bluuebunny/crossref_metadata_2025_split huggingface dataset:
Freeze-dried Carboxymethyl Chitosan/starch Foam for Use as Hemostatic Wound Dressing
Authors: Jungprasertchai Nalintorn , Chuysinuan Piyachat , Ekabutr Pongpol , Niamlang Pimolpun , Suphaphol Pitt 
Published: March 2021

Abstract
Prolonged bleeding is a general complication that occurs after tooth extraction or oral surgery. Thus, patients must apply pressure and use absorbable wound dressings to stop bleeding and prevent blood loss. This method can stop bleeding and create blood clotting. However, some people have bleeding disorders or cannot stop bleeding with applied pressure after oral surgery. Therefore, hemostatic foam dressing has been an interesting material that can be used to stop bleeding and not damage blood clotting in the wound site. In this study, foam was prepared using a blend of starch with carboxymethyl chitosan and glyoxal as a crosslinking agent. The foam was formed by freeze-drying. Carboxymethyl chitosan/starch foam can absorb and hold water rapidly as analyzed by blood clotting assay and maximum swelling. Thus, carboxymethyl chitosan/starch foam (CM/starch foam) in a 1:4 ratio with 1% glyoxal can also absorb blood very well with suitable properties. It is non-cytotoxic to human dermal fibroblast cells by MTT assay and has good mechanical properties in a wet environment.
Nitrification Inhibitor 3,4-dimethylpyrazole Phosphate Improves Nitrogen Recovery and Accumulation in Cotton Plants by Reducing NO3- Leaching Under 15N-urea Fertilization
Authors: de Paulo Ezio Nalin , Galindo Fernando Shintate , Rabêlo Flávio Henrique Silveira , Frazão Joaquim José , Lavres Jose 
Published: March 2021

Abstract
Purpose: The use of nitrification inhibitors could be an interesting alternative to enhance nitrogen (N) fertilizer use efficiency in annual crops such as cotton, under tropical soil conditions. Thus, our aim was to evaluate the efficiency of nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) in a typical tropical soil, evaluating the fate of nitrogen (N-NO3-, N-NH4+ and total N in soil and leached water), N-accumulation and N recovery by cotton plants and soil. Methods: Leaching columns with cotton plants were used to access N-NO3- and N-NH4+ losses in drainage water. Treatments consisted in three N levels applied in side-dressing (corresponding to 50, 100 and 150 kg N ha-1) as 15N-urea with and without DMPP application. An additional treatment (absence of N application in side-dressing) was used as control. Results: 3,4-dimethylpyrazole phosphate was efficient to improve N recovery from applied urea fertilizer in plants and in the soil by reducing NO3- leaching, leading to enhanced N acquisition from fertilizer and soil, augmenting plants N-accumulation, mainly when high N levels above 100 kg N ha-1 were applied. We found that total N recovery increased 31% when 150 kg N ha-1 was applied as urea + DMPP source compared to conventional urea. In addition, DMPP application reduced NO3- leaching losses (c.a. of 11 to 20%), although had no significant effect on shoot and root dry matter yield. Conclusion: The reduction of NO3- leaching losses highlights the potential of DMPP to mitigate the impact of increased urea input on leaching losses thereby improving N use efficiency and N uptake in cotton crop.
Ecotourism risk assessment in Yaoluoping Nature Reserve, Anhui, China based on GIS
Authors: Tang Xuehai , Wu Yanping , Ye Jun , Lv Haiyan , Sun Feixia , Huang Qingfeng 
Published: March 2021

Abstract
With the continuous increase of tourism development and human disturbance, the functional structure distribution, sustainable utilization of resources and ecological benefits of nature reserves have been affected, and its ecological risk has increased significantly. This study proposes ecotourism development patterns for risk areas at each level, to provide a basis for stabilizing and promoting the ecological sustainable development of nature reserves. Yaoluoping National Nature Reserve in China is used as a study example. Based on GF-2 satellite data within the reserve area in 2017, ENVI, Fragstats and ArcGIS10.2 are used for land use classification as well as evaluation indicators selection and analysis. The ecotourism risk assessment model of the reserve is constructed, which is combined with the analytic hierarchy process and the fuzzy comprehensive evaluation method. The model consists of landscape ecology, topographic hydrology, land use and human activities factors, and it can produce the distribution map at the ecotourism risk level of the reserve. Results show that the high ecotourism risk areas in the reserve are mainly located around rivers and roads, and they are distributed in strips. Overall, the ecotourism risk level in the northern part of the reserve is higher than that in the southern part. Nearly 90% of the regional ecotourism risk is at the middle or low level, implying the reserve in a healthy level overall. However, except for low risk areas, the proportion of risk areas at all levels in the core zone is higher than that in the buffer zone.
Spatial landslide susceptibility mapping using integrating an adaptive neuro-fuzzy inference system (ANFIS) with two multi-criteria decision-making approaches
Authors: Paryani Sina , Neshat Aminreza , Pradhan Biswajeet 
Published: March 2021

Abstract
Landslide is a type of slope processes causing a plethora of economic damage and loss of lives worldwide every year. This study aimed to analyze spatial landslide susceptibility mapping in the Khalkhal-Tarom Basin by integrating an adaptive neuro-fuzzy inference system (ANFIS) with two multi-criteria decision-making approaches, i.e. the stepwise weight assessment ratio analysis (SWARA) and the new best-worst method (BWM) techniques. For this purpose, the first step was to prepare a landslide inventory map, which were then divided randomly by the ratio of 30/70 for model training and validation. Thirteen conditioning factors were used as slope angle, slope aspect, altitude, topographic wetness index (TWI), plan curvature, profile curvature, distance to roads, distance to streams, distance to faults, lithology, land use, rainfall and normalized difference vegetation index (NDVI). After the database was created, the BWM and the SWARA methods were utilized to determine the relationships between the sub-criteria and landslides. Finally, landslide susceptibility maps were generated by implementing ANFIS-SWARA and ANFIS-BWM hybrid models, and the ROC curve was employed to appraise the predictive accuracy of each model. The results showed that the areas under curves (AUC) for the ANFIS-SWARA and ANFIS-BWM models were 73.6% and 75% respectively, and that the novel BWM yielded more realistic relationships between effective factors and the landslides. As a result, it was more efficient in training the ANFIS. Evidently, the generated landslide susceptibility maps (LSMs) can be very efficient in managing land use and preventing the damage caused by the landslide phenomenon.
Design and investigation of a high-sensitivity PCF sensor for the detection of sulfur dioxide
Authors: Nizar Mohamed , Caroline Elizabeth , Krishnan Prabu 
Published: March 2021

Abstract
A vertical photonic crystal fiber (V-PCF) and horizontal PCF (H-PCF) are designed for the detection of sulfur dioxide (SO2) in this paper. A demanding numerical investigation is carried out in a wider range of wavelengths from 0.8 µm to 1 µm. SO2 is a major contributor to air pollution, which is responsible for asthma and cancer. The optical parameters are analyzed by using the Finite Element Method (FEM) which consumes a completely circular isotropic Perfectly Matched Layer (PML). The designed V-PCF sensor test is performed with different PML radius values, different elliptical constants for the inner cladding, the outer cladding layer, and the core. The higher relative sensitivity of 59.34% makes this proposed V-PCF a good design for SO2 detection.
Cardiovascular Health In Pediatric Heart Transplant Patients
Authors: Bogle Carmel , Perak Amanda M. , Wilkens Sarah J. , Aljiffry Alaa , Rychlik Karen , Costello John M. , Jones Donald Lloyd , Pahl Elfriede 
Published: March 2021

Abstract
Background
Ideal “cardiovascular health” (CVH)–optimal diet, exercise, nonsmoking, BMI, BP, lipids, and glucose—is associated with healthy longevity in adults. Pediatric heart transplant (HT) patients may be at risk for suboptimal CVH.
Methods
Single-center retrospective study of HT patients 2003–2014 who survived 1 year post-transplant. Five CVH metrics were collected at listing, 1, 3 and 5 years post-transplant (diet and exercise were unavailable). CVH was scored by summing individual metrics: ideal = 2, intermediate = 1, and poor = 0 points; total scores of 8–10 points were considered high (favorable). CVH was compared between HT patients and the US pediatric population (GP) utilizing NHANES 2007–2016. Logistic regression was performed to examine the association of CVH 1 year post-transplant with a composite adverse outcome (death, re-listing, coronary vasculopathy, or chronic kidney disease) 3 years post-transplant.
Results
We included 110 HT patients (median age at HT: 6 years [range 0.1–21]) and 19,081 NHANES participants. CVH scores among HT patients were generally high at listing (75%), 1 (74%), 3 (87%) and 5 (76%) years post-transplant and similar to GP, but some metrics (e.g., glucose) were worse among HT patients. Among HT patients, CVH was poorer with older age and non-Caucasian race/ethnicity. Per 1-point higher CVH score, the demographic-adjusted OR for adverse outcomes was 0.95 (95% CI, 0.7–1.4).
Conclusions
HT patients had generally favorable CVH, but some metrics were unfavorable and CVH varied by age and race/ethnicity. No significant association was detected between CVH and adverse outcomes in this small sample, but study in a larger sample is warranted.
Overlapping of independent SARS-CoV-2 nosocomial transmissions in a complex outbreak
Authors: Pérez-Lago Laura , Lozano Helena Martinez , Diaz Jose Antonio pajares , Gomez Arantxa Diaz , Machado Marina , Sola-Campoy Pedro J , Herranz Marta , valerio Maricela , Cubo Victor Quesada , Ruiz Maria del Mar Gomez , Fresneña Nieves Lopez , Arcilla Ignacio Sanchez , Comas Iñaki , Candelas Fernando Gonzalez , Jose sonia García de San , Bañares rafael , Catalán Pilar , Muñoz Patricia , de Viedma Darío García 
Published: March 2021

Abstract
SARS-CoV-2 nosocomial outbreaks in the first COVID-19 wave were likely associated to a shortage of personal protective equipment and scare indications on control measures. Having covered these limitations, updates on current SARS-CoV-2 nosocomial outbreaks are required. We carried out an in-depth analysis of a 27-day nosocomial outbreak in a gastroenterology ward in our hospital, potentially involving 15 patients and three healthcare workers. Patients had stayed in one of three neighbouring rooms in the ward. The severity of the infections in six of the cases and a high fatality rate suggested the possible involvement of a single virulent strain persisting in those rooms. Whole genome sequencing of the strains from 12 patients and one healthcare worker revealed an unexpected complexity. Five different SARS-CoV-2 strains were identified, two infecting a single patient each, ruling out their relationship with the outbreak; the remaining three strains were involved in three independent overlapping limited transmission clusters with three, three, and five cases. Whole genome sequencing was key to understand the complexity of this outbreak.
SARS-CoV-2 mRNA vaccines induce a robust germinal centre reaction in humans
Authors: Ellebedy Ali , Turner Jackson , O'Halloran Jane , Kalaidina Elizaveta , Kim Wooseob , Schmitz Aaron , Lei Tingting , Thapa Mahima , Chen Rita , Case James , Amanat Fatima , Rauseo Adriana , Haile Alem , Klebert Michael , Suessen Teresa , Middleton William , Krammer Florian , Teefey Sharlene , Diamond Michael , Presti Rachel , Xie Xuping , Shi Pei-Yong 
Published: March 2021

Abstract
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) messenger RNA (mRNA)-based vaccines are ~95% effective in preventing coronavirus disease 2019. However, the dynamics of antibody secreting plasmablasts (PBs) and germinal centre (GC) B cells induced by these vaccines in SARS-CoV-2 naïve and antigen-experienced humans remains unclear. Here we examined peripheral blood and/or lymph node (LN) antigen-specific B cell responses in 32 individuals who received two doses of BNT162b2, an mRNA-based vaccine encoding the full-length SARS-CoV-2 spike (S) gene. Circulating IgG- and IgA-secreting PBs targeting the S protein peaked one week after the second immunization then declined and were undetectable three weeks later. PB responses coincided with maximal levels of serum anti-S binding and neutralizing antibodies to a historical strain as well as emerging variants, especially in individuals previously infected with SARS-CoV-2, who produced the most robust serological responses. Fine needle aspirates of draining axillary LNs identified GC B cells that bind S protein in all participants sampled after primary immunization. GC responses increased after boosting and were detectable in two distinct LNs in several participants. Remarkably, high frequencies of S-binding GC B cells and PBs were maintained in draining LNs for up to seven weeks after first immunization, with a substantial fraction of the PB pool class-switched to IgA. GC B cell-derived monoclonal antibodies predominantly targeted the RBD, with fewer clones binding to the N-terminal domain or shared epitopes within the S proteins of human betacoronaviruses OC43 and HKU1. Our studies demonstrate that SARS-CoV-2 mRNA-based vaccination of humans induces a robust and persistent GC B cell response that engages pre-existing as well as new B cell clones, which enables generation of high-affinity, broad, and durable humoral immunity.
Energy system analytics and good governance -U4RIA goals of Energy Modelling for Policy Support
Authors: Howells Mark , Quiros-Tortos Jairo , Morrison Robbie , Rogner Holger , Niet Taco , Petrarulo Luca , Usher Will , Blyth William , Godínez Guido , Victor Luis F. , Angulo Jam , Bock Franziska , Ramos Eunice , Gardumi Francesco , Hülk Ludwig , Van-Hove Patrick , Peteves Estathios , Leon Felipe de , Meza Andrea , Alfstad Thomas , Taliotis Constantinos , Partasides George , Lindblad Nicolina , Stewart Benjamin , Shrestha Ashish , Rysankova Dana , Vogt-Schilb Adrien , Bataille Chris , Waisman Henri , Miketa Asami , Carvajal Pablo , Russo Daniel , Bazilian Morgan , Gritsevskyi Andrii , Tot Mario , Tompkins Adrian 
Published: March 2021

Abstract
Energy modelling is the process of using mathematical models to develop abstractions and then seek insights into future energy systems. It can be an abstract academic activity. Or, it can insert threads that influence our development. We argue therefore, that energy modelling that provides policy support (EMoPS) should not only be grounded in rigorous analytics, but also in good governance principles. As, together with other policy actions, it should be accountable. Almost all aspects of society and much of its impact on the environment are influenced by our use of energy. In this context, EMoPS can inspire, motivate, calibrate, and ‘post assess’ energy policy. But, such modeling is often undertaken by too few analysts under time and resource pressure. Building on the advances of ‘class leaders’, we propose that EMoPS should reach for practical goals — including engagement and accountability with the communities it involves, and those it will later affect. (We use the term Ubuntu, meaning ‘I am because you are’ to capture this interdependency). We argue that Ubuntu, together with retrievability, repeatability, reconstructability, interoperability and auditability (U4RIA) of EMoPS should be used to signal the beginnings of a new default practice. We demonstrate how the U4RIA principles can contribute in practice using recent modelling of aspirational energy futures by Costa Rica as a case study. This modelling effort includes community involvement and interfaces and integrates stakeholder involvement. It leaves a trail that allows for its auditing and accountability, while building capacity and sustainable institutional memory.
Outlining the Offshore Marine Environment and Mammal Habitation with the Changing Climate: the case of Ghana’s waters
Authors: Sackey Anthony Djaba , Lamptey Benjamin Lantei , Ofori-Danson Patrick 
Published: March 2021

Abstract
Understanding environmental baseline parameters within Gulf of Guinea offshore areas— as relevant delineating conditions favourably ensuring the survival of marine life bounded within was examined against environmental baseline surveys (EBS) conducted during the Environmental Impact Assessment (EIA) by licensed oil and gas operators of the region. The case of the EBS within Ghana’s western basin is mainly because offshore marine habitation over a decade has seen a rise in anthropogenic activities. Current concerns span pollution, over-exploitation of natural resources, air emissions, growing anthropogenic activity, and climate change. A series of samplings were taking at essential offshore and coastal facility locations to investigate baseline ocean environment; understand the nature of ecology and identify issues of vulnerabilities that could ensure destructive tendencies. The paper observes EBS conditions were consistent with findings of EIAs. The tropical nature of the region meant high radiation influx from the sun— leading to the thermal insulation of the area. Temperatures recorded are a direct function of solar energy absorbed in the atmosphere –delimiting humidity over infrared wave outputs, atmospheric precipitations and occasional poor visibility. Absorbed heat energy in the ocean depicted a generalised thermocline at the surface. Several surfaces and underwater factors including wind influenced the salinity, and temperature along water-depth, sound velocity, and dissolved oxygen concentrations –useful to marine animals such as turtles, seagull, pilot whales, dolphins, and sharks; clustered along with various webs of the food chain. The main challenge to the environment was the concerns of growing anthropogenic activities, plastic pollution and oil spills from operations and possible blowouts.
Morphosyntactic Analysis of Political News on Online Tempo
Authors: Nurdiani Pertiwi Rini , Fauzan Umar 
Published: March 2021

<p><em>Morphology and Syntax are very important studies in learning English. Morphology learns about how the words are structured and how they are put together from smaller part. It can be considered as the grammar of words. Meanwhile, Syntax discusses how the sentence is structured. The objectives of the research are to find out inflectional morphemes, derivational morphemes, and the patterns of clause structure which are found in political news on online Tempo in January 2019. This research used qualitative design and content analysis design where the source of data was article political news on Online Tempo in January, 2019. The major instrument of this research is the researchers themselves because they actively obtained and clustered the data and the secondary data was data sheet. The findings revealed three types of morphosyntactic, firstly, the researchers found 5 patterns of inflectional morpheme with 26 words. The most dominant pattern of inflectional morpheme was singular changing to the plural. Secondly, for derivational morpheme, it identified two types of classes including class-changing and class-mantaining. There were 3 patterns with 10 words in class-changing and 1 pattern with 1 word in class-mantaining. The study also showed that the common pattern of derivational morpheme was class-changing pattern (verb to noun). Thirdly, there were 7 patterns with 15 clauses that were used in political news. The result of this study proved that the dominant pattern of clause structure was S-V- to Infinitive pattern with 4 clauses.</em></p>
Exploring Prognostic Signatures of Hepatocellular Carcinoma and the
Potential Implications in Tumor Immune Microenvironment
Authors: Chen Hongxu , Jiang Zhijing , Yang Bingshi , Yan Guiling , Wang Xiaochen , Zang Shuning 
Published: March 2021

Objective:
The objective of this study is to construct a prognostic model using genetic markers of liver cancer and explore the signature genes associated with the tumor immune microenviroment.

Methods:
Cox proportional hazards regression analysis was carried out to screen the significant HR using dataset of TCGA Liver Cancer (LIHC) gene expression data, then LASSO (Least absolute shrinkage and selection operator) was performed to select the minimal variables with significant HR of genes. Thus, the prognostic model was constructed by the minimal variables with their HR and time-dependent receiver-operating characteristic (ROC) curve and area under the ROC curve (AUC) value used to assess the prognostic performance. Then dividing the patients into high and low risk groups by the median of the model, survival analysis was performed by two groups with testing and independent dataset. Furthermore, enrichment analysis of signature mRNAs and lncRNAs and their co-expression genes were performed, then, spearman rank correlation used to calculate the correlation between immune cells and genes in the prognostic model, and testing abundance difference of the immune cells in high and low risks groups.

Results:
A total of 5989 genes with significant HR were identified, then 6 key genes (three mRNAs: DHX37, SMIM7 and MFSD1, three lncRNAs: PIWIL4, KCNE5 and LOC100128398) screened by LASSO were used to construct the model with their HR value respectively. The AUC values of 1 and 5 year overall survival were 0.78 and 0.76 in discovery data and 0.67 and 0.68 in testing data. Survival analysis performed significantly in discriminating high and low groups with testing and independent data. Furthermore, many immune cells such as nTreg found a significant correlation with the genes in the prognostic model, and many immune cells show significantly different abundance in high and low risk groups.

Conclusion:
In the study, we used Univariate Cox analyses and LASSO algorithm with TCGA gene expression data to construct the prognostic model in liver cancer patients. And the prognostic model comprising three mRNAs including DHX37, SMIM7, MFSD1, and three lncRNAs including PIWIL4, KCNE5 and LOC100128398. Furthermore, these genes expression levels were associated with the abundance of some immune cells, such as nTreg. Also, many immune cells have significantly different abundance in high and low risk groups. All these results indicated combination with all these six genes could be the potential biomarker for the prognosis of liver cancer.