bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of food waste and green waste composts on yield and nitrogen‐use efficiency in irrigated tomato crops
Authors: Haas Savannah M. , Horwath William R. , Zhu‐Barker Xia 
Published: May 2024

AbstractComposts are increasingly used to enhance soil health and agricultural sustainability, but their impacts on nitrogen (N) availability are unclear. In a 3‐year field experiment with subsurface drip‐irrigated tomatoes (Solanum lycopersicum), we investigated the effects of food waste and green waste co‐compost (FW) and green waste compost (GW) on yield, nitrogen‐use efficiency (NUE), nitrate leaching potential, and fertilizer N retention. Various combinations of compost rates (0, 9, or 18 t ha−1) and fertilizer N levels (0%, 70%, 85%, and 100% of the recommended rate) were examined, and 15N‐labeled fertilizer was used. In Years 2 and 3, FW and GW either maintained or increased crop yield compared to no compost when 0% or 70% N was applied; however, lower NUE was observed in the compost treatments compared to no compost when 70% or 85% N was supplied. Postharvest, FW showed greater fertilizer N retention in topsoil than GW and controls, while no difference in nitrate leaching potential was found among treatments, except for Year 2 during which FW exhibited the lowest potential. These results suggest that compost can immobilize fertilizer N, reducing its uptake by crops but enhancing soil retention, potentially acting as an N source or a primer of soil N mineralization. Future research is needed to assess compost's impact on N gaseous emissions and distinguish its dual roles as an N source and a soil N mineralization primer. This is essential for developing nutrient management guidelines to minimize N losses.
Ranking genotype, environment, management effects on the optimum nitrogen rate for maize: A cropping system modeling analysis
Authors: Baum Mitchell E. , Sawyer John E. , Castellano Michael J. , Archontoulis Sotirios V. 
Published: May 2024

AbstractRanking the contribution of genotype, environment, and management (G × E × M) on maize's economic optimum nitrogen fertilizer rate (EONR) variability could improve understanding and predictability of EONR. We performed a simulation experiment using the Agricultural Production Systems sIMulator model with the objectives to (1) rank the effects of 24 individual G × E × M factors on the magnitude and interannual variability of the EONR across the US Midwest and (2) investigate the impact of G × M factors on the EONR variability under present and future climate scenarios. Results indicate that genetics (27%), management (31%), and environmental conditions (41%) each influence the EONR variability. Within these broad categories, the top three individual factors impacting the EONR were interannual weather variability, crop radiation use efficiency, and the soil inorganic N carryover from the previous year. The G × E × M factors influenced the yield response to N fertilizer in different ways. Soil‐related factors (e.g., organic matter and residual nitrate) influenced grain yields at the low N rates, while management factors (e.g., planting date and density) influenced yield at all N rates. Combining increases in plant density and changes in genetics synergistically increased the EONR by 15% from baseline. Future climate scenarios without adaptation decreased the EONR and yield loss, but crop adaptation was buffered against the negative climate change impacts. We concluded that 59% of the annual EONR variability is manageable (due to genetics and management) and that G × M factors could buffer climate change's negative effects on crop production. Present results can inform experimental research on N fertilizer and N rate decisions.
Application of volume‐translated rescaled perturbed‐chain statistical associating fluid theory equation of state to pure compounds using an expansive experimental database
Authors: Shi Jialin , Wu Changxu , Liu Honglai , Li Huazhou 
Published: May 2024

AbstractThe performance of the perturbed‐chain statistical associating fluid theory‐type equations of state (PC‐SAFT‐type EOSs) is compromised in predicting properties of pure compounds in the critical region. In our previous research, we introduced an improved volume‐translated rescaled PC‐SAFT EOS (VTR‐PC‐SAFT EOS) by incorporating a dimensionless distance‐function. Such VTR‐PC‐SAFT EOS is built based on a critical point‐based PC‐SAFT EOS that can reproduce the critical temperature, critical pressure, and critical molar volume of pure compounds. VTR‐PC‐SAFT EOS is found to significantly improve the accuracy of phase behavior predictions in both critical and noncritical regions for pure compounds. In this study, we assess the performance of VTR‐PC‐SAFT EOS in reproducing the critical and noncritical properties of 251 pure compounds, encompassing 20 distinct chemical species. The testing results indicate that, compared to the other three PC‐SAFT‐type EOSs, the VTR‐PC‐SAFT EOS can consistently provide more accurate representations of critical and noncritical properties of 251 pure compounds.
Process safety 4.0: Artificial intelligence or intelligence augmentation for safer process operation?
Authors: Arunthavanathan Rajeevan , Sajid Zaman , Amin Md. Tanjin , Tian Yuhe , Khan Faisal , Pistikopoulos Efstratios 
Published: May 2024

AbstractThe growth of artificial intelligence (AI) has allowed industries to automate and improve their efficiency in operations. Especially in process industries, AI helps to develop intelligent models and tools to proactively monitor and predict equipment or system failures, minimize downtime, and optimize maintenance schedules. With the advancements in AI and its ability to perform tasks, there is a growing belief that AI may eventually replace humans. However, the absence of human involvement in operations in the process industry raises safety concerns. Therefore, AI should collaborate with humans rather than replace them in processing facility operations. This technology is referred to as intelligence augmentation (IA). This article (i) presents a detailed comparison between AI and IA's potential in process systems, (ii) identifies the feasibility of using AI and IA in process safety, and (iii) identifies the risk associated with the implementation of AI or IA in process industries.
Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health‐related comorbidities in a community‐dwelling cohort
Authors: Rudolph Marc D. , Sutphen Courtney L. , Register Thomas C. , Whitlow Christopher T. , Solingapuram Sai Kiran K. , Hughes Timothy M. , Bateman James R. , Dage Jeffrey L. , Russ Kristen A. , Mielke Michelle M. , Craft Suzanne , Lockhart Samuel N. 
Published: May 2024

AbstractINTRODUCTIONWe evaluated associations between plasma and neuroimaging‐derived biomarkers of Alzheimer's disease and related dementias and the impact of health‐related comorbidities.METHODSWe examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ‐positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion‐weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N = 299), mild cognitive impairment (MCI; N = 192), or dementia (DEM; N = 65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma‐imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]).RESULTSPlasma biomarkers differed across diagnostic groups (DEM > MCI > CU), were altered in Aβ‐PET‐positive individuals, and were associated with poorer brain health and kidney function.DISCUSSIONeGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers.Highlights
Plasma biomarkers differ across diagnostic groups (DEM > MCI > CU) and are altered in Aβ‐PET‐positive individuals.
Altered plasma biomarker levels are associated with poorer brain health and kidney function.
Plasma and neuroimaging biomarker associations are largely independent of comorbidities.
DNA Methylation in the Anti‐Mullerian Hormone Gene and the Risk of Disease Activity in Multiple Sclerosis
Authors: Giordano Antonino , Pignolet Béatrice , Mascia Elisabetta , Clarelli Ferdinando , Sorosina Melissa , Misra Kaalindi , Bucciarelli Florence , Ferrè Laura , Moiola Lucia , Liblau Roland , Filippi Massimo , Esposito Federica 
Published: May 2024

ObjectiveMultiple sclerosis (MS) has a complex pathobiology, with genetic and environmental factors being crucial players. Understanding the mechanisms underlying heterogeneity in disease activity is crucial for tailored treatment. We explored the impact of DNA methylation, a key mechanism in the genetics‐environment interplay, on disease activity in MS.MethodsPeripheral immune methylome profiling using Illumina Infinium MethylationEPIC BeadChips was conducted on 249 untreated relapsing–remitting MS patients, sampled at the start of disease‐modifying treatment (DMT). A differential methylation analysis compared patients with evidence of disease activity (EDA) to those with no evidence of disease activity (NEDA) over 2 years from DMT start. Utilizing causal inference testing (CIT) and Mendelian randomization (MR), we sought to elucidate the relationships between DNA methylation, gene expression, genetic variation, and disease activity.ResultsFour differentially methylated regions (DMRs) were identified between EDA and NEDA. Examining the influence of single nucleotide polymorphisms (SNPs), 923 variants were found to account for the observed differences in the 4 DMRs. Importantly, 3 out of the 923 SNPs, affecting DNA methylation in a DMR linked to the anti‐Mullerian hormone (AMH) gene, were associated with disease activity risk in an independent cohort of 1,408 MS patients. CIT and MR demonstrated that DNA methylation in AMH acts as a mediator for the genetic risk of disease activity.InterpretationThis study uncovered a novel molecular pathway implicating the interaction between DNA methylation and genetic variation in the risk of disease activity in MS, emphasizing the role of sex hormones, particularly the AMH, in MS pathobiology. ANN NEUROL 2024;96:289–301
Alumina – Stabilized SEI and CEI in Potassium Metal Batteries
Authors: Liu Pengcheng , Hao Hongchang , Singla Aditya , Vishnugopi Bairav S. , Watt John , Mukherjee Partha P. , Mitlin David 
Published: May 2024

AbstractAluminum oxide (Al2O3) nanopowder is spin‐coated onto both sides of commercial polypropene separator to create artificial solid‐electrolyte interphase (SEI) and artificial cathode electrolyte interface (CEI) in potassium metal batteries (KMBs). This significantly enhances the stability, including of KMBs with Prussian Blue (PB) cathodes. For example, symmetric cells are stable after 1,000 cycles at 0.5 mA/cm2–0.5 mAh/cm2 and 3.0 mA/cm2–0.5 mAh/cm2. Alumina modified separators promote electrolyte wetting and increase ionic conductivity (0.59 vs. 0.2 mS/cm) and transference number (0.81 vs. 0.23). Cryo‐stage focused ion beam (cryo‐FIB) analysis of cycled modified anode demonstrates dense and planar electrodeposits, versus unmodified baseline consisting of metal filaments (dendrites) interspersed with pores and SEI. Alumina‐modified CEI also suppresses elemental Fe crossover and reduces cathode cracking. Mesoscale modeling of metal – SEI interactions captures crucial role of intrinsic heterogeneities, illustrating how artificial SEI affects reaction current distribution, conductivity and morphological stability.
An Enzymatic Prodrug‐like Route to Thio and Selenoamides
Authors: Ishida Keishi , Litomska Agnieszka , Dunbar Kyle L. , Hertweck Christian 
Published: May 2024

Abstract6‐Thioguanine (6TG) is a clinically used antitumor agent that was rationally designed as a DNA‐targeting antimetabolite, but it also occurs naturally. 6TG is a critical virulence factor produced by Erwinia amylovorans, a notorious plant pathogen that causes fire blight of pome fruit trees. The biosynthesis of the rare thioamide metabolite involves an adenylating enzyme (YcfA) and a sulfur‐mobilizing enzyme (YcfC), but the mechanism of sulfur transfer and putative intermediates have remained elusive. Through dissection and in vitro reconstitution of the thionation process using diverse substrates, we uncover an intermediate, prodrug‐like thio‐conjugate and elucidate the precise enzyme functions. YcfA not only adenylates GMP but also transfers the mercapto group of l‐cysteine to the activated carbonyl. A designated C−S lyase (YcfC) then cleaves the resulting S‐adduct to yield the thioamide. This pathway is distinct from canonical tRNA sulfur modifications and known enzymatic peptide thionations. By exploring a wide range of substrate surrogates, we exploited the tolerance of the enzyme pair to produce even a seleno analog. This study provides valuable insight into a previously unexplored area of bacterial thioamide formation and lays the groundwork for synthetic biology approaches to produce thioamide antimetabolites.
Characterization of holocellulose extracted from agricultural and food processing byproducts via ecofriendly delignification pulping process
Authors: Lin Chieh‐Yi , Jung Jooyeoun , Zhao Yanyun 
Published: May 2024

AbstractThis study investigated an ecofriendly peracetic acid delignification process to extract holocellulose from various fiber rich plant‐based byproducts (coconut palm spathe/leaf, apple pulp, wine grape pomace, hazelnut shell, and hemp fiber/hurd), and evaluated their physicochemical, morphological, and thermophysical properties in comparison with commercial cellulose nanofibers produced from wood. Holocellulose from coconut palm spathe has long fiber (~846.7 μm), whereas that from wine grape pomace and hazelnut shell exhibits a cylinder shape of particles with short fiber length (~123.8 and ~ 71.1 μm, respectively). Biofilms cast from apple pulp and hemp fiber holocellulose have higher degradation temperature (361 and 358°C, respectively) than biofilms from other materials, thus more thermally stable. All biofilms demonstrate high UV absorbance, and the biofilm cast from apple pulp holocellulose is transparent with smooth surface. Fourier‐transform infrared spectroscopy analysis confirms the presence of cellulose and hemicellulose as the main components in the biofilms, along with traces of residual lignin that remained after the extraction process. This study demonstrates that holocellulose with varied cellulose morphology and polymeric characteristics could be extracted depending on the type of byproducts and be employed to produce sustainable packaging materials.
Processing and performance of 3D‐printed gelatin‐based edible composite hydrogels
Authors: Chen Bicheng , Xu Hongyu , Liu Shiwen , Shi Hanzhe , Tuo Xiaohang , Gong Yumei 
Published: May 2024

Abstract3D‐printed food exhibits unique advantages in precision nutrition food and personalized customization, achieving disease prevention and treatment through personalized nutrition plans and scientific addition. In this study, 3D‐printing and stable structure of gelatin‐based foods were achieved by heating extrusion. On this basis, we compared the relationship between gelatin viscosity and formability, quantified the water diffusion of composite hydrogels, and verified the edibility of each stage and component by gel strength test and texture profile analysis. The optimal content of the composite hydrogel was 35% gelatin and 5% glycerol, and the concentration of TG enzyme solution was 5%. On this basis, the content of brown sugar increased to 15% did not affect the 3D‐printing formability. Therefore, the 3D‐printed gelatin‐based composite hydrogels in this study provided a processing scheme for high adding nutrients to food 3D‐printed products.
Fundamental Principles and Emerging Opportunities for Selectively‐Solvated Block Copolymer Networks in Nonpolar Media: A Perspective
Authors: McFeaters Fontaine E. , Spontak Richard J. 
Published: May 2024

AbstractBlock polymers remain an extensively studied class of macromolecules due to their ability to self‐organize spontaneously as a result of microphase separation into a variety of ordered nanostructures, depending on the number of contiguous sequences (“blocks”) present and their sequential arrangement. These polymers are classified as multifunctional since they exhibit two or more different property sets during application. In this work, the focus is on bicomponent block copolymers composed of soft and hard segments arranged as linear triblock or higher‐order multiblock copolymers and possessing the properties of a thermoplastic elastomer (TPE). Of particular interest are selectively‐solvated TPEs, designated as TPE gels (TPEGs), with precisely‐ and composition‐tunable properties. An important aspect of TPEs and their TPEG analogs is their elasticity, which reflects the ability of the soft block(s) to form a contiguous molecular network connected by dispersed microdomains composed of the hard block. Here, the origins of microphase separation and network formation in styrenic TPEs and TPEGs are explored, and experimental, theoretical, and simulation results are examined to elucidate chemistry‐structure‐property‐processing (CSPP) relationships in these self‐networking materials. Once such relationships are established, several unconventional technologies that can directly benefit from TPEGs, along with TPEGs fabricated from TPEs possessing different chemical moieties, are likewise considered.
Real‐Time Observation of Slowed Charge Density Wave Dynamics in Thinned 1T‐TaS2
Authors: Yin Shenchu , He Keke , Barut Bilal , Randle Michael D. , Dixit Ripudaman , Nathawat Jubin , Adinehloo Davoud , Perebeinos Vasili , Han Jong E. , Bird Jonathan P. 
Published: May 2024

AbstractTransient electrical pulsing is used to investigate the slowed charge density wave (CDW) kinetics of 1T‐TaS2. These measurements distinguish a fast response of the material, consistent with the onset of self‐heating, from much slower transients that occur on timescales orders of magnitude longer than this. The latter variations appear consistent with slow configurational changes in the CDW, which, due to the thin nature of the 1T‐TaS2, can be distinguished from the much faster dynamics of Joule heating. Experiments in which the cooling of the material is interrupted, demonstrate the possibility of “programming” it in different, strongly nonequilibrium, CDW phases. Collectively, the results point to the existence of a complex free‐energy space for the thinned material, whose multi‐valley structure and hidden metastable states govern the resulting thermal and field‐driven dynamics. Crucially, this work demonstrates that while the CDW dynamics in this material may have a thermal character, the timescales associated with these motions can be very different from those on which self‐heating occurs. This discovery will be important for efforts to implement active devices that utilize the CDW states of thinned 1T‐TaS2.
Oregon's Unprecedented Labor Day 2020 Fires: Impacts and Response
Authors: Toth Nancy , Harper Craig , Del Moro Matthew , Henry Robert M. , Fischer Erica C. , Davis Emily Jane 
Published: May 2024

Key TakeawaysThe prevalence of hotter, more destructive wildfires will continue to threaten water systems’ ability to maintain source water quality and effective treatment.Over the Labor Day weekend in 2020, wildfires burned more than one million acres in Oregon; case studies illustrate three communities’ recovery and restoration strategies.Preparing for and responding to wildfires is done most effectively as a collaborative effort of utilities and local organizations and agencies.Utilities can protect their drinking water systems from a distribution standpoint and at a landscape level (i.e., protecting the source water).
A systematic literature review of group contingencies with adults
Authors: Fuhrmann‐Knowles Angela , Deshpande Madhura , Leaf Justin B. 
Published: May 2024

AbstractA group contingency is one in which a common consequence (e.g., a reinforcer or a punisher) is contingent on the behavior of one member of a group, the behavior of part of a group, or the behavior of every member in a group. The most commonly used group contingencies in behavior‐analytic practice and research include interdependent, independent, and dependent group contingencies. Group contingencies are advantageous for multiple reasons, including their versatility, as they have been demonstrated to be effective across individuals, settings, and behaviors. Additionally, they are efficient as they can facilitate behavior change in multiple individuals at once. Previous literature reviews have supported the use of group contingencies with children; however, there has yet to be a systematic literature review conducted on group contingencies with adults. Because group contingencies have multiple benefits, it is important that a literature review be conducted to assess the evidence of these interventions when implemented with adults. A literature review of studies utilizing group contingencies with adults was conducted. Trends across studies, the efficacy of different group contingencies, clinical implications, and recommendations for future research are provided.
Quantitative analysis of CL‐20 explosive by smartphone‐based chemiluminescence method
Authors: Rafee Reihne Sadat , Pouretedal Hamid Reza , Damiri Sajjad 
Published: May 2024

AbstractA new smartphone‐based chemiluminescence method has been introduced for the quantitative analysis of CL‐20 (Hexanitroazaisowuertzitan) explosive. The solvent mixture, oxidizer agent, and concentration of the reactants were optimized using statistical procedures. CL‐20 explosive showed a quenching effect on the chemiluminescence intensity of the luminol−NaClO reaction in the solvent mixture of DMSO/H2O. A smartphone was used as a detector to record the light intensity of chemiluminescence reaction as a video file. The recorded video file was converted to an analytical signal as intensity luminescence–time curve by a written code in MATLAB software. Dynamic range and limit of detection of the proposed method were obtained 2.0–240.0 and 1.1 mg⋅L−1, respectively, in optimized concentrations 1.5 × 10−3 mol⋅L−1 luminol and 1.0 × 10−2 mol⋅L−1 NaClO. Precursors TADB, HBIW, and TADNIW in CL‐20 explosive synthesis did not show interference in measurement the CL‐20 purity. The analysis of CL‐20 spiked samples of soil and water indicated the satisfactory ability of the method in the analysis of real samples. The interaction of CL‐20 molecules and OCl− ions is due to quench of chemiluminescence reaction of the luminol−NaClO.