bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validation of The Turkish Version of The Obstetric Quality-of-Recovery Score 11 (ObsQoR-11T) After Cesarean Delivery
Authors: OZKAN Gökhan , KARA Umut , INCE Mehmet Emin , Ozdemir Ozhan , Ulubay Mustafa , SENKAL Serkan 
Published: November 2022

Abstract
Background: To translate and validate the psychometric characteristics of a Turkish version of the Obstetric Quality-of-Recovery score 11 tool used to measure post-cesarean delivery recovery in Turkish-speaking patients.
Methods: After the original English version of the Obstetric Quality-of-Recovery score 11 tool was translated into Turkish, it was psychometrically validated to assess the post-cesarean delivery quality of recovery. Validity, reliability, and feasibility were investigated. The Obstetric Quality-of-Recovery score 11 tool was administered to Turkish-speaking patients on postoperative day 1. On postoperative day 1, a global health visual analog scale was used to assess the patient's perceived global recovery.
Results: One hundred and eighty-six patients completed their questionnaires, providing a completion rate of 97.35%. The Spearman rho (ρ) correlation coefficient between the Obstetric Quality-of-Recovery score and global health visual analog scale (0-100 points) was 0.850 at postoperative day 1 following surgery (P<0.001). Internal consistency, measured using Cronbach’s alpha, was 0.822. The split-half coefficient was 0.708. The Obstetric Quality-of-Recovery score differed significantly between the emergency and elective cesarean delivery groups (74.54±13.25 vs. 82.50±12.75; P<0.05). The test-retest reliability of the Obstetric Quality-of-Recovery score items was more than 0.6 in 82% of cases, indicating good repeatability and reliability.
Conclusion: The Obstetric Quality-of-Recovery score 11 is a valid and reliable tool to measure the post-cesarean quality of recovery in Turkish-speaking patients. The psychometric properties of the Turkish version of the scale to measure the post-cesarean quality of recovery were similar to those of the seminal English version.
Improved DEA model by quantifying the extreme degree of weight schemes
Authors: Wu Meiqin , Chen Ruixin , Fan Jianping 
Published: November 2022

Abstract
Data Envelopment Analysis (DEA) is a kind of nonparametric methodology used to evaluate different DMUs. DEA allows different DMUs to choose a set of weights that can maximize their efficiency score. Unfortunately, the flexibility in choosing weights is not only an advantage but also a source of disadvantages of DEA. To overcome the shortfalls of the traditional DEA model, a new DEA model based on quantifying the extreme degree of weights is proposed in this paper. The new model uses a pair of parameters and a set of inequalities to limit the selection range of weights. In order to get evaluation results independent of parameters, a novel method based on calculating the area under curve is proposed. Furthermore, the reasonableness of the new model is illustrated by comparing the results of a numerical example between the proposed model and the popular models. Finally, some conclusive remarks and suggestions are proposed for future research.
Comparative effectiveness of interventions for managing urological postoperative catheter-related bladder discomfort: a systematic review and network meta-analysis
Authors: Ren Jingwen , Ting YU , Tian Ye , Luo Guangheng 
Published: November 2022

Abstract
Background
Catheter-related bladder discomfort (CRBD) is a common postoperative bladder pain syndrome. Many drugs and interventions for managing CRBD have been studied, but their comparative effectiveness remains controversial. We made a study to assess the comparative effectiveness of interventions included Ketorolac, Lidocaine, Chlorpheniramine, Gabapentin, Magnesium, Nefopam, Oxycodone, Parecoxib, Solifenacin, Tolterodine, Bupivancaine, Dexmedetomidine, Hyoscine N-butyl bromide Ketamine, Penile nerve block on urological postoperative CRBD.
Methods
We performed a network meta-analysis (NMA) via ADDIS software included 18 studies with 1816 patients and assessed the risk of bias by Cochrane Collaboration tool. The incidence of moderate to severe CRBD at 0, 1, and 6 h after surgery and the incidence severe CRBD at 1h after surgery were compared. We ranked these interventions according outcomes.
Result
The number of best rank is 0.48(Nefopam) and 0.22(Nefopam) in the incidence of moderate to severe CRBD at 1h and incidence severe CRBD at 1h. More than half of studies at unclear or high risk of bias.
Conclusion
Nefopam ranked first in reducing incidence and severity of CRBD but with heterogeneity in study settings and outcome measures.
Estimating Medication Adherence from Electronic Health Records: Comparing Methods for Mining and Processing Asthma Treatment Prescriptions
Authors: Tibble Holly , Sheikh Aziz , Tsanas Athanasios 
Published: November 2022

Abstract
Background
Medication adherence is usually defined as the extent of the agreement between the medication regimen agreed to by patients with their healthcare provider and the real-world implementation. Proactive identification of those with poor adherence may be useful to identify those with poor disease control and offers the opportunity for ameliorative action. Adherence can be estimated from Electronic Health Records (EHRs) by comparing medication dispensing records to the prescribed regimen. Several methods have been developed in the literature to infer adherence from EHRs, however there is no clear consensus on what should be considered the gold standard in each use case.
Our objectives were to critically evaluate different measures of medication adherence in a large longitudinal Scottish EHR dataset. We used asthma, a chronic condition with high prevalence and high rates of non-adherence, as a case study.
Methods
Over 1.6 million asthma controllers were prescribed for our cohort of 91,334 individuals, between January 2009 and March 2017. Eight adherence measures were calculated, and different approaches to estimating the amount of medication supply available at any time were compared.
Results
Estimates from different measures of adherence varied substantially. Three of the main drivers of the differences between adherence measures were the expected duration (if taken as in accordance with the dose directions), whether there was overlapping supply between prescriptions, and whether treatment had been discontinued. However, there are also wider, study-related, factors which are crucial to consider when comparing the adherence measures.
Conclusions
We evaluated the limitations of various medication adherence measures, and highlight key considerations about the underlying data, condition, and population to guide researchers choose appropriate adherence measures. This guidance will enable researchers to make more informed decisions about the methodology they employ, ensuring that adherence is captured in the most meaningful way for their particular application needs.
Development and Validation of the Knowledge, Attitude, and Practice Questionnaire for Community Pharmacy Personnel in Tuberculosis Case Detection, Drug Monitoring, and Education
Authors: Kausar Mersa , Fitriana Efi , Khairunnisa Khairunnisa , Bahar Muh. Akbar , Alfian Sofa , pradipta Ivan , Faruque Md. Omar 
Published: November 2022

Abstract

Background
Validated and standardized structured questionnaires based on psychometric analysis are extremely limited, particularly for assessing community pharmacy personnel's knowledge, attitude, and practice (KAP) in tuberculosis (TB) case detection, drug monitoring, and education. We, therefore, developed and validated a questionnaire to assess the KAP of community pharmacy personnel in TB case detection, drug monitoring, and community education.
Methods
This study was conducted in two phases. First, we developed the questionnaire, which included framework development, item generation, item screening, and pre-testing. Second, we validated the questionnaire with 400 participants using various analyses, including participant analysis, individual item content validity index (I-CVI), confirmatory factor analysis (CFA), adjusted goodness-of-fit index (AGFI), comparative fit index (CFI), non-normed fit index (NNFI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR). We determined the reliability test using Cronbach’s alpha and test-retest reliability using Pearson’s correlation.
Results
In the development phase, we defined 63 items that comprised 18 sociodemographic, 18 knowledge, 18 attitude, and 9 practice items. Across the 63 items, the I-CVI scores of sociodemographic and KAP items were one each. The CFA model parameter values were X2 /df= 2.28; AGFI = 0.95; CFI = 0.99; NNFI = 0.98; RMSEA = 0.06; and SRMR = 0.03 (p < 0.05 for all). Cronbach’s alpha coefficients of KAP items were 0.75, 0.91, and 0.95, respectively. The test-retest reliability coefficients of KAP were 0.84, 0.55, and 0.91, respectively (p < 0.01).
Conclusion
This study indicates that the developed questionnaire is a valid and reliable instrument for assessing the KAP of community pharmacy personnel for TB case detection, drug monitoring, and community education. The questionnaire can identify further strategies to engage community pharmacies in TB prevention and care.
An Online Biased Signaling Atlas
Authors: Caroli Jimmy , Mamyrbekov Alibek , Harpsøe Kasper , Gardizi Sahar , Dörries Linda , Ghosh Eshan , Hauser Alexander , Kooistra Albert , Gloriam David 
Published: November 2022

Abstract
Biased signaling is a paradigm in signal transduction whereby hormones, probes, or drugs bind the same receptor but engage different intracellular signaling pathways leading to distinct functional outcomes. Whereas there is a wealth of knowledge of bias signaling, it is scattered throughout literature and the vast majority of signaling pathways still lack a biased tool compound and functional annotation. Here, we provide an online Biased Signaling Atlas (https://BiasedSignalingAtlas.org) letting any researcher swiftly navigate 9,000 ligand bias datapoints and 640 functional/therapeutic annotations of signaling pathways, analyze ligand-bias relationships, download machine learning-ready data, select tool compounds, and calculate consistent bias values. We invite the global community to together advance biased signaling by depositing its data into the shared repository. This provides a common hub for the global research community to jointly explore the principals of signal transduction and to translate mapped molecular mechanisms to design drugs with better efficacy and safety.
In situ synthesis of g-C3N4/TiO2 heterojunction by a concentrated absorption process for efficient photocatalytic degradation of tetracycline hydrochloride
Authors: Bi Renke , Liu Jialong , Zhou Chutong , Shen Yijie , Liu Zhe , Wang Zhiyu 
Published: November 2022

Abstract
A facile and feasible method was innovatively evolved to in-situ prepare g-C3N4/TiO2 heterojunctions through a high concentration absorption process, to satisfy the exigent requirements of an efficient, low-cost and environmental-friendly photocatalyst for massive antibiotic effluent treatment. This synthesis method was much easier and more rapid than the traditional routes, which can be primarily depicted as follows: the nitrogen precursors were uniformly dispersed on the amorphous hydrolysis product of titanium precursors (titanic acid or metatitanic acid) driven by a concentration gradient, and then, affording the heterostructure of granular TiO2 coupled with lamellar g-C3N4 through a calcination process. The effects of the one-step synthesis on the characteristics of g-C3N4/TiO2 nanocomposites were investigated by XRD, HRTEM, XPS, UV-vis DRS and PL, and the results demonstrated that the nanocomposites exhibited a well-defined micromorphology and enhanced photoabsorption capacity. For the degradation of tetracycline hydrochloride, the g-C3N4/TiO2 heterojunction displayed remarkably elevated photocatalytic activity over bare g-C3N4 and commercial TiO2 under simulated sunlight and visible light. The sample with 4 g of urea content was optimal, with photodegradation efficiencies 3.9 and 2 times higher than those of pure g-C3N4 and TiO2 respectively. Besides, photodegradation pathways based on the role of active species •O2− and •OH were identified by the trapping experiments, indicating that the substantial increase in photocatalytic efficiency can be credited to the construction of direct Z-scheme heterojunctions. This work has provided a novel in-situ synthesis approach to the heterostructure, which would open up new horizons for the rational design and the wide-scale application of high-performance photocatalysts for the photodegradation of antibiotic-based pollutants.
Pressure controlled ventilation versus pressure controlled ventilation - volume guaranteed in patients undergoing bariatric surgery: a randomized trial
Authors: Zhou Zhengyu , Wu Pan , Hua Rong , Yu Qiong 
Published: November 2022

AbstractBackground The optimal ventilation mode for patients with obesity undergoing laparoscopic surgery remains unclear. In this prospective randomized controlled study, the effects of two ventilation modes, pressure-controlled ventilation (PCV) and pressure-controlled ventilation - volume guaranteed (PCV-VG), on perioperative oxygenation and respiratory mechanics were compared in patients undergoing laparoscopic bariatric surgey. Methods A total of 110 subjects were randomly divided into PCV-VG group (n = 56) or PCV group (n = 54). The perioperative pulmonary mechanics and arterial blood gas results were compared between the two groups. Postoperative extubation time, the incidences of postoperative pulmonary complications (PPCs) and abnormal radiographic changes (ARCs) were also recorded. Results During intraoperative pneumoperitoneum, the respiratory dynamic compliance (Cdyn) was significantly lower in PCV-VG group than that in PCV group. There were no significant differences in perioperative oxygenation index and respiratory peak pressure (Ppeak) between the two groups. Eighty-six subjects (78.2%) had ARCs on the 1st day after surgery, only ten subjects (9.1%) developed PPCs. There was no significant difference in extubation time, ARCs or PPCs between the two groups. After adjustment, anesthesia duration and oxygenation index before anesthesia induction were significantly associated with extubation time. Anesthesia duration of more than 2 hours was a risk factor for postoperative radiographic abnormalities. Conclusions Compared with PCV-VG mode, PCV mode provides better pulmonary compliance during intraoperative pneumoperitoneum. Further large-sample studies are needed to determine the optimal ventilation mode in subjects with obesity undergoing laparoscopic surgery.
Has land resource misallocation increased air pollution in Chinese cities?
Authors: Xie Wancheng , Gao Wen , Zhang Ming 
Published: November 2022

Abstract
As a fundamental production factor for economic development, rational land allocation is not only relevant to economic development but also an important factor affecting urban air pollution. In this paper, 284 cities in China were selected as samples to analyze the impact of land resource misallocation on air pollution and the underlying mechanisms. The findings are as follows: First, land resources misallocation increases urban air pollution. Second, land resources misallocation inhibits technological innovation, government technology investment and foreign direct investment, thereby increasing local air pollution. Third, the impact of land resources misallocation on air pollution is affected by heterogeneous conditions such as geographic region, city type, and city size. Finally, based on the air pollution caused by land resources misallocation, local governments should not only optimize the land supply structure but also improve the environment for technological innovation and investment.
Persistent organic pollutants in hospitalized individuals in the municipality of Petropolis - Brazil
Authors: de Rezende Louise Moura , Rosa Ana Cristina Simões , Santos Sabrina da Silva , Monteiro Gina Torres Rego 
Published: November 2022

Abstract
Persistent organic pollutants (POPs) are highly lipophilic and can accumulate and biomagnify in food chains. Characterized as a public health problem, exposure to these compounds enables the development of diseases like cancer, cardiovascular disease, diabetes, and obesity. The objective of this study was to estimate the plasma levels of organochlorine pesticides and PCBs in hospitalized individuals in Petropolis, Brazil. Individuals over 18 years of age and residing for at least two years in the mountainous region of the State of Rio de Janeiro, Brazil, participated in a cross-sectional study. Interviews using a structured questionnaire and blood samples to estimate plasma levels of persistent organic pollutants provided data. Gas chromatography coupled with triple quadrupole mass spectrometry provided the levels of organochlorine pesticides and PCBs. Compared to data present in the literature, the concentration of POPs was lower, and individuals from 55 to 64 years of age (3.28 ng mL− 1) and women (2.52 ng mL− 1) presented a higher average concentration of organochlorine pesticides; men (0.05 ng mL− 1) also presented a high concentration of PCBs. This is the first Brazilian study to estimate the concentration of several POPs in a hospital-based sample that includes men and women, thus contributing to the characterization of our population regarding environmental exposures relevant to health.
Ionic Liquids: Environmentally Sustainable Materials for Energy Conversion and Storage Applications
Authors: Choudhary Gaurav , Dhariwal Jyoti , Saha Moumita , Trivedi Shruti , Banjare Manoj K. , Kanaoujiya Rahul , Behera Kamalakanta 
Published: November 2022

Abstract
Ionic liquids (ILs), known as green designer solvents, have shown tremendous application potential in various fields of science and technology. Their unusual and unique physicochemical properties have attracted researchers worldwide from interdisciplinary research areas. ILs possess high boiling point and low volatility, that makes them suitable environmentally benign candidates for many potential applications. The more important aspect associated with ILs is their physicochemical properties can be effectively changed for desired applications just by tuning the structure of the cationic and/or anionic part of ILs. Furthermore, these environmentally benign designer materials can be used as both electrolytes as well as solvents depending on the requirement. Owing to thedistinctive properties such as low volatility, high thermal and electrochemical stability, better ionic conductivity, ILs are nowadays immensely used in variety of energy applications, particularly in the development of green and sustainable energy storage and conversion devices. Suitable ILs are designed for specific purposesto be used as electrolytes and/or solvents for fuel cells, lithium-ion batteries, supercapacitors(SCs) and solar cells. Herein, we have highlighted the utilization of ILs as unique green designer materials in Li-batteries, fuel cells,SCs and solar cells. This review will enlighten the promising prospects of these unique environmentally sustainable materials for next-generation green energy conversion and storage devices.
Prediction and Early Warning Model of Mixed Exposure of Air Pollution and Meteorological Factors on Death of Respiratory Diseases Based on Machine Learning
Authors: Sun Hongying , Chen Siyi , Li Xinyi , Cheng Liping , Luo Yipei , Xie Lingli 
Published: November 2022

Abstract
In recent years, with the repeated occurrence of extreme weather and the continuous increase of air pollution, the incidence of weather-related diseases is increasing year by year. Air pollution and extreme temperature bring serious threats to the lives of sensitive groups, among which air pollution is most closely related to respiratory diseases. Owing to the skewed attention, timely intervention is necessary to better predict and warn the occurrence of death from respiratory diseases.In this paper, according to the existing research, based on a number of environmental monitoring data, the regression model is established by integrating the machine learning methods XGBoost, SVM and GAM model. The distributed lag nonlinear model (DLNM) is used to set the warning threshold to transform the data and establish the warning model. According to the DLNM model, the cumulative lag effect of meteorological factors is explored. There is a cumulative lag effect between air temperature and PM2.5, which reaches the maximum when the lag is 3 days and 5 days respectively. If the low temperature and high environmental pollutants (PM2.5) continue to influence for a long time, the death risk of respiratory diseases will continue to rise, and the early warning model based on DLNM has better performance.
Examination of one-dimensional S-wave velocity structure using strong-motion data for high-seismic-intensity area during 2018 Hokkaido Eastern Iburi earthquake
Authors: Nakagawa Naofumi , Takai Nobuo , Shigefuji Michiko 
Published: November 2022

Abstract
The Yufutsu Plain, a sedimentary basin surrounded by mountains, is located in the southern part of the Ishikari-Yufutsu Lowlands, Hokkaido, Japan. The Hidaka arc-arc collision zone, located in the eastern part of the Yufutsu Plain, forms the Hidaka Mountain range in central Hokkaido, with the Ishikari-Teichi-Toen Fault Zone of the Ishikari-Yufutsu Lowlands on the west side, which forms part of a major geological boundary that extends in the north-south direction. The 2018 Hokkaido Eastern Iburi earthquake (Mw 6.6) occurred at 03:08 JST on September 6, 2018, in this arc-arc collision zone. The K-NET HKD126 station in Mukawa Town, which is close to the severely damaged basin margin area, recorded strong-motion data with strong power for a period of 1–2 s during the main shock. The site amplification characteristics of the shallow S-wave velocity structure, which was estimated from microtremor array observations and surface wave explorations, were one of the causes of this strong ground motion. It is essential to accurately estimate the depth of the seismic bedrock and basin margin to evaluate the long period of large earthquakes. In this study, we used strong-motion data recorded at HKD126 and three temporary strong-motion stations near the basin margin area to tune the deep S-wave velocity structure. First, we performed microtremor array observations and surface wave explorations to estimate the S-wave velocity structure to a depth of 1 km beneath the station at the hill site because a detailed shallow structure is not available for this site. Then, with a combination of the estimated S-wave velocity structure and the existing structure, we tuned the deep structures based on an autocorrelation function analysis using strong-motion data. The validity of the estimated structures from the shallowest depth to the seismic bedrock was verified based on the observed arrival time and theoretical travel time differences for the S-wave initial motion. We estimated the seismic bedrock of the four stations to be at a depth of 7–10 km. In addition, an autocorrelation function analysis suggests topological basement irregularity.