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Internationally marine ecosystem-based management has been embraced as an approach to design holistic marine management regimes. In this article a comparative research strategy is applied in the analysis of the holistic marine management regimes in Norway, Australia, US, Canada and the European Union. How can holistic marine management regimes based on an ecosystem approach contribute to sustainable ocean development? Important in this context is how the origin and theory of an ecosystem-based management is implemented and interpreted, and to what extent this is manifested through policies, strategies and legal frameworks. The results of this research indicate that the implementation of marine-ecosystem based management is heterogeneous. This article discusses the concrete mechanisms that are used to reach the aim of sustainable ocean management. Implementation challenges are related to lack of functional metrics, weak spatial measures, weak integration and lack of adaptive management. Still marine ecosystem-based management is an important step forward for sustainable ocean governance. [ABSTRACT FROM AUTHOR]

Newborns with prenatal opioid exposure (POE) are commonly diagnosed with neonatal abstinence/opioid-withdrawal syndromes due to characteristic symptoms and overt behaviors. However, little is known about the underlying physiology of opioid-exposed newborns. Cardiac, respiratory and movement activity were measured to identify physiologic dysregulation and quantify pathophysiologic instabilities of the central and autonomic nervous systems in POE newborns. In this pilot study, 30 hospitalized POE newborns (>35 wks gestational age) participated in one of two study phases wherein physiologic activity was measured for an 8-10 h session. In Phase 1, 17 infants received usual treatment to provide a general assessment of physiologic activity. In Phase 2, 13 infants participated in an interventional study (NCT02768844) using a prototype mattress that delivered stochastic vibratory stimulation (SVS). Changes in physiologic activity were compared for device on (N) and off (F) for three interfeed periods (FNF or NFN). Phase 1 showed that although infants' heart rate was on average within normal newborn range (mean 137 bpm, SD 7), infants were tachycardic 16% of the study period and tachypneic (mean 74 breaths/min, SD 13) 62% of the period. Infants moved 33% of the period; 17% were durations >30 s. In Phase 2, heart rate, respiratory rate, movement duration and frequency were each reduced for SVS N compared to SVS F in the FNF protocol (P < 0.05). Findings support that physiologic measures can identify dysregulation not captured with current withdrawal scoring assessments. Larger studies are warranted to assess if mattress SVS helps regulate pathophysiologic instabilities in infants with POE. • Little is known about underlying physiology in opioid-exposed newborns. • Conventional assessments do not capture physiologic dysregulation. • This study identified dysregulation using cardiac and respiratory measures. • Movement activity was used to quantify infant irritability versus calm. • A prototype vibrating mattress reduced pathophysiologic dysregulation. [ABSTRACT FROM AUTHOR]

Voltage-dependent potassium (Kv) channels are tetramers of six transmembrane domain (S1-S6) proteins. Crystallographic data demonstrate that the tetrameric pore (S5-S6) is surrounded by four voltage sensor domains (S1-S4). One key question remains: how do voltage sensors (S4) regulate pore gating? Previous mutagenesis data obtained on the Kv channel KCNQ1 highlighted the critical role of specific residues in both the S4-S5 linker (S4S5L) and S6 C terminus (S6T). From these data, we hypothesized that S4S5L behaves like a ligand specifically interacting with S6T and stabilizing the closed state. To test this hypothesis, we designed plasmid-encoded peptides corresponding to portions of S4S5L and S6T of the voltage-gated potassium channel KCNQ1 and evaluated their effects on the channel activity in the presence and absence of the ancillary subunit KCNE1. We showed that S4S5L peptides inhibit KCNQ1, in a reversible and state-dependent manner. S4S5L peptides also inhibited a voltage-independent KCNQ1 mutant. This inhibition was competitively prevented by a peptide mimicking S6T, consistent with S4S5L binding to S6T. Val254 in S4S5L is known to contact Leu353 in S6T when the channel is closed, and mutations of these residues alter the coupling between the two regions. The same mutations introduced in peptides altered their effects, further confirming S4S5L binding to S6T. Our results suggest a mechanistic model in which S4S5L acts as a voltage-dependent ligand bound to its receptor on S6 at rest. This interaction locks the channel in a closed state. Upon plasma membrane depolarization, S4 pulls S4S5L away from S6T, allowing channel opening. [ABSTRACT FROM AUTHOR]

The transbilayer diffusion of unlabeled ceramides with different acyl chains (C6-Cer, C10-Cer, and C16-Cer) was investigated in giant unilamellar vesicles (GUVs) and in human erythrocytes. Incorporation of a very small percentage of ceramides (∼0.1% of total lipids) to the external leaflet of egg phosphatidylcholine GUVs suffices to trigger a shape change from prolate to pear shape vesicle. By observing the reversibility of this shape change the transmembrane diffusion of lipids was inferred. We found a half-time for unlabeled ceramide flip-flop below 1 min at 37 °C. The rapid diffusion of ceramides in a phosphatidylcholine bilayer was confirmed by flip-flop experiments with a spin-labeled ceramide analogue incorporated into large unilamellar vesicles. Shape change experiments were also carried out with human erythrocytes to determine the trans-membrane diffusion of unlabeled ceramides into a biological membrane. Addition of exogenous ceramides to the external leaflet of human erythrocytes did not trigger echinocyte formation immediately as one would anticipate from an asymmetrical accumulation of new amphiphiles in the outer leaflet but only after ∼15 min of incubation at 20 °C in the presence of an excess of ceramide. We interpret these data as being indicative of a rapid ceramide equilibration between both erythrocyte leaflets as indicated also by electron spin resonance spectroscopy with a spin-labeled ceramide. The late appearance of echinocytes could reveal a progressive trapping of a fraction of the ceramide molecules in the outer erythrocytes leaflet. Thus, we cannot exclude the trapping of ceramides into plasma membrane domains. [ABSTRACT FROM AUTHOR]

• Provides a novel online predictive model of aircraft landing performance using data collected on-board an aircraft during the approach phase. • Demonstrates accurate prediction of the critical metrics further ahead in time than existing approaches and at a higher accuracy. • Introduces innovations in generating feature vectors and target labels using a flexible approach that can be easily replicated for other metrics of interest. • Significantly improves over previous similar work in literature both in terms of accuracy and applicability in an online setting. In recent years, due to the increased availability of data and improvements in computing power, application of machine learning techniques to various aviation safety problems for identifying, isolating, and reducing risk has gained momentum. Data collected from on-board recorders in commercial aircraft contain thousands of parameters in the form of multivariate time-series (continuous, discrete, categorical, etc.) which are used to train the machine learning models. Among the phases of flight, approach and landing phases result in the most accidents and incidents. The performance and trajectory of the aircraft during the approach phase is an indicator of its landing performance which, in turn, affects incident or accident probability such as runway excursions. Landing performance is commonly measured using metrics such as landing airspeed, vertical speed, location of touchdown point on runway, etc. While current applications of machine learning to aviation focus on retrospective insights to implement corrective measures, they offer limited value for real-time risk identification or decision-making as they are inherently reactive in nature. In this work, a novel offline-online framework is developed for building a global predictive model offline to predict landing performance metrics online. The framework leverages flight data from the approach phase between certain approach altitudes (also called gates) in order to train the offline model to predict the landing true airspeed and ground speed using a Random Forest regression algorithm. Permutation importance is used to identify and retain important features among those available and the training data is balanced with respect to flight safety events to ensure a good performing model. The developed global model is robust and can predict landing true airspeed and ground speed with root mean square errors of 2.62 and 2.98 knots respectively over six different airframes operating at over seventy airports. The model operates fast in prediction mode which, coupled with the ability to provide the prediction at an altitude where a go-around decision may be made, makes it particularly suitable for online application. The framework is demonstrated using data obtained from commercial airline operations that contains thousands of flight records and performs better than existing techniques in literature at predicting true airspeed and ground speed at touchdown. [ABSTRACT FROM AUTHOR]

Abstract: The explosion sensitivity of various gas or vapor/dust mixtures has been studied thanks to specifically modified apparatuses based on a 20L sphere and a Hartmann tube. Experiments have shown that concentration of gas/vapors as low as 1% vol. causes a significant decrease of the minimum ignition energy and induces changes in the rate-limiting step of the combustion reaction, from boundary diffusion to homogeneous gas phase reaction. They also confirm that a hybrid mixture explosion is possible even when both dust and vapor concentrations are respectively lower than their minimum explosion concentration and lower explosivity limit. Comparisons have been done between our experimental data and classical models such as those developed by Bartknecht or Le Chatelier. It appears that these laws are not always conservative from a safety point of view. The influences of the diameter, of the adiabatic flame temperatures and of the critical ignition kernel, directly related to the quenching distance, have also been highlighted. This work demonstrates the peculiar behavior of gas or vapor/dust explosions and proposes simple models in order to estimate their ignition sensitivity. [Copyright &y& Elsevier]