bluuebunny/crossref_metadata_2025_split huggingface dataset:
Greenhouse Gas Forcing a Necessary Causation for Marine Heatwaves Over the Northeast Pacific Warming Pool
Authors: Barkhordarian Armineh , Nielsen David Marcolino , Baehr Johanna 
Published: January 2022

Abstract
Over the last decade, the northeast Pacific (NP) experienced strong marine heatwaves (MHWs) that produced devastating marine ecological impacts and received major societal concerns. Here, we assess the link between the well-mixed greenhouse gas (GHG) forcing and the occurrence probabilities of the duration and intensity of the NP MHWs. To begin with, we apply attribution technique on the SST time series, and detect a region of systematically and externally-forced SST increase -- the long-term warming pool -- co-located with the past notably Blob-like SST anomalies. The anthropogenic signal has recently emerged from the natural variability of SST over the warming pool, which we attribute primarily to increased GHG concentrations, with anthropogenic aerosols playing a secondary role. With extreme event attribution technique, we further show that GHG forcing is a necessary, but not a sufficient, causation for the multi-year persistent MHW events in the current climate, such as that happened in 2019/2020 over the warming pool. However, the occurrence of the 2019/2020 MHW was extremely unlikely in the absence of GHG forcing. Thus, as GHG emissions continue to firmly rise, it is very likely that GHG forcings will become a sufficient cause for events of the magnitude of the 2019/2020 record event.
Genetic Diversity and Population Structure Analysis in Early Generations Maize Inbreds Derived From Local Germplasm of Eastern Himalayan Regions Using Microsatellite Markers
Authors: DEVI E LAMALAKSHMI , Ngangkham Umakanta , Singh Akoijam Ratankumar , S Bhuvaneswari , Sarika Konsam , Meetei Chongtham Chinglen , singh Thokchom Nepolian , Chongtham Sunil Kumar , Verma Harendra , Bhupenchandra Ingudam , Devi Chingakham Premabati , Singh Tensubam Basanta , Das Shaon Kumar , Singh Irengbam Meghachandra , Avasthe Ravikant , Kumar Amit , Mishra V K 
Published: January 2022

Abstract
North- Eastern parts of India fall under the Eastern Himalayan region and it is a diversity hotspot of many crops, including maize. Maize is an important traditional cereal crop grown in hill ecology of the region mainly for food, fodder and feed. To tap the potentiality of maize genetic resources in crop improvement programmes, assessment of genetic diversity is a basic requirement. Hence, in the present study, assessment of genetic diversity in thirty early generation maize inbreds developed from different germplasm of NE India was taken up using genome wide distributed fifty two microsatellite markers. The marker analysis revealed a large variation with a total of 189 alleles with an average of 3.63 alleles per marker locus. The allele size ranged from 50 bp ( phi 036 ) to 295 bp ( p 101049 ) which revealed a high level of genetic diversity among the loci. The PIC value ranged from 0.17 ( umc 1622 ) to 0.76 ( umc 1153 ) with an average value of 0.49. The value of expected Heterozygosity (H Exp ) ranged from 0.19 to 0.80 with an average of 0.57, whereas the Observed Heterozygosity (H Obs ) ranged from 0 to 0.89 with a mean of 0.14.The genetic dissimilarity between the genotype pairs ranged from 0.40 to 0.64 with a mean value of 0.57. Cluster analysis resolved the inbreds into three distinct sub-clusters. Similarly, population structure analysis also classified the inbred lines into three-subpopulations. Marker-trait associations showed a total of twelve SSR markers significantly associated with seven agronomic traits. From the present study, wide genetic variability was found among the maize inbreds with high potential to contribute new beneficial and unique alleles in genetic enhancement program of maize in India and particularly, in NE region.
Should Preoperative Computed Tomography Be Routine Examination For Cervicofacial Space Infections?
Authors: Liang Jiayu , Jiang Linli , Li Maoye , Liu Lei , Li Hui 
Published: January 2022

Abstract
Background: Cervicofacial space infections are potentially life-threatening, which require accurate diagnosis, early incision, and adequate drainage. The utilization of computed tomography (CT) in cervicofacial space infections has significantly increased. However, the clinical value of preoperative CT imaging in cervicofacial space infections remains controversial. We, therefore, investigated whether CT examination should be used as a routine examination in the treatment of patients with cervicofacial space infections.Methods: A retrospective study of all patients affected by cervicofacial space infections that received incision and drainage surgery from Jan 2016 to Dec 2020 was performed. Patients were divided into 2 groups: the group with preoperative CT and the group without preoperative CT. Outcomes, including re-operation rate, missed diagnosis rate, days of symptom relief, length of stay, duration of surgery, and total cost of hospitalization, were analyzed.Results: Of 153 patients, 108 patients underwent surgery with preoperative CT and 45 patients without preoperative CT. The re-operation rate in the preoperative CT group (6/108, 5.6%) was significantly lower (P<0.05) than that in the group without preoperative CT (10/45, 22.2%). Significant reduction of missed diagnosis rate, days of symptom relief, length of stay, and duration of surgery (P<0.05) were detected in the preoperative CT group. Conclusions: Preoperative CT examination should be recommended as a routine examination in the treatment of cervicofacial space infections for its usefulness in reducing the missed diagnosis rate and repeated surgery complication.
Hydraulic Performance Evaluation of Community-Managed Irrigation Scheme, North Shewa, Amhara, Ethiopia
Authors: Shumye Albachew , Meshesha Tesfa Worku 
Published: January 2022

Abstract
Background: Irrigation scheme performance assessment is vital to evaluate the impacts of irrigation practices, to identify performance gaps and to improve system performances. However, irrigation performance assessment has not been carried out for Yelen irrigation scheme since its operation. Therefore, this study has been done with the purpose of identifying and understanding the current level of irrigation performance of Yelen irrigation scheme. The indicators of adequacy, efficiency, dependability, deficiency and equity were used to determine hydraulic performance. Primary data were collected through flow measurement using current meter and Parshall flume, transect walk, household surveys and group discussions, whereas Secondary data were collected from different sources. CROPWAT 8.0 model, SPSS, Microsoft excels and GIS software was used to analyze the data. Water delivery indicators were evaluated from the amounts of water which was actually applied and which should have been applied.Results: According to the results of the study, the value of adequacy, dependability, efficiency, deficiency and equity were found to be 0.84, 0.26, 0.93, 0.17and 0.34 respectively. Generally, the performance of the irrigation system is poor. It mainly resulted due to water scarcity, illegal water abstraction, sedimentation of canals and inadequate operation and maintenance provisions.Concussions: Therefore, adequate maintenance and suitable management approaches are required to improve the irrigation system performance. Under the water scarce situations, improving the performance of water delivery systems can offer an opportunity to realize field level water savings.
Conservation Status of Forest Types Vary Greatly in Myanmar - the Most Forested Country in the Indo-burma Biodiversity Hotspot
Authors: Biswas Sumalika , Huang Qiongyu , Swe Khine Khine , Arnold Franz-Eugen , Mon Myat Su , Connette Katherine J. LaJeunesse , Connette Grant , Leimgruber Peter 
Published: January 2022

Abstract
Diverse forests with distinct forest types, harbor exceptional biodiversity and provide many ecosystem goods and services, making some forest types more economically valuable and prone to exploitation than others. The high rates of deforestation in Southeast Asia endanger the existence of such vulnerable forest types. Myanmar, the region’s largest forest frontier provides a last opportunity to conserve these vulnerable forest types. However, the exact distribution and spatial extent of Myanmar’s forest types has not been well characterized. To address this research gap, we developed a national scale Forest Type map of Myanmar at 20m resolution, using moderate resolution, multi-sensor satellite images (Sentinel-1, Sentinel-2 and ALOS-PALSAR), extensive field data, and a machine learning model (RandomForest). We mapped nine major forest types and developed a Conservation Status Score to evaluate the conservation status of the mapped forest types. Swamp, Mangrove, Dry Deciduous, Lowland Evergreen and Thorn forests were ranked as the five least conserved forest types. We also identified the largest remaining patch for each of the five least conserved forest types and determined their protection status to inform future forest conservation policy. In most cases, these patches lay outside protected areas indicating areas that may be prioritized for future conservation.
Functional Identification of MicroRNA-Centered Complexes in C. elegans.
Authors: Hebbar Shilpa , Panzade Ganesh , Vashisht Ajay , Wohlschlegel James , Veksler-Lublinsky Isana , Zinovyeva Anna 
Published: January 2022

Abstract
microRNAs (miRNAs) are crucial for normal development and physiology. To identify factors that might coordinate with miRNAs to regulate gene expression, we used 2’-O methylated oligonucleotides to precipitate Caenorhabditis elegans let-7, miR-58, and miR-2 miRNAs and the associated proteins. A total of 211 proteins were identified through mass-spectrometry analysis of miRNA co-precipitates, which included previously identified interactors of key miRNA pathway components. Gene ontology analysis of the identified interactors revealed an enrichment for RNA binding proteins, suggesting that we captured proteins that may be involved in mRNA lifecycle. To determine which miRNA interactors are important for miRNA activity, we used RNAi to deplete putative miRNA co-factors in animals with compromised miRNA activity and looked for alterations of the miRNA mutant phenotypes. Depletion of 25 of 39 tested genes modified the miRNA mutant phenotypes in three sensitized backgrounds. Modulators of miRNA phenotypes ranged from RNA binding proteins RBD-1 and CEY-1 to metabolic factors such as DLST-1 and ECH-5, among others. The observed functional interactions suggest widespread coordination of these proteins with miRNAs to ultimately regulate gene expression. This study provides a foundation for future investigations aimed at deciphering the molecular mechanisms of miRNA-mediated gene regulation.
A molecular dynamics study on the diffusion and imprint ability of spectinomycin under different sizes of aniline oligomers
Authors: Douykhumklaw Chanadan , Sutthibutpong Thana 
Published: January 2022

Abstract
Molecularly imprinted polymers (MIP) are the polymers created by molecular imprinting techniques that leave cavities for the specific interactions with a template molecule, and have been applied in molecular selectivity tasks. In this study, the molecular dynamics (MD) simulation technique was used to demonstrate that aniline oligomer could be developed as a potential MIP for detection and separation of the spectinomycin drug molecule for gonorrhoea treatment. MD simulations were performed for the systems of a spectinomycin within aniline oligomers of different sizes. The mean square displacement (MSD) and the diffusivity calculated from MD simulations showed that the diffusion coefficient was significantly dropped when the length of aniline oligomer was greater than two. The diffusion coefficient of spectinomycin became the lowest within aniline trimers, corresponded to the highest atomic distribution of MIP around the template. Then, the specific cavity in MIP systems with and without spectinomycin were calculated to assess the stability of the cavity created by the template. The volume of a cavity created within the trimer system was closest to the spectinomycin volume, and therefore became the optimal oligomer size for further development of MIP.
An Automatic Evaluation Method for Parkinson's Dyskinesia Using Finger Tapping Video for Small Samples
Authors: Li Zhu , kang lu , Cai Miao , Liu Xiaoli , Wang Yanwen , Yang Jiayu 
Published: January 2022

Abstract
PurposeThe assessment of dyskinesia in Parkinson's disease (PD) based on Artificial Intelligence technology is a significant and challenging task. At present, doctors usually use MDS-UPDRS scale to assess the severity of patients. This method is time-consuming and laborious, and there are subjective differences. The evaluation method based on sensor equipment is also widely used, but this method is expensive and needs professional guidance, which is not suitable for remote evaluation and patient self-examination. In addition, it is difficult to collect patient data in medical research, so it is of great significance to find an objective and automatic assessment method for Parkinson's dyskinesia based on small samples.MethodsIn this study, we design an automatic evaluation method combining manual features and convolutional neural network (CNN), which is suitable for small sample classification. Based on the finger tapping video of Parkinson's patients, we use the pose estimation model to obtain the action skeleton information and calculate the feature data. We then use the 5-folds cross validation training model to achieve optimum trade-of between bias and variance, and finally make multi-class prediction through fully connected network (FCN). ResultsOur proposed method achieves the current optimal accuracy of 79.7% in this research. We have compared with the latest methods of related research, and our method is superior to them in terms of accuracy, number of parameters and FLOPs. ConclusionThe method in this paper does not require patients to wear sensor devices, and has obvious advantages in remote clinical evaluation. At the same time, the method of using motion feature data to train CNN model obtains the optimal accuracy, effectively solves the problem of difficult data acquisition in medicine, and provides a new idea for small sample classification.
Stability of Enveloped and Nonenveloped Viruses in a Stable Gelatin Liquid Formulation
Authors: Kadji Francois Marie Ngako , Kotani Kazuki , Tsukamoto Hiroshi , Hiraoka Yosuke , Hagiwara Katsuro 
Published: January 2022

Abstract
The thermal stability of relevant viruses in gelatin liquid formulations for medical research and application is poorly understood. Bovine herpesvirus (BHV) was used as a model virus to examine the molecular weight (MW), concentration and gelatin type and to optimize virus stability in liquid formulations at 25 °C and 4 °C. Using the model virus stable liquid formulation, the stability of multiple enveloped and nonenveloped RNA and DNA viruses, including parainfluenza virus (PIV), reovirus (RV), BHV, and adenovirus (AdV), was monitored over up to a 30-week storage period. The BHV model virus was considered stable after 3 weeks in hydrolyzed gelatin (MW: 4000) with a 0.8 LRV (log10 reduction value) at 25 °C or a 0.2 LRV at 4 °C, compared to the stabilities observed in higher MW gelatin (60000 and 160000) with an LRV above 1. Based on the gelatin type, BHV in B-type gelatin samples were unexpectantly more stable than in A-type gelatin sample. All four viruses exhibited stability at 4 °C for at least 8 weeks, BHV or AdV remained stable for over 30 weeks of storage, and at 25 °C, AdV and RV remained stable for 8 weeks. The results demonstrated that 5% hydrolyzed gelatin can act as a relevant stabilizer for the thermal stability of viruses in medical research and application.
The Depression Anxiety Stress Scale 8: Its Psychometric Evaluation Among Women with Chronic Non-Cancer Pelvic Pain
Authors: Ali Amira , Hendawy Amin Omar , Al-Amer Rasmieh , Shahrour Ghada , Ali Esraa M. , Alkhamees Abdulmajeed A. , Ibrahim Nashwa , Ahmed Afaf Hassan , Lamadah Sahar Mansour Taha 
Published: January 2022

Abstract
Psychiatric comorbidity and abusive experiences in chronic pelvic pain (CPP) conditions may prolong disease course. This study investigated the psychometrics of the Depression Anxiety Stress Scale 8 (DASS-8) among women with CPP (N = 214, mean age = 33.3 ± 12.4 years). The DASS-8 expressed excellent fit, invariance across age groups and menopausal status, good discriminant validity (differentiating women with psychiatric comorbidity from those without comorbidity: U = 2018.0, p = 0.001), excellent reliability (alpha = 0.90), adequate predictive and convergent validity indicated by strong correlation with the DASS-21 (r = 0.94) and high values of item-total correlations (r = 0.884 to 0.893). In two-step cluster analysis, it classified women into low and high distress clusters (n = 141 and 73), with significantly higher levels of distress, pain severity and duration, and physical symptoms in cluster 2. The DASS-8 correlated with pain severity/duration, depression/anxiety symptoms, sexual assault, fatigue, headache severity, and physical symptoms at the same level expressed by the parent scale, or even greater. Accordingly, distress may represent a target for early identification of psychiatric comorbidity, CPP severity, sexual assault, fatigue, etc. Therefore, the DASS-8 is a useful brief measure of mental symptoms among women with CPP.
An Aging Giant At The Center of Global Warming: Population Dynamics and Its Effect on CO2 Emissions in China
Authors: Guo Hongwei , Jiang Jia , Li Yuanyuan , Liu Mengqing , Han Ji 
Published: January 2022

Abstract
Managing the aging crisis and mitigating CO2 emissions are currently two great challenges faced by China. Revealing the complex correlation between aging and CO2, and projecting their future dynamics are fundamentally necessary to inform effective strategies and policies toward a low-carbon and sustainable development in China. In this paper, we quantitatively investigated the impacts of population aging, economy, and energy intensity on CO2 emissions through a STIRPAT model based on balanced provincial panel data from 1995-2019, and employed a cohort model and scenario analysis to project the demographic change and CO2 emissions till 2050. It is found that CO2 emissions in China has witnessed a significant growth during 1995-2019, and will exhibit an inverted U-shaped growth till 2050 with its peak appears between 2030-2040. Every 1% increase of aging will exert a 0.69% emission of CO2 in China. However, a big regional difference was also detected as aging contributed to CO2 reduction in the eastern region, but stimulated CO2 emissions in the central and western regions. Policy implications for achieving a low-carbon and aging-oriented sustainable development include the integration of aging into the decision-making of industrial structure upgrading and CO2 emission reduction in both national and region levels, the promotion of the further transition to low-carbon consumption and green products in the eastern region, and strengthening the deep fusion of aging-oriented industries with local resource and environmental endowment in the central and western regions such as the development of eco-agriculture and green pension industries.
Exploring the Mechanism of Danggui Shaoyao San in the treatment of Non-alcoholic Fatty Liver Disease: A Study based on Network Pharmacology and Molecular Docking
Authors: xia luyun , Luo Zheng , Zhu Haiyan , Tang Yu-qin , Huang Lili , Huai Wenying , Zhang Chunjiang , Wang Yanqiu , Fang Zhiyan , Yin Qiaozhi , Yan Zhiyong , Zhang Tian-e 
Published: January 2022

Abstract
Background

Non-alcoholic fatty liver disease (NAFLD), the most prevalent chronic liver disease in the world, has yet to identify a particular medicine for treatment. Danggui Shaoyao San (DSS), a traditional Chinese medicine formula, has steadily been employed to treat NAFLD in recent years.
Methods

The active ingredients of the DSS were screened from the Traditional Chinese Medicine Systems Pharmacology (TCMSP), and the candidate targets of the ingredients were collected through the PharmMapper platform. NAFLD-related targets were acquired from NCBI, DisGeNet, Genecards databases. Venn diagram was used to identify possible DSS drug strategies in the treatment of NAFLD. Active ingredients - potential therapeutic targets network constructed in Cytoscape. The STRING database provides PPI networks. Metascape was used to evaluate targets using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, molecular docking simulations were performed using Pymol 2.4.0, AutoDuck Tools 1.5.6 and LigPlot 2.2.4 software to assess the affinity of key ingredients and targets.
Results

51 compounds were screened in the DSS, including paeoniflorin, poric acid A and poric acid B. There are a total of 38 cross-targets between herbs and NAFLD. PPI network analysis identified AKT1, ALB, PPARG, and CASP3 as priority targets. GO analysis focused on vesicle lumen, nutrition levels, and nitrous-oxide synthase regulator activity. DSS may have therapeutic benefits via the pathways in cancer,foxo signaling pathway,IL-17 signaling pathway, Th17 cell differentiation, PI3K-Akt signaling pathway according to KEGG analysis. Sitosterol and β- sitosterol were proven to be true promising compounds with excellent affinity in the final molecular docking.
Conclusions

DSS entails a number of components, targets, and routes, and it provides novel therapy and preventative alternatives for NAFLD.
Study on Sentiment Classification Strategies Based on the Fuzzy Logic with Crow Search Algorithm
Authors: Mohammed Mazen , Yu Lasheng , Aldhubri Ali , S.Qaid Gamil R. 
Published: January 2022

Abstract
In recent times, sentiment analysis research has gained wide popularity. That situation is caused by the nature of online applications that allow users to express their opinions on events, services, or products through social media applications such as Twitter, Facebook, and Amazon. This paper proposes a novel sentiment classification method according to the Fuzzy rule-based system (FRBS) with crow search algorithm (CSA). FRBS is used to classify the polarity of sentences or documents, and the CSA is employed to optimize the best output from the fuzzy logic algorithm. The FRBS is applied to extract the sentiment and classify its polarity into negative, neutral, and positive. Sometimes, the outputs of the FRBS must be enhanced, especially since many variables are present and the rules between them overlap. For such cases, the CSA is used to solve this limitation faced by FRBS to optimize the outputs of FRBS and achieve the best result. We compared the performance of our proposed model with different machine learning algorithms, such as SVM, maximum entropy, boosting, and SWESA. We tested our model on three famous data sets collected from Amazon, Yelp, and IMDB. Experimental results demonstrated the effectiveness of the proposed model and achieved competitive performance in terms of accuracy, recall, precision, and the F–score.