bluuebunny/crossref_metadata_2025 huggingface dataset:
Awareness, attitude and barriers of colorectal cancer screening among high-risk populations in China: a cross-sectional study
Authors: Huang Ruo-lin , Liu Qi , Wang Ying-xin , Zou Jin-yu , Hu Li-feng , Wang Wen , Huang Ying-hui , Wang Yi-zhuo , Zeng Bo , Zeng Xi , Zeng Ying
Published: July 2021

Objective

To assess the awareness, attitude and barriers of colorectal cancer screening among high-risk populations in China.

Design

A cross-sectional study was employed.

Setting

This study was conducted in nine hospitals in Hunan province, China.

Participants

Individuals with a high-risk for colorectal cancer were interviewed using a pretested structured questionnaire.

Primary and secondary outcome measures

Knowledge, attitude towards colorectal cancer screening, sociodemographic factors associated with screening knowledge and behaviour and barriers of colorectal cancer screening.

Results

This study included 684 participants. The mean knowledge score was 11.86/24 (SD 4.84). But over 70% of them held a positive attitude towards screening. Only 13.3% had undergone colorectal cancer screening. Independent factors related to knowledge were education level of college or above, working as a white collar, higher income, having health insurance, having seen a doctor in the past year and with a high perceived risk (p<0.05). Factors independently associated with screening behaviour included personal history of colorectal disease, having seen a doctor in the past year, previous discussion of colorectal cancer screening, high perceived risk and better knowledge (p<0.05). Main reasons for not undergoing screening were no symptoms or discomfort (71.1%), never having thought of the disease or screening (67.4%) and no doctor advised me (29.8%).

Conclusion

In China, the majority of high-risk people had deficient knowledge and had never undergone colorectal cancer screening. But most of them held a positive attitude towards the benefits of colorectal cancer screening. This has promising implications to design targeted educational campaigns and establish screening programmes to improve colorectal cancer awareness and screening participation. Healthcare professionals should advise high-risk individuals to participate in screening and inform them about cancer risk.
Telemedicine in primary healthcare for the quality of care in times of COVID-19: ascoping reviewprotocol
Authors: Silva Cícera Renata Diniz Vieira , Lopes Rayssa Horácio , Júnior Osvaldo de Goes Bay , Fuentealba-Torres Miguel , Arcêncio Ricardo Alexandre , da Costa Uchôa Severina Alice
Published: July 2021

Introduction

Telemedicine gained strength in primary healthcare (PHC) during the COVID-19 pandemic. Thus, there is a need to know its scope, technologies used and impacts on people’s health. This study will map telemedicine use in PHC around the world and its impacts on quality of care in the context of the COVID-19 pandemic.

Methods

This is a scoping review protocol developed according to Arksey and O"Malley and Levacet al, based on the Joanna Briggs Institute manual, and guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). The records will be mapped in the following multidisciplinary health sciences databases: Virtual Health Library, PubMed, Scopus, Web of Science, CINAHL and Embase. Searches will also be conducted on Google Scholar, preprint repositories and specific COVID-19 databases (grey literature). Quantitative data will be analysed using descriptive statistics, while thematic analysis will be performed for qualitative data. Preliminary findings will be presented to stakeholders to identify missing studies and develop effective dissemination strategies.

Ethics and dissemination

Results will be disseminated through publication in an open access scientific journal, scientific events, and academic and community newspapers. Ethical approval was obtained due to stakeholder consultation, but will not involve the direct participation of patients. Link to the protocol record in the Open Science Framework (OSF) (osf.io/q94en).
What do patients expect? Assessing patient-centredness from the patients’ perspective: an interview study
Authors: Zeh Stefan , Christalle Eva , Zill Jördis M , Härter Martin , Block Andreas , Scholl Isabelle
Published: July 2021

Objective

Although there has been much conceptual work on patient-centredness (PC), patients‘ perspectives on PC were neglected. In a previous study, participating patients rated the relevance of 16 dimensions of an integrative model of PC as high to very high. However, it remained unclear which specific behaviours described in the dimensions were considered most relevant. Thus, the aim of the current study was to further explore which of the specific behaviours described in the model are especially relevant for the high ratings in the previous study.

Methods and design

We conducted semistructured interviews with 20 patients with chronic diseases (16 females, 4 males, mean age: 52 years). Patients answered questions regarding their experiences in the German healthcare system and how optimal healthcare would look like from their perspective. Furthermore, patients were asked to reflect on the most important aspects which they had mentioned in the interview before. Data were analysed via content analysis.

Results

Participants addressed many different aspects of PC, but mostly focused on three major themes: (1) time appropriate access to care, (2) competence, empathy and being taken seriously by HCPs, (3) HCPs’ individual consideration of each patient’s situation (eg, wishes and needs). Minor themes were: (1) taking a holistic perspective of the patient, (2) patient-centred communication, (3) integration of multidisciplinary treatment elements, (4) transparency regarding waiting time and (5) reduction of unequal access to care.

Conclusion

This study enriches the construct of PC by depicting essential aspects of PC from the patients’ perspective. The results allow prioritising strategies to implement patient-centred care. Thus, this study helps to pursue the ultimate goal of fostering patient-centred healthcare delivery in Germany.
Epidemiology of healthcare harm in New Zealand general practice: a retrospective records review study
Authors: Leitch Sharon , Dovey Susan , Cunningham Wayne , Wallis Katharine , Eggleton Kyle , Lillis Steven , McMenamin Andrew , Williamson Martyn , Reith David , Samaranayaka Ariyapala , Tilyard Murray
Published: July 2021

Objectives

To determine the epidemiology of healthcare harm observable in general practice records.

Design

Retrospective cohort records review study.

Setting

72 general practice clinics were randomly selected from all 988 New Zealand clinics stratified by rurality and size; 44 clinics consented to participate.

Participants

9076 patient records were randomly selected from participating clinics.

Intervention

Eight general practitioners examined patient records (2011–2013) to identify harms, harm severity and preventability. Analyses were weighted to account for the stratified sampling design and generalise findings to all New Zealand patients.

Main outcome measures

Healthcare harm, severity and preventability.

Results

Reviewers identified 2972 harms affecting 1505 patients aged 0–102 years. Most patients (82.0%, weighted) experienced no harm. The estimated incidence of harm was 123 per 1000 patient-years. Most harms (2160; 72.7%, 72.4% weighted) were minor, 661 (22.2%, 22.8% weighted) were moderate, and 135 (4.5%, 4.4% weighted) severe. Eleven patients died, five following a preventable harm. Of the non-fatal harms, 2411 (81.6%, 79.4% weighted) were considered not preventable. Increasing age and number of consultations were associated with increased odds of harm. Compared with patients aged ≤49 years, patients aged 50–69 had an OR of 1.77 (95% CI 1.61 to 1.94), ≥70 years OR 3.23 (95% CI 2.37 to 4.41). Compared with patients with ≤3 consultations, patients with 4–12 consultations had an OR of 7.14 (95% CI 5.21 to 9.79); ≥13 consultations OR 30.06 (95% CI 21.70 to 41.63).

Conclusions

Strategic balancing of healthcare risks and benefits may improve patient safety but will not necessarily eliminate harms, which often arise from standard care. Reducing harms considered ‘not preventable’ remains a laudable challenge.
Lifestyle and Empowerment Techniques in Survivorship of Gynaecologic Oncology (LETSGO study): a study protocol for a multicentre longitudinal interventional study using mobile health technology and biobanking
Authors: Vistad Ingvild , Skorstad Mette , Demmelmaier Ingrid , Småstuen Milada Cvancarova , Lindemann Kristina , Wisløff Torbjørn , van de Poll-Franse Lonneke V , Berntsen Sveinung
Published: July 2021

Introduction

The number of gynaecological cancer survivors is increasing and there is a need for a more sustainable model of follow-up care. Today’s follow-up model is time-consuming and patients have reported unmet needs regarding information about their cancer and strategies for managing the consequences of treatment. The main aim of this study is to assess health-related empowerment—in terms of patient education, psychosocial support, and promotion of physical activity—in a new follow-up model by comparing it to standard follow-up in a quasi-randomised study involving intervention hospitals and control hospitals.

Methods and analysis

At the intervention hospitals, patients will be stratified by risk of recurrence and late effects to either 1 or 3 years’ follow-up. Nurses will replace doctors in half of the follow-up visits and focus in particular on patient education, self-management and physical activity. They will provide patients with information and guide them in goal setting and action planning. These measures will be reinforced by a smartphone application for monitoring symptoms and promoting physical activity. At the control hospitals, patients will be included in the standard follow-up programme. All patients will be asked to complete questionnaires at baseline and after 3, 6, 12, 24 and 36 months. Blood samples will be collected for biobanking at 3, 12 and 36 months. The primary outcome is health-related empowerment. Secondary outcomes include health-related quality of life, adherence to physical activity recommendations, time to recurrence, healthcare costs and changes in biomarkers. Changes in these outcomes will be analysed using generalised linear mixed models for repeated measures. Type of hospital (intervention or control), time (measurement point), and possible confounders will be included as fixed factors.

Ethics and dissemination

The study is approved by the Regional Committee for Medical Research Ethics (2019/11093). Dissemination of findings will occur at the local, national and international levels.

Trial registration number

NCT04122235.
Age-dependent effect of susceptibility factors on the risk of intracerebral haemorrhage: Multicenter Study on Cerebral Hemorrhage in Italy (MUCH-Italy)
Authors: Locatelli Martina , Grassi Mario , Saba Valentina , Iacovello Licia , di Castelnuovo Augusto , de Gaetano Giovanni , Zedde Marialuisa , Marcheselli Simona , silvestrelli Giorgio , Ciccone Alfonso , Delodovici Maria Luisa , Princiotta Cariddi Lucia , giossi Alessia , Zini Andrea , Paciaroni Maurizio , Acciarresi Monica , Azzini Cristiano , De Vito Alessandro , Gamba Massimo , Magoni Mauro , del Sette Massimo , Toriello Antonella , Gandolfo Carlo , Finocchi Cinzia , Bonifati Domenico Marco , Tassi Rossana , Martini Giuseppe , Cavallini Anna , Morotti Andrea , bonacina sonia , Mazzoleni Valentina , Pezzini Debora , Chiti Alberto , Calabrò Rocco Salvatore , Musolino Rosa , La Spina Paolo , Grillo Francesco , Tomelleri Giampaolo , Lodigiani Corrado , Ritelli Marco , Colombi Marina , Padovani Alessandro , Pezzini Alessandro
Published: July 2021

Objective

To investigate the age-dependent impact of traditional stroke risk factors on the occurrence of intracerebral haemorrhage (ICH).

Methods

We performed a case–control analysis, comparing consecutive patients with ICH with age-matched and sex-matched stroke-free controls, enrolled in the setting of the Multicenter Study on Cerebral Hemorrhage in Italy (MUCH-Italy) between 2002 and 2014 by multivariable logistic regression model within subgroups stratified by age quartiles (Q1–Q4).

Results

We analysed 3492 patients and 3492 controls. The impact of untreated hypertension on the risk of ICH was higher in the lower than in the upper age quartile (OR 11.64, 95% CI 7.68 to 17.63 in Q1 vs OR 6.05, 95% CI 3.09 to 11.85 in Q4 with intermediate ORs in Q2 and Q3), while the opposite trend was observed for untreated hypercholesterolaemia (OR 0.63, 95% CI 0.45 to 0.97 in Q1 vs OR 0.36, 95% CI 0.26 to 0.56 in Q4 with intermediate ORs in Q2 and Q3). The effect of untreated diabetes and excessive alcohol intake was detected only in the older age group (OR 3.63, 95% CI 1.22 to 10.73, and OR 1.69, 95% CI 1.13 to 2.51, respectively).

Conclusions

Our findings provide evidence of age-dependent differences in the effects of susceptibility factors on the risk of ICH.
Can we learn from hidden mistakes? Self-fulfilling prophecy and responsible neuroprognostic innovation
Authors: Mertens Mayli , King Owen C. , van Putten Michel J. A. M. , Boenink Marianne
Published: July 2021

A self-fulfilling prophecy (SFP) in neuroprognostication occurs when a patient in coma is predicted to have a poor outcome, and life-sustaining treatment is withdrawn on the basis of that prediction, thus directly bringing about a poor outcome (viz. death) for that patient. In contrast to the predominant emphasis in the bioethics literature, we look beyond the moral issues raised by the possibility that an erroneous prediction might lead to the death of a patient who otherwise would have lived. Instead, we focus on the problematic epistemic consequences of neuroprognostic SFPs in settings where research and practice intersect. When this sort of SFP occurs, the problem is that physicians and researchers are never in a position to notice whether their original prognosis was correct or incorrect, since the patient dies anyway. Thus, SFPs keep us from discerning false positives from true positives, inhibiting proper assessment of novel prognostic tests. This epistemic problem of SFPs thus impedes learning, but ethical obligations of patient care make it difficult to avoid SFPs. We then show how the impediment to catching false positive indicators of poor outcome distorts research on novel techniques for neuroprognostication, allowing biases to persist in prognostic tests. We finally highlight a particular risk that a precautionary bias towards early withdrawal of life-sustaining treatment may be amplified. We conclude with guidelines about how researchers can mitigate the epistemic problems of SFPs, to achieve more responsible innovation of neuroprognostication for patients in coma.
Lord Sumption and the values of life, liberty and security: before and since the COVID-19 outbreak
Authors: Coggon John
Published: July 2021

Lord Sumption, a former Justice of the Supreme Court, has been a prominent critic of coronavirus restrictions regulations in the UK. Since the start of the pandemic, he has consistently questioned both the policy aims and the regulatory methods of the Westminster government. He has also challenged rationales that hold that all lives are of equal value. In this paper, I explore and question Lord Sumption’s views on morality, politics and law, querying the coherence of his broad philosophy and his arguments regarding coronavirus regulations with his judicial decision in the assisted-dying case of R (Nicklinson) v Ministry of Justice. In Nicklinson, Lord Sumption argued for restrictions on liberty given the priority of the sanctity of life principle and the protection of others who may be vulnerable, as well as for deference to policy-making institutions in instances of values-based disagreement. The apparent inconsistencies in his positions, I argue, are not clearly reconcilable, and invite critical analysis of his impacts on health law and policy.
Manipulating strong electromagnetic fields with the average transverse momentum of relativistic nuclear collisions
Authors: Giacalone Giuliano , Shen Chun
Published: July 2021

We show that an event-shape engineering based on the mean transverse momentum of charged hadrons, $$[p_t]$$

[

p
t

]

, provides an optimal handle on the strength of the magnetic field created in central heavy-ion collisions at high energy. This is established through quantitative evaluations of the correlation existing between the event-by-event magnetic field produced by the spectator protons in 5.02 TeV Pb + Pb collisions and the event-by-event $$[p_t]$$

[

p
t

]

at a given collision centrality. We argue that the event selection based on $$[p_t]$$

[

p
t

]

provides a better handle on the magnetic field than the more traditional selection based on the event ellipticities. Advantages brought by this new method for the experimental search of the chiral magnetic effect are discussed.
On the Safety of Mobile Robots Serving in Public Spaces
Authors: Salvini Pericle , Paez-Granados Diego , Billard Aude
Published: July 2021

Since 2014, a specific standard has been dedicated for the safety certification of personal care robots, which operate in close proximity to humans. These robots serve as information providers, object transporters, personal mobility carriers, and security patrollers. In this article, we point out the shortcomings concerning EN ISO 13482:2014, which encompasses guidelines regarding the safety and design of personal care robots. In particular, we argue that the current standard is not suitable for guaranteeing people's safety when these robots operate in public spaces. Specifically, the standard lacks requirements to protect pedestrians and bystanders. The guideline implicitly assumes that private spaces, such as households and offices, present the same hazards as in public spaces. We highlight the existence of at least three properties pertaining to robots’ use in public spaces. These properties include (1) crowds, (2) social norms and proxemics rules, and (3) people's misbehaviours. We discuss how these properties impact robots’ safety. This article aims to raise stakeholders’ awareness on individuals’ safety when robots are deployed in public spaces. This could be achieved by integrating the gaps present in EN ISO 13482:2014 or by creating a new dedicated standard.
Using Machine Learning for Dependable Outlier Detection in Environmental Monitoring Systems
Authors: Jesus Gonçalo , Casimiro António , Oliveira Anabela
Published: July 2021

Sensor platforms used in environmental monitoring applications are often subject to harsh environmental conditions while monitoring complex phenomena. Therefore, designing dependable monitoring systems is challenging given the external disturbances affecting sensor measurements. Even the apparently simple task of outlier detection in sensor data becomes a hard problem, amplified by the difficulty in distinguishing true data errors due to sensor faults from deviations due to natural phenomenon, which look like data errors. Existing solutions for runtime outlier detection typically assume that the physical processes can be accurately modeled, or that outliers consist in large deviations that are easily detected and filtered by appropriate thresholds. Other solutions assume that it is possible to deploy multiple sensors providing redundant data to support voting-based techniques.

In this article, we propose a new methodology for dependable runtime detection of outliers in environmental monitoring systems, aiming to increase data quality by treating them. We propose the use of machine learning techniques to model each sensor behavior, exploiting the existence of correlated data provided by other related sensors. Using these models, along with knowledge of processed past measurements, it is possible to obtain accurate estimations of the observed environment parameters and build failure detectors that use these estimations. When a failure is detected, these estimations also allow one to correct the erroneous measurements and hence improve the overall data quality. Our methodology not only allows one to distinguish truly abnormal measurements from deviations due to complex natural phenomena, but also allows the quantification of each measurement quality, which is relevant from a dependability perspective.

We apply the methodology to real datasets from a complex aquatic monitoring system, measuring temperature and salinity parameters, through which we illustrate the process for building the machine learning prediction models using a technique based on Artificial Neural Networks, denoted
ANNODE
(
ANN Outlier Detection
). From this application, we also observe the effectiveness of our ANNODE approach for accurate outlier detection in harsh environments. Then we validate these positive results by comparing ANNODE with state-of-the-art solutions for outlier detection. The results show that ANNODE improves existing solutions regarding accuracy of outlier detection.
Critical role of the mineralocorticoid receptor in aldosterone-dependent and aldosterone-independent regulation of ENaC in the distal nephron
Authors: Nesterov Viatcheslav , Bertog Marko , Canonica Jérémie , Hummler Edith , Coleman Richard , Welling Paul A. , Korbmacher Christoph
Published: July 2021

Using a mouse model with inducible nephron-specific mineralocorticoid receptor (MR) deficiency, we demonstrated that MR is not only critical for maintaining aldosterone-dependent ENaC activity in CNT/CCD but also for aldosterone-independent ENaC activity in DCT2/CNT. Furthermore, we demonstrated that cells of this latter nephron segment express little 11β-HSD2, which probably allows glucocorticoids to stimulate MR, resulting in aldosterone-independent ENaC activity in DCT2/CNT. This site-specific ENaC regulation has physiologically relevant implications for renal sodium and potassium homeostasis.
Prenatal Diagnosis of Fetal Cleft Lip and Palate with Three-Dimensional Ultrasound Information Technology
Authors: Deng Xinglong , He Suhui , Wu Qiumei , Weng Zongjie , Yang Minmin , Liu Min
Published: July 2021

Objective. To evaluate the three-dimensional ultrasound paper cleft lip and palate deformities in applications in prenatal diagnosis. Methods. 25 cases of cleft lip and palate fetus, 20–32 weeks of gestational age, with the maternal age of 22–44 years, were examined by prenatal ultrasound in our hospital; conventional two-dimensional ultrasound examination was performed after a cleft lip, and the application of three-dimensional ultrasound imaging surface and a transparent imaging showed the alveolar process and the palate of the fetus. Also, the results of two-dimensional ultrasound and postnatal (or after induction) results were compared. Results. Of the 25 cases, there were 6 cases of postpartum induction or simply unilateral cleft lip, 17 cases of unilateral cleft palate, and two cases of bilateral cleft lip palate. There was no significant (

P
>
0.05

) difference of two- and three-dimensional ultrasound detection rate of pure cleft lip; two-dimensional ultrasound cleft palate detection rate was 36.8% (7/19), and three-dimensional ultrasound cleft palate detection rate was 89.5% (17/19). The two methods showed a statistically significant (

P
<
0.05

) difference in the detection rate of cleft palate. Conclusion. Three-dimensional ultrasound can significantly improve the diagnostic accuracy of prenatal cleft palate.
Numerical Analysis on the Storage of Nuclear Waste in Gas-Saturated Deep Coal Seam
Authors: Teng Teng , Wang Yuming , Zhu Xiaoyan , Zhang Xiangyang , Yi Sihai , Fan Guowei , Liu Bin
Published: July 2021

Nuclear power has contributed humanity a lot since its successful usage in electricity power generation. According to the global statistics, nuclear power accounts for 16% of the total electricity generation in 2020. However, the rapid development of nuclear power also brings up some problems, in which the storage of nuclear waste is the thorny one. This work carries out a series of modeling and simulation analysis on the geological storage of nuclear waste in a gas-saturated deep coal seam. As the first step, a coupled heat-solid-gas model with three constitutional fields of heat transfer, coal deformation, and gas seepage that based on three governing conservation equations is proposed. The approved mechanical model covers series of interactive influences among temperature change, dual permeability of coal, thermal stress, and gas sorption. As the second step, a finite element numerical model and numerical simulation are developed to analyze the storage of nuclear waste in a gas-saturated deep coal seam based on the partial differential equations (PDE) solver of COMSOL Multiphysics with MATLAB. The numerical simulation is implemented and solved then to draw the following conclusions as the nuclear waste chamber heats up the surrounding coal seam firstly in the initial storage stage of 400 years and then be heated by the far-field reservoir. The initial velocity of gas flow decreases gradually with the increment of distance from the storage chamber. Coal gas flows outward from the central storage chamber to the outer area in the first 100 years when the gas pressure in the region nearby the central storage chamber is higher than that in the far region and flows back then while the temperature in the outer region is higher. The modeling and simulation studies are expected to provide a deep understanding on the geological storage of nuclear waste.
Biosynthesis of Organic Nanocomposite Using Pistacia vera L. Hull: An Efficient Antimicrobial Agent
Authors: Bakhshi Omolbanin , Bagherzade Ghodsieh , Ghamari kargar Pouya
Published: July 2021

Here presented a quick and easy synthesis of copper nanoparticles (CuNPs). Pistachio hull extract has been used as a reducing and stabilizing agent in the preparation of CuNPs. This biosynthesis is a kind of supporter of the environment because chemical agents were not used to making nanoparticles, and on the other hand, it prevents the release of pistachio waste in nature and its adverse effects on nature. The biosynthesized CuNPs and CuNPs/silver Schiff base nanocomposite (CSS NC) were characterized by UV-VIS spectroscopy, Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and energy-dispersive X-ray spectroscopy (EDS). CuNP and CSS NC antimicrobial activity was examined by both well diffusion and determination MIC methods against four bacteria Staphylococcus aureus, Bacillus cereus, Escherichia coli, and Pseudomonas aeruginosa and two fungi Aspergillus Niger and Candida albicans. CuNPs and CSS NC showed significant antimicrobial activity on the samples, preventing the growth of bacteria and fungi at very low concentrations. CuNPs and CSS NC had the greatest effect on Escherichia coli bacteria and Aspergillus niger fungi. Phenolic compounds are one of the most important antioxidants that are involved in various fields, including pharmacy. Pistacia vera hull is a rich source of phenolic compounds. In this study, the most phenolic compound in Pistacia vera hull is gallic acid and rutin, which has been identified by HPLC analysis. In this study, Pistacia vera hull essential oil analysis was performed by the GC-MS method, in which α-pinene, D-limonene, and isobornyl acetate compounds constitute the highest percentage of Pistacia vera hull essential oil.
Application of Data Mining Algorithms for Dementia in People with HIV/AIDS
Authors: Pinheiro Luana Ibiapina Cordeiro Calíope , Pereira Maria Lúcia Duarte , Fernandez Marcial Porto , Filho Francisco Mardônio Vieira , de Abreu Wilson Jorge Correia Pinto , Pinheiro Pedro Gabriel Calíope Dantas
Published: July 2021

Dementia interferes with the individual’s motor, behavioural, and intellectual functions, causing him to be unable to perform instrumental activities of daily living. This study is aimed at identifying the best performing algorithm and the most relevant characteristics to categorise individuals with HIV/AIDS at high risk of dementia from the application of data mining. Principal component analysis (PCA) algorithm was used and tested comparatively between the following machine learning algorithms: logistic regression, decision tree, neural network, KNN, and random forest. The database used for this study was built from the data collection of 270 individuals infected with HIV/AIDS and followed up at the outpatient clinic of a reference hospital for infectious and parasitic diseases in the State of Ceará, Brazil, from January to April 2019. Also, the performance of the algorithms was analysed for the 104 characteristics available in the database; then, with the reduction of dimensionality, there was an improvement in the quality of the machine learning algorithms and identified that during the tests, even losing about 30% of the variation. Besides, when considering only 23 characteristics, the precision of the algorithms was 86% in random forest, 56% logistic regression, 68% decision tree, 60% KNN, and 59% neural network. The random forest algorithm proved to be more effective than the others, obtaining 84% precision and 86% accuracy.
Joint Angle and Frequency Estimation in Linear Arrays Based on Covariance Reconstruction and ESPRIT
Authors: Chen Shihong , Tao Qingchang , Yang Zhongtian , Wang Xudong , Liu Sijia , Xu Wei
Published: July 2021

Joint angle and frequency estimation, one of the key technologies in wireless communication and radar science, has been extensively studied by scholars. For linear arrays, this paper proposes a joint angle and frequency estimation method based on covariance reconstruction and the estimation of signal parameters via rotational invariance techniques (CR-ESPRIT). We first use the received conjugate signal to reconstruct a covariance matrix. Then, we use the least squares-ESPRIT (LS-ESPRIT) algorithm to estimate the desired frequencies. Finally, we estimate the angles according to the reconstructed matrix. The proposed method can estimate signal parameters via automatic pairing and without an additional parameter pairing process under the condition of a uniform or a nonuniform array. Moreover, this method has high estimation accuracy, excellent and stable anti-noise performance, and strong algorithmic robustness. Through a computer simulation analysis, we can confirm the reliability and validity of the proposed parameter estimation method. A comparison with other methods further proves the performance advantages of the developed method. The method in this paper can be easily applied to many signal processing contexts, such as electronic reconnaissance and wireless communication.
Classification of Digital Modulated COVID‐19 Images in the Presence of Channel Noise Using 2D Convolutional Neural Networks
Authors: Khan Rahim , Yang Qiang , Tufail Ahsan Bin , Noor Alam , Ma Yong-Kui
Published: July 2021

The wireless environment poses a significant challenge to the propagation of signals. Different effects such as multipath scattering, noise, degradation, distortion, attenuation, and fading affect the distribution of signals adversely. Deep learning techniques can be used to differentiate among different modulated signals for reliable detection in a communication system. This study aims at distinguishing COVID‐19 disease images that have been modulated by different digital modulation schemes and are then passed through different noise channels and classified using deep learning models. We proposed a comprehensive evaluation of different 2D Convolutional Neural Network (CNN) architectures for the task of multiclass (24‐classes) classification of modulated images in the presence of noise and fading. It is used to differentiate between images modulated through Binary Phase Shift Keying, Quadrature Phase Shift Keying, 16‐ and 64‐Quadrature Amplitude Modulation and passed through Additive White Gaussian Noise, Rayleigh, and Rician channels. We obtained mixed results under different settings such as data augmentation, disharmony between batch normalization (BN), and dropout (DO), as well as lack of BN in the network. In this study, we found that the best performing model is a 2D‐CNN model using disharmony between BN and DO techniques trained using 10‐fold cross‐validation (CV) with a small value of DO before softmax and after every convolution and fully connected layer along with BN layers in the presence of data augmentation, while the least performing model is the 2D‐CNN model trained using 5‐fold CV without augmentation.
The Research of Coal and Gas Outburst Warning Based on Logistic Regression and Geographic Information System
Authors: You Bo , Li Bo , Shi Shi Liang , Liu He Qing , Lu Yi , Li He
Published: July 2021

Coal and gas outburst is one of the major disasters in the safety production of coal mine. According to the mechanism of coal and gas outburst, based on the comprehensive analysis of various influencing factors of coal and gas outburst, with the principles of selected early warning indicator, the basic information database of coal and gas outburst warning is constructed, and the information data query function is realized. The mathematical model of coal and gas outburst warning is established by the logistic regression analysis based on the gas concentration, the gas desorption index of drill cuttings, and the initial velocity of gas emission from the borehole. The multivariate information coupled warning was conducted according to the selected early warning indicator system, and the early warning level was divided with the result of early warning. The design and research of the coal and gas outburst warning system are carried out based on the geographic information system (GIS). The coal and gas outburst warning system was verified by taking the Tunliu mine of Lu’an Group as an example. The establishment of the early warning system is a new technical way to the early warning management of coal and gas outburst and can provide a guarantee for coal and gas outburst prevention.
Massive Acetaminophen Overdose Treated Successfully with N-Acetylcysteine, Fomepizole, and Hemodialysis
Authors: Chiu Michael H. , Jaworska Natalia , Li Nicholas L. , Yarema Mark
Published: July 2021

Acetaminophen overdose is one of the most common causes of acute hepatic failure in the developed world. There is strong evidence for N-acetylcysteine (NAC) as a safe and effective antidote for acetaminophen toxicity. However, there is less clarity in the management of massive overdoses (acute, singleingestions>500 mg/kg with 4-hour equivalent concentrations ~6000 μmol/L) which are often associated with metabolic acidosis and multiorgan dysfunction. In such ingestions, the role of adjuvant treatments such as fomepizole and extracorporeal removal is unclear. We present a case of a 20-year-old female presenting with an acute ingestion of over 120 grams (1764.7 mg/kg) and an acetaminophen concentration of 5880 μmol/L who developed refractory shock, decreased level of consciousness, and metabolic acidosis requiring mechanical ventilation and vasopressor support. She was treated with gastric decontamination with activated charcoal, IV NAC, fomepizole, and hemodialysis. The patient had complete clearance of acetaminophen by 32 hours after presentation and normalization of her acid base and hemodynamic status without any organ failure. This case highlights the potential benefit of a triple strategy of NAC, fomepizole, and early hemodialysis in massive acetaminophen overdose, potentially sparing complications of prolonged intubation and ICU hospitalization.
Reader Scheduling for Tag Population Estimation in Multicategory and Multireader RFID Systems
Authors: He Zhiyong
Published: July 2021

Radio Frequency Identification (RFID) technology has been used in numerous applications, e.g., supply chain management and inventory control. This paper focuses on the practically important problem of the rapid estimation of the number of tags in large‐scale RFID systems with multiple readers and multicategory RFID tags. RFID readers are often static and have to be deployed strategically after careful planning to cover the entire monitoring area, but reader‐to‐reader collision (R2Rc) remains a problem. R2Rc decreases the reliability of the estimation of the tag population size, because it results in the failure of communication between the reader and tags. In this paper, we propose a coloring graph‐based estimation scheme (CGE), which is the first estimation framework designed for multireader and multicategory RFID systems to determine the distribution of tags in different categories. CGE allows for the use of any estimation protocol to determine the number of tags, prevents R2Rc, and results in higher time efficiency and less power‐consumption than the classic scheduling method DCS.
LncRNA ELF3-AS1 is a Prognostic Biomarker and Correlated with Immune Infiltrates in Hepatocellular Carcinoma
Authors: Chen Tianming , Zhu Changhao , Wang Xing , Pan Yaozhen
Published: July 2021

Background. Expression of long noncoding RNA (lncRNA) ELF3 antisense RNA 1 (ELF3-AS1) is observed in some cancers, while its role in hepatocellular carcinoma (HCC) is unclear. The study aimed to investigate the relationship between ELF3-AS1 and HCC based on database, bioinformatics, and statistical analysis. Methods. In this study, Kruskal–Wallis test, Wilcoxon sign-rank test, logistic regression, Kaplan–Meier method, Cox regression analysis, gene set enrichment analysis (GSEA), and immunoinfiltration analysis were used to assess the relationship between ELF3-AS1 expression and clinical characteristics of HCC patients, the relationship between ELF3-AS1 expression and prognosis of HCC patients, and the possible functions of ELF3-AS1 in HCC. Results. High expression of ELF3-AS1 in patients with HCC was related to T stage (

P

 < 0.001), gender (

P

 = 0.006), residual tumor (

P

 = 0.008), histologic grade (

P

 < 0.001), adjacent hepatic tissue inflammation (

P

 = 0.011), AFP (

P

 < 0.001), and vascular invasion (

P

 = 0.028). High ELF3-AS1 expression was associated with poor overall survival (OS) (

P

 = 0.001) and DSS (

P

 = 0.047). ELF3-AS1 expression (

P

 = 0.011) was independently correlated with OS in HCC patients. In the high ELF3-AS1 expression group, GPCR-radioligand binding, M phase, Class A/1 (rhodopsin-like receptors), cell cycle checkpoints, translation, mitotic metaphase and anaphase, signaling by robo receptors, keratinization, and rRNA processing were differentially enriched by GESA. ELF3-AS1 expression was associated with immune infiltrating cells. Conclusions. ELF3-AS1 expression was associated with poor prognosis in HCC. ELF3-AS1 expression was significantly associated with immune infiltration. ELF3-AS1 is a promising biomarker that can be used for the diagnosis and prognosis of HCC.
Novel Dombi Aggregation Operators in Spherical Cubic Fuzzy Information with Applications in Multiple Attribute Decision-Making
Authors: Tehreem  , Hussain Amjad , Alsanad Ahmed
Published: July 2021

The notion of spherical fuzzy sets (SFSs) is one of the most effective ways to model the fuzzy information in decision-making processes. The sum of squares of membership, neutral, and nonmembership degrees in SFSs lies in the interval [0, 1] and accommodates more uncertainties. Henceforth, in this article, the idea of spherical cubic fuzzy sets (SCFSs) is introduced, which is the generalization of SFSs. Spherical cubic fuzzy set is the combination of spherical fuzzy sets and interval-valued spherical fuzzy sets. The membership, neutral, and nonmembership degrees in an SCFS are cubic fuzzy numbers (CFNs). Consequently, this set outperforms the pre-existing structures of fuzzy set theory. Moreover, some fundamental operations for the comparison of two spherical CFNs are defined such as score function and accuracy function. Further, several new operations through Dombi t-norm and Dombi t-conorms are characterized to get the best results during the decision criteria. Furthermore, spherical cubic fuzzy Dombi weighted averaging (SCFDWA), SCFD ordered weighted averaging (SCFDOWA), SCFD hybrid weighted averaging (SCFDHWA), SCFD weighted geometric (SCFDWG), SCFD ordered weighted geometric (SCFDOWG), and the SCFD hybrid weighted geometric (SCFDHWG) aggregated operators are discussed, and their characteristics are examined. In addition, some of the operational laws of these operators are defined. Also, a decision-making approach based on these operators is proposed. Since the proposed methods and operators are the generalizations of the existing methods and operators, therefore, these techniques produce more general, accurate, and precise results as compared with existing ones. Finally, a descriptive example is given in order to describe the validity, practicality, and effectiveness of the proposed methods.
Dimension Reduction Big Data Using Recognition of Data Features Based on Copula Function and Principal Component Analysis
Authors: Badakhshan Farahabadi Fazel , Fathi Vajargah Kianoush , Farnoosh Rahman
Published: July 2021

Nowadays, data are generated in the world with high speed; therefore, recognizing features and dimensions reduction of data without losing useful information is of high importance. There are many ways to dimension reduction, including principal component analysis (PCA) method, which is by identifying effective dimensions in an acceptable level, reducing dimension of data. In the usual method of principal component analysis, data are usually normal, or we normalize data; then, the principal component analysis method is used. Many studies have been done on the principal component analysis method as a step of data preparation. In this paper, we propose a method that improves the principal component analysis method and makes data analysis easier and more efficient. Also, we first identify the relationships between the data by fitting the multivariate copula function to data and simulate new data using the estimated parameters; then, we reduce the dimensions of new data by principal component analysis method; the aim is to improve the performance of the principal component analysis method to find effective dimensions.
Association of Circulating Extracellular Matrix Components with Central Hemodynamics and Arterial Distensibility of Peripheral Arteries
Authors: Melnikov Vladimir N. , Kim Lena B. , Putyatina Anna N. , Krivoschekov Sergey G.
Published: July 2021

Background: In addition to neuronal and endothelial regulators of vascular tone, the passive mechanical properties of arteries, determined by the molecular structure of extracellular matrices, are the principle modulators of vascular distensibility. Specifically, the association between collagen type IV (Col IV), a constituent of basement membrane, and arterial compliance remains unclear. Methods: In 31 healthy adult men, radial applanation tonometry and pulse wave analysis were used to assess aortic augmentation index (AIx), aortic-to-radial pulse pressure amplification (PPAmpl), and time to reflection wave. Results: Plasma Col IV and tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) concentrations were correlated with AIx (r = 0.51, p = 0.021 and r = −0.45, p = 0.042, respectively) after adjustment for age and heart rate (HR). Greater matrix metalloproteinase-9 (MMP-9) and TIMP-1 levels were associated with high PPAmpl (r = 0.45 and r = 0.64, respectively) and hence with compliant arteries. Multiple regression analyses revealed that 99% of the variation in PPAmpl was attributable to age, HR, Col IV, TIMP-1, and Col × TIMP-1 interaction (p < 0.001). No relations between tonometric variables and levels of MMP-1, -2, and -3; TIMP-2 and -4; fibronectin; glycosaminoglycans; and hydroxyproline were found. Conclusion: High circulating Col IV level indexes were associated with stiffer peripheral arteries whereas increased MMP-9 and TIMP-1 concentrations were associated with more compliant ones.
Editorial
Authors: Zanella Adroaldo José , Gameiro Mariana Bombo Perozzi
Published: July 2021

Editorial for the special Donkeys and Mules
Spatiotemporality in the Anthropocene: Deleuzoguattarian Philosophy, Quantum Physics, and the German Netflix Series Dark
Authors: Fraunhofer Hedwig
Published: July 2021

Crises alter our perception of time. For medical personnel faced with treating unprecedented numbers of critically ill patients under conditions of personal threat, COVID-19 has most recently accelerated the subjective perception of time. For millions of others, social isolation has decelerated our lives. For all of us, at least in the short term, the future has become more uncertain. Theoretical physicists tell us, however, that under any conditions, the human perception of the flowing of time is only a result of our blurred, limited, macroscopic vision. As the quantum physicist Carlo Rovelli writes, therefore, “[t]o understand ourselves is to reflect on time” (2018: 179). Potentially caused by humans’ failed interactions with wild animals, the contemporary global pandemic, as well as previous outbreaks such as SARS (Severe Acute Respiratory Syndrome-related coronavirus) or the bird flu, has led to calls to reevaluate humans’ relationships with nonhuman life, with the natural environment that includes us, in the epoch that may soon be named for our very failure – the Anthropocene. In an era in which our usual, day-to-day certainties and desire for human control have been upended, not only by the current medical crisis but also by the continuing existential threat to terrestrial life that is climate change, a rethinking of the category of the human, a new conceptualization of the entangled (human and nonhuman) material relationships on our planet and beyond, requires reflecting on time. This article engages in such reflection through a conversation with the philosophical writings of Gilles Deleuze and Félix Guattari.
The imf Conditionality in the Age of Post-National Governance
Authors: Belling Vojtěch , Kollert Lukáš , Vojta Martin
Published: July 2021

The paper focuses on conditionality in imf programs for member states of monetary unions in light of the decision of the imf’s Executive Board on Program Design in Currency Unions (2018). Despite the growing importance of supranational institutions, the imf lacked until 2018 any explicit framework for imposing conditions on currency union bodies in cases where a member state of such a union requested an imf program. The aim of this paper is to assess the newly adopted imf approach to conditionality for currency union institutions based on the concept of “policy assurances” and to answer the question of whether the imf had authority to impose conditions on supranational institutions prior to the 2018 Board decision and whether the imf should in principle have such authority.
Climate Change and Sea-Level Rise
Authors: Lanovoy Vladyslav , O’Donnell Sally
Published: July 2021

This article examines the challenges that climate change and sea-level rise pose to certain key aspects of the law of the sea. Sea-level rise is likely to impact maritime baselines, the qualification of maritime features and the entitlements they generate, and ultimately the stability of maritime boundaries, which are critical for the peaceful co-existence of sovereign States. This article examines whether some of the relevant provisions of the United Nations Convention on the Law of the Sea can accommodate a liberal interpretation so as to provide some, even if incomplete, answers to the challenges posed by sea-level rise to the law of the sea regime. It is argued that the legal fiction of permanency that underpins key elements of this legal regime, and thus ignores future physical changes to coastlines, is the most appropriate temporary solution, unless and until new rules are agreed by States to deal comprehensively with sea-level rise.