scholarly journals Comparison Between Non-Invasive Methane Measurement Techniques in Cattle

Animals ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 563 ◽  
Author(s):  
Rey ◽  
Atxaerandio ◽  
Ruiz ◽  
Ugarte ◽  
González-Recio ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Measurement Techniques ◽  
Genetic Selection ◽  
Mitigation Strategies ◽  
Population Means ◽  
Individual Level ◽  
Non Invasive ◽  
Ch4 Concentration ◽  
The Individual ◽  
Methane Measurement

The aim of this trial was to study the agreement between the non-dispersive infrared methane analyzer (NDIR) method and the hand held laser methane detector (LMD). Methane (CH4) was measured simultaneously with the two devices totaling 164 paired measurements. The repeatability of the CH4 concentration was greater with the NDIR (0.42) than for the LMD (0.23). However, for the number of peaks, repeatability of the LMD was greater (0.20 vs. 0.14, respectively). Correlation was moderately high and positive for CH4 concentration (0.73 and 0.74, respectively) and number of peaks (0.72 and 0.72, respectively), and the repeated measures correlation and the individual-level correlation were high (0.98 and 0.94, respectively). A moderate concordance correlation coefficient was observed for the CH4 concentration (0.62) and for the number of peaks (0.66). A moderate-high coefficient of individual agreement for the CH4 concentration (0.83) and the number of peaks (0.77) were observed. However, CH4 concentrations population means and all variance components differed between instruments. In conclusion, methane concentration measurements obtained by means of NDIR and LMD cannot be used interchangeably. The joint use of both methods could be considered for genetic selection purposes or for mitigation strategies only if sources of disagreement, which result in different between-subject and within-subject variabilities, are identified and corrected for.

scholarly journals Analyzing 24-Hour Blood Pressure Measurements with a Novel Cuffless Pulse Transit Time Device in Clinical Practice—Does the Software for Heartbeat Detection Matter?

Diagnostics ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 361
Author(s):  
Leo Kilian ◽  
Philipp Krisai ◽  
Thenral Socrates ◽  
Christian Arranto ◽  
Otmar Pfister ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Transit Time ◽  
Pulse Transit Time ◽  
Population Level ◽  
Raw Data ◽  
Invasive Blood Pressure ◽  
Individual Level ◽  
Non Invasive ◽  
The Individual ◽  
The Impact

Background: The Somnotouch-Non-Invasive-Blood-Pressure (NIBP) device delivers raw data consisting of electrocardiography and photoplethysmography for estimating blood pressure (BP) over 24 h using pulse-transit-time. The study’s aim was to analyze the impact on 24-hour BP results when processing raw data by two different software solutions delivered with the device. Methods: We used data from 234 participants. The Somnotouch-NIBP measurements were analyzed using the Domino-light and Schiller software and compared. BP values differing >5 mmHg were regarded as relevant and explored for their impact on BP classification (normotension vs. hypertension). Results: Mean (±standard deviation) absolute systolic/diastolic differences for 24-hour mean BP were 1.5 (±1.7)/1.1 (±1.3) mm Hg. Besides awake systolic BP (p = 0.022), there were no statistically significant differences in systolic/diastolic 24-hour mean, awake, and asleep BP. Twenty four-hour mean BP agreement (number (%)) between the software solutions within 5, 10, and 15 mmHg were 222 (94.8%), 231 (98.7%), 234 (100%) for systolic and 228 (97.4%), 232 (99.1%), 233 (99.5%) for diastolic measurements, respectively. A BP difference of >5 mmHg was present in 24 (10.3%) participants leading to discordant classification in 4–17%. Conclusion: By comparing the two software solutions, differences in BP are negligible at the population level. However, at the individual level there are, in a minority of cases, differences that lead to different BP classifications, which can influence the therapeutic decision.

scholarly journals Counting Carbon: The Politics of Carbon Footprints and Climate Governance from the Individual to the Global

2014 ◽  
Vol 14 (1) ◽  
pp. 59-78 ◽  
Author(s):  
James Morton Turner
Keyword(s):  
Carbon Footprint ◽  
Science Studies ◽  
Mitigation Strategies ◽  
Climate Governance ◽  
Carbon Footprints ◽  
Individual Level ◽  
Electricity Use ◽  
Conceptual Shift ◽  
Governmentality Studies ◽  
The Individual

This article considers carbon footprints as a form of climate governance. Drawing on science studies to consider the contingent nature of calculative devices and governmentality studies to examine the intrinsic relationship between how problems are framed and remedied, this article advances two arguments. First, it argues that efforts to define and deploy carbon footprints contributed to a conceptual shift in emissions accounting, from a narrower metric focused on emissions from fossil fuel and electricity use—Carbon Footprint 1.0—to a more expansive metric that includes emissions embodied in consumption and trade—Carbon Footprint 2.0. Second, this article argues that these approaches to carbon footprints at the individual level have intersected with broader discussions about allocating emissions responsibilities and examining mitigation strategies at the national and international levels, offering alternative grounds for assigning responsibility for climate-change mitigation and expanding the range of policy options available for addressing emissions.

scholarly journals Is it all in our head? When subjective beliefs about receiving an intervention are better predictors of experimental results than the intervention itself

2020 ◽  
Author(s):  
Luisa Fassi ◽  
Roi Cohen Kadosh
Keyword(s):  
Training Programs ◽  
Active Form ◽  
Mind Wandering ◽  
Placebo Control ◽  
Individual Level ◽  
Subjective Beliefs ◽  
Non Invasive ◽  
The Individual ◽  
Experimental Findings ◽  
Actual Intervention

AbstractIn recent years, there has been debate about the effectiveness of interventions from different fields (e.g., non-invasive brain stimulation (NIBS), neurofeedback, cognitive training programs) due to contradictory and nuanced experimental findings. Up to date, studies are focused on comparing the effects of an active form of the intervention to a placebo/control condition. However, a neglected question is how to consider individual differences in response to blinding procedures, and their effect on behavioural outcomes, rather than merely compare the efficacy of blinding using a group-based approach. To address this gap in the literature, we here suggest using subjective intervention—the participants’ subjective beliefs about receiving or not receiving an intervention—as a factor. Specifically, we examined whether subjective intervention and subjective dosage (i.e. participants’ subjective beliefs about the intensity of the intervention they received) affected performance scores independently, or interacting with, the active experimental condition. We carried out data analysis on an open-access dataset that has shown the efficacy of active NIBS in altering mind wandering. We show that subjective intervention and subjective dosage successfully explained alteration in mind wandering scores, over and beyond the objective intervention. These findings highlight the importance of accounting for the participants’ beliefs about receiving interventions at the individual level by demonstrating their effect on human behaviour independently of the actual intervention. Altogether, our approach allows more rigorous and improved experimental design and analysis, which will strengthen the conclusions coming from basic and clinical research, for both NIBS and non-NIBS interventions.

scholarly journals Assessing the sensitivity of EEG-based frequency-tagging as a metric for statistical learning

2021 ◽  
Author(s):  
Danna Pinto ◽  
Anat Prior ◽  
Elana Zion Golumbic
Keyword(s):  
Statistical Learning ◽  
Artificial Language ◽  
Group Level ◽  
Behavioral Measures ◽  
Individual Level ◽  
Non Invasive ◽  
Eeg Data ◽  
Eeg Recordings ◽  
The Individual ◽  
Low Sensitivity

Statistical Learning (SL) is hypothesized to play an important role in language development. However, the behavioral measures typically used to assess SL, particularly at the level of individual participants, are largely indirect and often have low sensitivity. Recently, a neural metric based on frequency-tagging has been proposed as an alternative and more direct measure for studying SL. Here we tested the sensitivity of frequency-tagging measures for studying SL in individual participants in an artificial language paradigm, using non-invasive EEG recordings of neural activity in humans. Importantly, we use carefully constructed controls, in order to address potential acoustic confounds of the frequency-tagging approach. We compared the sensitivity of EEG-based metrics to both explicit and implicit behavioral tests of SL, and the correspondence between these presumed converging operations. Group-level results confirm that frequency-tagging can provide a robust indication of SL for an artificial language, above and beyond potential acoustic confounds. However, this metric had very low sensitivity at the level of individual participants, with significant effects found only in 30% of participants. Conversely, the implicit behavior measures indicated that SL has occurred in 70% of participants, which is more consistent with the proposed ubiquitous nature of SL. Moreover, there was low correspondence between the different measures used to assess SL. Taken together, while some researchers may find the frequency-tagging approach suitable for their needs, our results highlight the methodological challenges of assessing SL at the individual level, and the potential confounds that should be taken into account when interpreting frequency-tagged EEG data.

scholarly journals Household transmissions of SARS-CoV-2 in the time of unprecedented travel lockdown in China

2020 ◽  
Author(s):  
Xiao-Ke Xu ◽  
Xiao-Fan Liu ◽  
Lin Wang ◽  
Sheikh Taslim Ali ◽  
Zhanwei Du ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Severe Acute Respiratory Syndrome ◽  
Age Groups ◽  
Hubei Province ◽  
Mitigation Strategies ◽  
Limited Information ◽  
Individual Level ◽  
Epidemiological Features ◽  
The Individual ◽  
Epidemiological Characteristics

AbstractImportanceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in the city of Wuhan, China, in December 2019 and then spread globally. Limited information is available for characterizing epidemiological features and transmission patterns in the regions outside of Hubei Province. Detailed data on transmission at the individual level could be an asset to understand the transmission mechanisms and respective patterns in different settings.ObjectiveTo reconstruct infection events and transmission clusters of SARS-CoV-2 for estimating epidemiological characteristics at household and non-household settings, including super-spreading events, serial intervals, age- and gender-stratified risks of infection in China outside of Hubei Province.Design, Setting, and Participants9,120 confirmed cases reported online by 264 Chinese urban Health Commissions in 27 provinces from January 20 to February 19, 2020. A line-list database is established with detailed information on demographic, social and epidemiological characteristics. The infection events are categorized into the household and non-household settings.ExposuresConfirmed cases of SARS-CoV-2 infections.Main Outcomes and MeasuresInformation about demographic characteristics, social relationships, travel history, timelines of potential exposure, symptom onset, confirmation, and hospitalization were extracted from online public reports. 1,407 infection events formed 643 transmission clusters were reconstructed.ResultsIn total 34 primary cases were identified as super spreaders, and 5 household super-spreading events were observed. The mean serial interval is estimated to be 4.95 days (standard deviation: 5.24 days) and 5.19 days (standard deviation: 5.28 days) for households and non-household transmissions, respectively. The risk of being infected outside of households is higher for age groups between 18 and 64 years, whereas the hazard of being infected within households is higher for age groups of young (<18) and elderly (>65) people.Conclusions and RelevanceThe identification of super-spreading events, short serial intervals, and a higher risk of being infected outside of households for male people of age between 18 and 64 indicate a significant barrier to the case identification and management, which calls for intensive non-pharmaceutical interventions (e.g. cancellation of public gathering, limited access of public services) as the potential mitigation strategies.Key PointsQuestionWhat epidemiological characteristics and risk factors are associated with household and non-household transmissions of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China outside of Hubei Province?FindingsIn this epidemiological study analyzing 1,407 SARS-CoV-2 infection events reported between 20 January 2020 and 19 February 2020, 643 transmission clusters were reconstructed to demonstrate the non-negligible frequency of super-spreading events, short duration of serial intervals, and a higher risk of being infected outside of household for male people of age between 18 and 64 years.MeaningThese findings provide epidemiological features and risk estimates for both household and non-household transmissions of SARS-CoV-2 in China outside of Hubei Province.

scholarly journals Heart Rate Variability as a Prospective Predictor of Early COVID-19 Symptoms

2021 ◽  
Author(s):  
Alexey Ponomarev ◽  
Konstantin Tyapochkin ◽  
Ekaterina Surkova ◽  
Evgeniya Smorodnikova ◽  
Pavel Pravdin
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Viral Infections ◽  
Group Analysis ◽  
Interval Data ◽  
Time Interval ◽  
Individual Level ◽  
Non Invasive ◽  
Invasive Method ◽  
The Individual

Heart rate variability (HRV) is the fluctuation in the time interval between consecutive heartbeats, the measurement of which is a non-invasive method for assessing the autonomic status. The autonomic nervous system plays an important role in physiological situations, and in various pathological processes such as in cardiovascular diseases and viral infections. This study examined the cardiac autonomic responses, as measured by HRV before, after, and during coronavirus disease. In this study, we used beat interval data extracted from the Welltory app from 14 eligible subjects (9 men and 5 women) with a mean age (SD) of 44 (8.7) years. HRV analysis was performed through an assessment of time-domain indices (SDNN and RMSSD). Group analysis did not reveal any statistical difference between HRV metrics before, during, and after COVID-19. However, HRV at the individual level showed a statistically significant individual change during COVID-19 in some users. These data further support the usefulness of using individual-level HRV tracking for the detection of early diseases inclusive of COVID-19.

scholarly journals Structural Nested Mean Models to Estimate the Effects of Time-Varying Treatments on Clustered Outcomes

2015 ◽  
Vol 11 (2) ◽  
Author(s):  
Jiwei He ◽  
Alisa Stephens-Shields ◽  
Marshall Joffe
Keyword(s):  
Repeated Measures ◽  
Regression Method ◽  
Time Varying ◽  
Treatment Allocation ◽  
Individual Level ◽  
Nested Models ◽  
Unit Level ◽  
Effect Of Treatment ◽  
Structural Nested Models ◽  
The Individual

AbstractIn assessing the efficacy of a time-varying treatment structural nested models (SNMs) are useful in dealing with confounding by variables affected by earlier treatments. These models often consider treatment allocation and repeated measures at the individual level. We extend SNMMs to clustered observations with time-varying confounding and treatments. We demonstrate how to formulate models with both cluster- and unit-level treatments and show how to derive semiparametric estimators of parameters in such models. For unit-level treatments, we consider interference, namely the effect of treatment on outcomes in other units of the same cluster. The properties of estimators are evaluated through simulations and compared with the conventional GEE regression method for clustered outcomes. To illustrate our method, we use data from the treatment arm of a glaucoma clinical trial to compare the effectiveness of two commonly used ocular hypertension medications.

Individual and Social Network Predictors of Physical Bullying: A Longitudinal Study of Taiwanese Early Adolescents

2014 ◽  
Vol 29 (4) ◽  
pp. 701-716 ◽  
Author(s):  
Hsi-Sheng Wei ◽  
Wonjae Lee
Keyword(s):  
Social Network ◽  
Repeated Measures ◽  
Economic Status ◽  
Friendship Networks ◽  
Friendship Network ◽  
Individual Level ◽  
School Year ◽  
Bullying Experiences ◽  
The Individual ◽  
Physical Bullying

This study followed 125 7th-grade students in Taiwan for the entire school year and analyzed the individual and social network factors predicting their involvement in physical bullying over 5 waves of data. Using self-reports of bullying experiences, 20 classroom-level networks of bullying and friendship were constructed for 4 classrooms and 5 temporal points, from which 4 individual-level network measures were calculated. They included bully and victim centrality, popularity, and embeddedness in friendship networks. A series of mixed models for repeated measures were constructed to predict students’ bully and victim centrality in bullying network at time t + 1. Compared to girls, boys were more likely to be both the bullies and victims. Lower self-esteem and higher family economic status contributed to victim centrality. Having parents married and living together predicted lower bully centrality. Higher educational level of parents predicted lower victim and bully centrality. Regarding the social network factors, students’ bully centrality at t positively predicted their bully centrality at t + 1, whereas victim centrality predicted their subsequent victim centrality. Interaction effects between friendship network and bullying network were observed. Embeddedness in friendship network reduced victim centrality at t + 1 except for those students with low victim centrality at t. For those with high victim centrality at t, popularity increased their risk of physical victimization over time. Implications for research and practice are discussed.

Differential Effects of Competence and Morality on Self-Esteem at the Individual and the Collective Level

2020 ◽  
Vol 51 (3) ◽  
pp. 183-198
Author(s):  
Wiktor Soral ◽  
Mirosław Kofta
Keyword(s):  
Self Esteem ◽  
Differential Effects ◽  
Individual Level ◽  
The Subject ◽  
The Individual

Abstract. The importance of various trait dimensions explaining positive global self-esteem has been the subject of numerous studies. While some have provided support for the importance of agency, others have highlighted the importance of communion. This discrepancy can be explained, if one takes into account that people define and value their self both in individual and in collective terms. Two studies ( N = 367 and N = 263) examined the extent to which competence (an aspect of agency), morality, and sociability (the aspects of communion) promote high self-esteem at the individual and the collective level. In both studies, competence was the strongest predictor of self-esteem at the individual level, whereas morality was the strongest predictor of self-esteem at the collective level.

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