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Bacillus thuringiensis var. kenyae (B.t.k.) is a microbial insecticide effective against lepidopteran pest species. Acute oral toxicity in rats and acute dermal toxicity, ocular irritation, skin irritation in rabbits were studied for the wettable powder formulation of B.t.k. In addition, toxicity of the wettable powder formulation was also studied in fresh water fish (Gambussia affinis). The results of these studies indicate that this wettable powder formulation of B.t.k. is nontoxic and nonirritant to rats, rabbits, and fish.

Summary In opportunistic networks (OppNets), which are characterized by intermittent end‐to‐end connections, the messages are routed in a store‐carry‐and‐forward fashion using the locally inferred knowledge about the behavior of nodes. As such, most OppNets routing protocols use social metrics that are dependent on the nodes' past information. But the participation of nodes in the message forwarding process is not guaranteed without incentivizing them because most nodes are reluctant in sharing their private resources for public uses. In this paper, some socially derived psychological attributes of a node are introduced to ensure their trustworthy participation in the message forwarding process, leading to the design of an altruism‐dependent trust‐based data forwarding mechanism for OppNets (called ATDTN). In this protocol, each node is associated with a dynamically changing altruism value representing its trust in the network, which is used to determine its status with regard to its participation in message forwarding. Through trace‐driven simulations using the ONE simulator, it is shown that ATDTN outperforms IronMan and SimBet protocols for routing in OppNets (respectively, 18% and 48% improvement), in terms of delivery ratio, end‐to‐end delay, overhead count, and average number of hops, under varying buffer size and time‐to‐live.

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Cloud Computing plays a momentous role for the speedy computation and provides resources to the user on-demand. The conventional single cloud has assorted number of confrontations and they are named as vendor lock-in, resource un-availability, latency, etc. To resolve these conflicts, multi cloud computing is utilized to provide heterogeneous services to the cloud users on demand. Task scheduling is a mechanism used to assign user requests to the cloud server. The proposed PIMTSA algorithm works well for the independent batch of tasks in the static environment. The algorithm is constituted to miniaturize the makespan of the multi cloud systems. It is designed for the batch mode offline multi cloud systems. The priority based approach works to cater the needs of the cloud user. High priority and low priority tasks are the two different priority levels defined by the user. High priority tasks are given more importance and are executed in the high speed VM with minimum completion time. But, the High priority tasks with maximum execution time are given more priority. After the execution of the high priority tasks, the low priority tasks with minimum execution time are allocated to VMs with minimum completion time in the clouds. This algorithm provides a high reliable and scalable computing service to the user with minimum time. In future this work can be extended for dynamic multi cloud environment.