bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of virtual reality content for learning Japan Prehospital Trauma Evaluation and Care initial assessment procedures
Authors: Kiyozumi Tetsuro , Ishigami Norio , Tatsushima Daisuke , Araki Yoshiyuki , Sekine Yasumasa , Saitoh Daizoh 
Published: May 2022

AimThe Japan Prehospital Trauma Evaluation and Care (JPTEC) is a standardized educational program for prehospital trauma care in Japan. The initial assessment in the JPTEC course comprises a training segment that includes a 30‐min session. Given the limited face‐to‐face training due to the coronavirus disease 2019, virtual reality (VR) content has become an alternative. However, creating VR content typically requires the assistance of expert technicians. We aimed to create VR content for the initial assessment segment of the JPTEC and verify its educational effectiveness.MethodsWe created VR content for learning the initial assessment of the JPTEC using our easy‐to‐use VR content creation system. The participants played the VR content for 15 min. The number of times they “cleared” (i.e., made a correct decision and completed the initial assessment) was recorded every 5 min. Then, a JPTEC‐certified instructor tested their practical skills through face‐to‐face simulation.ResultsThe authors had no specialized skills and created the VR content in 2 days. Fourteen students used the material. They cleared the scenario 3 (3–4) times in the first 5 min in 15 min, 5 (4–5) times in the second 5 min, and 5 (5–5) times in the third 5 min (P < 0.05). All participants passed the practical evaluation.ConclusionA shorter VR training developed using our easy‐to‐use VR content creation system can replace the 30‐min JPTEC session on the initial assessment. This system allows for the free and easy creation of VR content.
Tuning Electrostatic and Hydrophobic Surfaces of Aromatic Rings to Enhance Membrane Association and Cell Uptake of Peptides
Authors: de Araujo Aline D. , Hoang Huy N. , Lim Junxian , Mak Jeffrey Y. W. , Fairlie David P. 
Published: May 2022

AbstractAromatic groups are key mediators of protein–membrane association at cell surfaces, contributing to hydrophobic effects and π‐membrane interactions. Here we show electrostatic and hydrophobic influences of aromatic ring substituents on membrane affinity and cell uptake of helical, cyclic and cell penetrating peptides. Hydrophobicity is important, but subtle changes in electrostatic surface potential, dipoles and polarizability also enhance association with phospholipid membranes and cell uptake. A combination of fluorine and sulfur substituents on an aromatic ring induces microdipoles that enhance cell uptake of 12‐residue peptide inhibitors of p53‐HDM2 interaction and of cell‐penetrating cyclic peptides. These aromatic motifs can be readily inserted into peptide sidechains to enhance their cell uptake.
An Energy‐Dense, Powerful, Robust Bipolar Zinc–Ferrocene Redox‐Flow Battery
Authors: Luo Jian , Hu Bo , Hu Maowei , Wu Wenda , Liu T. Leo 
Published: May 2022

AbstractZinc metal represents a low‐cost, high‐capacity anode material to develop energy‐dense aqueous redox‐flow batteries (RFB). However, the energy‐storage applications of traditional inorganic Zn halide flow batteries are primarily plagued by the material challenges of traditional halide cathode electrolytes (e.g., bromine), including corrosion, toxicity, and severe crossover. Herein, we report a bipolar zinc–ferrocene salt compound, zinc 1,1′‐bis(3‐sulfonatopropyl)ferrocene, Zn[Fc(SPr)2] (1.80 M solubility or 48.2 Ah L− charge storage capacity)—a robust, energy‐dense, bipolar redox‐active electrolyte material for RFBs. Zn[Fc(SPr)2]‐based redox‐flow batteries operated at high current densities of up to 200 mA cm−2 and delivered an energy efficiency of up to 81.5 % and a power density of up to 270.5 mW cm−2. A Zn[Fc(SPr)2] flow battery demonstrated an energy density of 20.2 Wh L−1 and displayed nearly 100 % capacity retention for 2000 cycles (1284 h or 53.5 days).
Asymmetric Double Hydroxycarbonylation of Alkynes to Chiral Succinic Acids Enabled by Palladium Relay Catalysis
Authors: Ji Xiaolei , Shen Chaoren , Tian Xinxin , Zhang Hongru , Ren Xinyi , Dong Kaiwu 
Published: May 2022

AbstractA Pd‐catalyzed asymmetric double hydroxycarbonylation of terminal alkynes was developed by using relay catalysis, providing a highly efficient route to chiral succinic acids (41 examples, 76–94 %, 94–99 %ee). Key to success was the combinatorial use of a Pd precursor with two distinct phosphine ligands in one pot. The synthetic utilities of this protocol were showcased in the facile synthesis of key intermediates for chiral pharmaceuticals.
Programming Receptor Clustering with DNA Probabilistic Circuits for Enhanced Natural Killer Cell Recognition
Authors: Xiao Mingshu , Lai Wei , Yao Xiaowei , Pei Hao , Fan Chunhai , Li Li 
Published: May 2022

AbstractDeveloping strategies to enhance the recognition ability of immune cells is important to the success of cell‐based cancer immunotherapy. Herein, we report programming receptor clustering on membrane with DNA probabilistic circuits for enhanced immune cell recognition. By designing the circuit output to activate receptors for binding to adjacent receptors, we can engineer DNA probabilistic circuits for programmable regulation of receptor clustering. The generated receptor clusters show higher binding affinity to target cancer cells and improved membrane‐anchoring stability compared with monomers. We demonstrate that programming receptor clustering could allow to modulate the recognition capability of natural killer cells and control natural killer cell–cancer cell interactions to promote efficient cancer cell killing. This work provides insights for precise control over cellular recognition and opens new opportunities for the development of cell‐based immunotherapy.
Stepping Out of the Blue: From Visible to Near‐IR Triggered Photoswitches
Authors: Zhang Zhiwei , Wang Wenhui , O'Hagan Michael , Dai Jinghong , Zhang Junji , Tian He 
Published: May 2022

AbstractLight offers unique opportunities for controlling the activity of materials and biosystems with high spatiotemporal resolution. Molecular photoswitches are chromophores that undergo reversible isomerization between different states upon irradiation with light, allowing a convenient means to control their influence over the system of interest. However, a significant limitation of classical photoswitches is the requirement to initiate the switching in one or both directions using deleterious UV light with poor tissue penetration. Red‐shifted photoswitches are hence in high demand and have attracted keen recent research interest. In this Review, we highlight recent progress towards the development of visible‐ and NIR‐activated photoswitches characterized by distinct photochromic reaction mechanisms. We hope to inspire further endeavors in this field, allowing the full potential of these tools in biotechnology and materials chemistry applications to be realized.
Silver(I) complexes ofN,N′‐diarylformamidine ligands: Synthesis, crystal structures, and in vitro antibacterial studies
Authors: Bongoza Unathi , Zamisa Sizwe J. , Munzeiwa Wisdom A. , Omondi Bernard 
Published: May 2022

AbstractNine silver(I)N,N′‐diarylformamidine complexes of type [Ag (Ln)2X] (where X = NO3−, CF3COO−, and CF3SO3−,n = 1–5) were synthesised and characterised by physiochemical and spectroscopic techniques. Further confirmation for the formation of the complexes was provided by single‐crystal X‐ray crystallography. All complexes (but one) adopted linear geometry in which coordination was via twoNatoms of two formamidine ligands with the anion (X) displaced from coordination sphere. In the structure of the exception, the anion is part of the coordination sphere and a T‐shaped geometry was adopted. The antimicrobial activity of the Ag(I) complexes were investigated against two Gram‐positive bacteria, that is,S. aureusATCC 25923 andMethicillin‐resistant S. aureusATCC 700699 (MRSA) and four Gram‐negative bacteria, that is,K. pneumoniaeATCC 31488,S. typhimuriumATCC 14026,P. aeruginosaATCC 27853 andE. coliATCC 25922 and they were evaluated based on ciprofloxacin and silver nitrate standards. The newly synthesised target complexes demonstrated promising antibacterial activity against Gram‐positive bacteria although less than the reference drug ciprofloxacin. The best active silver(I) complex contains a nitrate counter‐ion.
Graphene oxide/thermoplastic polyurethane wrinkled foams with enhanced compression performance fabricated by dynamic supercritical CO2 foaming
Authors: Zhu Xiaoshuai , Li Xijue , Mi Hao‐Yang , Jing Xin , Dong Binbin , He Ping , Liu Chuntai , Shen Changyu 
Published: May 2022

AbstractThermoplastic polyurethane (TPU) foams are commonly used buffering materials due to their lightweight, high elasticity, and excellent energy absorption properties. Improving their compressive property without increase foam density is a challenge for TPU foams. Herein, graphene oxide (GO)/TPU composite foams containing micro‐sized wrinkles on the cell surface were fabricated by a novel dynamic supercritical carbon dioxide (scCO2) foaming method. The addition of GO created hydrogen bonding and physical crosslinking sites with the TPU molecules, which acted as nucleation agents to improve the cell density of the GO/TPU foams. With the increase of GO content, the mechanical properties of GO/TPU foams were significantly enhanced, and the wrinkled foams prepared via dynamic scCO2 foaming displayed superior compressive modulus, strength, energy absorption, and recoverability compared with the counterpart foams without wrinkly structure. The wrinkled GO/TPU foams with 0.5 wt% GO revealed higher expansion ratio, lower foam density, superior compressive property and energy absorption than both neat TPU and 1 wt% GO foams owing to the reinforcing effect of the wrinkly structure. This study is of great significance in the development of low‐density composite foams with enhanced compressive performance by wrinkly structures.
Programming of micro/nano‐scale information on low switching temperature shape memory film
Authors: Zhang Ziyou , Li Zhenpeng , Sun Ruolin , Olah Andrew , Baer Eric 
Published: May 2022

AbstractShape memory polymer films have been of great interests in storing functional information because of their optical and mechanical variability. High molecular weight polyvinyl acetate (PVAc) is an ideal shape memory material to program micro‐ and nano‐scale patterns on the surface of highly transparent films. By blending PVAc with polyethylene glycol (PEG) plasticizer, lower switching temperatures could be achieved. We develop a shape memory PVAc/PEG blend film system featuring a unique design by taking advantage of multiple switching temperatures. The effect of the PEG composition was studied relative to different surface patterns, switching temperatures and efficiency of information retrieval by utilizing differential scanning calorimetry and UV/Vis analysis. The results indicate that higher contents of PEG enhanced the recovery efficiency of both the micro‐scale and nano‐scale patterns and the corresponding optical properties. Furthermore, a dual switching shape memory film was developed enabling multiple switching temperatures that can lead to versatile applications.
A green composite hydrogel based on xylan and lignin with adjustable mechanical properties, high swelling, excellent UV shielding, and antioxidation properties
Authors: Yi Yanbin , Wang Xiaohui , Liu Zhongming , Gao Chao , Fatehi Pedram , Wang Shoujuan , Kong Fangong 
Published: May 2022

AbstractThis study successfully prepared a novel green composite hydrogel based on carboxymethyl xylan and lignin with adjustable mechanical properties, high swelling, excellent UV shielding, and antioxidation performance. The structure and morphology of the hydrogel were characterized by Fourier transform infrared spectra, scanning electron microscopy, thermogravimetric analysis, rheological analysis, and swelling ratio. Results showed that lignin could significantly improve the mechanical properties of composite hydrogels. The compression stress and toughness of the composite hydrogel contained lignin increased by 39% and 60%, respectively, and the compressive deformation reached 90%. In addition, the addition of lignin increased the swelling ratio of the composite hydrogel reached 79.9 g/g. In addition, the composite hydrogel exhibited excellent UV shielding and antioxidation performance. The removal ratio of UV and free radicals is as high as 80% and 90%, respectively. The simple procedure and cost‐effective lignin as raw material for hydrogel with adjustable properties are favorable for medical‐biological applications.
The value of in‐person undergraduate dissection in anatomical education in the time of Covid‐19
Authors: MacPherson Emily , Lisk Kristina 
Published: May 2022

AbstractWhile several innovative pedagogical practices have been developed and implemented in anatomy education since the onset of the coronavirus disease 2019 (Covid‐19) pandemic, considering the value of in‐person undergraduate dissection remains crucial. In this commentary, a human dissection course at the University of Toronto is used as an example to highlight the value of dissection for undergraduate learners in non‐professional programs. In‐person dissection allows for real life, anatomical variation, and supports the advancement of students' conceptual knowledge of the human body and visual–spatial abilities. Direct involvement with dissection during undergraduate training also provides students with an opportunity to practice and refine non‐technical skills, such as communication and collaboration, while simultaneously promoting the development of students' professional identity formation. Further, dissection is a practical, hands‐on experience that can provide students with insight into potential career aspirations related to anatomy and the health professions. It is suggested that as institutions veer from traditional pedagogical practices and evaluate how to best move forward post‐pandemic, it is imperative that the value of undergraduate dissection is considered among new innovations in the field of anatomy.
Finite‐time input L2 bumpless transfer control for switched systems with its application to aircraft model
Authors: Zhao Ying , Wang Xinying , Chen Yuqing , Li Wenqing 
Published: May 2022

SummaryThis article addresses the finite‐time (FT) input
bumpless transfer (BT) control problem for switched systems. First, the performance of the input
BT is described, quantifying the energy difference caused by the input signal jumps. The objective is to suppress large jumps during switching. Second, a sufficient evidence is established through the multiple Lyapunov functions method to ensure that the switched systems satisfy both the FT
property and input
BT performance. Also, this evidence allows that the control issue may not be addressed by subsystems. Then, a switching controller and a switching rule are simultaneously constructed for purpose of addressing the issue of the FT input
BT control for switched systems. Finally, an effective validation of the established control method is verified by an
‐18 aircraft model simulation.
Assessment of the sustainability and economic potential of hydrotreated vegetable oils to complement diesel and biodiesel blends in Brazil
Authors: Julio Alisson Aparecido Vitoriano , Milessi Thais Suzane , Maya Diego Mauricio Yepes , Lora Electo Silva , Palacio José Carlos Escobar 
Published: May 2022

Abstract‘Curb CO2 emissions’ is a common expression today and it will be heard even more frequently in the future. Biofuels have attracted attention for many years, and recently this attention has been directed, in particular, to biofuels in heavy‐duty vehicles. This sector contributes to a significant quantity of emissions in Brazil. This class of fuels – biodiesel, fatty acid methyl esters (FAMEs) – has an established industry in Brazil. However, the limited capacity for the production of biodiesel, and the limitations imposed by its properties, make it difficult to expand the industry. Thus, hydrotreated vegetable oils (HVOs) have emerged as a more environmental friendly fuel and a potential alternative to cut emissions in the transportation sector. To identify ways to use such fuels in Brazil, this study reviews environmental indicators for diesel, biodiesel, and HVO, and compares then using a composite score. Based on specific emission factors, scenarios for the use of HVO are evaluated in terms of emissions avoided, potential granting of decarbonization credits, and feasibility for investment. The results in one of the scenarios evaluated show that 0.5 decarbonization credits can be granted for each liter of HVO consumed in Brazil. There is room for profitability in all of the scenarios. This work also shows that Brazil has the necessary public policies to foster biofuels on a large scale, and, with blend mandates being reformulated, the country could avoid emissions of over 12.9 million CO2 tons per year in the transport sector. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.
Time‐dependent ROC curve estimation for interval‐censored data
Authors: Beyene Kassu Mehari , El Ghouch Anouar 
Published: May 2022

AbstractThe receiver‐operating characteristic (ROC) curve is the most popular graphical method for evaluating the classification accuracy of a diagnostic marker. In time‐to‐event studies, the subject's event status is time‐dependent, and hence, time‐dependent extensions of ROC curve have been proposed. However, in practice, the calculation of this curve is not straightforward due to the presence of censoring that may be of different types. Existing methods focus on the more standard and simple case of right‐censoring and neglect the general case of mixed interval‐censored data that may involve left‐, right‐, and interval‐censored observations. In this context, we propose and study a new time‐dependent ROC curve estimator. We also consider some summary measures (area under the ROC curve and Youden index) traditionally associated with ROC as well as the Youden‐based cutoff estimation method. The proposed method uses available data very efficiently. To this end, the unknown status (positive or negative) of censored subjects are estimated from the data via the estimation of the conditional survival function given the marker. For that, we investigate both model‐based and nonparametric approaches. We also provide variance estimates and confidence intervals using Bootstrap. A simulation study is conducted to investigate the finite sample behavior of the proposed methods and to compare their performance with a competitor. Globally, we observed better finite sample performances for the proposed estimators. Finally, we illustrate the methods using two data sets one from a hypobaric decompression sickness study and the other from an oral health study. The proposed methods are implemented in theRpackagecenROC.
Regression‐based heterogeneity analysis to identify overlapping subgroup structure in high‐dimensional data
Authors: Luo Ziye , Yao Xinyue , Sun Yifan , Fan Xinyan 
Published: May 2022

AbstractHeterogeneity is a hallmark of complex diseases. Regression‐based heterogeneity analysis, which is directly concerned with outcome–feature relationships, has led to a deeper understanding of disease biology. Such an analysis identifies the underlying subgroup structure and estimates the subgroup‐specific regression coefficients. However, most of the existing regression‐based heterogeneity analyses can only address disjoint subgroups; that is, each sample is assigned to only one subgroup. In reality, some samples have multiple labels, for example, many genes have several biological functions, and some cells of pure cell types transition into other types over time, which suggest that their outcome–feature relationships (regression coefficients) can be a mixture of relationships in more than one subgroups, and as a result, the disjoint subgrouping results can be unsatisfactory. To this end, we develop a novel approach to regression‐based heterogeneity analysis, which takes into account possible overlaps between subgroups and high data dimensions. A subgroup membership vector is introduced for each sample, which is combined with a loss function. Considering the lack of information arising from small sample sizes, an norm penalty is developed for each membership vector to encourage similarity in its elements. A sparse penalization is also applied for regularized estimation and feature selection. Extensive simulations demonstrate its superiority over direct competitors. The analysis of Cancer Cell Line Encyclopedia data and lung cancer data from The Cancer Genome Atlas show that the proposed approach can identify an overlapping subgroup structure with favorable performance in prediction and stability.
A two‐way additive model with unknown group‐specific interactions applied to gene expression data
Authors: Zheng Tianqi , Guo Jianhua , Ma Yanyuan 
Published: May 2022

AbstractWe propose a two‐way additive model with group‐specific interactions, where the group information is unknown. We treat the group membership as latent information and propose an EM algorithm for estimation. With a single observation matrix and under the situation of diverging row and column numbers, we rigorously establish the estimation consistency and asymptotic normality of our estimator. Extensive simulation studies are conducted to demonstrate the finite sample performance. We apply the model to the triple negative breast cancer (TNBC) gene expression data and provide a new way to classify patients into different subtypes. Our analysis detects the potential genes that may be associated with TNBC.
Revival of wind‐powered shipping: Comparing the early‐stage innovation process of an incumbent and a newcomer firm
Authors: Stalmokaitė Ignė , Larsson Segerlind Tommy , Yliskylä‐Peuralahti Johanna 
Published: May 2022

AbstractDespite the urgency of decarbonising, the shipping sector has demonstrated a slow‐paced response to climate change challenges. Some frontrunner firms are engaged in sustainability‐oriented innovation processes. However, there is limited knowledge of how such processes emerge and contribute to societal sustainability transitions and what the role of technology is in companies' (re)orientation towards sustainable business models. This study contributes to filling these gaps through a comparative case study of the ongoing innovation process within an incumbent and a newcomer firm developing wind‐powered energy solutions for deep‐sea transportation. The study's findings bear implications for theory and practice. This paper's combination of a dynamic capabilities approach and a multi‐level perspective from sustainability transitions research is a conceptual novelty, enabling an understanding of the activities involved in the (re)orientation process towards sustainable business from a company's perspective, as well as broader societal and sustainability needs.