Tropical forest and peatland conservation in Indonesia: Challenges and directions

1. Tropical forests and peatlands provide important ecological, climate and socio‐economic benefits from the local to the global scale. However, these ecosystems and their associated benefits are threatened by anthropogenic activities, including agricultural conversion, timber harvesting, peatland drainage and associated fire. Here, we identify key challenges, and provide potential solutions and future directions to meet forest and peatland conservation and restoration goals in Indonesia, with a particular focus on Kalimantan. 2.Through a round‐table, dual‐language workshop discussion and literature evaluation, we recognized 59 political, economic, legal, social, logistical and research challenges, for which five key underlying factors were identified. These challenges relate to the 3Rs adopted by the Indonesian Peatland Restoration Agency (Rewetting, Revegetation and Revitalization), plus a fourth R that we suggest is essential to incorporate into (peatland) conservation planning: Reducing Fires. 3.Our analysis suggests that (a) all challenges have potential for impact on activities under all 4Rs, and many are inter‐dependent and mutually reinforcing, implying that narrowly focused solutions are likely to carry a higher risk of failure; (b) addressing challenges relating to Rewetting and Reducing Fire is critical for achieving goals in all 4Rs, as is considering the local socio‐political situation and acquiring local government and community support; and (c) the suite of challenges faced, and thus conservation interventions required to address these, will be unique to each project, depending on its goals and prevailing local environmental, social and political conditions. 4.With this in mind, we propose an eight‐step adaptive management framework, which could support projects in both Indonesia and other tropical areas to identify and overcome their specific conservation and restoration challenges.Biotechnology and Biosciences Research Council; Borneo Nature Foundatio

Quality Measures for the Diagnosis and Non-Operative Management of Carpal Tunnel Syndrome in Occupational Settings

Introduction: Providing higher quality medical care to workers with occupationally associated carpal tunnel syndrome (CTS) may reduce disability, facilitate return to work, and lower the associated costs. Although many workers’ compensation systems have adopted treatment guidelines to reduce the overuse of unnecessary care, limited attention has been paid to ensuring that the care workers do receive is high quality. Further, guidelines are not designed to enable objective assessments of quality of care. This study sought to develop quality measures for the diagnostic evaluation and non-operative management of CTS, including managing occupational activities and functional limitations. Methods: Using a variation of the well-established RAND/UCLA Appropriateness Method, we developed draft quality measures using guidelines and literature reviews. Next, in a two-round modified-Delphi process, a multidisciplinary panel of 11 U.S. experts in CTS rated the measures on validity and feasibility. Results: Of 40 draft measures, experts rated 31 (78%) valid and feasible. Nine measures pertained to diagnostic evaluation, such as assessing symptoms, signs, and risk factors. Eleven pertain to non-operative treatments, such as the use of splints, steroid injections, and medications. Eleven others address assessing the association between symptoms and work, managing occupational activities, and accommodating functional limitations. Conclusions: These measures will complement existing treatment guidelines by enabling providers, payers, policymakers, and researchers to assess quality of care for CTS in an objective, structured manner. Given the characteristics of previous measures developed with these methods, greater adherence to these measures will probably lead to improved patient outcomes at a population level

Tropical forest and peatland conservation in Indonesia: Challenges and directions

Tropical forests and peatlands provide important ecological, climate and socio‐economic benefits from the local to the global scale. However, these ecosystems and their associated benefits are threatened by anthropogenic activities, including agricultural conversion, timber harvesting, peatland drainage and associated fire. Here, we identify key challenges, and provide potential solutions and future directions to meet forest and peatland conservation and restoration goals in Indonesia, with a particular focus on Kalimantan. Through a round‐table, dual‐language workshop discussion and literature evaluation, we recognized 59 political, economic, legal, social, logistical and research challenges, for which five key underlying factors were identified. These challenges relate to the 3Rs adopted by the Indonesian Peatland Restoration Agency (Rewetting, Revegetation and Revitalization), plus a fourth R that we suggest is essential to incorporate into (peatland) conservation planning: Reducing Fires. Our analysis suggests that (a) all challenges have potential for impact on activities under all 4Rs, and many are inter‐dependent and mutually reinforcing, implying that narrowly focused solutions are likely to carry a higher risk of failure; (b) addressing challenges relating to Rewetting and Reducing Fire is critical for achieving goals in all 4Rs, as is considering the local socio‐political situation and acquiring local government and community support; and (c) the suite of challenges faced, and thus conservation interventions required to address these, will be unique to each project, depending on its goals and prevailing local environmental, social and political conditions. With this in mind, we propose an eight‐step adaptive management framework, which could support projects in both Indonesia and other tropical areas to identify and overcome their specific conservation and restoration challenges

Pre-clinical imaging of transgenic mouse models of neuroblastoma using a dedicated 3-element solenoid coil on a clinical 3T platform.

Background The use of clinical MRI scanners to conduct pre-clinical research facilitates comparisons with clinical studies. Here the utility and sensitivity of anatomical and functional MRI data/biomarkers acquired from transgenic mouse models of neuroblastoma using a dedicated radiofrequency (RF) coil on a clinical 3T scanner was evaluated.Methods Multiparametric MRI of transgenic mice bearing abdominal neuroblastomas was performed at 3T, and data cross-referenced to that acquired from the same mice on a pre-clinical 7T MRI system. T2-weighted imaging, quantitation of the native longitudinal relaxation time (T1) and the transverse relaxation rate (R2*), and dynamic contrast-enhanced (DCE)-MRI, was used to assess tumour volume, phenotype and response to cyclophosphamide or cabozantinib.Results Excellent T2-weighted image contrast enabled clear tumour delineation at 3T. Significant correlations of tumour volume (R=0.98, P2* (R=0.87, P2* (Ptrans for each tumour (median Ktrans values of 0.202, 0.168 and 0.114 min-1). Cyclophosphamide elicited a significant reduction in both tumour burden (P1 (P<0.01), whereas cabozantinib induced significant (P<0.01) tumour growth delay.Conclusions Simultaneous multiparametric MRI of multiple tumour-bearing animals using this coil arrangement at 3T can provide high efficiency/throughput for both phenotypic characterisation and evaluation of novel therapeutics, and facilitate the introduction of functional MRI biomarkers into aligned imaging-embedded clinical trials

Applying simulation optimization to dynamic financial analysis for the asset-liability management of a property-casualty insurer

The Dynamic Financial Analysis (DFA) system is a useful decision-support system for the insurer, but it lacks optimization capability. This article applies a simulation optimization technique to a DFA system and use the enhanced system to search an Asset-Liability Management (ALM) solution for a Property-Casualty (P&C) insurance company. The simulation optimization technique used herein is a Genetic Algorithm (GA), and the optimization problem is a constrained, multi-period asset allocation problem that takes account of insurance liability dynamics. We find that coupling a DFA system with simulation optimization results in significant improvements over the search method currently available to the DFA system. The results were robust across random number sets. Furthermore, the resulting asset allocations changes with the asset-liability setting in a way that is consistent with the differences in the settings. Applying simulation optimization to a DFA system is therefore promising.