Path Planning of Anti ship Missile based on Voronoi Diagram and Binary Tree Algorithm

The path planning of anti-ship missile should be considered both cruising in safety and striking in quick, which is an intractable problem. In particular, it is difficult to consider the safety of each missile path in the path planning of multiple missiles. To solve this problem, the “AREA Algorithm” is presented to divide the relative relations of areas：relative security area of the threat areas and fast-attack area of target approaching. Specifically，it is a way to achieve area division through the relationship between the target and the center of the operational area. The Voronoi diagram topology network, Dijkstra algorithm and binary tree algorithm have been used in the above process as well. Finally, Simulations have verified the feasibility and obvious advantages of “AREA Algorithm” compared with the single algorithm, and the tactical meaning in path planning of multiple missiles

The Role of IL-33 in Rheumatic Diseases

Interleukin-33 (IL-33), a novel member of IL-1 family, has been recently implicated in several inflammatory and autoimmune diseases. IL-33 can be produced by various types of tissues and cells and induce gene expression of Th2-associated cytokines via binding to the orphan receptor ST2. By promoting Th2 type immune response, IL-33 plays important roles in the allergy, whereas its function in autoimmune diseases attracts more attention. Recent studies reported the correlation of IL-33 with rheumatic diseases, and most of them found that the IL-33 expression levels were consistent with disease activity and development. Furthermore, evidence has indicated that IL-33-related treatment may ameliorate the pathogenic conditions and attenuate disease progression of those rheumatic diseases. Therefore, elucidation of the roles of IL-33 in rheumatic diseases would be beneficial to understand the pathogenesis and therapy of these diseases. In this paper, we will summarize the roles of IL-33 in the rheumatic diseases

Planning Emergency Shelters for Urban Disasters: A Multi-Level Location–Allocation Modeling Approach

In recent years, cities are threatened by various natural hazards. Planning emergency shelters in advance is an effective approach to reducing the damage caused by disasters and ensuring the safety of residents. Thus, providing the optimal layout of urban emergency shelters is an important stage of disaster management and an act of humanitarian logistics. In order to study the optimal layout of emergency shelters in small mountain cities, this paper constructs multi-level location models for different grades of emergency shelters so as to minimize the travel and construction costs and maximize the coverage rate. Specifically, the actual service of emergency shelters is determined using Geographic Information System (GIS) software and Weighted Voronoi Diagram (WVD) models under the limitation of site capacity, and the space layout is adjusted through combining the actual urban land with the construction position. In this paper, the Jianchuan county seat at Yunnan Province, China, was considered as a case study to illustrate the models of emergency shelters in which the feasibility of the presented models is verified. The proposed research methods and models have provided theoretical basis and a benchmark for the optimal layout of emergency shelters in other small mountain cities

Bioassay and enzymatic comparison of six entomopathogenic fungal isolates for virulence or toxicity against green peach aphids Myzus persicae

Myzus persicae is an economically important pest infecting more than 40 families of crops throughout the world. Six entomopathogenic fungal isolates, three each of Beauveria bassiana and Verticillium lecanii, were screened for pathogenicity test against the M. persicae to select high virulent isolate with the most suitable application and to determine the role of individual enzyme in its virulence. Two treatments that is, conidial shower (190±23 conidia/mm2) and filtrate (3 ml filtrate per treatment from six days liquid broth culture of 1.0x108 conidia ml-1) were conducted for virulence or toxicity test and a comparison was made between treatments and among fungal isolates against the target pest. The percent mortality rates of filtrate at each day, after inoculation was found higher as compared to percent mortality of conidial showering. V. lecanii 3 showed highest virulence or toxicity against the target pest treated either with conidial (80.70%) or filtrate (88.36%) application while B. bassiana 70 and B. bassiana 76 showed high toxicity (77.14 and 80.86%, respectively) in filtrate application at 6th day of incubation. The aphidicial activities of the fungal isolates were evaluated by correlating the enzymes (Chitinase, protease and lipase) activities with enzymes production. On the basis of enzymatic activities, lipase was assumed to participate more in the total virulence or pathogenicity as compared to protease and chitinase while protease was assumed to participate more than chitinase. The pathogenicity test reveals the selection, effective application of most virulent isolate and the role of individual enzyme to develop an alternative control agent against M. persicae.Keywords: Beauveria bassiana, filtrate, conidia, enzymes, Verticillium lecani

Factors influencing the generation of teachers’ emotions

Background and aimThe teaching profession plays an important role in shaping individuals’ lives, with teachers performing complex emotional labour. The management of emotions is an integral part of teachers’ professional work, and it is essential to clarify their emotional experiences and the generating of their emotions within a specific cultural context.MethodsBased on a phenomenological approach and the use of anecdotal texts, this study examined six common emotional states among teachers, including happiness, guilt, worry, fear, annoyance, and anger, along with the emotional experiences of two specialised categories of teachers, class supervisors, and pre-service teachers. The factors influencing teachers’ emotions and their generative mechanisms were analysed.Results and discussionThis investigation found that key influences on teachers’ emotions stem from factors within the teachers’ themselves, the contextual nature of their work, and sociocultural dynamics. Drawing on the analytical frameworks of emotional geography theory, ecological theory of human development, and the ecosystem model of teachers’ emotional interactions, the study constructs a model highlighting the generative mechanisms of teachers’ emotions, and in which three systems are reflected.ConclusionTeachers’ personal attributes are in the direct area of the model and directly govern the formation of their emotions, while their work context consists of a transitional area in emotion formation and the sociocultural system acts as the latent band influencing emotion development. The mechanism model helps us to understand and recognise teachers’ emotions and to explore their pedagogical implications

Design and characteristic analysis of a novel quasi-zero-stiffness isolator using magnets as negative stiffness

Considering that the static load of marine equipment and the packing space of vibration isolation is limited, a novel quasi-zero-stiffness-isolator (QZSI) using magnets as negative stiffness is designed. The conditions that the QZSI realizes quasi-zero-stiffness at the equilibrium position is obtained by analyzing the static characteristics. The dynamical model of system under a vertical harmonic force is established. The harmonic balance method is used to analyze the dynamic characteristics of QZSI, and the amplitude- frequency relationship expression and force transmissibility are deduced. The influence of different parameters on the performances is analyzed by means of controlling variables. It is shown that the novel QZSI can reduce the response peaks and extend the frequency band of isolator, and that the QZSI provided suitable system parameters can outperform the linear system

Causal clustering: design of cluster experiments under network interference

This paper studies the design of cluster experiments to estimate the global treatment effect in the presence of spillovers on a single network. We provide an econometric framework to choose the clustering that minimizes the worst-case mean-squared error of the estimated global treatment effect. We show that the optimal clustering can be approximated as the solution of a novel penalized min-cut optimization problem computed via off-the-shelf semi-definite programming algorithms. Our analysis also characterizes easy-to-check conditions to choose between a cluster or individual-level randomization. We illustrate the method's properties using unique network data from the universe of Facebook's users and existing network data from a field experiment