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The taste of fruits is an important attribute of fruit quality. The taste substances in fruits stimulate the taste buds to produce taste sensations, which are transmitted through the gustatory nerves into the neural center, finally entering the cerebral cortex. The major taste substances in fruits are soluble sugars, organic acids, polyphenols, alkaloids, and other bitter substances. These taste substances altogether contribute to the unique taste of fruits. Taste regulation of fruit products such as canned fruits, dried fruit products, liquid fruit products, jams and preserved fruits has received increasing attention, and there are a growing number of studies on methods for the regulation of fruit product taste. Many methods including electronic tongue technology, molecular sensory science, and quantitative descriptive analysis have been applied for studying the taste of fruits. This article provides an overview of taste substances in fruits and fruit products and methods for their taste regulation, and introduces commonly used methods in fruit taste research, aiming to provide theoretical guidance for research in the field of fruit taste.

Color is an important factor affecting the sensory quality of fruit and vegetable (FV) products. The vibrant and stable color of FV products can give people a good visual enjoyment, which can in turn promote consumers’ appetite and increase the market value of the products. This paper summarizes the types and properties of natural colorants in FV, clarifies the effects of thermal and non-thermal drying technologies and their combination on the color of FV products, reveals the influence mechanism of colorant degradation products on the products’ quality, and reviews the color preservation technologies of dried FV. We hope that this review could provide a theoretical basis for the color preservation and quality enhancement of dried FV products.

To study the dynamic response of multi-span mortise and tenon stone bridges under natural excitation, a bluestone multi-span stone bridge with a main span of 2.56 m in southern China was taken as the research object. Based on the collected pulsating signals of bridge piers and slabs, the natural frequencies and damping ratios of the main span bridge slab and pier were analyzed using the half-power broadband method (HPBM) and random decrement technique (RDT). Modal analysis was conducted using ANSYS, and the results were compared with those obtained from on-site experiments for further performance analysis. The research results of this article indicate that the natural frequency range of the 2.56-m bridge slab identified by measured signals is 48–49 Hz, and the damping ratio range is 33.33–36.61%. The natural frequency of the central pier is 75–76 Hz, and the damping ratio range is 26.39–27.83%. Through finite element modal analysis, the natural frequency of the bridge slab is 54.401 Hz, with an error of 10.5%. The natural frequency of the overall stone bridge is about 82.2 Hz, with an error of about 8.2%. The validated finite element model was subjected to normal water flow impact and erosion simulation. The results indicate that under erosion with fewer particles and lower flow rates, the upstream pier bottom at the center receives the highest relative erosion mass and displacement per unit area. The bridge deck near the main span also experienced relative displacement. Therefore, in the subsequent protection work, special attention should be paid to these components. [ABSTRACT FROM AUTHOR]

Traffic light control is a cost‐effective method to alleviate traffic congestion and deep reinforcement learning (DRL) that is increasingly favored as a method for real‐time traffic light control. However, the complexities of modern urban intersections, including crossroads and T‐junctions, pose challenges for DRL‐based traffic light control systems that do not work well for such heterogeneous intersections. To address this problem, a Heterogeneous Advantage Actor‐Critic (HA2C) model is proposed to control traffic lights for heterogeneous intersections. First, HA2C employs an intersection structure transformation scheme to mask intersection heterogeneity. Second, it develops a two‐stage approach on top of an Advantage Actor‐Critic (A2C) reinforcement learning model to learn both general and structure‐specific policies, leading to more accurate decisions. The extensive simulations on both synthetic and real‐world maps demonstrate that HA2C outperforms the state‐of‐the‐art models in terms of higher throughput and faster travel time, while using a smaller model size in most scenarios. [ABSTRACT FROM AUTHOR]

A long-term load test performed for 470 days on two two-span prestressed concrete (PC) continuous box girders is reported in this paper. Load types were selected as the test variates, and structural responses such as support reactions, deflections, and concrete strains were monitored. Simultaneously, affiliated experiments such as material strength, creep, and shrinkage tests were conducted to investigate the time-dependent performances of the materials. Data obtained from these tests showed that deflections, strains, and support reactions develop rapidly in the beginning and stabilize afterward; the reactions of mid- and end-supports decline and rise over time, respectively. Time-dependent patterns of deflections and support reactions were analyzed on the basis of an effective modulus method, and a practical calculation method for long-term deflections considering reaction redistributions was proposed. The effects of the service environment on the performance of PC girders were evaluated through an incremental analysis method. Key words: natural environment, prestressed concrete (PC), continuous box girders, long-term mechanical performance, reaction distribution. Un essai de chargement a long terme effectue pendant 470 jours sur deux poutres-caissons continues en beton precontraint (BP) a deux travees est presente dans ce document. Les types de chargement ont ete selectionnes a mesure que l'essai variait, et les reponses structurelles, comme les reactions des soutiens, les flexions et les deformations du beton, ont ete surveillees. Simultanement, des experiences connexes, telles que des essais de resistance des materiaux, de fluage et de retrait, ont ete menees pour etudier les performances temporelles des materiaux. Les donnees obtenues a partir de ces essais ont montre que les flexions, les deformations et les reactions des soutiens se developpent rapidement au debut et se stabilisent par la suite; les reactions des soutiens intermediaires et d'extremite diminuent et augmentent au fil du temps, respectivement. Les tendances temporelles des flexions et des reactions des soutiens ont ete analysees sur la base d'une methode modulaire efficace, et une methode de calcul pratique des flexions a long terme tenant compte des redistributions de reactions a ete proposee. Les effets de l'environnement d'exploitation sur la performance des poutres en BP ont ete evalues au moyen d'une methode d'analyse incrementielle. [Traduit par la Redaction] Mots-cles : environnement naturel, beton precontraint (BP), poutres-caissons continues, performance mecanique a long terme, repartition des reactions., 1. Introduction Prestressed concrete (PC) girder bridges are common bridge structures in highway and railway networks with the advances in construction materials, construction technologies, and calculation methods. At present, the [...]

Ancient masonry pagodas hold significant scientific, historical, and cultural importance. However, due to the complexity of masonry materials, structures, and boundary conditions, establishing finite element static and dynamic models for ancient masonry pagodas is highly challenging. This study aimed to explore the dynamic characteristics and finite element numerical simulation methods of ancient masonry pagodas in Yongzhou, Hunan province. It focused on the Huilong Pagoda in Yongzhou, where in situ test experiments under natural excitation are conducted. The SSI and NExT-ERA methods were employed to determine the ancient pagoda's natural frequencies, vibration patterns, and damping ratios, and to validate the NExT-ERA method. The macroscopic numerical model of the Huilong Pagoda was calibrated using measured results. Subsequently, the NExT-ERA identification results were compared and analyzed with the numerical simulation results of the dynamic characteristics. The results indicate that the first three orders of natural frequencies for the ancient pagoda in the east–west direction are 1.937 Hz, 6.802 Hz, and 21.361 Hz, respectively. Similarly, the first three orders of natural frequencies in the north–south direction are 1.935 Hz, 7.439 Hz, and 21.398 Hz. The results obtained from both methods revealed that the overall structural damping ratio ranges from 0.21% to 2.89%. The numerical model was analyzed using ANSYS, and the first three orders of natural frequencies obtained were highly consistent with the measured values, exhibiting a maximum relative error of 8.54%. The numerical simulation method developed in this study can effectively simulate masonry pagodas. [ABSTRACT FROM AUTHOR]

Emotion cause extraction (ECE) task that aims at extracting potential trigger events of certain emotions has attracted extensive attention recently. However, current work neglects the implicit emotion expressed without any explicit emotional keywords, which appears more frequently in application scenarios. The lack of explicit emotion information makes it extremely hard to extract emotion causes only with the local context. Moreover, an entire event is usually across multiple clauses, while existing work merely extracts cause events at clause level and cannot effectively capture complete cause event information. To address these issues, the events are first redefined at the tuple level and a span‐based tuple‐level algorithm is proposed to extract events from different clauses. Based on it, a corpus for implicit emotion cause extraction that tries to extract causes of implicit emotions is constructed. The authors propose a knowledge‐enriched joint‐learning model of implicit emotion recognition and implicit emotion cause extraction tasks (KJ‐IECE), which leverages commonsense knowledge from ConceptNet and NRC_VAD to better capture connections between emotion and corresponding cause events. Experiments on both implicit and explicit emotion cause extraction datasets demonstrate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]