Poly(AAc-co-DMAPMA) membrane (PADMA) is synthesized by free radical aqueous copolymerization of acrylic acid (AAc) and N-3-[dimethylamino)propyl]-methacrylamide (DMAPMA) to check its stability and conductivity. The hy...Poly(AAc-co-DMAPMA) membrane (PADMA) is synthesized by free radical aqueous copolymerization of acrylic acid (AAc) and N-3-[dimethylamino)propyl]-methacrylamide (DMAPMA) to check its stability and conductivity. The hydrogel membrane characterized physically to study morphology by SEM, thermal stability by TGA and mechanical stability by measuring compressive strength and ionic conductivity by electrochemical impedance spectroscopy in alkaline as well as in acidic environment at different temperatures. The compression modulus of the hydrogel membrane is 24 kPa at pH = 1.0 and 16 kPa at pH = 7.0, and stable (no fracture) till 72% deformation. The PADMA hydrogel membrane ionic conductivity increased with the increase in temperature and structurally stable up to 190°C. Improvement in ionic conductivity is observed after the heat treatment of the membrane. Compared with ionic conductivity of Nafion? (SE512), the PADMA membrane found to be inferior. However, the PADMA hydrogel membrane conductivity was greater (~1 × 10-4S/cm) at low and high pH compared with neutral pH (~1 × 10-5S/cm) indicating the possibility of using the membrane as either a proton and hydroxyl ion conductor.展开更多
Background： Canopy structure, defined by leaf area index （LAI）, fractional vegetation cover （FCover） and fraction of absorbed photosynthetically active radiation （fAPAR）, regulates a wide range of forest functi...Background： Canopy structure, defined by leaf area index （LAI）, fractional vegetation cover （FCover） and fraction of absorbed photosynthetically active radiation （fAPAR）, regulates a wide range of forest functions and ecosystem services. Spatially consistent field-measurements of canopy structure are however lacking, particularly for the tropics. Methods： Here, we introduce the Global LAI database： a global dataset of field-based canopy structure measurements spanning tropical forests in four continents （Africa, Asia, Australia and the Americas）. We use these measurements to test for climate dependencies within and across continents, and to test for the potential of anthropogenic disturbance and forest protection to modulate those dependences. Results： Using data collected from 887 tropical forest plots, we show that maximum water deficit, defined across the most arid months of the year, is an important predictor of canopy structure, with all three canopy attributes declining significantly with increasing water deficit. Canopy attributes also increase with minimum temperature, and with the protection of forests according to both active （within protected areas） and passive measures （through topography）. Once protection and continent effects are accounted for, other anthropogenic measures （e.g. human population） do not improve the model. Conclusions： We conclude that canopy structure in the tropics is primarily a consequence of forest adaptation to the maximum water deficits historically experienced within a given region. Climate change, and in particular changes in drought regimes may thus affect forest structure and function, but forest protection may offer some resilience against this effect.展开更多
When a person's neuromuscular system is affected by an injury or disease,Activities‐for‐Daily‐Living(ADL),such as gripping,turning,and walking,are impaired.Electroen-cephalography(EEG)and Electromyography(EMG)a...When a person's neuromuscular system is affected by an injury or disease,Activities‐for‐Daily‐Living(ADL),such as gripping,turning,and walking,are impaired.Electroen-cephalography(EEG)and Electromyography(EMG)are physiological signals generated by a body during neuromuscular activities embedding the intentions of the subject,and they are used in Brain–Computer Interface(BCI)or robotic rehabilitation systems.However,existing BCI or robotic rehabilitation systems use signal classification technique limitations such as(1)missing temporal correlation of the EEG and EMG signals in the entire window and(2)overlooking the interrelationship between different sensors in the system.Furthermore,typical existing systems are designed to operate based on the presence of dominant physiological signals associated with certain actions;(3)their effectiveness will be greatly reduced if subjects are disabled in generating the dominant signals.A novel classification model,named BIOFIS is proposed,which fuses signals from different sensors to generate inter‐channel and intra‐channel relationships.It ex-plores the temporal correlation of the signals within a timeframe via a Long Short‐Term Memory(LSTM)block.The proposed architecture is able to classify the various subsets of a full‐range arm movement that performs actions such as forward,grip and raise,lower and release,and reverse.The system can achieve 98.6%accuracy for a 4‐way action using EEG data and 97.18%accuracy using EMG data.Moreover,even without the dominant signal,the accuracy scores were 90.1%for the EEG data and 85.2%for the EMG data.The proposed mechanism shows promise in the design of EEG/EMG‐based use in the medical device and rehabilitation industries.展开更多
Apart from the direct threat to human lives, the flood waves as a result of the rapid catchment response to intense rainfall, breaches of flood defences, tsunamis or storm surges may induce huge impact forces on struc...Apart from the direct threat to human lives, the flood waves as a result of the rapid catchment response to intense rainfall, breaches of flood defences, tsunamis or storm surges may induce huge impact forces on structures, causing structural damage or even failures. Most existing design codes do not properly account for these impact forces due to the limited understanding of the underlying physical processes and the lack of reliable empirical formulae or numerical approaches to quantifying them. This paper presents laboratory experiments to better understand the interaction between the extreme flow hydrodynamics and the hydraulic structures and uses the measured data to validate a numerical model. The model solves the two-dimensional shallow water equations using a finite volume Godunov-type scheme for the reliable simulation of complex flow hydrodynamics. New model components are developed for estimating the hydrostatic and hydrodynamic pressure to quantify the flow impact on structures. The model is applied to reproduce two selected experiment tests with different settings and satisfactory numerical results are obtained, which confirms its predictive capability. The model will therefore provide a potential tool for wider and more flexible field-scale applications.展开更多
文摘Poly(AAc-co-DMAPMA) membrane (PADMA) is synthesized by free radical aqueous copolymerization of acrylic acid (AAc) and N-3-[dimethylamino)propyl]-methacrylamide (DMAPMA) to check its stability and conductivity. The hydrogel membrane characterized physically to study morphology by SEM, thermal stability by TGA and mechanical stability by measuring compressive strength and ionic conductivity by electrochemical impedance spectroscopy in alkaline as well as in acidic environment at different temperatures. The compression modulus of the hydrogel membrane is 24 kPa at pH = 1.0 and 16 kPa at pH = 7.0, and stable (no fracture) till 72% deformation. The PADMA hydrogel membrane ionic conductivity increased with the increase in temperature and structurally stable up to 190°C. Improvement in ionic conductivity is observed after the heat treatment of the membrane. Compared with ionic conductivity of Nafion? (SE512), the PADMA membrane found to be inferior. However, the PADMA hydrogel membrane conductivity was greater (~1 × 10-4S/cm) at low and high pH compared with neutral pH (~1 × 10-5S/cm) indicating the possibility of using the membrane as either a proton and hydroxyl ion conductor.
基金supported by the‘Uncovering the variable roles of fire in savannah ecosystems’project,funded by Leverhulme Trust under grant IN-2014-022 and‘Resilience in East African Landscapes’project funded by European Commission Marie Curie Initial Training Network(FP7-PEOPLE-2013-ITN project number606879)funding from Australian Research Council,IUCN Sustain/African Wildlife Foundation and University of York Research Pump Priming Fund+1 种基金funding through the European Research Council ERC-2011-St G_20101109(project number 281986)and the British Ecological Society-Ecologists in Africa programmesupport through the‘Climate Change Impacts on Ecosystem Services and Food Security in Eastern Africa(CHIESA)’project(2011–2015),which was funded by the Ministry for Foreign Affairs of Finland,and coordinated by the International Centre of Insect Physiology and Ecology(icipe)in Nairobi,Kenya
文摘Background： Canopy structure, defined by leaf area index （LAI）, fractional vegetation cover （FCover） and fraction of absorbed photosynthetically active radiation （fAPAR）, regulates a wide range of forest functions and ecosystem services. Spatially consistent field-measurements of canopy structure are however lacking, particularly for the tropics. Methods： Here, we introduce the Global LAI database： a global dataset of field-based canopy structure measurements spanning tropical forests in four continents （Africa, Asia, Australia and the Americas）. We use these measurements to test for climate dependencies within and across continents, and to test for the potential of anthropogenic disturbance and forest protection to modulate those dependences. Results： Using data collected from 887 tropical forest plots, we show that maximum water deficit, defined across the most arid months of the year, is an important predictor of canopy structure, with all three canopy attributes declining significantly with increasing water deficit. Canopy attributes also increase with minimum temperature, and with the protection of forests according to both active （within protected areas） and passive measures （through topography）. Once protection and continent effects are accounted for, other anthropogenic measures （e.g. human population） do not improve the model. Conclusions： We conclude that canopy structure in the tropics is primarily a consequence of forest adaptation to the maximum water deficits historically experienced within a given region. Climate change, and in particular changes in drought regimes may thus affect forest structure and function, but forest protection may offer some resilience against this effect.
文摘When a person's neuromuscular system is affected by an injury or disease,Activities‐for‐Daily‐Living(ADL),such as gripping,turning,and walking,are impaired.Electroen-cephalography(EEG)and Electromyography(EMG)are physiological signals generated by a body during neuromuscular activities embedding the intentions of the subject,and they are used in Brain–Computer Interface(BCI)or robotic rehabilitation systems.However,existing BCI or robotic rehabilitation systems use signal classification technique limitations such as(1)missing temporal correlation of the EEG and EMG signals in the entire window and(2)overlooking the interrelationship between different sensors in the system.Furthermore,typical existing systems are designed to operate based on the presence of dominant physiological signals associated with certain actions;(3)their effectiveness will be greatly reduced if subjects are disabled in generating the dominant signals.A novel classification model,named BIOFIS is proposed,which fuses signals from different sensors to generate inter‐channel and intra‐channel relationships.It ex-plores the temporal correlation of the signals within a timeframe via a Long Short‐Term Memory(LSTM)block.The proposed architecture is able to classify the various subsets of a full‐range arm movement that performs actions such as forward,grip and raise,lower and release,and reverse.The system can achieve 98.6%accuracy for a 4‐way action using EEG data and 97.18%accuracy using EMG data.Moreover,even without the dominant signal,the accuracy scores were 90.1%for the EEG data and 85.2%for the EMG data.The proposed mechanism shows promise in the design of EEG/EMG‐based use in the medical device and rehabilitation industries.
基金supported by the National Natural Science Foundation of China(Grant Nos.51379074,51411130125)the Chinese Government "Recruitment Program of Global Experts"
文摘Apart from the direct threat to human lives, the flood waves as a result of the rapid catchment response to intense rainfall, breaches of flood defences, tsunamis or storm surges may induce huge impact forces on structures, causing structural damage or even failures. Most existing design codes do not properly account for these impact forces due to the limited understanding of the underlying physical processes and the lack of reliable empirical formulae or numerical approaches to quantifying them. This paper presents laboratory experiments to better understand the interaction between the extreme flow hydrodynamics and the hydraulic structures and uses the measured data to validate a numerical model. The model solves the two-dimensional shallow water equations using a finite volume Godunov-type scheme for the reliable simulation of complex flow hydrodynamics. New model components are developed for estimating the hydrostatic and hydrodynamic pressure to quantify the flow impact on structures. The model is applied to reproduce two selected experiment tests with different settings and satisfactory numerical results are obtained, which confirms its predictive capability. The model will therefore provide a potential tool for wider and more flexible field-scale applications.
