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The co-occurrence of warm spells and droughts can lead to detrimental socio-economic and ecological impacts, largely surpassing the impacts of either warm spells or droughts alone. We quantify changes in the number of compound warm spells and droughts from 1979 to 2018 in the Mediterranean Basin using the ERA5 data set. We analyse two types of compound events: 1) warm season compound events, which are extreme in absolute terms in the warm season from May to October and 2) year-round deseasonalised compound events, which are extreme in relative terms respective to the time of the year. The number of compound events increases significantly and especially warm spells are increasing strongly – with an annual growth rates of 3.9 (3.5) % for warm season (deseasonalised) compound events and 4.6 (4.4) % for warm spells –, whereas for droughts the change is more ambiguous depending on the applied definition. Therefore, the rise in the number of compound events is primarily driven by temperature changes and not the lack of precipitation. The months July and August show the highest increases in warm season compound events, whereas the highest increases of deseasonalised compound events occur in spring and early summer. This increase in deseasonalised compound events can potentially have a significant impact on the functioning of Mediterranean ecosystems as this is the peak phase of ecosystem productivity and a vital phenophase.
Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts.
Leveraging large-deviation statistics to decipher the stochastic properties of measured trajectories
(2021)
Extensive time-series encoding the position of particles such as viruses, vesicles, or individualproteins are routinely garnered insingle-particle tracking experiments or supercomputing studies.They contain vital clues on how viruses spread or drugs may be delivered in biological cells.Similar time-series are being recorded of stock values in financial markets and of climate data.Such time-series are most typically evaluated in terms of time-averaged mean-squareddisplacements (TAMSDs), which remain random variables for finite measurement times. Theirstatistical properties are different for differentphysical stochastic processes, thus allowing us toextract valuable information on the stochastic process itself. To exploit the full potential of thestatistical information encoded in measured time-series we here propose an easy-to-implementand computationally inexpensive new methodology, based on deviations of the TAMSD from itsensemble average counterpart. Specifically, we use the upper bound of these deviations forBrownian motion (BM) to check the applicability of this approach to simulated and real data sets.By comparing the probability of deviations fordifferent data sets, we demonstrate how thetheoretical bound for BM reveals additional information about observed stochastic processes. Weapply the large-deviation method to data sets of tracer beads tracked in aqueous solution, tracerbeads measured in mucin hydrogels, and of geographic surface temperature anomalies. Ouranalysis shows how the large-deviation properties can be efficiently used as a simple yet effectiveroutine test to reject the BM hypothesis and unveil relevant information on statistical propertiessuch as ergodicity breaking and short-time correlations.
Stereoselective [4+2] Cycloaddition of Singlet Oxygen to Naphthalenes Controlled by Carbohydrates
(2021)
Stereoselective reactions of singlet oxygen are of current interest. Since enantioselective photooxygenations have not been realized efficiently, auxiliary control is an attractive alternative. However, the obtained peroxides are often too labile for isolation or further transformations into enantiomerically pure products. Herein, we describe the oxidation of naphthalenes by singlet oxygen, where the face selectivity is controlled by carbohydrates for the first time. The synthesis of the precursors is easily achieved starting from naphthoquinone and a protected glucose derivative in only two steps. Photooxygenations proceed smoothly at low temperature, and we detected the corresponding endoperoxides as sole products by NMR. They are labile and can thermally react back to the parent naphthalenes and singlet oxygen. However, we could isolate and characterize two enantiomerically pure peroxides, which are sufficiently stable at room temperature. An interesting influence of substituents on the stereoselectivities of the photooxygenations has been found, ranging from 51:49 to up to 91:9 dr (diastereomeric ratio). We explain this by a hindered rotation of the carbohydrate substituents, substantiated by a combination of NOESY measurements and theoretical calculations. Finally, we could transfer the chiral information from a pure endoperoxide to an epoxide, which was isolated after cleavage of the sugar chiral auxiliary in enantiomerically pure form.
The Human Takes It All
(2020)
Background: The increasing involvement of social robots in human lives raises the question as to how humans perceive social robots. Little is known about human perception of synthesized voices.
Aim: To investigate which synthesized voice parameters predict the speaker's eeriness and voice likability; to determine if individual listener characteristics (e.g., personality, attitude toward robots, age) influence synthesized voice evaluations; and to explore which paralinguistic features subjectively distinguish humans from robots/artificial agents.
Methods: 95 adults (62 females) listened to randomly presented audio-clips of three categories: synthesized (Watson, IBM), humanoid (robot Sophia, Hanson Robotics), and human voices (five clips/category). Voices were rated on intelligibility, prosody, trustworthiness, confidence, enthusiasm, pleasantness, human-likeness, likability, and naturalness. Speakers were rated on appeal, credibility, human-likeness, and eeriness. Participants' personality traits, attitudes to robots, and demographics were obtained.
Results: The human voice and human speaker characteristics received reliably higher scores on all dimensions except for eeriness. Synthesized voice ratings were positively related to participants' agreeableness and neuroticism. Females rated synthesized voices more positively on most dimensions. Surprisingly, interest in social robots and attitudes toward robots played almost no role in voice evaluation. Contrary to the expectations of an uncanny valley, when the ratings of human-likeness for both the voice and the speaker characteristics were higher, they seemed less eerie to the participants. Moreover, when the speaker's voice was more humanlike, it was more liked by the participants. This latter point was only applicable to one of the synthesized voices. Finally, pleasantness and trustworthiness of the synthesized voice predicted the likability of the speaker's voice. Qualitative content analysis identified intonation, sound, emotion, and imageability/embodiment as diagnostic features.
Discussion: Humans clearly prefer human voices, but manipulating diagnostic speech features might increase acceptance of synthesized voices and thereby support human-robot interaction. There is limited evidence that human-likeness of a voice is negatively linked to the perceived eeriness of the speaker.
In a changing world, phytoplankton communities face a large variety of challenges including altered light regimes. These alterations are caused by more pronounced stratification due to rising temperatures, enhanced eutrophication, and browning of lakes. Community responses toward these effects can emerge as alterations in physiology, biomass, biochemical composition, or diversity. In this study, we addressed the combined effects of changes in light and nutrient conditions on community responses. In particular, we investigated how light intensity and variability under two nutrient conditions influence (1) fast responses such as adjustments in photosynthesis, (2) intermediate responses such as pigment adaptation and (3) slow responses such as changes in community biomass and species composition. Therefore, we exposed communities consisting of five phytoplankton species belonging to different taxonomic groups to two constant and two variable light intensity treatments combined with two levels of phosphorus supply. The tested phytoplankton communities exhibited increased fast reactions of photosynthetic processes to light variability and light intensity. The adjustment of their light harvesting mechanisms via community pigment composition was not affected by light intensity, variability, or nutrient supply. However, pigment specific effects of light intensity, light variability, and nutrient supply on the proportion of the respective pigments were detected. Biomass was positively affected by higher light intensity and nutrient concentrations while the direction of the effect of variability was modulated by light intensity. Light variability had a negative impact on biomass at low, but a positive impact at high light intensity. The effects on community composition were species specific. Generally, the proportion of green algae was higher under high light intensity, whereas the cyanobacterium performed better under low light conditions. In addition to that, the diatom and the cryptophyte performed better with high nutrient supply while the green algae as well as the cyanobacterium performed better at low nutrient conditions. This shows that light intensity, light variability, and nutrient supply interactively affect communities. Furthermore, the responses are highly species and pigment specific, thus to clarify the effects of climate change a deeper understanding of the effects of light variability and species interactions within communities is important.
In this paper the use of two different scaffolds in a seminar on the topic of heterocycles is discussed. The students first used both scaffolds (stepped supporting tools and a task navigator) on two tasks and could then choose for one other task the scaffold that suited them more. The scaffolds were evaluated in a mixedmethods study by the use of questionnaires and the conducting of a focus group interview. Both scaffolds were assessed as being helpful. However, students who thought they didn’t need different sorts of tips, as provided by the task navigator, chose the stepped supporting tools. All students reflected on their use of the scaffolds; their choices for one of both are therefore well-founded. As the reasons for choosing the scaffold are very individual, in future seminars both types of scaffolds will be provided.
Objective: We investigated the effects of combined balance and strength training on measures of balance and muscle strength in older women with a history of falls.
Methods: Twenty-seven older women aged 70.4 ± 4.1 years (age range: 65 to 75 years) were randomly allocated to either an intervention (IG, n = 12) or an active control (CG, n = 15) group. The IG completed 8 weeks combined balance and strength training program with three sessions per week including visual biofeedback using force plates. The CG received physical therapy and gait training at a rehabilitation center. Training volumes were similar between the groups. Pre and post training, tests were applied for the assessment of muscle strength (weight-bearing squat [WBS] by measuring the percentage of body mass borne by each leg at different knee flexions [0°, 30°, 60°, and 90°], sit-to-stand test [STS]), and balance. Balance tests used the modified clinical test of sensory interaction (mCTSIB) with eyes closed (EC) and opened (EO), on stable (firm) and unstable (foam) surfaces as well as spatial parameters of gait such as step width and length (cm) and walking speed (cm/s).
Results: Significant group × time interactions were found for different degrees of knee flexion during WBS (0.0001 < p < 0.013, 0.441 < d < 0.762). Post hoc tests revealed significant pre-to-post improvements for both legs and for all degrees of flexion (0.0001 < p < 0.002, 0.697 < d < 1.875) for IG compared to CG. Significant group × time interactions were found for firm EO, foam EO, firm EC, and foam EC (0.006 < p < 0.029; 0.302 < d < 0.518). Post hoc tests showed significant pre-to-post improvements for both legs and for all degrees of oscillations (0.0001 < p < 0.004, 0.753 < d < 2.097) for IG compared to CG. This study indicates that combined balance and strength training improved percentage distribution of body weight between legs at different conditions of knee flexion (0°, 30°, 60°, and 90°) and also decreased the sway oscillation on a firm surface with eyes closed, and on foam surface (with eyes opened or closed) in the IG.
Conclusion: The higher positive effects of training seen in standing balance tests, compared with dynamic tests, suggests that balance training exercises including lateral, forward, and backward exercises improved static balance to a greater extent in older women.
We study the experimentally measured ciprofloxacin antibiotic diffusion through a gel-like artificial sputum medium (ASM) mimicking physiological conditions typical for a cystic fibrosis layer, in which regions occupied by Pseudomonas aeruginosa bacteria are present. To quantify the antibiotic diffusion dynamics we employ a phenomenological model using a subdiffusion-absorption equation with a fractional time derivative. This effective equation describes molecular diffusion in a medium structured akin Thompson’s plumpudding model; here the ‘pudding’ background represents the ASM and the ‘plums’ represent the bacterial biofilm. The pudding is a subdiffusion barrier for antibiotic molecules that can affect bacteria found in plums. For the experimental study we use an interferometric method to determine the time evolution of the amount of antibiotic that has diffused through the biofilm. The theoretical model shows that this function is qualitatively different depending on whether or not absorption of the antibiotic in the biofilm occurs. We show that the process can be divided into three successive stages: (1) only antibiotic subdiffusion with constant biofilm parameters, (2) subdiffusion and absorption of antibiotic molecules with variable biofilm transport parameters, (3) subdiffusion and absorption in the medium but the biofilm parameters are constant again. Stage 2 is interpreted as the appearance of an intensive defence build–up of bacteria against the action of the antibiotic, and in the stage 3 it is likely that the bacteria have been inactivated. Times at which stages change are determined from the experimentally obtained temporal evolution of the amount of antibiotic that has diffused through the ASM with bacteria. Our analysis shows good agreement between experimental and theoretical results and is consistent with the biologically expected biofilm response. We show that an experimental method to study the temporal evolution of the amount of a substance that has diffused through a biofilm is useful in studying the processes occurring in a biofilm. We also show that the complicated biological process of antibiotic diffusion in a biofilm can be described by a fractional subdiffusion-absorption equation with subdiffusion and absorption parameters that change over time.
One of the most important social cognitive skills in humans is the ability to “put oneself in someone else’s shoes,” that is, to take another person’s perspective. In socially situated communication, perspective taking enables the listener to arrive at a meaningful interpretation of what is said (sentence meaning) and what is meant (speaker’s meaning) by the speaker. To successfully decode the speaker’s meaning, the listener has to take into account which information he/she and the speaker share in their common ground (CG). We here further investigated competing accounts about when and how CG information affects language comprehension by means of reaction time (RT) measures, accuracy data, event-related potentials (ERPs), and eye-tracking. Early integration accounts would predict that CG information is considered immediately and would hence not expect to find costs of CG integration. Late integration accounts would predict a rather late and effortful integration of CG information during the parsing process that might be reflected in integration or updating costs. Other accounts predict the simultaneous integration of privileged ground (PG) and CG perspectives. We used a computerized version of the referential communication game with object triplets of different sizes presented visually in CG or PG. In critical trials (i.e., conflict trials), CG information had to be integrated while privileged information had to be suppressed. Listeners mastered the integration of CG (response accuracy 99.8%). Yet, slower RTs, and enhanced late positivities in the ERPs showed that CG integration had its costs. Moreover, eye-tracking data indicated an early anticipation of referents in CG but an inability to suppress looks to the privileged competitor, resulting in later and longer looks to targets in those trials, in which CG information had to be considered. Our data therefore support accounts that foresee an early anticipation of referents to be in CG but a rather late and effortful integration if conflicting information has to be processed. We show that both perspectives, PG and CG, contribute to socially situated language processing and discuss the data with reference to theoretical accounts and recent findings on the use of CG information for reference resolution.