Accredited qualifications for capacity development in disaster risk reduction and climate change adaptation

Increasingly practitioners and policy makers working across the globe are recognising the importance of bringing together disaster risk reduction and climate change adaptation. From studies across 15 Pacific island nations, a key barrier to improving national resilience to disaster risks and climate change impacts has been identified as a lack of capacity and expertise resulting from the absence of sustainable accredited and quality assured formal training programmes in the disaster risk reduction and climate change adaptation sectors. In the 2016 UNISDR Science and Technology Conference on the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030, it was raised that most of the training material available are not reviewed either through a peer-to-peer mechanism or by the scientific community and are, thus, not following quality assurance standards. In response to these identified barriers, this paper focuses on a call for accredited formal qualifications for capacity development identified in the 2015 United Nations landmark agreements in DRR and CCA and uses the Pacific Islands Region of where this is now being implemented with the launch of the Pacific Regional Federation of Resilience Professionals, for DRR and CCA. A key issue is providing an accreditation and quality assurance mechanism that is shared across boundaries. This paper argues that by using the United Nations landmark agreements of 2015, support for a regionally accredited capacity development that ensures all countries can produce, access and effectively use scientific information for disaster risk reduction and climate change adaptation. The newly launched Pacific Regional Federation of Resilience Professionals who work in disaster risk reduction and climate change adaptation may offer a model that can be used more widely

Accredited qualifications for capacity development in disaster risk reduction and climate change adaptation

Increasingly practitioners and policy makers working across the globe are recognising the importance of bringing together disaster risk reduction and climate change adaptation. From studies across 15 Pacific island nations, a key barrier to improving national resilience to disaster risks and climate change impacts has been identified as a lack of capacity and expertise resulting from the absence of sustainable accredited and quality assured formal training programmes in the disaster risk reduction and climate change adaptation sectors. In the 2016 UNISDR Science and Technology Conference on the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030, it was raised that most of the training material available are not reviewed either through a peer-to-peer mechanism or by the scientific community and are, thus, not following quality assurance standards. In response to these identified barriers, this paper focuses on a call for accredited formal qualifications for capacity development identified in the 2015 United Nations landmark agreements in DRR and CCA and uses the Pacific Islands Region of where this is now being implemented with the launch of the Pacific Regional Federation of Resilience Professionals, for DRR and CCA. A key issue is providing an accreditation and quality assurance mechanism that is shared across boundaries. This paper argues that by using the United Nations landmark agreements of 2015, support for a regionally accredited capacity development that ensures all countries can produce, access and effectively use scientific information for disaster risk reduction and climate change adaptation. The newly launched Pacific Regional Federation of Resilience Professionals who work in disaster risk reduction and climate change adaptation may offer a model that can be used more widely

Accredited qualifications for capacity development in disaster risk reduction and climate change adaptation

Increasingly practitioners and policy makers working across the globe are recognising the importance of bringing together disaster risk reduction and climate change adaptation. From studies across 15 Pacific island nations, a key barrier to improving national resilience to disaster risks and climate change impacts has been identified as a lack of capacity and expertise resulting from the absence of sustainable accredited and quality assured formal training programmes in the disaster risk reduction and climate change adaptation sectors. In the 2016 UNISDR Science and Technology Conference on the Implementation of the Sendai Framework for Disaster Risk Reduction 2015-2030, it was raised that most of the training material available are not reviewed either through a peer-to-peer mechanism or by the scientific community and are, thus, not following quality assurance standards. In response to these identified barriers, this paper focuses on a call for accredited formal qualifications for capacity development identified in the 2015 United Nations landmark agreements in DRR and CCA and uses the Pacific Islands Region of where this is now being implemented with the launch of the Pacific Regional Federation of Resilience Professionals, for DRR and CCA. A key issue is providing an accreditation and quality assurance mechanism that is shared across boundaries. This paper argues that by using the United Nations landmark agreements of 2015, support for a regionally accredited capacity development that ensures all countries can produce, access and effectively use scientific information for disaster risk reduction and climate change adaptation. The newly launched Pacific Regional Federation of Resilience Professionals who work in disaster risk reduction and climate change adaptation may offer a model that can be used more widely

Automated Detection of Macular Diseases by Optical Coherence Tomography and Artificial Intelligence Machine Learning of Optical Coherence Tomography Images

Purpose. Although optical coherence tomography (OCT) is essential for ophthalmologists, reading of findings requires expertise. The purpose of this study is to test deep learning with image augmentation for automated detection of chorioretinal diseases. Methods. A retina specialist diagnosed 1,200 OCT images. The diagnoses involved normal eyes (n=570) and those with wet age-related macular degeneration (AMD) (n=136), diabetic retinopathy (DR) (n=104), epiretinal membranes (ERMs) (n=90), and another 19 diseases. Among them, 1,100 images were used for deep learning training, augmented to 59,400 by horizontal flipping, rotation, and translation. The remaining 100 images were used to evaluate the trained convolutional neural network (CNN) model. Results. Automated disease detection showed that the first candidate disease corresponded to the doctor’s decision in 83 (83%) images and the second candidate disease in seven (7%) images. The precision and recall of the CNN model were 0.85 and 0.97 for normal eyes, 1.00 and 0.77 for wet AMD, 0.78 and 1.00 for DR, and 0.75 and 0.75 for ERMs, respectively. Some of rare diseases such as Vogt–Koyanagi–Harada disease were correctly detected by image augmentation in the CNN training. Conclusion. Automated detection of macular diseases from OCT images might be feasible using the CNN model. Image augmentation might be effective to compensate for a small image number for training

Accredited qualifications for capacity development in disaster risk reduction and climate change adaptation

Increasingly practitioners and policy makers working across the globe are recognising the importance of bringing together disaster risk reduction and climate change adaptation. From studies across 15 Pacific island nations, a key barrier to improving national resilience to disaster risks and climate change impacts has been identified as a lack of capacity and expertise resulting from the absence of sustainable accredited and quality assured formal training programmes in the disaster risk reduction and climate change adaptation sectors. In the 2016 UNISDR Science and Technology Conference on the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030, it was raised that most of the training material available are not reviewed either through a peer-to-peer mechanism or by the scientific community and are, thus, not following quality assurance standards. In response to these identified barriers, this paper focuses on a call for accredited formal qualifications for capacity development identified in the 2015 United Nations landmark agreements in DRR and CCA and uses the Pacific Islands Region of where this is now being implemented with the launch of the Pacific Regional Federation of Resilience Professionals, for DRR and CCA. A key issue is providing an accreditation and quality assurance mechanism that is shared across boundaries. This paper argues that by using the United Nations landmark agreements of 2015, support for a regionally accredited capacity development that ensures all countries can produce, access and effectively use scientific information for disaster risk reduction and climate change adaptation. The newly launched Pacific Regional Federation of Resilience Professionals who work in disaster risk reduction and climate change adaptation may offer a model that can be used more widely

Concordance of human equilibrative nucleoside transporter‐1 expressions between murine ( 10D7G2 ) and rabbit ( SP120 ) antibodies and association with clinical outcomes of adjuvant chemotherapy for pancreatic cancer: A collaborative study from the JASPAC 01 trial

BACKGROUND: Expression of human equilibrative nucleoside transporter‐1 (hENT1) is reported to predict survival of gemcitabine (GEM)‐treated patients. However, predictive values of immunohistochemical hENT1 expression may differ according to the antibodies, 10D7G2 and SP120. AIM: We aimed to investigate the concordance of immunohistochemical hENT1 expression between the two antibodies and prognosis. METHODS: The subjects of this study were totally 332 whose formalin‐fixed paraffin‐embedded specimens and/or unstained sections were obtained. The individual H‐scores and four classifications according to the staining intensity were applied for the evaluation of hENT1 expression by 10D7G2 and SP120, respectively. RESULTS: The highest concordance rate (79.8%) was obtained when the cut‐off between high and low hENT1 expression using SP120 was set between moderate and strong. There were no correlations of hENT1 mRNA level with H‐score (p = .258). Although the hENT1 mRNA level was significantly different among four classifications using SP120 (p = .011), there was no linear relationship among them. Multivariate analyses showed that adjuvant GEM was a significant predictor of the patients with low hENT1 expression using either 10D7G2 (Hazard ratio [HR] 2.39, p = .001) or SP120 (HR 1.84, p < .001). In contrast, agent for adjuvant chemotherapy was not significant predictor for the patients with high hENT1 expression regardless of the kind of antibody. CONCLUSION: The present study suggests that the two antibodies for evaluating hENT1 expression are equivalent depending on the cut‐off point and suggests that S‐1 is the first choice of adjuvant chemotherapy for pancreatic cancer with low hENT1 expression, whereas either S‐1 or GEM can be introduced for the pancreatic cancer with high hENT1 expression, no matter which antibody is used

Clinical characteristics of study patients.

Clinical characteristics of study patients.</p

The course of best-corrected visual acuity among the tnAMD, PCV, and RAM groups.

The course of best-corrected visual acuity among the tnAMD, PCV, and RAM groups.</p

Initially selected treatments in eyes with SMH in tnAMD, PCV and RAM groups.

Initially selected treatments in eyes with SMH in tnAMD, PCV and RAM groups.</p