bluuebunny/crossref_metadata_2025_split huggingface dataset:
MLOsMetaDB, a meta‐database to centralize the information on liquid–liquid phase separation proteins and membraneless organelles
Authors: Orti Fernando , Fernández María Laura , Marino‐Buslje Cristina 
Published: December 2023

AbstractOver the past few years, there has been a focus on proteins that create separate liquid phases in the intracellular liquid environment, known as membraneless organelles (MLOs). These organelles allow for the spatiotemporal associations of macromolecules that dynamically exchange within the cellular milieu. They provide a form of compartmentalization crucial for organizing key functions in many cells. Metabolic processes and signaling pathways in both the cytoplasm and nucleus are among the functions performed by MLOs, which are facilitated by diverse combinations of proteins and nucleic acids. However, disruptions in these liquid–liquid phase separation processes (LLPS) may lead to several diseases, such as neurodegenerative disorders and cancer, among others. To foster the study of this process and MLO function, we present MLOsMetaDB (http://mlos.leloir.org.ar), a comprehensive resource of information on MLO‐ and LLPS‐related proteins. Our database integrates and centralizes available information for every protein involved in MLOs, which is otherwise disseminated across a plethora of different databases. Our manuscript outlines the development and features of MLOsMetaDB, which provides an interactive and user‐friendly environment with modern biological visualizations and easy and quick access to proteins based on LLPS role, MLO location, and organisms. In addition, it offers an advanced search for making complex queries to generate customized information. Furthermore, MLOsMetaDB provides evolutionary information by collecting the orthologs of every protein in the same database. Overall, MLOsMetaDB is a valuable resource as a starting point for researchers studying the many processes driven by LLPS proteins and membraneless organelles.
Novel nonparametric control charts for monitoring dispersion of count data
Authors: Wang Zhiqiong , Wu Qingxia , Qiu Peihua 
Published: December 2023

AbstractCount data are common in practice. Statistical process control for count data thus has attracted much attention in recent years. Most existing methods on this topic focus on the detection of mean shifts of count data based on parametric modeling. However, their assumed parametric models (e.g., the Poisson probability model) are often invalid in practice due mainly to the potential impact of some latent confounding risk factors, which would lead to unreliable performance of the related control charts. In addition, it is highly desirable and important to monitor the dispersion of count data when the Poisson probability model is invalid. To this end, new nonparametric cumulative sum control charts and their corresponding self‐starting versions are suggested in this paper for monitoring the dispersion of count data based on data categorization and categorical data analysis. Numerical results show that the proposed method can provide more effective and robust monitoring of count data in comparison with some representative existing methods. A real‐data example is used to demonstrate its implementation and application.
Tracking landscape scale vegetation change in the arid zone by integrating ground, drone and satellite data
Authors: Francis Roxane J. , Kingsford Richard T. , Moseby Katherine , Read John , Pedler Reece , Fisher Adrian , McCann Justin , West Rebecca 
Published: December 2023

AbstractA combined multiscale approach using ground, drone and satellite surveys can provide accurate landscape scale spatial mapping and monitoring. We used field observations with drone collected imagery covering 70 ha annually for a 5‐year period to estimate changes in living and dead vegetation of four widespread and abundant arid zone woody shrub species. Random forest classifiers delivered high accuracy (> 95%) using object‐based detection methods, with fast repeatable and transferrable processing using Google Earth Engine. Our classifiers performed well in both dominant arid zone landscape types: dune and swale, and at extremes of dry and wet years with minimal alterations. This highlighted the flexibility of the approach, potentially delivering insights into changes in highly variable environments. We also linked this classified drone vegetation to available temporally and spatially explicit Landsat satellite imagery, training a new, more accurate fractional vegetation cover model, allowing for accurate tracking of vegetation responses at large scales in the arid zone. Our method promises considerable opportunity to track vegetation dynamics including responses to management interventions, at large geographic scales, extending inference well beyond ground surveys.
Sustaining organic matter in forest soils: What we have learned and what is left
Authors: Prescott Cindy E. 
Published: December 2023

AbstractA concerted research effort over the last three decades has transformed our understanding of the processes through which soil organic matter (SOM) is formed. Although recalcitrant plant litter is important, especially for particulate organic matter, we now know that a large proportion of SOM, particularly the more persistent material associated with soil minerals, has been transformed by soil microorganisms. A major source of energy for these microorganisms is labile compounds that are exuded by plant roots and associated mycorrhizal fungi. Much of this exuded carbon (C) arises from surplus carbohydrates produced by plants growing under mild‐to‐moderate deficiencies of nitrogen, phosphorus, or water. Managing forests in a manner that sustain or enhance this flux of labile C from trees to soil would augment efforts to sequester more C in forest soils.
The generalized hyperbolic family and automatic model selection through the multiple‐choiceLASSO
Authors: Bagnato Luca , Farcomeni Alessio , Punzo Antonio 
Published: December 2023

AbstractWe revisit the generalized hyperbolic (GH) distribution and its nested models. These include widely used parametric choices like the multivariate normal, skew‐, Laplace, and several others. We also introduce the multiple‐choice LASSO, a novel penalized method for choosing among alternative constraints on the same parameter. A hierarchical multiple‐choice Least Absolute Shrinkage and Selection Operator (LASSO) penalized likelihood is optimized to perform simultaneous model selection and inference within the GH family. We illustrate our approach through a simulation study and a real data example. The methodology proposed in this paper has been implemented in R functions which are available as supplementary material.
Physicochemical and compositional properties of blended beef patties formulated with pea and faba bean protein isolates and texturized pea protein
Authors: Miao Xinyu , Hastie Melindee , Ha Minh , Shand Phyllis J. , Warner Robyn D. 
Published: December 2023

AbstractThis study investigated the physicochemical characteristics of blended beef patties formulated with pea and faba bean protein isolates (PPI and FPI, respectively) and hydrated texturized pea protein (HTPP, 1 part TPP: 2 parts water). Minced beef was combined with nothing (control) or 4.25% PPI/FPI and 0%, 8.5%, 21.3%, or 42.5% HTPP. The pH, Warner‐Bratzler shear force (WBSF), texture profile analysis (TPA), compression juiciness, cooking loss, color, and chemical composition were determined. In general, plant proteins increased pH values and ash content, and decreased cooking loss and fat content of blended meat patties. The addition of PPI/FPI did not lead to substantial changes in texture or color but resulted in lower cooking loss. HTPP resulted in decreased WBSF, hardness, and other TPA attributes. The combination of PPI/FPI as binders/gelling agents and HTPP as a meat extender resulted in a softer texture than conventional beef patties. This study provides an indication of PPI, FPI, and HTPP functionality in blended meat product formulation.
To commercialize inside or outside of the firm: Behavioral considerations in patent exploitation by family firms
Authors: Birhanu Addis Gedefaw , Gambardella Alfonso 
Published: December 2023

AbstractResearch SummaryThis article examines the relationship between family ownership and patent use strategy using primary data from a patent survey, as well as patent and firm‐level data from secondary sources. The findings reveal that family firms are less likely than non‐family firms to license their patents and more likely to internally commercialize them. We show that the decision of family firms to license less does not depend on lower patent quality or inefficient patent use. Instead, it arises from their preference for patent uses that allow them to exert greater control over the value they can derive from their innovations. We also show that family firms commercialize more patents because they leverage their managerial discretion to explore and seize emerging internal patent commercialization opportunities.Managerial SummaryWhether the desire of families in family firms to maintain control over the company and strategic resources negatively impacts their economic performance has important governance implications. Within the context of patent commercialization, in line with this desire for control, our study highlights the preference of family firms to prioritize internal commercialization over licensing. To offset their underlicensing tendency, family firms internally commercialize more patents by being nimble to identify and capitalize on emerging commercialization opportunities. This enables them to align their control ambitions with patent commercialization efficiency, akin to nonfamily firms.
One‐Pot Colloidal Synthesis Enables Highly Tunable InSb Short‐Wave Infrared Quantum Dots Exhibiting Carrier Multiplication
Authors: Mir Wasim J. , Sheikh Tariq , Nematulloev Saidkhodzha , Maity Partha , Yorov Khursand E. , Emwas Abdul‐Hamid , Hedhili Mohamed Nejib , Khan Mudeha Shafat , Abulikemu Mutalifu , Mohammed Omar F. , Bakr Osman M. 
Published: December 2023

AbstractColloidal quantum dots (CQDs) are emerging materials for short‐wave infrared (SWIR, ≈1100–3000 nm) photodetectors, which are technologically important for a broad array of applications. Unfortunately, the most developed SWIR CQD systems are Pb and Hg chalcogenides; their toxicity and regulated compositions limit their applications. InSb CQD system is a potential environmentally friendly alternative, whose bandgap in theory, is tunable via quantum confinement across the SWIR spectrum. However, InSb CQDs are difficult to exploit, due to their complex syntheses and uncommon reactive precursors, which greatly hinder their application and study. Here, a one‐pot synthesis strategy is reported using commercially available precursors to synthesize—under standard colloidal synthesis conditions—high‐quality, size‐tunable InSb CQDs. With this strategy, the large Bohr exciton radius of InSb can be exploited for tuning the bandgap of the CQDs over a wide range of wavelengths (≈1250–1860 nm) across the SWIR region. Furthermore, by changing the surface ligands of the CQDs from oleic acid (OA) to 1‐dodecanthiol (DDT), a ≈20‐fold lengthening in the excited‐state lifetime, efficient carrier multiplication, and slower carrier annihilation are observed. The work opens a wide range of SWIR applications to a promising class of Pb‐ and Hg‐free CQDs.
Modified Ion Migration via Multi‐Ion Competitive Transportation for Stable Aqueous Zn Metal Batteries
Authors: Li Yuqian , Liu Huanrong , Wang Wenju 
Published: December 2023

AbstractThe application of metal batteries is seriously affected by active ions transport and deposition stability during operation. This article takes water−based Zn metal electrodes as an example to analyze the factors that affect ion distribution and the impact of ion distribution on electrodeposition morphology through electrochemical model simulation calculation, in situ observation and electrochemical experiment: 1) high concentration will reduce the concentration polarization and the overpotential; 2) The passage of active ions through channels are facilitated by small anion (Cl−) rather than bigger one (SO42−), which means small deposition overpotential; 3) The transportability−reaction properties of cations (Zn2+, Li+, Na+ and H+) depends on their concentration, solvent coordination structure, and the energy changes during redox reactions. Based on the diffusion and reaction properties, a Li+ coupled Zn2+ electrolyte is designed to achieve the rapid transportation of doped ions to cover uneven growth sites and maintain a stable interface for the steady deposition of active Zn2+, guiding the interface design for high stability metal batteries in addition to the traditional addition of organic solvents.
A Choline‐Based Antifreezing Complexing Agent with Selective Compatibility for Zn–Br2 Flow Batteries
Authors: Zhao Ming , Cheng Tao , Li Tianyu , Bi Ran , Yin Yanbin , Li Xianfeng 
Published: December 2023

AbstractThe high freezing point of polybromides, charging products, is a significant obstacle to the rapid development of zinc–bromine flow batteries (Zn–Br2 FBs). Here, a choline‐based complexing agent (CCA) is constructed to liquefy the polybromides at low temperatures. Depending on quaternary ammonium group, choline can effectively complex with polybromide anions and form dense oil‐phase that has excellent antifreezing property. Benefiting from indispensable strong ion‐ion interaction, the highly selectively compatible CCA, consisting of choline and N‐methyl‐N‐ethyl‐morpholinium salts (CCA‐M), can be achieved to further enhance bromine fixing ability. Interestingly, the formed polybromides with CCA‐M are able to keep liquid even at −40 °C. The CCA‐M endows Zn–Br2 FBs at 40 mA cm−2 with unprecedented long cycle life (over 150 cycles) and high Coulombic efficiency (CE, average ≈98.8%) at −20 °C, but also at room temperature (over 1200 cycles, average CE: ≈94.7%). The CCA shows a promising prospect of application and should be extended to other antifreezing bromine‐based energy storage systems.
Lyotropic Lamellar Nanostructures Enabled High‐Voltage Windows, Efficient Charge Transport, and Thermally Safe Solid‐State Electrolytes for Lithium‐Ion Batteries
Authors: Ruan Hao , Lu Kai , Meng Shengxi , Zhao Qiang , Ren Haisheng , Wu Yong , Wang Caihong , Tan Shuai 
Published: December 2023

AbstractDeveloping electrolytes combining solid‐like instinct stability and liquid‐like conducting performance will be satisfactory for efficient and durable Li‐ion batteries. Herein lamellar lyotropic liquid crystals (LLCs) demonstrate high‐voltage windows, efficient charge transport, and inherent thermal safety as solid‐state electrolytes in lithium‐ion batteries. Lamellar LLCs are simply prepared by nanosegregation of [C16Mim][BF4] and LiBF4/Propylene carbonate (PC) liquid solutions, which induce lamellar assembly of the liquids as dynamic conducting pathways. Broadened liquid conducting pathways will boost the conducting performance of the LLC electrolytes. The lyotropic lamellar nanostructures enable liquid‐like ion conductivity of the LLC electrolytes at ambient temperatures, as well as provide solid‐like stability for the electrolytes to resist high voltage and flammability overwhelming to LiBF4/PC liquid electrolytes. Despite minor consumption of PC solvents (34.5 wt.%), the lamellar electrolytes show energy conversion efficiency comparable to the liquid electrolytes (PC wt. 92.8%) in Li/LiFePO4 batteries under ambient temperatures even at a 2 C current density, and exhibit attractively robust stability after 200th cyclic charge/discharge even under 60 °C. The work demonstrates LLC electrolytes have great potential to supersede traditional liquid electrolytes for efficient and durable Lithium‐ion (Li‐ion) batteries.
The vital role of community in open source software development: A framework for assessment and ranking
Authors: Singh Jaswinder , Gupta Anu , Kanwal Preet 
Published: December 2023

AbstractOpen source software (OSS) follows a software development paradigm whereby self‐motivated volunteers scattered all around the globe contribute to the development in the form of code, documentation, feedback, feature recommendations, bug reporting, and bug resolution. These volunteers, commonly referred to as OSS project community, serve as the foundation of the OSS project, fostering its creation and sustenance and providing long‐term support. The quality and sustainability of the OSS project is reliant upon the development and structure of the self‐governing community. When a business organization plans to acquire an OSS solution, it not only takes into consideration the factors such as reliability, security, and scalability but also attaches significant importance to the likelihood of the OSS project being maintained and supported in the future so that it can rely on it as a stable and secure technology solution. Modern cloud‐based software hosting platforms, such as GitHub, offer a range of options for automatically and freely accessing the complete development history of millions of OSS projects. This easy availability of detailed development history has enabled researchers to analyze and draw quantitative and scientific inferences about the quality of an OSS project which generally involves assessing three aspects, namely, software product, development process, and project community. With focus on project community part, a Framework for Assessment and Ranking of OSS Community is being presented in the current research work, following a detailed examination of the largest source code hosting and project collaboration platform, GitHub. Technique for Order of Preference by Similarity to Ideal Solution from Multi‐Criteria Decision‐Making toolkit has been utilized for assessing the quality of the project community. The framework has been validated by applying it on nine OSS projects and comparing the results with the outcomes obtained through an existing OSS evaluation methodology. The comparative analysis demonstrated that the proposed framework aligns with the aforementioned evaluation methodology while offering an opportunity for in‐depth analysis on the dynamics of volunteer communities, which is lacking in previous evaluation methods. These insights can prove valuable for both potential adopters and project maintainers, aiding them in making informed strategic decisions.
Unlocking the Potential of 2D MoS2 Cathodes for High‐Performance Aqueous Al‐Ion Batteries: Deciphering the Intercalation Mechanisms
Authors: Pan Wending , Zhang Yulong , Leong Kee Wah , Zhang Yingguang , Mao Jianjun , Wang Yifei , Zhao Xiaolong , Luo Shijing , Leung D.Y.C 
Published: December 2023

AbstractIn recent years, there have been significant advancements in Al‐ion battery development, resulting in high voltage and capacity. Traditionally, only carbon‐based materials with layered structures and strong bonding capabilities can deliver superior performance. However, most other materials exhibited low discharge voltages of 1.4 V, especially in aqueous Al‐ion battery systems lacking anion intercalation. Thus, the development of high‐voltage cathode materials has become crucial. This study introduces 2D MoS2 as a high‐performance cathode for aqueous Al‐ion batteries. The material's interlayer structure enables the intercalation of AlCl4− anions, resulting in high‐voltage intercalation. The resulting battery achieved a high voltage of 1.8 V with a capacity of 750 mAh g−1, contributing to a high energy density of 890 Wh kg−1 and an impressive retention rate of ≈100% after 200 cycles. This research not only sheds light on the high‐voltage anion‐intercalation mechanism of MoS2 but also paves the way for the further development of advanced cathode materials in the field of Al‐ion batteries. By demonstrating the potential of using 2D MoS2 as a cathode material, this finding can lead to the development of more efficient and innovative energy storage technologies, ultimately contributing to a sustainable and green energy future.
“We need to step it up—We are basically the future”: Latinx young women co‐construct science storylines in high school chemistry
Authors: Nation Jasmine , Kang Hosun 
Published: December 2023

AbstractResearchers and practitioners in the United States increasingly promote phenomena‐based instruction in science that supports the development of a coherent storyline throughout the unit. Questions about who is constructing the science storyline and how still remain. Employing a qualitative ethnographic case study approach, we explore how three Latinx female students authentically contribute in their high school chemistry class and change the science storyline originally developed by the teacher. Data include over 950 min of video recordings, student artifacts, and interviews collected from a unit about reaction rate, which was contextualized by students' experiences with a local wildfire. The analysis points to three instructional moves that appear to play an important role in shifting the collective storyline: connecting to Latinx students' personal concerns, moving across multiple figured worlds, and recognizing students' epistemological contributions. Implications for supporting minoritized students are discussed.
Bardoxolone methyl attenuates doxorubicin‐induced cardiotoxicity by inhibiting the TXNIP–NLRP3 pathway through Nrf2 activation
Authors: Zhang Wei , Shi Chao , Yao Zhuoya , Qian Shaohuan 
Published: December 2023

AbstractBardoxolone methyl, which triggers nuclear factor erythroid 2‐related factor (Nrf2), has therapeutic effects against myocardial infarction, heart failure, and other diseases. Nrf2 can inhibit the activation of the thioredoxin‐interacting protein (TXNIP)/NLR family pyrin domain‐containing protein 3 (NLRP3) pathway. Doxorubicin is an anthracycline chemotherapeutic drug associated with cardiotoxicity, limiting its clinical use. In this study, we explored the specific mechanism of the Nrf2–TXNIP–NLRP3 pathway in doxorubicin‐induced cardiotoxicity using bardoxolone methyl in animal and cell models. Using in vivo and in vitro experiments, we show that doxorubicin can induce oxidative stress and pyroptosis in the heart. Western blot and co‐immunoprecipitation experimental results found that doxorubicin can reduce the interaction between TXNIP and TRX, increase the interaction between TXNIP and NLRP3, and activate the pyroptosis process. Bardoxolone methyl reduces the accumulation of reactive oxygen species in cardiomyocytes through the Nrf2 pathway, inhibits the interaction between TXNIP and NLRP3, and alleviates the progression of myocardial damage and cardiac fibrosis. Bardoxolone methyl lost its therapeutic effect when the expression of Nrf2 was decreased. Additionally, repressing the expression of TXNIP can inhibit the activation of NLRP3 and alleviate myocardial damage caused by doxorubicin. Collectively, our findings confirm that bardoxolone methyl alleviates doxorubicin‐induced cardiotoxicity by activating Nrf2 and inhibiting the TXNIP–NLRP3 pathway.