Secure Cloud Communication for Effective Cost Management System through MSBE

In Cloud Computing Architecture, Brokers are responsible to provide services to the end users. An Effective Cost Management System (ECMS) which works over Secure Cloud Communication Paradigm (SCCP) helps in finding a communication link with overall minimum cost of links. We propose an improved Broker Cloud Communication Paradigm (BCCP) with integration of security issues. Two algorithms are included, first is Secure Optimized Route Cost Finder (S-ORCF) to find optimum route between broker and cloud on the behalf of cost factor and second is Secure Optimized Route Management (S-ORM) to maintain optimum route. These algorithms proposed with cryptographic integrity of the secure route discovery process in efficient routing approaches between broker and cloud. There is lack in Dynamic Source Routing Approach to verify whether any intermediate node has been deleted, inserted or modified with no valid authentication. We use symmetric cryptographic primitives, which is made possible due to multisource broadcast encryption scheme. This paper outlines the use of secure route discovery protocol (SRDP)that employs such a security paradigm in cloud computing.Comment: 12 pages, 3 figures, International Journal on Cloud Computing: Services and Architecture(IJCCSA),Vol.2, No.3, June 201

Prediction of Crop Yield Using LS-SVM

Agriculture sector is the backbone of Indian economy. Yield prediction of crop is very important problem in agriculture field. Predicting the yield is very popular among farmer nowadays, which especially contributes to the correct choice of crop for growing. Earlier, crop production was implemented by considering the farmer's experience on an appropriate field as well as crop. Information technology has an important area to predict the crop production because it includes the latest advancement. In this paper, our aim is to develop the system to achieve high accuracy and resolve the problem of yielding in agriculture. We use the LS-SVM and deep neural network learning technique to predict the yield of crop based physical and chemical feature of plant and soil. This system helps the farmer to take the right decision about sowing particular crop in available land

Prediction of Plant Disease from Weather Forecasting using Data Mining

Plant disease determination is an art and also science. Plant disease is essential problem that lower the quantity and also reduced the quality of agricultural production. Recent, pesticide is applied on plant without learned what the essential requirement of plant. Disease is the main the cause to death the plant and also influences the human health. Data mining is a comparatively novel research in agricultural. In this paper, our aim to develop the system to evaluate high accuracy and also detects the disease of the orange plant. The proposed system use segmentation techniques such as k-means clustering and deep neural network learning to predict the disease based on weather feature of the orange plant. This system helps the farmer to understand the disease of orange plant and also increase the yield of orange plant

Control of fibroblast-mediated collagen contaction: Importance and mechanism of cell attachment in the contraction process

The repair of damaged adult tissue is achieved by the production of scar tissue. Irregular healing can lead to hypertrophic scarring, where the healed scar continues to contract after wound closure, producing 'scar contracture'. Current understanding of mechanisms leading to both wound contraction and scar contracture are limited. This study aimed to investigate and modify early phase cell-matrix attachment and contraction mechanisms, using a 3-dimensional in vitro model of wound contraction, the Culture Force Monitor (CFM). Three areas of research were pursued: Firstly, cell-matrix interaction and contraction was manipulated using neutralising antibodies, synthetic peptides and specific protein depleted sera. As well as the CFM, effect of such modifications were monitored by observing changes in cytoskeletal proteins, using confocal microscopy. Secondly, effect of the potent cytokine, TGFβ1, on early phase contraction was tested. TGFβ1 related changes in cellular morphology and integrin expression were also monitored. The final part of the study used Photodynamic Therapy (PDT) to manipulate cell-matrix attachment and subsequent contraction. Drug dose, wavelength and time of irradiation was optimised using a cell viability assay, to find conditions that were minimally toxic to fibroblasts. Contraction was then monitored using untethered (free floating) and tethered (CFM) gels. Results suggest a sequential role for fibronectin, vitronectin, and collagen mediated attachment during fibroblast-mediated contraction. Studies have shown that TGFβ1 may promote early granulation tissue contraction, by directly upregulating specific integrin expression. Data shows that PDT successfully reduced cell-matrix attachment and contraction, and thus, may be of value in an in vivo situation. Mechanisms through which contraction may be controlled are discussed. In order to potentially regulate the process of collagen contraction in tissue repair or in tissue engineering, and to formulate potential therapeutic regimes to control scar contracture, it would seem that clinical intervention is required at a very early stage

The Proteolytic Stability and Cytotoxicity Studies of l‐Aspartic Acid and l‐Diaminopropionic Acid derived β‐Peptides and a Mixed α/β‐Peptide

The use of peptides as drugs in pharmaceutical applications is hindered by their susceptibility to proteolysis and therefore low bioavailability. β‐Peptides that contain an additional methylene group in the backbone, are gaining recognition from a pharmaceutical stand point as they are considerably more resilient to proteolysis and metabolism. Recently, we reported two new classes of β‐peptides, β3‐ and β2‐peptides derived from l‐aspartic acid and l‐diaminopropionic acid, respectively. Here, we report the proteolytic stability of these β‐peptidic compounds and a mixed α /β‐peptide against three enzymes (pronase, trypsin and elastase), as well as, human serum. The stability of these peptides was compared to an α‐peptide. Peptides containing β‐linkages were resistant to all conditions. The mixed α /β‐peptide, however, exhibited proteolysis in the presence of trypsin and pronase but not elastase. The rate of degradation of the mixed α /β‐peptide was slower than that would be expected for an α‐peptide. In addition, these β‐peptides were not toxic to HeLa and COS‐1 cell lines as observed by MTT cytotoxicity assay. These results expand the scope of mixed α /β‐peptides containing β‐amino acids or small β‐peptide fragments as therapeutic peptides

Peptide–Drug Conjugates with Different Linkers for Cancer Therapy

Drug conjugates are chemotherapeutic or cytotoxic agents covalently linked to targeting ligands such as an antibody or a peptide via a linker. While antibody–drug conjugates (ADCs) are now clinically established for cancer therapy, peptide–drug conjugates (PDCs) are gaining recognition as a new modality for targeted drug delivery with improved efficacy and reduced side effects for cancer treatment. The linker in a drug conjugate plays a key role in the circulation time of the conjugate and release of the drug for full activity at the target site. Herein, we highlight the main linker chemistries utilized in the design of PDCs and discuss representative examples of PDCs with different linker chemistries with the related outcome in cell and animal studies

A Systematic Evaluation of Literature on Internet of Things (IoT) and Smart Technologies with Multiple Dimensions

The advent of state of the art advanced technologies is necessitated by the ever-increasing onset and infiltration of our lives by the smart devices and gadgets for providing an array of services. The conventional methods and techniques already becoming obsolete and the consistent and persistent demand for provision of high end services with a greater degree of accuracy by various sectors, paves the way for collaboration of smart technologies such as Internet of things, Internet of everything, Internet of Vehicles etc. with the smart gadgets and devices. This systematic review tries to explore the avenues for research and multiple streaming of segments by the analysis of allied smart systems comprising of smart devices and multi-dimensional IoT, IoE, IoV etc.&nbsp

Engineering and Characterization of Human β-defensin-3 and Its Analogues and Microcin J25 Peptides Against \u3cem\u3eMannheimia haemolytica\u3c/em\u3e and Bovine Neutrophils

Mannheimia haemolytica-induced bovine respiratory disease causes loss of millions of dollars to Canadian cattle industry. Current antimicrobials are proving to be ineffective and leave residues in meat. Antimicrobial peptides (AMPs) may be effective against M. haemolytica while minimizing the risk of drug residues. Cationic AMPs can kill bacteria through interactions with the anionic bacterial membrane. Human β-Defensin 3 (HBD3) and microcin J25 (MccJ25) are AMPs with potent activity against many Gram-negative bacteria. We tested the microbicidal activity of wild-type HBD3, three HBD3 peptide analogues (28 amino acid, 20AA, and 10AA) derived from the sequence of natural HBD3, and MccJ25 in vitro against M. haemolytica. Three C-terminal analogues of HBD3 with all cysteines replaced with valines were manually synthesized using solid phase peptide synthesis. Since AMPs can act as chemoattractant we tested the chemotactic effect of HBD3, 28AA, 20AA, and 10AA peptides on bovine neutrophils in Boyden chamber. Minimum bactericidal concentration (MBC) assay showed that M. haemolytica was intermediately sensitive to HBD3, 28AA and 20AA analogues with an MBC of 50 µg/mL. The 10AA analogue had MBC 6.3 µg/mL which is likely a result of lower final inoculum size. MccJ25 didn’t have significant bactericidal effect below an MBC \u3c 100 µg/mL. Bovine neutrophils showed chemotaxis towards HBD3 and 20AA peptides (P \u3c 0.05) but not towards 28AA analogue. Co-incubation of neutrophils with any of the peptides did not affect their chemotaxis towards N-formyl-l-methionyl-l-leucyl-phenylalanine (fMLP). The data show that these peptides are effective against M. haemolytica and are chemotactic for neutrophils in vitro