bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physicochemical Modeling of Barium and Sulfate Transport in Porous Media and Its Application in Seawater-Breakthrough Monitoring
Authors: Wang Yanqing , Li Xiang , Lu Jun 
Published: May 2021

SummarySeawater injection is widely used to improve oil recovery in offshore oil reservoirs. However, injecting seawater into reservoirs can cause many flow-assurance issues, such as scaling and reservoir souring, which are strongly related to the percentage of seawater breakthrough. Thermodynamic models have been developed to evaluate the effects of barite deposition on oil production, but the reservoir stripping effect has not been fully considered. In this study, a new model that incorporates both chemical reaction (barium and sulfate reaction) and physical reactions (ion adsorption/desorption) is developed to investigate the in-situ barite-deposition process. To the best of our knowledge, for the first time, ion adsorption/desorption is integrated by coupling the adsorption/desorption isotherm to the reservoir simulator. The barium and sulfate chemical reaction is modeled by incorporating the solubility product constant into the model. The model accuracy is verified through convergence rate tests and comparison with the coreflood experimental results. The simulation results of both barium and sulfate concentration profiles are greatly improved by integrating the ion adsorption/desorption process. The new physicochemical model is further used to investigate barite deposition under various scenarios. Simulation results indicate that most barite deposits are in the deep reservoir for the areal model. Barite that deposits in the reservoir before seawater breakthrough accounts for 45% of total barite deposition and the barite deposited during the seawater-breakthrough period makes up 54%, while the deposition during the tailing period, where the seawater fraction is larger than 95%, is negligible. For a homogeneous reservoir, the barite-deposition period at the near-wellbore area of the producer is between 30% and 65% of the seawater-breakthrough percentage, and heterogeneity leads to a broader deposition period. For vertical heterogeneous reservoirs, a considerable amount of barite forms in the wellbore, which accounts for 17% of total barite deposition. Based on the accurate simulation of barium and sulfate transport in the reservoir, barium and sulfate concentration profiles can be used to determine the seawater-breakthrough percentage and help optimize production operations that aim to mitigate flow assurance issues.
Colonization with Extensively Drug-Resistant Acinetobacter baumannii and Prognosis in Critically Ill Patients: An Observational Cohort Study
Authors: Zheng Yue , Xu Nana , Pang Jiaojiao , Han Hui , Yang Hongna , Qin Weidong , Zhang Hui , Li Wei , Wang Hao , Chen Yuguo 
Published: May 2021

Abstract
BackgroundAcinetobacter baumannii is one of the most frequently isolated opportunistic pathogens in intensive care units (ICUs). Extensively drug-resistant A. baumannii (XDR-AB) strains lack susceptibility to almost all antibiotics and pose a heavy burden on healthcare institutions. In this study, we evaluated the impact of XDR-AB colonization on both the short-term and long-term survival of critically ill patients.MethodsWe prospectively enrolled patients from two adult ICUs in Qilu Hospital of Shandong University from March 2018 through December 2018. Using nasopharyngeal and perirectal swabs, we evaluated the presence of XDR-AB colonization. Participants were followed up for 6 months. The primary endpoints were 28-day and 6-month mortality after ICU admission. The overall survival rate was estimated by the Kaplan-Meier method. We identified risk factors associated with 28-day and 6-month mortality using the logistic regression model and a time-dependent Cox regression model, respectively. ResultsOut of 431 patients, 77 were colonized with XDR-AB. Based on the Kaplan-Meier curve results, the overall survival before 28 days did not differ by colonization status; however, a significantly lower overall survival rate was obtained at 6 months in colonized patients. Univariate and multivariate analysis results confirmed that XDR-AB colonization was not associated with 28-day mortality, but was an independent risk factor of lower overall survival at 6 months (HR = 1.749, 95% CI = 1.174–2.608).ConclusionsXDR-AB colonization has no effect on short-term overall survival, but is associated with lower long-term overall survival in critically ill patients.
Piloting A Self-Reported Symptom Assessment Tool In Three Outpatient Oncology Palliative Care Clinics
Authors: Patel Mallikaben Bhanubhai , Bryant Ashley Leak , Mayer Deborah K , Winzelberg Gary 
Published: May 2021

Abstract
Background: Palliative care outpatient clinics should assess patients’ symptoms and quality of life prior to visits to guide care and response to treatments. We describe the implementation of a quality improvement initiative to increase symptom and quality of life screening in the outpatient oncology palliative care (OOPC) clinics of one National Cancer Institute-designated Comprehensive Cancer Center. Method: Our quality improvement project structure was based on the RE-AIM framework. Guided by the Plan-Do-Study-Act (PDSA) approach, we focused on assessing effective implementation of the Edmonton Symptom Assessment Scale (ESAS-r ) and one Quality of Life (QoL) question at each OOPC visit. At the end of each 3-week PDSA cycle, barriers and facilitators were recognized and addressed. The implementation’s effectiveness was determined by percentage of adherence using the following formula: [(number of ESAS-r +1 QoL forms completed per clinic/Number of OOPC completed patient appointments per clinic) x 100].Results: A total of 372 patient appointments were completed during the four PDSA cycles, with overall 59% adherence. The first PDSA cycle compliance was 69%, 58% in the second, 52% in the third, and 65% at the last PDSA cycle. The primary barrier was staff turnover.Conclusion: We were able to implement the ESAS-r + 1 QoL form in a complex clinical outpatient setting. We identified barriers for sustainability, including staff turnover. We addressed these barriers by providing robust instructions that outlined an overview of the clinic workflow and education for all staff members involved in the implementation process. Based on our experience, we suggest integrating this form into the electronic medical record to monitor patient outcomes in the outpatient oncology clinics.
Detection of A Novel PAX6 Mutation In A Chinese Family With Multiple Ocular Abnormalities
Authors: Ouyang Junyi , Cai Ziyan , Guo Yinjie , Nie Fen , Cao Mengdan , Duan Xuanchu 
Published: May 2021

Abstract
Background:Aniridia is a congenital, panocular disease which could affect cornea, anterior chamber angle, iris, lens, retina and optic nerve. PAX6 loss-of-function mutations were the most common cause of aniridia. Mutations throughout the PAX6 gene have been linked to a range of ophthalmic abnormalities. Distinct mutations at a given site in PAX6 lead to distinctive phenotypic findings. This study aimed to characterize genetic mutations associated with congenital aniridia in a Chinese family.Methods:The proband and family underwent ophthalmologic examinations as well as exome sequencing. Results have been confirmed by Next Generation Sequencing.Results:A novel mutation(c.114_119delinsAATTTCC:p.Pro39llefsTer17)in the PAX6 gene was identified in subjectsⅡ-1, III-1 and III-2 in these family who exhibited complete aniridia and cataract. Proband and the proband’s brother also exhibited glaucoma, high myopia, and foveal hypoplasia.Conclusions：We identified a novel PAX6 frameshift heterozygous deletion mutation in a Chinese family and infered this mutation a probable cause of various eye abnormalities in carriers. Trial registration：We did not do any health-related interventions on the participants.
Opposition-Based Multi-Objective Whale Optimization Algorithm with Multi-Leader Guiding
Authors: Li Yang , Li Wei-gang , Zhao Yun-tao , Liu Ao 
Published: May 2021

Abstract
Over the years, heuristic algorithms have been widely studied, especially in multi-objective optimization problems (MOPs). The multi-objective whale optimization algorithm based on multi-leader guiding (MOWOAMLG) is proposed in this paper, which is the multi-objective version of whale optimization algorithm (WOA). The proposed algorithm adopts several improvements to enhance optimization performance. First, multiple leadership solutions guide the population to search the sparse space to achieve more homogeneous exploration in per iteration, and the leadership solutions are selected on the Pareto front by grid mechanism and the principle of maximum crowding distance. Second, the differential evolution (DE) is employed to generate the offspring for the leadership solutions, while WOA is employed for the ordinary solutions. In addition, a novel opposition-based learning (OBL) strategy is developed to improve the distribution of the initial population. To show the significance of the proposed algorithm, it is tested on the 20 bi-objective and tri-objective unconstrained benchmark problems of varying nature and complexities. The result of numerical experiments shows that the proposed algorithm has competitive advantages in convergence and distribution while compared with other 10 classic or state-of-the-arts algorithms. The convergence curve of IGD indicates that MOWOAMLG is able to obtain good Pareto front in cost of fewer optimization iterations. Moreover, it is tested on load distribution of hot rolling, and the result proves its good performance in real-world applications. Thus, all of the aforementioned results have indicated that MOWOAMLG is comparatively effective and efficient to solve MOPs.
In vitro and In Silico Approach For Characterization of Antimicrobial Peptide From Probiotics Against Staphylococcus Aureus and Escherichia Coli
Authors: Bindu Amrutha , Devi Lakshmi 
Published: May 2021

Abstract
The focus of present study was to characterize antimicrobial peptide produced by probiotic cultures, Enterococcus durans DB-1aa (MCC4243), Lactobacillus plantarum Cu2-PM7 (MCC4246) and Lactobacillus fermentum Cu3-PM8 (MCC4233) against Staphylococus aureus and E. coli. The growth kinetic assay revealed 24 h of incubation to be optimum for bacteriocin production. The partially purified compound after ion-exchange chromatography was found to be thermoresistant and stable under wide range of pH. The compound was sensitive to proteinase-K, but resistant to trypsin, a-amylase and lipase. The apparent molecular weight of bacteriocin from MCC4243 and MCC4246 was found to be 3.5 KDa. Translated partial amino acid sequence of plnA gene in MCC4246 displayed 48 amino acid sequences showing 100% similarity with plantaricin A of Lactobacillus plantarum (WP_0036419). The sequence revealed 7 β sheets, 6 α sheets, 6 predicted coils and 9 predicted turns. The functions on cytoplasm show 10.82 isoelectric point and 48.6% hydrophobicity. The molecular approach of using Geneious Prime software and protein prediction data base for characterization of bacteriocin is novel and predicts “KSSAYSLQMGATAIKQVKKLFKKWGW” as peptide responsible for antimicrobial activity. The study provides information about broad spectrum bacteriocin in native probiotic culture and paves a way towards its application in functional foods as biopreservative agents.
Preoperative Risk-Stratification of Pediatric Malignant Brainstem Glioma based on a validated nomogram: A SEER based Analysis
Authors: Che wenqiang , Lyu Jun , Li Chengzhuo , Wang Xiangyu 
Published: May 2021

Abstract
Purpose: Pediatric patients diagnosed with brainstem malignant gliomas (BSMGs) have a poor prognosis. Our study aimed to construct and validate a prognostic nomogram to predict the cancer‐specific survival preoperatively (CSS) rates and then a risk-stratification given to these patients.Methods: From 1998 to 2016, we extracted patients' data from Surveillance Epidemiology and End Results (SEER) database. A total of 1160 patients were enrolled and randomly divided into training and validating groups. Subsequently, the Cox regression analysis was used to screen variables. Then, the nomogram was constructed. Lastly, we calculated C-indexes and plotted calibration curves and the utility of decision curve analyses (DCAs) to assess our survival model's benefits.Result: Here, after multivariate cox regression analysis, we established four variables for constructing nomogram for CSS rates. Subsequently, the C-index, the area under the receiver operating characteristic curve, and calibration curves were used to confirm the nomogram's good performance. DCAs of the nomogram indicated that both groups obtained good 1-, 3-, and 5-year net benefits. Conclusion: The nomogram model for preoperatively predicting CSS provided a convenient and practical tool to assess pediatric patients' prognosis with BSMG.
Development of a Neural Statistical Model for the Relative Humidity Levels Prediction in the Region of Rabat-Kenitra (Morocco)
Authors: Elazhari Kaoutar , ABDALLAOUI Badreddine , DEHBI Ali , ABDALLAOUI Abdelaziz , ZINEDDINE Hamid 
Published: May 2021

Abstract
This work provides the development of a powerful artificial neural network (ANN) model, for the prediction of relative humidity levels, using other meteorological parameters of the Rabat-Kenitra region. The treatment was applied to a database containing a daily history of five meteorological parameters of 9 stations covering this region for a period from 1979 to mid-2014. We have shown that for the prediction of relative humidity in this region, the best performing three-layer ANN (input, hidden and output) mathematical model is the multi-layer perceptron (MLP) model. This neural model using the Levenberg-Marquard algorithm, having an architecture [5-11-1] and the transfer functions Tansig in the hidden layer and Purelin in the output layer was able to estimate values for relative humidity very close to those observed. Indeed, this was affirmed by a low mean squared error (MSE) and a fairly high correlation coefficient (R), compared to the statistical indicators relating to the other models developed as part of this study.
Putting the Meaning Into Meaningful Change Research
Authors: Braid Jessica , Clinch Susanne , Staunton Hannah M , Corey-Lisle Patricia K , Kovic Bruno , Connor Siobhan , Ciobanu Teofil , Willgoss Thomas 
Published: May 2021

Abstract
PurposeMethods for deriving clinically meaningful change thresholds have advanced considerably in recent years, however, key questions remain about what the identified change score actually means for an individual patient or group of patient. This is particularly important in the case of ClinROs where the translation from clinically meaningful change to patient-relevance in daily living is not clear. This paper provides case studies from an Industry perspective, where we have addressed this challenge using varied approaches. We have explored meaningful change at both the group and individual level.MethodsWe provide several case studies to illustrate different approaches to understanding and communicating a meaningful outcome on a ClinRO. These include alternative methods for interpreting group-level MCIDs, and several examples of linking ClinRO items to patient-relevant real-world concepts e.g. through exit interviews, translation of ClinRO items into patient-friendly concepts, and use of the Rasch model to equate ClinRO items to real-world functional measures.ResultsEach case study provides unique learning opportunities. For example, contextualising group-level differences, converting MCIDs into other metrics like numbers needed to treat and responder deltas supports interpretation of clinical meaning, especially for clinicians. For interpreting individual-level meaningful change, exit interviews and the development of patient-friendly versions of ClinROs provide a means of linking clinician-focused content to real-world functional outcomes in a meaningful way for patients. Finally, the Rasch model can help predict probable item scores on a ClinRO associated with the threshold at which a function is gained or lost.Conclusion﻿While methods for deriving meaningful change thresholds have evolved, there remains a significant challenge in communicating what observed changes mean to the patient, a challenge which is further complicated in ClinROs. These case studies showcase novel approaches to addressing this challenge and may provide a useful addition to the COA scientist’s toolbox.
Hepatoprotective Effect of Costus Afer On Trace Metal Mixture Treated Rats Mediated By Regulation of Oxidative Stress Markers, Inflammatory Cytokines And Bio-Metal Chelation
Authors: Anyanwu Brilliance Onyinyechi , Ezejiofor Anthonet N. , Nwaogazie Ify L. , Orisakwe Orish Ebere 
Published: May 2021

Abstract
Technological developments have led to exposure to various substances that are harmful to the environment and public health, including heavy metals. In the environment, these grades of metals are usually diverse mixtures shown to cause physiological, biochemical and neurological dysfunctions in humans and laboratory animals. Cadmium, Lead, and mercury have been envisaged to exhibit their hepatotoxic effects by oxidative induction damage and synthesis of reactive oxygen species (ROS). The current work evaluated the protective activity of aqueous leaf extract of Costus afer (ALECA)) on liver damage arsing from exposure to trace metal mixture (TMM): cadmium chloride (CdCl2), lead chloride (PbCl2), and mercury chloride (HgCl2). Five groups of weight matched Sprague Dawley rats were treated for 90 days. Metal mixture and deionized water were used to treat the 2 groups of rats whereas the other 3 groups were treated with various doses of the ALECA through oral gavage alongside the metal mixture. Hepatic function parameters, oxidative biomarkers, inflammatory cytokines, Morphological changes and trace metals (concentrations were monitored in the liver). TMM treatment resulted in significant increase in ALT, AST, ALP, bilirubin, IL-6, MDA, but decreased albumin, total protein, IL-10, SOD, CAT and GSH levels. TMM also caused some morphological changes and increased the heavy metal (Pb, Cd and Hg) concentrations in the liver. The leaf extract gave a reasonable protective effect on the hepatotoxicity caused by trace metal mixture - through the mechanisms of metal chelation, anti-inflammatory, and antioxidant although this depends on the dosage to the rats. ALECA may be beneficial in the management of liver toxicity.
Weighted k-domination problem in fuzzy networks
Authors: Chen Xue-gang , Sohn Moo Young 
Published: May 2021

Abstract
In real-life scenarios, both the vertex weight and edge weight in a network are hard to define exactly. We can incorporate the fuzziness into a network to handle this type of uncertain situation. Here, we use triangular fuzzy number to describe the vertex weight and edge weight of a fuzzy network G. In this paper, we consider weighted k-domination problem in fuzzy networks. The weighted k-domination (WKD) problem is to find a k dominating set D which minimizes the cost $f(D):=\sum_{u\in D}w(u)+\sum_{v\in V\setminus D}\min\{\sum_{u\in S}w(uv)|S\subseteq N(v)\cap D, |S|=k\}$. First, we put forward an integer linear programming model with a polynomial number of constrains for the WKD problem. If G is a cycle, we design a dynamic algorithm to determine its exact weighted 2-domination number. If G is a tree, we give a label algorithm to determine its exact weighted 2-domination number. Combining a primal-dual method and a greedy method, we put forward an approximation algorithm for general fuzzy network on the WKD problem. Finally, we describe an application of the WKD problem to police camp problems.2010 Mathematics Subject Classiﬁcation. 05C69, 05C35, 03E72
Joint Emission Reduction Dynamic Decisions and Coordination in a Supply Chain Considering Altruistic Behavior and Reference Low-Carbon Effect
Authors: zhang ziyuan , Yu Liying 
Published: May 2021

Abstract
In the context of low-carbon economy, supply chain members’ joint emission reduction issue has become a research hotspot, while there are few researches which synthetically studies the effect of consumers’ reference low-carbon effect and supply chain members’ altruistic behavior on their decisions. To study the impact of supply chain members’ altruistic behavior and consumers’ reference low-carbon effect on their joint emission reduction decisions and profits, we build optimization models under four decision scenarios, in which we solve the manufacturer’s and the retailer’s optimal emission reduction strategies and other equilibrium solutions by differential game theory. We obtain some findings. First, consumers' reference low-carbon effect will harm the profits of the manufacturer and the retailer, discourage the manufacturer's enthusiasm to reduce emissions and retailer's enthusiasm for low-carbon publicity. Second, the altruistic behavior of the manufacturer and the retailer can not only weaken the negative impact of the reference low-carbon effect, but also promote both parties to actively reduce emissions, help achieve Pareto improvement of their own profits and utilities, and obtain additional social welfare. Third, the cost-sharing contract can encourage the manufacturer to increase emission reduction investment without affecting the retailer’s low-carbon publicity investment, and can achieve a Pareto improvement of both parties’ profits and utilities. In addition, the cost-sharing ratio is only proportional to the marginal profits and altruistic intensity of both parties, and is not affected by the reference low-carbon effect. Meanwhile, the cost-sharing ratio will decrease as the manufacturer’s marginal profit and altruistic intensity increase, and will increase as the retailer’s marginal profit and altruistic intensity increase. In particular, when the retailer is completely altruistic, the cost-sharing contract can achieve perfect coordination of the supply chain.
Implementation of Sustainable Bioeconomy in European Union Countries: The Decomposition Analysis Approach
Authors: Liobikiene Genovaite , Krikštolaitis Ričardas , Miceikienė Astrida 
Published: May 2021

Abstract
Sustainability is highlighted in renewed European Union (EU) bioeconomy strategy. Sustainable bioeconomy requires improvement in the productivity level of bioresources, which is included in almost all national bioeconomy strategies. Therefore, the aim of this paper is to reveal how productivity (or conversely, intensity) level contributes to the changes in biomass extraction in all EU countries. Applying the IPAT approach, the results showed that in separate EU countries and analyzed periods, the changes in biomass extraction were different. During the period of economic growth (2000-2007) and transition (2008-2012), biomass extraction decreased in more than half of all EU countries. The decline of value added in the agriculture sector and/or reduction in biomass intensity level were the main determinants of these changes. Meanwhile, during the bioeconomy strategy period (2013-2018), the reduction of biomass extractions was observed in only 6 EU countries. During this period it was only in Greece, Italy and Malta that the productivity level of biomass offset the driving forces: economic and population growth. Meanwhile, in Estonia, Germany and Poland, despite the reduction of value added in the agriculture sector, the growth of the intensity level of biomass determined the increase in extraction of biomass. Therefore, this study showed that achievement of sustainable bioeconomy principles in the majority of EU countries remains a great challenge, and countries should make all efforts to enhance the productivity level of biomass.