bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surface soil microbiome changes in Grain for Green Project accelerates organic carbon mineralization on the Loess Plateau in China
Authors: Zhang Yi , Liu Xiaojun , Li Peng , Wang Xing , Xiao Lie , Zhou Shixuan 
Published: February 2024

AbstractIncreasing amounts of greenhouse gases, such as CO2, released into the atmosphere have a profound impact on global climate change. Understanding how soil organic carbon (SOC) mineralization changes as a result of land‐use change can shed light on the mechanisms by which SOC mineralization occurs, thus illuminating pathways to achieve global C neutrality targets. Accordingly, the Grain for Green Project (GGP) on the Loess Plateau was used as the starting point to observe how microorganisms affect SOC mineralization through field sampling and laboratory incubation experiments. We found a significant increase in SOC mineralization rates resulting from the GGP, though only at the soil surface (0.47–6.40 mg·kg−1 soil·day−1). We also found that soil microorganisms had a significant effect on different types of C sources, and Proteobacteria and Ascomycota/Mortierellomycota were the dominant bacterial and fungal groups at the GGP sites. The factors limiting SOC mineralization varied with farmland conversion to other land‐use types, and the direct and interactive contributions of these factors were quantified. The explanatory power examined in terms of land‐use ability to directly predict SOC mineralization rates was as follows: farmland (0.82), grassland (0.76), shrubland (0.41), and forestland (0.29). Along the increasing vegetative complexity gradient from farmland to forestland, the individual variable explanatory values decreased, while the relative importance of the interactive effects between variables increased. Our research demonstrates that the GGP increased soil biological activity and improved microbial community ability to metabolize C sources, thereby accelerating SOC mineralization. This will provide a scientific basis for decisions to enhance global semidrought recovery.
Culturally responsive evaluation and emergence: Shifting power through data that is humanizing, liberatory, and healing
Authors: McBride Dominica , Garcia Gabriela , Christian Scott 
Published: February 2024

AbstractIn the process of developing a complicated, community‐driven evaluation initiative, Dr. Stafford Hood indicated the importance of allowing the project to “unfold as it should.” This indication of emergence is too often missing in the dialogue of what it means to do Culturally Responsive Evaluation. This chapter explores and elucidates the concept of emergence and presents two examples of how it has influenced evaluation practice and enhanced the ongoing application of culturally responsive frameworks. The authors provide examples rooted in Dr. Hood's childhood home community while showcasing the power of simple interactions, fluidity, and attending to contextual and human nuances.
An absolute environmental sustainability assessment of food
Authors: Goss Megan A. , Sherwood James 
Published: February 2024

AbstractThe food sector is a major user of land and freshwater and a source of considerable greenhouse gas (GHG) emissions. This puts pressure on Earth systems and jeopardizes the future of food production. The environmental impact of foods is well understood, but our interpretation lacks the context to judge whether those impacts are sufficiently small to describe a food as environmentally sustainable or not. In this work, we describe a metric that converts the environmental impact of foods into a quantitative environmental sustainability scale (performance‐weighted environmental sustainability, PwES). Land use, freshwater use, and GHG emission impacts of common foods have been weighted by their nutritional content and normalized so that values greater than 100% are considered unsustainable. Our findings concur with the conventional wisdom that the high impact of meat is unsustainable, whereas vegetables are typically produced sustainably. Further to this, the PwES metric was used to establish rational targets for sustainable food supply and design nutritious and environmentally sustainable meal plans. It was found that without reductions to the environmental impact of food, it is very difficult to eat sustainably. A high‐bread vegan diet could be found that provided minimum nutritional requirements and was environmentally sustainable.
Employment of an efficient particle tracking algorithm based on barycentric coordinates in hybrid finite‐volume/probability‐density‐function Monte Carlo methods
Authors: Barezban Mohamad Bagher , Darbandi Masoud 
Published: February 2024

AbstractOne main concern of this work is to develop an efficient particle‐tracking‐managing algorithm in the framework of a hybrid pressure‐based finite‐volume/probability‐density‐function (FV/PDF) Monte‐Carlo (MC) solution algorithm to extend the application of FV/PDF MC methods to absolutely incompressible flows and speedup the convergence rate of solving the fluctuating velocity‐turbulent frequency joint PDF equation in turbulent flow simulations. Contrary to the density‐based algorithms, the pressure‐based algorithms have stable convergence rates even in zero‐Mach number flows. As another contribution, literature shows that the past developed methods mostly used mesh searching techniques to attribute particles to cells at the beginning of each tracking time‐step. Also, they had to calculate the linear basis functions at every time‐step to estimate the particle mean fields and interpolate the data. These calculations would be computationally very expensive, time‐consuming, and inefficient in computational domains with arbitrary‐shaped 3D meshes. As known, the barycentric tracking is a continuous particle tracking method, which provides more efficiency in case of handling 3D domains with general mesh shapes. The barycentric tracking eliminates any mesh searching technique and readily provides the convenient linear basis functions. So, this work benefits from these advantages and tracks the particles based on their barycentric coordinates. It leads to less computational work and a better efficiency for the present method. A bluff‐body turbulent flow case is examined to validate the present FV/PDF MC method. From the accuracy perspective, it is shown that the results of the present algorithm are in great agreement with experimental data and available numerical solutions. The present study shows that the number of particle time‐steps required to reach the statistically steady‐state condition is at least one‐sixth less than the previously developed algorithms. This also approves a faster convergence rate for the present hybrid pressure‐based algorithm.
Measuring the advantages of contemporaneous aggregation in forecasting
Authors: Li Zeda , Wei William W. S. 
Published: February 2024

AbstractSuppose an underlying multivariate time series is contemporaneously aggregated under a known aggregation mechanism, and a lower dimensional multivariate aggregated time series is obtained. To forecast the aggregated time series, one could consider two general strategies: first, aggregate the forecasts of the underlying time series; second, forecast the aggregated time series directly. Intuitively, the first strategy should be more accurate, as the underlying time series contains more comprehensive information than the aggregated time series. However, the model‐building process and estimation procedure for the higher dimensional underlying multivariate time series are more complex compared with that for the lower dimensional aggregated time series, which may increase the chances of model misspecification and result in larger estimation errors. Therefore, it may be preferable to forecast the aggregated time series directly. It is then crucial to measure the relative precision between the two forecasting strategies in practice. To this end, we introduce a forecasting measure to quantify the advantages of using contemporaneous aggregation in forecasting in the sense of the mean‐squared error. The forecasting measure is constructed under the assumption that the underlying time series follows the vector autoregressive moving average (VARMA) process. The estimation procedure does not require specifying any particular form of the VARMA, namely, the lag order
and
. Asymptotic properties of the estimation procedure are established, and we evaluate the finite‐sample performance of the proposed method through Monte Carlo simulations and a real data example.
CO2 dynamic mass balance of low permeability reservoir based on “four regions”
Authors: Chen Xiaofan , Wang Jian , Fan Qingzhen , Zhang Rujie , Yue Ping , Li Jian 
Published: February 2024

AbstractIn order to limit the increase in global average temperature to 1.5°C, it is necessary to reduce carbon dioxide (CO2) emissions by 45% by 2030. CO2 capture, utilization and storage (CCUS) is one of the effective ways to reduce CO2 emissions. Geological storage of CO2 provides a solution with the lowest economic cost and the fastest effect for reducing CO2 emissions. This article proposes a CO2 storage regional division method based on the characteristics of low‐permeability reservoirs in the Yanchang W oilfield in China. The storage space is divided into four regions: gas phase region, two‐phase or near‐miscible region, diffusion region, and oil phase region. As the displacement progresses, the volume of the gas phase region and the two‐phase or near‐miscible region gradually increases; the volume of the diffusion region first increases and then decreases. By calculating the storage capacity of each region separately, the total storage capacity is finally calculated. The impact of different pressures and injection rates on dynamic CO2 storage capacity was evaluated. The results show that pressure and injection rate are positively correlated with total storage capacity. When CO2 miscible conditions are reached, the increase in total storage capacity will significantly decrease. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.
Humoral immunity trends in a hemodialysis cohort following SARS‐CoV‐2 mRNA booster: A cohort study
Authors: Goggins Eibhlin , Sharma Binu , Ma Jennie Z. , Gautam Jitendra , Bowman Brendan 
Published: February 2024

AbstractBackground and AimsPatients with end stage kidney disease on hemodialysis are vulnerable to SARS‐CoV‐2 infection. Current guidelines recommend boosters of SARS‐CoV‐2 mRNA‐based vaccines. The long‐term humoral response of hemodialysis patients infected with SARS‐CoV‐2 after receiving a booster of SARS‐CoV‐2 mRNA‐based vaccines has been incompletely characterized. Here, we determined the long‐term humoral response of hemodialysis patients to two and three doses of the Pfizer BioNTech (BNT162b2) mRNA SARS‐CoV‐2 vaccine and investigated the effect of postbooster SARS‐CoV‐2 infection on antibody levels over time.MethodsSamples were collected on a monthly basis and tested for anti‐SARS‐CoV‐2 antibodies against anti‐spike S1 domain. Thirty‐five hemodialysis patients were enrolled in the original study and 27 of these received a booster. Patients were followed up to 6 months after the first two doses and an additional 7 months after the third BNT162b2 dose. Results are presented as the internationally harmonized binding antibody units (BAU/mL).ResultsAntibody level significantly increased from prebooster to 2 weeks postbooster, with a median [25th, 75th percentile] rise from 52.72 [28.55, 184.7] to 6216 [3806, 11,730] BAU/mL in the total population. Of patients with a negative or borderline detectable antibody level 6 months after vaccination who received a third dose, 89% developed positive antibody levels 2 weeks postbooster. Postbooster antibody levels declined an average rate of 29% per month in infection‐naïve patients. Antibody levels spiked in patients infected with SARS‐CoV‐2 after receiving a booster but declined rapidly. No patients infected postbooster required hospitalization.ConclusionsA third dose of BNT162b2 restores antibody levels to high levels in dialysis patients but levels decline over time. A third dose did not necessarily prevent infection, but no patients suffered severe infection or required hospitalization. SARS‐CoV‐2 recovered patients appear to have a blunted rise in antibody levels after a third dose. Although patients infected with SARS‐CoV‐2 postbooster had an immediate spike in antibody levels, these declined over time.
Fragmented QRS, a strong predictor of mortality and major arrhythmic events in patients with nonischemic cardiomyopathy: A systematic review and meta‐analysis
Authors: Zangiabadian Moein , Sharifian Ardestani Mohammad , Rezaee Malihe , Saberi Sharbabaki Elahe , Nikoohemmat Mahdi , Eslami Mohammad , Goudarzi Kian , Sanjari Mojgan , Namazi Mohammad Hasan , Akbarzadeh Mohammad Ali , Aletaha Azadeh 
Published: February 2024

AbstractBackground and AimsFragmented QRS (fQRS), which is associated with rhythm disturbances, can predispose the heart to fatal ventricular arrhythmias. Recently, accumulating studies indicates that fQRS is associated with poor prognosis in various types of cardiomyopathies. Therefore, we assessed the association between fQRS with all‐cause mortality and major arrhythmic events (MAEs) in patients with nonischemic cardiomyopathy, in this systematic review and meta‐analysis study.MethodsWe performed a comprehensive search in databases of PubMed/Medline, EMBASE, and Web of Science from the beginning to December 31, 2022. Published observational studies (cohorts, case–control, or analytical cross‐sectional studies) were included that report the prognostic value of fQRS in patients with different types of nonischemic cardiomyopathies for MAEs (sudden cardiac death, sudden cardiac arrest, sustained ventricular tachycardia [VT], ventricular fibrillation [VF], and appropriate shock) and all‐cause mortality. We pooled risk ratios (RRs) through raw data and adjusted hazard ratios (aHRs) using “Comprehensive Meta‐Analysis” software, Version 2.0.ResultsNineteen cohort and three analytical cross‐sectional studies were included in this meta‐analysis involving a total of 4318 subjects with nonischemic cardiomyopathy (1279 with fQRS and 3039 without fQRS). FQRS was significantly associated with an increased risk of all‐cause mortality in patients with nonischemic cardiomyopathy (pooled RR: 1.920; 95% confidence interval [CI]: 1.388–2.656, p < 0.0001/pooled HR: 1.729; 95% CI: 1.327–2.251, p < 0.0001). Also, the risk of developing MAEs in the presence of fQRS was significantly increased (pooled RR: 2.041; 95% CI: 1.644–2.533, p < 0.0001/pooled HR: 3.626; 95% CI: 2.119–6.204, p < 0.0001). In the subgroup analysis, the strongest association between fQRS presence and increased MAEs was observed in patients with hypertrophic cardiomyopathy (HCM) (pooled RR: 3.44; 95% CI: 2.07–5.71, p < 0.0001/pooled HR: 3.21; 95% CI: 2.04–5.06, p < 0.0001).ConclusionFragmented QRS could be a prognostic marker for all‐cause mortality and MAEs in patients with various types of nonischemic cardiomyopathies, particularly HCM.
Use, reuse, and waste management of single-use products associated with the COVID-19 pandemic in the United States
Authors: Rodriguez Morris Monica I. , Kontar Wissam , Hicks Andrea L. 
Published: February 2024

Abstract
Single-use product usage is not a new concern. However, during the early stages of the COVID-19 pandemic, the use and disposal of single-use products, especially those related to managing the pandemic, rose to prominence. Reports of shortages—and at the same time litter formation arising from improper disposal of various pandemic-related materials such as gloves, masks, wipes, and food takeout containers—were frequently relayed. To address shortages, it was recommended that single-use products be reused in some instances. As these recommendations were widely adopted, it became essential to assess consumer preferences regarding single-use product usage. Aiming to fill that void, a survey was distributed to learn about single-use product usage, possible reuse of single-use products, and waste-management practices during the COVID-19 pandemic in the US. Respondents preferred reusable fabric masks followed by disposable surgical masks. A significant percentage of respondents answered that they would reuse a disposable mask and mostly selected rotating masks as the preferred “disinfection” method in between the reuse of single-use masks. Gloves were not used by most respondents whereas wipes and/or paper towels were used by more than half of respondents. Free-response answers were analyzed for common themes. Concerns related to pandemic-related product use and disposal, and food packaging or food preparation were observed in the free-response answers. This survey reveals that respondents perceived changes in their consumption and waste generation or perceived a change in the type of products consumed and discarded due to the pandemic. Overall, respondents expressed a preference for reuse and a concern over the increase in single-use products. Results of this study can be used to make projections on the consumption and reuse of single-use products in crisis scenarios. In addition, the data can be used to model the use and disposal phase in single-use product life-cycle assessments. Integr Environ Assess Manag 2024;20:1736–1746. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
Key Points
Plastic waste increased during the COVID-19 pandemic. Human behavior with respect to plastic waste is heterogeneous. Face masks in particular reached a new level of use during the pandemic.
Intestinal mRNA expression analysis of polarity‐related genes identified the discriminatory ability of CRB3 as a diagnostic marker for celiac disease
Authors: Taraz Tannaz , Asri Nastaran , Nazemalhosseini‐Mojarad Ehsan , Forouzesh Flora , Rezaei‐Tavirani Mostafa , Rostami‐Nejad Mohammad 
Published: February 2024

AbstractBackgroundCeliac disease (CD) is a chronic autoimmune disorder characterized by an abnormal immune response to gluten, a protein found in wheat, barley, and rye. It is well established that the integrity of epithelial tight junctions (TJs) and adherens junctions (AJs) plays a crucial role in the pathogenesis of CD. These junctional complexes contribute to the apical–basal polarity of the intestinal epithelial cells, which is crucial for their proper functioning.MethodsSixty CD subjects, and 50 controls were enrolled in the current study. Mucosal samples were obtained from the distal duodenum, total RNA was extracted and complementary DNA was synthesized. The relative expression levels of the desired genes were evaluated by quantitative real‐time polymerase chain reaction based on ΔΔCt method. The gene–gene interaction network was also constructed using GeneMANIA.ResultsCRB3 (p = .0005), LKB1 (p < .0001), and SCRIB (p = .0005) had lower expression in CD patients compared to controls, while PRKCZ expression did not differ between groups (p > .05). CRB3 represented a significant diagnostic value for differentiating CD patients from the control group (p = .02).ConclusionThe aim of the current study was to evaluate the changes in the mRNA expression levels of SCRIB, PRKCZ, LKB1, and CRB3 genes in the small intestinal biopsy samples of CD patients in comparison to the healthy control subjects. Our data uncover the importance of polarity‐related genes (especially CRB3) in CD pahtomechanism, that may facilitate the planning of the future studies looking for finding innovative diagnostic and therapeutic strategies for CD.
Association between preoperative systemic immune inflammation index and postoperative sepsis in patients with intestinal obstruction: A retrospective observational cohort study
Authors: Yang Jirong , Ran Taojia , Lin Xiaoyu , Xu Jinyan , Zhou Shaoli , Chen Chaojin , Huang Pinjie 
Published: February 2024

AbstractBackgroundSepsis is a severe complication that results in increased morbidity and mortality after intestinal obstruction surgery. This study examined the role of preoperative systemic immune inflammation index (SII) for postoperative sepsis in intestinal obstruction patients.MethodsData on patients who underwent intestinal obstruction surgery were collected. SII was determined and separated into two groups (≤1792.19 and >1792.19) according to the optimal cut‐off value of SII for postoperative sepsis. The odds ratio (OR) is calculated for the correlation between SII and postoperative sepsis. Additional analyses were used to estimate the robustness of SII.ResultsA total of 371 intestinal obstruction patients undergoing surgery were included in the final cohort, and 60 (16.17%) patients developed postoperative sepsis. Patients with an SII ＞1792.19 had a significantly higher risk for developing postoperative sepsis after multivariable adjustment [adjusted odds ratio = 2.12, 95% confidence interval: [1.02–4.40]]. The analysis of interaction showed no correlation between the preoperative SII and postoperative sepsis regarding age, hypertension, American Society of Anesthesiologists classification, blood loss, albumin, hemoglobin, creatinine, and leukocyte (all interactions p > .05). In subgroup analysis, all statistically significant subgroups showed that SII was a risk factor for postoperative sepsis (all p < .05). The analyses of subgroups and interactions revealed that the interaction effect of a preoperative SII ＞1792.19 and postoperative sepsis remained significant. A sensitivity analysis confirmed the robustness of the results.ConclusionsA preoperative SII ＞ 1792.19 was a risk factor for postoperative sepsis in patients undergoing intestinal obstruction surgery.
Cost‐sensitive machine learning to support startup investment decisions
Authors: Setty Ronald , Elovici Yuval , Schwartz Dafna 
Published: February 2024

SummaryIn 2022, global startup investments exceeded US$445 billion, sourced from entities like venture capital (VC) funds, angel investors, and equity crowdfunding. Despite their role in driving innovation, startup investments often fall short of S&P 500 returns. Surprisingly, the potential of artificial intelligence (AI) remains untapped by investors, despite AI's growing sway in financial decision‐making. Our empirical analysis predicts the success of 10,000 Israeli startups, utilizing diverse machine learning models. Unlike prior research, we employ the MetaCost algorithm to convert models into cost‐sensitive variants, minimizing total cost instead of total error. This innovative approach enables varied costs linked to different prediction errors. Our results underscore that these cost‐sensitive machine learning models significantly reduce risk for VC funds and startup investors compared to traditional ones. Furthermore, these models provide investors with a distinct capability to tailor their risk profiles, aligning predictions with their risk appetite. However, while cost‐sensitive machine learning reduces risk, it may limit potential gains by predicting fewer successful startups. To address this, we propose methods to enhance successful startup identification, including aggregating outcomes from multiple MetaCost models, particularly advantageous for smaller deal flows. Our research advances AI's role in startup investing, presenting a pivotal tool for investors navigating this domain.