Exploitation of TerraSAR-X Data for Land use/Land Cover Analysis Using Object-Oriented Classification Approach in the African Sahel Area, Sudan.

Recently, object-oriented classification techniques based on image segmentation approaches are being studied using high-resolution satellite images to extract various thematic information. In this study different types of land use/land cover (LULC) types were analysed by employing object-oriented classification approach to dual TerraSAR-X images (HH and HV polarisation) at African Sahel. For that purpose, multi-resolution segmentation (MRS) of the Definiens software was used for creating the image objects. Using the feature space optimisation (FSO) tool the attributes of the TerraSAR-X image were optimised in order to obtain the best separability among classes for the LULC mapping. The backscattering coefficients (BSC) for some classes were observed to be different for HH and HV polarisations. The best separation distance of the tested spectral, shape and textural features showed different variations among the discriminated LULC classes. An overall accuracy of 84 % with a kappa value 0.82 was resulted from the classification scheme, while accuracy differences among the classes were kept minimal. Finally, the results highlighted the importance of a combine use of TerraSAR-X data and object-oriented classification approaches as a useful source of information and technique for LULC analysis in the African Sahel drylands

Barriers and enablers for participation in healthy lifestyle programs by adolescents who are overweight: a qualitative study of the opinions of adolescents, their parents and community stakeholders

Background: Overweight or obesity during adolescence affects almost 25% of Australian youth, yet limited research exists regarding recruitment and engagement of adolescents in weight-management or healthy lifestyle interventions, or best-practice for encouraging long-term healthy behaviour change. A sound understanding of community perceptions, including views from adolescents, parents and community stakeholders, regarding barriers and enablers to entering and engaging meaningfully in an intervention is critical to improve the design of such programs. Methods: This paper reports findings from focus groups and semi-structured interviews conducted with adolescents (n=44), parents (n=12) and community stakeholders (n=39) in Western Australia. Three major topics were discussed to inform the design of more feasible and effective interventions: recruitment, retention in the program and maintenance of healthy change. Data were analysed using content and thematic analyses.Results: Data were categorised into barriers and enablers across the three main topics. For recruitment, identified barriers included: the stigma associated with overweight, difficulty defining overweight, a lack of current health services and broader social barriers. The enablers for recruitment included: strategic marketing, a positive approach and subsidising program costs. For retention, identified barriers included: location, timing, high level of commitment needed and social barriers. Enablers for retention included: making it fun and enjoyable for adolescents, involving the family, having an on-line component, recruiting good staff and making it easy for parents to attend. For maintenance, identified barriers included: the high degree of difficulty in sustaining change and limited services to support change. Enablers for maintenance included: on-going follow up, focusing on positive change, utilisation of electronic media and transition back to community services. Conclusions: This study highlights significant barriers for adolescents and parents to overcome to engage meaningfully with weight-management or healthy lifestyle programs. A number of enablers were identified to promote ongoing involvement with an intervention. This insight into specific contextual opinions from the local community can be used to inform the delivery of healthy lifestyle programs for overweight adolescents, with a focus on maximising acceptability and feasibility

CATMoS: Collaborative Acute Toxicity Modeling Suite.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495

Key signalling nodes in mammary gland development and cancer. The Snail1-Twist1 conspiracy in malignant breast cancer progression

Breast cancer is the most common cancer among women, and despite significant advances in diagnosing and treating it, metastatic spread of cancer cells results in a high mortality rate. Epithelial-to-mesenchymal transition (EMT) is an embryonic program in which epithelial cells lose their characteristics and gain mesenchymal features. Therefore, EMT might play a very important role during malignant tumour progression. In this review we summarise recent advances in breast cancer research with a particular focus on the transcription factors Snail1 and Twist1. Besides discussing the role of EMT in normal mammary gland development, we describe regulatory mechanisms involving newly discovered upstream regulators and microRNAs, the association of EMT with breast cancer stem cells, and the involvement of the tumour microenvironment in breast cancer progression

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Volume decorrelation effects in polarimetric SAR interferometry

Volume decorrelation is an aspect of SAR interferometry that is currently at stake. It stems from the distribution in height of the backscattering cross-section in a imaged scene and it widely affects interferometric coherence images, for example, in presence of forests or buildings. The interest in its reduction lies on the fact that ``resolving'' volume decorrelation and fixing the exact position of the scattering centres in a resolution cell may lead to an estimation of the height of the observed distributed scatterers. Indeed, the determination of the volume scattering contribution is determinant in digital elevation model (DEM) generation as well as in biomass estimation. However, volume decorrelation itself may be a source of information on the mechanisms which originate it. In this paper, a distinction is made between the behaviour of volume decorrelation due to random volumes and stationary distributed targets. The two cases are then studied by means of polarimetry: the response of such targets to different polarizations is considered by applying a series of decompositions of the scattering matrix and a systematic analysis of the interferometric coherence characteristics is reported

Combined application of target decomposition methods and polarimetric SAR interferometry: some preliminary results

The application of interferometric techniques to polarimetric SAR data is a relative new and promising research field. Noteworthy examples of its potential have been reported by Cloude and Papathanassiou for the retrieval of forests height. In general, polarimetric analysis approaches have been considered for optimizing the interferometric coherence, mainly in order to improve the generation of digital elevation models. In this paper, we will present the first results that we obtained by combining interferometric analysis with coherent target decomposition methods (in particular, the one proposed by Krogager); the different coherence properties of target models will be investigated and a provisional evaluation of the usefulness of this approach will be given

A comparison of target decomposition theorems in SAR interferometry applications

Theorems performing decompositions of the scattering matrix have been introduced to recognize observed targets and distinguish some of their characteristics, most of all the geometrical ones. For this reason, their main applications in the field of remote sensing have been suggested to be just the target identification and the classification of land coverages. A controversial aspect deals with their use with distributed targets that seem to be hardly representable by means of the scattering matrix and require for this scope higher order matrices. Some hints on these limits may be retrieved by considering interferometry, i. e., by studying interferometric quantities after performing the decompositions: those targets better resembling "ideal point scatterers" would present a degree of coherence considerably different from that of distributed targets. More generally, the correlation properties of various decomposition theorems will be presented and discussed, and the usefulness of the information so derived will be estimated