bluuebunny/crossref_metadata_2025 huggingface dataset:
Eighteenth-Century Identified Copies of MāšāʾAllāh’s Kitāb Qiyām al-Ḫulafāʾ from Yemen: Text Edition and Contextualization
Authors: Regourd Anne
Published: December 2020

A copy of the Kitāb Qiyām al-Ḫulafāʾ (Book on the reign of Rulers), identified in Ḏamār, Yemen, in 1993, is dated 8 Ǧumādā Awwal 1150 AH (= Sept. 1737 AD). Under the name of the famous Jewish astrologer MāšāʾAllāh, who practised at the early ʿAbbasid Court together with the Banū Nawbaḫt, this book displays the horoscopes of the Prophet Muhammad and of the caliphs up to Hārūn al-Rašīd. E.S. Kennedy & D. Pingree offered an English translation of the Kitāb Qiyām al-Ḫulafāʾ in The Astrological History of MāšāʾAllāh, Cambridge (MA), Harvard U. Press, 1971, Appendix 2, on the basis of “two late manuscripts”, one from Berlin, the other at the Biblioteca Apostolica Vaticana. Since then, K. Yamamoto & Ch. Burnett have edited the text on the basis of three manuscripts, adding one from Bursa, and offered a revised English translation. Meanwhile, I came upon a second copy of the book in Ṣanʿāʾ.

The copy preserved at the Waqf Library of Ḏamār belonged to the personal collection of a Yemeni cadi, who was a divinatory practitioner (munaǧǧim).

At the intersection of textual studies and field work, this paper, following an introduction to the text, will concentrate on the circulation of the 1150/1737 manuscript and its potential uses.
The Golden Rule in The 101 Nights’ Version of The Book of Sindbād, the Question of Literary Context and a Possible Solution Formulated in Later Arabic Versions
Authors: Lerner Amir
Published: December 2020

This paper presents a brief account of, and a number of comments on, the literary history of the golden rule (“do not do unto others what you dislike for yourself”) as found seemingly a bit out of context in the version of The Book of Sindbād contained in the medieval popular story collection The 101 Nights (“The Story of the Prince and the Seven Viziers”). The problem of context and its possible solution are addressed by examining other versions of The Book of Sindbād in Arabic, such as the one contained in the so-called Breslau edition of The 1001 Nights, and in various other languages.
Espace, déplacement et identité dans le roman Amīrkā (2009) de Rabīʿ Ǧābir
Authors: Censi Martina
Published: December 2020

In the novel Amīrkā (2009), the Lebanese novelist Rabīʿ Ǧābir narrates the story of Martha Ḥaddād, a young woman who, in 1913, leaves her village in Mount Lebanon to go to the United States of America. She is in search of her husband who left Lebanon before. The path of Martha is a physical and symbolic displacement from the village of her origins – poor and conservative – to the United States, the “New World” where a new life, rich and prosperous, seems possible. This article focuses on the role of space in shaping individual and collective identities through Martha’s paths of “deterritorialization” and “reterritorialization”. Her experience of displacement in migration is the standpoint for deconstruction and reconstruction of her individual identity which becomes the symbol of the collective search for a Lebanese national identity after the fall of the Ottoman Empire.
Prosodic Rules of wolofal Compositions
Authors: Minerba Emiliano
Published: December 2020

The paper focuses on the prosodic norms that rule the formation of the metrical patterns of wolofal verses. Wolofal is a genre, developed between 1800 and 1900 in Senegambia, of poetry in Wolof but composed according to Arabic metrical schemas and stanzas. From the beginning this genre used al-Ḫalīl’s metres, widely employed in Classical Arabic literature: it was therefore necessary for wolofal poets to elaborate a prosodic norm that allowed them to use the Arabic metres with their language’s phonology. Among the phonological particularities of Wolof one finds the syllabic structures CVC and CVCC, the possibility of crasis between different words, and the particular phonological status of prenasalised and geminate consonants. All these peculiarities have certain consequences for the metric and prosodic organisation of the verse, which will be analysed here both through metrical analysis of the texts studied, and by looking at the orthography adopted for the transcription of these poems in Arabic script.
Maqriziana X: al-Maqrīzī and His al-Tārīḫ al-Kabīr al-Muqaffā li-Miṣr. Part 2: The Fortunes of the Work and Its Copies
Authors: Bauden Frédéric
Published: December 2020

This second part of a study devoted to the history of al-Maqrīzī’s al-Tārīḫ al-Kabīr al-Muqaffā li-Miṣr retraces the history of its copies, first the holograph, then the apograph. By considering their users (readers, owners), this article focuses on the paratextual elements in the preserved copies and on references to al-Maqrīzī’s text in other works to reconstruct the itineraries of these copies across several centuries. By examining consultation notes and ownership marks, we can better understand how these manuscripts changed hands, how the text evolved over time, and how the text we have today may ultimately differ from al-Maqrīzī’s intent. Our analysis of similar paratextual marks – by owners and readers of al-Muqaffā – found in other manuscripts also helps us better understand the interactions between these users and the copies of al-Muqaffā they owned or had access to.
Maranta nanica (Marantaceae), a new dwarf species from Central Brazil

Authors: FRAGA FERNANDA RIBEIRO DE MELLO , BRAGA JOÃO MARCELO ALVARENGA
Published: December 2020

A new species of Maranta (Marantaceae) from Central Brazil is described and illustrated. The species is recognizable due to its small rosulate habit, unbranched aerial shoot, hirtellous bracts with apex acute, sub-brachyblastic cymules, and each bracteole subtending a single flower.
A revision of the bee genus Augochlora Smith (Hymenoptera; Apoidea) in Southern South America
Authors: LEPECO ANDERSON , GONÇALVES RODRIGO BARBOSA
Published: December 2020

Even after more than 250 years of taxonomic research on bees, there are still many gaps in the knowledge about their identity, classification and distribution patterns. Regarding the New World tribe Augochlorini, many efforts have been made in the last years to describe and organize its diversity. Within the tribe, Augochlora Smith has the widest distribution range, as these bees occur from Argentina to Southern Canada, including Caribbean islands. The genus comprises 124 described species in two extant subgenera, and, to date, two partial revisions are available, accounting for central Argentina and Uruguay and for northeastern Brazil. In the present study we review the Augochlora species occurring in Argentina, Paraguay, Uruguay and the southern Brazilian states of Paraná, Rio Grande do Sul, and Santa Catarina. Specimens from other Brazilian states and South American countries were also examined to help with species circumscription. We found 27 species in the studied area, including nine new species (Augochlora atlantica sp. nov., A. australis sp. nov., A. genalis sp. nov., A. helena sp. nov., A. hestia sp. nov., A. hirsuta sp. nov., A. laevicarinata sp. nov., A. mendax sp. nov., and A. scabrata sp. nov.) and the remaining redescribed when necessary. A key for the species occurring in the studied area is provided. Five new synonymies are proposed and the lectotypes of Augochlora francisca and Halictus esox are presently designated. The geographic distribution of most studied species is associated with the Atlantic biome in many ways.
Experimental Study on Early Diagnosis of Malignant Pleural Mesothelioma with Computed Tomography Combined Serum Soluble Mesothelin-Related Proteins
Authors: Jie Jiang , Zhanxiong Qin , Li Wu , Xiaojie Xie , Xunran Zhao , Wen Zhao , Dan Han
Published: December 2020

Objective: To investigate the value on early diagnosis of experimental rat according to computed tomography (CT) combined with the serum level of Serum Soluble Mesothelin-related Proteins (SMRP). Methods: Thirty-two SD rat were divided into three groups, including group
A (experimental group) of 20 rats with pleural cavity injection of crocidolite suspension, group B (negative control group) of 6 rats with pleural cavity injection of saline, group C (blank control group) of 6 rats without any processing. Chest and abdominal CT scan and enhancement were performed
in the three months and six months after induction and the pleural thickening was analyzed. The serum level of SMRP was measured at the different time period including pre-injection, the postinjection first month, the second month, the third month and the sixth month. The correlation between
pleural thickening and serum level of SMRP was analyzed. Results: In group A: 20 cases were performed on CT scan in post-injection third month and we found 13 cases without pleural lesions and 7 cases with pleural lesions including of 4 cases with mild pleural thickening, 1 moderate
thickening and 2 severe thickening (2 cases died). Moreover, 18 cases were done by CT in post-injection third month and we found 3 cases without pleural lesions and 15 cases with pleural lesions including of 6 cases with mild pleural thickening, 5 moderate thickening and 4 severe thickening
(3 cases died). No pleural lesions were found in group B and group C. SMRP expression level differences in the three groups was statistically significant. However, there was no difference in pre-injection in the three groups and there were no difference in group B and C at the different time
period. In group A, there was no difference between post-injection first month and second month, whereas, there had statistically difference in post-injection third and sixth month. In group A, SMRP level gradually increased over time. The high correlation between pleural thickening and serum
level of SMRP was seen at the post-injection third and sixth month, which the expression of SMRP gradually increased as the pleural thickening. Conclusion: Serum SMRP expression level has a certain value for early diagnosis and staging of MPM, which can be used as an important biomarker
for early screening of high-risk groups exposed to asbestos.
Analysis of Microarray Data by Empirical Wavelet Transform for Cancer Classification Using Block by Block Method
Authors: Jayanthi S. , Rene Robin C. R.
Published: December 2020

In this study, DNA microarray data is analyzed from a signal processing perspective for cancer classification. An adaptive wavelet transform named Empirical Wavelet Transform (EWT) is analyzed using block-by-block procedure to characterize microarray data. The EWT wavelet basis depends
on the input data rather predetermined like in conventional wavelets. Thus, EWT gives more sparse representations than wavelets. The characterization of microarray data is made by block-by-block procedure with predefined block sizes in powers of 2 that starts from 128 to 2048. After characterization,
a statistical hypothesis test is employed to select the informative EWT coefficients. Only the selected coefficients are used for Microarray Data Classification (MDC) by the Support Vector Machine (SVM). Computational experiments are employed on five microarray datasets; colon, breast, leukemia,
CNS and ovarian to test the developed cancer classification system. The obtained results demonstrate that EWT coefficients with SVM emerged as an effective approach with no misclassification for MDC system.
Comparative Study of Ultrasound Signs of Scar Pregnancy in Patients with Cesarean Section and Their Clinical Outcomes
Authors: Xie Shasha , Dong Wei , Liu Yeting , Gao Haixiao
Published: December 2020

Caesarean scar pregnancy is the implantation of fertilized eggs in the scar of the previous cesarean section in the lower uterus. It is a serious long-term complication after cesarean section. Ultrasound examination, as the first choice to evaluate cesarean scar pregnancy plays an important role in its diagnosis, treatment and follow-up. This study first tried to propose new ultrasound diagnostic indicators to distinguish cesarean scar pregnancy from non-scar pregnancy of the lower uterine cavity; Logistic regression analysis was used to screen for risk factors related to scar pregnancy bleeding, with a view to providing clinical ultrasound indicators to predict bleeding risk; Secondly, the use of contrast-enhanced ultrasound and three-dimensional ultrasound to observe the scar diverticulum of cesarean section more than six months after the different surgical treatments of scar pregnancy, and to evaluate whether surgical scar repair can improve the scar diverticulum. Finally, using ultrasound to predict the position of the embryonic placenta, the new type of scar pregnancy in cesarean section is divided into three types: anterior wall placenta, anterior wall posterior placenta and posterior wall placental. The three types of CSP have significant differences in the thickness of the muscular layer in the scar of the lower part of the anterior wall of the uterus, the blood flow in the scar of the lower part of the anterior wall of the uterus, the number of days of hospitalization, the treatment method, and the treatment effect, which indicate that the new type is used for the diagnosis of CSP. Treatment and prognosis evaluation have high clinical value, can be used to guide clinical work, and provide a new idea for clinical diagnosis and treatment.
Effect of Noise Adaptive Wavelet Filter on Diagnostic Performance in Stroke Perfusion
Authors: Inal Tolga , Kaan Atac Gokce , Telatar Ziya
Published: December 2020

Background: Computed tomography perfusion (CTP) images include more noise than routine clinic computed tomography (CT) images. Singular value decomposition based deconvolution algorithms are widely used for obtaining several functional perfusion maps. Recently block circulant
singular value decomposition algorithms become popular for its superior property of immunity to contrast bolus lag. It is well known from literature that these algorithms are very sensitive to noise. There are a lot of examples of noise reduction filters in the literature as well as commercial
ones. Functional maps which help physicians in the diagnostic process can be obtained with better image quality by de-noising CTP images with adaptive noise reduction filters. Objective: In this study, the effect of a noise adaptive wavelet filtering method on diagnostic performance
on CTP stroke patient images is investigated. Method: Images of acute stroke patients were de-noised by this method and their diagnostic value were evaluated by visual means, peak signal-to-noise ratio and time intensity profile metrics. An observer evaluation study was carried out
in order to validate quantitative image quality metrics. The results are compared with Gaussian and a bilateral filter based filtering method called TIPS (Time Intensity Profile Similarity) on same images sets to benchmark proposed method. Results: The diagnostic value of the images
obtained from noise adaptive wavelet filtering method were better than Gaussian filter method and were compatible with a wellknown time intensity profile similarity bilateral filter method. Diagnostic performance of the both observers were improved compared to both Gaussian and TIPS methods.
Conclusion: The noise adaptive wavelet filter method succeeded to reduce noise while preserving details contained in the contrast bolus. Its final effect on the timeintensity profiles and generated perfusion maps are compatible with the literature and showed improvements on diagnostic
performance on specificity and overall accuracy when compared to other methods.
Monitoring and Analysis of Early Heart Structure of Fetus in Gynecology and Obstetrics Based on Ultrasound Image
Authors: Yan Jingbin , Liang Birong , Lv Ying , Li Yanbin
Published: December 2020

As the core organ of cardiovascular system, fetal heart plays a very important role. With the development of pregnancy, the early fetal heart rate tends to mature, and the corresponding cardiac function tends to mature and stable. But the fetal heart is very fragile during pregnancy. Various diseases during pregnancy directly lead to fetal heart growth restriction, and even lead to fetal heart function damage. Ultrasound image diagnosis is one of the most important diagnostic methods in medical imaging. It is of great significance to detect the early heart structure of the fetus in gynecology and obstetrics. It can detect the early fetal heart in real time and noninvasively. However, the traditional ultrasonic image detection has many disadvantages in the process of application, such as many noise points, low performance of processing algorithm, which to some extent affects the detection performance of ultrasonic image detection in the detection of fetal heart structure in gynecology and obstetrics. Based on the above problems, this paper proposes an adaptive detection algorithm of superimposed moving image based on ultrasonic image detection, which can accurately extract and analyze fetal heart region when the signal-to-noise ratio of ultrasonic image sequence is low. The average anisotropy algorithm is also proposed innovatively in this paper. In order to predict the structure of fetal heart more accurately, the active heart model combining fetal heart structure and motion information is considered in the actual analysis process. Experiments show that the accuracy error of the algorithm is less than 11 pixels.
Analysis of Three-Dimensional Ultrasound in Diagnosis of Shoulder and Neck Inflammation and Surrounding Tissue Lesions
Authors: Zhou Ziqiang
Published: December 2020

Ultrasound imaging technology can not only show neck tear the degree and extent of disease, to help make the correct diagnosis, can also be used to assess shoulder neck inflammation after surgery to repair a shoulder muscle neck tissue integrity and healing. Ultrasound imaging with high-resolution, real-time operation, low cost, etc. gradually become shoulder neck inflammatory disease preferred imaging modality. The sensitivity and specificity for three-dimensional ultrasound imaging of shoulder neck inflammation were 78% and 93% in this study. The full-thickness inflammation sensitivity and specificity were 50% and 95%. The sensitivity and specificity of inflammation were 57% and 87%, respectively. This study shows that the diagnostic accuracy of 3D ultrasound imaging in shoulder and neck inflammation and surrounding tissue lesions is close to that of MRI. Three-dimensional appearance of new technologies such as ultrasound imaging will further improve ultrasound imaging techniques in shoulder neck inflammation application in the diagnosis and treatment assessment.
Comparison of Differential Diagnosis of Lung Cancer by Diffuse Weighted Imaging and Sagittal Imaging with Short Inversion Recovery Sequence
Authors: Zhang Wei , Cai Qingyu , Wei Guoli
Published: December 2020

The differential diagnosis of advanced lung cancer is difficult in clinical practice. Our study aims to compare the value of diffusion weighted imaging (DWI) with short-term inversion recovery sequence (STIR) for sagittal imaging in the differential diagnosis of lung cancer. 149 patients with non-small cell lung carcinoma (NSCLC) were enrolled and underwent DWI and STIR sagittal imaging. To quantify cancer types, we evaluated the apparent diffusion coefficient (ADC) value on DWI and the contrast ratio (CRs) on sagittal imaging. The ADC values of subclasses in NSCLC were significantly higher than small cell lung carcinoma (SCLC) (p<0.01). The mean CRs were 1.59 for SCLC and 1.30 for NSCLC with a significant difference (p< 0.01). Large cell carcinomas (LCC) and adenocarcinomas have significant differences compared to small cell carcinomas (SCC) without difference between squamous cell carcinomas (p> 0.05); this is also the case for CRs. Squamous cell carcinoma and adenocarcinoma have significant differences compared to SCC without difference in LCC (p> 0.05). Qualitative evaluation of the feasible thresholds DWI and STIR showed that the thresholds were 0.9810−3mm2/s and 1.37 respectively. The specificity and accuracy was 78.5% is 85.3% for DWI, which was significantly higher than STIR (56.3% and 61.0%). The combination of DWI and STIR sequences was superior to DWI alone with an accuracy rate of 94.3%. DWI is more helpful than STIR in differentiating SCLC and NSCLC, and their combined use can significantly improve diagnosis accuracy.
Brain MRI Intelligent Diagnostic Using an Improved Deep Convolutional Neural Network
Authors: Zhang Xiangsheng , Pan Feng , Zhou Leyuan
Published: December 2020

The diagnosis of brain diseases based on magnetic resonance imaging (MRI) is a mainstream practice. In the course of practical treatment, medical personnel observe and analyze the changes in the size, position, and shape of various brain tissues in the brain MRI image, thereby judging whether the brain tissue has been diseased, and formulating the corresponding medical plan. The conclusion drawn after observing the image will be influenced by the subjective experience of the experts and is not objective. Therefore, it has become necessary to try to avoid subjective factors interfering with the diagnosis. This paper proposes an intelligent diagnosis model based on improved deep convolutional neural network (IDCNN). This model introduces integrated support vector machine (SVM) into IDCNN. During image segmentation, if IDCNN has problems such as irrational layer settings, too many parameters, etc., it will make its segmentation accuracy low. This study made a slight adjustment to the structure of IDCNN. First, adjust the number of convolution layers and down-sampling layers in the DCNN network structure, adjust the network’s activation function, and optimize the parameters to improve IDCNN’s non-linear expression ability. Then, use the integrated SVM classifier to replace the original Softmax classifier in IDCNN to improve its classification ability. The simulation experiment results tell that compared with the model before improvement and other classic classifiers, IDCNN improves segmentation results and promote the intelligent diagnosis of brain tissue.
An Intelligent Particle Swarm Optimization with Convolutional Neural Network for Diabetic Retinopathy Classification Model
Authors: Jayanthi J. , Jayasankar T. , Krishnaraj N. , Prakash N. B. , Sagai Francis Britto A. , Vinoth Kumar K.
Published: December 2020

Diabetic retinopathy (DR), a major cause of vision loss and it raises a major issue among diabetes people. DR considerably affect the financial condition of the society specially in medicinal sector. Once proper treatment is given to the DR patients, roughly 90% of patients can be saved
from vision loss. So, it is needed to develop a DR classification model for classifying the stages and severity level of DR to offer better treatment. This article develops a novel Particle Swarm Optimization (PSO) algorithm based Convolutional Neural Network (CNN) Model called PSO-CNN model
to detect and classify DR from the color fundus images. The proposed PSO-CNN model comprises three stages namely preprocessing, feature extraction and classification. Initially, preprocessing is carried out as a noise removal process to discard the noise present in the input image. Then, feature
extraction process using PSO-CNN model is applied to extract the useful subset of features. Finally, the filtered features are given as input to the decision tree (DT) model for classifying the set of DR images. The simulation of the PSO-CNN model takes place using a benchmark DR database
and the experimental outcome stated that the PSO-CNN model has outperformed all the compared methods in a significant way. The outcome of the simulation process indicated that the PSO-CNN model has offered maximum results.
Differential Diagnosis of Malignant Thyroid Calcification Nodule Based on Computed Tomography Image Texture
Authors: Peng Wenxian , Qian Yijia , Shi Yingying , Chen Shuyun , Chen Kexin , Xiao Han
Published: December 2020

Purpose: Calcification nodules in thyroid can be found in thyroid disease. Current clinical computed tomography systems can be used to detect calcification nodules. Our aim is to identify the nature of thyroid calcification nodule based on plain CT images. Method: Sixty-three
patients (36 benign and 27 malignant nodules) found thyroid calcification nodules were retrospectively analyzed, together with computed tomography images and pathology finding. The regions of interest (ROI) of 6464 pixels containing calcification nodules were manually delineated by radiologists
in CT plain images. We extracted thirty-one texture features from each ROI. And nineteen texture features were picked up after feature optimization by logistic regression analysis. All the texture features were normalized to [0, 1]. Four classification algorithms, including ensemble learning,
support vector machine, K-nearest neighbor, decision tree, were used as classification algorithms to identity the benign and malignant nodule. Accuracy, PPV, NPV, SEN, and AUC were calculated to evaluate the performance of different classifiers. Results: Nineteen texture features were
selected after feature optimization by logistic regression analysis (P <0.05). Both Ensemble Learning and Support Vector Machine achieved the highest accuracy of 97.1%. The PPV, NPV, SEN, and SPC are 96.9%, 97.4%, 98.4%, and 95.0%, respectively. The AUC was 1. Conclusion: Texture
features extracted from calcification nodules could be used as biomarkers to identify benign or malignant thyroid calcification.
Segmentation of Pulmonary Parenchyma from Pulmonary CT Based on ResU-Net++ Model
Authors: Yan Xuantong , Wu Yuejiang , Tan Wenjun
Published: December 2020

Pulmonary parenchyma segmentation is an important basic step in CT detection, which requires high accuracy and speed. According to the characteristics of lung structure, we present a method for segmenting CT images of lung parenchyma based on the ResU-net++ neural network model. The
model preserves the deep feature parameters extracted from the residual blocks while paying attention to preserving the feature parameters obtained by transferring the shallow convolution blocks. The experimental results show that compared with U-net and U-net++ models, the lung parenchyma
segmentation results using this method are more accurate, the accuracy of lung parenchyma edge identification is significantly improved, and it is more suitable for the diverse structures at both ends of the lung.
Magnetic Particle Imaging Reconstruction Based on the Least Absolute Shrinkage and Selection Operator Regularization
Authors: Chen Xiaojun , Han Xiao , Tang Xiaoying
Published: December 2020

Magnetic particle imaging is a new medical imaging modality which is based on the non-linear response of magnetic nanoparticles. The reconstruction task is an inverse problem and ill-posed in nature. To overcome the problem, we propose to use the least absolute shrinkage and selection operator (LASSO) regularization model. In order to reach a good result with a short reconstruction time, we use the truncated system matrix and the truncated measurement based on two threshold setting methods for reconstruction research. In this paper, we study the reconstruction quality of different threshold values and different regularization parameter values. We compare the reconstruction performance of the proposed model with the Tikhonov model from visualization and performance indicators. The conducted study illustrated that the proposed method yields significantly higher reconstruction quality than the state-of-the-art reconstruction method based on Tikhonov model.
Physical Activity Assessment and Recommendation for Adults With Arthritis by Primary Care Providers—DocStyles, 2018
Authors: Guglielmo Dana , Murphy Louise B. , Theis Kristina A. , Helmick Charles G. , Omura John D. , Odom Erica L. , Croft Janet B.
Published: December 2020

Purpose:

To examine primary care providers' (PCPs) physical activity assessment and recommendation behaviors for adults with arthritis.

Design:

Cross-sectional.

Setting:

2018 DocStyles online national market research survey of US physicians and nurse practitioners.

Sample:

1,389 PCPs seeing adults with arthritis.

Measures:

2 independent behaviors (assessment and recommendation) as 3 non-mutually exclusive groups: “always assesses,” “always recommends,” and “both” (“always assesses and recommends”).

Analysis:

Calculated percentages of each group (overall and by PCP characteristics), and multivariable-adjusted prevalence ratios (PRs) using binary logistic regression.

Results:

Among PCPs, 49.2% always assessed and 57.7% always recommended physical activity; 39.7% did both. Across all 3 groups, percentages were highest for seeing ≥20 adults with arthritis weekly (“both”: 56.4%; “always assesses”: 66.7%; “always recommends”: 71.3%) and lowest among obstetrician/gynecologists (“both”: 26.9%; “always assesses”: 36.8%; “always recommends”: 40.7%). Multivariable-adjusted associations were strongest for seeing ≥20 adults with arthritis weekly (referent: 1-9 adults) and each of “always assesses” (PR = 1.5 [95% confidence interval (CI): 1.3−1.8] and “both” (PR = 1.6 [95% CI: 1.4−1.9]).

Conclusions:

Approximately 40% of PCPs sampled always engaged in both behaviors (assessing and recommending physical activity) with adults with arthritis; seeing a high volume of adults with arthritis was consistently related to engaging in each behavior. Evidence-based approaches to support PCP counseling include offering provider education and training, raising awareness of available resources, and using health system supports.
Cannabis users and stigma: A comparison of users from European countries with different cannabis policies
Authors: Skliamis Kostas , Benschop Annemieke , Korf Dirk J
Published: December 2020

Cannabis is commonly characterized as the most normalized illicit drug. However, it remains a prohibited substance in most parts of the world, including Europe, and users can still be subject to stigmatization. The objective of this study is to assess to what extent and how cannabis users in different countries with different cannabis policies perceive, experience and respond to stigmatization. We conducted a survey in the Dutch coffeeshops among 1225 last year cannabis users from seven European countries, with national cannabis policies ranging from relatively liberal to punitive. Three dimensions of cannabis-related stigma were investigated (discrimination, perceived devaluation and alienation) and a sum score was used to reflect the general level of stigmatization. Perceived devaluation was the highest-scoring dimension of stigma and discrimination the lowest-scoring. The general level of stigmatization was lowest in the Netherlands and highest in Greece. This indicates that punitive cannabis policy is associated with stigma and liberal cannabis policy is associated with de-stigmatization. Besides country, daily cannabis use was also found to be a significant predictor of stigma, but gender, age, household type and employment status were not.
Biofield Frequency Bands—Definitions and Group Differences
Authors: Rowold Jens , Hewson Paul D
Published: December 2020

Background

In the biofield literature, it is suggested that electromagnetic energy is part of the biofield. However, little is known about the exact definition of potential electromagnetic biofield frequency bands (FBs). Primary Study Objective: The current study sought to identify biofield FBs and test potential group differences. Methods/Design: High-frequency (i.e. >200 Hertz) voltage was measured at body parts along the spine and the brain.

Setting

Measurements were conducted in an electrically shielded laboratory.

Participants

Twenty experienced biofield practitioners (BPs, sample 1) and twenty-four students (STs, sample 2) participated in the study.

Interventions

The BPs performed a wide set of biofield exercises, while the STs participated in an assessment centre (with exercises such as role play). A total of N =  342 exercises were performed. Primary Outcome Measures: Based on surface electromyography, high-frequency (i.e., >200 Hertz) voltage was utilized as outcome measure.

Results

10 FBs were identified across all the data sets. The BPs had higher spectral power across these bands compared to the STs.

Conclusion

The present paper presents a replicable method for the assessment of electromagnetic FBs which are potentially useful for future biofield research.
A community effort for automatic detection of postictal generalized EEG suppression in epilepsy
Authors: Kim Yejin , Jiang Xiaoqian , Lhatoo Samden D. , Zhang Guo-Qiang , Tao Shiqiang , Cui Licong , Li Xiaojin , Jolly Robert D. , Chen Luyao , Phan Michael , Ha Cung , Detranaltes Marijane , Zhang Jiajie
Published: December 2020

Applying machine learning to healthcare sheds light on evidence-based decision making and has shown promises to improve healthcare by combining clinical knowledge and biomedical data. However, medicine and data science are not synchronized. Oftentimes, researchers with a strong data science background do not understand the clinical challenges, while on the other hand, physicians do not know the capacity and limitation of state-of-the-art machine learning methods. The difficulty boils down to the lack of a common interface between two highly intelligent communities due to the privacy concerns and the disciplinary gap. The School of Biomedical Informatics (SBMI) at UTHealth is a pilot in connecting both worlds to promote interdisciplinary research. Recently, the Center for Secure Artificial Intelligence For hEalthcare (SAFE) at SBMI is organizing a series of machine learning healthcare hackathons for real-world clinical challenges. We hosted our first Hackathon themed centered around Sudden Unexpected Death in Epilepsy and finding ways to recognize the warning signs. This community effort demonstrated that interdisciplinary discussion and productive competition has significantly increased the accuracy of warning sign detection compared to the previous work, and ultimately showing a potential of this hackathon as a platform to connect the two communities of data science and medicine.
2019 World of Shipping Portugal. An International Research Conference on Maritime Affairs editorial “Leading the shipping industry into the future”
Authors: Casaca Ana Cristina Paixão , Loja Maria Amélia Ramos
Published: December 2020

Background, the context and purpose of the study

The current Editorial addresses the evolutionary path of the shipping industry. It mentions its role throughout the years, identifies the leading market segments, refers to the different operational modes due to the inherent nature of the cargoes they carry and lists some trends that appear to have been shaping the maritime industry. Within the scope of this background, the Editorial claims that all maritime market segments face the same future challenges and lists a range of international legislation released by the International Maritime Organisation which industry players must comply with.

Findings, the main results

Not/aplicable.

Conclusions, brief summary and potential implications

The Editorial concludes by stating that the maritime industry will benefit from the implementation of innovative solutions and further claims that wrong decisions will have severe impacts on the finances of the shipping companies and the environment. Moreover, it presents in a brief way the papers published in this Special Issue, which were selected among the ones presented at the 2019 World of Shipping Portugal, an International Research Conference on Maritime Affairs, 21–22 November 2019, that took place at Hotel Riviera, in Carcavelos, Portugal.
3D forward modeling of controlled-source electromagnetic data based on the radiation boundary method
Authors: Dehiya Rahul
Published: December 2020

I have developed an efficient 3D forward modeling algorithm based on radiation boundary conditions for controlled-source electromagnetic data. The proposed algorithm derives computational efficiency from a stretch-free discretization, air-free computational domain, and a better initial guess for an iterative solver. A technique for estimation of optimum grid stretching for multifrequency modeling of electromagnetic (EM) data is developed. This technique is similar to the L-curve method used for the estimation of the trade-off parameter in inversion. Using wavenumber-domain analysis, it is illustrated that, as one moves away from the source, the EM field varies smoothly even in the case of a complex model. A two-step modeling algorithm based on radiation boundary conditions is developed by exploiting the smoothness of the EM field. The first step involves a coarse-grid finite-difference modeling and computation of a radiation boundary field vector. In the second step, a relatively fine grid modeling is performed with radiation boundary conditions. The fine-grid discretization does not include the stretched grid and air medium. An initial solution derived from coarse-grid modeling is used for fine-grid modeling. Numerical experiments demonstrate that the developed algorithm is one order faster than the finite-difference modeling algorithm in most of the cases presented.
Determination of the time-dependent moment tensor using time reverse imaging
Authors: Finger Claudia , Saenger Erik H.
Published: December 2020

We have developed an approach to determine the time-dependent moment tensor and the origin time in addition to commonly derived locations of seismic events using time reverse imaging (TRI). It is crucial to locate and characterize the occurring microseismicity without making a priori assumptions about the sources to fully understand the subsurface processes inducing seismicity. Low signal-to-noise ratios (S/Ns) often force standard methods to make assumptions about sources or only characterize selected larger magnitude events. In TRI, microearthquakes are located by back propagating the full-recorded time-reversed wavefield through a velocity model until it ideally convergences on the source location. Therefore, it is less affected by low S/Ns and potentially locates and characterizes most of the events. After distinguishing artificial convergence locations from source locations, the quality of the source location and the moment tensors are derived by recording the stress at the determined source locations during the back propagation of the time-reversed wavefield. A robust workflow is derived using synthetic test cases in a realistic scenario with velocity models that only approximate the true velocity model and/or noisy displacement traces. The influence of a rudimentary velocity model on the source-location accuracy and characterization is significant. Our workflow handles these less-than-optimal station distributions and velocity models. Finally, the derived workflow is successfully applied to field data recorded at the geothermal field of Los Humeros, Mexico. Although only a 1D velocity model is currently available, source locations and (time-dependent) moment tensors could be determined for selected events.
A finite-difference iterative solver of the Helmholtz equation for frequency-domain seismic wave modeling and full-waveform inversion
Authors: Huang Xingguo , Greenhalgh Stewart
Published: December 2020

We have developed a finite-difference iterative solver of the Helmholtz equation for seismic modeling and inversion in the frequency domain. The iterative solver involves the shifted Laplacian operator and two-level preconditioners. It is based on the application of the preconditioners to the Krylov subspace stabilized biconjugate gradient method. A critical factor for the iterative solver is the introduction of a new preconditioner into the Krylov subspace iteration method to solve the linear equation system resulting from the discretization of the Helmholtz equation. This new preconditioner is based on a reformulation of an integral equation-based convergent Born series for the Lippmann-Schwinger equation to an equivalent differential equation. We have determined that our iterative solver combined with the novel preconditioner when incorporated with the finite-difference method accelerates the convergence of the Krylov subspace iteration method for frequency-domain seismic wave modeling. A comparison of a direct solver, a one-level Krylov subspace iterative solver, and our two-level iterative solver verified the accuracy and accelerated convergence of the new scheme. Extensive tests in full-waveform inversion demonstrate the solver’s applicability to such problems.
PS energy imaging condition for microseismic data — Part 1: Theory and applications in 3D isotropic media
Authors: Oren Can , Shragge Jeffrey
Published: December 2020

Accurately estimating event locations is of significant importance in microseismic investigations because this information greatly contributes to the overall success of hydraulic-fracturing monitoring programs. Full-wavefield time-reverse imaging (TRI) using one or more wave-equation imaging conditions offers an effective methodology for locating surface-recorded microseismic events. Although, to be most beneficial in microseismic monitoring programs, the TRI procedure requires using accurate subsurface models that account for elastic media effects. We have developed a novel microseismic (extended) PS energy imaging condition that explicitly incorporates the stiffness tensor and exhibits heightened sensitivity to isotropic elastic model perturbations compared with existing imaging conditions. Numerical experiments demonstrate the sensitivity of the microseismic TRI results to perturbations in P- and S-wave velocity models. Zero-lag and extended microseismic source images computed at selected subsurface locations yield useful information about 3D P- and S-wave velocity model accuracy. Thus, we assert that these image volumes potentially can serve as the input into microseismic elastic velocity model building algorithms.
PS energy imaging condition for microseismic data — Part 2: Sensitivity analysis in 3D anisotropic media
Authors: Oren Can , Shragge Jeffrey
Published: December 2020

In microseismic monitoring, obtaining reliable information about event properties, such as the location, origin time, and moment-tensor components, is critical for evaluating the success of fluid-injection programs. Elastic wavefield-based migration approaches can robustly image microseismic sources by extrapolating data through an earth model and evaluating an imaging condition. The success of these imaging methods, though, primarily depends on the elastic model’s accuracy. The previously developed extended PS energy imaging condition can provide valuable information about the accuracy of the elastic model parameters including vertical P- and S-wave velocities as well as anisotropy coefficients. Using the SEG advanced modeling Barrett Unconventional model, we have assessed the influence of errors in the anisotropy parameters by conducting a sensitivity analysis in three types of 3D models: transversely isotropic with a vertical symmetry axis, transversely isotropic with a horizontal symmetry axis, and orthorhombic media. Our analysis on zero-lag and extended PS energy images computed with perturbed anisotropy models shows that event images exhibit different moveout patterns of misfocused energy with respect to the distorted Thomsen parameters [Formula: see text] and [Formula: see text]; however, for this model, the [Formula: see text] parameters have almost no influence on images regardless of the applied perturbations, which are reflected in the minimal traveltime differences in the data. The dependence of microseismic source images on these parameters provides essential insights into anisotropic model accuracy, and it suggests that misfocused energy on extended image gathers may be used as a criterion for updating earth models through anisotropic elastic image-domain inversion.
Synthesis, Photophysical and Electrochemical Properties of 1-, 2-, and 6-(2-Benzofuryl)azulenes
Authors: Shoji Taku , Ariga Yukino , Yamazaki Akari , Uda Mayumi , Nagasawa Takuya , Ito Shunji
Published: December 2020

The synthesis of 2- and 6-(2-benzofuryl)azulenes was accomplished by the Sonogashira-Hagihara coupling reaction of the corresponding haloazulenes with 2-ethynylphenol. 1-(2-Benzofuryl)azulenes were prepared by the decarboxylation of the corresponding 3-methoxycarbonyl derivatives with 100% H3PO4, of which the synthesis has been reported by us, recently. The photophysical properties of the (2-benzofuryl)azulenes were investigated by UV/Vis and fluorescence spectroscopies that revealed their pronounced halochromic behavior and luminescent characteristics under the light-irradiation in acidic media. The electrochemical properties of (2-benzofuryl)azulenes were also evaluated by voltammetry experiments and spectroelectrochemistry measurements.
ФЕНОМЕН КОРРУПЦИИ В СИСТЕМЕ ВОЕВОДСКОГО УПРАВЛЕНИЯ В СИБИРИ XVII В.: МЕЖДИСЦИПЛИНАРНЫЙ ПОДХОД К ИЗУЧЕНИЮ ПРИЧИН
Authors: Elantseva Olga Pavlovna , Shakhodanova Olga Yuryevna
Published: December 2020

Цель. Статья посвящена актуальной для современной науки теме – формированию феномена коррупциогенного поведения сибирских воевод XVII в. Предметом анализа выступают различные источники, отражающие факты злоупотреблений сибирских воевод. Авторы ставят целью проведение анализа причин формирования феномена коррупциогенного поведения сибирских воевод XVII в., основываясь на применении различных методологических подходов к изучению данного явления.Метод или методология проведения работы. Методологической основой исследования является принцип научного плюрализма, принцип историзма и научной объективности, методы источниковедческого анализа, герменевтический, феноменологический и компаративистский методы, а также принцип историко-философской реконструкции, предложенный А. Кожевым, при анализе проблем государства, власти и права.Результаты. Авторы считают, что модель существования «реальности коррупции» среди сибирских воевод совершенно не изучена в силу сложности интерпретации источников, в «лаборатории ученого», изучающего проблему коррупции, необходимо применение междисциплинарного многоаспектного инструментария.Область применения результатов. Результаты исследования могут быть применены в практике преподавания истории, теории государства и права, административного права и процесса, курса исторических дисциплин.
ИЗОБРЕТЕНИЕ ТРАДИЦИЙ KAK «ОТЛОЖЕННОЕ» ВООБРАЖЕНИЕ НАЦИИ В СОРБСКОМ НАЦИОНАЛИЗМЕ ЧАСТЬ 2. ВООБРАЖЕНИЕ СОРБСКОЙ ЭТНИЧЕСКОЙ И ПОЛИТИЧЕСКОЙ НАЦИИ В НАЦИОНАЛИЗМЕ МЕНЬШИНСТВА С «НЕГАТИВНЫМ» СОЦИАЛЬНЫМ НАСЛЕДИЕМ
Authors: Kyrchanoff Maksym W.
Published: December 2020

Цель. Автор анализирует проблемы сорбской этнической культуры как одной из изобретенных традиций сорбского национализма. Целью статьи является анализ стратегий, используемых интеллектуалами для актуализации и визуализации этнической культуры сорбов как формы идентичности и изобретенной традиции в современной ситуации.Методы. Методологически статья основана на принципах междисциплинарной историографии национализма, включая концепции воображения сообществ и изобретения традиций.Выводы. Анализируя роль и значение этничности и этнической культуры в ее систематизированной и стандартизированной версии автор полагает, что эти факторы в сорбском национализме были более важны чем в других европейских национализмах, которые постепенно утрачивали потенциал этничности, сократив и минимизировав ее до музеифицированных форм. Автор полагает, что несколько факторов, включая угрозы германизации, отсутствие полных социальных структур, медленная динамика политических и социальных трансформаций стали стимулами для сорбских интеллектуалов использовать потенциал традиционной культуры в ее этнических формах. В целом предполагается, что актуальная фаза в развитии сорбского культурного национализма привела к его виртуализации, изменению форм этнической мобилизации, окончательному превращению культурных активностей националистов в одну из практик изобретения традиций. В статье показано, что существование этнической культуры как изобретенной традиции является важным фактором в существовании сорбов как воображаемого сообщества и политической нации.