bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of compressed air consumption in a pneumatic vehicle
Authors: Marko P , Fiebig W 
Published: May 2022

Abstract
The aim of the research described in the article was to optimize compressed air consumption in a pneumatic driven vehicle to achieve the maximum traveled distance and maximum acceleration over a short distance. The Pneumatic vehicle was equipped with a 10-liter tank. The vehicle drive system consists of an actuator, a reciprocating movement which is converted into rotary motion and transmitted to the road wheels. The article analyses the impact on the range and maximum speed of a pneumatic vehicle based on parameters such as gear ratio, the amount of air supplied to the actuator, opening the drain valves before the piston reaches dead center, setting on the reduction valve, size of the buffer tank, and gear shift time. After the initial analytical estimation of the actuator operating parameters, a numerical analysis of the vehicle operation of the pneumatic and drive systems of the vehicle was performed in the Simcenter Amesim program. In this program, a pneumatic system model was created together with the vehicle drive system. Finally, conclusions from the simulations are presented, showing how the pneumatic system should be built and how it should be powered to obtain the maximum range and the greatest acceleration of the vehicle.
Matrix representation of an EV’s Sensory and Control System
Authors: Nagy István 
Published: May 2022

Abstract
This article will be the continuation of previously published papers and journal articles. The previous developments have been finished by the suggestion of possible matrix-representation of the sensory and control block diagram system of the examined, fully electric vehicle1 (EV) [1], [2], [3], [5]. This article will show, how these block diagrams can be represented by some special matrices. The first step in the developments was the creation of the sensory and control map of the system (in this form of expression the “system” is the electrical network of the vehicle). Later, this electrical network, based on functionality, was segmented into the different subsystems, like: EV Control System, Driver Control System,…, see [2]. Hereupon the subsystems could be represented by the graph of the subsystem and, as it is well known, each graph can be represented as a matrix. The problem arose from the fact, that these subsystems are overlapped with each other. The present article will show, how these overlaps can be handled by a special matrix representation.
The impact of COVID on the digitization of Hungarian maintenance sector
Authors: Juhász L , Pokorádi L 
Published: May 2022

Abstract
One of the biggest recent innovation trends in the manufacturing industry is the use of Industry 4.0 tools and the introduction of various digitalization solutions. However, in 2020, the COVID19 pandemic significantly changed the way companies organize their day-to-day operations and the way they plan to innovate in their sector, in the near future. In this paper, we present the views of maintenance professionals in Hungarian automotive companies. We have compared the status of different types of enterprises. In particular, we looked at the differences in the status of these companies in terms of digitalization development. This allowed us to draw further conclusions.
An Improved Equipment for Measuring Heating Caused by Reactive Loads
Authors: Bihari János , Marada Imre 
Published: May 2022

Abstract
In the case of gears that also perform a support function, taking into account the effect of reactive loads is an essential element of sizing. Pulsating or continuous but variable reactive loads can cause heating similar to or greater than in case of normal operation. This heating can be such that it significantly affects both the operating clearance and the strength characteristics of the gears. The effects of reactive loads were previously measured with the help of special drive units, which proved to be a useful method. However, due to the design of the drive units, these measurements were only able to demonstrate that the effect of the reactive loads is significant for the sizing even if they are not of a magnitude causing immediate failure of the gears. Our new research aims to quantify these effects for as many applications as possible. In this article, we introduce the features of the old method and the solutions, which aim to eliminate their disadvantages.
Innovative methods and research directions in the field of logistics
Authors: Juhászné Bíró T , Németh P 
Published: May 2022

Abstract
By the 21st century, logistics and various supply chains had become key units in the global market and corporate structures. Industry 4.0 has brought developments and implementations to life that have drastically changed and are still changing the practices used in certain areas of logistics. Many new technologies (advanced robotics, additive manufacturing, artificial intelligence (AI), blockchain, drones, Internet of Things (IoT)) have emerged in the digital world, which many companies are using to develop cyber-physical systems in order to increase efficiency, speed, accuracy and the ability to change and steer competition between companies around the world. Planning tasks at the strategic, tactical and operational levels are covered in the areas of production and logistics. The tasks presented here can be identified as extremely complex optimization problems that belong to the np-hard complexity class. These can be addressed in many cases with metaheuristics, and industry also often uses search strategies inspired by biological or physical processes. Metaheuristic algorithms simulate the behavior of a selected phenomenon in a given search area. Algorithms based on various principles can help optimize processes, such as: population-based algorithms, evolutionary methods, behavior-inspired procedures, swarm intelligence methods, etc. New technologies or metaheuristic procedures are also increasingly used in logistics due to the complexity of the tasks. This paper presents theoretical application possibilities of digital transformation, AI and IoT in the field of logistics. The paper provides a further brief overview of the problems surrounding metaheuristics, supported by examples. The article shows the impact of different Industry 4.0 technologies on logistics. There is a shortage of such comprehensive studies, so the article helps provide insight into innovative optimization opportunities in a larger area - the field of logistics. Within this one paper, the impact of new technologies on the field of logistics was collected. A brief description of these will help to identify further directions and deepen the applicability of the new methods in logistics.
Software developments for an electric motor test bench developed at the Faculty of Engineering of the University of Debrecen
Authors: Ádámkó É , Szántó A , Sziki G Á 
Published: May 2022

Abstract
At the Faculty of Engineering of the University of Debrecen, our research group has long-term experience in the dynamic modeling and simulation of electric motors. Several simulation modules have been developed during the last few years. The input data of the developed simulation modules are the technical parameters and characteristics of the analyzed motors. The mentioned technical data from the manufacturers is either not provided or it’s incomplete, thus, it is necessary to measure it. Additionally, the accuracy of the output dynamic functions, generated by the simulation modules, has to be tested experimentally. As a consequence, it was decided by the research group to realize a Measurement System for performing both above-mentioned experimental tasks routinely, at high accuracy and at a precision level. In this paper, a brief description of the Hardware Component of the Measurement System and a full detailed one of the developed Software Component is given. The Software Component of the Measurement System is implemented in NI LabVIEW, Java SE, and VBA with an underlying MySQL database. Applying the Software Component, the measured quantities can be monitored in real-time, displayed graphically while being stored in a database for later use.
Vehicle Dynamic Development and System Analysis Project
Authors: Szakács Tamás , Frigyik András B. 
Published: May 2022

Abstract
The Vehicle Construction Laboratory of the Óbuda University has been funded to develop Shell EcoMaraton, Bosch GoKart, Bosch Electromobile, Emerson Pneubobile, and Formula Student Hungary project cars. Some international cooperation, based on the European Commission’s Erasmus+ program, has already taken place in the lab. In the year 2021 a mixed team of Hungarian, and international students (participants of the Stipendium Hungaricum scholarship program) started to work on a project related to Vehicle Dynamic. The scope of the project is to develop a test car, that can be driven in a conventional way or capable of autonomous operation. The short range goals are the following: to build a car, with electric driving and steering capabilities, and to work out the system scheme of sensor, controller, and actuator network, for system development, mathematical analysis, and modelling/simulation.
Improved hepatoblast differentiation of human pluripotent stem cells by coffee bean derived graphene quantum dots
Authors: Kang Hyun Kyoung , Kim Dong Jin , Kim Min Soo , Kim Da-Hyun , Lee Jin Young , Sung Eun-Ah , Sarsenova Madina , Chae Park Seong , Hong Byung Hee , Kang Kyung-Sun 
Published: May 2022

Abstract
Graphene quantum dots (GQDs) have been found to promote the efficient differentiation of stem cells into a variety of cell types. However, their bioactivity and signaling mechanisms in the hepatic lineage have not been fully investigated. Here, we report that the hepatoblast (HB) differentiation rate can be promoted by using Ca2+-rich coffee bean (CB)-derived GQDs, where the incorporated calcium ions activate the signaling of insulin-like growth factor 1 receptor (IGF1R)-protein kinase B (AKT). We also found that the human pluripotent stem cell (hPSC)-derived HBs from the CB-GQD treatment tend to upregulate the maturation into hepatocyte-like cells and downregulate the differentiation towards cholangiocytes, thereby successfully obtaining a large number of functional hepatocyte-like cells. Moreover, the activation of IGF1R from the CB-GQD treatment enhances the HB differentiation efficiency regardless of growth factors, implying that chelated calcium may play a key role in activating IGF1R. Our findings suggest that CB-GQDs with independent bioactivity can be widely used in place of IGF1 and represent a cost-effective growth factor as well as a potential differentiation factor.
A frequency selective surface loaded two-layer composite for tunable microwave absorption
Authors: Zhao Yiming , Wang Qichao , Sun Yungang , Xuan Shanyong , Li Minghang 
Published: May 2022

Abstract
To obtain tunable microwave absorption, a strategy of constructing a frequency selective surface (FSS) on a two-layer composite is proposed. The designed FSS loaded two-layer composite is composed of a FSS constructed by evenly spaced circular copper sheet, an impedance matching layer (SiO2 fiber reinforced epoxy resin (EP) composite, SiO2f/EP) and a lossy layer. Both simulation and experiments indicate that the SiO2f/EP layer serves as a good impedance matching layer with increased microwave absorption efficiency. By analyzing the distributions of electric field, magnetic field as well as the power loss, the strong resonance should be attributed to the enhanced incident microwave caused by FSS.
Hydrogen storage in complex hydrides: past activities and new trends
Authors: Dematteis Erika Michela , Amdisen Mads B , Autrey Tom , Barale Jussara , Bowden Mark E , Buckley Craig E , Cho Young Whan , Deledda Stefano , Dornheim Martin , de Jongh Petra , Grinderslev Jakob B , Gizer Gökhan , Gulino Valerio , Hauback Bjørn C , Heere Michael , Heo Tae Wook , Humphries Terry D , Jensen Torben R , Kang Shin Young , Lee Young-Su , Li Hai-Wen , Li Sichi , Møller Kasper T , Ngene Peter , Orimo Shin-ichi , Paskevicius Mark , Polanski Marek , Takagi Shigeyuki , Wan Liwen , Wood Brandon C , Hirscher Michael , Baricco Marcello 
Published: May 2022

Abstract
Intense literature and research efforts have focussed on the exploration of complex hydrides for energy storage applications over the past decades. A focus was dedicated to the determination of their thermodynamic and hydrogen storage properties, due to their high gravimetric and volumetric hydrogen storage capacities, but their application has been limited because of harsh working conditions for reversible hydrogen release and uptake. The present review aims at appraising the recent advances on different complex hydride systems, coming from the proficient collaborative activities in the past years from the research groups led by the experts of the Task 40 ‘Energy Storage and Conversion Based on Hydrogen’ of the Hydrogen Technology Collaboration Programme of the International Energy Agency. An overview of materials design, synthesis, tailoring and modelling approaches, hydrogen release and uptake mechanisms and thermodynamic aspects are reviewed to define new trends and suggest new possible applications for these highly tuneable materials.
Uniform inference in high-dimensional Gaussian graphical models
Authors: Klaassen S , Kueck J , Spindler M , Chernozhukov V 
Published: May 2022

SummaryGraphical models have become a popular tool for representing dependencies within large sets of variables and are crucial for representing causal structures. We provide results for uniform inference on high-dimensional graphical models, in which the number of target parameters $d$ is potentially much larger than the sample size, under approximate sparsity. Our results highlight how graphical models can be estimated and recovered using modern machine learning methods in high-dimensional complex settings. To construct simultaneous confidence regions on many target parameters, it is crucial to have sufficiently fast estimation rates of the nuisance functions. In this context, we establish uniform estimation rates and sparsity guarantees for the square-root lasso estimator in a random design under approximate sparsity conditions. These might be of independent interest for related problems in high dimensions. We also demonstrate in a comprehensive simulation study that our procedure has good small sample properties in comparison to existing methods, and we present two empirical applications.
0013 Psychomotor Vigilance Test Performance Declines Related to Illness Severity, not Sleep
Authors: Doty Tracy , Mantua Janna , Gutierrez Ramiro , Alcala Ashley , Testa Kayla , Talaat Kawsar , Chaudhury Sidhartha , Isidean Sandra , Porter Chad 
Published: May 2022

Abstract

Introduction
While the Psychomotor Vigilance Test (PVT) has been used extensively to track vigilance degradation following sleep loss, there is evidence that it may also track vigilance degradation related to illness. However, it is unclear how much performance decline is driven by sleep loss related to an illness or the illness itself independent of sleep loss. Here we assessed how sleep and acute infectious diarrhea impact vigilance performance in a controlled human infection model (CHIM) with enterotoxigenic Escherichia coli (ETEC).

Methods
During a CHIM assessing the efficacy of an immunoprophylactic targeting ETEC, we measured sleep via actigraphy over an 8-day inpatient period. A 10-minute PVT was also administered up to three times each day in the morning, afternoon, and evening. Participants ingested an oral immunoprophylaxis 3 times/day on days -2 and -1, and ingested ETEC on day 0. Participants were categorized as to whether or not they experienced the primary endpoint of moderate-severe diarrhea (MSD).

Results
Among 56 participants (aged 34.7±8.5 years, 64% male), 54% reached the primary endpoint of moderate-severe diarrhea following ETEC infection. Total sleep times across the study did not differ between those with and without MSD. While PVT minor lapses (i.e., not responding within 500 milliseconds) did increase following ETEC infection for all subjects as revealed by a mixed linear model [effect of day: f(7,657)=3.35, p=0.002], there was also a significant main effect of group [f(1,657)=5.85, p=0.016], where those participants who experienced MSD following ETEC infection had more minor lapses across the study than those who did not experience MSD (6.28±0.43 vs 4.88±0.38).

Conclusion
While the negative impact of sleep loss on performance has been well demonstrated, these are the first data to suggest that illness severity[KT1] , independent of sleep loss, also negatively impacts performance. In operational populations such as the military, special care should be taken to prevent illness and remove ill operators from the field, just as this care should be taken to prevent sleep loss and remove sleepy operators. By preventing and monitoring sleep loss and illness, these operations can avoid potentially costly performance errors.

Support (If Any)
The clinical trial from which these data were obtained was funded by the Congressionally Directed Medical Research Program through the Joint Warfighter Medical Research Program under Award No. W81XWH-15-C-0083 to the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. The U.S. Army Medical Research Acquisition Activity was the awarding and administering acquisition office. The study was also funded by a Collaborative Research and Development Agreement with PATH Enteric Vaccine Solutions (NCRADA-NMRC-15-9589), as well as by the Military Operational Medicine Research Program (MOMRP).
0022 Improving predicted effectiveness of shiftworkers in watchfloors
Authors: Matsangas Panagiotis , Shattuck Nita , Sheehan Sarah , Dotson Elizabeth 
Published: May 2022

Abstract

Introduction
In support of 24/7 hour operations around the globe, Navy and Marine Corps shore-based watchfloors provide information, intelligence, and technical support to the warfighter. Personnel working on these watchfloors are challenged to obtain consistent sleep due to shift working. The study objectives were to model the predicted effectiveness (PE) of the current watch schedule and recommend a new schedule to improve sleep, safety, and performance.

Methods
In a 3-week longitudinal, naturalistic study, we assessed the work/rest patterns and well-being of watchstanders while on their typical watch schedule. Participants (N=11, age:19-33yrs) completed an online sleep/activity log for the study period. Standardized tools (Pittsburgh Sleep Quality Index--PSQI, Epworth Sleepiness Scale--ESS, Insomnia Severity Index--ISI, Profile of Mood States--POMS) were completed pre/post-study. Based on study findings combined with information gathered from the command leadership, we designed an improved watch schedule. The Fatigue Avoidance Scheduling Tool (version 3.3.01T) employing the Sleep, Activity, Fatigue, and Task Effectiveness model (SAFTE/FAST) was used to model PE in the legacy and newly improved watch schedules.

Results
The median daily reported sleep duration was 6hrs (range: 5-8.5hrs). Nine participants (82%) were classified as poor sleepers and six (55%) had elevated daytime sleepiness. Four (36%) participants had moderately severe/severe insomnia symptoms. In terms of mood, 10 (91%) participants had a lower vigor-activity score than the adult norms, whereas eight (73%) scored higher than the adult norms for fatigue. The mid-shift watches had low PE that dropped steeply throughout the shift. The timing of low PE coincided with the period in which personnel was briefing leadership and/or commuting from work.

Conclusion
Based on our findings, we recommended a schedule that enables more regular sleep patterns. Compared to the legacy schedule, the new schedule increased both the number of week days and weekend days off, with 2-3 full weekends off per month. Also, PE was improved and the trough in PE did not occur during the commute. Lastly, we recommended that the new watch schedule should rotate less frequently with longer times on an assigned shift.

Support (If Any)
This work was supported in part by the Naval Medical Research Center's Naval Advanced Medical Development Program.
0041 Chronotype predicts health outcomes but not sleep duration in early pandemic sleep schedules
Authors: Zendels Philip , Gaultney Jane 
Published: May 2022

Abstract

Introduction
Lockdowns associated with the COVID-19 pandemic allowed for individuals to change their schedules. Chronicity is a trait-like preference for individuals’ times of the day for activity and feeling best. As a result of the lockdowns, some individuals were able to adjust their schedule to reflect personal chronotype needs. This study examined whether chronotype predicted sleep duration and health outcomes.

Methods
A sample of 304 participants were recruited through Amazon’s Mechanical Turk service to fill out surveys relating to personality and health. Individuals responded with their normal bedtime and waketime for weeknights and weekends and filled out the Morningness-Eveningness Questionnaire (MEQ; Horne & Östberg, 1976). Self-reported health outcomes were measured via 9 items on the Patient Reported Outcomes Measurement Information System (PROMIS; Cella et al., 2010). Data were cleaned and analyzed via linear regressions in SPSS with age, sex, race, ethnicity and education as covariates.

Results
Participants reported an average of 8.52 hours of sleep (SD = 1.97 hours). 35.3% of the sample scored strong- or moderately morning-type, 54.7% were neither morning-nor evening-type and 10% scored as evening- or strong-evening types (M = 54.95; SD = 9.42). Results from the PROMIS ranged from 18 to 45 (M = 32.24, SD = 5.49). The model predicting sleep duration (R2 = .06, p = .03) produced a significant effect of ethnicity but not chronicity. Hispanic or Latino ethnicity reported shorter sleep durations relative to those who self-identified as non-Hispanic or Latino. The model predicting PROMIS (general health) scores (R2 = .14, p &lt; .001) produced effects of education (b = .46, p = .04) and Morningness (b = .21, p &lt; .001). People with higher educational levels and those with morning preferences reported better health.

Conclusion
Morningness is often associated with better self-regulation, lower risky behaviors, better physical and mental health and better sleep. During the early stages of the COVID-19 pandemic, lockdowns allowed many individuals more scheduling flexibility. As a result, sleep duration differences across chronotypes were absent, though health differences remained. Future research should continue to explore differences in sleep schedules in predicting health outcomes.

Support (If Any)
Charlie Reeve and the Misfits lab at UNCC.