SECURITY CLASSIFICATION BASED QUIC TRAFFIC STEERING IN A SECURE INTERNET GATEWAY (SIG)

The Quick User Datagram Protocol (UDP) Internet Connection (QUIC) protocol is slated to become the next (third) major version of the Hypertext Transfer Protocol (HTTP) – i.e., HTTP/3. As applications transition to QUIC for web traffic, a Secure Internet Gateway (SIG) needs to effectively load balance, proxy, and classify QUIC traffic. Techniques are presented herein that make use of a custom Connection ID (CID) artifact to allow a load balancer to determine, with minimal processing, a target server, and potentially the application that the QUIC flow is serving, in support of steering traffic to the appropriate upstream services. Additionally, techniques are presented herein that leverage an exchange of data over an out-of-band channel in support of the enforcement of Quality of Service (QoS) requirements on an enterprise gateway

Modern Car Safety System using PIC Microcontroller

Intelligent car will provide very reliable and safe life to human. Safety is the most essential factor in automobile industry. One single move of driver can cause terrify accident. Percentage of the road accident is increasing day by day. Most   of the innocent people lost their life in the road accident so there have always been great needs of intelligent systems. Individual car can be equipped with feature of autonomy. There are many causes of the road accident like some technical error or human error but most of them are due to the human error. The human error can be avoided by using intelligent system in the vehicles can make the journey safer. Intelligent systems in the vehicles will help to secure the lives of people on the roads and to decrease the car accidents. The intelligent car system includes Automatic wiper movement control, Automatic cooling system, obstacle detection, as well as Vehicle tracking using GPS and GSM. Also this system includes heat to electricity conversion unit which helps to generate electricity from exhaust heat

SUPPORTING DYNAMIC NETWORK SLICING AND POLICY CREATION FOR END DEVICES IN PRIVATE 5G NETWORKS

Described herein are techniques for handling dynamic slicing requirements of User Equipment (UE) by performing remote activation (e.g., Over-the-Air Provisioning (OTAP)) of the logical profiles captured in the embedded Subscriber Identity Module (eSIM) which are created for the different slicing needs in private 5G networks. Also described are techniques for installing policies based on the Manufacturer Usage Description (MUD) Uniform Resource Locator (URL) in a private 5G network and efficiently retaining it during a 5G outage

Students’ attitude toward didactic lecture versus problem-based learning in pharmacology: a questionnaire based study

Background: The study was conducted to assess student attitude toward learning by didactic lectures versus problem-based learning (PBL).Methods: A questionnaire containing 11 statements was distributed to the students. Statements ranged from general information on lectures and PBL to benefits of lecture-based learning (LBL) over PBL and vice versa. The students were asked to score each individual statement. The median total scores and median with inter-quartile range of individual statements was calculated. A comparison between questions that support LBL or PBL was performed. Student t-test was employed to compare the mean scores of different groups.Results: Two hundred and seven students participated in this questionnaire study. The individual median total score was 42 when compared with possible total score of 55. There was a statistically significant (p<0.05) difference between the total score (mean±standard deviation) for the questions related to LBL (3.2391±0.05120) and those related to PBL (4.0640±0.05688).Conclusion: The score for PBL was significantly higher than LBL showing that students liked PBL more than LBL

Analysis and Classification of Breast Cancer Disease Via Different Datasets and Classifier Models

Nowadays, Tumour is one of the important reasons of human death worldwide, producing about 9.6 million people in 2018. BC (breast cancer) is the common reason for cancer deaths in females. BC is a type of cancer that can be treated when detected early. The main motive of this analysis is to detect cancer early in life using ML (machine learning) techniques. The features of the people included in the WDBC (Wisconsin diagnostic breast cancer) and Coimbra BC datasets were classified by SVOF-KNN, KNN, and Naïve Bayes techniques. The pre-processing data phase was applied to the datasets before classification. After the data pre-processing steps, three classification methods were applied to the data. Specificity and Sensitivity rates were used to calculate the success of the techniques. As an outcome of the BC diagnosis classification, the SVOF-KNN technique was found with a 91 percent specificity rate and 90 percent sensitivity rate. When the outcomes attained from feature extraction and selection are calculated. It is seen that feature extraction, selection, and data pre-processing techniques improve the specificity and sensitivity rate of the detection system

Exploring the therapeutic mechanisms of Cassia glauca in diabetes mellitus through network pharmacology, molecular docking and molecular dynamics

Cassia glauca is reported as anti-diabetic medicinal plant and is also used as an ethnomedicine. However, its mode of action as an anti-diabetic agent has not been clearly elucidated. Hence, the present study investigated the probable mechanism of action of C. glauca to manage diabetes mellitus via network pharmacology and molecular docking and simulations studies. The reported bioactives from C. glauca were retrieved from an open-source database, i.e. ChEBI, and their targets were predicted using SwissTargetPrediction. The proteins involved in the pathogenesis of diabetes were identified from the therapeutic target database. The targets involved in diabetes were enriched in STRING, and the pathways involved in diabetes were identified concerning the KEGG. Cytoscape was used to construct the network among bioactives, proteins, and probably regulated pathways, which were analyzed based on edge count. Similarly, molecular docking was performed using the Glide module of the Schrodinger suite against majorly targeted proteins with their respective ligands. Additionally, the drug-likeness score and ADMET profile of the individual bioactives were predicted using MolSoft and admetSAR2.0 respectively. The stability of these complexes were further studied via molecular dynamics simulations and binding energy calculations. Twenty-three bio-actives were retrieved from the ChEBI database in which cassiarin B was predicted to modulate the highest number of proteins involved in diabetes mellitus. Similarly, GO analysis identified the PI3K-Akt signaling pathway to be primarily regulated by modulating the highest number of gene. Likewise, aldose reductase (AKR1B1) was majorly targeted via the bioactives of C. glauca. Similarly, docking study revealed methyl-3,5-di-O-caffeoylquinate (docking score −9.209) to possess the highest binding affinity with AKR1B1. Additionally, drug-likeness prediction identified cassiaoccidentalin B to possess the highest drug-likeness score, i.e. 0.84. The molecular dynamics simulations and the MMGBSA indicate high stability and greater binding energy for the methyl-3,5-di-O-caffeoylquinate (ΔGbind = −40.33 ± 6.69 kcal mol−1) with AKR1B1, thus complementing results from other experiments. The study identified cassiarin B, cassiaoccidentalin B, and cinnamtannin A2 as lead hits for the anti-diabetic activity of C. glauca. Further, the PI3K-Akt and AKR1B1 were traced as majorly modulated pathway and target, respectively

Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems

Funding: This research was funded by the Generation Challenge Program (GCP) project G3008.06, “Targeting Drought-Avoidance Root Traits to Enhance Rice Productivity under Water-Limited Environments". The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

The Persistency of the India-Pakistan Conflict: Chances and Obstacles of the Bilateral Composite Dialogue

This article investigates the underlying causes for the persistency of the India–Pakistan conflict and, on this basis, the chances and obstacles of the bilateral composite dialogue initiated in 2004. In particular, it wants to provide a theoretically grounded account of the factors that facilitated and constrained the bilateral composite dialogue process. Drawing on the regional security complex theory, this article examines the rivalry between the two South Asian nuclear powers on four levels of analysis: the domestic, the regional, the interregional and the global level. The analysis shows that there have been some substantial changes on all four levels in the recent decade or so and that these changes have provided more beneficial conditions for a peace process. These changes include, inter alia, India’s new regional policy, the consequences of the 9/11 terrorist attacks for the region and India’s growing power capacities. However, major obstacles to the India–Pakistan dialogue and a permanent conflict resolution continue to persist: the dominant role of the military in Pakistan, conflicting national identities and the still partially contested nature of statehood in India and Pakistan, which is in the case of Pakistan linked to the growing power of Islamic fundamentalists

First narrow-band search for continuous gravitational waves from known pulsars in advanced detector data

Spinning neutron stars asymmetric with respect to their rotation axis are potential sources of continuous gravitational waves for ground-based interferometric detectors. In the case of known pulsars a fully coherent search, based on matched filtering, which uses the position and rotational parameters obtained from electromagnetic observations, can be carried out. Matched filtering maximizes the signalto- noise (SNR) ratio, but a large sensitivity loss is expected in case of even a very small mismatch between the assumed and the true signal parameters. For this reason, narrow-band analysis methods have been developed, allowing a fully coherent search for gravitational waves from known pulsars over a fraction of a hertz and several spin-down values. In this paper we describe a narrow-band search of 11 pulsars using data from Advanced LIGO’s first observing run. Although we have found several initial outliers, further studies show no significant evidence for the presence of a gravitational wave signal. Finally, we have placed upper limits on the signal strain amplitude lower than the spin-down limit for 5 of the 11 targets over the bands searched; in the case of J1813-1749 the spin-down limit has been beaten for the first time. For an additional 3 targets, the median upper limit across the search bands is below the spin-down limit. This is the most sensitive narrow-band search for continuous gravitational waves carried out so far