bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel Composites Polymer Electrolytes Based on Methylcellulose-pectin Blend Complexed With Potassium Phosphate and Ethylene Carbonate
Authors: Adam Abdullahi Abbas , Soleimani Hassan , Shukur Muhammad Fadhlullah Bin Abd. , Dennis John Ojur , Hassan Yarima Mudassir , Abdulkadir Bashir Abubakar , Yusuf Jemilat Yetunde , Ahmed Omar Sami Sultan , Ayub Saba , Abdullahi Suleiman Shuaibu 
Published: July 2022

Abstract

In large-scale all-solid-state storage technologies, solid polymer electrolytes (SPEs) provide greater safety and longer cycle life than traditional liquid or gel polymer electrolytes. Polymer electrolytes (PEs) derived from biopolymers have been intensively explored for use in electrochemical devices due to their great flexibility, low cost, and environmental sustainability. However, biopolymer-based electrolytes cannot meet the expectations of practical applications at room temperature due to their low ionic conductivity. Over the years, improving the performance of this class of electrolytes has been the focus of intense research and development, notably polymer blending, plasticization, and structural functionalization. Here, we investigate the performance of an all-biopolymer solid electrolyte based on a methylcellulose-pectin blend doped with potassium phosphate. FESEM micrographs as well as the shifting and changing intensity of FTIR bands in the electrolyte specimens confirm the polyblend homogeneity with no phase separation. The increased amorphous fraction of the composites polymer electrolytes (CPEs) is seen in the XRD and DSC patterns of the plasticized and unplasticized samples. Impendence studies performed on the system recorded a maximum ionic conductivity of 1×10-5 Scm-1 by doping with 50 wt.% K3PO4. This value further increased to 5.9×10-5 Scm-1 upon adding 25 wt.% EC to the polymer system. This sample also possesses an electrochemical stability window of 4.24V and an ion transference number of 0.95.
High-throughput iSpinach fluorescent aptamer-based real-time monitoring of in vitro transcription
Authors: Qin Weitong , Li Liang , Yang Fan , Wang Siyuan , Yang Guangyu 
Published: July 2022

Abstract
In vitro transcription (IVT) is an essential technique for RNA synthesis. Methods for the accurate and rapid screening of IVT conditions will facilitate RNA polymerase engineering, promoter optimization, and screening for new transcription inhibitor drugs. However, traditional polyacrylamide gel electrophoresis (PAGE) and HPLC methods are labor intensive, time-consuming and not compatible with real time analysis. Here we developed an inexpensive, high throughput, and real-time detection method for the monitoring of in vitro RNA synthesis so-called STAR (iSpinach aptamer-based monitoring of Transcription Activity in Real-time). STAR has a detection speed at least 100 times faster than conventional PAGE method and provides comparable results in the analysis of in vitro RNA synthesis reactions. It also can be used as an easy and quantitative method to detect the catalytic activity of T7 RNA polymerase. To further demonstrate the utility of STAR, it was applied to optimize the initially transcribed region of the GFP gene and several variants were identified with obvious enhanced transcription output. STAR may provide a valuable tool for many biotechnical applications related to the transcription process, which may pave the way for the development of better RNA related enzymes and new drugs.
Observed Trends and Coherent Changes in Daily Rainfall Extremes over Greater Mumbai, 1985-2020
Authors: Mann Rohit , Gupta Anju , Dhorde Amit , Sharma Swati 
Published: July 2022

Abstract
Climate extremes are predicted to become more frequent and severe in the future, owing to rising green-house gas emissions in the atmosphere. Using appropriate trend indices, this study intends to analyze the effects of climate change on rainfall variability and extreme rainfall events in the millennium city of Mumbai. The analysis was carried out for the period 1985-2020 for 25 different stations that were picked using a distance-matrix method to simulate the study area's rainfall regime. To comprehend the trend and behavior of rainfall and extreme events, three statistical models were used: Mann–Kendall test, Sen's slope estimator, and simple linear regression; for abrupt change point detection, Pettitt's test, standard normal homogeneity test, Buishand's range test, and von Neumann ratio test were used. The results indicated that average annual rainfall in the study area is 2208.82 mm which is increasing at the rate of 5.18mm/year (at 99% confidence level). The frequency of heavy (>120mm/day) and extreme heavy rainfall events (250 mm/day) increased over Santacruz after 1994 and in case of Colaba, it increased after 2005. The examination of rainfall and temperature data series for abrupt change point identification suggests that several change points exist, with the highest change points occurring between 2001 and 2005. Extreme climate event scenarios shown here could have large-scale negative consequences for the ecosystem and ecological resources of the study area.
Establishment and validation of a postoperative predictive model for patients with colorectal mucinous adenocarcinoma
Authors: Wang Pengchao , Song Qingyu , Lu Ming , Xia Qingcheng , Wang Zijun , Zhao Qinghong , Ma Xiang 
Published: July 2022

Abstract
BackgroundThe aim of this study was to develop comprehensive and effective nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) rates in patients with colorectal mucinous adenocarcinoma (CRMA). MethodsA total of 4711 CRMA patients who underwent radical surgery between 2010 and 2018 from the Surveillance, Epidemiology, and End Results (SEER) database were collected and randomized into development (n=3,299) and validation (n=1,412) cohorts at a ratio of 7:3 for model development and validation. OS and CSS nomograms were developed using the prognostic factors from the development cohort after multivariable Cox regression analysis. The performance of the nomograms was evaluated using Harrell’s concordance index (C-index), calibration diagrams, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).ResultsThe study included 4,711 patients. Multivariate Cox regression analysis demonstrated that age, tumor size, grade, pT stage, pN stage, M stage, carcinoembryonic antigen, perineural invasion, tumor deposits, regional nodes examined, and chemotherapy were correlated with OS and CSS. Marital status was independently related to OS. In the development and validation cohorts, the C-index of OS was 0.766 and 0.744, respectively, and the C-index of CSS was 0.826 and 0.809, respectively. Calibration curves and ROC curves showed predictive accuracy. DCA showed that the nomograms had excellent potency over the 8th edition of TNM staging system with higher clinical net benefits. Significant differences in OS and CSS were observed among low-, medium-, and high-risk groups.ConclusionsNomograms were developed for the first time to predict personalized 1-, 3-, and 5-year OS and CSS in CRMA postoperative patients. External and internal validation confirmed the excellent discrimination and calibration ability of the nomograms. The nomograms can help clinicians design personalized treatment strategies and assist with clinical decisions.
Determination of antibiotic drug residues in milk and meat using different analytical methods: A review
Authors: Feleke Melaku Getahun , Abebe Rahel Belete , Sendekie Ashenafi Kibret , Woldeyohannis Alem Endeshaw , Kasahun Asmamaw Emagn 
Published: July 2022

Abstract
Veterinary antibiotics are used in livestock production for control of animal diseases and as growth promoter. The repeated application of veterinary drugs for animals may result the occurrence of residues at various concentration levels in animal derived food products. Veterinary antibiotic residue is defined as small amounts of antibiotics, or its active metabolites which persists in animal derived food products after applying it in animals for different purposes. In particular antibiotic residues occur due to extensive application of antibiotics in veterinary services produce complications not only in dairy and meat industry but also have extensive public health consequences. Deleterious effects of drug residues residing in animal derived food products may induce carcinogenic and mutagenic effects and leads to the condition of antimicrobial resistance and antimicrobial allergy in the individuals who consume animal derived food products. Accordingly, it is important to effectively control antibiotic residues in animal derived food products. For that reason, regulatory authorities have enacted maximum residue limits (MRLs) for a number of veterinary drugs in different animal derived food products (milk, eggs and meat). Performing effective monitoring program requires specific, sensitive and reliable analytical methods that can identify all veterinary drug residues under regulated levels (MRL).
Stratigraphic sequence and Deformation Style of the Part of a Geologically Complex Terrain, NW Himalayas, Pakistan
Authors: Farooq Majid , Khan Muhammad Yasin 
Published: July 2022

Abstract
The project area forms the outer rim of Northwestern Himalayan Syntaxis in Sub-Himalayan and Lesser Himalayan rock sequences of Hazara area, Pakistan. The detail scale studies may produce a well presentation of deformational style of structurally unexplored project area. The study deals with the stratigraphic sequence and structural style of geologically complex Himalayan Terrain. The Stratigraphic Formations mapped on ArcGIS 10.4 includes Precambrian to Cambrian unconformable rock sequences of Hazara Formation, Tanawal Formation and Abbottabad Formation intruded by a Paleozoic Manshera granite, Eocene Kuldana Formation and the Quaternary alluvium along drainage. The structural deformations includes folds such as Ghari Habibullah syncline, Ghari Habibullah overturned anticline, Besian overturned anticline and Balakot overturned anticline. The folds are either northwest-southeast trending or northeast-southwest trending, northeast or southwest vergent and close to tight in nature. The Main Boundary Thrust (MBT), Panjal Thrust (PT) and Balakot Bagh Fault (B-B fault) are regional faults, reverse and thrust as well as active in nature.
Clinical effects of combined anteversion and offset on postoperative dislocation in total hip arthroplasty
Authors: Matsuda Kenta , Nakamura Shigeru , Hidaka Ryo , Nakamura Masaki , Kawano Hirotaka 
Published: July 2022

Abstract
Background
Implant impingement and soft tissue tension are factors involved in dislocation after total hip arthroplasty (THA). Combined anteversion (CA) has been used as an indicator for implant placement; however, placing implants optimally remains challenging. Moreover, the effect of changes in offset on dislocation remains unclear. We aimed to clarify the effects of postoperative CA and pre- and postoperative changes in offset on dislocation.
Methods
We included patients who underwent primary cementless THA performed between 2013 and 2020. The mean values of CA and offset in the dislocation and non-dislocation groups were compared. The CA values within ± 10% of the recommended values were defined as good CA, and those outside the range were defined as poor CA. The dislocation rates in the good and poor CA groups and in the groups with and without increased offset were compared.
Results
A total of 283 hips were included. The mean values of CA in the dislocation and non-dislocation groups were significantly different (p < 0.001). The dislocation rate was significantly lower in the good CA group (p < 0.05). The dislocation rates in the groups with and without increased total offset were 0.5% and 4.3%, respectively (p = 0.004). There were no dislocations in patients with good CA and increased offset.
Conclusions
The dislocation rate was significantly lower when implants were placed within ± 10% of the recommended CA value. Our results suggest that dislocation can be avoided by placing the implant in the good CA range and considering the increase in total offset on the operative side.
Ex-situ Biological Removal of Nitrate from Groundwater with Sterile and Non-sterile Porous media (Lab Experiment and Simulation)
Authors: Samani Farideh Ansari , Tabatabaei Sayyed-Hassan , Abbasi Fariborz , Nourmahnad Negar , Rabiee Mohammad 
Published: July 2022

Abstract
Nitrate is potentially harmful in an aquatic environment however it can be converted into other forms by microbial activities. In this research, we tested the efficiency of nitrate removal by using a denitrification bed containing two porous media; sterile soil (SS) and non-sterile soil (NSS). A Marriott column which is making constant water flux and a Plexiglas column filled with a clay loam soil, respectively. Potassium nitrate used to make different nitrate concentrations including 24, 50 and 100 (mg l− 1). The nitrate was injected up to ten pore volumes (PV( .The solute transfer parameters were estimated by using soil hydraulic parameters at HYDRUS model. As result, the growth of bacteria and the concentration of pollutants in the output of the column decreased in SS media. In the NSS with a concentration of 100 mg/ l nitrate, the number of bacteria increased to the highest, 80000 bacterial number. The presence of rival anions in the solution has a negative impact on removal of nitrate. In NSS with nitrate concentration of 24 (mg l− 1), the removal nitrate efficiency nearly 99.5 (%). Sensitivity analyses demonstrated that saturated hydraulic conductivity had the greatest effect on the variations of nitrate concentration. Besides, the correlation coefficient between simulated and observed values varied between 0.90 and 0.99. Overall, the NSS with an inlet nitrate concentration of 24 (mg l− 1), the highest nitrate removal efficiency was obtained. The total amount of bacteria of NSS at the end of the experiment has been increased because of the bacteria growth.
Factors associated with good death of patients with advanced cancer: A prospective study in Japan
Authors: Ikari Tomoo , Hiratsuka Yusuke , Cheng Shao-Yi , Miyashita Mitsunori , Morita Tatsuya , Mori Masanori , Uneno Yu , Amano Koji , Uehara Yuko , Yamaguchi Takashi , Maeda Isseki , Inoue Akira 
Published: July 2022

Abstract
Purpose:
It is important for palliative care providers to identify what factors are associated with "good death" for patients with advanced cancer. We aimed to clarify factors associated with "good death" evaluated by the Good Death Scale (GDS) score among inpatients with advanced cancer in palliative care units (PCUs) in Japan.
Methods:
The study is a sub-analysis of a multicenter prospective cohort study conducted in Japan. All variables were recorded on a structured data collecting sheet designed for the study. We classified each patient into better GDS group or worse GDS group, and examined factors associated with better GDS using multivariate analysis.
Results:
Between January to December in 2017, 1896 patients were enrolled across 22 PCUs in Japan. Among them, a total of 1157 patients were evaluated. Five variables were significantly associated with a better GDS score in multivariate analysis: preferred place of death at PCU (odds ratio [OR] 2.85; 95% confidence interval [CI] 1.72–4.71; p < 0.01), longer survival time (OR 1.02; 95% CI 1.00–1.03; p < 0.01), not sudden death (OR 1.96; 95% CI 1.27–3.04; p < 0.01), better spiritual well-being Integrated Palliative Outcome Scale in the last 3 days in life (OR 0.53; 95% CI 0.42–0.68; p < 0.01) and better communication between patient and family (OR 0.81; 95% CI 0.66–0.98; p = 0.03).
Conclusions:
We clarified factors associated with "good death" using GDS among advanced cancer patients in Japanese PCUs. Recognition of factors associated with GDS could improve the quality of end-of-life care.
A Factor Set Based GNSS Fault Detection and Exclusion for Vehicle Navigation in Urban Environments
Authors: Chen Hanzhi , Sun Rui , Cheng Qi , Yang Lei 
Published: July 2022

Abstract
With the rapid development of safety critical applications of Intelligent Transportation Systems (ITS), Global Navigation Satellite System (GNSS) fault detection and exclusion (FDE) methods have made navigation systems increasingly reliable. However, in multi-fault scenarios of urban environments, FDE methods generally demand massive calculations and have a high risk of missed detection and false alarm. To deal with this issue, we proposed a factor set based FDE algorithm for the integration of GNSS and Inertial Measurement Units (IMU). The FDE is first performed efficiently via consistency checking over far fewer subsets of the pseudorange. Afterwards, the FDE results are validated by missed-detection and false-alarm checks. The missed-detection-check factor is designed by predicting the maximum horizontal GNSS positioning error, while the false-alarm-check factor is designed with the aid of IMU mechanization. Following FDE, a loosely coupled GNSS/IMU integration is carried out to output the final estimation of the position, velocity and attitude of the vehicle. The proposed algorithm improved both horizontal and 3D positioning accuracy by more than 50% in the field test, compared to the traditional GNSS/IMU loosely coupled scheme. Additionally, with the proposed algorithm, the resultant accuracy of the velocity and of the heading angle were improved by over 20% and 50% respectively.
Coal Country Supports Climate Policy in Exchange for Transition Assistance
Authors: Gazmararian Alexander 
Published: July 2022

Abstract
Fossil fuel communities often oppose climate policy due to the concentrated costs they anticipate. How could climate policy be designed to win support for decarbonization in fossil fuel communities? We leverage an original sampling strategy -- fielding surveys at county fairs -- to access this hard-to-reach population. Employing a multi-attribute policy experiment, we find that policies reducing transition costs, such as investments in worker healthcare and pensions and income compensation, increase support for transition assistance. In turn, respondents report willingness to back climate policy coupled with assistance for workers and community members. The findings suggest that smart policy design can build climate coalitions for decarbonization.
Effect of Game-based Training on Selected Physical Fitness Qualities among U-17 Male Volleyball Players in Injibara, Ethiopia
Authors: Ayalew Alemayehu , Belay Alemayehu , Nigeru Dagnachew 
Published: July 2022

Abstract
Aim
The purpose of this study was to examine the effect of game-based training on selected physical fitness qualities among u-17 male volleyball players in Injibara, Ethiopia.
Method
To achieve the purpose of the study, a true experimental design with a randomized pre-test and post-test control group design was used. However, a simple random sampling technique was used to select forty male subjects and randomly assigned to two equal groups of EG (n = 20) and CG (n = 20). The ages of the subjects ranged from 15 to 17 years. Therefore, EG was exposed to a game-based training program lasting for twelve weeks, on three non-consecutive days per week, i.e., Monday, Wednesday, and Friday, each lasting for two hours in the afternoon session. But CG did not perform game-based training other than the usual volleyball training given by the coach. Both groups had taken pre-test and post-test measurements. The two groups were measured by the T-test for agility, the thirty-second jump test for endurance, and the vertical jump test for power. The collected data for this study was analyzed and interpreted using descriptive and inferential statistics. In sum, all the statistical tests were calculated using SPSS version 26 software. However, the level of statistical significance was set at p ≤ 0.05. Finally, the test results were interpreted and displayed in tables in connection to physical fitness qualities.
Results
According to the analyzed data, the results obtained from the EG showed significant changes in agility, endurance, and power but not in the CG.
Conclusion
Based on the results, it can be concluded that 12-week game-based training has a positive effect on the improvement of selected physical fitness qualities.
Optimizing Structure and Internal Unit Weights of Echo State Network for an Efficient LMS-based Online Training
Authors: Saadat Javad , Farshad Mohsen , Eliasi Hossein 
Published: July 2022

Abstract
Echo State Network (ESN) is a special type of Recurrent Neural Networks (RNN) wherein a dynamic reservoir is used in the hidden layer, the weight of internal units of ESN is kept fix during training process, and output weights are the only trainable weights. Therefore, network training in an offline mode can be changed into a linear regression equation which is simply solved, although it is required to use online training of ESN in some applied problems. Least Mean Square (LMS) algorithm can provide an easy and constant method for online training of ESN; however, the huge eigenvalue spreads of the correlation matrix of internal network states reduces the speed of the algorithm convergence. In this study, Harmony Search Algorithm (HSA) is used to optimally produce the structure and weight of internal network units. It is possible to significantly reduce the eigenvalue spreads of correlation matrix of network states by means of this algorithm. Thereafter, LMS algorithm is used for the online training of ESN built with the help of HSA. Already-obtained simulation results show that the eigenvalue spreads of the correlation matrix are reduced millions of times and LMS algorithm increases online training speed of the network several times with an acceptable precision of training.