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aimed to investigate the effect of emotional recognition training and its consequences on emotional attention and aggression. Methods: Seventy-three male juvenile delinquents were randomly assigned to two groups. One group was the modification group, which received eight days of training on an emotional recognition task. The purpose of the training was to modify interpretative biases in emotion recognition to encourage the perception of happiness over anger in ambiguous expressions. The other group was the waitlist group, which did not perform a task and continued with their usual programme. Before and after the training, participants completed the aggression questionnaire (AQ) and two behavioural tasks, including the emotional recognition task and a visual search task with happy and angry faces as targets. Results: The modification group recognized more faces as happy after emotional recognition training than the waitlist group. Furthermore, the hostility in the modification group decreased significantly. Importantly, emotional recognition training further affected attention to emotional faces as participants responded faster in searching for happy and angry faces after training. Conclusion: Emotional recognition training could modify juvenile delinquents' emotional recognition, enhance their visual attention to emotional faces and reduce hostility. [ABSTRACT FROM AUTHOR]

Automatically detecting mud in bauxite ores is important and valuable, with which we can improve productivity and reduce pollution. However, distinguishing mud and ores in a real scene is challenging for their similarity in shape, color, and texture. Moreover, training a deep learning model needs a large amount of exactly labeled samples, which is expensive and time consuming. Aiming at the challenging problem, this paper proposed a novel weakly supervised method based on deep active learning (AL), named YOLO-AL. The method uses the YOLO-v3 model as the basic detector, which is initialized with the pretrained weights on the MS COCO dataset. Then, an AL framework-embedded YOLO-v3 model is constructed. In the AL process, it iteratively fine-tunes the last few layers of the YOLO-v3 model with the most valuable samples, which is selected by a Less Confident (LC) strategy. Experimental results show that the proposed method can effectively detect mud in ores. More importantly, the proposed method can obviously reduce the labeled samples without decreasing the detection accuracy. [ABSTRACT FROM AUTHOR]

Green computing mode becomes a social concern in recently years. Consequently people have higher demand for Bluetooth device with lower power consumption. In this paper, a green energy consumption policy (ECP) of battery of Bluetooth devices during data transmission was put forward. ECP extracted detail information from four key configuration parameters during Bluetooth data transmission, namely, transmission mode, connection type, packet type and communication rate. Based on the verification data time, verification data transmission time and Bluetooth package time acquired by the computer processor unit, it calculated the battery energy consumption during equipment idle. Moreover, it calculated the actual transmission data and energy consumption according to the data size of the transmitted document. A simulation analysis on ECP was carried out in this paper. Results showed that ECP could estimate energy consumption for document transmission in the independent Bluetooth communication module. [ABSTRACT FROM AUTHOR]

Cloud computing is an emerging distributed system that provides flexible and dynamically scalable computing resources for use at low cost. Task scheduling in cloud computing environment is one of the main problems that need to be addressed in order to improve system performance and increase cloud consumer satisfaction. Although there are many task scheduling algorithms, existing approaches mainly focus on minimizing the total completion time while ignoring workload balancing. Moreover, managing the quality of service (QoS) of the existing approaches still needs to be improved. In this paper, we propose a novel algorithm named MGGS (modified genetic algorithm (GA) combined with greedy strategy). The proposed algorithm leverages the modified GA algorithm combined with greedy strategy to optimize task scheduling process. Different from existing algorithms, MGGS can find an optimal solution using fewer number of iterations. To evaluate the performance of MGGS, we compared the performance of the proposed algorithm with several existing algorithms based on the total completion time, average response time, and QoS parameters. The results obtained from the experiments show that MGGS performs well as compared to other task scheduling algorithms. [ABSTRACT FROM AUTHOR]

Although environmental economics research explores the impacts of green innovation on reducing CO 2 emissions, most studies ignore these effects in emerging economies. This paper examines how alternative energy production innovation (AEPI) reduces CO 2 emissions. Using a sample of 30 provinces in China during the 1997–2017 period, we find AEPI is negatively related to CO 2 emissions. Specifically, the results show that innovations in raw coal and crude oil are negatively related to CO 2 emissions, while innovations in natural gas are positively related to CO 2 emissions. This study contributes to research on technological innovation and environmental economics. First, we find AEPI as the main driver of all types of green innovation in reducing CO 2 emissions. Second, we explore the heterogeneous effects of different energy sources and deepen our understanding of different reduction mechanisms. Third, this study makes a methodological contribution to research using a series of quantitative analyses. [Display omitted] • AEPI plays a significant role in reducing the CO 2 emissions of China. • Effects of different energy sources are heterogeneous. • Compared with natural gas, the innovation of coal and oil show stronger impacts on CO 2 emissions. [ABSTRACT FROM AUTHOR]

Irisin, which was recently identified as a myokine and an adipokine, transforms white adipose tissue to brown adipose tissue and has increasingly caught the attention of the medical and scientific community. However, the signaling pathway of irisin and the molecular mechanisms responsible for the lipolysis effect remain unclear. In this study, we established an efficient system for the expression and purification of GST-irisin in Escherichia coli. The biological activity of GST-irisin was verified using the cell counting kit-8 assay and by detecting the mRNA expression of uncoupling protein 1. Our data showed that GST-irisin regulates mRNA levels of lipolysis-related genes such as adipose triglyceride lipase and hormone-sensitive lipase and proteins such as the fatty acid-binding protein 4, leading to increased secretion of glycerol and decreased lipid accumulation in 3T3-L1 adipocytes. In addition, exogenous GST-irisin can increase its autocrine function in vitro by regulating the expression of fibronectin type III domain-containing protein 5. GST-irisin could regulate glucose uptake in 3T3-L1 adipocytes. Hence, we believe that recombinant GST-irisin could promote lipolysis and its secretion in vitro and can potentially prevent obesity and related metabolic diseases. [ABSTRACT FROM AUTHOR]

Cheng, H.; Li, F., and Mao, Q., 2015. The empirical analysis on the influence of CO2 emission regulation on the export transformation of Chinese manufacturing industries. Since China has begun to implement stringent CO2 emission regulation, foreign trade competitiveness suffers from great impact. Under fixed emission regulation concerning different emission distribution methods, there exist differences in effects on export competitiveness as well as industrial transformation and upgrading. In this paper, based on the bilateral panel data of China and 32 trading partners during 1992 and 2011, model of multiple panel regression is applied to conduct empirical analysis on the influence of CO2 emission regulation. The results show that the enhancement of CO2 emission regulation is conducive to the improvement of the export competitiveness of Chinese manufacturing industries. Meanwhile, there are different influence degrees of regulation on various industries, among which the clean industry is the most influenced by the regulation. As for various manufacturing industries, there are three distribution policies, namely, emission distribution on the basis of output, average distribution on the basis of unit emission and accumulative distribution on the basis of unit emission. Moreover, the advantages and disadvantages of the influences of these three policies on export competitiveness, transformation and upgrading of Chinese manufacturing industries would be compared so as to determine which distribution policy is most beneficial. The results illustrate that 'average CO2 emission distribution on the basis of unit emission' makes the greatest contribution to the export transformation and upgrading of Chinese manufacturing industries, and it is in conformity with development need of Chinese trade at current phase. The innovation of the paper lies in its adoption of bilateral trade data to specifically study the influence of CO2 emission regulation on trade competitiveness. The attention is specially attached to the performance differences of different emission distribution policies in trade competitiveness, which is the further exploration on the basis of previous studies. [ABSTRACT FROM AUTHOR]

Abstract: A class of Yb3+/Ho3+ ions co-doped CaLa2ZnO5 (CLZ) up-conversion (UC) phosphors were synthesized by sol–gel method. Under 980nm excitation, UC spectra consist of two prominent emission bands centered at 545 and 662nm originating from 5F4, 5S2→5I8 and 5F5→5I8 transitions of Ho3+ ion, respectively. The UC spectra as a function of the concentration of the dopants were also investigated to determine the optimal composition. The possible UC mechanism was proposed, and lifetime measurements were also carried out to support our proposal. [Copyright &y& Elsevier]

Highlights: [•] We present a method which estimates number of motion human in sensor network. [•] The independent criterion is modeled by Bayesian network. [•] The objective function is optimally solved by the Laplace estimation. [•] Numerous experiments are completed by using LiTaO3 pyroelectric infrared sensor. [Copyright &y& Elsevier]

The rapid development of animal husbandry has resulted in serious pollution issues in the livestock and poultry breeding industry, increasing the cost of environmental management. This issue is particularly prominent in China due to its rapid economic development, significant domestic consumption, and aggressive carbon neutrality targets. This study analyses pollution emissions and spatial-temporal variation in China's cattle breeding industry. Using an emission coefficient method and panel data of 31 Chinese provinces/municipalities between 2002 and 2017, we measure the total volume of pollutant emissions from China's cattle breeding industry and five major pollutants: chemical oxygen demand, total nitrogen, total phosphorus, copper, and zinc. We also analyse the dynamic variation of the spatial distribution. The results show that both the total emissions volume and emissions of the five major pollutants have decreased to different extents, among which chemical oxygen demand has decreased the fastest. Spatial divergence is strengthened as the heavy pollution areas have moved from the southeast to the northwest of the country. This study contributes to current research by its focus on the cattle breading industry and by our improvements to the pollutant emission measurement method. • The pollutant emissions brought by cattle breeding has been significant in China. • The emissions show a decreasing trend in total. • Specific five types of major pollutant emissions are examined further. • There is a spatial transferring of emissions from the east to the northwest of China. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel modified biochar for environmental remediation was synthesized. • Sulfamic acid significantly improved the adsorption performance of biochar. • Pore filling played an important role in adsorption. • The maximum adsorption capacity of SABC exceeded 412.95 mg/g. In this work, a novel modified biochar was prepared by pretreatment of Camellia oleifera shell with sulfamic acid. The effects of sulfamic acid on the properties of feedstock and biochar, and the influence of pyrolysis temperature on the modification was investigated. Furthermore, the adsorption mechanism of modified biochar for tetracycline (TC) was explore. The results showed that the specific surface area (170.97 m2/g) of the modified biochar was 2.6 times larger than that of the original biochar (65.31 m2/g). In addition, sulfamic acid treatment introduced more functional groups for biochar. These modification effects significantly improved the adsorption performance of biochar. The maximum adsorption capacity of sulfamic acid modified biochar for TC was 412.95 mg/g. The adsorption mechanism studies demonstrated that there were many interactions in the adsorption process, including electrostatic interaction, H bonding, π-π interaction, pore filling. In general, sulfamic acid was a potential green modification reagent, which could be used to improve the adsorption performance of biochar. [ABSTRACT FROM AUTHOR]

Three years field experiments were conducted from 1999 to 2002 to evaluate winter wheat (Triticum aestivum L.) yield, nitrogen efficiency (NE) including nitrogen efficiency ratio (NER), nitrogen uptake efficiency (NUpE), nitrogen use efficiency (NUE), and nitrogen fertilizer use efficiency (NfUE) as influenced by a new coated urea as CRF. Results showed that both coated urea and common urea treatments produced significant higher biomass, grain, and straw yields, and higher NUE and nitrogen fertilizer recovery rate over the control. The maximum yield and nitrogen (N) efficiency were observed in the treatment of coated urea in the three years. On average, the grain, straw, and biomass yield of coated urea treatment was 9.09–15.06, 13.11–14.96, and 11.73–14.99% higher than those of common urea respectively. The coated urea not only resulted in higher yield, but nitrogen fertilizer recovery rate (NfUE) of the treatment was 16.50–68.72% more than that of common urea treatment. Compared to normal dosage of N fertilization (150 kg N ha−1) insufficient amount increase of N fertilizer (8% increase) does not affect both yield and NE. However, sufficient amount increase of N fertilizer (20% higher) can result in significant increase of yield, N uptake and N fertilizer recovery rate (NfUE) under the experiment condition. [ABSTRACT FROM AUTHOR]

Establishing an accurate edge server power model is helpful for resource providers to predict and optimize power consumption within edge data centers. Considering the fact that the accuracy of the previous energy consumption model is easily affected by the workload types, this paper develops an edge server power model based on BP (back propagation) neural network and feature selection, which is denoted by DSBF. For different task types, DSBF leverages "principal component analysis (PCA)" to analyze the contribution of each energy consumption parameter and selects "representative parameter", and then builds a power model based on BP neural network. In contrast to other power models, DSBF can effectively handle the variable workload. To measure the effectiveness of the DSBF model, a series of experiments were conducted. The results suggest that compared with other energy consumption models, DSBF can better adapt to the changing workload and has advantages in predicting the accuracy of the energy consumption model. • Designing the power modeling process, including parameter selection, parameter analysis and screening, model training and evaluation. • Using the "principal component analysis (PCA)" to analyze the factor contribution of each parameter. • Building a new power model named DSBF based on BP neural network and feature selection. [ABSTRACT FROM AUTHOR]

The large heat input welding performance of uncoated weathering steel remains a great challenge since their coarse grain heat-affected zones (CGHAZs) are usually occupied by coarse and brittle microstructure consisting of granular bainitic ferrite (GBF) and martensite/austenite (M/A) constituents. In this article, a V-Ti-N microalloying weathering steel suitable for large heat input welding was achieved through the N addition, and the mechanism dominating the modified microstructure and the enhanced impact toughness of CGHAZ was deeply elucidated mainly by HRTEM. The results indicated that in the simulated CGHAZ with large heat input of 80 kJ/cm, the increase of N content from 0.0030 wt% to 0.0075 wt%, and 0.0115 wt% elevated the density of nano- and submicron-sized particles of (Ti, V)(C, N) containing VN, which in turn resulted in the refinement of prior austenite grains (PAGs) by the improved grain boundary pinning effect and the enhancement in heterogeneous nucleation of intragranular ferrite (IGF) by the decreased lattice disregistry (δ) between (Ti, V)(C, N) and IGF. The fraction of high-angle grain boundaries (HAGBs) with misorientation tolerance angles (MTAs) higher than 15° was thereby increased while the mean equivalent diameter (MED) of ferritic grains with HAGBs was decreased. Simultaneously, the N addition scattered the M/A constituents, promoted the internal substructure of dislocation-type M/A at the expense of twin-type M/A, and accordingly reduced the hardness difference between the M/A constituents and the matrix. All these factors retarded brittle crack initiation and propagation, and low-temperature impact toughness of simulated CGHAZ increased from 62.8 J to 141.2 J. [ABSTRACT FROM AUTHOR]

Macrophage therapy for liver fibrosis is on the cusp of meaningful clinical utility. Due to the heterogeneities of macrophages, it is urgent to develop safer macrophages with a more stable and defined phenotype for the treatment of liver fibrosis. Herein, a new macrophage‐based immunotherapy using macrophages stably expressing a pivotal cytokine from Toxoplasma gondii, a parasite that infects ≈ 2 billion people is developed. It is found that Toxoplasma gondii macrophage migration inhibitory factor‐transgenic macrophage (Mφtgmif) shows stable fibrinolysis and strong chemotactic capacity. Mφtgmif effectively ameliorates liver fibrosis and deactivates aHSCs by recruiting Ly6Chi macrophages via paracrine CCL2 and polarizing them into the restorative Ly6Clo macrophage through the secretion of CX3CL1. Remarkably, Mφtgmif exhibits even higher chemotactic potential, lower grade of inflammation, and better therapeutic effects than LPS/IFN‐γ‐treated macrophages, making macrophage‐based immune therapy more efficient and safer. Mechanistically, TgMIF promotes CCL2 expression by activating the ERK/HMGB1/NF‐κB pathway, and this event is associated with recruiting endogenous macrophages into the fibrosis liver. The findings do not merely identify viable immunotherapy for liver fibrosis but also suggest a therapeutic strategy based on the evolutionarily designed immunomodulator to treat human diseases by modifying the immune microenvironment. [ABSTRACT FROM AUTHOR]

An accurate deep-tissue thermometer with excellent photothermal conversion efficiency is desired for effective photo-thermal therapy (PTT), which will minimize collateral damages to normal cells from overheating or ineffective treatment from insufficient heat. Herein, a nano-thermometer with Nd3+/Yb3+/Ho3+ tri-doped Na 3 InF 6 was designed by hydrothermal method to real-time monitor tissue temperature, and its luminescent performance and temperature sensing behavior based on the luminescence intensity ratio (LIR) technology in the visible and near infrared regions were analyzed under 808 nm excitation. The advantage of temperature probes located in the near infrared (NIR) biological window region was demonstrated by the penetration depth in simulating biological tissue agar. Furthermore, the feasibility of the sample as a self-monitoring photothermal platform was verified by in vitro bactericidal experiments, which expressed excellent photothermal conversion performance and sterilizing rates reached 59.8 % (E. coli) and 53.6 % (S. aureus), respectively. Results demonstrated that the present single-phased Na 3 InF 6 :Nd3+/Yb3+/Ho3+ nanophosphor could serve as a bifunctional photothermal agent with internal tissue temperature measurement and photothermal conversion. Na 3 InF 6 : Nd3+, Yb3+, Ho3+ UC nanoparticles with multimode temperature detection and photothermal conversion functions. [Display omitted] [ABSTRACT FROM AUTHOR]

Parental burnout refers to exhaustion caused by the parenting role. This devastating negative emotion can have repercussions for adolescent social development. Nevertheless, much remains unclear about the association between parental burnout and adolescent prosocial behavior and the potential mechanisms underlying this relationship. Based on theoretical and empirical evidence, the current study examined the relationship between parental burnout and adolescent prosocial behavior by using a sequential mediation model that included both parental empathy and adolescent empathy as potential mediators. A total of 488 parent–adolescent dyads (for adolescents: 45.7% men, 54.3% women, Mage = 15.28 ± 1.67 years; for parents: 36.5% fathers, 63.5% mothers, Mage = 41.30 ± 3.79 years) completed questionnaires regarding demographics, social desirability, parental burnout, parental empathy, adolescent empathy, and adolescent prosocial behavior. After controlling for demographic covariates and social desirability, the results showed that parental burnout had a negative effect on adolescent-reported prosocial behavior through parental cognitive empathy and adolescent other-oriented empathy (adolescent cognitive empathy and empathic concern) sequentially. These findings contribute to our understanding of the role of parental burnout as a family environmental factor detrimental to the positive functioning of adolescents through parental reactions to their children's emotions and children's own social competence. [ABSTRACT FROM AUTHOR]

To deal with the problem of unbalanced load and ignoring task priority in previous task scheduling algorithms, this paper proposes a task scheduling algorithm named P-Min-Min-Max, which combines with priority and greedy strategy. Under the condition of considering the task priority, the algorithm leverages the execution time of tasks for greedy strategy, and binding large task and small task in the task list to form "task pair" to perform scheduling, so as to effectively solve the problem of unbalanced load. To reduce the average response time of tasks, the algorithm priority schedules the small task from the "task pair". The experimental results show that, compared with the Min-Min and P-Min-Min algorithm, the proposed algorithm improves the system resource utilization and service quality of user, and saves the total execution time for tasks. Compared with Max-Min and P-Max-Min algorithm, the proposed algorithm improves the system resource utilization and service quality of user, and reduces the total completion time and average response time. [ABSTRACT FROM AUTHOR]

In this study, we aim to examine how socialization practices predict newcomers' career adaptability during their organizational transitions. Drawing on career construction theory and conservation of resources theory, we argue that newcomers' job embeddedness, as predicted by their perceived organizational socialization tactics, positively predicts their career adaptability during career transitions. We investigate the role of past transition experiences (i.e., career variety) in moderating the relationship between job embeddedness and career adaptability. Data were collected at three time points from 492 newcomers in an information technology company in China. The newcomers' perceived organizational socialization tactics (i.e., training, future prospects and coworker support) positively predicted their job embeddedness, which was positively associated with their career adaptability. Additionally, career variety weakened the positive effect of job embeddedness on career adaptability. Furthermore, career variety moderated the indirect effects of future prospects and coworker support on career adaptability via job embeddedness, but not that of training. We conclude the article with discussions of our theoretical and practical contributions. [ABSTRACT FROM AUTHOR]

The combination of Multi-access Edge Computing (MEC) and New Radio Unlicensed (NR-U) can provide more powerful computing power and wireless access for the Internet of Things (IoT). An essential function in NR-U is to allocate time-frequency resources for IoT devices while ensuring coexistence with wireless local area networks (Wi-Fi) in the same spectrum. However, in the licensed assisted access (LAA) based NR-U, the listen-before-talk (LBT) mechanism makes the nodes located at the edges of the NR-U suffer from the hidden node problem. This can lead to a waste of time-frequency resources in NR-U and degrade the system performance. In this paper, we propose a determinantal point process (DPP) based link scheduling to improve the terminals downlink performance in the hidden nodes zone. Instead of scheduling relay links based on assignment methods, we introduce a recommendation scheme that recommends the D2D transmission nodes from a set of candidate nodes for hidden nodes and establishes D2D relay links. The recommendation scheme is designed based on a DPP model. The simulation results demonstrate that the proposed DPP method is capable of effectively selecting the optimal transmitting nodes and optimizing more hidden nodes while maximizing the sum rate. [ABSTRACT FROM AUTHOR]

By leveraging the cloud computing paradigm, the cloud-assisted Internet of Things (IoT) is able to offer the massive storage and highly available computation services for end-users. When the data collected from IoT devices is endlessly gathering to the cloud center, the data security become new challenges. Encrypting data is an effective measure to guarantee data confidentiality. However, traditional encryption techniques make the data searching and access control inoperative. Current attribute-based keyword search (ABKS) techniques provide a feasibility to achieve data searching and access control over encrypted data simultaneously. However, existing ABKS schemes leak sensitive information via clear access policy and may be unsuitable for certain IoT applications, where the access policies in data might contain private information of data owners such as the security number or the residential area of a resident in smart grids. In this work, we design an efficient and policy-hiding attribute-based keyword search and data sharing scheme (PH-ABKS-DS) in cloud-assisted IoT. To the best of our knowledge, this construction is the first PH-ABKS-DS with practical efficiency that is constructed on prime order group. We provide detailed correctness and security analyses for PH-ABKS-DS. Extensive experiments demonstrate that our proposed PH-ABKS-DS is correct and practical. [ABSTRACT FROM AUTHOR]

In abundant location-based service applications, it is necessary to process continuous spatial keyword queries over geo-textual data streaming. As an important spatial keyword query, the collective spatial keyword (CSK) query aims to find a set of objects such that it covers all the given keywords collectively, the objects within the set are nearest to the query point, and it has the minimum distance between different objects. The existing approaches for the CSK query are mostly index-based algorithms. Although these approaches gain superior performance, their applicability is significantly limited by the necessity to create an index to organize the dataset. Therefore, these index-based approaches cannot be utilized to process data streaming that prevalently exists in most location-based service applications. In addition, the existing algorithms have much room for improvement as the distances between different objects are overlooked when generating feasible candidate sets. Moreover, the results returned by the proposed algorithms could be further refined to offer better decision support for users. In this paper, a greedy algorithm and an approximate algorithm with a provable approximate bound are proposed for the CSK query. Our approaches are appropriate to the CSK queries where the datasets are not suitable to be organized by indexes and can get better query results with less objects and smaller function scores. To boost the query performance, new pruning strategies and heuristic rules are developed. The experimental results demonstrate scalability, efficiency, and effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Necrotizing enterocolitis (NEC) is a leading cause of death in preterm infants. Compared to formula milk, breastfeeding protects against NEC. However, the composition of breast milk is quite complicated, and many immunological compositions remain unknown. In this study, we aimed to investigate the concentration of a secreted protein, Mesencephalic astrocyte-derived neurotrophic factor (MANF), in breastmilk and evaluate its immune-regulatory function in protecting the intestinal epithelial barrier. Our data indicated that MANF was secreted in human milk but could not be detected in infant formulas. More importantly, the amount of MANF in colostrum was higher than that in mature milk. We also clarified that MANF was mainly expressed in intestinal macrophages and was capable of inducing apoptosis and decreasing the inflammation of pro-inflammatory macrophages in both NEC intestinal tissues and BMDMs. Mechanismly, MANF protein significantly inhibited the apoptosis of intestinal epithelial cells and protected epithelial tight junctions through downregulation of the NF-κB pathway in pro-inflammatory macrophages. These results reveal the crucial function of human milk-derived MANF in intestinal macrophages, which contributes to downregulating the intestinal inflammatory response and protecting the homeostasis of intestinal epithelial cells. Our study not only demonstrates a potential mechanism underlying breastfeeding protective effects in NEC but also, more importantly, enables clinical translation, facilitating new strategies for the development of nutritional interventions in the prevention of NEC. [Display omitted] [ABSTRACT FROM AUTHOR]

With the rapid development of cloud computing, secure search has become a hot research spot, which is a promising technique that allows a data user to perform privacy-preserving keyword-based search over encrypted cloud data. In this paper, we further consider the secure search problem based on a practical application scenario that a data owner needs to grant different keyword query permissions for different data users to achieve flexible access control on outsourced encrypted data in the cloud computing environment. To address this problem, we propose a fine-grained authorized keyword secure search scheme by leveraging the ciphertext policy attribute-based encryption (ABE), which not only supports privacy-preserving keyword-based search over encrypted data, but also inherits flexible and fine-grained data privilege control properties of ABE. Moreover, our proposed scheme is able to achieve fine-grained search permission update with very small communication and computation cost. By running the attribute revocation sub-protocol and attribute addition sub-protocol, the data owner can flexibly and efficiently update a data user's keyword search permissions when the data user's system role changes. We provide detailed performance analysis and rigorous security proof for our scheme. Extensive experiments demonstrate the correctness and practicality of the proposed scheme. • Presented a fine-grained authorized keyword secure search scheme in cloud computing. • Presented an efficient and fine-grained search permission update protocol. • Analyzed and proved the security of the proposed scheme. • Analyzed the complexity and tested the performance of the proposed scheme. [ABSTRACT FROM AUTHOR]