be easily calibrated using publically available data without the need to gather in-field instantaneous data.

Power consumption in a field emission panel

The power consumption and electric field distribution in a field emission display （FED） panel is optimized with a novel pixel structure. A circuit model is proposed to estimate the total power consumption in an FED panel which is composed of anode energy consumption, energy loss due to the leakage current and the energy dissipated in the parasitic capacitances. Moreover, the parasitic capacitances play a vital part in the power consumption and driving performance. In order to lower the parasitic capacitances, multiple dielectric layers are used as the gate electrode. Due to different etching speeds, a novel pixel structure is formed. As a result, the power consumption of an FED panel is reduced by 28% in a full white picture, and the electron beam performance is also better than that of the conventional structure.

Load reduction sintering for increasing productivity and decreasing fuel consumption

The technical and economical indexes and the physical properties of load reduction sintering processes with the supporting stands of installation at different height levels （300, 350, and 400 mm）： in a sintering bed were studied under the same conditions of raw material, bed height, and sintering parameters. Sintering pot tests with different bed heights and fuel ratios of the mixture with or without supporting stands were performed to decrease the fuel consumption. The airflow rate through the sintering bed was measured with an anemoscope fixed on the bed surface to reveal the effects of supporting stands. The utilization of load reduction sintering can improve the permeability of the sintering bed, and the airflow rate through the sintering bed is increased. When the stand height is half of the sintering bed, the productivity increases by 27.9%, and the drum index slightly decreases. Keeping at the same productivity level with normal sintering, the utilization of load reduction sintering can decrease the solid fuel consumption by 9.2%.

Influence of driving cycles on exhaust emissions and fuel consumption of gasoline passenger car in Bangkok

The influence of different driving cycles on their exhaust emissions and fuel consumption rate of gasoline passenger car was investigated in Bangkok based on the actual measurements obtained from a test vehicle driving on a standard chassis dynamometer. A newly established Bangkok driving cycle （BDC） and the European driving cycle （EDC） which is presently adopted as the legislative cycle for testing automobiles registered in Thailand were used. The newly developed BDC is constructed using the driving characteristic data obtained from the real on-road driving tests along selected traffic routes. A method for selecting appropriate road routes for real driving tests is also introduced. Variations of keyed driving parameters of BDC with different driving cycles were discussed. The results showed that the HC and CO emission factors of BDC are almost two and four times greater than those of EDC, respectively. Although the difference in the NOx emission factor is small, the value from BDC is still greater than that of EDC by 10%. Under BDC, the test vehicle consumes fuel about 25% more than it does under EDC. All these differences are mainly attributed to the greater proportion of idle periods and higher fluctuations of vehicle speed in the BDC cycle. This result indicated that the exhausted emissions and fuel consumption of vehicles obtained from tests under the legislative modal-type driving cycle （EDC） are significantly different from those actually produced under real traffic conditions especially during peak periods.

RHEOLOGICAL CHARACTERISTICS,POWER CONSUMPTION,MASS AND HEAT,TRANSFER DURING XANTHAN GUM FERMENTATION

Xanthan gum fermentation is probably the most complex fermentation process in terms ofrheological property variations and associated mixing,power consumption,mass and heat transferproblems.In order to obtain these data,fermentations of Xanthomonas campestris were carried outon pilot scale bioreactor with different D/T ratios and different feeding strategies(batch andfed-batch).It was discovered that the rheology of xanthan fermentation broth is of paramountimportance to the above characteristics.The aerated power consumption and power number are both afunction of aeration rate during the initial stage of the fermentation when the viscosity is low andthe Reynolds number high.However when the becames viscous and Reynolds unmber≤10~3,thegas velocity does not show any effect on the power number.The oxygen mass transfer coefficientsand the overall heat transfer coefficients are both dependent on the impeller speed,the apparentviscosity of the broth and the D/T ratio.These data taken from practical

Combining artificial neural network and multi-objective optimization to reduce a heavy-duty diesel engine emissions and fuel consumption

Nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is well known for engine optimization problem. Artificial neural networks(ANNs) followed by multi-objective optimization including a NSGA-Ⅱ and strength pareto evolutionary algorithm(SPEA2) were used to optimize the operating parameters of a compression ignition(CI) heavy-duty diesel engine. First, a multi-layer perception(MLP) network was used for the ANN modeling and the back propagation algorithm was utilized as training algorithm. Then, two different multi-objective evolutionary algorithms were implemented to determine the optimal engine parameters. The objective of the present study is to decide which algorithm is preferable in terms of performance in engine emission and fuel consumption optimization problem.

Effect of the Inclination of Baffles on the Power Consumption and Fluid Flows in a Vessel Stirred by a Rushton Turbine

The role of baffles in mechanically stirred tanks is to promote the stability of power drawn by the impeller and to avoid the fluid swirling, thus enhancing mixing. The present paper numerically investigates the baffles effects in a vessel stirred by a Rushton turbine. The geometric factor of interest is the baffle inclination which is varying between 25°, 32.5°, 45°, 70° and 90° at different impeller rotational speeds. The impeller rotational direction has also been varied. The vortex size and power consumption were evaluated for each geometrical configuration. It was found that the best configuration is the baffle inclination by = 70° at a negative angular velocity.

Fuel Consumption Potential of the Pushbelt CVT

The efforts to further reduce fuel consumption of vehicles equipped with a pushbelt type Continuously Variable Transmission(CVT) focus on different sources of loss.In this paper the magnitude of these losses and their potential for reduction is described.Inside the CVT,the variator,its control strategy and the hydraulic actuation circuit can be distinguished as the main potentials.A major opportunity is offered by a new control strategy that takes the actual slip between belt and pulley as the control parameter.The resulting decrease of clamping forces on the pushbelt leads to a reduction of variator and actuation losses.Further potential is found in the hydraulic actuation circuit by an improved tuning of the power supply to the actual power requirement.Outside the CVT additional potential is found in start-stop functionality as supported by measures inside the transmission.The paper describes the theoretical background as well as practical fuel savings of up to 5.5% that were obtained in tests on vehicle level.Slip control adds an inherent robustness to the operation of the pushbelt and opens up the fuel saving potential of the CVT thus reinforcing its position as the benchmark for the near future.

Low power consumption 4-channel variable optical attenuator array based on planar lightwave circuit technique

The power consumption of a variable optical attenuator（VOA） array based on a silica planar lightwave circuit was investigated. The thermal field profile of the device was optimized using the finite-element analysis. The simulation results showed that the power consumption reduces as the depth of the heat-insulating grooves is deeper, the up-cladding is thinner,the down-cladding is thicker, and the width of the cladding ridge is narrower. The materials component and thickness of the electrodes were also optimized to guarantee the driving voltage under 5 V. The power consumption was successfully reduced to as low as 155 mW at an attenuation of 30 dB in the experiment.

Experimental study of power consumption, local characteristics distributions and homogenization energy in gas–liquid stirred tank reactors

In this paper, the power consumption, the vertical local void fraction and the local gas–liquid interfacial area are investigated in the aerated stirred tank reactors(STRs) equipped with a rigid-flexible impeller. Meanwhile, the regressive correlation based on power consumption and interfacial area is proposed. Then a novel homogenization energy(HE = RSDPtm) expression based on power consumption and local interfacial area is redefined and used to indicate the mixing efficiency. The optimal operating mode is selected based on the change of the HE value. This paper can provide research ideas for structural optimization of stirred reactors.

A Novel Hybrid FA-Based LSSVR Learning Paradigm for Hydropower Consumption Forecasting

Due to the nonlinearity and nonstationary of hydropower market data, a novel hybrid learning paradigm is proposed to predict hydropower consumption, by incorporating firefly algorithm （FA） into least square support vector regression （LSSVR）, i.e., FA-based LSSVR model. In the novel model, the powerful and effective artificial intelligence （AI） technique, i.e., LSSVR, is employed to forecast hydropower consumption. Furthermore, a promising AI optimization tool, i.e., FA, is espe- cially introduced to address the crucial but difficult task of parameters determination in LSSVR （e.g., hyper and kernel function parameters）. With the Chinese hydropower consumption as sample data, the empirical study has statistically confirmed the superiority of the novel FA-based LSSVR model to other benchmark models （including existing popular traditional econometric models, AI models and similar hybrid LSSVRs with other popular parameter searching tools）~ in terms of level and direc- tional accuracy. The empirical results also imply that the hybrid FA-based LSSVR learning paradigm with powerful forecasting tool and parameters optimization method can be employed as an effective forecasting tool for not only hydropower consumption but also other complex data.

Design and Fuel Consumption Optimization for a Bio-Inspired Semi-floating Hybrid Vehicle

Based on a bionic concept and combing air-cushion techniques and track driving mechanisms, a novel semi-floating hybrid concept vehicle is proposed to meet the transportation requirements on soft terrain. First, the vehicle scheme and its improved duel-spring flexible suspension design are described. Then, its fuel consumption model is proposed accordingly with respect to two vehicle operating parameters. Aiming at minimizing the fuel consumption, two Genetic Algorithms （GAs） are designed and implemented. For the initial one （GA-1）, despite getting an acceptable result, there still existed some problems in its optimiza- tion process. Based on an analysis of the defects of GA-1, an improved algorithm GA-2 was developed whose effectiveness and stability were embodied in the optimization process and results. The proposed design scheme and optimization approaches can provide valuable references for this new kind of vehicle with industry, military or scientific exploitations, etc. promising applications in the areas of agriculture, petroleum industry, military or scientific explaitations, etc.

Forecasting increasing rate of power consumption based on immune genetic algorithm combined with neural network

Considering the factors affecting the increasing rate of power consumption, the BP neural network structure and the neural network forecasting model of the increasing rate of power consumption were established. Immune genetic algorithm was applied to optimizing the weight from input layer to hidden layer, from hidden layer to output layer, and the threshold value of neuron nodes in hidden and output layers. Finally, training the related data of the increasing rate of power consumption from 1980 to 2000 in China, a nonlinear network model between the increasing rate of power consumption and influencing factors was obtained. The model was adopted to forecasting the increasing rate of power consumption from 2001 to 2005, and the average absolute error ratio of forecasting results is 13.521 8%. Compared with the ordinary neural network optimized by genetic algorithm, the results show that this method has better forecasting accuracy and stability for forecasting the increasing rate of power consumption.

Balancing the Power Consumption Speed in Flat and Hierarchical WSN

A combination of a cluster tree routing protocol and an Ad hoc on demand vector (AODV) routing protocol is used in the latest ZigBee standard wireless sensor networks (WSNs) technology.However,the AODV routing protocol has no means by which to take into consideration the power consumption of the nodes during the routing process.Therefore,a new approach is proposed in this paper to balance the power consumption speed and to distribute the responsibilities of routing among flat wireless sensor nodes and the three levels of hierarchical wireless sensor nodes.These three levels are based on the three types of devices,which are used in the ZigBee standard:the coordinator,the routers,and the end devices.In this paper,we have compared the original AODV routing protocol with our extension approach for the distribution of power consumption.Based on the simulation results,our new approach has achieved better performance in terms of increasing the lifetime of the flat wireless sensor network,the personal area network (PAN) coordinator,the routers,and the whole network of the hierarchical wireless sensor network.Additionally,it has better performance in terms of distributing the power consumption among the key nodes of the wireless sensor network.

Power consumption and flow field characteristics of a coaxial mixer with a double inner impeller

A coaxial mixer meeting the actual demand of a system with high and variable viscosity is investigated. It has an outer wall-scraping frame and a double inner impeller consisting of a four-pitched-blade turbine and Rushton turbine. The power consumption and flow field characteristics of the coaxial mixer in laminar and transitional flow are simulated numerically, and then the distribution of velocity field, shear rate and mass flow rate are analyzed. The simulation results indicate that the outer frame has little effect on the power consumption of the double inner impeller whether in laminar or transitional flow, whereas the inner combined impeller has a great effect on the power consumption of the outer frame. Compared with the single rotation mode, the power consumption of the outer frame will decrease in co-rotation mode and increase in counter-rotation mode. The velocity, shear rate and mass flow rate are relatively high near the inner impeller in all operating modes, and only under double-shaft agitation will the mixing performance near the free surface be improved.In addition, these distributions in the co-rotation and counter-rotation modes show little difference, but the co-rotation mode is recommended for the advantage of low power consumption.

Fuel characteristics, loads and consumption in Scots pine forests of central Siberia

Forest fuel investigations in central and southern Siberian taiga of Scots pine forest stands dominated by lichen and feather moss ground vegetation cover revealed that total aboveground biomass varied from 13.1 to 21.0 kg/m 2.Stand biomass was higher in plots in the southern taiga,while ground fuel loads were higher in the central taiga.We developed equations for fuel biomass(both aerial and ground)that could be applicable to similar pine forest sites of Central Siberia.Fuel loading variability found among plots is related to the impact and recovery time since the last wildfi re and the mosaic distribution of living vegetation.Fuel consumption due to surface fi res of low to high-intensities ranged from 0.95 to 3.08 kg/m 2,that is,18–74%from prefi re values.The total amount of fuels available to burn in case of fi re was up to 4.5–6.5 kg/m 2.Moisture content of fuels(litter,lichen,feather moss)was related to weather conditions characterized by the Russian Fire Danger Index(PV-1)and FWI code of the Canadian Forest Fire Weather Index System.The data obtained provide a strong foundation for understanding and modeling fi re behavior,emissions,and fi re eff ects on ecosystem processes and carbon stocks and could be used to improve existing global and regional models that incorporate biomass and fuel characteristics.