Context Based Classification of Reviews Using Association Rule Mining, Fuzzy Logics and Ontology

The Internet has facilitated the growth of recommendation system owing to the ease of sharing customer experiences online. It is a challenging task to summarize and streamline the online textual reviews. In this paper, we propose a new framework called Fuzzy based contextual recommendation system. For classification of customer reviews we extract the information from the reviews based on the context given by users. We use text mining techniques to tag the review and extract context. Then we find out the relationship between the contexts from the ontological database. We incorporate fuzzy based semantic analyzer to find the relationship between the review and the context when they are not found therein. The sentence based classification predicts the relevant reviews, whereas the fuzzy based context method predicts the relevant instances among the relevant reviews. Textual analysis is carried out with the combination of association rules and ontology mining. The relationship between review and their context is compared using the semantic analyzer which is based on the fuzzy rules

Accomplishes Foreign Direct Investment Affect Private Investment In Arab Nations In The Period Between (2000 – 2021)?

The article desires to examine the impact of FDI on PI with a sampling of 10 selected Arab countries from 2000- 2021. For further analysis, the study used OLS. Test method with fixed and random effects model, and after making Haussmanns test and accepting the Alternative Hypothesis (H1), the study used the fixed effects model. The results confirm the presence of crowding in reality, which indicates that FDI encourages PI in only one model. Aside from this, the delayed PI has a positive and essential impact on herself in the coming period reflecting stagnation in the direction of PI in the beneficiary nations. In the complete panel sample, thither is a significant negative effect between inflation and PI, there are some macro elements that as per capita GDP, electro, domestic credit, and labor force, which were positive and not statistically significant, while trade openness was negative and not statistically significant

Redescription of Arcotheres placunae and three new records, A. aff. alcocki, A. casta and Pinnotheres quadratus from Pakistan with a note on previously recorded Pakistani Pinnotherid crabs

Arcotheres placunae a commen commensal of bivalve Placuna placenta is redescribed;two species of the same genus :A. aff. alcocki and A. casta and one species of another genus Pinnotheres P.quadratus are reported as new records from Pakistan. Previously recorded Pakistani pinnotherid crabs are reviewed

Underweight, overweight and obesity among reproductive Bangladeshi women : a nationwide survey

The double burden of malnutrition is becoming more prevalent among Bangladeshi women. Underweight, overweight, and obesity were examined among women aged 15–49 years using the 2017–2018 Bangladesh Demographic and Health Survey (BDHS). A dataset of 20,127 women aged 15–49 years with complete Body Mass Index (BMI) measurements were extracted and categorized as underweight, normal weight, overweight, and obesity. A multiple logistic regression that adjusts for clustering and sampling weights was used to examine underweight, overweight, and obesity among reproductive age Bangladeshi women. Our analyses revealed that the odds of being overweight and obese were higher among women who completed primary and secondary or more levels of education, rich households, breastfeeding women, and women exposed to media (newspapers and television (TV). Women from the poorest households were significantly more likely to be underweight (AOR = 3.86, 95%CI: 2.94–5.07) than women from richer households. The likelihood of being underweight was higher among women with no schooling, adolescent women, and women not using contraceptives. Conclusions: Overweight and obesity was higher among educated and affluent women while underweight was higher among women from low socioeconomic status, indicating that tailored messages to combat overweight and obesity should target educated and affluent Bangladeshi women while improving nutrition among women from low socioeconomic status

Meta-analysis of host response networks identifies a common core in tuberculosis

Tuberculosis remains a major global health challenge worldwide, causing more than a million deaths annually. To determine newer methods for detecting and combating the disease, it is necessary to characterise global host responses to infection. Several high throughput omics studies have provided a rich resource including a list of several genes differentially regulated in tuberculosis. An integrated analysis of these studies is necessary to identify a unified response to the infection. Such data integration is met with several challenges owing to platform dependency, patient heterogeneity, and variability in the extent of infection, resulting in little overlap among different datasets. Network-based approaches offer newer alternatives to integrate and compare diverse data. In this study, we describe a meta-analysis of host’s whole blood transcriptomic profiles that were integrated into a genome-scale protein–protein interaction network to generate response networks in active tuberculosis, and monitor their behaviour over treatment. We report the emergence of a highly active common core in disease, showing partial reversals upon treatment. The core comprises 380 genes in which STAT1, phospholipid scramblase 1 (PLSCR1), C1QB, OAS1, GBP2 and PSMB9 are prominent hubs. This network captures the interplay between several biological processes including pro-inflammatory responses, apoptosis, complement signalling, cytoskeletal rearrangement, and enhanced cytokine and chemokine signalling. The common core is specific to tuberculosis, and was validated on an independent dataset from an Indian cohort. A network-based approach thus enables the identification of common regulators that characterise the molecular response to infection, providing a platform-independent foundation to leverage maximum insights from available clinical data

Global Tuberculosis Report 2020 - Reflections on the Global TB burden, treatment and prevention efforts

The October 2020 Global TB report reviews TB control strategies and United Nations (UN) targets set in the political declaration at the September 2018 UN General Assembly high-level meeting on TB held in New York. Progress in TB care and prevention has been very slow. In 2019, TB remained the most common cause of death from a single infectious pathogen. Globally, an estimated 10.0 million people developed TB disease in 2019, and there were an estimated 1.2 million TB deaths among HIV-negative people and an additional 208, 000 deaths among people living with HIV. Adults accounted for 88% and children for 12% of people with TB. The WHO regions of South-East Asia (44%), Africa (25%), and the Western Pacific (18%) had the most people with TB. Eight countries accounted for two thirds of the global total: India (26%), Indonesia (8.5%), China (8.4%), the Philippines (6.0%), Pakistan (5.7%), Nigeria (4.4%), Bangladesh (3.6%) and South Africa (3.6%). Only 30% of the 3.5 million five-year target for children treated for TB was met. Major advances have been development of new all oral regimens for MDRTB and new regimens for preventive therapy. In 2020, the COVID-19 pandemic dislodged TB from the top infectious disease cause of mortality globally. Notably, global TB control efforts were not on track even before the advent of the COVID-19 pandemic. Many challenges remain to improve sub-optimal TB treatment and prevention services. Tuberculosis screening and diagnostic test services need to be ramped up. The major drivers of TB remain undernutrition, poverty, diabetes, tobacco smoking, and household air pollution and these need be addressed to achieve the WHO 2035 TB care and prevention targets. National programs need to include interventions for post-tuberculosis holistic wellbeing. From first detection of COVID-19 global coordination and political will with huge financial investments have led to the development of effective vaccines against SARS-CoV2 infection. The world now needs to similarly focus on development of new vaccines for TB utilizing new technological methods

Interactive Effect of Learning Rate and Batch Size to Implement Transfer Learning for Brain Tumor Classification

For classifying brain tumors with small datasets, the knowledge-based transfer learning (KBTL) approach has performed very well in attaining an optimized classification model. However, its successful implementation is typically affected by different hyperparameters, specifically the learning rate (LR), batch size (BS), and their joint influence. In general, most of the existing research could not achieve the desired performance because the work addressed only one hyperparameter tuning. This study adopted a Cartesian product matrix-based approach, to interpret the effect of both hyperparameters and their interaction on the performance of models. To evaluate their impact, 56 two-tuple hyperparameters from the Cartesian product matrix were used as inputs to perform an extensive exercise, comprising 504 simulations for three cutting-edge architecture-based pre-trained Deep Learning (DL) models, ResNet18, ResNet50, and ResNet101. Additionally, the impact was also assessed by using three well-known optimizers (solvers): SGDM, Adam, and RMSProp. The performance assessment showed that the framework is an efficient framework to attain optimal values of two important hyperparameters (LR and BS) and consequently an optimized model with an accuracy of 99.56%. Further, our results showed that both hyperparameters have a significant impact individually as well as interactively, with a trade-off in between. Further, the evaluation space was extended by using the statistical ANOVA analysis to validate the main findings. F-test returned with p < 0.05, confirming that both hyperparameters not only have a significant impact on the model performance independently, but that there exists an interaction between the hyperparameters for a combination of their levels

Mitigating the impact of COVID-19 on tuberculosis and HIV services: A cross-sectional survey of 669 health professionals in 64 low and middle-income countries.

OBJECTIVE: The experiences of frontline healthcare professionals are essential in identifying strategies to mitigate the disruption to healthcare services caused by the COVID-19 pandemic. METHODS: We conducted a cross-sectional study of TB and HIV professionals in low and middle-income countries (LMIC). Between May 12 and August 6, 2020, we collected qualitative and quantitative data using an online survey in 11 languages. We used descriptive statistics and thematic analysis to analyse responses. FINDINGS: 669 respondents from 64 countries completed the survey. Over 40% stated that it was either impossible or much harder for TB and HIV patients to reach healthcare facilities since COVID-19. The most common barriers reported to affect patients were: fear of getting infected with SARS-CoV-2, transport disruptions and movement restrictions. 37% and 28% of responses about TB and HIV stated that healthcare provider access to facilities was also severely impacted. Strategies to address reduced transport needs and costs-including proactive coordination between the health and transport sector and cards that facilitate lower cost or easier travel-were presented in qualitative responses. Access to non-medical support for patients, such as food supplementation or counselling, was severely disrupted according to 36% and 31% of HIV and TB respondents respectively; qualitative data suggested that the need for such services was exacerbated. CONCLUSION: Patients and healthcare providers across numerous LMIC faced substantial challenges in accessing healthcare facilities, and non-medical support for patients was particularly impacted. Synthesising recommendations of frontline professionals should be prioritised for informing policymakers and healthcare service delivery organisations

Building nurse education capacity in India: insights from a faculty development programme in Andhra Pradesh

Background: India faces an acute shortage of nurses. Strategies to tackle the human resource crisis depend upon scaling up nursing education provision in a context where the social status and working conditions of nurses are highly variable. Several national and regional situation assessments have revealed significant concerns about educational governance, institutional and educator capacity, quality and standards. Improving educational capacity through nursing faculty development has been proposed as one of several strategies to address a complex health human resource situation. This paper describes and critically reflects upon the experience of one such faculty development programme in the state of Andhra Pradesh. Discussion: The faculty development programme involved a 2 year partnership between a UK university and 7 universities in Andhra Pradesh. It adopted a participatory approach and covered training and support in 4 areas: teaching, research/scholarship, leadership/management and clinical education. Senior hospital nurses were also invited to participate. Summary: The programme was evaluated positively and some changes to educational practice were reported. However, several obstacles to wider change were identified. At the programme level, there was a need for more intensive individual and institutional mentorship as well as involvement of Indian Centres of Excellence in Nursing to provide local (as well as international) expertise. At the organisational level, the participating Colleges reported heavy workloads, lack of control over working conditions, lack of control over the curriculum and poor infra-structure/resources as ongoing challenges. In the absence of wider educational reform in nursing and government commitment to the profession, faculty development programmes alone will have limited impac

The nature of fibrous dysplasia

Fibrous dysplasia has been regarded as a developmental skeletal disorder characterized by replacement of normal bone with benign cellular fibrous connective tissue. It has now become evident that fibrous dysplasia is a genetic disease caused by somatic activating mutation of the Gsα subunit of G protein-coupled receptor resulting in upregulation of cAMP. This leads to defects in differentiation of osteoblasts with subsequent production of abnormal bone in an abundant fibrous stroma. In addition there is an increased production of IL-6 by mutated stromal fibrous dysplastic cells that induce osteoclastic bone resorption