bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pre‐Posterior Distributions in Drug Development and Their Properties
Authors: Grieve Andrew P. 
Published: November 2024

ABSTRACTThe topic of this article is pre‐posterior distributions of success or failure. These distributions, determined before a study is run and based on all our assumptions, are what we should believe about the treatment effect if we are told only that the study has been successful, or unsuccessful. I show how the pre‐posterior distributions of success and failure can be used during the planning phase of a study to investigate whether the study is able to discriminate between effective and ineffective treatments. I show how these distributions are linked to the probability of success (PoS), or failure, and how they can be determined from simulations if standard asymptotic normality assumptions are inappropriate. I show the link to the concept of the conditional introduced by Temple and Robertson in the context of the planning of multiple studies. Finally, I show that they can also be constructed regardless of whether the analysis of the study is frequentist or fully Bayesian.
Insights into science, technology, engineering and mathematics (STEM) achievement: A comprehensive review of factors and methodologies
Authors: Bong Debbie Chien Nyut , Chen Chwen Jen 
Published: November 2024

AbstractIn the past decade, numerous literature reviews have delved into understanding the factors influencing STEM achievement. While prior studies have concentrated on specific associations, a holistic synthesis of diverse factors is crucial for comprehensive comprehension. This review, guided by Bronfenbrenner's Ecological Systems Theory, offers an overview of factors associated with secondary school students' STEM achievement by scrutinising literature from 2019 to 2023 through content analysis. Within the myriad associations and subfactors, 15 factors across four ecological levels (i.e., individual characteristics, psychological factors, learning abilities, learning approaches and educational involvement at the self‐level; classroom characteristics and culture, teacher characteristics and instructional practices, family support and influence, and access to resources and technology at the microsystem level; teacher‐parent interaction at the mesosystem level; school characteristics and culture, school leadership and practices, school resources and technology, educational policies, and local environment at the exosystem level) emerged. Methodologically, the reviewed studies predominantly employed quantitative analyses, often utilising statistical and variable‐centred approaches, concentrating on science and mathematics domains of STEM, and employing achievement tests. This review sheds light on the current landscape and provides valuable insights for future policies, practices and research directions.
Context and implicationsRationale for this studyNumerous reviews have explored specific factors influencing STEM achievement, emphasising the need for a holistic synthesis of available factors to achieve a comprehensive understanding of the complex interaction between these influences and how they collectively impact student outcomes in STEM education.Why the new findings matterStudents' achievement in STEM is influenced by various factors, suggesting that attributing success solely to minimal number of factors may oversimplify the complex nature of the factors that influence achievement.Implications for policy makers, practitioners, the public and researchersA thorough understanding of the factors influencing success in STEM achievement can inform the development of educational policies and investments across different levels, from local schools to national initiatives. Educators can use this knowledge to implement tailored early interventions that enhance student achievement and foster better prospects in STEM careers. Additionally, students and parents can benefit from valuable insights to make informed decisions about educational and career pathways. This review also sheds light on future research directions.
Discover the secrets of supercommunicators
Authors: Dennis Marguerite J. 
Published: November 2024

George Bernard Shaw said, “The single biggest problem with communication is the illusion it has taken place.” That's why I think that all college and university administrators, including student affairs professionals, could benefit from the advice that Charles Duhigg presented in his book Supercommunicators. Duhigg is a Pulitzer Prize‐winning investigative journalist who previously worked as a senior editor at The New York Times.
“Mood features of world leaders' commitments to carbon neutrality in COP28 climate communication”
Authors: Karlson Nsom Nsom , Chowdhari Brinda 
Published: November 2024

AbstractThe world faces a critical era for climate action, and research pinpoints the role of linguistic analysis in enhancing our understanding of climate discourses (Zanaty, 2023; Dormer, 2020). In light of this, examining mood features in world leaders’ commitments to carbon neutrality is timely and essential. Defined as the balance between emitted and absorbed carbon (European Parliament, 2023), carbon neutrality has become a focal point in climate agendas. World leaders frequently use public speeches to shape perceptions and drive engagement on the issue. This study analyzes 85 speeches delivered at COP28, sourced from the official United Nations Framework Convention on Climate Change (UNFCCC) website. A sample of 70 speeches was selected using Yamane's formula (1967), and Halliday's Systemic Functional Grammar (1985) was applied to examine 2,553 mood features in these speeches. Findings reveal a significant imbalance in mood feature usage, with 84.17% in the indicative mood to assess climate conditions, 9.67% in the imperative mood for directives, 2.50% in the conditional mood for future vision, 3.17% in the substantive mood for contextual framing, and 0.47% in the interrogative mood for audience engagement. This study underscores the importance of balanced mood features in climate discourses to reinforce global commitment toward emission reduction and to promote a more compelling, resonant narrative for climate action.
Do hiring strategies change in successive entrepreneurial stints?
Authors: Rocha Vera , Pozzoli Dario 
Published: November 2024

AbstractResearch SummaryMost key decisions in startups are linked to their founders, but what entrepreneurs do differently as they launch successive ventures remains poorly understood. Using Danish register data, we investigate how hiring strategies change in successive entrepreneurial stints. We compare the employee sourcing practices of serial entrepreneurs running knowledge‐based startups with those of novice founders in similar industries, who later transition into serial entrepreneurship. We find that serial entrepreneurs, particularly after experiencing a prior failure, engage in pipeline hiring practices (i.e., hiring repeatedly from some external sources) more than their novice counterparts. This finding is robust to different sampling, measurement, and estimation choices. Further investigation into the underlying mechanisms supports the roles of experiential learning and improved employee‐firm matching quality, while excluding alternative explanations.Managerial SummaryHow do hiring strategies evolve across successive entrepreneurial stints? Using employer–employee linked data from Denmark, we investigate the changes in employee sourcing strategies employed by entrepreneurs as they launch successive ventures. We compare the practices of experienced and first‐time founders of knowledge‐based startups and observe a greater tendency to repeatedly hire from some external source organizations (reflected by an increased concentration of hiring sources) among entrepreneurs who have discontinued an underperforming venture. This hiring strategy—known as pipeline hiring—correlates with both higher‐quality hires and improved venture performance. This change in hiring strategy is suggestive of experiential learning. We rule out several alternative explanations and pave the way for future research to further explore the complex impact of entrepreneurial experience on key entrepreneurial strategies.
Fast Autograft Generation Using Transferable 3D Keratinocyte Cell Sheet on PEDOT:PSS Composite PDMS Membrane for Enhancing Wound Healing
Authors: Jang Yeongseok , Lee Dongwon , Oh Jonghyun 
Published: November 2024

AbstractThe application of cell sheet technology for wound healing preserves dense cell tissue and the natural extracellular matrix (ECM), contributing to disease prevention. Despite the effectiveness of autologous and allograft cell sheets for wound healing, conventional cell sheets, although stable, may experience necrosis in their middle layers due to a lack of nutrients or oxygen. To address these issues, a novel approach is proposed to create cell sheets using mechanical and electrical stimulation. This method not only facilitates the transfer of cell sheets but also enhances cell bioactivity. The performance of the proposed membrane, with a mechanically controlled microstructure under electrical stimulation, is validated in both in vitro and in vivo models. The micro‐structured membrane allows for diverse electrical stimulation compared to flat membranes, which accelerates the detachment of cell sheets and promotes angiogenesis and re‐epithelialization. These findings indicate that the innovative cell sheet technology could significantly enhance rapid wound healing in regenerative medicine.
Favorable Moderate Adsorption of Polysulfide on FeNi3 Intermetallic Compound Accelerating Conversion Kinetics for Advanced Lithium–Sulfur Batteries
Authors: Liu Shujun , Guo Tong , Jiang Jun , Qi Zhijie , Zhang Yunfan , Guo Xiangjie , Tang Tian , Bi Min , Wu Zhen , Sun Jingwen , Xiong Pan , Zhang Wenyao , Wang Xin , Zhu Junwu , Fu Yongsheng 
Published: November 2024

AbstractSluggish conversion kinetics of polysulfides during discharge and the severe shuttle effect significantly hinder the practical application of lithium–sulfur (Li–S) batteries. In this work, the lattice engineering strategy of Fe hybridization is employed to manipulate the bulk phase spacing of FeNi3 (space group Pm3m) intermetallic compounds to adjust the 3d electronic structure, optimizing the adsorption of polysulfides, thereby accelerating the catalytic conversion. As a result, FeNi2.25@OC achieves favorable moderate adsorption toward polysulfides. Due to the larger number of electrons occupying the lowest occupied molecular orbital of Li2S4, the S−S bonds are weakened and broken. Temperature‐dependent experiments confirm that FeNi2.25@OC exhibits the lowest activation energy and can effectively accelerate the catalytic conversion of polysulfides. The Li−S cell assembled with FeNi2.25@OC modified PP separator delivers a high initial discharge specific capacity of 1219.5 mAh g−1 at 0.2 C. Even at a high sulfur loading of 6.06 mg cm−2 and lean electrolyte conditions (6 µL mg−1), it can cycle stably for 60 cycles.
A Ratiometric Time‐Gated Luminescence Probe for Imaging H2O2 in Endoplasmic Reticulum of Living Cells and Its Application to Smartphone‐Guided Bioimaging
Authors: Huang Yundi , Chen Kaiwen , Kong Deshu , Song Bo , Zhang Xinyue , Liu Qi , Yuan Jingli 
Published: November 2024

AbstractThe significance of H2O2 as a marker of reactive oxygen species (ROS) and oxidative stress in living organisms has spurred growing interest in its roles in inflammation and disease progression. In this report, a ratiometric time‐gated luminescence (RTGL) probe is proposed based on mixed lanthanide complexes, ER‐BATTA‐Tb3+/Eu3+, for imaging the H2O2 generation both in vitro and in vivo. Upon exposure to H2O2, the probe undergoes cleavage of the benzyl boric acid group, releasing hydroxyl (─OH) groups, which significantly reduces the emission of the Eu3+ complex while slightly increasing the emission of the Tb3+ complex. This response allows the I540/I610 ratio to be used as an indicator for monitoring the H2O2 level changes. The probes are capable of selectively accumulating in the endoplasmic reticulum (ER), allowing effective imaging of H2O2 in the ER of living cells and liver‐injured mice under oxidative stress. Moreover, by integrating ER‐BATTA‐Tb3+/Eu3+ into (polyethylene glycol) PEG hydrogels, the H2O2‐responsive smart sensor films, PEG‐H2O2‐Sensor films, are created, which enable the real‐time monitoring of H2O2 levels in various wounds using a smartphone imaging platform and R/G channel evaluation. The sensor films are also innovatively applied for the in situ monitoring of H2O2 in brains of epileptic rats, facilitating the precise assessment of brain damage. This study provides a valuable tool for the quantitative detection of H2O2 in vitro and in vivo, as well as for the clinical monitoring and treatment of H2O2‐related diseases in multiple scenarios.
Bionanoparticles with In Situ Nitric Oxide Release for Precise Modulation of ER‐TRPV1 Ion Channels in Multimodal Killing of Glioblastoma
Authors: Li Chaoqun , Peng Jinlei , Wang Bing , Gao Dong , Liu Xiaoning , Cheng Guodong , Li Boying , Zhang Ran , Shuai Xintao , Feng Fude , Xing Chengfen 
Published: November 2024

AbstractGlioblastoma (GBM) with highly immunosuppressive tumor microenvironment is a significant factor contributing to its treatment resistance and low survival rate. The activation of the transient receptor potential vanilloid 1 (TRPV1) ion channel, which is overexpressed on the endoplasmic reticulum (ER) of GBM cells, governs the control of multi‐organelle stress pathway branches to inhibit GBM expansion. Precise modulation of ER‐TRPV1 is considered an effective strategy for inhibition of GBM. As an effective intracellular and extracellular second messenger, nitric oxide (•NO) activates the TRPV1 ion channel through nitrosylation of cysteine residues. However, the short lifespan and limited effective range of •NO makes it challenging to achieve precise regulation of ER‐TRPV1. Herein, a biomimetic upconversion nanoassembly (M‐UCN‐T) is constructed, which encapsulates an organic •NO donor and is coated with homologous tumor‐targeting cell membrane and ER‐targeting peptide. In response to near‐infrared light and glutathione, M‐UCN‐T releases •NO in situ to activate the ER‐TRPV1 ion channels. This study developed a •NO‐targeted release nanoplatform with stepwise targeting functions, which allow for the precise modulation of ER‐TPRV1 in GBM through in situ release of •NO. This approach induces multi‐organelle stress signaling pathways, ultimately resulting in multi‐modal killing of tumor cells.
Covalent Organic Frameworks with Constrained Palladium Nanoclusters Lock the Enol‐Keto Tautomerism Enhancing Hydrogen Peroxide Photosynthesis
Authors: Zhou Jie , Chen Jinyang , Li Na , Gou Faliang , Yang Zhen , Zeng Minfeng , Shao Mingchao 
Published: November 2024

AbstractThe production of hydrogen peroxide from natural seawater is green and sustainable. However, the efficiency of photocatalytic hydrogen peroxide production is low due to the degradation and poisoning of photocatalysts by the abundant ions in natural seawater. Precisely controlling the structure of photocatalysts to enhance their corrosion resistance and minimize the impact of external particles is a challenging task. Here, a novel molecular engineering strategy is reported in which confined Pd nanoclusters locked keto structures to enhance photocatalytic hydrogen peroxide production. Both experimental and theoretical findings reveals that Pd nanoclusters, when confined within a keto structure, not only bolster the stability of the photocatalyst but also augment the efficiency of photogenerated charge carriers' separation and transport. This dual enhancement significantly boosts the photocatalytic performance for hydrogen peroxide synthesis. One of the photocatalysts, TAPT‐2KtTb Pd COF, exhibits an impressive photocatalytic hydrogen peroxide production rate of 2676.3 µmol g−1 h−1, which is one of the highest values reported so far. Integral photocatalyzed H2O2 synthesis using confined Pd nanoclusters locked keto conformation COF provides a new insight for developing innovative photocatalysts for H2O2 synthesis.
Prioritization of Software Bugs Using Entropy‐Based Measures
Authors: Kumari Madhu , Singh Rashmi , Singh V. B. 
Published: November 2024

ABSTRACTOpen‐source software is evolved through the active participation of users. In general, a user request for bug fixing, the addition of new features, and feature enhancements. Due to this, the software repositories are increasing day by day at an enormous rate. Additionally, user distinct requests add uncertainty and irregularity to the reported bug data. The performance of machine learning algorithms drastically gets influenced by the inappropriate handling of uncertainty and irregularity in the bug data. Researchers have used machine learning techniques for assigning priority to the bug without considering the uncertainty and irregularity in reported bug data. In order to capture the uncertainty and irregularity in the reported bug data, the summary entropy–based measure in combination with the severity and summary weight is considered in this study to predict the priority of bugs in the open‐source projects. Accordingly, the classifiers are build using these measures for different machine learning techniques, namely, k‐nearest neighbor (KNN), naïve Bayes (NB), J48, random forest (RF), condensed nearest neighbor (CNN), multinomial logistic regression (MLR), decision tree (DT), deep learning (DL), and neural network (NNet) for bug priority prediction This research aims to systematically analyze the summary entropy–based machine learning classifiers from three aspects: type of machine learning technique considered, estimation of various performance measures: Accuracy, Precision, Recall, and F‐measure and through existing model comparison. The experimental analysis is carried out using three open‐source projects, namely, Eclipse, Mozilla, and OpenOffice. Out of 145 cases (29 products X 5 priority levels), the J48, RF, DT, CNN, NNet, DL, MLR, and KNN techniques give the maximum F‐measure for 46, 35, 28, 11, 15, 4, 3, and 1 cases, respectively. The result shows that the proposed summary entropy–based approach using different machine learning techniques performs better than without entropy‐based approach and also entropy‐based approach improves the Accuracy and F‐measure as compared with the existing approaches. It can be concluded that the classifier build using summary entropy measure significantly improves the machine learning algorithms' performance with appropriate handling of uncertainty and irregularity. Moreover, the proposed summary entropy–based classifiers outperform the existing models available in the literature for predicting bug priority.
Working with Memos
Authors: Mortelmans Dimitri 
Published: November 2024

AbstractMemos are personal instruments that a qualitative researcher generally uses for themself or in team research, whereby ideas are written down when they arise during the analytical process. Memos enhance the analytical depth of qualitative research by allowing researchers to record insights, reflect on data, and document the analysis process. NVivo contains two memoing tools discussed in this chapter: memos and annotations. The creation of memos and annotations is demonstrated, and the connection of memos to data is shown with the memo link.
Preventing an Anti-climatic Response to Climate Change
Authors: Stewart Simon 
Published: November 2024

AbstractThis book has provided a wide-ranging review (from global health issues to individuals traits of climatic vulnerability) of the key issues surrounding climate change and heart disease. In the process it has argued for a ‘paradigm change’ in how clinicians and the broader health system consider ‘where’ people with antecedent risk factors and established forms of heart disease live and work and also ‘when’ climatic conditions in that location, might provoke a clinical crisis and even death. This requires a new mindset around clinical management (including specific sections/reference to climate factors in expert guidelines) and extends to how disease statistics are reported and presented. However, it would be disingenuous to present all the facts, figures and opinions proffered in this book as the unbridled truth or beyond contest. There is still so much to learn and understand about heart disease and other forms of cardiovascular disease—especially beyond high-income populations with well-developed health systems. This truism is even more stark when considering our knowledge (and potential response) to the impact of climate change and how it will affect the global burden of heart disease and other common forms of cardiovascular disease sensitive to external factors. Thus, this final chapter will critically reflect on the topics covered in each chapter and then identify what is needed in terms of action (including new research and resources) to ensure that climate-provoked cardiac events don’t overwhelm already capacity constrained health systems worldwide.
Climate-Driven Variations in Cardiovascular Events
Authors: Stewart Simon 
Published: November 2024

AbstractPrevious chapters have focussed on the broader picture of global health in the context of climate change, before examining why climatic conditions/acute weather events can influence an individual’s heart and broader cardiovascular health through the lens of ‘vulnerability to resilience’. In doing so, an argument for why and how we should alter our collective thinking around the role of climate and health (essentially embracing a new paradigm in providing clinical care) is urgently needed. However, such a radical change would be pointless, or at least a low priority, if there was little evidence that health outcomes are indeed—(1) Shaped and influenced by the weather/climatic conditions, thereby resulting in clinically significant variations in event rates and, (2) Climate change is likely to exacerbate the problem in terms of provoking more events that might be preventable. Thus, in the context of a growing body of research and published data (much of which is gravitating towards a more simplistic “heat is bad” mindset), this chapter provides hard evidence that the timing and frequency of concrete events such as hospital admissions and deaths linked to cardiovascular disease and the main subtypes of heart disease are not random. Instead, they ebb and flow according to both predictable climatic transitions (seasons) and unpredictable weather conditions (heatwaves and cold spells) in different ways.
From Pollution to Parasites
Authors: Stewart Simon 
Published: November 2024

AbstractThis chapter brings together a range of themes covered within the book thus far. It reflects on the diversity of problems different parts of the world are facing as the impact of climate change gathers pace. These problems encompass more cardiac complications arising from the air pollution generated from climate-triggered fires to the proliferation of vector-borne infectious diseases. In doing so, it discusses the complexity of pathways provoked by climatic change that might increase and even extend the burden of heart disease globally. Concurrently, the prospect of some unexpected benefits (in terms of disease reduction due to climate change) are identified. From that global perspective, some important changes in the ‘infectious threats’ posed to people living in the major continents are presented, noting, once again, how the poorest people in the world will likely bear the brunt of any changes in the pattern of disease provoked by climate change.