bluuebunny/crossref_metadata_2025_split huggingface dataset:
Disparity in Guideline‐Based Antidiabetic Drugs Prescribing for Type 2 Diabetes Patients in Primary Healthcare Facilities Across China, 2017–2019
Authors: Fu Mengyuan , Gong Zhiwen , Zhu Yuezhen , Li Can , Li Huangqianyu , Shi Luwen , Guan Xiaodong 
Published: August 2024

ABSTRACTPurposeThe purpose of this study is to evaluate the pattern, appropriateness, and cost of antidiabetic drugs prescribed for patients with Type 2 diabetes at primary healthcare facilities (PHFs) in China.MethodsWe collected outpatient‐visit prescriptions from 363 PHFs in 31 cities covering eastern, central, and western regions of China. The visits of adult patients with Type 2 diabetes diagnosis were collected and classified the antidiabetic medication pattern of each patient use as recommended or non‐recommended according to Chinese guidelines. We then calculated the proportion of guideline‐recommended patterns and the average monthly cost for each pattern, overall and by region.ResultsOf 33 519 prescriptions for Type 2 diabetes, most (73.9%) were for guideline‐recommended antidiabetic treatments. The proportion of guideline‐recommended prescriptions varied by region (eastern [75.9%], central [87.5%], and western [59.7%]). Metformin monotherapy was the most common guideline‐recommended treatment in all three regions (eastern [20.1%], central [28.0%], and western [24.6%]). The most common non‐guideline‐recommended treatments were monotherapy of insulin (eastern [16.5%], central [5.1%], and western [25.7%]) and traditional Chinese antidiabetic medicines (eastern [5.6%], central [5.7%], and western [11.1%]). The average monthly costs were lower for guideline‐recommended treatments compared to non‐recommended treatments in all regions (eastern [13.6 ± 15.4 USD vs. 28.1 ± 22.0 USD], central [9.8 ± 10.9 USD vs. 28.7 ± 19.4 USD], and western [17.9 ± 21.4 USD vs. 30.3 ± 23.6 USD]).ConclusionsThe majority of patients with Type 2 diabetes received guideline‐recommended antidiabetic medications at PHFs in China, with only half of the prescriptions containing guideline‐recommended metformin. Utilization of guideline‐recommended therapies differed across regions. Tailored interventions to promote evidence‐based antidiabetic prescribing are urgently needed, especially in the undeveloped western region.
Empowering Antimicrobial Peptides: Harnessing Nanotechnology and Engineering Strategies to Combat Microbial Resistance
Authors: Avinash Dubey , Bisht Anjali , Kumar Manish , Thakur Shubham , Patel Preeti , Kurmi Balak Das 
Published: August 2024

ABSTRACTAntimicrobial peptides (AMPs) are being studied for their potential in addressing microbial resistance, a significant issue in treating infections. More than 22,500 AMPs are listed in the database, but their clinical use faces challenges like instability and selectivity. Nanodrug delivery systems are now seen as a beneficial method to improve the effectiveness of AMPs. These systems can shield AMPs from degradation, enhance their availability, and deliver them to specific infection sites, enhancing their ability to combat resistance. One example is liposomal nanoparticles loaded with a mix of AMPs, targeting drug‐resistant bacteria directly. Strategies to develop novel AMPs through engineering methods, including design approaches, computational techniques, and modifications for stability, are discussed in this review. Combinatorial approaches with antibiotics, patents, and clinical trials involving AMPs against infections are also considered, highlighting the potential of AMPs in battling microbial resistance.
Effects of pre‐treatment, historical age, and sample characteristics on the stable isotope analyses of killer whale (Orcinus orca) bone
Authors: Bowen Kelly R. , Kurle Carolyn M. 
Published: August 2024

RationaleStable isotope analysis of bone provides insight into animal foraging and allows for ecological reconstructions over time, however pre‐treatment is required to isolate collagen. Pre‐treatments typically consist of demineralization to remove inorganic components and/or lipid extraction to remove fats, but these protocols can differentially affect stable carbon (δ13C) and nitrogen (δ15N) isotope values depending on the chemicals, tissues, and/or species involved. Species‐specific methodologies create a standard for comparability across studies and enhance understanding of collagen isolation from modern cetacean bone.MethodsElemental analyzers coupled to isotope ratio mass spectrometers were used to measure the δ13C and δ15N values of powdered killer whale (Orcinus orca) bone that was intact (control) or subjected to one of three experimental conditions: demineralized, lipid‐extracted, and both demineralized and lipid‐extracted. Additionally, C:N ratios were evaluated as a proxy for collagen purity. Lastly, correlations were examined between control C:N ratios vs. historical age and control C:N ratios vs. sample characteristics.ResultsNo significant differences in the δ15N values were observed for any of the experimental protocols. However, the δ13C values were significantly increased by all three experimental protocols: demineralization, lipid extraction, and both treatments combined. The most influential protocol was both demineralization and lipid extraction. Measures of the C:N ratios were also significantly lowered by demineralization and both treatments combined, indicating the material was closer to pure collagen after the treatments. Collagen purity as indicated via C:N ratio was not correlated with historical age nor sample characteristics.ConclusionsIf only the δ15N values from killer whale bone are of interest for analysis, no pre‐treatment seems necessary. If the δ13C values are of interest, samples should be both demineralized and lipid‐extracted. As historical age and specimen characteristics are not correlated with sample contamination, all samples can be treated equally.
Management of Refractory/Resistant Herpes Simplex Virus Infections in Haematopoietic Stem Cell Transplantation Recipients: A Literature Review
Authors: Sallée Léo , Boutolleau David 
Published: August 2024

ABSTRACTHerpes simplex virus (HSV) infections in allogeneic haematopoietic stem cell transplantation (HSCT) recipients pose significant challenges, with higher incidence, severity, and risk of emergence of resistance to antivirals due to impaired T‐cell mediated immunity. This literature review focuses on acyclovir‐refractory/resistant HSV infections in HSCT recipients. The review addresses the efficacy of antiviral prophylaxis, the incidence of acyclovir‐refractory/resistant HSV infections, and the identification of risk factors and potential prognostic impact associated with those infections. Additionally, alternative therapeutic options are discussed. While acyclovir prophylaxis demonstrates a significant benefit in reducing HSV infections in HSCT recipients and, in some cases, overall mortality, concerns arise about the emergence of drug‐resistant HSV strains. Our systematic review reports a median incidence of acyclovir‐resistant HSV infections of 16.1%, with an increasing trend in recent years. Despite limitations in available studies, potential risk factors of emergence of HSV resistance to acyclovir include human leucocyte antigen (HLA) mismatches, myeloid neoplasms and acute leukaemias, and graft‐versus‐host disease (GVHD). Limited evidences suggest a potentially poorer prognosis for allogeneic HSCT recipients with acyclovir‐refractory/resistant HSV infection. Alternative therapeutic approaches, such as foscarnet, cidofovir, topical cidofovir, optimised acyclovir dosing, and helicase‐primase inhibitors offer promising options but require further investigations. Overall, larger studies are needed to refine preventive and therapeutic strategies for acyclovir‐refractory/resistant HSV infections in allogeneic HSCT recipients and to identify those at higher risk.
Reachable set estimation for switched homogeneous positive systems of degree greater than one
Authors: Zhang Na , Sun Yuangong 
Published: August 2024

AbstractThis article estimates the reachable set for a class of switched nonlinear positive systems with disturbance. The systems we discussed are homogeneous of degree greater than one and cooperative. Criteria are derived for the existence of a ball where all the solutions of the system converge asymptotically within. Then the results are extended to switched homogeneous positive time‐varying system of degree greater than one and general switched time‐varying system. Finally numerical examples are proposed to illustrate the theoretical results.
Chance, probability, and uncertainty at the edge of human reasoning: What is Knightian uncertainty?
Authors: Townsend David M. , Hunt Richard A. , Rady Judy 
Published: August 2024

AbstractResearch SummaryFor more than a century, Frank Knight's Risk, Uncertainty, and Profit has significantly influenced entrepreneurship theory development by exploring the nature of uncertainty and the epistemic limits of entrepreneurial action. Knight's work highlights how economic actors cannot fully predict the consequences of their actions. Despite its broad influence, debates persist regarding the nature of Knightian uncertainty. This study addresses these debates through a comprehensive analysis of RUP and Knight's other published and unpublished writings to offer new insights into the nature and meaning of Knightian uncertainty, revealing Knight's holistic theory that integrates “real indeterminism,” “partial knowledge,” and “subjective beliefs.” This analysis provides much needed construct clarity to advance contemporary theories of entrepreneurial action and the role of uncertainty in business venturing processes.Managerial SummaryThis article revisits Frank Knight's foundational work, Risk, Uncertainty, and Profit, a cornerstone in entrepreneurship research for over a century. We highlight Knight's holistic approach to uncertainty, which integrates the concepts of real indeterminism (the inherent unpredictability of future events), partial knowledge (the incomplete understanding of the present and future), and subjective beliefs (individual perceptions and interpretations). The study offers new perspectives on how Knightian uncertainty influences entrepreneurial decision‐making and action, highlighting how this unique type of uncertainty plays a critical role in the business venturing process. These insights provide valuable contributions to contemporary theories of entrepreneurship, emphasizing the complexity and multifaceted nature of navigating uncertainty in business.
Selective Segregation of Thermo‐Responsive Microgels via Microfluidic Technology
Authors: Sharma Anjali , Rohne Fabian , Vasquez‐Muñoz Daniela , Jung Se‐Hyeong , Lomadze Nino , Pich Andrij , Santer Svetlana , Bekir Marek 
Published: August 2024

AbstractSeparation of equally sized particles distinguished solely by material properties remains still a very challenging task. Here a simple separation of differently charged, thermo‐responsive polymeric particles (for example microgels) but equal in size, via the combination of pressure‐driven microfluidic flow and precise temperature control is proposed. The separation principle relies on forcing thermo‐responsive microgels to undergo the volume phase transition during heating and therefore changing its size and correspondingly the change in drift along a pressure driven shear flow. Different thermo‐responsive particle types such as different grades of ionizable groups inside the polymer matrix have different temperature regions of volume phase transition temperature (VPTT). This enables selective control of collapsed versus swollen microgels, and accordingly, this physical principle provides a simple method for fractioning a binary mixture with at least one thermo‐responsive particle, which is achieved by elution times in the sense of particle chromatography. The concepts are visualized in experimental studies, with an intend to improve the purification strategy of the broad distribution of charged microgels into fractioning to more narrow distribution microgels distinguished solely by slight differences in net charge.
Identifying Heterogeneous Micromechanical Properties of Biological Tissues via Physics‐Informed Neural Networks
Authors: Wu Wensi , Daneker Mitchell , Turner Kevin T. , Jolley Matthew A. , Lu Lu 
Published: August 2024

AbstractThe heterogeneous micromechanical properties of biological tissues have profound implications across diverse medical and engineering domains. However, identifying full‐field heterogeneous elastic properties of soft materials using traditional engineering approaches is fundamentally challenging due to difficulties in estimating local stress fields. Recently, there has been a growing interest in data‐driven models for learning full‐field mechanical responses, such as displacement and strain, from experimental or synthetic data. However, research studies on inferring full‐field elastic properties of materials, a more challenging problem, are scarce, particularly for large deformation, hyperelastic materials. Here, a physics‐informed machine learning approach is proposed to identify the elasticity map in nonlinear, large deformation hyperelastic materials. This study reports the prediction accuracies and computational efficiency of physics‐informed neural networks (PINNs) in inferring the heterogeneous elasticity maps across materials with structural complexity that closely resemble real tissue microstructure, such as brain, tricuspid valve, and breast cancer tissues. Further, the improved architecture is applied to three hyperelastic constitutive models: Neo‐Hookean, Mooney Rivlin, and Gent. The improved network architecture consistently produces accurate estimations of heterogeneous elasticity maps, even when there is up to 10% noise present in the training data.
Systemic Brain Delivery of Oligonucleotide Therapeutics Enhanced by Protein Corona‐Assisted DNA Cubes
Authors: Kim Kyoung‐Ran , Kang Ji Hee , Thai Hien Bao Dieu , Back Ji Hyun , Mao Chengde , Lee Ji Eun , Ko Young Tag , Ahn Dae‐Ro 
Published: August 2024

AbstractThe systemic delivery of oligonucleotide therapeutics to the brain is challenging but highly desirable for the treatment of brain diseases undruggable with traditional small‐molecule drugs. In this study, a set of DNA nanostructures is prepared and screened them to develop a protein corona‐assisted platform for the brain delivery of oligonucleotide therapeutics. The biodistribution analysis of intravenously injected DNA nanostructures reveals that a cube‐shaped DNA nanostructure (D‐Cb) can penetrate the brain‐blood barrier (BBB) and reach the brain tissue. The brain distribution level of D‐Cb is comparable to that of other previous nanoparticles conjugated with brain‐targeting ligands. Proteomic analysis of the protein corona formed on D‐Cb suggests that its brain distribution is driven by endothelial receptor‐targeting ligands in the protein corona, which mediate transcytosis for crossing the BBB. D‐Cb is subsequently used to deliver an antisense oligonucleotide (ASO) to treat glioblastoma multiforme (GBM) in mice. While free ASO is unable to reach the brain, ASO loaded onto D‐Cb is delivered efficiently to the brain tumor region, where it downregulates the target gene and exerts an anti‐tumor effect on GBM. D‐Cb is expected to serve as a viable platform based on protein corona formation for systemic brain delivery of oligonucleotide therapeutics.
Combining Social–Emotional Learning Competencies and Contemporary Concerns Picturebooks to Foster Early Literacy Practices: An Interdisciplinary Approach
Authors: Deliman Amanda , Robertson Marla K. , Turner Rachel K. 
Published: August 2024

AbstractThere is value in integrating social–emotional learning with academic development as a way to support children's abilities to effectively communicate ideas, collaboratively solve problems, and strengthen early literacy practices. In this article, we discuss suggestions for using picturebook read‐alouds as stepping stones for integrating social–emotional learning (SEL) competencies and core standards (ELA and SS) to address topics related to social justice, equity, and inclusion. We connect each SEL competency with a related topic for discussion and highlight lesson ideas for early grades to examine these themes, including potential prompts a teacher may use to foster curiosity and help students develop questions about each topic.
Specification-Compliant Motion Planning of Cooperative Vehicles Using Reachable Sets
Authors: Liu Edmond Irani , Althoff Matthias 
Published: August 2024

AbstractAutomated vehicles must comply explicitly with specifications, including traffic-based and handcrafted rules, in order for them to safely and effectively participate in mixed traffic. In addition to driving individually, there are many traffic situations in which cooperation between vehicles maximizes their collective benefits, including preventing collisions. To realize these benefits, we compute specification-compliant reachable sets for vehicles, i.e., sets of states which can be reached by vehicles over time that are constrained by a set of considered specifications. We summarize and combine our previous works on computing specification-compliant reachable sets and negotiating conflicting reachable sets within a group of cooperating vehicles. As a result, conflicts between specification-compliant reachable sets of vehicles are resolved, and specification-compliant trajectories can be individually planned for each vehicle within the negotiated reachable sets using arbitrary motion planners.
Cooperation Between Vehicle and Driver: Predicting the Driver’s Takeover Capability in Cooperative Automated Driving Based on Orientation Patterns
Authors: Herzberger Nicolas , Usai Marcel , Schwalm Maximilian , Flemisch Frank 
Published: August 2024

AbstractThis chapter first describes central development steps of cooperative vehicle control before focusing on the cooperation within the vehicle, between driver and co-system. To enable smooth transitions within this internal cooperation, both agents (driver and co-system) need a mutual understanding of the current capabilities for safely executing the driving task. For this purpose, first the model of confidence horizons is briefly introduced, which represents these mutual capability assessments. In the following, the focus of this chapter is on the assessment of the driver’s ability to take over. First, the state of the art of Driver State Monitoring Systems (DSMS) as well as current challenges are presented. Here it is shown that a prediction based purely on driver observation is not yet possible. Therefore, an alternative approach, the diagnostic takeover request (TOR), is presented, which predicts the takeover capability based on the driver’s initial orientation reaction. In the following, two driving simulator studies are presented in which the diagnostic TOR was used for the first time and thereafter the results are presented and discussed. Finally, a brief outlook is given on how both the diagnostic TOR and the concept of confidence horizons will be further developed.
Confidence Horizons: Dynamic Balance of Human and Automation Control Ability in Cooperative Automated Driving
Authors: Usai Marcel , Herzberger Nicolas , Yu Yang , Flemisch Frank 
Published: August 2024

AbstractThis chapter presents the concept of confidence horizon for cooperative vehicles. The confidence horizon is designed to let the automation predict its own and the human’s abilities to control the vehicle in the near future. Based on the pattern approach originating from Alexander et al. [1], the confidence horizon concept is instantiated with a pattern framework. In case of a necessary takeover of the driving task by the human, a mode transition pattern is initiated. In order to determine when the takeover is required, which pattern to start and when to omit the takeover attempt and directly start a minimum risk maneuver, the confidence horizon for both human and co-system is an important parameter. A visual representation of the confidence horizon for the driver in different scenarios prior to a takeover request was explored. Intermediate results of a simulator study are presented, which assess the confidence horizon in automation safety-critical takeover scenarios involving an intersection and a broken-down vehicle on a highway.
Prediction of Cyclists’ Interaction-Aware Trajectory for Cooperative Automated Vehicles
Authors: Raeck Dominik , Pech Timo , Trommler Daniel , Mößner Klaus 
Published: August 2024

AbstractCooperative behaviour is one of the most crucial factors for safety and comfort in shared traffic spaces. While a human driver might be able to automatically identify behavioural indicators of other traffic participants to predict their movement, an automated vehicle is not. This is especially important in interaction situations with vulnerable road users (VRU), such as cyclists. The focus of this work is to implement, evaluate and compare different possible methods of trajectory forecasts for cyclists in order to estimate their behavioural intention. With accurate trajectory information of the VRU, an automated vehicle might be able to plan a cooperative reaction ahead in time and guarantee a comfortable traffic flow. In sum, three different neural network architectures have been tested with the main focus on a CNN, which is capable of incorporating map data into the trajectory forecast. The results showed, that including external influencing factors, like the infrastructure of a traffic scene, can have a beneficial effect on the accuracy of the cyclist’s predicted movement.
Total gluon helicity from lattice without effective theory matching
Authors: Pang Zhuoyi , Yao Fei , Zhang Jian-Hui 
Published: August 2024

Abstract
We propose two approaches for extracting the total gluon helicity contribution to proton spin from lattice QCD, one from local operator matrix elements in a fixed gauge accessible on lattice with feasible renormalization, and the other from gauge-invariant nonlocal gluon correlators. Neither of these approaches requires a matching procedure when converted to the $$ \overline{\textrm{MS}} $$

MS
¯

scheme. Our proposal resolves a long-standing inconsistency in the literature regarding lattice calculations of the total gluon helicity, and has the potential to greatly facilitate these calculations.
Green’s functions in the presence of a bubble wall
Authors: Kubota Takahiro 
Published: August 2024

Abstract
Field theoretical tools are developed so that one can analyze quantum phenomena such as transition radiation that must have occurred during the Higgs condensate bubble expansion through plasma in the early universe. Integral representations of Bosonic and Fermionic propagators are presented for the case that particle masses are varied continuously during the passage through the bubble wall interface between symmetry-restored and symmetry-broken regions. The construction of propagators is based on the so-called eigenfunction expansion method associated with self-adjoint differential operators, developed by Weyl, Stone, Titchmarsh, Kodaira and several others. A novel method of field quantization in the presence of the bubble wall is proposed by using the spectral functions introduced in constructing the two-point Green’s functions.