Modelling the impact of social network on energy savings

It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout programmes

Enhancing Building Semantic Segmentation Accuracy with Super Resolution and Deep Learning: Investigating the Impact of Spatial Resolution on Various Datasets

The development of remote sensing and deep learning techniques has enabled building semantic segmentation with high accuracy and efficiency. Despite their success in different tasks, the discussions on the impact of spatial resolution on deep learning based building semantic segmentation are quite inadequate, which makes choosing a higher cost-effective data source a big challenge. To address the issue mentioned above, in this study, we create remote sensing images among three study areas into multiple spatial resolutions by super-resolution and down-sampling. After that, two representative deep learning architectures: UNet and FPN, are selected for model training and testing. The experimental results obtained from three cities with two deep learning models indicate that the spatial resolution greatly influences building segmentation results, and with a better cost-effectiveness around 0.3m, which we believe will be an important insight for data selection and preparation

Spatial Optimization of Residential Urban District - Energy and Water Perspectives

AbstractMany cities around the world have reached a critical situation when it comes to energy and water supply, threatening the urban sustainable development. The aim of this paper is to develop a spatial optimization model for the planning of residential urban districts with special consideration of renewables and water harvesting integration. In particular, the paper analyses the optimal configuration of built environment area, PV area, wind turbines number and relative occupation area, battery and water harvester storage capacities, as a function of electricity and water prices. The optimization model is multi-objective which uses a genetic algorithm to minimize the system life cycle costs, and maximize renewables and water harvesting reliability.The developed model can be used for spatial optimization design of new urban districts. It can also be employed for analyzing the performances of existing urban districts under an energy-water-economic viewpoint.Assuming a built environment area equal to 75% of the total available area, the results show that the reliability of the renewables and water harvesting system cannot exceed the 6475 and 2500 hours/year, respectively. The life cycle costs of integrating renewables and water harvesting into residential districts are mainly sensitive to the battery system specific costs since most of the highest renewables reliabilities are guaranteed through the energy storage system

PGAweb: A Web Server for Bacterial Pan-Genome Analysis

An astronomical increase in microbial genome data in recent years has led to strong demand for bioinformatic tools for pan-genome analysis within and across species. Here, we present PGAweb, a user-friendly, web-based tool for bacterial pan-genome analysis, which is composed of two main pan-genome analysis modules, PGAP and PGAP-X. PGAweb provides key interactive and customizable functions that include orthologous clustering, pan-genome profiling, sequence variation and evolution analysis, and functional classification. PGAweb presents features of genomic structural dynamics and sequence diversity with different visualization methods that are helpful for intuitively understanding the dynamics and evolution of bacterial genomes. PGAweb has an intuitive interface with one-click setting of parameters and is freely available at http://PGAweb.vlcc.cn/

China's coal-fired power plants impose pressure on water resources

Coal is the dominant fuel for electricity generation around the world. This type of electricity generation uses large amounts of water, increasing pressure on water resources. This calls for an in-depth investigation in the water-energy nexus of coal-fired electricity generation. In China, coal-fired power plants play an important role in the energy supply. Here we assessed water consumption of coal-fired power plants (CPPs) in China using four cooling technologies: closed-cycle cooling, once-through cooling, air cooling, and seawater cooling. The results show that water consumption of CPPs was 3.5 km3, accounting for 11% of total industrial water consumption in China. Eighty-four percent of this water consumption was from plants with closed-cycle cooling. China's average water intensity of CPPs was 1.15 l/kWh, while the intensity for closed-cycle cooling was 3-10 times higher than that for other cooling technologies. About 75% of water consumption of CPPs was from regions with absolute or chronic water scarcity. The results imply that the development of CPPs needs to explicitly consider their impacts on regional water resources

Simultaneous Single-Position Oblique Lateral Interbody Fusion Combined With Unilateral Percutaneous Pedicle Screw Fixation for Single-Level Lumbar Tuberculosis: A 3-Year Retrospective Comparative Study

Objective To illustrate a simultaneous single-position oblique lateral interbody fusion (SP-OLIF) combined with unilateral percutaneous pedicle screw fixation in treating single-level lumbar tuberculosis, compared with posterior-only approach in clinical and radiographic evaluations. Methods Consecutive patients who had undergone surgeries for single-level lumbar tuberculosis from January 2018 to December 2020 were retrospectively reviewed. The patients included were divided into SP-OLIF and posterior-only groups according to surgical methods applied, with follow-up for at least 36 months. Outcomes included estimated blood loss, operative time, and complications for safety evaluation; visual analogue scale (VAS), Oswestry Disability Index (ODI) for efficacy evaluation; erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) for evaluating tuberculosis activity; x-ray and computed tomography scan were used for radiographic evaluation. Results A total of 136 patients had been enrolled in the study (60 for SP-OLIF and 76 for Posterior-only). The median operative time, blood loss, and hospital stay in SP-OLIF group were significantly less, with a lower complication rate. Meanwhile, the SP-OLIF group showed substantially lower VAS in 1 and 7 days and decreased ODI in the first month postoperatively, without significant difference afterward. Similarly, the median CRP and ESR in SP-OLIF group were significantly lower in 3 and 7 days postoperatively. All indicators had reduced to normal after 3 months. No recurrence had been reported throughout the whole follow-up. Conclusion SP-OLIF was an efficient minimally invasive protocol for single-level lumbar tuberculosis, facilitating earlier clinical improvement, with decreased blood loss, operative time and hospital stay compared with posterior-only approach

Substantially enhanced plasticity of bulk metallic glasses by densifying local atomic packing

Common wisdom to improve ductility of bulk metallic glasses (BMGs) is to introduce local loose packing regions at the expense of strength. Here the authors enhance structural fluctuations of BMGs by introducing dense local packing regions, resulting in simultaneous increase of ductility and strength

Understanding the energy consumption and greenhouse gas emissions and the implication for achieving climate change mitigation targets

[No abstract

Identification of candidate genes and clarification of the maintenance of the green pericarp of weedy rice grains

The weedy rice (Oryza sativa f. spontanea) pericarp has diverse colors (e.g., purple, red, light-red, and white). However, research on pericarp colors has focused on red and purple, but not green. Unlike many other common weedy rice resources, LM8 has a green pericarp at maturity. In this study, the coloration of the LM8 pericarp was evaluated at the cellular and genetic levels. First, an examination of their ultrastructure indicated that LM8 chloroplasts were normal regarding plastid development and they contained many plastoglobules from the early immature stage to maturity. Analyses of transcriptome profiles and differentially expressed genes revealed that most chlorophyll (Chl) degradation-related genes in LM8 were expressed at lower levels than Chl a/b cycle-related genes in mature pericarps, suggesting that the green LM8 pericarp was associated with inhibited Chl degradation in intact chloroplasts. Second, the F2 generation derived from a cross between LM8 (green pericarp) and SLG (white pericarp) had a pericarp color segregation ratio of 9:3:4 (green:brown:white). The bulked segregant analysis of the F2 populations resulted in the identification of 12 known genes in the chromosome 3 and 4 hotspot regions as candidate genes related to Chl metabolism in the rice pericarp. The RNA-seq and sqRT-PCR assays indicated that the expression of the Chl a/b cycle-related structural gene DVR (encoding divinyl reductase) was sharply up-regulated. Moreover, genes encoding magnesium-chelatase subunit D and the light-harvesting Chl a/b-binding protein were transcriptionally active in the fully ripened dry pericarp. Regarding the ethylene signal transduction pathway, the CTR (encoding an ethylene-responsive protein kinase) and ERF (encoding an ethylene-responsive factor) genes expression profiles were determined. The findings of this study highlight the regulatory roles of Chl biosynthesis- and degradation-related genes influencing Chl accumulation during the maturation of the LM8 pericarp