Comparison of Cardiovascular Parameters and Internal Training Load of Different 1-h Training Sessions in Non-elite CrossFit^(®)Athletes

Purpose The fact that CrossFit^(®)is the best-known and rapidly growing concept for high-intensity interval training(HIIT)and high-intensity functional training(HIFT)results in a continuous increase of athletes performing CrossFit^(®).In the more than 15,000 CrossFit^(®)Affiliates worldwide,the training concept is usually offered in 1-h training sessions containing the CrossFit^(®)-related workout of the day(WOD),as well as a general warm-up,movement demonstrations,and skill training.Here,we report how physiological parameters measured by heart rate(HR)values vary during four different 1-h CrossFit^(®)training sessions of non-elite athletes(n=27)in a local affiliated training center and what influencing factors may exist.Methods The duration of the 1-h training sessions were divided into a warm-up part(WU-part),a skill development part combined with strength exercises(A-part),followed by the WOD part(B-part).Results Analysis of HR values shows high training intensity(≥91%HR_(max))not throughout the duration of each training session,only during B-part.The mean HR values in B-part differ significantly compared to the remaining training parts(P<0.001)for all four training sessions.Comparison of different CrossFit^(®)experience levels revealed no significant differ-ence in acute physiological demands and training load between beginner and experienced CrossFit^(®)athletes.Conclusion Our results may suggest that practicing CrossFit^(®)in 1-h training sessions combined anaerobic and aerobic exercise intensities,with the training concept allows beginners and experienced athletes to be trained with the same cardio-vascular responses and training intensities.

Nanoelectromechanical Sensors Based on Suspended 2D Materials

The unique properties and atomic thickness of two-dimensional(2D)materials enable smaller and better nanoelectromechanical sensors with novel functionalities.During the last decade,many studies have successfully shown the feasibility of using suspended membranes of 2D materials in pressure sensors,microphones,accelerometers,and mass and gas sensors.In this review,we explain the different sensing concepts and give an overview of the relevant material properties,fabrication routes,and device operation principles.Finally,we discuss sensor readout and integration methods and provide comparisons against the state of the art to show both the challenges and promises of 2D material-based nanoelectromechanical sensing.

Synthesis of tungsten ditelluride thin films and highly crystalline nanobelts from pre-deposited reactants

Tungsten ditelluride(WTe_(2))is a layered transition metal dichalcogenide(TMD)that has attracted increasing research inter-est in recent years.WTe_(2) has demonstrated large non-saturating magnetoresistance,potential for spintronic applications and promise as a type-II Weyl semimetal.The majority of works on WTe_(2) have relied on mechanically exfoliated flakes from chemical vapour transport(CVT)-grown crystals for their investigations.While producing high-quality samples,this method is hindered by several disadvantages including long synthesis time,high-temperature annealing and an inherent lack of scalability.In this work,a synthesis method is demonstrated that allows the production of large-area polycrystalline films of WTe_(2).This is achieved by the reaction of pre-deposited films of W and Te at a relatively low temperature of 550℃.Sputter X-ray photoelectron spectroscopy reveals the rapid but self-limiting nature of the oxidation of these WTe_(2) films in ambient conditions.The WTe_(2) films are composed of areas of micrometre-sized nanobelts that can be isolated and offer potential as an alternative to CVT-grown samples.These nanobelts are highly crystalline with low defect densities indicated by transmission electron microscopy and show promising initial electrical results.

Sifu-a cybersecurity awareness platform with challenge assessment and intelligent coach

Software vulnerabilities,when actively exploited by malicious parties,can lead to catastrophic consequences.Proper handling of software vulnerabilities is essential in the industrial context,particularly when the software is deployed in critical infrastructures.Therefore,several industrial standards mandate secure coding guidelines and industrial software developers’training,as software quality is a significant contributor to secure software.CyberSecurity Challenges(CSC)form a method that combines serious game techniques with cybersecurity and secure coding guidelines to raise secure coding awareness of software developers in the industry.These cybersecurity awareness events have been used with success in industrial environments.However,until now,these coached events took place on-site.In the present work,we briefly introduce cybersecurity challenges and propose a novel platform that allows these events to take place online.The introduced cybersecurity awareness platform,which the authors call Sifu,performs automatic assessment of challenges in compliance to secure coding guidelines,and uses an artificial intelligence method to provide players with solution-guiding hints.Furthermore,due to its characteristics,the Sifu platform allows for remote(online)learning,in times of social distancing.The CyberSecurity Challenges events based on the Sifu platform were evaluated during four online real-life CSC events.We report on three surveys showing that the Sifu platform’s CSC events are adequate to raise industry software developers awareness on secure coding.

The Perception of Flood Risks: A Case Study of Babessi in Rural Cameroon

Although risk perception of natural hazards has been identified as an important determinant for sound policy design,there is limited empirical research on it in developing countries.This article narrows the empirical literature gap.It draws from Babessi,a rural town in the Northwest Region of Cameroon.Babessi was hit by a severe flash flood in 2012.The cross-disciplinary lens applied here deciphers the complexity arising from flood hazards,often embedded in contexts characterized by poverty,a state that is constrained in disaster relief,and market-based solutions being absent.Primary data were collected via snowball sampling.Multinomial logistic regression analysis suggests that individuals with leadership functions,for example,heads of households,perceive flood risk higher,probably due to their role as household providers.We found that risk perception is linked to location,which in turn is associated with religious affiliation.Christians perceive floods riskier than Muslims because the former traditionally reside at the foot of hills and the latter uphill;rendering Muslims less exposed and eventually less affected by floods.Finally,public disaster relief appears to have built up trust and subsequently reduced risk perception,even if some victims remained skeptical of state disaster relief.This indicates strong potential benefits of public transfers for flood risk management in developing countries.

On the helium bubble swelling in nano-oxide dispersion-strengthened steels

The development of structural materials resistant to harsh radiation environments requires an in-depth understanding of the early stage of the aging processes.In radiation environments with high transmutation helium production rates such as in fusion and spallation applications,even materials with otherwise acceptable radiation stability may suffer from radiation embrittlement related to helium bubble formation.While theoretical modeling of helium-assisted cavity nucleation in pure metals and simple alloys provides some useful guidelines at the atomic scale level,these,however,do not overlap with the size resolution of available experimental techniques.In this study,we employed slow positron beam spectroscopy to characterize the nucleation and growth of nano-scale helium bubbles in martensitic steels strengthened by thermodynamically stable nano-oxide dispersoids.In combination with transmission electron microscopy,we experimentally characterized the evolution of helium bubbles from small clusters of radiation-induced vacancies to large cavities well resolvable by TEM.Superior radiation resistance of oxide-dispersion strengthened steels dominates only in the early stages of bubble evolution,where positron lifetime measurements provide a missing piece of the microstructural puzzle conventionally constructed by TEM.

On strong-scaling and open-source tools for analyzing atom probe tomography data

The development of strong-scaling computational tools for high-throughput methods with an open-source code and transparent metadata standards has successfully transformed many computational materials science communities.While such tools are mature already in the condensed-matter physics community,the situation is still very different for many experimentalists.Atom probe tomography(APT)is one example.This microscopy and microanalysis technique has matured into a versatile nano-analytical characterization tool with applications that range from materials science to geology and possibly beyond.Here,data science tools are required for extracting chemo-structural spatial correlations from the reconstructed point cloud.For APT and other high-end analysis techniques,post-processing is mostly executed with proprietary software tools,which are opaque in their execution and have often limited performance.Software development by members of the scientific community has improved the situation but compared to the sophistication in the field of computational materials science several gaps remain.This is particularly the case for open-source tools that support scientific computing hardware,tools which enable high-throughput workflows,and open welldocumented metadata standards to align experimental research better with the fair data stewardship principles.To this end,we introduce paraprobe,an open-source tool for scientific computing and high-throughput studying of point cloud data,here exemplified with APT.We show how to quantify uncertainties while applying several computational geometry,spatial statistics,and clustering tasks for post-processing APT datasets as large as two billion ions.These tools work well in concert with Python and HDF5 to enable several orders of magnitude performance gain,automation,and reproducibility.

Status,perspectives and trends of satellite navigation

This paper reviews the status of satellite navigation(as per 11 May 2020)-without claim for completeness-and discusses the various global navigation satellite systems,regional satellite navigation systems and satellite-based augmentation systems.Problems and challenges for delivering nowadays a safe and reliable navigation are discussed.New opportunities,perspectives and megatrends of satellite navigation are outlined.Some remarks are closing this paper emphasizing the great value of satellite navigation at present and in future.