Smartphone-based Calorie Estimation From Food Image Using Distance Information

Personal assistive systems for diet control can play a vital role to combat obesity. As smartphones have become inseparable companions for a large number of people around the world, designing smartphone-based system is perhaps the best choice at the moment. Using this system people can take an image of their food right before eating, know the calorie content based on the food items on the plate. In this paper, we propose a simple method that ensures both user flexibility and high accuracy at the same time. The proposed system employs capturing food images with a fixed posture and estimating the volume of the food using simple geometry. The real world experiments on different food items chosen arbitrarily show that the proposed system can work well for both regular and liquid food items

Feature Engineering in Learning-to-Rank for Community Question Answering Task

Community question answering (CQA) forums are Internet-based platforms where users ask questions about a topic and other expert users try to provide solutions. Many CQA forums such as Quora, Stackoverflow, Yahoo!Answer, StackExchange exist with a lot of user-generated data. These data are leveraged in automated CQA ranking systems where similar questions (and answers) are presented in response to the query of the user. In this work, we empirically investigate a few aspects of this domain. Firstly, in addition to traditional features like TF-IDF, BM25 etc., we introduce a BERT-based feature that captures the semantic similarity between the question and answer. Secondly, most of the existing research works have focused on features extracted only from the question part; features extracted from answers have not been explored extensively. We combine both types of features in a linear fashion. Thirdly, using our proposed concepts, we conduct an empirical investigation with different rank-learning algorithms, some of which have not been used so far in CQA domain. On three standard CQA datasets, our proposed framework achieves state-of-the-art performance. We also analyze importance of the features we use in our investigation. This work is expected to guide the practitioners to select a better set of features for the CQA retrieval task.Comment: 20 page

Pathologic evaluation of tumor-associated macrophage density and vessel inflammation in invasive breast carcinomas

Tumor-associated macrophages (TAMs) are major constituents of the tumor microenvironment in solid tumors and have been implicated as mediators of tumor progression, invasion and metastasis. Correspondingly, accumulation of TAMs is associated with unfavorable clinical outcomes in numerous types of solid tumors. E-selectin is a hallmark of inflammation and a key adhesion molecule that accommodates the initial contact of circulating immune cells with the inflamed vessel surface. Currently, the association between E-selectin and TAMs is not fully elucidated; therefore, the present study investigated the association between vessel inflammation, TAM infiltration, and clinical outcome in breast cancer. A total of 53 procedure-naïve invasive breast cancer cases were immunohistochemically analyzed for the presence of cluster of differentiation (CD)68+ TAMs, E-selectin+ vessels and tumor inflammation. The association between CD68 and E-selectin expression, and tumor inflammation as well as overall survival was evaluated using Kaplan-Meier survival curves and multivariable Cox\u27s proportional hazards regression analysis. The abundance of TAMs was identified to be positively associated with tumor inflammation, estrogen receptor and E-selectin expression levels. A greater prevalence of TAMs and tumor inflammation was significantly associated with shorter overall survival times. E-selectin expression levels were significantly higher in tumor vessels among elderly patients, but were not associated with overall survival. The abundance of TAMs was associated with the presence of E-selectin-expressing inflamed tumor vessels and tumor inflammation, as well as overall survival in patients with invasive breast carcinoma. © 2017, Spandidos Publications. All rights reserved

Implementation of lean tools as waste assessment method in a coil spring manufacturing

Lean manufacturing is a systematic methodology to minimize waste while maximizing resource utilization which helps business become more effective and competitive in the marketplace. Lean manufacturing is about the enthusiasm for waste elimination. Any business can remain competitive if it is flexible enough to continuously and systematically improve its manufacturing process by eliminating waste, optimize processes, and cut unnecessary cost. This review aims to discuss a wastage assessment method that has been used to implement lean manufacturing across all manufacturing sectors like automotive, electronics, plastic, textile, food, dairy, even services. Specifically, it investigates which are the most common lean tools to be utilized and which has an impact on an organization’s performance. In this context, waste is defined as unproductive manufacturing practices by which it does not add value to the product or services and customers are not willing to pay. A comparison of lean tools was made and discussed to analyse the effectiveness of the tool’s performance

Functional Blockade of E-Selectin in Tumor-Associated Vessels Enhances Anti-Tumor Effect of Doxorubicin in Breast Cancer

Chemotherapy is a mainstay of treatment for solid tumors. However, little is known about how therapy-induced immune cell infiltration may affect therapy response. We found substantial CD45+ immune cell density adjacent to E-selectin expressing inflamed vessels in doxorubicin (DOX)-treated residual human breast tumors. While CD45 level was significantly elevated in DOX-treated wildtype mice, it remained unchanged in DOX-treated tumors from E-selectin null mice. Similarly, intravenous administration of anti-E-selectin aptamer (ESTA) resulted in a significant reduction in CD45+ immune cell density in DOX-treated residual tumors, which coincided with a delay in tumor growth and lung metastasis in MMTV-pyMT mice. Additionally, both tumor infiltrating T-lymphocytes and tumor associated-macrophages were skewed towards TH2 in DOX-treated residual breast tumors; however, ESTA suppressed these changes. This study suggests that DOX treatment instigates de novo intratumoral infiltration of immune cells through E-selectin, and functional blockade of E-selectin may reduce residual tumor burden as well as metastasis through suppression of TH2 shift

Fibroblast growth factor-2 (FGF2) and syndecan-1 (SDC1) are potential biomarkers for putative circulating CD15+/CD30+ cells in poor outcome Hodgkin lymphoma patients.

BACKGROUND: High risk, unfavorable classical Hodgkin lymphoma (cHL) includes those patients with primary refractory or early relapse, and progressive disease. To improve the availability of biomarkers for this group of patients, we investigated both tumor biopsies and peripheral blood leukocytes (PBL) of untreated (chemo-naïve, CN) Nodular Sclerosis Classic Hodgkin Lymphoma (NS-cHL) patients for consistent biomarkers that can predict the outcome prior to frontline treatment. METHODS AND MATERIALS: Bioinformatics data mining was used to generate 151 candidate biomarkers, which were screened against a library of 10 HL cell lines. Expression of FGF2 and SDC1 by CD30+ cells from HL patient samples representing good and poor outcomes were analyzed by qRT-PCR, immunohistochemical (IHC), and immunofluorescence analyses. RESULTS: To identify predictive HL-specific biomarkers, potential marker genes selected using bioinformatics approaches were screened against HL cell lines and HL patient samples. Fibroblast Growth Factor-2 (FGF2) and Syndecan-1 (SDC1) were overexpressed in all HL cell lines, and the overexpression was HL-specific when compared to 116 non-Hodgkin lymphoma tissues. In the analysis of stratified NS-cHL patient samples, expression of FGF2 and SDC1 were 245 fold and 91 fold higher, respectively, in the poor outcome (PO) group than in the good outcome (GO) group. The PO group exhibited higher expression of the HL marker CD30, the macrophage marker CD68, and metastatic markers TGFβ1 and MMP9 compared to the GO group. This expression signature was confirmed by qualitative immunohistochemical and immunofluorescent data. A Kaplan-Meier analysis indicated that samples in which the CD30+ cells carried an FGF2+/SDC1+ immunophenotype showed shortened survival. Analysis of chemo-naive HL blood samples suggested that in the PO group a subset of CD30+ HL cells had entered the circulation. These cells significantly overexpressed FGF2 and SDC1 compared to the GO group. The PO group showed significant down-regulation of markers for monocytes, T-cells, and B-cells. These expression signatures were eliminated in heavily pretreated patients. CONCLUSION: The results suggest that small subsets of circulating CD30+/CD15+ cells expressing FGF2 and SDC1 represent biomarkers that identify NS-cHL patients who will experience a poor outcome (primary refractory and early relapsing)

Arsenic Exposure of Mothers and Low Birth Weight

Low birth weight (LBW) of the babies was found to be associated with arsenic exposure through consuming arsenic-contaminated water in Bangladesh. But the influences of maternal nutritional status and hemoglobin level remains to be dealt with. This study was conducted to assess the LBW of the babies in reference to arsenic exposure of mothers controlling the influences of the nutritional status (BMI) and hemoglobin level. This was a cross-sectional study carried out amongst the pregnant mothers who came to a district hospital for delivery. The mothers aged ≥18 years and had no complication were included in the study. A total of 101 mothers and their newborn babies were the study sample. Of the total 101 participant mothers, 41.5% were arsenic exposed. Comparatively, on an average, lower birth weight (2492± 477gr) was found among the babies born to arsenic exposed-mother. The exposed mother of LBW babies had significantly a higher urine arsenic concentration (381.38µg/L). The correlation analysis revealed that there was a negative relationship with the urine arsenic concentration (r=-.619; p=.000) and positive relationship with the hemoglobin level (r=.280; p=.092) and BMI (r=.204; p=195) of the exposed mother with the birth weight. After controlling the influence of hemoglobin level and BMI, an almost same association was found between LBW and urine arsenic. Mothers with arsenic exposure were at risk of giving birth to LBW babies, this could increase as evident by higher maternal urine arsenic concentration. And any positive effect of maternal nutritional status and hemoglobin level on birth weight of newborn could be offset by arsenic exposure

Mapping disparities in education across low- and middle-income countries

Analyses of the proportions of individuals who have completed key levels of schooling across all low- and middle-income countries from 2000 to 2017 reveal inequalities across countries as well as within populations. Educational attainment is an important social determinant of maternal, newborn, and child health(1-3). As a tool for promoting gender equity, it has gained increasing traction in popular media, international aid strategies, and global agenda-setting(4-6). The global health agenda is increasingly focused on evidence of precision public health, which illustrates the subnational distribution of disease and illness(7,8); however, an agenda focused on future equity must integrate comparable evidence on the distribution of social determinants of health(9-11). Here we expand on the available precision SDG evidence by estimating the subnational distribution of educational attainment, including the proportions of individuals who have completed key levels of schooling, across all low- and middle-income countries from 2000 to 2017. Previous analyses have focused on geographical disparities in average attainment across Africa or for specific countries, but-to our knowledge-no analysis has examined the subnational proportions of individuals who completed specific levels of education across all low- and middle-income countries(12-14). By geolocating subnational data for more than 184 million person-years across 528 data sources, we precisely identify inequalities across geography as well as within populations.Peer reviewe

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations

Mapping child growth failure across low- and middle-income countries

Child growth failure (CGF), manifested as stunting, wasting, and underweight, is associated with high 5 mortality and increased risks of cognitive, physical, and metabolic impairments. Children in low- and middle-income countries (LMICs) face the highest levels of CGF globally. Here we illustrate national and subnational variation of under-5 CGF indicators across LMICs, providing 2000–2017 annual estimates mapped at a high spatial resolution and aggregated to policy-relevant administrative units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the World Health 10 Organization’s ambitious Global Nutrition Targets to reduce stunting by 40% and wasting to less than 5% by 2025. Large disparities in prevalence and rates of progress exist across regions, countries, and within countries; our maps identify areas where high prevalence persists even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where subnational disparities exist and the highest-need populations reside, these geospatial estimates can support policy-makers in planning locally 15 tailored interventions and efficient directing of resources to accelerate progress in reducing CGF and its health implications