Intelligent and Improved Self-Adaptive Anomaly based Intrusion Detection System for Networks

With the advent of digital technology, computer networks have developed rapidly at an unprecedented pace contributing tremendously to social and economic development. They have become the backbone for all critical sectors and all the top Multi-National companies. Unfortunately, security threats for computer networks have increased dramatically over the last decade being much brazen and bolder. Intrusions or attacks on computers and networks are activities or attempts to jeopardize main system security objectives, which called as confidentiality, integrity and availability. They lead mostly in great financial losses, massive sensitive data leaks, thereby decreasing efficiency and the quality of productivity of an organization. There is a great need for an effective Network Intrusion Detection System (NIDS), which are security tools designed to interpret the intrusion attempts in incoming network traffic, thereby achieving a solid line of protection against inside and outside intruders. In this work, we propose to optimize a very popular soft computing tool prevalently used for intrusion detection namely Back Propagation Neural Network (BPNN) using a novel machine learning framework called “ISAGASAA”, based on Improved Self-Adaptive Genetic Algorithm (ISAGA) and Simulated Annealing Algorithm (SAA). ISAGA is our variant of standard Genetic Algorithm (GA), which is developed based on GA improved through an Adaptive Mutation Algorithm (AMA) and optimization strategies. The optimization strategies carried out are Parallel Processing (PP) and Fitness Value Hashing (FVH) that reduce execution time, convergence time and save processing power. While, SAA was incorporated to ISAGA in order to optimize its heuristic search. Experimental results based on Kyoto University benchmark dataset version 2015 demonstrate that our optimized NIDS based BPNN called “ANID BPNN-ISAGASAA” outperforms several state-of-art approaches in terms of detection rate and false positive rate. Moreover, improvement of GA through FVH and PP saves processing power and execution time. Thus, our model is very much convenient for network anomaly detection.

Emotional Intelligence and Psychological Adjustment among Doctors and Nurses in a Tertiary Care Hospital in Rawalpindi-Pakistan: A Cross Sectional Study

Objective: This study aimed to determine the relationship between EI and the quality of nursing care from the viewpoint of nurses and patients. Methods: This cross-sectional study was conducted at a public sector tertiary care hospital in Rawalpindi, Pakistan, over 6 months from November 2019 to April 2020. The convenience sampling technique was employed. The study groups were qualified practising doctors and nurses including nursing assistants and paramedics. Study groups were provided with a self-administered questionnaire that was filled out after getting consent from the study participants. Data analysis was done by entering it into SPSS version 22. The relationship between emotional intelligence and psychological adjustments among the two groups was assessed by applying an independent T-test. Results: The current study explored that doctors were emotionally intelligent and psychologically well-adjusted as compared to nurses. Females were more emotionally intelligent than males; however, males were better adjusted psychologically. Years of experience had no significant results between both groups, while there was a positive correlation between the department of practice and psychological well-being. Conclusions: It shows that harmonious work environments and friendly interpersonal relationships positively affect the well-being of HCWs and patients. What this indicates is a need to bring about changes within work environments to produce friendly interpersonal relationships and a positive impact on the well-being of HCWs and patients.

'Aariz: A Benchmark Dataset for Automatic Cephalometric Landmark Detection and CVM Stage Classification

The accurate identification and precise localization of cephalometric landmarks enable the classification and quantification of anatomical abnormalities. The traditional way of marking cephalometric landmarks on lateral cephalograms is a monotonous and time-consuming job. Endeavours to develop automated landmark detection systems have persistently been made, however, they are inadequate for orthodontic applications due to unavailability of a reliable dataset. We proposed a new state-of-the-art dataset to facilitate the development of robust AI solutions for quantitative morphometric analysis. The dataset includes 1000 lateral cephalometric radiographs (LCRs) obtained from 7 different radiographic imaging devices with varying resolutions, making it the most diverse and comprehensive cephalometric dataset to date. The clinical experts of our team meticulously annotated each radiograph with 29 cephalometric landmarks, including the most significant soft tissue landmarks ever marked in any publicly available dataset. Additionally, our experts also labelled the cervical vertebral maturation (CVM) stage of the patient in a radiograph, making this dataset the first standard resource for CVM classification. We believe that this dataset will be instrumental in the development of reliable automated landmark detection frameworks for use in orthodontics and beyond

How Functional and Emotional Ads Drive Smartphone Adoption: A Study of University Students of Pakistan

The purpose of this study is to examine the advertising strategies and know that how the functional and emotional ads drive smartphone adoption how they capture the attention of audience and fulfill their demands by ads. Advertising play important role in decision making. Firms use emotional ads to hit positive emotions about products it help us to know that how functional and emotional ads help in awaking the person's adoption feeling. The study investigates the influence of emotional and functional ads on indiviuals purchasing behavior that how many people change their purchasing towards smartphones. We use quantitative approach in this study. This research is survey based and we done collection of data through questionnaire. All the data accumulated through questionnaires are transferred into numerical form through SPSS (statistical package for the social science) and PLS (partial least square) it accepts the numerical variable. we collected the data of 509 respondents. The purpose of this study is to identify that what are the variables which effects so they have to be a simple and make a good and functional ad which attract the audience. Another one is also showing significant relationship between emotional advertising and expected enjoyment they have to make a benefits and facilities which their product give they have to see their competitors that what they are doing and comeup with something new to encourage the customers they have to connect people by showing emotional images. Moreover, another significant relationship is There is significant relationship between attitude towards using and adoption intention now my suggestion that to increase adoption intention they have to fulfill all the needs of their customers It is also recommended that research should also be done by using different variables It is also recommended that research should also be done in offices and take the employees perception

CEPHA29: Automatic Cephalometric Landmark Detection Challenge 2023

Quantitative cephalometric analysis is the most widely used clinical and research tool in modern orthodontics. Accurate localization of cephalometric landmarks enables the quantification and classification of anatomical abnormalities, however, the traditional manual way of marking these landmarks is a very tedious job. Endeavours have constantly been made to develop automated cephalometric landmark detection systems but they are inadequate for orthodontic applications. The fundamental reason for this is that the amount of publicly available datasets as well as the images provided for training in these datasets are insufficient for an AI model to perform well. To facilitate the development of robust AI solutions for morphometric analysis, we organise the CEPHA29 Automatic Cephalometric Landmark Detection Challenge in conjunction with IEEE International Symposium on Biomedical Imaging (ISBI 2023). In this context, we provide the largest known publicly available dataset, consisting of 1000 cephalometric X-ray images. We hope that our challenge will not only derive forward research and innovation in automatic cephalometric landmark identification but will also signal the beginning of a new era in the discipline

How Functional and Emotional Ads Drive Smartphone Adoption: A Study of University Students of Pakistan

The purpose of this study is to examine the advertising strategies and know that how the functional and emotional ads drive smartphone adoption how they capture the attention of audience and fulfill their demands by ads. Advertising play important role in decision making. Firms use emotional ads to hit positive emotions about products it help us to know that how functional and emotional ads help in awaking the person's adoption feeling. The study investigates the influence of emotional and functional ads on indiviuals purchasing behavior that how many people change their purchasing towards smartphones. We use quantitative approach in this study. This research is survey based and we done collection of data through questionnaire. All the data accumulated through questionnaires are transferred into numerical form through SPSS (statistical package for the social science) and PLS (partial least square) it accepts the numerical variable. we collected the data of 509 respondents. The purpose of this study is to identify that what are the variables which effects so they have to be a simple and make a good and functional ad which attract the audience. Another one is also showing significant relationship between emotional advertising and expected enjoyment they have to make a benefits and facilities which their product give they have to see their competitors that what they are doing and comeup with something new to encourage the customers they have to connect people by showing emotional images. Moreover, another significant relationship is There is significant relationship between attitude towards using and adoption intention now my suggestion that to increase adoption intention they have to fulfill all the needs of their customers It is also recommended that research should also be done by using different variables It is also recommended that research should also be done in offices and take the employees perception

Synthesis, Spectroscopic Characterization, DFT and Molecular Dynamics of Quinoline-based Peptoids

Peptoids mimic the functions of peptides which have a side chain appended to amidic nitrogen instead of α carbon. This structural change in their backbone gives them increased resistance from proteolysis, improved biostability, greater immunogenicity, and better bioavailability. Therefore, they are specifically designed for various biological activities, including antibacterial, antifungal, antioxidant, antifouling, and anticancer properties. The aim of the research is the one-pot synthesis of quinoline-based peptoids 5(a-b) via Ugi-4CR by the reaction of 1R-(-)-myrtenal 1, benzylamine 2, quinoline-based carboxylic acids 3(a-b), and cyclohexyl isocyanide 4. These peptoids were characterized by FT-IR, 1H NMR, 13C NMR, and HR ESI-MS. In computational studies, the spectral results of 5(a-b) were compared with the calculated spectral values computed at B3LYP/6-311G (d,p) level. TD-DFT method was used to predict electron excitation of 5(a-b) and the contribution of orbitals. The electronic transition of peptoids from charge distribution was computed using natural bond order (NBO) analysis. NPA and MEP analysis was calculated to predict charge distribution in 5(a-b). The FMOs analysis was executed to calculate the global reactivity descriptor to predict the reactivity and stability of peptoids. DFT analysis showed that 5b was slightly more reactive than 5a due to extended conjugation. The biological activities were also predicted using an in silico approach that involved molecular docking and molecular dynamic (MD) simulations. The antiulcer, antibacterial, and antifungal activities were predicted based on ligand–protein binding interactions, binding energy calculations, and dissociation constants. 5(a-b) were evaluated in-vitro for anticholinesterase activity, and they showed 71% inhibition. The umbrella sampling was performed to probe ligand–protein binding

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century