bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of spatial distribution pattern of buildings on the distribution of urban gaseous pollutants
Authors: Yu Xinwei , Shan Baoyan , Chen Yanqiu , Zhang Qiao , Ren Qixin , Lv Yongqiang 
Published: August 2022

Abstract
Buildings are the main component of urban, and their three-dimensional spatial patterns affect meteorological conditions and consequently, the spatial distribution of gaseous pollutants (CO, NO, NO2, and SO2). This study uses the Jinan Central District as the study area, and constructs a building spatial distribution index system based on DEM, urban road network, and building big data. ANOVA and spatial regression models were used to study the effects of building spatial distribution indicators on the distribution of gaseous pollutants along with their spatial heterogeneity. The results showed that (1) The effect of each spatial distribution index of building on the concentration distribution of the four gaseous pollutants was significant, with one-way ANOVA outcomes reaching a significance level of 0.01 or more. The DEM mean, building altitude, and their interaction with other building spatial distribution indicators are important factors affecting the distribution of gaseous pollutants; The interaction of other three-factor indicators did not have a significant effect on the distribution of gaseous pollutant concentrations. (2) The spatial distribution of CO and NO2 is mainly influenced by the indicators of the spatial distribution of buildings in this study unit, and the effects of CO and NO2 concentrations in adjacent study units are the result of the action of stochastic factors. The NO and SO2 concentrations are influenced by the spatial distribution index of buildings in this study unit, the neighborhood homogeneity index, and NO and SO2 concentrations. (3) Spatial heterogeneity was observed in the effects of building spatial distribution indicators on the concentrations of different pollutants. The GWR models constructed using CO and NO concentrations and building spatial distribution indicators were well fitted globally and locally. The CO and NO concentrations were negatively correlated with the mean topographic elevation and NO concentrations were correlated with building density.
Social media as a source of drug safety information in the paediatric population
Authors: Vilimelis-Piulats Ingrid , Pérez-Ricart Ariadna , Calvo Albert , Negre JM Suñé , Juárez-Gimenez Juan Carlos 
Published: August 2022

Abstract
Purpose: Children are vulnerable to suffer negative outcomes due to medication (NOM), social media (SM) can be a non-interventional tool to gather safety data. The aim of this study is to assess paediatric Adverse Events (AE) or suspected Adverse Drug Reaction (ADR) detected in SM. Secondary objectives are the assessment of NOM, Drug Related Problems (DRP) and Medication Errors (ME). Methods: Observational, ambispective study assessing NOM in Public Parenting Forums (PPF) using data mining software. Entries that mentioned a medicine administered to children were analyzed and, if NOMs were detected, DRP, ME and AE were categorized. ME and ADR seriousness were assessed. ADR causality according Liverpool Causality Assessment (LCAT) and prevalence compared with those reported in Summary of Product Characteristics (SmPC) of each product. Results: Two forums (mumsnet.uk; socpetit.cat 2733 (81%)) were analyzed. Of 3375 entries, 635 contained a NOM and a DRP, 214 in English, 6 in Spanish and 217 in Catalan. 161 ADR were detected, including Serious AEs (SAEs), unknown, rare or very rare ADR. 29(16%) were not reported in SmPC. 95 ME were found, caused parents or caregivers (40; 42%) and healthcare professionals (HCP) (55; 58%). Severity ranged from no harm up to harm required intervention. Conclusion: ADR were found in PPF, including SAEs and ADR with low or unknown prevalence and suspect ADRs not included in the SmPC. ME that reached children were also found. As consequence, despite that the overall number of entries is not high, forums are a source of valuable pharmacovigilance information.
Fine mapping via QTL-seq, Target-seq and RNA-seq of a novel QTL controlling early flowering time in spring B.napus
Authors: Tang Jie , Liu Haidong , Quan Youjuan , Yao Yanmei , Li Kaixiang , Tang Guoyong , Du Dezhi 
Published: August 2022

Abstract
Days to flowering (DTF) is a very important trait of rapeseed, but the molecular mechanism in spring B. napus is unknown. We previously located a novel candidate QTL for the early-flowering trait in spring B. naopus, which was named BnaC08cqDTF. Here, DNA pools of extreme early-flowering and late-flowering BC3F2 plants from crosses between spring-type B. napus No. 4512 (early flowering parent) and No. 5246 (late flowering parent) were bulked for QTL sequencing (QTL-seq) and initial mapping. Target sequencing (Target-seq) and fine mapping were performed using the BC3F2 and BC4F2 population plants. BnaC08cqDTF was narrowed to the 86 kb region of chromosome C08. RNA-seq and qRT‒PCR analyses indicated that the expressing levels of two candidate genes (BnaC08G0010400ZS and BnaC08G0011200ZS) in No. 4512 were significantly higher than those in No. 5246. Furthermore, we cloned the genes of BnaC08G0010400ZS and BnaC08G0011200ZS from parents and NILs. An A/G nonsynonymous mutation was identified in the 1,259 bp locus of exon 3 in the CDS of BnaC08G00101400ZS, causing a 374 E to K amino acid substitution. This SNP haplotype also exists in a natural population. BnaC08G0010400ZS may be the candidate gene of BnaC08cqDTF, and this gene is homologous to the AT1G04400 gene (CRY2) in Arabidopsis. Our results may contribute to a better understanding of the molecular mechanism of early flowering regulation and promote the breeding program for prematurity in spring B. napus.
Indigenous knowledge of farmers on classification, utilization and on-farm management of Enset (Ensete ventricosum) diversity in Hadiya, southern Ethiopia
Authors: Dilebo Tesfaye , Feyissa Tileye , Asfaw Zemede , Zewdu Ashagrie 
Published: August 2022

Abstract
Background
Farmers have a wealth of indigenous knowledge on enset cultivation in their communities acquired through the accumulation of experience over a long period. Enset (Ensete ventricosum (Welw.) Cheesman) is a multipurpose species and one of the most widely grown perennial crops in southern Ethiopia. Although enset is a high-value and vital crop for local farmers, necessary information is insufficiently documented and still not fully explored at the local level. Thus, this study was designed to assess and record the wealth of indigenous knowledge related to the local identification, naming, categorization, and traditional uses of enset landraces (farmers’ varieties) relevant for the maintenance of on-farm landrace diversity in Hadiya Zone, southern Ethiopia.
Results
In this study, we identified 99 locally named enset landraces under cultivation. Farmers regularly identify the name and classify numerous enset landraces based on different criteria, the four morphological traits (namely: leaf, midrib, petiole, and pseudostem colors) are primarily used as criteria for identification. In addition, the local names of some enset landraces are usually indicators and show their uniqueness in morphological traits, places of origin, agronomic features, and quality attributes of products. Based on farmers, cultivated enset landraces are classified into two general groups according to the characteristics regarding the ease of harvesting and processing, rate of fermentation, and quality and values of the end products. Enset products named qocho, bulla and amicho are commonly produced by each family. Furthermore, three types of qocho are traditionally produced by local farmers based on types of the landraces used during harvesting, the presence absence of fermentation starter (gammama), and the duration of fermentation.
Conclusion
The traditional farming system and associated wisdom contributed to the availability of the present-day on-farm diversity maintained under continuous cultivation and conservation practices. The indigenous knowledge of local farmers regarding the cultural, social, and economic values of enset and its production system is crucial for understanding how the local communities utilize, maintain, and manage the existing enset landrace diversity in their homegardens. It is necessary to integrate indigenous knowledge with the modern system for continuous utilization and conservation strategies of enset genetic resources and their diversity.
Identification of DSPP Novel Variants and Phenotype Analysis in dentinogenesis dysplasia shields type II Patients
Authors: Du Qin , Cao Li , Yan Nana , Kang Sujun , Lin Mu , Cao Peilin , Jia Ran , Wang Chenyang , Qi Hanyu , Yu Yue , Zou Jing , Yang Jiyun 
Published: August 2022

Abstract
Objectives: To investigate the genetic causes and characteristics of teeth of dentin dysplasia Shields Type-II(DD-II) in three Chinese families.Materials and Methods: Three Chinese families affected with DD-II were collected. The whole-exome sequencing(WES) and whole-genome sequencing(WGS) were conducted to screen for variations, and sanger sequencing was used to verify mutation sites. The physical and chemical characteristics of the affected teeth including tooth structure, hardness, mineral content and ultrastructure were investigated.Results: A novel frameshift deletion mutation c.1871_1874del(p.Ser624fs) in DSPP was found in family A and family B, while no pathogenic mutation was found in family C. The affected teeth’s pulp cavities were obliterated, and the root canals were smaller than normal teeth and irregularly distributed comprising a network. The patients’ teeth also had reduced dentin hardness and highly irregular dentinal tubules. The Mg content of the teeth was significantly higher than the controls but the Na content was obviously lower than the controls.Conclusions: A novel frameshift deletion mutation c.1871_1874del(p.Ser624fs) in the DPP region of the DSPP gene caused DD-II. The DD-II teeth demonstrated compromised mechanical properties and changed ultrastructure, suggesting an impaired function of DPP. Our findings expanded the mutational spectrum of DSPP gene and strengthen the understanding of clinical phenotypes related to the frameshift deletion in the DPP region of the DSPP gene.Clinical Relevance: DSPP mutation can cause the characteristics of the affected teeth including tooth structure, hardness, mineral content and ultrastructure.
Quantitative CT lung COVID scores: Prediction of rapid progression and monitoring longitudinal changes in COVID-19 pneumonia patients
Authors: Kang Da Hyun , Kim Grace Hyun J. , Park Sa-Beom , Lee Song-I , Koh Jeong Suk , Brown Matthew S. , Abtin Fereidoun , McNitt-Gray Michael F. , Lee Jeong Seok , Goldin Jonathan G. 
Published: August 2022

Abstract
Background
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, known as coronavirus disease 2019 (COVID-19), is an ongoing issue in some populations with rapidly worsening pneumonia and persistent symptoms. This study aimed to test the predictability of rapid progression within 7 days of hospitalization using radiographic scores with laboratory markers at baseline and to present longitudinal changes.
Methods
This retrospective study included 222 subjects (mean age: 53.4 years, 50.9% male) diagnosed with COVID-19 and admitted between February and September 2020 at Chungnam National University Hospital. Rapid progression was defined as respiratory failure requiring ventilator support. From high-resolution computed tomography (HRCT) analyses, quantitative COVID (QCOVID) scores were derived: (1) ground glass opacity (QGGO), (2) mixed diseases (QMD), and (3) consolidation (QCON), and the sum, quantitative total lung diseases (QTLD). ROC analyses were performed to predict progression. Mixed-effects models were performed using serial 2–6 HRCTs over 2–4 months, where the last scans were obtained after discharge. The laboratory data including white blood cell count, platelet count, neutrophil count, lymphocyte count, C-reactive protein (CRP), procalcitonin, and interleukin-6 (IL-6) were obtained from electronic medical records.
Results
Rapid progression was observed in 10.4% (23/222) of patients. All QCOVID scores predicted rapid progression, with QMD showing the best predictability (area under the curve, AUC = 0.813, p < 0.001). In multivariate analyses, QMD, CRP, and IL-6 were important predictors (AUCs:0.86–0.87). Patients with a high QMD score (≥ 10%) likely progressed > 10 folds (p < 0.001). QCOVID scores were positively correlated with the neutrophil count, neutrophil-to-lymphocyte ratio, CRP, and IL-6 levels. In 21 subjects with > 2 months follow-up, parenchymal areas were still observed with a QTLD of 1.4–29.3%, even after several weeks of negative reverse transcription polymerase chain reaction test.
Conclusions
AI-driven quantitative scores can be useful in predicting the rapid progression and monitoring of COVID-19 with other laboratory markers.
Hydrothermally grown defect-free ZnO nanorods with high angular distribution for enhanced excitonic emission
Authors: Fiedler Saskia , Ton-That Cuong , Phillips Matthew R. 
Published: August 2022

Abstract
Low-temperature hydrothermal growth has emerged as a popular method for the fabrication of ZnO nanorods (NRs), increasing the functionality and utility of ZnO-based devices. In this work, we study the influence of growth time, temperature and seed layer on the dimensions and angular distribution of hydrothermally grown ZnO NRs. High-quality ZnO NRs with a crisscrossed 60° angular distribution with respect to the substrate normal have been grown with a small diameter (20–60 nm) and a length of approximately 600 nm. We show that, within the ideal range of growth parameters (70–100°C for 2–4 hours), the growth time and temperature have no controllable influence on diameter and length, while the deposition method and size of the pre-growth deposited ZnO seeds affects diameter and NR angular alignment. Control over both is important for device structures involving wave-guided, angular dependent light emission and for high sensitivity and speed of chemical sensors. Furthermore, we demonstrate advantages of using crisscross-aligned ZnO NRs over planar ZnO for the enhancement of ZnO excitonic emission by optical coupling with gold nanoparticles (NPs). These results can be readily adapted for various applications that involve surface (NP) coating-mediated enhancement of both light emission or injection.
Development of a nomogram to predict hospitalized mortality of patients with sepsis
Authors: Cheng Kun , Yu Guangwei , Zhou XiaoFen , Lin Fenghui 
Published: August 2022

Abstract
Background
Sepsis is a severe organ dysfunction caused by infection, which is a leading cause of morbidity and mortality in critically ill patients. We developed a novel risk-predicted nomogram of hospitalized mortality for this retrospective study.
Methods
The study involved a retrospective analysis of sepsis patients diagnosed between January 2013 and December 2019. Based on clinical outcomes, patients were categorized into a survival group and a death group. Using logistic regression analysis, a predictive model with a nomogram was formulated in the training set, after which internal validation and sensitivity analysis were performed. C-index and calibration curves were used in the training and validation cohorts to evaluate nomogram discrimination and calibration. Utilizing decision curve analysis, an assessment of the clinical utility of the final nomogram was conducted.
Results
A total of 494 patients were enrolled for analysis. In the multivariate analysis, cardiac function (OR: 1.58, P = 0.039) stood out as an independent sepsis risk factor, whereas hemoglobin (OR: 0.98, P = 0.025) served as a protective factor. Although the multivariate regression analysis did not detect any significant differences in AKI staging, in light of the previous studies, a nomogram for the prediction of hospitalized sepsis mortality was constructed by taking into account these three factors. Based on this model's C-index of 0.626, it suggested moderate predictive power.
Conclusions
Our study indicates that patients with sepsis in combination with anemia, cardiac dysfunction, and AKI are associated with significantly high mortality. To some extent, this may contribute to the determination of risk assessments and treatment strategies.
Defining priorities areas for biodiversity conservation and trading forest certificates in the Cerrado biome in Brazil
Authors: Schwaida Samuel Fernando , Cicerelli Rejane , Almeida Tati , Sano Edson Eyji , Pires Carlos Henrique , Ramos Ana Paula Marques 
Published: August 2022

Abstract
Habitat loss and natural vegetation fragmentation are significant causes of global biodiversity decline, impacting plant and animal species negatively. This issue is worrisome in the private areas of Cerrado in Brazil, which is the second-largest biome, considered a hotspot for biodiversity conservation, and a provider of ecosystem services. Herein, we present a novel integrated approach to define priority areas for biodiversity conservation and environmental compensation in Cerrado, using multicriteria analysis. Our approach combines variables like deforestation projection, integral connectivity index, threatened species occurrence, and environmental information of rural properties, ranking the importance of remaining native vegetation for biodiversity conservation and forest certificate issuance. Landscape metrics were used to observe and predict land use and land cover changes from 1988 to 2038. We found a loss of native vegetation in the Cerrado superior to 20% between 1988 and 2018, associated with increased of its fragmentation and its connectivity loss, especially after 2008. Moreover, we determined that is expected a loss of native vegetation of around 55% by 2038 in Cerrado. Its natural cover was replaced by pasture mostly, and agriculture more recently. The proposed approach can predict the consequences of future changes in the landscape of the private areas in the Cerrado biome. It should be replicated in other ecosystems, supporting the decision-making process for biodiversity protection.
Estimating population ITN access at council level in Tanzania
Authors: Koenker Hannah , Worges Matt , Yukich Joshua , Gitanya Peter , Chacky Frank , Lazaro Samwel , Mwalimu Charles Dismas , Aaron Sijenunu , Ibrahim Raya , Abbas Faiza , Khamis Mwinyi , Mwingizi Deodatus , Dadi David , Selby Ato , Serbantez Naomi , Msangi Lulu , Loll Dana , Kamala Benjamin 
Published: August 2022

Abstract
BackgroundSince 2013, the National Malaria Control Program in mainland Tanzania and the Zanzibar Malaria Elimination Program have implemented mass ITN campaigns, routine ITN distribution to pregnant women and infants, and continuous distribution through primary schools (mainland) and community leaders (Zanzibar) to further malaria control efforts. Mass campaigns are triggered when ITN access falls below 40%. In this context there is a need to monitor ITN access annually to assess whether it is below threshold and inform quantification of ITNs for the following year. Annual estimates of access are needed at the council level to inform programmatic decision making.MethodsAn age-structured stock and flow model was used to predict annual net crops from council-level distribution data in Tanzania from 2012-2020 parameterized with a Tanzania-specific net median lifespan of 2.15 years. Annual nets-per-capita (NPC) was calculated by dividing each annual net crop by mid-year council projected population. A previously fit nonparametric conditional quartile function for the proportion of the population with access to an ITN (ITN access) as a function of NPC was used to predict ITN access at the council level based on the predicted NPC value. These estimates were compared to regional-level ITN access from large household surveys. ResultsFor regions with the same ITN strategy for all councils, predicted council-level ITN access was consistent with regional-level survey data for 79% of councils. Regions where ITN strategy varied by council had regional estimates of ITN access that diverged from the council-specific estimates. Predicted ITN access reached 60% only when “nets issued as a percentage of the council population” (NPP) exceeded 15%, and approached 80% ITN access when NPP was at or above 20%.ConclusionModeling ITN access with country-specific net decay rates, council-level population, and ITN distribution data is a promising approach to monitor ITN coverage sub-regionally and between household surveys in Tanzania and beyond.
Groundwater Level Monitoring Networks Design with Machine Learning Methods
Authors: Teimoori Sadaf , Olya Mohammad Hessam , Miller Carol 
Published: August 2022

Abstract
Collecting and analyzing groundwater data are essential to evaluate the regional groundwater flow patterns and quality under existing and future temporal/spatial hydraulic stressors. These data also provide researchers with the information required to calibrate the groundwater models and study the interaction between surface water and groundwater resources. In general, frequent and well-organized groundwater monitoring improves the comprehension of groundwater systems and enhances groundwater resource management. Both surface water and groundwater quality monitoring networks have been extensively studied and presented in literature reviews. In contrast, there is much less literature focused on groundwater level monitoring networks. In many regions, groundwater level monitoring networks are limited and do not provide sufficient data for decision-making purposes. This gap in data availability is due to multiple reasons but includes financial constraints and the limited interest in those areas that rely more heavily on surface water resources for human consumption and industrial purposes. Here, we introduce methods employing K-means clustering and/or Relevance Vector Machine to design an optimal groundwater level monitoring network. The machine learning algorithms utilize the hydrogeological datasets obtained from the initial groundwater MODFLOW models and consider the uncertainties in the aquifer characterization through stochastic simulations. The result of this research is three groundwater level monitoring networks which the optimal one is selected based on the minimum modeling error. The network configurations are demonstrated in terms of the number and location of the observation wells. The proposed monitoring network improves the procedure of groundwater modeling and significantly reduces modeling errors.
Dynamic Response Analysis of Coastal Piled Bridge Pier Subjected to Current, Wave and Earthquake Actions with Different Structure Orientations
Authors: Alsultani Riyadh A.A. , Karim Ibtisam R. , Khassaf Saleh I. 
Published: August 2022

Abstract
The goal of the experiment described in this paper was to examine the effects of structure orientation (0° to 90°) and fluid-structure interaction (FSI) under combined water loads, represented by water current and waves, and earthquake actions, on the dynamic response of a reduced-scale bridge pier specimen with pile foundation. The peak relative displacement and peak acceleration of the specimen are measured using first time innovative in Iraq, Reality Water-Structure-Earthquake Interaction Test (RWSEIT). The findings are given and analyzed in relation to water depths, current speed, wave characteristics, earthquake amplitudes, and structural orientations. A numerical model of the examined specimen with three dimensions (3D) was constructed, and the findings were successfully confirmed using the data from the experiments. A pile foundation bridge pier's 3D structural response under orientations that cannot be tested in a lab was computed using the constructed numerical model. The complicated dynamically produced FSI effects on the response of coastal pile foundation bridges may be better understood according to the research's experimental and numerical findings.