The Influence of Georgia’s Quality Rated System on School Readiness in Preschool Children

Background: Initially launched in 2012, the Quality Rated (QR) program in Georgia is a policy tool for assessing, improving, and communicating the quality of early childhood education and care. Star level designations – zero-star, one-star, two-star, and three-star – are assigned based on a portfolio of QR standards and an onsite Environment Rating Scales observation. In the present study, we used QR data to determine if childcare quality measures (QR ratings) are linked with the readiness of children to enter kindergarten. Methods: QR data were collected from one-star, two-star, and three-star childcare learning centers (n = 16) located within Child Care Resource and Referral Regions 3 and 5 in Georgia. The Bracken School Readiness Assessment – 3rd Edition (BSRA-3) was administered to each child (n =318) eligible for inclusion. Height and weight information (n =335) was collected before assessment. Multilevel analyses were used to establish whether children in programs that score higher on QR (0 to 3 stars) show better school readiness (i.e., by BSRA-3 assessment or body mass index) than peers in programs with lower scores. Results: For the children, there were no significant differences in scores of school readiness based on the QR of childcare and learning centers. Conclusions: The results reinforce the need for continued research of the childcare QR system in Georgia to inform stakeholders in early childcare and education about ways to enhance the quality of early child care and to improve the long-term educational and health outcomes of children across the state. Future studies should examine a larger sample size, which would allow for more precise, multilevel analyses

Emerging issues for international family law. Part 2: possibilities and challenges to providing effective legal remedies in cases of transnational marriage abandonment

This is the second article in a tripartite series of papers about transnational marriage abandonment of women. The first article, published in October [2013] Fam Law 1247, outlines three forms of transnational abandonment of women. In this article we focus on the second category of abandonment where a wife is abandoned abroad by her husband who returns to England with her travel documents. Within this category we discuss cases where children are involved who in the majority of cases remain living in England while their mother is abandoned abroad. A common theme running through all these cases is that the wives are subjected to domestic servitude, isolation and domestic violence by their husbands and in-laws during the perpetuation of the marriage on the basis that their immigration status is insecure. This article will also touch upon legal remedies that are available to women who fall within the third category of abandonment, having never been sponsored to the UK following marriage, and explores the lack of safeguards and redress available to them within the family law arena – what is referred to as the ‘justice gap’ in the first article

Emerging issues for international family law. Part 3: transnational marriage abandonment and the dowry question

This article is the last in the series of three articles on transnational marriage abandonment. It will consider the particular problem of dowry in transnational marriages which has implications for cases arising from abandonment in particular, and more broadly for cases of domestic violence and in financial settlements upon divorce in (international) family law. This article examines the meaning and nature of the practice of dowry and the contexts in which dowry is practiced in South Asia and in South Asian communities in the UK, as well as the implications of dowry for legal practice in England & Wales. The particular, the implications of dowry in transnational marriage abandonment will be scrutinised. Reflecting on the themes and issues emerging from the series, a set of recommendations in relation to gaps in current practice as well as risk indicators and recommendations to foster a more effective practice will be presented

TLR4-Induced Inflammation Is a Key Promoter of Tumor Growth, Vascularization, and Metastasis

Toll-like receptor-4 (TLR4) is a powerful pathway best known for inducing inflammation in response to bacteria-produced lipopolysaccharide. TLR4 is also activated by endogenous ligands produced by host-damaged cells and a chemo-drug paclitaxel. Under normal conditions, TLR4 is expressed mainly in macrophages and, at a lower level, in epithelial, endothelial, and stromal cells. Activated TLR4 significantly increases inflammatory cytokines and enhances cell proliferation, migration, invasion, and survival. While these functions in normal cells are essential for host defense and tissue repair, TLR4 overexpression in malignant cells promotes tumor growth and metastasis. This is because pro-oncogenic effects of activated TLR4 in tumor cells are amplified by similar event in TLR4-positive tumor-associated cells including endothelial cells and their mobilized progenitors. The collective activation of multiple cell types within the tumor promotes chemoresistance and metastasis. Here, we summarize the current knowledge of the TLR4 pathway and its functional outcomes in normal and tumor cells. We also discuss its underappreciated role in supporting tumor progression through vascular activation and recruitment of endothelial progenitors. The review considers several open questions regarding the impact of TLR4-mediated pro- and antitumor effects, structural requirements for recognition of the TLR4 complex, and a potential contribution of chemotherapy to tumor spread

Detection of macular atrophy in age-related macular degeneration aided by artificial intelligence

INTRODUCTION: Age-related macular degeneration (AMD) is a leading cause of irreversible visual impairment worldwide. The endpoint of AMD, both in its dry or wet form, is macular atrophy (MA) which is characterized by the permanent loss of the RPE and overlying photoreceptors either in dry AMD or in wet AMD. A recognized unmet need in AMD is the early detection of MA development. AREAS COVERED: Artificial Intelligence (AI) has demonstrated great impact in detection of retinal diseases, especially with its robust ability to analyze big data afforded by ophthalmic imaging modalities, such as color fundus photography (CFP), fundus autofluorescence (FAF), near-infrared reflectance (NIR), and optical coherence tomography (OCT). Among these, OCT has been shown to have great promise in identifying early MA using the new criteria in 2018. EXPERT OPINION: There are few studies in which AI-OCT methods have been used to identify MA; however, results are very promising when compared to other imaging modalities. In this paper, we review the development and advances of ophthalmic imaging modalities and their combination with AI technology to detect MA in AMD. In addition, we emphasize the application of AI-OCT as an objective, cost-effective tool for the early detection and monitoring of the progression of MA in AMD

Prepaying Fare for Multi-hop Trip with a Single Purchase

Routes involving transportation transfers require users to make multiple separate fare purchases covering different individual segments of the trip. Purchasing tickets for a trip separately from choosing the routing option and needing to make multiple purchases for a single trip is a complex, cumbersome, and inefficient user experience. This disclosure describes techniques that enable users to prepay the fare covering all segments of a desired transportation route with a single purchase. The prepaid fare is represented with a single unique code that can be scanned to verify fare validity at fare readers. The techniques also enable users to purchase multiple tickets for future use and save routes and/or source-destination pairs for easier future purchases and dynamic pricing updates. The techniques improve the convenience, ease, transparency, and efficiency of planning and paying for travel, and reduce the potential for ticketing-related disruption during a trip

DBGC:Dimension-Based Generic Convolution Block for Object Recognition

The object recognition concept is being widely used a result of increasing CCTV surveillance and the need for automatic object or activity detection from images or video. Increases in the use of various sensor networks have also raised the need of lightweight process frameworks. Much research has been carried out in this area, but the research scope is colossal as it deals with open-ended problems such as being able to achieve high accuracy in little time using lightweight process frameworks. Convolution Neural Networks and their variants are widely used in various computer vision activities, but most of the architectures of CNN are application-specific. There is always a need for generic architectures with better performance. This paper introduces the Dimension-Based Generic Convolution Block (DBGC), which can be used with any CNN to make the architecture generic and provide a dimension-wise selection of various height, width, and depth kernels. This single unit which uses the separable convolution concept provides multiple combinations using various dimension-based kernels. This single unit can be used for height-based, width-based, or depth-based dimensions; the same unit can even be used for height and width, width and depth, and depth and height dimensions. It can also be used for combinations involving all three dimensions of height, width, and depth. The main novelty of DBGC lies in the dimension selector block included in the proposed architecture. Proposed unoptimized kernel dimensions reduce FLOPs by around one third and also reduce the accuracy by around one half; semi-optimized kernel dimensions yield almost the same or higher accuracy with half the FLOPs of the original architecture, while optimized kernel dimensions provide 5 to 6% higher accuracy with around a 10 M reduction in FLOPs

A Case of Sepsis by a Rare Pathogen Delftia acidovorans in a Patient Undergoing Chemotherapy

Patients undergoing chemotherapy for any malignant disease are at a higher risk of developing central line related blood stream infection, as a result of lack of proper care of the central line used for giving chemotherapy. Here, a case of sepsis by an unusual pathogen Delftia acidovorans is shown in a 29-year-old female patient undergoing chemotherapy for breast cancer with no other related co-morbidities and family history. On investigation, elevated procalcitonin showed presence of bacterial sepsis. Despite of empirical antimicrobial therapy, the patient showed features of continued sepsis. Blood specimens were taken and sent as paired sets of BACTEC blood culture bottles. This was identified as Delftia acidovorans which is rarely known to cause central line related blood stream infection and has a ubiquitous presence and cause infection mostly in immunocompromised patients. Empirical therapy was continued in the patient but could not be revived because of sudden episode of bradycardia. This report highlights the significance of appropriate diagnosis and treatment of such rare pathogen as a causative pathogen for sepsis. In this report, authors also emphasise the need of education of patients and healthcare providers for proper care of any chemoport inserted to avoid incidence of central line associated blood stream infection

Quality assessment of anterior segment OCT images: development and validation of quality criteria

Background: The utility of medical imaging is dependent on image quality. We aimed to develop and validate quality criteria for ocular anterior segment optical coherence tomography (AS-OCT) images. Methods: We undertook a cross-sectional study using AS-OCT images from patients aged 6-16. A novel three-level grading system (good, limited or poor) was developed based on the presence of image artefact (categorised as lid, eyelash, cropping, glare, or movement artefact). Three independent experts graded 2825 images, with agreement assessed using confusion matrices and intraclass correlation coefficients (ICC) for each parameter. Results: There was very good inter-grader IQA agreement assessing image quality with ICC 0.85 (95%CI: 0.84-0.87). The most commonly occurring artefact was eyelash artefact (1008/2825 images, 36%). Graders labelled 621/2825 (22%) images as good and 384 (14%) as poor. There was complete agreement at either end of the confusion matrix with no ‘good’ images labelled as ‘poor’ by other graders, and vice versa. Similarly, there was very good agreement when assessing presence of lash (0.96,0.94-0.98), movement (0.97,0.96-0.99), glare (0.82,0.80-0.84) and cropping (0.90,0.88-0.92). Conclusions: The novel image quality assessment criteria (IQAC) described here have good interobserver agreement overall, and excellent agreement on the differentiation between ‘good’ and ‘poor’ quality images. The large proportion of images graded as ‘limited’ suggests the need for refine this classification, using the specific IQAC features, for which we also report high interobserver agreement. These findings support the future potential for wider clinical and community care implementation of AS-OCT for the diagnosis and monitoring of ocular disease