bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mobility Prediction of Off-Road Ground Vehicles Using a Dynamic Ensemble of NARX Models
Authors: Liu Yixuan , Barthlow Dakota , Mourelatos Zissimos P. , Zeng Jice , Gorsich David , Singh Amandeep , Hu Zhen 
Published: June 2022

Abstract
Mobility prediction of off-road autonomous ground vehicles (AGV) in uncertain environments is essential for their model-based mission planning, especially in the early design stage. While surrogate modeling methods have been developed to overcome the computational challenge in simulation-based mobility prediction, it is very challenging for a single surrogate model to accurately capture the complicated vehicle dynamics. With a focus on vertical acceleration of an AGV under off-road conditions, this article proposes a surrogate modeling approach for AGV mobility prediction using a dynamic ensemble of nonlinear autoregressive models with exogenous inputs (NARX) over time. Synthetic vehicle mobility data of an AGV are first collected using a limited number of high-fidelity simulations. The data are then partitioned into different segments using a variational Gaussian mixture model to represent different vehicle dynamic behaviors. Based on the partitioned data, multiple surrogate models are constructed under the NARX framework with different numbers of lags. The NARX models are then assembled together dynamically over time to predict the mobility of the AGV under new conditions. A case study demonstrates the advantages of the proposed method over the classical NARX models for AGV mobility prediction.
Zero-Free-Length Elastic System for Gravity Compensation of Parallel Mechanisms With Delta and Delta-Like Architectures
Authors: Jin Lixing , Lai Quanbin , Ma Rui , Zhang Weijun , Duan Xingguang , Li Changsheng 
Published: June 2022

Abstract
Passive gravity compensation can effectively reduce the load of actuators, but existing methods are commonly complex in terms of mechanisms and elastic systems with zero-free-length (ZFL) property. A compensation strategy using all joint information is further developed in this paper, as well as the involved elastic system. This approach with considerable compensation effect is simple in principle, and the ZFL property is precisely and completely realized by commercial springs. Compared with the previous method, the process of spring selection is also greatly simplified. Possible arrangements with approximate compensation are also calculated and discussed to achieve a compromise between the compensation effect and the mechanism complexity. The elastic system for Delta-like is implemented and calibrated as an illustration. The results show that the stiffness error rate is reduced from 23.53% to 3.92% and the compensation effect is improved by 63.36% for full compensation and 24.01% for approximate compensation, respectively.
Nonlinear Temperature Gradient Focusing of Deoxyribose Nucleic Acid in a Microfluidic Channel With Patterned Surface Charges: A Numerical Study
Authors: Dutta Amitava , Santra Apurba Kumar , Ganguly Ranjan 
Published: June 2022

Abstract
We present a numerical analysis of electrophoretic transport of a biological sample, such as, deoxyribose nucleic acid (DNA) via nonlinear temperature gradient within a microfluidic channel having patterned surface charges. The transport of the electrolyte is induced by electroosmotic force by imposing an axial electric field, superposed with the wall electric field via electrodes embedded along the wall of the microchannel. We consider the periodic variation of wall zeta potential in electrokinetic motion of an electrolyte wherein the DNA sample exhibits electrophoretic migration. Temperature dependence of the thermophysical properties of the electrolyte and the electrophoretic mobility and diffusivity of the analyte sample is accounted for in the model to improve its accuracy. Nonlinear longitudinal temperature field along the microchannel is induced via Joule heating by suitably shaping the channel geometry, which enhances the concentration of DNA approximately 270 folds by applying just 500 V DC field with constant zeta potential at the walls. The study further reveals that the concentration of DNA reduces drastically when a periodic wall zeta potential is applied. Results of the study lend to the design of novel electrically actuated bio-microfluidic devices with tunable solute separation and dispersion capabilities.
Simulation of Flow Field of Solution Mining Salt Cavities for Underground Gas Storage
Authors: Wang Jinchao , Wang Zhiming , Zeng Quanshu , Ding Guosheng , Li Kang , Wanyan Qiqi , Wang Yanxi 
Published: June 2022

Abstract
Salt cavern solution mining is a complicated process of fluid dynamics and chemical dynamics, including salt boundary dissolution, cavern expansion, brine flow, and species transport. The reaction processes occur simultaneously and interact with each other. In this study, a multiphysical coupled model is established to evaluate the real-time three-dimensional salt cavern shape expansion, the velocity field, and the brine concentration distribution. Then, the predicted results are compared with the field data of a Jintan Gas Storage Well in China. The average relative deviations with the turbulent flow are 5.7% for outlet brine concentration and 4.0% for cavern volume. The results show that salt cavern can be divided into four regions, including the shock region, plume region, reflow region, and suction region. The results also indicate that the turbulent flow will stimulate the formation of the vortex, thus affecting the distribution of brine concentration. And, the brine concentration distribution primarily influences cavern corrosion. The results suggest that adjusting the inject velocity and the tube position can change the cavern construction rate and the cavern shape. Overall, these results have guiding significance for the design and engineering practice of salt cavern construction for energy storage.
Application of the Equivalent Markov Motion Model in Solving Solid Particle Erosion and Droplet Deposition
Authors: Zhang Ri , Wang Yumiao 
Published: June 2022

Abstract
The equivalent Markov motion model (EMMM) is used to improve the probability model for solid particle erosion and droplet deposition. When calculating the solid particle erosion, the probability density distribution of particle velocity developed by EMMM is used to improve the solution of the impact parameters of solid particles. When calculating the droplet deposition rate of annular flow, the conversion coefficient proposed by EMMM is used to correct the variance of the particle displacement. The proportion of the particles deposited is calculated by solving the probability of a single particle reaching the pipe wall or liquid film. The improved model involving the EMMM is well verified by comparison with experimental data. Compared with the previous probability model, the present model can provide more accurate predictions. In addition, the self-compatibility of the EMMM is discussed in detail.
Composite Imagery-Based Non-Uniform Illumination Sensing for System Health Monitoring of Solar Power Plants
Authors: Arosh Sirshendu , Ghosh Kuntal , Dheer Dharmendra Kumar , Prakash Surya 
Published: June 2022

Abstract
Incidence of non-uniform illumination (NUI) degrades the affected solar photovoltaic modules temporarily. However, in worst case, it may also lead to permanent degradation. Thus, non-uniform illumination sensing in terms of encompassed area over solar photovoltaic module becomes important for sustainable power generation. An integrated framework by combining optical and thermal images for non-uniform illumination sensing and classification (static and dynamic) is proposed. The proposed technique detects hotspots along with identification of the nature of shading on the solar photovoltaic modules. Additionally, Hungarian Kalman filter is implemented for estimating the coverage of the non-uniform illumination-affected region including its abrupt shape. The proposed estimation technique also calculates the total loss in the output energy of the solar photovoltaic system due to non-uniform illumination. Overall, the proposed methodology develops a hybrid imagery-dependent advanced early warning system for large-scale solar power plants which are cost-effective and bypass multi-sensor data fusion to attain real-time application.
Multimodal imaging analysis for the impact of retinal peripheral lesions on central neurovascular structure and retinal function in type 2 diabetes with diabetic retinopathy
Authors: Zhuang Xuenan , Chen Ruoyu , Liang Anyi , Yao Jie , Wang Zicheng , Chen Yesheng , Zheng Kangyan , Lu Peiyao , Zhang Liang , Cao Dan 
Published: June 2022

ObjectivesTo explore the possible role of peripheral lesions (PLs) detected by ultrawide field (UWF) imaging system on central neurovascular structure and retinal function.MethodsNinety-seven diabetic patients were included in this cross-sectional study using UWF pseudocolour colour imaging with Optos Daytona (Optos, PLC). UWF images were graded as with predominantly peripheral lesions (PPLs) and without PPL. Macular neurovascular alterations and retinal function were measured by optical coherence tomography angiography (OCTA) and RETeval device, respectively. Central microcirculation and retinal function were compared between eyes with and without PPL.ResultsThe study evaluated 186 eyes (97 patients; 43 females (44.3%)), including 92 eyes without PPL and 94 eyes with PPL. Central retinal vessel density was comparable between eyes with and without PPL. Delayed implicit time and decreased pupil area ratio were found in the PPL group compared with eyes without PPL, and this difference remained unchanged after adjusting for systemic factors (all p＜0.01).ConclusionsOur study suggests that retinal function is worse in diabetic eyes with PPL. These findings challenged the conventional ETDRS protocols which ignored peripheral retina in determining DR severity. Furthermore, combining UWF imaging with RETeval system to detect more retinal abnormalities may be helpful in DR management.
Perspectives on the production, and use, of rapid evidence in decision making during the COVID-19 pandemic: a qualitative study
Authors: Clyne Barbara , Hynes Lisa , Kirwan Colette , McGeehan Máire , Byrne Paula , Killilea Martha , Smith Susan M. , Ryan Máirín , Collins Claire , O’Neill Michelle , Wallace Emma , Murphy Andrew W , Kelly Maureen E 
Published: June 2022

ObjectivesTo describe perceptions of providing, and using rapid evidence, to support decision making by two national bodies (one public health policy and one front-line clinical practice) during the COVID-19 pandemic.DesignDescriptive qualitative study (March–August 2020): 25 semistructured interviews were conducted, transcribed verbatim and thematically analysed.SettingData were obtained as part of an evaluation of two Irish national projects; the Irish COVID-19 Evidence for General Practitioners project (General Practice (GP) project) which provided relevant evidence to address clinical questions posed by GPs; and the COVID-19 Evidence Synthesis Team (Health Policy project) which produced rapid evidence products at the request of the National Public Health Emergency Team.ParticipantsPurposive sample of 14 evidence providers (EPs: generated and disseminated rapid evidence) and 11 service ssers (SUs: GPs and policy-makers, who used the evidence).Main outcome measuresParticipant perceptions.ResultsThe Policy Project comprised 27 EPs, producing 30 reports across 1432 person-work-days. The GP project comprised 10 members from 3 organisations, meeting 49 times and posting evidence-based answers to 126 questions. Four unique themes were generated. ‘The Work’ highlighted that a structured but flexible organisational approach to producing evidence was essential. Ensuring quality of evidence products was challenging, particularly in the context of absent or poor-quality evidence. ‘The Use’ highlighted that rapid evidence products were considered invaluable to decision making. Trust and credibility of EPs were key, however, communication difficulties were highlighted by SUs (eg, website functionality). ‘The Team’ emphasised that a highly skilled team, working collaboratively, is essential to meeting the substantial workload demands and tight turnaround time. ‘The Future’ highlighted that investing in resources, planning and embedding evidence synthesis support, is crucial to national emergency preparedness.ConclusionsRapid evidence products were considered invaluable to decision making. The credibility of EPs, a close relationship with SUs and having a highly skilled and adaptable team to meet the workload demands were identified as key strengths that optimised the utilisation of rapid evidence.Ethics approvalEthical approval was obtained from the National Research Ethics Committee for COVID-19-related Research, Ireland.
Investing in the health workforce: fiscal space analysis of 20 countries in East and Southern Africa, 2021–2026
Authors: Asamani James Avoka , Kigozi Jesse , Sikapande Brivine , Christmals Christmal Dela , Okoroafor Sunny C , Ismaila Hamza , Ahmat Adam , Nyoni Jennifer , Nabyonga-Orem Juliet , Mwinga Kasonde 
Published: June 2022

Background and objectivesThe health workforce (HWF) is at the core of ensuring an efficient, effective and functional health system, but it faces chronic underinvestment. This paper presents a fiscal space analysis of 20 countries in East and Southern Africa to generate sustained evidence-based advocacy for significant and smarter investment in the HWF.MethodsWe adapted an established empirical framework for fiscal space analysis and applied it to the HWF. Country-specific data were curated and triangulated from publicly available datasets and government reports to model the fiscal space for the HWF for each country. Based on the current knowledge, three scenarios (business as-usual, optimistic and very optimistic) were modelled and compared.FindingsA business-as-usual scenario shows that the cumulative fiscal space across the 20 countries is US$12.179 billion, which would likely increase by 28% to US$15.612 billion by 2026 but varies across countries—the highest proportional increases expected in Seychelles (117%) and Mozambique (69%) but lowest in Zambia (15%). Under optimistic assumptions, allocating an additional 1.5% of gross domestic product (GDP) to health even without further prioritising the proportional allocation to the wage bill could boost the cumulative fiscal space for HWF by US$4.639 billion. In a very optimistic scenario of a 1.5% increase in health expenditure as a proportion of GDP and further prioritisation of HWF within the health expenditure, the cumulative fiscal space for HWF could improve by some 105%—ranging from 24% in Zambia to 330% in Lesotho.ConclusionSmall increments in government health expenditure and increased prioritisation of HWF in funding in tandem with the 57% global average could potentially increase the fiscal space for HWF by at least 32% in 11 countries. Unless the HWF is sufficiently prioritised within the health expenditures, only increasing the overall health expenditure to even recommended levels would still portend severe underinvestment in HWF amid unabating shortages to deliver health services. Thus, HWF strategies and investment plans should include fiscal space analysis to deepen advocacy for sustainable investment in the HWF.
Selective internal radiation therapy (SIRT) for hepatocellular carcinoma (HCC): informing clinical practice for multidisciplinary teams in England
Authors: Reeves Helen L , Reicher John , Priona Georgia , Manas Derek M , Littler Peter 
Published: June 2022

ObjectiveHepatocellular carcinoma (HCC) deaths are rising alarmingly. Many patients are unsuitable for available therapies. Poor response rates further hamper outcomes for those that are. Selective internal radiation therapy (SIRT) offers hope, although which patients benefit over standard approaches remains unclear.Design/methodAs a quality/service improvement, we audited consecutive patients treated with SIRT (2015-2020) by the Newcastle upon Tyne Hospitals National Health Service Foundation Trust HCC multidisciplinary team . Indications, Barcelona clinic liver cancer (BCLC) stage, treatment response, subsequent therapies and survival at 30 September 2021 were assessedResultsFifty-one patients received SIRT. Thirty-day mortality was zero. Three months partial response, stable disease and progressive disease on imaging were 50%, 22% and 28%, respectively. Overall median survival was 21 months. There were four subgroups: (1) BCLC-B: HCC>7 cm too large for transarterial chemoembolisation (TACE) alone (n=21); (2) BCLC-B: HCC progressed post TACE (n=7); (3) BCLC-C: HCC with any combination of large tumour burden, branch portal vein thrombosis, non-hepatitis C virus aetiology (n=16); (4) BCLC-C: sorafenib inappropriate (n=7). In group 1, 5/21 (23.8%) of patients were downstaged to resection, 33% received subsequent medical therapies and median survival was >40 months. In BCLC-B patients treated second line (group 2), median survival was 14.2 months. In BCLC–C, median survival was 20.2 months for group 3 and 4.2 months for group 4.ConclusionSIRT outcomes for advanced HCC, often bridging patients with adverse predictive factors to subsequent surgery or medical therapies, were encouraging. A role after TACE or for BCLC-C patients requires further assessment.
Prediction models of diabetes complications: a scoping review
Authors: Ndjaboue Ruth , Ngueta Gérard , Rochefort-Brihay Charlotte , Delorme Sasha , Guay Daniel , Ivers Noah , Shah Baiju R , Straus Sharon E , Yu Catherine , Comeau Sandrine , Farhat Imen , Racine Charles , Drescher Olivia , Witteman Holly O 
Published: June 2022

BackgroundDiabetes often places a large burden on people with diabetes (hereafter ‘patients’) and the society, that is, in part attributable to its complications. However, evidence from models predicting diabetes complications in patients remains unclear. With the collaboration of patient partners, we aimed to describe existing prediction models of physical and mental health complications of diabetes.MethodsBuilding on existing frameworks, we systematically searched for studies in Ovid-Medline and Embase. We included studies describing prognostic prediction models that used data from patients with pre-diabetes or any type of diabetes, published between 2000 and 2020. Independent reviewers screened articles, extracted data and narratively synthesised findings using established reporting standards.ResultsOverall, 78 studies reported 260 risk prediction models of cardiovascular complications (n=42 studies), mortality (n=16), kidney complications (n=14), eye complications (n=10), hypoglycaemia (n=8), nerve complications (n=3), cancer (n=2), fracture (n=2) and dementia (n=1). Prevalent complications deemed important by patients such as amputation and mental health were poorly or not at all represented. Studies primarily analysed data from older people with type 2 diabetes (n=54), with little focus on pre-diabetes (n=0), type 1 diabetes (n=8), younger (n=1) and racialised people (n=10). Per complication, predictors vary substantially between models. Studies with details of calibration and discrimination mostly exhibited good model performance.ConclusionThis rigorous knowledge synthesis provides evidence of gaps in the landscape of diabetes complication prediction models. Future studies should address unmet needs for analyses of complications n> and among patient groups currently under-represented in the literature and should consistently report relevant statistics.Scoping review registrationhttps://osf.io/fjubt/
Interpretations of the new LHCb $$P_c(4337)^+$$ pentaquark state
Authors: Yan Mao-Jun , Peng Fang-Zheng , Sánchez Mario Sánchez , Valderrama Manuel Pavon 
Published: June 2022

AbstractRecently the LHCb Collaboration has observed a new pentaquark state, the $$P_c(4337)^+$$

P
c

(
4337
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+

. Owing to its proximity to the $$\chi _{c0}(1S) p$$

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(
1
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)

p

, $${\bar{D}}^* \varLambda _c$$

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∗

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, $${\bar{D}} \varSigma _c$$

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and $${\bar{D}} \varSigma _c^*$$

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c
∗

thresholds, this new pentaquark might very well be a meson–baryon bound state. However its spin and parity have not been determined yet and none of the previous possibilities can be ruled out.We briefly explore a few of these options and the consequences they entail in the present manuscript: (i) the $$P_c(4337)^+$$

P
c

(
4337
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+

might be a $$\chi _{c0}(1S) p$$

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c
0

(
1
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)

p

bound state, (ii) the $$P_c(4312)^+$$

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c

(
4312
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+

and $$P_c(4337)^+$$

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c

(
4337
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+

might be $${\bar{D}}^* \varLambda _c$$

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∗

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and $${\bar{D}} \varSigma _c$$

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states close to threshold, respectively, where the Breit–Wigner mass might not correspond to the location of the poles, (iii) the locations of the $$P_c(4312)^+$$

P
c

(
4312
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+

and $$P_c(4337)^+$$

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c

(
4337
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might be explained in terms of the $${\bar{D}}^* \varLambda _c$$

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∗

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-$${\bar{D}} \varSigma _c$$

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and $${\bar{D}}^* \varLambda _c$$

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-$${\bar{D}} \varSigma _c^*$$

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coupled channel dynamics. This last option, though not the most probable explanation, is still potentially compatible with the double peak solution of the $$P_{cs}(4459)^0$$

P

cs

(
4459
)

0

and with what we know of the $$P_c(4312)^+$$

P
c

(
4312
)

+

. As a byproduct of the previous explorations, we conjecture the existence of a series of anticharmed meson – antitriplet charmed baryon bound states and calculate their masses.
Rolling bearing fault diagnosis based on quantum LS-SVM
Authors: Li Yuanyuan , Song Liyuan , Sun Qichun , Xu Hua , Li Xiaogang , Fang Zhijun , Yao Wei 
Published: June 2022

AbstractRolling bearing is an indispensable part of the contemporary industrial system, and its working conditions affect the state of the entire industrial system. Therefore, there is great engineering value to researching and improving the fault diagnosis technology of rolling bearings. However, with the involvement of the whole mechanical equipment, we need to have a large quantity of data to support the accuracy of fault diagnosis, while the efficiency of classical machine learning algorithms is poor in processing big data, and huge amount of computing resources is required. To solve this problem, this paper combines the HHL algorithm in quantum computing with the LS-SVM algorithm in machine learning and proposes a fault diagnosis model based on a quantum least square support vector machine (QSVM). Based on experiments simulated on analog quantum computers, we demonstrate that our fault diagnosis based on QSVM is feasible, and it can play a far superior advantage over the classical algorithm in the context of big data.