bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dry Polymer Electrolyte Concepts for Solid‐State Batteries
Authors: Popovic Jelena 
Published: October 2021

AbstractDry polymer electrolytes are a promising class of materials for future safer high‐energy‐density battery technologies. This review deals with the relevant physico‐chemical properties of the dry polymer electrolytes, ionic transport mechanism, molecular structure, and interfacial issues in a widely investigated model system (poly(ethylene oxide) with lithium bis(trifluoromethanesulfonyl)imide). At the end of the review, latest macromolecular approaches for high‐performance lithium battery applications are discussed.
Gain‐clamping in L‐band zirconium–erbium co‐doped fiber amplifier with FBG based lasing control
Authors: Sadik Serif Ali , Durak Firat Ertac , Paul Mukul Chandra , Zulkipli Nur Farhanah , Altuncu Ahmet , Harun Sulaiman Wadi 
Published: October 2021

AbstractIn this study, gain clamping performance in an L‐band zirconium‐erbium co‐doped fiber amplifier (Zr‐EDFA) with a very short length of heavily doped fiber and FBG based lasing control structure was presented. A simple gain clamping design based on a symmetrical narrow band C‐band fiber Bragg grating (FBG) pair addition was used in the L‐band Zr‐EDFA with bidirectionally pumping scheme. An L‐band gain of higher than 25 dB was obtained with a maximum noise figure (NF) of 5 dB in the conventional Zr‐EDFA design which was higher than the previous results obtained with forward pumping scheme. When a couple of narrow band FBGs at Bragg reflection wavelength of 1542 nm are used as the lasing mechanism for gain clamping in L‐band operation, small signal gain of Zr‐EDFA decreases, but on the other hand, the gain is clamped at almost 15.5 dB with a flattened gain spectrum along a dynamic range of 25 dB for the signal input powers between −30 and −5 dBm with the expense of 1.5 dB NF penalty.
Calf circumference is an independent predictor of mortality in older adults: An approach with generalized additive models
Authors: Fernandes Dalila Pinto de Souza , Juvanhol Leidjaira Lopes , Lozano Manuel , Ribeiro Andréia Queiroz 
Published: October 2021

AbstractBackground:There is a wide variation in the cutoff points of body mass index (BMI) and calf circumference (CC) , and it is necessary to assess their adequacy in predicting mortality, especially in the older adults in the community. This study aimed to investigate the association of low muscle mass and underweight with mortality in older adults, comparing different cutoff points.Methods: This was a prospective study that included 796 older adults, not institutionalized, from a Brazilian city. Generalized additive models (GAMs) were used to identify cutoff points for CC and BMI, which were compared with values available in the literature. Survival analysis using Cox regression models was used to assess the independent association between these nutrition indicators and mortality.Results: Over the 9 years of follow‐up, 197 deaths (24.7%) occurred. Cutoff points established for CC and BMI as predictors of mortality were, respectively, <34.5 cm and <24.5. In the adjusted Cox models, older adults with a BMI <18.5 showed a significant increase in the risk of death (hazard ratio [HR], 2.57; 95% CI, 1.23–5.35). Higher mortality was observed among older adults with CC <34.5 cm (HR, 1.72; 95% CI, 1.27–2.33) and CC <31 cm (HR, 2.11; 95% CI, 1.44–3.10).Conclusion: CC was an independent predictor of mortality, and the cutoff point identified by GAMs was higher than recommended by literature (31 cm). This study suggests a review of cutoff points for CC currently adopted to assess low muscle mass in older adults.
Prophylactic supplementation of phosphate, magnesium, and potassium for the prevention of refeeding syndrome in hospitalized individuals with anorexia nervosa
Authors: Gallagher Donna , Parker Anna , Samavat Hamed , Zelig Rena 
Published: October 2021

AbstractMedical stabilization, nutrition rehabilitation, and weight restoration, while minimizing risk for the potentially fatal complication of refeeding syndrome, are the primary goals for the treatment of hospitalized individuals with anorexia nervosa and other restrictive‐type eating disorders. The purpose of this review was to examine the literature exploring the prophylactic supplementation of phosphate, magnesium, and potassium, in addition to routine thiamin and multivitamin supplementation, for the prevention of refeeding syndrome in adolescents and adults with anorexia nervosa. Through evaluation of outcomes (including serum electrolyte levels and clinical signs and symptoms such as respiratory failure, cardiac failure, peripheral edema, rhabdomyolysis, and encephalopathy), three studies found that prophylactic supplementation of potassium, magnesium, and/or phosphate were effective in preventing refeeding syndrome or refeeding hypophosphatemia (a characteristic of refeeding syndrome). Although all studies found that prophylactic supplementation was effective in preventing refeeding syndrome, refeeding approaches (including the method, amount, and duration of nutrient delivery) as well as the populations studied varied considerably, making it difficult to arrive at specific recommendations for practice. Randomized controlled trials are needed to further examine the safety and effectiveness of prophylactic supplementation of phosphate, magnesium, and potassium on the prevention of refeeding syndrome, utilizing similar feeding and supplementation protocols.
Young children’s experiences of support when fearful during treatment for acute lymphoblastic leukaemia—A longitudinal interview study
Authors: Leibring Ingela , Anderzén‐Carlsson Agneta 
Published: October 2021

AbstractAim and objectivesTo describe young children's experiences of valuable support in managing their fears about treatment for acute lymphoblastic leukaemia. The focus was specifically on support from parents and healthcare professionals.DesignThe study had a qualitative descriptive longitudinal design.MethodsThe study analysed 35 interviews with 13 children at three different times during their treatment period. Data were analysed using a matrix‐based method. The Consolidated criteria for reporting qualitative research (COREQ) guidelines have been followed.ResultsParents and healthcare professionals provide important support to children undergoing treatment for acute lymphoblastic leukaemia, although their roles differ. Children valued their parents’ closeness and advocacy, being able to participate in their own care, and being given pain relief during procedures known to create pain. Valued support from healthcare professionals changed over time, from providing information and showing the tools that would be used in procedures, to paying attention to the child's needs and desires. It was more important for children to be able to choose between different alternatives in medical procedures than deciding on major treatment issues.
A systematic, concept‐based method of developing the exposure measure for drug safety and effectiveness studies
Authors: Kuramoto Lisa K. , Sobolev Boris G. , Rosner Jan , Brasher Penelope M. A. , Azoulay Laurent , Cragg Jacquelyn J. 
Published: October 2021

AbstractPurposeIn drug safety and effectiveness studies based on secondary data, the choice of an appropriate exposure measure for a given outcome can be challenging. Different measures of exposure can yield different estimates of treatment effect and safety. There is a knowledge gap with respect to developing and refining measures of drug exposure, to ensure that the exposure measure addresses the study question and is suitable for statistical analysis.MethodsWe present a transparent, step‐by‐step approach to the development of drug exposure measures involving secondary data. This approach would be of interest to students and investigators with initial training in pharmacoepidemiology. We illustrate the approach using a study about Parkinson's disease.ResultsWe described the exposure specifications according to the study question. Next, we refined the exposure measure by linking it to knowledge about four major concepts in drug safety and effectiveness studies: drug use patterns, duration, timing, and dose. We then used this knowledge to guide the ultimate choice of exposure measure: time‐varying, cumulative 6‐month exposure to tamsulosin (a drug used to treat prostate hyperplasia).ConclusionsThe proposed approach links exposure specifications to four major concepts in drug safety and effectiveness studies. Formulating subject‐matter knowledge about these major concepts provides an avenue to develop the rationale and specifications for the exposure measure.
Modal consensus observers for distributed parameter systems
Authors: Demetriou Michael A. 
Published: October 2021

AbstractThis article proposes a new type of a consensus protocol for the synchronization of distributed observers in systems governed by parabolic partial differential equations. Addressing the goal of sharing useful information among distributed observers, it delves into the details governing the modal decompositions of distributed parameter systems. Assuming that two different groups of sensors are available to provide process information to the two distributed observers, the proposed modal consensus design ensures that only useful information is transmitted to the requisite modal components of each of the observers. Without any consensus protocol, the observers capture different frequency content of the spatial process in differing degrees, as it relates to the concept of modal observability. Their modal components exhibit different learning behavior toward the process state. In the extreme case, it turns out that certain modal components of the distributed observers occasionally behave as naïve observers. To ensure that, both collectively and modal componentwise, the observers agree both with the process state and with each other, a modal component consensus protocol is proposed. Such a consensus protocol is mono‐directional and provides only useful information necessary to the appropriate modal component of the distributed filters that behaves as a naïve modal observer. This protocol, when abstracted and applied to different state decompositions can be viewed as mono‐directional projections of information transmitted and received by the participating distributed observers. Detailed numerical studies of advection PDE in one and two spatial dimensions are included to elucidate the details of the proposed modal consensus observers.
Further results on the design of a class of discrete‐time set‐valued state estimators
Authors: Meslem Nacim , Raïssi Tarek , Besançon Gildas 
Published: October 2021

AbstractIn this work, two improvements are proposed for a class of interval‐based state estimators applied to discrete‐time uncertain linear systems subject to additive bounded process and measurement uncertainties. First, we propose to compute the observer gain as a solution of an off‐line constrained nonlinear optimization problem, where the cost function depends on the estimation error width and the constraints ensure the invariance of the estimation error set. Second, to obtain tighter state enclosures, we propose to apply zonotope set computation instead of interval analysis to design a new set‐valued state estimation algorithm. Through simulations, we highlight the interest of the proposed technical improvements.
ABayesianapproach to calibrate system dynamics models usingHamiltonian Monte Carlo
Authors: Andrade Jair , Duggan Jim 
Published: October 2021

AbstractModel calibration is an essential test that dynamic hypotheses must pass in order to serve as tools for decision‐making. In short, it is the search for a match between actual and simulated behaviours using parameter inference. Here, we approach such an inference process from a Bayesian perspective. Under this paradigm, we provide statements about the parameters (viewed as random variables) and data in probabilistic terms. These statements stem from a posterior distribution whose solution is often found via statistical simulation. However, the uptake of these methods within the system dynamics field has been somewhat limited, and state‐of‐the‐art algorithms have not been explored. Therefore, we introduce Hamiltonian Monte Carlo (HMC), an efficient algorithm that outperforms random‐walk methods in exploring complex parameter spaces. We apply HMC to calibrate an SEIR model and frame the process within a practical workflow. In doing so, we also recommend visualisation tools that facilitate the communication of results. © 2021 The Authors.System Dynamics Reviewpublished by John Wiley & Sons Ltd on behalf of System Dynamics Society.
Adaptively stacking ensembles for influenza forecasting
Authors: McAndrew Thomas , Reich Nicholas G. 
Published: October 2021

AbstractSeasonal influenza infects between 10 and 50 million people in the United States every year. Accurate forecasts of influenza and influenza‐like illness (ILI) have been named by the CDC as an important tool to fight the damaging effects of these epidemics. Multi‐model ensembles make accurate forecasts of seasonal influenza, but current operational ensemble forecasts are static: they require an abundance of past ILI data and assign fixed weights to component models at the beginning of a season, but do not update weights as new data on component model performance is collected. We propose an adaptive ensemble that (i) does not initially need data to combine forecasts and (ii) finds optimal weights which are updated week‐by‐week throughout the influenza season. We take a regularized likelihood approach and investigate this regularizer's ability to impact adaptive ensemble performance. After finding an optimal regularization value, we compare our adaptive ensemble to an equal‐weighted and static ensemble. Applied to forecasts of short‐term ILI incidence at the regional and national level, our adaptive model outperforms an equal‐weighted ensemble and has similar performance to the static ensemble using only a fraction of the data available to the static ensemble. Needing no data at the beginning of an epidemic, an adaptive ensemble can quickly train and forecast an outbreak, providing a practical tool to public health officials looking for a forecast to conform to unique features of a specific season.
Development and Validation of Reverse‐Phase High‐Performance Liquid Chromatography Method for Estimation of Itraconazole through Hydroxypropyl Methylcellulose Acetate Succinate based Polymeric Films using Quality by Design principles
Authors: Damle Shantanu , Choudhari Manisha , Singhvi Gautam , Saha Ranendra Narayan , Dubey Sunil Kumar 
Published: October 2021

AbstractThe present work encompasses the application of quality by design principles through the design of experiments for analytical method development using reverse‐phase high‐performance liquid chromatography for estimation of itraconazole as pure drug and from polymeric amorphous dispersion films. A three‐factor three‐level Box Behnken design was used for multivariate analysis of the critical method parameters namely mobile phase composition, flow rate, and pH with a target of achieving a faster retention time of less than 4 min. The optimized method conditions were mobile phase composition of acetonitrile:water in 70:30 ratio, a flow rate of 1 mL/min, and pH of water at pH 7.0. With these method conditions, a retention time of 3.7 min was achieved, and the method was successfully validated to establish linearity in the concentration range of 29.5–129.5 μg/mL with a correlation coefficient of 1.0. The limits of detection and quantification were 0.3 μg/mL and 1.0 μg/mL, respectively. Forced degradation study revealed the ability of the method to detect degradation to oxidation and acidic conditions. This method was used for estimation of drug assay and dissolution from polymeric solid dispersion films prepared at different drug loading concentrations with hydroxypropyl methyl cellulose acetate succinate for accessing formulation variables like polymer type and concentration for improved drug dissolution of Itraconazole.
Macronutrient Interactions to Facilitate Sustained Carbohydrate Digestibility in Tertiary Food Matrix Systems and Their Potential Applications in Indian Pancake
Authors: Prakash Pavan Kumar , Aswathanarayana Setty Jyothi Lakshmi 
Published: October 2021

AbstractThe increasing prevalence of non‐communicable diseases has shifted the consumers' preference for food products with sustained glucose release. This investigation is undertaken to modulate the pattern of carbohydrate digestibility of wheat flour (which is a staple) using oilseed and milk proteins at different levels, which form the binary matrix and with varying levels of fat which form the tertiary matrix. The effect of starch–water gelatinization systems in different ratios (1:10, 1:20) is also studied. Whey protein concentrates and casein reduced the rapidly available glucose (RAG) to a significant extent at 5% protein (p < 0.0001). The addition of fat decreased the RAG further by 1–4%, and RAG increased as a function of hydration (p < 0.0001). The enthalpy values from differential scanning calorimeter revealed that soy protein concentrate and whey protein are the least, at 3.15 and 3.24 J g−1, respectively, which further decreased with fat at 1.52 and 2.81 J g−1. Carbohydrate digestibility is modulated by the interaction of macronutrients in the matrix that is further aided by hydrothermal treatment. The extrapolation of the concept resulted in the formulation of Neer dosa – an instant protein‐enriched Indian pancake with sustained carbohydrate digestibility.
Genomic selection of parents and crosses beyond the native gene pool of a breeding program
Authors: Michel Sebastian , Löschenberger Franziska , Ametz Christian , Bürstmayr Hermann 
Published: October 2021

AbstractGenomic selection has become a valuable tool for selecting cultivar candidates in many plant breeding programs. Genomic selection of elite parents and crossing combinations with germplasm developed outside a breeding program has, however, hardly been explored until now. The aim of this study was to assess the potential of this method for commonly ranking and selecting elite germplasm developed within and beyond a given breeding program. A winter wheat (Triticum aestivum L.) population consisting of 611 in‐house and 87 externally developed lines was used to compare training population compositions and statistical models for genomically predicting baking quality in this framework. Augmenting training populations with lines from other breeding programs had a larger influence on the prediction ability than adding in‐house generated lines when aiming to commonly rank both germplasm sets. Exploiting preexisting information of secondary correlated traits resulted likewise in more accurate predictions both in empirical analyses and simulations. Genotyping germplasm developed beyond a given breeding program is moreover a convenient way to clarify its relationships with a breeder's own germplasm because pedigree information is oftentimes not available for this purpose. Genomic predictions can thus support a more informed diversity management, especially when integrating simply to phenotype correlated traits to partly circumvent resource reallocations for a costly phenotyping of germplasm from other programs.
GPR39 localization in the aging human brain and correlation of expression and polymorphism with vascular cognitive impairment
Authors: Davis Catherine M. , Bah Thierno M. , Zhang Wenri H. , Nelson Jonathan W. , Golgotiu Kirsti , Nie Xiao , Alkayed Farah N. , Young Jennifer M. , Woltjer Randy L. , Silbert Lisa C. , Grafe Marjorie R. , Alkayed Nabil J. 
Published: October 2021

AbstractIntroductionThe pathogenesis of vascular cognitive impairment (VCI) is not fully understood. GPR39, an orphan G‐protein coupled receptor, is implicated in neurological disorders but its role in VCI is unknown.MethodsWe performed GPR39 immunohistochemical analysis in post mortem brain samples from mild cognitive impairment (MCI) and control subjects. DNA was analyzed for GPR39 single nucleotide polymorphisms (SNPs), and correlated with white matter hyperintensity (WMH) burden on pre mortem magnetic resonance imaging.ResultsGPR39 is expressed in aged human dorsolateral prefrontal cortex, localized to microglia and peri‐capillary cells resembling pericytes. GPR39–capillary colocalization, and density of GPR39‐expressing microglia was increased in aged brains compared to young. SNP distribution was equivalent between groups; however, homozygous SNP carriers were present only in the MCI group, and had higher WMH volume than wild‐type or heterozygous SNP carriers.DiscussionGPR39 may play a role in aging‐related VCI, and may serve as a therapeutic target and biomarker for the risk of developing VCI.
Suspected local anaesthetic systemic toxicity (LAST) after several bupivacaine injections through an epidural catheter in a cat
Authors: Quesada Nuria , Pelligand Ludovic , Doig Michael , Sanchis‐Mora Sandra 
Published: October 2021

AbstractA 9‐year‐old male neutered domestic short hair cat was referred to our practice after a road traffic accident. On presentation, the cat was obtunded, with bilateral hindlimb fractures. The fractures were surgically repaired, and an epidural catheter was placed for perioperative pain management. Postoperative analgesia consisted of bupivacaine administered intermittently through the epidural catheter. In the days after surgery, the cat became duller and more obtunded, and marked bilateral mydriasis with absence of a pupillary reflex was noted. After ruling out different causes for mydriasis and weaning the cat from systemic opioids, local anaesthetic systemic toxicity (LAST) emerged the primary differential diagnosis. Bupivacaine plasma concentrations were measured and found a fourfold increase in concentration over that reported after a perineural block. Mydriasis and absent pupillary light reflex, among other clinical signs, could be early indicators of LAST secondary to accumulation of the local anaesthetic in patients with an epidural catheter.
What Is the Sublinear Computation Paradigm?
Authors: Katoh Naoki , Ito Hiro 
Published: October 2021

AbstractThis chapter introduces the “sublinear computation paradigm.” A sublinear-time algorithm is an algorithm that runs in time sublinear in the size of the instance (input data). In other words, the running time iso(n), wherenis the size of the instance. This century marks the start of the era of big data. In order to manage big data, polynomial-time algorithms, which are considered to be efficient, may sometimes be inadequate because they may require too much time or computational resources. In such cases, sublinear-time algorithms are expected to work well. We call this idea the “sublinear computation paradigm.” A research project named “Foundations on Innovative Algorithms for Big Data (ABD),” in which this paradigm is the central concept, was started under the CREST program of the Japan Science and Technology Agency (JST) in October 2014 and concluded in September 2021. This book mainly introduces the results of this project.
Review of Sublinear Modeling in Probabilistic Graphical Models by Statistical Mechanical Informatics and Statistical Machine Learning Theory
Authors: Tanaka Kazuyuki 
Published: October 2021

AbstractWe review sublinear modeling in probabilistic graphical models by statistical mechanical informatics and statistical machine learning theory. Our statistical mechanical informatics schemes are based on advanced mean-field methods including loopy belief propagations. This chapter explores how phase transitions appear in loopy belief propagations for prior probabilistic graphical models. The frameworks are mainly explained for loopy belief propagations in the Ising model which is one of the elementary versions of probabilistic graphical models. We also expand the schemes to quantum statistical machine learning theory. Our framework can provide us with sublinear modeling based on the momentum space renormalization group methods.