Picosecond coherent electron motion in a silicon single-electron source

Understanding ultrafast coherent electron dynamics is necessary for application of a single-electron source to metrological standards, quantum information processing, including electron quantum optics, and quantum sensing. While the dynamics of an electron emitted from the source has been extensively studied, there is as yet no study of the dynamics inside the source. This is because the speed of the internal dynamics is typically higher than 100 GHz, beyond state-of-the-art experimental bandwidth. Here, we theoretically and experimentally demonstrate that the internal dynamics in a silicon singleelectron source comprising a dynamic quantum dot can be detected, utilising a resonant level with which the dynamics is read out as gate-dependent current oscillations. Our experimental observation and simulation with realistic parameters show that an electron wave packet spatially oscillates quantum-coherently at $\sim$ 200 GHz inside the source. Our results will lead to a protocol for detecting such fast dynamics in a cavity and offer a means of engineering electron wave packets. This could allow high-accuracy current sources, high-resolution and high-speed electromagnetic-field sensing, and high-fidelity initialisation of flying qubits

Abundance, movements and biodiversity of flying predatory insects in crop and non-crop agroecosystems

[EN] Predatory insects are key natural enemies that can highly reduce crops pest damage. However, there is a lack of knowledge about the movements of flying predatory insects in agroecosystems throughout the year. In particular, it is still unclear how these predators move from crop to non-crop habitats, which are the preferred habitats to overwinter and to spread during the spring and if these predators leave or stay after chemical treatments. Here, the Neuroptera, a generalist, highly mobile, flying predator order of insects, was selected as model. We studied the effects of farming management and the efficiency of edge shelterbelts, ground cover vegetation, and fruit trees canopy on holding flying predatory insects in Mediterranean traditional agroecosystems. Seasonal movements and winter effects were also assessed. We evaluated monthly nine fruit agroecosystems, six organic, and three pesticides sprayed, of 0.5-1 ha in eastern Spain during 3 years using two complementary methods, yellow sticky traps and aspirator. Results show surprisingly that the insect abundance was highest in pesticide sprayed systems, with 3.40 insects/sample versus 2.32 insects/sample in organic systems. The biodiversity indices were highest in agroecosystems conducted under organic management, with S of 4.68 and D of 2.34. Shelterbelts showed highest biodiversity indices, S of 3.27 and D of 1.93, among insect habitats. Insect species whose adults were active during the winter preferred fruit trees to spend all year round. However, numerous species moved from fruit trees to shelterbelts to overwinter and dispersed into the orchard during the following spring. The ground cover vegetation showed statistically much lower attractiveness for flying predatory insects than other habitats. Shelterbelts should therefore be the first option in terms of investment in ecological infrastructures enhancing flying predators.Sorribas Mellado, JJ.; González Cavero, S.; Domínguez Gento, A.; Vercher Aznar, R. (2016). Abundance, movements and biodiversity of flying predatory insects in crop and non-crop agroecosystems. Agronomy for Sustainable Development. 36(2). doi:10.1007/s13593-016-0360-3S362Altieri MA, Letourneau DK (1982) Vegetation management and biological control in agroecosystems. Crop Prot 1:405–430. doi: 10.1016/0261-2194(82)90023-0Altieri MA, Schmidt LL (1986) The dynamics of colonizing arthropod communities at the interface of abandoned, organic and commercial apple orchards and adjacent woodland habitats. Agric Ecosyst Environ 16:29–43. doi: 10.1016/0167-8809(86)90073-3Bengtsson J, Ahnström J, Weibull A (2005) The effects of organic agriculture on biodiversity and abundance: a meta-analysis. 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Biol Conserv 54:193–207. doi: 10.1016/0006-3207(90)90051-PEilenberg J, Hajek A, Lomer C (2001) Suggestions for unifying the terminology in biological control. BioControl 46:387–400. doi: 10.1023/A:1014193329979Forman RTT, Baudry J (1984) Hedgerows and hedgerow networks in landscape ecology. Environ Manage 8:495–510. doi: 10.1007/BF01871575Gurr GM, Wratten SD, Luna JM (2003) Multi-function agricultural biodiversity: pest management and other benefits. Basic Appl Ecol 4:107–116. doi: 10.1078/1439-1791-00122Hole DG, Perkins AJ et al (2005) Does organic farming benefit biodiversity? Biol Conserv 122:113–130. doi: 10.1016/j.biocon.2004.07.018Landis DA, Wratten SD, Gurr GM (2000) Habitat management to conserve natural enemies of arthropod pests in agriculture. Annu Rev Entomol 45:175–201. doi: 10.1146/annurev.ento.45.1.175Long RF, Corbett A, Lamb C, Reberg-Horton C, Chandler J, Stimmann M (1998) Beneficial insects move from flowering plants to nearby crops. 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Effectiveness of an mHealth intervention combining a smartphone app and smart band on body composition in an overweight and obese population: Randomized controlled trial (EVIDENT 3 study)

Background: Mobile health (mHealth) is currently among the supporting elements that may contribute to an improvement in health markers by helping people adopt healthier lifestyles. mHealth interventions have been widely reported to achieve greater weight loss than other approaches, but their effect on body composition remains unclear. Objective: This study aimed to assess the short-term (3 months) effectiveness of a mobile app and a smart band for losing weight and changing body composition in sedentary Spanish adults who are overweight or obese. Methods: A randomized controlled, multicenter clinical trial was conducted involving the participation of 440 subjects from primary care centers, with 231 subjects in the intervention group (IG; counselling with smartphone app and smart band) and 209 in the control group (CG; counselling only). Both groups were counselled about healthy diet and physical activity. For the 3-month intervention period, the IG was trained to use a smartphone app that involved self-monitoring and tailored feedback, as well as a smart band that recorded daily physical activity (Mi Band 2, Xiaomi). Body composition was measured using the InBody 230 bioimpedance device (InBody Co., Ltd), and physical activity was measured using the International Physical Activity Questionnaire. Results: The mHealth intervention produced a greater loss of body weight (–1.97 kg, 95% CI –2.39 to –1.54) relative to standard counselling at 3 months (–1.13 kg, 95% CI –1.56 to –0.69). Comparing groups, the IG achieved a weight loss of 0.84 kg more than the CG at 3 months. The IG showed a decrease in body fat mass (BFM; –1.84 kg, 95% CI –2.48 to –1.20), percentage of body fat (PBF; –1.22%, 95% CI –1.82% to 0.62%), and BMI (–0.77 kg/m2, 95% CI –0.96 to 0.57). No significant changes were observed in any of these parameters in men; among women, there was a significant decrease in BMI in the IG compared with the CG. When subjects were grouped according to baseline BMI, the overweight group experienced a change in BFM of –1.18 kg (95% CI –2.30 to –0.06) and BMI of –0.47 kg/m2 (95% CI –0.80 to –0.13), whereas the obese group only experienced a change in BMI of –0.53 kg/m2 (95% CI –0.86 to –0.19). When the data were analyzed according to physical activity, the moderate-vigorous physical activity group showed significant changes in BFM of –1.03 kg (95% CI –1.74 to –0.33), PBF of –0.76% (95% CI –1.32% to –0.20%), and BMI of –0.5 kg/m2 (95% CI –0.83 to –0.19). Conclusions: The results from this multicenter, randomized controlled clinical trial study show that compared with standard counselling alone, adding a self-reported app and a smart band obtained beneficial results in terms of weight loss and a reduction in BFM and PBF in female subjects with a BMI less than 30 kg/m2 and a moderate-vigorous physical activity level. Nevertheless, further studies are needed to ensure that this profile benefits more than others from this intervention and to investigate modifications of this intervention to achieve a global effect

A fuzzy analytic hierarchy process (AHP)/data envelopment analysis (DEA) hybrid model for efficiently allocating energy R&D resources:In the case of energy technologies against high oil prices

“The Low Carbon, Green Growth” was declared as Korean national agenda in 2008. Korea has been enhancing the green growth for the sustainable economic development and fostering energy. To improve Korean national energy security and promote the “Low Carbon, Green Growth”, we established a long term strategic energy technology roadmap. In this paper, five criteria, such as economical impact, commercial potential, inner capacity, technical spin-off, and development cost, were used to assess the strategic energy technologies against high oil prices. We developed the integrated two-stage multi-criteria decision making (MCDM) approach which was used to evaluate the relative weights of criteria and measures the relative efficiency of energy technologies against high oil prices. On the first stage, the fuzzy analytic hierarchy process, reflecting the vagueness of human thought with interval values instead of crisp numbers, allocated the relative weights of criteria effectively instead of the AHP approach. On the second stage, the data envelopment analysis approach measured the relative efficiency of energy technologies against high oil prices with economic viewpoints. The relative efficiency score of energy technologies against high oil prices can be the fundamental decision making data which help decision markers to effectively allocate the limited R&D resources

Econometric analysis of the R&D performance in the national hydrogen energy technology development for measuring relative efficiency:The fuzzy AHP/DEA integrated model approach

Hydrogen energy technology can be one of the best key players related to the sector of the United Nations Framework Convention on Climate Change (UNFCCC) and the hydrogen economy. Comparing to other technologies, hydrogen energy technology is more environmentally sound and friendly energy technology and has great potential as a future dominant energy carrier. Advanced nations including Korea have been focusing on the development of hydrogen energy technology R&D for the sustainable development and low carbon green society. In this paper, we applied the integrated fuzzy analytic hierarchy process (Fuzzy AHP) and the data envelopment analysis (DEA) for measuring the relative efficiency of the R&D performance in the national hydrogen energy technology development. On the first stage, the fuzzy AHP effectively reflects the vagueness of human thought. On the second stage, the DEA approach measures the relative efficiency of the national R&D performance in the sector of hydrogen energy technology development with economic viewpoints. The efficiency score can be the fundamental data for policymakers for the well focused R&D planning. Crow

Measuring the relative efficiency of hydrogen energy technologies for implementing the hydrogen economy:An integrated fuzzy AHP/DEA approach

To provide and improve national energy security and low-carbon green energy economy, as a government-supported research institute related to developing new and renewable energy technologies, including energy efficiency, Korea Institute of Energy Research (KIER) needs to establish a long-term strategic energy technology roadmap (ETRM) in the hydrogen economy sector for sustainable economic development. In this paper, we establish a strategic ETRM for hydrogen energy technologies in the hydrogen economy considering five criteria: economic impact (EI), commercial potential (CP), inner capacity (IC), technical spin-off (TS), and development cost (DC). As an extended research, we apply the integrated two-stage multi-criteria decision-making approach, including the hybrid fuzzy analytic hierarchy process (AHP) and data envelopment analysis (DEA) model, to assess the relative efficiency of hydrogen energy technologies in order to scientifically implement the hydrogen economy. Fuzzy AHP reflects the vagueness of human thought with interval values, and allocates the relative importance and weights of four criteria: EI, CP, IC, and TS. The DEA approach measures the relative efficiency of hydrogen energy technologies for the hydrogen economy with a ratio of outputs over inputs. The result of measuring the relative efficiency of hydrogen energy technologies focuses on 4 hydrogen technologies out of 13 hydrogen energy technologies. KIER has to focus on developing 4 strategic hydrogen energy technologies from economic view point in the first phase with limited resources. In addition, if energy policy makers consider as some candidates for strategic hydrogen technologies of the other 9 hydrogen energy technology, the performance and productivity of 9 hydrogen energy technologies should be increased and the input values of them have to be decreased. With a scientific decision-making approach, we can assess the relative efficiency of hydrogen energy technologies efficiently and allocate limited research and development (R&D) resources effectively for well-focused R&D