bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blending Participatory Action Synthesis and Meta-ethnography: An Innovative Approach to Evaluating Complex Community Health Transformation
Authors: Reed Kristin , Carr Tara , Rabbani Rumana S. , Chandler Caroline E. , Scaccia Jonathan , Cook Brittany S. , Howard Paul , Ramaswamy Rohit 
Published: November 2020

Abstract
Background: Community health improvement processes are diverse and complex, and evaluation methods to gain generalizable knowledge across community are limited by available data, and the need for deep contextual knowledge. Methods: This article describes an innovative participatory approach to evaluation of a community transformation initiative involving up to eighteen communication nationwide. The approach blends two qualitative research synthesis methods: participatory action synthesis and meta-ethnography and applies them to the pragmatic evaluation of a program in real-life settings. Results: In this article, we present the justification for and details about the evaluation process. Four cycles of synthesis and engagement resulted in development of concepts to describe community actions for transformation.Conclusion: The approach presented here will be useful to both researchers and practitioners interested in evaluating community-based health and well-being initiatives and other complex interventions conducted in complex settings.
High Expression of PABPC1 Predicts Worse Survival of Gastric Cancer Patients
Authors: An Tailai , Deng Lingna , Yang Zheng , Chai Cuicui , Wang Yan , Ouyang Jun , Lu Xiaofang , Zhang Changhua 
Published: November 2020

Abstract
Background: Gastric cancer (GC) is one of the most common cancers with one of the highest mortality rates. Unfortunately, underlying molecular mechanisms contributing to GC have not been fully illuminated. PABPC1 is involved in a series of processes, such as mRNA translation, and mRNA deadenylation and decay. We performed this study to clarify the role of PABPC1 in GC. Methods: To evaluate PABPC1 expressions in GC and normal tissues, we performed bioinformatics analysis of data from TCGA. PABPC1 expressions were evaluated by immunohistochemical (IHC) staining of 170 GC specimens. Associations between PABPC1 expression and clinicopathological variables were analyzed. Independent predictive factors for survival of GC patients were determined by Cox regression analysis. Results: It was revealed by bioinformatics analysis that compared with normal gastric tissues, PABPC1 expressions in GC tissues were significantly higher (P=0.002, paired) (P=3.605e^-9, unpaired). It was revealed that PABPC1 expression was significantly associated with tumor size (P=0.008), Borrmann classification (P=0.003), vessel invasion (P=0.017), depth of invasion (P=0.032), lymph node metastasis (P=0.001), and TNM stage (P=0.019). It was demonstrated through Cox regression analysis that PABPC1 expression was a predictive factor for both overall survival (OS) (P<0.001) and disease-free survival (DFS) (P<0.001) of GC patients. Conclusions: Compared with that of normal gastric tissue, expression level of PABPC1 in GC tissue was significantly higher and PABPC1,s high expression was significantly associated with poorer survival, suggesting its potential as a therapeutic biomarker for GC.
Rainfall–streamflow relationships for three chalk escarpment springs (Oxfordshire, United Kingdom): effective rainfall and groundwater recharge area computational issues
Authors: Littlewood Ian G. 
Published: November 2020

AbstractFlow responses to rainfall are investigated for three small chalk springs located within about 30 km of each other. A high degree of synchronicity is shown for the spring hydrographs, which exhibit a lag of about 50 days relative to a much larger local reference catchment. Rainfall–streamflow models with six or fewer parameters, calibrated using free-to-download software, account for about 75% of the variance in daily streamflow for the reference catchment, and between about 76 and 85% for the chalk springs. Several modelling issues are discussed related to computation of the daily effective rainfall that forms the input to a Unit Hydrograph part of the model. Descriptions are given of how and why, when the recharge area used for a spring is far too small, the modelling software generates physically unrealistic effective rainfall depths much greater than the rainfall, without affecting model-fit to streamflow or the calibrated values of model parameters (except one). Reasons are suggested why it can be pragmatically acceptable for computed effective rainfall to occasionally exceed the corresponding recorded rainfall by small amounts. Wider implications of the modelling results are outlined and some suggestions for further work are made.
Study of regional heterogeneity of cloud properties during different rainfall scenarios over monsoon-dominated region
Authors: Shah Ruchita , Srivastava Rohit , Patel Jigisha 
Published: November 2020

AbstractVariability in precipitation pattern is increasing even at regional scale due to advancement in global warming, which could be of higher importance in study for monsoon-dominated region such as India. Precipitation varies with region, thus the present study focuses on two types of heterogeneous regions: a region closer to the coast and an inland region. Long-term analysis over inland region shows that the high cloud fraction and low penetration of outgoing radiation at the top of the atmosphere may be due to the presence of thicker clouds during southwest monsoon. Further study of cloud parameters shows domination of stratiform clouds over nearby coastal region with high range specific humidity (6.67 × 10−6–1.81 × 10−2 kg/kg) and higher cloud effective radius (13.35–15.75 μm), probably due to fewer hygroscopic nuclei. Heterogeneity in rainfall may also depend on types of monsoon (viz., normal, excess and deficit) by altering cloud formation processes. During periods of low rainfall over the coast, clouds are observed at low altitude with high cloud top temperature (−0.52 ± 3.08 °C) but have low specific humidity and lower cloud effective radius, which depict mixed characteristics of stratiform and convective clouds. Thus, it has been observed that cloud characteristics depend largely on the region than on the rainfall scenario. Such studies can be useful to understand uneven rainfall patterns.
Solar-assisted membrane technology for water purification: a review
Authors: Zewdie Tsegahun Mekonnen , Habtu Nigus Gabbiye , Dutta Abhishek , Van der Bruggen Bart 
Published: November 2020

Abstract
A shortage of safe drinking water is one of the leading problems in the world. Even in developed countries where water treatment systems are present, safe drinking water may not be always available due to the limitations of advanced water treatment techniques and high energy costs. On the other hand, many rural communities in Asia and Africa situated in semi-arid to arid regions are without reliable access to clean drinking water. It is, therefore, important to explore how solar energy can be linked to water treatment systems for clean drinking water production. Membrane-based water purification technologies play a major role in water purification by utilization of low-cost heat sources to make the process economically and technically viable for small, medium, and large-scale applications. Solar energy can be a viable source of power for water purification facilities in the coming years. Photovoltaic panels and solar thermal collectors are appropriate solar energy collectors for making a solar-powered water treatment system. Solar-assisted membrane-based water purification techniques could have a viable solution to the existing problems in semi-arid and arid regions. Due to the high quality of potable water demand, studies have been carried out on solar-assisted membrane-based technologies in water purification. This review considers basic concepts, specific energy consumption, water production cost, and applications of solar-driven membrane-based water purification technologies such as reverse osmosis, forward osmosis, electrodialysis, membrane distillation, and hybrid membrane systems. This review will allow the researchers to have a wider overview of the effort made by several investigators in the area of solar-assisted membrane-based water purification technology.
Current Insights into the Chemistry and Antitubercular Potential of Benzimidazole and Imidazole Derivatives
Authors: Parwani Deepa , Bhattacharya Sushanta , Rathore Akash , Mallick Chaitali , Asati Vivek , Agarwal Shivangi , Rajoriya Vaibhav , Das Ratnesh , Kashaw Sushil Kumar 
Published: November 2020

:
Tuberculosis is a disease caused by Mycobacterium tuberculosis (Mtb), affecting millions
of people worldwide. The emergence of drug resistance is a major problem in the successful treatment
of tuberculosis. Due to the commencement of MDR-TB (multi-drug resistance) and XDR-TB (extensively
drug resistance), there is a crucial need for the development of novel anti-tubercular agents with
improved characteristics such as low toxicity, enhanced inhibitory activity and short duration of
treatment. In this direction, various heterocyclic compounds have been synthesized and screened
against Mycobacterium tuberculosis. Among them, benzimidazole and imidazole containing derivatives
have been found to have potential anti-tubercular activity. The present review focuses on various
imidazole and benzimidazole derivatives (from 2015-2019) with their structure-activity relationships
in the treatment of tuberculosis.
Chemometric Comparison of Data Files Using Several Thermal Analytical Techniques for Dating Fossil Bones from Two Old Burial Sites
Authors: Tomassetti Mauro , Martini Elisabetta , Castrucci Mauro , Campanella Luigi , Coppa Alfredo 
Published: November 2020

Background::
The possibility of estimating the age of fossil bones using only classic
thermogravimetry, on the basis of proper % mass loss ratio values, has been widely considered in
the past years.

Objective::
Our research has brought some innovations to the previous background, by using
chemometric methods and by processing the numerical files of whole thermogravimetric curves.
The objective of this paper is the selection, among the main thermal analysis methods available,
i.e., thermogravimetry (TG), derivative thermogravimetry (DTG), differential thermal analysis
(DTA) and thermal dilatometry analysis (TDA), of the most suitable one, in order to evaluate the
age of fossil bones.

Methods::
Fossil bone samples from two ancient cemeteries in Sudan were analyzed using different
thermal methods (TG, DTG, DTA, and TDA). Data of whole recorded thermal curves have
been processed by PCA analysis.

Results::
A systematic comparison of several thermal analytical techniques allowed to conclude
that TG or DTG curves can provide more appropriate information to determine how old fossil
bones of different ages are, as evidenced by PCA processing of the entire file set of TG or DTG
curves.

Conclusion::
It can be concluded that the chemometric processing of TG or DTG curves data files
is the best method; however, discussing other thermal analytical curves (DTA and TDA) can
complete the information found by means of chemometric processing of whole TG and DTG
curves.
Effects of Objective and Subjective Health Literacy on Patients’ Accurate Judgment of Health Information and Decision-Making Ability: Survey Study
Authors: Schulz Peter Johannes , Pessina Annalisa , Hartung Uwe , Petrocchi Serena 
Published: November 2020

Background
Interpreting health information and acquiring health knowledge have become more important with the accumulation of scientific medical knowledge and ideals of patient autonomy. Health literacy and its tremendous success as a concept can be considered an admission that not all is well in the distribution of health knowledge. The internet makes health information much more easily accessible than ever, but it introduces its own problems, of which health disinformation is a major one.

Objective
The objective of this study was to determine whether objective and subjective health literacy are independent concepts and to test which of the two was associated more strongly with accurate judgments of the quality of a medical website and with behavioral intentions beneficial to health.

Methods
A survey on depression and its treatments was conducted online (n=362). The Newest Vital Sign was employed to measure objective, performance-based health literacy, and the eHealth Literacy Scale was used to measure subjective, perception-based health literacy. Correlations, comparisons of means, linear and binary logistic regression, and mediation models were used to determine the associations.

Results
Objective and subjective health literacy were weakly associated with one another (r=0.06, P=.24). High objective health literacy levels were associated with an inclination to behave in ways that are beneficial to one’s own or others’ health (Exp[B]=2.068, P=.004) and an ability to recognize low-quality online sources of health information (β=–.4698, P=.005). The recognition also improved participants’ choice of treatment (β=–.3345, P<.001). Objective health literacy helped people to recognize misinformation on health websites and improved their judgment on their treatment for depression.

Conclusions
Self-reported, perception-based health literacy should be treated as a separate concept from objective, performance-based health literacy. Only objective health literacy appears to have the potential to prevent people from becoming victims of health disinformation.
Interpretation of Maturity-Onset Diabetes of the Young Genetic Variants Based on American College of Medical Genetics and Genomics Criteria: Machine-Learning Model Development
Authors: Liu Yichuan , Qu Hui-Qi , Wenocur Adam S , Qu Jingchun , Chang Xiao , Glessner Joseph , Sleiman Patrick , Tian Lifeng , Hakonarson Hakon 
Published: November 2020

Background
Maturity-onset diabetes of the young (MODY) is a group of dominantly inherited monogenic diabetes, with HNF4A-MODY, GCK-MODY, and HNF1A-MODY as the three most common forms based on the causal genes. Molecular diagnosis of MODY is important for precise treatment. Although a DNA variant causing MODY can be assessed based on the criteria of the American College of Medical Genetics and Genomics (ACMG) guidelines, gene-specific assessment of disease-causing mutations is important to differentiate among MODY subtypes. As the ACMG criteria were not originally designed for machine-learning algorithms, they are not true independent variables.

Objective
The aim of this study was to develop machine-learning models for interpretation of DNA variants and MODY diagnosis using the ACMG criteria.

Methods
We applied machine-learning models for interpretation of DNA variants in MODY genes defined by the ACMG criteria based on the Human Gene Mutation Database (HGMD) and ClinVar database.

Results
With a machine-learning procedure, we found that the weight matrix of the ACMG criteria was significantly different between the three MODY genes HNF1A, HNF4A, and GCK. The models showed high predictive abilities with accuracy over 95%.

Conclusions
Our results highlight the need for applying different weights of the ACMG criteria in relation to different MODY genes for accurate functional classification. As proof of principle, we applied the ACMG criteria as feature vectors in a machine-learning model and obtained a precision-based result.
User Experience of a Chatbot Questionnaire Versus a Regular Computer Questionnaire: Prospective Comparative Study
Authors: te Pas Mariska E , Rutten Werner G M M , Bouwman R Arthur , Buise Marc P 
Published: November 2020

Background
Respondent engagement of questionnaires in health care is fundamental to ensure adequate response rates for the evaluation of services and quality of care. Conventional survey designs are often perceived as dull and unengaging, resulting in negative respondent behavior. It is necessary to make completing a questionnaire attractive and motivating.

Objective
The aim of this study is to compare the user experience of a chatbot questionnaire, which mimics intelligent conversation, with a regular computer questionnaire.

Methods
The research took place at the preoperative outpatient clinic. Patients completed both the standard computer questionnaire and the new chatbot questionnaire. Afterward, patients gave their feedback on both questionnaires by the User Experience Questionnaire, which consists of 26 terms to score.

Results
The mean age of the 40 included patients (25 [63%] women) was 49 (SD 18-79) years; 46.73% (486/1040) of all terms were scored positive for the chatbot. Patients preferred the computer for 7.98% (83/1040) of the terms and for 47.88% (498/1040) of the terms there were no differences. Completion (mean time) of the computer questionnaire took 9.00 minutes by men (SD 2.72) and 7.72 minutes by women (SD 2.60; P=.148). For the chatbot, completion by men took 8.33 minutes (SD 2.99) and by women 7.36 minutes (SD 2.61; P=.287).

Conclusions
Patients preferred the chatbot questionnaire over the computer questionnaire. Time to completion of both questionnaires did not differ, though the chatbot questionnaire on a tablet felt more rapid compared to the computer questionnaire. This is an important finding because it could lead to higher response rates and to qualitatively better responses in future questionnaires.
A Nutrition Intervention to Promote the Consumption of Pulse-Based Foods in Childcare Centers: Protocol for a Multimethod Study
Authors: Haileslassie Hiwot Abebe , Ramikie Renee , Vatanparast Hassan , Ramdath D Dan , Froehlich Chow Amanda , Shand Phyllis , Engler-Stringer Rachel , Lieffers Jessica RL , Hood-Niefer Shannon , Henry Carol 
Published: November 2020

Background
Plant-based foods, including pulses (dry beans, lentils, chickpeas, and peas), have gained worldwide attention owing to their health and environmental benefits. Despite high production, the consumption of pulses is low in Canada. Behavior change interventions systematically designed to promote the consumption of pulse-based foods are scarce.

Objective
We describe the utilization of intervention mapping (IM) in the development of a multicomponent nutrition intervention aimed at promoting consumption of pulse-based foods among preschool children in childcare centers in Saskatchewan, Canada.

Methods
The Pulse Discovery Toolkit intervention was developed following the six steps of the IM protocol. Decisions at each step were either based upon literature review, expert consultation, pretesting, or a combination of these. Following the initial phase of the study, which focused on intervention development, phases II and III of the study were concerned with pilot testing and roll-out of the intervention, respectively. In total, one, two, and four childcare centers participated in phases I, II, and III, respectively. A multimethod approach was designed to evaluate the intervention during pilot testing and roll-out.

Results
The application of IM steps 1 to 3 in phase I resulted in the creation of performance objectives at different levels, including at the individual level (preschool children), and the social and environmental levels (parents, early childhood educators, and cooks). These objectives were then used to create a matrix of objectives matching the constructs of the social cognitive theory while taking Piaget cognitive development into consideration. This step was followed by defining program components, implementation, adoption, and evaluation strategies, which were utilized in phases II and III. Data have been collected from 2015 to 2018 and analyzed. The results will be reported elsewhere.

Conclusions
The IM protocol provided a rigorous framework for the development of a multicomponent evidence-based intervention to promote pulse-based foods in childcare centers.

International Registered Report Identifier (IRRID)
RR1-10.2196/22775
Extraction of Family History Information From Clinical Notes: Deep Learning and Heuristics Approach
Authors: Silva João Figueira , Almeida João Rafael , Matos Sérgio 
Published: November 2020

Background
Electronic health records store large amounts of patient clinical data. Despite efforts to structure patient data, clinical notes containing rich patient information remain stored as free text, greatly limiting its exploitation. This includes family history, which is highly relevant for applications such as diagnosis and prognosis.

Objective
This study aims to develop automatic strategies for annotating family history information in clinical notes, focusing not only on the extraction of relevant entities such as family members and disease mentions but also on the extraction of relations between the identified entities.

Methods
This study extends a previous contribution for the 2019 track on family history extraction from national natural language processing clinical challenges by improving a previously developed rule-based engine, using deep learning (DL) approaches for the extraction of entities from clinical notes, and combining both approaches in a hybrid end-to-end system capable of successfully extracting family member and observation entities and the relations between those entities. Furthermore, this study analyzes the impact of factors such as the use of external resources and different types of embeddings in the performance of DL models.

Results
The approaches developed were evaluated in a first task regarding entity extraction and in a second task concerning relation extraction. The proposed DL approach improved observation extraction, obtaining F1 scores of 0.8688 and 0.7907 in the training and test sets, respectively. However, DL approaches have limitations in the extraction of family members. The rule-based engine was adjusted to have higher generalizing capability and achieved family member extraction F1 scores of 0.8823 and 0.8092 in the training and test sets, respectively. The resulting hybrid system obtained F1 scores of 0.8743 and 0.7979 in the training and test sets, respectively. For the second task, the original evaluator was adjusted to perform a more exact evaluation than the original one, and the hybrid system obtained F1 scores of 0.6480 and 0.5082 in the training and test sets, respectively.

Conclusions
We evaluated the impact of several factors on the performance of DL models, and we present an end-to-end system for extracting family history information from clinical notes, which can help in the structuring and reuse of this type of information. The final hybrid solution is provided in a publicly available code repository.