bluuebunny/crossref_metadata_2025_split huggingface dataset:
When one door closes: a qualitative exploration of women’s experiences of access to sexual and reproductive health services during the COVID-19 lockdown in Nigeria
Authors: Adelekan Babatunde , Ikuteyijo Lanre , Goldson Erika , Abubakar Zubaida , Adepoju Oluwatomi , Oyedun Olaitan , Adebayo Gbenga , Dasogot Andat , Mueller Ulla , Fatusi Adesegun O. 
Published: July 2022

Abstract

BackgroundCOVID-19 pandemic widely disrupted health services provision, especially during the lockdown period, with females disproportionately affected. Very little is known about alternative healthcare sources used by women when access to conventional health services became challenging. This study examined the experiences of women and adolescent girls regarding access to sexual and reproductive health (SRH) services during the COVID-19 lockdown in Nigeria and their choices of alternative healthcare sources.MethodsThe study sites were two northern states, two southern states, and the Federal Capital Territory. Qualitative data were obtained through 10 focus group discussion sessions held with married adolescents, unmarried adolescents, and older women of reproductive age. The data were transcribed verbatim and analysed using a thematic approach and with the aid of Atlas ti software.ResultsWomen reported that access to family planning services was the most affected SRH services during the COVID-19 lockdown. Several barriers to accessing SRH services during COVID-19 lockdown were reported, including restriction of vehicular movement, harassment by law enforcement officers, fear of contracting COVID-19 from health facilities, and fear of undergoing compulsory COVID-19 tests when seeking care in health facilities. In the face of constrained access to SRH services in public sector facilities during the COVID-19 lockdown, women sought care from several alternative sources, mostly locally available and informal services, including medicine vendors, traditional birth attendants, and neighbours with some health experience. Women also widely engaged in self-medication, using both orthodox drugs and non-orthodox preparations like herbs. The lockdown negatively impacted on women’s SRH, with increased incidence of sexual- and gender-based violence, unplanned pregnancy resulting from lack of access to contraceptives, and early marriage involving adolescents with unplanned pregnancies. ConclusionCOVID-19 negatively impacted access to SRH services and forced women to utilise mostly informal service outlets and home remedies as alternatives to conventional health services. There is a need to ensure the continuity of essential SRH services during future lockdowns occasioned by disease outbreaks. Also, community systems strengthening that ensures effective community-based health services, empowered community resource persons, and health-literate populations are imperative for overcoming barriers to healthcare access during future lockdowns.
Link between Seashore Water Temperature and Open Ocean State in Peru
Authors: Masuda Shuhei , Kobayashi Masato , Salas Luis Alfredo Icochea , Quintana Gandy Maria Rosales 
Published: July 2022

Abstract
The link between the coastal ocean and the open sea varies greatly by region. This factor must be elucidated to consider climate projections for a particular coastal region. This study examines this link between coastal areas in Peru and open seas. Water temperature loggers were installed at six sites along the Peruvian coast between 2017 and 2020. The obtained data and that from the EN4 dataset of the open ocean were compared. The coastal water temperature changes in Peru correlates well with the open ocean sea surface temperature in terms of monthly mean anomalies. The correlation coefficient values range from 0.80 to 0.92 with a > 99% confidence level except for one observation point (0.26). This suggests a global ocean observation system underlying EN4 can directly contribute to a reliable climate (water temperature) prediction of coastal areas in Peru. On shorter timescales, the logger-derived temperature changes show spectral peaks at 80 and 120 days north of 5°S, suggesting the coastal monitoring can capture the sub-seasonal dynamical aspects of equatorial Kelvin waves. In contrast, clear peaks are not detected south of 5ºS, implying that a practical leak of equatorial wave energy into off-equatorial regions is not anticipated along Peruvian coast on this time scale.
Inhibition of XPO1 with KPT-330 induces autophagy-dependent apoptosis in gallbladder cancer by activating the p53/mTOR pathway
Authors: Zhao Cheng , Yang Zi-yi , Zhang Jian , Li Ou , Liu Shi-lei , Cai Chen , Shu Yi-jun , Pan Li-jia , Gong Wei , Dong Ping 
Published: July 2022

Abstract
Background
Gallbladder cancer (GBC) is a highly aggressive malignant cancer in the biliary system with poor prognosis. XPO1 (chromosome region maintenance 1 or CRM1) mediates the nuclear export of several proteins, mainly tumor suppressors. Thus, XPO1 functions as a pro-oncogenic factor. KPT-330 (Selinexor) is a United States Food and Drug Administration approved selective inhibitor of XPO1 that demonstrates good therapeutic effects in hematologic cancers. However, the function of XPO1 and the effect of KPT-330 have not been reported in GBC.
Methods
We analyzed the correlation between XPO1 expression levels by q-PCR and clinical features of GBC patients. Cell proliferation assays were used to analyze the in vitro antitumor effects of XPO1 inhibitor KPT-330. mRNA sequencing was used to explore the underlying mechanisms. Western blot was performed to explore the relationship between apoptosis and autophagy. The in vivo antitumor effect of KPT-330 was investigated in a nude mouse model of gallbladder cancer.
Results
We found high expression of XPO1 was related to poor prognosis of GBC patients. We observed that XPO1 inhibitor KPT-330 the proliferation of GBC cells in vitro. Furthermore, XPO1 inhibitor KPT-330 induced apoptosis by reducing the mitochondrial membrane potential and autophagy in NOZ and GBC-SD cells. Indeed, KPT-330 led to nuclear accumulation of p53 and activated the p53/mTOR pathway to regulate autophagy-dependent apoptosis. Importantly, KPT-330 suppressed tumor growth with no obvious toxic effects in vivo.
Conclusion
XPO1 may be a promising prognostic indicator for GBC, and KPT-330 appears to be a potential drug for treating GBC effectively and safely.
Network distance teaching of minimally invasive spinal endoscopic surgery video of orthopedist amid COVID-19 pandemic
Authors: Wu Jianxin , Qiu Yuanyuan , Xiao Bing , Ye Xiaojian , Shi Zhicai , Xu Guohua , Xi Yanhai , Wang Weiheng 
Published: July 2022

Abstract
Background: The global outbreak of COVID-19 has prompted reforms in the teaching model of orthopedics. The wide spread of mutant strains such as Omicron has put the epidemic prevention and control in a high-pressure state for a long time in China. Due to the control of people gathering and social distancing restrictions, offline medical training and education have been greatly affected. The traditional spinal endoscopic surgery training mode cannot meet the increasing training needs of spine surgeons. This study aimed to explore the network distance teaching of minimally invasive spinal endoscopic surgery (MISES) videos of orthopedist amid COVID-19 pandemic.Methods: From January 2021 to June 2022, 76 orthopaedical surgeons who were trained in the orthopedics department of Shanghai Changzheng Hospital were selected to do network distance teaching. After the 2-month training, the training effect assessment and the satisfaction survey of trainers were conducted. Results: After an average of 2 months of training, the average examination score of trainees was 87.211±7.278, and the pass rate was 100%, the excellent and good rate was 92.11%. The results of the satisfaction survey showed that the overall satisfaction was as high as 88.184±6.560%. The videos database of MISES, as well as the distance teaching and training mode are continuously improved according to the satisfaction survey.Conclusions: The training mode of MISES network distance teaching can help orthopedic surgeons to quickly master MISES and improve the training effect, especially amid COVID-19.
Functional Gastrointestinal Disorders Qualified for Both Upper and Lower Abdominal Pains and Its Associated Factors among Adults in Urban Community of Jimma, Southwest Ethiopia
Authors: Zawdie Belay , Hassen Kalkidan , Tamiru Desalegn , Belachew Tefera 
Published: July 2022

Abstract
Background
The occurrence of multiple Functional Gastrointestinal Disorders (FGIDs) and their potentiation risk factors are varying substantially from region to region. Therefore, this study aims to detect multiple FGIDs qualified for both upper and lower abdominal pains and associated factors in the urban community of Jimma. Southwest Ethiopia.
Methods
A cross-sectional community based was used to select 865 adults in Jimma town aged ≥ 18 years. Structured questionnaires were used retrospectively to collect data on multiple FGIDs. A stepwise approach was employed to collect socio-demographic, behavioural, anthropometric, biomarkers and clinical measurements data. For screening multiple FGIDs symptoms among the study population, Rome III criteria was employed. Data was entered to Epi Data version 3.1 and export to SPSS version 27. Bivariate and multivariate logistic regression analyses were used to assess the association between explanatory variables and the outcome variable. The association was declared at p < 0.05
Results
More than half of study participants, 52%, were males. The mean age of the study participants was 38.4 ± 13.5 years. The prevalence of unrecognized FGIDs qualified for both upper and lower abdominal pain was, 19.4%. However, the occurrences of FGIDs qualified for only upper abdominal pain(dyspepsia) and lower abdominal pain were 17.6% and 15.5% respectively. In the multivariable analysis, khat chewing [AOR (95% CI) 7.37(1.76–30.87)], alcohol conception [AOR (95% CI) 3.24(1.15–9.18), low-income wealth index [AOR (95% CI) 2.63(1.16–5.96)], using butter or ghee and margarine[AOR (95% CI) 6.79(2.82–16.37) ], sedentary life [AOR (95% CI) 12.28(3.19–48.40) ], less physical activity [AOR (95% CI) 4.44(1.43–13.75)], elevated LDL [AOR (95% CI) 4.26(1.61–11.29)],elevated TAG [AOR (95% CI) 5.44(2.78–8.10)],higher WC [AOR(95% CI) 6.91(2.78(1.08–7.14))], low HDL [AOR (95% CI) 5.89(2.22–15.00))] and being positive H-pylori stool antigen test [AOR(95% CI) 2.7(1.86–7.72) ] were positively associated with multiple FGIDs
Conclusion
Multiple FGIDs were exists unrecognizably among adults in southwest Ethiopia. khat chewing, alcohol conceptions, often high conception of butter or ghee and margarine, sedentary life, less physical activity, higher central obesity, dyslipidemia, and positive H-pylori stool antigen tests were found to be significantly associated with occurrence of multiple FGIDs qualified for both upper and lower abdominal symptoms in the community at this study area. Therefore, early screening and create awareness about factors positively associated with Multiple FGIDs recommendable at the study community.
A Novel Method for Reducing Dispensing Error in Hospital Pharmacy
Authors: Meng Mingzhu , Li Hong , Wang Yuqun 
Published: July 2022

Abstract
Background
Dispensing Error occurs frequently in outpatient pharmacies. The aim of this article is to explore the value of the YOLO-V5 deep learning algorithm for object detection in packaging drugs from outpatient pharmacies and to develop an artificial intelligence assist pharmacist drug dispensation system (AI-APDDS) capable of completely reducing or eliminating dispensing errors.
Methods
A total of 1784 images from 136 different packaging drugs were collected and labeled to form a deep learning dataset. The dataset was split into training and validation sets at a ratio of 3:1. The YOLO-V5 deep-learning algorithm was trained using images from our dataset (training epochs:1000, batch size:4, learning rate:0.01). The values of precision (Pr) and mean average precision(mAP) were used as measures for model performance evaluation.
Results
Pr in the training set was, for all models, equal to 1.00. The mAP_0.5 of YOLO-V5x was 0.992, which was higher than that of YOLO-V5n (0.975), YOLO-V5s (0.976), YOLO-V5m (0.978), and YOLO-V5l (0.983). The mAP_0.5:0.95 of YOLO-V5x was 0.955, which was higher than those of YOLO-V5n (0.916), YOLO-V5s (0.920), YOLO-V5m (0.921) and YOLO-V5l (0.935). The training time and model size were 92.67 hours and 465MB, respectively, for YOLO-V5x, which were the highest among the four models. The speed of detection for one image was 6.0ms for YOLO-V5n, which was the fastest among the four models.
Conclusions
It can identify the packaging drugs accurately for five submodels of YOLO-V5, it is feasible to implement the artificial-intelligence assisted drug dispensation system for pharmacist to achieve “zero” dispensing error.
Study on BP-LSTM fusion prediction model and application of gas concentration in gas tunnel blasting
Authors: Qiu Daohong , Fu Yusong , Xue Yiguo , Fu Kang , Feng Jianxiang 
Published: July 2022

Abstract
With the development of China's transportation industry, more and more tunnel projects will pass through the gas geological area, resulting in the tunnel construction will face a huge hidden danger. The gas will flow out rapidly after the excavation of the working face. The distribution and concentration of gas in the tunnel are the key factors affecting the gas disaster. In time, grasping the gas concentration near the excavation face is the key to avoiding safety accidents. Therefore, predicting the gas concentration near the tunnel excavation face is necessary after blasting excavation. This paper relies on the NEW Chengdu-Kunming Railway Like Tunnel project to conduct research. According to the collected historical gas concentration data, based on the back-propagation neural network and long and short-term memory neural network, a new gas concentration prediction model based on the fusion algorithm of back-propagation and long and short-term memory (BP-LSTM) is proposed to realize the long-term prediction of gas concentration near the face of the tunnel after blasting excavation. This paper used the Pearson correlation method to improve model prediction accuracy and analyze the correlation between geological parameters and environmental factors and gas concentration occurrence. This model predicts the gas concentration of four monitoring points (LAFEF monitoring point, RAFEF monitoring point, EFV monitoring point, and AFEF monitoring point) in actual tunnel engineering. And compared with the prediction results of the back-propagation and long and short-term memory models, the model was evaluated according to the error. The results indicate that the prediction result of this model has high accuracy, and it can be successfully applied to predict the gas concentration after excavating the face of the gas tunnel, which can ensure the safety of construction.
A Hybrid SEIHCRDV-UKF Model for COVID-19 Prediction. Application on real-time data
Authors: Papageorgiou Vasileios E. , Tsaklidis George 
Published: July 2022

Abstract
The prevalence of COVID-19 has been the most serious health challenge of the 21th century to date, concerning national health systems on a daily basis, since December 2019 when it appeared in Wuhan City. Prediction of pandemic spread plays an important role in effectively reducing this highly contagious disease. Nevertheless, most of the proposed mathematical methodologies, which aim to describe the dynamics of the pandemic, rely on deterministic models that are not able to reflect the true nature of the spread of COVID. In this paper, we propose a SEIHCRDV model – an extension of the classic SIR compartmental model – which also takes into consideration the populations of exposed, hospitalized, admitted in intensive care units (ICU), deceased and vaccinated cases, in combination with an unscented Kalman filter (UKF), providing a dynamic estimation of the time dependent parameters of the system. Apparently, this new consideration could be useful for examining also other pandemics. We examine the reliability of our model over a long period of 265 days, where we observe two major waves of infection, starting in January 2021 which signified the start of vaccinations in Europe, providing quite encouraging predictive performance. Finally, special emphasis is given to proving the non-negativity of SEIHCRDV model, to achieve a representative basic reproductive number R0 and to investigating the existence and stability of disease equilibriums in accordance with the formula produced to estimate R0.
Identification of hub genes and its relationship with colorectal cancer patient prognosis
Authors: Li Shan , Sun Xuguang , Li Ting , Shi Yanqing 
Published: July 2022

Abstract
Background
Colon cancer is a common gastrointestinal malignancy that with high morbidity and mortality, however, predicting prognosis in colon cancer is imperfect, so searching for effective prognostic biomarkers is in urgent need. Our study aimed to investigate hub genes and their prognostic value in colon cancer via bioinformatics analysis.
Methods
The data set of colon cancer was downloaded from GEO database (GSE21510, GSE110225, GSE74602) for differential gene analysis using the GEO2R tool, and hub gene was identified by Cytoscape. The Human Protein Atlas database was used to analyze the expression of hub genes and evaluate their prognostic value using GEPIA. TIMER database was used to study the correlation between hub gene and immune infiltration of COAD cells. After that, PPI networks were established using the SRTING database and Cytoscape to analyze hub genes and protein-protein interactions. Finally, identify hub gene mutation through cBioPortal, the co-expression analysis of hub genes were identified by LinkedOmics, and gene set enrichment analysis (GSEA) were analyzed using the comprehensive functional classification database in the Web-based Web Gestalt.
Results
We identified 349 differentially expressed genes (DEGs), including 117 upregulated and 229 downregulated. The PPI network was constructed and four hub genes (AURKA, CCNB1, EXO1 and CCNA2) were selected by survival analysis and expression validation. The expression level of AURKA, CCNB1, EXO1 and CCNA2 were all higher in COAD tumor tissues than in adjacent tissues, as well as the immunohistochemical results. There has varying degrees gene mutation and varying degrees immune cell infiltration about AURKA, CCNB1, EXO1 and CCNA2, especially B cells and CD8 + T cells. GSEA was performed to determine co-expressed genes of AURKA, CCNB1, CCNA2 and EXO1, the results showed that they both had a close relationship with chromosome segregation, DNA replication, translational elongation and cell cycle.
Conclusion
Overexpression of AURKA, CCNB1, CCNA2 and EXO1 had a better prognosis in colon cancer and this consequences was correlation with gene mutation and infiltration of immune cells.
Facilitators supporting settlement among women who are Syrian refugees and mothering: Findings from a longitudinal participatory action research study
Authors: Kassam Shahin , O'Mahony Joyce , Clark Nancy 
Published: July 2022

Abstract
Background
Over 13 million Syrians have been forcibly displaced since the start of the Syrian civil war in 2011. In response to this overwhelming humanitarian crisis, several high income countries have settled thousands of Syrian refugees. In Canada, over 50,000 Syrian refugees have resettled through varying resettlement programs. Half of these refugees are women who are mothers or of child-bearing age. Women who are refugees and mothering comprise a population that experience numerous health disparities including higher rates of depression and anxiety, social exclusion and lower socioeconomic status. This article reports findings from a larger, Canadian-based study inquiring into the factors supporting and shaping the settlement and integration experiences among women who are Syrian refugees and mothering.
Methods
This study employed a longitudinal intersectionality-framed participatory action approach. This design was initiated through multiple community-based meetings with a diverse range of non-profit organizations focused on refugee health and settlement. Through these meaningful engagements, sustainable relationships were formed and trust was built toward further immersing ourselves within the Syrian refugee mothering women population. Consequential establishment of a core group of 4 women led to the emergence of a peer research assistant model which informed data collection, reflexive analysis, and knowledge mobilization activities.
Results
In total, 40 Syrian refugee mothering women participated in this study and six themes emerged from data analysis of their lived experiences of resettlement. Four of the themes are published elsewhere. We focus this article on two of the six key findings: harnessing strength-based capabilities, and peer research assistant experiences.
Conclusions
While multiple barriers continue to exist within recent re-settlement processes of Syrian refugee mothering women, these two findings convey facilitators that add to understanding influences to the mental well-being of this often overlooked population. Unique to this study is the novel integration of peer research assistants and a model of support which contributes to an ethical and inclusive approach to understanding lived experiences among refugee women. This article highlights how this model benefits the peer research assistant and promotes community engagement among women.
Learning Inverse Problem from Sparse Noisy Data with Operator Split and Physics-Constraints Machine Learning
Authors: Li Chun , Deng Lijun 
Published: July 2022

Abstract
Inverse problems (IPs) begin with measured data and try to estimate the model parameters. In science and engineering, many problems are seen as inverse problems. Partial differential equations (PDEs) or variational problems are also used to characterize similar issues (VPs). A VP is usually an energy functional that is solved by lowering the energy function. Since curvature-driven regularities have been proven to need considerable prior understanding of physics, they have gotten a lot of attention. Unfortunately, the curvaturedriven regularities correlate to the higher-order EulerLagrangian equations. Furthermore, they frequently have non-smooth and non-convex features, making numerical solutions a difficult challenge in a variety of applications. In this paper (AD), we introduced a method based on physics-constrained deep learning (PCL) and automatic differentiation to handle inverse issues from noisy data. In addition, to address this challenge, we combine standard variational approaches (VMs) with DL-based algorithms. The operator split technique may successfully break non-convex variational models into multiple simple sub-problems to solve. Each sub-problem corresponds to an Euler-Lagrangian PDE, which is effectively solved using deep neural networks (DNNs) via the AD process.