Integrating the EGC, EF, and ECS Trio Approaches to Ensure Security and Load Balancing in the Cloud

According to data protection studies, "Distributed Denial-of-Service (DDoS)" threats have cost governments and businesses throughout the globe a large number of financial resources. Despite this, the existing practices fall short of the standards set by "Cloud Computing (CC)" monitoring technology. They ignore the "Intrusion Detection Systems (IDS)" techniques, which take advantage of the CC's multiple tenants and elasticity qualities, and also the hardware limitations. Attackers are finding increasing ways to effectively exploit them because of their rising complexity. DDoS assaults of this scale have never been observed online before 2018. As online services get more popular, so does the amount of DDoS assaults and malevolent hackers leading to terrible. Numerous IDS for DDoS are already in place to address this problem. One of the most challenging aspects of virtualization is establishing a "Trust Model (TM)" between the many "Virtual Machines (VMs)". The lack of a standard formulation for generating a TM would be the primary reason. As a consequence, the integrity of every VM might not have been recognized by an independent trust, which might lead to a decrease in trust value. In this research for TM creation, "Enhanced Graph Based Clustering (EGC)" is proposed, while "Enhanced Fuzzy (EF)" is used for detecting attacks, and the "Enhanced Cuckoo Search (ECS)" method is used to find the ideal "Load Balancing (LB)" distribution. By creating a new TM, the proposed (EGC-EF-ECS) system strengthens trust value. To expand the CC model's stability, it optimizes attacker recognition percentage and makes better use of resources by restricting each VM's processing, bandwidth, and storage requirements. The proposed EGC-EF-ECS outperformed the previously used BPA-SAB, and DCRI-RI approaches in terms of the "Intrusion-Detection-Rate (IDR)", "Load-Balancing-Efficiency (LBE)", and "Data-Accessing-Time (DAT)" evaluation metrics

PER PREFIX FLEXIBLE METRIC FOR INTENT BASED ROUTING AND TRAFFIC ENGINEERING USING EIGRP

Routing protocols are typically designed to use a single-cost formula for all of a protocol\u27s routes. In some instances, a network administrator can adjust the cost formula of the Enhanced Interior Gateway Routing Protocol (EIGRP), but the protocol applies the formula uniformly to all prefixes, which can cause all applications to suffer from lower performance. In order to address such issues, techniques are presented herein through which a flexible metric can be applied that is isolated to prefixes. for example, the techniques presented herein provide for the reduced use of Virtual Private Network (VPN) routing & forwarding (VRF) instances on routers and ease network configuration as configurations provided in accordance with the techniques presented herein are only needed at prefix originators

INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & MANAGEMENT CHEMICAL SYNTHESIS OF BONE-LIKE HYDROXYAPATITE FROM CUTTLE FISH BONES AND ITS CHARACTERIZATION

ABSTRACT Hydroxyapatite (Hap) was synthesized from cuttle fish bone by using a wet chemical method at room temperature. In this method powdered cuttle fish bones were reacted with phosphoric acid (H3PO4). The synthesized Hap was characterized by Atomic Force Microscopy (AFM), Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM). Fine and Crystallized Chap was obtained. The particular cuttlefish bones are biocompatible and used in implants for osseointegration

FORMULATION AND EVALUATION OF LEVOFLOXACIN-CHITOSAN / β- CYCLODEXTRIN NANOPARTICLES BY IONIC GELATION

Background: Levofloxacin is a broad spectrum anti-infective agent, which is rapidly and completely absorbed after oral administration. The half life of Levofloxacin is 6-8 h after conventional dosing. The objective of the present work was to develop Levofloxacin nanoparticles to retain the dosage form in the absorption site more than the half life of the drug, enhance the bioavailability of drugs, reduce dose frequency, toxicity and patient compliance. Methods: The compositions of different formulations of Levofloxacin nanoparticles by the ionic gelation method using biodegradable polymer chitosan and tripolyphosphate as cross linking agent. Result and Discussion: The particle size lies of the prepared nanoparticles between 199 and 369 nm and the drug content found between 51.13± 0.28 and 71.12 ± 0.14 %. The particle size of nanoparticles increased with increasing concentration of polymer matrix density and this may be due to the increased viscosity of the inner phase and decreased with increasing concentration of β-cyclodextrin. Scanning electron microscopy indicated that the prepared nanoparticles were discrete, uniform and spherical with a smooth surface. The in vitro release showed that the drug release from the prepared nanoparticles was characterized by an initial fast release and followed by a delayed release phase. During and at the end of the accelerated stability study, the tested formulation showed almost same drug content, in vitro drug release and no colour changes were observed from that observed at the opening of the study. Conclusion: Among all the formulations (GIA, GIB, GIC, GID, GIE and GIF), the formulations G1C, G1E and G1F followed the drug release in a controlled manner. The in vitro release profile showed that this is a potential drug delivery for Levofloxacin and has to confirm in the in vivo settings as a separate investigation in future. Key words: Controlled drug delivery, In vitro drug release, Nanoparticle, Particle size, Stability studies, Surface morpholog

Author Correction:Genetic effects on the timing of parturition and links to fetal birth weight (Nature Genetics, (2023), 55, 4, (559-567), 10.1038/s41588-023-01343-9)

Correction to: Nature Genetics. Published online 3 April 2023. In the version of this article originally published, the surname of author Stefan Johansson was misspelled as Johanson. In the abstract and “Genome-wide association analyses” section of the Results, the number of loci associated with preterm birth was shown as six instead of seven. In addition, there was a production error in the Figure 1a y-axis units shown below 0, where “10” and “20” were shown as negative numbers. The errors have been corrected in the HTML and PDF versions of the article.</p

Genetic effects on the timing of parturition and links to fetal birth weight

The timing of parturition is crucial for neonatal survival and infant health. Yet, its genetic basis remains largely unresolved. We present a maternal genome-wide meta-analysis of gestational duration (n = 195,555), identifying 22 associated loci (24 independent variants) and an enrichment in genes differentially expressed during labor. A meta-analysis of preterm delivery (18,797 cases, 260,246 controls) revealed six associated loci and large genetic similarities with gestational duration. Analysis of the parental transmitted and nontransmitted alleles (n = 136,833) shows that 15 of the gestational duration genetic variants act through the maternal genome, whereas 7 act both through the maternal and fetal genomes and 2 act only via the fetal genome. Finally, the maternal effects on gestational duration show signs of antagonistic pleiotropy with the fetal effects on birth weight: maternal alleles that increase gestational duration have negative fetal effects on birth weight. The present study provides insights into the genetic effects on the timing of parturition and the complex maternal–fetal relationship between gestational duration and birth weight.</p

Quantifying Preterm Birth Risk And Heterogeneity Using Evolutionary History And Electronic Health Records

Preterm birth, defined as a birth before 37 weeks of gestation, is prevalent and leads to significant morbidity and mortality worldwide. The pathogenesis of preterm birth, and more generally the mechanisms of birth timing, remain poorly understood. Twin based studies estimate that up to 30-40% of the variation in birth timing can be explained by genetic variation. Although a few genomic regions have been identified to date, there are likely many more that influence preterm birth risk. In addition, preterm birth is a complex phenotype with multiple etiologies and heterogenous clinical presentations. In this dissertation, I refine the phenotypic heterogeneity using machine learning approaches and evaluate the genomic basis for preterm birth using an evolutionary perspective. First, I identify sub-phenotype of preterm birth with distinct longitudinal trajectories and comorbid signatures. Some of these sub-phenotypes associate with genetic risk scores for known risk factors of preterm birth. Second, using dense phenotyping data from electronic health records, I develop a machine learning model to predict preterm birth and obtain interpretable representation of the learned rules. The model is able to discriminate between preterm and term births and serves as a proof-of-concept for predictive machine learning models for adverse pregnancy outcomes. Third, I test genomic regions associated with preterm birth for evolutionary signatures and identify diverse patterns of selection across many regions. The independent evolutionary signatures enable prioritization of candidate regions for further experimental validation. This dissertation refines the phenotypic definition and illustrates the role of diverse evolutionary forces on genomic regions associated with preterm birth. Disentangling the phenotypic heterogeneity and understanding the genetic basis of preterm birth will aid to isolate specific pathways of birth timing and tailor clinical management to each patient

Effects of Low Level Laser Therapy Vs Ultrasound Therapy in the Management of Active Trapezius Trigger Points.

Effects of Low Level Laser Therapy Vs Ultrasound Therapy in the Management of Active Trapezius Trigger Points.</p