Relationship between adverse childhood experiences and arterial stiffness over time from childhood into early adulthood

It is well established in the literature that there is an association among adults between adverse childhood experiences (ACEs) and arterial stiffness, and between arterial stiffness and cardiovascular disease. However, recent cross-sectional evidence suggests that ACEs may play an important role in the development and progression of arterial stiffness, but it remains unclear when these changes begin to manifest. Therefore, the purpose of this research was to examine the relationship between ACEs and arterial stiffness from childhood into adulthood using population-based longitudinal data. A total of 76 young adults (females = 44), with an average age of 21 years (SD = 1) were included in this study. Overall, a total of 71 respondents reported to have experienced at least one ACE. The findings of this study showed ACEs-exposed individuals have a greater increase in arterial stiffness over time from childhood into young adulthood. This increase was similar for both males and females. Also, differences in heart rate, systolic blood pressure, body mass index, and physical activity did not mediate the relationship between ACEs and arterial stiffness over time. It is therefore important to recognize individuals with exposure to ACEs early on in life in an effort to lower the risk of arterial stiffness and in turn the cascade of events leading to cardiovascular disease

Spatio-temporally Resolved Methane Fluxes From the Los Angeles Megacity

We combine sustained observations from a network of atmospheric monitoring stations with inverse modeling to uniquely obtain spatiotemporal (3‐km, 4‐day) estimates of methane emissions from the Los Angeles megacity and the broader South Coast Air Basin for 2015–2016. Our inversions use customized and validated high‐fidelity meteorological output from Weather Research Forecasting and Stochastic Time‐Inverted Lagrangian model for South Coast Air Basin and innovatively employ a model resolution matrix‐based metric to disentangle the spatiotemporal information content of observations as manifested through estimated fluxes. We partially track and constrain fluxes from the Aliso Canyon natural gas leak and detect closure of the Puente Hills landfill, with no prior information. Our annually aggregated fluxes and their uncertainty excluding the Aliso Canyon leak period lie within the uncertainty bounds of the fluxes reported by the previous studies. Spatially, major sources of CH_4 emissions in the basin were correlated with CH_4‐emitting infrastructure. Temporally, our findings show large seasonal variations in CH_4 fluxes with significantly higher fluxes in winter in comparison to summer months, which is consistent with natural gas demand and anticorrelated with air temperature. Overall, this is the first study that utilizes inversions to detect both enhancement (Aliso Canyon leak) and reduction (Puente Hills) in CH_4 fluxes due to the unintended events and policy decisions and thereby demonstrates the utility of inverse modeling for identifying variations in fluxes at fine spatiotemporal resolution

Methane emissions from underground gas storage in California

Accurate and timely detection, quantification, and attribution of methane emissions from Underground Gas Storage (UGS) facilities is essential for improving confidence in greenhouse gas inventories, enabling emission mitigation by facility operators, and supporting efforts to assess facility integrity and safety. We conducted multiple airborne surveys of the 12 active UGS facilities in California between January 2016 and November 2017 using advanced remote sensing and in situ observations of near-surface atmospheric methane (CH₄). These measurements where combined with wind data to derive spatially and temporally resolved methane emission estimates for California UGS facilities and key components with spatial resolutions as small as 1–3 m and revisit intervals ranging from minutes to months. The study spanned normal operations, malfunctions, and maintenance activity from multiple facilities including the active phase of the Aliso Canyon blowout incident in 2016 and subsequent return to injection operations in summer 2017. We estimate that the net annual methane emissions from the UGS sector in California averaged between 11.0 ± 3.8 GgCH₄ yr⁻¹ (remote sensing) and 12.3 ± 3.8 GgCH₄ yr⁻¹ (in situ). Net annual methane emissions for the 7 facilities that reported emissions in 2016 were estimated between 9.0 ± 3.2 GgCH₄ yr⁻¹ (remote sensing) and 9.5 ± 3.2 GgCH₄ yr⁻¹ (in situ), in both cases around 5 times higher than reported. The majority of methane emissions from UGS facilities in this study are likely dominated by anomalous activity: higher than expected compressor loss and leaking bypass isolation valves. Significant variability was observed at different time-scales: daily compressor duty-cycles and infrequent but large emissions from compressor station blow-downs. This observed variability made comparison of remote sensing and in situ observations challenging given measurements were derived largely at different times, however, improved agreement occurred when comparing simultaneous measurements. Temporal variability in emissions remains one of the most challenging aspects of UGS emissions quantification, underscoring the need for more systematic and persistent methane monitoring

Impact of novel processing techniques on the functional properties of egg products and derivatives: a review

Eggs are an excellent source of quality proteins. Eggs as a whole and its components (egg white and egg yolk) are employed in a range of food preparations. Thermal processing employed for stabilizing and improving shelf‐life of egg components is known to have adverse effect on heat‐sensitive proteins leading to protein denaturation and aggregation thus, reducing the required functional, technological, and overall quality of egg proteins and other constituents. Therefore, the current challenge is to identify novel processing techniques that not only improve the intrinsic functional properties of eggs or its components, but also improve the quality of the product. This review focuses on the use of technologies such as ultrasound, pulsed electric field, high‐pressure processing, radiofrequency, ultraviolet light, microwave, and cold plasma for egg products. These novel technologies are known for their advantages over thermal treatments especially in protecting the heat sensitive nature and retaining the overall quality of the egg and egg products. Availability of alternatives processing has significantly improved the structural properties, techno‐functional, nutritional and as well improving the safety egg and egg products. PRACTICAL APPLICATION: Eggs are consumed worldwide as whole egg or in some cases, consumed partly as egg whites or egg yolks. Egg components with improved techno‐functional properties can be used in various food industries (such as baking, confectionery, and culinary preparation, etc.). Value addition of new products can be achieved through modification of egg proteins. Additionally, these techniques also provide microbial safety and have a reduced impact on nutritional content and overall food quality

California’s methane super-emitters

Methane is a powerful greenhouse gas and is targeted for emissions mitigation by the US state of California and other jurisdictions worldwide. Unique opportunities for mitigation are presented by point-source emitters—surface features or infrastructure components that are typically less than 10 metres in diameter and emit plumes of highly concentrated methane. However, data on point-source emissions are sparse and typically lack sufficient spatial and temporal resolution to guide their mitigation and to accurately assess their magnitude4. Here we survey more than 272,000 infrastructure elements in California using an airborne imaging spectrometer that can rapidly map methane plumes. We conduct five campaigns over several months from 2016 to 2018, spanning the oil and gas, manure-management and waste-management sectors, resulting in the detection, geolocation and quantification of emissions from 564 strong methane point sources. Our remote sensing approach enables the rapid and repeated assessment of large areas at high spatial resolution for a poorly characterized population of methane emitters that often appear intermittently and stochastically. We estimate net methane point-source emissions in California to be 0.618 teragrams per year (95 per cent confidence interval 0.523–0.725), equivalent to 34–46 per cent of the state’s methane inventory for 2016. Methane ‘super-emitter’ activity occurs in every sector surveyed, with 10 per cent of point sources contributing roughly 60 per cent of point-source emissions—consistent with a study of the US Four Corners region that had a different sectoral mix. The largest methane emitters in California are a subset of landfills, which exhibit persistent anomalous activity. Methane point-source emissions in California are dominated by landfills (41 per cent), followed by dairies (26 per cent) and the oil and gas sector (26 per cent). Our data have enabled the identification of the 0.2 per cent of California’s infrastructure that is responsible for these emissions. Sharing these data with collaborating infrastructure operators has led to the mitigation of anomalous methane-emission activity

Spatio-temporally Resolved Methane Fluxes From the Los Angeles Megacity

We combine sustained observations from a network of atmospheric monitoring stations with inverse modeling to uniquely obtain spatiotemporal (3‐km, 4‐day) estimates of methane emissions from the Los Angeles megacity and the broader South Coast Air Basin for 2015–2016. Our inversions use customized and validated high‐fidelity meteorological output from Weather Research Forecasting and Stochastic Time‐Inverted Lagrangian model for South Coast Air Basin and innovatively employ a model resolution matrix‐based metric to disentangle the spatiotemporal information content of observations as manifested through estimated fluxes. We partially track and constrain fluxes from the Aliso Canyon natural gas leak and detect closure of the Puente Hills landfill, with no prior information. Our annually aggregated fluxes and their uncertainty excluding the Aliso Canyon leak period lie within the uncertainty bounds of the fluxes reported by the previous studies. Spatially, major sources of CH_4 emissions in the basin were correlated with CH_4‐emitting infrastructure. Temporally, our findings show large seasonal variations in CH_4 fluxes with significantly higher fluxes in winter in comparison to summer months, which is consistent with natural gas demand and anticorrelated with air temperature. Overall, this is the first study that utilizes inversions to detect both enhancement (Aliso Canyon leak) and reduction (Puente Hills) in CH_4 fluxes due to the unintended events and policy decisions and thereby demonstrates the utility of inverse modeling for identifying variations in fluxes at fine spatiotemporal resolution

A Geospatial Analytical Framework for Understanding Methane Emissions in California

Methane (CH4), an important greenhouse gas and pollutant, has been targeted for mitigation. Our recent California airborne survey identified >500 CH4 point sources, which accounted for 34-46% of the statewide CH4 emissions inventory for 2016. Individual plumes were observed in close proximity to expected CH4 emitting infrastructure. In order to systematically attribute these plumes to their sources, we developed Vista-CA a geospatial database, that contains more than 900,000 validated CH4 infrastructure elements in the state of California. In parallel, we developed a complimentary algorithm that attributes any individual CH4 plume observation to high confidence Vista-CA source with 99% accuracy. This research illustrates the capabilities of the Vista-CA CH4 database along with Airborne Visible/Infrared Imaging Spectrometer – Next Generation’s (AVIRIS-NG) airborne CH4 retrievals to locate and attribute CH4 point sources to specific economic sectors. Additionally, this research delivers two emissions products for Kern County: a top-down estimate called the AVIRIS-NG Source Data product and the Vista-CA Bottom-Up emissions dataset. We found general agreement in the source apportionment and magnitudes between these datasets. Moreover, due to current CH4 inventories having large uncertainties in emissions from the energy processing and production sectors where fugitive emissions predominate, we used airborne CH4 imaging survey data to show that CH4 emissions from power plants in California are underestimated by current CH4 inventory approaches. We developed process-based bottom-up emission estimates for over 300 power plants in California using Intergovernmental Panel on Climate Change (IPCC) methods. We used airborne CH4 imaging to attribute CH4 observations to over 250 California power plants and characterize the frequency and persistency of top-down CH4 emissions. We found that fugitive emissions constitute 90% of total observed emissions from power plants with the remainder derived from process-driven activity while bottom-up emissions are 28 – 54 times smaller than top-down observations. Comparing the inventory-based estimates with observations, the data show “super-emitter” behavior with 60% of total power plant emissions coming from a handful of facilities, likely due to fugitive CH4 emissions. Future inventories should take advantage of emission observations to quantify CH4 from these sources to improve the state CH4 budget and identify mitigation targets

A temporal and ecological analysis of the Huntington Beach Wetlands through an unmanned aerial system remote sensing perspective

Wetland monitoring and preservation efforts have the potential to be enhanced with advanced remote sensing acquisition and digital image analysis approaches. Progress in the development and utilization of Unmanned Aerial Systems (UAS) and Unmanned Aerial Vehicles (UAV) as remote sensing platforms has offered significant spatial and temporal advantages over traditional aerial and orbital remote sensing platforms. Photogrammetric approaches to generate high spatial resolution orthophotos of UAV acquired imagery along with the UAV’s low-cost and temporally flexible characteristics are explored. A comparative analysis of different spectral based land cover maps derived from imagery captured using UAV, satellite, and airplane platforms provide an assessment of the Huntington Beach Wetlands. This research presents a UAS remote sensing methodology encompassing data collection, image processing, and analysis in constructing spectral based land cover maps to augment the efforts of the Huntington Beach Wetlands Conservancy by assessing ecological and temporal changes at the Huntington Beach Wetlands

Sources of Variation in Food-Related Metabolites during Pregnancy

The extent to which variation in food-related metabolites are attributable to non-dietary factors remains unclear, which may explain inconsistent food-metabolite associations observed in population studies. This study examined the association between non-dietary factors and the serum concentrations of food-related biomarkers and quantified the amount of variability in metabolite concentrations explained by non-dietary factors. Pregnant women (n = 600) from two Canadian birth cohorts completed a validated semi-quantitative food frequency questionnaire, and serum metabolites were measured by multisegment injection-capillary electrophoresis-mass spectrometry. Hierarchical linear modelling and principal component partial R-square (PC-PR2) were used for data analysis. For proline betaine and DHA (mainly exogenous), citrus foods and fish/fish oil intake, respectively, explained the highest proportion of variability relative to non-dietary factors. The unique contribution of dietary factors was similar (15:0, 17:0, hippuric acid, TMAO) or lower (14:0, tryptophan betaine, 3-methylhistidine, carnitine) compared to non-dietary factors (i.e., ethnicity, maternal age, gestational age, pre-pregnancy BMI, physical activity, and smoking) for metabolites that can either be produced endogenously, biotransformed by gut microbiota, and/or derived from multiple food sources. The results emphasize the importance of adjusting for non-dietary factors in future analyses to improve the accuracy and precision of the measures of food intake and their associations with health and disease

Interplay of relational governance, task conflict, opportunism and their effect on the performance of projects.

Practitioners and academics have been perplexed over the years by low efficiency and bad performance in construction projects. Several critical factors have been uncovered by previous studies which are governance mechanism, task conflict and opportunism. But an obvious question arises how the mechanism of governance in the presence of conflict can mitigate opportunism. The overarching objective of this study is therefore to create a model to study the effectiveness of these mechanisms of governance in the presence of task conflict. This paper is based on a positivist study philosophy in which a quantitative deductive method was used to collect data from 139 participants. Hypotheses were tested using structural equation modeling (SEM) through SmartPLS3.The research findings show that relational governance affects project efficiency considerably and is helpful in decreasing opportunism and conflict. In addition, there is proof that opportunistic behavior will increase the task conflict among parties but both task conflict and opportunism doesn’t have direct impact on the performance of projec