Passport: Enabling Accurate Country-Level Router Geolocation using Inaccurate Sources

When does Internet traffic cross international borders? This question has major geopolitical, legal and social implications and is surprisingly difficult to answer. A critical stumbling block is a dearth of tools that accurately map routers traversed by Internet traffic to the countries in which they are located. This paper presents Passport: a new approach for efficient, accurate country-level router geolocation and a system that implements it. Passport provides location predictions with limited active measurements, using machine learning to combine information from IP geolocation databases, router hostnames, whois records, and ping measurements. We show that Passport substantially outperforms existing techniques, and identify cases where paths traverse countries with implications for security, privacy, and performance

Passport: enabling accurate country-level router geolocation using inaccurate sources

When does Internet traffic cross international borders? This question has major geopolitical, legal and social implications and is surprisingly difficult to answer. A critical stumbling block is a dearth of tools that accurately map routers traversed by Internet traffic to the countries in which they are located. This paper presents Passport: a new approach for efficient, accurate country-level router geolocation and a system that implements it. Passport provides location predictions with limited active measurements, using machine learning to combine information from IP geolocation databases, router hostnames, whois records, and ping measurements. We show that Passport substantially outperforms existing techniques, and identify cases where paths traverse countries with implications for security, privacy, and performance.First author draf

Machine Vision Approach for Identification of Four Variant Pakistani Rice Using Multi-Features Dataset

Crops are the most important and beneficial food source in Pakistan. The demand for food has been an increase in Pakistan due to population growth. Pakistan produced 7,410 million tons of rice according to the financial year survey 2020 (FYS-2020). Pakistani rice has been cultivated in 3,304 hectares of the agricultural land zone, and it is also export around the world. Rice is also increased by 0.6% Gross Domestic Product (GDP) of Pakistan (FYS-2020). The old and manual process of rice classification is more expensive and time-consuming. In this study, we describe a machine vision approach for rice identification. We use four different varieties of rice for the experimental process such as Pakei_Kaynat, Kaynat_Kauchei, and Kauchei_Super_Banaspati and Tootaa_Kauchei (P1, P2, P3, and P4). The 100 images dataset have been used for practical work and total calculated of 400 (4 x 100) image of rice. The different process has been deploying on available datasets such as introduction, preprocessing methodology, and result discussion. A quality enhancement technique has been implementing for clarifying between rice color and shape sampling, and it is also converted color image in gray scale level. Every image has been employing six different non-overlapping regions of interest (ROI’s) and calculated a total of 2400 (6 x 400) ROI’s. Binary (B), Histogram (H) and Texture (T) features have been implemented and extract 43 features on each ROI’s and total calculated 103,200 (2400 x 43) machine learning (ML) features. Best First Search (BFS) Algorithm was used for feature optimization. Different ML classifiers are implementing for experimental process namely; Function Multi-Layer-Perception, Function SMO, Random Tree, J48 Tree, Meta Classifier via Regression and Meta Bagging. The Function Multi-Layer-Perception overall accuracy (OA) has describe better accuracy result is 99.8333%

Cholestyramine, a cost-effective yet efficacious anti-dote in digoxin toxicity

Digoxin is a cardiac glycoside obtained from digitalis lanata, is a positive inotropic and negative chronotropic agent. Digoxin works by blocking Na-K ATPase pump resulting in raised intracellular sodium which in turn raise intracellular calcium in the myocytes resulting in increase in inotropic effect [1, 2]. Digoxin causes several adverse effects in overdose leading to both bradyarrhythmias and tachyarrhythmias. The approved antidote, digoxin-specific antibody fragments (DIGIFAB), is costly yet effective option for managing digoxin toxicity [3] we describe the cases in which levels of digoxin fell to acceptable therapeutic levels with the use of Cholestyramine

Dual-chamber versus single chamber pacemakers, a systemic review and meta-analysis on sick sinus syndrome and atrioventricular block patients

Aims: The atrioventricular block (AVB) is a conduction system problem that results from the impairment in the transmission of an impulse from the atria to the ventricle, the disease has many etiologies. This article aimed to evaluate the efficacy and safety of dual and single-chamber pacemakers in patients with SSS and AVB. Methods: An electronic search of PubMed (Medline), EMBASE, and Google Scholar was performed from 2000 till August 15th, 2022. Retrieved articles were exported to Endnote Reference Library Software, where duplicate studies were removed from the list, and only articles meeting the eligibility criteria of this study were selected. RevMan 5.4 and STATA 16 software were used for the analysis. The modified Cochrane Collaboration's risk of bias and New-castle Ottawa scale were used for quality assessment of RCTs and observational studies respectively. Results: This study is composed of 8953 patients with sick-sinus syndrome and atrioventricular block. A total of thirteen outcomes are included in this meta-analysis, out of which atrial fibrillation significantly favored dual chamber [OR = 1.29; 95 % CI = 1.05–1.59; P = 0.01 I2 = 29 %] and overall complications [OR = 0.48; 95 % CI = 0.29–0.77; p = 0.03 I2 = 0 %] and pneumothorax [OR = 0.31; 95 % CI = 0.10–0.93; p = 0.04, I2 = 0 %] were satisfied by single-chamber pacing. Conclusion: This study concluded that neither single-chamber nor dual-chamber pacemakers are superior to each other, but they are unique in their own ways as the results of this study manifest remarkable reduction in atrial fibrillation rates and pneumothorax using dual-chamber and single-chamber pacemakers respectively

Frequency of Common CYP2C9 Polymorphisms and Their Impact on Warfarin Dose Requirement in Pakistani Population

Polymorphisms in cytochrome P450 (CYP) 2C9 (CYP2C9) gene result in interindividual variability in warfarin dose requirement. There is a need for characterization of genotype frequency distribution in different populations for construction of customized dosing algorithms to enhance the efficacy and reduce the toxicity of warfarin therapy. This study was carried out in Pakistani population to evaluate the contribution of common CYP2C9 polymorphisms to warfarin therapy. A total of 550 stable patients taking warfarin were enrolled after medical history, physical examination, and laboratory investigations. Single blood sample was collected after informed consent. Genomic DNA was extracted, and genotype analysis for CYP2C9*2 and CYP2C9*3 polymorphisms was done by polymerase chain reaction-restriction fragment length polymorphism assay. A number of samples were also analyzed by direct DNA sequencing for validation of the results. Data were analyzed using SPSS version 20. Genotype frequency distribution of CYP2C9*2 and CYP2C9*3 was found to be different from other populations. Of these 2 polymorphisms, CYP2C9*2 did not demonstrate significant effect on warfarin dose requirement, whereas CYP2C9*3 did show significant effect (P value = .012). It is concluded that there is a need to study genotype frequency distribution and their effect on warfarin dose variability among different populations due to diversity in outcome

Genome-Wide Identification, Genomic Organization, and Characterization of Potassium Transport-Related Genes in <i>Cajanus cajan</i> and Their Role in Abiotic Stress

Potassium is the most important and abundant inorganic cation in plants and it can comprise up to 10% of a plant’s dry weight. Plants possess complex systems of transporters and channels for the transport of K+ from soil to numerous parts of plants. Cajanus cajan is cultivated in different regions of the world as an economical source of carbohydrates, fiber, proteins, and fodder for animals. In the current study, 39 K+ transport genes were identified in C. cajan, including 25 K+ transporters (17 carrier-like K+ transporters (KUP/HAK/KTs), 2 high-affinity potassium transporters (HKTs), and 6 K+ efflux transporters (KEAs) and 14 K+ channels (9 shakers and 5 tandem-pore K+ channels (TPKs). Chromosomal mapping indicated that these genes were randomly distributed among 10 chromosomes. A comparative phylogenetic analysis including protein sequences from Glycine max, Arabidopsis thaliana, Oryza sativa, Medicago truncatula Cicer arietinum, and C. cajan suggested vital conservation of K+ transport genes. Gene structure analysis showed that the intron/exon organization of K+ transporter and channel genes is highly conserved in a family-specific manner. In the promoter region, many cis-regulatory elements were identified related to abiotic stress, suggesting their role in abiotic stress response. Abiotic stresses (salt, heat, and drought) adversely affect chlorophyll, carotenoids contents, and total soluble proteins. Furthermore, the activities of catalase, superoxide, and peroxidase were altered in C. cajan leaves under applied stresses. Expression analysis (RNA-seq data and quantitative real-time PCR) revealed that several K+ transport genes were expressed in abiotic stress-responsive manners. The present study provides an in-depth understanding of K+ transport system genes in C. cajan and serves as a basis for further characterization of these genes

Genome-Wide Identification, Genomic Organization, and Characterization of Potassium Transport-Related Genes in Cajanus cajan and Their Role in Abiotic Stress

Potassium is the most important and abundant inorganic cation in plants and it can comprise up to 10% of a plant’s dry weight. Plants possess complex systems of transporters and channels for the transport of K+ from soil to numerous parts of plants. Cajanus cajan is cultivated in different regions of the world as an economical source of carbohydrates, fiber, proteins, and fodder for animals. In the current study, 39 K+ transport genes were identified in C. cajan, including 25 K+ transporters (17 carrier-like K+ transporters (KUP/HAK/KTs), 2 high-affinity potassium transporters (HKTs), and 6 K+ efflux transporters (KEAs) and 14 K+ channels (9 shakers and 5 tandem-pore K+ channels (TPKs). Chromosomal mapping indicated that these genes were randomly distributed among 10 chromosomes. A comparative phylogenetic analysis including protein sequences from Glycine max, Arabidopsis thaliana, Oryza sativa, Medicago truncatula Cicer arietinum, and C. cajan suggested vital conservation of K+ transport genes. Gene structure analysis showed that the intron/exon organization of K+ transporter and channel genes is highly conserved in a family-specific manner. In the promoter region, many cis-regulatory elements were identified related to abiotic stress, suggesting their role in abiotic stress response. Abiotic stresses (salt, heat, and drought) adversely affect chlorophyll, carotenoids contents, and total soluble proteins. Furthermore, the activities of catalase, superoxide, and peroxidase were altered in C. cajan leaves under applied stresses. Expression analysis (RNA-seq data and quantitative real-time PCR) revealed that several K+ transport genes were expressed in abiotic stress-responsive manners. The present study provides an in-depth understanding of K+ transport system genes in C. cajan and serves as a basis for further characterization of these genes

A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data

The main objective of this study is to find out the importance of machine vision approach for the classification of five types of land cover data such as bare land, desert rangeland, green pasture, fertile cultivated land, and Sutlej river land. A novel spectra-statistical framework is designed to classify the subjective land cover data types accurately. Multispectral data of these land covers were acquired by using a handheld device named multispectral radiometer in the form of five spectral bands (blue, green, red, near infrared, and shortwave infrared) while texture data were acquired with a digital camera by the transformation of acquired images into 229 texture features for each image. The most discriminant 30 features of each image were obtained by integrating the three statistical features selection techniques such as Fisher, Probability of Error plus Average Correlation, and Mutual Information (F + PA + MI). Selected texture data clustering was verified by nonlinear discriminant analysis while linear discriminant analysis approach was applied for multispectral data. For classification, the texture and multispectral data were deployed to artificial neural network (ANN: n-class). By implementing a cross validation method (80-20), we received an accuracy of 91.332% for texture data and 96.40% for multispectral data, respectively