bluuebunny/crossref_metadata_2025_split huggingface dataset:
Soft systems methodology for implementing clinical practice guidelines in a general hospital: a study protocol
Authors: Soltani Ali , Heyrani Ali , Fakhr-Movahedi Ali , Khajavi Abdoljavad 
Published: April 2021

Abstract
Background: Adhering to Clinical Practice Guidelines (CPGs) serves as the driving force behind making decisions based on the best evidence and making efforts for improving the quality of patient care and outcomes. In 2010, promoting the quality of clinical care through implementing CPGs was turned into a priority health policy in Iran as in many other countries. Despite requiring Iranian hospitals to implement CPGs in January 2017, the concept and implementation method of CPGs remained to be clarified. This action research focuses on acquiring an in-depth understanding of how to define and implement CPGs in a selected general hospital in Iran.Methods: This study employs Soft Systems Methodology (SSM) as a commonly-used approach for tackling complex problems with social, political and human dimensions. Given the inherent roles of technical processes, organizational culture, and personnel’ perspectives in providing clinical care, implementing CPGs was considered a complex problem situation, and conceptualized by use of a purposeful activity model. We will conduct semi-structured in-depth interviews and hold group discussions with different stakeholders to enquire into the situation. Moreover, we will use SSM tools and techniques to identify the main areas of changes, and select necessary measures to facilitate the implementation of CPGs. Flexible qualitative methods of data collection and analysis are utilized throughout the study.Discussion: Applying SSM in implementing CPGs can generate knowledge by recognizing hyper-complexity in healthcare setting, adopting an attitude of inquiry, and fostering dynamic changes in diverse and numerous worldviews of professionals in the accommodation process. This knowledge can provide a model for the successful implementation of CPGs at a macro-system level and facilitate the persuasion process at the hospital mesosystem level. More importantly, adopting SSM can create iterative learning loops over time and thus help the actors of clinical microsystems face future healthcare complexities.
Habitat ephemerality affects the evolution of contrasting growth strategies and cannibalism in anuran larvae
Authors: Oh Dogeun , Kim Yongsu , Yoo Sohee , Kang Changku 
Published: April 2021

Abstract
Ephemeral streams are challenging environments for tadpoles; thus adaptive features that increase the survival of these larvae should be favored by natural selection. In this study, we compared the adaptive growth strategies of Bombina orientalis (the oriental fire-bellied toad) tadpoles from ephemeral streams with those of such tadpoles from non-ephemeral streams. Using a common garden experiment, we tested the interactive effects of location (ephemeral vs. non-ephemeral), food availability, and growing density on larval period, weight at metamorphosis, and cannibalism. We found that tadpoles from ephemeral streams underwent a shorter larval period compared with those from non-ephemeral streams but that this difference was contingent on food availability and density. The observed faster growth is likely to be an adaptive response because tadpoles in ephemeral streams experience more biotic/abiotic stressors, such as desiccation risk and limited resources, compared with those in non-ephemeral streams, with their earlier metamorphosis potentially resulting in survival benefits. As a trade-off for their faster growth, tadpoles from ephemeral streams had a lower body weight at metamorphosis compared with those from non-ephemeral streams, but only when food was sufficient. We also found lower cannibalism rates among tadpoles from ephemeral streams, which can be attributed to the indirect fitness costs of cannibalizing their kin. Our study is the first to demonstrate how ephemeral habitats have affected the evolutionary change in cannibalistic behaviors in anurans and provides additional evidence that natural selection has mediated the evolution of growth strategies of tadpoles in ephemeral streams.
The Effect of Ecological Factors on Cats’ Weight in Tehran - First Phase
Authors: Rahimi Farid 
Published: April 2021

Abstract
Urban cats live in cities like humans and humans affect their life intentionally or unintentionally. Waste production is only one of the human effects on the urban cat ecosystem. The waste produced by human supply some of the food needed by urban cats. This descriptive - estimation research is the first study in the world to measure the cats’ weight to investigate the effect of the increase or decrease in urban wastes on physical status of cats. In the first phase of the research (Spring 2016-Winter 2017) in Tehran, we found that the average volume of the collected wastes had increased by 14% and the average weight of cats in the mentioned period had increased 1%. The 9.5% decrease in the waste volume in Autumn 2016 had led to the decrease in the average weight of cats in Winter 2017. The male cats were more affected by the decrease in waste volume.
Pathophysiological Complexity of Amiodarone-Induced Hypothyroidism (AIH) in patient With Congenital Heart Disease- Ebstein Anomaly: a case report
Authors: Bosnic Zvonimir , Vucic Domagoj , Marinic Nikica , Saric Blazenka , Majnaric Ljiljana Trtica 
Published: April 2021

Abstract
Background: Amiodarone is a class III antiarrhythmic drug, used for the threatment of life threatening supraventricular and ventricular tachyarrhythmias and widely used in prevention of life threatening tachyarrhythmia in adults with congenital heart disease. Thyroid dysfunction is a potentially serious complication of amiodarone therapy, especially in older patients with acquired heart disease. Cause there is no published systematic study on amiodarone-associated hypothirodism in patients with congenital heart disease, we report the case of a patient with Ebstein anomaly, a rare congenital heart disorder, who developed hypothyroidism after prolonged amiodrone therapy. We report a possible pathophysiological link of amiodarone-induced hypothyroidism in a patient with rare congenital heart disease, that has not been reported in a significant number in the literature so far.Case presentation: A female, 55-year-old patient with history of Ebstein anomaly (non operated), presented to a family medicine doctor with symptoms of progressive dyspnoea, fatigue and dysfagia for several months. Electrocardiography, echocardiography and chest X- ray confirmed presence of Ebstain anomaly. Laboratory results (including thyroid hormone values) and thyroid ultrasound were performed which confirmed the presence of hypothyroidism.Conclusions: According to available data, there is no published systematic study on amiodarone-associated hypothirodism in patients with congenital heart disease (large cohort studies). Pathophysiological complexity, however, could be due to the agent triggering autoimmune thyroid disease, so it is possible that amiodarone precipitated the onset of preexisting autoimmune disease. The value of regular thyroid function testing and measurement of thyroid antibodies should be considered in patients during amiodarone administration, especially in older patients with rare congenital heart disease.
Analysing the Severity of Coronavirus Infection in Air Pollution: Evidence-Based Study From Saudi Arabia
Authors: Ghanim Abdulnoor Ali Jazem 
Published: April 2021

Abstract
COVID-19 has been considered as one of the major global pandemic which has caused different health problems by affecting the majority of the population throughout the world. Several studies have evolved the concerns of air pollution being considered as a major risk factor causing respiratory infection that are carried out by microorganisms which further affects the immunity system of the body. The present study involves the relationship between the air pollutants and COVID-19 total infection along with estimation of death rates in the several regions of Saudi Arabia. The major goal of this study comprises the analysis of the relationship between air pollutants concentration such as (PM10, NO2, CO, SO2 and O3) and COVID-19 wide outbreak, concerning the transmission, number of patients, critical cases and death rates . The results show that the estimation of COVID-19 cases were highest in number recorded in the most polluted regions, the mortality rate and critical cases were also more distinct in these regions more than other regions in Saudi Arabia. The finding of this study shows a positive correlation between mean PM 10, NO2, CO and SO2 pollutants. The results represent the significant relationship between air pollution resulting from high concentration of NO2 and COVID-19 infection and deaths. Null hypothesis of the relation between other pollutants and COVID-19 infection couldn’t be rejected. The study also indicates significant correlation between mean NO2 and CO and total number of critical cases, and negative correlations were obtained between Mean O3 and total number of cases, total deaths and critical case per cumulative days.
Effect of the staggered impeller on reducing unsteady pressure pulsations of a centrifugal pump
Authors: Zhang Ning , Jiang Junxian , Liu Xiaokai , Gao Bo 
Published: April 2021

Abstract
High pressure pulsations excited by rotor stator interaction is always focused in pumps, especially for its control considering the stable operation. In the current research, a special staggered impeller is proposed to reduce intense pressure pulsations of a centrifugal pump with ns=69 based on alleviating rotor stator interaction. The numerical simulation method is conducted to illustrate the influence of staggered impeller on the pump performance and pressure pulsations, and three typical flow rates (0.8ФN-1.2ФN) are simulated. Results show that the staggered impeller will lead to the pump head increasing, and at the design working condition, the increment reaches about 3% compared with the original impeller. Meanwhile, the pump efficiency is little affected by the staggered impeller, which is almost identical with the original impeller. From comparison of pressure spectra at twenty monitoring points around the impeller outlet, it is validated that the staggered impeller contributes significantly to decreasing pressure pulsations at the concerned working conditions. At the blade passing frequency, the averaged reduction of twenty points reaches 89% by using the staggered impeller at 1.0ФN. The reduction reaches to 90%, 80% at 0.8ФN, 1.2ФN respectively. Caused by the rib within the staggered impeller, the internal flow field in the blade channel will be affected. Finally, it is concluded that the proposed staggered impeller surely has a significant effect on alleviating intense pressure pulsation of the model pump, which is very promising during the low noise pump design considering its feasibility for manufacturing.
Tree Biomass Carbon in different Land Use Types Managed by Smallholder Farmers Along Altitudinal Gradient in Central Highlands of Ethiopia
Authors: Haile Getahun , Lemenih Mulugeta , Itanna Fisseha , Agegnehu Getachew 
Published: April 2021

Abstract
Background and Aims Biomass carbon (C) stocks of trees across three common traditional agroforestry practices (i.e. home-garden, farmland, and grazing land) and along altitudinal gradients (i.e. upper, middle and lower) in southern Ethiopia are presented and evaluated. These traditional AF systems are characterized by a high proportion and diversity of trees hence can play a remarkable role in climate change adaptation and mitigation.Methods Data were collected from a total of 89 plots: 41 home-gardens, 29 croplands, and 19 grazing lands using total count and Y-frame transect sampling methods. Above- and belowground biomass of trees were calculated using allometric equations developed somewhere else but proven for application in agroforestry systems. Trees with DBH ≥ 2 cm were considered for biomass carbon stock determination.Results above-ground biomass carbon stock of the three land uses showed the order: Home-garden > grazing land > cropland, but the differences in the carbon stocks were not statistically significant. Soil carbon stocks measured from the studied land uses at middle altitude also followed a similar trend. Similarly, differences among altitudinal gradients were not statistically significant. However, the variations observed reflected differences in species composition among the system as well as altitudinal gradients. Other factors such as wealth and garden size also significantly affected biomass C stocks per ha, where rich household holds higher above-ground biomass than medium and poor households. Overall, this reflects that rich households own a large parcel and large total number of trees, compared to that of medium and poor wealth classes.Conclusions The biomass C stocks of the tree across the three studied AF systems were found to be lower than reported for tropical forests and agro-forestry systems due to the recently agro-forestry intensification in the form of reduction in tree diversity and density. For enhancing their biomass carbon stocks traditional agro-forestry should be integrated in future REDD+ projects. As the biomass C stocks were more determined by socioeconomic factors such as wealth and garden size than the types of agro-forestry practice and climate (elevation) future carbon management strategies should also considered them.
Consensus Tracking-based Clock Synchronization&nbsp;for the Internet of Things
Authors: niu yuqing , Yang Ting , hou yucheng , cai shaotang , yan peng 
Published: April 2021

Abstract
Clock synchronization provides fundamental timing reference for various services in the Internet of Things (IoT). Unlike centralized synchronization algorithm, which relies heavily on the synchronization routing and brings about error accumulation consequently, the distributed synchronization algorithm achieves clock synchronization through time message exchange and calculation among adjacent nodes, hence the error accumulation can be greatly eliminated. However, the convergence speed of existing distributed synchronization algorithms is generally slow, and network topology information is seldom utilized to improve the convergence speed, which may cause additional energy consumption especially in resource constrained scenarios. To improve the convergence speed of distributed clock synchronization, a consensus tracking-based clock synchronization (CTCS) algorithm is proposed in this paper. By analyzing the synchronization process in the state space framework, the convergence acceleration term is designed to optimize the eigenvalue distribution of synchronization error matrix, hence the convergence speed can be greatly improved. To be suitable for clock synchronization in the dynamic network, a reference clock input term is designed in the clock update formula, which eliminates the oscillation of synchronized clocks triggered by synchronization of newly joined nodes. To prove the convergence of CTCS, an in-depth analysis of the algorithm is conducted. Both simulation and experimental results validate the effectiveness of CTCS in comparison with other solutions.
Forward variable selection improves the power of random forest for high-dimensional microbiome data
Authors: Dang Tung , Kishino Hirohisa 
Published: April 2021

Abstract
Background: Random forest (RF) captures complex feature patterns that differentiate groups of samples and is rapidly being adopted in microbiome studies. However, a major challenge is the high dimensionality of microbiome datasets. They include thousands of species or molecular functions of particular biological interest. This high dimensionality significantly reduces the power of random forest approaches for identifying true differences. The widely used Boruta algorithm iteratively removes features that are proved by a statistical test to be less relevant than random probes. Result: We developed a massively parallel forward variable selection algorithm and coupled it with the RF classifier to maximize the predictive performance. The forward variable selection algorithm adds new variable to a set of selected variables as far as the prespecified criterion of predictive power is improved. At each step, the parameters of random forest are optimized. We demonstrated the performance of the proposed approach, which we named RF-FVS, by analyzing two published datasets from large-scale case-control studies: (i) 16S rRNA gene amplicon data for Clostridioides difficile infection (CDI) and (ii) shotgun metagenomics data for human colorectal cancer (CRC). The RF-FVS approach further screened the variables that the Boruta algorithm left and improved the accuracy of the random forest classifier from 81% to 99.01% for CDI and from 75.14% to 90.17% for CRC. Conclusion: Valid variable selection is essential for the analysis of high-dimensional microbiota data. By adopting the Boruta algorithm for pre-screening of the variables, our proposed RF-FVS approach improves the accuracy of random forest significantly with minimum increase of computational burden. The procedure can be used to identify the functional profiles that differentiate samples between different conditions.
The Impact of Mandatory Environmental Information Disclosure and the Green Innovation of Pollution-Intensive Companies? Evidence From China
Authors: Guo Qianghua , Wei Yidan 
Published: April 2021

Abstract
Based on the Guidelines of the Shanghai Stock Exchange on Environmental Information Disclosure for Listed Companies issued in 2008, this paper constructs a quasi-natural experiment and uses the did method to study the impact of mandatory environmental information disclosure on the green innovation of pollution-intensive companies in China. The results show that mandatory environmental information disclosure can significantly promote the green innovation of pollution-intensive companies by strengthening the company's motivation and pressure to comply with the regulation; in addition, the positive effect is more obvious in state-owned companies, small companies and companies with poor information condition in pollution-intensive industries. This paper enriches the literature of mandatory environmental information disclosure and offers guidance for policymakers seeking to improve environmental information disclosure policies in emerging countries.
Factors Affecting Germination and Establishment Success of an Endemic Cactus of the Chihuahuan Desert
Authors: Martínez Eder Ortiz , Golubov Jordan , Mandujano Maria C. , Cosultchi Gabriel Arroyo 
Published: April 2021

Abstract
Seeds and seedlings are the most critical stages of cacti life cycles. From the thousands of seeds produced in a reproductive season, only a small fraction successfully germinate, the rest are lost to predation, go dormant and remain viable in the seed bank or lose viability. These early stages often depend on facilitation by nurse plants for germination and seedling recruitment. We aim to prescribe actions for the conservation of Cephalocereus polylophus by improving recruitment in the population. The viability of seeds with different storage times was evaluated as an indicator of their potential to form a short-term seed bank. Through the analysis of seed germination and seedling survival under the canopy of two nurse plant species and open areas, we assessed the importance of facilitation for recruitment. A predator exclusion experiment evaluated the intensity of herbivory on seeds and seedlings of different ages. Seeds had germination rates above 90\% under laboratory conditions, even after two years of storage. Seed germination was only registered under one of the two nurses and after two years, up to 4 % of the seedlings planted under both nurse plants survived and protection against herbivores increased seedlings survival. Considering that facilitation and age are crucial for seedling survival of C. polylophus, future conservation programs should include the protection of plant communities and the introduction of seedlings instead of seeds.
WITHDRAWN: A Novel Axis HIF1A/miR-1271-5p/lncRNA PTTG3P/YAP1 Contributes to Colorectal Cancer Progression and Relates to an Immune-Suppressing Microenvironment
Authors: zheng yang , zhang ke , liu yiyang , xie longfei , ge jinnian , wang yue , zhao guohua 
Published: April 2021

Abstract
Background Pseudogene has emerged as key regulators of important biological processes involved in human cancers. However, the PTTG3P biological function in colorectal cancer (CRC) needs further to be clarified. Methods qRT-PCR was adopted to measure the PTTG3P expression in different cell line and CRC tissues. Cellular localization of PTTG3P was detected by subcellular fractionation assay. In vitro and in vivo experiments were carried out to explore the bioeffect of PTTG3P in CRC cells. Chromatin immunoprecipitation (ChIP), luciferase assay and RIP were explored to certify the direct binding of PTTG3P and microRNA. Results PTTG3P was upregulated in CRC and closely related to poor prognosis. Through gain and loss of function approaches, PTTG3P facilitated proliferation and glycolysis through YAP1, and glycolysis inhibitor (2-DG,3-BG) and LDHA knockdown could rescue cell proliferation and tumorigenesis. Mechanically, miR-1271-5p modulates PTTG3P expression and miR-1271-5p mimics could recover the PTTG3P function. Also HIF1A increased PTTG3P expression in both normoxia and hypoxia conditions by ameliorating miR-1271-5p expression. In addition, silencing PTTG3P decreases the level of inflammatory cytokines TNF-α, IL-1β and IL-6, and low PTTG3P expression relates with CD8+ T, NK and TFH cells infiltration. Conclusions Our findings verified the oncogenic function of PTTG3P in assisting the cell proliferation and glycolysis, demonstrating the pivotal roles of HIF1A/miR-1271-5p/lncRNA PTTG3P/YAP1 in CRC progression, which proposes a novel approach for clinical treatment.
Air Pollution and Cardiorespiratory Hospitalization, Modeling and Analysis Using Artificial Intelligence Techniques
Authors: Usmani Raja Sher Afgun , Pillai Thulasyammal Ramiah , Hashem Ibrahim Abaker Targio , Marjani Mohsen , Shaharudin Rafiza , Latif Mohd Talib 
Published: April 2021

Abstract
Air pollution has a serious and adverse effect on human health, and it has become a risk to human welfare and health throughout the globe. In this paper, we present the modeling and analysis of air pollution and cardiorespiratory hospitalization. This study aims to investigate the association between cardiorespiratory hospitalization and air pollution, and predict cardiorespiratory hospitalization based on air pollution using the Artificial Intelligence (AI) techniques. We propose the Enhanced Long Short-Term Memory (ELSTM) model and provide a comparison with other AI techniques, i.e., Long Short-Term Memory (LSTM), Deep Learning (DL), and Vector Autoregressive (VAR). This study was conducted at seven study locations in Klang Valley, Malaysia. The prediction results show that the ELSTM model performed significantly better than other models in all study locations, with the best RMSE scores in Klang study location (ELSTM: 0.002, LSTM: 0.013, DL: 0.006, VAR: 0.066). The results also indicated that the proposed ELSTM model was able to detect and predict the trends of monthly hospitalization significantly better than the LSTM and other models in the study. Hence, we can conclude that we can utilize AI techniques to accurately predict cardiorespiratory hospitalization based on air pollution in Klang Valley, Malaysia.