Comparing perceived effects of climate-related environmental change and adaptation strategies for the Pacific small island states of Tuvalu, Samoa, and Tonga

Inhabitants of Pacific small island states are facing multiple socio-ecological pressures, with climate change being one of the most prominent. Nevertheless, the agency of local stakeholders in decisions on how to adapt to climate-related environmental change has been largely underappreciated in the climate change sciences as well as in policy decisions. We, therefore, conducted a survey study in Tuvalu, Samoa, and Tonga, asking specifically how residents perceive their situation regarding climate-related challenges, what adaptation strategies they have devised and implemented, and what they expect of governmental and nongovernmental organisations in these efforts. In contrast to the common perception that Pacific small island states are primarily threatened by rising sea levels, residents’ perceptions indicate that drought, cyclones and other flood-related problems pose a far more imminent danger. Our results suggest that further research on those perceived environmental changes is advisable to provide reliable data for scientific models and policy decisions

Perception of Climate Change in a Pacific Island City

According to the International Panel on Climate Change (IPCC 2007) small island states (SIS) will be severely affected by global climate change. Especially a rising sea level, increased frequency and intensity of extreme weather events and rising temperature will have serious impact on life on small islands in tropical regions. SIS hardly contribute to the emission of greenhouse gases, therefore their main challenge will be focussing on adaptation to prevent further damages

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Intelligent Vehicle Complex Environment Path Following Capabilities, Based on a Telemetry Sensor Fusion Approach, Utilizing Open Loop Navigation

Intelligent Vehicles (IVs) present an emerging sector of automotive technology development. This study explores a specific subset of IV control logic known as path following. Complex environments, such as roadway intersections, present a significant challenge to autonomous navigation, due to the many non-standard permutations. This research sought to quantify the accuracy with which an IV could follow a set path, through a complex environment, without the aid of environmental sensors. This required the vehicle to utilize only onboard telemetry sensors to determine its relative global location in free space, and subsequently execute a move through it. The results validated the hypothesis, that an IV could follow a path, as described, with reasonable accuracy, for short distances. The vehicle navigated a 1:4.5 scale version of a complex intersection in Statesboro, GA, while maintaining effective lane tracking through four permutations of turns from the main avenue. This was accomplished by using a reverse kinematic telemetry sensor fusion approach, which leveraged the relative strengths and weaknesses of real-time processing, inertial measurement, and individual wheel speed

Telemetry Based Location Sensor Fusion and Error Correction in Intelligent Vehicles

Intelligent vehicle navigation systems rely on accurate and timely sensor input to determine a vehicle‰Ûªs location, attitude, speed, and acceleration. External sensors provide the primary guidance data required to determine a vehicle\u27s current and planned location, as well as path planning data, relative to the environment around the vehicle. This paper describes a telemetry sensor fusion approach, which enables an intelligent vehicle to navigate, over short distances, based on previously planned paths and near field sensors. This reduces computational overhead on the vehicle\u27s computer, and provides real time redundancy for system errors or delays. In conjunction with a full compliment of environmental sensors, this path planning - path following approach enhances the robustness of intelligent vehicle operating models. Simulation validated by small-scale tests indicates that telemetry sensor fusion provides a viable method for short distance navigation, based on pre-planned paths. This research supports the rapidly expanding field of intelligent automobiles by examining novel concepts for robust telemetry sensor fusion, which allows for error correction and enhanced positional accuracy, when compared to conventional navigation algorithms. This concept will improve the safety and performance of autonomous vehicles by providing path following methods which enable obstacle avoidance and navigation through complex environments. Research methods include simulation, small-scale modeling, and meso-scale application testing. Sensor fusion algorithms were created which enable the fusion of multiple on board telemetry sensors to determine the vehicle localization and trajectory, with sufficient accuracy to navigate complex planned paths. Small scale tests validated the sensor fusion algorithms developed, and ongoing meso-scale testing enables human machine interaction on

Comparing perceptions of climate - related environmental changes for Tuvalu, Samoa, and Tonga

Individual perceptions of climate-related environmental changes are essential to understand behavioural responses to such changes. Despite several studies on change-perception in single Pacific Small Island States (PSIS), the variance in these perceptions within and between different PSIS has so far largely been neglected. We, therefore, explored perceptions of climate-related environmental changes and attributed causes in Tuvalu, Samoa, and Tonga. Our survey (N=180) shows that perceptions of environmental changes vary considerably between the three island states and also within each country. A certain fraction of this variance can be explained by (i) geographical and climatic differences between the island states and (ii) selected socio-demographic variables. The socio-demographic factors that proved most relevant include (i) the size of the settlement in which respondents live, (ii) their distance to the sea, (iii) their interaction with nature, and (iv) their self-assessment of their own religiosity. Moreover, we found that people attribute reported changes to manifold irresponsible and unsustainable human behaviours, and to a lesser extent to natural processes and divine acts. By illustrating the variance of perceptions and also the awareness of anthropogenic causes, the study helps to communicate the diversity of local voices and offers ways for finding a basis for discussing and implementing more sustainable behaviour alternatives

FROM SENSOR TO STREET – INTELLIGENT VEHICLE CONTROL SYSTEMS

The future of automotive engineering lies in intelligent vehicles. The combined effects of multiple intelligent sub-systems will provide drivers with essential feedback to increase driving safety and reduce fuel wasted in unnecessary acceleration and inefficient traffic routing. Discrete intelligent sub-systems have been increasingly incorporated into consumer vehicles for decades, and continue to evolve. The revolutionary next step in development is fully integrating intelligent capabilities into a total vehicle control system. This may be accomplished through a multilevel control architecture, starting with sensor fusion. Fused sensors, such as LIDAR and RADAR, will provide their inputs to a single virtual model from which a control computer may plot an optimum trajectory. Fully informed of the environment immediately surrounding the vehicle, a trajectory following the road and traffic controls will be plotted. As the vehicle follows this path, its sensors continually update the virtual model and provide obstacle avoidance and updated guidance information. Finally, a reverse kinematic approach, applied to a fully electric drivetrain, will enable the vehicle to respond to its driving environment, and compensate for unknown conditions. If an emergency maneuver becomes necessary, the optimal combination of brake and steering application will be computed to prevent loss of control

DIVISIBILITY OF AN EIGENFORM BY AN EIGENFORM

Abstract. It has been shown in several settings that the product of two eigenforms is rarely an eigenform. In this paper we consider the more general question of when the product of an eigenform with any modular form is again an eigenform. We prove that this can occur only in very special situations. We then relate the divisibility of eigenforms to linear independence of vectors of Rankin-Selberg L-values

A dried blood spot protocol for high throughput analysis of SARS-CoV-2 serology based on the Roche Elecsys anti-N assay

Beyerl J, Rubio-Acero R, Castelletti N, et al. A dried blood spot protocol for high throughput analysis of SARS-CoV-2 serology based on the Roche Elecsys anti-N assay. EBioMedicine. 2021;70: 103502