bluuebunny/crossref_metadata_2025_split huggingface dataset:
Decarboxylation of Hydroxybenzoic Acids to Phenol Via Deep Eutectic Solvents
Authors: Oh Da Hae , Rashid Al Mamunur , Yoo Chun‐Jae , Ha Jeong‐Myeong , Koo Bonwook , Choi Jungkyu , Jeong Keunhong , Kim Kwang Ho 
Published: August 2024

AbstractThe development of greener and more sustainable synthesis processes for manufacturing commodity chemicals is of great importance. The majority of current phenol production methods involve harsh reaction conditions with high energy consumption, causing severe environmental pollution. In this study, we present a novel approach for the decarboxylation of hydroxybenzoic acids (HBAs) to phenol using a choline chloride‐urea (ChCl‐urea) deep eutectic solvent (DES). Our study reveals the remarkable dual performance of ChCl‐urea both as a catalyst and solvent for the decarboxylation of HBA, resulting in a high phenol yield (94 mol %) under mild reaction conditions. The proposed reaction pathway, established through a combination of experiments and computational simulations, enhances our understanding of this process. The recyclability of the DES system during decarboxylation was also assessed. Our findings demonstrate that the integration of DES into conventional chemical processes can pave the way for sustainable manufacturing, exemplifying a novel approach for producing phenol from abundant natural resources using designer solvents.
Macroscopic state‐based reactive voltage control of virtual synchronous generator in AC microgrid
Authors: Li Fangyuan , Liu Yan , Liu Yanhong 
Published: August 2024

AbstractIn building a smarter and more flexible low‐carbon smart grid system, alternating current (AC) microgrids using virtual synchronous generator (VSG) technology are viewed as a key link in integrating distributed renewable energy access into the main grid. Given that renewable energy sources (such as solar, hydroenergy, and wind) do not have sufficient capacity for reactive power when not available, AC microgrids face challenges in maintaining stable operation. In order to overcome this difficulty, it is hoped that digging deeper and applying more system information can significantly improve the overall performance of the microgrid. This paper proposes a novel method based on macroscopic state dynamic modeling. This method expands the understanding of the inherent rational control mechanism within the microgrid, enabling the overall control objective of the microgrid to be expressed in a more abstract and direct manner. Additionally, by implementing additional convergence constraint conditions on the macroscopic state dynamics, such as based on some optimality criteria, a set of macroscopic state controllers can be obtained to meet specific performance indicators. Theoretical analysis combined with simulation validation demonstrate the effectiveness of this macroscopic state based control strategy. It proves that when meeting the predefined design requirements, the designed controller can enhance the transient response of microgrids in practical applications, thus supporting higher rate of renewable energy access and promoting the development of the smart grid.
Analysis and design of a three‐coil IPT system with independent dual output ports
Authors: Zhou Xuebin , Dong Kangshuai , Wang Jiabin , Yang Lin 
Published: August 2024

AbstractIndustrial applications tend to involve a substantial assemblage of electronic devices, and it is imperative to consider diverse charging requirements while charging these devices. This paper proposes a three‐coil single‐input‐and‐dual‐output (SIDO) inductive power transfer (IPT) system to meet the charging requirements of different devices. The system includes two independent output ports, providing constant voltage (CV) output and constant current (CC) output for different loads, respectively. In addition, the zero‐phase angle (ZPA) operation can be achieved, thus avoiding injection of reactive power and improving energy transfer efficiency. Unlike previous related studies, the receiver of the proposed SIDO IPT system only includes one receiving coil to pick up energy, eliminating unnecessary cross‐coupling and complex decoupling circuits in traditional IPT systems with multiple outputs. This study first analyzes the CC/CV output theory of the proposed SIDO IPT system in detail, and designs and optimizes the parameters by establishing an equivalent model. Then, the conditions for achieving zero‐voltage switching (ZVS) operation of the inverter are obtained by analyzing the sensitivity of CC/CV performance to the variation of the compensation capacitors. Finally, a verification experimental prototype with 2.5A CC output and 72 V CV output is established to verify the effectiveness of the proposed IPT system.
OMIP‐105: A 30‐color full‐spectrum flow cytometry panel to characterize the immune cell landscape in spleen and tumor within a syngeneic MC‐38 murine colon carcinoma model
Authors: DeNiro Gabriel , Que Kathryn , Fujimoto Trevor , Koo Soo Min , Schneider Bridget , Mukhopadhyay Anandaroop , Kim Jeong , Sawant Anandi , Nguyen Tuan Andrew 
Published: August 2024

AbstractThis panel was designed to characterize the immune cell landscape in the mouse tumor microenvironment as well as mouse lymphoid tissues (e.g., spleen). As an example, using the MC‐38 mouse syngeneic tumor model, we demonstrated that we could measure the frequency and characterize the functional status of CD4 T cells, CD8 T cells, regulatory T cells, NK cells, B cells, macrophages, granulocytes, monocytes, and dendritic cells. This panel is especially useful for understanding the immune landscape in “cold” preclinical tumor models with very low immune cell infiltration and for investigating how therapeutic treatments may modulate the immune landscape.
Multi‐cohort survival of northern red oak seedlings at a northern hardwood forest transition
Authors: Cleavitt Natalie L. , Battles John J. , Matthes Jaclyn Hatala , Wentzell‐Brehme Sage 
Published: August 2024

AbstractGlobal change has created less stable forest systems and given urgency to understanding limitations to the establishment of tree seedlings beyond current range boundaries. We quantified trends in 13 years of annual northern red oak (QURU) seedling survival data for 1733 marked individuals at a local species distribution boundary within the northern hardwood forest in New Hampshire, USA. Over the study period, the median distance of seedlings into the valley did not change, although there was a net gain of 89 plots (5 m2) occupied. For a subset of seedlings that were marked in their year of birth (N = 937), we examined relationships among terrain, vegetation community, and initial individual seedling traits, and evaluated their effects on time to seedling mortality using a parametric accelerated failure time model. The year of seedling germination had the largest effect on survival with increasing mortality rates for seedlings from more recent cohorts. Seedlings had longer survival times where oak seedling densities were lower, shrub cover was higher, and when the acorn remained attached. Additionally, survival time was increased in higher elevation plots, which were also located further into the valley. Interannual seedling survival (N = 1580) was strongly impacted by seedling condition in the previous year, particularly leaf number and amount of leaf damage. Most seedling deaths occurred over winter, and seedlings failed to break bud the following spring. Interannual variation in seasonal climate, particularly deep, heavy snowpack in 2019 followed by drought conditions in 2020, coincided with recent elevated mortality. Overall, the median survival time of 3–4 years and the rapid turnover of the oak seedling population currently limit ability for expansion, although the net gain of occupied plots and increase in survival at higher elevation plots with lower QURU densities present some mechanisms that could promote expansion if the current suboptimal understory conditions shift to favor QURU.
Influence of nano graphene filler on hardness, impact strength and density of glass epoxy composites
Authors: Mangisetty Srinivasaiah Aswathanarayan , Nagaraja Santhosh , Munipapanna Aswatha , Bellary Gopalakrishna Sumana , Krishnappa Manjunath , Hassan Venkataramaiah Harish 
Published: August 2024

AbstractThis study investigates the effects of graphene reinforcement on the hardness and impact strength of glass epoxy composites. Four different materials were examined: pure epoxy (EP), glass epoxy (GE), glass epoxy with 1 wt.% graphene (GE1), and glass epoxy with 2 wt.% graphene (GE2). The results show that the incorporation of graphene significantly enhances the hardness of the composites. Pure epoxy (EP) exhibited a Shore D hardness of 60 and an impact strength of 0.09 J/m2. The glass epoxy (GE) showed a reduction in hardness to 56 but an increased impact strength of 0.15 J/m2 due to the inclusion of 33 wt.% glass fiber. Further addition of graphene in GE1 and GE2 led to notable improvements in hardness, reaching 68 and 74 Shore D, respectively. However, the impact strength displayed a decrease with the inclusion of graphene, with GE1 and GE2 showing values of 0.13 and 0.11 J/m2, respectively. When transitioning from pure epoxy (EP) to glass epoxy (GE), there is a 6.67% decrease in hardness, while the impact strength increases by 66.67%. Introducing 1 wt.% of graphene to the glass epoxy (GE1) results in a 21.43% increase in hardness but a 13.33% decrease in impact strength. Further adding 2 wt.% of graphene (GE2) leads to an additional 8.82% increase in hardness, though the impact strength decreases by 15.38%. X‐ray diffraction (XRD) analysis has revealed nano graphene presence and distribution, while fractography has revealed its effectiveness in enhancing interfacial adhesion and toughening mechanisms. Furthermore, XRD identifies potential changes in crystallinity or phase composition induced by nano graphene incorporation, further elucidating the composite's structure and properties. The study highlights the novel and significant trade‐offs encountered in optimizing the mechanical properties of epoxy‐based composites by incorporating graphene and glass fiber.
Anthropogenic and meteorological effects on the counts and sizes of moderate and extreme wildfires
Authors: Lawler Elizabeth S. , Shaby Benjamin A. 
Published: August 2024

AbstractThe growing frequency and size of wildfires across the US necessitates accurate quantitative assessment of evolving wildfire behavior to predict risk from future extreme wildfires. We build a joint model of wildfire counts and burned areas, regressing key model parameters on climate and demographic covariates. We use extended generalized Pareto distributions to model the full distribution of burned areas, capturing both moderate and extreme sizes, while leveraging extreme value theory to focus particularly on the right tail. We model wildfire counts with a zero‐inflated negative binomial model, and join the wildfire counts and burned areas sub‐models using a temporally‐varying shared random effect. Our model successfully captures the trends of wildfire counts and burned areas. By investigating the predictive power of different sets of covariates, we find that fire indices are better predictors of wildfire burned area behavior than individual climate covariates, whereas climate covariates are influential drivers of wildfire occurrence behavior.
Unlocking Biological Activity and Metabolomics Insights: Primary Screening of Cyanobacterial Biomass from a Tropical Reservoir
Authors: Médice Rhuana Valdetário , Arruda Renan Silva , Yoon Jaewon , Borges Ricardo Moreira , Noyma Natália Pessoa , Lürling Miquel , Crnkovic Camila Manoel , Marinho Marcelo Manzi , Pinto Ernani 
Published: August 2024

Abstract
Cyanobacterial harmful algal blooms can pose risks to ecosystems and human health worldwide due to their capacity to produce natural toxins. The potential dangers associated with numerous metabolites produced by cyanobacteria remain unknown. Only select classes of cyanopeptides have been extensively studied with the aim of yielding substantial evidence regarding their toxicity, resulting in their inclusion in risk management and water quality regulations. Information about exposure concentrations, co-occurrence, and toxic impacts of several cyanopeptides remains largely unexplored. We used liquid chromatography–mass spectrometry (LC–MS)-based metabolomic methods associated with chemometric tools (NP Analyst and Data Fusion-based Discovery), as well as an acute toxicity essay, in an innovative approach to evaluate the association of spectral signatures and biological activity from natural cyanobacterial biomass collected in a eutrophic reservoir in southeastern Brazil. Four classes of cyanopeptides were revealed through metabolomics: microcystins, microginins, aeruginosins, and cyanopeptolins. The bioinformatics tools showed high bioactivity correlation scores for compounds of the cyanopeptolin class (0.54), in addition to microcystins (0.54–0.58). These results emphasize the pressing need for a comprehensive evaluation of the (eco)toxicological risks associated with different cyanopeptides, considering their potential for exposure. Our study also demonstrated that the combined use of LC–MS/MS-based metabolomics and chemometric techniques for ecotoxicological research can offer a time-efficient strategy for mapping compounds with potential toxicological risk. Environ Toxicol Chem 2024;43:2222–2231. © 2024 SETAC
New forecasting methods for an old problem: Predicting 147 years of systemic financial crises
Authors: du Plessis Emile , Fritsche Ulrich 
Published: August 2024

AbstractThis paper develops new forecasting methods for an old and ongoing problem by employing 13 machine learning algorithms to study 147 years of systemic financial crises across 17 countries. Findings suggest that fixed capital formation is the most important variable. GDP per capita and consumer inflation have increased in prominence whereas debt‐to‐GDP, stock market, and consumption were dominant at the turn of the 20th century. A lag structure and rolling window both improve on optimized contemporaneous and individual country formats. Through a lag structure, banking sector predictors on average describe 28% of the variation in crisis prevalence, the real sector 64%, and the external sector 8%. Nearly half of all algorithms reach peak performance through a lag structure. As measured through AUC,
and Brier scores, top‐performing machine learning methods consistently produce high accuracy rates, with both random forests and gradient boosting in front with 77% correct forecasts, and consistently outperform traditional regression algorithms. Learning from other countries improves predictive strength, and non‐linear models generally deliver higher accuracy rates than linear models. Algorithms retaining all variables perform better than those minimizing the influence of variables.
Front Cover
Authors: Shigeyama Mayu , Nishio Naoki , Wada Akihisa , Mitani Sohei , Morimoto Gaku , Yokoi Sayaka , Mukoyama Nobuaki , Yokoi Mai , van Keulen Stan , Rosenthal Eben , Sone Michihiko 
Published: August 2024

The cover image is based on the article Development of a plant‐based surgical training model for fluorescence‐guided cancer surgery by Mayu Shigeyama MD et al., https://doi.org/10.1002/hed.27835.image
PD‐L1+ macrophage and tumor cell abundance and proximity to T cells in the pretreatment large B‐cell lymphoma microenvironment impact CD19 CAR‐T cell immunotherapy efficacy
Authors: Hirayama Alexandre V. , Wright Jocelyn H. , Smythe Kimberly S. , Fiorenza Salvatore , Shaw Akira N. , Gauthier Jordan , Maloney David G. , Naresh Kikkeri N. , Yeung Cecilia C. S. , Turtle Cameron J. 
Published: August 2024

AbstractCD19‐targeted chimeric antigen receptor T‐cell (CAR‐T) immunotherapy has transformed the management of relapsed/refractory large B‐cell lymphoma (LBCL), yet durable remissions are observed in less than half of treated patients. The tumor microenvironment (TME) is a key and understudied factor impacting CD19 CAR‐T therapy outcomes. Using NanoString nCounter transcriptome profiling (n = 24) and multiplex immunohistochemistry (mIHC, n = 15), we studied the TME in pretreatment biopsies from patients with LBCL undergoing CD19 CAR‐T therapy. Patients who achieved complete response (CR) after CAR‐T therapy demonstrated higher expression of genes associated with T‐cell trafficking and function, whereas those who did not achieve CR had higher expression of genes associated with macrophages and T‐cell dysfunction. Distinct patterns of immune infiltration and fibrosis in the TME were associated with CAR‐T therapy outcomes, and these findings were corroborated using artificial intelligence‐assisted image analyses. Patients who achieved CR had a lower proportion of the biopsy occupied by an interspersed immune infiltrate and a higher proportion of hypocellular/fibrotic regions. Furthermore, mIHC revealed lower density of CD4+ T cells and higher densities of both macrophages and tumor cells expressing PD‐L1 in non‐CR patients. Spatial analysis revealed that PD‐1+ T cells were in close proximity to PD‐L1+ macrophages or PD‐L1+ tumor cells in patients who did not compared to those who did achieve CR after CAR‐T therapy. These findings suggest that morphologic patterns in the TME and engagement of the PD‐1/PD‐L1 axis in pretreatment biopsies may impact CD19 CAR‐T immunotherapy response in patients with LBCL.
Impact of stretching and shrinking on the thermal profile and efficiency of a wet and porous longitudinal fin in motion subject to convection and radiation
Authors: Lalith Kumar S. , Nagaraja H. G. , Gireesha B. J. 
Published: August 2024

AbstractWe consider heat transfer with convection and radiation effect on a longitudinal wet and porous fin. The trapezoidal fin moving at a constant speed is subject to stretching and shrinking, and their influence on the fin's heat transfer rate and thermal distribution is investigated. The governing equation of the model mentioned above is nondimensionalized, and the resultant second‐order nonlinear boundary value problem is solved numerically using the Chebyshev collocation method and validated using the shooting technique. All the simulations are carried out using MATLAB software. The impact of the critical dimensionless parameters on the fin tip temperature, the thermal profile, and the base heat transfer rate are analyzed graphically. Fin efficiency is also computed, and the influence of the pertinent parameters on it is inferred. For a moving fin, the shrinking mechanism favors a faster base heat transfer, an uptick of about 9%, and the stretching fin enhances thermal distribution and efficiency by around 3% and 14%, respectively. The rise is further accelerated with the enhancement of the Peclet number. The fin tapering from that of a rectangular profile () helps achieve a faster heat transfer rate along the fin length, a gain of nearly 22%, when the fin taper ratio varies from 0 to 0.8.
Optimizing task‐analysis instruction: Effects of descriptions and pictures of antecedent stimuli and outcomes
Authors: Tyner Bryan C. , Floumanhaft Steven D. , Marin Ramon , Fienup Daniel M. 
Published: August 2024

AbstractLittle research has examined specific instructional variables that influence the development and effectiveness of task‐analysis instruction. We conducted two experiments using text‐based task analyses to teach college students to create single‐subject reversal design graphs. In Experiment 1, we tested the effects of presenting antecedent and outcome stimuli on graphing performance (accuracy, yield, time to completion). Different groups of participants experienced graphing tutorials with descriptions and pictures of (a) responses; (b) antecedent stimuli and responses; (c) responses and outcomes of correct responses; and (d) antecedent stimuli, responses, and outcomes. In Experiment 2, we compared tutorials with and without pictures. Collectively, the results suggest that graphing accuracy was positively affected by task analyses that included pictures and descriptions of antecedent stimuli and that adding outcome stimuli further benefited graphing accuracy. These results suggest critical instructional elements that should be included in future task analyses of graphing or other complex behavior chains.
Fast and order‐invariant inference in Bayesian VARs with nonparametric shocks
Authors: Huber Florian , Koop Gary 
Published: August 2024

SummaryThe shocks that hit macroeconomic models such as Vector Autoregressions (VARs) have the potential to be non‐Gaussian, exhibiting asymmetries and fat tails. This consideration motivates the VAR developed in this paper that uses a Dirichlet process mixture (DPM) to model the reduced‐form shocks. However, we do not follow the obvious strategy of simply modeling the VAR errors with a DPM as this would lead to computationally infeasible Bayesian inference in larger VARs and potentially a sensitivity to the way the variables are ordered in the VAR. Instead, we develop a particular additive error structure inspired by Bayesian nonparametric treatments of random effects in panel data models. We show that this leads to a model that allows for computationally fast and order‐invariant inference in large VARs with nonparametric shocks. Our empirical results with nonparametric VARs of various dimensions show that nonparametric treatment of the VAR errors often improves forecast accuracy and can be used to analyze the changing transmission of US monetary policy.
Investigating the anticancer properties of six benzothiazolopyrimidine derivatives on colon carcinoma cells, in vitro and in vivo
Authors: Bakharzi Melika , Attar Elham , Garmabi Hossein , Esmaeili Abbas Ali , Bahrami Ahmad Reza , Danehchin Maryam , Matin Maryam M. 
Published: August 2024

AbstractColorectal cancer (CRC) is the third most common cancer in the world. Despite considerable improvements in the treatment of this cancer, further research to discover novel and more effective agents is ongoing. In this study, possible cytotoxic and apoptotic properties of six benzothiazolopyrimidine derivatives were studied. To assess the IC50 values of these agents, MTT assay was performed on HCT 116, CT26, and NIH/3T3 cells. Moreover, cell death mechanism induced by studied compounds was evaluated by PI/annexin V staining. Then, based on molecular docking results and in vitro experiments, the compounds with the highest anticancer properties were further analyzed in vivo in a mouse model of CRC. MTT results indicated that BTP(1) and BTP(4) had the highest selective cytotoxicity on colorectal cancer cells. Furthermore, flow cytometry results demonstrated a considerable increase in the percentage of the early apoptotic cells in BTP(1)‐ and BTP(4)‐treated groups. In vivo studies confirmed the antitumor properties of the two compounds by a significant regression in tumor size of BTP(1)‐ and BTP(4)‐treated mice compared to control groups. Histopathological examination of tumor tissues showed an increased number of apoptotic cells in these two groups compared to the control animals. Additionally, hematoxylin and eosin staining of the spleen and liver of treated mice did not exhibit considerable tissue damage. Thus, BTP(1) and BTP(4) can be considered promising agents in the treatment of colorectal cancer, although further experiments are required to assess their mechanism of action before their application in clinical studies.