Mass casualty incident after the Taba terrorist attack: an organisational and medical challenge

Two suicide bombings in and around Taba, Egypt, on 7 October 2004 created a complex medical and organisational situation. Since most victims were Israeli tourists, the National Emergency and Disaster Management Division handled their evacuation and treatment. This paper describes the event chronologically, as well as the organisational and management challenges confronted and applied solutions. Forty-nine emergency personnel and physicians were flown early to the disaster area to reinforce scarce local medical resources. Two hundred casualties were recorded: 32 dead and 168 injured. Eilat hospital was transformed into a triage facility. Thirty-two seriously injured patients were flown to two remote trauma centres in central Israel. Management of mass casualty incidents is difficult when local resources are inadequate. An effective response should include: rapid transportation of experienced trauma teams to the disaster zone; conversion of local medical amenities into a triage centre; and rapid evacuation of the seriously injured to higher level medical facilities.     

Earth stewardship: Shaping a sustainable future through interacting policy and norm shifts

Transformation toward a sustainable future requires an earth stewardship approach to shift society from its current goal of increasing material wealth to a vision of sustaining built, natural, human, and social capital—equitably distributed across society, within and among nations. Widespread concern about earth’s current trajectory and support for actions that would foster more sustainable pathways suggests potential social tipping points in public demand for an earth stewardship vision. Here, we draw on empirical studies and theory to show that movement toward a stewardship vision can be facilitated by changes in either policy incentives or social norms. Our novel contribution is to point out that both norms and incentives must change and can do so interactively. This can be facilitated through leverage points and complementarities across policy areas, based on values, system design, and agency. Potential catalysts include novel democratic institutions and engagement of non-governmental actors, such as businesses, civic leaders, and social movements as agents for redistribution of power. Because no single intervention will transform the world, a key challenge is to align actions to be synergistic, persistent, and scalable.     

Recognizing animal personhood in compassionate conservation

Compassionate conservation is based on the ethical position that actions taken to protect biodiversity should be guided by compassion for all sentient beings. Critics argue that there are 3 core reasons harming animals is acceptable in conservation programs: the primary purpose of conservation is biodiversity protection; conservation is already compassionate to animals; and conservation should prioritize compassion to humans. We used argument analysis to clarify the values and logics underlying the debate around compassionate conservation. We found that objections to compassionate conservation are expressions of human exceptionalism, the view that humans are of a categorically separate and higher moral status than all other species. In contrast, compassionate conservationists believe that conservation should expand its moral community by recognizing all sentient beings as persons. Personhood, in an ethical sense, implies the individual is owed respect and should not be treated merely as a means to other ends. On scientific and ethical grounds, there are good reasons to extend personhood to sentient animals, particularly in conservation. The moral exclusion or subordination of members of other species legitimates the ongoing manipulation and exploitation of the living worlds, the very reason conservation was needed in the first place. Embracing compassion can help dismantle human exceptionalism, recognize nonhuman personhood, and navigate a more expansive moral space.     

Climate change adaptation and mitigation in smallholder crop–livestock systems in sub-Saharan Africa: a call for integrated impact assessments

African mixed crop–livestock systems are vulnerable to climate change and need to adapt in order to improve productivity and sustain people’s livelihoods. These smallholder systems are characterized by high greenhouse gas emission rates, but could play a role in their mitigation. Although the impact of climate change is projected to be large, many uncertainties persist, in particular with respect to impacts on livestock and grazing components, whole-farm dynamics and heterogeneous farm populations. We summarize the current understanding on impacts and vulnerability and highlight key knowledge gaps for the separate system components and the mixed farming systems as a whole. Numerous adaptation and mitigation options exist for crop–livestock systems. We provide an overview by distinguishing risk management, diversification and sustainable intensification strategies, and by focusing on the contribution to the three pillars of climate-smart agriculture. Despite the potential solutions, smallholders face major constraints at various scales, including small farm sizes, the lack of response to the proposed measures and the multi-functionality of the livestock herd. Major institutional barriers include poor access to markets and relevant knowledge, land tenure insecurity and the common property status of most grazing resources. These limit the adoption potential and hence the potential impact on resilience and mitigation. In order to effectively inform decision-making, we therefore call for integrated, system-oriented impact assessments and a realistic consideration of the adoption constraints in smallholder systems. Building on agricultural system model development, integrated impact assessments and scenario analyses can inform the co-design and implementation of adaptation and mitigation strategies.F     

Microarray testing for the presence of toxic algae monitoring programme in Galicia (NW Spain)

Rapid and reliable detection of harmful algae in coastal areas and shellfish farms is an important requirement of monitoring programmes. Monitoring of toxic algae by means of traditional methods, i.e., light microscopy, can be time consuming when many samples have to be routinely analysed. Reliable species identification requires expensive equipment and trained personnel to carry out the analyses. However, all techniques for the monitoring of harmful algae usually require transportation of samples to specialised laboratories. In many monitoring laboratories, results are usually obtained within five working days after receiving the sample and therefore preventative measures are not always possible. Molecular technologies are rapidly improving the detection of phytoplankton and their toxins and the speed at which the results can be obtained. Assays are based on the discrimination of the genetic differences of the different species and species-specific probes can be designed. Such probes have been adapted to a microarray or phylochip format and assessed in several EU monitoring sites. Microarray results are presented for 1 year of field samples validated with cell counts from concentrated samples taken during toxic events from the weekly sampling of the Galician Monitoring Programme done by INTECMAR. The Galician monitoring laboratory does their own counting and their results are posted on their web site within 24 h. There was good correlation between cells present and microarray signals. In the few cases of false negatives, these can be attributed to poor RNA extraction of the target species, viz. Prorocentrum or Dinophysis. Where potential false positives were encountered, the smaller volume taken for cell counts as compared to the upto 300 times more volume taken for RNA extraction for the microarray is likely the cause for these differences, making the microarray more sensitive. The microarray was able to provide better species resolution in Alexandrium and Pseudo-nitzschia. In all cases, the toxins recovered by the toxin array were matched by target species in the array or in the cell counts.     

Fuzzy logic and adaptive neuro-fuzzy inference system for characterization of contaminant exposure through selected biomarkers in African catfish

This study represents a first attempt at applying a fuzzy inference system (FIS) and an adaptive neuro-fuzzy inference system (ANFIS) to the field of aquatic biomonitoring for classification of the dosage and time of benzo[a]pyrene (BaP) injection through selected biomarkers in African catfish (Clarias gariepinus). Fish were injected either intramuscularly (i.m.) or intraperitoneally (i.p.) with BaP. Hepatic glutathione S-transferase (GST) activities, relative visceral fat weights (LSI), and four biliary fluorescent aromatic compounds (FACs) concentrations were used as the inputs in the modeling study. Contradictory rules in FIS and ANFIS models appeared after conversion of bioassay results into human language (rule-based system). A “data trimming” approach was proposed to eliminate the conflicts prior to fuzzification. However, the model produced was relevant only to relatively low exposures to BaP, especially through the i.m. route of exposure. Furthermore, sensitivity analysis was unable to raise the classification rate to an acceptable level. In conclusion, FIS and ANFIS models have limited applications in the field of fish biomarker studies.     

Investigation of hit-and-run crash occurrence and severity using real-time loop detector data and hierarchical Bayesian binary logit model with random effects

Objective: Most of the extensive research dedicated to identifying the influential factors of hit-and-run (HR) crashes has utilized typical maximum likelihood estimation binary logit models, and none have employed real-time traffic data. To fill this gap, this study focused on investigating factors contributing to HR crashes, as well as the severity levels of HR.

Methods: This study analyzed 4-year crash and real-time loop detector data by employing hierarchical Bayesian models with random effects within a sequential logit structure. In addition to evaluation of the impact of random effects on model fitness and complexity, the prediction capability of the models was examined. Stepwise incremental sensitivity and specificity were calculated and receiver operating characteristic (ROC) curves were utilized to graphically illustrate the predictive performance of the model.

Results: Among the real-time flow variables, the average occupancy and speed from the upstream detector were observed to be positively correlated with HR crash possibility. The average upstream speed and speed difference between upstream and downstream speeds were correlated with the occurrence of severe HR crashes. In addition to real-time factors, other variables found influential for HR and severe HR crashes were length of segment, adverse weather conditions, dark lighting conditions with malfunctioning street lights, driving under the influence of alcohol, width of inner shoulder, and nighttime.

Conclusions: This study suggests the potential traffic conditions of HR and severe HR occurrence, which refer to relatively congested upstream traffic conditions with high upstream speed and significant speed deviations on long segments. The above findings suggest that traffic enforcement should be directed toward mitigating risky driving under the aforementioned traffic conditions. Moreover, enforcement agencies may employ alcohol checkpoints to counter driving under the influence (DUI) at night. With regard to engineering improvements, wider inner shoulders may be constructed to potentially reduce HR cases and street lights should be installed and maintained in working condition to make roads less prone to such crashes.     

Male aggression varies with consortship rate and habitat in a dolphin social network

Behavioral Ecology and Sociobiology - In many species, outcomes of male duels determine access to females and, ultimately, male reproductive success. Ritualization of behavior in male contests can...