bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trajectories and determinants of acute stress disorder during the COVID‐19 centralized quarantine: A latent class growth analysis
Authors: Chen Bowen , Zhang Jun , Yu Shuxin , Yu Nancy Xiaonan 
Published: November 2023

AbstractCOVID‐19 centralized quarantine may cause acute stress disorder (ASD). However, it is unknown how individuals present heterogeneous ASD trajectories during the COVID‐19 centralized quarantine and what factors contribute to these patterns. This study aimed to identify the ASD trajectories and their determinants during the centralized quarantine period, and the mediating effects of resilience on these associations. A longitudinal survey with three waves was conducted in a randomly selected quarantine hotel in Shenzhen, China from October to November 2020. A total of 273 participants completed online measures assessing ASD symptoms, Eysenck's personality constructs of extraversion (E), neuroticism (N), psychoticism (P), and resilience on Day 1, and reported ASD symptoms on Days 7 and 14 during their 14‐day centralized quarantine periods. Latent class growth analysis identified three trajectories: constantly high symptoms (CHS, 4.76%), decreasing symptoms (DS, 11.72%), and constantly low symptoms (CLS, 83.52%). The CHS and DS subgroups both reported lower E and higher N scores, but not P, compared with the CLS subgroup. Resilience mediated the effects of three personality constructs on ASD trajectories, except for the association between N and DS membership. Our study highlights the heterogeneity in stress responses to the COVID‐19 centralized quarantine. The high‐risk subgroup with persistent ASD symptoms was characterized by lower E and higher N. The resilience process accounted for the effects of personality in shaping distinct ASD trajectories. Our findings have implications to detect the populations vulnerable to ASD and provide insights for developing timely resilience enhancement intervention programs.
Multifunctional Injectable Hydrogel Microparticles Loaded with miR‐29a Abundant BMSCs Derived Exosomes Enhanced Bone Regeneration by Regulating Osteogenesis and Angiogenesis
Authors: Pan Shaowei , Yin Zhaowei , Shi Chen , Xiu Haonan , Wu Guanfu , Heng Yongyuan , Zhu Zhangyu , Zhang Jing , Gui Jianchao , Yu Ziyi , Liang Bin 
Published: November 2023

AbstractThe study investigated whether both the osteogenic and angiogenic potential of Exos (Exosomes) can be enhanced by overexpression of exosomal miRNA (microRNA) and to confirm whether Exos loaded in HMPs (Hydrogel microparticles) exert long‐term effects during new bone formation. BMSCs and Exos are successfully obtained. In vitro and in vivo experiments confirmed that HDAC4 (Histone deacetylase 4) is inhibited by miR‐29a overexpression accompanied by the upregulation of RUNX2 (Runt‐related transcription factor 2) and VEGF (Vascular Endothelial Growth Factor), thereby enhancing osteogenic and angiogenic capabilities. The HMP@Exo system is synthesized from HB‐PEGDA (Hyperbranched Poly Ethylene Glycol Diacrylate)‐ and SH‐HA (Sulfhydryl‐Modified Hyaluronic Acid)‐containing Exos using a microfluidic technique. The HMP surface is modified with RGD (Arg‐Gly‐Asp) peptides to enhance cell adhesion. The system demonstrated good injectability, remarkable compatibility, outstanding cell adhesion properties, and slow degradation capacity, and the sustained release of Agomir‐29a‐Exos (Exosomes derived from Agomir‐29a transfected BMSCs) from HMPs enhanced the proliferation and migration of BMSCs and HUVECs (Human Umbilical Vein Endothelial Cells) while promoting osteogenesis and angiogenesis. Overall, the findings demonstrate that the HMP@Exo system can effectively maintain the activity and half‐life of Exos, accompanied by overexpression of miR‐29a (microRNA‐29a). The injectable system provides an innovative approach for accelerating fracture healing by coupling osteogenesis and angiogenesis.
Self‐Healing Porous Microneedles Fabricated Via Cryogenic Micromoulding and Phase Separation for Efficient Loading and Sustained Delivery of Diverse Therapeutics
Authors: Ling Zhixin , Zheng Yanting , Li Zhiming , Zhao Puxuan , Chang Hao 
Published: November 2023

AbstractSustained‐release drug delivery formulations are preferable for treating various diseases as they enhance and prolong efficacy, minimize adverse effects, and avoid frequent dosing. However, these formulations are associated with poor patient compliance, require trained personnel for administration, and involve harsh manufacturing conditions that compromise drug stability. Here, a self‐healing biodegradable porous microneedle (PMN) patch is reported for sustained drug delivery. The PMN patch is fabricated by a cryogenic micromoulding followed by phase separation, leading to formation of interconnected pores on the surface and internals of MNs. The pores with self‐healing feature enable the PMNs to load hydrophilic drugs with different molecular weights in a mild and efficient manner. The healed PMNs can easily penetrate into the skin under press and detach from the supporting substrate under shear, thereby acting as implantable drug reservoirs for achieving sustained release of drugs for at least 40 days. One‐time administration of desired therapeutics using the sustained‐release healed PMNs resulted in stronger and longer‐lasting efficacy in mitigating psoriasis and eliciting immunity compared to conventional methods with multiple administrations. The self‐healing PMN patch for self‐administrated and long‐acting drug delivery can eventually improve medication adherence in prophylactic and therapeutic protocols that typically require frequent dosages.
CloudSim express: A novel framework for rapid low code simulation of cloud computing environments
Authors: Hewage Tharindu B. , Ilager Shashikant , Rodriguez Maria A. , Buyya Rajkumar 
Published: November 2023

AbstractCloud computing environment simulators enable cost‐effective experimentation of novel infrastructure designs and management approaches by avoiding significant costs incurred from repetitive deployments in real Cloud platforms. However, widely used Cloud environment simulators compromise on usability due to complexities in design and configuration, along with the added overhead of programming language expertise. Existing approaches attempting to reduce this overhead, such as script‐based simulators and graphical user interface (GUI) based simulators, often compromise on the extensibility of the simulator. Simulator extensibility allows for customization at a fine‐grained level, thus reducing it significantly affects flexibility in creating simulations. To address these challenges, we propose an architectural framework to enable human‐readable script‐based simulations in existing Cloud environment simulators while minimizing the impact on simulator extensibility. We implement the proposed framework for the widely used Cloud environment simulator, the CloudSim toolkit, and compare it against state‐of‐the‐art baselines using a practical use case. The resulting framework, called CloudSim Express, achieves extensible simulations while surpassing baselines with over a % reduction in code complexity and an 89.42% reduction in lines of code.
Detection of attacks on software defined networks using machine learning techniques and imbalanced data handling methods
Authors: Hassan Heba A. , Hemdan Ezz El‐Din , El‐Shafai Walid , Shokair Mona , Abd El‐Samie Fathi E. 
Published: November 2023

AbstractSoftware‐defined networks (SDNs) have gained popularity in recent years as a solution for the fundamental issues that affect traditional dispersed networks. The primary advantage of SDNs is the decoupling of the control plane from the data plane, which increases the flexibility of the network. The SDN represents a network architecture of the next generation, however, its configuration options are centralized, leaving it open for cyber‐attacks. This paper concentrates on the early identification of attacks in an SDN environment. When malicious traffic is affecting in an SDN topology, an artificial intelligence (AI) module in the topology is used to detect the attack and stop the attack source using machine learning (ML) techniques. The architecture presented in this research allows for the comparison of several ML classification techniques that are used to identify different sorts of network attacks. For attack detection, eight ML techniques are used, namely logistic regression (LR), linear discriminant analysis (LDA), Naïve Bayes (NB), k‐nearest neighbor (KNN), classification and regression tree (CART), AdaBoost (AB), random forest (RF), and support‐vector machine (SVM) classifiers. These techniques are tested on the InSDN dataset, which is a novel attack‐specific SDN dataset. The results show that the highest accuracy of 98.6% is achieved with the LDA classifier. Further improvement in the accuracy of classification models is observed when random over‐sampling, synthetic minority oversampling technique (SMOTE), random under‐sampling, and under‐sampling with Tomek links and near‐miss concept are applied to address the class imbalance problem. After applying these methods, the LDA classifier showed an accuracy of 98.79%.
Exploring the predictiveness of curiosity and interest in science learning in and after class
Authors: Kang Jihoon , Kim Jina 
Published: November 2023

AbstractScience learning takes place not only in the context of science class but also after class. Students' internal forms of motivation, such as curiosity and interest, affect the entire science learning process in both in‐class and after‐class contexts. In addition, both stable existing learner characteristics, such as science curiosity and interest in a specific natural phenomenon (phenomenon interest), and temporary emotional states, such as state curiosity, are considered essential factors in improving learning. Given the importance of understanding how learners' two aspects of motivational variables influence their science learning in different learning contexts, this study aimed to examine the extent to which existing learner characteristics, such as science curiosity and phenomenon interest, and temporary emotional states, such as state curiosity, predict science learning both during and following class and how these variables are related to exploration after class. To achieve this goal, an explanatory sequential mixed‐method approach was employed, based on a correlational design, with a total of 706 cases from fifth‐grade and sixth‐grade students (45.5% female). In the context of science class, relatively stable existing learner characteristics, such as science curiosity and phenomenon interest, and temporary emotional states, such as state curiosity, were positively associated with learning, and temporary states were more predictive of learning than existing characteristics. In addition, state curiosity was directly related to learning, whereas science curiosity and phenomenon interest were only indirectly related to learning, mediated by state curiosity. In the context of the after‐class, however, only phenomenon interest significantly predicted spontaneous follow‐up learning and was positively associated with students' continued learning. An interpretation of these results was discussed, as well as their implications for science education and future research. Our findings will enable more fine‐grained analyses regarding how curiosity and interest can predict learning in science.
“So, what English do I speak, really?”: A transnational‐translingual‐and‐transracial pracademic inquires into her raciolinguistic entanglements and transraciolinguistic transgressions
Authors: Jain Rashi 
Published: November 2023

AbstractIdentities are fluid, dynamic, and contextual; and identity (co)construction is a deeply contextualized process, especially when seen through postmodern and poststructural lenses. Adopting a qualitative‐researcher‐as‐bricoleuse stance, the author presents an overarching autoethnographic narrative where she specifically analyzes three critical, nonsimplistic, and layered incidents of linguistic racializations, or raciolinguistic entanglements, that occurred across a multiyear timespan and serve to exemplify similar recurring experiences, and which collectively represent a narrative arc of conflict, crisis, and resolution. Building upon Alim's ideas around transracialization and her own prior individual and collaborative inquiries, the author proposes that agentive transnational‐translingual‐and‐transracial participants explore the liminal spaces and generative tensions created when our languages are (mis)racialized and the co‐construction of our raciolinguistic identities gets entangled across inequitable raciolinguistic landscapes. She further suggests that we do so in order to resist and contest the (mis)racialization of our languages and linguistic identities, especially when originating from postcolonial Global South contexts, as both part of our own critical transraciolinguistic transgressions and a broader transraciolinguistic reckoning currently taking place in the Global North.
A journey from univariate to multivariate functional time series: A comprehensive review
Authors: Haghbin Hossein , Maadooliat Mehdi 
Published: November 2023

AbstractFunctional time series (FTS) analysis has emerged as a potent framework for modeling and forecasting time‐dependent data with functional attributes. In this comprehensive review, we navigate through the intricate landscape of FTS methodologies, meticulously surveying the core principles of univariate FTS and delving into the nuances of multivariate FTS. The journey commences with an exploration of the foundational aspects of univariate FTS analysis. We delve into representation, estimation, and modeling, spotlighting the effectiveness of various parametric and nonparametric models at our disposal. The stage then transitions to multivariate FTS analysis, where we confront the intricacies posed by high‐dimensional data. We explore strategies for dimensionality reduction, forecasting, and the integration of diverse parametric and nonparametric models within the multivariate realm. We also highlight commonly used R packages for modeling and forecasting FTS and multivariate FTS. Acknowledging the dynamic evolution of the field, we dissect challenges and chart future directions, paving a course for refinement and innovation. Through a fusion of multivariate statistics, functional analysis, and time series forecasting, this review underscores the interdisciplinary essence of FTS analysis. It not only reveals past accomplishments, but also illuminates the potential of FTS in unraveling insights and facilitating well‐informed decisions across diverse domains.This article is categorized under:
Data: Types and Structure > Time Series, Stochastic Processes, and Functional Data
Statistical and Graphical Methods of Data Analysis > Multivariate Analysis
High‐yield access to long‐sought 1,8‐bis[pinacolato(boryl)]naphthalene
Authors: Scholz Alexander Stefan , Virovets Alexander , Lerner Hans‐Wolfram , Wagner Matthias 
Published: November 2023

AbstractDespite their apparent simplicity and numerous potential applications, 1,8‐bis(boronic ester) derivatives of naphthalene, 1,8‐C10H6[B(OR)2]2, have remained elusive until today. We now disclose a facile access route to this compound class via alkoholysis of the 1,8‐naphthalenediyl‐bridged diborane(6) 1. In the cases of monotopic MeOH or EtOH, the target compounds 1,8‐C10H6[B(OR)2]2 (R=Me (2), Et (4)) are contaminated with about 10 % of the corresponding mixed boronic ester/anhydride. By using ditopic pinacol (pin) or 1,8‐naphthalenediol (ndl), the formation of the undesired side products is suppressed and 1,8‐C10H6(Bpin)2 (6) can be isolated in 80 % yield (due to solubility issues, the yield of 1,8‐C10H6(Bndl)2 (7) is lower and less reproducible). The bis(boronic ester)s 2, 4, 6, and 7 have been structurally characterized by X‐ray diffraction. 6 has a sterically encumbered, remarkably distorted molecular framework with a torsion angle B−C(ipso)−C’(ipso)−B’ of 38.63(9)°.
Practices of Care with the Anthropocene: Scenes from the 2019 Nebraska Flood
Authors: Nordstrom Susan Naomi 
Published: November 2023

AbstractThis chapter, written not too long after the March 2019 US Midwestern floods, responds to those floods and the connective practices of care they created. Inspired by Gough’s (Shaking the treed, making a rhizome: Towards a nomadic geophilosophy of science education. Educational Philosophy and Theory, 38(5), 625–645, 2006) call for more literary and artistic modes of representation in science education, this chapter offers an affect-rich account of the flood and learning to live in the Anthropocene. Drawing on a trip to the area in July 2019, newspaper articles, social media, and discussions with family and friends, this account follows the watery we’s—the connections between humans, nonhumans, and so much more—that the flood collected and the affective practices of care that the flood continues to generate. To do this work, I first situate the 2019 Midwestern flood, with a focus on Eastern Nebraska. Then, I share how I put Puig de la Bellacasa’s (Matters of care: Speculative ethics in more than human worlds. University of Minnesota Press, 2017) conception of care to work by examining moments that created different affect-rich currents in practices of care. This responsive work, told in more artistic modes of representation, aims to create resonating moments for careful thoughts about learning to live in the Anthropocene.
Fluid Accumulation and Deresuscitation
Authors: Malbrain Manu L. N. G. , Wilkinson Jonny , Malbrain Luca , Nasa Prashant , Wong Adrian 
Published: November 2023

AbstractOverzealous fluid administration and capillary leaks may lead to overhydration or tissue edema. The deleterious effects of tissue edema involve disruption of tissue and endothelial glycocalyx, impeding capillary and lymphatic drainage, and causing cellular hypoxia and organ dysfunction. Evidence suggests that a progressive, cumulative positive fluid balance in patients with sepsis is an independent risk factor for organ failure and death. A combination of clinical, laboratory tests (such as hematocrit, brain natriuretic peptide, and serum electrolytes), radiological (point-of-care ultrasound or imaging) and advanced hemodynamic monitor may be used to diagnose and monitor overhydration. Various strategies to avoid and correct overhydration include fluid restriction and deresuscitation. Recent evidence supports the feasibility and safety of fluid restriction after initial resuscitation. Deresuscitation is defined as the active removal of excessive fluid using pharmacological or non-pharmacological measures and was coined during the 2011 International Fluid Academy meeting. A combination of diuretics, ultrafiltration, and fluid restriction, can be used for deresuscitation along with adequate monitoring to prevent hypoperfusion.
A Logical Prescription of Intravenous Fluids
Authors: Wilkinson Jonny , Yates Lisa , Nasa Prashant , Malbrain Manu L. N. G. , Miller Ashley 
Published: November 2023

AbstractThis chapter guides clinicians through the assessment and management of patients requiring intravenous (IV) fluids during hospitalization in the regular ward and ICU. It aims to aid in the determination of the patient’s actual fluid or volume status and guides the prescription and management of electrolyte replacement whilst avoiding potential harm to patients from fluid mismanagement leading to electrolyte disturbances, fluid accumulation, and organ impairment (or a combination). This is referred to as IV Fluid Stewardship, and it incorporates much of the National Institute for Health and Care Excellence (NICE) guidance published.
The Place of Crystalloids
Authors: Singh Amandeep , Chawla Aayush 
Published: November 2023

AbstractCrystalloids are commonly used in medicine as solutions containing electrolytes dissolved in water, with or without glucose. They can be used as maintenance, replacement, or resuscitation fluids, but should be administered with caution. This chapter provides an overview of basic definitions, terminology, and concepts regarding crystalloids, including their categorization by tonicity, their balanced or unbalanced nature, and the importance of strong ion difference (SID). Improper administration of crystalloids can lead to morbidity, particularly hyperchloremic metabolic acidosis (HMA) and fluid overload. Moreover, saline with a SID of zero can cause a positive sodium balance and subsequent fluid accumulation, which can lead to renal dysfunction and the need for vasopressors and renal replacement therapy. Recent systematic reviews and post-hoc analyses of six major fluid trials have shown that balanced solutions (not containing glucose) reduce mortality by 1%, making them a good first choice for resuscitation in patients with sepsis and septic shock, burns, or diabetic ketoacidosis. Traumatic brain injury and gastrointestinal losses may be the only indications left for (ab)normal saline. The pediatric community still favors isotonic solutions for maintenance, although a growing body of evidence supports hypotonic crystalloids as a better choice. Hypertonic crystalloids have been described for small volume resuscitation in specific patient populations, such as post cardiac arrest, but their sodium burden may outweigh the temporarily beneficial hemodynamic effects. In case of excessive losses, fluids should be substituted or replaced by those that mimic the fluids that are lost, such as blood. Prescribing crystalloid solutions should be done with care. Fluid overload or accumulation and HMA should be avoided, as it can induce extra morbidity and mortality. Choosing the right fluid, indication, dose, and duration is crucial for preventing morbidity and mortality: it is all about giving the right dose of the right fluid at the right time for the right patient!
Using Causal Threads to Explain Changes in a Dynamic System
Authors: Allen Robert B. 
Published: November 2023

AbstractWe explore developing rich semantic models of systems. Specifically we consider structured causal explanations about state changes in those systems. Essentially, we are developing process-based dynamic knowledge graphs. As an example, we construct a model of the causal threads for geological changes proposed by the Snowball Earth theory. Further, we describe an early prototype of a graphical interface to present the explanations. Unlike statistical approaches to summarization and explanation such as Large Language Models (LLMs), our approach of direct representation can be inspected and verified directly.
Scale invariant Einstein-Cartan gravity and flat space conformal symmetry
Authors: Karananas Georgios K. , Shaposhnikov Mikhail , Zell Sebastian 
Published: November 2023

Abstract
We find the conditions under which scale-invariant Einstein-Cartan gravity with scalar matter fields leads to an approximate conformal invariance of the flat space particle theory up to energies of the order of the Planck mass. In the minimal setup, these models, in addition to the fields of the Standard Model and the graviton, contain only one extra particle — a massless dilaton. Theories of this type can pave the way for a self-completion all the way up the Planck scale and lead to rather universal inflationary predictions, close to those of the simplest Higgs-inflation scenario in the metric theory of gravity.