bluuebunny/crossref_metadata_2025_split huggingface dataset:
Profit optimization for multi-mode repetitive construction project with cash flows using metaheuristics
Authors: Sroka Bartłomiej , Rosłon Jerzy , Podolski Michał , Bożejko Wojciech , Burduk Anna , Wodecki Mieczysław 
Published: April 2021

Abstract
The article presents the profit optimization model for multi-unit construction projects. Such projects constitute a special case of repetitive projects and are common in residential, commercial, and industrial construction projects. Due to the specific character of construction works, schedules of such projects should take into account many different aspects, including durations and costs of construction works, the possibility of selecting alternative execution modes, and specific restrictions (e.g., deadlines for the completion of units imposed by the investor). To solve the NP-hard problem of choosing the order of units’ construction and the best variants of works, the authors used metaheuristic algorithms (simulated annealing and genetic search). The objective function in the presented optimization model was the total profit of the contractor determined on the basis of the mathematical programming model. This model takes into account monthly cash flows subject to direct and indirect costs, penalties for missing deadlines, costs of work group discontinuities, and borrowing losses. The presented problem is very important for maintaining a good financial condition of the enterprise carrying out construction projects. In the article, an experimental analysis of the proposed method of solving the optimization task was carried out in a model that showed high efficiency in obtaining suboptimal solutions. In addition, the operation of the proposed model has been presented on a calculation example. The results obtained in it are fully satisfying.
Analysis of microbial lipids deposited on Mars Global Simulant (MGS-1) by geomatrix-assisted laser desorption/ionization-mass spectrometry
Authors: dos Santos Alef , Rodrigues-Filho Edson , Homem Manoel Gustavo Petrucelli 
Published: April 2021

AbstractLipids are among the organic substances that can work as biosignatures, indicating life in an environment. We present an experimental investigation concerning analysis of lipids from a microbial source deposited on the Mars Global Simulant (MGS-1) regolith by geomatrix-assisted laser desorption/ionization-mass spectrometry (GALDI-MS). Our results indicate that lipids from intact microbial cells of a black yeast strain can be detected in these mimetic samples of Martian soil. These lipid molecules are predominantly associated with the occurrence of adducts in the GALDI-MS spectra. The results can be helpful in the planning of future planetary missions.
Improvements in Cloud and Water Vapor Simulations Over the Tropical Oceans in CMIP6 Compared to CMIP5
Authors: Jiang Jonathan H. , Su Hui , Wu Longtao , Zhai Chengxing , Schiro Kathleen A. 
Published: April 2021

AbstractClouds and water vapor are among the most difficult quantities for global climate models to simulate because they are affected by physical processes that operate over scales unresolved by current climate models. We use NASA satellite data to assess the representation of clouds and water vapor structures in 28 climate models that participate in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Each model is assigned numerical scores based on its performance in simulating spatial mean, variance and pattern correlation of multi‐year mean clouds and water vapor structures in lower, middle, upper troposphere, and near the tropopause over tropical oceans. We find measurable improvements in CMIP6 models relative to CMIP5 models for both clouds and water vapor. The differences between models and satellite observations and the spread across the models are reduced. In addition, we find that the models' equilibrium climate sensitivity (ECS) is correlated with overall performance scores for both CMIP5 and CMIP6 models, with a weaker correlation in CMIP6, suggesting that the models that capture better tropical clouds and water vapor distributions tend to have higher ECS. The physical processes responsible for the apparent correlation between ECS and model performance score warrant further study.
Uncovering the Past and Future Climate Drivers of Wheat Yield Shocks in Europe With Machine Learning
Authors: Zhu Peng , Abramoff Rose , Makowski David , Ciais Philippe 
Published: April 2021

AbstractRecently, yield shocks due to extreme weather events and their consequences for food security have become a major concern. Although long yield time series are available in Europe, few studies have been conducted to analyze them in order to investigate the impact of adverse climate events on yield shocks under current and future climate conditions. Here we designated the lowest 10th percentile of the relative yield anomaly as yield shock and analyzed subnational wheat yield shocks across Europe during the last four decades. We applied a data‐driven attribution framework to quantify primary climate drivers of wheat yield shock probability based on machine learning and game theory, and used this framework to infer the most critical climate variables that will contribute to yield shocks in the future, under two climate change scenarios. During the period 1980–2018, our attribution analysis showed that 32% of the observed wheat yield shocks were primarily driven by water limitation, making it the leading climate driver. Projection to future climate scenarios RCP4.5 and RCP8.5 suggested an increased risk of yield shock and a paradigm shift from water limitation dominated yield shock to extreme warming induced shocks over 2070–2099: 46% and 54% of areas were primarily driven by extreme warming under RCP4.5 and RCP8.5, respectively. A similar analysis conducted on yields simulated by an ensemble of crop models showed that models can capture the negative impact of low water supply but missed the impact of excess water. These discrepancies between observed and simulated yield data call for improvement in crop models.
Dual Carbon Isotope‐Based Source Apportionment and Light Absorption Properties of Water‐Soluble Organic Carbon in PM2.5 Over China
Authors: Mo Yangzhi , Li Jun , Cheng Zhineng , Zhong Guangcai , Zhu Sanyuan , Tian Chongguo , Chen Yingjun , Zhang Gan 
Published: April 2021

AbstractWater‐soluble organic carbon (WSOC) makes up a large fraction of organic carbon, which has attracted considerable attention due to its light absorption properties and effects on human health. However, the poorly constrained sources and light absorption properties of WSOC give rise to large uncertainties in its effects on climate and health, especially in regions with high pollutant loading. Here, we investigated the sources and light absorption properties of WSOC in 10 cities across China by dual carbon isotope analysis and UV−visible spectrophotometry, respectively. Despite a dominant contribution of nonfossil sources, the fossil source contribution to WSOC was higher in China than in other regions of the world. The average mass absorption efficiency of WSOC at 365 nm (MAE365) the fossil source contribution of WSOC were 1.13 ± 0.37 m2/gC and 39.9 ± 9.4%, respectively; both values were higher in northern than southern China. The nonfossil source contribution and δ13C of WSOC exhibited significant seasonal variations, with higher values in cold seasons, likely in association with enhanced corn residue burning. In addition, higher MAE365 in the cold seasons (fall and winter) was strongly related to enhanced biomass burning emissions. However, the fossil source contribution of WSOC showed a positive relationship with MAE365 in the cold seasons. This may be because the primary fossil WSOC emitted directly by coal combustion and the secondary fossil WSOC generated under the high NOx conditions in the cold seasons would enhance the color of the entire WSOC. To limit the impacts of WSOC on regional climate and human health, it is suggested that mitigation strategies should consider spatiotemporal variation in WSOC sources, its light absorption properties, and the various formation pathways.
A Global High‐Resolution Mesoscale Convective System Database Using Satellite‐Derived Cloud Tops, Surface Precipitation, and Tracking
Authors: Feng Zhe , Leung L. Ruby , Liu Nana , Wang Jingyu , Houze Robert A. , Li Jianfeng , Hardin Joseph C. , Chen Dandan , Guo Jianping 
Published: April 2021

AbstractA new methodology is developed to construct a global (60°S–60°N) long‐term (2000–2019) high‐resolution (∼10‐km h) mesoscale convective system (MCS) database by tracking MCS jointly using geostationary satellite infrared brightness temperature (Tb) and precipitation feature (PF) characteristics from the Integrated Multi‐satellitE Retrievals for GPM precipitation data sets. Independent validation shows that the satellite‐based MCS data set is able to reproduce important MCS statistics derived from ground‐based radar network observations in the United States and China. We show that by carefully considering key PF characteristics in addition to Tb signatures, the new method significantly improves upon previous Tb‐only methods in detecting MCSs in the midlatitudes for all seasons. Results show that MCSs account for over 50% of annual total rainfall across most of the tropical belt and in selected regions of the midlatitudes, with a strong seasonality over many regions of the globe. The tracking database allows Lagrangian aspects such as MCS lifetime and translational speed and direction to be analyzed. The longest‐lived MCSs preferentially occur over the subtropical oceans. The land MCSs have higher cloud‐tops associated with more intense convection, and oceanic MCSs have much higher rainfall production. While MCSs are observed in many regions of the globe, there are fundamental differences in their dynamic and thermodynamic structures that warrant a better understanding of processes that control their evolution. This global database provides significant opportunities for observational and modeling studies of MCSs, their characteristics, and roles in regional and global water and energy cycles, as well as their hydrologic and other impacts.
Characterization of the Coherence Between Soil Moisture and Precipitation at Regional Scales
Authors: Wu Dongdong , Di Chongli , Wang Tiejun , Wang Lichun , Chen Xi 
Published: April 2021

AbstractKnowledge of the interplays between soil moisture (SM) and precipitation (P) across different temporal scales is crucial to understand the land‐atmosphere interactions. To examine the factors influencing SM–P coherences, observed long‐term SM and P datasets were obtained from two regional networks (i.e., the Nebraska Mesonet and part of the Soil Climate Analysis Network in Utah) within the continental United States. We evaluated the intricate SM–P interactions by checking high‐ and low‐frequency components using wavelet analysis. The analysis revealed that the global coherence coefficients (GCCs) between SM and P at all frequencies tended to be greater under wetter climatic conditions, suggesting that higher P could promote the SM–P interactions. Moreover, GCCs were more correlated with meteorological factors in Nebraska with wetter climates (e.g., positively with mean annual P and negatively with aridity index at high‐frequency periodicities (daily to 3 monthly), and opposite interactions at low‐frequency periodicities (3 monthly to yearly); whereas, significant correlations emerged between GCCs and soil texture at all frequency periodicities in Utah (e.g., positively with sand fraction while negatively with silt and clay fractions). Part of the reason for the impact of soil texture in Utah was that as the P periodicities weakened with increasing climatic dryness in Utah, soil texture played a more important role in controlling infiltration processes, which directly affected SM–P coherences. Overall, this study demonstrates that SM–P interactions at regional scales were possibly affected by the relative importance of meteorological and local land surface conditions in controlling SM dynamics.
Unsaturated Flow Processes and the Onset of Seasonal Deformation in Slow‐Moving Landslides
Authors: Finnegan N. J. , Perkins J. P. , Nereson A. L. , Handwerger A. L. 
Published: April 2021

AbstractPredicting rainfall‐induced landslide motion is challenging because shallow groundwater flow is extremely sensitive to the preexisting moisture content in the ground. Here, we use groundwater hydrology theory and numerical modeling combined with five years of field monitoring to illustrate how unsaturated groundwater flow processes modulate the seasonal pore water pressure rise and therefore the onset of motion for slow‐moving landslides. The onset of landslide motion at Oak Ridge earthflow in California’s Diablo Range occurs after an abrupt water table rise to near the landslide surface 52–129 days after seasonal rainfall commences. Model results and theory suggest that this abrupt rise occurs from the advection of a nearly saturated wetting front, which marks the leading edge of the integrated downward flux of seasonal rainfall, to the water table. Prior to this abrupt rise, we observe little measured pore water pressure response within the landslide due to rainfall. However, once the wetting front reaches the water table, we observe nearly instantaneous pore water pressure transmission within the landslide body that is accompanied by landslide acceleration. We cast the timescale to reach a critical pore water pressure threshold using a simple mass balance model that considers variable moisture storage with depth and explains the onset of seasonal landslide motion with a rainfall intensity‐duration threshold. Our model shows that the seasonal response time of slow‐moving landslides is controlled by the dry season vadose zone depth rather than the total landslide thickness.
On the Reliability of Parameter Inferences in a Multiscale Model for Transport in Stream Corridors
Authors: Rathore Saubhagya S. , Jan Ahmad , Coon Ethan T. , Painter Scott L. 
Published: April 2021

AbstractNonreacting tracer tests capture information about physical processes in transient storage zones including the hyporheic zone (HZ). However, reliably extracting this information from breakthrough curves (BTCs) and distinguishing the effects of in‐channel dispersion and transient storage are well‐known challenges. Using BTCs from a nonreacting tracer test monitored at multiple locations, we explore ways for reliable parameter estimations. The identifiability of parameters is greatly influenced by the choice of forward and inverse modeling frameworks in addition to the quality of the data. Our forward model is a recently proposed multiscale model that uses subgrid transport models written in the Lagrangian form to represent transport along a diverse set of HZ pathways with a shape‐free distribution of travel times. Joint distributions of HZ and channel parameters are estimated using the Markov Chain Monte Carlo technique. Numerical experiments show ambiguity between channel dispersion and HZ transport when the reach length is too short to allow significant solute‐HZ interaction, the observation period is too brief to observe the tailing behavior, or the solute source is spread in time. In contrast, we obtained reliable parameter estimates by simultaneously fitting BTCs observed at different locations in the test reach using a single set of HZ parameters and section‐specific channel areas and dispersion coefficients. This study demonstrates the estimation of travel time distributions, HZ exchange rates, and channel parameters in a new multiscale approach and offers guidance for extracting reliable parameter estimates from multiple BTCs.
Evolution of Organic Aerosol From Wood Smoke Influenced by Burning Phase and Solar Radiation
Authors: Li Siyuan , Liu Dantong , Hu Dawei , Kong Shaofei , Wu Yangzhou , Ding Shuo , Cheng Yi , Qiu Hao , Zheng Shurui , Yan Qin , Zheng Huang , Hu Kang , Zhang Jiale , Zhao Delong , Liu Quan , Sheng Jiujiang , Ye Jianhuai , He Hui , Ding Deping 
Published: April 2021

AbstractEmissions of carbonaceous aerosols (black carbon [BC] and organic aerosol [OA]) from biomass burning have important climate and human health impacts. Not only the primary emissions are complicated by combustion phases, but also the evolution after emission is not well understood. In this study, single plumes from residential wood burning, extracted from either flaming or smoldering phase, were injected into our novel chamber, to investigate their evolution in real atmospheric conditions with or without solar radiation. Initial compositions of flaming or smoldering plumes were dominated by BC or OA respectively, with higher NOx emission in flaming. Replicable results showed that in light, smoldering plumes had faster secondary OA (SOA) formation than flaming, due to the higher emissions of volatile organic compounds in smoldering. Furanic and carboxylic acid compounds were found to be the main gaseous precursors and products, respectively. Evaporation and photooxidation concurrently caused increased oxidation in the beginning, but at a later stage of evolution, SOA evolution showed remarkable divergence: enhanced oxidation for smoldering but decreased for flaming plumes, leading to a higher oxygen‐to‐carbon ratio for smoldering than flaming up to 0.25. We found the higher NOx emission in flaming promoted the gaseous fragmentation reactions, while the seeding particles dominated by OA in smoldering may cause these contrasting tendencies of OA oxidation between combustion phases. Distinct particulate/gas emissions and resultant evolutions in producing SOA at different combustion phases should be therefore considered in evaluating the impacts of biomass burning emissions.
Comparison of cardiovascular risk factors between children and adolescents with classes III and IV obesity: findings from the APV cohort
Authors: Reinehr Thomas , Tittel Sascha R. , Holle Rolf , Wiegand Susanna , Gellhaus Ines , Hebebrand Johannes , Greber-Platzer Susanne , Denzer Christian , Linke Sabine , Kiess Wieland , Holl Reinhard W. 
Published: April 2021

Abstract
Objective
Obesity is associated with many cardiovascular risk factors (CVRF) in childhood. There is an ongoing discussion whether there is a linear relationship between degree of overweight and deterioration of CVRFs justifying body mass index (BMI) cut-offs for treatment decisions.

Methods
We studied the impact of BMI-SDS on blood pressure, lipids, and glucose metabolism in 76,660 children (aged 5–25 years) subdivided in five groups: overweight (BMI-SDS 1.3 to <1.8), obesity class I (BMI-SDS 1.8 to <2.3), class II (BMI-SDS 2.3–2.8), class III (BMI-SDS > 2.8–3.3), and class IV (BMI-SDS > 3.3). Analyses were stratified by age and sex.

Results
We found a relationship between BMI-SDS and blood pressure, triglycerides, HDL cholesterol, liver enzymes, and the triglycerides–HDL-cholesterol ratio at any age and sex. Many of these associations lost significance when comparing children with obesity classes III and IV: In females < 14 years and males < 12 years triglycerides and glucose parameters did not differ significantly between classes IV and III obesity. Prevalence of dyslipidemia was significantly higher in class IV compared to class III obesity only in females ≥ 14 years and males ≥ 12 years but not in younger children. In girls < 14 years and in boys of any age, the prevalences of type 2 diabetes mellitus did not differ between classes III and IV obesity.

Conclusions
Since a BMI above the highest BMI cut-off was not associated consistently with dyslipidemia and disturbed glucose metabolism in every age group both in boys and girls, measurements of CVRFs instead of BMI cut-off seem preferable to guide different treatment approaches in obesity such as medications or bariatric surgery.
Vascular normalisation as the stepping stone into tumour microenvironment transformation
Authors: Magnussen Anette L. , Mills Ian G. 
Published: April 2021

AbstractA functional vascular system is indispensable for drug delivery and fundamental for responsiveness of the tumour microenvironment to such medication. At the same time, the progression of a tumour is defined by the interactions of the cancer cells with their surrounding environment, including neovessels, and the vascular network continues to be the major route for the dissemination of tumour cells in cancer, facilitating metastasis. So how can this apparent conflict be reconciled? Vessel normalisation—in which redundant structures are pruned and the abnormal vasculature is stabilised and remodelled—is generally considered to be beneficial in the course of anti-cancer treatments. A causality between normalised vasculature and improved response to medication and treatment is observed. For this reason, it is important to discern the consequence of vessel normalisation on the tumour microenvironment and to modulate the vasculature advantageously. This article will highlight the challenges of controlled neovascular remodelling and outline how vascular normalisation can shape disease management.
Genetic inactivation of RIP1 kinase activity in rats protects against ischemic brain injury
Authors: Stark Kimberly , Goncharov Tatiana , Varfolomeev Eugene , Xie Luke , Ngu Hai , Peng Ivan , Anderson Keith R. , Verschueren Erik , Choi Meena , Kirkpatrick Donald S. , Easton Amy , Webster Joshua D. , McKenzie Brent S. , Vucic Domagoj , Bingol Baris 
Published: April 2021

AbstractRIP1 kinase-mediated inflammatory and cell death pathways have been implicated in the pathology of acute and chronic disorders of the nervous system. Here, we describe a novel animal model of RIP1 kinase deficiency, generated by knock-in of the kinase-inactivating RIP1(D138N) mutation in rats. Homozygous RIP1 kinase-dead (KD) rats had normal development, reproduction and did not show any gross phenotypes at baseline. However, cells derived from RIP1 KD rats displayed resistance to necroptotic cell death. In addition, RIP1 KD rats were resistant to TNF-induced systemic shock. We studied the utility of RIP1 KD rats for neurological disorders by testing the efficacy of the genetic inactivation in the transient middle cerebral artery occlusion/reperfusion model of brain injury. RIP1 KD rats were protected in this model in a battery of behavioral, imaging, and histopathological endpoints. In addition, RIP1 KD rats had reduced inflammation and accumulation of neuronal injury biomarkers. Unbiased proteomics in the plasma identified additional changes that were ameliorated by RIP1 genetic inactivation. Together these data highlight the utility of the RIP1 KD rats for target validation and biomarker studies for neurological disorders.