bluuebunny/crossref_metadata_2025 huggingface dataset:
Subaxial cervical articular process subluxation and dislocation: Cervical locked facet injuries in dogs
Authors: Woelfel Christian W. , Bray Katherine Y. , Early Peter J. , Mariani Christopher L. , Olby Natasha J.
Published: November 2021

Objective

To describe neurologic signs, diagnostic imaging findings, potential treatments, and outcomes in dogs with subaxial cervical articular process subluxation and dislocation, or a “locked facet.”

Study design

Retrospective case series.

Animals

Ten client‐owned dogs.

Methods

Dogs with a diagnosis of cervical locked facets were identified through medical records and imaging reports searches. Data on presenting signs, diagnostic findings, treatment, and outcome were recorded.

Results

All cases were small or toy‐breed dogs with preceding trauma. Four dogs were tetraplegic with intact pain perception, five were nonambulatory tetraparetic, and one was ambulatory tetraparetic, with half of the tetraparetic dogs having worse motor function in the thoracic limbs. The only sites affected were C5/6 (n = 6) and C6/7 (n = 4). All dogs had unilateral dorsal displacement of the cranial articular process of the caudal vertebra relative to the caudal articular process of the cranial vertebra at the luxation site. Five dogs were treated surgically, three by external coaptation, one by restriction, and one was euthanized the day after diagnosis. All dogs with outcome data (n = 8) became ambulatory. Nonambulatory dogs returned to ambulation in a median of 4 weeks (IQR 1‐12; range 1‐28).

Conclusion

In these dogs, locked facet injuries affected the caudal cervical vertebrae in small breeds and could be identified on imaging through the presence of dorsal displacement of a cranial articular process. Our small cohort had a functional recovery regardless of treatment.

Clinical signiicance

Locked facet injuries should be a differential for small or toy‐breed dogs with a cervical myelopathy secondary to trauma.
Whole-animal multiplexed single-cell RNA-seq reveals transcriptional shifts acrossClytiamedusa cell types
Authors: Chari Tara , Weissbourd Brandon , Gehring Jase , Ferraioli Anna , Leclère Lucas , Herl Makenna , Gao Fan , Chevalier Sandra , Copley Richard R. , Houliston Evelyn , Anderson David J. , Pachter Lior
Published: November 2021

Whole-organism perturbations reveal single-cell responses across theClytiamedusa.
Gender-related data missingness, imbalance and bias in global health surveys
Authors: Weber Ann M , Gupta Ribhav , Abdalla Safa , Cislaghi Beniamino , Meausoone Valerie , Darmstadt Gary L
Published: November 2021

Global surveys have built-in gender-related biases associated with data missingness across the gender dimensions of people’s lives, imbalanced or incomplete representation of population groups, and biased ways in which gender information is elicited and used. While increasing focus is being placed on the integration of sex-disaggregated statistics into national programmes and on understanding effects of gender-based disparities on the health of all people, the data necessary for elucidating underlying causes of gender disparities and designing effective intervention programmes continue to be lacking. Approaches exist, however, that can reasonably address some shortcomings, such as separating questions of gender identification from biological sex. Qualitative research can elucidate ways to rephrase questions and translate gendered terms to avoid perpetuating historical gender biases and prompting biased responses. Non-health disciplines may offer lessons in collecting gender-related data. Ultimately, multidisciplinary global collaborations are needed to advance this evolving field and to set standards for how we measure gender in all its forms.
Identifying research priorities in newborn medicine: a Delphi study of parents’ views
Authors: Eeles Abbey L , Burnett Alice C , Cheong Jeanie LY , Aldis Alex , Pallot Louise , Polonidis Tien , Rust Krista , Hunt Rod W , Delany Clare , Spittle Alicia J
Published: November 2021

Objective

Neonatal conditions can have lifelong implications for the health and well-being of children and families. Traditionally, parents and patients have not been included in shaping the agenda for research and yet they are profoundly affected by the neonatal experience and its consequences. This study aimed to identify consensus research priorities among parents/patients of newborn medicine in Australia and New Zealand.

Design

Parents/patients with experience of neonatal care in Australia and New Zealand completed an online Delphi study to identify research priorities across four epochs (neonatal admission, early childhood, childhood/adolescence and adulthood). Parents/patients first generated key challenges in each of these epochs. Through inductive thematic analysis, recurring topics were identified and research questions generated. Parents/patients rated these questions in terms of priorities and a list of questions consistently rated as high priority was identified.

Participants

393 individuals participated, 388 parents whose children had received neonatal care and 5 adults who had received neonatal care themselves.

Results

Many research questions were identified as high-priority across the lifespan. These included how to best support parental mental health, relationships between parents and neonatal clinical staff (including involvement in care and communication), bonding and the parent–child relationship, improving neonatal medical care and addressing long-term impacts on child health and neurodevelopment.

Conclusions

Parents with experience of newborn medicine have strong, clear and recurring research priorities spanning neonatal care practices, psychological and other impacts on families, and impacts on child development. These findings should guide neonatal research efforts. In addition to generating new knowledge, improved translation of existing evidence to parents is also needed.
Predictive model and risk analysis for diabetic retinopathy using machine learning: a retrospective cohort study in China
Authors: Li Wanyue , Song Yanan , Chen Kang , Ying Jun , Zheng Zhong , Qiao Shen , Yang Ming , Zhang Maonian , Zhang Ying
Published: November 2021

Objective

Aiming to investigate diabetic retinopathy (DR) risk factors and predictive models by machine learning using a large sample dataset.

Design

Retrospective study based on a large sample and a high dimensional database.

Setting

A Chinese central tertiary hospital in Beijing.

Participants

Information on 32 452 inpatients with type-2 diabetes mellitus (T2DM) were retrieved from the electronic medical record system from 1 January 2013 to 31 December 2017.

Methods

Sixty variables (including demography information, physical and laboratory measurements, system diseases and insulin treatments) were retained for baseline analysis. The optimal 17 variables were selected by recursive feature elimination. The prediction model was built based on XGBoost algorithm, and it was compared with three other popular machine learning techniques: logistic regression, random forest and support vector machine. In order to explain the results of XGBoost model more visually, the Shapley Additive exPlanation (SHAP) method was used.

Results

DR occurred in 2038 (6.28%) T2DM patients. The XGBoost model was identified as the best prediction model with the highest AUC (area under the curve value, 0.90) and showed that an HbA1c value greater than 8%, nephropathy, a serum creatinine value greater than 100 µmol/L, insulin treatment and diabetic lower extremity arterial disease were associated with an increased risk of DR. A patient’s age over 65 was associated with a decreased risk of DR.

Conclusions

With better comprehensive performance, XGBoost model had high reliability to assess risk indicators of DR. The most critical risk factors of DR and the cut-off of risk factors can be found by SHAP method to render the output of the XGBoost model clinically interpretable.
Diabetes, obesity, hypertension and risk of severe COVID-19: a protocol for systematic review and meta-analysis
Authors: Li Chaoyang , Islam Nazrul , Gutierrez Juan Pablo , Lacey Ben , Moolenaar Ronald L , Richter Patricia
Published: November 2021

Introduction

Previous evidence from several countries, including China, Italy, Mexico, UK and the USA, indicates that among patients with confirmed COVID-19 who were hospitalised, diabetes, obesity and hypertension might be important risk factors for severe clinical outcomes. Several preliminary systematic reviews and meta-analyses have been conducted on one or more of these non-communicable diseases, but the findings have not been definitive, and recent evidence has become available from many more populations. Thus, we aim to conduct a systematic review and meta-analysis of observational studies to assess the relationship of diabetes, obesity and hypertension with severe clinical outcomes in patients with COVID-19.

Method and analysis

We will search 16 major databases (MEDLINE, Embase, Global Health, CAB Abstracts, PsycINFO, CINAHL, Academic Research Complete, Africa Wide Information, Scopus, PubMed Central, ProQuest Central, WHO Virtual Health Library, Homeland Security COVID-19 collection, SciFinder, Clinical Trials and Cochrane Library) for articles published between December 2019 and December 2020. We will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2016 guidelines for the design and reporting the results. We will include observational studies that assess the associations of pre-existing diabetes, obesity and hypertension in patients with COVID-19 with risk of severe clinical outcomes such as intensive care unit admission, receiving mechanical ventilation or death. Stata V.16.1 and R-Studio V.1.4.1103 statistical software will be used for statistical analysis. Meta-analysis will be used to estimate the pooled risks and to assess potential heterogeneities in risks.

Ethics and dissemination

The study was reviewed for human subjects concerns by the US CDC Center for Global Health and determined to not represent human subjects research because it uses data from published studies. We plan to publish results in a peer-reviewed journal and present at national and international conferences.

PROSPERO registration number

CRD42021204371.
Identification of the most vulnerable populations in the psychosocial sphere: a cross-sectional study conducted in Catalonia during the strict lockdown imposed against the COVID-19 pandemic
Authors: Farrés Judith , Ruiz Jose Luis , Mas Jose Manuel , Arias Lilibeth , Sarrias Maria-Rosa , Armengol Carolina , Cardona Pere-Joan , Munoz-Moreno Jose A , Vilaplana Miriam , Arranz Belen , Usall Judith , Serrano-Blanco Antoni , Vilaplana Cristina
Published: November 2021

Design and objectives

A cross-sectional study to evaluate the impact of COVID-19 on the psychosocial sphere in both the general population and healthcare workers (HCWs).

Methods

The study was conducted in Catalonia (Spain) during the first wave of the COVID-19 pandemic when strict lockdown was in force. The study population included all people aged over 16 years who consented to participate in the study and completed the survey, in this case a 74-question questionnaire shared via social media using snowball sampling. A total of 56 656 completed survey questionnaires were obtained between 3 and 19 April 2020.

The primary and secondary outcome measures included descriptive statistics for the non-psychological questions and the psychological impact of the pandemic, such as depression, anxiety, stress and post-traumatic stress disorder question scores.

Results

A n early and markedly negative impact on family finances, fear of working with COVID-19 patients and ethical issues related to COVID-19 care among HCWs was observed. A total of seven target groups at higher risk of impaired mental health and which may therefore benefit from an intervention were identified, namely women, subjects aged less than 42 years, people with a care burden, socioeconomically deprived groups, people with unskilled or unqualified jobs, patients with COVID-19 and HCWs working with patients with COVID-19.

Conclusions

Active implementation of specific strategies to increase resilience and to prepare an adequate organisational response should be encouraged for the seven groups identified as high risk and susceptible to benefit from an intervention.

Trial registration number

NCT04378452.
Sequential multiple assignment randomised trial of a brief contact intervention for suicide risk management among discharged psychiatric patients: an implementation study protocol
Authors: Liu Huiming , Chen Guanjie , Li Jinghua , Hao Chun , Zhang Bin , Bai Yuanhan , Song Liangchen , Chen Chang , Xie Haiyan , Liu Tiebang , Caine Eric D , Hou Fengsu
Published: November 2021

Introduction

The postdischarge suicide risk among psychiatric patients is significantly higher than it is among patients with other diseases and general population. The brief contact interventions (BCIs) are recommended to decrease suicide risk in areas with limited mental health service resources like China. This study aims to develop a postdischarge suicide intervention strategy based on BCIs and evaluate its implementability under the implementation outcome framework.

Methods and analysis

This study will invite psychiatric patients and family members, clinical and community mental health service providers as the community team to develop a postdischarge suicide intervention strategy. The study will recruit 312 patients with psychotic symptoms and 312 patients with major depressive disorder discharged from Shenzhen Kangning Hospital (SKH) in a Sequential Multiple Assignment Randomised Trial. Participants will be initially randomised into two intervention groups to receive BCIs monthly and weekly, and they will be rerandomised into three intervention groups to receive BCIs monthly, biweekly and weekly at 3 months after discharge according to the change of their suicide risk. Follow-ups are scheduled at 1, 3, 6 and 12 months after discharge. With the intention-to-treat approach, generalised estimating equation and survival analysis will be applied. This study will also collect qualitative and quantitative information on implementation and service outcomes from the community team.

Ethics/dissemination

This study has received ethical approval from the Ethics Committee Review Board of SKH. All participants will provide written informed consent prior to enrolment. The findings of the study will be disseminated through peer-reviewed scientific journals, conference presentations. A project report will be submitted to the National Natural Science Foundation of China as the concluding report of this funded project, and to the mental health authorities in the Shenzhen to refine and apply evidence-based and pragmatic interventions into health systems for postdischarge suicide prevention.

Trial registration number

NCT04907669.
Feasibility of completing Multidimensional Dyspnea Profile and Dyspnea-12 over the telephone in patients with oxygen-dependent disease
Authors: Bech Thea Wilhelmine , Eklund Moa , Spaak Elisabeth , Palm Andreas , Ekström Magnus
Published: November 2021

Background

Breathlessness is prevalent in severe disease and consists of different dimensions that can be measured using the Multidimensional Dyspnea Profile (MDP) and Dyspnea-12 (D-12). We aimed to evaluate the feasibility of MDP and D-12 over telephone interviews in oxygen-dependent patients, compared with other patient-reported outcomes (modified Medical Research Council (mMRC) and Chronic Obstructive Pulmonary Disease Assessment Test (CAT)) and with completion by hand.

Methods

Cross-sectional, telephone study of 50 patients with home oxygen therapy. Feasibility was assessed as completion time (self-reported by patients and measured), difficulty (self-reported) and help required to complete the instruments (staff). Completion time was compared with mMRC and CAT, and feasibility was compared with completion by hand in cardiopulmonary outpatients (n=182). Feasibility by age and gender was analysed using logistic regression.

Results

Of 136 patients approached, 50 (37%) participated (mean age: 72±10 years, 66% women). Completion times (in minutes) were relatively short for MDP (self-reported 6 (IQR 5–10), measured 8 (IQR 6–10)) and D-12 (self-reported 5 (IQR 3–8), measured 3 (IQR 3–4)), and slightly longer than mMRC (median 1 (IQR 1–1)) and CAT (median 3 (IQR 2–5)). Even though the majority of patients required no help, more assistance was required by older patients. Compared with patients reporting by hand, completion over the telephone required somewhat longer time and more assistance.

Conclusion

Many patients with severe oxygen-dependent disease were unable or unwilling to assess symptoms over the telephone. However, among those able to participate, MDP and D-12 are feasible to measure multiple dimensions of breathlessness over the telephone.
Footprints of a microbial toxin from the gut microbiome to mesencephalic mitochondria
Authors: Esteves A Raquel , Munoz-Pinto Mário F , Nunes-Costa Daniela , Candeias Emanuel , Silva Diana F , Magalhães João D , Pereira-Santos A Raquel , Ferreira I Luisa , Alarico Susana , Tiago Igor , Empadinhas Nuno , Cardoso Sandra Morais
Published: November 2021

Objective

Idiopathic Parkinson’s disease (PD) is characterised by alpha-synuclein (aSyn) aggregation and death of dopaminergic neurons in the midbrain. Recent evidence posits that PD may initiate in the gut by microbes or their toxins that promote chronic gut inflammation that will ultimately impact the brain. In this work, we sought to demonstrate that the effects of the microbial toxin β-N-methylamino-L-alanine (BMAA) in the gut may trigger some PD cases, which is especially worrying as this toxin is present in certain foods but not routinely monitored by public health authorities.

Design

To test the hypothesis, we treated wild-type mice, primary neuronal cultures, cell lines and isolated mitochondria with BMAA, and analysed its impact on gut microbiota composition, barrier permeability, inflammation and aSyn aggregation as well as in brain inflammation, dopaminergic neuronal loss and motor behaviour. To further examine the key role of mitochondria, we also determined the specific effects of BMAA on mitochondrial function and on inflammasome activation.

Results

BMAA induced extensive depletion of segmented filamentous bacteria (SFB) that regulate gut immunity, thus triggering gut dysbiosis, immune cell migration, increased intestinal inflammation, loss of barrier integrity and caudo-rostral progression of aSyn. Additionally, BMAA inducedin vitroandin vivomitochondrial dysfunction with cardiolipin exposure and consequent activation of neuronal innate immunity. These events primed neuroinflammation, dopaminergic neuronal loss and motor deficits.

Conclusion

Taken together, our results demonstrate that chronic exposure to dietary BMAA can trigger a chain of events that recapitulate the evolution of the PD pathology from the gut to the brain, which is consistent with ‘gut-first’ PD.
Building leadership capabilities in maternity
Authors: Ashmore Ayisha Adeeba , Kanga Kate , Kaur-Desai Tejinder , Thorman Kate , Archer Natasha
Published: November 2021

Background

Over recent years, there has been increasing recognition that effective leadership is critical to establishing positive organisational culture and improving patient outcomes. In maternity, there is a unique interplay between different specialties and disciplines in providing high-quality services.

Methods

Review of literature pertaining to leadership and maternity.

Results

Good leadership is the key determinant in ensuring that our multi-professional teams function effectively. The relational aspects of teamworking, linked to safer delivery of services, have been explored in great detail in maternity services. However, there has been less focus on the application of leadership theory in this environment and the impact of interventions used in developing leadership skills within maternity teams.

Conclusions

In this paper, we discuss how leadership theory can be used to understand high profile maternity service failures and how effective team culture, clinical team building and individual leadership skill-development are strong contributors to this thinking. Specific examples are used to describe ongoing work in our drive for improvement and to highlight the current lack of evidence in this area.
Prevention and partial reversion of the lupus phenotype in ABIN1[D485N] mice by an IRAK4 inhibitor
Authors: Petrova Tsvetana , Nanda Sambit K , Scudamore Cheryl , Wright Stephen W , Rao Vikram R , Cohen Philip
Published: November 2021

Objective

We have reported previously that the IRAK4 inhibitor PF06426779 given to ubiquitin-binding-defective ABIN1[D485N] mice at 6 weeks of age prevents the major facets of lupus that develop 10 weeks later. The present study was undertaken to investigate whether PF06426779 could reverse the lupus phenotype when administered to 13-week-old ABIN1[D485N] mice that had already developed symptoms of lupus.

Methods

Splenomegaly, the number of splenic neutrophils, TFHand Germinal Centre B (GCB) cells, serum levels of immunoglobulins, the extent of kidney, liver and lung pathology, and glomerular IgA and IgM were measured after feeding 13-week-old ABIN1[D485N] and wild-type mice for another 10 weeks with R&M3 diet with and without PF06426779 (4 g/kg).

Results

Following drug treatment, spleen size and weight, splenic neutrophil numbers, and serum IgA and glomerular IgA levels of ABIN1[D485N] mice returned to those seen in wild-type mice. The rise in splenic TFHand GCB numbers, the increase in kidney and liver pathology, and the concentrations of serum IgG1, IgG2A and IgE between 13 and 23 weeks were suppressed. There was no reduction in the level of anti-self double-stranded DNA, anti-self nuclear antigens or IgM during the drug treatment.

Conclusions

The results demonstrate the therapeutic potential of IRAK4 inhibitors for the treatment of lupus and raise the possibility of monitoring efficacy by measuring decreases in the serum levels of IgA. Our results support the view that there may be a closer connection between lupus and IgA nephropathy than realised previously.
Benefit–harm analysis of azithromycin for the prevention of acute exacerbations of chronic obstructive pulmonary disease
Authors: Ahmadian Safa , Sin Don D , Lynd Larry , Harrison Mark , Sadatsafavi Mohsen
Published: November 2021

Background

Low-dose oral azithromycin therapy is recommended as a preventive treatment for acute exacerbations of COPD. However, the overall benefit–harm balance of this treatment has not been well studied.

Methods

A probabilistic Markov model of COPD was created to simulate the course of COPD over 20 years. The model was populated with evidence from the literature and dedicated data analysis. The benefit of azithromycin was modelled as a reduction in exacerbation rates. Adverse events, including cardiovascular events, hearing loss, gastrointestinal symptoms and antimicrobial resistance (leading to a gradual decline in the effectiveness of azithromycin), were considered. All outcomes were assigned a health-related utility weight to estimate the overall net change in the quality-adjusted life year (QALY) associated with the use of azithromycin.

Results

In patients with a positive exacerbation history, azithromycin resulted in a net QALY gain of 17.9 per 100 patients (99.8% probability of expected QALY gain) over 20 years. The net benefit increased to 21.8 QALYs per 100 patients (99.9% probability of expected QALY gain) among the ‘frequent exacerbator’ subgroup. Azithromycin was not net beneficial among those without any moderate/severe exacerbations in the previous year. Findings were robust against series of sensitivity, scenario and threshold analyses.

Conclusions

Long-term therapy with azithromycin confers a net benefit to ex-smoker patients with COPD with a recent history of exacerbations and an even larger benefit to those who are frequent exacerbators.
Commodity Price Recognition and Simulation of Image Recognition Technology Based on the Nonlinear Dimensionality Reduction Method
Authors: Liu Yongbin , Wang Jingjie , Bai Wei
Published: November 2021

Dimensionality reduction of images with high-dimensional nonlinear structure is the key to improving the recognition rate. Although some traditional algorithms have achieved some results in the process of dimensionality reduction, they also expose their respective defects. In order to achieve the ideal effect of high-dimensional nonlinear image recognition, based on the analysis of the traditional dimensionality reduction algorithm and refining its advantages, an image recognition technology based on the nonlinear dimensionality reduction method is proposed. As an effective nonlinear feature extraction method, the nonlinear dimensionality reduction method can find the nonlinear structure of datasets and maintain the intrinsic structure of data. Applying the nonlinear dimensionality reduction method to image recognition is to divide the input image into blocks, take it as a dataset in high-dimensional space, reduce the dimension of its structure, and obtain the low-dimensional expression vector of its eigenstructure so that the problem of image recognition can be carried out in a lower dimension. Thus, the computational complexity can be reduced, the recognition accuracy can be improved, and it is convenient for further processing such as image recognition and search. The defects of traditional algorithms are solved, and the commodity price recognition and simulation experiments are carried out, which verifies the feasibility of image recognition technology based on the nonlinear dimensionality reduction method in commodity price recognition.
Integrated Lateral and Longitudinal Control with Optimization-Based Allocation Strategy for Autonomous Electric Vehicles
Authors: Kovacs Adorjan , Vajk Istvan
Published: November 2021

This paper presents a novel approach for path-following control of a four-wheeled autonomous vehicle. The rear wheels of the vehicle are driven independently, all four wheels can be braked independently, and the front wheels are steered together. The proposed cascade structure consists of two convex optimization-based parts: one for path-following and another for the control allocation problem of the actuators. The control algorithm presents cost functions for the allocation problem focusing on safety. The proposed cost functions were examined and compared to former ones in a simulation environment. After all, the controller was tested in real-time test on a Lotus Evora test vehicle developed by ThyssenKrupp.
Magnetic Resonance Imaging Based on Wavelet Algorithm in the Diagnosis and Treatment of Tibial Osteomyelitis Wound Infection
Authors: Ou Xiaoran , Wang Qi , Li Chunxiao , Zhao Hongjin , Guo Lei
Published: November 2021

This study was to explore the therapeutic effect of magnetic resonance imaging (MRI) images based on the image processing algorithm under the correlation of dyadic wavelet coefficients on the diagnosis of tibial osteomyelitis patients. 32 tibial osteomyelitis patients admitted to hospital were randomly selected as the research objects. According to the patients’ wishes, patients who were willing to use new MRI imaging techniques for disease detection were set as the experimental group and conventional MRI imaging detection methods were set as the control group. The application effect of the new MRI imaging technology was evaluated by comparing the treatment effect of the two groups of patients. It was found that the mean square error (MSE) (38.5642) and signal-to-noise ratio (SNR) (18.5122) processed by the improved wavelet algorithm were much better than those of unimproved dyadic wavelet algorithm (59.1096 and 15.2341) (

P
<
0.05

). The possibilities of soft tissue swelling, bone invasion or destruction, thickening and sclerosis of bone cortex, bone abscess, periosteum response, dense dead bone, and bone sinus of patients in the experimental group were higher than those of the control group, which were 100% vs. 55%, 100% vs. 80%, 92% vs. 65%, 50% vs. 25%, 42% vs. 15%, 67% vs. 45%, and 50% vs. 15%, respectively (

P
<
0.05

). The healing time of osteomyelitis (22.89 ± 2.19 d vs. 32.32 ± 2.81 d) and the recovery of wound infection (14% vs. 45%) in the patients in control and experimental groups showed that the results of the experimental group were obviously better than those of the control group. The kappa value of the diagnosis results and tissue biopsy of the experimental group was higher than that of the control group (0.45 vs. 0.34) (

P
<
0.05

). In conclusion, the results of the enhanced and improved MRI images were relatively more accurate and the treatment methods adopted were more symptomatic, resulting in more effective treatment. In addition, the wavelet algorithm had certain application value in the enhancement processing of medical images and showed a good development prospect.
A Data-Driven Optimization Model of Important Multidimensional Factors Affecting College Students’ Cognitive Engagement in Ideological and Political Theory Course
Authors: Wang Liangliang
Published: November 2021

The optimization of important multidimensional factors is conducive to cognitive engagement, which is a crucial dimension of student engagement and plays a significant role in college students’ learning of the Ideological and Political Theory Course. However, because there are many influencing factors associated with cognitive engagement, the influence mechanism and analysis strategy of this kind of model are relatively complex. In order to solve this research gap, this paper establishes an optimization model affecting Chinese college students’ cognitive engagement in IPTC on the basis of sample collection and investigation. In this process, 4,700 questionnaires were distributed to 47 colleges and universities across the country, and copies were effectively recovered (N = 3992); the effective recovery rate was 84.94%. Cronbach’s alpha of 0.759 indicates that the scale has high reliability and Pearson’s correlation coefficient

P

 ≤ 0.001 shows that the scale has good validity. The KMO value of 0.703 in the Bartlett sphere test also shows that the scale is suitable for factor analysis. Firstly, according to the method of factor analysis, there are six important factor dimensions affecting college students’ cognitive engagement in the IPTC, namely, attention and motivation factor dimension, behavior and value attainment factor dimension, interest and practicality factor dimension, personality and will factor dimension, evaluation and time factor dimension, and knowledge and strategy factor dimension. Then, through descriptive analysis, it is found that personality and will factor dimension (M = 6.5837) plays a relatively major role while knowledge motivation dimension (M = 6.3505) has a weak impact on cognitive engagement. Finally, from linear regression analysis, there is a significant positive correlation between cognitive engagement and other variables. In addition, undergraduates are slightly lacking motivation in the learning of the course, and vigorously strengthening college students’ cognitive engagement is still necessary, so as to effectively enhance the effectiveness of the IPTC in the future.
Enterococcus faecium Alleviates Gut Barrier Injury in C57BL/6 Mice with Dextran Sulfate Sodium-Induced Ulcerative Colitis
Authors: He Wei , Ni Weijie , Zhao Junning
Published: November 2021

The involvement of gut microbiota composition in ulcerative colitis is strongly supported by previous research. Growing evidence suggests that probiotic therapy protects against inflammatory bowel disease in animal models and patients. However, as a probiotic, the role of Enterococcus faecium (E. faecium) in UC remains unclear. Nevertheless, the potential mechanism of the protective effect of E. faecium remains unknown. In this study, a dextran sulphate sodium-induced (DSS-induced) colitis model was used to detect the underlying mechanism of E. faecium in maintaining gut homeostasis. ELISA was performed to detect the levels of cytokines (TNF-α, IL-1β, IL-6, and IL-10). Furthermore, 454 pyrosequencing was used to investigate the microbiota composition in fecal samples. The results illustrate that E. faecium administration could prevent DSS-induced gut inflammation and intestinal flora imbalance. At the same time, the damage to intestinal mucosal barrier and tight junctions was partially repaired. These results demonstrate the preventive effect of E. faecium in DSS-induced intestinal injury. The present study provides new insights into the medicinal value of E. faecium for UC.
[Retracted] Geological Mineral Energy and Classification Based on Machine Learning
Authors: Lv Yan , Lu Laijun
Published: November 2021

In order to mine geological mineral energy and study on geological mineral energy classification, a method based on a wireless sensor was proposed. Of logistic regression, artificial neural networks, random forests, and main wireless sensor algorithms of support vector machine (SVM) with the model in the application of the energy mineral resource prediction practice effects are reviewed and discuss the practical application in the process of sample selection, the wrong points existing in the cost, the uncertainty evaluation, and performance evaluation of the model using wireless sensor algorithm, random forest of the probability distribution of mineralization in the study area is calculated, and five prospecting potential areas are delineated. The results show that the ratio of ore‐bearing unit and non‐ore‐bearing unit is 1 : 1, and the best random forest training model is obtained. 70% of the training sample set was randomly selected as the training set, and the remaining 30% was used as the test set to construct the random forest model. The training accuracy of the model is 96.7%, and the testing accuracy is 96.5%. Both model training accuracy and model testing accuracy are very high, which proves the accuracy of RF model construction and achieves satisfactory results. In this study, a wireless sensor is successfully applied to 3D mineral energy prediction, which makes a positive exploration for mineral resource prediction and evaluation in the future. Finally, the prediction of mineral resource energy based on a wireless sensor is an important trend of future development.
Role of 5G and Artificial Intelligence for Research and Transformation of English Situational Teaching in Higher Studies
Authors: Yu Haojie , Nazir Shah
Published: November 2021

We live in a modern and technological society run by intelligent and human-like machines and systems. This is due to the advancements in the field of artificial intelligence. The machines are directly or indirectly used in different sectors like healthcare, automatic vehicles, and complex decision-making and at the same used in educational institutes. The usage of AI-based systems and the Internet has brought numerous educational innovations for both teachers and students. With the online learning platforms grounded on AI techniques, 5G has revolutionized the teaching and learning methods by smooth and faster access to educational content. Students of foreign languages, especially English learners, can now use chatbots and intelligent tutoring systems to learn and practice their speaking and listening skills offline and online. With Computer-Assisted Language Learning (CALL), the English learning process can now be interactive and productive. The students can now improve their language skills by conversing with AI-based agents instead of native speakers to avoid any fear and anxiety. The intelligent platforms can understand the consuming power of the student and hence can create and give content according to their level to create an individualized learning environment. With the help of digital assistants, people can also find it very easy and productive to improve English proficiency. To accomplish the goal of English teaching very easily and ideally, the teachers should use AI-based techniques in the classrooms. With the help of intelligent assistants for the daily workload of a teacher, we will be able to concentrate fully on the language learning and skills of the students. The current study has presented a detailed overview of 5G and AI’s role in research and transformation of English situational teaching in higher studies. The search results are compiled and presented with different details of the area.
Research Progress on the Role of Inflammatory Mechanisms in the Development of Postoperative Cognitive Dysfunction
Authors: Tan Xiao-xiang , Qiu Li-Li , Sun Jie
Published: November 2021

Postoperative cognitive dysfunction (POCD), as one of the common postoperative complications, mainly occurs after surgery and anesthesia, especially in the elderly. It refers to cognitive function changes such as decreased learning and memory ability and inability to concentrate. In severe cases, there could be personality changes and a decline in social behavior. At present, a great deal of research had been carried out on POCD, but its specific mechanism remains unclear. The release of peripheral inflammation‐related factors, the degradation and destruction of the blood‐brain barrier, the occurrence of central inflammation, and the neuronal apoptosis and synaptic loss could be promoted by neuroinflammation indicating that inflammatory mechanisms may play key roles in the occurrence of POCD.
Analysis of Rural Talent Scale in Hebei Province Based on Fractional GM (1,1) and the Grey Relational Analysis Model
Authors: Li Yibo , Bi Wenbin , Xiao Kuo , Li Huan , Yin Shi , Tang Chaoyong
Published: November 2021

Talents are the key of rural revitalization. Under the background of Beijing-Tianjin-Hebei Coordinated Development, Hebei Province has always put talent revitalization at the core of rural revitalization. In order to promote the process of rural revitalization in Hebei Province, it is very important to understand the scale of rural talents. Firstly, the GM (1,1) model was used to predict the scale of rural talents in Hebei Province from 2020 to 2025. The prediction results showed that, in the rural development of Hebei Province in the next few years, the scale of production-oriented talents would gradually decline, while the scale of service-oriented, business-oriented, management-oriented, and skilled talents would show varying degrees of growth. Secondly, the grey relational analysis was used to analyze the importance of different factors for rural talents. Through the grey relational analysis, it was found that the infrastructure had the greatest impact on production-oriented talents, the agricultural industrialization operating rate had the strongest impact on service-oriented talents, and the urban-rural income level had the greatest impact on business-oriented talents, management-oriented talents, and skilled talents. Finally, according to the results of the GM (1,1) model and grey relational analysis, aiming at different types of rural talents, this paper puts forward countermeasures and suggestions from the aspects of strengthening rural infrastructure construction, improving rural medical and health conditions and improving income distribution pattern.
Dual Logic of Sports Violence Governance in China: A Comprehensive Survey of Law and Industry Autonomy
Authors: Ren Lei , Shi Yan , Ma Hong
Published: November 2021

Sports violence is a critical issue that has hindered China’s sports development. Dual logic is currently the mainstream rule of law and industrial autonomy, although it has not produced satisfactory results. In this paper, we used expert interviews, text analysis, and case analysis to investigate the flaws in the current governance process and found that the dual logic of sports violence governance has problems of varying degrees. The low degree of legislative specialization, the hazy limit of judicial intervention, and disparate law enforcement are examples of the rule of law. The clash of rights and interests between the association and the state, the association’s ineffectual control over the junior leagues, and the limited scope of governance are all examples of industry autonomy. Based on the issues mentioned above, this paper proposes dual logic strengthening measures and the notion of integrated governance. In particular, we should improve the rule of law thinking and construct a legal system for sports violence in China from legislation, justice and law enforcement, and law-abidingness to compensate for the current lack of law in sports violence. Second, we define the scope of the association’s “postdecoupling era” powers and obligations, resolve conflicts through state involvement based on the rule of law, and remove governance hurdles. Finally, we thoroughly investigate three aspects of integrated governance between the rule of law and industry autonomy: respecting industry autonomy and providing specific implementation space for industry norms, not excluding the rule of law’s intervention, and establishing an industry autonomy supervision mechanism. The rule of law and industry autonomy permeate each other and realize integration.
Experimental Investigation of the Effects of the Gangue Particle Size on the Evolution Rules of Key Seepage Parameters
Authors: Wang Lihua , Zhang Jixiong , Wei Yongqi , Zhu Cunli , Zhu Gaolei
Published: November 2021

In order to deal with solid wastes and protect the fragile ecological environment on the ground, using gangues as the filling materials in the underground goaf can not only achieve favorable waste disposal but also alleviate surface subsidence and protect surface buildings and the ecological environment, with great practical significance and application prospects. During the water seepage process, the evolution rules of inner seepage channels in the bulk filling materials are the theoretical foundation for the realization of water-preserved mining. In order to gain clear knowledge of the seepage characteristics of the bulk filling gangues with different sizes, the evolution rules of some seepage parameters mainly including the displacement, the porosity, and the permeability of gangues and hydraulic pressure were analyzed via COMSOL numerical simulation. The evolution rules of the seepage characteristics of the bulk filling materials with different sizes were revealed by combining the present experimental and numerical results. Moreover, the present seepage experiment was proved to be reliable by comparing with numerical simulation results. This work can provide theoretical foundation for investigating the evolution characteristics of inner seepage paths in the bulk filling materials and selecting appropriate bulk filling materials under different stress and seepage environments.
Comparison of Machine Learning Algorithms for the Prediction of Mechanical Stress in Three-Phase Power Transformer Winding Conductors
Authors: Valencia Fausto , Arcos Hugo , Quilumba Franklin
Published: November 2021

This research compares four machine learning techniques: linear regression, support vector regression, random forests, and artificial neural networks, with regard to the determination of mechanical stress in power transformer winding conductors due to three-phase electrical faults. The accuracy compared with finite element results was evaluated for each model. The input data were the transient electrical fault currents of power system equivalents with impedances from low to high values. The output data were the mechanical stress in the conductors located in the middle of the winding. To simplify the design, only one hyperparameter was varied on each machine learning technique. The random forests technique had the most accurate results. The highest errors were found for low-stress values, mainly due to the high difference between maximum and minimum stresses, which made the training of the machine learning models difficult. In the end, an accurate model that could be used in the continuous monitoring of mechanical stress was obtained.
[Retracted] Effects of Ozone on Hippocampus BDNF and Fos Expressions in Rats with Chronic Compression of Dorsal Root Ganglia
Authors: Zhu Lingling , Wang Yanxiu , Lin Xiaowen , Zhao Xu , Fu Zhi jian
Published: November 2021

The effects of ozone on hippocampal expression levels of brain‐derived neurotrophic factor (BDNF) and c‐fos protein (Fos) were evaluated in rats with chronic compression of dorsal root ganglia (CCD). Forty‐eight adult female Sprague‐Dawley rats were randomly divided into the following 4 groups (n = 12): sham operation (sham group), CCD group, CCD with 20 μg/ml of ozone (CCD + AO3 group), and CCD with 40 μg/ml of ozone (CCD + BO3 group). Except the sham group, unilateral L5 dorsal root ganglion (DRG) compression was performed on all other groups. On days 1, 2, and 4 after the operation, the CCD + AO3 and CCD + BO3 groups were injected with 100 μl of ozone with concentrations of 20 and 40 μg/ml, respectively. Thermal withdrawal latencies (TWLs) and mechanical withdrawal thresholds (MWTs) were measured at various time points before and after the operation. BDNF and Fos expressions were examined in the extracted hippocampi using immunohistochemistry. The TWLs and MWTs of CCD model rats that received ozone were lower with decreased BDNF and increased Fos expression levels, on day 21 after the operation, compared to those of the sham group (P < 0.05). The TWLs and MWTs of the CCD + AO3 and CCD + BO3 groups were higher with increased BDNF and decreased Fos expression levels, on day 21 after the operation, compared to those of the CCD group (P < 0.05). The TWLs were longer and the MWTs were higher in the CCD + BO3 group at each time point with increased BDNF and decreased Fos expression levels, on day 21 after the operation, compared to those of the CCD + AO3 group (P < 0.05). Our results revealed that ozone can relieve the neuropathic pain caused by the pathological neuralgia resulting from DRG compression in rats. The mechanism of action for ozone is likely associated with changes in BDNF and Fos expression levels in the hippocampus.
A Single-Step Method for Over-the-Horizon Geolocation Using Importance Sampling
Authors: Yin Jiexin , Wang Ding , Yang Bin , Yang Xin
Published: November 2021

This paper investigates the geolocation for an over-the-horizon (OTH) transmitter observed by widely separated arrays. We propose a maximum likelihood (ML) based direct position determination (DPD) method to directly locate the transmitter in a single step by exploiting the position information embedded in azimuth angles. The Monte Carlo importance sampling (IS) technique is employed to find an approximate global solution to this DPD problem, where the importance function analogous to Gaussian distribution is derived. This enables the transmitter to be precisely located with low complexity in a noniterative manner. Additionally, we derive the Cramér–Rao bound (CRB) expression for the investigated problem. The simulation results corroborate the superior localization performance of the proposed method with respect to the conventional two-step approaches and the iterative DPD method.