Isolation and characterization of cDNA encoding stilbene synthases from Chinese wild Vitis pseudoreticulata

mRNA differential display was employed to study powdery mildew disease resistance gene expression in Chinese wild Vitis pseudoreticulata 'Baihe-35-1' inoculated with Erysiphe necator (syn. Uncinula necator) under natural field conditions. A cDNA fragment T11AC/B0320-723 showing homology to stilbene synthase (STS) gene expressed more strongly at 1, 3, 5, 7 and 9 days after inoculation of leaves than in controls was found. The full cDNA length was cloned by rapid amplification of cDNA ends (RACE). Sequencing of the full length cDNA revealed cDNA sequences, sized 1288, 1411, 1468, 1492, 1506 and 1556 base pairs encoding 6 homologous polypeptides with 392 amino acid residues each, that were designated as VpSTS1, VpSTS2, VpSTS3, VpSTS4, VpSTS5 and VpSTS6 respectively. The deduced amino acid sequences shared identity of 65 %, 77 % and more than 94 % with Pinus strobus STS, Vitis vinifera chalcone synthase (CHS), and Vitis riparia, Vitis labrusca, Parthenocissus henryana, Cissus rhombifolia, Parthenocissus quinquefolia and Vitis vinifera STS, respectively.

Design and analysis of building thermal model for grid-interactive efficient operations

Heating and cooling in residential buildings, provided by Heating, Ventilation, and Air-Conditioning (HVAC) systems, represent a crucial load for electric utilities. Fluctuations of heating and cooling loads in residential buildings have a significant impact on a utility’s load profile. Electricity suppliers have introduced time-of-day (TOD) or time-of-use (TOU) electricity pricing, making peak electricity very expensive to consumers, as a means of managing load demand when the grid is near capacity. The impact on the utility’s load profile can be mitigated by grid-interactive efficient HVAC operations that reduce the peak load demand. Pre-cooling is a strategy that reduces the load during on-peak hours by shifting cooling operation from on-peak hours to off-peak hours. Accordingly, many manufacturers have built in rule-based pre-cooling operation strategies into their smart thermostats by setting the space temperature a few degrees lower for a period preceding the start of on-peak hours. However, common rule-based pre-cooling operation strategies might not be an optimal solution for a specific home with specific thermal properties and HVAC system cooling capacity under a given utility rate structure and varying weather conditions in terms of cost savings. Moreover, even though the smart thermostat and utility industries have increasingly collected abundant operational data, there is still a lack of a systematic framework that can utilize such data to generate actionable information for advanced home HVAC system diagnosis and control, and for realizing home energy cost savings and grid-interactive efficient operations. Therefore, the primary research question to address in this study is — What is the fundamental system science underlying the design of such a framework using the data collected from smart devices for the intelligent dynamic management of cooling energy use in a home? Recognizing that a home thermal model, which is capable of connecting the data such as weather with HVAC operations, is at the heart of this framework, this study first aims to develop such model that is built upon the standard RC (Resistance–Capacitance) approach for one lumped virtual envelope to describe the thermal dynamics of a home. A parameter estimation scheme is also developed that enables automatic, sequential, and optimal estimation of the model parameters, i.e., the thermal properties, of a home, using the data collected through smart thermostats and internet connections. The technical approach includes the development and validation of the home thermal model and its parameter estimation scheme using data collected from a test home. Moreover, with reasonable simplifications to the home thermal model, a model-based envelope performance evaluation method is also proposed to assess the thermal performance of a home envelope in this study. The simplicity of the method allows the parameter to be automatically estimated using a short period of indoor and outdoor air temperature data through data screening without the need for a home’s physical information. Then, an optimal pre-cooling strategy is developed based on an optimization algorithm that is constructed utilizing the automatically identified home thermal model, which is unique for each home, to search optimal HVAC operations for minimizing energy cost with a given TOU utility rate structure, HVAC system capacity, and weather condition. The algorithm determines the HVAC on/off control signal that minimizes the 24-h energy cost while maintaining thermal comfort and calculates the corresponding optimal indoor air temperature. Through simulations, the results demonstrate that the optimal pre-cooling strategy is indeed significantly more effective than the common rule-based pre-cooling strategies. Since the optimal pre-cooling is heavily dependent on a specific set of conditions, such as specific thermal properties, HVAC system capacity, utility rate structure, and weather condition, the impact of different sets of conditions on the optimal pre-cooling is investigated by the operation and energy performance analysis on the thermal dynamics, total energy consumption, and energy cost and is also compared with a rule-based pre-cooling through simulations. It is found that the optimal pre-cooling is adaptive based on changing conditions and its performance is significantly dependent on weather conditions and home thermal properties, while its performance may vary for different cooling capacities and utility rate structures. The better the home thermal condition is, the less energy cost the operation requires. In terms of weather condition, it has the dominant impact on the performance of the optimal pre-cooling operation. The hotter the weather is in summer, the more cost savings a good thermal condition home can achieve. Moreover, less energy cost can be achieved for a HVAC system with a higher cooling capacity only when a home has a better thermal condition, and also tends to be achieved for a utility rate structure with a much higher on-peak electricity price than the price during off-peak or/and mid-peak hours. For a home with a poor thermal condition, however, it is found that the optimal pre-cooling strategy may need more energy consumption, while the least energy consumption can always be achieved without sacrificing thermal comfort for a home with a good or better thermal condition, compared with rule-based operation pre-cooling strategies. The superb energy performance of the optimal strategy is attributed to a longer runtime of the HVAC system in cool outdoor air conditions and to the elimination of deadband in the HVAC operation, which is required by the rule-based operation strategies, to allow the indoor air temperature to stay near the thermal comfort upper bound as much as possible. These observations are in line with the analysis and expectations and experience. Additionally, this study conducts several experiments through a real test home, including the investigations of the impact of internal heat gains on the home thermal model and cooling load calculations using the mode-based method and the HVAC efficiency. This study also investigates the implementation of the optimal pre-cooling strategy and meanwhile demonstrates the effectiveness of the optimal pre-cooling strategy in terms of the operation and energy performance analysis through experiments. Overall, this study has helped to answer important questions about effective decision making for the operation of HVAC systems, with tremendous potential for minimizing home energy cost. This study is a fundamental research that has culminated in understanding of thermal interactions and investigation of methodologies for achieving grid-interactive efficient operation of HVAC system. This study also contributes to knowledge through the development of step-by-step approach that may be followed to achieve optimal operation of HVAC systems, based on consideration of thermal properties, weather condition, HVAC cooling capacity, and utility rate structure in a smart grid environment. Therefore, the developed framework in this study is useful for advanced home HVAC system diagnosis and control, and for realizing home energy savings and grid-interactive efficient operations

(E)-3-Bromo-N-(1,3-oxazolidin-2-yl­idene)benzamide

The five- and six-membered rings in the title compound, C10H9BrN2O2, are essentially coplanar. This is consistent with a highly conjugated system, as seen in the short N—C bond distances of 1.308 (6) and 1.317 (5) Å

A STUDY ON COPPER SURFACE PRE-TREATMENT AND WELDING WITH LASERS

ABSTRACT To improve the copper absorption coefficient to lasers, and to realize a high welding quality with a low power laser machine, a black-treating method was proposed in this study. With this method, the reflection coefficient of the copper to lasers with 1064nm wavelength could be reduced from 95% to 15.5%. The experimental study of copper welding with a 500 W fiber laser machine was carried out. The shape, the strength and the micro-hardness of the welding seam with different welding velocity and defocus amount were compared. And, the best welding parameter was obtained. Moreover, the laser welding quality of copper with black-treating and that with graphite coating was compared, and the result showed that the microhardness and the strength of the welding seam of copper with black-treating was better than that with graphite coating

Small molecule dopant-free dual hole transporting material for conventional and inverted perovskite solar cells

Interfacial layers play very important roles in perovskite solar cells and the enormous diversity of reported materials has contributed to the outstanding progress of these photovoltaic devices. Nevertheless, the interfacial materials are commonly developed to be used in solar cells with a specific architecture, either conventional (n-i-p) or inverted (p-i-n). We report the exceptional performance of a small molecule, whose structural features, based on hydrogen bond-directed self-assembly, allow its application as hole transporting layer (HTL) in n-i-p and p-i-n perovskite solar cells with the same efficiency. This particularity has been investigated through a comparative study with a very similar molecule that cannot self-assemble, evidencing the benefits of the structural integrity of hydrogen bonded HTLs in terms of charge extraction and recombination, independently on the device architecture.</p

Efficient Video Transformers with Spatial-Temporal Token Selection

Video transformers have achieved impressive results on major video recognition benchmarks, which however suffer from high computational cost. In this paper, we present STTS, a token selection framework that dynamically selects a few informative tokens in both temporal and spatial dimensions conditioned on input video samples. Specifically, we formulate token selection as a ranking problem, which estimates the importance of each token through a lightweight scorer network and only those with top scores will be used for downstream evaluation. In the temporal dimension, we keep the frames that are most relevant to the action categories, while in the spatial dimension, we identify the most discriminative region in feature maps without affecting the spatial context used in a hierarchical way in most video transformers. Since the decision of token selection is non-differentiable, we employ a perturbed-maximum based differentiable Top-K operator for end-to-end training. We mainly conduct extensive experiments on Kinetics-400 with a recently introduced video transformer backbone, MViT. Our framework achieves similar results while requiring 20% less computation. We also demonstrate our approach is generic for different transformer architectures and video datasets. Code is available at https://github.com/wangjk666/STTS.Comment: Accepted by ECCV 202

Ketamine Inhibits Lung Fluid Clearance through Reducing Alveolar Sodium Transport

Ketamine is a broadly used anaesthetic for analgosedation. Accumulating clinical evidence shows that ketamine causes pulmonary edema with unknown mechanisms. We measured the effects of ketamine on alveolar fluid clearance in human lung lobes ex vivo. Our results showed that intratracheal instillation of ketamine markedly decreased the reabsorption of 5% bovine serum albumin instillate. In the presence of amiloride (a specific ENaC blocker), fluid resolution was not further decreased, suggesting that ketamine could decrease amiloride-sensitive fraction of AFC associated with ENaC. Moreover, we measured the regulation of amiloride-sensitive currents by ketamine in A549 cells using whole-cell patch clamp mode. Our results suggested that ketamine decreased amiloride-sensitive Na+ currents (ENaC activity) in a dose-dependent fashion. These data demonstrate that reduction in lung ENaC activity and lung fluid clearance following administration of ketamine may be the crucial step of the pathogenesis of resultant pulmonary edema