bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of dexmedetomidine on hemodynamic and recovery responses during tracheal extubation
Authors: Kunikkakath Shamjith , Aboobacker C P Shabeel , Baby Melbin , Kutty C Salman Mohammed 
Published: June 2021

Endotracheal extubation is associated with cardiovascular and airway responses leading to tachycardia, hypertension, arrhythmias, myocardial ischemia, coughing, agitation, bronchospasm, increased bleeding, raised intracranial and intraocular pressure which may be life threatening especially in vulnerable patients. Dexmedetomidine, a highly selective α2-adrenoreceptor agonist is found to attenuate these effects and provide a smooth extubation. To assess the effect of dexmedetomidine on hemodynamic and ventilatory recovery during tracheal extubation. This comparative study was done in 42 patients who fulfilled the inclusion and exclusion criteria between the age group of 20 to 45 years from both sexes were randomly allocated in to two groups of 21 each. One group received 0.5mg Dexmedetomidine and the other group received 100 ml NS. Both groups were compared for the hemodynamic parameters at different time intervals during the whole procedure and were compared for differences if any. In the study group, parameters like Mean arterial pressure, Systolic Blood Pressure, Diastolic Blood Pressure and Heart Rate were under control than the control group. The extubation quality score between controls and dexmedetomidine group (2.14 vs. 1.24) is statistically significant (P&#60;0.001). 14.28% of study group had cough compared to 52.39% in the control group. Bradycardia and Hypertension were significantly higher in the study population. Justbefore extubation, administration of dexmedetomidine ensures the smooth extubation of the trachea and reduces the cardiovascular responses. It also provides adequate sedation postoperatively.
Integration concepts of central ST systems in DHC
Authors: Leoni Paolo , Nielsen Jan Erik 
Published: June 2021

This factsheet focuses on the integration hydraulics and control of central ST systems in DHC. The first part gives an overview of the typical integration concepts and operating modes implemented in the state of the art. The second part illustrates general aspects of the integration of heat pumps to achieve higher shares of ST and describes recent projects: two implementation projects (Crailsheim and Salzburg-Lehen), and one feasibility study performed by the Technische Universität Dresden.
ANALYSIS OF AMPLIFICATION OF STUDENT CHARACTER IN THE SCHOOL ENVIRONMENT
Authors: Wulandari Fajar , Marhayani Dina Anika 
Published: June 2021

This study aims to strengthen the character of students in maintaining environmental cleanliness, especially in schools. Strengthening of students is needed to be more loving and caring for the environment, thus students can implement positive attitudes wherever they are. This research was conducted at SDN 5 Singkawang. An environmentally friendly school that applies the characteristics of caring for the environment as an effort to manage and preserve the environment. Recycling activities are activities carried out to aim to support the application of environmental care characters to all elements of students in the school. The method used in this study uses a descriptive qualitative approach. data source sampling is done <em>purposively </em>and<em> snowball</em>, collection techniques with triangulation (combined) data analysis are inductive and qualitative, and the results of qualitative research emphasize the meaning rather than generalization.
A stochastic SEIHR model for COVID-19 data fluctuations
Authors: Niu Ruiwu , Chan Yin-Chi , Wong Eric W. M. , Wyk Michaël Antonie van , Chen Guanrong 
Published: June 2021

Abstract
Although deterministic compartmental models are useful for predicting the general trend of a disease's spread, they are unable to describe the random daily fluctuations in the number of new infections and hospitalizations, which is crucial in determining the necessary healthcare capacity for a specified level of risk. In this paper, we propose a stochastic SEIHR (sSEIHR) model to describe such random fluctuations and provide sufficient conditions for stochastic stability of the disease-free equilibrium, based on the basic reproduction number that we estimated. Our extensive numerical results demonstrate strong threshold behavior near the estimated basic reproduction number, suggesting that the necessary conditions for stochastic stability are close to the sufficient conditions derived. Furthermore, we found that increasing the noise level slightly reduces the final proportion of infected individuals. In addition, we analyze COVID-19 data from various regions worldwide and demonstrate that by changing only a few parameter values, our sSEIHR model can accurately describe both the general trend and the random fluctuations in the number of daily new cases in each region, allowing governments and hospitals to make more accurate caseload predictions using fewer compartments and parameters than other comparable stochastic compartmental models.
Analysis of Critical Success Factors to Design E-waste Collection Policy in India: A Fuzzy DEMATEL Approach
Authors: Singh Shailender , Dasgupta Mani Sankar , Routroy Srikanta 
Published: June 2021

Abstract
The design of an e-waste collection policy is challenging, especially for a country like India, where the economy is developing state, and there is a large diversity in socio-economic factors. The e-waste collection policy has an impact on the various stakeholders such as the manufacturer, the raw material producers, the assemblers, the retailers, the generator (households and bulk consumers), the scrap dealers, the smelters and the recyclers as well as the regulators. The design of an e-waste collection policy needs to consider the appropriate set of Critical Success Factors (CSFs) which will maximize the e-waste collection providing business sustainability to the stakeholders at the same time satisfying the environmental regulations in the operating locations. Twenty-three CSFs identified along with six implication factors for e-waste collection policy framework based on a literature survey and experts view. The fuzzy DEMATEL approach is employed to analyze the CSFs to design an e-waste collection policy in India from a wide perspective. Cause and effect interrelationship is established among the CSFs, and also their impacts are evaluated to segregate the CSFs into cause group (prominent influencing and independent) and effect group (influenced and dependent). The CSFs such as technology involvement, green practices, environmental program, certification and licensing, public ethics and stakeholder’s awareness for circular economy are prominent influencing CSFs for e-waste collection policy in India. The current study is expected to provide a platform for policymakers to design the e-waste collection policy.
A Model-Based Bayesian Framework for Pipeline Leakage Enumeration and Location Estimation
Authors: Li Juan , Wu Ying , Lu Changgang 
Published: June 2021

Abstract
Leak detection in pipelines is an important issue, because leakages pose financial losses, environmental pollution and even health risks. The paper considers the problem of detecting multiple leaks based on transient wave theory for a reservoir pipeline valve system. The given measured data under consideration may contain one or multiple leaks originating from different locations when estimating the leak locations. This leads to two problems to be solved: first determine the correct number of leaks, and then identify the actual location of each leak. Thus, a probabilistic method of model-based Bayesian analysis is applied to this paper. This work employs a model to describe various scenes, individually defined by a specific number of leaks and their locations. Bayesian inference is used to select which model that is the most appropriate to fit the measured data. Through the process, the number of leaks is first estimated, and then the leak locations are extracted from the model that the measured data prefers. This paper presents different experimental setups and scenarios to demonstrate the availability of the proposed method, demonstrating that this model-based Bayesian analysis is an accurate tool for leakage enumeration and location estimation.
Contribution of Nitrogen Sources to Streams in Mixed-use Watershed Varies Seasonally in a Temperate Region
Authors: Lin Zuhong , Liu Junchi , Xiao Yong , Yu Chaojie , Zhang Jinlan , Zhang Tingting 
Published: June 2021

Abstract
The Beiyun river flows through a hot spot region of Beijing-Tianjin-Hebei in China that serves a majority of occupants. However, the region experiences severe nitrate pollution, posing a threat to human health due to inadequate self-purification capacity. In that context, there is an urgent need to assess nitrate levels in this region. Herein, we used δ15N-NO3, δ18O-NO3 isotopes analysis, and stable isotope analysis model to evaluate the nitrate source apportionment in the Beiyun river. A meta-analysis was then used to compare the potential similarity of nitrate sources among the Beiyun riverine watershed and other watersheds. Results of nitrate source apportionment revealed that nitrate originated from the manure & sewage (contribution rate: 89.6%), soil nitrogen (5.9%), and nitrogen fertilizer (3.9%) in the wet season. While in the dry season, nitrate mainly originated from manure & sewage (91.6%). Further, different land-use types exhibited distinct nitrate compositions. Nitrate in urban and suburban areas mostly was traced from manure & sewage (90.5% and 78.8%, respectively). Notably, the different nitrate contribution in the rural-urban fringe and plant-covered areas were manure & sewage (44.3% and 32.8%), soil nitrogen (26.9% and 35.7%), nitrogen fertilizer (23.5% and 29.4%), and atmospheric deposition (5.3% and 2.0%). Through a meta-analysis, we found nitrogen fertilizer, soil nitrogen, and manure & sewage as the main nitrate sources in the Beiyun riverine watershed or the other similar complex watersheds in the temperate. Thus, this study provides a scientific basis for nitrate source apportionment and nitrate preventive management in watersheds with complex land-use types in temperate regions.
An Improved Modelling of User Clustering For Small Cell Deployment In Heterogeneous Cellular Network.
Authors: Bora Joyatri , Hussain Anwar 
Published: June 2021

Abstract
Users in practical cellular geographical areas are found to be non-uniformly distributed. Small cell ( SC ) deployments in heterogeneous user distribution in a cellular geographical area help to meet high data rate user demands for multimedia data communications in hot spots. SCs help to offload traffic burden from the macro cell ( MC ) base station, and also cater the data traffic need for the edge users where signal strength from the MC base station ( BS ) is very weak. For deployments of SCs along with the central MC BS (hence called HetNet ) in such spatial heterogeneous user distribution, effective user grouping or clustering algorithm is required for appropriate and satisfactory service coverage. We call it service grouping or clustering of users to be put under a SC for data transmission and reception. It does not disturb the spatial positions of users in clustered non-uniform distribution. Efficient grouping or clustering of users and then deploying a SC at optimal location enhances the performance of the HetNet . It is found that the K-means algorithm used for such grouping of users to position SCs is not efficient. A novel and improved user grouping algorithm is proposed in this paper which performs much better compared to the k-means algorithm. The proposed algorithm of modelling of user clustering results in increase in the number of users under SCs , increase in more offloading of data traffic from MC BS thereby increasing data throughput of MC users. The algorithm also increases in the energy efficiencies of the SCs which is considered as one important performance metric. A doubly stochastic poison process ( DSPP ) also called Cox process is assumed here for simulation of non-uniform user distributions. We consider Rayleigh distributed small scale fading model, large scale fading factor representing shadow fading, and users’ geographical distances from BSs to evaluate users’ data rates.
Bandwidth Enhancement of Cross-Shaped Fractal Antenna Using Lanthanum Doped Ba-Sr Hexagonal Ferrite As Substrate Material For X-Band Applications
Authors: Gujral Shally , Bhatia Kamaljit Singh , Singh Harjitpal , Kaur Harsimrat , Gupta Nancy 
Published: June 2021

Abstract
This paper analyzes and compares the performance of a proposed cross-shaped fractal antenna design with two different substrate materials FR4 epoxy and lanthanum doped Ba-Sr hexagonal ferrite in X-band, where the lanthanum doped Ba-Sr hexagonal ferrite substrate is synthesized based on solid-state reaction method. The proposed antenna design is simulated using HFSS (High frequency structure simulator) version 15. The antenna is intended to work at 10 GHz frequency and involves four iterations. The antenna design is optimized for significant performance parameters viz. return loss, bandwidth, and gain. It provides better results with ferrite substrate as compared to FR4 epoxy substrate and provides − 10 dB broad bandwidth in three frequency regions 6.2969-6.4 GHz, 7.8702-9.44 GHz, and 9.68-9.7746 GHz. The prototype of proposed antenna with FR4 epoxy substrate is fabricated and tested to attain experimental results. The measured results are in good liaison with simulated results. This antenna structure can be considered suitable for RADAR, satellite, microwave communication, and weather forecasting applications in X-Band.
Comparison of the Effect of Electronic Learning and Blended Learning on the Empowerment of the Caregivers of Cancer Patients Under Chemotherapy
Authors: Karimi Nahid , ZarifSanaiey Nahid , Vizeshfar Fatemeh 
Published: June 2021

Abstract
Objective: Cancer is a chronic disease that affects the person and family. E-learning is a common method of educating for patients and caregivers. The present study aimed to compare the impact of electronic learning and blended learning on the empowerment of the caregivers of cancer patients under chemotherapy. Methods: This clinical trial was performed in the main chemotherapy center of Shiraz University of Medical Sciences during October 2018-December 2020. A total of 123 caregivers of cancer patients who were under chemotherapy were selected through simple random sampling based on drawing in two intervention groups and one control group. The empowerment of caregivers was evaluated using the caregivers’ empowerment questionnaire in all three groups at the beginning of the study, immediately after the intervention, and one month after intervention. The data were analyzed by descriptive and statistical tests utilizing the SPSS software version 22. Results: The comparison of knowledge scores between the two intervention groups shows not significant difference between the two groups (P=0.3). Comparison of attitude scores demonstrated the group intervention one had a better attitude than the two others groups after intervention (P0.003). The mean performance score increased in both intervention groups with a significant difference (P=000). No significant differences were observed between demographic data and knowledge, attitude and performance of three groups (P>0.05). Conclusion: Our results indicated that electronic and blended learning types affected the attitude and performance of patients’ caregivers. Therefore, blended learning could be applied as a source of enhancing the empowerment of caregivers.
Improved OD and OC Fragmentation using Deep Learning for the Progression Recognition of Glaucoma
Authors: P Shanmugam , J Raja , R Pitchai 
Published: June 2021

Abstract
Glaucoma is one of the most hazardous diseases, proceeding to impact and burden an extensive bit of our general population. Appropriately, the initial stage of identification of glaucoma is significant to prevent the permanent vision misfortune. The CDR is the important factor for glaucoma recognition. The precise fragmentation of optic disc and cup is yet an evolving issue. Most of the segmentation based glaucoma recognition methods depends on the handcrafted features. It affects the overall performance of the glaucoma recognition. To resolve this issue, an efficient deep learning based optic cup and disc segmentation using technique multi-label segmentation Au-net has been developed in this paper. The proposed method focusing on the optic cup-to-disc ratio for the recognition of glaucoma, which may be the best system for building a capable, energetic, and accurate structure for glaucoma analysis. This system has been simulated on DRISHTI datasets. The exploratory outcomes indicates the proposed strategy performs well to the best with state-of-the-art methodologies accomplishing a 99% of Accuracy, 88% of Sensitivity and 95.5% of Specificity on the DRISHTI GS1 dataset individually.
Monitoring of The Impact of Road Salting On Spruce Forest Ecosystem In The Vicinity of The Highway D1 In The Bohemian-Moravian Highlands, Czech Republic
Authors: Hegrová Jitka , Prokeš Lubomír , Anděl Petr , Bucková Martina , Jandová Vilma , Effenberger Karel , Ličbinský Roman 
Published: June 2021

Abstract
Monitoring of pollution in the vicinity of roads connected to winter road maintenance is one of the important tools for optimising winter maintenance technology and reducing its environmental impact. The aim of this study was to determine the relationship between winter road maintenance and the increased concentration of sodium ion to characterize the harm caused by the de-icing agents on selected types of individual components grown in the Norway Spruce ecosystem. The model area is located in the immediate vicinity of the D1 motorway connecting Prague and Brno (Czech Republic), at 103rd kilometer. The area is thus exposed to long-term contamination from automobile transport and the monitoring was carried out for three consecutive years. A clear effect of the de-icing agents on conifers near the road has been demonstrated by the symptoms of salt damage visually observed in close proximity to the road (at a sampling distance of 5 m). The needles of these spruce trees also showed increased sodium concentrations, regardless of the age of the needles. The study also confirms that sodium accumulates in all selected components of the analysed ecosystem (moos, humus, soil). The sodium concentration has been found to decrease with increasing distance from the road for all of the components.
Effect of Family Cohesion On Symptom Distress During Hematopoietic Stem Cell Transplantation
Authors: Yang Yesol , Pan Wei , Farag Sherif S , Von Ah Diane 
Published: June 2021

Abstract
Purpose: Family may play an important role in Hematopoietic stem cell transplantation (HSCT) recovery; however, little is known about the effect of family functioning on an individual’s health. The purpose of this study was to examine the effect of family cohesion (family functioning) on the trajectory of HSCT recipients’ symptom distress (symptom frequency and symptom bother) before, during, and after HSCT. Methods: Secondary analysis was conducted using data collected from178 individuals who underwent HSCT. Longitudinal parallel-process (LPP) modeling was used to examine how family cohesion and HSCT associated symptoms (symptom frequency and symptom bother) change over time; and how these longitudinal changes relate to each other. Results: The trajectory of family cohesion predicted the trajectories of HSCT associated symptom frequency and bother. HSCT recipients who experienced higher family cohesion at baseline (T1) showed lower symptom frequency (p<.01) as well as symptom bother (p<.01) at T1. This trajectory analysis also showed that HSCT recipients who had improved family cohesion over time reported decrease in symptom frequency (p<.01) as well as bother (p<.01) over time. Conclusion: Findings indicate that higher family cohesion predicts decrease in symptom distress over the HSCT trajectory. Interventions aimed at enhancing family cohesion have the potential to lower HSCT recipients’ symptom distress. Further research is needed to understand the critical role of family cohesion and family functioning and their relationship with HSCT symptom distress prevention, early detection, and risk stratification.
Multi-Watershed Nonpoint Source Pollution Management Through Coupling Bayesian-Based Simulation And Mechanism-Based Effluent Trading Optimization
Authors: Xu Xiaomei , Zeng Xueting , Li Yongping , Wang Chunrong , Yu Lei , Huang Guohe , Zhang Junlong , Feng Juan , Han Xinyu 
Published: June 2021

Abstract
Multiple rivers flowing into the same bay can be correlated in water quality management and together determine the environmental status of the bay. Nonpoint source pollution management for multi-watershed aiming to alleviate environmental contamination can be under additional challenges and yield considerable economic and environmental benefits. In this study, a Bayesian simulation-based multi-watershed effluent trading designing model (BS-METM) is established for multi-watershed nonpoint source pollution management through incorporating techniques of water quality simulation, uncertainty analysis with Bayesian inference, optimal design for effluent trading, as well as mechanism analysis. BS-METM is capable of reflecting parameter uncertainties in nutrient simulation, disclosing the detailed optimal trading schemes under the impact of uncertainties and vital factors, and identifying optimal effluent trading mechanisms through revealing interaction among trading processes of multiple watersheds. BS-METM is applied to a real case of adjacent coastal watersheds (i.e. Daguhe and Moshuihe watersheds), which are identified as major sources of total phosphorus and ammonia nitrogen loadings to Jiaozhou Bay, China. Effluent trading optimization under multiple mechanisms, including intra-watershed trading, cross-watershed trading and non-trading, are conducted. The optimized industry scales and trading processes are obtained. The effects of vital factors on the trading process (i.e. environmental allowance-violation risk level and water availability level) are investigated. The interactions between water availability level and trading mechanism are also analyzed. It is proved that non-trading mechanism would be recommended under low water availability level and cross-watershed trading mechanism would be recommended under medium and high water availability level. The results provide a solid scientific basis for nonpoint source pollution management as well as effective sustainable development for multi-watershed region.