The equivalent translational stiffness of steel studs

The effect of the resilience of the steel studs on the sound insulation of steel stud cavity walls can be modelled as an equivalent translational stiffness in simple models for predicting the sound insulation of walls. Numerical calculations (Poblet-Puig et al., 2009) have shown that this equivalent translational stiffness varies with frequency. Vigran (2010a) has derived a best-fit third order polynomial approximation to the logarithm of these numerical values as a function of the logarithm of the frequency for the most common type of steel stud. This paper uses an inverse experimental technique. It determines the values of the equivalent translational stiffness of steel studs which make Davy’s (2010) sound insulation theory agree best with experimental sound insulation data from the National Research Council of Canada (NRCC) (Halliwell et al., 1998) for 126 steel stud cavity walls with gypsum plasterboard on each side of the steel studs and sound absorbing material in the wall cavity. These values are approximately constant as a function of frequency up to 400 Hz. Above 400 Hz they increase approximately as a non-integer power of the frequency. The equivalent translational stiffness also depends on the mass per unit surface area of the cladding on each side of the steel studs and on the width of the steel studs. Above 400 Hz, this stiffness also depends on the stud spacing. The equivalent translational stiffness of steel studs determined in this paper and the best-fit approximation to that data are compared with that determined numerically by Poblet-Puig et al. (2009) and with Vigran’s (2010a) best-fit approximation as a function of frequency. The best-fit approximation to the inversely experimentally determined values of equivalent translational stiffness are used with Davy’s (2010) sound insulation prediction model to predict the sound insulation of steel stud cavity walls whose sound insulation has been determined experimentally by NRCC (Halliwell et al., 1998) or CSTB (Guigou-Carter and Villot, 2006)

An empirical model for the equivalent translational compliance of steel studs

The effect of the resilience of the steel studs on the sound insulation of steel stud cavity walls can be modeled as an equivalent translational compliance in simple models for predicting the sound insulation of walls. Recent numerical calculations have shown that this equivalent translational compliance varies with frequency

The prediction of flanking sound transmission below the critical frequency

Although reliable methods exist to predict the apparent sound reduction index of heavy, homogeneous isotopic building constructions, these methods are not appropriate for use with lightweight building constructions which typically have critical frequencies in or above the frequency range of interest. Three main methods have been proposed for extending the prediction of flanking sound transmission to frequencies below the critical frequency

Experimental and numerical characterization of metallic studs

In this paper, the characterization of metallic studs used to mount lightweight double wall systems is studied both experimentally and numerically. The metallic studs are usually considered by introducing translational and rotational springs to couple the plasterboards composing the double wall. Therefore, the characterization involves determining these spring characteristics. The performance of this type of lightweight double wall in terms of sound transmission is presented in a companion paper. Different experimental setups have been investigated to determine the equivalent translational and rotational spring values. These experimental setups are described and involve the measurement of an input mobility. A finite element model of the laboratory tests has been developed. Shell and massive finite elements are employed in order to reproduce the experimental setups. A comparison of the measured and numerical results is shown. The FEM modelling is intended to help in developing new type of studs for double walls in order to obtain better sound transmission performance.Peer ReviewedPostprint (published version

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

On-farm evaluation of multiparametric models to predict subacute ruminal acidosis in dairy cows

This research aimed: (i) to evaluate on-farm (FARM data) multiparametric models developed under controlled experiment (INRAE data) and based on non-invasive indicators to detect subacute ruminal acidosis (SARA) in dairy cows. We also aimed to recover high discrimination capacity, if needed, by (ii) building new models with combined INRAE and FARM data; and (iii) enriching the models increasing from 2 to 5 indicators per model. For model enrichment, we focused on indicators determinable on-farm by quick and inexpensive routine analysis. Fifteen commercial dairy farms were selected to cover a wide range of SARA risk. In each farm, four Holstein early-lactating healthy primiparous cows were selected based on their last on-farm recording of milk yield and somatic cell count analysis. Cows were equipped with a reticulo-rumen pH sensor. The pH kinetics were analysed over a subsequent 7-day period. Relative pH indicators were used to classify cows with or without SARA. Milk, blood, faeces, and urine were collected for analysis of the indicators included in the models developed by Villot et al. (2020) on INRAE data that were externally evaluated using FARM data. Then, new models based on the same indicators were developed combining INRAE and FARM data to test whether a possible loss in performance was due to a limited validity domain of model by Villot et al (2020). Finally, the models developed combining INRAE and FARM data were adapted to the on-farm application and enriched by increasing indicators from 2 to 5 per model using linear discriminant analysis and leave-one-out cross-validation. The sensitivities (true-positive rate) in external evaluation on FARM data were substantially lower than those from cross-validation by Villot et al. (2020) (range: 0.1–0.75 vs 0.79–0.96, respectively), and the specificities (true-negative rate) showed a larger range with lower minimum values (range: 0.18–1.0 vs 0.62–0.97, respectively). The sensitivities of new models developed combining INRAE and FARM data ranged from 0.63 to 0.77. Models involving blood cholesterol, β-hydroxybutyrate, haptoglobin, milk and blood urea, and models involving milk fat/protein ratio, dietary starch proportion, and milk fatty acids had the highest performances, whereas models including sieved faecal residues and urine pH had the lowest. Enriching models to three indicators per model improved sensitivity and specificity, but the inclusion of more indicators was less or not effective. Larger field trials are required to validate our results and to increase variability and validity domain of models

Association between nutritional values of hays fed to horses and sensory properties as perceived by human sight, touch and smell

International audienceAlthough hay is the foundation of most equine diets, horse owners rarely ask for biochemical analysis and the routine practice is to choose hay based on its 'perceived' nutritional value. The present study aimed at exploring the relationship between sensory properties as perceived by sight, touch and smell, and the nutritional value of hay measured by biochemical analysis using a 'free sorting task' method. Fifty-four non-expert participants were asked individually to: (1) observe 21 hays samples, (2) group together hays that they perceived as similar for each of the three modalities (hay appearance, odour or texture) and (3) characterize each formed group with a maximum of five descriptive terms. For each modality, results were recorded in a contingency matrix (hays × terms) where only terms cited at the minimum five times for at least one sample, were kept for data analysis. A correspondence analysis (CA) was performed on the contingency matrix to plot both samples and descriptive terms on a χ 2 metric map. Then, a Hierarchical Ascending Classification (HAC) was performed on the coordinates of samples in the CA space. Clusters were identified by truncating the HAC tree-diagrams. The attributes that defined the best resulting clusters were identified by computing their probability of characterizing a cluster. Correlations were computed between each biochemical parameter on one hand, and the first two dimensions of the CA map on the other. Finally, correlations between the values of each hay on the first dimension of the three CA maps (appearance, odour and texture) were computed. Hedonic descriptive terms were primarily used for describing odour and texture modalities. For describing hay appearance, participants spontaneously used visual cues referring to colour or aspect. Based on the tree-diagrams resulting from the HAC, 3, 5 and 2 groups were clustered, respectively for appearance, odour and texture description. Digestible energy was correlated to the first dimension on the three CA maps, whereas CP was correlated to the first dimension of the CA appearance map only. While NDF value was correlated to the first and second dimensions on the CA odour map only, ADF content was correlated to the first dimension on the three CA maps. Non-fibre carbohydrates were correlated to the first dimension of the CA appearance map only. The similarity-based approach which is part of the standard toolbox of food sensory evaluation by untrained consumers was well adapted to animal feeds evaluation by non-experts

Graduate Student Literature Review: Developmental adaptations of immune function in calves and the influence of the intestinal microbiota in health and disease

ABSTRACT: This graduate student literature review provides an examination of the ontological adaptations of the calf's immune system and how the intestinal microbiota influences calf immune function in health and disease. Within dairy rearing systems, various nutritional and management factors have emerged as critical determinants of development influencing multiple physiological axes in the calf. Furthermore, we discuss how multiple pre- and postnatal maternal factors influence the trajectory of immune development in favor of establishing regulatory networks to successfully cope with the new environment, while providing early immune protection via immune passive transfer from colostrum. Additionally, our review provides insights into the current understanding of how the intestinal microbiota contributes to the development of the intestinal and systemic immune system in calves. Lastly, we address potential concerns related to the use of prophylactic antimicrobials and waste milk, specifically examining their adverse effects on intestinal health and metabolic function. By examining these factors, we aim to better understand the intricate relationship between current management practices and their long-term effect on animal health