Use of LYMESIM 2.0 to assess the potential for single and integrated management methods to control blacklegged ticks (Ixodes scapularis; Acari: Ixodidae) and transmission of Lyme disease spirochetes

Annual Lyme disease cases continue to rise in the U.S. making it the most reported vector-borne illness in the country. The pathogen (Borrelia burgdorferi) and primary vector (Ixodes scapularis; blacklegged tick) dynamics of Lyme disease are complicated by the multitude of vertebrate hosts and varying environmental factors, making models an ideal tool for exploring disease dynamics in a time- and cost-effective way. In the current study, LYMESIM 2.0, a mechanistic model, was used to explore the effectiveness of three commonly used tick control methods: habitat-targeted acaricide (spraying), rodent-targeted acaricide (bait boxes), and white-tailed deer targeted acaricide (4-poster devices). Work was done to evaluate their effectiveness when used alone and in combination with one another. Optimized application strategies were also identified. Additionally, pilot work was done to incorporate prescribed fire into the model and compare its efficacy to the acaricide-based approaches. It was determined that any singular use or combination of methods that included spraying were most effective amongst acaricide-based treatments, suppressing the density of I. scapularisnymphs (DON) by \u3e80%. Furthermore, the best time to apply treatments was between January and mid-April, and mid-September to early December. Optimized treatment strategies identified by the model include application of treatment twice annually, every other year at a minimum effectiveness of 25%, which achieves 80% DON suppression and no increases in I. scapularis nymphs once treatments are complete. Interestingly, preliminary work to integrate prescribed fire in the model indicated that it achieved 93-100% efficacy in burn years and one-year post burn, making prescribed fire more effective than all acaricide-based treatments. Overall, this study illustrates the value in using models to identify the best method of blacklegged tick population control that is both time- and cost-effective. Future field research should be done to validate the findings of this model

A Tangible Structure To Comprehend Circuits Cipher text-Policy Based Hybrid Encryption With Verifiable Delegation (VD-CPABE)

Since strategy for general circuits empowers to accomplish the most grounded type of access control, a development for acknowledging circuit ciphertext-approach attribute based half and half encryption with obvious assignment has been considered in our work. In such a framework, joined with irrefutable calculation and encode then-mac mechanism the information privacy, the fine-grained get to control and the rightness of the assigned figuring results are very much ensured in the meantime. In addition, our plan accomplishes security against picked plaintext attacks under the k-multilinear Decisional Diffie-Hellman presumption. In addition, a broad simulation campaign affirms the practicality and effectiveness of the proposed arrangement

A Review on Protecting Location Privacy for Task Allocation in Mobile Cloud Computing

Cloud computing has extensively been observed as the next-generation calculating example which provides limitless cloud resources to finale users in anon request manner. The amusing cloud resources in cloud figuring can be subjugated to upsurge, augment, and improve abilities of mobile devices, important to the thought of mobile cloud computing(MCC).We recommend a basis that affords explanations to the beyond contests, where together position concealment and package equality are measured. In our outline, the CCP only has contact to sanitized location data of mobile servers rendering to differential privacy (DP).Mean while each mobile server is pledged to a cellular service provider(CSP) with which it previously has a faith association, the CSP can assimilate mobile server position and standing information, and delivers the data to the CCP in deafening form according to DP. To produce the deafening mobile server data, we acclimate the Private Spatial Decomposition (PSD) method and paradigm a new assembly called Reputation-based PSD (R-PSD)

A LDSS-CP-ABE Algorithm to Migrate Major Computation Overhead from Mobile Devices on to Proxy Server

Cloud has hugequantity of resources. In such a situation, to attain the acceptable presentation, it is indispensable to usage the possessionsdelivered by the cloud service provider (CSP) to stock and segment the data. At the moment, many cloud mobile claims have been extensivelycastoff. In these claims, data owners can upload their photos, videos, documents and other files to the cloud and segment these data with other data users they like to stake.  Explanations with stumpy computational overhead are in prodigious need for mobile cloud applications. In this paper, we recommend a lightweight data sharing scheme (LDSS) for mobile cloud computing.  The investigational results show that LDSS can confirm data concealment in mobile cloud and decrease the overhead on users’ side in mobile cloud

LISF: A Security Framework for Internet of Things (IoT) Integrated Distributed Applications

Distributed applications where Internet of Things (IoT) technology integrated are vulnerable to different kinds of attacks. Machine learning algorithms are widely used to detect intrusions in such applications. However, there is need for an effective unsupervised learning approach which can detect known and also unknown attacks. Towards this end, in this paper, we proposed a framework to protect security of IoT integrated architectures that are distributed in nature. Our framework is named Learning based IoT Security Framework (LISF). The framework is designed to have machine learning based security to IoT integrated use cases. Since IoT networks cause network traffic that is to be monitored and protected from external attacks, the proposed system uses deep learning technique for automatic detection of cyber-attacks. Particularly, the system exploits deep autoencoder which comprises of encoder and decoder for automatic detection of different kinds of intrusions. It is based on unsupervised learning which is crucial for distributed environments where network flows cannot have sophisticated training samples. We proposed an algorithm named Deep Autoencoder based Cyber Attack Detection (DAE-CAD). Experiments are made using IoT use case dataset known as UNSW-NB15. Our empirical results revealed that DAE-CAD outperforms existing methods with highest accuracy 91.36%

Initial Commitment to Pre-Exposure Prophylaxis and Circumcision for HIV Prevention amongst Indian Truck Drivers

Studies of HIV prevention interventions such as pre-exposure prophylaxis (PREP) and circumcision in India are limited. The present study sought to investigate Indian truck-drivers initial commitment to PREP and circumcision utilizing the AIDS Risk Reduction Model. Ninety truck-drivers completed an in-depth qualitative interview and provided a blood sample for HIV and HSV-2 testing. Truck-drivers exhibited low levels of initial commitment towards PREP and even lower for circumcision. However, potential leverage points for increasing commitment were realized in fear of infecting family rather than self, self-perceptions of risk, and for PREP focusing on cultural beliefs towards medication and physicians. Cost was a major barrier to both HIV prevention interventions. Despite these barriers, our findings suggest that the ARRM may be useful in identifying several leverage points that may be used by peers, health care providers and public health field workers to enhance initial commitment to novel HIV prevention interventions in India

Big Data: Theory, Challenges and Application’s Roadmap

Now a days the world has experienced the problems to store and manage a huge amount of data efficiently. Various sectors are facing those problems. To overcome those problems as well as the challenges, there is one solution to this is Big Data. Big data is a game changing thing. Big data is a game changing thing. Big data is going to use in wide areas to handle data produced by number of applications. It has received significant attention in recent years. To manage Big Data, it has some challenges. In this study, an attempt is made to review the basic theory and challenges of Big Data along with its usage in various sectors

Preparation and optimization of various parameters of enteric coated pellets using the Taguchi L9 orthogonal array design and their characterization

Duloxetine hydrochloride enteric coated pellets were formulated using fluidized bed. Three separate layers, the drug layer, the barrier layer, and the enteric layer, were coated onto the inert core pellets. The pellets were optimized with the acid resistance and drug release in simulated intestinal fluid as the process parameters, using the Taguchi L9 orthogonal array. Various other properties, such as surface morphology, bulk and tapped density, Hausner's ratio, hardness, friability, yield of pellets, moisture content, and particle size distribution, were also studied in the optimized pellets. The concentration of the enteric polymer played a vital role in acid resistance, while the type of enteric polymer affected the drug release in simulated intestinal fluid. In both cases, it was determined that binder polymer concentration was not affected much. The comparisons between the optimized pellets and a market formulation yielded f1 and f2 values within a range of 4–5 and 60–65, respectively. Three month stability studies, conducted at accelerated conditions, showed the optimized pellets to be stable. Taguchi plays an important role in optimizing parameters, and optimization of duloxetine hydrochloride can be achieved with minimal trials

Big Data: Theory, Challenges and Application’s Roadma

Now a days the world has experienced the problems to store and manage a huge amount of data efficiently. Various sectors are facing those problems. To overcome those problems as well as the challenges, there is one solution to this is Big Data. Big data is a game changing thing. Big data is a game changing thing. Big data is going to use in wide areas to handle data produced by number of applications. It has received significant attention in recent years. To manage Big Data, it has some challenges. In this study, an attempt is made to review the basic theory and challenges of Big Data along with its usage in various sector