bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hemorrhagic risk prediction in coronary artery disease patients based on photoplethysmography and machine learning
Authors: He Zhengling , Zhang Huajun , Chen Xianxiang , Shi Junshan , Bai Lu , Fang Zhen , Wang Rong 
Published: November 2022

AbstractHemorrhagic events are the main focus of attention during antithrombosis therapy in patients with coronary artery disease (CAD). This study aims to investigate the potential of using photoplethysmography (PPG) and machine learning techniques to assess hemorrhagic risk in patients with CAD. A total of 1638 patients with CAD were enrolled from January 2018 to October 2019, among which 114 patients were observed to have at least one positive event. Importantly, 102 patients with 9933 records were finally retained for analysis in this study. Participants were required to collect data using the portable PPG acquisition device and the specially designed Android APP. The data was collected and uploaded to a remote server. Based on collected PPG signals, we extracted features in a total of 30 dimensions from time-domain, frequency-domain, and wavelet packet decomposition. Logistic regression, support vector regression, random forest, and XGBoost regression models were established to achieve hemorrhagic risk evaluation, and then, their performances were compared. In total, 10 features extracted from PPG showed statistical significance (p < 0.01) between negative and positive groups. The newly established XGBoost model performed best in the hemorrhagic risk evaluation experiment, wherein the mean area under the curve (AUC) with tenfold cross-validation was 0.762 ± 0.024 and the sensitivity and specificity were 0.679 ± 0.051 and 0.714 ± 0.014, respectively. We established a data acquisition system for PPG signal collection, and demonstrated that a set of features extracted from PPG and the proposed machine learning model are promising in the evaluation of hemorrhagic risk among patients with CAD. In comparison with the traditional HAS-BLED score, the proposed method can obtain the quantitative risk prediction probability from a single PPG record, which has the advantages of dynamics and continuity, and can provide timely feedback for doctors' antithrombotic treatment, which is of great significance for doctors to quickly determine the effectiveness of the treatment and adjust the timely treatment plans accordingly.
Thirty percent conversion efficiency from radiofrequency power to thrust energy in a magnetic nozzle plasma thruster
Authors: Takahashi Kazunori 
Published: November 2022

AbstractInnovations for terrestrial transportation technologies, e.g., cars, aircraft, and so on, have driven historical industries so far, and a similar breakthrough is now occurring in space owing to the successful development of electric propulsion devices such as gridded ion and Hall effect thrusters, where solar power is converted into the momentum of the propellant via acceleration of the ionized gases, resulting in a high specific impulse. A magnetic nozzle (MN) radiofrequency (rf) plasma thruster consisting of a low-pressure rf plasma source and a MN is an attractive candidate for a high-power electric propulsion device for spacecraft, as it will provide a long lifetime operation at a high-power level due to the absence of an electrode exposed to the plasma and a high thrust density. The high-density plasma produced in the source is transported along the magnetic field lines toward the open-source exit and the plasma is then spontaneously accelerated in the MN. By ejecting the plasma flow from the system, the reaction forces are exerted to the thruster structure including the source and the MN, and the spacecraft is resultantly propelled. The thruster will open the next door for space technologies, while the performance of the MN rf plasma thruster has been lower than those of the mature electric propulsion devices due to the energy loss to the physical walls. Here the thruster efficiency of about 30%, being the highest to date in this type of thruster, is successfully obtained in the MN rf plasma thruster by locating a cusp magnetic field inside the source, which acts as a virtual magnetic wall isolating the plasma from the source wall. The increase in the thrust by the cusp can be explained by considering the reductions of the loss area and the plasma volume in a thrust analysis combining a global source model and a one-dimensional MN model.
Rosa26-LSL-dCas9-VPR: a versatile mouse model for tissue specific and simultaneous activation of multiple genes for drug discovery
Authors: Pakalniškytė Dalia , Schönberger Tanja , Strobel Benjamin , Stierstorfer Birgit , Lamla Thorsten , Schuler Michael , Lenter Martin 
Published: November 2022

AbstractTransgenic animals with increased or abrogated target gene expression are powerful tools for drug discovery research. Here, we developed a CRISPR-based Rosa26-LSL-dCas9-VPR mouse model for targeted induction of endogenous gene expression using different Adeno-associated virus (AAV) capsid variants for tissue-specific gRNAs delivery. To show applicability of the model, we targeted low-density lipoprotein receptor (LDLR) and proprotein convertase subtilisin/kexin type 9 (PCSK9), either individually or together. We induced up to ninefold higher expression of hepatocellular proteins. In consequence of LDLR upregulation, plasma LDL levels almost abolished, whereas upregulation of PCSK9 led to increased plasma LDL and cholesterol levels. Strikingly, simultaneous upregulation of both LDLR and PCSK9 resulted in almost unaltered LDL levels. Additionally, we used our model to achieve expression of all α1-Antitrypsin (AAT) gene paralogues simultaneously. These results show the potential of our model as a versatile tool for optimized targeted gene expression, alone or in combination.
Testing the effects of perceptual grouping on visual search in older adults
Authors: Jingling Li , Lai Sung-Nan 
Published: November 2022

AbstractVisual search is to find targets while ignoring distractors. Previous studies established that a target is more difficult to identify if aligned collinearly with other items, called the collinear search impairment. Since older adults have lower perceptual grouping ability than younger adults, benefits in visual search may occur for older adults for they may be less distracted by the collinear distractors. Three experiments were carried out to compare 45 younger and 45 older healthy adults. Participants were asked to identify a local target either in the column with items collinearly aligned to each other (the overlapping condition) or in the background (the non-overlapping condition), and the response difference between the two conditions is the collinear search impairment. Results showed that both groups showed reliable search impairment specific to collinear distractor regardless of grouping difficulty and task demands, and the impairment strength increased with the grouping strength of the collinear distractor. Further analysis revealed that the response times of older adults increased in a multiplicative manner to that of younger adults, suggesting that longer response of older adults spread to multiple underlying processing including grouping and suppression of collinear distractors. Together, the results suggest that older adults were still distracted in visual search even when grouping was required on a distractor. Our findings also highlight how general slowing may delay suppression processing in visual search.
Deep learning signature of brain [18F]FDG PET associated with cognitive outcome of rapid eye movement sleep behavior disorder
Authors: Ryoo Hyun Gee , Byun Jung-Ick , Choi Hongyoon , Jung Ki-Young 
Published: November 2022

AbstractAn objective biomarker to predict the outcome of isolated rapid eye movement sleep behavior disorder (iRBD) is crucial for the management. This study aimed to investigate cognitive signature of brain [18F]FDG PET based on deep learning (DL) for evaluating patients with iRBD. Fifty iRBD patients, 19 with mild cognitive impairment (MCI) (RBD-MCI) and 31 without MCI (RBD-nonMCI), were prospectively enrolled. A DL model for the cognitive signature was trained by using Alzheimer’s Disease Neuroimaging Initiative database and transferred to baseline [18F]FDG PET from the iRBD cohort. The results showed that the DL-based cognitive dysfunction score was significantly higher in RBD-MCI than in RBD-nonMCI. The AUC of ROC curve for differentiating RBD-MCI from RBD-nonMCI was 0.70 (95% CI 0.56–0.82). The baseline DL-based cognitive dysfunction score was significantly higher in iRBD patients who showed a decrease in CERAD scores during 2 years than in those who did not. Brain metabolic features related to cognitive dysfunction-related regions of individual iRBD patients mainly included posterior cortical regions. This work demonstrates that the cognitive signature based on DL could be used to objectively evaluate cognitive function in iRBD. We suggest that this approach could be extended to an objective biomarker predicting cognitive decline and neurodegeneration in iRBD.
Large studies reveal how reference bias limits policy applications of self-report measures
Authors: Lira Benjamin , O’Brien Joseph M. , Peña Pablo A. , Galla Brian M. , D’Mello Sidney , Yeager David S. , Defnet Amy , Kautz Tim , Munkacsy Kate , Duckworth Angela L. 
Published: November 2022

AbstractThere is growing policy interest in identifying contexts that cultivate self-regulation. Doing so often entails comparing groups of individuals (e.g., from different schools). We show that self-report questionnaires—the most prevalent modality for assessing self-regulation—are prone to reference bias, defined as systematic error arising from differences in the implicit standards by which individuals evaluate behavior. In three studies, adolescents (N = 229,685) whose peers performed better academically rated themselves lower in self-regulation and held higher standards for self-regulation. This effect was not observed for task measures of self-regulation and led to paradoxical predictions of college persistence 6 years later. These findings suggest that standards for self-regulation vary by social group, limiting the policy applications of self-report questionnaires.
Effect of the sagittal osteotomy inclination angle on the posterior tibial slope change in high tibial osteotomy: three-dimensional simulation study
Authors: Chung Jai Hyun , Choi Chong Hyuk , Kim Sung-Hwan , Kim Sung-Jae , Suk Yong June , Jung Min 
Published: November 2022

AbstractIn performing medial open-wedge high tibial osteotomy, it is recommended not to alter the posterior tibial slope. However, it remains unclear whether the osteotomy inclination angle affects the posterior tibial slope in the sagittal plane. This study aimed to verify how anterior or posterior osteotomy inclination angle affects the tendency of change in the posterior tibial slope and to conduct quantitative analysis of the extent to which the posterior tibial slope changes according to the degree of the osteotomy inclination angle change in MOWHTO. Computed tomography images of 30 patients who underwent MOWHTO were collected. Three-dimensional models of preoperative original tibia were reconstructed, and virtual osteotomies were performed. The sagittal osteotomy inclination angles formed by the osteotomy line and the medial tibial plateau line were classified as positive in case of anteriorly inclined osteotomy and negative in case of posteriorly inclined osteotomy. Thirteen osteotomies were performed for each tibial model at intervals of 5° from − 30° to 30°. The posterior tibial slope was assessed, and the proportional relationship between the sagittal osteotomy inclination angle and the posterior tibial slope change was analyzed. The posterior tibial slope changed significantly after osteotomy (p < 0.001), except for the cases where the sagittal osteotomy inclination angles were 5°, 0°, and − 5°. Anteriorly and posteriorly inclined osteotomy caused increase and decrease in the posterior tibial slope, respectively. As the inclination angle increased by 1°, the posterior tibial slope increased by 0.079° in anterior inclination osteotomy, while in posterior inclination osteotomy, as the inclination angle decreased by 1°, the posterior tibial slope decreased by 0.067°. The osteotomy inclination angle in the sagittal plane significantly affected the posterior tibial slope. When there was an inclination angle occurred between the osteotomy line and the medial tibial plateau line in the sagittal plane, the posterior tibial slope changed after MOWHTO. The posterior tibial slope tended to increase in anteriorly inclined osteotomy and decrease in posteriorly inclined osteotomy. The change in the posterior tibial slope was proportionally related to the absolute value of the osteotomy inclination angle.
Real-world clinical effectiveness and sustainability of universal bloodborne virus testing in an urban emergency department in the UK
Authors: Smout Elizabeth , Phyu Khine , Hughes Gareth J. , Parker Lee , Rezai Roozbeh , Evans Amy , McLaren Joscelyne , Bush Stephen , Davey Sarah , Aldersley Mark A. , Ruf Murad , Page Emma E. 
Published: November 2022

AbstractInnovative testing approaches and care pathways are required to meet HIV, hepatitis B (HBV) and hepatitis C (HCV) elimination goals. Routine testing for blood-borne viruses (BBVs) within emergency departments (EDs) is suggested by the European Centre for Disease Prevention and Control but there is a paucity of supporting evidence. We evaluated the introduction of routine BBV testing in EDs at a large teaching hospital in northern England. In October 2018, we modified the electronic laboratory ordering system to reflex opt-out HIV, HBV and HCV testing for all ED attendees aged 16–65 years who had a routine blood test for urea and electrolytes (U&Es). Linkage to care (LTC) was attempted for newly diagnosed patients, those never referred and those who had previously disengaged from care. The project operated for 18 months, here we present evaluation of the initial nine months (2 October 2018–1 July 2019). We analysed testing uptake, BBV seropositivity, LTC and treatment initiation within six months post-diagnosis. Over 9 months, 17,026/28,178 (60.4%) ED attendees who had U&Es performed were tested for ≥ 1 BBV. 299 active BBV infections were identified: 70 HIV Ab/Ag-positive (0.4% seroprevalence), 73 HBsAg-positive (0.4%) and 156 HCV RNA-positive (1.0%). Only 24.3% (17/70) HIV Ab/Ag-positive individuals required LTC, compared to 94.9% (148/156) HCV RNA-positive and 53.4% (39/73) HBsAg-positive individuals. LTC was successful in 94.1% (16/17) HIV Ab/Ag-positive and 69.3% (27/39) HBsAg-positive individuals. However, at 6 months LTC was just 39.2% (58/148) for HCV RNA-positive individuals, with 64% (37/58) of these commencing treatment. Universal opt-out ED BBV testing proved feasible and effective in identifying active BBV infections, especially among marginalised populations with reduced healthcare access. Our integrated approach achieved good LTC rates although further service development is necessary, particularly for HCV RNA-positive people who inject drugs.
Sensing whales, storms, ships and earthquakes using an Arctic fibre optic cable
Authors: Landrø Martin , Bouffaut Léa , Kriesell Hannah Joy , Potter John Robert , Rørstadbotnen Robin André , Taweesintananon Kittinat , Johansen Ståle Emil , Brenne Jan Kristoffer , Haukanes Aksel , Schjelderup Olaf , Storvik Frode 
Published: November 2022

AbstractOur oceans are critical to the health of our planet and its inhabitants. Increasing pressures on our marine environment are triggering an urgent need for continuous and comprehensive monitoring of the oceans and stressors, including anthropogenic activity. Current ocean observational systems are expensive and have limited temporal and spatial coverage. However, there exists a dense network of fibre-optic (FO) telecommunication cables, covering both deep ocean and coastal areas around the globe. FO cables have an untapped potential for advanced acoustic sensing that, with recent technological break-throughs, can now fill many gaps in quantitative ocean monitoring. Here we show for the first time that an advanced distributed acoustic sensing (DAS) interrogator can be used to capture a broad range of acoustic phenomena with unprecedented signal-to-noise ratios and distances. We have detected, tracked, and identified whales, storms, ships, and earthquakes. We live-streamed 250 TB of DAS data from Svalbard to mid-Norway via Uninett’s research network over 44 days; a first step towards real-time processing and distribution. Our findings demonstrate the potential for a global Earth-Ocean-Atmosphere-Space DAS monitoring network with multiple applications, e.g. marine mammal forecasting combined with ship tracking, to avoid ship strikes. By including automated processing and fusion with other remote-sensing data (automated identification systems, satellites, etc.), a low-cost ubiquitous real-time monitoring network with vastly improved coverage and resolution is within reach. We anticipate that this is a game-changer in establishing a global observatory for Ocean-Earth sciences that will mitigate current spatial sampling gaps. Our pilot test confirms the viability of this ‘cloud-observatory’ concept.
Machine learning-based assessment of storm surge in the New York metropolitan area
Authors: Ayyad Mahmoud , Hajj Muhammad R. , Marsooli Reza 
Published: November 2022

AbstractStorm surge generated from low-probability high-consequence tropical cyclones is a major flood hazard to the New York metropolitan area and its assessment requires a large number of storm scenarios. High-fidelity hydrodynamic numerical simulations can predict surge levels from storm scenarios. However, an accurate prediction requires a relatively fine computational grid, which is computationally expensive, especially when including wave effects. Towards alleviating the computational burden, Machine Learning models are developed to determine long-term average recurrence of flood levels induced by tropical cyclones in the New York metropolitan area. The models are trained and verified using a data set generated from physics-based hydrodynamic simulations to predict peak storm surge height, defined as the maximum induced water level due to wind stresses on the water surface and wave setup, at four coastal sites. In the generated data set, the number of low probability high-level storm surges was much smaller than the number of high probability low-level storm surges. This resulted in an imbalanced data set, a challenge that is addressed and resolved in this study. The results show that return period curves generated based on storm surge predictions from machine learning models are in good agreement with curves generated from high-fidelity hydrodynamic simulations, with the advantage that the machine learning model results are obtained in a fraction of the computational time required to run the simulations.
Data analysis of the unsteadily accelerating GPS and seismic records at Campi Flegrei caldera from 2000 to 2020
Authors: Bevilacqua Andrea , De Martino Prospero , Giudicepietro Flora , Ricciolino Patrizia , Patra Abani , Pitman E. Bruce , Bursik Marcus , Voight Barry , Flandoli Franco , Macedonio Giovanni , Neri Augusto 
Published: November 2022

AbstractOngoing resurgence affects Campi Flegrei caldera (Italy) via bradyseism, i.e. a series of ground deformation episodes accompanied by increases in shallow seismicity. In this study, we perform a mathematical analysis of the GPS and seismic data in the instrumental catalogs from 2000 to 2020, and a comparison of them to the preceding data from 1983 to 1999. We clearly identify and characterize two overlying trends, i.e. a decennial-like acceleration and cyclic oscillations with various periods. In particular, we show that all the signals have been accelerating since 2005, and 90–97% of their increase has occurred since 2011, 40–80% since 2018. Nevertheless, the seismic and ground deformation signals evolved differently—the seismic count increased faster than the GPS data since 2011, and even more so since 2015, growing faster than an exponential function The ground deformation has a linearized rate slope, i.e. acceleration, of 0.6 cm/yr2 and 0.3 cm/yr2 from 2000 to 2020, respectively for the vertical (RITE GPS) and the horizontal (ACAE GPS) components. In addition, all annual rates show alternating speed-ups and slow-downs, consistent between the signals. We find seven major rate maxima since 2000, one every 2.8–3.5 years, with secondary maxima at fractions of the intervals. A cycle with longer period of 6.5–9 years is also identified. Finally, we apply the probabilistic failure forecast method, a nonlinear regression that calculates the theoretical time limit of the signals going to infinity (interpreted here as a critical state potentially reached by the volcano), conditional on the continuation of the observed nonlinear accelerations. Since 2000, we perform a retrospective analysis of the temporal evolution of these forecasts which highlight the periods of more intense acceleration. The failure forecast method applied on the seismic count from 2001 to 2020 produces upper time limits of [0, 3, 11] years (corresponding to the 5th, 50th and 95th percentiles, respectively), significantly shorter than those based on the GPS data, e.g. [0, 6, 21] years. Such estimates, only valid under the model assumption of continuation of the ongoing decennial-like acceleration, warn to keep the guard up on the future evolution of Campi Flegrei caldera.
Modeling the role of police corruption in the reduction of organized crime: Mexico as a case study
Authors: Aldana Andrés , Larralde Hernán , Aldana Maximino 
Published: November 2022

AbstractAmong all types of corruption, police corruption is probably the one that most directly hurts society, as those trusted with protecting the people either side with the criminals that victimize the citizens, or are themselves, criminals. However, both corruption and its effects are very difficult to measure quantitatively other than by perception surveys, but the perception that citizens have of this phenomenon may be different from reality. Using a simple agent-based model, we analyze the effect on crime rates as a result of both corruption and the perception of corruption within law-enforcement corporations. Our results show a phase transition in which crime can propagate across the population even when the majority of police officers are honest. We find that one of the parameters that strongly controls crime incidence is the probability that regular citizens become criminals. In contrast, other actions, such as arresting crime lords, or the amount of crime-associated money that is confiscated, have little impact on the long-term crime incidence. Our results suggest that in addition to combating corruption within law-enforcement institutions, to further reduce the incidence of crime, policymakers should strive to restore confidence in these institutions and the justice system.