bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genomic Machine Learning Model Predicts Radiation Therapy Benefit in Early-Stage Breast Cancer Patients with High Accuracy
Authors: Badal Kimberly , Foster Jerome E. , Haraksingh Rajini , John Melford 
Published: January 2022

Abstract
BackgroundRadiation therapy (RT) is frequently recommended for post-surgery treatment of early-stage breast cancer (BC) patients, though not all benefit. Clinical factors currently guide RT treatment decisions. At present, models to predict RT-benefit predominantly use statistical methods with modest performance. In this paper we present a high-accuracy genomic Machine Learning (ML) model to predict RT-benefit in early-stage BC patients. We also present a novel method for selecting genomic features for training ML algorithms. MethodsGene expression data from 463 early-stage BC patients treated with surgery and RT from the METABRIC cohort were obtained. Wilcoxon Rank Sum (Wilcoxon RS) test and Cox Proportional Hazards (Cox PH) were used to reduce the number of genes used to train eight ML algorithms. ML algorithms were trained on 80% of data using 10-fold cross validation and tested on 20% of data to assess performance in predicting relapse status. Results Genome-wide gene expression data was reduced by 96% using Wilcoxon RS and Cox PH to a 1,596 gene set and a 977 gene set. These gene sets were used to train eight ML algorithms resulting in models that ranged in performance accuracies from 54.01% to 95.6%. Highest accuracies were obtained using Support Vector Machine (SVM977–93.41%, SVM1596–95.6%) and Neural Networks algorithms (NN977 – 92.31%, NN1596 – 93.41%). In RT-untreated patients, accuracies of all models were 30% to 40% lower compared to RT-treated patients. SVM977 had the highest sensitivity of 91.09%. Members of the 977 set were enriched with genes involved in cell cycle and differentiation as well as genes associated with radiosensitivity and radioresistance. Conclusion This study presents a novel genomic feature selection approach that used Wilcoxon RS followed by Cox PH to reduce the number of genes from genome-wide gene expression data used for training ML algorithms by 96%. This approach led to an SVM model that used the expression values of 977 genes to predict RT-benefit in early-stage BC patients with 93.41% accuracy. This work demonstrates that ML models can be clinically useful for predicting cancer patient outcomes.
Einstein-Roscoe Regression for the Slag Viscosity Prediction Problem in Steelmaking
Authors: Saigo Hiroto , Bahadur K.C. Dukka , Saito Noritaka 
Published: January 2022

Abstract
In classical machine learning, regressors are trained without attempting to gain insight into the mechanism connecting inputs and outputs. Natural sciences, however, are interested in finding a robust interpretable function for the target phenomenon, that can return predictions even outside of the training domains. This paper focuses on viscosity prediction problem in steelmaking, and proposes Einstein-Roscoe regression (ERR), which learns the coefficients of the Einstein-Roscoe equation, and is able to extrapolate to unseen domains. Besides, it is often the case in the natural sciences that some measurements are much more expensive than the others due to physical constraints. To this end, we employ a transfer learning framework based on Gaussian process, which allows us to estimate the regression parameters using the auxiliary measurements available in a reasonable cost. In experiments using the viscosity measurements in high temperature slag system, ERR is compared favorably with various machine learning approaches in interpolation settings, while outperformed all of them in extrapolation settings. Furthermore, after estimating parameters using the auxiliary dataset obtained at room temperature, increase in accuracy is observed in the high temperature dataset, which corroborates the effectiveness of the proposed approach.
The Combined Effects of Animal Products Intake and Physical Activity With Cause-specific and All-cause Mortality Among Patients With Type 2 Diabetes Mellitus in China: A Prospective Cohort Study
Authors: He Chenlu , Hou Hao , Pei Yifei , Chen Qian , Zhang Ying , Wang Jingjing , Tang Jie , Yan Na , Pan Enchun , Sun Zhongming , Lou Peian , Zhang Xunbao , Wang Wei 
Published: January 2022

Abstract
BackgroundTo determine the associations of animal products intake and physical activity and their combined effects with cause-specific and all-cause mortality among type 2 diabetes mellitus (T2DM) patients in China.MethodsBaseline data of 7311 type 2 diabetes mellitus (T2DM) patients recruited with a stratified random cluster sampling method were collected from December 2013 to January 2014. Participants were followed up until the date of their death or December 2019 for survivors, whichever came first. Nonlinear trends of cause-specific and all-cause mortality were assessed using restricted cubic splines with three knots placed at centiles 10, 50, and 90 of diet intake. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the combined relationship of physical activity and animal products with cause-specific and all-cause mortality.ResultsDuring a median follow-up of 6.1 years, 692 (9.5%) T2DM patients died. The main cause of death was cardiovascular disease (CVD) (35.8%), followed by cancer (20.6%). After multivariable adjustment, a higher level of physical activity was nonlinearly associated with lower all-cause and CVD mortality in a J-shaped pattern, with the protective effect observed >8 MET-h/d. Higher consumption of red meat, poultry, and aquatic products was associated with a lower risk of all-cause mortality (HR = 0.75, 0.64, 0.75, respectively, all P<0.05). In the highest tertiles of physical activity, a higher intake of red meat, poultry, and aquatic products was associated with a lower risk for all-cause mortality than in the lowest tertiles (red meat, HR = 0.80, 0.62, 0.51, and 0.48; poultry, HR = 0.85, 0.51, 0.48, and 0.45; aquatic products, HR = 0.80, 0.57, 0.55, and 0.40, respectively). Similarly, the protective effect of moderate to high intake of poultry, aquatic products, and eggs on CVD mortality in high physical activity was found. ConclusionsOur study highlights that in T2DM patients, better adherence to moderate to high consumption of animal products, including red meat, poultry, and aquatic products, together with engaging in moderate to high levels of physical activity exerts a beneficial effect in lowering cause-specific and all-cause mortality in China.
Practical Quinone-Based Organic Supercapacitor &gt; 6 V
Authors: Katsuyama Yuto , Takehi Takayuki , Sokabe Shu , Tanaka Mai , Ishizawa Mizuki , Abe Hiroya , Watanabe Masaru , Honma Itaru , Nakayasu Yuta 
Published: January 2022

Abstract
Inexpensive, high-performing, and environmentally friendly energy storage devices are required for smart grids that efficiently utilize renewable energy. Energy storage devices consisting of organic active materials are promising because organic materials, especially quinones, are ubiquitous and usually do not require harsh conditions for synthesis, releasing less CO2 during mass production. Although fundamental research-scale aqueous quinone-based organic supercapacitors have shown excellent energy storage performance, no practical research has been conducted. We aimed to develop a practical-scale aqueous-quinone-based organic supercapacitor. By connecting 12 cells of size 10 cm × 10 cm × 0.5 cm each in series, we fabricated a high-voltage (> 6 V) aqueous organic supercapacitor that can charge a smartphone at a 1 C rate. This is the first step in commercializing aqueous organic supercapacitors that could solve environmental problems, such as high CO2 emissions, air pollution by toxic metals, and limited electricity generation by renewable resources.
The Influence of the Geometrical Features on the Seismic Response of Historical Churches Reinforced by Different Cross Lam Roof-Solutions
Authors: Longarini Nicola , Crespi Pietro Giuseppe , Zucca Marco 
Published: January 2022

Abstract
Recent Italian earthquakes have shown the seismic vulnerability of many typical historical masonry churches characterized by one nave and wooden roofs. Under transverse earthquake the nave transverse response of this kind of churches can be influenced by the geometrical and material features. To increase the seismic performance, strengthening interventions aimed to pursue the global box-behavior by the realization of dissipative roof-structure represent a valid strategy especially for avoiding out-of-plane mechanisms. In this way, the roof structure must be able to represent a tool for the damped rocking of the perimeter walls. Cross-laminated timber panels (CLT) have been recently adopted as roof-diaphragm having shown valid ductile behavior in experimental tests, satisfying the conservative restoration criteria at the same time. In this paper, after a description of the numerical approach for the damped rocking mechanism for one nave configuration church, the effectiveness of different CLT based roof-diaphragms in the nave transverse response is investigated for four historical churches. The seismic responses are performed by comparative dynamic nonlinear analyses and the results are shown in terms of displacements and shear actions transferred to the façade. The influence of the geometrical features of the churches on the nave transversal response is deepened by sensitivity analyses with the aim to predict the displacements and shear variations under the same earthquake excitation.
Risk-Targeted Behavioral Activation for the Management of Work-Disability Associated with Co-Morbid Pain and Depression: A Feasibility Study
Authors: Sullivan Michael , Wideman Timothy H. , Gauthier Nathalie , Thibault Pascal , Ellis Tamra , Adams Heather 
Published: January 2022

Abstract
Purpose

The purpose of the present study was to conduct a preliminary evaluation the feasibility and impact of a risk-targeted behavioral activation intervention for work-disabled individuals with co-morbid pain and depression.
Methods

The design of the study was a single arm non-randomized trial. The sample consisted of 66 work-disabled individuals with co-morbid pain and depression. The treatment program consisted of a 10-week standardized behavioral activation intervention supplemented by techniques to target two psychosocial risk-factors for delayed recovery, namely, catastrophic thinking and perceptions of injustice. Measures of pain severity, depression, catastrophic thinking, perceived injustice and self-reported disability were completed pre-, mid-, and post-treatment. Satisfaction with treatment was assessed at post-treatment. Return to work was assessed at 6-month follow-up.
Results

The drop-out rate was 18%. At treatment termination, 91% of participants indicated that they were ‘very’ or ‘completely’ satisfied with their involvement in the treatment program. Significant reductions in pain (d = .71), depression (d = .86), catastrophic thinking (d = 1.1) and perceived injustice (d = 1.0) were observed through the course of treatment. In multivariate analyses, treatment-related reductions in depression, catastrophic thinking, perceived injustice, but not pain, contributed significant unique variance to the prediction of return-to-work outcomes.
Conclusions

Risk-targeted behavioral activation was found to be an acceptable and effective intervention for work-disabled individuals with co-morbid pain and depression. The findings suggest that interventions targeting psychosocial risk factors for pain and depression might contribute to more positive recovery outcomes in work-disabled individuals with co-morbid pain and depression.
Data-Driven Analysis In Magnetic Field-Assisted Electrical Discharge Machining of High Volume SiCp/Al
Authors: Xue Tao , Chen Long , Zhang Zhen , Zhao Jiaquan , Zhang Yi , Wen Dongxu , Wang Huachang 
Published: January 2022

Abstract
This paper presents a framework of data-driven intelligence system which can be applied on magnetic field-assisted electrical discharge machining (MF-EDM) machining process for SiC particulate reinforced Al-based metal matrix composites (SiCp/Al) with different high-volume fractions. The implemented system consists of data modelling, predicating, optimization and monitoring modules. A multi-objective moths search (MOMS) optimization algorithm with back-propagation neural network (BPNN) model and multi-hierarchy non-dominated strategy is proposed for tuning optimal processing performance. Data are collected from machining different fraction volumes of SiCp/Al composites by MF-EDM, with peak current, magnetic, pulse width and pulse interval time as input, and material removal rate, electrode wear rate, surface roughness as output. The BPNN model shows the best accuracy compared to K-nearest neighbours, least square support vector machine and Kriging model. To demonstrate the effectiveness of the MOMS optimization algorithm, a set of results is selected as paradigm, which dominates 95.83% original experiments. A verification experiment is also done for an optimized parameter with 65% fraction and 0.2T magnetic. Both result data and three-dimensional surface topography comparison show that the verification experiment result dominates the original experiment of similar input designs.
Implementation of A Perinatal Problem Identification Program (PPIP) In Zambia: A Feasibility Study
Authors: Mwamba Bupe , Ameyaw Edward K. , Singogo Marjory Malizyani 
Published: January 2022

Abstract
Background: Zambia is among the African countries with a high perinatal mortality rate. Though programs teaching medical practitioners about advanced neonatal resuscitation have reduced deaths and improved survival, more information is needed to further decrease morbidity and mortality in newborns. The objectives of this study was to implement a Perinatal Problem Identification Program (PPIP) to improve collection of information on early and late neonatal mortalities. Methods: The Perinatal Problem Identification Program was implemented in the Neonatal intensive Care unit of the Women and Newborn Hospital in Lusaka Zambia. The program started on 1 May 2019 and ended on 31 December 2019. Data entry was conducted and analysis was undertaken using the PPIP computer based software program. The PPIP software calculated neonatal deaths and their causes.Results: The Neonatal intensive care unit at women and newborn hospital recorded a total of 2640 deaths in 7 months from May 1st 2019 to 31st December 2019.The highest cause of death was prematurity with its complications at 126 (54%) in the sampled 238 recorded deaths. Followed by infection at 46 (19%) and hypoxia at 44 (18%). These deaths ranged from birth weights of less than 1000 grams to more than 2500 grams.Conclusion: The results reveal that it is possible to implement PPIP in Zambia and its use eases the audit review process, which combined with audit review meetings can improve the quality of care of neonates in the neonatal intensive care unit.
Association Between Microsatellite Instability and 18F-FDG PET/CT Data in Colorectal Cancer Patients
Authors: HASBEK ZEKİYE , DEMİR NECLA , YILMAZ MUKADDES , ÖZER HATİCE , ERTÜRK SEYİT AHMET , BABACAN ÖZGE ULAŞ 
Published: January 2022

Abstract
Aim: Our aim in this study was to evaluate the relationship between microsatellite instability (MSI) status and 18F-FDG PET/CT data in patients with colorectal cancer.Materials and Methods: Our study included 74 patients who underwent PET/CT in preoperative staging with the diagnosis of colorectal cancer and then underwent surgical resection. In the immunohistochemical examination, nuclear staining was considered positive for all antibodies. Normal colon mucosa and lymphocytes in tissue were used as an internal positive control group. The absence of nuclear staining in tumor cells was considered "loss" in "Mismatch Repair Gen" proteins. MSI status of patients was divided into 3 groups according to the occurrence of MLH1, PMS2, MSH2, MSH6 gene proteins, and also the number of MSI genes. It is defined as a high frequency of microsatellite instability (MSI-H) when two or more of the five markers in the tumor DNA were positive. If only one marker was positive, the tumor is termed as low frequency of MSI (MSI-L). And MSS is determined when all of the five markers were negative. Results: While MSI was not detected in 56 of the patients (75.7%), MSI was detected in 18 patients (24.3%). 4 patients (5.4%) had MSH-L, while 14 patients (18.9%) had MSH-H. In the analysis made considering all 3 groups, there was no statistically significant relationship between MSI status and SUVmax (p=0.835). Liver metastases were present in 11 (36.7%) of 30 patients who were metastatic at the time of diagnosis. Distant metastasis incidence was lower in 18F-FDG PET/CT in patients with MSI-H (p=0.010). In addition, a significant correlation was found between the presence of liver metastases and MSI, and liver metastasis was not observed in any of the 14 patients with MSI-H (p=0.041).Conclusion: Although not statistically significant, SUVmax values were found to be higher in patients with MSI-H. In addition, metastasis rates were found to be lower in patients with microsatellite instability in accordance with the literature data.
Temperature Dependence of The Thermo-Optic Coefficient In 4H-SiC and GaN Slabs At The Wavelength of 1550 nm
Authors: Rao Sandro , Mallemace Elisa Demetra , Cocorullo Giuseppe , Faggio Giuliana , Messina Giacomo , Corte Francesco Giuseppe Della 
Published: January 2022

Abstract
The refractive index and its variation with temperature, i.e. the thermo-optic coefficient, are basic optical parameters for all those semiconductors that are used in the fabrication of linear and non-linear opto-electronic devices and systems. Recently, 4H single-crystal Silicon Carbide (4H-SiC) and Gallium Nitride (GaN) have emerged as excellent building materials for high power and high temperature electronics, and wide parallel applications in photonics can be consequently forecasted in the near future, in particular in the infrared telecommunication band of λ=1500-1600 nm.In this paper, the thermo-optic coefficient (dn/dT) is experimentally measured in 4H-SiC and GaN substrates, from room temperature to 480 K, at the wavelength of 1550 nm. Specifically, the substrates, forming natural Fabry-Perot etalons, are exploited within a simple hybrid fiber–free space optical interferometric system to take accurate measurements of the transmitted optical power in the said temperature range. It is found that, for both semiconductors, dn/dT is itself remarkably temperature dependent, in particular quadratically for GaN and almost linearly for 4H-SiC.
Chronic Kidney Disease in a Large National Human Immunodeficiency Virus Treatment Program
Authors: Paengsai Ninutcha , Noppakun Kajohnsak , Jourdain Gonzague , Cressey Tim R. , Salvadori Nicolas , Chaiwarith Romanee , Tantraworasin Apichat , Mary Jean Yves , Bowonwatanuwong Chureeratana , Bhakeecheep Sorakij , Traisathit Patrinee , Kosachunhanun Natapong 
Published: January 2022

Abstract
Introduction:
Tenofovir disoproxil fumarate (TDF) is associated with a risk of chronic kidney disease (CKD), especially when used with protease inhibitors or in Asian populations. Data from the Thai national health insurance system were used to assess the incidence of CKD in patients receiving antiretroviral therapy (ART) in real-world practice.
Materials and methods
We analyzed data from patients who initiated one of the following first-line ART regimens: (i) zidovudine+lamivudine+nevirapine (AZT+3TC+NVP); (ii) zidovudine+lamivudine+efavirenz (AZT+3TC+EFV); (iii) tenofovir+lamivudine+nevirapine (TDF+3TC+NVP); (iv) tenofovir+lamivudine/emtricitabine+efavirenz (TDF+3TC/FTC+EFV); and (v) tenofovir+lamivudine+lopinavir/ritonavir (TDF+3TC+LPV/r). CKD was defined as glomerular filtration rate <60 mL/min/1.73 m2 for >3 months, or a confirmed 2010 WHO diagnosis (ICD-10 code N183, N184, or N185). Death competing risks survival regression models were used for the analysis.
Results
Among 27,313 participants, median age 36.8 years, body mass index 20.4 kg/m2, and absolute CD4 cell count 146 cells/mm3, followed for a median 2.3 years, 245 patients (0.9%) were diagnosed CKD (incidence 3.2 per 1,000 patient-years of follow-up; 95% confidence interval [CI] 2.8-3.6). Compared with patients receiving AZT+3TC+NVP, the risk of CKD measured by adjusted sub-distribution hazard ratio (aSHR) was higher in patients on TDF+3TC+LPV/r (6.5, 95% CI 3.9-11.1), on TDF+3TC+NVP (3.8, 95% CI 2.3-6.0) and on TDF+3TC/FTC+EFV (1.6, 95% CI 1.2-2.3). Among patients receiving TDF, compared with those receiving TDF+3TC/FTC+EFV, the risk was higher on TDF+3TC+LPV/r (4.0, 95%CI 2.3-6.8) on TDF+3TC+NVP (2.3, 95%CI 1.4-3.6) .
Conclusions
This real-world study suggest that the role of TDF in increasing the risk of CKD, especially when combined with LPV/r or NVP.
A Novel 2-Phase U-net Algorithm Combined with Optimal Mass Transportation for 3D Brain Tumor Detection and Segmentation
Authors: Lin Wen-Wei , Lin Jia-Wei , Huang Tsung-Ming , Li Tiexiang , Yueh Mei-Heng , Yau Shing-Tung 
Published: January 2022

Abstract
Utilizing the optimal mass transportation (OMT) technique to convert an irregular 3D brain image into a cube, a required input format for the U-net algorithm, is a brand new idea for medical imaging research. We develop a cubic volume-measure-preserving OMT (V-OMT) model for the implementation of this conversion. The contrast-enhanced histogram equalization grayscale of fluid attenuated inversion recovery (FLAIR) in a brain image creates the corresponding density function. We then propose an effective two-phase U-net algorithm combined with the V-OMT algorithm for training and validation. First, we use the U-net and V-OMT algorithms to precisely predict the whole tumor (WT) region. Second, we expand this predicted WT region with dilation and create a smooth function by convoluting the step-like function associated with the WT region in the brain image with a 5×5×5 blur tensor. Then, a new V-OMT algorithm with mesh refinement is constructed to allow the U-net algorithm to effectively train Net1--Net3 models. Finally, we propose ensemble voting postprocessing to validate the final labels of brain images. We randomly choose 1000 and 251 brain samples from theBraTS 2021 training dataset, which contains 1251 samples, for training and validation, respectively. The Dice scores of the WT, tumor core (TC) and enhanced tumor (ET) regions for validation computed by Net1--Net3 were 0.93705, 0.90617 and 0.87470, respectively. A significant improvement in brain tumor detection and segmentation with higher accuracy is achieved.
Defect levels coupled with oscillations and frustrated spins by Fe+3 in co-precipitated Aluminum ferrites
Authors: Dash Ritambhara , Gaurav Kumar , Kumari Neha , Kumar Prashant , Ranjan Saurabh , Bhagat Vikash , Bhattacharyya Arnab S 
Published: January 2022

Abstract
The degradation of organic dyes determines the suitability of a photocatalyst for wastewater treatments. Metal oxides like TiO2, ZnO, CuO, Fe2O3, Ce2O3, and Al-doped Ni Ferrites can degrade dyes. However, fine-tuning of physicochemical properties of the reaction system and characteristics of the reactor plays a significant role in making photocatalytic degradation a large-scale activity. The photoactivity gets altered by altering the Fe+3 ion concentration. The mechanism behind such changes has been addressed here, along with a unique magnetic property of frustrated spins observed.