bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kinetics of bitumen extraction from oil sands using organic solvents
Authors: Yuan Wei , Zhu Peiliang , Kang Zhuang , Sun Yinlu 
Published: November 2022

AbstractThe kinetic study of bitumen extraction from oil sands is significant for efficiency improvement and reactor design in industrial applications. Here, an improved pseudo‐first‐order kinetic model was established with the assumption of a constant Sherwood number, which took into account the mass transfer area. Five organic solvents were used for the extraction kinetics of the prepared bitumen microbeads. The improved pseudo‐first‐order kinetic model exhibited excellent fitting effects. Petroleum ether/dichloromethane was proved to be the best solvent. The results also showed an exponential decrease in the diameter of the bitumen microbeads and a linear increase in mass transfer coefficients with time for all the solvents. The kinetics of bitumen extraction from oil sands using different solvents were predicted according to the corresponding average mass transfer coefficients. The experimental results confirmed that the improved kinetic model was capable of describing the mass transfer process of bitumen extraction from oil sands.
Differences in the prevalence of cardiovascular and metabolic diseases coinciding with clinical subtypes of obstructive sleep apnea
Authors: Gao Yang , Guo Yaxin , Dong Jiajia , Liu Yifan , Hu Wen , Lu Mi , Shen Yueran , Liu Yi , Wei Yongxiang , Wang Zhenlin , Zhan Xiaojun 
Published: November 2022

AbstractBackgroundIt is unclear about the cardiovascular and metabolic diseases (CMD) among Chinese patients with different clinical subtypes of obstructive sleep apnea (OSA).HypothesisThe prevalence of CMD varies among OSA patients of different clinical subtypes.MethodsA total of 1483 Chinese patients with OSA were assessed to evaluate the existence of clinical subtypes of OSA using latent class analysis. We compared the differences in demographic characteristics and prevalence of CMD using ANOVA and χ2 tests. Associations between clinical subtypes and disease prevalence were assessed using adjusted logistic regression.ResultsWe identified prevalent CMD in Chinese patients with the four subtypes of OSA: excessively sleepy (ES), moderately sleepy with disturbed sleep (ModSwDS), moderately sleepy (ModS), and minimally symptomatic (MinS). The ES subtype had a higher body mass index, average Epworth Sleepiness Scale score, Apnea‐hypopnea index, and oxyhemoglobin saturation below 90% compared with the other subtypes (p < .05). The MinS subtype had the lowest mean ESS score (p < .05). We found a significant difference in the prevalence of CMD among the four subtypes, with the highest proportion of cases of CMD in the ES subtype. In adjusted models, significant associations with CMD were also found. ES, ModSwDS, ModS, and MinS subtypes are very high‐risk, high‐risk, medium‐risk, and low‐risk in prevalent CMD.ConclusionsThis study identified four clinical subtypes of OSA in Chinese patients. Each clinical subtype corresponds with a different level of prevalence of CMD; this finding is helpful for the more precise treatment of patients with different clinical manifestations.
Initial experience of a novel method for electrical isolation of the superior vena cava using cryoballoon in patients with atrial fibrillation
Authors: Lin Changjian , Bao Yangyang , Xie Yun , Wei Yue , Luo Qingzhi , Ling Tianyou , Zhang Ning , Jin Qi , Pan Wenqi , Xie Yucai , Wu Liqun 
Published: November 2022

AbstractBackgroundDamage to the sinus node (SN) has been described as a potential complication of superior vena cava (SVC) isolation. There have been reports of permanent SN injury requiring pacemaker implantation during isolation of the SVC.HypothesisIt is safe and effective to isolate SVC with the second‐generation 28‐mm cryoballoon by using a novel method.MethodsForty‐three patients (including six redo cases) with SVC‐related atrial fibrillation (AF) from a consecutive series of 650 patients who underwent cryoballoon ablation were included. After pulmonary vein isolation was achieved, if the SVC trigger was identified, the SVC was electrically isolated using the cryoballoon. First, the cryoballoon was inflated in the right atrium (RA) and advanced towards the SVC‐RA junction. After total occlusion was confirmed by dye injection with total retention of contrast in the SVC, the SVC‐RA junction was determined. Next, the cryoballoon was deflated, advanced into SVC, then reinflated, and pulled back gently. The equatorial band of the cryoballoon was then set slightly (4.32 ± 0.71 mm) above the SVC‐RA junction for isolation of the SVC.ResultsReal‐time SVC potential was observed in all patients during ablation. The mean time to isolation was 24.5 ± 10.7 s. The SVC was successfully isolated in all patients. The mean number of freeze cycles was 2.5 ± 1.4 per patient, and the mean ablation time was 99.8 ± 22.7 s. A transient phrenic nerve (PN) injury occurred in one patient (2.33%). There were no SN injuries. Freedom from AF rates at 6 and 12 months was 97.7% and 93.0%, respectively.ConclusionsThis novel method for SVC isolation using the cryoballoon is safe and feasible when the SVC driver during AF is determined and could avoid SN injury. PN function should still be carefully monitored during an SVC isolation procedure.
The predictive value of changes in left atrial volume index for rehospitalization in heart failure with preserved ejection fraction
Authors: Hao Zhujing , Xu Guiwen , Yuan Mengyang , Sun Yuxi , Tan Ruopeng , Liu Yang , Xia Yun‐Long 
Published: November 2022

AbstractAimsLeft atrial volume index (LAVI) is an adequate analysis to predicate the left ventricle (LV) filling pressures, providing a powerful predictive marker of LV diastolic dysfunction. LAVI is a dynamic morphophysiological marker, and whether LAVI changes can predicate clinical outcomes in HF with preserved ejection fraction (HFpEF) is unknown.MethodsHFpEF patients were retrospectively studied from the First Affiliated Hospital of Dalian Medical University. Patients were classified into deteriorated, stable and improved groups according to the change in LAVI. Rehospitalization was defined as the main endpoint, the composite outcome of rehospitalization or all‐cause death was defined as the secondary endpoint.ResultsA total of 409 patients were included. In this cohort, the percentage of deteriorated, stable, and improved LAVI were 99 (24.2%), 235 (57.4%), and 75 (18.4%), respectively. During the 22 months follow‐up period, 168 patients (41.1%) were rehospitalized, 31 patients (7.5%) died and 182 patients (44.5%) experienced a composite outcome. Multivariate Cox regression showed that compared to improved LAVI, those with deteriorated and stable LAVI experienced higher risk of rehospitalization. Logistic regression showed atrial fibrillation (AF) and higher creatinine were independent predictors of deteriorated LAVI, whereas the use of loop diuretics, calcium channel blockers (CCB), and high level of high‐density lipoprotein cholesterol (HDL‐C) were significantly associated with improved LAVI.ConclusionsChange in LAVI provides a powerful and dynamic morphophysiological marker of LV filling status and can be used to evaluate the rehospitalization in HFpEF patients.
Examining the effect of climate vulnerabilities on the discounting behaviour of farmers
Authors: Begho Toritseju , Anik Asif Reza 
Published: November 2022

AbstractIn agriculture, the possibility of climatic hazards negatively impacting small farmers’ livelihood is high. Thus, there are reasons to contend that climate vulnerabilities could determine economic behaviour. This paper investigates whether discounting behaviour varies with exposure to natural hazards. We analyse data from a survey involving an experiment in which farmers made choices between a smaller immediate payment compared with larger future amounts. The results show that 58% heavily discounted the future in favour of the immediate payment. Among the climatic shocks examined, flood, drought and salinity were the main hazards farmers faced on their plots. However, these natural hazards varied across locations. Our examination of the effect of the experience of natural hazards and the severity of climate vulnerability on farmers’ discounting behaviour suggests that experience and vulnerability had different impacts on discounting behaviour. Recent exposure to drought and flood reduces patience. However, the opposite is the case for a recent experience of salinity. This paper shows that under circumstances of climate vulnerabilities, farmers may be willing to make decisions that result in immediate albeit lower rewards in place of potential higher rewards in the future. The implication is that experience and vulnerability to natural hazards might affect farmers’ decision‐making to the extent that it prevents them from a speedy economic recovery post‐disaster.
Hybrid optimization based deep neuro fuzzy network for skin cancer detection
Authors: Majji Ramachandro , P. G Om Prakash , S Vairamuthu , B Selva Rani 
Published: November 2022

SummaryMelanoma is the most prevalent type of skin cancer, affecting skin surface cells. The risk features of the disease are minimized by finding the disease at time or in the initial stage. Even through, various skin cancer detection methods are developed, detecting the disease using discriminative features still results a challenging task. An efficient detection strategy based on the proposed Lion Cat Swarm Optimization‐based Deep Neuro Fuzzy Network (LCSO‐based DNFN) is created to identify skin cancer in its early stages. The LCSO is the integration of the lion optimization algorithm (LOA) and cat swarm optimization (CSO) algorithm. To make treatment measure at right time increases the probability of survival and so detecting the disease using deep learning classifier is performed with hybrid optimization algorithm. The segmentation result is effective through the fusion model and it ensures to achieve accurate detection process. Rather than extracting the features, the proposed method generates optimal result through data augmentation. The performance of the proposed LCSO‐based DNFN is determined using skin disease dataset, and the introduced approach obtained outstanding performance with the measures of accuracy, sensitivity, and specificity with the values of 93.10%, 92.95%, and 92.87%, respectively.
Maladaptive therapist schemas in CBT practice, training and supervision: A scoping review
Authors: Roscoe Jason , Taylor Julie 
Published: November 2022

AbstractBackgroundMaladaptive therapist schemas are hypothesized to generate difficulties within cognitive behavioural therapy (CBT) practice, training and supervision. Without adequate identification and management, they negatively affect the cognitions and emotions of the therapist, leading them to behave in ways that risk ruptures or therapy and supervision being delivered in a suboptimal fashion. Consequently, there is a need to synthesize the research that has been undertaken to date on the content, prevalence, identification and management of maladaptive therapist schemas.MethodA scoping review was undertaken of studies that have been published since 2001 on the impact of maladaptive therapist schemas (also referred to interchangeably as beliefs or cognitions) in CBT practice, training and supervision. Thirteen studies were identified in a literature search from four electronic databases, a reference list search of identified articles and hand searches.ResultsThree overall themes were identified in the research: (1) prevalence of therapist schemas, (2) specific therapist beliefs and (3) therapist characteristics associated with the delivery of suboptimal CBT or supervision. While there is little empirical support for therapist schemas, therapist resistance and beliefs relating to the fear of using exposure therapy were identified. Therapist intolerance of uncertainty and self‐esteem were recurrent factors.ConclusionThere is no consensus on how to define, identify, formulate or respond to maladaptive therapist beliefs or schemas in clinical practice, training or supervision. Further research is needed to better understand their origins, maintaining factors and appropriate management of their impact.
A Model for Evaluating the Crystallinity Quality of Single Crystals Grown by the Floating Zone Technique
Authors: Xu Benyan , Li Zhenyou , Wang Kunpeng , Wang Xuejiao , Zhang Jianxiu , Liang Lanju , Li Longfei , Ren Yanbiao , Liu Yong , Liu Meng , Xue Dongfeng 
Published: November 2022

AbstractThe floating zone technique is a popular method for crystal growth of nonconventional superconductors and magnetic materials. However, the quality must be characterized with particular care with respect to their actual crystallinity since not everything grown by floating zone method is a single crystal. In this paper, the molten‐zone sensitive material LiCoPO4 has been grown by the floating zone method using Co(NO3)2∙6H2O and CoO precursors, respectively, abbreviated as LCPN and LCPO. The grown materials are characterized regarding their chemical composition, phase purity, crystal perfection, and orientation. In order to optimize crystal growth and quantitatively characterize its crystallinity quality, the development factor (V) has been proposed to determine the growth rate of the grains, while the orientation deviation factor (δ) for assessing the quality of the grown crystals. The development factors V for LCPN and LCPO are calculated to be 0.05 and 0.09, respectively, indicating that the grains of LCPO develop faster than those of LCPN. At the same time, the orientation deviation factor of LCPO exceeds that of LCPN (δ(LCPO) = 2.00, δ(LCPN) = 0.77) suggesting a higher quality for the latter. This model provides significant guidance for the evaluation of other materials grown by the floating zone method.
Sustainability reporting in view of the European sustainable finance taxonomy: Is the financial sector ready to disclose circular economy?
Authors: Moneva José M. , Scarpellini Sabina , Aranda‐Usón Alfonso , Alvarez Etxeberria Igor 
Published: November 2022

AbstractThe European sustainable finance taxonomy requires financial and nonfinancial companies to provide investors with information about the environmental performance of their assets and economic activities. For financial institutions, making socially and environmentally responsible investments visible through a common label that guarantees specific standards for the entire European Union is crucial. Against this background, this study analyzes the evolution of sustainability reporting practices and their assurance in a sample of European financial institutions. To this end, we used a double qualitative methodological approach, based on (a) an external analysis of nonfinancial information and its relationship with the main economic‐financial variables of the sample companies, and (b) a case study of a bank carried out through semi‐structured interviews. This study provides an external measurement analysis of nonfinancial information in entities from different countries, which can contribute to broadening the scope and level of sustainability and circular economy accountability.
Enhanced image compression method exploiting NTT for internet of thing
Authors: Zhou Runjian , Wen Jiangang , Zou Yuanping , Wang Anding , Hua Jingyu , Sheng Bin 
Published: November 2022

AbstractJoint photographic experts group (JPEG) is the common compression technology of image transmission with the Internet of Things (IoT), which probably causes low compression ratio (CR) and increases the requirement for transmission rate. Therefore, a lightweight image compression method combining JPEG and number theoretic transformation (NTT) is proposed to address the above problems. Simulation results show that the proposed method has higher CR than JPEG, embedded zerotree wavelet (EZW), and combining singular value decomposition with wavelet difference reduction (SVD‐WDR) compression algorithms, which reduces the requirement of IoT devices for transmission rate.
β3 adrenergic agonist treatment in chronic pulmonary hypertension associated with heart failure (SPHERE‐HF): a double blind, placebo‐controlled, randomized clinical trial
Authors: García‐Álvarez Ana , Blanco Isabel , García‐Lunar Inés , Jordà Paloma , Rodriguez‐Arias Juan J. , Fernández‐Friera Leticia , Zegri Isabel , Nuche Jorge , Gomez‐Bueno Manuel , Prat Susanna , Pujadas Sandra , Sole‐Gonzalez Eduard , Garcia‐Cossio Maria D. , Rivas Mercedes , Torrecilla Estefanía , Pereda Daniel , Sanchez Javier , García‐Pavía Pablo , Segovia‐Cubero Javier , Delgado Juan F , Mirabet Sonia , Fuster Valentín , Barberá Joan A. , Ibañez Borja ,   for the SPHERE‐HF Investigators
Published: November 2022

AimsPulmonary hypertension (PH) associated with left heart disease is an increasingly prevalent problem, orphan of targeted therapies, and related to a poor prognosis, particularly when pre‐ and post‐capillary PH combine. The current study aimed to determine whether treatment with the selective β3 adrenoreceptor agonist mirabegron improves outcomes in patients with combined pre‐ and post‐capillary PH (CpcPH).Methods and resultsThe β3 Adrenergic Agonist Treatment in Chronic Pulmonary Hypertension Secondary to Heart Failure (SPHERE‐HF) trial is a multicentre, randomized, parallel, placebo‐controlled clinical trial that enrolled stable patients with CpcPH associated with symptomatic heart failure. A total of 80 patients were assigned to receive mirabegron (50 mg daily, titrated till 200 mg daily, n = 39) or placebo (n = 41) for 16 weeks. Of them, 66 patients successfully completed the study protocol and were valid for the main analysis. The primary endpoint was the change in pulmonary vascular resistance (PVR) on right heart catheterization. Secondary outcomes included the change in right ventricular (RV) ejection fraction by cardiac magnetic resonance or computed tomography, other haemodynamic variables, functional class, and quality of life. The trial was negative for the primary outcome (placebo‐corrected mean difference of 0.62 Wood units, 95% confidence interval [CI] −0.38, 1.61, p = 0.218). Patients receiving mirabegron presented a significant improvement in RV ejection fraction as compared to placebo (placebo‐corrected mean difference of 3.0%, 95% CI 0.4, 5.7%, p = 0.026), without significant differences in other pre‐specified secondary outcomes.ConclusionsSPHERE‐HF is the first clinical trial to assess the potential benefit of β3 adrenergic agonists in PH. The trial was negative since mirabegron did not reduce PVR, the primary endpoint, in patients with CpcPH. On pre‐specified secondary outcomes, a significant improvement in RV ejection fraction assessed by advanced cardiac imaging was found, without differences in functional class or quality of life.
Hybrid photovoltaic‐liquid air energy storage system for deep decarbonization
Authors: Chen Yu , Feng Juan , Liu Rui , Chen Jingyu , Jiang Zhaomin , Yu Chengbiao , Chen Xiaoyuan , Shen Boyang , Fu Lin 
Published: November 2022

AbstractNowadays most photovoltaic (PV) plants usually use battery energy storage technology to smooth fluctuant power, but batteries have the drawbacks of a short lifetime and environmental pollution. The existing renewable power networks have serious problems with decarbonizing electricity on the end‐user side. This paper investigates a new hybrid photovoltaic‐liquid air energy storage (PV‐LAES) system to provide solutions for the low‐carbon transition for future power and energy networks. In this article, a local PV power plant cooperates with its maximum power point tracking (MPPT)‐based boost converter, to generate low‐carbon electricity with some uncertain fluctuations. Then a zero‐emission‐air‐based LAES unit is used to absorb the surplus power from the PV plant, and also compensate power for the local load with inadequate power level. This makes the new system save a large proportion of power from main grids, which can also indirectly reduce greenhouse gas emissions. For the MW‐class PV‐LAES case, results show that the surplus renewable electricity (6.73 MWh) generates 27.12 tons of liquid air for energy backups during the day time, and then the LAES unit has a round‐trip efficiency of 47.4% that can discharge a flexible power compensation to the load in the night. Accordingly, the grid power demand reduces significantly from 12.78 to 3.33 MWh in a day. In this way, the annual power savings is estimated to be 3449.25 MWh, and the corresponding carbon emission can be reduced by 2607.63 tons. Regarding the economic performance, the PV‐LAES system presents a dynamic payback period of 9.33 years and an accumulated life‐cycle net profit of $2,260,011. Overall, the proposed PV‐LAES scheme is economically feasible from a life‐cycle perspective, and can potentially realize flexible energy interaction with local renewables to achieve an integrated low‐carbon power generation and storage system.
Deep hybrid models for daily natural gas consumption forecasting and complexity measuring
Authors: Bai Shengxi , Huang Xiaomei , Luo Min , Su Junfu 
Published: November 2022

AbstractAccurately forecasting daily natural gas consumption (NGC) is challenging due to its complex time‐varying high‐dimensional features. Therefore, this paper proposes a novel hybrid model for daily NGC forecasting consisting of two stages. In Phase I, the parallel local outlier factor‐isolation forest‐based data preprocessing algorithm is applied to denoise input data and preserve valuable features. In Phase II, the convolutional neural network (CNN)–stacked long short‐term memory (SLSTM) can extract and model spatio‐temporal features and is a hybrid deep learning forecaster. The influencing mechanism of different factors on the daily NGC prediction accuracy has not been mathematically and experimentally revealed. Thus, a hybrid complexity measure model () is developed by combining the variation coefficient analysis, local fluctuation coefficient analysis, and kurtosis analysis. The historical data sets of three representative cities were collected in the case studies, and six advanced models were selected for comparison. The results reveal that high‐quality input data preprocessed in Phase I enables better prediction performance for all models. The CNN‐SLSTM outperforms other algorithms with an average prediction improvement of about 26%–49%. Prediction models perform better in low NGC periods and cities with predominantly industrial natural gas users due to their lower data complexity.