FIREFIGHTS AND FUEL MANAGEMENT: A NESTED ROTATION MODEL FOR WILDFIRE RISK MITIGATION

Scientists and policymakers are increasingly aware that wildfire management efforts should be broadened beyond the century-long emphasis on suppression to include more effective efforts at fuel management. Because wildfire risks change over time as vegetation matures, fuel management can be viewed as a timing problem, much like timber harvest itself. We develop a nested rotation model to examine the fuel treatment timing issue in the context of a forest environment with both timber value and non-timber values at-risk. Simulations are performed for a ponderosa pine forest and discussed with a focus on three important aspects of wildfire management: 1) the economic tradeoffs between fuel treatments, suppression, and timber harvest 2) the effects of public wildfire suppression on private fuel management incentives, 3) externality problems when non-timber values-at-risk such as wildland- urban interface property is not accounted for in private fuel management decisions.wildfire, fuels management, fire suppression, optimal rotation, wildfire economics.

An Econometric Model of Wildfire Suppression Productivity

We estimate a model of suppression productivity for individual fires, where suppression productivity is measured in terms of the reduction in the estimated market value of wildfire losses. Estimation results show that at the margin, every dollar increase in suppression costs reduces resource damage by 12 cents, while each dollar invested in pre-suppression reduces suppression expenditures by 3.76 dollars. These results suggest that there is an over-allocation of fire management funds to suppression activities relative to prevention measures in terms of cost-effectiveness. This paper provides an empirical basis for a widely used economic model of wildfire management that seeks to minimize the sum of suppression costs and economic losses from wildfires, the cost plus net value change model of fire suppression (C+NVC).wildfire suppression, productivity

Optimal wildfire insurance in the wildland-urban interface in the presence of a government subsidy for fire risk mitigation

We investigate the effectiveness of a government subsidy and mitigation based insurance contracts at discouraging migration into the wildland interface and at inducing incentives for risk mitigation. We construct a model of the individual migration decision, where the individual maximizes expected utility defined over attributes of locations including cost of insurance and mitigation, wildfire damage, and the availability of a subsidy for reducing wildfire risks through fuel management. Our analysis shows that standard insurance policies provide inefficiently weak incentive for wildfire risk mitigation by offering a low insurance premium to high-risk landowners. We find on the other hand that in the presence of optimal government subsidy, contingent contracts provide an efficient solution where a homeowner chooses a mitigation level that maximizes social benefit and insurers provide actuarially fair contracts such that each individual is offered a premium of the exact value of her wildfire risk.Insurance; Insurance Companies, Government Policy and Regulation, General, Government Policy

Access to Opioids in Palliative Care in Low-and Middle-Income Countries : The Case of Burkina-Faso -How Can Blockchain and Internet of Things Assist? –

Background: People requesting palliative care or suffering from pain are subjected to adhere to opioid-based treatment in order to alleviate their pain. Commonly, access to opioids is strictly controlled. Access to Healthcare delivery services remains challenging in Low-and Middle-Income Countries (LMIC). In Burkina-Faso (BF), a Sub-Saharan African (SSA) country, patients requiring palliative care (PC) are especially facing poor access to pain drugs such as morphine. Facing poor access to pain-alleviating medicine can severely impact the daily quality of life (QoL). On one hand, patients are experiencing poor opioids access. On another hand opioids abuse, leading to drug addiction is noticed. The question arising here is how can they face poor access and at the same time abuse the given drug? One plausible answer is the counterfeit chain, which provides illegal drugs. Beyond the counterfeit issues faced, the public health care system is also facing, amongst others, prescription falsification, fraud in the distribution, and stock shortage. Method & Design:  Mixed-Method-Design was applied to this study. National stipulations, regulations, and the state-of-the-art in the field of palliative care in BF were investigated and analyzed. Based on the investigation‘s outcomes and following the paradigm of design science research, and information system based improvement solution is proposed to tackle the poor access to opioids, improve the supply and distribution chain as well as to efficiently monitor the consumption of opioids in BF, and prevent patients from any health issues, drug addiction, and death. Objectives: The main objectives are to fight against opioid addiction, counterfeits, a stock shortage, and prevent related health safety issues. The main aim is to enable the traceability of any opioids prescription, secure the supply and distribution, and thus early detect any fraud in the system. This editorial paper would, therefore, focus on investigating the reasons underlying the poor access to opioids in palliative care in BF and make suggestions for improvement. A blockchain (BC) and the Internet of Things (IoT) based system to secure and improve opioids supply, distribution, and prescription will be proposed. Results: The contribution analysis reveals the potential of the proposed model to assist in many ways to improve access to opioids and to secure this access. The model could contribute to preventing drug abuse, overprescription, supporting off-label-use of opioids and thus providing a knowledge database for off-label use of opioids. This model shows promise to deliver accurate data and information about the exact opioid’s needs and consumption atlas. This will assist to better distribute the product in the entire country. A proof-of-concept of the proposed model is required. This is ongoing and will be presented in a forthcoming paper. Conclusion: This editorial paper investigates access to opioids in Burkina Faso. It pointed out by analyzing out the computer science perspectives the different causes of the crisis. A contextualized model is provided. A test in situ needs to be performed

Speckle noise modeling and reduction of SAR Images based Markov random fields

One of the major factors plaguing the performance of synthetic aperture radar (SAR) imagery is the signal-dependent, speckle noise. Grainy in appearance, it is due to the phase fluctuations of the electromagnetic returned signals. Since the inherent spatial-correlation characteristics of speckle in SAR images are not embedded in the multiplicative models for speckle noise, a new mathematical framework for modeling speckled imagery is introduced. It is based on embedding the spatial correlation properties of speckled imagery, obtained from statistical optics, into a Markov-random-field (MRF) framework. The model is then used to perform speckle-noise reduction through the utilization of a global energy-minimization algorithm, which consists of simulated annealing in conjunction with the Metropolis sampler algorithm. A comparative study using both simulations and real SAR images indicates that the proposed approach performs better compared to filtering techniques such as the Gamma Map, the modified-Lee and the enhanced-Frost algorithms. This success is attributable to the ability of the proposed model to capture the physical spatial statistics of speckle within the confines of a MRF framework

Speckle Reduction of SAR Images Based on a Combined Markov Random Field and Statistical Optics Approach (Version1)

One of the major factors plaguing the performance of synthetic aperture radar (SAR) imagery is the presence of signal-dependent, speckle noise. Grainy in appearance, speckle noise is primarily due to the phase fluctuations of the electromagnetic returned signals. Since the inherent spatial-correlation characteristics of speckle in SAR images are not exploited in existing multiplicative models for speckle noise, a new approach is proposed here that provides a new mathematical framework for modeling and mitigation of speckle noise. The contribution of this paper is twofold. First, a novel model for speckled SAR imaging is introduced based on Markov random fields (MRFs) in conjunction with statistical optics. Second, utilizing the model, a global energy-minimization algorithm based on simulated annealing (SA), is introduced for speckle reduction. In particular, the joint conditional probability density function (cpdf) of the intensity of any two points in the speckled image and the associated correlation function are used to derive the cpdf of any center pixel intensity given its four neighbors. The Hammersley-Clifford theorem is then used to derive the energy function associated with the MRF. The SA, built on the Metropolis sampler, is employed for speckle reduction. Four metrics are used to assess the quality of the speckle reduction: the mean-square error, SNR, an edge-preservation parameter and the equivalent number of looks. A comparative study using both simulations and real SAR images indicates that the proposed approach performs better in comparison to filtering techniques such as the Gamm Map, the modified Lee and the enhanced Frost algorithms

Inhospital Outcome of Elderly Patients in an Intensive Care Unit in a Sub-Saharan Hospital

People living more and more longer and elderly is growing and that requires change in health system including geriatric care to be innovative. The aim of this study was to analyze causes and prognosis of older patients admitted in an intensive care unit (ICU) in Sub-Sahara area. A retrospective study over 5 years of patients aged 65 years and above admitted in ICU of Yalgado Ouedraogo was carried out. Of the 2116 patients admitted in ICU, 237 (11.2%) were older. The mean age was 71.7 ± 6.1 years. Males were predominant (sex ratio = 2.4). Medical history was present in 80.6%. The Charlson mean score was 4.8 ± 1.8. Patients with coma represented 42%. Ambulatory Simplified Acute Physiologic Score (ASAPS) up to 8 was recorded in 49%. Medical diseases (60%) like nervous system (37.9%) were reported. Stroke and general surgery were the main affection. Globally treatment was based on fluid management and oxygen supply. During ICU stay, complications occurred in 37.5% like acute respiratory distress syndrome (ARDS) in 10.5%. The mean length of stay was 5.3 ± 7.4 days. The elderly mortality was 73%; those 90% died within 7 days. In multivariate analysis, shock (odds ratio: OR = 2.2, p = 0.002), severe brain trauma (OR = 9.6, p = 0.002), coma (OR 5.8 p < 0.003), surgical condition (OR = 4.2, p = 0.003), ASAPS ≥ 8 (OR = 4.3, p = 0.001), complication occurring (OR = 5.2, p = 0.001), and stroke (OR = 3.7, p = 0.001) were independent risk factors of death. Elderly patients are frequently admitted in ICU with high mortality