Active platform stabilization with a 6D seismometer

We demonstrate the control scheme of an active platform with a six degree of freedom (6D) seismometer. The inertial sensor simultaneously measures translational and tilt degrees of freedom of the platform and does not require any additional sensors for the stabilization. We show that a feedforward cancelation scheme can efficiently decouple tilt-to-horizontal coupling of the seismometer in the digital control scheme. We stabilize the platform in the frequency band from 250 mHz up to 10 Hz in the translational (X, Y) degrees of freedom and achieve a suppression factor of 100 around 1 Hz. Further suppression of ground vibrations was limited by the non-linear response of the piezo actuators of the platform and by its limited range (5 lm). In this paper, we discuss the 6D seismometer, its control scheme, and the limitations of the test bed

Chapter 19 Noise pollution and its impact on human health and the environment

This chapter deals with (1) the basic theory of sound propagation; (2) an overview of noise pollution problem in view of policy and standards by the World Health Organization, the United States, and the European Union; (3) noise exposure sources from aircraft, road traffic and railways, in-vehicle, work, and construction sites, and occupations, and households; (4) the noise pollution impact on human health and the biological environment; (5) modeling of regional noise-affected habitats in protected and unprotected land areas and the marine environment; (6) noise control measures and sustainability in view of sustainable building design, noise mapping, and control measures such as barriers and berms along roadsides, acoustic building materials, roadway vehicle noise source control, road surface, and pavement materials; and (7) environmental noise pollution management measures and their impact on human health

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Predicting direct healthcare costs of general practitioner-guided care in patients with musculoskeletal complaints

Information on healthcare utilization and costs of general practitioner (GP)-guided care in patients with musculoskeletal complaints is important for keeping healthcare affordable and accessible. A registry-based study was performed to describe healthcare utilization and costs of GP-guided care in patients with musculoskeletal complaints and to predict having higher direct healthcare costs. Healthcare costs of GP-guided care included all healthcare resources used by patients due to a musculoskeletal condition in 2018. Data were extracted from the database with a 1-year follow-up and descriptively analyzed. A general linear model was developed to predict having higher direct healthcare costs. In total, 403,719 patients were included, of whom 92% only received a single consultation. The number of referrals varied across the different types of complaints. Total annual direct healthcare costs amounted to €39,180,531, of which a key cost driver was referrals. Primary care consultations accounted for the largest part of referral-related costs. For all musculoskeletal conditions combined, the mean annual direct healthcare cost per patient was €97 (SEM = €0.18). Older age, being a woman, low socioeconomic status, spine complaints, high number of musculoskeletal diagnoses, and a high comorbidity score were predictive of having higher direct healthcare costs and explained 0.7% of the variance. This study showed that mean annual direct healthcare costs of GP-guided care in patients with musculoskeletal conditions were relatively low and did not differ considerably across conditions. The predictive model explained a negligible part of the variance in costs. Thus, it is unclear which factors do predict high direct healthcare costs in this population.</p

High Systemic Immune Inflammation Index Is Associated With Low Skeletal Muscle Quantity in Resectable Pancreatic Ductal Adenocarcinoma

Background and Aims: Failing immune surveillance in pancreatic ductal adenocarcinoma (PDAC) is related to poor prognosis. PDAC is also characterized by its substantial alterations to patients’ body composition. Therefore, we investigated associations between the host systemic immune inflammation response and body composition in patients with resected PDAC. Methods: Patients who underwent a pancreatectomy for PDAC between 2004 and 2016 in two tertiary referral centers were included. Skeletal muscle mass quantity and muscle attenuation, as well as subcutaneous and visceral adipose tissue at the time of diagnosis, were determined by CT imaging measured transversely at the third lumbar vertebra level. Baseline clinicopathological characteristics, laboratory values including the systemic immune inflammation index (SIII), postoperative, and survival outcomes were collected. Results: A total of 415 patients were included, and low skeletal muscle mass quantity was found in 273 (65.7%) patients. Of the body composition indices, only low skeletal muscle mass quantity was independently associated with a high (≥900) SIII (OR 7.37, 95% CI 2.31-23.5, p=0.001). The SIII was independently associated with disease-free survival (HR 1.86, 95% CI 1.12-3.04), and cancer-specific survival (HR 2.21, 95% CI 1.33-3.67). None of the body composition indices were associated with survival outcomes. Conclusion: This study showed a strong association between preoperative low skeletal muscle mass quantity and elevated host systemic immune inflammation in patients with resected PDAC. Understanding how systemic inflammation may contribute to changes in body composition or whether reversing these changes may affect the host systemic immune inflammation response could expose new therapeutic possibilities for improving patients’ survival outcomes