Search

Abstract The NA60 experiment has studied low-mass muon pair production in proton–nucleus collisions with a system of Be, Cu, In, W, Pb and U targets, using a 400 GeV proton beam at the CERN SPS. The transverse momentum spectra of the $$\rho /\omega $$ ρ/ω and $$\phi $$ ϕ mesons are measured in the full $$p_{\mathrm {T}}$$ pT range accessible, from $$p_{\mathrm {T}}= 0$$ pT=0 up to $$2 \, {\hbox {GeV/c}}$$ 2GeV/c . The nuclear dependence of the production cross sections of the $$\eta $$ η , $$\omega $$ ω and $$\phi $$ ϕ mesons has been found to be consistent with the power law $$\sigma _{\mathrm {pA}} \propto {\mathrm {A}}^\alpha $$ σpA∝Aα , with the $$\alpha $$ α parameter increasing as a function of $$p_{\mathrm {T}}$$ pT for all the particles, and an approximate hierarchy $$\alpha _\eta \approx \alpha _\phi > \alpha _\omega $$ αη≈αϕ>αω . The cross section ratios $$\sigma _\eta /\sigma _\omega $$ ση/σω , $$\sigma _\rho /\sigma _\omega $$ σρ/σω and $$\sigma _\phi /\sigma _\omega $$ σϕ/σω have been studied as a function of the size A of the production target, and an increase of the $$\eta $$ η and $$\phi $$ ϕ yields relative to the $$\omega $$ ω is observed from p–Be to p–U collisions.

Conditionally automated vehicles (Level 3 SAE) are emerging on the roads, but long periods without engaging in a non-driving-related task can reduce drivers’ vigilance. This study aims to determine whether driver fatigue can be accurately predicted using physiological signals and machine learning (ML) techniques in such a context. 63 young drivers completed two separate conditional automated drives of 30 min each, in either a rural or a urban area. Half of them had been mildly sleep-deprived the previous night (slept less than six hours). Electrocardiogram (ECG), electrodermal activity (EDA), and respiration were collected, along with subjective measures of sleepiness and affective state. Using ML, sleep deprivation, driving environment, and sleepiness could be predicted from physiological features with an accuracy of 99%, 85%, and 73% respectively. Signal segmentation increased model accuracy, and EDA features were the most predictive. The differences between the results obtained from statistical analyses of sleepiness measures and the accuracy achieved by ML models are discussed. The results of this empirical study indicate that even mild sleep deprivation affects the physiological state of drivers, which can have serious consequences when combined with long periods of inactivity. Car manufacturers and researchers should take this into account when designing intelligent systems capable of providing drivers with appropriate warnings before a critical situation arises.

Abstract Hybrid teaching (synchronous online and on-site teaching) offers many advantages (e.g., increased flexibility). However, previous research has suggested that students who join classes online suffer higher levels of distractibility, which might translate into students engaging in more off-task activities. This, in turn, can impair students’ learning performance. The following quasi-experimental field study investigated this specific link between teaching mode, engagement in off-task activities, and learning performance. We collected survey data from N = 690 students in six hybrid classes (N = 254 online, N = 436 on-site). Participants reported the amount of time they spent engaging in digital and non-digital off-task activities and responded to a quiz on the course material. Results revealed that online students spent more time engaging in off-task activities than on-site students. Further, results were consistent with our hypothesis that joining the class online is associated with lower learning performance via time spent on digital off-task activities.

Abstract Aortic vascular graft infections have high morbidity and mortality rate, however, patients often do not show symptoms. Continuous implant surface monitoring will allow for early detection of infections on implant surfaces, which allows for antibiotic treatment prior to biofilm formation. We explore the possibility of using heat flux sensors mounted on an aortic vascular graft to sense the localized heat production at the onset of infectious growth. We apply Finite Element Model simulations to demonstrate changes of the heat transfer coefficient depending on different pulsatile flow parameters. We determine various differences, the main influence being the distance travelled from the inlet of the simulation with the highest heat transfer coefficient closest to the inlet and decreasing along the direction of travel of the fluid. The determined range of heat transfer coefficients of 200 to 4800 W/m2 was applied to a second simulation of the thermal environment of the implant. We determined the heat transfer efficiency of the aortic graft system depending on different graft materials and thicknesses. We are further able to determine that the early detection of infection is possible by comparing the simulated amount of heat flux produced locally with the resolution of a commercial heat flux sensor.

This paper explores the minimal knowledge a listener needs tocompensate for phonological assimilation, one kind of phono-logical process responsible for variation in speech. We usedstandard automatic speech recognition models to represent En-glish and French listeners. We found that, first, some typesof models show language-specific assimilation patterns com-parable to those shown by human listeners. Like English lis-teners, when trained on English, the models compensate morefor place assimilation than for voicing assimilation, and likeFrench listeners, the models show the opposite pattern whentrained on French. Second, the models which best predict thehuman pattern use contextually-sensitive acoustic models andlanguage models, which capture allophony and phonotactics,but do not make use of higher-level knowledge of a lexiconor word boundaries. Finally, some models overcompensate forassimilation, showing a (super-human) ability to recover theunderlying form even in the absence of the triggering phono-logical context, pointing to an incomplete neutralization notexploited by human listeners.

Advanced driver assistances are becoming increasingly common in commercial cars, not only to assist but also to free drivers from manual driving whenever possible. Soon, drivers should be allowed to engage in non-driving-related tasks. The fact that responsibility for driving is shifting from humans to machines must be considered in the development of these assistances in order to guarantee safety and trust. In this article, we introduce AdVitam (for Advanced Driver-Vehicle Interaction to Make future driving safer), an autonomous system aiming at maintaining driver’s situation awareness and optimizing takeover quality during conditionally automated driving. The information conveyed to drivers is dynamically adapted to achieve these goals, depending on the driving environment and the driver’s physiological state. This system consists of three connected modules. The first module (Driver State) predicts the driver’s state with machine learning and physiological signals as inputs. The second module (Supervision) uses different interfaces (a haptic seat, a personal device, and ambient lights) to maintain the drivers’ situation awareness during the autonomous driving phases. The third module (Intervention) is a machine learning model that chooses the most appropriate combination among haptic, auditory, and visual modalities to request the driver to take over control and thus optimize takeover quality. To evaluate the system and each module independently, a preliminary user study with 35 drivers was conducted in a fixed-base driving simulator. All participants drove in two different environments (rural and urban). In addition, the activation of the Supervision and Intervention modules were manipulated as two between-subject factors. Results show that conveying information on the driving environment status through multimodal interfaces increases drivers’ situation awareness (i.e., better identification of potential problems in the environment) and trust in the automated vehicle. However, the system does not show positive outcomes on takeover quality. Besides, the Driver State module provided consistent predictions with the experimental manipulation. The system proposed in this paper could lead to better acceptance and safety when conditionally automated vehicles will be released by increasing drivers’ trust during phases of automated driving.

This dataset contains data of 346 drivers collected during six experiments conducted in a fixed-base driving simulator. Five studies simulated conditionally automated driving (L3-SAE), and the other one simulated manual driving (L0-SAE). The dataset includes physiological data (electrocardiogram (ECG), electrodermal activity (EDA), and respiration (RESP)), driving and behavioral data (reaction time, steering wheel angle, …), performance data of non-driving-related tasks, and questionnaire responses. Among them, measures from standardized questionnaires were collected, either to control the experimental manipulation of the driver's state, or to measure constructs related to human factors and driving safety (drowsiness, mental workload, affective state, situation awareness, situational trust, user experience).In the provided dataset, some raw data have been processed, notably physiological data from which physiological indicators (or features) have been calculated. The latter can be used as input for machine learning models to predict various states (sleep deprivation, high mental workload, ...) that may be critical for driver safety. Subjective self-reported measures can also be used as ground truth to apply regression techniques. Besides that, statistical analyses can be performed using the dataset, in particular to analyze the situational awareness or the takeover quality of drivers, in different states and different driving scenarios.Overall, this dataset contributes to better understanding and consideration of the driver's state and behavior in conditionally automated driving. In addition, this dataset stimulates and inspires research in the fields of physiological/affective computing and human factors in transportation, and allows companies from the automotive industry to better design adapted human-vehicle interfaces for safe use of automated vehicles on the roads.

This study investigates the acceptance of social robots by higher education students in the social sciences. Pepper, a humanoid social robot from SoftBank Robotics, provided a sample of its capabilities during a first semester, large-scale, university course, "Introduction to academic writing."From this course, 462 freshmen participated in our survey. The unified theory of acceptance and use of technology (UTAUT) acts as the conceptual framework, and partial least squares structural equation modelling (PLS-SEM) as the method for data analysis. The four perceived characteristics--trustworthiness, adaptiveness, social presence and appearance--all predict the intention to use the robot for learning purposes; anxiety regarding making mistakes in handling the robot and about privacy issues are not significant predictors. An importance-performance map analysis indicated adaptiveness as the robot's most important characteristic for predicting student behavioural intention. Overall, however, the study shows that students do not have the intention to rely on social robots for learning purposes at the current level of state-of-the-art technology: behavioural intention reaches only 36.6% of the theoretical maximum.

BackgroundMelioidosis is a disease caused by the bacterium Burkholderia pseudomallei, infecting humans and non-human primates (NHP) through contaminated soil or water. World-wide there are an estimated 165,000 human melioidosis cases each year, but recordings of NHP cases are sporadic. Clinical detection of melioidosis in humans is primarily by culturing B. pseudomallei, and there are no standardized detection protocols for NHP. NHP are an important animal model for melioidosis research including clinical trials and development of biodefense countermeasures.Methodology/principle findingsWe evaluated the diagnostic potential of the multiple antigen serological assay, BurkPx, in NHP using two sera sets: (i) 115 B. pseudomallei-challenged serum samples from 80 NHP collected each week post-exposure (n = 52) and at euthanasia (n = 47), and (ii) 126 B. pseudomallei-naïve/negative serum samples. We observed early IgM antibody responses to carbohydrate antigens followed by IgG antibody recognition to multiple B. pseudomallei protein antigens during the second week of infection. B. pseudomallei negative serum samples had low to intermediate antibody cross reactivity to the antigens in this assay. Infection time was predicted as the determining factor in the variation of antibody responses, with 77.67% of variation explained by the first component of the principal component analysis. A multiple antigen model generated a binary prediction metric ([Formula: see text]), which when applied to all data resulted in 100% specificity and 63.48% sensitivity. Removal of week 1 B. pseudomallei challenged serum samples increased the sensitivity of the model to 95%.Conclusion/significanceWe employed a previously standardized assay for humans, the BurkPx assay, and assessed its diagnostic potential for detection of B. pseudomallei exposure in NHP. The assay is expected to be useful for surveillance in NHP colonies, in investigations of suspected accidental releases or exposures, and for identifying vaccine correlates of protection.

Burkholderia pseudomallei, the causative agent of melioidosis, is a gram-negative soil bacterium well recognized in Southeast Asia and northern Australia. However, wider and expanding global distribution of B. pseudomallei has been elucidated. Early diagnosis is critical for commencing the specific therapy required to optimize outcome. Serological testing using the indirect hemagglutination (IHA) antibody assay has long been used to augment diagnosis of melioidosis and to monitor progress. However, cross reactivity and prior exposure may complicate the diagnosis of current clinical disease (melioidosis). The goal of our study was to develop and initially evaluate a serology assay (BurkPx) that capitalized upon host response to multiple antigens. Antigens were selected from previous studies for expression/purification and conjugation to microspheres for multiantigen analysis. Selected serum samples from non-melioidosis controls and serial samples from culture-confirmed melioidosis patients were used to characterize the diagnostic power of individual and combined antigens at two times post admission. Multiple variable models were developed to evaluate multivariate antigen reactivity, identify important antigens, and determine sensitivity and specificity for the diagnosis of melioidosis. The final multiplex assay had a diagnostic sensitivity of 90% and specificity of 93%, which was superior to any single antigen in side-by-side comparisons. The sensitivity of the assay started at >85% for the initial serum sample after admission and increased to 94% 21 days later. Weighting antigen contribution to each model indicated that certain antigen contributed to diagnosis more than others, which suggests that the number of antigens in the assay can be decreased. In summation, the BurkPx assay can facilitate the diagnosis of melioidosis and potentially improve on currently available serology assays. Further evaluation is now required in both melioidosis-endemic and non-endemic settings.

ObjectiveTo observe the real-world utilization patterns, effectiveness and safety profile of follitropin delta in women ≥18 years naïve to ovarian stimulation undergoing in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI).DesignProspective, multinational, multicenter, observational study. All IVF/ICSI treatment protocols were conducted according to routine clinical practice, including undertaking fresh/frozen transfers. Outcomes included use of dosing algorithm, follitropin delta dosing patterns, ovarian response, pregnancy rates and adverse drug reactions (ADRs).ResultsThe first ovarian stimulation cycle using follitropin delta was initiated in 944 women. Mean baseline demographics were: age, 33.5 ± 4.7 years; bodyweight, 67.1 ± 13.6 kg; anti-Müllerian hormone, 20.3 ± 16.1 pmol/L (2.84 ± 2.25 ng/mL). The dosing algorithm was used to calculate the follitropin delta daily starting dose in 893/944 women (94.5%). The mean difference between the calculated and prescribed daily dose was small (0.2 ± 1.40 µg). The mean daily starting follitropin delta dose was 10.4 ± 2.72 µg and the mean total dose administered was 104 µg. Follitropin delta dose adjustments were reported for 57/944 (6.0%) women. The mean number of retrieved oocytes was 10.1 ± 7.03. Ongoing pregnancy at 10–11 weeks was reported for 255 women (27.0% per initiated cycle and 43.1% per fresh transfer [n=592]). Cumulative ongoing pregnancy rate after fresh and/or frozen transfer was 36.4% (344/944). Four women discontinued follitropin delta due to ADRs. Ovarian hyperstimulation syndrome (OHSS) was the most frequently reported ADR (n=37 [3.9%]); most cases of OHSS were of mild or moderate intensity (n=30 [3.2%]).ConclusionsThis large real-world study of follitropin delta utilization patterns confirms its good pregnancy rates while minimizing OHSS risk during first ovarian stimulation cycle.

ABSTRACT Bioactivities of fungal peptides are of interest for basic research and therapeutic drug development. Some of these peptides are derived from “KEX2-processed repeat proteins” (KEPs), a recently defined class of precursor proteins that contain multiple peptide cores flanked by KEX2 protease cleavage sites. Genome mining has revealed that KEPs are widespread in the fungal kingdom. Their functions are largely unknown. Here, we present the first in-depth structural and functional analysis of KEPs in a basidiomycete. We bioinformatically identified KEP-encoding genes in the genome of the model agaricomycete Coprinopsis cinerea and established a detection protocol for the derived peptides by overexpressing the C. cinerea KEPs in the yeast Pichia pastoris. Using this protocol, which includes peptide extraction and mass spectrometry with data analysis using the search engine Mascot, we confirmed the presence of several KEP-derived peptides in C. cinerea, as well as in the edible mushrooms Lentinula edodes, Pleurotus ostreatus, and Pleurotus eryngii. While CRISPR-mediated knockout of C. cinerea kep genes did not result in any detectable phenotype, knockout of kex genes caused defects in mycelial growth and fruiting body formation. These results suggest that KEP-derived peptides may play a role in the interaction of C. cinerea with the biotic environment and that the KEP-processing KEX proteases target a variety of substrates in agaricomycetes, including some important for mycelial growth and differentiation. IMPORTANCE Two recent bioinformatics studies have demonstrated that KEX2-processed repeat proteins are widespread in the fungal kingdom. However, despite the prevalence of KEPs in fungal genomes, only few KEP-derived peptides have been detected and studied so far. Here, we present a protocol for the extraction and structural characterization of KEP-derived peptides from fungal culture supernatants and tissues. The protocol was successfully used to detect several linear and minimally modified KEP-derived peptides in the agaricomycetes C. cinerea, L. edodes, P. ostreatus, and P. eryngii. Our study establishes a new protocol for the targeted search of KEP-derived peptides in fungi, which will hopefully lead to the discovery of more of these interesting fungal peptides and allow a further characterization of KEPs.

Voluntary Sustainability Standards (VSS) are prominent governance instruments that define and verify sustainable agricultural land use at farm and supply chain levels. However, agricultural production can prompt spillover dynamics with implications for sustainability that go beyond these scales, e.g., through runoff of chemical inputs or long-distance migrant worker flows. Scientific evidence on the governance of spillovers through VSS is, however, limited. This study investigates the extent to which VSS regulate a set of 21 environmental and socio-economic spillovers of agricultural land use. To this end, we assessed the spillover coverage in 100 sustainability standards. We find that VSS have a clear tendency to cover environmental spillovers more extensively than socio-economic spillovers. Further, we show how spillover coverage differs across varying types of standard-setting organizations and VSS verification mechanisms. Finally, we discuss the role and limitations that VSS can have in addressing the revealed gaps.

Global commodity flows between distally connected social-ecological systems pose important challenges to sustainability governance. These challenges are partly due to difficulties in designing and implementing governance institutions that fit or match the scale of the environmental and social problems generated in such telecoupled systems. We focus on the spatial dimension of governance fit in relation to global commodity flows and telecoupled systems. Specifically, we draw on examples from land use and global agricultural commodity governance to examine two overarching types of governance mismatches: boundary mismatches and resolution mismatches. We argue that one way to address mismatches is through governance rescaling and illustrate this approach with reference to examples of three broad types of governance approaches: trade agreements, due diligence laws, and landscape approaches to supply chain governance. No single governance approach is likely to address all mismatches, highlighting the need to align multiple governance approaches to govern telecoupled systems effectively.

Vaccine hesitancy (VH) is a complex and context-specific phenomenon that is linked to under-immunization and poses challenges to immunization programs. The Parent Attitudes about Childhood Vaccines (PACV) is an instrument developed to measure VH. We translated the PACV into three languages (German, French and Italian) and administered it to 1388 Swiss parents. We used exploratory factor analysis (EFA) to confirm the scale sub-domains, Cronbach’s alpha to assess internal consistency reliability, and Mokken scale analysis (MSA), to explore unidimensionality of each language version. We determined to construct validity by linking parental PACV score to children’s immunization status for the first dose of measles vaccine. For the 15-item PACV, EFA extracted three sub-domains in German and French and four sub-domains in Italian. Cronbach’s alpha was >0.8 across the three languages, and MSA produced a 13-item German, 14-item French, and 11-item Italian PACV. EFA and MSA of the short version PACV extracted a single factor and scale with Cronbach’s alpha >0.7 in all three language versions. VH was significantly associated with non-timely receipt of the first dose of measles in all languages (odds ratio of 20.7, 21.3, and 8.3 for German, French, and Italian languages, respectively). The translated and revised PACV-15 versions are valid and reliable instruments for VH measurement. The structure and reliability of the short version of the PACV was as good as the long version. Our results suggest that the PACV can be used to measure parental VH outside the US in the validated languages.

Abstract Background Endothelial dysfunction might contribute to the development of leptospiral pulmonary hemorrhage syndrome (LPHS). Hypothesis Serum concentrations of markers of endothelial activation and dysfunction are higher in dogs with leptospirosis and correlate with the occurrence of LPHS and a higher case fatality rate. Animals Clinically healthy dogs (n = 31; 10/31 dogs confirmed healthy based on no detected abnormalities on blood work), dogs with leptospirosis with LPHS (n = 17) and without LPHS (n = 15), dogs with acute kidney injury not due to leptospirosis (AKI‐nL, n = 34). Methods Observational study. Serum concentrations of soluble intercellular adhesion molecule 1 (sICAM‐1), vascular endothelial growth factor (VEGF), and angiopoietin‐2 (Ang‐2) at admission were compared between groups. Correlations with outcome and the accuracy to predict LPHS were examined. Results Soluble intercellular adhesion molecule (sICAM‐1), VEGF, and Ang‐2 concentrations were higher in dogs with AKI‐nL (sICAM‐1 34.7 ng/mL, interquartile range [IQR] = 24.4‐75.5; VEGF 43.1 pg/mL, IQR = 12.3‐79.2; Ang‐2 8.5 ng/mL, IQR = 6.2‐12.3), leptospirosis without LPHS (sICAM‐1 45.1 ng/mL, IQR = 30.6‐59.0; VEGF 32.4 pg/mL, IQR = 12.5‐62.6; Ang‐2 9.6 ng/mL, IQR = 6.9‐19.3), and LPHS (sICAM‐1 69.7 ng/mL, IQR = 42.1‐89.1; VEGF 51.8 pg/mL, IQR = 26.3‐96.7; Ang‐2 8.0 ng/mL, IQR = 5.6‐12.2) compared to controls (P

Abstract Background A strong health workforce is a key building block of a well-functioning health system. To achieve health systems goals, policymakers need information on what works to improve and sustain health workforce performance. Most frameworks on health workforce planning and policymaking are high-level and conceptual, and do not provide a structure for synthesizing the growing body of empirical literature on the effectiveness of strategies to strengthen human resources for health (HRH). Our aim is to create a detailed, interactive logic model to map HRH evidence and inform policy development and decision-making. Methods We reviewed existing conceptual frameworks and models on health workforce planning and policymaking. We included frameworks that were: (1) visual, (2) comprehensive (not concentrated on specific outcomes or strategies), and (3) designed to support decision-making. We compared and synthesized the frameworks to develop a detailed logic model and interactive evidence visualization tool. Results Ten frameworks met our inclusion criteria. The resulting logic model, available at hrhvisualizer.org , allows for visualization of high-level linkages as well as a detailed understanding of the factors that affect health workforce outcomes. HRH data and governance systems interact with the context to affect how human resource policies are formulated and implemented. These policies affect HRH processes and strategies that influence health workforce outcomes and contribute to the overarching health systems goals of clinical quality, responsiveness, efficiency, and coverage. Unlike existing conceptual frameworks, this logic model has been operationalized in a highly visual, interactive platform that can be used to map the research informing policies and illuminating their underlying mechanisms. Conclusions The interactive logic model presented in this paper will allow for comprehensive mapping of literature around effective strategies to strengthen HRH. It can aid researchers in communicating with policymakers about the evidence behind policy questions, thus supporting the translation of evidence to policy.

Dieser Beitrag führt den westafrikanischen Arzt und Autor Africanus Horton (1835–1883) als einen modernen politischen Denker vor Augen. Er verfolgte außerordentlich aufmerksam die Untersuchung konkreter Verhältnisse und Situationen in Westafrika, und er bezog zwischen 1865 und 1870 klar Stellung zu den im Wandel begriffenen euroafrikanischen Beziehungen, die zunehmend in die Fänge einer »kolonialen Moderne« zu geraten drohten. Mit seinem Buch West African Countries and Peoples schaltete sich Africanus Horton 1868 explizit und gewichtig in die zeitgenössische Debatte ein. Zu deren drei konstitutiven Elementen – Kolonialismus, Kapitalismus und Rassismus – finden sich kluge, definitiv »moderne« und gelegentlich gar »revolutionär« anmutende Bemerkungen in dem Werk. Der Beitrag arbeitet das politische Denken von Africanus Horton heraus, eingebettet in eine Darstellung seiner Lebens- und Zeitumstände und eine Diskussion des Begriffs »Moderne«, und trifft eine abschließende Einschätzung der Wirkung und Relevanz seines Denkens.

En algunas regiones del litoral sur de Brasil, el fandango conserva la acepción de evento festivo comunitario con música y baile, producto del mestizaje, cuya tradición hunde sus raíces desde la época colonial. El fandango caiçara ha vivenciado un punto crítico para la continuación de su práctica como consecuencia de la depredación ambiental, la especulación inmobiliaria y la alteración de modos de subsistencia comunitarios de la población caiçara. Por ello, múltiples acciones sociales e institucionales se han puesto en marcha para su investigación, revitalización y difusión en las últimas décadas. En estas páginas se explicita el proceso de salvaguarda del fandango caiçara con el trabajo pionero del Museu Vivo do Fandango, entendido en la articulación de actores sociales, estatales, instituciones y agentes culturales.

The tumour microenvironment provides signals to support leukaemic stem cells (LSC) maintenance and chemoresistance. Here, the authors show that disrupting niche-associated signalling by inhibiting receptor-mediated endocytosis with a dynamin GTPase inhibitor overcomes chemoresistance of LSC.

Abstract Drivers are often held responsible for road crashes. Previous research has shown that stressors such as carrying passengers in the vehicle can be a source of accidents for young drivers. To mitigate this problem, this study investigated whether the presence of a passenger behind the wheel can be predicted using machine learning, based on physiological signals. It also addresses the question whether relaxation before driving can positively influence the driver's state and help controlling the potential negative consequences of stressors. Sixty young participants completed a 10‐min driving simulator session, either alone or with a passenger. Before their driving session, participants spent 10 min relaxing or listening to an audiobook. Physiological signals were recorded throughout the experiment. Results show that drivers experience a higher increase in skin conductance when driving with a passenger, which can be predicted with 90%‐accuracy by a k‐nearest neighbors classifier. This might be a possible explanation for increased risk taking in this age group. Besides, the practice of relaxation can be predicted with 80% accuracy using a neural network. According to the statistical analysis, the potential beneficial effect of relaxation did not carry out on the driver's physiological state while driving, although machine learning techniques revealed that participants who exercised relaxation before driving could be recognized with 70% accuracy. Analysis of physiological characteristics after classification revealed several relevant physiological indicators associated with the presence of a passenger and relaxation.

AbstractIn recent years, a variety of fungal cyclic peptides with interesting bioactivities have been discovered. For many of these peptides, the biosynthetic pathways are unknown and their elucidation often holds surprises. The cyclic and backbone NOmphalotus oleariusMariannaea elegansNMyrothecium verrucariaSphaerostilbella broomeana.Rhizopogon roseolusMariannaea elegans, Myrothecium verrucariaSphaerostilbella broomeana..M. verrucariaTrichoderma

In the United States, humans spend the majority of their time indoors, where they are exposed to the microbiome of the built environment (BE) they inhabit. Despite the ubiquity of microbes in BEs and their potential impacts on health and building materials, basic questions about the microbiology of these environments remain unanswered. We present a study on the impacts of geography, material type, human interaction, location in a room, seasonal variation, and indoor and microenvironmental parameters on bacterial communities in offices. Our data elucidate several important features of microbial communities in BEs. First, under normal office environmental conditions, bacterial communities do not differ on the basis of surface material (e.g., ceiling tile or carpet) but do differ on the basis of the location in a room (e.g., ceiling or floor), two features that are often conflated but that we are able to separate here. We suspect that previous work showing differences in bacterial composition with surface material was likely detecting differences based on different usage patterns. Next, we find that offices have city-specific bacterial communities, such that we can accurately predict which city an office microbiome sample is derived from, but office-specific bacterial communities are less apparent. This differs from previous work, which has suggested office-specific compositions of bacterial communities. We again suspect that the difference from prior work arises from different usage patterns. As has been previously shown, we observe that human skin contributes heavily to the composition of BE surfaces. IMPORTANCE Our study highlights several points that should impact the design of future studies of the microbiology of BEs. First, projects tracking changes in BE bacterial communities should focus sampling efforts on surveying different locations in offices and in different cities but not necessarily different materials or different offices in the same city. Next, disturbance due to repeated sampling, though detectable, is small compared to that due to other variables, opening up a range of longitudinal study designs in the BE. Next, studies requiring more samples than can be sequenced on a single sequencing run (which is increasingly common) must control for run effects by including some of the same samples in all of the sequencing runs as technical replicates. Finally, detailed tracking of indoor and material environment covariates is likely not essential for BE microbiome studies, as the normal range of indoor environmental conditions is likely not large enough to impact bacterial communities.

This study examines the mentoring experiences of prospective and beginning special education administrators to determine whether on the job mentoring is a viable method of equipping the prospective and beginning special education administrator with essential knowledge and skills. Three research questions were asked: What is the attainment of knowledge and skills and how does mentor support function for prospective and beginning special education administrators as a result of engagement in a mentoring relationship? Do mentors and protégés agree on the protégé's attainment of knowledge and skills and the level of the mentors' support? Do the attainment of knowledge and skills and the level of mentor support for protégés depend on whether the mentoring relationship is formal or informal? Study findings support mentoring as a critical component in the preparation of administrators in special education.

This essay presents insights into the early career of Ruth Guimarães (1920-2014), the Afro-Brazilian writer from the São Paulo area renowned for her depiction of the Brazilian countryside. Coming of age in Brazil – an ex-colonial and post- emancipatory society, deeply (though unconsciously) shaped by both its oppressive past and present inequalities – her take on Brazilian national identity and on blackness is full of ambiguity but with a sharp sense of Africa`s impact on its history. Becoming part of a literary avant-garde group (the Baruel Circle) at the end of the 1930s allowed Ruth Guimarães to publish her early writings and enter the realm of Brazil`s literary establishment. With her first novel (Água-funda) published in 1946, she rose to prominence, but her first publication was the poem Caboclo originally appearing in 1939 – already full of hints to the issues of identity, rootedness and belonging, seen through the lens of mixture; the poem is republished here in its entirety for the first time. As none of her many works have been translated to English to date, this essay serves as an introduction of this Black woman writer – and of the worlds of Brazilian literature, journalism and publishing in the late 1930s and 40s, in which she launched her career – to an international audience.

The highly immersive Virtual reality (VR) headset is gaining popularity in multiple application domains. In the context of learning, it has been proposed to be beneficial by increasing presence and attention in noisy and distracting environments, both factors that are considered important for learning. Despite intensified research efforts in recent years, empirical knowledge of experimental research addressing the link between presence and learning in specific environmental contexts is still rather scarce. In this study following an experimental mixed-method approach, the link between presence and memorization as a particular form of learning is addressed by comparing memorization with a highly immersive VR headset to a less immersive system (desktop screen) in noisy and calm learning environments. Using a 2 (learning location) x 2 (learning device) between-subjects design, 63 participants interacted with one of the two devices in either of the two environments. As expected, VR headset users reported higher presence levels. While participants subjectively evaluated the VR headset as a better device for learning, the memorization test scores were higher for desktop screen users in both calm and noisy environments. Learning location did not show significant effects. Attention distraction and context-dependent learning are discussed with regard to the unexpected results, while implications for practice and future research are discussed.

In future conditionally automated driving, drivers may be asked to take over control of the car while it is driving autonomously. Performing a non-driving-related task could degrade their takeover performance, which could be detected by continuous assessment of drivers' mental load. In this regard, three physiological signals from 80 subjects were collected during 1 h of conditionally automated driving in a simulator. Participants were asked to perform a non-driving cognitive task (N-back) for 90 s, 15 times during driving. The modality and difficulty of the task were experimentally manipulated. The experiment yielded a dataset of drivers' physiological indicators during the task sequences, which was used to predict drivers' workload. This was done by classifying task difficulty (three classes) and regressing participants' reported level of subjective workload after each task (on a 0–20 scale). Classification of task modality was also studied. For each task, the effect of sensor fusion and task performance were studied. The implemented pipeline consisted of a repeated cross validation approach with grid search applied to three machine learning algorithms. The results showed that three different levels of mental load could be classified with a f1-score of 0.713 using the skin conductance and respiration signals as inputs of a random forest classifier. The best regression model predicted the subjective level of workload with a mean absolute error of 3.195 using the three signals. The accuracy of the model increased with participants' task performance. However, classification of task modality (visual or auditory) was not successful. Some physiological indicators such as estimates of respiratory sinus arrhythmia, respiratory amplitude, and temporal indices of heart rate variability were found to be relevant measures of mental workload. Their use should be preferred for ongoing assessment of driver workload in automated driving.

Abstract Background Innovative human stromal cell therapeutics require xeno-free culture conditions. Various formulations of human platelet lysate (HPL) are efficient alternatives for fetal bovine serum (FBS). However, a consistent lack of standardized manufacturing protocols and quality criteria hampers comparability of HPL-products. Aim of this study was to compare the biochemical composition of three differential HPL-preparations with FBS and to investigate their impact on stromal cell biology. Methods Stromal cells were isolated from bone marrow (BM), white adipose tissue (WAT) and umbilical cord (UC) and cultured in medium supplemented with pooled HPL (pHPL), fibrinogen-depleted serum-converted pHPL (pHPLS), mechanically fibrinogen-depleted pHPL (mcpHPL) and FBS. Biochemical parameters were analyzed in comparison to standard values in whole blood. Distinct growth factors and cytokines were measured by bead-based multiplex technology. Flow cytometry of stromal cell immunophenotype, in vitro differentiation, and mRNA expression analysis of transcription factors SOX2, KLF4, cMYC, OCT4 and NANOG were performed. Results Biochemical parameters were comparable in all pHPL preparations, but to some extent different to FBS. Total protein, glucose, cholesterol and Na+ were elevated in pHPL preparations, K+ and Fe3+ levels were higher in FBS. Compared to FBS, pHPL-based media significantly enhanced stromal cell propagation. Characteristic immunophenotype and in vitro differentiation potential were maintained in all four culture conditions. The analysis of growth factors and cytokines revealed distinct levels depending on the pre-existence in pHPL, consumption or secretion by the stromal cells. Interestingly, mRNA expression of the transcription and mitotic bookmarking factors cMYC and KLF4 was significantly enhanced in a source dependent manner in stromal cells cultured in pHPL- compared to FBS-supplemented media. SOX2 mRNA expression of all stromal cell types was increased in all pHPL culture conditions. Conclusion All pHPL-supplemented media equally supported proliferation of WAT- and UC-derived stromal cells significantly better than FBS. Mitotic bookmarking factors, known to enable a quick re-entry to the cell cycle, were significantly enhanced in pHPL-expanded cells. Our results support a better characterization and standardization of humanized culture media for stromal cell-based medicinal products.