bluuebunny/crossref_metadata_2025 huggingface dataset:
Three Es of linked injury data: Episodes, Encounters and Events
Authors: Vallmuur Kirsten , McCreanor Victoria , Cameron Cate , Watson Angela , Shibl Rania , Banu Shahera , McPhail Steven M , Warren Jacelle
Published: April 2021

Background

Treatment and recovery times following injury can be lengthy, comprising multiple interactions with the hospital system for initial acute care, subsequent rehabilitation and possible re-presentation due to complications.

Aims

This article aims to promote the use of consistent terminology in injury data linkage studies, suggest important factors to consider when managing linked injury data, and encourage thorough documentation and a robust discourse around different approaches to data management to ensure reproducibility, consistency and comparability of analyses arising from linked injury data.

Approach

This paper is presented in sections describing: (1) considerations for identifying injury cohorts, (2) considerations for grouping Episodes into Encounters and (3) considerations for grouping Encounters into Events. Summary tools are provided to aid researchers in the management of linked injury data.

Discussion

Careful consideration of decisions made when identifying injury cohorts and grouping data into units of analysis (Episodes/Encounters/Events) is essential when using linked injury data. Choices made have the potential to significantly impact the epidemiological and clinical findings derived from linked injury data studies, which ultimately affect the quality of injury prevention initiatives and injury management policy and practice. It is intended that this paper will act as a call to action for injury linkage methodologists, and those using linked data, to critique approaches, share tools and engage in a robust discourse to further advance the use of linked injury data, and ultimately enhance the value of linked injury data for clinicians and health and social policymakers.
Role reconfiguration: what ethnographic studies tell us about the implications of technological change for work and collaboration in healthcare
Authors: Agreli Heloise , Huising Ruthanne , Peduzzi Marina
Published: April 2021

New technologies including digital health and robotics are driving the evolution of healthcare. At the same time, healthcare systems are transitioning from a multiprofessional model approach of healthcare delivery to an interprofessional model. The concurrence of these two trends may represent an opportunity for leaders in healthcare because both require renegotiation of the complex division of work and enhanced interdependency. This review examines how the introduction of new technologies alters the role boundaries of occupations and interdependencies among health occupations. Based on a scoping review of ethnographic studies of technology implementation in a variety of contexts (from primary care to operating room) and of diverse technologies (from health informatics systems to robotics), we develop the concept of role reconfiguration to capture simultaneous adjustments of multiple, interdependent roles during technological change. Ethnographic and qualitative studies provide rich, detailed accounts of what people actually do and how their work and role is changed (or not) when a new technology arrives. Through a synthesis of these studies, we develop a typology of four types of role reconfiguration: negotiation, clarification, enlargement and restriction. We discuss leadership challenges in managing role reconfiguration and formulate four leadership priorities. We suggest that leaders: redesign roles proactively, paying attention to interdependencies; offer opportunities for collective learning about new technologies; ensure that knowledge of new technologies is distributed across roles and prepare to address resistance.
Genomic privacy, identity and dignity
Authors: Cohen Shlomo , Zultan Ro'i
Published: April 2021

Significant advancements towards a future of big data genomic medicine, associated with large-scale public dataset repositories, intensify dilemmas of genomic privacy. To resolve dilemmas adequately, we need to understand the relative force of the competing considerations that make them up. Attitudes towards genomic privacy are complex and not well understood; understanding is further complicated by the vague claim of ‘genetic exceptionalism’. In this paper, we distinguish between consequentialist and non-consequentialist privacy interests: while the former are concerned with harms secondary to exposure, the latter represent the interest in a private sphere for its own sake, as an essential component of human dignity. Empirical studies of attitudes towards genomic privacy have almost never targeted specifically this important dignitary component of the privacy interest. In this paper we first articulate the question of a non-consequentialist genomic privacy interest, and then present results of an empirical study that probed people’s attitudes towards that interest. This was done via comparison to other non-consequentialist privacy interests, which are more tangible and can be more easily assessed. Our results indicate that the non-consequentialist genomic privacy interest is rather weak. This insight can assist in adjudicating dilemmas involving genomic privacy.
Cadaveric investigation of the minimum effective volume for ultrasound-guided suprainguinal fascia iliaca block
Authors: Kantakam Perada , Maikong Naraporn , Sinthubua Apichat , Mahakkanukrauh Pasuk , Tran De Q , Leurcharusmee Prangmalee
Published: April 2021

Background

This cadaveric dose-finding study investigated the minimum effective volume of dye in 90% of cases (MEV90), required to stain the femoral, lateral femoral cutaneous and obturator nerves for ultrasound-guided suprainguinal fascia iliaca block (SIFIB).

Methods

In cadaveric specimens of the lower limb, the block needle was advanced, medial to the anterosuperior iliac spine, until its tip was positioned between the internal oblique and iliacus muscles underneath the fascia iliaca. The dye was injected inside the fascia iliaca compartment. Volume assignment was carried out using a biased coin design, whereby the volume of dye administered to each cadaveric specimen depended on the response of the previous one. In case of failure, the next one received a higher volume (defined as the previous volume with an increment of 2.5 mL). If the previous cadaveric specimen had a successful block, the next one was randomized to a lower volume (defined as the previous volume with a decrement of 2.5 mL), with a probability of
b
=0.11, or the same volume, with a probability of 1–
b
=0.89. Success was defined as the staining of the femoral, lateral femoral cutaneous, and obturator nerves on dissection.

Results

Thirty-six cadavers (60 cadaveric specimens) were included in the study. Using isotonic regression and bootstrap CI, the MEV90 for ultrasound-guided SIFIB was estimated to be 62.5 mL (95% CI 60 to 65).

Conclusion

For ultrasound-guided SIFIB, the MEV90 of dye required to stain the femoral, lateral femoral cutaneous and obturator nerves is 62.5 mL. Further studies are required to correlate this finding with the MEV90 of local anesthetic in human subjects.
Leaders rewiring mechanism promotes cooperation in public goods game
Authors: Bahbouhi Jalal Eddine , Moussa Najem
Published: April 2021

This paper investigates the evolutionary public goods game on a network and studies the effect of the leaders rewiring mechanism (LRM) on the evolution of cooperation. A trust mechanism is introduced to give information to the leader about the sincerity of the group. The network dynamics is driven by the LRM, allowing leaders to change their game groups if these groups are not trusted anymore. We investigate how the emergence of the network guided by LRM affects the transformation of individuals’ strategies and empowers them to cooperate. We find that LRM plays a crucial role in the emergence of cooperation, by clustering the graph into regions with high clusters of cooperators and small one of defectors. LRM enables cooperators to form compact big clusters, thus reducing exploitation by defectors.
Analytical versus numerical solutions of the nonlinear fractional time–space telegraph equation
Authors: Khater Mostafa M. A. , Lu Dianchen
Published: April 2021

In this paper, the stable analytical solutions’ accuracy of the nonlinear fractional nonlinear time–space telegraph (FNLTST) equation is investigated along with applying the trigonometric-quantic-B-spline (TQBS) method. This investigation depends on using the obtained analytical solutions to get the initial and boundary conditions that allow applying the numerical scheme in an easy and smooth way. Additionally, this paper aims to investigate the accuracy of the obtained analytical solutions after checking their stable property through using the properties of the Hamiltonian system. The considered model for this study is formulated by Oliver Heaviside in 1880 to define the advanced or voltage spectrum of electrified transmission, with day-to-day distances from the electrified communication or the application of electromagnetic waves. The matching between the analytical and numerical solutions is explained by some distinct sketches such as two-dimensional, scatter matrix, distribution, spline connected, bar normal, filling with two colors plots.
Cumulants and factorial cumulants in the three-dimensional Ising universality class
Authors: Pan Xue , Xu Mingmei , Wu Yuanfang
Published: April 2021

The high-order cumulants and factorial cumulants of conserved charges are suggested to study the critical dynamics in heavy ion collisions. In this paper, using parametric representation of the three-dimensional Ising model, density plots on the phase diagram and temperature dependence of the order parameter cumulants and factorial cumulants are studied and compared. In the vicinity of the critical point, cumulants and factorial cumulants can not be distinguished. Far away from the critical point, sign changes occur in the factorial cumulants comparing with the same order cumulants. The cause of sign changes is analyzed. These features may be used to measure the distance to the critical point.
Surface Reconstruction: Roles in the Field of Computer Vision and Computer Graphics
Authors: Dhar Soumi , Pal Shyamosree
Published: April 2021

Surface Reconstruction is the most potent aspect of 3D computer vision. It allows recapturing or imitating of the shape of real objects. It also provides sufficient knowledge regarding the mathematical foundation for rendering applications which are widely used for analyzing medical volume data, modeling, 3D interior designing, architectural designing. In our paper, we have mentioned various algorithms and approaches for surface reconstruction and their applications. Moreover, we have tried to emphasize the necessity of surface reconstruction for solving image analysis related problem.
Impulsive multidirectional associative memory neural networks: New results
Authors: Aouiti Chaouki , Rezeg Mahjouba Ben
Published: April 2021

An Impulsive Multidirectional Associative Memory Neural Network (IMAMNN) with time-varying and leakage delays is proposed. Through the use of a continuation theorem of coincidence degree theory and differential inequality techniques we establish new conditions for the existence and exponential stability of anti-periodic solutions for the model considered in this work. Moreover, two examples and its numerical simulations are presented to show the validity and the effectiveness of the results.
Design and validation of a handheld capnography device for cardiopulmonary assessment based on the Arduino platform
Authors: Singh Om Prakash , El-Badawy Ismail M. , Malarvili M. B.
Published: April 2021

The design of a handheld capnography device is in great demand because of its effective and practical uses in all cardiac arrest resuscitations, according to the recommendation of the American Heart Association. Herein, a handheld capnography device that can be used in clinical settings and the home environment is reported. The proposed device was developed by using an infrared CO2 sensor, Arduino Mega2560, and a high-resolution display (2.8”). Furthermore, two rechargeable batteries (7.6[Formula: see text]V, 0.99[Formula: see text]A) and a secure digital card with a capacity of 16[Formula: see text]GB were incorporated to increase the portability and usability of the device. Algorithms were implemented to measure standard features, namely, inspired CO2 (ICO2), end-tidal CO2 (EtCO2), and respiratory rate (RR). The features of 15 healthy subjects were recorded by using the developed prototype and the standard capnography device (CapnostreamTM20 Model CS08798). Validation was performed with Bland–Altman plots. Findings revealed that mean differences [Formula: see text] standard deviations for the set limits of ICO2, EtCO2 and RR were 0.29 ± 1.30 millimeters of mercury (mmHg), 0.15 ± 1.77 mmHg and 0.40 ± 0.97 breaths per minute (bpm), respectively. Most of the differences among device measurements across all features fell within the 95% limits of agreement. Thus, the developed device may help manage respiratory distress conditions in and outside of a hospital setting.
A DFT Study of Graphitic Carbon Nitride as Drug Delivery Carrier for Flutamide (Anticancer Drug)
Authors: Rashid Ateeqa , Perveen Mehvish , Khera Rasheed Ahmad , Asif Khadija , Munir Iqra , Noreen Lubna , Nazir Sidra , Iqbal Javed
Published: April 2021

Graphitic carbon nitride ([Formula: see text]-C3N4) is the most efficient nanocarrier which is used in the delivery of many drugs. In this study, [Formula: see text]-C3N4 was used as a carrier for flutamide (anticancer drug) loading, and its effectiveness as a drug-delivery carrier for flutamide drug is explored. At ground and excited states, various calculations including noncovalent-interaction analysis (NCI) charge-decomposition analysis (CDA), electron localization function (ELF) analysis, Nonbonding-orbital analysis (NBO), dipole moment and bandgap of [Formula: see text]-C3N4, flutamide drug and [Formula: see text]-C3N4-flutamide complex ([Formula: see text]-C3N4-FLUT complex) were performed. The nitrogen atom of [Formula: see text]-C3N4 makes a weak van der Waals interaction with the oxygen and fluorine of flutamide anticancer drug, and these interactions were further illustrated by the NCI graph. These weak van der Waals interactions are helpful in drug-offloading from [Formula: see text]-C3N4 at its targeted-spot. The investigation of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) demonstrated that the charge was transferred from [Formula: see text]-C3N4 to flutamide drug. To further understand the phenomena of charge-transfer in the [Formula: see text]-C3N4-FLUT complex, CDA analysis was performed. The calculated [Formula: see text] of excited states of [Formula: see text]-C3N4-FLUT was blue-shifted by 25[Formula: see text]nm. The Photoinduced Electron Transfer (PET) process was fully described by the electron-hole theory, which demonstrated that the fluorescence-quenching may occur. Overall, it can be stated that the [Formula: see text]-C3N4 is a promising nanocarrier for use in drug delivery among other nanocarriers owing to their higher drug loading capability and low cytotoxicity.
Fine-Grained Visual Computing Based on Deep Learning
Authors: Lv Zhihan , Qiao Liang , Singh Amit Kumar , Wang Qingjun
Published: April 2021

With increasing amounts of information, the image information received by people also increases exponentially. To perform fine-grained categorization and recognition of images and visual calculations, this study combines the Visual Geometry Group Network 16 model of convolutional neural networks and the vision attention mechanism to build a multi-level fine-grained image feature categorization model. Finally, the TensorFlow platform is utilized to simulate the fine-grained image classification model based on the visual attention mechanism. The results show that in terms of accuracy and required training time, the fine-grained image categorization effect of the multi-level feature categorization model constructed by this study is optimal, with an accuracy rate of 85.3% and a minimum training time of 108 s. In the similarity effect analysis, it is found that the chi-square distance between Log Gabor features and the degree of image distortion show a strong positive correlation; in addition, the validity of this measure is verified. Therefore, through the research in this study, it is found that the constructed fine-grained image categorization model has higher accuracy in image recognition categorization, shorter training time, and significantly better performance in similar feature effects, which provides an experimental reference for the visual computing of fine-grained images in the future.
Privacy Maintenance in Self-Digitization
Authors: Bélanger France , Crossler Robert E. , Correia John
Published: April 2021

Individuals are increasingly using personal Internet of Things (IoT) devices that digitize their day-to-day lives. Those devices, however, often require substantial personal information to generate their intended benefits. For example, fitness technologies collect health, sleep, personal, and a vast array of other information ubiquitously, creating possible privacy issues for the users when fitness technology platform providers store or share their information, whether users know this or not. To explore the role of privacy perceptions in the context of continued use of fitness technologies, this study collected data from 212 fitness tracker users. We find empirical support for the importance of privacy perceptions in a user's intention to continue to use their fitness tracker. More specifically, consistent with privacy calculus research, privacy concern is negatively related to willingness to disclose information while perceived benefit is positively related to it. As an extension to calculus variables, users' expectations towards the data sharing practices of organizations also influences their willingness to disclose information. Importantly, willingness to disclose information has a direct effect on continued use intentions but also moderates the relationship between perceived benefit and users' intentions to continue using a fitness tracker. We discuss the implications of these findings for research and practice.
Emerging Roles of Posttranslational Modifications in Plant-Pathogenic Fungi and Bacteria
Authors: Liu Wende , Triplett Lindsay , Chen Xiao-Lin
Published: April 2021

Posttranslational modifications (PTMs) play crucial roles in regulating protein function and thereby control many cellular processes and biological phenotypes in both eukaryotes and prokaryotes. Several recent studies illustrate how plant fungal and bacterial pathogens use these PTMs to facilitate development, stress response, and host infection. In this review, we discuss PTMs that have key roles in the biological and infection processes of plant-pathogenic fungi and bacteria. The emerging roles of PTMs during pathogen–plant interactions are highlighted. We also summarize traditional tools and emerging proteomics approaches for PTM research. These discoveries open new avenues for investigating the fundamental infection mechanisms of plant pathogens and the discovery of novel strategies for plant disease control.
Fabrication of Cellulosic Nonwoven Material Coated with Polyvinyl Alcohol and Zinc Oxide/Mesoporous Silica Nanoparticles for Wound Dressing Purposes with Cephalexin Delivery
Authors: Nikdel Mozhgan , Rajabinejad Hossein , Yaghoubi Hashem , Mikaeiliagah Elmira , Cella Monica A. , Sadeghianmaryan Ali , Ahmadi Ali
Published: April 2021

Wound dressings with antibacterial properties have emerged as a promising material to accelerate wound healing treatments. The present study explores the fabrication of non-woven fabric treated with polyvinyl alcohol (PVA) hydrogel including zinc oxide nanoparticles (ZnO-NPs), and mesoporous silica nanoparticles (MS-NPs) to develop wound dressings that can help to heal the wound. In addition, the antibiotic cephalexin was loaded to the composite coating to aid in mitigating the establishment of opportunistic bacterial infection. Accordingly, the antibacterial efficiency was evaluated against two common pathogenic bacteria: Staphylococcus aureus (S. aureus) and Escherichia coli (E.coli). To characterize the coated nonwoven, SEM images, XRD pattern, FTIR spectra, swelling ratio, drug release, and MTT assays were employed to describe the potential wound dressing. It was observed that the fabricated nanocomposite possesses a considerable capacity to take up water through swelling, and incorporation of ZnO-NPs and MS-NPs into the hydrogel network increased the swelling ratio of the samples to about 8 times. Moreover, the fabricated composite appeared to have significant properties of degradation: the release of the loaded drugs from the nanocomposite displayed a burst release at the first hours and by 80% release of the cephalexin happened after 32 h. Lastly, the treated composite demonstrated excellent antibacterial properties against the selected bacteria. The results of this study indicate that the novel nanocomposite wound dressing may be a significant innovation for the medical treatment of infected skin wounds.
Ethanol-induced lymphatic endothelial cell permeability via MAP-kinase regulation
Authors: Herrera Matthew , Molina Patricia , Souza-Smith Flavia M.
Published: April 2021

Chronic alcohol alters the immune system enhancing the susceptibility to inflammation, bacterial, and viral infections in alcohol users. We have shown that alcohol causes increased permeability of mesenteric lymphatic vessels in alcohol-fed rats. The mechanisms of alcohol-induced lymphatic leakage are unknown. Endothelial cell monolayer permeability is controlled by junctional proteins complexes called tight junctions (TJ) and adherens junctions (AJ), and each can be regulated by MAPK activation. We hypothesize that ethanol induces lymphatic endothelial cell (LEC) permeability via disruption of LEC TJ through MAPK activation. An in vitro model of rat LECs was used. Ethanol-supplemented medium was added at concentrations of 0, 25, and 50 mM to confluent cells. Resistance-based barrier function, transwell permeability, cell viability, TJ, AJ, and MAPK protein activity, TJ and AJ gene expressions, and the role of p38 MAPK in barrier function regulation were measured. Ethanol increased the permeability of LECs compared to controls that was not associated with decreased cell viability. LECs treated with 50 mM ethanol showed an increase in phosphorylated levels of p38. No significant changes in TJ and AJ gene or protein expressions were observed after ethanol treatment. p38 inhibition prevented ethanol-induced increases in permeability. These findings suggest that p38 may play a role in the regulation of ethanol-induced LEC permeability, but altered permeability may not be associated with decreased TJ or AJ protein expression. Further investigation into junctional protein localization is needed to better understand the effects of ethanol on lymphatic endothelial cell-to-cell contacts and hyperpermeability.
Targeting myosin 1c inhibits murine hepatic fibrogenesis
Authors: Arif Ehtesham , Wang Cindy , Swiderska-Syn Marzena K. , Solanki Ashish K. , Rahman Bushra , Manka Paul P. , Coombes Jason D. , Canbay Ali , Papa Salvatore , Nihalani Deepak , Aspichueta Patricia , Lipschutz Joshua H. , Syn Wing-Kin
Published: April 2021

The incidences of liver fibrosis are growing at a rapid pace and have become one of the leading causes of end-stage liver disease. Although TGF-β1 is known to play a prominent role in transforming cells to produce excessive extracellular matrix that lead to hepatic fibrosis, the therapies targeting TGF-β1 have achieved very limited clinical impact. This study highlights motor protein myosin-1c-mediated mechanisms that serve as novel regulators of TGF-β1 signaling and fibrosis
An opioid receptor-independent mechanism underlies motility dysfunction and visceral hyperalgesia in opioid-induced bowel dysfunction
Authors: Lin You-Min , Tang Yanbo , Fu Yu , Hegde Shrilakshmi , Shi Daniel W. , Huang Li-Yen M. , Shi Xuan-Zheng
Published: April 2021

Our preclinical study shows that fecal retention is a pathogenic factor in opioid-induced bowel dysfunction, as prevention of fecal retention with liquid diet improved motility and attenuated visceral hyperalgesia in morphine-treated animals by blocking expression of cyclooxygenase-2 and nerve growth factor in the colon.
Differential expression of sputum and serum autoantibodies in patients with chronic obstructive pulmonary disease
Authors: Cass Steven P. , Dvorkin-Gheva Anna , Yang Yuqiong , McGrath Joshua J.C. , Thayaparan Danya , Xiao Jing , Wang Fengyan , Mukherjee Manali , Long Fei , Peng Tao , Nair Parameswaran , Liang Zhenyu , Stevenson Christopher S. , Li Quan-Zhen , Chen Rongchang , Stampfli Martin R.
Published: April 2021

Chronic obstructive pulmonary disease (COPD) is a complex and progressive respiratory disease. Autoimmune processes have been hypothesized to contribute to disease progression; however, the presence of autoantibodies in the serum has been variable. Given that COPD is a lung disease, we sought to investigate whether autoantibodies in sputum supernatant would better define pulmonary autoimmune processes. Matched sputum and serum samples were obtained from the Airways Disease Endotyping for Personalized Therapeutics (ADEPT) study and at the Guangzhou Institute of Respiratory Health (GIRH). Samples were collected from patients with varying severity of COPD, asymptomatic smokers, and healthy control subjects. IgG and IgM autoantibodies were detected in sputum and serum of all subjects in both cohorts using a broad-spectrum autoantigen array. No differences were observed in sputum autoantibodies between COPD and asymptomatic smokers in either cohort. In contrast, 16% of detectable sputum IgG autoantibodies were decreased in subjects with COPD compared to healthy controls in the ADEPT cohort. Compared to asymptomatic smokers, approximately 13% of detectable serum IgG and 40% of detectable serum IgM autoantibodies were differentially expressed in GIRH COPD subjects. Of the differentially expressed specificities, anti-nuclear autoantibodies were predominately decreased. A weak correlation between increased serum IgM anti-tissue autoantibodies and a measure of airspace enlargement was observed. The differential expression of specificities varied between the cohorts. In closing, using a comprehensive autoantibody array, we demonstrate that autoantibodies are present in subjects with COPD, asymptomatic smokers, and healthy controls. Cohorts displayed high levels of heterogeneity, precluding the utilization of autoantibodies for diagnostic purposes.
Similar masking effects of natural backgrounds on detection performances in humans, macaques, and macaque-V1 population responses
Authors: Bai Yoon , Chen Spencer , Chen Yuzhi , Geisler Wilson S. , Seidemann Eyal
Published: April 2021

We measured macaque detection performance in natural images and compared their performance to the detection sensitivity of neurophysiological responses recorded in the primary visual cortex (V1), and to the performance of human subjects. We found that 1) human and macaque behavioral performances are in quantitative agreement and 2) are consistent with near‐optimal decoding of V1 population responses.
Comparative Studies on the Hepatoprotective Effect of White and Coloured Rice Bran Oil against Acetaminophen‐Induced Oxidative Stress in Mice through Antioxidant‐ and Xenobiotic‐Metabolizing Systems
Authors: Phannasorn Warunyoo , Chariyakornkul Arpamas , Sookwong Phumon , Wongpoomchai Rawiwan
Published: April 2021

Rice bran oil (RBO) comprises various nutrients and phytochemicals which exhibit several health benefits. There are no studies regarding the functional effects of different colours of RBO. This study was aimed to compare the constituents and antioxidant activities of white rice bran oil (WRBO) and coloured rice bran oil (CRBO). Each RBO showed similar free fatty acid profiles. However, greater amounts of vitamin E, phytosterols, carotenoids, and chlorophylls were found in CRBO, which had lower γ‐oryzanol content than WRBO. Oxidative stress was induced in male mice by an overdose of acetaminophen (APAP) at 300 mg/kg body weight. The mice were then fed with RBO at the equivalent dose to 100 mg/kg body weight of γ‐oryzanol three hours later and sacrificed six hours after APAP treatment. The administration of 100 mg γ‐oryzanol equivalent in CRBO ameliorated APAP‐induced hepatotoxicity in mice more strongly than 100 mg γ‐oryzanol equivalent in WRBO, as evidenced by the significant reduction of serum ALT, hepatocellular necrosis, and hepatic lipid peroxidation. CRBO could improve xenobiotic‐metabolizing and antioxidant enzyme activities, including glutathione S‐transferase, superoxide dismutase, glutathione peroxidase, and glutathione reductase, and also increase mRNA expression of various antioxidant‐responsive genes. Vitamin E, phytosterols, carotenoids, and chlorophyll might be the protective compounds in CRBO that alleviate APAP‐induced hepatotoxicity through the interruption of APAP metabolism and the activation of antioxidant systems at both transcriptional and enzymatic levels. These findings might provide a protective role of CRBO on oxidative stress associated with several degenerative diseases.
Diagnosis of Alzheimer’s Disease Severity with fMRI Images Using Robust Multitask Feature Extraction Method and Convolutional Neural Network (CNN)
Authors: Amini Morteza , Pedram MirMohsen , Moradi AliReza , Ouchani Mahshad
Published: April 2021

The automatic diagnosis of Alzheimer’s disease plays an important role in human health, especially in its early stage. Because it is a neurodegenerative condition, Alzheimer’s disease seems to have a long incubation period. Therefore, it is essential to analyze Alzheimer’s symptoms at different stages. In this paper, the classification is done with several methods of machine learning consisting of

K

-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), linear discrimination analysis (LDA), and random forest (RF). Moreover, novel convolutional neural network (CNN) architecture is presented to diagnose Alzheimer’s severity. The relationship between Alzheimer’s patients’ functional magnetic resonance imaging (fMRI) images and their scores on the MMSE is investigated to achieve the aim. The feature extraction is performed based on the robust multitask feature learning algorithm. The severity is also calculated based on the Mini-Mental State Examination score, including low, mild, moderate, and severe categories. Results show that the accuracy of the KNN, SVM, DT, LDA, RF, and presented CNN method is 77.5%, 85.8%, 91.7%, 79.5%, 85.1%, and 96.7%, respectively. Moreover, for the presented CNN architecture, the sensitivity of low, mild, moderate, and severe status of Alzheimer patients is 98.1%, 95.2%,89.0%, and 87.5%, respectively. Based on the findings, the presented CNN architecture classifier outperforms other methods and can diagnose the severity and stages of Alzheimer’s disease with maximum accuracy.
Real-World Survival in Patients with Metastatic Melanoma after Discontinuation of Anti-PD-1 Immunotherapy for Objective Response or Adverse Effects: A Retrospective Study
Authors: Valentin Julie , Ferté Thomas , Dorizy-Vuong Valérie , Dousset Léa , Prey Sorilla , Dutriaux Caroline , Pham-Ledard Anne , Beylot-Barry Marie , Gérard Emilie
Published: April 2021

Objective. Anti-PD-1 has dramatically improved the survival of patients with advanced melanoma. However, there is a lack of data on maintenance of the response after treatment discontinuation. We aimed to evaluate the progression-free survival (PFS) of patients with metastatic melanoma after anti-PD-1 interruption for objective response (OR) or limiting toxicity during clinical trials. Methods. All patients with advanced melanoma who stopped single-agent anti-PD-1 antibodies for objective response or toxicity were included between April 2014 and January 2019 in our institution (data cut-off, September 10th, 2019). Clinical and biological factors associated with relapse were studied. Results. The median follow-up after introduction of treatment was 36.5 months [4.6–62.4], and the median follow-up after discontinuation of treatment was 15.7 months (2.5–45.1). Out of 65 patients, 28 patients stopped immunotherapy for limiting adverse effects (AEs) (43.1%), 25 for complete response (CR) (38.4%), and 12 for partial response (PR) or long-term stable disease (SD) (18.5%). Twelve patients relapsed (18.5%) after a median time of 9 months [1.9–40.9 months]. Seven relapsed after discontinuation for AEs, 3 after discontinuation for CR, and 2 after discontinuation for PR/SD. The median PFS after therapy discontinuation was not reached. No statistical association was found between recurrence and age, sex, increased LDH, BRAF status, presence of brain metastases, previous treatments, radiotherapy, or time on anti-PD-1 treatment. Conclusion. This cohort shows a global recurrence rate of 18.5% and confirms a long-lasting response after anti-PD-1 cessation regardless of the cause of discontinuation.
Combination Forecast of Economic Chaos Based on Improved Genetic Algorithm
Authors: Yang Yankun
Published: April 2021

The deterministic economic system will also produce chaotic dynamic behaviour, so economic chaos is getting more and more attention, and the research of economic chaos forecasting methods has become an important topic at present. The traditional economic chaos forecasting models are mostly based on large samples, but in actual production activities, there are a large number of small‐sample economic chaos problems, and there is still no effective solution. This paper proposes a combined forecasting model based on the traditional economic chaos forecasting method. First of all, through the decision tree classification, priority selection of features, rough prediction is achieved. Secondly, we use BP neural network to make secondary prediction. Because the initial weight is randomly selected, it is easy to fall into the defect of local minimum. This paper optimizes the BP neural network. Finally, the decision tree model and the BP neural network model optimized by the improved genetic algorithm are combined, and the combined model is optimized by the improved GA. This method can take advantage of many prediction models and combine the prediction information of multiple different prediction models to effectively improve the fitting ability of the model and improve the prediction accuracy.
Reconstructing 3D Model from Single‐View Sketch with Deep Neural Network
Authors: Wang Fei , Yang Yu , Zhao Baoquan , Jiang Dazhi , Chen Siwei , Sheng Jianqiang
Published: April 2021

In this paper, we introduce a novel 3D shape reconstruction method from a single‐view sketch image based on a deep neural network. The proposed pipeline is mainly composed of three modules. The first module is sketch component segmentation based on multimodal DNN fusion and is used to segment a given sketch into a series of basic units and build a transformation template by the knots between them. The second module is a nonlinear transformation network for multifarious sketch generation with the obtained transformation template. It creates the transformation representation of a sketch by extracting the shape features of an input sketch and transformation template samples. The third module is deep 3D shape reconstruction using multifarious sketches, which takes the obtained sketches as input to reconstruct 3D shapes with a generative model. It fuses and optimizes features of multiple views and thus is more likely to generate high‐quality 3D shapes. To evaluate the effectiveness of the proposed method, we conduct extensive experiments on a public 3D reconstruction dataset. The results demonstrate that our model can achieve better reconstruction performance than peer methods. Specifically, compared to the state‐of‐the‐art method, the proposed model achieves a performance gain in terms of the five evaluation metrics by an average of 25.5% on the man‐made model dataset and 23.4% on the character object dataset using synthetic sketches and by an average of 31.8% and 29.5% on the two datasets, respectively, using human drawing sketches.
[Retracted] Music Recommendation Algorithm Based on Multidimensional Time‐Series Model Analysis
Authors: Shi Juanjuan
Published: April 2021

This paper proposes a personalized music recommendation method based on multidimensional time‐series analysis, which can improve the effect of music recommendation by using user’s midterm behavior reasonably. This method uses the theme model to express each song as the probability of belonging to several hidden themes, then models the user’s behavior as multidimensional time series, and analyzes the series so as to better predict the use of music users’ behavior preference and give reasonable recommendations. Then, a music recommendation method is proposed, which integrates the long‐term, medium‐term, and real‐time behaviors of users and considers the dynamic adjustment of the influence weight of the three behaviors so as to further improve the effect of music recommendation by adopting the advanced long short time memory (LSTM) technology. Through the implementation of the prototype system, the feasibility of the proposed method is preliminarily verified.
Measuring Empathy among Dental Students and Interns: A Cross-Sectional Study from Dammam, Saudi Arabia
Authors: Nazir Muhammad , Alhareky Muhanad , Alqahtani Abdulrahman , Alsulaimi Leenah , Alotaibi Reema , Yousef Najwa , Abushal Fatimah , Alhumaid Jehan
Published: April 2021

Objective. To evaluate empathy and its related factors among undergraduate dental students and interns enrolled in a public dental college in Dammam, Saudi Arabia. Materials and Methods. This cross-sectional study used the Jefferson Scale of Empathy-Health Profession Students (JSE-HPS) version to determine empathy in 362 dental students and interns in Dammam, Saudi Arabia. The JSE-HPS is a 20-item 7-point Likert scale questionnaire, and its score ranges from 20 to 140 with high values indicating increased empathy. Influences of age, gender, class year, previous year’s grade point average (GPA), educational attainment of parents, and monthly family income on empathy were evaluated. Results. Of 501 enrolled students and interns, 362 returned completed questionnaires, and the response rate of the study was 72%. The sample’s empathy score (JSPE-HPS scale) ranged from 70 to 129 with a mean of 96.75 (±13.76). Most participants believed that empathy is important for effective communication with patients (96.1%) and can improve the provider-patient relationship (95.6%). Females demonstrated a significantly higher mean empathy score (99.98 ± 14.01) than males (92.72 ± 12.35) (

P
<
0.001

). Similarly, the participants with high GPA (98.06 ± 13.69) had significantly greater mean empathy scores than those with low GPA (94.84 ± 13.68) (

P
=
0.029

). The mean empathy score increased significantly from junior students (3rd and 4th year students) to senior students (5th and 6th year students) and interns (

P
=
0.008

). Multiple linear regression analysis showed that class year (B = 2.03,

P
=
0.006

) and GPA (B = 8.67,

P
=
0.003

) were significant factors associated with empathy. Conclusions. Empathy is important for effective patient communication and improved provider-patient relationship. Female gender, high GPA, and class years were associated with empathy. Empathy should be integrated into dental curricula for effective student learning and positive patient care outcomes.
Game-Based Multiobjective Optimization of Suspension System for In-Wheel Motor Drive Electric Vehicle
Authors: Feng Tang , Shu Lin
Published: April 2021

Since the driving motor is embedded in the wheel, the unsprung mass and the wheel rotational inertia of the in-wheel motor drive electric vehicle both increase, which not only affect the vehicle smoothness but also worsen the motor’s working condition due to its own vertical vibration. The evaluation index of in-wheel motor’s vertical vibration is introduced on the basis of vehicle smoothness analysis. The parameters’ optimization of vibration absorber and suspension are carried out, respectively, and the optimization results show the contradictory relationship between smoothness objective and the motor’s vertical vibration acceleration objective. Regarding the contradictory indices of the smoothness and the motor’s vertical acceleration as the objective function, a multiobjective optimization scheme is designed. Then, the orthogonal experimentation and fuzzy clustering method are applied in the multiobjective optimized design based on the game decision analysis, and the Nash equilibrium and cooperative competition game theory are used to optimize the parameters of suspension and vibration absorber. The optimized results verify the game relation between the optimization variables, the game optimization obtains better optimized results than traditional linear weight sum method, and the in-wheel motor functional stability and the vehicle smoothness can be both achieved. Compared with the traditional complex iterative process and the manmade preassurance weight allocation, the game optimization has the advantages of less iterations, faster convergence, and less influence by human experience.
Effects of Acupuncture on Oxidative Stress Amelioration via Nrf2/ARE-Related Pathways in Alzheimer and Parkinson Diseases
Authors: Huang Teng-I , Hsieh Ching-Liang
Published: April 2021

Oxidative stress is responsible for the pathogeneses of various diseases. Mitochondrial dysfunction, impaired DNA repair, and cellular damage followed by oxidative stress contribute to neurodegenerative diseases, such as Alzheimer disease (AD) and Parkinson disease (PD). Acupuncture is a traditional therapy that has been practiced for >3000 years in Asia. Many studies have demonstrated that acupuncture has notable antioxidative, anti-inflammatory, and antiapoptotic effects. However, the exact mechanism remains unclear. Nuclear factor erythroid 2-related factor (Nrf2) is crucial in regulating the redox equilibrium. Activated Nfr2 translocates into the nucleus, binds to the antioxidant response element (ARE), and initiates antioxidative enzyme transcription. In this review, we demonstrated the effects of acupuncture on oxidative stress amelioration in AD and PD animal models through Nrf2/ARE pathway activation and Nrf2/ARE-related pathway regulation. Thus, acupuncture could be a therapeutic option for AD and PD.
LncRNA PCNAP1 Promotes Hepatoma Cell Proliferation through Targeting miR-340-5p and is Associated with Patient Survival
Authors: He Miao , Hu Lingjing , Bai Ping , Guo Tingting , Liu Nan , Feng Fei , Zhang Jin
Published: April 2021

Hepatocellular carcinoma (HCC) is one of the most common malignancies and causes poor outcome. Dysregulation of long noncoding RNA (lncRNA) is involved in HCC. Upregulation of the lncRNA PCNAP1 has been reported to promote HBV-infectious HCC growth, but its clinical significance and underlying mechanisms in HCC development remain unclear. Here, we report that PCNAP1 expression is increased in both HBV-infectious and noninfectious HCC tissues compared with matched normal tissues, and its upregulation correlates with poor survival rates of HCC patients. Furthermore, we found that PCNAP1 promotes HCC cell proliferation through acting as a competitive endogenous RNA (ceRNA) to sponge miR-340-5p, which has been reported to directly inhibit ATF7 expression in HCC cells. Moreover, the PCNAP1/miR-340-5p/ATF7 signaling associates with the poor survival rates of HCC patients. Collectively, our findings suggest that the PCNAP1/miR-340-5p/ATF7 signaling may be a potential biomarker for the prognosis of HCC patients and a potential therapeutic target for HCC.
Filter Realization of the Time‐Domain Average Denoising Method for a Mechanical Signal
Authors: Feng Wuwei , Wang Cuizhu , Chen Xin , Shi Yuzhou , Jiang Meng , Wang Di
Published: April 2021

Time‐domain averaging (TDA) is an effective signal processing technique in fault diagnosis that can extract the periodic components of interest from signals mixed with noise interference while suppressing other irrelevant periodic signals. However, there are two obvious shortcomings to TDA: first, the acquisition of keyphasor signals is often restricted by the application environment and conditions. Even if the signal is obtained by TDA, owing to the existence of periodic truncation errors, satisfactory results cannot be obtained. Second, due to the velocity fluctuation, the actual mechanical signal is easy to produce a large error in TDA stacking. To solve the above challenges, first, based on the disadvantage of using traditional resampling to solve the TDA synchronization problem, this paper proposes a new method of subsection resampling, which improves the analysis effect of the traditional TDA. Second, to further expand the range of the practical applications, according to the amplitude‐frequency map of TDA, a method for realizing TDA function by using the FIR multiband filter is proposed. This approach effectively avoids the requirement of traditional methods to collect the keyphasor signals and broadens the application in practical engineering. Finally, the improved TDA method is compared with the filter implementation technology, and their respective application conditions are given.
Acupuncture as Adjuvant Therapy for Treating Stable Angina Pectoris with Moderate Coronary Artery Lesions and the Mechanism of Heart-Brain Interactions: A Randomized Controlled Trial Protocol
Authors: Zhao Long , Song Qingqiao , Wu Huaqin , Wang Yanli , Wu Jiani , Fang Jiliang , Li Zhigang
Published: April 2021

Background. Stable angina pectoris with moderate coronary artery lesions is a syndrome caused by coronary artery stenosis, which endangers the quality of life. Previous acupuncture studies have shown effectiveness as a complementary therapy for ischaemic heart disease. However, more clinical evidence is needed for verification, and the mechanism should be investigated, especially involving the functional interactions between the heart and brain. Therefore, we designed a clinical trial to provide more evidence for acupuncture efficacy and its mechanism in ischaemic heart disease. Methods/Design. A total of 80 participants will be randomized to the electroacupuncture group and sham-electroacupuncture group at a ratio of 1 : 1. This trial will be conducted over 8 weeks, including a 2-week screening, 2-week treatment, and 4-week follow-up. All participants will continue to receive similar basic disease treatment procedures before the trial (including lifestyle changes and treatment for standard supportive medications, hypertension, and hyperlipidaemia, such as aspirin, metoprolol succinate, atorvastatin, and sodium fosinopril). Additionally, 12 sessions of acupuncture will be administered during the treatment period. The main outcome is Seattle Angina Questionnaire scores. The other observation indices are the heart rate variability and self-rating anxiety scale and self-rating depression scale scores. To explore mechanisms based on the hypothesis of a correlation between heart and brain function, fMRI scans will be used to detect functional brain changes in 15 patients from each group at baseline and at the end of treatment. Finally, the efficacy of acupuncture will be evaluated, and the HRV and imaging data will be correlated with clinical data to investigate the possible relationships between the brain and heart activity. Discussion. This trial will provide evidence for acupuncture as adjuvant therapy for the treatment of stable angina pectoris with moderate coronary artery lesions. The results will shed light on potential mechanisms of heart-brain interactions underlying acupuncture as an adjuvant therapy for treating ischaemic heart disease. Trials registration: Clinical Trial, https://clinicaltrials.gov/ct2/show/ChiCTR1900024937. Registered 4 August 2019, http://www.chictr.org.cn/.