Tuberculosis in Pediatric Antiretroviral Therapy Programs in Low- and Middle-Income Countries: Diagnosis and Screening Practices

Background The global burden of childhood tuberculosis (TB) is estimated to be 0.5 million new cases per year. Human immunodeficiency virus (HIV)-infected children are at high risk for TB. Diagnosis of TB in HIV-infected children remains a major challenge. Methods We describe TB diagnosis and screening practices of pediatric antiretroviral treatment (ART) programs in Africa, Asia, the Caribbean, and Central and South America. We used web-based questionnaires to collect data on ART programs and patients seen from March to July 2012. Forty-three ART programs treating children in 23 countries participated in the study. Results Sputum microscopy and chest Radiograph were available at all programs, mycobacterial culture in 40 (93%) sites, gastric aspiration in 27 (63%), induced sputum in 23 (54%), and Xpert MTB/RIF in 16 (37%) sites. Screening practices to exclude active TB before starting ART included contact history in 41 sites (84%), symptom screening in 38 (88%), and chest Radiograph in 34 sites (79%). The use of diagnostic tools was examined among 146 children diagnosed with TB during the study period. Chest Radiograph was used in 125 (86%) children, sputum microscopy in 76 (52%), induced sputum microscopy in 38 (26%), gastric aspirate microscopy in 35 (24%), culture in 25 (17%), and Xpert MTB/RIF in 11 (8%) children. Conclusions Induced sputum and Xpert MTB/RIF were infrequently available to diagnose childhood TB, and screening was largely based on symptom identification. There is an urgent need to improve the capacity of ART programs in low- and middle-income countries to exclude and diagnose TB in HIV-infected childre

Sign language recognition

There is an absence of communication with deaf people in our society. To overcome this barrier the introduction of Sign Language (SL) took place. To convey meaning to normal people, sign language makes use of patterns that are visually transmitted sign patterns. Sign language is also useful for people suffering with Autism Spectrum Disorder (ASD). Normal people cannot understand the signs used by deaf, as they do not know the meaning of a particular sign. The system proposed here aims at solving this problem. This system uses a camera, which captures various gestures of the hand. Then, processing of the image takes place by using various algorithms. First, pre-processing of the image takes place. Then, determination of edges occurs by using an edge detection algorithm. Finally, a template-matching algorithm identifies the sign and display the text. As the output is text, one can easily interpret the meaning of a particular sign. This also curtails the difficulty to communicate with the deaf. The implementation of the system is by using Python. The system uses various libraries

Profitability enhancement by digital transformation and canvas digital model on strategic processes in post-Covid-19 in logistics SMEs

The main objective of every Small and Medium Enterprise is to develop the ability to generate profits permanently over time; However, the Covid-19 pandemic significantly affected the global economy, generating an average reduction of 27% in global production and consumption, as well as a reduction in the use of labor, either due to reduced wages or reduction in working hours, which has had an impact on the increase in poverty. It is in this context that SMEs, with the aim of continuing to operate, implemented a strategy to reinvent themselves, which has been based on the greater use of the Internet and digital platforms with the aim of energizing their market or changing their line of business. , will thus develop activities in other areas or new services that did not exist before the moment of this reinvention. In this context, electronic commerce increased in a first stage, promoting the need to develop the so-called ‘last mile’ processes, which is provided most of the time by light logistics companies; However, the lack of agile and rapid implementation methodologies that facilitate the identification and selection of digital technologies appropriate to the processes of SMEs has caused the growth rate of e-commerce sales to decrease, which affects consumption and poverty reduction. Therefore, the objectives of this research are to provide a methodology that allows improving the strategic planning of the organization, adapting the strategy to changes in the environment in an agile and rapid manner, and identifying the resources and actions required that contribute to increasing the productivity through the Digital Canvas Model and Digital Transformation in logistics SMEs in the short term

Sign Language Recognition

There is an absence of communication with deaf people in our society. To overcome this barrier the introduction of Sign Language (SL) took place. To convey meaning to normal people, sign language makes use of patterns that are visually transmitted sign patterns. Sign language is also useful for people suffering with Autism Spectrum Disorder (ASD). Normal people cannot understand the signs used by deaf, as they do not know the meaning of a particular sign. The system proposed here aims at solving this problem. This system uses a camera, which captures various gestures of the hand. Then, processing of the image takes place by using various algorithms. First, pre-processing of the image takes place. Then, determination of edges occurs by using an edge detection algorithm. Finally, a template-matching algorithm identifies the sign and display the text. As the output is text, one can easily interpret the meaning of a particular sign. This also curtails the difficulty to communicate with the deaf. The implementation of the system is by using Python. The system uses various libraries

Using PPI-GA for identifying protein complexes in protein-protein interaction networks

The major focus of an interdisciplinary field of study termed proteomics is a comprehensive analysis of proteins to evaluate their genetic variety, examine their distinctions, and respond to stresses. Proteomics' major goal is to use protein chemistry, bioinformatics, and biology to detect and measure proteins as well as analyze their post-translational modifications and interactions. Any disruption in the interacting network of proteins can lead to biological abnormalities and diseases like Alzheimer's and cancer. The majority of existing computational approaches for detecting protein complexes are based on certain topological properties of protein-protein networks (PPI). In this paper, it initially provides a novel encoding technique for representing the clarification and solution, and next we recommend the concept of PPI-GA, an innovative clustering based algorithm which is based on genetic approach algorithm which employs a innovative multi based objective excellence function to find out the protein complexes. A different two gold based standard and the real-world based datasets are been used to evaluate proposed algorithm. The obtained result shows that the suggested method can discover key protein complexes and that it offers more accurate results than existing protein complex identification techniques