bluuebunny/crossref_metadata_2025_split huggingface dataset:
The hemodynamic characteristics of severe chronic lung disease referred for lung transplantation
Authors: Ling Wood H. I. , Wong Chi F. , Yan See W. , Fan Yue Y. K. , Wong Ka L. 
Published: April 2022

AbstractSevere pulmonary hypertension (PH) is not common even in patients with severe chronic lung disease (CLD) but data on hemodynamic characteristics among patients with severe CLD is scarce. All adult patients who had right heart catheterization for lung transplant assessment for severe CLD in the only lung transplant service and for PAH management in the only tertiary pulmonary hypertension service in Hong Kong from 2010 to 2020 were included and classified into CLD group and PAH group. Patient characteristics and hemodynamic parameters were analyzed. There were 153 patients included with 106 patients in the CLD group and 47 in the PAH group. There were only 19.8% of the patients in the CLD group had severe pulmonary hypertension. Patients in the CLD group had significantly lower systolic pulmonary arterial pressure (PAPs), lower mean pulmonary arterial pressure (PAPm), higher cardiac index, and lower PVR when compared with the PAH group (p < 0.001). The area under curve (AUC) of PAPs, PAPm, and PVR were excellent, 0.973, 0.970, and 0.938, respectively for discrimination between CLD and PAH on receiver operator characteristics curve analysis. Optimal cutoff values were 55.5 mmHg, 35.5 mmHg, and 6.1 Wood Units for PAPs, PAPm, and PVR with Youden Index 0.85, 0.80, and 0.82, respectively. There were distinct hemodynamic characteristics between the CLD group and the PAH group. Systolic pulmonary arterial pressure, mean pulmonary arterial pressure, and pulmonary vascular resistance are useful to discriminate between the phenotype of severe CLD and PAH.
Predictor‐based bipartite time‐varying formation control of nonlinear multi‐agents systems via disturbance observer
Authors: Yang Yang , Chen Didi , Liu Qidong , Yue Dong 
Published: April 2022

AbstractFormation control is one of critical control issues in multi‐agent systems (MASs). In this article, we extend the traditional formation to a bipartite one in a structurally balanced signed graph and propose a bipartite formation control strategy for an MAS with unknown external disturbances and nonsymmetric input saturation constraints. Neural networks (NNs) are developed to approximate followers' dynamics, and their transient performance are improved by prediction errors. On this basis, an NN‐based nonlinear disturbance observer (NDO) is constructed to estimate generalized disturbances including external disturbances and NNs approximation errors. In order to reduce the number of learning parameters, a normalization method is introduced for NNs weights and applied to the proposed NDO. An auxiliary system is constructed to compensate for asymmetric input saturation, and it is not required to access unknown control gains. The stability analysis is presented, and it is proven that all signals in the MAS are bounded. A numerical simulation and a team of quadrotors examples corroborate the effectiveness and feasibility of the strategy.
An LMIs‐based back‐stepping sliding mode control framework for robust velocity tracking of the automatic driving vehicle on sloped roads
Authors: Chen Zhiqiang , Cao Haotian , Zhao Song , Li Mingjun , Yi Binlin , Guo Wenfeng , Song Xiaolin 
Published: April 2022

AbstractAutomatic driving has received a broad of attention from academia and industry since it is effective in greatly reducing the severity of potential traffic accidents and achieving the ultimate automobile safety and comfort. This article presents a back‐stepping sliding mode controller (BSMC) through linear matrix inequalities (LMIs) for the highly automatic driving vehicle on sloped roads. It includes three key modules, namely, an extended Kalman filter (EKF)‐based road slope estimation module, a robust BSMC‐LMIs velocity‐tracking controller based on the input–output feedback linearization, as well as a longitudinal inverse vehicle dynamics module. The nonlinear combined slip tire model with the transient behavior is introduced to calculate the tire forces properly, which would be further proven to offer more accurate road slope estimations even in a fierce acceleration or deceleration situation. The proposed BSMC‐LMIs controller for velocity tracking can handle the lumped uncertainties which include the modeling error, the parameter perturbation, external disturbances, and noises, and guarantee the reachability of the sliding surface, meanwhile, alleviating the chattering phenomenon inherited from the sliding mode structure. Besides, a sufficient condition for the existence of the proposed BSMC is derived by using the LMIs, which ensures the asymptotical stability on the sliding surface. Finally, the robustness, feasibility, and effectiveness of the proposed BSMC‐LMIs controller for velocity‐tracking are verified by simulation tests in various working scenarios, which shows satisfying results when dealing with the lumped uncertainties on sloped roads. Moreover, the comparative study also shows that the proposed BSMC‐LMIs controller has the best tracking performance when compared to the model predictive control, conventional sliding mode control, and the cubic proportional‐integral controller.
High‐Efficiency Poly(Vinylidene Fluoride‐Co‐Hexafluoropropylene) Loaded 3D Marigold Flower‐Like Bismuth Tungstate Triboelectric Films for Mechanical Energy Harvesting and Sensing Applications
Authors: Manchi Punnarao , Graham Sontyana Adonijah , Patnam Harishkumarreddy , Paranjape Mandar Vasant , Yu Jae Su 
Published: April 2022

AbstractTriboelectric nanogenerators (TENGs) are one of the most trending energy harvesting devices because of their efficient and simple mechanism in harvesting mechanical energy from the environment into electricity. Herein, ferroelectric and dielectric bismuth tungstate (Bi2WO6 (BWO)) with a marigold flower‐like structure is prepared via a hydrothermal method, which is embedded in poly(vinylidene fluoride‐co‐hexafluoropropylene) (PVDF‐HFP), forming a PVDF‐HFP/BWO composite polymer film (CPF) to fabricate TENGs. Generally, the ferroelectric materials exhibit a large piezoelectric coefficient, high electrostatic dipole moment, and high dielectric constant. The prepared PVDF‐HFP/BWO CPF reveals a high polar crystalline β‐phase which leads to enhanced piezoelectric and ferroelectric properties of the CPF, thus resulting in the increased electrical performance of the fabricated TENG. The electrical output performance of the proposed TENG is systematically investigated by varying the amount of BWO material embedded in the PVDF‐HFP polymer. The fabricated PVDF‐HFP/2.5 wt% BWO CPF‐based TENG device exhibits the highest electrical output performance. Additionally, the robust test of the TENG device is conducted to investigate the electrical performance for long‐term durability and mechanical stability. Finally, the proposed TENG is operated as a self‐powered sensor, harvesting mechanical energy from daily life human activities, and powering various low‐power portable electronics.
Implementing an Air Suction Effect Induction Strategy to Create Super Thermally Insulating and Superelastic SiC Aerogels
Authors: Yan Mingyuan , Zhang Heping , Fu Yangyang , Pan Yuelei , Lun Zhiyi , Zhang Zhongxin , He Pan , Cheng Xudong 
Published: April 2022

AbstractSilicon carbide (SiC) aerogels are promising thermal insulators that are lightweight and possess high thermal stability. However, their application is hindered by their brittleness. Herein, an air suction effect induction (ASEI) strategy is proposed to fabricate a super thermally insulating SiC aerogel (STISA). The ASEI strategy exploits the air suction effect to subtly regulate the directional flow of the SiO gas, which can induce directional growth and assembly of SiC nanowires to form a directional lamellar structure. The sintering time is significantly reduced by >90%. Significant improvements in the compression and elasticity performance of the STISA are achieved upon the formation of a directional lamellar structure through the ASEI strategy. Moreover, the lamellar structure endows the STISA with an ultralow thermal conductivity of 0.019 W m−1 K−1. The ASEI strategy paves the way for structural design of advanced ceramic aerogels for super thermal insulation.
Recent Advances in Modified Cap Analogs: Synthesis, Biochemical Properties, and mRNA Based Vaccines
Authors: Shanmugasundaram Muthian , Senthilvelan Annamalai , Kore Anilkumar R. 
Published: April 2022

AbstractThe recent FDA approval of the mRNA vaccine for severe acute respiratory syndrome coronavirus (SARS‐CoV‐2) emphasizes the importance of mRNA as a powerful tool for therapeutic applications. The chemically modified mRNA cap analogs contain a unique cap structure, m7G[5′]ppp[5′]N (where N=G, A, C or U), present at the 5′‐end of many eukaryotic cellular and viral RNAs and several non‐coding RNAs. The chemical modifications on cap analog influence orientation's nature, translational efficiency, nuclear stability, and binding affinity. The recent invention of a trinucleotide cap analog provides groundbreaking research in the area of mRNA analogs. Notably, trinucleotide cap analogs outweigh dinucleotide cap analogs in terms of capping efficiency and translational properties. This review focuses on the recent development in the synthesis of various dinucleotide cap analogs such as dinucleotide containing a triazole moiety, phosphorothiolate cap, biotinylated cap, cap analog containing N1 modification, cap analog containing N2 modification, dinucleotide containing fluorescence probe and TAT, bacterial caps, and trinucleotide cap analogs. In addition, the biological applications of these novel cap analogs are delineated.
C2 translaminar screw fixation in pediatric occipitocervical fusion
Authors: Lee Young M. , Lu Alex Y. , Oh Taemin , Hwang Joan Y. , Lu Daniel C. , Sun Peter P. 
Published: April 2022

Abstract
Purpose
Rigid occipitocervical (O-C) instrumentation can reduce the anterior pathology and has a high fusion rate in children with craniovertebral instability. Typically, axis (C2) screw fixation utilizes C1–C2 transarticular screws or C2 pars screws. However, anatomic variation may preclude these screw types due to the size of fixation elements or by placing the vertebral artery at risk for injury. Pediatric C2 translaminar screw fixation has low risk of vertebral artery injury and may be used when the anatomy is otherwise unsuitable for C1–C2 transarticular screws or C2 pars screws.

Methods
We retrospectively reviewed a neurosurgical database at UCSF Benioff Children’s Hospital Oakland for patients who had undergone a cervical spinal fusion that utilized translaminar screws for occipitocervical instrumentation between 2002 and 2020. We then reviewed the operative records to determine the parameters of C2 screw fixations performed. Demographic and all other relevant clinical data were then recorded.

Results
Twenty-five patients ranging from 2 to 18 years of age underwent O-C fusion, with a total of 43 translaminar screws at C2 placed. Twenty-three patients were fused (92%) after initial surgery with a mean follow-up of 43 months. Two patients, both with Down syndrome, had a nonunion. Another 2 patients had a superficial wound dehiscence that required wound revision. One patient died of unknown cause 7 months after surgery. One patient developed an adjacent-level kyphosis.

Conclusion
When performing occipitocervical instrumentation in the pediatric population, C2 translaminar screw fixation is an effective option to other methods of C2 screw fixation dependent on anatomic feasibility.
Southern Ocean sea ice concentration budgets of five ocean-sea ice reanalyses
Authors: Nie Yafei , Uotila Petteri , Cheng Bin , Massonnet François , Kimura Noriaki , Cipollone Andrea , Lv Xianqing 
Published: April 2022

AbstractIn this study, sea ice concentration (SIC) budgets were calculated for five ocean-sea ice reanalyses (CFSR, C-GLORSv7, GLORYS12v1, NEMO-EnKF and ORAS5), in the Southern Ocean and compared with observations. Benefiting from the assimilation of SIC, the reanalysis products display a realistic representation of sea ice extent as well as sea ice area. However, when applying the SIC budget diagnostics to decompose the changes in SIC into contributions from advection, divergence, thermodynamics, deformation and data assimilation, we find that both atmospheric and oceanic forcings and model configurations are significant contributors on the budget differences. For the CFSR, the primary source of deviation compared to other reanalyses is the stronger northward component of ice velocity, which results in stronger sea ice advection and divergence. Anomalous surface currents in the CFSR are proposed to be the main cause of the ice velocity anomaly. Furthermore, twice the mean ice thickness in the CFSR compared to other reanalyses makes it more susceptible to wind and oceanic stresses under Coriolis forces, exacerbating the northward drift of sea ice. The C-GLORSv7, GLORYS12v1 and NEMO-EnKF have some underestimation of the contribution of advection and divergence to changes in SIC in autumn, winter and spring compared to observations, but are more reasonable in summer. ORAS5, although using the same coupled model and atmospheric forcing as C-GLORSv7 and GLORYS12v1, has a more significant underestimation of advection and divergence to changes in SIC compared to these two reanalyses. The results of the SIC budgets of five ocean-sea ice reanalyses in the Southern Ocean suggest that future reanalyses should focus on improving the modelling of sea ice velocities, for example through assimilation of sea ice drift observations.
CT-guided vs. fluoroscopically guided transforaminal epidural steroid injections for lumbar radiculopathy: a comparison of efficacy, safety and cost
Authors: Kamp Jozef P. M. , Bartlett Jonathan , Fahmy Amr , To Kendrick , Hossain Rumana , Akula Maheswara 
Published: April 2022

Abstract
Introduction
There are no formal guidelines for whether CT-guided or fluoroscopy-guided TFESI should be undertaken for patients with symptoms of lumbar nerve root irritation and corresponding nerve impingement. Here, we sought to compare the efficacy, safety and cost of computer tomography (CT)-guided and fluoroscopically guided transforaminal epidural steroid injection (TFESI).

Materials and methods
All patients who underwent lumbar TFESI at our institution between June 2016 and June 2018 were identified. Six-week follow-up outcomes were categorised. The radiation doses and associated cost was retrieved from our institution’s costing system.

Results
One hundred and sixteen patients were included (CT—50; fluoroscopy—56). There were no complications. More patients were discharged 6 weeks after CT-guided lumbar TFESI when compared with fluoroscopically guided TFESI (CT—23, fluoroscopy—14 (P = 0.027)). There was no difference in the number of patients who were referred to surgery (P = 0.18), for further pain management (P = 0.45), or for further TFESI (P = 0.43). The effective radiation dose was significantly higher for CT-guided TFESI (CT—5.73 mSv (3.87 to 7.76); fluoroscopy—0.55 mSv (0.11 to 1.4) (P < 0.01)). The total cost for CT-guided lumbar TFESI was £237.50 (£235 to £337), over £800 less than under fluoroscopic guidance (£1052 (£892.80 to £1298.00), P < 0.01)). Removing cost associated with staff and theatre use (staffing, theatre, medical indemnity and overheads) revealed CT-guided lumbar TFESI to be less expensive than if the procedure was fluoroscopy-guided—CT-guided: £132.6 (130.8 to 197.5); fluoroscopy: £237.4 (£209.2 to £271.9) (P = 0.019).

Conclusions
CT-guided TFESI was associated with a higher discharge rate, a lower cost, but a ten times higher radiation dose when compared with fluoroscopically guided TFESI. Prospective studies are required to compare the efficacy of these procedures and to investigate how the radiation dose of CT-guided TFESI can be reduced without jeopardising efficacy or safety.
Awareness of non-communicable diseases in women: a cross-sectional study
Authors: Irani Fiona , Coquoz Eloïse , von Wolff Michael , Bitterlich Norman , Stute Petra 
Published: April 2022

AbstractChronic non-communicable diseases (NCD) are the major reason for death, morbidity, loss of independency and public health cost. NCD prevalence could be significantly reduced by adopting a healthy lifestyle. This cross-sectional cohort study (online survey) in 221 women aimed to assess NCD awareness, knowledge about NCD prevention and willingness to adopt a healthier lifestyle in women. Overall, NCD awareness level was quite high with, however, information mainly originating from lay media, probably being one reason for false estimations of age groups mainly affected by NCD, impact of NCD on quality of life, NCD mortalities, and the extent of NCD prevention by lifestyle interventions, respectively. Furthermore, also due to mainly lay media, half of women knew online NCD risk calculators, most of them would like to know their NCD risk, but only few had been offered NCD risk calculation by their physician. The mean threshold for willing to adopt a healthier lifestyle was a roughly calculated 37% 5–10 years risk to develop a certain NCD. Acceptance of non-pharmacological interventions for NCD prevention was high, however, major barriers for not implementing a healthier lifestyle were lack of expert information and lack of time. In conclusion, future public health strategies should focus on distributing better understandable and correct information about NCD as well as meeting the individuals’ request for personalized NCD risk calculation. Furthermore, physicians should be better trained for personalized NCD prevention counseling.
Automated porosity estimation using CT-scans of extracted core data
Authors: Chawshin Kurdistan , Berg Carl Fredrik , Varagnolo Damiano , Lopez Olivier 
Published: April 2022

AbstractEstimation of porosity at a millimeter scale would be an order of magnitude finer resolution than traditional logging techniques. This enables proper description of reservoirs with thin layers and fine scale heterogeneities. To achieve this, we propose an end-to-end convolutional neural network (CNN) regression model that automatically predicts continuous porosity at a millimeter scale resolution using two-dimensional whole core CT scan images. More specifically, a CNN regression model is trained to learn from routine core analysis (RCA) porosity measurements. To characterize the performance of such approach, we compare the performance of this model with two linear regression models trained to learn the relationship between the average attenuation and standard deviation of the same two-dimensional images and RCA porosity. Our investigations reveal that the linear models are outperformed by the CNN, indicating the capability of the CNN model in extracting textures that are important for porosity estimations. We compare the predicted porosity results against the total porosity logs calculated from the density log. The obtained results show that the predicted porosity values using the proposed CNN method are well correlated with the core plug measurements and the porosity log. More importantly, the proposed approach can provide accurate millimeter scale porosity estimations, while the total porosity log is averaged over an interval and thus do not show such fine scale variations. Thus, the proposed method can be employed to calibrate the porosity logs, thereby reducing the uncertainties associated with indirect calculations of the porosity from such logs.
A generalized framework for lung Cancer classification based on deep generative models
Authors: Salama Wessam M. , Shokry Ahmed , Aly Moustafa H. 
Published: April 2022

AbstractA new generalized framework for lung cancer detection and classification are introduced in this paper. Specifically, two types of deep models are presented. The first model is a generative model to capture the distribution of the important features in a set of small class-unbalanced collected CXR images. This generative model can be utilized to synthesize any number of CXR images for each class. For example, our generative model can generate images with tumors with different sizes and positions in the lung. Hence, the system can automatically convert the small unbalanced collected dataset to a larger balanced one. The second model is the ResNet50 that is trained using the large balanced dataset for cancer classification into benign and malignant. The proposed framework acquires 98.91% overall detection accuracy, 98.85% area under curve (AUC), 98.46% sensitivity, 97.72% precision, 97.89% F1 score. The classifier takes 1.2334 s on average to classify a single image using a machine with 13GB RAM.
Virtual reality in training artificial intelligence-based systems: a case study of fall detection
Authors: Bui Vinh , Alaei Alireza 
Published: April 2022

AbstractArtificial Intelligent (AI) systems generally require training data of sufficient quantity and appropriate quality to perform efficiently. However, in many areas, such training data is simply not available or incredibly difficult to acquire. The recent developments in Virtual Reality (VR) have opened a new door for addressing this issue. This paper demonstrates the use of VR for generating training data for AI systems through a case study of human fall detection. Fall detection is a challenging problem in the public healthcare domain. Despite significant efforts devoted to introducing reliable and effective fall detection algorithms and enormous devices developed in the literature, minimal success has been achieved. The lack of recorded fall data and the data quality have been identified as major obstacles. To address this issue, this paper proposes an innovative approach to remove the afformentioned obstacle using VR technology. In this approach, a framework is, first, proposed to generate human fall data in virtual environments. The generated fall data is then tested with state-of-the-art visual-based fall detection algorithms to gauge its effectiveness. The results have indicated that the virtual human fall data generated using the proposed framework have sufficient quality to improve fall detection algorithms. Although the approach is proposed and verified in the context of human fall detection, it is applicable to other computer vision problems in different contexts, including human motion detection/recognition and self-driving vehicles.
Precision land leveling for sustainable rice production: case studies in Cambodia, Thailand, Philippines, Vietnam, and India
Authors: Nguyen-Van-Hung  , Balingbing Carlito , Sandro Joseph , Khandai Suryakanta , Chea Hong , Songmethakrit Thanach , Meas Pyseth , Hitzler Gerald , Zwick Walter , Viriyangkura Ladda , Bautista Elmer , Gummert Martin 
Published: April 2022

AbstractLaser-controlled land leveling (LLL) can help improve rice production's spatial and temporal management, leading to optimized water and crop management. This research resulted in sustainable performance indicators to illustrate that LLL is a sustainable technology for rice production. The assessment was conducted in Cambodia, the Philippines, Thailand, Vietnam, and India. Benefits of LLL include saving land use, water, and agronomic inputs, increasing yield, and decreasing postharvest losses resulting in saving energy of 3.0–6.9 GJ ha−1and decreasing emissions by 1151–1486 kg CO2-eq ha−1. Additionally, LLL application can obtain a net profit of USD 52–84 ha−1per rice production season in the countries studied. The result demonstrated that LLL is a sustainable technology as well as strongly supports sustainable rice production. The study would lead to better adoption of this technology through its evidence-based promotion.