Measurement-based modeling of RF-EMF exposure in urban environments using artificial intelligence techniques

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Childhood mitochondrial encephalomyopathies: clinical course, diagnosis, neuroimaging findings, mtDNA mutations and outcome in six children

Mitochondrial dysfunction manifests in many forms during childhood. There is no effective therapy for the condition; hence symptomatic therapy is the only option. The effect of symptomatic therapy are not well known. We present clinical course, diagnosis and effect of current treatments for six children suffering from mitochondrial encephalomyopathy identified by clinical demonstrations, brain MRI findings and DNA mutations. Two were male and four were female. Their age ranged between 2 and 17 years. Skeletal muscle biopsies were obtained in three and one showed misshaped and enlarged mitochondria under electron microscope. mtDNA mutation frequency was >30%. Five children were diagnosed with MELAS (mitochondrial encephalopathy, lactic acidosis, and strokelike episodes) and one with Leigh’s syndrome (LS). All were given cocktail and symptomatic treatments. One of the five MELAS children died from severe complications. The other four MELAS children remain alive; four showed improvement, and one remained unresponsive. Of the four who showed improvement, two do not have any abnormal signs and the other two have some degree of motor developmental delay and myotrophy. The LS child is doing well except for ataxia. Until better therapy such as mitochondrial gene therapy is available, cocktail and symptomatic treatments could at least stabilize these children

Assessment of Long-Term Watershed Management on Reservoir Phosphorus Concentrations and Export Fluxes.

Source water nutrient management to prevent eutrophication requires critical strategies to reduce watershed phosphorus (P) loadings. Shanxi Drinking-Water Source Area (SDWSA) in eastern China experienced severe water quality deterioration before 2010, but showed considerable improvement following application of several watershed management actions to reduce P. This paper assessed the changes in total phosphorus (TP) concentrations and fluxes at the SDWSA outlet relative to watershed anthropogenic P sources during 2005⁻2016. Overall anthropogenic P inputs decreased by 21.5% over the study period. Domestic sewage, livestock, and fertilizer accounted for (mean ± SD) 18.4 ± 0.6%, 30.1 ± 1.9%, and 51.5 ± 1.5% of total anthropogenic P inputs during 2005⁻2010, compared to 24.3 ± 2.7%, 8.8 ± 10.7%, and 66.9 ± 8.0% for the 2011⁻2016 period, respectively. Annual average TP concentrations in SDWSA decreased from 0.041 ± 0.019 mg/L in 2009 to 0.025 ± 0.013 mg/L in 2016, a total decrease of 38.2%. Annual P flux exported from SDWSA decreased from 0.46 ± 0.04 kg P/(ha·a) in 2010 to 0.25 ± 0.02 kg P/(ha·a) in 2016, a decrease of 44.9%. The success in reducing TP concentrations was mainly due to the development of domestic sewage/refuse collection/treatment and improved livestock management. These P management practices have prevented harmful algal blooms, providing for safe drinking water

Application of DMSP/OLS nighttime light images : a meta-analysis and a systematic literature review

© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 6 (2014): 6844-6866, doi:10.3390/rs6086844.Since the release of the digital archives of Defense Meteorological Satellite Program Operational Line Scanner (DMSP/OLS) nighttime light data in 1992, a variety of datasets based on this database have been produced and applied to monitor and analyze human activities and natural phenomena. However, differences among these datasets and how they have been applied may potentially confuse researchers working with these data. In this paper, we review the ways in which data from DMSP/OLS nighttime light images have been applied over the past two decades, focusing on differences in data processing, research trends, and the methods used among the different application areas. Five main datasets extracted from this database have led to many studies in various research areas over the last 20 years, and each dataset has its own strengths and limitations. The number of publications based on this database and the diversity of authors and institutions involved have shown promising growth. In addition, researchers have accumulated vast experience retrieving data on the spatial and temporal dynamics of settlement, demographics, and socioeconomic parameters, which are “hotspot” applications in this field. Researchers continue to develop novel ways to extract more information from the DMSP/OLS database and apply the data to interdisciplinary research topics. We believe that DMSP/OLS nighttime light data will play an important role in monitoring and analyzing human activities and natural phenomena from space in the future, particularly over the long term. A transparent platform that encourages data sharing, communication, and discussion of extraction methods and synthesis activities will benefit researchers as well as public and political stakeholders.This work is supported by the 111 project “Hazard and Risk Science Base at Beijing Normal University” under Grant B08008 (Ministry of Education and State Administration of Foreign Experts Affairs, PRC), the State Key Laboratory of Earth Surface Processes and Resource Ecology of Beijing Normal University (No. 2013-RC-03), and the Fundamental Research Funds for the Central Universities (Grant No. 201413037)

Pulmonary alveolar type I cell population consists of two distinct subtypes that differ in cell fate.

Pulmonary alveolar type I (AT1) cells cover more than 95% of alveolar surface and are essential for the air-blood barrier function of lungs. AT1 cells have been shown to retain developmental plasticity during alveolar regeneration. However, the development and heterogeneity of AT1 cells remain largely unknown. Here, we conducted a single-cell RNA-seq analysis to characterize postnatal AT1 cell development and identified insulin-like growth factor-binding protein 2 (Igfbp2) as a genetic marker specifically expressed in postnatal AT1 cells. The portion of AT1 cells expressing Igfbp2 increases during alveologenesis and in post pneumonectomy (PNX) newly formed alveoli. We found that the adult AT1 cell population contains both Hopx+Igfbp2+ and Hopx+Igfbp2- AT1 cells, which have distinct cell fates during alveolar regeneration. Using an Igfbp2-CreER mouse model, we demonstrate that Hopx+Igfbp2+ AT1 cells represent terminally differentiated AT1 cells that are not able to transdifferentiate into AT2 cells during post-PNX alveolar regeneration. Our study provides tools and insights that will guide future investigations into the molecular and cellular mechanism or mechanisms underlying AT1 cell fate during lung development and regeneration

Coexistence of spin glass and ferroelectricity in highly ordered Bi2FeMnO6 epitaxial thin film

Highly ordered Bi2FeMnO6 epitaxial thin films have been successfully grown on SrTiO3 substrate. Both synchrotron X-ray reciprocal space mapping and high resolution transmission electron microscopy confirmed the alternative alignment of Fe and Mn along [111] direction of Bi2FeMnO6 films. Magnetic and ferroelectric properties of Bi2FeMnO6 films are characterized and analyzed. The room-temperature ferroelectricity is well kept in Bi2FeMnO6 film as expected. However, it is very interesting that Bi2FeMnO6 film exhibits a typical spin-glass behavior and very weak magnetism rather than a ferri/ferromagnetism as generally believed. Our first-principles calculations suggest a spin frustration model for Bi2FeMnO6, which can well explain the intriguing magnetic property of Bi2FeMnO6 film.Comment: Main text: 30 pages and 14 figure

Personalized Estimate of Chemotherapy-Induced Nausea and Vomiting: Development and External Validation of a Nomogram in Cancer Patients Receiving Highly/Moderately Emetogenic Chemotherapy.

Chemotherapy-induced nausea and vomiting (CINV) is presented in over 30% of cancer patients receiving highly/moderately emetogenic chemotherapy (HEC/MEC). The currently recommended antiemetic therapy is merely based on the emetogenic level of chemotherapy, regardless of patient's individual risk factors. It is, therefore, critical to develop an approach for personalized management of CINV in the era of precision medicine.A number of variables were involved in the development of CINV. In the present study, we pooled the data from 2 multi-institutional investigations of CINV due to HEC/MEC treatment in Asian countries. Demographic and clinical variables of 881 patients were prospectively collected as defined previously, and 862 of them had full documentation of variables of interest. The data of 548 patients from Chinese institutions were used to identify variables associated with CINV using multivariate logistic regression model, and then construct a personalized prediction model of nomogram; while the remaining 314 patients out of China (Singapore, South Korea, and Taiwan) entered the external validation set. C-index was used to measure the discrimination ability of the model.The predictors in the final model included sex, age, alcohol consumption, history of vomiting pregnancy, history of motion sickness, body surface area, emetogenicity of chemotherapy, and antiemetic regimens. The C-index was 0.67 (95% CI, 0.62-0.72) for the training set and 0.65 (95% CI, 0.58-0.72) for the validation set. The C-index was higher than that of any single predictor, including the emetogenic level of chemotherapy according to current antiemetic guidelines. Calibration curves showed good agreement between prediction and actual occurrence of CINV.This easy-to-use prediction model was based on chemotherapeutic regimens as well as patient's individual risk factors. The prediction accuracy of CINV occurrence in this nomogram was well validated by an independent data set. It could facilitate the assessment of individual risk, and thus improve the personalized management of CINV

Privacy Analysis and Compliance Approach with a Focus on Children

In recent years, with wearable technologies being brought to use, a significant number of risks have arisen due to the collection and processing of sensitive personal information, particularly in the context of privacy and compliance challenges associated with wearable technologies such as smartwatches designed for children. Considering this, this thesis proposes an automated compliance checking application aimed at ensuring adherence to comprehensive privacy regulations, including the General Data Protection Regulation (GDPR), the California Privacy Rights Act (CPRA), the New Federal Act on Data Protection (nFADP), Personal Information Protection Law of the People’s Republic of China (PIPL) and Protection of Personal Information Act (POPIA). The application leverages Natural Language Processing (NLP) techniques, specifically the Bidirectional Encoder Representations from Transformers (BERT) model, to facilitate consistent evaluation of smartwatches’ compliance with privacy standards. To achieve this, the thesis encompasses regulatory analysis, database design, API development, and user interface implementation. The proposed application aims to empower guardians with tools to safeguard children’s digital privacy and urge device manufacturers to design more compliant devices