bluuebunny/crossref_metadata_2025 huggingface dataset:
Blood eosinophils, fractional exhaled nitric oxide and the risk of asthma attacks in randomised controlled trials: protocol for a systemic review and control arm patient-level meta-analysis for clinical prediction modelling
Authors: Couillard Simon , Steyerberg Ewout , Beasley Richard , Pavord Ian
Published: April 2022

Introduction

The reduction of the risk of asthma attacks is a major goal of guidelines. The fact that type-2 inflammatory biomarkers identify a higher risk, anti-inflammatory responsive phenotype is potentially relevant to this goal. We aim to quantify the relation between blood eosinophils, exhaled nitric oxide (FeNO) and the risk of severe asthma attacks.

Methods and analysis

A systematic review of randomised controlled trials (RCTs) will be conducted by searching MEDLINE from January 1993 to April 2021. We will include RCTs that investigated the effect of fixed treatment(s) regimen(s) on severe asthma exacerbation rates over at least 24 weeks and reported a baseline value for blood eosinophils and FeNO. Study selection will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, and the methodological appraisal of the studies will be assessed by the Cochrane Risk-of-Bias Tool for RCTs. Study authors will be contacted to request anonymised individual participant data (IPD) for patients randomised to the trial’s control arm. An IPD meta-analysis will be performed for multivariable prognostic modelling with performance assessment (calibration plots and the c-statistic) in a cross-validation by study procedure. The outcome to predict is the absolute number of severe asthma attacks to occur in the following 12 months if anti-inflammatory therapy is not changed (ie, annualised number of attacks requiring ≥3 days of systemic corticosteroids and/or hospitalisation if the patient was randomised to the control arm of an RCT). A summary prognostic equation and risk stratification chart will be reported as a basis for further analyses of individualised treatment benefit.

Ethics and dissemination

The protocol has been reviewed by the relevant Oxford academic ethics committee and found to comprise fully anonymised data not requiring further ethical approbation. Results will be communicated in an international meeting and submitted to a peer-reviewed journal.

PROSPERO registration number

CRD42021245337.
Prediction of the need for intensive oxygen supplementation during hospitalisation among subjects with COVID-19 admitted to an academic health system in Texas: a retrospective cohort study and multivariable regression model
Authors: Davis John W , Wang Beilin , Tomczak Ewa , Chi-Fu Chia , Harmouch Wissam , Reynoso David , Keiser Philip , Cabada Miguel Mauricio
Published: March 2022

Objective

SARS-CoV-2 has caused a pandemic claiming more than 4 million lives worldwide. Overwhelming COVID-19 respiratory failure placed tremendous demands on healthcare systems increasing the death toll. Cost-effective prognostic tools to characterise the likelihood of patients with COVID-19 to progress to severe hypoxemic respiratory failure are still needed.

Design

We conducted a retrospective cohort study to develop a model using demographic and clinical data collected in the first 12 hours of admission to explore associations with severe hypoxemic respiratory failure in unvaccinated and hospitalised patients with COVID-19.

Setting

University-based healthcare system including six hospitals located in the Galveston, Brazoria and Harris counties of Texas.

Participants

Adult patients diagnosed with COVID-19 and admitted to one of six hospitals between 19 March and 30 June 2020.

Primary outcome

The primary outcome was defined as reaching a WHO ordinal scale between 6 and 9 at any time during admission, which corresponded to severe hypoxemic respiratory failure requiring high-flow oxygen supplementation or mechanical ventilation.

Results

We included 329 participants in the model cohort and 62 (18.8%) met the primary outcome. Our multivariable regression model found that lactate dehydrogenase (OR 2.36), Quick Sequential Organ Failure Assessment score (OR 2.26) and neutrophil to lymphocyte ratio (OR 1.15) were significant predictors of severe disease. The final model showed an area under the curve of 0.84. The sensitivity analysis and point of influence analysis did not reveal inconsistencies.

Conclusions

Our study suggests that a combination of accessible demographic and clinical information collected on admission may predict the progression to severe COVID-19 among adult patients with mild and moderate disease. This model requires external validation prior to its use.
Primary care and cancer: an analysis of the impact and inequalities of the COVID-19 pandemic on patient pathways
Authors: Watt Toby , Sullivan Richard , Aggarwal Ajay
Published: April 2022

Objectives

We explore the routes to cancer diagnosis to further undertanding of the inequality in the reduction in detection of new cancers since the start of the pandemic. We use different data sets to assess stages in the cancer pathway: primary care data for primary care consultations, routine and urgent referrals and published analysis of cancer registry data for appointments and first treatments.

Setting

Primary and cancer care.

Participants

In this study we combine multiple data sets to perform a population-based cohort study on different areas of the cancer pathway. For primary care analysis, we use a random sample of 5 00 000 patients from the Clinical Practice Research Datalink. Postreferral we perform a secondary data analysis on the Cancer Wait Times data and the National Cancer Registry Analysis Service COVID-19 data equity pack.

Outcome measures

Primary care: consultation, urgent cancer referral and routine referral rates, then appointments following an urgent cancer referral, and first treatments for new cancer, for all and by quintile of patient’s local area index of multiple deprivation.

Results

Primary care contacts and urgent cancer referrals in England fell by 11.6% (95% CI 11.4% to 11.7%) and 20.2% (95% CI 18.1% to 22.3%) respectively between the start of the first non-pharmaceutical intervention in March 2020 and the end of January 2021, while routine referrals had not recovered to prepandemic levels. Reductions in first treatments for newly diagnosed cancers are down 16.3% (95% CI 15.9% to 16.6%). The reduction in the number of 2-week wait referrals and first treatments for all cancer has been largest for those living in poorer areas, despite having a smaller reduction in primary care contact.

Conclusions

Our results further evidence the strain on primary care and the presence of the inverse care law, and the dire need to address the inequalities so sharply brought into focus by the pandemic. We need to address the disconnect between the importance we place on the role of primary care and the resources we devote to it.
Use of infrared thermography in medical diagnostics: a scoping review protocol
Authors: Kesztyüs Dorothea , Brucher Sabrina , Kesztyüs Tibor
Published: April 2022

Introduction

Thermography offers a non-invasive radiation-free methodology for diagnostic imaging and temperature measurement, but the extent of the current application is unclear, as is the level of evidence for each use case. Moreover, population-based thermographic reference values for diagnostic purposes are nearly unknown. The aim of this scoping review is to identify patient populations and diseases in which thermography is applied, cataloguing of technical and environmental modalities, investigation of the existence of specific reference data and finally exploration of gaps and future tasks.

Methods and analysis

PubMed, Cochrane Database of Systematic Reviews and CENTRAL, Embase, Web of Science and OpenGrey are to be searched using pretested suitable search strategies, with no language restriction, but abstracts should be available in English or German and articles should not have been published before 2000. This limited time frame is due to the rapid technological progress, which makes it necessary to exclude reports based on outdated technology. The literature found will be selected on the basis of previously defined inclusion and exclusion criteria. Subsequently, relevant data will be extracted from the included references into a predesigned table. The selection and extraction process will be conducted by two researchers independently. The report of the results will be according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. The entire review process will follow the Joanna Briggs Institute approach. The scoping review protocol is registered at the Open Science Framework.

Ethics and dissemination

Ethical approval is not required for this work, but ethical medicine also obliges us to carefully consider diagnostic alternatives and compare them with current standards. The dissemination of the results will take place in a variety of ways. First and foremost through publication in an open access journal, but also through conference proceedings. In addition, this scoping review will serve to open up new research foci with regard to thermography.
Understanding maternal postnatal blood pressure changes following hypertensive disorders in pregnancy: protocol for a prospective cohort study
Authors: Sheehan Elaine , Wang Chao , Cauldwell Matthew , Bick Debra , Thilaganathan Basky
Published: April 2022

Introduction

Hypertensive disorders occur in approximately 10% of women during pregnancy. There is robust population-based data to show that women who have hypertension in pregnancy are much more likely to develop cardiovascular disease (CVD) in the postpartum period. Women with a hypertensive disorder of pregnancy (HDP) are twice more at risk of heart disease and stroke, and four times more likely to develop hypertension after birth. Two out of three women who had HDP will die from CVD. Recent evidence suggests that young women with HDP develop signs of CVD in the immediate postpartum period, rather than several decades later as previously presumed. If confirmed, this concerning finding presents healthcare practitioners with an opportunity to influence women’s cardiovascular health by advising on lifestyle choices and considering therapeutic interventions to prevent the development of CVD.

Methods and analysis

This prospective cohort study design will ask approximately 300 participants to complete 3 days of home blood pressure monitoring every fortnight for 12 weeks postpartum and will culminate with a 24-hour episode of ambulatory blood pressure monitoring at 12 weeks postpartum. Women and healthcare professionals will complete questionnaires surrounding postpartum care for women who had HDP and knowledge of CVD risk. In addition, the relationship between hypertension and factors likely to influence outcomes such as severity of HDP, maternal age, body mass index and ethnicity will be analysed using logistic regression. Blood pressure and data from questionnaires will be analysed using descriptive statistics, with temporal stratification.

Ethics and dissemination

Research ethics approval was obtained from London-West London & GTAC Research Ethics Committee. Research outputs will be published and disseminated through midwifery, obstetric or general practitioner targeted academic journals. The patient and public involvement group will disseminate findings to women who have experienced HDP among their peer groups.

Trial registration number

NCT05137808.
Sensitizing immune unresponsive colorectal cancers to immune checkpoint inhibitors through MAVS overexpression
Authors: Hwang Bin-Jin , Tsao Li-Chung , Acharya Chaitanya R , Trotter Timothy , Agarwal Pankaj , Wei Junping , Wang Tao , Yang Xiao-Yi , Lei Gangjun , Osada Takuya , Lyerly Herbert Kim , Morse Michael A , Hartman Zachary Conrad
Published: March 2022

Background

The majority of colorectal carcinomas (CRCs) are insensitive to programmed death protein-1/programmed death-ligand 1 (anti-PD-1/PD-L1) immune checkpoint inhibitor (ICI) antibodies. While there are many causes for ICI insensitivity, recent studies suggest that suppression of innate immune gene expression in tumor cells could be a root cause of this insensitivity and an important factor in the evolution of tumor immunosuppression.

Methods

We first assessed the reduction of mitochondrial antiviral signaling gene (MAVS) and related RIG-I pathway gene expression in several patient RNA expression datasets. We then engineered MAVS expressing tumor cells and tested their ability to elicit innate and adaptive anti-tumor immunity using both in vitro and in vivo approaches, which we then confirmed using MAVS expressing viral vectors. Finally, we observed that MAVS stimulated PD-L1 expression in multiple cell types and then assessed the combination of PD-L1 ICI antibodies with MAVS tumor expression in vivo.

Results

MAVS was significantly downregulated in CRCs, but its re-expression could stimulate broad cellular interferon-related responses, in both murine and patient-derived CRCs. In vivo, local MAVS expression elicited significant anti-tumor responses in both immune-sensitive and insensitive CRC models, through the stimulation of an interferon responsive axis that provoked tumor antigen-specific adaptive immunity. Critically, we found that tumor-intrinsic MAVS expression triggered systemic adaptive immune responses that enabled abscopal CD8 +T cell cytotoxicity against distant CRCs. As MAVS also induced PD-L1 expression, we further found synergistic anti-tumor responses in combination with anti-PD-L1 ICIs.

Conclusion

These data demonstrate that intratumoral MAVS expression results in local and systemic tumor antigen-specific T cell responses, which could be combined with PD-L1 ICI to permit effective anti-tumor immunotherapy in ICI resistant cancers.
Genetic characteristics involving the PD-1/PD-L1/L2 and CD73/A2aR axes and the immunosuppressive microenvironment in DLBCL
Authors: Zhang Tingting , Liu Hengqi , Jiao Lei , Zhang Zhenzhen , He Jin , Li Lanfang , Qiu Lihua , Qian Zhengzi , Zhou Shiyong , Gong Wenchen , Meng Bin , Ren Xiubao , Zhang Huilai , Wang Xianhuo
Published: April 2022

Background

Targeting the PD-1/PD-L1/L2 (programmed cell death protein 1/programmed cell death ligand 1/ligand 2) pathway combined with other immunosuppressive signalings, such as CD73/A2aR (A2a adenosine receptor) adenosine signaling, has emerged as a promising strategy for cancer treatment. The genetic characteristics of these immune checkpoints need to be further investigated in diffuse large B-cell lymphoma (DLBCL).

Methods

We performed whole-exome sequencing/targeted deep sequencing to investigate the genetic characteristics of PD-1/PD-L1/L2 and CD73/A2aR. The immunosuppressive effect of these two pathways on the tumor microenvironment was evaluated via RNA sequencing. Single-cell RNA sequencing was further applied to investigate the dysfunctional CD8+ T cells. In addition, multiplex immunofluorescence staining was used to quantitatively assess the expression of dysfunctional CD8+T cells in DLBCL.

Results

SP140 was identified as a novel translocation partner for PD-L1, and a new inversion was detected between PD-L1 and PD-L2, both leading to the upregulation of PD-L1 expression. CD73 genetic mutations did not increase mRNA and protein expression. Patients with genetically altered CD73 tended to have a better overall survival than patients with wild-type CD73. Both PD-1/PD-L1 and CD73/A2aR signaling mediated the immunosuppressive microenvironment in DLBCL. The numbers of CD8+T cells with PD-1 and A2aR expression were positively correlated with the number of dysfunctional CD8+T cells (R2=0.974, p=0.013). According to the grades of dysfunctional CD8+T cells we defined,grade1 dysfunctional CD8+T cells, with either PD-1+or A2aR+, were significantly associated with poorer survival thangrade0 dysfunctional CD8+T cells, with both PD-1−and A2aR−; and patients withgrade2 dysfunctional CD8+T cells showed the worst clinical outcomes.

Conclusions

This study describes the additional genetic basis of PD-L1 overexpression and characterizes certain genetic alterations of CD73/A2aR in DLBCL. The degree of T-cell dysfunction is correlated with clinical outcomes. Strategies that reverse T-cell dysfunction by inhibiting PD-1/PD-L1/L2, particularly in combination with CD73/A2aR, may show potential as effective therapeutic options for DLBCL.
Clinical, genomic, and transcriptomic correlates of response to immune checkpoint blockade-based therapy in a cohort of patients with angiosarcoma treated at a single center
Authors: Rosenbaum Evan , Antonescu Cristina R , Smith Shaleigh , Bradic Martina , Kashani Daniel , Richards Allison L , Donoghue Mark , Kelly Ciara M , Nacev Benjamin , Chan Jason E , Chi Ping , Dickson Mark A , Keohan Mary L , Gounder Mrinal M , Movva Sujana , Avutu Viswatej , Thornton Katherine , Zehir Ahmet , Bowman Anita S , Singer Samuel , Tap William , D’Angelo Sandra
Published: April 2022

Background

Angiosarcoma is a histologically and molecularly heterogeneous vascular neoplasm with aggressive clinical behavior. Emerging data suggests that immune checkpoint blockade (ICB) is efficacious against some angiosarcomas, particularly cutaneous angiosarcoma of the head and neck (CHN).

Methods

Patients with histologically confirmed angiosarcoma treated with ICB-based therapy at a comprehensive cancer center were retrospectively identified. Clinical characteristics and the results of targeted exome sequencing, transcriptome sequencing, and immunohistochemistry analyses were examined for correlation with clinical benefit. Durable clinical benefit was defined as a progression-free survival (PFS) of ≥16 weeks.

Results

For the 35 patients included in the analyses, median PFS and median overall survival (OS) from the time of first ICB-based treatment were 11.9 (95% CI 7.4 to 31.9) and 42.5 (95% CI 19.6 to 114.2) weeks, respectively. Thirteen patients (37%) had PFS ≥16 weeks. Clinical factors associated with longer PFS and longer OS in multivariate analyses were ICB plus other therapy regimens, CHN disease, and white race. Three of 10 patients with CHN angiosarcoma evaluable for tumor mutational burden (TMB) had a TMB ≥10. Five of six patients with CHN angiosarcoma evaluable for mutational signature analysis had a dominant mutational signature associated with ultraviolet (UV) light. No individual gene or genomic pathway was significantly associated with PFS or OS; neither were TMB or UV signature status. Analyses of whole transcriptomes from nine patient tumor samples found upregulation of angiogenesis, inflammatory response, and KRAS signaling pathways, among others, in patients with PFS ≥16 weeks, as well as higher levels of cytotoxic T cells, dendritic cells, and natural killer cells. Patients with PFS <16 weeks had higher numbers of cancer-associated fibroblasts. Immunohistochemistry findings for 12 patients with baseline samples available suggest that neither PD-L1 expression nor presence of tumor-infiltrating lymphocytes at baseline appears necessary for a response to ICB-based therapy.

Conclusions

ICB-based therapy benefits only a subset of angiosarcoma patients. Patients with CHN angiosarcoma are more likely to have PFS ≥16 weeks, a dominant UV mutational signature, and higher TMB than angiosarcomas arising from other primary sites. However, clinical benefit was seen in other angiosarcomas also and was not restricted to tumors with a high TMB, a dominant UV signature, PD-L1 expression, or presence of tumor infiltrating lymphocytes at baseline.
“There’s so much to be done”: a qualitative study to elucidate research priorities in childhood-onset systemic lupus erythematosus
Authors: Cannon Laura , Caliendo Anne , Hersh Aimee , Knight Andrea M
Published: March 2022

Objective

There is a pressing need for high-quality, comprehensive research to describe the natural history, best treatments, access to care and disparities in care for patients with childhood-onset SLE (cSLE). Building on a previously published survey study of cSLE clinicians and researchers to describe research priorities in cSLE, the primary objective of this study was to conduct expert interviews to define high-priority areas for cSLE research.

Methods

Individuals with identified multidisciplinary expertise in cSLE were recruited worldwide using purposive sampling technique. Experts participated in open-ended, semistructured qualitative interviews. Interviews were designed to elicit expert perspectives on research priorities, optimal research approaches, and factors that facilitate and hinder advancing cSLE research. Interviews were digitally recorded, transcribed and de-identified for analysis. Analysis for underlying themes of cSLE expert perspectives was performed using a constant comparative approach.

Results

Twenty-nine experts with diverse clinical and research backgrounds participated. Themes emerged within five domains: (1) expanding disease knowledge; (2) investigator collaboration; (3) partnering with patients and families; (4) improving care to optimise research; and (5) overcoming investigator barriers. Choosing a singular area of focus was difficult; experts identified many competing priorities. Despite the numerous priorities that emerged, experts described several existing and potential opportunities for advancing cSLE research.

Conclusions

In addition to the priorities identified by cSLE experts in this study, the opportunities for advancing cSLE research and care that were proposed should be used as a foundation for creation of a cSLE research agenda for both research and funding allocation.
A 3D visualization method for identifying fabric characteristics during suffusion using transparent soil
Authors: Deng Zezhi , Wang Gang
Published: March 2022

Suffusion is a process by which fine particles move through the voids between coarse particles (intergranular voids) by seepage flow. Therefore, identifying the arrangement of coarse particles (coarse matrix), intergranular voids, and the spatial distribution of fine particles is a key issue for studying suffusion. Transparent soil is being increasingly used to replace real soil in laboratory model tests for studying the internal particle movements and pore fluid flow in soils. This study established an experimental setup for scanning a transparent soil specimen during seepage by a moving laser and made an attempt to construct a 3D digital mesostructural model of the specimen based on the images of the sequentially illuminated cross-sections. An example test on a gap-graded soil was conducted to show the performance of the presented method. It demonstrated that the coarse matrix and intergranular voids can be visualized and quantified at satisfactory precisions; moreover, the loss and redistribution of fine particles as well as important phenomena such as deposition at pore bodies and clogging of pore throats can also be visualized and identified qualitatively.
Nitrogen use efficiency of wheat and canola from urea treated with different types of double inhibitors
Authors: Lasisi Ahmed A. , Akinremi Olalekan O. , Kumaragamage Darshani
Published: March 2022

Urease inhibitor (specifically, N-( n-butyl) thiophosphoric triamide, NBPT) and nitrification inhibitors (NIs) have been used to minimize nitrogen (N) loss from urea. However, their effects on improving crop N use efficiency (NUE) are usually inconsistent. A 2-year study was conducted to determine the best combination of NBPT and different NIs on urea that will maximize NUE while reducing nitrate leaching. Treatments consisted of untreated urea, NBPT-treated urea, and six types of (NBPT + NI)-treated urea that were surface applied at 80 kg N ha−1 on plots seeded to canola (2019) and wheat (2020) at Carman and Portage in Manitoba, Canada. Plots at Carman had lysimeters installed to measure leached water and nitrate. The sites had at least 35% lesser rainfall than climate normal during each growing season. At each site, average grain yields, N removal, and residual nitrate were not significantly different between untreated urea and inhibitor-treated urea. Over the 2 years, there was no significant benefit of NBPT or NBPT + NI on crop NUE at each site. Cumulative leached nitrate (19–40 kg N ha−1) did not differ significantly among urea treated with and without inhibitors. This is because >50% of the precipitation occurred when the effectiveness of NI had elapsed. Although NBPT and NI are known to reduce N losses to the atmosphere, this study suggests that the agronomic benefit and nitrate leaching prevention by NI applied in the spring may be limited in regions where large precipitation occurs later in the growing season or during non-growing season.
Integrating an electronic compass for position tracking on a wheeled tricycle mobile robot
Authors: Chand Praneel
Published: March 2022

Dead-reckoning via encoders on wheeled-mobile robots is a simple but inaccurate method to estimate position. The major drawback of encoders is wheel slippage errors that accumulate over time. This problem is often addressed by using additional sensors such as compass, gyroscope, or GPS. This paper details the integration and effectiveness of a relatively low-cost solution using an electronic compass to reduce positioning error on a wheeled tricycle mobile robot. A customised Visual Studio program has been developed to adjust the settings of the electronic compass and integrate it with the Visual Studio based robot control system. The electronic compass heading data is fused with the encoder odometry heading data in three different ways: simple fusion, linear weighted fusion, and Kalman filter fusion. Simple fusion and linear weighted fusion rely on parameters determined from angular acceleration and angular velocity, respectively. The Kalman filter uses variance data for the encoders and electronic compass to determine an optimal heading. Experiments have been conducted in an indoor corridor environment to evaluate and compare the various fusion methods. Position error is successfully reduced and is sufficient to locate the robot within the corridor.
FINANCIAL LIBERALIZATION, DEMOCRATIC INSTITUTIONS, AND INCOME INEQUALITY: NEW INSIGHTS FROM PAKISTAN
Authors: RAHMAN ABDUL , KHAN MUHAMMAD ARSHAD
Published: March 2022

This study investigates the relationship between financial liberalization, democratic institutions, and income inequality in Pakistan by using a two-state Markov switching (MS) methodology for the period 1972–2017. The dynamic factor modelling approach is used to construct the financial liberalization index. The impact of the Global Financial Crisis (GFC) of 2007–2008 on financial liberalization–institutions–inequality nexus was checked using the Chow breakpoint test. The result reveals no significant effect of GFC on Pakistan’s economy. Results from the MS model divulge that financial liberalization lessens income inequality in the high-income inequality regime as well as in the low-income inequality regime. The result further discloses that democratic institutions enhance income inequality in high-income inequality regimes while reduce income inequality in the low-inequality regime. While studying the joint role of democratic institutions and financial liberalization, it is observed that the weak role of democratic institutions offsets the benefits of financial liberalization in the high-income inequality regime; however, institutions and financial liberalization are supportive in reducing income inequality in the low-inequality regime. Besides, the results also confirm the existence of Kuznets hypothesis in Pakistan. Therefore, there is a need for further reforms to revamp institutions to reduce income inequality in Pakistan.
Determination of the concentration of prepared Rehmannia root solution by fluorescence polarization spectroscopy combined with the least-square method
Authors: Li Xiao-Lin , Sun Yun-Ling , Ma Hai-Ying , Wang Jie , Yang Hang , Zhu Chun
Published: March 2022

In recent years, the safety of traditional Chinese medicine has gradually attracted consumers’ attention. Therefore, the qualitative and quantitative detection of traditional Chinese medicine has become a hot research topic in recent years. In this paper, we chose prepared Rehmannia root as the research object. By using the fluorescence polarization spectrum and the least-square method, a method for predicting the concentration of traditional Chinese medicine solutions was established. First, we scanned the fluorescence polarization spectra of the prepared Rehmannia root solution to obtain the inner anisotropy and anisotropy of each sample. Then, the least-square method was used to obtain the functional relationship between concentration and anisotropy. Finally, the functional relation was applied to predict the concentration of the prepared Rehmannia root solution. The correlation coefficients of the predicted concentration were 0.9944 and 0.9928, with an average recovery rate of 100.94% and 99.58%, respectively. The results show that fluorescence polarization spectroscopy combined with the least-squares method can quickly and accurately detect the concentration of Rehmannia glutinosa root solution. This provides a new method for the content detection of traditional Chinese medicine components.
Optimize classification testing of apple juice combining derivative fluorescence spectroscopy with PCA
Authors: Zhu Chun , Song Xin-Shu , Liu Huai-Bo , Chen Guo-Qing , Zhu Tuo
Published: March 2022

Cluster analysis of apple juice is an important method in the quality identification of fruit juice. However, the traditional principal component analysis (PCA) is to reduce the dimension of high dimensional data and to achieve clustering by way of score value. Experiments have found that this clustering method is not suitable for real samples with fluorescence overlap. In this paper, we propose a processing mechanism to optimize the derivative of the fluorescence spectrum. When the derivative is calculated, we can amplify the spectral difference of the similar matter and improve the ability of the PCA to achieve the best effect of clustering. Experiments show that the optimized method for the actual sample classification accuracy rate of 100%, which can fully realize the type of commercially available apple juice beverage distinction and achieve the practical application of quality testing.
Manipulation of the topology and solid-state spin using a mechanic-based hybrid system
Authors: Huang Wen-Tao , Lü Dong-Yan , Li Xin-Ke , Jin Long , Ren Hong-Tao , Zhou Yuan
Published: March 2022

In this paper, a three-body hybrid quantum system with the solid-state spin and topological qubit both mediated by a torsional nanomechanical resonator (NMR) is built by taking advantage of two different coupling mechanisms, the so-called strain and the magnetism, respectively. Two basic quantum manipulation (QM) schemes with respect to the quantum interface for arbitrary-state transfer and two-qubit Mølmer–Sørensen (MS) gate are also studied here. Then the efficiency for both QM processes is also systematically estimated, even under the influence of all kinds of adverse factors such as dissipation, decoherence and dephasing. This work may provide an extensible route towards a wider range of applications in quantum manipulation.
CPRO: Competitive Poor and Rich Optimizer-Enabled Deep Learning Model and Holoentropy Weighted-Power K-Means Clustering for Brain Tumor Classification Using MRI
Authors: Agalya V. , Kandasamy Manivel , Venugopal Ellappan , Maram Balajee
Published: March 2022

A brain tumor is a collection of irregular and needless cell development in the brain region, and it is considered a life-threatening disease. Therefore, early level segmentation and brain tumor detection with Magnetic Resonance Imaging (MRI) is more important to save the patient’s life. Moreover, MRI is more effective in identifying patients with brain tumors since the recognition of this modality is moderately larger than considering other imaging modalities. The classification of brain tumors is the most important, difficult task in medical imaging systems because of size, appearance and shape variations. In this paper, Competitive Poor and Rich Optimization (CPRO)-based Deep Quantum Neural Network (Deep QNN) is proposed for brain tumor classification. Additionally, the pre-processing process assists in eradicating noises and uses image intensity to eliminate the artifacts. The significant features are extracted from pre-processed image to perform a productive classification process. The Deep QNN classifier is employed for classifying the brain tumor regions. Besides, the Deep QNN classifier is trained by the developed CPRO approach, which is newly designed by integrating Poor and Rich Optimization (PRO) and Competitive Swarm Optimizer (CSO). The developed brain tumor detection model outperformed other existing models with accuracy, sensitivity and specificity of 94.44%, 97.60% and 93.78%.
A Conservative Memristive System with Amplitude Control and Offset Boosting
Authors: Zhang Xin , Li Chunbiao , Dong Enzeng , Zhao Yibo , Liu Zuohua
Published: March 2022

Based on a variable-boostable chaotic system, a conservative chaotic system with controllable amplitude and offset is proposed. The system exhibits rich symmetrical dynamics under different parameters and initial conditions. More interestingly, a parameter of memristor poses a partial amplitude control to a system variable. Furthermore, the derived memristive system has the property of offset boosting, where an independent constant can be introduced for free rescaling of the average value of a system variable. Experimental circuit with a memristor rheostat is designed for amplitude control. Circuit simulation based on Multisim software agrees well with the systematic analysis and numerical exploration. To the best of our knowledge, in the literature there is no 3D conservative memristive system reported with such properties as amplitude control and offset boosting.
Bifurcation Analysis and Finite-Time Contraction Stability of an Alzheimer Disease Model
Authors: Hu Jing , Zhang Qimin , Meyer-Baese Anke , Ye Ming
Published: March 2022

In this paper, considering reaction–diffusion, delay and random disturbances, two classes of mathematical models associated with Alzheimer’s disease (AD) are developed. For the deterministic AD model, the stability of the unique positive equilibrium and the Hopf bifurcation are analyzed. On the other hand, focusing on the influence of uncertain factors in the environment on AD, we investigate the finite-time contractive stability (FTCS) for the stochastic AD model modulated by Markov switching process. The basic method used to formulate the FTCS of the system is the comparison method. Several illustrative examples are considered to demonstrate and verify the effectiveness of the obtained theoretical results.
Nonlinear Analysis on Flow-Induced Vibration of Single-Walled Carbon Nanotubes Employing Analytical Methods
Authors: Ghasemi S. E. , Gouran Sina
Published: March 2022

In this research, the vibration and frequency of single-walled carbon nanotubes (SWCNTs) with conveyance a fluid flow are assessed analytically. The nanotube is imbedded in a Pasternak foundation and the nonlocal beam model is utilized to study on flow-induced vibration of the SWCNT. The differential transform method and variation iteration scheme have been employed to solve the nonlinear differential equation of the problem. The validity of proposed approaches is evaluated by comparing with numerical findings obtained using Keller Box method (KBM). The effects of main parameters including velocity of flow, nonlinear amplitude, nonlocal parameter as well as axial tensions on variation of the SWCNT’s frequency are examined. The outcomes indicate that increment of the nonlocal parameter leads to enhancement in variation of frequency. Also, the frequency variation of the SWCNT increases by elevating the axial tension.
MULTI-FEATURE FUSION EMOTION RECOGNITION BASED ON RESTING EEG
Authors: ZHANG JUN-AN , GU LIPING , CHEN YONGQIANG , ZHU GENG , OU LANG , WANG LIYAN , LI XIAOOU , ZHONG LICHANG
Published: March 2022

An important task of brain–computer interface (BCI) research is to read or decode mental content from a large number of electroencephalographic (EEG) signals, which is an exciting, attractive, and challenging goal. In this paper, resting EEG data are collected from spontaneous EEG, and 16 random features such as correlation coefficient, covariance, and brainpower spectrum are extracted as reference vectors. In the subsequent emotion recognition experiment, the same feature information is extracted and separated from the EEG signal, and the translation and normalization processing are carried out based on the resting-state features. Finally, with the machine learning methods such as [Formula: see text]-means clustering and multi-feature fusion, the positive, negative, and neutral emotional characteristic parameters were correctly separated. In a group of 12 subjects, the correct recognition rate of visual evoked positive, negative, and neutral emotions reached 83.9%, which was better than the literature mentioned in this paper. Another highlight of this method is that it can quickly, accurately, and efficiently select the number of features with the best matching and the least resource consumption from multiple features and multiple potential acquisition points. Further analysis and comparison of EEG characteristics can find the relationship between specific stimuli and corresponding EEG characteristic signals.
Dynamical decoupling and NNN discrete quantum networks
Authors: Hoskovec Antonín , Jex Igor
Published: March 2022

Perfect State Transfer is known to be possible on complex next-to-nearest-neighbor structures of qubits. The complexity of these networks coupled with the pervasive imperfections of the real world can lead to shortcomings in their practical construction. We analyze several realistic categories of flaws in the networks and show that they can have a harsh effect on the network’s performance. Dynamical decoupling is a known quantum error correction algorithm that can be used for partial or complete mitigation of undesired artefacts in quantum systems. We show here that dynamical decoupling can, in principle, also be used to stabilize the complex next-to-nearest-neighbor networks of qubits. We compare the proposed dynamical decoupling schemes with a baseline of dynamical decoupling scheme that eliminates all but one path to quantum state transfer on the network, thus effectively transforming it to a nearest-neighbor chain.
A Machine Learning-Based Approach for the Design of Lower Limb Exoskeleton
Authors: Varma V. S. , Rao R. Yogeshwar , Vundavilli P. R. , Pandit M. K. , Budarapu P. R.
Published: March 2022

Active Exoskeletons can become a powerful tool for therapists for the rehabilitation of patients suffering from neurophysiological conditions. The mathematical modeling for estimating joint moments required for human walking movement proves difficult due to the high number of degrees of freedom (DoF) and the complexity of movement. Another factor that poses a problem is the unavailability of ground reaction force (GRF) data, which must be present as the external applied forces in the model. This paper presents a machine learning-based approach for predicting joint moments for walking that uses only the kinematic data of the subjects. The dataset used includes data available from published sources as well as data collected by the authors. The predictions have been compared with and validated using the joint moment results from optimization-based inverse dynamics model in OpenSim. Subsequently, a concept design of a lower limb exoskeleton has been presented and actuator requirements for the same are set according to the joint moment predictions for a specific human subject. The prototype design includes eight rotational degrees of freedom (DOF) in total, i.e., four degrees of freedom per leg: two at the hip joint, one at the knee joint and one at the ankle joint. The feasibility study of the prototype has been carried out with the help of finite element analysis (FEA) in Ansys software after utilizing the weight of the human being and joint rotations as inputs to the model. Based on the results obtained from the FEM, the design has been optimized to ensure structural stability.
Molybdenum Disulfide Nanoparticles Coated with Silver Nanoparticles for Low-Toxicity and Dual Photothermal–Chemical Antibacterial Activity
Authors: Zheng Lei , Xu Di , Zhang Dongdong
Published: March 2022

In this paper, a simple method has been used to synthesize silver-molybdenum disulfide nanoparticles (Ag-MoS2NPs) with photothermal and physical inhibition of bacteria. The MoS2nanocarriers were obtained by an environment-friendly liquid-phase separation method. The coated Ag NPs with high antibacterial activity and fluorescence property endowed the synthesized Ag-MoS2NPs with the ability to be traced. The Ag-MoS2NPs had photothermal properties with a maximum photothermal increase of [Formula: see text]C. The results of the dual photothermal–chemical antibacterial activity using Ag-MoS2NP carriers showed that Ag-MoS2NPs had broad-spectrum inhibition activity with MIC values up to [Formula: see text][Formula: see text][Formula: see text]g/mL against Escherichia coli. The Ag-MoS2NPs were also used to destroy cell integrity by disrupting cell membranes and cell walls to achieve the inhibition of cell survival. The toxicity test in mice demonstrated the nontoxicity of Ag-MoS2NPs. Ag-MoS2NPs were studied for dual photothermal–chemical antibacterial activity, and the material reduced the amount of Ag NPs used, resulting in lower biotoxicity, hence providing a possible avenue for the clinical application of Ag NPs.
ICA-Unet: An improved U-net network for brown adipose tissue segmentation
Authors: Wang Haolin , Wang Zhonghao , Wang Jingle , Li Kang , Geng Guohua , Kang Fei , Cao Xin
Published: March 2022

Brown adipose tissue (BAT) is a kind of adipose tissue engaging in thermoregulatory thermogenesis, metaboloregulatory thermogenesis, and secretory. Current studies have revealed that BAT activity is negatively correlated with adult body weight and is considered a target tissue for the treatment of obesity and other metabolic-related diseases. Additionally, the activity of BAT presents certain differences between different ages and genders. Clinically, BAT segmentation based on PET/CT data is a reliable method for brown fat research. However, most of the current BAT segmentation methods rely on the experience of doctors. In this paper, an improved U-net network, ICA-Unet, is proposed to achieve automatic and precise segmentation of BAT. First, the traditional 2D convolution layer in the encoder is replaced with a depth-wise over-parameterized convolutional (Do-Conv) layer. Second, the channel attention block is introduced between the double-layer convolution. Finally, the image information entropy (IIE) block is added in the skip connections to strengthen the edge features. Furthermore, the performance of this method is evaluated on the dataset of PET/CT images from 368 patients. The results demonstrate a strong agreement between the automatic segmentation of BAT and manual annotation by experts. The average DICE coefficient (DSC) is 0.9057, and the average Hausdorff distance is 7.2810. Experimental results suggest that the method proposed in this paper can achieve efficient and accurate automatic BAT segmentation and satisfy the clinical requirements of BAT.
GREENPEG – exploration for pegmatite minerals to feed the energy transition: first steps towards the Green Stone Age
Authors: Müller Axel , Reimer Wolfgang , Wall Frances , Williamson Ben , Menuge Julian , Brönner Marco , Haase Claudia , Brauch Klaus , Pohl Claudia , Lima Alexandre , Teodoro Ana , Cardoso-Fernandes Joana , Roda-Robles Encarnación , Harrop John , Smith Kate , Wanke Dietrich , Unterweissacher Thomas , Hopfner Mario , Schröder Mathias , Clifford Brendan , Moutela Paulo , Lloret Carla , Ranza Luigi , Rausa Andrea
Published: April 2022

The GREENPEG project, which is funded by the European Commission Horizon 2020 ‘Climate action, environment, resource efficiency and raw materials’ programme, aims to develop multimethod exploration toolsets for the identification of European, buried, small-scale (0.01–5 million m
3
) pegmatite ore deposits of the Nb–Y–F (NYF) and Li–Cs–Ta (LCT) chemical types. The project is being coordinated by the Natural History Museum of the University of Oslo and involves four exploration services/mining operators, one geological survey, one non-profit helix association of administration, industry and academia, two consulting companies and five academic institutions from eight European countries. The target raw materials are Li, high-purity quartz for silica and metallic Si, ceramic feldspar, rare earth elements, Ta, Be and Cs, which are naturally concentrated in granitic pegmatites. Silicon and Li are two of the most sought-after green technology metals as they are essential for photovoltaics and Li-ion batteries for electric cars, respectively. GREENPEG will change the focus of exploration strategies from large-volume towards small-volume, high-quality ores and overcome the lack of exploration technologies for pegmatite ore deposits by developing toolsets tailored to these ore types. This contribution focuses on the methods applied in the GREENPEG project and as such provides a potential pathway towards the ‘Green Stone Age’ from the perspective of pegmatite-sourced minerals.
Equity and Inclusion through UDL in K-6 Computer Science Education: Perspectives of Teachers and Instructional Coaches
Authors: Israel Maya , Kester Brittany , Williams Jessica J. , Ray Meg J.
Published: March 2022

Through a mixed-methods approach that utilized teacher surveys and a focus group with computer science (CS) instructional coaches, this study examined elementary teachers’ confidence in meeting the needs of students with disabilities, the extent to which the teachers could use the Universal Design for Learning (UDL) framework in CS education, and the strategies that their CS instructional coaches used with them to help meet the needs of all learners, including those with disabilities. Findings from a Wilcoxon signed-rank test and a general linear regression of the teacher surveys revealed that teachers’ confidence in teaching CS and in meeting the needs of students with disabilities increased over the 5 month coaching study, but their understanding of UDL remained low throughout the study. A qualitative thematic analysis of open-response survey questions revealed that the teachers could identify instructional strategies that support the inclusion of students with disabilities in CS instruction. These strategies aligned with high leverage practices (HLPs) and included modeling, the use of explicit instruction, and opportunities for repeated instruction. When asked to identify UDL approaches, however, they had more difficulty. The focus group with coaches revealed that the coaches’ primary aim related broadly to equity and specifically to access to and the quality of CS instruction. However, although they introduced UDL-based strategies, they struggled to systematically incorporate UDL into coaching activities and did not explicitly label these strategies as part of the UDL framework on a consistent basis. This finding explains, to a large extent, the teachers’ limited understanding of UDL in the context of CS education.