bluuebunny/crossref_metadata_2025_split huggingface dataset:
Production of mycosporine‐like amino acid (MAA)‐loaded emulsions as chemical barriers to control sunscald in fruits and vegetables
Authors: Pedrosa Vanessa MD , Sanches Alex G , da Silva Maryelle B , Gratão Priscila L , Isaac Vera LB , Gindri Marcelo , Teixeira Gustavo HA 
Published: July 2021

AbstractBACKGROUNDSunscald is a physiological disorder that occurs in many horticultural products when exposed to excessive solar radiation and high temperatures. Traditionally, sunscald is controlled using physical barriers that reflect radiation, however this practice is not always efficient. A possible alternative would be the use of chemical barriers, such as mycosporine‐like amino acids (MAAs), which protect aquatic organisms against ultraviolet (UV) radiation. Thus, this study aimed to develop a lipid‐based emulsion containing MAAs for using in the preharvest of horticultural products.RESULTSEmulsions were developed using 10% (w/v) of corn oil (CO) and soybean oil (SO), carnauba wax (CW), and beeswax (BW) as lipid bases (LBs). The emulsion containing CW and ammonium hydroxide was the most stable, resembling commercial wax. Therefore, this formulation was used as the basis for the incorporation of the commercial product Helioguard™ 365, a source of MAA, in concentrations of 0%, 1%, 2%, and 4% (v/v). The MAA incorporation resulted in little modifications in the stability of the emulsion, providing an increase in the absorbance with peaks in the UV‐B ranging from 280 to 300 nm.CONCLUSIONThe lipid‐base emulsion containing MAAs could be used as a chemical barrier to control sunscald in horticultural products. © 2021 Society of Chemical Industry.
Pre‐operative testing for SARS‐CoV‐2 and outcomes in otolaryngology surgery during the pandemic: A multi‐center experience
Authors: Kavanagh Fergal G. , Callanan Deirdre , Connolly Carmel , Brinkman David , Fitzgerald Conall , Elsafty Naisrin , Thong Gerard , Hintze Justin , Barry Conor , Kinsella John , Timon Conrad , Lennon Paul , Dias Andrew , O'Brien Deirdre , Sheahan Patrick 
Published: July 2021

AbstractIntroductionPreoperative testing for COVID‐19 has become widely established to avoid inadvertent surgery on patients with COVID‐19 and prevent hospital outbreaks.MethodsA prospective cross sectional study was carried out in two university hospitals examining the pre‐operative protocols for patients undergoing otolaryngology surgery and the incidence of COVID‐19 within 30 days of surgery in patients and the otolaryngologists performing surgery.ResultsOne hundred and seventy‐three patients were recruited. One hundred and twenty‐three (71%) patients “cocooned” for 14 days prior to surgery. All completed a questionnaire prior to admission. One hundred and fifty‐six patients (90%) had reverse transcriptase‐polymerase chain reaction (RT‐PCR) nasopharyngeal swabs, 14 patients (8%) had CT thorax. No cases of COVID‐19 were detected among patients followed up at 30 days. Two surgeons developed COVID‐19 early during the study period.ConclusionCurrent pre‐operative testing protocols consisting primarily of questionnaires and RT‐PCR resulted in zero cases of COVID in this cohort. It is possible that COVID‐19 restrictions and high proportion of patients cocooning preoperatively were factors in ensuring a low rate of COVID‐19 post‐operatively.
Graphene and MXene‐based Sponge Pressure Sensor Array for Rectal Model Pressure Detection
Authors: Sang Shengbo , Jing Zhu , Cheng Yongqiang , Ji Chao , Zhang Qiang , Dong Xiushan 
Published: July 2021

AbstractFlexible sensor is one of the prevalent directions in the sensor field, and the sensing material and structure are the main aspects that affect the performance of the sensor. This paper studies a flexible pressure sensor based on Graphene/MXene‐PDMS @ sponge. Using the porous skeleton structure of sponge and the high conductivity and synergy of Graphene and MXene to prepare a set of high sensitivity (0.053kPa−1), high stability (2000 cycles loading), and variability (0–35 kPa detection limit), all‐in‐one sensor. In the rectal model pressure detection experiment, the sensor array can effectively detect static pressure, systolic pressure, and corresponding abnormal pressure detection. Experimental results show that the sensor has a good prospect in detecting rectal pressure.
Mapping the jungle: A bibliometric analysis of research into construal level theory
Authors: Adler Susanne , Sarstedt Marko 
Published: July 2021

AbstractConstrual level theory (CLT) offers a valuable framework to explain the mechanisms that trigger evaluations, predictions, and behaviors by linking the degree of mental abstraction (the construal level) to psychological distance. CLT‐related research has produced numerous publications in a variety of domains, impeding an ongoing overview of the research field and limiting its advancement. Addressing this concern, our paper presents the results of a comprehensive bibliometric analysis of CLT‐related research. This analysis identifies leading authors and the networks in which they operate. We find that a well‐connected, stable core of prominent authors predominantly shaped CLT research and was responsible for its expansion. In addition, we used topic modeling to identify latent topics and research trends, with the results showing that CLT research has expanded into more interdisciplinary and applied contexts. Specifically, although CLT's relevance for consumer research has amplified and applications in areas such as climate change and sustainability have surged, the classic areas of CLT research, such as planning fallacy and impulse control, have lost momentum. Building upon the results of our topic analysis, we identify future research paths and specifically call for a more comprehensive societal focus in CLT‐related research.
More innovative but less socially responsible: The influence of using metaphors in marketing communications on product perception, choice, and adoption intention
Authors: Luffarelli Jonathan , Feiereisen Stephanie , Zoghaib Alice 
Published: July 2021

AbstractMetaphors appear frequently in marketing communications. Prior literature evokes various positive outcomes of using metaphors to promote products but offers relatively limited insights into the potentially negative effects of this rhetorical figure on product perception, product choice, and adoption intention. Building on processing fluency theory, the authors investigate benefits and drawbacks of using metaphors to promote products. The results of eight studies reveal that, compared with literal claims, metaphors can make products appear more innovative but also less socially responsible. A dual process explains these effects on product perception: consumers tend to view products promoted with metaphors as more unfamiliar and thus innovative, but also as more untrustworthy and thus less socially responsible. In a further step, by examining whether using metaphors to promote products increases or decreases product choice and adoption intentions, the authors find increased product choice for brands with innovative personalities but diminished product choice for brands with socially responsible personalities. Using metaphors also boosts the adoption intentions of consumers who value innovativeness in products but lowers these intentions among consumers who value social responsibility. These findings offer novel insights into the effects of metaphors, along with actionable recommendations for practitioners.
Dietary EPA‐Enriched Phospholipids Alleviate Chronic Stress and LPS‐Induced Depression‐ and Anxiety‐Like Behavior by Regulating Immunity and Neuroinflammation
Authors: Wang Cheng‐Cheng , Du Lei , Shi Hao‐Hao , Ding Lin , Yanagita Teruyoshi , Xue Chang‐Hu , Wang Yu‐Ming , Zhang Tian‐Tian 
Published: July 2021

ScopeA growing number of studies have reported the effects of eicosapentaenoic acid (EPA) and terrestrial phospholipids on ameliorating mood disorders. Marine‐derived EPA‐enriched phospholipids (EPA‐PL) exhibit the structural characteristics of EPA and phospholipids. However, the effect of dietary EPA‐PL, and the differences between amphiphilic EPA‐PL and lyophobic EPA on mood disorders had not been studied.Methods and ResultsA comparative investigation to determine the effects of dietary EPA‐enriched ethyl ester (EPA‐EE) and EPA‐PL on improving depression‐ and anxiety‐like behavior in a mouse model is performed, induced by 4 week chronic unpredictable mild stress (CUMS) coupled with lipopolysaccharide (LPS) challenge. It is found that dietary 4 week 0.6% (w/w) EPA‐PL rescued depression‐ and anxiety‐like behavior to a greater extent than did EPA‐EE. Moreover, dietary EPA‐PL significantly reduced the immobility time by 56.6%, close to the normal level, in forced swimming test, which revealed a reversal of depression‐like behavior. Further studies revealed that dietary EPA‐PL regulated immunity, monoamine systems, and the hypothalamic–pituitary–adrenal (HPA) axis by multi‐target interactions, including inhibition of neuroinflammation and apoptosis.ConclusionEPA‐PL exerted superior effects to EPA‐EE in alleviating depression‐ and anxiety‐like behavior. The data suggest potential novel candidate or targeted dietary patterns to prevent and treat mood disorder.
Diosmetin Protects Against Obesity and Metabolic Dysfunctions Through Activation of Adipose Estrogen Receptors in Mice
Authors: Xie Baocai , Pan Dengke , Liu Huan , Liu Min , Shi Xiaochen , Chu Xinyi , Lu Junfeng , Zhu Mengqing , Xia Bo , Wu Jiangwei 
Published: July 2021

ScopeObesity is a major public health and economic problem of global significance. Here, we investigate the role of diosmetin, a natural flavonoid presents mainly in citrus fruits, in the regulation of obesity and metabolic dysfunctions in mice.Methods and ResultsEight‐week‐old male C57BL/6 mice fed a high‐fat diet (HFD) or 5‐week‐old male ob/ob mice fed a normal diet are treated with diosmetin (50 mg kg−1 daily) or vehicle for 8 weeks. Diosmetin treatment decreases body weight and fat mass, improves glucose tolerance and insulin resistance in obese mice. These metabolic benefits are mainly attributed to increase energy expenditure via enhancing thermogenesis in brown adipose tissue (BAT) and browning of white adipose tissue (WAT). Mechanistically, diosmetin acts as an agonist for estrogen receptors (ERs), and subsequently elevates adipose expressions of ERs in mice and in cultured adipocytes. When ERs are blocked by their antagonist fulvestrant in mice, diosmetin loses its beneficial effects, suggesting that ERs are indispensable for the metabolic benefits of diosmetin.ConclusionThe results indicate that diosmetin may be a potential anti‐obesity nutritional supplement and could be explored for low ERs‐related obesity populations.
An effective deep network for automatic segmentation of complex lung tumors in CT images
Authors: Wang Bing , Chen Kang , Tian Xuedong , Yang Ying , Zhang Xin 
Published: July 2021

AbstractPurposeAccurate segmentation of complex tumors in lung computed tomography (CT) images is essential to improve the effectiveness and safety of lung cancer treatment. However, the characteristics of heterogeneity, blurred boundaries, and large‐area adhesion to tissues with similar gray‐scale features always make the segmentation of complex tumors difficult.MethodsThis study proposes an effective deep network for the automatic segmentation of complex lung tumors (CLT‐Net). The network architecture uses an encoder–decoder model that combines long and short skip connections and a global attention unit to identify target regions using multiscale semantic information. A boundary‐aware loss function integrating Tversky loss and boundary loss based on the level‐set calculation is designed to improve the network's ability to perceive boundary positions of difficult‐to‐segment (DTS) tumors. We use a dynamic weighting strategy to balance the contributions of the two parts of the loss function.ResultsThe proposed method was verified on a dataset consisting of 502 lung CT images containing DTS tumors. The experiments show that the Dice similarity coefficient and Hausdorff distance metric of the proposed method are improved by 13.2% and 8.5% on average, respectively, compared with state‐of‐the‐art segmentation models. Furthermore, we selected three additional medical image datasets with different modalities to evaluate the proposed model. Compared with mainstream architectures, the Dice similarity coefficient is also improved to a certain extent, which demonstrates the effectiveness of our method for segmenting medical images.ConclusionsQuantitative and qualitative results show that our method outperforms current mainstream lung tumor segmentation networks in terms of Dice similarity coefficient and Hausdorff distance. Note that the proposed method is not limited to the segmentation of complex lung tumors but also performs in different modalities of medical image segmentation.
A deep learning‐based dual‐omics prediction model for radiation pneumonitis
Authors: Bin Liang , Yuan Tian , Zhaohui Su , Wenting Ren , Zhiqiang Liu , Peng Huang , Shuying You , Lei Deng , Jianyang Wang , Jingbo Wang , Tao Zhang , Xiaotong Lu , Nan Bi , Jianrong Dai 
Published: July 2021

PurposeRadiation pneumonitis (RP) is the main source of toxicity in thoracic radiotherapy. This study proposed a deep learning‐based dual‐omics model, which aims to improve the RP prediction performance by integrating more data points and exploring the data in greater depth.Materials and methodsThe bimodality data were the original dose (OD) distribution and the ventilation image (VI) derived from four‐dimensional computed tomography (4DCT). The functional dose (FD) distribution was obtained by weighting OD with VI. A pre‐trained three‐dimensional convolution (C3D) network was used to extract the features from FD, VI, and OD. The extracted features were then filtered and selected using entropy‐based methods. The prediction models were constructed with four most commonly used binary classifiers. Cross‐validation, bootstrap, and nested sampling methods were adopted in the process of training and hyper‐tuning.ResultsData from 217 thoracic cancer patients treated with radiotherapy were used to train and validate the prediction model. The 4DCT‐based VI showed the inhomogeneous pulmonary function of the lungs. More than half of the extracted features were singular (of none‐zero value for few patients), which were eliminated to improve the stability of the model. The area under curve (AUC) of the dual‐omics model was 0.874 (95% confidence interval: 0.871–0.877), and the AUC of the single‐omics model was 0.780 (0.775–0.785, VI) and 0.810 (0.804–0.811, OD), respectively.ConclusionsThe dual‐omics outperformed single‐omics for RP prediction, which can be contributed to: (1) using more data points; (2) exploring the data in greater depth; and (3) incorporating of the bimodality data.
3D 31P MRSI of the human brain at 9.4 Tesla: Optimization and quantitative analysis of metabolic images
Authors: Ruhm Loreen , Dorst Johanna , Avdievitch Nikolai , Wright Andrew Martin , Henning Anke 
Published: July 2021

PurposeTo present 31P whole brain MRSI with a high spatial resolution to probe quantitative tissue analysis of 31P MRSI at an ultrahigh field strength of 9.4 Tesla.MethodsThe study protocol included a 31P MRSI measurement with an effective resolution of 2.47 mL. For SNR optimization, the nuclear Overhauser enhancement at 9.4 Tesla was investigated. A sensitivity correction was achieved by applying a low rank approximation of the γ‐adenosine triphosphate signal. Group analysis and regression on individual volunteers were performed to investigate quantitative concentration differences between different tissue types.ResultsDifferences in gray and white matter tissue 31P concentrations could be investigated for 12 different 31P resonances. In addition, the first highly resolved quantitative MRSI images measured at B0 = 9.4 Tesla of 31P detectable metabolites with high SNR could be presented.ConclusionWith an ultrahigh field strength B0 = 9.4 Tesla, 31P MRSI moves further toward quantitative metabolic imaging, and subtle differences in concentrations between different tissue types can be detected.
Analysis of a momentum conservative mixed‐FEM for the stationary Navier–Stokes problem
Authors: Camaño Jessika , García Carlos , Oyarzúa Ricardo 
Published: July 2021

AbstractIn this paper, we propose and analyze a new momentum conservative mixed finite element method for the Navier–Stokes problem posed in nonstandard Banach spaces. Our approach is based on the introduction of a pseudostress tensor relating the velocity gradient with the convective term, leading to a mixed formulation where the aforementioned pseudostress tensor and the velocity are the main unknowns of the system. Then the associated Galerkin scheme can be defined by employing Raviart–Thomas elements of degree for the pseudostress tensor and discontinuous piece–wise polynomial elements of degree for the velocity. With this choice of spaces, the equilibrium equation is exactly satisfied if the external force belongs to the velocity discrete space, thus the method conserves momentum, which constitutes one of the main feature of our approach. For both, the continuous and discrete problems, the Banach–Nečas–Babuška and Banach's fixed‐point theorems are employed to prove unique solvability. We also provide the convergence analysis and particularly prove that the error decay with optimal rate of convergence. Further variables of interest, such as the fluid pressure, the fluid vorticity and the fluid velocity gradient, can be easily approximated as a simple postprocess of the finite element solutions with the same rate of convergence. Finally, several numerical results illustrating the performance of the method are provided.
Operator splitting for the fractional Korteweg‐de Vries equation
Authors: Dutta Rajib , Sarkar Tanmay 
Published: July 2021

AbstractOur aim is to analyze operator splitting for the fractional Korteweg‐de Vries (KdV) equation, , , where is a non‐local operator with . Under the appropriate regularity of the initial data, we demonstrate the convergence of approximate solutions obtained by the Godunov and Strang splitting. Obtaining the Lie commutator bound, we show that for the Godunov splitting, first order convergence in is obtained for the initial data in and in case of the Strang splitting, second order convergence in is obtained by estimating the Lie double commutator for initial data in . The obtained rates are expected in comparison with the KdV case.
Basaloid squamous cell carcinoma of the floor of the mouth: A case report with review of the literature
Authors: Kim Yusoon , Yagihara Kazuhiro , Yagishita Hisao , Ishii Junichi , Kanda Hiroaki , Ishikawa Ayataka 
Published: July 2021

AbstractWe present the case of a 66‐year‐old man with basaloid squamous cell carcinoma (BSCC) of the floor of the mouth, which is extremely rare. The patient underwent wide resection of the tumor with partial mandibulectomy and neck dissection. The immunohistochemical staining of surgical specimen showed the p16 positivity, and the examination for human papillomavirus was performed. The patient was followed up for 2 years without any evidence of disease. To address the pathophysiological features of oral BSCC, we reviewed the literature and revealed that the number of early stage cases and the survival rate were higher than in previous reports.
Synthesis of poly(styrene‐co‐allylamine)‐b‐poly(2‐(dimethylamino)ethyl methacrylate) graft copolymers via “grafting from” atom transfer radical polymerization and their self‐assembly in aqueous media
Authors: Azadbakht Maryam , Salami‐Kalajahi Mehdi , Esmizadeh Elnaz , Vahidifar Ali 
Published: July 2021

AbstractIn this work, we report a new synthetic scheme for synthesis of graft copolymers. At first, poly(styrene‐co‐acrylonitrile) copolymers with different molecular weights were synthesized via atom transfer radical polymerization (ATRP). Then, lithium aluminum hydride was used as reducing catalyst of nitrile groups to obtain poly(styrene‐co‐allylamine) copolymers. Amine groups of poly(styrene‐co‐allylamine) copolymers were reacted to 2‐bromo‐2‐methylpropionyl bromide (BiBB) to yield poly(styrene‐co‐N‐allyl‐2‐bromo‐2‐methylpropanamide) (poly(styrene‐co‐NABMPA)) as macroinitiator for “grafting from” ATRP. Then, ATRP of 2‐(dimethylamino)ethyl methacrylate (DMAEMA) was performed to graft PDMAEMA side chains. Finally, self‐assembly behavior of synthesized graft copolymers was investigated in aqueous media with different pH values and morphology of obtained supramolecular structures was studied. Synthesized copolymers were well‐characterized by 1H NMR, 13C NMR, and gel permeation chromatography. Also, morphology of self‐assembled structures was studied by FE‐SEM images whereas dynamic light scattering was utilized to measure particle size and particle size distribution. Results showed that morphology of self‐assembled supramolecular structures depended on molecular weight of backbone and pH value of media. By changing the self‐assembly conditions, different morphologies including spherical, Janus, and interconnected Janus were obtained.
A practical guide to quartz crystal microbalance with dissipation monitoring of thin polymer films
Authors: Easley Alexandra D. , Ma Ting , Eneh Chikaodinaka I. , Yun Junyeong , Thakur Ratul M. , Lutkenhaus Jodie L. 
Published: July 2021

AbstractQuartz crystal microbalance with dissipation (QCM‐D) monitoring is a powerful tool used to sensitively examine the real‐time responses of polymer films to external responses. For example, the technique is commonly used to monitor film growth, material adsorption, thin film swelling, and ion exchange. With its rapidly expanding use, this review is intended to introduce new users to the basic principles of QCM‐D, along with practical challenges and remedies specific to polymer thin films. For both new and experienced users, specific case studies are highlighted including layer‐by‐layer assembly, electrochemical QCM‐D, swelling, sensing, and biological application. Last, the review recommends future directions for research and areas of growth.
Event‐triggered composite anti‐disturbance dissipative control for nonlinear systems with multiple noises and quantized inputs via nonlinear disturbance observer
Authors: Wang Hong‐Du , Liu Yan , Karkoub Mansour , Li Ming , Yuan Lin , Quan Zhao‐Yu 
Published: July 2021

AbstractIn this article, the design problem of an event‐triggered composite anti‐disturbance dissipative control (ECADC) based on nonlinear disturbance observer (NLDO) is considered for a class of nonlinear stochastic systems. These systems comprise quantized inputs and multiple noises including nonlinear disturbances and multiplicative noises. First, a NLDO‐based control scheme is constructed to estimate and then compensate the noise modeled by the nonlinear exosystem. Then, an event‐triggered scheme and a quantized input technique are adopted to alleviate the channel transmission pressure. Subsequently, by combining dissipative control theory, an ECADC design method is developed such that the closed‐loop system is dissipative in the presence of multiple noises. Finally, the effectiveness of the proposed control scheme is validated through numerical simulations.