Salt tolerance is an important constrain for rice, which is generally categorized as a typicalglycophyte. Soil salinity is one of the major constraints affecting rice production worldwide, especially ...inthe coastal areas. Susceptibility or tolerance of rice plants to high salinity is a coordinated action ofmultiple stress responsive genes, which also interacts with other components of stress signaltransduction pathways. Salt tolerant varieties can be produced by marker-assisted selection or geneticengineering by introducing salt-tolerance genes. In this review, we have updated on mechanisms andgenes which can help in transferring of the salt tolerance into high-yielding rice varieties. We havefocused on the need for integrating phenotyping, genomics, metabolic profiling and phenomics intotransgenic and breeding approaches to develop high-yielding as well as salt tolerant rice varieties.
The poor photovoltaic performance of state‐of‐the‐art blends of poly4,8‐bis(2‐ethylhexyl)oxybenzo1,2‐b:4,5‐b′dithiophene‐2,6‐diyl3‐fluoro‐2‐(2‐ethylhexyl)carbonylthieno3,4‐bthiophenediyl (PTB7) and ...6,6‐phenyl‐C61‐butyric acid (PCBM) at large active layer thicknesses is studied using space‐charge‐limited current mobility and photovoltaic device measurements. The poor performance is found to result from relatively low electron mobility. This is attributed to the low tendency of PTB7 to aggregate, which reduces the ability of the fullerene to form a connected network. Increasing the PCBM content 60–80 wt% increases electron mobility and accordingly improves performance for thicker devices, resulting in a fill factor (FF) close to 0.6 at 300 nm. The result confirms that by improving only the connectivity of the fullerene phase, efficient electron and hole collection is possible for 300 nm‐thick PTB7:PCBM devices. Furthermore, it is shown that solvent additive 1,8‐diiodooctane (DIO), used in the highest efficiency PTB7:PCBM devices, does not improve the thickness dependence and, accordingly, does not lead to an increase in either hole or electron mobility or in the carrier lifetime. A key challenge for researchers is therefore to develop new methods to ensure connectivity in the fullerene phase in blends without relying on either a large excess of fullerene or strong aggregation of the polymer.
Low electron mobility is identified as the primary reason for the poor thickness dependence of poly4,8‐bis(2‐ethylhexyl)oxybenzo1,2‐b:4,5‐b′dithiophene‐2,6‐diyl3‐fluoro‐2‐(2‐ethylhexyl)carbonylthieno3,4‐bthiophenediyl (PTB7):6,6‐phenyl‐C61‐butyric acid (PCBM) organic photovoltaic (OPV) devices relative to poly(3‐hexylthiophene) (P3HT):PCBM. A thickness dependence in PTB7:PCBM comparable to that in P3HT:PCBM is achieved using an increased fullerene loading, demonstrating the considerable efficiency gains available through improving connectivity in the fullerene phase.
The pandemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused a public health emergency, and research on the development of various types of vaccines is rapidly progressing ...at an unprecedented development speed internationally. Some vaccines have already been approved for emergency use and are being supplied to people around the world, but there are still many ongoing efforts to create new vaccines. Virus-like particles (VLPs) enable the construction of promising platforms in the field of vaccine development. Here, we demonstrate that non-infectious SARS-CoV-2 VLPs can be successfully assembled by co-expressing three important viral proteins membrane (M), envelop (E) and nucleocapsid (N) in plants. Plant-derived VLPs were purified by sedimentation through a sucrose cushion. The shape and size of plant-derived VLPs are similar to native SARS-CoV-2 VLPs without spike. Although the assembled VLPs do not have S protein spikes, they could be developed as formulations that can improve the immunogenicity of vaccines including S antigens, and further could be used as platforms that can carry S antigens of concern for various mutations.
The coordination chemistry of plant polyphenols and metal ions can be used for coating various substrates and for creating modular superstructures. We herein explored this chemistry for the ...controlled release of guests from mesoporous silica nanoparticles (MSNs). The selective adsorption of tannic acids (TAs) on MSN silica walls opens the MSN mesoporous channels without disturbing mass transport. The channel may be closed by the coordination of TA with CuII ions. Upon exposure to light, photolysis of Trojan horse guests (photoacid generators, PAGs) leads to acid generation, which enables the release of payloads by decomposing the outer coordination shell consisting of TA and CuII. We also fabricated a modular assembly of MSNs on glass substrates. The photoresponsive release characteristics of the resulting film are similar to those of the individual MSNs. This method is a fast and facile strategy for producing photoresponsive nanocontainers by non‐covalent engineering of MSN surfaces that should be suitable for various applications in materials science.
The unique adsorption and coordination characteristics of tannic acid were used to fabricate a photolatent supramolecular cage. Mesoporous silica nanoparticles that had been loaded with a photoacid generator and guest molecules were wrapped with a shell of tannic acid and CuII ions. Photoresponsive hybrid assemblies that can release guest molecules on demand were obtained.
Abstract
We investigate the origin of star formation activity in early-type galaxies with current star formation using spatially resolved spectroscopic data from the Mapping Nearby Galaxies at Apache ...Point Observatory in the Sloan Digital Sky Survey (SDSS). We first identify star-forming early-type galaxies from the SDSS sample, which are morphologically early-type but show current star formation activity in their optical spectra. We then construct comparison samples with different combinations of star formation activity and morphology, which include star-forming late-type galaxies, quiescent early-type galaxies, and quiescent late-type galaxies. Our analysis of the optical spectra reveals that the star-forming early-type galaxies have two distinctive episodes of star formation, which is similar to late-type galaxies but different from quiescent early-type galaxies with a single star formation episode. Star-forming early-type galaxies have properties in common with star-forming late-type galaxies, which include stellar population, gas and dust content, mass, and environment. However, the physical properties of star-forming early-type galaxies derived from spatially resolved spectroscopy differ from those of star-forming late-type galaxies in the sense that the gas in star-forming early-type galaxies is more concentrated than their stars, and is often kinematically misaligned with stars. The age gradient of star-forming early-type galaxies also differs from those of star-forming late-type galaxies. Our findings suggest that the current star formation in star-forming early-type galaxies has an external origin including galaxy mergers or accretion gas from the cosmic web.
We report on solid-state mesoscopic heterojunction solar cells employing nanoparticles (NPs) of methyl ammonium lead iodide (CH(3)NH(3))PbI(3) as light harvesters. The perovskite NPs were produced by ...reaction of methylammonium iodide with PbI(2) and deposited onto a submicron-thick mesoscopic TiO(2) film, whose pores were infiltrated with the hole-conductor spiro-MeOTAD. Illumination with standard AM-1.5 sunlight generated large photocurrents (J(SC)) exceeding 17 mA/cm(2), an open circuit photovoltage (V(OC)) of 0.888 V and a fill factor (FF) of 0.62 yielding a power conversion efficiency (PCE) of 9.7%, the highest reported to date for such cells. Femto second laser studies combined with photo-induced absorption measurements showed charge separation to proceed via hole injection from the excited (CH(3)NH(3))PbI(3) NPs into the spiro-MeOTAD followed by electron transfer to the mesoscopic TiO(2) film. The use of a solid hole conductor dramatically improved the device stability compared to (CH(3)NH(3))PbI(3) -sensitized liquid junction cells.
Electric vehicles (EVs) parking lots are representing significant charging loads for relatively a long period of time. Therefore, the aggregated charging load of EVs may coincide with the peak demand ...of the distribution power system and can greatly stress the power grid. The stress on the power grid can be characterized by the additional electricity demand and the introduction of a new peak load that may overwhelm both the substations and transmission systems. In order to avoid the stress on the power grid, the parking lot operators are required to limit the penetration level of EVs and optimally distribute the available power among them. This affects the EV owner’s quality of experience (QoE) and thereby reducing the quality of performance (QoP) for the parking lot operators. The QoE is represents the satisfaction level of EV owners; whereas, the QoP is a measurement representing the ratio of EVs with QoE to the total number of EVs. This study proposes a fuzzy logic weight-based charging scheme (FLWCS) to optimally distribute the charging power among the most appropriate EVs in such a way that maximizes the QoP for the parking lot operators under the operational constraints of the power grid. The developed fuzzy inference mechanism resolves the uncertainties and correlates the independent inputs such as state-of-charge, the remaining parking duration and the available power into weighted values for the EVs in each time slot. Once the weight values for all EVs are known, their charging operations are controlled such that the operational constraints of the power grid are respected in each time slot. The proposed FLWCS is applied to a parking lot with different capacities. The simulation results reveal an improved QoP comparing to the conventional first-come-first-served (FCFS) based scheme.
This paper proposes an optimal route and charging station selection (RCS) algorithm based on model-free deep reinforcement learning (DRL) to overcome the uncertainty issues of the traffic conditions ...and dynamic arrival charging requests. The proposed DRL based RCS algorithm aims to minimize the total travel time of electric vehicles (EV) charging requests from origin to destination using the selection of the optimal route and charging station considering dynamically changing traffic conditions and unknown future requests. In this paper, we formulate this RCS problem as a Markov decision process model with unknown transition probability. A Deep Q network has been adopted with function approximation to find the optimal electric vehicle charging station (EVCS) selection policy. To obtain the feature states for each EVCS, we define the traffic preprocess module, charging preprocess module and feature extract module. The proposed DRL based RCS algorithm is compared with conventional strategies such as minimum distance, minimum travel time, and minimum waiting time. The performance is evaluated in terms of travel time, waiting time, charging time, driving time, and distance under the various distributions and number of EV charging requests.
The widespread adoption of electric vehicles (EVs) has entailed the need for the parking lot operators to satisfy the charging and discharging requirements of all the EV owners during their parking ...duration. Meanwhile, the operational constraints of the power grids limit the amount of simultaneous charging and discharging of all EVs. This affects the EV owner’s quality of experience (QoE) and thereby reducing the quality of performance (QoP) for the parking lot operators. The QoE represents a certain percentage of the EV battery required for its next trip distance; whereas, the QoP refers to the ratio of EVs with satisfied QoE to the total number of EVs during the operational hours of the parking lot. This paper proposes a two-stage fuzzy logic inference based algorithm (TSFLIA) to schedule the charging and discharging operations of EVs in such a way that maximizes the QoP for the parking lot operators under the operational constraints of the power grid. The first stage fuzzy inference system (FIS) of TSFLIA is modeled based on the real-time arrival and departure probability density functions in order to calculate the aggregated charging and discharging energies of EVs according to their next trip distances. The second stage FIS evaluates several dynamic and uncertain input parameters from the electric grid and from EVs to distribute the aggregated energy among the EVs by controlling their charging and discharging operations through preference variables. The feasibility and effectiveness of the proposed algorithm are demonstrated through the IEEE 34-node distribution system.
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