Analysis of vibration based windmill coupled micromachined energy harvester

The present work exploits the centripetal, Coriolis and Euler forces generated in a rotating windmill. The MEMS device is placed on the blade of a windmill to harvest the energy. Modal analysis is carried out to optimize the dimensions of the structure to match the desired conditions. The real time response of the structure and the voltage generated in the piezoelectric layer are evaluated using transient analysis. It was noticed that Euler and Coriolis forces have a significant contribution in the initial time when the wind turbine accelerates from rest. The later portion is dominated by the Coriolis and Euler forces, and in some instances they cancel out each other. However, there is always a steady contribution from the centripetal force which is proportional to the magnitude of angular velocity of the wind turbine

Control Barrier Functions in UGVs for Kinematic Obstacle Avoidance: A Collision Cone Approach

In this paper, we propose a new class of Control Barrier Functions (CBFs) for Unmanned Ground Vehicles (UGVs) that help avoid collisions with kinematic (non-zero velocity) obstacles. While the current forms of CBFs have been successful in guaranteeing safety/collision avoidance with static obstacles, extensions for the dynamic case with torque/acceleration-controlled unicycle and bicycle models have seen limited success. Moreover, with these nonholonomic UGV models, applications of existing CBFs have been conservative in terms of control, i.e., steering/thrust control has not been possible under certain common scenarios. Drawing inspiration from the classical use of collision cones for obstacle avoidance in path planning, we introduce its novel CBF formulation with theoretical guarantees on safety for both the unicycle and bicycle models. The main idea is to ensure that the velocity of the obstacle w.r.t. the vehicle is always pointing away from the vehicle. Accordingly, we construct a constraint that ensures that the velocity vector always avoids a cone of vectors pointing at the vehicle. The efficacy of this new control methodology is experimentally verified on the Copernicus mobile robot. We further extend it to the bicycle model and demonstrate collision avoidance under various scenarios in the CARLA simulator.Comment: Submitted to 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 8 pages, 8 figures, For supplement video follow https://youtu.be/4qWYaWEPduM. The first and second authors have contributed equall

Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions

Background: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. Objective: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. Methods: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. Results: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. Discussion: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice

Disease Gene Characterization through Large-Scale Co-Expression Analysis

In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET).Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2) and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis

Epidemiology of intra-abdominal infection and sepsis in critically ill patients: “AbSeS”, a multinational observational cohort study and ESICM Trials Group Project

Purpose: To describe the epidemiology of intra-abdominal infection in an international cohort of ICU patients according to a new system that classifies cases according to setting of infection acquisition (community-acquired, early onset hospital-acquired, and late-onset hospital-acquired), anatomical disruption (absent or present with localized or diffuse peritonitis), and severity of disease expression (infection, sepsis, and septic shock). Methods: We performed a multicenter (n = 309), observational, epidemiological study including adult ICU patients diagnosed with intra-abdominal infection. Risk factors for mortality were assessed by logistic regression analysis. Results: The cohort included 2621 patients. Setting of infection acquisition was community-acquired in 31.6%, early onset hospital-acquired in 25%, and late-onset hospital-acquired in 43.4% of patients. Overall prevalence of antimicrobial resistance was 26.3% and difficult-to-treat resistant Gram-negative bacteria 4.3%, with great variation according to geographic region. No difference in prevalence of antimicrobial resistance was observed according to setting of infection acquisition. Overall mortality was 29.1%. Independent risk factors for mortality included late-onset hospital-acquired infection, diffuse peritonitis, sepsis, septic shock, older age, malnutrition, liver failure, congestive heart failure, antimicrobial resistance (either methicillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci, extended-spectrum beta-lactamase-producing Gram-negative bacteria, or carbapenem-resistant Gram-negative bacteria) and source control failure evidenced by either the need for surgical revision or persistent inflammation. Conclusion: This multinational, heterogeneous cohort of ICU patients with intra-abdominal infection revealed that setting of infection acquisition, anatomical disruption, and severity of disease expression are disease-specific phenotypic characteristics associated with outcome, irrespective of the type of infection. Antimicrobial resistance is equally common in community-acquired as in hospital-acquired infection

Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classification

<p>Abstract</p> <p>Background</p> <p>Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of identification and annotation of bimodal genes in the human and mouse genomes. These switch-like genes consist of 15% of known human genes, and are enriched with genes coding for extracellular and membrane proteins. It is of interest to determine the prediction potential of bimodal genes for class discovery in large-scale datasets.</p> <p>Results</p> <p>Use of a model-based clustering algorithm accurately classified more than 400 microarray samples into 19 different tissue types on the basis of bimodal gene expression. Bimodal expression patterns were also highly effective in differentiating between infectious diseases in model-based clustering of microarray data. Supervised classification with feature selection restricted to switch-like genes also recognized tissue specific and infectious disease specific signatures in independent test datasets reserved for validation. Determination of "on" and "off" states of switch-like genes in various tissues and diseases allowed for the identification of activated/deactivated pathways. Activated switch-like genes in neural, skeletal muscle and cardiac muscle tissue tend to have tissue-specific roles. A majority of activated genes in infectious disease are involved in processes related to the immune response.</p> <p>Conclusion</p> <p>Switch-like bimodal gene sets capture genome-wide signatures from microarray data in health and infectious disease. A subset of bimodal genes coding for extracellular and membrane proteins are associated with tissue specificity, indicating a potential role for them as biomarkers provided that expression is altered in the onset of disease. Furthermore, we provide evidence that bimodal genes are involved in temporally and spatially active mechanisms including tissue-specific functions and response of the immune system to invading pathogens.</p

Identification of surgeon burnout via a single-item measure

Background Burnout is endemic in surgeons in the UK and linked with poor patient safety and quality of care, mental health problems, and workforce sustainability. Mechanisms are required to facilitate the efficient identification of burnout in this population. Multi-item measures of burnout may be unsuitable for this purpose owing to assessment burden, expertise required for analysis, and cost. Aims To determine whether surgeons in the UK reporting burnout on the 22-item Maslach Burnout Inventory (MBI) can be reliably identified by a single-item measure of burnout. Methods Consultant (n = 333) and trainee (n = 217) surgeons completed the MBI and a single-item measure of burnout. We applied tests of discriminatory power to assess whether a report of high burnout on the single-item measure correctly classified MBI cases and non-cases. Results The single-item measure demonstrated high discriminatory power on the emotional exhaustion burnout domain: the area under the curve was excellent for consultants and trainees (0.86 and 0.80), indicating high sensitivity and specificity. On the depersonalisation domain, discrimination was acceptable for consultants (0.76) and poor for trainees (0.69). In contrast, discrimination was acceptable for trainees (0.71) and poor for consultants (0.62) on the personal accomplishment domain. Conclusions A single-item measure of burnout is suitable for the efficient assessment of emotional exhaustion in consultant and trainee surgeons in the UK. Administered regularly, such a measure would facilitate the early identification of at-risk surgeons and swift intervention, as well as the monitoring of group-level temporal trends to inform resource allocation to coincide with peak periods

Erratum: “Searches for Gravitational Waves from Known Pulsars at Two Harmonics in 2015–2017 LIGO Data” (2019, ApJ, 879, 10)

Due to an error at the publisher, in the published article the number of pulsars presented in the paper is incorrect in multiple places throughout the text. Specifically, "222" pulsars should be "221." Additionally, the number of pulsars for which we have EM observations that fully overlap with O1 and O2 changes from "168" to "167." Elsewhere, in the machine-readable table of Table 1 and in Table 2, the row corresponding to pulsar J0952-0607 should be excised as well. Finally, in the caption for Table 2 the number of pulsars changes from "188" to "187.

GW190412: Observation of a Binary-Black-Hole Coalescence with Asymmetric Masses

We report the observation of gravitational waves from a binary-black-hole coalescence during the first two weeks of LIGO’s and Virgo’s third observing run. The signal was recorded on April 12, 2019 at 05∶30∶44 UTC with a network signal-to-noise ratio of 19. The binary is different from observations during the first two observing runs most notably due to its asymmetric masses: a ∼30 M_⊙ black hole merged with a ∼8 M_⊙ black hole companion. The more massive black hole rotated with a dimensionless spin magnitude between 0.22 and 0.60 (90% probability). Asymmetric systems are predicted to emit gravitational waves with stronger contributions from higher multipoles, and indeed we find strong evidence for gravitational radiation beyond the leading quadrupolar order in the observed signal. A suite of tests performed on GW190412 indicates consistency with Einstein’s general theory of relativity. While the mass ratio of this system differs from all previous detections, we show that it is consistent with the population model of stellar binary black holes inferred from the first two observing runs