bluuebunny/crossref_metadata_2025_split huggingface dataset:
Make nature's role visible to achieve the SDGs
Authors: Hole David G. , Collins Pamela , Tesfaw Anteneh , Barrera Lina , Mascia Michael B. , Turner Will R. 
Published: April 2022

Non-technical summaryImplicit in the UN's Sustainable Development Goal (SDG) Agenda is the notion that environmental sustainability is intertwined with, and underpins, the 17 Goals. Yet the language of the Goals, and their Targets and indicators is blind to the myriad ways in which nature supports people's health and wealth – which we argue represents a key impediment to progress. Using examples of nature–human wellbeing linkages, we assess the language of all 169 Targets to identify urgent research, policy, and action needed to spotlight and leverage nature's foundational role, to help enable truly sustainable development for all.Technical summaryNature's foundational role in helping achieve the SDGs is implicit rather than explicit in the language of SDGs Goals, Targets, and indicators. Drawing from the scientific literature describing how nature underpins human wellbeing, we carry out a systematic assessment of the language of all 169 Targets, categorizing which Targets aredependentupon nature for their achievement, couldharmnature if attained through business-as-usual actions, or may synergisticallybenefitnature through their attainment. We find that half are dependent upon nature for their achievement – yet for more than two-thirds of those nature's role goes unstated and risks being downplayed or ignored. Moreover, while achieving the overwhelming majority of the 169 Targets could potentially benefit nature, more than 60% are likely to deliver ‘mixed outcomes’ – benefitting or harming nature depending on how they're achieved. Furthermore, of the 241 official indicators <5% track nature's role in achieving the parent Target. Our analysis provides insights important for increasing effectiveness across the SDG agenda regarding where to invest, how to enhance synergies and limit unanticipated impacts, and how to measure success. It also suggests a path for integrating the ‘nature that people need’ to achieve the SDGs into the CBD's post-2020 Global Biodiversity Framework.Social media summaryHarmonizing links between the SDGs and the CBD's post-2020 Global Biodiversity Framework is vital for promoting sustainable development
Remotely Sensed Carbonyl Sulfide Constrains Model Estimates of Amazon Primary Productivity
Authors: Stinecipher James R. , Cameron‐Smith Philip , Kuai Le , Glatthor Norbert , Höpfner Michael , Baker Ian , Beer Christian , Bowman Kevin , Lee Meemong , Miller Scot M. , Parazoo Nicholas , Campbell J. Elliott 
Published: April 2022

AbstractUnderstanding the magnitude of tropical gross primary production (GPP) is critical for carbon cycle modeling and climate projections, but this quantity is poorly constrained at regional scales. Biospheric uptake of carbonyl sulfide (OCS) provides a promising approach to estimating regional GPP. Here, we simulate OCS concentrations driven by surface flux scenarios encompassing a wide range of GPP estimates for the Amazon basin. We compare the model output to satellite retrievals and find a regional GPP estimate of 2375 ± 914 g(C) m−2 yr−1, consistent with previous estimates, including the TRENDY model ensemble range of 1431–3812 g(C) m−2 yr−1.
Trace H2S Promotes Organic Aerosol Production and Organosulfur Compound Formation in Archean Analog Haze Photochemistry Experiments
Authors: Reed Nathan W. , Wing Boswell A. , Tolbert Margaret A. , Browne Eleanor C. 
Published: April 2022

AbstractOrganic haze and sulfur gases are ubiquitous in planetary atmospheres and were likely present in Earth's Archean atmosphere. Currently, there are few experiments investigating how H2S influences organic haze chemistry on Archean Earth. Here, we present results from laboratory haze‐analog experiments probing the role of H2S in the composition and total mass of aerosol produced from precursor mixtures of Archean‐like gas fluxes (e.g., pCO2 ∼3–50xPAL). We show that trace H2S enhances organic aerosol production at all carbon dioxide mixing ratios studied, and we observe both organic and inorganic sulfur aerosol products. Our finding challenges predictions that H2SO4 and S8 were the primary sulfur reservoirs in Earth's Archean atmosphere, and these results suggest that inorganic sulfur and organic haze chemistry are tightly coupled during the formation of organic hazes in the atmospheres of the Archean Earth and likely Archean‐like exoplanets.
Slow Contraction of Flash Aurora Induced by an Isolated Chorus Element Ranging From Lower‐Band to Upper‐Band Frequencies in the Source Region
Authors: Ozaki Mitsunori , Yagitani Satoshi , Shiokawa Kazuo , Tanaka Yoshimasa , Ogawa Yasunobu , Hosokawa Keisuke , Kasahara Yoshiya , Ebihara Yusuke , Miyoshi Yoshizumi , Imamura Kousuke , Kataoka Ryuho , Oyama Shin‐ichiro , Chida Teppei , Kadokura Akira 
Published: April 2022

AbstractFlash aurora driven by an isolated chorus element can be a useful ionospheric indicator for identifying the source wave properties via wave‐particle interactions. Using ground observation and modeling approaches, here we report the temporal characteristics of flash aurora that depend on the chorus frequency width and the sweep rate. We found that the contraction time increases more than the expansion time in patchy auroral variations, due to the difference in the minimum electron energies resonated with the chorus wave packet away from the equatorial source to higher latitudes. Especially, the contraction time strongly depends on the higher‐frequency chorus waves due to cyclotron resonance with lower‐energy electrons. The model calculations support that the chorus element ranges from lower‐band to upper‐band frequencies with respect to half the gyrofrequency at the exact generation region. Our study provides the prompt (milliseconds) chorus‐driven electron dynamics through the spatiotemporal characteristics of flash aurora in the ionosphere.
Deep Learning for Global Ionospheric TEC Forecasting: Different Approaches and Validation
Authors: Ren Xiaodong , Yang Pengxin , Liu Hang , Chen Jun , Liu Wanke 
Published: April 2022

AbstractThe application of deep learning technology to ionospheric prediction has become a new research hotspot. However, there are still some gaps, such as the prediction effect with different input solar and geomagnetic activity parameters, and the forecast accuracy with different prediction methods as well as the validation of long period data results, to be filled. We developed an ionospheric long short‐term memory network (Ion‐LSTM) with multiple input parameters to predict the global ionospheric total electron content (TEC). Two solutions with different ionospheric data based on Ion‐LSTM were assessed, namely spherical harmonic coefficients (SHC) and vertical TEC (VTEC) prediction solution. The results show two solutions, both perform well in accuracy and stability. The input of the geomagnetic activity index improves the prediction effect of the model in the storm period. For the 1‐ and 2‐day‐predicted global ionospheric maps (GIMs) from 2015 to 2020, the root mean square error (RMSE) of SHC prediction solution is 1.69 TECU and 1.84 TECU while that of the VTEC prediction solution is 1.70 TECU and 1.84 TECU, respectively. Over 70% of the absolute residuals are within 3 TECU in high solar activity and over 96% in low solar activity. Further, by comparing the predicted results between Ion‐LSTM and conventional methods (e.g., Center for Orbit Determination in Europe (CODE) predicted GIMs), the evaluation results show that the RMSE of Ion‐LSTM is 0.7 TECU lower than that of CODE predicted GIMs under different solar and geomagnetic activities. Additionally, the accuracy of the Ion‐LSTM prediction results decreases slightly as the input time span increases.
Multivariate Regional Frequency Analysis Using Conditional Extreme Values Approach
Authors: Kiran K. G. , Srinivas V. V. 
Published: April 2022

AbstractFloods can be characterized by various correlated variables such as peak flow, flood volume, duration, and time to peak. Hence, flood risk can be better assessed by performing frequency analysis in a multivariate (rather than a univariate) framework. However, multivariate approaches involve sophisticated analyses that require considerably more data than univariate approaches. In a univariate framework, flood risk assessment at an ungauged or data‐sparse location/site is generally performed through regional frequency analysis (RFA), based on information pooled from a group of sites resembling the target site. However, RFA has received little attention in the multivariate framework. The available literature recommends the use of index‐flood approach (IFA) for multivariate RFA (MRFA), even though IFA has theoretical shortcomings. Another issue is that marginals of all the flood‐related variables may not exhibit extreme behavior simultaneously. Conventionally used at‐site multivariate models are not suitable for describing the dependence structure of extremes in the regions of the support of the joint distribution where only some variables exhibit extreme behavior. This article proposes a conditional extreme values approach (CEA) to address the aforementioned issues in MRFA. Its effectiveness is demonstrated through Monte Carlo simulation experiments and a case study on watersheds from a flood‐prone region in India. Results indicate that the proposed approach can reliably predict the joint distribution of multiple flood‐related variables (and thus flood risk) at ungauged/sparsely gauged sites by effectively capturing the regional dependence structure between those variables.
Leakage From Coexisting Geologic Forcing and Injection‐Induced Pressurization: A Semi‐Analytical Solution for Multilayered Aquifers With Multiple Wells
Authors: Cihan A. , Oldenburg C. M. , Birkholzer J. T. 
Published: April 2022

AbstractAbnormal fluid pressures (above or below hydrostatic pressure) can develop and persist in sedimentary basins. The common occurrence of abnormal pressures may cause challenges for project permitting of geological carbon sequestration (GCS), particularly in reservoirs with pre‐injection overpressure. The leaky wells that may exist in some sedimentary basins can provide flow paths between deep brine aquifers and shallower freshwater aquifers. Pre‐injection relative overpressures can cause brine leakage through leaky wells even before any injection occurs. The tendency for flow through leaky wells is coupled with the process of pressure dissipation that occurs through aquitards. Specifically, with non‐zero permeability, aquitards can dissipate pressure over large areal extents and thereby reduce leakage rates through leaky wells. This study presents development of a semi‐analytical solution for hydraulic head and brine leakage in multilayered aquifer–aquitard systems with geologic pressure forcing. The geologic forcing that causes abnormal pressures in the multilayered system can coexist with any number of injection, extraction, and leaky wells that also affect fluid pressure. The semi‐analytical model is applied to explore how leakage through leaky wells varies as functions of pressurization rate, along with aquitard and leaky well properties in an overpressured multilayered system. The results show that although injection‐induced pressures can dissipate rapidly through suitably permeable aquitards, coexisting geologic forcing may create sustained rates of brine leakage into freshwater aquifers through leaky wells. In GCS, a very low‐permeability aquitard with high capillary entry pressure to free‐phase CO2 is desired to serve as the caprock to prevent leakage of CO2 from the storage reservoir. Nevertheless, the results from this study show that the brine leakage impact to shallow freshwater aquifers through leaky wells might substantially decrease with increasing aquitard permeability values, as long as small aquitard permeability and high capillary entry pressure serve to prevent CO2 leakage.
Managing direct oral anticoagulants in accordance with the Scottish Dental Clinical Effectiveness Programme guidance for patients undergoing dentoalveolar surgery
Authors: Woolcombe Sarah A. , Ball Rebecca E. , Patel Jignesh P. 
Published: April 2022

AbstractIntroduction The Scottish Dental Clinical Effectiveness Programme (SDCEP) guidance on the management of dental patients taking anticoagulant or antiplatelet drugs provides recommendations on the management of patients taking direct oral anticoagulants (DOACs). This guidance was developed by a multidisciplinary Guidance Development Group, based on available resources at the time of publication. We aim to describe our experience of managing a cohort of adult patients prescribed DOACs, undergoing dentoalveolar procedures in accordance with the SDCEP guidance, between April 2017 and March 2020.Methods As part of our routine practice, patients received a telephone consultation one week following treatment, to assess any post-operative bleeding. Review of the clinical notes was used to assess clinician adherence to the guidance recommendations.Results In total, 98 patients underwent 119 dentoalveolar procedures. Persistent bleeding followed 17 (14.3%) procedures, of which 11 (9.2%) procedures required specific intervention. Absolute compliance with the recommendations was 43.7%, supporting the recommendation for audit and staff education.Discussion A diagnosis of heart failure and advanced age were identified as contributory factors to post-operative bleeding.Conclusions The SDCEP guidance is safe to follow, with no patients experiencing major haemorrhage. Consulting a medical specialist for patients with heart failure of likely significance, based on the medical or drug history, in addition to those who report an advanced heart failure diagnosis and the frail/older person, could reduce the incidence of post-operative bleeding.
Concatenated convolutional neural network model for cuffless blood pressure estimation using fuzzy recurrence properties of photoplethysmogram signals
Authors: Malayeri Ali Bahari , Khodabakhshi Mohammad Bagher 
Published: April 2022

AbstractDue to the importance of continuous monitoring of blood pressure (BP) in controlling hypertension, the topic of cuffless BP estimation has been widely studied in recent years. A most important approach is to explore the nonlinear mapping between the recorded peripheral signals and the BP values which is usually conducted by deep neural networks. Because of the sequence-based pseudo periodic nature of peripheral signals such as photoplethysmogram (PPG), a proper estimation model needed to be equipped with the 1-dimensional (1-D) and recurrent layers. This, in turn, limits the usage of 2-dimensional (2-D) layers adopted in convolutional neural networks (CNN) for embedding spatial information in the model. In this study, considering the advantage of chaotic approaches, the recurrence characterization of peripheral signals was taken into account by a visual 2-D representation of PPG in phase space through fuzzy recurrence plot (FRP). FRP not only provides a beneficial framework for capturing the spatial properties of input signals but also creates a reliable approach for embedding the pseudo periodic properties to the neural models without using recurrent layers. Moreover, this study proposes a novel deep neural network architecture that combines the morphological features extracted simultaneously from two upgraded 1-D and 2-D CNNs capturing the temporal and spatial dependencies of PPGs in systolic and diastolic BP estimation. The model has been fed with the 1-D PPG sequences and the corresponding 2-D FRPs from two separate routes. The performance of the proposed framework was examined on the well-known public dataset, namely, multi-parameter intelligent in Intensive Care II. Our scheme is analyzed and compared with the literature in terms of the requirements of the standards set by the British Hypertension Society (BHS) and the Association for the Advancement of Medical Instrumentation (AAMI). The proposed model met the AAMI requirements, and it achieved a grade of A as stated by the BHS standard. In addition, its mean absolute errors and standard deviation for both systolic and diastolic blood pressure estimations were considerably low, 3.05 ± 5.26 mmHg and 1.58 ± 2.6 mmHg, in turn.
A cross-sectional analysis about bacterial vaginosis, high-risk human papillomavirus infection, and cervical intraepithelial neoplasia in Chinese women
Authors: Xu Xiaolin , Zhang Yichan , Yu Liqun , Shi Xingxian , Min Min , Xiong Lijuan , Pan Jia , Liu Peipei , Wu Guizhen , Gao Guolan 
Published: April 2022

AbstractBacterial vaginosis (BV) is a genital infection that frequently presents in women infected with human papillomavirus (HPV), but the correlation between BV, HPV and cervical intraepithelial neoplasia (CIN) development is still elusive. We organized a cross-sectional analysis which enrolled 624 participants and obtained 423 samples of vaginal secretions from them, including 193 HPV-negative samples and 230 HR-HPV-positive samples. We used 16S rRNA sequencing to measure the vaginal microbiota diversity in women with different BV, HPV and CIN status, and then calculated risk factors for CIN by logistic regression. We found that the diversity of vaginal microbiota was significantly increased after BV, HPV and BV-infected CIN group. The Observed species and Chao1 index of H.C group showed little difference with normal group, while its Shannon index was considerable higher than normal group. L. iners enriched in HPV infection group compared with others significantly. BV (OR = 0.358; 95% CI = 0.195–0.656; P < .05) and HR-HPV infection (OR = 0.016; 95% CI = 0.004–0.072; P < .001) were risk factors for CIN. In conclusion, we consider BV as a risk factor for CIN. The enrichment of L. iners under HPV infection state may contribute to maintenance of vaginal dysbiosis, and BV infection could facilitate the disturb.
Protein-bound sialic acid in saliva contributes directly to salivary anti-influenza virus activity
Authors: Kobayashi Kaori , Shono Chika , Mori Takuya , Kitazawa Hidefumi , Ota Noriyasu , Kurebayashi Yuki , Suzuki Takashi 
Published: April 2022

AbstractThe oral cavity is an entrance for respiratory viruses, such as influenza. Recently, saliva has been shown to exert both antimicrobial and antiviral activities. Thus, saliva may be a biological factor that contributes to the prevention of influenza infection. However, the actual salivary anti-influenza A virus (IAV) activity in individuals and its determinant factors are unknown. By assessing individual variations in salivary anti-IAV activity in 92 people using an established new high-throughput system in this study, we found that the anti-IAV activity varied widely between individuals and showed a significant positive correlation with protein-bound sialic acid (BSA) level (ρ = 0.473;p < 0.001). Furthermore, the anti-IAV activity of saliva with enzymatically reduced BSA content was significantly lower. These results indicate that BSA is a direct regulator of salivary anti-IAV activity and is a determinant of individual differences. Additionally, after comparing the anti-IAV activity across the groups by age, anti-IAV activity in young people (aged 5–19 years) were lower than in adults aged 20–59 years and elderly people aged 60–79 years. Our study suggests that BSA levels in saliva may be important in preventing influenza infection.
ADAM12 is an independent predictor of poor prognosis in liver cancer
Authors: Du Shuangqiu , Sun Linlin , Wang Yun , Zhu Wenhao , Gao Jialin , Pei Wenjun , Zhang Yao 
Published: April 2022

AbstractDisintegrin and metalloproteinase 12 (ADAM12) is thought to trigger the occurrence and development of numerous tumours, including colorectal, breast, and pancreatic cancers. On the basis of The Cancer Genome Atlas (TCGA) datasets, in this study, the relationship between ADAM12 gene expression and hepatocellular carcinoma (HCC), the prognostic value of this relationship, and the potential mechanisms influencing HCC development were evaluated. The results showed that the ADAM12 gene was significantly and highly expressed in liver cancer tissue. The high expression of the ADAM12 gene in liver cancer tissue significantly and positively correlated with T stage, pathological stage, and residual tumour. Kaplan–Meier and Cox regression analyses revealed that ADAM12 gene expression is an independent risk factor influencing the prognosis of patients with liver cancer. Pathway analyses of ADAM12 in HCC revealed ADAM12-correlated signalling pathways, and the expression level of ADAM12 was associated with immune cell infiltration. In vitro experiments demonstrated that the expression level of ADAM12 in Huh-7 and Hep3B cells was significantly higher than that in other HCC cells. ShRNA transfection experiments confirmed that the expression levels of TGF-β and Notch pathway-related proteins were significantly decreased. An EdU cell proliferation assay showed that a low level of ADAM12 gene expression significantly inhibited the proliferative activity of HCC cells. Cell cycle experiments showed that low ADAM12 expression blocked the G1/S phase transition. Overall, this research revealed that high ADAM12 gene expression implies a poor prognosis for patients with primary liver cancer. In addition, it is a potential indicator for the diagnosis of liver cancer.
Uterine fibroids increase the risk of thyroid goiter and thyroid nodules
Authors: Yuk Jin-Sung , Kim Jung Min 
Published: April 2022

AbstractUterine fibroid and benign thyroid disease are both common diseases in women. This study aimed to evaluate whether these diseases are related. We established the uterine fibroid group according to diagnosis and surgery codes using the Korea National Health Insurance data from 2009 to 2020. All women from 20 to 50 years old who underwent uterine myomectomy from 2009 to 2020 were identified. We selected the control group by performing a 1:1 propensity score matching on age at 5-year intervals, socioeconomic status (SES), region, Charlson comorbidity index (CCI), menopause, and year among women who visited a medical institution for a health check-up. Thyroid disease cases were selected using the thyroid disease diagnosis code and thyroid-associated laboratory tests. A total of 181,419 patients were included in the uterine fibroid and control groups. The median age of each group was 40 (range, 35 ~ 44) and 40 (range, 35 ~ 45) years old, respectively. Benign thyroid disease affected 1162 (0.6%) in the uterine fibroid group and 1137 (0.6%) in the control group. Among the benign thyroid diseases, hypothyroidism was the most common in both groups, followed by a nontoxic single thyroid nodule. The uterine fibroid group had a higher risk of thyroid goiter (hazard ratio (HR) 1.169, 95% confidence interval (CI) 1.022–1.338), nontoxic single thyroid nodule (HR 1.268, 95% CI 1.182–1.361), and total thyroid disease (HR 1.078, 95% CI 1.036–1.121) in stratified Cox regression analysis adjusted for age, SES, region, CCI, parity, menopause, hypertension, diabetes, dyslipidemia, systemic lupus erythematosus, irritable bowel syndrome, Crohn’s disease, and endometriosis than the control group. The results suggest that women with uterine fibroids have an increased risk of thyroid goiters and thyroid nodules. Although the mechanism is not well known, estrogen and iodide might be a link between uterine fibroids and thyroid goiters and nodules. Future studies that prospectively follow women with uterine fibroids across a lifetime are needed.