bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing the impact of COVID-19 pandemic on ambulance transports for self-harm: a population-based study in Osaka Prefecture, Japan
Authors: Nakao Shunichiro , Katayama Yusuke , Kitamura Tetsuhisa , Tanaka Kenta , Hirose Tomoya , Tachino Jotaro , Iwami Taku , Masui Jun , Domi Hisaya , Shimazu Takeshi , Oda Jun , Matsuoka Tetsuya 
Published: September 2023

ObjectivesThe COVID-19 pandemic might have affected emergency medical services transports for self-harm in Japan. However, the available data are insufficient to fully understand the pandemic’s impact on ambulance transports due to self-harm. This study aimed to investigate the change in the incidence of ambulance transports for self-harm from 2018 to 2021 and to identify vulnerable age groups during the pandemic.DesignA population-based observational study using a database from the Osaka Prefectural Government.SettingThe database covers the entire area of Osaka Prefecture and included information on ambulance transports and hospital details.ParticipantsAmbulance transport of patients due to self-harm from 2018 through 2021 was investigated.Primary outcome measuresThe primary outcome was the incidence of ambulance transport for self-harm.ResultsWe analysed 10 843 patients. Their median age was 38 years, and 69.0% were female. We observed an increasing trend of the incidence rate in cases per 100 000 population per year from 29.4 in 2018 to 31.2 in 2021. However, after adjusting for age group, sex and month, there was no difference in the incidence of ambulance transport due to self-harm in 2019 (adjusted incidence rate ratio (aIRR) 1.007; 95% CI 0.955 to 1.063), 2020 (aIRR 1.041; 95% CI 0.987 to 1.098) and 2021 (aIRR 1.022; 95% CI 0.968 to 1.078), compared with 2018. We observed no difference in 21-day mortality from 2018 through 2021. In the age group of 20–29 years, despite no difference in 2019 compared with 2018, we found an 11.7% increase in the incidence of ambulance transport due to self-harm in 2020 (aIRR 1.117; 95% CI 1.002 to 1.245) and no difference in 2021.ConclusionsThere was no difference in the incidence of ambulance transport due to self-harm and 21-day mortality from 2018 through 2021. However, the incidence rate of ambulance transport due to self-harm in 2020 increased in the age group of 20–29 years.
Intervention to reduce sedentary behaviour and improve outcomes after stroke (Get Set Go): a study protocol for the process evaluation of a pilot cluster randomised controlled trial (RECREATE)
Authors: Johansson Jessica Faye , Shannon Rosie , Mossabir Rahena , Airlie Jennifer , Ozer Seline , Moreau Lauren A , Farrin Amanda , Mead Gillian , English Coralie , Fitzsimons Claire F , Clarke David J , Forster Anne 
Published: September 2023

IntroductionStroke survivors spend long periods of time engaging in sedentary behaviour (SB) even when their functional recovery is good. In the RECREATE programme, an intervention aimed at reducing SB (‘Get Set Go’) will be implemented and evaluated in a pragmatic external pilot cluster randomised controlled trial with embedded process and economic evaluations. We report the protocol for the process evaluation which will address the following objectives: (1) describe and clarify causal assumptions about the intervention, and its mechanisms of impact; (2) assess implementation fidelity; (3) explore views, perceptions and acceptability of the intervention to staff, stroke survivors and their carers; (4) establish the contextual factors that influence implementation, intervention mechanisms and outcomes.Methods and analysisThis pilot trial will be conducted in 15 UK-based National Health Service stroke services. This process evaluation study, underpinned by the Medical Research Council guidance, will be undertaken in six of the randomised services (four intervention, two control). Data collection includes the following: observations of staff training sessions, non-participant observations in inpatient and community settings, semi-structured interviews with staff, patients and carers, and documentary analysis of key intervention components. Additional quantitative implementation data will be collected in all sites. Training observations and documentary analysis data will be summarised, with other observational and interview data analysed using thematic analysis. Relevant theories will be used to interpret the findings, including the theoretical domains framework, normalisation process theory and the theoretical framework of acceptability. Anticipated outputs include the following: recommendations for intervention refinements (both content and implementation); a revised implementation plan and a refined logic model.Ethics and disseminationThe study was approved by Yorkshire & The Humber - Bradford Leeds Research Ethics Committee (REC reference: 19/YH/0403). Findings will be disseminated via peer review publications, and national and international conference presentations.Trial registration numberISRCTN82280581.
Understanding polysubstance use at the daily and event levels: protocol for a mixed-methods qualitative and ecological momentary assessment study in a community-based sample of people who use illicit drugs in Oakland, California, USA
Authors: Lorvick Jennifer , Hemberg Jordana , George Madeleine J , Piontak Joy , Comfort Megan L 
Published: September 2023

IntroductionPolysubstance use is extremely common among people who use illicit opioids in the USA. It is associated with poor substance use treatment outcomes, infectious disease risk and alarming rates of drug overdose. Nearly all extant literature examines polysubstance use over broad time frames, such as 30 days or 6 months. However, both substance use and overdose risk are episodic. To build a stronger understanding of polysubstance use and overdose risk, we need to expand the knowledge base to include daily-level and event-level data that examine how substances are used together, in which combinations and in which contexts. The study described in this protocol will use qualitative and ecological momentary assessment (EMA) methods to examine polysubstance use and overdose risk on a daily and event level.Methods and analysisThis is a mixed-methods observational study with three phases. The first phase is formative, consisting of qualitative interviews with people who use multiple substances (N=20), to inform the development of items for the EMA component. The second phase is EMA data collection with people who use multiple substances (N=120), three times daily for 28 days. The third phase consists of mixed-methods inquiries with a subset of participants (N=20), using participant-level EMA data and qualitative techniques to build a nuanced understanding of the motivations and contexts of polysubstance use in everyday life. Analytical induction methods will be used to interpret qualitative data. Hierarchical linear modelling methods will be used to analyse EMA data.Ethics and disseminationThis research has been reviewed and approved by the Institutional Review Board at RTI International (#MOD00001782 for EMA procedures and #MOD00001241 for qualitative procedures). Participants engage in an informed consent procedure for each component of the study. Data will be managed and shared per the National Institutes of Health extramural data sharing policy.
Mortality and failure-to-rescue major complication trends after lung cancer surgery between 2005 and 2020: a nationwide population-based study
Authors: Bernard Alain , Cottenet Jonathan , Pagès Pierre-Benoit , Quantin Catherine 
Published: September 2023

ObjectivesTo estimate the evolution of quality indicators (30-day mortality and failure-to-rescue) inpatients who underwent lung cancer surgery in France over the past 15 years and to study the potential influencing factors.DesignRetrospective cohort study using data from the French hospital database (PMSI).SettingNationwide population-based study.ParticipantsAll patients who underwent pulmonary resection for lung cancer in France (2005–2020) were included (N=1 57 566). Characteristics of patients (age, gender, comorbidities), surgery (surgical approach, type of resection, extent of resection) and hospital (type of hospital, hospital volume for pulmonary resections) were retrieved.Primary and secondary outcome measuresWe studied two outcome indicators: 30-day mortality and failure-to-rescue. We used regression-based techniques (including interrupted time-series) to assess the effects of patient and hospital characteristics on 30-day mortality and failure-to-rescue (number of deaths among patients with at least one major postoperative complication within the 30 days after surgery), adjusting for case mix.ResultsThe 30-day mortality rate increased from 3.8% in 2005 to 4.9% in 2010 and then decreased to 2.9% in 2020. The failure-to-rescue rate decreased from 12.2% in 2005 to 7.1% in 2020. The pneumonectomy rate decreased significantly over time (18.1% in 2005 to 4.8% in 2020) and had the greatest contribution on the reduction of mortality between two periods (2005–2010/2015–2020). The use of video-assisted thoracoscopic surgery or robot-assisted surgery had a great influence on the reduction of mortality (16% of the observed difference in mortality) between the two periods, as did hospital volume.ConclusionsThe change in surgical practices, particularly the reduction in pneumonectomies, could be one of the main reasons for reduction in postoperative mortality and failure-to-rescue in France since 2011. Hospital volume is another important factor in reducing postoperative mortality. Our study should encourage the use of technological or organisational innovation, such as changes in surgical practice and cancer surgery authorisations, to improve quality of care.
Factors associated with racial and ethnic disparities in chronic pain after acute traumatic injury
Authors: Jacoby Sara F , Wong Eunice C , Schell Terry L , Powers Mark B , Warren Ann Marie , Richmond Therese S 
Published: September 2023

BackgroundChronic pain represents a substantial health burden and source of disability following traumatic injury. This study investigates factors associated with racial and ethnic disparities in chronic pain.MethodsProspective, longitudinal, panel study. Seriously injured patients were recruited from two trauma centres in the Northeastern and Southwestern USA. Data from medical records and individual surveys were collected in-hospital, and at 3-month and 12-month postinjury from a balanced cohort of non-Hispanic black, non-Hispanic white and Hispanic patients. We used linear regression to estimate the associations between race and ethnicity and 3-month and 12-month pain severity outcomes. We grouped all available cohort data on factors that theoretically influence the emergence of chronic pain after injury into five temporally ordered clusters and entered each cluster sequentially into regression models. These included: participant race and ethnicity, other demographic characteristics, preinjury health characteristics, acute injury characteristics and postinjury treatment.Results650 participants enrolled (Hispanic 25.6%; white 38.1%; black 33.4%). Black participants reported highest relative chronic pain severity. Injury-related factors at the time of acute hospitalisation (injury severity, mechanism, baseline pain and length of stay) were most strongly associated with racial and ethnic disparities in chronic pain outcomes. After controlling for all available explanatory factors, a substantial proportion of the racial and ethnic disparities in chronic pain outcomes remained.ConclusionRacial and ethnic disparities in chronic pain outcomes may be most influenced by differences in the characteristics of acute injuries, when compared with demographic characteristics and postacute treatment in the year after hospitalisation.
Patients with cancer and hospital admissions: disease trajectory and strategic choices
Authors: Numico Gianmauro , Ferrua Rachele , Fea Elena , Giamello Jacopo , Colantonio Ida , Occelli Marcella , Vandone Anna Maria , Vanella Paola , Aimar Giacomo , Pisano Chiara , Parlagreco Elena , Persano Irene , Milanesio Michela , Ippoliti Roberto 
Published: September 2023

ObjectivesHospital admission (HA) in cancer history is a common, repeated and frequently unplanned event. The emergency departments (EDs) and the oncological outpatient service (OOS) are the ordinary way of entry. We studied the reasons of admission, pathways of access and discharge and prognostic factors in a population of admitted patients with cancer.MethodsThe health records of the admitted patients in the oncological ward of a referral hospital in a 6-month period were retrieved and analysed. The characteristics of those admitted in the last 3 months of life were compared with the other group.ResultsAmong the 147 HA, 79.5% were unplanned, 48.9% passing through the ED and 30.6% through the OOS; 56.5% were due to cancer-related symptoms; 50.3% occurred in the last 3 months of life. Median overall survival was 90 days (95% IC 53.1–126.9). Independent prognostic factors for survival were: being admitted for symptoms, referral through the ED and not being discharged at home.ConclusionsHospital is a turning point in the cancer care pathway. Patients needing HA have a dismal prognosis, half of them being in the last 3 months of life. This group can be identified using universally available variables.
Rationale and design of the GOLDEN BRIDGE II: a cluster-randomised multifaceted intervention trial of an artificial intelligence-based cerebrovascular disease clinical decision support system to improve stroke outcomes and care quality in China
Authors: Li Zixiao , Zhang Xinmiao , Ding Lingling , Jing Jing , Gu Hong-Qiu , Jiang Yong , Meng Xia , Du Chunying , Wang Chunjuan , Wang Meng , Xu Man , Zhang Yanxu , Hu Meera , Li Hao , Gong Xiping , Dong Kehui , Zhao Xingquan , Wang Yilong , Liu Liping , Xian Ying , Peterson Eric , Fonarow Gregg C , Schwamm Lee H , Wang Yongjun 
Published: September 2023

BackgroundGiven the swift advancements in artificial intelligence (AI), the utilisation of AI-based clinical decision support systems (AI-CDSSs) has become increasingly prevalent in the medical domain, particularly in the management of cerebrovascular disease.AimsTo describe the design, rationale and methods of a cluster-randomised multifaceted intervention trial aimed at investigating the effect of cerebrovascular disease AI-CDSS on the clinical outcomes of patients who had a stroke and on stroke care quality.DesignThe GOLDEN BRIDGE II trial is a multicentre, open-label, cluster-randomised multifaceted intervention study. A total of 80 hospitals in China were randomly assigned to the AI-CDSS intervention group or the control group. For eligible participants with acute ischaemic stroke in the AI-CDSS intervention group, cerebrovascular disease AI-CDSS will provide AI-assisted imaging analysis, auxiliary stroke aetiology and pathogenesis analysis, and guideline-based treatment recommendations. In the control group, patients will receive the usual care. The primary outcome is the occurrence of new vascular events (composite of ischaemic stroke, haemorrhagic stroke, myocardial infarction or vascular death) at 3 months after stroke onset. The sample size was estimated to be 21 689 with a 26% relative reduction in the incidence of new composite vascular events at 3 months by using multiple quality-improving interventions provided by AI-CDSS. All analyses will be performed according to the intention-to-treat principle and accounted for clustering using generalised estimating equations.ConclusionsOnce the effectiveness is verified, the cerebrovascular disease AI-CDSS could improve stroke care and outcomes in China.Trial registration numberNCT04524624.
Pulsar timing array observations as possible hints for nonsingular cosmology
Authors: Zhu Mian , Ye Gen , Cai Yong 
Published: September 2023

AbstractRecent pulsar timing array (PTA) experiments have reported strong evidence of the stochastic gravitational wave background (SGWB). If interpreted as primordial gravitational waves (GWs), the signal favors a strongly blue-tilted spectrum. Consequently, the nonsingular cosmology, which is able to predict a strongly blue-tilted GW spectrum with$$n_T \simeq 2$$nT≃2on certain scales, offers a potential explanation for the observed SGWB signal. In this paper, we present a Genesis-inflation model capable of explaining the SGWB signal observed by the PTA collaborations while also overcoming the initial singularity problem associated with the inflationary cosmology. Furthermore, our model predicts distinctive features in the SGWB spectrum, which might be examined by forthcoming space-based gravitational wave experiments.
Blandford–Znajek process in Einsteinian cubic gravity
Authors: Peng Jun , Feng Xing-Hui 
Published: September 2023

AbstractIn this paper, we investigate the Blandford–Znajek (BZ) process within the framework of Einsteinian cubic gravity (ECG). To analytically study the BZ process using the split monopole configuration, we construct a slowly rotating black hole in ECG up to cubic order in small spin, considering the leading order in small coupling constant of higher curvature terms. By deriving the magnetosphere solution around the black hole, we determine the BZ power up to the second relative order in spin. The BZ power is modified by the coupling constant compared to Kerr black hole case. Although the general nature of the BZ process in ECG remains unchanged at the leading order in spin, the coupling constant introduces modification at the second relative order in spin. Therefore, we anticipate that it is feasible to discern general relativity from higher derivative gravities by examining the BZ power in rapidly rotating black holes.
Hidden charmonium decays of $$\psi (nS)$$ through charmed meson loops
Authors: Liu Shidong , Cai Zuxin , Zheng Yuanxin , Li Gang 
Published: September 2023

AbstractWe calculated transitions of the higher radial excited charmonia $$ \psi (nS) ~ ( n=3,4,5 )$$

ψ
(
n
S
)

(
n
=
3
,
4
,
5
)

to the orbital excited charmonium $$ h_c(1P) $$

h
c

(
1
P
)

with emission of one pion or eta meson. In calculations, the intermediate S- and P-wave charmed meson loops were considered in terms of the nonrelativistic effective field theory. The results indicate that the transitions of interest are dominated by the loops involving the $$ s_l^P=(1/2)^+ $$

s
l
P

=

(
1
/
2
)

+

charmed mesons, whereas the $$ s_l^P=(1/2)^- $$

s
l
P

=

(
1
/
2
)

-

charmed meson loops are of minor contributions. The partial decay widths of $$ \psi (nS) \rightarrow h_c \pi ^0 $$

ψ

(
n
S
)

→

h
c

π
0

are of the order of 0.01–1 keV. For the case of $$ \psi (nS) \rightarrow h_c \eta $$

ψ

(
n
S
)

→

h
c

η

, the partial decay widths are from 0.1 to 100 keV, implying the branching ratios from $$ 10^{-5} $$

10

-
5

to $$ 10^{-3} $$

10

-
3

. Moreover, the partial decay widths for $$ \psi (nS) \rightarrow h_c \eta $$

ψ

(
n
S
)

→

h
c

η

are found to decrease as the $$ \eta $$
η
-$$ \eta ' $$

η
′

mixing angle increases. It is hoped that the present calculated results would be observed in the future experiments.
FRACTIONAL MODEL OF BRINKMAN-TYPE NANOFLUID FLOW WITH FRACTIONAL ORDER FOURIER’S AND FICK’S LAWS
Authors: MURTAZA SAQIB , KUMAM POOM , AHMAD ZUBAIR , SITTHITHAKERNGKIET KANOKWAN , SUTTHIBUTPONG THANA 
Published: September 2023

Nanofluids are used to achieve maximum thermal performance with the smallest concentration of nanoparticles and stable suspension in conventional fluids. The effectiveness of nanofluids in convection processes is significantly influenced by their increased thermophysical characteristics. Based on the characteristics of nanofluids, this study examines generalized Brinkman-type nanofluid flow in a vertical channel. Three different types of ultrafine solid nanoparticles such as GO, [Formula: see text], and [Formula: see text] are dispersed uniformly in regular water to form nanofluid. Partial differential equations (PDEs) are used to model the phenomena. Fick’s and Fourier’s laws of fractional order were then used to formulate the generalized mathematical model. The exact solution of the generalized mathematical model has been obtained by the joint use of Fourier sine and the Laplace transform (LT) techniques. The obtained solution is represented in Mittag-Leffler function. To analyze the behavior of fluid flow, heat and mass distribution in fluid, the obtained solution was computed numerically and then plotted in response to different physical parameters. It is worth noting from the analysis that the heat transfer efficiency of regular water has been improved by 25% by using GO nanoparticles, 23.98% by using [Formula: see text], and 20.88% by using [Formula: see text].
IntelligentFaceNet: Designing a multi-cascaded attentive and adaptive deep learning network for facial recognition using heuristic approach
Authors: Manoharan Giriprasad 
Published: September 2023

One of the significant application of robot vision technique that serves in biometric verification systems is Face Recognition (FR) technology. However, the effectiveness of the model is affected by disturbance from the real-world environment, including alterations in lighting, facial occlusion, and fluctuation in poses. Even though the recognition of faces has gained popularity due to the variety of applications, it still remains a complicated task to recognize because of an enormous variety of biometric data features. In the past few years, FR technology has seen a lot of development in this area of biometric and computer vision-oriented applications. The most important steps in creating an accurate FR system are the extraction of features and the categorization of these extracted features. The conventional method of feature extraction includes frequency domain features or the Eigenface technique. However, they are not robust to altering external factors like occlusion, illumination, and posture. Using deep learning techniques, a unique approach to address this problem in FR is suggested to recognize faces successfully. The images are aggregated in the initial phase. It is then uploaded to the Viola–Jones Face Detector tools to find the face. The detected face images are then subjected to the Adaptive Deep Convolutional Generative Adversarial Network (ADCGAN) to remove the occlusion from the facial images, where the parameters are subsequently optimized using the Modified Random Variable-based Galactic Swarm Optimizations (MRV-GSO) algorithm. The occlusion-removed face images are then given to the Multi-Cascaded Attentive and Adaptive Deep Learning Network (MCADN) model, where the outputs from the Dilated DenseNet and Residual Network (ResNet) are serially passed to the Bidirectional Long-Short Term Memory (Bi-LSTM) model forming the MCDAN. The MRV-GSO algorithm is performed to tune the hyperparameters in the MCADN model to produce the final recognized facial images. As a result of conducting several experimental studies, it is proved that the generated model outperformed standard approaches in terms of effective recognition rate.
Lower bound estimation for a family of high-dimensional sparse covariance matrices
Authors: Li Huimin , Liu Youming 
Published: September 2023

Lower bound estimation plays an important role for establishing the minimax risk. A key step in lower bound estimation is deriving a lower bound of the affinity between two probability measures. This paper provides a simple method to estimate the affinity between mixture probability measures. Then we apply the lower bound of the affinity to establish the minimax lower bound for a family of sparse covariance matrices, which contains Cai–Ren–Zhou’s theorem in [T. Cai, Z. Ren and H. Zhou, Estimating structured high-dimensional covariance and precision matrices: Optimal rates and adaptive estimation, Electron. J. Stat. 10(1) (2016) 1–59] as a special example.