bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating the Effectiveness of Self-management Program based on 5A Model on Fatigue and Dyspnea in Patients with Heart Failure
Authors: Hajmohamadi Maryam , Sabzvari Sakineh , Jahani Yones , Goghary Zahra Imani- 
Published: September 2021

Abstract
Background: Some symptoms such as fatigue and dyspnea decrease the quality of life in patients with heart failure. The effectiveness of self-management programs on management chronic conditions was discussed. So, this study aimed to investigate the effectiveness of self-management program based on 5A model on fatigue and dyspnea in patients with heart failure.Materials and Methods: In this clinical trial study, 60 patients with heart failure were included. The intervention group underwent self-management program based on 5A model and the control group received routine care. All the enrolled patients were evaluated once at baseline and once after 3 months using fatigue severity and Borg dyspnea scales. The obtained data were analyzed using SPSS software version 16 by descriptive statistics and independent t-test, covariance test, and paired sample t- test. The significance level was set at 0.05.Results: There was no significant difference in the mean scores of fatigue and dyspnea at the beginning of the study between control and intervention groups (p>0.05), but 3 months after intervention a significant difference was found in mean scores of fatigue and dyspnea between two groups, (p<0.05). The difference between pre- and post-intervention scores in terms of the dyspnea and fatigue variables was significant based on the result of paired sample t- test (p<0.05).Conclusion: according to the results of this study, self-management program based on 5A Model can be used to reduce the severity of fatigue and dyspnea as well as improve the quality of life in patients with heart failure. Trial registration number: IRCT20141109019862N8 Trial registration date: 11/Aug/2019First participant enrollment: 30 /Sep/ 2019:
Uncovering Patterns of Public Perceptions Towards Biodiversity Crime Using Conservation Culturomics
Authors: Troumbis Andreas Y , Iosifidis Spyridon , Kalloniatis Christos 
Published: September 2021

Abstract
This paper examines aspects of the relationship between (1) the recently typified form of biodiversity crime, (2) information made available to the public through the Internet, and (3) cultural dynamics quantified through info-surveillance methods through Culturomics techniques. Two conceptual models are proposed: (1) the building-up process of a biodiversity crime culturome, in a language, and (2) a multi-stage biodiversity conservation chain and biodiversity-crime activities relating to each stage. Crowd search volumes on the Internet on biodiversity crime-related terms and topics are used as proxies for the public’s interest measurement. The main findings are: (1) the concept of biodiversity-crime per se is still immature and presents low penetration to the general public; (2) biodiversity-crime issues, which are not recognized as such, are amalgamated in conservation-oriented websites and pages; and (3) differences in perceptions and priorities between general vs. ‘niche’ public with particular interest(s) in environmental issues- are discernable.
Municipal Solid Waste Status in Iran; From Generation to Disposal
Authors: Golhosseini Zeynab , Ghazizade Mahdi Jalili 
Published: September 2021

Abstract
The critical step of policymaking and planning for the local governments to select appropriate waste management methods and accomplish the required programs and projects, is comprehensive information on solid waste generation. Since in the last decade there has not been a comprehensive and integrated study for identifying waste management practices at a nationwide level, so this paper presents an overview of the current solid waste generation, characteristics and disposal method covering all 31 provinces of Iran based on available information and integrated waste management plans. The results show the average of solid waste generation (municipal and rural) throughout the country is 630 grams per capita per day. Although this is 10 percent higher than its level in the past decade, it is still lower than the global average per capita (740 grams per day). Solid waste composition in Iran comprises primarily organic, with 70 percent, followed by paper and plastic that account 7 percent, make up the waste stream. In addition, on average over 90 percent of generated solid waste in Iran is still openly dumped that increase healthy and environmental risk. So it is suggested that due to obtain accurate and reliable data, a comprehensive waste monitoring plan at the national level should be defined and waste composition and generation rate determined and updated through a standard method within certain interval time. According to the data of this research, planning and financial support for source separation can decrease environmental, economic and social problems in current solid waste management systems.
The Effect of Caregiver Key Opinion Leaders on Increasing Caregiver Demand for Evidence-Based Practices to Treat Youth Anxiety: Protocol for a Randomized Control Trial
Authors: Crane Margaret , Atkins Marc S. , Becker Sara J. , Purtle Jonathan , Olino Thomas M. , Kendall Philip C. 
Published: September 2021

Abstract
Background:Research has identified cognitive behavioral therapy with exposures (CBT) as an effective treatment for youth anxiety. Despite implementation efforts, few anxious youth receive CBT. Direct-to-consumer marketing offers a different approach to address the unmet need for youth receiving effective treatments. Involving a local caregiver key opinion leader in direct-to-consumer initiatives may be an effective strategy to increase caregiver demand for CBT. Research indicates that key opinion leaders improve health promotion campaigns, but key opinion leaders have not been studied in the context of increasing caregiver demand for evidence-based treatments.Method:Project CHAT (Caregivers Hearing about Anxiety Treatments) will test the role of key opinion leader participation in conducting outreach presentations to increase caregiver desire to seek CBT for their youth’s anxiety. Caregiver attendees (N = 180) will be cluster-randomized by school to receive one of two different approaches for presentations on CBT for youth anxiety. Both approaches will involve community outreach presentations providing information on recognizing youth anxiety, strategies caregivers can use to decrease youth anxiety, and how to seek CBT for youth anxiety. The researcher-only condition will be co-facilitated by two researchers. In the key opinion leader condition, a caregiver key opinion leader from each local community will be involved in tailoring the content of the presentation to the context of the community, co-facilitating the presentation with a researcher, and endorsing strategies in the presentation that they have found to be helpful. In line with the theory of planned behavior, caregiver attendees will complete measures assessing their knowledge of, attitudes towards, perceived subjective norms about, and intention to seek CBT pre- and post-presentation; they will indicate whether they sought CBT for their youth at three-month follow-up. Results will be analyzed using a mixed method approach to assess the effectiveness of a key opinion leader to increase caregiver demand for CBT.Discussion:This study will be the first to examine the potential of key opinion leaders to increase caregiver demand for CBT. If proven effective, the use of key opinion leaders could serve as a scalable dissemination strategy to increase the reach of evidence-based treatments.Trial registration:This trial was registered on clinicaltrials.gov (NCT04929262) on June 18, 2021. At the time of trial registration, pre/post presentation data had been collected from 17 participants; thus, it was retrospectively registered.
Modeling and Control for an Underwater Vehicle using Dual Quaternions.
Authors: Zamora Angel , Garcia Miguel , Manzanilla Adrian , Muñoz Filiberto , Salazar Sergio , Lozano Rogelio 
Published: September 2021

Abstract
In this work, the analysis of the dynamic general model of an unmanned underwater vehicle (UUV) based on dual quaternions is presented, then the general dynamic model is reduced to a specific vehicle of 4 DoF, this model eliminates the singularities that exist with the representation of the Euler angle and that the model is more compact than others proposed in the literature [1],[2]. To demonstrate the applicability of the model, three controller strategies are proposed for tracking a trajectory, the first controller is a PD + G, under unknown disturbances it produces a considerable tracking error, the second is an adaptive controller that estimates unknown hydrodynamic parameters, and the third is a robust controller for unknown disturbances and parameter uncertainties. The closed-loop system stability analysis for each controller is based on Lyapunov’s theory, a set of numerical simulations is performedto show the behavior of the vehicle with the proposed controllers. The efficiency of the controllers is shown in Table 2 where it is deduced that the adaptive controller has a better performance. The graphics show that the robust controller has little error tracking and the computational cost is lower.
Spatial Analysis of Seasonal Precipitation Using Various Interpolation Methods in the Euphrates Basin, Turkey
Authors: Katipoğlu Okan Mert 
Published: September 2021

Abstract
It is vital to accurately map the spatial distribution of precipitation, which is widely used in many fields such as hydrology, climatology, meteorology, ecology, and agriculture. In this study, it was aimed to reveal the spatial distribution of seasonal long-term average precipitation in the Euphrates Basin by using various interpolation methods. For this reason, Simple Kriging (SK), Ordinary Kriging (OK), Universal Kriging (UK), Ordinary CoKriging (OCK), Empirical Bayesian Kriging (EBK), Radial Basis Functions (Completely Regularized Spline (CRS), Thin Plate Spline (TPS), Multiquadratic, Inverse Multiquadratic (IM), Spline with Tensor (ST)), Local Polynomial Interpolation (LPI), Global Polynomial Interpolation (GPI), Inverse Distance Weighting (IDW) methods have been applied in the Geographical Information Systems (GIS) environment. Long-term seasonal precipitation averages between 1966 and 2017 are presented as input for the prediction of precipitation maps. The accuracy of the precipitation prediction maps created was based on root mean square error (RMSE) values obtained from the cross-validation tests. The method of precipitation by interpolation yielding the lowest RMSE was selected as the most appropriate method. As a result of the study, OCK in spring and winter precipitation, LPI in summer precipitation, and OK in autumn precipitation were determined as the most appropriate estimation method.
ID2 Inhibits Lung Adenocarcinoma Cell Malignant Behaviors Through Inhibiting the Activation of the PI3K/AKT/mTOR Signaling Pathway
Authors: Peng Wenzhong , Chen Jia , He Ruoxi , Tang Yongjun , Jiang Juan , Li Ying 
Published: September 2021

Abstract
Background: Lung cancer is the most common cancer and one of the main causes of cancer-related deaths, and it manifests as metastatic disease in most cases. Considering frequent gene mutation and/or signaling deregulation in lung adenocarcinoma, identifying novel factors or agents targeting these signaling pathways might be promising strategies for lung adenocarcinoma therapy. Methods: GEO datasets were analyzed to identify differentially expressed genes (DEGs) in lung adenocarcinoma. The specific effects of candidate gene overexpression or knockdown on lung adenocarcinoma cell phenotypes were examined. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) are used to connect the genomic and functional information of DEGs. The dynamic effects of candidate gene and signaling pathway agonist on lung adenocarcinoma malignant behaviors were investigated. Finally, clinical lung adenocarcinoma and adjacent non-cancerous tissues were collected and the levels of candidate gene were examined in tissue samples.Results: Inhibitor of DNA binding 2 (ID2) was identified as an aberrantly downregulated gene in lung adenocarcinoma. ID2 overexpression suppressed lung adenocarcinoma cell viability, colony formation capacity, and migration. ID2 overexpression also reduced the protein levels of N-cadherin, MMP2, MMP9, and the phosphorylation of AKT and mTOR. The PI3K/AKT/mTOR signaling agonist exerted opposite effects on lung adenocarcinoma cells to those of ID2 overexpression, and partially reversed the effects of ID2 overexpression. In tissue samples, ID2 protein levels and mRNA expression were also downregulated compared with those in adjacent non-cancerous tissues. Conclusion: ID2 exerts its tumor-suppressive effects on lung adenocarcinoma cell malignant behaviors through inhibiting the activation of the PI3K/AKT/mTOR signaling pathway. Restoring ID2 expression in lung adenocarcinoma cells might improve the curative effect of lung adenocarcinoma therapies.
Comparison of Imputation Methods on Retrospective Breast Cancer Data in Tanzania: A Case Study of Muhimbili and Ocean Road Hospitals
Authors: Abassi Rahibu A. , Msengwa Amina S. , Akarro Rocky R. J. 
Published: September 2021

Abstract
Background
Clinical data are at risk of having missing or incomplete values for several reasons including patients’ failure to attend clinical measurements, wrong interpretations of measurements, and measurement recorder’s defects. Missing data can significantly affect the analysis and results might be doubtful due to bias caused by omission of missed observation during statistical analysis especially if a dataset is considerably small. The objective of this study is to compare several imputation methods in terms of efficiency in filling-in the missing data so as to increase the prediction and classification accuracy in breast cancer dataset.
Methods
Five imputation methods namely series mean, k-nearest neighbour, hot deck, predictive mean matching, and multiple imputations were applied to replace the missing values to the real breast cancer dataset. The efficiency of imputation methods was compared by using the Root Mean Square Errors and Mean Absolute Errors to obtain a suitable complete dataset. Binary logistic regression and linear discrimination classifiers were applied to the imputed dataset to compare their efficacy on classification and discrimination.
Results
The evaluation of imputation methods revealed that the predictive mean matching method was better off compared to other imputation methods. In addition, the binary logistic regression and linear discriminant analyses yield almost similar values on overall classification rates, sensitivity and specificity.
Conclusion
The predictive mean matching imputation showed higher accuracy in estimating and replacing missing/incomplete data values in a real breast cancer dataset under the study. It is a more effective and good method to handle missing data in this scenario. We recommend to replace missing data by using predictive mean matching since it is a plausible approach toward multiple imputations for numerical variables, as it improves estimation and prediction accuracy over the use complete-case analysis especially when percentage of missing data is not very small.
A Cross-sectional Examination of the Association Between Parental Distress and the Well-being of Children With Neurodevelopmental Disorders During the COVID-19 Pandemic
Authors: Diaz Antonio Mendoza , Tully Lucy , Masi Anne , Lin Ping-I , Efron Daryl , Woolfenden Sue , Eapen Valsamma 
Published: September 2021

Abstract
Background: The COVID-19 pandemic and its concomitant impacts have been unevenly shared across society, this is particularly true for children with neurodevelopmental disorders (NDD), who often rely on a network of services and social connections for their well-being. Children with NDD during the COVID-19 pandemic have had worrying trends regarding their worsening well-being and poorer parental mental health. This study’s aim was to test whether these two factors were associated in a survey of Australian parents.Methods: This cross-sectional study of Australian parents of children with neurodevelopmental disorders (n = 304, ages 2 – 17, 63.8% male) sought to test the association between parental distress (as captured by the Kessler-6 distress scale) and two child outcomes, worsening NDD symptoms and worsening health behaviours (i.e., sleep, diet, exercise, and media use).Results: Parent distress was significantly associated with a worsening of symptoms of NDD and associated mental health comorbidities, and poorer child well-being. These results were significant even when including other variables of interest such as the families’ sociodemographic characteristics, indicating parental distress is a key factor for the well-being of children and parents.Conclusions: Overall, this study found relatively high levels of parental psychological distress, anxiety and poor well-being and demonstrated that parental psychological distress was significantly associated with parent-reported worsening of child diagnostic symptoms as well as poorer child well-being in relation to sleep, diet, exercise, and use of electronics. Together these findings suggest that deteriorating parental mental health (distress) due to COVID-19 is associated with adverse child mental health symptoms and well-being, as indexed by the behaviours described above.
Physico-chemical Characteristics of Pulverized Coals and Their Interrelations- A Spontaneous Combustion and Explosion Perspective
Authors: Mishra Devi Prasad 
Published: September 2021

Abstract
Characteristics of pulverized coals have significant influence on the spontaneous combustion and explosion processes. This paper presents an experimental and theoretical framework on physico-chemical characteristics of coal and analyzes their interrelations from spontaneous combustion and explosion perspectives. The chemical properties, morphology, bulk density, particle size and specific surface area of pulverized coals from nine different coal subsidiaries of India are vividly investigated in five distinct sizes. Moreover, the effects of particle size on bulk density, specific surface area and N2 adsorption capacity of pulverized coals are critically analyzed. The micrographs revealed that the coal particles are mostly irregular in shape with angular outlines and sharp edges. With decrease in particle size, the bulk density of pulverized coals decreased and the specific surface area and N2 adsorption capacity increased. The relationships of bulk density and specific surface area of pulverized coals with particle size are established. Moreover, the specific surface areas determined by both the particle sizing and BET methods are compared and correlation factors between them are determined. This study led to the generation of insightful coal characteristic data which can be used as reference material for furthering researches on spontaneous combustion and explosion involving pulverized coals.
The Impact of Financial Support on Innovation Efficiency of Government Subsidies From the Perspective of DEA-Tobit——An Empirical Study Based on Chinese New Energy Vehicle Enterprises
Authors: Zhang Sha , Chen Fang 
Published: September 2021

Abstract
The new energy vehicle enterprises is a strategic emerging industry in China, so more and more government subsidies to promote innovative development are being accepted by new energy vehicle enterprises. What is the innovation efficiency of new energy vehicle enterprises receiving government subsidies? With the acceleration of the process of global economic financialization, whether financial support can promote the innovation efficiency of government subsidies and how enterprises should allocate financial assets have become issues that need to be deeply considered. Based on the annual report data of China's domestic listed new energy vehicle enterprises from 2015 to 2020, the relationship between government subsidies and enterprise innovation efficiency is empirically tested, and the impact of financial support on enterprise R&D innovation efficiency is investigated. The empirical results show that government subsidies are wasteful and fail to effectively promote R&D innovation, and the innovation efficiency of government subsidies is positively influenced by firm nature and firm age, while the total asset turnover ratio, operating cycle and firm size have a negative impact on innovation efficiency. Further research found that there is an inverted U-shaped relationship between financial support and the innovation efficiency of government subsidies. A certain degree of financial support has a positive impact on the innovation efficiency of government subsidies, but excessive financial support has a negative impact on the innovation efficiency of government subsidies. The conclusion provides empirical evidence for the Chinese government to improve the subsidy policy and standardize the development of new energy vehicle enterprises, and has a certain reference value for guiding new energy vehicle enterprises to reasonably allocate financial support.
Exogenous Production of Cold-Active Cellulase From Psychrophilic Actinobacteria With Increased Cellulose Hydrolysis Efficiency
Authors: Palaniappan Sivasankar , Subramaniam Poongodi , Kannan Sivakumar , Al-Qahtani Wahidah H , Selvaraj Arokiyaraj , Rajabathar Jothiramalingam 
Published: September 2021

Abstract
Actinobacteria form the largest phylum consisting of diverse, ecologically unique and biologically active members. The actinobacteria are omnipresent and occur in various habitats such as cold environment, aquatic, desert and terrestrial ecosystems. Though the studies are available on actinobacteria at various habitats very few reports are available on cold tolerant/loving actinobacteria in the Southern Ocean part of the Antarctic Ocean. In this context, the present work was designed to isolate and characterize the actinobacteria in the Polar Front region of the Southern Ocean waters and species of Nocardiopsis and Streptomyces were identified. Among those, the psychrophilic actinobacterium, Nocardiopsis dassonvillei PSY13 was found to have good cellulolytic activity and it was further studied for the production and characterization of cold-active cellulase enzyme. The latter was found to have a specific activity of 6.36 U/mg and a molar mass of 48 kDa with a 22.9-fold purification and 5% recovery at an optimum pH of 7.5 and a temperature of 10 ºC. Given the importance of psychrophilic actinobacteria N. dassonvillei PSY13 can be further exploited for its benefits, meaning that the Southern Ocean harbours biotechnologically important microorganisms that can be further explored for versatile biotechnological and industrial applications.