Panic disorder (PD) is characterized by recurrent and uncontrollable panic attacks associated with behavioral changes and/or persistent anxiety due to the attacks. The development of behavioral models in animals is important for the understanding of the psychobiological and behavioral bases of PD. The present article reviews the main models used in the current literature. Biobehavioral assays used in rats and mice include fear conditioning (which presents moderate predictive, face, and construct validities); the elevated T-maze (which presents good predictive validity, but low face and construct validities); electrical stimulation of the periaqueductal gray (which presents good face validity, but moderate construct validity); predator exposure models (which present good predictive and moderate construct validity); and hypercapnia-induced responses (which present moderate construct validity). These three approaches seek coherence with theories on fear as a way to increase its translational potential; thus, while the elevated T-maze is supported by the Deakin/Graeff theory, the mouse defense test battery relies on the concept of defensive distance, and periaqueductal gray stimulation is based on the functional neuroanatomy of fear. Moreover, to higher or lower degree the three models are supported by an “etho-experimental” approach, with careful observation of animal behavior as a way of discriminating different defensive strategies that model different aspects of anxiety, fear, and panic. These assays can be used, in conjunction with independent variables that attempt to simulate the vulnerabilities and stressors which lead to panic attacks, to produce true models of PD. Finally, an alternative/complementary model is proposed that uses zebrafish alarm reaction to study this disorder.

New setting is introduced to study the alliances. Alliances are about a set of vertices which are applied into the setting of neutrosophic graphs. Neighborhood has the key role to define these notions. Also, neighborhood is defined based on the edges, strong edges and some edges which are coming from connectedness. These three types of edges get a framework as neighborhood and after that, too close vertices have key role to define offensive alliance, defensive alliance, t-offensive alliance, and t-defensive alliance based on three types of edges, common edges, strong edges and some edges which are coming from connectedness. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs containing complete, empty, path, cycle, bipartite, t-partite, star and wheel are investigated in the terms of set, minimal set, number, and neutrosophic number. In this study, there’s an open way to extend these results into the family of these classes of neutrosophic graphs. The family of neutrosophic graphs aren’t study but it seems that analogous results are determined. There’s a question. How can be related to each other, two sets partitioning the vertex set of a graph? The ideas of neighborhood and neighbors based on different edges illustrate open way to get results. A set is alliance when two sets partitioning vertex set have uniform structure. All members of set have different amount of neighbors in the set and out of set. It leads us to the notion of offensive and defensive. New ideas, offensive alliance, defensive alliance, t-offensive alliance, t-defensive alliance, strong offensive alliance, strong defensive alliance, strong t-offensive alliance, strong t-defensive alliance, connected offensive alliance, connected defensive alliance, connected t-offensive alliance, and connected t-defensive alliance are introduced. Two numbers concerning cardinality and neutrosophic cardinality of alliances are introduced. A set is alliance when its complement make a relation in the terms of neighborhood. Different edges make different neighborhoods. Three types of edges are applied to define three styles of neighborhoods. General edges, strong edges and connected edges are used where connected edges are the edges arising from connectedness amid two endpoints of the edges. These notions are applied into neutrosophic graphs as individuals and family of them. Independent set as an alliance is a special set which has no neighbor inside and it implies some drawbacks for this notions. Finding special sets which are well-known, is an open way to purse this study. Special set which its members have only one neighbor inside, characterize the connected components where the cardinality of its complement is the number of connected components. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

There are several well-studied examples of protective symbiosis between insect-host and symbiotic actinobacteria, producing antimicrobial metabolites to inhibit host pathogens. These mutualistic relationships are best described for some wasps and leaf-cutting ants while a huge variety of insect species still remains poorly explored. For the first time we isolated actinobacteria from harvester ant Messor structor, and evaluated the isolates’ potential as antimicrobial producers. All isolates could be divided into two morphotypes of single and mycelial cells. We found that the highest frequency of occurrence of mycelial morphotype was observed among soldiers, and the lowest among larvae in the studied laboratory colony. The representative of this morphotype was identified as Streptomyces globisporus subsp. globisporus 4-3 by polyphasic approach. It was established using E. coli JW5503 pDualRep2 system, that crude broths of mycelial isolates inhibited a protein synthesis in reporter strains, but it did not disrupt the in vitro synthesis of proteins in cell-free extracts. Active compound was extracted, purified and identified as albomycin δ2. Pronounced ability of albomycin to inhibit the growth of entomopathogens suggests that Streptomyces globisporus subsp. globisporus may be involved in defensive symbiosis with the Messor structor ant against infections.

Besides a diffuse research activity on drug discovery and biodiversity carried out in natural contexts, more recently investigations concerning endophytic fungi have started considering their occurrence in crops based on the major role that these microorganisms have been recognized to play in plant protection and growth promotion. Fruit growing is particularly involved in this new wave, by reason that the pluriannual crop cycle implies a likely higher impact of these symbiotic interactions. Aspects concerning occurrence and effects of endophytic fungi associated with citrus species are revised in the present paper.

This paper makes the case that in an Internet of Things (IoT) world where data processing has become pervasive, the assessment of whether or not the underlying (statistical) modeling assumptions are justified and appropriate should no longer be limited to the perspective of mathematical statistics alone. The paper argues that large parts of sound academic research in engineering lack practical merit in that, akin to a concept car, they are not market-ready, most commonly due to feasibility and liability issues. Through an analysis of both statistical and legal aspects it will be shown that the stoic pursuit of ‘optimality’ more often than not yields to risky and suboptimal outcomes when applied to actual physical world problems. To address this, the concept of ‘Defensive Signal Processing’ is introduced and future research directions are briefly outlined.