Physical mechanism of mind changes and tradeoffs among speed,accuracy, and energy cost in brain decision making:Landscape, flux,and path perspectives

Cognitive behaviors are determined by underlying neural networks. Many brain functions, such as learning and memory, have been successfully described by attractor dynamics. For decision making in the brain, a quantitative description of global attractor landscapes has not yet been completely given. Here, we developed a theoretical framework to quantify the landscape associated with the steady state probability distributions and associated steady state curl flux, measuring the degree of non-equilibrium through the degree of detailed balance breaking for decision making. We quantified the decision-making processes with optimal paths from the undecided attractor states to the decided attractor states, which are identified as basins of attractions, on the landscape. Both landscape and flux determine the kinetic paths and speed. The kinetics and global stability of decision making are explored by quantifying the landscape topography through the barrier heights and the mean first passage time. Our theoretical predictions are in agreement with experimental observations： more errors occur under time pressure. We quantitatively explored two mechanisms of the speed-accuracy tradeoff with speed emphasis and further uncovered the tradeoffs among speed, accuracy, and energy cost. Our results imply that there is an optimal balance among speed, accuracy, and the energy cost in decision making. We uncovered the possible mechanisms of changes of mind and how mind changes improve performance in decision processes. Our landscape approach can help facilitate an understanding of the underlying physical mechanisms of cognitive processes and identify the key factors in the corresponding neural networks.

HVAC energy cost minimization in smart grids: A cloud-based demand side management approach with game theory optimization and deep learning

In this paper, we present a novel cloud-based demand side management (DSM) optimization approach for the cost reduction of energy usage in heating, ventilation and air conditioning (HVAC) systems in residential homes at the district level. The proposed approach achieves optimization through scheduling of HVAC energy usage within permissible bounds set by house users. House smart home energy management (SHEM) devices are connected to the utility/aggregator via a dedicated communication network that is used to enable DSM. Each house SHEM can predict its own HVAC energy usage for the next 24 h using minimalistic deep learning (DL) prediction models. These predictions are communicated to the aggregator, which will then do day ahead optimizations using the proposed game theory (GT) algorithm. The GT model captures the interaction between aggregator and customers and identifies a solution to the GT problem that translates into HVAC energy peak shifting and peak reduction achieved by rescheduling HVAC energy usage. The found solution is communicated by the aggregator to houses SHEM devices in the form of offers via DSM signals. If customers’ SHEM devices accept the offer, then energy cost reduction will be achieved. To validate the proposed algorithm, we conduct extensive simulations with a custom simulation tool based on GridLab-D tool, which is integrated with DL prediction models and optimization libraries. Results show that HVAC energy cost can be reduced by up to 36% while indirectly also reducing the peak-to-average (PAR) and the aggregated net load by up to 9.97%.

Biomass energy cost and feasibility of gasifier based biomass power generation system

The present research work has been carried out on biomass based on 10 kW capacity gasifier power generation system installed at College of Agricultural Engineering and Technology,Dr.Panjabrao Deshmukh Agricultural University(Dr.PDKV),Akola Maharashtra,India.The main objectives were to evaluate various costs and benefits involved in the power generation system.The costs of energy per unit were calculated for the first year of operation.The economics of gasifier based power generation system and thereby the feasibility of the system was examined by estimating per unit cost,Net Present Value(NPV),Benefit Cost Ratio(BCR),Internal Rate of Return(IRR)and payback period.The discount cash flow method was used to find out the IRR.In the present analysis,three costs viz.,installed capital cost,operation and maintenance cost,and levelised replacement cost were examined for the evaluation of the power generation per unit.Discount rate on investment in case of subsidy(Case I)and in case without subsidy(Case II)for installation cost of system was considered as 12.75%.The BCR comes in Case I for operating duration of 22 h,20 h,and 16 h are 1.24,1.18,and 1.13,respectively.Similarly for Case II BCR comes 1.44,1.38,and 2.39.The IRR comes in Case I for operating duration of 22 h,20 h,and 16 h are 26%,22%,and 19%,respectively.Similarly for Case II,IRR comes 52%,44%,and 39%for operating duration of 22 h,20 h,and 16 h,respectively.The payback period in the present analysis was worked out.The payback period for biomass based gasifier power generation system was observed to be for Case I from three to four years and for Case II it was one to two years.

Process reconfiguration and intensification:An emerging opportunity enabling efficient carbon capture and low-cost blue hydrogen production

Low-carbon hydrogen can play a significant role in decarbonizing the world. Hydrogen is currently mainly produced from fossil sources,requiring additional CO_(2)capture to decarbonize, which energy intense and costly. In a recent Green Energy & Environment paper, Cheng and Di et al. proposed a novel integration process referred to as SECLR_(HC) to generate high-purity H_(2) by in-situ separation of H_(2)and CO without using any additional separation unit. Theoretically, the proposed process can essentially achieve the separation of C and H in gaseous fuel via a reconfigured reaction process, and thus attaining high-purity hydrogen of ~99%, as well as good carbon and hydrogen utilization rates and economic feasibility. It displays an optimistic prospect that industrial decarbonization is not necessarily expensive, as long as a suitable CCS measure can be integrated into the industrial manufacturing process.

Economic Analysis of Energy-efficient Buildings in China

Applying energy-saving measures in residential buildings is usually constrained by the increase of initial investment. ＂However, if it is analyzed from the view of energy cost and life-cycle cost, the energy-saving benefit can offset ~he increase of initial investment. An analysis method based on life-cycle concept was developed to calcu- late the energy cost of residential building flats. Several uncertain factors were included into the model, making it more accurate to reflect practical situation. The model was solved using the software DeST and applied to one resi- dential building project in Shanghai. The case study shows that the initial investment （cost） is paid back during the operational phase through less consumption of energy. It further indicates that the investment recovery period is between 10 and 19 years which are acceptable to households and developers in China.

Regional differences and threshold characters of the impact of energy use efficiency on energy scarcity in China

The improvement of the technical efficiency of energy use has been widely seen as an important way to alleviate energy scarcity.However,the energy rebound effect demonstrates the vulnerability and unsustainability of alleviating energy scarcity relying on technology.Under the background of the consistent development of energy factor market,it is of great importance to explore the paths and differences of energy source allocation constrained by technology and cost to promote the sustainable use of energy.This study analyzed the regional differences and threshold characteristics in the impact of the technical and cost efficiency of energy use on energy scarcity using the instrumental variable-two-stage least square method,based on the panel data of Chinese provinces from 2003 to 2017.The results showed that:①Technology and price were the critical forces of the technical and cost efficiency of energy use.They changed the degree of use of surplus production factors by affecting the complementary and replacement demand relationship between energy and non-energy factors.Meanwhile,the impact of energy use efficiency on energy scarcity showed regional and time features due to the different technology capabilities and different levels of market development in different regions and different time.②The alleviation of energy scarcity at the national level relied on the improvement of energy cost efficiency.At the regional level,the alleviation of energy scarcity in central China came from the improvement of the technical efficiency of energy use.However,the alleviation of energy scarcity in the eastern and western regions was due to the improvement of energy cost efficiency.③Constrained by the economic development,openness,science and technology input and the industrial development structure,the impact of the technical and cost efficiency of energy use on energy scarcity demonstrated a nonlinear feature.And structural mutation occurred after passing a specific‘inflection point’,which showed a significant threshold feature.Therefore,energy price should play an important role in energy use and it is necessary to pay attention to the regional differences and time characteristics of energy economic development to promote the sustainable development of energy resources.

An IoT-Based Energy Conservation Smart Classroom System

With the increase of energy consumption worldwide in several domains such as industry,education,and transportation,several technologies played an influential role in energy conservation such as the Internet of Things(IoT).In this article,we describe the design and implementation of an IoT-based energy conser-vation smart classroom system that contributes to energy conservation in the edu-cation domain.The proposed system not only allows the user to access and control IoT devices(e.g.,lights,projectors,and air conditions)in real-time,it also has the capability to aggregate the estimated energy consumption of an IoT device,the smart classroom,and the building based on the energy consumption and cost model that we propose.Moreover,the proposed model aggregates the estimated energy cost according to the Saudi Electricity Company(SEC)rates.Furthermore,the model aggregates in real-time the estimated energy conservation percentage and estimated money-saving percentage compared to data collected when the system wasn't used.The feasibility and benefits of our system have been validated on a real-world scenario which is a classroom in the college of computer science and engineering,Taibah University,Yanbu branch.The results of the experimental studies are promising in energy conservation and cost-saving when using our proposed system.

ECONOMIC IMPACT OF NEW GREEN BUILDING CODE ON RESIDENTIAL PROJECT DEVELOPMENT FROM ENERGY CONSUMPTION PERSPECTIVES7

The new Green Building Code impacts the design and construction of building systems,which are vital for energy consumption estimation,especially since electricity prices are of great interest to today’s consumers.Through the integration of energy consumption and utility bills,this paper presents the results of the economic impacts of installing various energy efficient systems required by the Green Building Code.Energy consumption prediction models are developed using multiple regression statistical methods based on electricity data collected from 110 single-family houses located in Los Angeles,California,USA.These prediction models have found a significant difference in electricity consumption of a single-family house prior to the introduction of the code and after its introduction.In addition,life cycle cost analysis on two of the featured systems,photovoltaic system and hybrid water heater,discovered that consumers can pay off their up-front investments in state-of-the-art energy efficient systems and appliances and earn a profit within the stated life cycle time period.The findings provide useful guidelines for making initial monetary decisions in the residential building industry。

A Study on the Evaluation of Heating and Cooling Energy Efficiency in Residential Buildings for Climatic Zones of Turkey

In Turkey, most of the common type projects of mass production residential buildings are being developed and constructed by TOK1 （Housing Development Administration of Turkey）. These buildings, in which energy efficient approach has been disregarded for years, cause to gradually increase on heating and cooling energy consumptions. In regards to national economics, it is essential to evaluate energy efficiency and to develop suggestions to decrease energy consumptions in residential buildings. To achieve appropriate solutions, cost evaluation also becomes necessary. Therefore, this paper aims to introduce a study which serves the purpose of producing a choice of energy efficient solutions in order to reduce energy consumptions and energy cost. In this study, different heating and cooling energy efficient scenarios have been developed for a selected residential building, constructed by TOKI, for climatic zones of Turkey. For each scenario, energy simulations have been executed by means of the simulation program--DesignBuilder, the user-friendly visual interface of EnergyPlus, and cost analysis has been carried out by using the net present value and discounted payback period method. As a result, energy and cost effective solutions have been presented and discussed for different climatic zones.

Energy-balanced on demand clustering improved leach protocol for wireless sensor networks

In wireless sensor networks（WSNs）,appropriate topology control（TC）could efficiently balance the load among sensor nodes and extend network lifespan.Clustering is an effective topology control technique that could reduce energy consumption and provide scalability to WSNs.However,some clustering algorithms,including the traditional low energy adaptive clustering hierarchy（LEACH）,don＇t consider the residual energy and the communication distance.The energy consumption could dramatically increase in the case of long communication distance and high rate of control message exchange.In this paper we propose an energy-balanced clustering algorithm which considers the communication distance and the residual energy.Moreover the cluster head（CH）reselection is relevant to the current CH residual energy in order to reduce overheads.The simulation results demonstrate that the proposed algorithm prolongs the lifetime of the WSN in comparison to the LEACH and a hybrid clustering approach（HCA）.

Comparative Analysis for Evaluating Wind Energy Resources Using Intelligent Optimization Algorithms and Numerical Methods

Statistical distributions are used to model wind speed,and the twoparameters Weibull distribution has proven its effectiveness at characterizing wind speed.Accurate estimation of Weibull parameters,the scale(c)and shape(k),is crucial in describing the actual wind speed data and evaluating the wind energy potential.Therefore,this study compares the most common conventional numerical(CN)estimation methods and the recent intelligent optimization algorithms(IOA)to show how precise estimation of c and k affects the wind energy resource assessments.In addition,this study conducts technical and economic feasibility studies for five sites in the northern part of Saudi Arabia,namely Aljouf,Rafha,Tabuk,Turaif,and Yanbo.Results exhibit that IOAs have better performance in attaining optimal Weibull parameters and provided an adequate description of the observed wind speed data.Also,with six wind turbine technologies rating between 1 and 3MW,the technical and economic assessment results reveal that the CN methods tend to overestimate the energy output and underestimate the cost of energy($/kWh)compared to the assessments by IOAs.The energy cost analyses show that Turaif is the windiest site,with an electricity cost of$0.016906/kWh.The highest wind energy output is obtained with the wind turbine having a rated power of 2.5 MW at all considered sites with electricity costs not exceeding$0.02739/kWh.Finally,the outcomes of this study exhibit the potential of wind energy in Saudi Arabia,and its environmental goals can be acquired by harvesting wind energy.

Allocation of Hybrid Distributed Generations and Energy Management in Radial Electrical Systems

This paper presents a method for optimal sizing of a Micro grid connected to a hybrid source to ensure the continuity and quality of energy in a locality with a stochastically changing population. The hybrid system is composed of a solar photovoltaic system, a wind turbine, and an energy storage system. The reliability of the system is evaluated based on the voltage level regulation on IEEE 33-bus and IEEE 69-bus standards. Power factor correction is performed, despite some reliability and robustness constraints. This work focuses on energy management in a hybrid system considering climatic disturbances on the one hand, and on the other hand, this work evaluates the energy quality and the cost of energy. A combination of genetic algorithms of particle swarm optimization (CGAPSO) shows high convergence speed, which illustrates the robustness of the proposed system. The study of this system shows its feasibility and compliance with standards. The results obtained show a significant reduction in the total cost of production of this proposed system.

Investigative Study on Emissions Level and Cost Analysis of Diesel Powered and Solar PV-Diesel Hybrid Systems

In this work, a comparative study on emissions and cost implications of diesel powered and solar photovoltaic-diesel hybrid systems was carried out for three commercial banks. With the aid of HOMER Pro software, meteorological data, energy demand, system component data, capital and operating costs were used for analysis of the two systems. The results showed that in Bank A, the diesel generator alone releases 111,618 kg/yr of Carbon dioxide while the hybrid system releases 41,618 kg/yr of Carbon dioxide. For Bank B the quantity of carbon dioxide emissions released from the diesel generator in Bank B is 53,830 kg/yr, while the carbon dioxide released from the hybrid energy system is 24,082 kg/yr. For Bank C, the diesel generator alone released 177,799 kg/yr of Carbon dioxide and 129,060 kg/yr of carbon dioxide was released from the hybrid system. This suggests that the diesel generator alone releases more emissions when compared with the hybrid system in all the three banks. The Net present cost of energy and levelized cost of energy were used to find out the cost effectiveness of hybrid systems. The results showed that the levelized cost of energy for the generator alone and hybrid system, respectively in Bank A is $0.713 and $0.343. While for Bank B, it is $0.568 and $0.2553. Finally for Bank C, it was $0.731 and $0.556. Therefore, solar-diesel hybrid system has a comparatively low emission and can be considered as a more economical option for electricity generation.

Improving the Global Energy Industry by Integrating Macro-Technologies:Challenges and Opportunities for Corporations

Emerging energy technologies and market evolution of some energy products, particularly natural gas, can converge to produce a new global scenario closer to the objectives of Sustainable Development, with a smooth transition that would avoid social and economic upheavals and could open a new cycle of growth and wealth. The first steps of unconventional gas production have induced stabilization in the gas spot price that should be continued to guarantee stable prices in the long term. Another line of development that should start a second phase of consolidation and cost reduction is the field of Renewable Energies. Besides research and technology advancements, a new financial deal could substitute for subsidies and feed-in tariffs. Last but not least, electric vehicles and other emerging technologies from the demand side will also have a main role in this quest to re-structure the Energy sector, where a new hierarchy of energy goods and energy applications will appear, and a better integral use of energy will take place. A main consequence of that will be a significant reduction of CO2 emissions, and a cheaper cost of energy, although fiscal policies could swallow this advantage. In this transition, which would likely last thirty years or so, energy corporations will have to face challenges and opportunities to consolidate their working and value-adding status.

毛丝鼠体温调节发育的研究

毛丝鼠幼仔,六日龄已基本上达到恒温水平。吮乳期幼仔的静止代谢率较威体高;二日龄前,代谢率变化不符合体表面积定律;二日龄后,趋向成年恒温动物代谢类型,而符合体表面积定律。幼仔在25℃环境的热能消耗比20℃时少。

Design of a Passive Gait‑based Ankle‑foot Exoskeleton with Self‑adaptive Capability

Propulsion during push-off is the key to realizing human locomotion.Humans have evolved a way of walking with high energy utilization,but it can be further improved.Drawing inspiration from the muscle-tendon unit,a passive spring-actuated ankle-foot exoskeleton is designed to assist with human walking and to lengthen walking duration by mechanically enhancing walking efficiency.Detection of the gait events is realized using a smart clutch,which is designed to detect the contact states between the shoe sole and the ground,and automatically switch its working state.The engagement of a suspended spring behind the human calf muscles is hence controlled and is in synchrony with gait.The device is completely passive and contains no external power source.Energy is stored and returned passively using the clutch.In our walking trials,the soleus electromyography activity is reduced by as much as 72.2%when the proposed ankle-foot exoskeleton is worn on the human body.The influence of the exoskeleton on walking habits is also studied.The results show the potential use of the exoskeleton in humans’daily life.

An Eco-Friendly Approach for Reducing Carbon Emissions in Cloud Data Centers

Based on the Saudi Green initiative,which aims to improve the Kingdom’s environmental status and reduce the carbon emission of more than 278 million tons by 2030 along with a promising plan to achieve netzero carbon by 2060,NEOM city has been proposed to be the“Saudi hub”for green energy,since NEOM is estimated to generate up to 120 Gigawatts(GW)of renewable energy by 2030.Nevertheless,the Information and Communication Technology(ICT)sector is considered a key contributor to global energy consumption and carbon emissions.The data centers are estimated to consume about 13%of the overall global electricity demand by 2030.Thus,reducing the total carbon emissions of the ICT sector plays a vital factor in achieving the Saudi plan to minimize global carbon emissions.Therefore,this paper aims to propose an eco-friendly approach using a Mixed-Integer Linear Programming(MILP)model to reduce the carbon emissions associated with ICT infrastructure in Saudi Arabia.This approach considers the Saudi National Fiber Network(SNFN)as the backbone of Saudi Internet infrastructure.First,we compare two different scenarios of data center locations.The first scenario considers a traditional cloud data center located in Jeddah and Riyadh,whereas the second scenario considers NEOM as a potential cloud data center new location to take advantage of its green energy infrastructure.Then,we calculate the energy consumption and carbon emissions of cloud data centers and their associated energy costs.After that,we optimize the energy efficiency of different cloud data centers’locations(in the SNFN)to reduce the associated carbon emissions and energy costs.Simulation results show that the proposed approach can save up to 94%of the carbon emissions and 62%of the energy cost compared to the current cloud physical topology.These savings are achieved due to the shifting of cloud data centers from cities that have conventional energy sources to a city that has rich in renewable energy sources.Finally,we design a heuristic algorithm to verify the proposed approach,and it gives equivalent results to the MILP model.

Unpowered Knee Exoskeleton Reduces Quadriceps Activity during Cycling

Cycling is an eco-friendly method of transport and recreation. With the intent of reducing the energy cost of cycling without providing an additional energy source, we have proposed the use of a torsion spring for knee-extension support. We developed an exoskeleton prototype using a crossing four-bar mechanism as a knee joint with an embedded torsion spring. This study evaluates the passive knee exoskeleton using constant-power cycling tests performed by eight healthy male participants. We recorded the surface electromyography over the rectus femoris muscles of both legs, while the participants cycled at 200 and 225 W on a trainer with the developed wheel-accelerating system. We then analyzed these data in time-frequency via a continuous wavelet transform. At the same cycling speed and leg cadence, the median power spectral frequency of the electromyography increases with cycling load. At the same cycling load, the median power spectral frequency decreases when cycling with the exoskeleton. Quadriceps activity can be relieved despite the exoskeleton consuming no electrical energy and not delivering net-positive mechanical work. This fundamental can be applied to the further development of wearable devices for cycling assistance.

Comparative Study on Telecommunications Base Stations＇ Power Supply Systems on Remote Sites in the Northern Part of Cameroon

The TBS （telecommunications base stations） on remote sites in the northern part of Cameroon are mainly supplied by a system of two generating units. Only a few TBS located in the Waza and Benue National Parks are powered by a PV （photovoltaic） solar system to avoid any disturbance to wildlife. It is against this background that we decided to do a comparative study on these two systems. This study focuses on the reliability of electrical quantities, the environmental impact and the installation and operating costs of these two major systems namely the GU （generating unit） system comprising two generating units and the PV system. In conducting this study, we took a sample of TBS including those located in the Badjouma and Waza localities. After collecting data from mobile telephony operators, measurements of electrical quantities on the sites for twelve consecutive months and updating costs, their operation reveal indicators that are surprising, to say the least. Concerning the reliability index, the PV system is estimated at 99.9% as against 97.8% for the GU system. As for environmental impact, the mass of CO2 released by the GU system reached 1,707.5 tons in 25 years for a single TBS while the PV system produced no emissions. In addition to its contribution to climate change, the GU system pollutes its immediate environment through the spillage of waste and production of deafening noise. On the other hand, economic analysis shows mixed results. The GU system has a lower installation cost of $6,640 as against $174,550 for the PV system, whose investment cost is its main handicap. Regarding operating costs, the GU system peaks at $923,940 in 25 years while the PV system requires only $487,550 for the same duration.

DC-Gear:Gearing Duty Cycles in Delay-Constrained Wireless Sensor Networks

Many Wireless Sensor Network (WSN) systems are deployed in unattended areas using non-rechargeable batteries.To enable sustainable operations,most WSN systems employ duty-cycling mechanisms,such as Low Power Listening (LPL).For reliable delivery of each packet with LPL,the sender has to transmit a preamble that is long enough to span over a complete sleep interval of the receiver.In this way,the sensor nodes avoid idle listening,however,at the cost of remarkably increased end-to-end delay of multi-hop packet transmissions.To address this issue,in this paper we propose a new duty-cycling mechanism called DC-Gear.DC-Gear exploits a "sleep less but save more" phenomenon,which means increasing the duty cycle in a timely and appropriate manner whileminimizing the overall energy cost and satisfying the end-to-end delay constraint.We have implemented DC-Gear with TelosB motes and demonstrated its performance advantages through extensive experiments.