bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phase separation of the microtubule-associated protein tau
Authors: Chakraborty Pijush , Zweckstetter Markus 
Published: October 2022

Abstract
The aggregation and misfolding of the neuronal microtubule-associated protein tau is closely linked to the pathology of Alzheimer’s disease and several other neurodegenerative diseases. Recent evidence suggest that tau undergoes liquid–liquid phase separation in vitro and forms or associates with membrane-less organelles in cells. Biomolecular condensation driven by phase separation can influence the biological activities of tau including its ability to polymerize tubulin into microtubules. In addition, the high concentrations that tau can reach in biomolecular condensates provide a mechanism to promote its aggregation and the formation of amyloid fibrils potentially contributing to the pathology of different tauopathies. Here, the authors discuss the role of tau phase separation in physiology and disease.
Privacy‐preserving generative framework for images against membership inference attacks
Authors: Yang Ruikang , Ma Jianfeng , Miao Yinbin , Ma Xindi 
Published: October 2022

AbstractMachine learning has become an integral part of modern intelligent systems in all aspects of life. Membership inference attacks (MIAs), as the significant model attacks, also jeopardize the privacy of the intelligent systems. Previous works on defending MIAs concentrate on the model output perturbation or tampering with the training process. However, data and model reuse are common in intelligent systems, which results in the lack of scalability of previous defending works. This paper proposes a new privacy‐preserving framework for images to transform source data into synthetic data to train models against MIAs. The synthetic data makes it easy to defend MIAs during data and model reuse to improve the scheme's scalability. The framework generates synthetic data satisfying differential privacy through the variational autoencoder model's information extraction and data generation capabilities to improve model accuracy. A noise addition mechanism with metric privacy for the latent code generated from source data is proposed, where noise is the product of Γ‐distribution and unit hyper‐sphere samples. Moreover, it is proved that the synthetic data also satisfies metric privacy. The experimental evaluations demonstrate that the framework reduces MIAs' attack accuracy to about 0.5 and maintains higher utility than DP‐SGD under the same setting.
Retracted: Non‐stationary 3‐D GBSM channel model for V2V communications
Authors: Xu Yan , Saleem Asad , Asif Muhammad , Khan Wali Ullah , Akhtar Zain Ul Abiden , Ali Md. Sadek 
Published: October 2022

AbstractThe above article from IET Communications, published online on 17 October 2022 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Interim Editor‐in‐Chief, Jian Ren, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal's peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.
Robust convergence conditions of iterative learning control for time‐delay systems under random non‐repetitive uncertainties
Authors: Shokri‐Ghaleh Hamid , Ganjefar Soheil , Shahri Alireza Mohammad 
Published: October 2022

AbstractSome of the most fundamental assumptions in the design of iterative learning control (ILC) for uncertain systems are the strict repetitiveness (i.e. iteration‐independence) of uncertainties in all factors of plant dynamic, external disturbances, initial conditions, and reference trajectory, which may not always hold in practical applications. The simultaneous relaxation of all these assumptions is a challenging problem that has been addressed only for delay‐free systems. This problem is still open for time‐delay systems, especially when the time‐delay factor also has non‐repetitive (i.e. iteration‐dependent/varying) uncertainty. Hence, this study extends the problem of robust ILC for a class of time‐delay systems under nonrepetitive uncertainties in not only plant dynamic, external disturbances, initial conditions, and reference trajectory but also time‐delay. By using the ILC scheme introduced in this work, and based on the frequency domain analysis, it is shown that both monotonic convergence and boundedness of the expected tracking error can be achieved (in the sense of L2‐norm) when the non‐repetitiveness (i.e. iteration‐dependence) of all existing uncertainties from a random viewpoint are taken into account. The effectiveness of the proposed strategy is verified by two simulation examples.
A 1.2 V high‐speed low‐power preamplifier latch‐based comparator
Authors: He Yuefeng , Yuan Guoshun 
Published: October 2022

AbstractThe power consumption of chips has emerged as a major concern with the increased integration of analog circuitry. This work focuses on a two‐stage comparator based on a preamplifier with latch for a successive approximation analog‐to‐digital converter. In order to minimize power loss and delay time, the charge steering approach was used in the design of latch as well as preamplifier. The suggested comparator is simulated in SMIC 0.18‐um process in comparison to the comparator without charge steering mode. The results reveal that the average power consumption is only around 22 uW for varied input voltage at a supply voltage of 1.2 V, which is relatively lowered by approximately 30%. Meanwhile, delay time is also reduced by about 25%.
Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach
Authors: Zhang Jiarui , Mu Yunfei , Wu Zeqing , Liu Zhe , Gao Yi , Jia Hongjie , Li Hairun 
Published: October 2022

AbstractResidential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic‐based model predictive control approach (AA‐MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH‐based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA‐MPC approach that takes the thermal energy for emergency building heating as a time‐varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic‐based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively.
An exact MILP model for joint switch placement and preventive maintenance scheduling considering incentive regulation
Authors: Alizadeh Ali , Kamwa Innocent , Moeini Ali , Mohseni‐Bonab Seyed Masoud 
Published: October 2022

AbstractPower delivery with high reliability is one of the main objectives of any distribution system. In this regard, system operators are adapting the traditional distribution systems with sectionalized switches and optimal preventive maintenance (PM) scheduling techniques as two effective methods for reliability improvement. However, they suffer due to the lack of a practical model in which switch placement (SP) and PM scheduling problems are considered simultaneously. Furthermore, consideration of incentive regulation schemes, such as reward‐penalty scheme (RPS) is highly questionable in the separated reliability improvement problems. In this paper, a mix‐integer linear programming model is presented wherein both SP and PM scheduling problems are considered. Rather than using conventional methods for linearization, an exact formulation is proposed to avoid the impact of approximations on the final decision. Moreover, RPS is also regarded as an incentive regulation scheme to balance the reliability level and financial performance. The results of test and real network implementation confirm that a higher performance is reached in terms of reliability and financial issues when the proposed model is utilized compared to the other ones. Besides, analysis demonstrates that the proposed model behaves effectively in both mid and long terms.
Improving traffic signal control operations using proximal policy optimization
Authors: Huang Liben , Qu Xiaohui 
Published: October 2022

AbstractExisting traffic signal control systems present many limitations including fixed signal timing schemes, insufficient efficiency and flexibility, and difficulty in adapting to the changing traffic flows. In recent years, the development of deep reinforcement learning (RL) has shown great research potential and application prospects. This paper proposes an intersection signal control method based on the proximal policy optimization (PPO) method. Specifically, this paper uses the value vector representation method of traffic characteristics to encode the traffic state and then feeds the state encoding into the long short‐term memory (LSTM) network to obtain the signal phase output. Finally, to obtain the optimal signal control strategy, the PPO algorithm is utilized to train the neural network and adjust the signal phase. The proposed algorithm is benchmarked against other classic RL and adaptive signal control schemes in an experimental environment based on the traffic simulation software simulation of urban mobility (SUMO). Experimental results showed that the proposed algorithm greatly improves traffic efficiency. Specifically, the mean velocity of the vehicles increases by 45.09%, and the mean occupancy rate of each lane, the length of the longest jams during each step, and the mean halting duration dropped by 21.38%, 25.86%, and 12.94%, respectively.
Applying a hybrid model considering the interaction between train and power system for energy consumption surveys
Authors: Haghbin Mohammad , Khsoravani Mohammad , Golzar Tehrani Alireza , Farjah Ebrahim 
Published: October 2022

AbstractPower supply system plays an important role in the operation of urban rail systems. It has to provide high‐quality energy for trains continuously. Train's energy consumption is varied directly with operation conditions such as train's headway, train configuration, line characteristic and many other factors. Therefore, using a powerful simulation tool for estimating energy consumption considering these factors seems inevitable. This paper tries to develop a hybrid model in which the train model is based on acquired data from real measurement and an adapted network electrical model. Train empirical model is based on neural network on the basis of online data measured in line one of Shiraz metro and used for training of model. Then benefiting from optimization algorithms, a novel model of energy supply system of trains, including Traction Substations (TSS) and Overhead Catenary System (OCS), is proposed. Finally, the behaviour of trains during operation in 15‐min headway was simulated and the results under same conditions were compared with practical measurements. Currently, this model helps to determine power system behaviour during different operation conditions, predicting energy consumption for different headways, Train's driver behaviour during acceleration, deceleration and braking and also operation risk analysis during traction substations outages.
Hybrid models of subway passenger flow prediction based on convolutional neural network
Authors: Lai Yuan‐wen , Wang Yang , Xu Xin‐ying , Easa Said M. , Zhou Xiao‐wei 
Published: October 2022

AbstractAccurate and stable short‐term passenger flow prediction is an indispensable part of current intelligent transportation systems. This paper proposes two deep learning prediction models based on convolutional neural networks (CNN) and long short‐term memory neural network (LSTM). Combining the CNN characteristics and the LSTM, the ConvXD‐LSTM extracts passenger flow features through CNN and then inputs the time series into the LSTM. The ConvLSTM converts the weight calculation of the LSTM into convolution operation to realize short‐term passenger flow prediction. Fuzhou Metro Line 1 passenger flow data was used for verification. The models were used to predict the passenger flow of subway stations and cross‐sections and compared with the traditional prediction models. In terms of prediction accuracy, ConvLSTM has the highest accuracy, followed by ConvXD‐LSTM. In terms of running time, ConvXD is the fastest and LSTM takes the longest. ConvXD‐LSTM and ConvLSTM are in the middle of the two models, achieving a good balance between accuracy and efficiency. Compared with ConvXD‐LSTM, ConvLSTM has a relatively simple network structure, which reduces the computational burden and improves the prediction accuracy.
Pediatric endoscopy training across Europe: a survey of the ESPGHAN National Societies Network 2016–2019
Authors: Papadopoulou Alexandra , Ribes-Koninckx Carmen , Baker Alastair , Noni Maria , Koutri Eleni , Karagianni Maria-Vasiliki , Protheroe Sue , Guarino Alfredo , Mas Emmanuel , Wilschanski Michael , Roman Enriqueta , Escher Johanna , Furlano Raoul I. , Posovszky Carsten , Hoffman Ilse , Bronsky Jiri , Hauer Almuthe Christine , Tjesic-Drinkovic Duska , Fotoulaki Maria , Orel Rok , Urbonas Vaidotas , Kansu Aydan , Georgieva Miglena , Thomson Mike 
Published: October 2022

Background and study aims The ability to perform endoscopy procedures safely and effectively is a key aspect of quality clinical care in Pediatric Gastroenterology, Hepatology and Nutrition (PGHN). The aim of this survey, which was part of a global survey on PGHN training in Europe, was to assess endoscopy training opportunities provided across Europe.
Methods Responses to standardized questions related to endoscopy training were collected from training centers across Europe through the presidents/representatives of the European Society for Paediatric Gastroenterology, Hepatology and Nutrition National Societies from June 2016 to December 2019.
Results A total of 100 training centers from 19 countries participated in the survey. In 57 centers, the endoscopy suit was attached to the PGHN center, while in 23, pediatric endoscopies were performed in adult endoscopy facilities. Ninety percent of centers reported the availability of specialized endoscopy nurses and 96 % of pediatric anesthetists. Pediatric endoscopies were performed by PGHN specialists in 55 centers, while 31 centers reported the involvement of an adult endoscopist and 14 of a pediatric surgeon. Dividing the number of procedures performed at the training center by the number of trainees, ≤ 20 upper, lower, or therapeutic endoscopies per trainee per year were reported by 0 %, 23 %, and 56 % of centers, respectively, whereas ≤ 5 wireless capsule endoscopies per trainee per year by 75 %. Only one country (United Kingdom) required separate certification of competency in endoscopy.
Conclusions Differences and deficiencies in infrastructure, staffing, and procedural volume, as well as in endoscopy competency assessment and certification, were identified among European PGHN training centers limiting training opportunities in pediatric endoscopy.
Sleep disorders in multiple sclerosis: a case-control study using the São Paulo Epidemiologic sleep study (Episono) database
Authors: Toscano Vanessa Granato , Coelho Fernando Morgadinho , Prado Gilmar Fernandes do , Tufik Sergio , Oliveira Enedina Maria Lobato de 
Published: October 2022

Abstract
Background Sleep disorders such as obstructive sleep apnea and restless legs syndrome are prevalent in the general population and patients with chronic diseases such as multiple sclerosis (MS).
Objectives This study compared the prevalence of sleep disorders complaints, fatigue, depression, and chronotype of adult patients with multiple sclerosis (PwMS) to a representative sample of São Paulo city residents.
Methods A comparative study was made between PwMS and volunteers from the São Paulo Epidemiologic Sleep Study (Episono) study. We compared the scores of sleep questionnaires using the multivariate analysis of variance (MANOVA) test to evaluate the effects and analysis of variance (ANOVA) as a follow-up test. Covariates were age, sex, and physical activity. The Pearson correlation test was performed to measure the correlation between Expanded Disability Status Scale (EDSS) and the scores of the sleep questionnaires. Finally, we applied propensity score matching to reduce bias in estimating differences between the two groups. Analyses were performed using Stata 14 (StataCorp, College Station, TX, USA) and IBM SPSS Statistics for Windows version 22.0 (IBM Corp., Armonk, NY, USA).
Results The Episono group had worse sleep quality, and more excessive daytime sleepiness than PwMS. Obstructive sleep apnea and restless legs syndrome were more frequent in the Episono group. There was no difference in chronotype between the two groups, with morning and intermediate preference. There was no correlation between EDSS and sleep complaints. Fatigue was intensively present among PwMS.
Conclusions Disease Modifying Drug (DMD)-treated PwMS had a lower frequency of sleep complaints, no difference in chronotype, and a higher prevalence of fatigue than a sample of São Paulo city residents. The immunomodulatory drugs commonly used to treat MS may have contributed to these findings.
Systematic review of pharmacological management in Creutzfeldt-Jakob disease: no options so far?
Authors: Miranda Luiz Henrique Lélis , Oliveira André Felipe Pastick de Holanda , Carvalho Davi Mariano de , Souza Gustavo Marques Figueredo , Magalhães João Guilherme Monteiro , Júnior Joselmo Alberto Cabral , Lima Pedro Thadeu Mertens Brainer de Queiroz , Júnior Renato Melo Aguiar , Filho Sérgio Pereira Lins , Melo Hugo Moura de Albuquerque 
Published: October 2022

Abstract
Background The Creutzfeldt-Jakob disease (CJD) is a spongiform encephalopathy that manifests as a rapidly progressive dementia syndrome. Currently, CJD has no cure, and many patients die within the first year, but some drugs are being studied as options for managing this condition.
Objective To evaluate the effectiveness of pharmacological treatments offered to patients with CJD as a means to increase survival and reduce cognitive deterioration.
Methods A systematic review of the literature was performed using 4 independent reviewers and 1 extra reviewer to resolve possible divergences in the search and analysis of papers indexed in MedLINE (PubMed), SciELO and Lilacs databases. The Medical Subject Heading (MeSH) terms used were: prion diseases, Creutzfeldt-Jakob disease, pharmacologic therapy, therapeutics, quinacrine, doxycycline, flupirtine, and pentosan polysulfate, with the Boolean operators AND and OR. This search included controlled clinical trials, uncontrolled clinical trials, and case series published from the year 2000 onwards, in the English language.
Results A total of 85 papers were found using the descriptors used. At the end of the selection analyses, 9 articles remained, which were analyzed fully and individually.
Conclusions None of the drugs evaluated proved significantly effective in increasing survival in patients with CJD. Flupirtine appears to have a beneficial effect in reducing cognitive deterioration in patients with CJD. However, additional studies are needed to establish better evidence and therapeutic options for the management of patients with CJD.
Modified Thromboelastography for Peri-interventional Assessment of Platelet Function in Cardiology Patients: A Narrative Review
Authors: Hartmann Jan , Curzen Nick 
Published: October 2022

AbstractViscoelastic testing (VET), such as thromboelastography, can measure whole blood coagulation dynamics in real time and is used across a range of clinical settings, including cardiac surgery, liver transplant, and trauma. The use of modified thromboelastography with platelet function assessment (TEG(R) PlateletMapping(R) Assay) can provide an analysis of platelet contribution to hemostasis, including the contribution of the P2Y12 receptor and thromboxane pathway to platelet function. The TEG PlateletMapping Assay has shown high correlation with the current gold standard test of platelet function, light transmission aggregometry, to measure arachidonic acid and adenosine diphosphate agonist-induced platelet activation. Studies have also shown comparable results with other whole blood platelet function tests. In this review, we explore the clinical applications of modified thromboelastography with platelet function assessment. This includes guiding dual antiplatelet therapy in relation to cardiac procedures, such as percutaneous coronary interventions, transcatheter aortic valve replacement, and left atrial appendage closure. We also explore the developing use of thromboelastography in the emergency care setting of coronavirus disease 2019, which is commonly associated with a hypercoagulable and hypofibrinolytic state. Despite a general lack of high-quality, grade 1 evidence regarding the use of modified thromboelastography with platelet function assessment in these disease areas, the ability of the TEG PlateletMapping Assay to measure global hemostasis and platelet reactivity rapidly and to view and evaluate results at the point of care makes it a promising area for further study for managing patient treatment and optimizing hemostatic therapy.