bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficacy of topical lidocaine‐prilocaine (EMLA®) for management of infant pain during pneumococcal vaccination: A randomized controlled trial
Authors: Olsson Duse Beatrice , Sporrong Ylva , Bartocci Marco , Skoglund Karin 
Published: December 2021

AbstractFew studies have evaluated whether topical anesthetic cream reduces pain during pneumococcal vaccination. This is crucial, since effective pain management should be evidence‐based. Previous studies have shown that topical lidocaine‐prilocaine (EMLA®) reduces vaccination‐related pain, measured using pain‐rating instruments and observation of crying time. This intervention study aimed to compare the efficacy of topical lidocaine‐prilocaine cream with that of the standard of care on the expression of pain during the first pneumococcal vaccination administered at age 3 months under the Swedish national vaccination program. A randomized controlled trial included 72 infants receiving their first pneumococcal vaccination (Prevenar 13®). The study showed that topical lidocaine‐prilocaine before pneumococcal vaccination significantly reduced infants’ expression of pain according to the Face, Legs, Activity, Cry, Consolability (FLACC) score (P = .006) and increased latency to cry (P = .001). There were no statistically significant differences in the total crying time (P = .146) between the groups. Topical lidocaine‐prilocaine cream reduced pain expression and increased latency to cry in infants receiving their first pneumococcal vaccine. Systematic efforts are needed to successfully implement the use of topical anesthetic cream and other effective non‐pharmacological pain‐relieving strategies during infant vaccination procedures.
Tailoring electric field signals of nonequilibrium discharges by the deep learning method and physical corrections
Authors: Zhu Yifei , Bo Yin , Chen Xiancong , Wu Yun 
Published: December 2021

AbstractSmart modulation of discharges is necessary to generate specific reactive species in an energy‐efficient way. A physics corrected plasma + deep learning framework, the DeePlaskin, is proposed. This framework can be used for the nonequilibrium plasma systems that can be described by a global chemistry model (assuming global uniformity, e.g., in spark channels or the early afterglow of the fast ionization wave discharges). Knowing the kinetics scheme and the predefined temporal evolution of target species, we will be able to reconstruct the temporal profile of the reduced electric field and all the other species. To generate the same concentration of O atom at the end of the discharge, the electric field profiles customized by the DeePlaskin differ significantly depending on the predefined evolution, resulting in different energy consumption. The combination of the deep learning method and plasma physics/chemistry model shows great potential in optimizing the design of plasma sources in practical applications.
The return of RSV during the COVID‐19 pandemic
Authors: Ferrero Fernando , Ossorio Maria F. , Rial Maria J. 
Published: December 2021

AbstractRespiratory syncytial virus (RSV) hospitalizations practically disappeared in 2020. Now, with Southern Hemisphere 2021 winter behind us, RSV has returned. Despite it is difficult to weigh the impact of pandemic mitigation measures on common respiratory virus circulation, it appears that acute respiratory infections in children are returning to their usual epidemiology
Genomic analyses of the metastasis‐derived prostate cancer cell lines LNCaP, VCaP, and PC3‐AR
Authors: Sienkiewicz Karolina , Yang Chunsong , Paschal Bryce M. , Ratan Aakrosh 
Published: December 2021

AbstractBackgroundThe lymph node metastasis‐derived LNCaP, the bone metastasis‐derived PC3 (skull), and VCaP (vertebral) cell lines are widely used as preclinical models of human prostate cancer (CaP) and have been described in more than 19,000 publications. Here, we report on short‐read whole‐genome sequencing and genomic analyses of LNCaP, VCaP, and PC3 cells stably transduced with WT AR (PC3‐AR).MethodsLNCaP, VCaP, and PC3‐AR cell lines were sequenced to an average depth of more than 30‐fold using Illumina short‐read sequencing. Using various computational methods, we identified and compared the single‐nucleotide variants, copy‐number profiles, and the structural variants observed in the three cell lines.ResultsLNCaP cells are composed of multiple subpopulations, which results in nonintegral copy number states and a high mutational load when the data is analyzed in bulk. All three cell lines contain pathogenic mutations and homozygous deletions in genes involved in DNA mismatch repair, along with deleterious mutations in cell‐cycle, Wnt signaling, and other critical cellular processes. PC3‐AR cells have a truncating mutation in TP53 and do not express the p53 protein. The VCaP cells contain a homozygous gain‐of‐function mutation in TP53 (p.R248W) that promotes cancer invasion, metastasis, and progression and has also been observed in prostate adenocarcinomas. In addition, we detect the signatures of chromothripsis of the q arms of chromosome 5 in both PC3‐AR and VCaP cells, strengthening the association of TP53 inactivation with chromothripsis reported in other systems.ConclusionsOur work provides a resource for genetic, genomic, and biological studies employing these commonly‐used prostate cancer cell lines.
Evaluation of the clinical cardiac safety of pemigatinib, a fibroblast growth factor receptor inhibitor, in participants with advanced malignancies
Authors: Gong Xiaohua , Ji Tao , Liu Xiang , Chen Xuejun , Yeleswaram Swamy 
Published: December 2021

AbstractPemigatinib is a potent inhibitor of the fibroblast growth factor receptor (FGFR) family of receptors that is approved for the treatment of cholangiocarcinoma with FGFR2 fusion or other rearrangements. Data from a first‐in‐human clinical study were used to assess the potential for pemigatinib to produce clinically significant effects on heart rate (HR) and cardiac repolarization (QTc). A central tendency analysis for electrocardiogram (ECG) outliers and a plasma concentration‐QTc analysis were conducted to assess cardiac safety in the first‐in‐human pemigatinib study (FIGHT‐101; NCT02393248). The study included 113 participants who received at least one dose of pemigatinib as monotherapy and had at least one pair of plasma pharmacokinetic (PK) and ECG data points collected. Timed 12‐lead ECGs were performed within 15 min of PK blood draws. The ECG parameters for each dose group in the study varied within expectations for patients with advanced malignancies. Categorical analysis of QT interval corrected for HR by Fridericia's method did not reveal dose dependence in the incidence of outliers, and the results of the central tendency and concentration‐QTc analyses did not suggest a dose‐ or concentration‐dependent drug effect. Least squares mean change from baseline in HR was small and did not indicate a clinically relevant effect on HR, and no effect was observed on cardiac conduction as assessed by PR and QRS intervals. In conclusion, pemigatinib does not exhibit any clinically significant prolongation of QTc or dose‐dependent changes in HR.Clinical trial registration: ClinicalTrials.gov NCT02393248.
A new management tactic for Eucryptorrhynchus scrobiculatus (Coleoptera: Curculionidae) based on factors influencing the weevil population density
Authors: Yang Kailang , Wen Junbao 
Published: December 2021

AbstractBACKGROUNDThe tree of heaven root weevil, Eucryptorrhynchus scrobiculatus (TRW), is one of the most damaging pests of Ailanthus altissima in China. A limited number of studies have examined the effects of different variables on the population density of TRW adults. We investigated the relative impacts of the diameter at breast height of host trees (DBH), number of tree species in plots (NTS), weed coverage rate of the host tree base (WCR), plot area (PA), distance from plots to the nearest farmland (DNF), nearest human community (DNHC), nearest irrigation canal (DNIC), and nearest road (DNR) on TRW population density. We then evaluated the effect of removing weeds at the base of the tree trunk (RW) on TRW population density.RESULTSWe found that DBH, WCR, PA, and DNHC significantly affected the population density of TRW adults, whereas NTS, DNF, DNIC, and DNR did not. Adult TRW density was positively correlated with DBH, WCR, and PA but was negatively correlated with DNHC. Further field trials showed that RW treatments significantly reduced the density of adult TRW (an average annual reduction of 51.7% compared to untreated trees).CONCLUSIONThis information on the factors affecting the population density of TRW promoted the development of new TRW management strategies. Our results demonstrate that RW is an effective method for reducing the population density of TRW adults. Therefore, this new physical method using RW could be recommended as an alternative for TRW management in the framework of integrated pest management. © 2021 Society of Chemical Industry.
Estimation of multivariate treatment effects in contaminated clinical trials
Authors: Ye Zi , Harrar Solomon W. 
Published: December 2021

AbstractThe paper addresses estimating and testing treatment effects with multivariate outcomes in clinical trials where imperfect diagnostic devices are used to assign subjects to treatment groups. The paper focuses on the pre‐post design and proposes two novel methods for estimating and testing treatment effects. In addition, methods for sample size and power calculations are developed. The methods are compared with each other and with a traditional method in a simulation study. The new methods show significant advantages in terms of power, coverage probability, and required sample size. The application of the methods is illustrated with data from electroencephalogram (EEG) recordings of alcoholic and control subjects.
Energy efficient management for distributed state estimation under DoS attacks
Authors: Lei Hongyi , Yang Wen , Yu Yan 
Published: December 2021

AbstractIn this article, we consider the issue of energy efficient management for distributed state estimation over unknown packet‐dropping communication channels which are exposed to Denial‐of‐Service (DoS) attacks. After a packet is transmitted, the sensor determines whether to retransmit and the retransmission power levels based on the feedback information from the receiving sensor. We formulate the energy efficient management problem as a modified Markov decision problem (MMDP), and proposed an algorithm to seek a retransmission power schedule that achieves optimal tradeoff between energy consumption and communication rate for given channel noise power. In the case of unknown channel state, we design a statistical learning method to estimate channel noise power. Besides, inspired by the hypothesis testing, we design an anomaly detector to guarantee the instantaneity of channel noise power estimation and efficiency of energy management. Furthermore, we derive the optimal gain for each estimator, and provide a sufficient condition for the stability of estimator under the energy management. Finally, we verify the main results by numerical examples.
Adaptive fault‐tolerant optimized formation control for perturbed nonlinear multiagent systems
Authors: Ji Weiyu , Pan Yingnan , Zhao Meng 
Published: December 2021

AbstractThis article proposes an adaptive fault‐tolerant formation control strategy for strict‐feedback nonlinear multiagent systems with nonlinear faults and external disturbances. A simplified reinforcement learning algorithm is developed for approximating the optimized controller. Different from the existing optimized control results, the system dynamics is totally unknown in this article. In order to surmount “explosion of complexity”, the dynamic surface control technique is employed. A disturbance‐fault observer is employed to alleviate the influence caused by the external disturbances and the impact coming from the nonlinear faults. Based on the Lyapunov stability theorem, it can be demonstrated that all signals within the closed‐loop systems are semiglobal uniformly ultimately bounded and the optimized formation control performance can be guaranteed. Finally, some simulation results are exhibited the validity of the developed control method.
Coping strategies moderate the effect of perceived stress on sleep and health in older adults during the COVID‐19 pandemic
Authors: Tracy Eunjin L. , Chin Brian , Lehrer H. Matthew , Carroll Lucas W. , Buysse Daniel J. , Hall Martica H. 
Published: December 2021

AbstractStress in the context of the COVID‐19 pandemic may have a significant impact on health, including sleep health. Older adults may be particularly vulnerable. This study examined associations between perceived stress and sleep health, mental health, physical health, and overall perceived health outcomes among older adults. We also examined whether specific coping strategies moderate these associations. Older adults (n = 115; Mage = 68.62) reported perceived stress, coping strategies, global sleep quality, depressive symptoms, and perceived mental, physical, and overall health before and during the COVID‐19 pandemic. Stress‐health relationships were modelled with hierarchical linear regression. Higher perceived stress was associated with greater depressive symptoms and poorer mental health concurrently and longitudinally. Coping strategies moderated the association of perceived stress with physical health and overall perceived health. For example, higher perceived stress was associated with poorer overall perceived health among those with lower problem‐focussed coping, but not among those with higher problem‐focussed coping. Older adults may benefit from prevention and intervention strategies targeting stress management. Furthermore, identifying people with low problem‐focussed coping might be a useful strategy to prevent worsening health in future public health crises.
Degree assortativity in collaboration networks and invention performance
Authors: Khanna Rajat , Guler Isin 
Published: December 2021

AbstractResearch SummaryWe investigate the implications of the degree assortativity of intra‐firm networks for firms' innovation performance. We argue that prevalent patterns of collaborative relationships between organizational members can lead to variations in the levels of degree assortativity in intra‐firm networks, ranging from disassortative structures (highly central members connect with peripheral members) to assortative ones (highly central members connect with other highly central members and vice versa). These patterns influence knowledge access and resource mobilization pathways and are thus associated with various firm‐level invention outcomes. Using coarsened exact matching methodology and controlling for other characteristics of the intra‐firm network structures, we find that assortative structures in the pharmaceutical industry are associated with larger invention output, but inventions originating from assortative structures have lower average novelty and impact.Managerial SummaryA central challenge in knowledge‐based industries is the design of collaborative teams to increase innovative output. In this article, we show that firms in the pharmaceutical industry vary in the extent to which central inventors within a firm collaborate with peripheral inventors. Further, the ideal composition varies based on the desired innovative output: Firms with frequent collaborations between central inventors have higher inventive productivity, while firms with higher mixing between central and peripheral inventors generate inventions that are on average more novel and have higher impact. Results have implications for organizational design toward desired innovative outcomes, as well as management of strategic human capital.
Lattice Strain and Defects Analysis in Nanostructured Semiconductor Materials and Devices by High‐Resolution X‐Ray Diffraction: Theoretical and Practical Aspects
Authors: Dolabella Simone , Borzì Aurelio , Dommann Alex , Neels Antonia 
Published: December 2021

AbstractThe reliability of semiconductor materials with electrical and optical properties are connected to their structures. The elastic strain field and tilt analysis of the crystal lattice, detectable by the variation in position and shape of the diffraction peaks, is used to quantify defects and investigate their mobility. The exploitation of high‐resolution X‐ray diffraction‐based methods for the evaluation of structural defects in semiconductor materials and devices is reviewed. An efficient and non‐destructive characterization is possible for structural parameters such as, lattice strain and tilt, layer composition and thickness, lattice mismatch, and dislocation density. The description of specific experimental diffraction geometries and scanning methods is provided. Today's X‐ray diffraction based methods are evaluated and compared, also with respect to their applicability limits. The goal is to understand the close relationship between lattice strain and structural defects. For different material systems, the appropriate analytical methods are highlighted.
Spatial machine learning: new opportunities for regional science
Authors: Kopczewska Katarzyna 
Published: December 2021

AbstractThis paper is a methodological guide to using machine learning in the spatial context. It provides an overview of the existing spatial toolbox proposed in the literature: unsupervised learning, which deals with clustering of spatial data, and supervised learning, which displaces classical spatial econometrics. It shows the potential of using this developing methodology, as well as its pitfalls. It catalogues and comments on the usage of spatial clustering methods (for locations and values, both separately and jointly) for mapping, bootstrapping, cross-validation, GWR modelling and density indicators. It provides details of spatial machine learning models, which are combined with spatial data integration, modelling, model fine-tuning and predictions to deal with spatial autocorrelation and big data. The paper delineates “already available” and “forthcoming” methods and gives inspiration for transplanting modern quantitative methods from other thematic areas to research in regional science.
The interplay between unexpected events and behavior in the development of explicit knowledge in implicit sequence learning
Authors: Lustig Clarissa , Esser Sarah , Haider Hilde 
Published: December 2021

AbstractSome studies in implicit learning investigate the mechanisms by which implicitly acquired knowledge (e.g., learning a sequence of responses) becomes consciously aware. It has been suggested that unexpected changes in the own behavior can trigger search processes, of which the outcome then becomes aware. A consistent empirical finding is that participants who develop explicit knowledge show a sudden decrease in reaction times, when responding to sequential events. This so called RT-drop might indicate the point of time when explicit knowledge occurs. We investigated whether an RT-drop is a precursor for the development of explicit knowledge or the consequence of explicit knowledge. To answer this question, we manipulated in a serial reaction time task the timing of long and short stimulus-onset asynchronies (SOA). For some participants, the different SOAs were presented in blocks of either long or short SOAs, while for others, the SOAs changed randomly. We expected the participants who were given a blocked presentation to express an RT-drop because of the predictable timing. In contrast, randomly changing SOAs should hamper the expression of an RT-drop. We found that more participants in the blocked-SOA condition than in the random-SOA condition showed an RT-drop. Furthermore, the amount of explicit knowledge did not differ between the two conditions. The findings suggest that the RT-drop does not seem to be a presupposition to develop explicit knowledge. Rather, it seems that the RT-drop indicates a behavioral strategy shift as a consequence of explicit knowledge.
Adipocytokines and disease progression in endometrial cancer: a systematic review
Authors: Ray Irene , Meira Lisiane B. , Michael Agnieszka , Ellis Patricia E. 
Published: December 2021

AbstractThe objective of the study was to document the effect of adipocytokines on endometrial cancer progression. A search of the databases CINAHL, Medline, PubMed, Cochrane, Web of Science, Embase and Google Scholar was performed for English language articles from January 2000 to December 2020 using the keywords: (Endometrial cancer) AND (progression OR metastasis) AND (adipocytokine OR adiponectin OR leptin OR visfatin OR IL-6 OR TNF-α OR adipokine OR cytokine). Forty-nine studies on adipocytokines have been included in this review. Adiponectin has been linked with anti-proliferative and anti-metastatic effects on endometrial cancer cells and is associated with a better prognosis. Leptin, visfatin and resistin are linked to the stimulation of endometrial cancer growth, proliferation, invasion and metastasis and are associated with worse prognosis or with a higher grade/stage of endometrial cancer. IL-6, Il-11, IL-31, IL-33, TNF-α, TGF-β1, SDF-1 and CXCR are involved in endometrial cancer cell growth and metastasis or involved in epithelial mesenchymal transformation (EMT) or associated with advanced disease. Adipocytokines have been found to directly impact endometrial cancer cell proliferation, invasion and migration. These molecules and their signalling pathways may be used to determine prognosis and course of the disease and may also be exploited as potential targets for cancer treatment and prevention of progression.
Tax collection in the Roman Empire: a new institutional economics approach
Authors: Gutiérrez Óscar , Martínez-Esteller Marco 
Published: December 2021

AbstractThis paper reviews the Roman tax collection system since the Late Republic to the Principality, focusing on the transition from the tax-farming system to a more centralized, census-based administration. We attempt to justify this transition according to New Institutional Economic theories (Transaction Cost Economics and Property Rights Theory). The paper argues that, during the Republic, the auction-based system of tax farming ended up giving place to opportunistic behaviors and abusing practices due to information asymmetries and contract incompleteness, enhanced by the collusion of tax farmers and governors. The Principality improved the efficiency of the tax collection system through the introduction of a bureaucratic and census-based administration, which allowed imperial employees to monitor the tax-farming activities.