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Trialeurodes vaporariorum Westwood (greenhouse whitefly) are worldwide polyphagous pests of economic importance that damage solanaceous vegetables. Neonicotinoid pesticides and parasitoid Encarsia formmosa Gahan are the main management strategies applied worldwide, but precise control methods in greenhouse vegetables need to be developed to reduce the application amounts of pesticides and improve the suppression of whitefly populations. Therefore, we assessed the indoor acute toxicities and risk assessment of neonicotinoids for T. vaporariorum and E. formosa adults and pupae and compared the control effects of E. formosa and neonicotinoid acetamiprid. According to the acute toxicities results, most neonicotinoid insecticides were more toxic to E. formosa than T. vaporariorum, and pupae were much less susceptible than adults of both species. Moreover, acetamiprid had a low risk effect on E. formosa. Sole application of E. formosa and acetamiprid could effectively control T. vaporariorum, but their combined application resulted in antagonistic effects on the control of T. vaporariorum. The results showed that a combined application or sole use of E. formosa could reduce the use of insecticides, slow down the development of insecticide resistance in whiteflies, and improve the efficiency of controlling the growth of whitefly populations in greenhouse vegetable production. [ABSTRACT FROM AUTHOR]

Benzene is the typical volatile organic compound (VOC) of indoor and outdoor air pollution, which harms human health and the environment. Due to the stability of their aromatic structure, the catalytic oxidation of benzene rings in an environment without an external energy input is difficult. In this study, the efficient degradation of benzene at room temperature was achieved by constructing Ag and Ni bimetallic active site catalysts (AgNi/BCN) supported on boron–carbon–nitrogen aerogel. The atomic-scale Ag and Ni are uniformly dispersed on the catalyst surface and form Ag/Ni-C/N bonds with C and N, which were conducive to the catalytic oxidation of benzene at room temperature. Further catalytic reaction mechanisms indicate that benzene reacted with ·OH to produce R·, which reacted with O2 to regenerate ·OH. Under the strong oxidation of ·OH, benzene was oxidized to form alcohols, carboxylic acids, and eventually CO2 and H2O. This study not only significantly reduces the energy consumption of VOC catalytic oxidation, but also improves the safety of VOC treatment, providing new ideas for the low energy consumption and green development of VOC treatment. [ABSTRACT FROM AUTHOR]

Flower-rich habitats are crucial for promoting biodiversity and ecosystem services within agricultural ecosystems, such as pollination and pest control. The present study investigates the efficacy of employing floral structures as a criterion for the selection of plant species in order to enhance the attraction of natural enemies within cucumber greenhouses, consequently augmenting floral resources. The results of our study provide evidence that flower strips have a beneficial effect on the fitness of critical natural predators, while not facilitating the proliferation of detrimental insect species. These findings exhibit potential for enhancing pest-management services in the agricultural sector. The findings of our study demonstrate that pest levels within greenhouse environments closely resemble those observed in real-world commercial cropping systems. As a result, the introduction of Coccinella septempunctata and Menochilus sexmaculatus biocontrol agents is confirmed to be a reliable and efficient method for pest management. The phenomenon of predator–prey density dependency is recognized as a crucial element in the implementation of biological control strategies. Furthermore, we investigate the impact of floral resources on the reproductive capacity of indigenous predators. The impact of Coriandrum sativum on fertility is substantial, indicating that the presence of a varied plant assortment with overlapping flowering periods can prolong the availability of floral resources. This study highlights the significance of flower-rich habitats and deliberate plant selection in augmenting biodiversity, ecosystem services, and pest management within agricultural settings. The implementation of conservation biological control technologies presents supplementary ecological advantages, thus offering practical implications for the promotion of sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

In the context of global warming, tropical cyclones (TCs) have garnered significant attention as one of the most severe natural disasters in China, particularly in terms of assessing the disaster losses. This study aims to evaluate the TC disaster loss (TCDL) using machine learning (ML) algorithms and identify the impact of specific feature factors on the prediction of model with an eXplainable Artificial Intelligence (XAI) approach, SHapley Additive exPlanations (SHAP). The results show that LightGBM outperforms Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB) for estimating the TCDL grades, achieving the highest accuracy value of 0.86. According to the SHAP values, the three most important factors in the LightGBM classifier model are proportion of stations with rainfall exceeding 50 mm (ProRain), maximum wind speed (MaxWind), and maximum daily rainfall (MaxRain). Specifically, in the estimation of high TCDL grade, events characterized with MaxWind exceeding 30 m/s, MaxRain exceeding 200 mm, and ProRain exceeding 30% tend to exhibit a higher susceptibility to TC disaster due to positive SHAP values. This study offers a valuable tool for decision-makers to develop scientific strategies in the risk management of TC disaster. [ABSTRACT FROM AUTHOR]

The battery system, as the core energy storage device of new energy vehicles, faces increasing safety issues and threats. An accurate and robust fault diagnosis technique is crucial to guarantee the safe, reliable, and robust operation of lithium-ion batteries. However, in battery systems, various faults are difficult to diagnose and isolate due to their similar features and internal coupling relationships. In this paper, the current research of advanced battery system fault diagnosis technology is reviewed. Firstly, the existing types of battery faults are introduced in detail, where cell faults include progressive and sudden faults, and system faults include a sensor, management system, and connection component faults. Then, the fault mechanisms are described, including overcharge, overdischarge, overheat, overcool, large rate charge and discharge, and inconsistency. The existing fault diagnosis methods are divided into four main types. The current research and development of model-based, data-driven, knowledge-based, and statistical analysis-based methods for fault diagnosis are summarized. Finally, the future development trend of battery fault diagnosis technology is prospected. This paper provides a comprehensive insight into the fault and defect diagnosis of lithium-ion batteries for electric vehicles, aiming to promote the further development of new energy vehicles. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries have become the primary electrical energy storage device in commercial and industrial applications due to their high energy/power density, high reliability, and long service life. It is essential to estimate the state of health (SOH) of batteries to ensure safety, optimize better energy efficiency and enhance the battery life-cycle management. This paper presents a comprehensive review of SOH estimation methods, including experimental approaches, model-based methods, and machine learning algorithms. A critical and in-depth analysis of the advantages and limitations of each method is presented. The various techniques are systematically classified and compared for the purpose of facilitating understanding and further research. Furthermore, the paper emphasizes the prospect of using a knowledge graph-based framework for battery data management, multi-model fusion, and cooperative edge-cloud platform for intelligent battery management systems (BMS). [ABSTRACT FROM AUTHOR]

Safety issues are one of the main limitations for further application of lithium-ion batteries, and battery degradation is an important causative factor. However, current state-of-health (SOH) estimation methods are mostly developed for a single feature and a single operating condition as well as a single battery material system, which consequently makes it difficult to guarantee robustness and generalization. This paper proposes a data-driven and multi-feature collaborative SOH estimation method based on equal voltage interval discharge time, incremental capacity (IC) and differential thermal voltammetry (DTV) analysis for feature extraction. The deep learning model is constructed based on bi-directional long short-term memory (Bi-LSTM) with the addition of attention mechanism (AM) to focus on the important parts of the features. The proposed method is validated based on a NASA dataset and Oxford University dataset, and the results show that the proposed method has high accuracy and strong robustness. The estimated root mean squared error (RMSE) are below 0.7% and 0.3%, respectively. Compared to single features, the collaboration between multiple features and AM resulted in a 25% error improvement, and the capacity rebound is well captured. The proposed method has the potential to be applied online in an end-cloud collaboration system. [ABSTRACT FROM AUTHOR]

The safety of batteries has become a major obstacle to the promotion and application of electric vehicles, and the use of cloud-based vehicle practical big data to summarize the fault knowledge of batteries to improve product quality and reduce maintenance costs has attracted widespread attention from academia and industrial communities. In this paper, a method is proposed to construct the battery fault knowledge graph which supports online knowledge query and fault inference. Reliability models for battery undervoltage, inconsistency, and capacity loss are built based on cloud data, and are deployed and continuously updated in the cloud platform to accommodate the migration of the models to different battery products. A bidirectional long short-term memory (Bi-LSTM) neural network was established for knowledge extraction of fault logs, and the results were imported into Neo4j to form a battery fault knowledge graph. Finally, a fault knowledge online query front-end interface was built to conduct inference tests on battery faults of a manufacturer, which proves the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The accurate estimation of the state of charge (SOC) plays a crucial role in ensuring the range of electric vehicles (EVs) and the reliability of the EVs battery. However, due to the dynamic working conditions in the implementation of EVs and the limitation of the onboard BMS computational force, it is challenging to achieve a reliable, high-accuracy and real-time online battery SOC estimation under diverse working scenarios. Therefore, this study proposes an end-cloud collaboration approach of lithium-ion batteries online estimate SOC. On the cloud-side, a deep learning model constructed based on CNN-LSTM is deployed, and on the end-side, the coulomb counting method and Kalman's filter are deployed. The estimation results at both sides are fused through the Kalman filtering algorithm, realizing high-accuracy and real-time online estimation of SOC. The proposed approach is evaluated with three dynamic driving profiles and the results demonstrate the proposed approach has high accuracy under different temperatures and initial errors, where the root means square error (RMSE) is lower than 1.5% and the maximum error is lower than 5%. Furthermore, this method could achieve high-accuracy and real-time SOC online estimation under the cyber hierarchy and interactional network (CHAIN) framework and can be extended to multi-state collaborative online estimation. [ABSTRACT FROM AUTHOR]

Cathepsin L protease, which belongs to the papain-like cysteine proteases family, is an important player in many physiological and pathological processes. However, little was known about the role of cathepsin L in ladybird beetles (Coccinella septempuctata Linnaeus) during diapause. Here, we analyzed the characteristics of cathepsin L (CsCatL) in the females of C. septempunctata and its role during the diapause of the ladybeetle. CsCatL was cloned and identified from beetle specimens by rapid amplification of cDNA-ends (RACE). The cDNA sequence of CsCatL was 971 bp in length, including an 843 bp open reading frame encoding a protein of 280 amino acids. It was identified as the cathepsin L group by phylogenetic analysis. Knockdown of CsCatL by RNA interference led to decreased expression levels of fatty acid synthase 2 (fas 2) genes and suppressed lipid accumulation. Furthermore, silencing the CsCatL gene distinctly reduced diapause-related features and the survival of female C. spetempunctata under diapause-inducing conditions. The results suggested that the CsCatL gene was involved in fatty acid biosynthesis and played a crucial role in the survival of adult C. septempunctata during the diapause preparation stage. [ABSTRACT FROM AUTHOR]

With rapid development of clean energy vehicles, the health diagnosis and prognosis of lithium batteries remain challenging for practical applications. Accurate state-of-health (SOH) and remaining useful life (RUL) estimation provides crucial information for improving the safety, reliability and longevity of batteries. In this paper, a fusion of deep-learning model and feature signal analysis methods are proposed to realize accurate and fast estimation of the health conditions for battery cathodes. Specifically, the long short-term memory (LSTM) network and differential thermal voltammetry (DTV) are utilized to verify our fusion method. Firstly, the DTV feature signal analysis is executed based on battery charging and discharging data, based on which useful feature variables are extracted with Pearson correlation analysis. Next, the deep-learning model is constructed and trained with the LSTM as the core based on timeseries datasets constructed with features. Finally, the validation and error analysis of proposed model are provided, showing a max mean absolute error of 0.6%. The proposed method enables highly accurate models for SOH and RUL estimation that can be potentially deployed on cloud-end for offline battery degradation tracking. [ABSTRACT FROM AUTHOR]

Simple Summary: Arma chinensis Fallou is a predaceous stink bug that can effectively control many kinds of agricultural and forest pests, such as fall armyworm, cotton bollworm and Colorado potato beetle. An insect-free artificial diet comprising chicken egg, tuna fish and raw pig liver was developed for A. chinensis. Several biological characteristics were diminished for A. chinensis reared on the artificial diet compared to the pupae of Chinese oak silk moth. Changes in the formulation of the diet were made in response to the transcriptome results and tested using biological characteristics. Several parameters were improved over 6 generations, although the improved artificial diet remained inferior to the pupae of Chinese oak silk moth regarding egg viability, fecundity, body weight, and nymphal development time. The current study reported the differential proteomic analysis revealing the mechanism of A. chinensis responding to the improved artificial diet. This information will be used to optimize the formulation of the artificial diet and decrease the cost of mass rearing in A. chinensis. The development of artificial diets could considerably simplify and reduce the cost of mass rearing of natural enemies compared to conventional rearing methods. However, improvement of artificial diets can be tedious, convoluted and often uncertain. For accelerating diet development, a better method that can offer informative feedback to target deficiencies in diet improvement is required. Our previous research demonstrated several biological characteristics were diminished in the insect predator, Arma chinensis Fallou, fed on an artificial diet formulated with the aid of transcriptomic methods compared to the Chinese oak silk moth pupae. The present study reports differential proteomic analysis by iTRAQ-PRM, which unravels the molecular mechanism of A. chinensis responding to improvements in the artificial diet. Our study provides multivariate proteomic data and provides comprehensive sequence information in studying A. chinensis. Further, the physiological roles of the differentially expressed proteins and pathways enable us to explain several biological differences between natural prey-fed and improved diet-fed A. chinensis, and subsequent proposed reformulation optimizations to artificial diets. [ABSTRACT FROM AUTHOR]

Simple Summary: Telenomus remus (Nixon) is a promising natural enemy of Spodoptera frugiperda (J. E. Smith). Successful implementation of a biocontrol program requires a mature rearing system to produce millions of beneficial insect products at lower costs. This parasitoid is successfully reared on Corcyra cephalonica (Stainton) eggs in several countries, however that host species is unsuitable for Chinese strains of T. remus. Fewer studies have been done using Spodoptera litura (Fabricius) eggs, but it is increasingly seen as the promising alternative host in China. In order to identify optimal mass-rearing conditions when using S. litura eggs as an alternative host, this novel study thus sought to comprehensively evaluate the effects of photoperiod, exposure time, and host egg:parasitoid ratio on the reproductive potential and mass-rearing efficiency of T. remus on S. litura eggs. Our results suggest using more than 12 h of light, 24 h exposure time, and 14–20:1 host egg:parasitoid ratio for rearing T. remus on S. litura eggs. These findings will help promote successful, large-scale rearing of T. remus for use against S. frugiperda in China. Telenomus remus (Nixon) is a dominant egg parasitoid of the destructive agricultural pest Spodoptera frugiperda (J. E. Smith), and so is used in augmentative biocontrol programs in several countries. An optimized mass-rearing system is essential to produce biological control products in a timely and cost-effective manner. In this study, the photoperiod, host egg:parasitoid ratio, and exposure time were evaluated to identify the optimal rearing conditions for T. remus on the alternative host Spodoptera litura (Fabricius) eggs. Results showed that increasing photoperiod above 12L:12D remarkably improved parasitoid progeny yield and life table parameters. Overlong photoperiods shortened female longevity, but within acceptable limits. There was a significant negative correlation between parasitism rate and host egg:parasitoid ratio under exposure times of 12 and 36 h, but not 24 h. Percentage of female progeny increased significantly along with increasing the host egg:parasitoid ratio. A significant negative relationship between the number of emerged adults per egg and the host egg:parasitoid ratio was observed at an exposure time of 36 h. It was concluded that T. remus may be mass-reared most efficiently on S. litura eggs using a photoperiod of more than 12L:12D, a 14–20:1 host egg:parasitoid ratio, and an exposure time of 24 h. These findings can be used to produce T. remus more efficiently and at lower costs. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman scattering (SERS) is a promising technique to study the plasma-driven photocatalytic reactions. Hemispherical alumina nanoarrays with a regular hexagonal arrangement are firstly prepared; then, silver hemispherical nanoarrays are synthesized on the surface of the arrays by silver evaporation. When a laser with a specific wavelength (633 nm) is irradiated on the silver nanoarrays, a large number of regularly arranged local surface plasmon enhancement regions (called "hot spots") would be generated on its surface. After that, a layer of evenly distributed p-aminothiophenol (PATP) probe molecules was placed on the substrate and the photocatalytic reaction of PATP was driven by the local surface plasmon to form four 4′-di-mercaptoazobenzene (DMAB). Then, under the same experimental conditions, the later product was reversely reacted to form PATP molecule by the action of plasma in the presence of in situ sodium borohydride. SERS can be used to monitor the whole process of the photocatalytic reaction of PATP probe molecules driven by the plasma on the surface of the silver nanoarrays. This research achieves the drawing and erasing of molecular graphics in the micro- and nano-scales, as well as information encryption, reading, and erasing that have strong application value. [ABSTRACT FROM AUTHOR]

Various effects caused by surface plasmons including enhanced electromagnetic field, local heating, and excited electrons/holes can not only redistribute the electromagnetic field in the time domain and space but also redistribute the excited carriers and drive chemical reactions. In this study, firstly, an Au nanoporous array photocatalyst with the arrayed gauge was prepared by means of the anodic alumina template. Then, the formation of 4,4′-dimercaptoazobenzene (DMAB) by the surface plasmon-driven photocatalysis under 633 nm laser irradiation was investigated by means of Raman spectroscopy using aminothiophenol (PATP) as a probe molecule on gold nananoporous arrays. In addition, sodium borohydride was introduced in situ to realize the reverse photocatalytic reaction driven by the surface plasma. With the help of FDTD software, the plasma distribution characteristics on the surface of Au nanoporous arrays were simulated and analyzed. Through this practical method, it is expected to draw specific graphics, letters, and Chinese characters on the micro/nano scale, and realize the functions of graphics drawing, information encryption, reading, and erasing on the micro/nano scale. [ABSTRACT FROM AUTHOR]

Simple Summary: The predaceous fly Coenosia attenuata Stein has received attention because of its ability to effectively suppress a wide range of agricultural pests, such as fungus gnats, whiteflies and leaf miners. An effective level of control requires large numbers of C. attenuata to be available at low cost for release. Adult fungus gnats and drosophilids are now the main prey used to rear C. attenuata adults. However, previous studies showed C. attenuata fertility is lower when fed drosophilids compared to fungus gnats. The current study investigated the performance of C. attenuata adults when reared on different densities of adult Drosophila melanogaster Meigen or Bradysia impatiens (Johannsem). Results showed that the optimal prey density in the mass rearing of adult C. attenuata was 12–24 adult B. impatiens daily per predator. Additionally, C. attenuata adults suffered more wing damage, at some of the prey densities, when reared on D. melanogaster compared to B. impatiens. This information will be used to optimize rearing methods and decrease the cost of mass rearing in C. attenuata. Mass production of Coenosia attenuata Stein at low cost is very important for their use as a biological control agent. The present study reports the performance of C. attenuata adults when reared on Drosophila melanogaster Meigen or Bradysia impatiens (Johannsem). Different densities (6, 9, 15, 24 and 36 adults per predator) of D. melanogaster or (6, 12, 24, 36 and 48 adults per predator) of B. impatiens were used at 26 ± 1 °C, 14:10 (L:D) and 70 ± 5% RH. The results concluded that C. attenuata adults had higher fecundity, longer longevity and less wing damage when reared on B. impatiens adults compared to D. melanogaster adults. Additionally, C. attenuata adults demonstrated greater difficulty catching and carrying heavier D. melanogaster adults than lighter B. impatiens adults. In this case, 12 to 24 adults of B. impatiens daily per predator were considered optimal prey density in the mass rearing of adult C. attenuata. [ABSTRACT FROM AUTHOR]

Simple Summary: Telenomus remus (Nixon) is an effective egg parasitoid for controlling Spodoptera frugiperda (J. E. Smith), which is a major destructive agricultural pest. Currently, this parasitoid is reared on Corcyra cephalonica (Stainton) eggs in several countries. However, previous studies carried out in China have reported that it cannot parasitize in C. cephalonica eggs. Meanwhile, those works have indicated that Spodoptera litura (Fabricius) can potentially be used as an alternative host. In order to evaluate this potential, our study compared the development and parasitism ability of T. remus on the eggs of S. frugiperda and S. litura at different temperatures in a laboratory. We found that S. litura eggs are more advantageous as an alternative host for the mass-rearing of parasitoid when compared with S. frugiperda eggs. Our results provide a more specific basis and reference for the large-scale production and low temperature storage of T. remus. Although Telenomus remus, a promising parasitoid of Spodoptera frugiperda, had been successfully reared on the eggs of Corcyra cephalonica in some countries, reports from China have argued that it is infeasible. Notably, studies from China have indicated that Spodoptera litura eggs could be a candidate host. Therefore, to further evaluate the potential of using S. litura eggs as hosts, we compared the development and parasitism of T. remus on the eggs of S. frugiperda and S. litura at temperatures between 20–32 °C. Our results showed that T. remus developed successfully on both host eggs at all of the tested temperatures, and the developmental duration and thermal requirements at each stage were similar between the two host species. The number of parasitized eggs was greater for S. litura than for S. frugiperda. Meanwhile, the emergence rate exceeded 86.6%, and it was significantly higher for S. litura than that for S. frugiperda, except at 29 °C. This study is the first time estimating the thermal requirements of T. remus at each stage. Moreover, we also recorded the morphological characteristics of T. remus at each stage. Our results demonstrate that S. litura eggs are more suitable than S. frugiperda eggs as an alternative host for the mass-rearing of T. remus in China. Understanding the thermal requirements and biological parameters contributes greatly to predicting the generation time and providing a reference for the mass-rearing and storage of the parasitoid. [ABSTRACT FROM AUTHOR]

Cathepsin L protease, which belongs to the papain-like cysteine proteases family, is an important player in many physiological and pathological processes. However, little was known about the role of cathepsin L in ladybird beetles ( Coccinella septempuctata Linnaeus) during diapause. Here, we analyzed the characteristics of cathepsin L ( CsCatL ) in the females of C. septempunctata and its role during the diapause of the ladybeetle. CsCatL was cloned and identified from beetle specimens by rapid amplification of cDNA-ends (RACE). The cDNA sequence of CsCatL was 971 bp in length, including an 843 bp open reading frame encoding a protein of 280 amino acids. It was identified as the cathepsin L group by phylogenetic analysis. Knockdown of CsCatL by RNA interference led to decreased expression levels of fatty acid synthase 2 (fas 2) genes and suppressed lipid accumulation. Furthermore, silencing the CsCatL gene distinctly reduced diapause-related features and the survival of female C. spetempunctata under diapause-inducing conditions. The results suggested that the CsCatL gene was involved in fatty acid biosynthesis and played a crucial role in the survival of adult C. septempunctata during the diapause preparation stage.