bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pain Catastrophizing Predicts Opioid and Health-Care Utilization After Orthopaedic Surgery
Authors: Rhon Daniel I. , Greenlee Tina A. , Carreño Patricia K. , Patzkowski Jeanne C. , Highland Krista B. 
Published: June 2022

Background:
Most individuals undergoing elective surgery expect to discontinue opioid use after surgery, but many do not. Modifiable risk factors including psychosocial factors are associated with poor postsurgical outcomes. We wanted to know whether pain catastrophizing is specifically associated with postsurgical opioid and health-care use.

Methods:
This was a longitudinal cohort study of trial participants undergoing elective spine (lumbar or cervical) or lower-extremity (hip or knee osteoarthritis) surgery between 2015 and 2018. Primary and secondary outcomes were 12-month postsurgical days’ supply of opioids and surgery-related health-care utilization, respectively. Self-reported and medical record data included presurgical Pain Catastrophizing Scale (PCS) scores, surgical success expectations, opioid use, and pain interference duration.

Results:
Complete outcomes were analyzed for 240 participants with a median age of 42 years (34% were female, and 56% were active-duty military service members). In the multivariable generalized additive model, greater presurgical days’ supply of opioids (F = 17.23, p < 0.001), higher pain catastrophizing (F = 1.89, p = 0.004), spine versus lower-extremity surgery (coefficient estimate = 1.66 [95% confidence interval (CI), 0.50 to 2.82]; p = 0.005), and female relative to male sex (coefficient estimate = −1.25 [95% CI, −2.38 to −0.12]; p = 0.03) were associated with greater 12-month postsurgical days’ supply of opioids. Presurgical opioid days’ supply (chi-square = 111.95; p < 0.001), pain catastrophizing (chi-square = 96.06; p < 0.001), and lower extremity surgery (coefficient estimate = −0.17 [95% CI, −0.24 to −0.11]; p < 0.001), in addition to age (chi-square = 344.60; p < 0.001), expected recovery after surgery (chi-square = 54.44; p < 0.001), active-duty status (coefficient estimate = 0.58 [95% CI, 0.49 to 0.67]; p < 0.001), and pain interference duration (chi-square = 43.47; p < 0.001) were associated with greater health-care utilization.

Conclusions:
Greater presurgical days’ supply of opioids and pain catastrophizing accounted for greater postsurgical days’ supply of opioids and health-care utilization. Consideration of several modifiable factors provides an opportunity to improve postsurgical outcomes.

Level of Evidence:
Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
The combined application of antibiotic-loaded bone cement and vacuum sealing drainage for sternal reconstruction in the treatment of deep sternal wound infection
Authors: Jiang Xia , Xu yong , Jiao GUOqing , Jing Zhaohui , Bu Fanyu , Zhang Jie , Wei Liuyan , Rong Xiaosong , LI Mingqiu 
Published: June 2022

Abstract
Background: Deep sternal wound infection (DSWI) is a rare but serious complication after median sternotomy, and treatment success depends mainly on surgical experience. Traditional treatment methods for DSWI include complete debridement, vacuum sealing drainage wound therapy and sometimes transposition of muscle flap. This study aimed to evaluate the utility of antibiotic-loaded bone cement combined with vacuum sealing drainage on DSWI and explore the effect of this treatment on lung function.Methods: Between January 2018 and December 2019, We treated 12 patients suffering a mediastinitis and open thorax using antibiotic-loaded bone cement combined with vacuum sealing drainage. Subsequently, the blood and local concentration of antibiotic were measured. The patient characteristics, pulmonary function, were retrospectively analyzed. Subjects were followed up for 12 months. Results: There were no intraoperative deaths. All patients’ healing wounds were first-stage healing without complications and reoperation, the mean hospital stay was 20.2±3.5 days. Local vancomycin concentrations largely exceeded the ones needed for their efficacy while little antibiotic was found in the blood. Pulmonary function testing was improved 2 weeks after the operation. No infection reoccurred in12-month follow-up.Conclusions: The antibiotic-loaded bone cement combined with vacuum sealing drainage might be an effective method for the sternal reconstruction of deep sternal wound infection and it can improve the patient's lung function in a short time.
Small nodules (≤ 6 mm in diameter) of multiple primary lung cancers: Prevalence and management
Authors: Cheng Hua , Li Wenhao , Li Xiaojian , Zhong Hongcheng , Wang Xiaojin , Lin Yujing , Liu Xueguo , Wu Xiangwen , Cao Qingdong 
Published: June 2022

Abstract
Background: Synchronous multiple primary lung cancers associated with small non-dominant nodules are commonly encountered. However, the incidence, follow-up, and treatment of small non-dominant tumors have been but little studied. We explored the prevalence and management of small non-dominant tumors and factors associated with interval growth.Methods: This observational, consecutive, retrospective single-center study enrolled patients diagnosed with synchronous multiple primary lung cancers and small non-dominant tumors (≤ 6mm in diameter) who underwent resection of the dominant tumor. The incidence, follow-up, and management of small non-dominant tumors and predictors of nodule growth were analyzed. Results: There were 88 patients (12% of all lung cancer patients) with pathological diagnoses of synchronous multiple primary lung cancers. A total of 131 (18%) patients were clinically diagnosed with at least one small (≤ 6 mm in diameter) multiple primary lung cancer non-dominant tumor. 94 patients with 125 small-nodule non-dominant tumors clinically diagnosed as multiple primary lung cancers were followed-up for at least 6 months. A total of 29 (29/125, 23.2%) evidenced small pulmonary nodules (≤ 6 mm in diameter) that exhibited interval growth on follow-up computed tomography (CT). On multivariate analysis, a part-solid nodule (compared to a pGGN) (OR 1.23; 95% CI 1.08–1.40) or a solid nodule (compared to a pGGN) (OR 3.50; 95% CI 1.94–6.30) predicted small nodule interval growth.Conclusions: We found a relatively high incidence of multiple primary lung cancers with small non-dominant tumors exhibiting interval growth on follow-up CT, suggesting that resection of non-dominant tumors at the time of dominant tumor resection, especially when the nodules are part-solid or solid, is the optimal treatment.
Identification of SNP of VDR and VDBP gene and its Dysregulated pathway through VDR-VDBP interaction network analysis in Vitamin D deficient Infertile Females
Authors: Rubab Zil e , Ashraf Mussarat , Naz Sumaira , Shahid Saba , Rehman Rehana 
Published: June 2022

Abstract
Research QuestionIs there an association of single nucleotide polymorphism (SNP) of VD Binding Protein (VDBP), VD receptor (VDR) with the dysregulated pathways and gene enrichment of VDR-VDBP in VD defecient unexplained infertile females ?DesignA cross sectional study was conducted on VD deficient ; fertile and unexplained infertile female subjects. VDBP and VDR were assessed by Enzyme Linked Immuno Assay and genotyping performed. FunRich version 3.1.3 employed for analysis of the identified proteins: VDR and VDBP a with their mapped gene data sets, enrichment and protein–protein interaction (PPI) network.ResultsThe mean VD values of infertile females were lower than fertile females (p=0.006). The mean VDR values of infertile females 27.32 ± 7.45 was less than fertile females 41.25 ± 8.1 (p<0.001). Levels of VDBP in infertile females [Median (IQR)]; [296.05 (232.58 – 420.23)] were lower than fertile females [ 469.9 (269.57 – 875.55)], (p=0.01).On sequence analysis a mutation rs 4588 SNP (Thr 436 Lys) was found in exon 11 of VDBP gene of infertile females and no mutation was found in exon 8 and 9 of VDR gene, however some intronic variants which were insignificant. The proteins: plasma membrane estrogen receptor signalling pathway (p ˂ 0.001) . VDR, SMAD3, NCOR1, CREBBP, NCOA1, STAT1, GRB2, PPP2CA, TP53 and NCOA2 were enriched after biological pathway grouping when VDR was made focused gene and directly interacting with VDBP .ConclusionUnexplained infertile females exhibited significantly low VD, VDBP and VDR. Plasma membrane estrogen receptor signaling pathway was enriched in VDD infertile females.
Using Game Theory to Identify Critical Watersheds based on Environmental Flow Components and Hydrological Indicators
Authors: Khiavi Ali Nasiri , Mostafazadeh Raoof , Talouki Fatemeh Ghanbari 
Published: June 2022

Abstract
Improper use of water resources has caused significant changes in Natural River Flow (NRF), which indicates the need to assess changes in Hydrological Indicators (HI) and Environmental Flow Components (EFC). Therefore, the present study was conducted to identify critical watersheds using HI and EFC under the influence of the dam and without the impact of the dam using the Borda Scoring Algorithm (BSA) based on Game Theory (GT) in Nir-Chay, Balkhlou-Chay and Qareh-Sou Rivers as consequent stations in northern Iran. Indicators of Hydrological Alteration (IHA) software was used to quantify river flow indices. 26 HI and 21 EFC have been quantified and were used to identify critical watersheds. Principal Component Analysis (PCA) was used to determine the most significant indicators. After the data reduction, the initial matrix and comparative preferences of Game Theory (GT) were used, and the scores were assigned to watersheds based on Borda Scoring Algorithm (BSA). Based on the results, it can be said that in the Doost-Beiglou watershed, the small flood peak in the pre-dam period was 14.08, which was reduced to 3.5 in the post-dam period. As a concluding remark, in the watersheds of Pol-e-Almas and Doost-Beiglou, which were affected by Yamchi and Sabalan dams, significant changes were observed in HI and EFCs. Therefore, in terms of NRF, Balkhlou-Chay and Qareh-Sou Rivers were categorized as critical conditions, which highlights the importance of these watersheds for managers and decision-makers in making optimal decisions.
Study on evaluation system of collaborative governance degree of universities in the GBA based on AHP and FCE
Authors: Shiqian Gu , shuxian Hao , Hongfei Guo 
Published: June 2022

Abstract
Under the background of national strategy and policy, the key to support Guangdong-Hong Kong-Macao Greater Bay Area (GBA)’s construction is the main role of active governance of colleges and universities. How to play the main role and promote the governance of colleges and universities in GBA has gained extensive attention. For catching up on the missing of the evaluation system of university collaborative governance degree in GBA and promote the improvement of university collaborative governance in GBA, this paper puts forward a new university collaborative governance path model in GBA, and establishes a relatively perfect evaluation system framework of university collaborative governance degree in GBA. By collecting a large number of 2754 questionnaires in GBA, Then the Analytic Hierarchy Process (AHP) is used to determine the weight of each level index of the collaborative governance degree of colleges and universities in GBA. According to the data, the Fuzzy Comprehensive Evaluation method (FCE) is used to evaluate the current collaborative governance degree of colleges and universities in GBA. Finally, detailed improvement suggestions are given on the weak links. Based on the evaluation results, this paper concludes that the improvement order of the current collaborative governance degree of universities in GBA is the collaboration between the government and universities, the market and universities, the internal collaboration between universities, and the society and universities, We should focus on optimizing the power of the Development Advisory Committee of colleges and universities and promoting the innovation of higher education system and mechanism in an all-round way. Using this method, we can accurately evaluate the current situation of university collaborative governance in GBA from both qualitative and quantitative aspects, and provide a scientific basis for improving the degree of university collaborative governance in GBA.
Segmentation of Restored Colour Texture Images Using MRF with Cellular Automata and Colour Block Matching 3D Algorithms
Authors: Kinge Sanjaykumar Ramchandra , Rani B. Sheela , Sutaone Mukul 
Published: June 2022

Abstract
Role of texture segmentation is vital due to its diversified applications in image analysis and understanding. Noise is an integral part of measurements and affects the performance of segmentation algorithms. Recently, researchers have initiated the work on noisy textures to address automatic quality evaluation of fruits and vegetables, diagnosis of thyroid cancer images, recognition of facial expressions, texture-based image retrieval and texture analysis, after restoring the noisy images. With these motivations, benchmark images from the Prague and Brodatz texture dataset are tainted with salt pepper and Gaussian noise and restored using recent cutting edge performance algorithms. A novel Markov Random Field based approach using a custom Median filter is developed for segmentation of restored texture images. A maximum improvement of 16% segmentation accuracy for salt pepper noise with 70% noise density and 15.1% accuracy for Gaussian noise with variance 50 has been achieved over recent approaches on Brodatz textures. An improvement of 8% accuracy for Gaussian noise with variance 50 and 4.47% accuracy improvement for salt pepper with 70% noise density is achieved on Prague texture benchmark images. The proposed approach can be applied for satellite and medical image analysis, industrial applications, remote sensing.
Characterization of drilling cuttings generated in oil and gas pre-salt drilling activities and leaching studies of contaminants present in these samples employing saline and aqueous solutions
Authors: Soares Andréia Silveira Freire , Marques Mônica Regina da Costa , Costa Luciana da Cunha 
Published: June 2022

Abstract
This article describes the characterization of pre-salt drilling cuttings generated during offshore activities. Samples were submitted to leaching by employing saline and aqueous solutions to evaluate the leaching of contaminants in marine and aqueous environments. The results of tests on samples indicated that some of the heavy metals had high levels of contamination. The metals present in the highest concentrations in saline and aqueous leachates were Si and Ba. Probably, the presence of Ba in the leachates was associated with leaching of barite. The metals Cd, Cu, Ni and Zn were present in varied concentrations in the saline leachates, and the metals Si, Ba, Cu and Zn were found in the aqueous leachates. There was a tendency of higher concentration of TOC in saline leachates derived from samples containing aqueous-based fluids, which may be related to the greater leaching tendency of polymers and emulsifiers in this medium.
Flood Hazard Assessment using Morphometry in Geospatial Environment
Authors: Ahad Ummar , Ali Umair , Ali Syed Ahmad 
Published: June 2022

Abstract
Morphometric analysis has been applied in flood assessment in selective catchment damaged in 2014 Kashmir flood. Sukhnag-Ferozpur catchment being located in hilly terrain of Kashmir basin, during heavy rainfall events all the water flows towards plainer low lying area causing floods in the urban areas along different drainage pathways. The drainage analysis of catchment helps to understand the physical behaviour with respect to floods. The sub-basins which contribute most in bringing floods in downstream plainer area were delineated. The analysis of 14 sub-basins (coded from SF1- SF14) reveal that SF1, 2, 5, 6, 7 and 8 lying in hilly terrain with high relief ratio (Rh), high drainage density (Dd), high ruggedness number (Rn), and less time of concentration (Tc) has greater peak discharge in a shorter time period to the plainer low lying areas. The low lying downstream area of SF10, 12, 13, and 14 are found most vulnerable to floods enhanced by other factors like anthropogenic activities, chaotic construction on the banks of waterways, and death of drainage streams. The mud and silt coming with flood water ultimately causes siltation problems to population and other aspect of life in low lying areas. The other ill effects of siltation with time leads to river course change, rise in bed level, change in rate of flow, and occurrence of frequent floods in the area. Thus, systematic evaluation of morphometric parameters using DEM in Geospatial environment helps to assess the flood behavior of catchment and apply suitable mitigation measures to reduce the hazard.
WITHDRAWN: A transferable force field for gallium nitride crystal growth from the melt using on-the-fly active learning
Authors: Clancy Paulette , Chen Xiangyu , Shao William , Le Nam 
Published: June 2022

Abstract
Atomic-scale simulations of reactive processes have been stymied by two factors: the general lack of a suitable semi-empirical force field on the one hand, and the impractically large computational burden of using ab initio molecular dynamics on the other. In this paper, we use an “on-the-fly” active learning technique to develop a non-parameterized force field that, in essence, exhibits the accuracy of density functional theory and the speed of a classical molecular dynamics simulation. We developed a force field suitable to capture the crystallization of gallium nitride (GaN) using a novel additive manufacturing route and a combination of liquid Ga and ammonia gas precursors to grow GaN thin films. We show that this machine learning model is capable of producing a transferable force field that can model all three phases, solid, liquid and gas, involved in this additive manufacturing process. We verified our computational results against a range of experimental measurements and ab initio molecular dynamics simulation, showing that this non parametric force field shows excellent accuracy as well as a computationally tractable efficiency. The development of this transferable force field opens the opportunity to simulate liquid phase epitaxial growth more accurately than before, analyze reaction and diffusion processes, and ultimately establish a growth model of the additive manufacturing process to create gallium nitride thin films.
Concrete Compressive Strength Prediction Using Machine Learning Algorithms
Authors: Turkey Firas Abed. , Beddu Salmia Bt. , Ahmed Ali Najah , Al-Hubboubi Suhair 
Published: June 2022

Abstract
The most widely utilized construction material is concrete. Concrete's physical qualities differ depending on the kind. In this paper, we predicted the compressive strength of four types of lightweight aggregate geopolymer concretes (LWAGC), namely, lightweigh expanded clay Leca, recycled foam masonry aggregate RFA, Porcelanite aggregate PA and recycled brick aggregate RBA. For predictions, we used seven models, specifically, Artificial Neural Network (ANN), Convolutional Neural Network (CNN), Long Short Term Memory (LSTM), Decision Tree (DT), Random Forest (RF), Support Vector Regressor (SVR) and Linear Regression (LR). For evaluation, we employed six metrics, Root Mean Square Error (RMSE), Mean Squared Logarithmic Error (MSLE), Mean Square Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Logarithmic Error (RMSLE) and Coefficient of Determination R². The results of predictions demonstrate that RF offers high accuracy for Leca type (MSE= 2,6697; RMSE= 1,6339; MSLE= 0,0072; RMSLE= 0,0851; MAE= 1,3434; R²=0,8687), Porcelanite type (MSE= 2,9650; RMSE= 1,7219; MSLE= 0,0065; RMSLE= 0,0805; MAE= 1,5693; R²=0,8437) and RFA type (MSE= 1,7028; RMSE= 1,3049; MSLE= 0,0059; RMSLE= 0,0768; MAE= 1,1300; R²=0,8099) because the predictions are closer to the real values, and DT offers better predictions than other models for RBA type (MSE= 3,3069; RMSE= 1,8185; MSLE= 0,0066; RMSLE= 0,0812; MAE= 1,5610; R²=0,8764). İn order to test the models in predicting new value we gave them a 675° as new temperature and we found that that LR is more accurate than other models in predicting the CS of Leca, RBA and Porcelanite types. However, CNN outperformed other models in predicting RFA type.
IUNet-UCD: Improved U-Net with weighted binary cross-entropy loss function for urban change detection of Sentinel-2 satellite images
Authors: Gomroki Masoomeh , Hasanlou Mahdi , Reinartz Peter 
Published: June 2022

Abstract
Detecting changes in urban areas have always been an important element of urban planning and resource management. With the widening impacts of human activities on the ground terrain and landscapes, in recent decades the analysis of remote sensing data, including satellite images, has become a method of choice for rapid tracking of changes in the ground surface over wide geographical areas. However, this approach requires automated and semi-automated methods with the ability to detect changes in remote sensing data. In this study, Sentinel-2 satellite images taken in 2017 and 2021 were used for binary change detection in urban areas of ​​northern Iran. This change detection was performed with a supervised deep learning method, which was used to generate a detailed change map of the area. Considering the generally good performance of convolutional neural networks in change detection applications, this study used an improved U-net with a weighted binary cross-entropy loss function, this function considers unequal weights for positive and negative targets so it performs better in detecting changes in complex urban areas especially small changes rather than binary cross-entropy. In addition to Sentinel-2 satellite images of northern Iran, Onera Satellite Change Detection (OSCD) dataset was also used to evaluate our proposed method. Experimental results showed the good performance of the method on both datasets, with the accuracy and F1score of final change maps reaching above 97%.
Establishment Of A Novel Glycolysis-Immune-Related Diagnosis Gene Signature For Endometriosis By Machine Learning
Authors: Chen Qizhen , Jiao Yufan , Yin Zhe , Fu Xiayan , Guo Shana , Xiang Jun , Wang Yanqiu 
Published: June 2022

Abstract
Purpose: The objective of this study was to investigate the key glycolysis-related genes linked to immune cell infiltration in endometriosis and to develop a new endometriosis(EMS) predictive model.Methods: A training set and a test set were created from the NCBI GEO public database. We identified five glycolysis-related genes using LASSO and the Random Forest method. Then we developed and tested a prediction model for EMS diagnosis. The method CIBERSORT was used to compare the infiltration of 22 different immune cells. We looked into the relationship between key glycolysis-related genes and immune factors in eutopic endometrial of women with endometriosis. Besides, GO-based semantic similarity and logistic regression model analyses were used to investigate core genes.Results: The five glycolysis-related hub genes (CHPF, CITED2, GPC3, PDK3, ADH6) were used to establish a predictive model for EMS. In the training and test set, the AUC of the ROC prediction model was 0.777, 0.824, and 0.774, respectively. Additionally, there was a remarkable difference in the immune environment between EMS and control. Conclusion: The glycolysis-immune-based predictive model was established to forecast EMS patients’ diagnosis, and a detailed comprehension of the interactions between endometriosis, glycolysis, and the immune system, may be vital for the recognition of potential novel therapeutic approaches and targets for EMS patients.