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This paper addresses the task of query-focused video summarization, which takes user queries and long videos as inputs and generates query-focused video summaries. Compared to video summarization, which mainly concentrates on finding the most diverse and representative visual contents as a summary, the task of query-focused video summarization considers the user’s intent and the semantic meaning of generated summary. In this paper, we propose a method, named query-biased self-attentive network (QSAN) to tackle this challenge. Our key idea is to utilize the semantic information from video descriptions to generate a generic summary and then to combine the information from the query to generate a query-focused summary. Specifically, we first propose a hierarchical self-attentive network to model the relative relationship at three levels, which are different frames from a segment, different segments of the same video, textual information of video description and its related visual contents. We train the model on video caption dataset and employ a reinforced caption generator to generate a video description, which can help us locate important frames or shots. Then we build a query-aware scoring module to compute the query-relevant score for each shot and generate the query-focused summary. Extensive experiments on the benchmark dataset demonstrate the competitive performance of our approach compared to some methods. [ABSTRACT FROM AUTHOR]

As a challenging task in visual information retrieval, open-ended long-form video question answering automatically generates the natural language answer from the referenced video content according to the given question. However, the existing video question answering works mainly focus on the short-form video, which may be ineffectively applied for long-form video question answering directly, due to the insufficiency of modeling the semantic representation of long-form video content. In this paper, we study the problem of open-ended long-form video question answering from the viewpoint of hierarchical multi-modal conditional adversarial network learning. We propose the hierarchical attentional encoder network to learn the joint representation of long-form video content and given question with adaptive video segmentation. We then devise the reinforced decoder network to generate the natural language answer for open-ended video question answering with multi-modal conditional adversarial network learning. We construct three large-scale open-ended video question answering datasets. The extensive experiments validate the effectiveness of our method. [ABSTRACT FROM AUTHOR]

Herein, Cu(NO3)2/acetonitrile was proven to be an efficient oxidation system in the oxidation of 5-HMF to DFF in an aqueous solution. After optimization of the reaction conditions, the DFF yield of 97.0% was obtained under the conditions of 1.5 mmol 5-HMF, 1.5 mmol Cu(NO3)2, 0.48 ml acetonitrile, 10 ml H2O, 80 °C, and 18 h. The oxidation system could be recycled at least three times by adding HNO3, which avoided the risk of production of Cu-containing waste. The formation of Cu(CH3CN)4+ in the aqueous solution played an important role in enabling the oxidation of 5-HMF via the redox cycle of Cu2+/Cu+. To further improve the reaction efficiency, a reactive-extraction process was developed by introducing toluene as the organic phase due to its excellent extraction capacity for DFF. As a result, the reaction time was shortened to 8 h, and the highest DFF yield of 98.9% was achieved. [ABSTRACT FROM AUTHOR]

Nitrite is harmful to aquatic animals in freshwater pond aquaculture environments. Nitrite is oxidized to nitrate mainly by nitrite-oxidizing bacteria (NOB). NOB may be promising in the control of nitrite concentration in aquaculture water. To better understand the role of NOB in the nitrogen cycling process of freshwater aquaculture ponds, we describe the characterization of NOB by using a culture derived from a freshwater aquaculture pond. Analysis by 16S rRNA sequence alignment showed that the NOB in the culture belong to the genus Nitrospira, whose generation time and nitrite–oxidizing rate were 9.87 h and 4.63 (± 0.07) pg NO2−–N cell−1·h−1 in the exponential growth phase, respectively. The oxidation of nitrite could be inhibited completely when the concentration of dissolved oxygen was 1.0 ± 0.5 mg/L.−1 The NOB could oxidize nitrite into nitrate at 29.84‰ salinity. However, the nitrification rate decreased significantly with an increase in salinity concentration ranging from 5.72‰ to 29.84‰. The optimal temperature range was 25–37 °C for the growth of NOB, and activity significantly decreased when the temperature was below 20 °C or reached 40 °C. In this study, the initial pH 6 ± 0.1–8 ± 0.1 was not observed to affect the nitrification activity of the NOB culture. Illumination of 410 ± 10 nm can completely inhibit NOB nitrification, and 520 ± 10 nm illumination partially inhibits NOB, whereas 660 ± 10 nm illumination has no effect. These findings indicate that the degree of photoinhibition in NOB increases with decreasing wavelength. [ABSTRACT FROM AUTHOR]

The synthesis of primary amines via the reductive amination of alcohols involves a hydrogen-borrowing or hydrogen-transfer mechanism, which consists of three main steps: alcohol hydroxyl dehydrogenation, carbonyl imidization, and imine hydrogenation. Heterogeneous catalysts are widely used for this reaction because of their high performance and amenability to separation and reuse. However, the efficiency of reductive amination is limited by the dehydrogenation step, which is severely affected by the competitive adsorption of NH3. We hope to improve the efficiency of reductive amination by increasing dehydrogenation efficiency. Therefore, in this overview, we introduce the research progress of alcohol reductive amination reaction catalyzed by heterogeneous metal catalysts, focusing on methods of enhancing dehydrogenation efficiency by screening the metal component and the acidity/alkalinity of the support. Finally, we propose some new strategies for the preparation of catalysts from the perspective of overcoming the competitive adsorption of NH3 and speculate on the design and synthesis of novel catalysts with high performance in the future. [ABSTRACT FROM AUTHOR]

Open-ended long-form video question answering is a challenging task in visual information retrieval, which automatically generates a natural language answer from the referenced long-form video contents according to a given question. However, the existing works mainly focus on short-form video question answering, due to the lack of modeling semantic representations from long-form video contents. In this paper, we introduce a dynamic hierarchical reinforced network for open-ended long-form video question answering, which employs an encoder–decoder architecture with a dynamic hierarchical encoder and a reinforced decoder. Concretely, we first propose a frame-level dynamic long-short term memory (LSTM) network with binary segmentation gate to learn frame-level semantic representations according to the given question. We then develop a segment-level highway LSTM network with a question-aware highway gate for segment-level semantic modeling. Furthermore, we devise the reinforced decoder with a hierarchical attention mechanism to generate natural language answers. We construct a large-scale long-form video question answering dataset. The extensive experiments on the long-form dataset and another public short-form dataset show the effectiveness of our method. [ABSTRACT FROM AUTHOR]

The improvement in thermal efficiency of GDI engine is severely limited by knocking. The effects of n-butanol combined with intake dilution on engine knock and thermal efficiency were studied in this paper. The results show that the combustion activity of n-butanol containing OH functional group can be improved by blending a small amount, and then the detonation intensity and thermal efficiency can be improved. When a high proportion of n-butanol is mixed, the knock strength and thermal efficiency will be reduced due to the effect of low calorific value and latent heat of vaporization. In particular, the maximum value is reached when 15% n-butanol is employed. The spontaneous combustion tendency is reduced by intake dilution, and the influence degree is reduced in the order of EGR dilution, compound dilution and air dilution, which is caused by the different amount of CO 2 in the three dilution gases. When R A = 1.2 and R A-E = 1.2, the knock intensity of GDI engine burning Bu15 is reduced by 96.3% and 98.4%, respectively. Therefore, when n-butanol combined with composite dilution is selected, the occurrence of knocking can be suppressed, while ensuring high thermal efficiency. Current study can provide theoretical guidance for knock suppression of GDI engines. • The mechanism about the intake dilution improving the performance of GDI engines. • When the Bu15 is employed, the peaks of both thermal efficiency and knock intensity. • When R A-E = 1.2, engine knock intensity of burning Bu15 is reduced by 98.4%. • Thermal efficiency can be improved by n-butanol combined with compound dilution. [ABSTRACT FROM AUTHOR]

Purpose: To examine the status of spouses' burdens of caring for breast cancer survivors and explore the relationships between social support, family resilience, breast cancer survivors' individual resilience, and caregiver burden.Methods: A cross-sectional study on 315 young and middle-aged breast cancer survivors and their spousal caregivers was conducted at eight comprehensive Southwest China hospitals. The caregivers completed the Chinese Version of the Family Resilience Assessment Scale, the Perceived Social Support Scale, and the Zarit Caregiver Burden Interview, while breast cancer survivors completed the shortened Chinese version of the Connor-Davidson Resilience Scale. Structural equation modeling was used to evaluate the relationships among social support, family resilience, survivors' individual resilience, and caregiver burden.Results: Caregiver burden (45.76 ± 14.66) was found to be severe. Social support, family resilience, and individual resilience were significantly negatively associated with caregiver burden (β =  - 0.421, P < 0.001; β =  - 0.208, P < 0.001; and β =  - 0.444, P < 0.001, respectively). Individual resilience not only partially mediated the relationship between family resilience and caregiver burden (b =  - 0.052; 95% confidence interval, - 0.110, - 0.018), but also partially mediated the relationship between support and caregiver burden (b =  - 0.045; 95% confidence interval, - 0.102, - 0.011).Conclusions: The findings suggest that higher social support, family resilience, and individual resilience tend to ease caregivers' burden. Healthcare workers should have an in-depth understanding of the care needs of survivors, actively contact social security departments and social organizations to provide financial, technical, and emotional support, and provide family-based care-skills training and psychological counseling to reduce spousal caregivers' burdens. [ABSTRACT FROM AUTHOR]

After a large number of electric vehicles (EVs) are connected to the integrated energy system, disorderly charging and discharging of EVs will have a negative impact on the safe and stable operation of the system. In addition, EVs' uncertain travel plans and the stochastic fluctuation of renewable energy output and load power will bring risks and challenges. In view of the above problems, this paper establishes a hierarchical stochastic optimal scheduling model of an electric thermal hydrogen integrated energy system (ETH-IES) considering the EVs vehicle-to-grid (V2G) mechanism. The EVs charging and discharging management layer aims to minimize the variance of the load curve and minimize the dissatisfaction of EV owners participating in V2G. The multi-objective sand cat swarm optimization (MSCSO) algorithm is used to solve the proposed model. On this basis, the daily stochastic economic scheduling of ETH-IES is carried out with the goal of minimizing the operation cost. The simulation results show that the proposed strategy can better achieve a win-win situation between EV owners and microgrid operators, and the operation cost of the proposed strategy is reduced by 16.55% compared with that under the disorderly charging and discharging strategy, which verifies the effectiveness of the proposed model and algorithm. [ABSTRACT FROM AUTHOR]

Reductive amination of furfuryl alcohol, furfural and 5‐hydroxymethylfurfural (5‐HMF) were carried out on various metal catalysts. Over Raney Ni catalyst, we obtained the highest furfurylamine yields of 81.8 % and 94.0 % from furfuryl alcohol in absence and presence of H2, respectively. While furfural was used as the substrate, 100 % yield of furfurylamine could be achieved over Raney Ni under rather moderate conditions. Although 5‐HMF was completely converted over all catalysts used, the highest yield of 2,5‐bisaminomethylfuran (60.7 %) was obtained over Raney Ni at 160 °C in 12 h. The DFT calculations on the adsorption behavior of NH3 and H2 on different metal surfaces showed that the difference of the adsorption energy between NH3 and H2 on Ni is lower than those of other metals, indicating that less metal active sites on Ni surface is occupied by NH3, which leaves more active sites for dehydrogenation/hydrogenation reactions and in the end promotes the reductive amination reactions. [ABSTRACT FROM AUTHOR]

More and more electromagnetics analyses need more detailed-level data validation technologies, which can focus on the specific data region. The feature selective validation (FSV) method is a key electromagnetics validation tool, which was adopted in 2008 as the core of 1597.1 standard for validation of computational electromagnetics computer modeling and simulations. However, despite its successful performance for electromagnetic compatibility (EMC) data, it still comes to apply to the validation of narrowband radar data, which, differing from EMC data, is quite problematic. For this reason, this paper proposes a novel approach, which is called segment FSV (S-FSV), to deal with the narrowband radar data. This approach divides the data into several segments, extracts the peak and oscillation regions, allocates an individual importance degree to each segment, and generates validation results for all segments. Finally, the efficiency and feasibility of the proposed approach is corroborated by the statistical results in a narrowband radar data survey. The proposed S-FSV approach is shown to outperform the traditional FSV one in reflecting the expert opinions and to be more suitable for validation of such data. [ABSTRACT FROM AUTHOR]

• A method of knock prediction using BP neural network is proposed. • Better anti-knock component proportion of fuel components is obtained. • The effect of hydrocarbon components on knock was studied by CFD simulation. In order to reduce emissions, the content of olefins and aromatic hydrocarbons in gasoline is required to be lower. The reduction of these two high-octane-number components increases the knock tendency of turbocharged engines, which limits thermal efficiency. Therefore, the optimization of the component proportion of gasoline in turbocharged GDI engines under the new gasoline standard is discussed in this paper. To blend the fuel with excellent anti-knock property, the influence of each component in the gasoline on the knock of turbocharged gasoline engine was analyzed by three-dimensional CFD simulation, and BP neural network was established based on a large number of data to predict the in-cylinder combustion of the fuels with different component proportion, which greatly saved the calculation cost. The results show that increasing of aromatic hydrocarbons and olefin in fuel can effectively improve the anti-knock property of fuel. Within the range of component proportion required by the Chinese gasoline standard specification, when the volume fraction of isooctane is 47%, n-heptane is 0, toluene is 35%, and diisobutylene is 18%, P max and MAPO value is the smallest, that is, the fuel has better anti-knock property. [ABSTRACT FROM AUTHOR]

• Lipocalin homologue protein from Haemaphysalis longicornis (HlLIP) was first cloned and analyzed. • The rHlLIP protein was purified and its immunogenicity was demonstrated by western blot. • The vaccination efficacy of the rHlLIP protein was 60.17 % based on engorged weight, oviposition and egg hatching rate of ticks. Haemaphysalis longicornis is distributed worldwide and transmits a variety of pathogens, causing human and animal disease. Use of chemical acaricides, as a primary tick control method, has several disadvantages, including acaricide resistance, environmental damage and residue accumulation in livestock. Development of a livestock vaccination aimed at a tick protective antigen could be an effective, labor-saving and environmentally-friendly method of reducing tick infestation and transmission of tick-borne pathogens. Lipocalins are low molecular weight proteins that play important roles in blood feeding, immune response and reproduction in ticks. In our study, the open reading frame (ORF) of a lipocalin homologue from H. longicornis (HlLIP) was successfully cloned, which consisted of 387 bp encoding a protein of 128 amino acids. The HlLIP protein sequence showed a close sequence homology with Ixodes persulcatus lipocalin. The HlLIP gene was constitutively detected in all developmental stages and in all tissues of the unfed female tick. The ORF of the HlLIP gene was sub-cloned into pET-32a (+) to obtain the recombinant protein (rHlLIP) and its immunogenicity was comfirmed by western blot. A vaccination trial on rabbits against H. longicornis infestation demonstrated that the rHlLIP protein could significantly prolong the period of tick blood feeding, and reduce tick engorged weight, oviposition and egg hatching rate. The vaccination efficacy of the rHlLIP protein was 60.17 % based on engorged weight, oviposition and egg hatching rate of ticks. The results obtained in this study demonstrate that rHlLIP protein is a promising antigen that could potentially be developed as a vaccine against H. longicornis infestation. [ABSTRACT FROM AUTHOR]