Search

In the current era of the Internet of Things (IoT), various devices can provide more services by connecting to the Internet. However, the explosive growth of connected devices will cause the cloud core overload and significant network delays. To overcome these problems, the Mobile Edge Computing (MEC) network is proposed to provide most of the computing and storage near the radio access network to reduce the traffic of the core cloud network and provide lower latency for the terminal.Mobile edge computing can work with third parties to develop multiple services, such as mobile big data analysis and context-aware services. However, when there is a large amount of popular data accessed in a short period, the system must generate many replicas, which will not only reduce access efficiency but also cause additional traffic overhead. To improve the above problems, an Adaptive Replica Configuration Mechanism (ARCM) is proposed in this paper to predict the popularity of the file and make a replica to the low-blocking node. This method spreads the subsequent access workload by copying the popular file in advance to improve the overall performance of the system.

Effective constraint handling techniques are of great significance for evolutionary algorithms dealing with constrained optimization problems. To date, many constraint handling techniques, such as penalty function, superiority of feasible solutions, and -constraint, have been designed. However, different constraint handling techniques are usually suited to different problems, even the most appropriate technique changes along with the stages of the optimization process. Motivated by this phenomenon, we propose a voting-mechanism based ensemble framework, named VMCH, to integrate multiple constraint handling techniques for solving various constrained optimization problems. In this framework, each constraint handling technique acts as a voter, all voters vote for each pair of solutions, and the solution in each pair with the highest weighted votes is considered better. In addition, an adaptive strategy is developed to adjust the voter weights according to their historical voting performance. To investigate the performance of VMCH in improving existing algorithms, the proposed VMCH is embedded into the three best algorithms in the competition on constrained single objective real-parameter optimization at CEC 2018, namely MAgES, iLSHADE, and IUDE, to form three new algorithm versions, i.e., MAgES-VMCH, iLSHADE-VMCH, and IUDE-VMCH. They are compared with seven state-of-the-art peer algorithms. Extensive experiments are conducted on 57 real-world constrained optimization problems. The ranking results show that the new algorithm version MAgES-VMCH takes first place among the ten comparison algorithms. Moreover, all the new VMCH-enhanced versions of the three best algorithms are superior to their original versions. Therefore, the proposed VMCH framework can achieve competitive performance in solving constrained optimization problems.

Gaze tracking is widely used in fatigue driving detection, eye disease diagnosis, mental illness diagnosis, website or advertising design, virtual reality, gaze-control devices and human-computer interaction. However, the influence of light, specular reflection and occlusion, the change of head pose, especially the ever-changing human pose in natural scenes, have brought great challenges to the accurate gaze tracking. In this paper, gaze tracking in natural scenes is studied, and a method based on Convolutional Neural Network (CNN) with residual blocks is proposed, in which attention mechanism is integrated into the network to improve the accuracy of gaze tracking. Furthermore, it is tested on the GazeFollow database which contains six kinds of databases. The results show that the performance of proposed method outperforms that of other state-of-the-art methods in natural scenes. Moreover, the proposed method has better real-time performance and is more suitable for practical applications.

Many mobile apps of social Internet of Things (sIOT) systems can help us record and share daily events, such as health and sport events. In fact, healthy diet recognition is an important and challenging problem in dish health assessment. Via the collection and monitoring of data pertaining to our daily diet, we can work in collaborative ways to achieve dish image annotation based on sIOT systems to enhance deep features. To this end, this article proposes a deep feature and attention mechanism-based method for dish health assessment, which aims to apply a hand-deep local-global net (HDLGN) for dish image recognition. Then, food taste is used as health guidance for people who want to lose weight or follow doctors' advice. First, the local attention mechanism is introduced to identify key areas of the dish image. Second, ingredient and handcrafted color features are extracted to learn deep features. Subsequently, we combine local and global attention mechanisms to return the dish taste as the recognition result. Finally, experiments show that our proposed method can effectively improve the accuracy of taste recognition.

In order to reduce the fatigue life of the car body caused by the dead weight of the car body, a lightweight design of the car body mechanism based on the fatigue life is proposed. The modal analysis of the car body is carried out by establishing the finite element model of the car body. According to the generated modal neutral file, a rigid-flexible coupling multi-body dynamic model is established, which enables the comprehensive and in-depth analysis of the fatigue life of the car body. According to the analysis results, the topological optimization theory is adopted, and the constraint conditions are established based on the static stiffness characteristics of the car body. Specific design schemes are put forward from two aspects of bending stiffness and torsional stiffness, and these two variables are limited to obtain the optimal value of the car body structure and realize the lightweight of the car body. The test results show that the proposed method can reduce the weight of car body structure, and the variation range of torsional stiffness and bending stiffness is within 5%, which can improve the fatigue life of car body. It shows that the proposed method has certain reference value for lightweight design of side body.

The Control Rod Drive Mechanism (CRDM) is an essential part of the reactor, which realizes the start-stop and power adjustment of the reactor by lifting and lowering the control rod assembly. As a moving part in CRDM, the latch directly contacts with the control rod assembly, and the life of latch is closely related to the service life of the reactor. In this paper, the relationship between the life of the latch and the step stress, friction stress, and impact stress in the process of movement is analyzed, and the optimization methodology and process of latch life based on the approximate model are proposed. The design variables that affect the life of the latch are studied through the experimental design, and the optimization objective of design variables based on the latch life is established. Based on this, an approximate model of the life of the latch is built, and the multi-objective optimization of the life of the latch is optimized through the NSGA-II algorithm.

Visual programming tools are widely applied in the game industry to assist game designers in developing game artificial intelligence (game AI) and gameplay. However, testing multiple game engines is a time-consuming operation, which degrades development efficiency. To provide an asynchronous platform for game designers, this paper introduces Asyncflow, an open-source visual programming solution. It consists of a flowchart maker for game logic explanation and a runtime framework integrating an asynchronous mechanism based on an event-driven architecture. Asyncflow supports multiple programming languages and can be easily embedded in various game engines to run flowcharts created by game designers.

In this work, a day-ahead to week-ahead solar irradiance prediction mechanism based on convolutional Long Short-Term Memory (LSTM) model is proposed. The system takes hourly irradiance data from several days previous to the prediction day as the input. Then, features are extracted from the input data using one dimensional convolutional filters. The extracted features from different days are concatenated and serve as the input of the LSTM network. The output of the LSTM is further concatenated with selected original data to emphasize its importance and enhance the prediction results. Afterwards, a fully connected layer is used to produce the final prediction output. The proposed framework can be trained using a relatively small amount of training data within the duration of only two months. Therefore, it has the advantage of being applicable in the initial deployment phase when the amount of training data is limited. The proposed system has been validated using a highly challenging dataset collected in Taiwan with tropical and subtropical marine island climate.

In view of the various types of fabric defects, and the problems of confusion, density unevenness and small target defects, which are difficult to detect, this paper builds a deep learning defect detection network incorporating an attention mechanism. The data augmentation strategy is used to enrich the number of samples of each defective type, and the enriched samples were extracted by the feature extraction network integrated with the attention mechanism, which can improve the feature extraction ability of confusable defect types and small defect types. Region proposal generation generates a proposal box for extracted features, and adds an online hard example mining strategy to re-learn hard examples to accelerate network convergence. Region feature aggregation maps the proposal box to the feature map to obtain the region of interest. Finally, the defect features are classified and the bounding boxes are regressed. The results show that this algorithm can effectively detect 39 categories of fabric defects with a detection speed of 0.085 s and a detection accuracy of 0.9338.

El objetivo general del presente artículo es analizar las prácticas proteccionistas en lo referente a la Inversión Extranjera Directa introducidas en los últimos años en Europa Central, así como las implicaciones para México. Para proteger el mercado europeo de las prácticas abusivas la Unión Europea creó el mecanismo de screening a partir del Reglamento de la Unión Europea No. 2019/452 de 2019. Los países de la Europa Central implementaron en sus marcos legales dichas provisiones. ¿Cuáles son las implicaciones de esos marcos legales para la relación económica con México? Se aplicó el método comparativo en lo referente a los marcos legales, así como el análisis de los datos empíricos. Con la técnica de investigación de la revisión documental el tipo de investigación es cualitativo. En la conclusión se observa que los países de la Europa Central presentan una heterogeneidad en lo referente a la implementación de las medidas proteccionistas de la UE. Además, se considera que la perspectiva post-pandemica de la recuperación económica la cooperación será un desafío por las prácticas proteccionistas, incluyendo un desafío para México para estrechar los lazos con Europa Central. Por ende, se considera el desarrollo de campos estratégicos de mutuo beneficio en los temas de energías renovables, transporte sustentable urbano, y proyectos conjuntos a nivel municipal.

Design of connections in mass timber are critical. Mass plywood panels (MPP) are a relatively new mass timber product, therefore, only a few studies characterizing their mechanical and connection properties exist. Dowel bearing strength is a critical parameter required in connection design regardless of the complexity of the connection. This study investigated the dowel bearing strength of MPP under the effect of exposure to elevated temperature. Thirty-two exposure duration-temperature combination was tested along with control group. Two analytical models are developed to explain the thermal degradation, one assuming a mechanism based on first-order kinetics and the second using a statistical regression. The degradation in the dowel bearing strength with respect to the increase in time and temperature exposure was characterized. In general, the kinetics model seemed to explain the data better than MLR using one less parameter.

The shear properties of bidisperse magnetorheological (MR) fluid have been extensively studied based on the experiment or simulation method, but the research on the enhancement mechanism is still not sufficient and need to be further investigated. In this paper, we proposed a new approach to analyze the mechanism based on the local microstructural models. The typical local configurations of particles in bidisperse MR fluid were determined by means of similarity experiment and confirmed by microstructure simulations. Subsequently, the evolution of local configurations under the shear process was simulated, and the corresponding shear resistance models were proposed. It is found that the configurations with small particles attached on sides of the chain can increase the shear resistance as well as the shear deformation, and the enhancement mechanism is determined based on the analysis of the relative position evolution of small and large particles in the local microstructures. The effect of particle size ratio on the properties of bidisperse MR fluid was also investigated. It is discovered that there is an optimal particle size ratio for MR fluid to achieve better performance.

In recent years, with the continuous improvement of China’s economic level and the accelerating social transformation, the social demand for grass-roots public services has begun to diversify and refine. As an important part of grass-roots public services, tax service is also facing the transformation of service demand. However, the traditional grass roots working mechanism of tax departments has limited effect under the new situation, it is difficult to meet the increasingly refined service needs of taxpayers, and there is a gap between the fragmented working mechanism at the grass- roots level and diversified service demands. It is urgent to respond to social needs and deliver services accurately through institutional reform and innovation. Firstly, this paper analyzes the problems existing in the grass-roots working mechanism of tax departments in China. Then, by introducing a series of measures for the reform and innovation of grass-roots working mechanism based on precise supply service in Shunde District Taxation Bureau of Foshan City, State Taxation Administration of The People’s Republic of China (hereinafter referred to as “Shunde Taxation Bureau”), and based on analyzing the achievements of its reform and innovation, this paper summarizes the reference and enlightenment of its reform experience to the innovation of grass roots working mechanism of tax departments in China.

In contrast to the multiple disease-modifying therapies that are available for relapsing–remitting multiple sclerosis (MS), the therapeutic options for progressive MS (PMS) are limited. Recent advances in our understanding of the neuroimmunology of PMS, including the mechanisms that drive slowly expanding lesions, have fuelled optimism for improved treatment of this condition. In this Review, we highlight the commonly observed neuropathology of PMS and discuss the associated mechanisms of CNS injury. We then apply this knowledge to formulate criteria for therapeutic efficacy in PMS, beginning with the need for early treatment owing to the substantial neuropathology that is already present at the initial clinical presentation. Other requirements include: antagonism of neuroaxonal injury mediators such as pro-inflammatory microglia and lymphocytes; remediation of oxidative stress resulting from iron deposition and mitochondrial dysfunction; and promotion of neuroprotection through remyelination. We consider whether current disease-modifying therapies for relapsing–remitting MS meet the criteria for successful therapeutics in PMS and suggest that the evidence favours the early introduction of sphingosine 1-phosphate receptor modulators. Finally, we weigh up emerging medications, including repurposed generic medications and Bruton’s tyrosine kinase inhibitors, against these fundamental criteria. In this new therapeutic era in PMS, success depends collectively on understanding disease mechanisms, drug characteristics (including brain penetration) and rational use. Despite substantial progress in the development of disease-modifying therapies for multiple sclerosis (MS), the therapeutic options for progressive MS (PMS) remain limited. The authors present criteria for therapeutic success in PMS and consider the extent to which current drugs meet these criteria.

Stocks with high maximum daily returns (MAX) in a given month yield low returns in the subsequent month. We thoroughly examine the underlying behavioral mechanism based on stock market and individual trading data. We argue that the short-term return predictability is driven by investor overreaction rather than cumulative prospect theory (CPT) preferences. First, we show empirically that high-MAX stocks are comparably not more attractive for CPT-investors. Second, we observe immediate price reversals and no preference-induced price pressure following the MAX return. Third, in line with theories on information-dependent over- and underreaction, the MAX effect reverses if MAX is caused by earnings announcements. Fourth, the MAX effect only exists for stocks far away from an anchoring point as overreaction is mitigated by anchors. Further, discount brokerage data shows that retail investors’ speculative buying pressure for lottery-like stocks cannot explain the specific return patterns associated with the MAX effect.

Flotation is a complex process that occurs in solid–liquid-gas multiphase systems, and its main factors include the minerals, separation medium, as well as various flotation reagents. The study of mineral properties and interactions with other components such as reagents and water lays the basic theoretical foundation for flotation. Density functional theory (DFT) calculations can qualitatively evaluate the exchange of matter and energy between the mineral system and the surroundings and quantitatively characterize these behaviors, which greatly expands the breadth and depth of flotation studies. This review systematically summarizes the advances of flotation research based on DFT studies, including the study of mineral crystal chemistry represented by the theory of lattice defects, mineral surface hydration such as hydrophilicity and hydrophobicity, surface regulation mechanism, and collecting mechanism based on surface adsorption theory. More significantly, it systematically elaborates different types of collectors according to their characteristics and emphatically explains the mechanism of some typical collectors in detail.

Accurate prediction of protein-ligand binding affinity is important in that it can lower the overall cost of drug discovery in structure-based drug design. For more accurate prediction, many classical scoring functions and machine learning-based methods have been developed. However, these techniques tend to have limitations, mainly resulting from a lack of sufficient interactions energy terms to describe complex interactions between proteins and ligands. Recent deep-learning techniques show strong potential to solve this problem, but the search for more efficient and appropriate deep-learning architectures and methods to represent protein-ligand complexes continues. In this study, we proposed a deep-neural network for more accurate prediction of protein-ligand complex binding affinity. The proposed model has two important features, descriptor embeddings that contains embedded information about the local structures of a protein-ligand complex and an attention mechanism for highlighting important descriptors to binding affinity prediction. The proposed model showed better performance on most benchmark datasets than existing binding affinity prediction models. Moreover, we confirmed that an attention mechanism was able to capture binding sites in a protein-ligand complex and that it contributed to improvement in predictive performance. Our code is available at https://github.com/Blue1993/BAPA.Author summaryThe initial step in drug discovery is to identify drug candidates for a target protein using a scoring function. Existing scoring functions, however, lack the ability to accurately predict the binding affinity of protein-ligand complexes. In this study, we proposed a deep learning-based approach to extract patterns from the local structures of protein-ligand complexes and to highlight the important local structures via an attention mechanism. The proposed model showed good performance for various benchmark datasets compared to existing models.

In order to improve the robustness of speech recognition systems, this study attempts to classify stressed speech caused by the psychological stress under multitasking workloads. Due to the transient nature and ambiguity of stressed speech, the stress characteristics is not represented in all the segments in stressed speech as labeled. In this paper, we propose a multi-feature fusion model based on the attention mechanism to measure the importance of segments for stress classification. Through the attention mechanism, each speech frame is weighted to reflect the different correlations to the actual stressed state, and the multi-channel fusion of features characterizing the stressed speech to classify the speech under stress. The proposed model further adopts SpecAugment in view of the feature spectrum for data augment to resolve small sample sizes problem among stressed speech. During the experiment, we compared the proposed model with traditional methods on CASIA Chinese emotion corpus and Fujitsu stressed speech corpus, and results show that the proposed model has better performance in speaker-independent stress classification. Transfer learning is also performed for speaker-dependent classification for stressed speech, and the performance is improved. The attention mechanism shows the advantage for continuous speech under stress in authentic context comparing with traditional methods.

Robot-assisted surgery has been extensively applied in various microsurgical disciplines owing to its enhanced accuracy and dexterity based on the motion-scaling function between a hand and a surgical instrument. However, the surgical robot system developed thus far incurs high manufacturing costs and restricted compatibility due to the complicated control system, including many actuators and sensors. This paper proposes a novel passive mechanism for motion scaling based on the pantograph structure to resolve these drawbacks of robotic assistance devices. As a first step, a design configuration featuring gravity compensation and the duplication of directional motion is suggested. Subsequently, the geometric dimensions required to satisfy the surgical space and structural constraints are defined. Moreover, the mass of elements required to enable gravity compensation is calculated using moment equations. After determining the principal design parameters, the motion scaling of the proposed passive model is identified using a three-dimensional computer-aided design. In addition, for an extremely precise operation in microsurgery, the dynamic reaction force is expected to be constant in any location. Therefore, to investigate dynamic dexterity, the mathematical model is formulated based on the Lagrangian dynamic equation. Then, the dynamic workspace range is analysed from the determinant of the mass matrix. In addition, the analysis results are evaluated through comparative simulations in different workspace ranges; hence, a constant reaction force can be achieved only in the dynamic workspace range.

The study aims to establish a platform-based enterprise credit supervision mechanism, and combined with big data, accurately evaluate the credit assets of enterprises under the influence of social stability risk, and improve the ability of enterprises to deal with risks. Using descriptive statistical methods, the study shows that most local enterprises exist in the form of micro loans, which promotes the development of local economy to a certain extent, but it is a vicious cycle of economic development; The overall prediction accuracy of the single enterprise risk assessment model under the influence of social stability risk is 65%. Compared with the single algorithm, the prediction accuracy of the integrated algorithm model is significantly improved, and the prediction accuracy can reach 83.5%, the standard deviation of data prediction is small, and the stability of the model is high.

Energy performance contracting (EPC) mechanism is a good choice for conducting energy-saving renovation projects of public buildings. Furthermore, risk analysis is critical to smoothly implement th...

Anchor link identification is a task that determines which pair of accounts in different social networks belongs to the same user. As a foundation of many applications, such as information dissemination across networks, anchor link identification has attracted much attention in recent years. Several methods learned a latent common space to preserve the structural proximity of accounts, such that the contributions of diverse neighbors are ignored due to the unweighted edges. In sparse networks, the overlapping of neighbors is rare and structural similarities are small, resulting in performance degradation of these methods. In this paper, we propose a triple-layer attention mechanism-based network embedding (TANE) method which utilizes the network structure to identify anchor links. TANE has two learning modules: the attention learning module which learns contribution weights of intranetwork and internetwork neighbors in anchor link identification under the supervision of observed anchor links, and the embedding learning module which tries to learn a latent common space by preserving weighted structural proximity of neighbors and second-order neighbors (i.e., neighbors of neighbors). By exploiting second-order neighbors, more structural information is introduced into embedding processing, which reduces sparsity. The weights and embeddings are transferred between modules and learned uniformly by Adam algorithm. Extensive experimental results of two real-world datasets show that TANE can improve the top-k hit ratio of anchor link identification compared with several state-of-the-art methods.

This paper describes a detailed mechanistic study of the silver-catalyzed Z-selective hydroalkylation of terminal alkynes. Considering the established mechanistic paradigms for Z-selective hydroalkylation of alkynes, we explored a mechanism based on the radical carbometalation of alkynes. Experimental results have provided strong evidence against the initially proposed radical mechanism and have led us to propose a new mechanism for the Z-selective hydroalkylation of alkynes based on boronate formation and a 1,2-metalate shift. The new mechanism provides a rationale for the excellent Z-selectivity observed in the reaction. A series of stoichiometric experiments has probed the feasibility of the proposed elementary steps and revealed an additional role of the silver catalyst in the protodeboration of an intermediate. Finally, a series of kinetic measurements, KIE experiments, and competition experiments allowed us to identify the turnover limiting step and the resting state of the catalyst. We believe that the results of this study will be useful in the further exploration and development of related transformations of alkynes.

Significance: Acetaminophen (APAP) is one of the quantitively most consumed drugs worldwide. Although safe at therapeutic doses, intentional or unintentional overdosing occurs frequently causing severe liver injury and even liver failure. In the United States, 50% of all acute liver failure cases are caused by APAP overdose. However, only one antidote with a limited therapeutic window, N-acetylcysteine, is clinically approved. Thus, more effective therapeutic interventions are urgently needed. Recent Advances: Although APAP hepatotoxicity has been extensively studied for almost 50 years, particular progress has been made recently in two areas. First, there is now a detailed understanding of involvement of oxidative and nitrosative stress in the pathophysiology, with identification of the reactive species involved, their initial generation in mitochondria, amplification through the c-Jun N-terminal kinase pathway, and the mechanisms of cell death. Second, it was demonstrated in human hepatocytes and through biomarkers in vivo that the mechanisms of liver injury in animals accurately reflect the human pathophysiology, which allows the translation of therapeutic targets identified in animals to patients. Critical Issues: For progress, solid understanding of the pathophysiology of APAP hepatotoxicity and of a drug's targets is needed to identify promising new therapeutic intervention strategies and drugs, which may be applied to humans. Future Directions: In addition to further refine the mechanistic understanding of APAP hepatotoxicity and identify additional drugs with complementary mechanisms of action to prevent cell death, more insight into the mechanisms of regeneration and developing of drugs, which promote recovery, remains a future challenge. Antioxid. Redox Signal. 35, 718–733.

Migraine is a type of primary headache with recurrent attacks, negatively affects the daily living activities of sufferers because of its severity, and causes a heavy economic burden. The economic, social, and physical burdens of migraine grow with the increasing frequency of headache attacks. Mechanism-based treatments are increasingly needed, especially for those with chronic migraine (CM) or episodic migraine (EM) with frequent attacks. Conventional migraine-preventive medications have been essentially developed for some other diseases and shown to be also effective against migraine headaches. Efficacy, safety, and tolerability issues limit their use for an adequate duration, and most patients are under the risk of medication-overuse headache because of the ineffectiveness of attack treatments. In recent decades, a better understanding of migraine pathophysiology has given a new direction to migraine drug research to fulfill the unmet need for the development of migraine-specific medications. Calcitonin gene-related peptide (CGRP) has attracted attention with its potential role in migraine pathogenesis and has become the focus of drug research in this area as of the 1990s. The first monoclonal antibody developed and approved for the treatment of migraine is erenumab. Being the only therapeutic antibody against the CGRP receptor, erenumab differs from the other monoclonal antibodies for migraine prevention that target the CGRP ligand. Erenumab is a fully human, immunoglobulin G2 class monoclonal antibody with no immunomodulatory effect. It blocks the CGRP receptor with high affinity and selectivity and prevents binding of the CGRP ligand to this receptor. It does not have a significant effect on other receptors in the calcitonin receptor family. Erenumab has been shown to diminish the number of migraine days and the need for attack treatment and to improve patient-reported outcomes in patients with EM and CM.

The present paper is focused on development of the thermodynamic model and a heat-driven Vuilleumier refrigerator. Thermodynamic properties and performance are predicted by thermodynamic model. On the other hand, a prototype Vuilleumier refrigerator with crank drive mechanism is built and the performance is measured. In the thermodynamic model, the refrigerator is divided into five working spaces for analysis, including hot chamber, hot regeneration chamber, middle chamber, cold regeneration chamber and cold chamber. Also, the influence of clearance leakage between middle chamber and buffer chamber is investigated. The effects of geometrical parameters, charged pressure, rotating speed, heating temperature, cooling temperature and heat loading on the cold head temperature are evaluated. In addition, the numerical results and the experimental data under different operating parameters are compared for model validation. As the Vuilleumier refrigerator operated at 22 bar pressure, 600 rpm rotating speed, 900 K heating temperature and 276 K cooling temperature, the cold head can reach a zero-load temperature of 221 K. When a 0.7 W heating load is applied on the cold head, cold head temperature of 252.6 K and coefficient of performance of 0.0068 can be obtained.

Background Rodents are thought to be produced their human-audible calls (AUDs, below 20 kHz) with phonation mechanism based on vibration of the vocal folds, whereas their ultrasonic vocalizations (USVs, over 20 kHz) are produced with aerodynamic whistle mechanism. Despite of different production mechanisms, the acoustic parameters (duration and fundamental frequency) of AUDs and USVs change in the same direction along ontogeny in collared lemming Dicrostonyx groenlandicus and fat-tailed gerbil Pachyuromys duprasi. We hypothesize that this unidirectional trend of AUDs and USVs is a common rule in rodents and test whether the AUDs of yellow steppe lemmings Eolagurus luteus would display the same ontogenetic trajectory (towards shorter and low-frequency calls) as their USVs, studied previously in the same laboratory colony. Results We examined for acoustic variables 1200 audible squeaks emitted during 480-s isolation-and-handling procedure by 120 individual yellow steppe lemmings (at 12 age classes from neonates to breeding adults, 10 individuals per age class, up to 10 calls per individual, each individual tested once). We found that the ontogenetic pathway of the audible squeaks, towards shorter and lower frequency calls, was the same as the pathway of USVs revealed during 120-s isolation procedure in a previous study in the same laboratory population. Developmental milestone for the appearance of mature patterns of the squeaks (coinciding with eyes opening at 9–12 days of age), was the same as previously documented for USVs. Similar with ontogeny of USVs, the chevron-like squeaks were prevalent in neonates whereas the squeaks with upward contour were prevalent after the eyes opening. Conclusion This study confirms a hypothesis of common ontogenetic trajectory of call duration and fundamental frequency for AUDs and USVs within species in rodents. This ontogenetic trajectory is not uniform across species.

Purpose The purpose of this paper is to evaluate three categories of four-degrees of freedom (4-DOFs) upper limb rehabilitation exoskeleton mechanisms from the perspective of relative movement offsets between the upper limb and the exoskeleton, so as to provide reference for the selection of exoskeleton mechanism configurations. Design/methodology/approach According to the configuration synthesis and optimum principles of 4-DOFs upper limb exoskeleton mechanisms, three categories of exoskeletons compatible with upper limb were proposed. From the perspective of human exoskeleton closed chain, through reasonable decomposition and kinematic characteristics analysis of passive connective joints, the kinematic equations of three categories exoskeletons were established and inverse position solution method were addressed. Subsequently, three indexes, which can represent the relative movement offsets of human–exoskeleton were defined. Findings Based on the presented position solution and evaluation indexes, the joint displacements and relative movement offsets of the three exoskeletons during eating movement were compared, on which the kinematic characteristics were investigated. The results indicated that the second category of exoskeleton was more suitable for upper limb rehabilitation than the other two categories. Originality/value This paper has a certain reference value for the selection of the 4-DOFs upper extremity rehabilitation exoskeleton mechanism configurations. The selected exoskeleton can ensure the safety and comfort of stroke patients with upper limb dyskinesia during rehabilitation training.

A redundantly actuated parallel manipulator (RAPM) with mixed translational and rotational degrees of freedom (DOFs) is challenged for its dimensionally homogeneous Jacobian modeling and optimal design of architecture. In this paper, a means to achieve redundant actuation by adding kinematic constraints is introduced, which reduces the DOFs of the end-effector (EE). A generic dimensionally homogeneous Jacobian is developed for this type of RAPMs, which maps the generalized velocities of three points on the EE to the joint velocities. A new optimization algorithm derived from this dimensionally homogeneous Jacobian is proposed for the optimal design of this type of RAPMs. As an example, this paper presents a spatial RAPM involving linkages and cam mechanisms. This RAPM has 4 DOFs and 6 translational actuations. The linkage lengths and the position of the universal joints of the RAPM are optimized based on the dimensionally homogeneous Jacobian.

Efforts to build a regional human rights mechanism in Asia are being renewed. Separation of powers adjudication will be inevitable if the right of access to court is included in the new mechanism. This is significant since the potential for separation of powers cases involving human rights issues in Asia is high. An Asian human rights mechanism must take this possibility into account, since adjudicating on such issues may severely impact its stability and long-term viability. A mechanism based on existing regional systems such as the ECHR can seek to minimize these risks via institutional solutions. On the other hand, an Asian mechanism can side-step these issues in the short term by focusing on a narrow set of rights, which minimize the potential for raising issues of separation of powers. In the long term, however, a complete charter of fundamental rights cannot ignore separation of powers issues being linked with human rights. The aim of this paper is to highlight both the inevitability and risks of adjudicating cases involving a nexus between separation of powers and human rights by a regional human rights court.

Crowdsourcing task assignment has become an important task assignment model in the Internet economy era. In this paper, we study the crowdsourcing task assignment problem based on employer net profit and employee satisfaction. First, the reliability and interest of employees are modeled, based on which the mathematical expressions for employer net profit and employee satisfaction are given. Then, a multi-objective optimization problem is formulated to maximize employer net profit and employee satisfaction by jointly optimizing the task assignment matrix and task offer vector. Since the considered problem contains discrete variables, it cannot be solved directly by traditional optimization methods. Therefore, two low-complexity high-performance algorithms are proposed. The first algorithm is based on a fast non-dominated ranking genetic algorithm with an elite, which is able to explore the Pareto bound of the considered problem. The second algorithm is based on a reinforcement learning framework, which is able to maximize the weighted sum of employer net profit and employee satisfaction. Numerical results show that the number of tasks assigned to employees affects both employee satisfaction and employer net profit. The Pareto bounds and Pareto optimal solutions based on the solutions of the two proposed algorithms are also presented numerically, which quantitatively characterize the tradeoff between employer net profit and employee satisfaction.

Conflict analysis has become a hot issue in management science. In the context of conflict analysis, there are three attitudes for agents to describe the opinion, including supportive, opposite, and neutral. Then, the conflict situation is discussed and analyzed. In this paper, we propose an extended Pawlak conflict model concerning the trust mechanism to solve the problem of the reaching consensus process. Firstly, the degree of conflict is defined by the weights of agents considering the penalty factors, and an extended Pawlak conflict model is presented. Then, the trust recommendation mechanism is proposed to modify the opinions of agents and reach conflict consensus. Four kinds of feedback mechanism are discussed by using four perspectives: 1) without the penalty factors and no limit to the range of adjustments; 2) without the penalty factors and the attitude of agents vary from pessimistic to neutral; 3) with the penalty factors and no limit to the range of adjustments; 4) with the penalty factors and the attitude of agents vary from pessimistic to neutral. Furthermore, this paper presents a process of reaching consensus based on the trust recommendation mechanism for the conflict analysis problem. Finally, a case study is used to validate the effectiveness and superiority of the proposed method. A comparative analysis is completed for the parameters and the maximum alliances could be obtained with the original Pawlak conflict model.

Adherence to new development concept, integration of integrity and innovation, and improvement of enterprise technological innovation capacity are the essence of new economic development in China. Tobacco economy is an important part of national economy, whose development is facing the internal and external pressure of development. Therefore, the enterprises above the designated scale in Shandong Province from 2011 to 2019 are selected as the holistic research sample to measure the R&D input-output index by DEA nonparametric method. It is found that (1) the technological innovation capacity of enterprises has been greatly improved but not reached the leading edge level; (2) the efficiency of technological innovation of enterprises has changed in the form of V; (3) the redundancy of full-time personnel equivalents exists and the technological efficiency and scale benefit do not meet the development expectation. The study indicates that the Chinese government should treat the development of tobacco economy carefully, adopt multiple measures of regulation and control, construct a healthy and synergetic development mechanism with the participation of innovation subjects, and realize the agglomeration and optimization of innovation factors, so as to make the development of tobacco enterprises meet the economic needs of China in the new era.

The success or failure of practical teaching in data structures and algorithms course determines the success or failure of the course group. The reform of practical teaching in this course takes the course group as the background and aims to meet the needs of students at different levels. It proposes a hierarchical practical teaching mode involving three levels in terms of foundation, design, and synthesis driven by cases throughout the whole course group and a fine process control mechanism based on multi-stage process assessment.

Bamboo is mainly grown in hilly areas, and the harvesting of bamboo basically relies on labor. Moreover, the bamboo is prone to splitting problems during harvesting. To liberate labor and improve work efficiency, the crack propagation principle of bamboo was studied. Based on this study, a new cutting scheme using spiral feed was proposed. Additionally, a new bamboo cutting mechanism was designed. The new cutting mechanism, when installed on a harvesting vehicle, can automatically complete the cutting operation. The cutting mechanism is different from the traditional ones, and it uses four sets of saw blades for spiral feed cutting around the bamboo, which can reduce the splitting probability during the cutting process. Finally, a solid model of the cutting mechanism was built, and the basic movement process was simulated to verify the feasibility of the bamboo cutting mechanism.

The airflow past flap side edges is an important contributor to airframe noise. It has been found that the dominant features of the flow at the flap side edges are the double-vortex structures and ...

Universal mobile networks require enhanced capability and appropriate quality of service (QoS) and experience (QoE). To achieve this, Long Term Evolution (LTE) system operators have intensively deployed femtocells (HeNBs) along with macrocells (eNBs) to offer user equipment (UE) with optimal capacity coverage and best quality of service. To achieve the requirement of QoS in the handover stage among macrocells and femtocells we need a seamless cell selection mechanism. Cell selection requirements are considered a difficult task in femtocell-based networks and effective cell selection procedures are essential to reduce the ping-pong phenomenon and to minimize needless handovers. In this study, we propose a seamless cell selection scheme for macrocell-femtocell LTE systems, based on the Q-learning environment. A novel cell selection mechanism is proposed for high-density femtocell network topologies to evaluate the target base station in the handover stage. We used the LTE-Sim simulator to implement and evaluate the cell selection procedures. The simulation results were encouraging: a decrease in the control signaling rate and packet loss ratio were observed and at the same time the system throughput was increased.

As an important expression of social public opinion, network public opinion develops rapidly with the popularization of the internet and then affects the real society. Therefore, the use of computer technology to study the network public opinion information transmission mechanism has strong practical significance. The purpose of this paper is to use cloud computing to realize the research of information dissemination mechanism in the context of cross-media public opinion network. Researched from three aspects of operator supervision, number of media, and user density, the hotspot propagation mechanism of Storm platform given in this paper can solve the efficiency problems of traditional algorithms while ensuring accuracy, improve efficiency, and lay the foundation for the research on the monitoring of Internet public opinion propagation.

In this paper, we report on a new path of ZnWO4 phase formation, synthesized by the polymerizable complex (PC) method. At 550 °C, we obtained a single phase of the ZnWO4 complex oxide. To explain the phase transformation processes, we propose a mechanism based on the coexistence of more than one amorphous phase after the pre-pyrolysis process. These amorphous metastable phases indicate a different phase formation path, which has not yet been described in the literature for multi-component oxides processed by the PC method. The formation path proposed here shows the relevance of the metastable phases in the reaction processes of complex oxides.