bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surveying cover crop root traits and their potential impacts on carbon and nitrogen cycling.
Authors: Wong Kong M , Griffiths Marcus , Moran Amelia , Johnston Andrea , Liu Alexander E , Sellers Mitchell A , Topp Christopher N 
Published: March 2023

Abstract
Background and Aims:
Cover crops have the potential to aid in adapting agricultural systems to climate change impacts through their ecosystem services, such as preventing soil erosion, remediating soil structure, and storing carbon belowground. Though roots are integral to these processes, there is a lack of cover crop root trait data. This study aims to characterize rooting behavior of several commercially available cover crops and assess their potential impact on soil carbon and nitrogen cycling.
Methods
Twenty-two cover crop cultivars across the grass, legume, and brassica families were grown in O’Fallon, Missouri. Canopy cover was monitored throughout the growing season. Shoot and root biomass samples were collected and analyzed.
Results
Cereal rye and winter triticale were the most winter hardy cultivars and provide the highest percent canopy cover. Cereal rye and winter triticale also generate the highest amount of shoot and root biomass among treatments but exhibit different rooting behavior. Winter triticale forms coarser roots and exhibits deeper rooting, which may be better suited for carbon sequestration. Similarly, rapeseed and Siberian kale have favorable C:N ratios for nutrient recycling, but rapeseed may invest more into lateral root formation and have a higher potential to “catch” excess nutrients.
Conclusion
Selection of cover crops for ecosystem services should account for root system architecture and their suitability for these ecosystem services. Differences in root traits among cultivars within the same taxonomic family highlight the potential to engineer cover crop root system architecture to further enhance ecosystem service efficacy.
Performance Evaluation of Deep Learning Techniques for Lung Cancer Prediction
Authors: Deepapriya B S , Kumar A. Anbarasa 
Published: March 2023

Abstract
Due to the increase in pollution, the number of deaths caused by lung disease is rising rapidly. It is essential to predict the disease in earlier stages by means of high-level knowledge and acquaintance. Deep learning based lung cancer prediction plays a vital role in assisting the medcial practioners for diagnosing lung cancer in earlier stage. Computer-Aided diagnosis (CAD) is considered to bring a boost to the field of medicine by tying it to automated systems. In this research paper, several models are experimented by using chest X-Ray image or CT scan as an input to detect a particular disease. This research work is carried out to identify the best performing deep learning techniques for lung disease prediction. The performance of the method is evalauted using various performance metrics such as precision, recall, accuracy and Jaccrd index.
A parameterized study on rainfall removal of aerosols
Authors: Chen Mingtao , Feng Qi , Zuo Yanqiu , Gao Xing , Huang Jun , Wang Hongqiang 
Published: March 2023

Abstract
Wet removal is the primary method for the natural removal of atmospheric aerosol particles, and wet removal is a very complex process. According to the PM2.5, PM10, and meteorological data from 71 cities in China from 2016 to 2018, this study utilizes theoretical analysis methods based on the existing rainfall aerosol removal theory and real-time monitoring data to calculate the measured removal coefficient and theoretical removal coefficient for verification. According to the different rainfall intensities and rainfall times in Guilin, the measured value and the simulated value are verified, and the linear relationship obtained was Λs = 1.589*10− 5 + 0.609Λm, R2 = 0.673, and the simulated value approximated to the measured value after correction. The same method was utilized to calculate the theoretical removal coefficient of polydisperse aerosols in 71 cities across the country, and the calculation parameters of the rainfall removal polydisperse aerosol model in different regions were modified.
Robust analysis of a novel PANoptosis-related prognostic gene signature model for hepatocellular carcinoma immune infiltration and therapeutic response
Authors: Wei Yongguang , Lan Chenlu , Yang Chengkun , Liao Xiwen , Zhou Xin , Huang Xinlei , Xie Haixiang , Zhu Guangzhi , Peng Tao 
Published: March 2023

Abstract
Background
PANoptosis, an interplay between pyroptosis, apoptosis, and necroptosis, is deeply involved in cancer development and immunity. However, the influence of PANoptosis in hepatocellular carcinoma (HCC) remains to be further investigated.
Methods
The differentially expressed PANoptosis-related genes (PANRGs) was screened in The Cancer Genome Atlas (TCGA) database. Accordingly, mutation, bioinformatics, and consensus clustering analyses were performed. Then, a prognostic risk model was developed by least absolute shrinkage and selection operator (LASSO) Cox regression. The prognostic value, immunity correlation and therapeutic response prediction ability of risk model were explored.
Results
A total of 18 PANRGs were differently expressed in the TCGA-HCC cohort and were mainly involved in cancer- and cell death-related signal pathways. Using unsupervised clustering method, we identified two PANRGs-mediated clustering patterns. The remarkable differences of overall survival (OS) and clinical features on two clusters were demonstrated. Based on the five-gene prognostic risk model, the calculated PANRG-scores were used to categorize the subgroups as high- and low-risk. Notably, the high-risk subgroup had a dismal prognosis and exhibited much lower immune cell infiltration levels of mast cells, nature killer cells and pDCs, but higher levels of aDCs, iDCs and Treg cells than those in the low-risk subgroup. Furthermore, we constructed a reliable nomogram combining clinical traits and PANRG-score to predict the OS of HCC patients. The significant correlation between PANoptosis and tumor mutation burden (TMB), and PANoptosis and ferroptosis were also revealed. In drug sensitivity analysis, the high-risk subgroup had a considerably lower TIDE score, suggesting a preferable response to immunotherapy, and may be more sensitive to Tipifarnib, Imatinib, Doxorubicin, and Gemcitabine. The upregulated mRNA expressions of FADD were validated in 16 paired HCC tissues of Guangxi cohort.
Conclusions
Based on PANoptosis-related genes, an integrated risk signature was constructed to provide a roadmap for patient stratification and predict HCC patient's prognosis. The patients with the higher PANRG-score showed a dismal survival and relatively low immune infiltration, but a potential better immunotherapy response.
Modeling and vibration feature analysis of a spur gear-bearing system with a misaligned shaft angle
Authors: Zhao Wei-qiang , Liu Jie , Zhao Wen-hui , Wang Hao , Yang Na 
Published: March 2023

Abstract
A gear-bearing dynamic model is presented to investigate the vibration features of the gear transmission system with a misaligned shaft angle. The time-varying mesh stiffness (TVMS), time-varying pressure angle and eccentricity are considered in the model. In addition, a new expression of the load distribution function for the gear tooth is proposed to obtain accurate effects of the misaligned shaft angle on the TVMS. Based on the proposed model, the vibration of the system and the TVMS are solved jointly. This model is solved by the 4th Runge-Kutta, and the TVMS is calculated by the energy potential method where one mesh stiffness value is determined by each time-varying misaligned shaft angle. Effects of the misaligned shaft angle on the vibration features are analyzed by the time-domain, frequency-domain and statistical indicator features.
A Plasma Irradiation System Optimized for Space Weathering of Solar System Bodies
Authors: Kimura Tomoki , Otsuki Misako , Kitano Tomohiro , Hoshino Ryo , Nakauchi Yusuke , Haganuma Shunsuke , Haganuma Ryu , Haganuma Tetsuo , Tsuchiya Fuminori , Tamagawa Toru , Hayato Asami , Kimura Jun , Terada Naoki , Usui Hideyuki , Nishino Masaki N. , Yokota Shoichiro , Miyake Yohei 
Published: March 2023

Abstract
In the tenuous atmospheric bodies of our solar system, space weathering on the celestial surface is an important process for its chemical and physical evolution and ambient environment on timescales of celestial evolution. Space plasma is a dominant energy and material source for space weathering. Plasma irradiation experiment in the laboratory is an effective method for modeling long-term space weathering driven by space plasma. However, comprehensive modeling of plasma space weathering has not yet been conducted because the capabilities of the earlier facilities were not optimized for long-term space weathering; for example, the machine time and number flux of incident particles. Here, we developed a plasma irradiation system, Plasma Irradiation Emulator for Celestial Environments (PIECE) of the solar system bodies, which reproduces long-term plasma space weathering in tenuous atmospheric bodies by exclusive use. We successfully developed a system with high electron and ion number fluxes of ~1013 − 1016 particles cm-2s-1 at any acceleration energy in the range of 1–30 keV, which leads to the first-ever high fluence of ~1019 − 1022 particles cm-2s-1 with a 10-day irradiation time. This fluence corresponds to a plasma irradiation time of ~104–108 years on Europa.
Study on synthesis of Ursodeoxycholic Acid by reduction of 7-Ketolithcholic Acid in Double Aprotic Solvents and Molecular simulations
Authors: Dai Mohan , Xu Binpeng , Guo Qing , Wan Junfen , Cao Xuejun 
Published: March 2023

Abstract

Ursodeoxycholic acid is not only safer than chenodeoxycholic acid in the treatment of hepatobiliary diseases, but also has a wide range of applications in Acute Kidney Injury and Parkinson's Disease.The purpose of this experiment is to improve the conversion rate of 7-ketocholic acid and the yield of ursodeoxycholic acid in Aprotic Solvents during electrochemical reduction process. Three aprotic solvents were investigated as electrolytes, 1,3-Dimethyl-2-imidazolidinone(DMI) has the stable five-membered ring structure, 7K-LCA has undergone two nucleophilic and "Walden" Inversion", the 7K-LCK was stereoselectively reduced to UDCA. hexamethylphosphoramide (HMPA) and 1,3-methyl-3,4,5,6- Tetrahydro-2(1H)-pyrimidinone (DMPU) can be attacked by chloride ions to produce by-products. Molecular simulation based on molecular orbital theory combines experiments to study reducibility of three aprotic solvents(hexamethylphosphoramide(HMPA), 1,3-methyl-3,4,5,6-Tetrahydro-2(1H)-pyrimidinone (DMPU), and 1,3-Dimethyl-2-imidazolidinone(DMI)). Choose the best solvent based on the simulation results, the electrolysis reaction can be carried out by applying current and voltage when lithium chloride is used as electrolytes. and the calculation using Materials studio showed that Cu, Pb, Hg-Cu, and Ni had the largest binding energy to the substrate in this system. Using Cu as the electrode when the solvent is a 1:1 mix of DMI and HMPA ,the conversion rate of 7-ketocholic acid could reach 98%,the yield of ursodeoxycholic acid was up to 80%. Under the same conditions, linear voltammetry was performed on the electrochemical workstation to study the electrolysis behavior, and the obtained results were consistent with the experiment.
Mass Media Impact on Opinion Evolution in Biased Digital Environments: a Bounded Confidence Model
Authors: Pansanella Valentina , Sirbu Alina , Kertész János , Rossetti Giulio 
Published: March 2023

Abstract
People increasingly shape their opinions by accessing and discussing content shared on social networking websites. These platforms contain a mixture of other users' shared opinions and content from mainstream media sources. While online social networks have fostered information access and diffusion, they also represent optimal environments for the proliferation of polluted information and contents, which are argued to be among the co-causes of polarization/radicalization phenomena. Moreover, recommendation algorithms - intended to enhance platform usage - likely augment such phenomena, generating the so-called Algorithmic Bias. In this work, we study the effects of the combination of social influence and mass media influence on the dynamics of opinion evolution in a biased online environment, using a recent bounded confidence opinion dynamics model with algorithmic bias as a baseline and adding the possibility to interact with one or more media outlets, modeled as stubborn agents. We analyzed four different media landscapes and found that an open-minded population is more easily manipulated by external propaganda - moderate or extremist - while remaining undecided in a more balanced information environment. By reinforcing users' biases, recommender systems appear to help avoid the complete manipulation of the population by external propaganda.
Evaluation of ERA5 and Dynamical Downscaling for Surface Energy Balance Modeling at Mountain Glaciers in Western Canada
Authors: Draeger Christina , Radic Valentina , White Rachel H. , Tessema Mekdes Ayalew 
Published: March 2023

Abstract
To project glacier melt in response to anthropogenic climate change, output from coarsely resolved global climate models needs to be downscaled to the local scale of glaciers. Due to the high computational cost of dynamical downscaling, statistical downscaling has been more commonly used in glacier studies despite yielding results with large uncertainties. Here we investigate the use of global reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5 and ERA5-Land reanalysis), with and without dynamical downscaling, for surface energy balance (SEB) modeling at four glaciers in Western Canada. We focus on the sites with available on-glacier meteorological measurements collected over different summer seasons from 2012 to 2019. We dynamically downscale ERA5 with the Weather Research and Forecasting (WRF) model at 3.3 km and 1.1 km grid spacing. We find that the SEB model, forced separately with observations and reanalysis, yields <10 % difference in simulated seasonal melt. Relative to the observations, the reanalysis gives slightly overestimated incoming shortwave radiation and substantially underestimated wind speed, yielding underestimated turbulent heat fluxes. These biases, however, cancel each other out in the SEB model of seasonal melt. Downscaling with WRF improves the simulation of wind speed, while other meteorological variables show similar performance to the reanalysis without downscaling. The choice of WRF physics parameterization schemes is shown to have a relatively large impact on the simulations of SEB components, but a small impact on the modeled total melt energy over the observational periods. The similar performance of WRF and ERA5, as input to the SEB model at our glacier sites, gives confidence in using WRF for projections of glacier melt in this region.
Childhood glaucoma profile in a Southwestern Ethiopia tertiary care center: a retrospective study
Authors: Mulugeta Tarekegn , Gebremichael Guteta , Adugna Sufa 
Published: March 2023

Abstract
Background
Childhood glaucoma is a major cause of childhood blindness worldwide. The profile of childhood glaucoma has not been well characterized in sub-Saharan Africa. Thus, this study was designed to describe demographics, clinical features, and managements of childhood glaucoma.
Methods
This retrospective study included glaucoma patients below 18 years old who were diagnosed between September 2019 to August 2022. Childhood glaucoma diagnosis and classification was made as per the Childhood Glaucoma Research Network Classification (CGRN). The extracted patient data included were the following: age at presentation, sex, family history of childhood-onset glaucoma, consanguinity, type of glaucoma, laterality, examination findings (visual acuity (VA), intraocular pressure (IOP) at the baseline and final visits), and the treatment modalities instituted (types and number of medications and surgeries).
Results
A total of 105 children (181 eyes) were diagnosed with glaucoma. The most common type of childhood glaucoma was primary congenital glaucoma (PCG) constituting 42%, followed by glaucoma suspect 22.1% and juvenile open-angle glaucoma (JOAG) 15.5%. While the most common type of secondary glaucoma was steroid-induced glaucoma, followed by glaucoma following cataract surgery. Bilateral glaucoma was found in 72.4% of children. In both primary and secondary glaucoma, boys were affected more than girls, in ratio of 2:1 and 2.7:1, respectively. The mean age at presentation for patients with PCG was 2.7 years. Close to 93.4% of PCG eyes were managed surgically, of which majority underwent combined trabeculotomy and trabeculectomy (CTT). Most of secondary glaucoma cases were treated medically. Overall, 85.3% of eyes had successful control of IOP ≤ 21 mmHg.
Conclusion
PCG was the most common type of childhood glaucoma. One of a well-recognized challenge in developing countries, late presentation of patients with PCG, was also observed in our study. Which highlights, the need of improvement on access to eye-care service and the importance of awareness creation in the general population. While steroid-induced glaucoma was the most common type of secondary glaucoma; appropriate measures should be taken to prevent this preventable glaucoma. In addition, this study encourages the establishment of prospective studies and surgical trials in this field.
The expression and prognostic role of sphingosine 1-phosphate receptor 4 (S1PR4) as a biomarker in skin cutaneous melanoma
Authors: Wang Zi , Zhang Suyi , Zhang Guangzhong 
Published: March 2023

Abstract
Background: Skin cutaneous melanoma (SKCM) is one of the most lethal skin malignancies worldwide. Sphingosine 1-phosphate (S1P) regulates tumor cells through S1P receptors (S1PRs). Unlike S1PR1/2/3/5, whose anti-apoptotic effects have been widely studied, the regulatory effect of S1PR4 on tumors has not been studied extensively. This study aimed to investigate the correlation between S1PR4 expression and the survival, clinical manifestations, tumor microenvironment, and immune infiltration in patients with SKCM.
Results: Low S1PR4expression was associated with poor prognosis in patients with SKCM. Patients in the high-expression group had significantly longer disease survival and progression-free survival than those in the low expression group.
Conclusion: High S1PR4expression was highly associated with better prognosis and milder clinical manifestations; thus, S1PR4 may be used as a prognostic marker to help physicians monitor patients with SKCM.
Uncovering Unique Screening Effects in 2D Perovskites: Implications for Exciton and Band Gap Engineering
Authors: Hansen Kameron , Wong Cindy , McClure C. Emma , Romrell Blake , Flannery Laura , Powell Daniel , Garden Kelsey , Berzansky Alex , Eggleston Michele , King Daniel , Shirley Carter , Beard Matthew , Nie Wanyi , Schleife Andre , Colton John , Whittaker-Brooks Luisa 
Published: March 2023

Abstract
Coulomb interactions govern most optoelectronic properties in semiconductors including bandgap, excitons, polaron formation, light absorption, interaction of carriers with defects, charge and energy transport. A clear signature of the strength of many-body Coulomb interactions is the exciton binding energy (Eb). As such, the importance of Eb is perhaps second only to the fundamental band gap (Eg) in understanding the physics and efficiency of low-dimensional semiconductors. However, despite their importance, Eg and Eb are difficult to measure. Here, by choosing 2D halide perovskites as the material and electroabsorption as the experimental probe, we measure Eg and Eb with a precision that is an order of magnitude better than typical methods. The Eb values are both lower than previous literature reports and lower than expected from standard theory. Using dielectric spectroscopy, density functional theory, and quantum mechanical modeling, we demonstrate these low Eb values are a consequence of unique screening effects, such as superlattice screening and phonon screening. We demonstrate a clear correlation between Eb and Eg and provide design principles in order to a priori tune Eg and Eb to their optimal values. As such, this work lays the blueprint for Eg-Eb engineering of low-dimensional semiconductors, as an even more useful replacement to simply band gap engineering.
An evaluation of statistical differential analysis methods in single-cell RNA-seq data
Authors: Li Dongmei , Zand Martin , Dye Timothy , Goniewicz Maciej , Rahman Irfan , Xie Zidian 
Published: March 2023

Abstract
Background: Single-cell RNA Sequencing is gaining popularity in recent years. Compared to bulk RNA-Seq, single-cell RNA Sequencing allows the gene expression being measured within individual cells instead of mean gene expression levels across all cells in the sample. Thus, cell-to-cell variation of gene expressions could be examined. Gene differential expression analysis remains the major purpose in most single-cell RNA sequencing experiments and many methods have been developed in recent years to conduct gene differential expression analysis for single-cell RNA sequencing data.
Results:Through simulation studies and real data examples, we evaluated the performance of five open-source popular methods used for gene differential expression analysis in single-cell RNA sequencing data. The five methods included DEsingle (Zero-inflated negative binomial model), Linnorm (Empirical Bayes method on transformed count data using the limma package), monocle (An approximate Chi-Square likelihood ratio test), MAST (A generalized linear hurdle model), and DESeq2 (A generalized linear model with empirical Bayes approach and also commonly used for bulk RNA sequencing differential express analyses). We assessed the false discovery rate (FDR) control, sensitivity, specificity, accuracy, and area under the receiver operating characteristics (AUROC) curve for all five methods under different sample sizes, distribution assumptions, and proportions of zeros in the data.
Conclusions: We found the MAST method performed the best among the five methods compared with the largest AUROC values across all tested sample sizes and different proportion of truly differential expressed genes, when the data followed negative binomial distributions. When the sample size increased to $100$ in each group, the MAST method showed the best performance with the highest AUROC regardless of the data distributions. If the excess zeros were first filtered out before the gene differential analyses, the DESingle, Linnorm, and DESeq2 performed relatively better than the MAST and the monocle methods with higher AUROC values.