bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nutritional value of child-targeted food products: results from the Food Quality Observatory
Authors: Gilbert-Moreau Joséane , Pomerleau Sonia , Perron Julie , Gagnon Pierre , Labonté Marie-Ève , Provencher Véronique 
Published: August 2021

AbstractObjective:To characterise the nutritional quality of food products targeted to children, we aimed: (1) to determine if the nutritional composition of child-targeted food products is different from those for the general population and (2) to verify differences in the nutrient content of child-targeted food products between three selected food categories.Design:The present study is part of the work conducted by the Food Quality Observatory, created in 2016 in the province of Quebec (Canada). Ready-to-eat (RTE) breakfast cereals (n 331), granola bars (n 310) and yoghurts and dairy desserts (n 380) were the food categories analysed.Setting:Nutritional values and all packaging information were obtained by purchasing every product available in supermarkets, grocery stores and specialty grocery stores. Free sugars were manually differentiated from total sugars for each product. Products were classified according to two targeted consumer groups: children or general population.Results:The nutrient profile of RTE breakfast cereals, granola bars and yoghurts and dairy desserts targeted to children differed from that of products intended at the general population. Child-targeted RTE breakfast cereals had the least favourable nutritional composition, with significantly higher content of carbohydrates, total sugars, free sugars and Na compared with breakfast cereals for the general population as well as child-targeted granola bars and yoghurts and dairy desserts. All child-targeted products analysed contained free sugars.Conclusions:The current study supports the relevance to further regulate marketing to children on food product packages to ensure that such marketing is not present on food products with poor nutritional quality.
Determining the nutritional immunity information-seeking behaviour during the COVID-19 pandemic in India: a Google Trends data analysis
Authors: Kushwaha Savitesh , Khanna Poonam , Jain Rachita , Srivastava Rachana 
Published: August 2021

AbstractObjective:During COVID-19, the Internet was a prime source for getting relevant updates on guidelines and desirable information. The objective of the present study was to determine the nutritional immunity information-seeking behaviour during COVID-19 in India.Design:Google Trends (GTs) data on relevant COVID-19 and nutritional topics were systematically selected and retrieved. Data on newly reported COVID-19 cases were also examined on a daily basis. The cross-correlation method was used to determine the correlation coefficient between the selected terms and daily new COVID-19 cases, and the joinpoint regression models were utilised to measure monthly percent change (MPC) in relative search volumes (RSV).Setting:Online.Participants:People using Google search during the period 1 January 2020–31 August 2020 in India.Results:The date of peak searches can be attributed to the COVID-19 guidelines announcement dates. All the nutritional terms showed a significant increase in average monthly percentage change. The higher than the average daily rise in COVID-19 cases leads to a higher than average increase in RSV of nutritional terms with the greatest association after 14–27 d. The highest mean relative search volume for nutritional terms was from Southern India (49·34 ± 7·43), and the lowest was from Western India (31·10 ± 6·30).Conclusion:There was a significant rise in the Google searches of nutritional immunity topics during COVID-19 in India. The local/regional terms can be considered for better outreach of public health guidelines or recommendations. Further automation of Google Trends using programming languages can help in real-time monitoring and planning various health/nutritional events.
Rationalisation of meat consumption in New Zealand adolescents
Authors: Latimer Kelly R , Peddie Meredith C , Scott Tessa , Haszard Jillian J 
Published: August 2021

AbstractObjective:This study aimed to describe meat consumption rationalisation and relationships with meat consumption patterns and food choice motivations in New Zealand adolescents.Design:This was a cross-sectional study of adolescents from high schools across New Zealand. Demographics, dietary habits, and motivations and attitudes towards food were assessed by online questionnaire and anthropometric measurements taken by researchers. The 4Ns questionnaire assessed meat consumption rationalisation with four subscales: ‘Nice’, ‘Normal’, ‘Necessary’ and ‘Natural’.Setting:Nineteen secondary schools from eight regions in New Zealand, with some purposive sampling of adolescent vegetarians in Otago, New Zealand.Participants:Questionnaires were completed by 385 non-vegetarian and vegetarian (self-identified) adolescents.Results:A majority of non-vegetarian adolescents agreed that consuming meat was ‘nice’ (65 %), but fewer agreed that meat consumption was ‘necessary’ (51 %). Males agreed more strongly than females with all 4N subscales. High meat consumers were more likely to agree than to disagree that meat consumption was nice, normal, necessary and natural, and vegetarians tended to disagree with all rationalisations. Adolescent non-vegetarians whose food choice was motivated more by convenience, sensory appeal, price and familiarity tended to agree more with all 4N subscales, whereas adolescents motivated by animal welfare and environmental concerns were less likely to agree.Conclusions:To promote a reduction in meat consumption in adolescents, approaches will need to overcome beliefs that meat consumption is nice, normal, necessary and natural.
Ultra-processed food intake and all-cause mortality: DRECE cohort study
Authors: Romero Ferreiro Carmen , Martín-Arriscado Arroba Cristina , Cancelas Navia Pilar , Lora Pablos David , Gómez de la Cámara Agustín 
Published: August 2021

AbstractObjective:To determine the association between ultra-processed food (UPF) intake and all-cause mortality in a representative sample of Spanish population.Design:Prospective cohort design in which follow-up lasted from baseline (1991) to mortality date or 31 December 2017, whichever was first. Dietary information was collected using a validated frequency questionnaire and categorised following the NOVA classification according to the extent of food processing. The association between consumption of UPF and mortality was analysed using Cox models. Isoenergetic substitution models were constructed to compare the health effects of the NOVA groups.Setting:Cohort from the Diet and Risk of Cardiovascular Diseases (CVD) in Spain (DRECE) study, representative of the Spanish populationParticipants:Totally, 4679 subjects between 5 and 59 years old.Results:Average consumption of UPF was 370·8 g/d (24·4 % of energy intake). After a median follow-up of 27 years, 450 deaths occurred. Those who consumed the highest amount of UPF had higher risk of mortality. For every 10 % of the energy intake from UPF consumption, an increase of 15 % in the hazard of all-cause mortality was observed (HR 1·15; (95 % CI 1·03, 1·27);P-value = 0·012). Substitution of UPF with minimally processed foods was significantly associated with a decreased risk of mortality.Conclusions:An increase in UPF consumption was associated with higher risk of all-cause mortality in a representative sample of the Spanish population. Moreover, the theoretical substitution of UPF with unprocessed or minimally processed foods leads to a decrease in mortality. These results support the need to promote diets based on unprocessed or minimally processed foods.
Evaluation of Air and Soil Temperatures for Determining the Onset of Growing Season
Authors: Leeper Ronald D. , Matthews Jessica L. , Cesarini Maria S. , Bell Jesse E. 
Published: August 2021

AbstractWhile air temperature has commonly been used to define the onset of the growing season (plant uptake of soil nutrients), there is evidence in the literature suggesting vegetation growth is sensitive to soil temperature. As soil temperature observations become increasingly available from monitoring networks, differences in the start of season (SOS) estimates based on both above and below‐ground temperatures should be explored. In this study, air, surface, and soil (at depths of 5, 10, and 20 cm) temperature from the U.S. Climate Reference Network were used to estimate SOS at 104 stations across the U.S.. Temperature thresholds of 0, 5, or 10°C were used to estimate the SOS as the earliest date of the year when temperatures remained above each threshold. SOS dates based on temperature were compared with MODIS‐satellite‐derived normalized difference vegetation index (NDVI). Results indicated that the day‐of‐year of SOS based on soil temperature occurred about two months earlier than SOS estimates from air and surface temperatures. Overall, 5 cm soil temperature SOS estimates using a 5°C threshold matched well with SOSNDVI; albeit, only slightly better than air temperature SOS estimates using the 0°C threshold. This was in part because air temperature conditions were more likely to dip back below a given threshold with the passage cold fronts than soil temperatures. This often resulted in later air temperature SOS estimates particularly in years with sub‐freezing late season cold fronts. This suggests soil temperature can improve SOS estimates for many locations across the U.S.
A Locally Smoothed Terrain‐Following Vertical Coordinate to Improve the Simulation of Fog and Low Stratus in Numerical Weather Prediction Models
Authors: Westerhuis Stephanie , Fuhrer Oliver 
Published: August 2021

AbstractThe correct simulation of fog and low stratus (FLS) is a difficult task for numerical weather prediction (NWP) models. The Swiss Plateau experiences many days with FLS in winter. Most NWP models employ terrain‐following vertical coordinates. As a consequence, the typically flat cloud top is intersected by sloping coordinate surfaces above hilly terrain such as the Swiss Plateau. Horizontal advection across the sloping coordinate surfaces leads to spurious numerical diffusion which promotes erroneous FLS dissipation. To address this problem, we propose a new vertical coordinate formulation which features a local smoothing of the model levels. We demonstrate the positive impact of the new vertical coordinate formulation on a case study in detail and for a full month using the COSMO model. The improved vertical coordinate formulation is not yet sufficient to obtain perfect FLS forecasts, it is however a crucial aspect to consider on the way thereto.
A Dynamic Light Scattering Approach for Detection of Nanomaterials in Tennessee River
Authors: Tareq Syed Mohammed , Boutchuen Armel , Roy Shuvashish , Zimmerman Dell , Jur Gitapun , Bathi Jejal Reddy , Palchoudhury Soubantika 
Published: August 2021

AbstractApplication of different engineered nanomaterials is fast‐growing, leading to increased chances of environmental release. Consequently, a robust preliminary detection method for nanomaterials in major ecological environments is beneficial. We report a facile strategy using intensity and number metric of dynamic light scattering to detect presence of nanomaterials in river water. Samples from eight locations of the Tennessee River within Chattanooga were analyzed using our dynamic light scattering technique as a representative assessment of an urban region of Southeastern United States. The average particle sizes (108–294 nm) indicated a possibility of nanomaterials in this region. The results were complemented via scanning electron microscopy. We found that a criteria of identifying peaks at the smallest size distribution for the intensity metric was useful in detecting presence of nanomaterials in environmental samples. The novelty of our approach is the ability to rapidly assess environmental water in solution form with minimum sample preparation artifacts.
A Simple Chamber Design for Calibrating Weiss Saturometers and Recommendations for Measuring and Reporting Total Dissolved Gases
Authors: Pleizier N. K. , Cooke S. J. , Brauner C. J. 
Published: August 2021

AbstractTotal dissolved gas (TDG) supersaturation downstream of features such as hydroelectric dams can cause harmful bubbles to grow in the tissues of aquatic animals. TDG supersaturation is often measured using Weiss saturometers, but information on the calibration and use of these instruments is scarce in the literature. Regular calibration, accurate measurement procedures, and standardized TDG reporting are important for generating reliable measurements that are easily interpreted. We provide a description of low‐cost calibration equipment that practitioners can build themselves and recommend a specific two‐point calibration protocol. We also recommend methods for the more accurate measurement and reporting of TDG.
Severe Convective Wind Environments and Future Projected Changes in Australia
Authors: Brown Andrew , Dowdy Andrew 
Published: August 2021

AbstractThunderstorms can produce severe convective winds (SCWs) that damage buildings and other infrastructure such as electricity transmission towers. Understanding the climatology of SCWs is therefore important for planning and risk management. An archive of observed SCWs is used to examine a diverse set of diagnostics for indicating SCW environments based on reanalysis data. These diagnostics are then applied to climate model data to examine projections of future climate change for Australia. A diagnostic based on logistic regression is found to provide a better representation of observed SCW occurrences than other diagnostics. Projections for the future based on that diagnostic indicate increases and decreases between −16% and 34% in the occurrence frequency of regionally averaged SCW environments, based on the 10th and 90th percentile estimates of annual mean changes from a 12‐member ensemble of global climate models. Projections based on other severe weather diagnostics indicate a wider range of future changes, including increases and decreases of up to 50% in magnitude, with regional and seasonal variations through Australia. Changes in the frequency of SCW environments appears to be largely driven by increased low level moisture concentrations which can lead to increased convective available potential energy, countered in some cases by a stabilization of the mid‐troposphere temperature lapse rate. These results represent the most comprehensive estimate to date for constraining the range of uncertainty in projected future changes in convective environments for Australia, including severe thunderstorms and associated SCWs, noting that this has significant implications for risk management and climate adaptation purposes.
Tracking Downstream Variability in Large Grain‐Size Distributions in the South‐Central Andes
Authors: Purinton Benjamin , Bookhagen Bodo 
Published: August 2021

AbstractMixed sand‐ and gravel‐bed rivers record erosion, transport, and fining signals in their bedload size distributions. Thus, grain‐size data are imperative for studying these processes. However, collecting hundreds to thousands of pebble measurements in steep and dynamic high‐mountain river settings remains challenging. Using the recently published digital grain‐sizing algorithm PebbleCounts, we were able to survey seven large ( 1,000 ) channel cross‐sections and measure thousands to tens‐of‐thousands of grains per survey along a 100‐km stretch of the trunk stream of the Toro Basin in Northwest Argentina. The study region traverses a steep topographic and environmental gradient on the eastern margin of the Central Andean Plateau. Careful counting and validation allows us to identify measurement errors and constrain percentile uncertainties using large sample sizes. In the coarse 2.5 cm fraction of bedload, only the uppermost size percentiles (95th) vary significantly downstream, whereas the 50th and 84th percentiles show less variability. We note a relation between increases in these upper percentiles and along‐channel junctions with large, steep tributaries. This signal is strongly influenced by lithology and geologic structures, and mixed with local hillslope input. In steep catchments like the Toro Basin, we suggest nonlinear relationships between geomorphic metrics and grain size, whereby the steepest parts of the landscape exert primary control on the upper grain‐size percentiles. Thus, average or median metrics that do not apply weights or thresholds to steeper topography may be less predictive of grain‐size distributions in such settings.
Limitations of the Q10 Coefficient for Quantifying Temperature Sensitivity of Anaerobic Organic Matter Decomposition: A Modeling Based Assessment
Authors: Wu Qiong , Ye Rongzhong , Bridgham Scott D. , Jin Qusheng 
Published: August 2021

AbstractThe Q10 coefficient is the ratio of reaction rates at two temperatures 10°C apart, and has been widely applied to quantify the temperature sensitivity of organic matter decomposition. However, biogeochemists and ecologists have long recognized that a constant Q10 coefficient does not describe the temperature sensitivity of organic matter decomposition accurately. To examine the consequences of the constant Q10 assumption, we built a biogeochemical reaction model to simulate anaerobic organic matter decomposition in peatlands in the Upper Peninsula of Michigan, USA, and compared the simulation results to the predictions with Q10 coefficients. By accounting for the reactions of extracellular enzymes, mesophilic fermenting and methanogenic microbes, and their temperature responses, the biogeochemical reaction model reproduces the observations of previous laboratory incubation experiments, including the temporal variations in the concentrations of dissolved organic carbon, acetate, dihydrogen, carbon dioxide, and methane, and confirms that fermentation limits the progress of anaerobic organic matter decomposition. The modeling results illustrate the oversimplification inherent in the constant Q10 assumption and how the assumption undermines the kinetic prediction of anaerobic organic matter decomposition. In particular, the model predicts that between 5°C and 30°C, the decomposition rate increases almost linearly with increasing temperature, which stands in sharp contrast to the exponential relationship given by the Q10 coefficient. As a result, the constant Q10 approach tends to underestimate the rates of organic matter decomposition within the temperature ranges where Q10 values are determined, and overestimate the rates outside the temperature ranges. The results also show how biogeochemical reaction modeling, combined with laboratory experiments, can help uncover the temperature sensitivity of organic matter decomposition arising from underlying catalytic mechanisms.
Modeled Surface‐Atmosphere Fluxes From Paired Sites in the Upper Great Lakes Region Using Neural Networks
Authors: Reed David E. , Poe Jeralyn , Abraha Michael , Dahlin Kyla M. , Chen Jiquan 
Published: August 2021

AbstractThe eddy covariance (EC) method is one of the most widely used approaches to quantify surface‐atmosphere fluxes. However, scaling up from a single EC tower to the landscape remains an open challenge. To address this, we used 63 site years of data to examine simulated annual and growing season sums of carbon fluxes from three paired land‐cover type sites of corn, restored‐prairie, and switchgrass ecosystems. This was also done across the landscape by modeling fluxes using different land‐cover type input data. An artificial neural network (ANN) approach was used to model net ecosystem exchange (NEE), ecosystem respiration (Reco), and gross primary production (GPP) at one paired site using environmental observations from the second site only. With a mean spatial separation of 11 km between paired sites, we were able to model annual sums of NEE, Reco, and GPP with uncertainties of 20%, 22%, and 8%, respectively, relative to observation sums. When considering the growing season only, model uncertainties were 17%, 22%, and 9%, respectively for the three flux terms. We also show that ANN models can estimate sums of Reco and GPP fluxes without needing the constraint of similar land‐cover‐type, with annual uncertainties of 12% and 10%. These results provide new insights to scaling up observations from one EC site beyond the footprint of the EC tower to multiple land‐cover types across the landscape.
A Type‐Curve Approach for Evaluating Aquifer Properties by Interpreting Shallow Strain Measured During Well Tests
Authors: Murdoch Lawrence C. , Germanovich Leonid N. , Roudini Soheil , DeWolf Scott J. , Hua Liwei , Moak Robert W. 
Published: August 2021

AbstractStrains occur at shallow depths in response to pressure changes during well tests in an underlying aquifer, and recent developments in instrumentation have made it feasible to measure essentially the full strain tensor. Simulations using poroelastic analyses indicate that shallow normal strains are approximately proportional to the logarithm of time when a well is injecting into or pumping from a deep aquifer or reservoir. The drawdown is also a linear function of log time, as shown by the classic Cooper‐Jacob type‐curve analysis. The time when the semilog straight line intercepts the zero‐strain axis is similar to the time determined from the Cooper‐Jacob pressure analysis, and it can be used to estimate hydraulic diffusivity, suggesting that horizontal strain data can be used directly to estimate aquifer properties. This approach was validated using measurements from shallow (30‐m deep) borehole strainmeters during an injection test at a 530‐m‐deep sandstone aquifer/reservoir in Oklahoma. The results show intercept times for the shallow normal strain data are essentially the same as for deep pressure data from an equivalent radial distance. The slopes of the semilog plots of the pressure and the strain increase at the same time, suggesting that they both respond to a lateral aquifer boundary. Significantly, though, strain was measured at shallow depths while the pressure data were measured at 530‐m depth. This suggests that strain data from shallow depths could be an effective way to improve the characterization of an underlying aquifer.
Low level of plasminogen increases risk for mortality in COVID-19 patients
Authors: Della-Morte David , Pacifici Francesca , Ricordi Camillo , Massoud Renato , Rovella Valentina , Proietti Stefania , Iozzo Mariannina , Lauro Davide , Bernardini Sergio , Bonassi Stefano , Di Daniele Nicola 
Published: August 2021

AbstractThe pathophysiology of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and especially of its complications is still not fully understood. In fact, a very high number of patients with COVID-19 die because of thromboembolic causes. A role of plasminogen, as precursor of fibrinolysis, has been hypothesized. In this study, we aimed to investigate the association between plasminogen levels and COVID-19-related outcomes in a population of 55 infected Caucasian patients (mean age: 69.8 ± 14.3, 41.8% female). Low levels of plasminogen were significantly associated with inflammatory markers (CRP, PCT, and IL-6), markers of coagulation (D-dimer, INR, and APTT), and markers of organ dysfunctions (high fasting blood glucose and decrease in the glomerular filtration rate). A multidimensional analysis model, including the correlation of the expression of coagulation with inflammatory parameters, indicated that plasminogen tended to cluster together with IL-6, hence suggesting a common pathway of activation during disease’s complication. Moreover, low levels of plasminogen strongly correlated with mortality in COVID-19 patients even after multiple adjustments for presence of confounding. These data suggest that plasminogen may play a pivotal role in controlling the complex mechanisms beyond the COVID-19 complications, and may be useful both as biomarker for prognosis and for therapeutic target against this extremely aggressive infection.