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We have directly resolved in the present work the interfacial composition during and after the interactions of a saturated atmosphere of oil vapor with soluble surfactant solutions at a planar water/air interface for the first time. Experiments were conducted on interactions of hexane vapor with solutions of alkyltrimethylammonium bromides and sodium dodecyl sulfate to observe the balance between cooperativity and competition of the components at the interface.
In all cases, hexane adsorption was strongly enhanced by the presence of the surfactant, even at bulk surfactant concentrations four orders of magnitude below the critical micelle concentration. Cooperativity of the surfactant adsorption was observed only for sodium dodecyl sulfate at intermediate bulk concentrations, yet for all four systems, competition set in at higher concentrations, as hexane adsorption reduced the surfactant surface excess. The data fully supported the complete removal of hexane from the interface following venting of the system to remove the saturated atmosphere of oil vapor.
These results help to identify future experiments that would elaborate and could explain the cooperativity of surfactant adsorption, such as on cationic surfactants with short alkyl chains and a broader series of anionic surfactants. This work holds relevance for oil recovery applications with foam, where there is a gas phase saturated with oil vapor.
The human language processing mechanism assigns a structure to the incoming materials as they unfold. There is evidence that the parser prefers some attachment types over others; however, theories of sentence processing are still in dispute over the stage at which each source of information contributes to the parsing system. The present study aims to identify the nature of initial parsing decisions during sentence processing through manipulating attachment type and verbs' argument structure. To this end, we designed a self-paced reading task using globally ambiguous constructions in Dutch. The structures included double locative prepositional phrases (PPs) where the first PP could attach both to the verb (high attachment) and the noun preceding it (low attachment). To disambiguate the structures, we presented a visual context in the form of short animation clips prior to each reading task. Furthermore, we manipulated the argument structure of the sentences using 2- and 3-argument verbs. The results showed that parsing decisions were influenced by contextual cues depending on the argument structure of the verb. That is, the visual context overcame the preference for high attachment only in the case of 2-argument verbs, while this preference persisted in structures including 3-argument verbs as represented by longer reading times for the low attachment interpretations. These findings can be taken as evidence that our language processing system actively integrates information from linguistic and non-linguistic sources from the initial stages of analysis to build up meaning. We discuss our findings in light of serial and parallel models of sentence processing.
Recent studies indicated severe decline of insect diversity and abundance across major parts of Central Europe.
Theoretical studies showed that the drivers behind biodiversity loss vary considerably over time. However, these scenarios so far have been insufficiently approved by long-term and large-scale data.
In this study we analysed the temporal trends of butterflies and Zygaenid moths across the federal state of Salzburg, northern Austria, from 1920 to 2019. Our study area covers a large variety of habitats and altitudes.
Various changes of land use and intensification occurred during and shortly before our studied period, with a first wave of habitat destruction starting in the late 19th century, followed by the deterioration of habitat quality since the mid-20th century. We used 59,870 presence-only data of 168 butterfly and burnet moth species.
Each of these species was classified according to ecological characteristics. Break point analyses for non-linear temporal trends in the community composition returned two major time windows.
These time windows coincide with periods characterized by severe habitat destruction and the deterioration of habitat quality due to agricultural intensification. We found significant reductions of the proportion of species requiring specific habitats since 1920 and until today.
We identified additional break points for species requiring high habitat qualities, endangered butterfly species, and sedentary species, particularly after a main break point in the 1960s.
Our findings underline that, apart from habitat destruction, the deterioration of habitat quality is a main driver of biodiversity loss in general.
Therefore, nature conservation should focus on maintaining the highest possible habitat quality.
Nudix hydrolase NUDT19 regulates mitochondrial function and ATP production in murine hepatocytes
(2022)
Changes in intracellular CoA levels are known to contribute to the development of non-alcoholic fatty liver disease (NAFLD) in type 2 diabetes (T2D) in human and rodents. However, the underlying genetic basis is still poorly understood.
Due to their diverse susceptibility towards metabolic diseases, mouse inbred strains have been proven to serve as powerful tools for the identification of novel genetic factors that underlie the patho-physiology of NAFLD and diabetes. Transcriptome analysis of mouse liver samples revealed the nucleoside diphosphate linked moiety X-type motif Nudt19 as novel candidate gene responsible for NAFLD and T2D development. Knockdown (KD) of Nudt19 increased mitochondrial and glycolytic ATP production rates in Hepa 1-6 cells by 41% and 10%, respectively.
The enforced utilization of glutamine or fatty acids as energy substrate reduced uncoupled respiration by 41% and 47%, respectively, in non-target (NT) siRNA transfected cells.
This reduction was prevented upon Nudt19 KD. Furthermore, incubation with palmitate or oleate respectively increased mitochondrial ATP production by 31% and 20%, and uncoupled respiration by 23% and 30% in Nudt19 KD cells, but not in NT cells.
The enhanced fatty acid oxidation in Nudt19 KD cells was accompanied by a 1.3-fold increased abundance of Pdk4.
This study is the first to describe Nudt19 as regulator of hepatic lipid metabolism and potential mediator of NAFLD and T2D development.
Due to the great potential of surface-enhanced Raman scattering (SERS) as local vibrational probe of lipid-nanostructure interaction in lipid bilayers, it is important to characterize these interactions in detail.
The interpretation of SERS data of lipids in living cells requires an understanding of how the molecules interact with gold nanostructures and how intermolecular interactions influence the proximity and contact between lipids and nanoparticles.
Ceramide, a sphingolipid that acts as important structural component and regulator of biological function, therefore of interest to probing, lacks a phosphocholine head group that is common to many lipids used in liposome models.
SERS spectra of liposomes of a mixture of ceramide, phosphatidic acid, and phosphatidylcholine, as well as of pure ceramide and of the phospholipid mixture are reported.
Distinct groups of SERS spectra represent varied contributions of the choline, sphingosine, and phosphate head groups and the structures of the acyl chains. Spectral bands related to the state of order of the membrane and moreover to the amide function of the sphingosine head groups indicate that the gold nanoparticles interact with molecules involved in different intermolecular relations.
While cryogenic electron microscopy shows the formation of bilayer liposomes in all preparations, pure ceramide was found to also form supramolecular, concentric stacked and densely packed lamellar, nonliposomal structures. That the formation of such supramolecular assemblies supports the intermolecular interactions of ceramide is indicated by the SERS data.
The unique spectral features that are assigned to the ceramide-containing lipid model systems here enable an identification of these molecules in biological systems and allow us to obtain information on their structure and interaction by SERS.
Describing the heterogeneous structure of forests is often challenging.
One possibility is to analyze forest biomass in different plots and to derive plot-based frequency distributions.
However, these frequency distributions depend on the plot size and thus are scale dependent.
This study provides insights about transferring them between scales. Understanding the effects of scale on distributions of biomass is particularly important for comparing information from different sources such as inventories, remote sensing and modeling, all of which can operate at different spatial resolutions. Reliable methods to compare results of vegetation models at a grid scale with field data collected at smaller scales are still missing.
The scaling of biomass and variables, which determine the forest biomass, was investigated for a tropical forest in Panama. Based on field inventory data from Barro Colorado Island, spanning 50 ha over 30 years, the distributions of aboveground biomass, biomass gain and mortality were derived at different spatial resolutions, ranging from 10 to 100 m. Methods for fitting parametric distribution functions were compared.
Further, it was tested under which assumptions about the distributions a simple stochastic simulation forest model could best reproduce observed biomass distributions at all scales. Also, an analytical forest model for calculating biomass distributions at equilibrium and assuming mortality as a white shot noise process was tested.
Scaling exponents of about 0.47 were found for the standard deviations of the biomass and gain distributions, while mortality showed a different scaling relationship with an exponent of 0.3. Lognormal and gamma distribution functions fitted with the moment matching estimation method allowed for consistent parameter transfers between scales. Both forest models (stochastic simulation and analytical solution) were able to reproduce observed biomass distributions across scales, when combined with the derived scaling relationships.
The study demonstrates a way of how to approach the scaling problem in model-data comparisons by providing a transfer relationship. Further research is needed for a better understanding of the mechanisms that shape the frequency distributions at the different scales.
Clusty is a new open source toolbox dedicated to earthquake clustering based on waveforms recorded across a network of seismic stations. Its main application is the study of active faults and the detection and characterization of faults and fault networks. By using a density-based clustering approach, earthquakes pertaining to a common fault can be recognized even over long fault segments, and the first-order geometry and extent of active faults can be inferred. Clusty implements multiple techniques to compute a waveform based network similarity from maximum cross-correlation coefficients at multiple stations. The clustering procedure is designed to be transparent and parameters can be easily tuned. It is supported by a number of analysis visualization tools which help to assess the homogeneity within each cluster and the differences among distinct clusters. The toolbox returns graphical representations of the results. A list of representative events and stacked waveforms facilitate further analyses like moment tensor inversion. Results obtained in various frequency bands can be combined to account for large magnitude ranges. Thanks to the simple configuration, the toolbox is easily adaptable to new data sets and to large magnitude ranges. To show the potential of our new toolbox, we apply Clusty to the aftershock sequence of the M-w 6.9 25 October 2018 Zakynthos (Greece) Earthquake. Thanks to the complex tectonic setting at the western termination of the Hellenic Subduction System where multiple faults and faulting styles operate simultaneously, the Zakynthos data set provides an ideal case-study for our clustering analysis toolbox. Our results support the activation of several faults and provide insight into the geometry of faults or fault segments. We identify two large thrust faulting clusters in the vicinity of the main shock and multiple strike-slip clusters to the east, west and south of these clusters. Despite its location within the largest thrust cluster, the main shock does not show a high waveform similarity to any of the clusters. This is consistent with the results of other studies suggesting a complex failure mechanism for the main shock. We propose the existence of conjugated strike-slip faults in the south of the study area. Our waveform similarity based clustering toolbox is able to reveal distinct event clusters which cannot be discriminated based on locations and/or timing only. Additionally, the clustering results allows distinction between fault and auxiliary planes of focal mechanisms and to associate them to known active faults.
Scanning manufacturing parameters determining the residual stress state in LPBF IN718 small parts
(2021)
The influence of scan strategy on the residual stress (RS) state of an as-built IN718 alloy produced by means of laser powder bed fusion (LPBF) is investigated. Two scan vector rotations (90 degrees-alternation and 67 degrees-rotation), each produced following two different scan vector lengths (long and short), are used to manufacture four rectangular prisms. Neutron diffraction (ND) and laboratory X-ray diffraction (XRD) techniques are used to map the bulk and surface RS state, respectively. The distortion induced upon removal from the baseplate is measured via profilometry. XRD measurements show that the two long scan vector strategies lead to higher RS when compared with the equivalent short scan vector strategies. Also, the 67 degrees-rotation strategies generate lower RS than their 90 degrees-alternation counterparts. Due to the lack of reliable stress-free d0 references, the ND results are analyzed using von Mises stress. In general, ND results show significant RS spatial non-uniformity. A comparison between ND and distortion results indicates that the RS component parallel to the building direction (Z-axis) has a predominant role in the Z-displacement. The use of a stress balance scheme allows to discuss the d0 variability along the length of the specimens, as well as examine the absolute RS state.
Impact of Late Pleistocene climate variability on paleo-erosion rates in the western Himalaya
(2022)
It has been proposed that at short timescales of 10(2)-10(5) yr, climatic variability can explain variations in sediment flux, but in orogens with pronounced climatic gradients rate changes caused by the oscillating efficiency in rainfall, runoff, and/or sediment transport and deposition are still not well-constrained.
To explore landscape responses under variable climatic forcing, we evaluate time windows of prevailing sediment aggradation and related paleo-erosion rates from the southern flanks of the Dhauladhar Range in the western Himalaya.
We compare past and present Be-10-derived erosion rates of well-dated Late Pleistocene fluvial landforms and modern river sediments and reconstruct the sediment aggradation and incision history based on new luminescence data.
Our results document significant variations in erosion rates ranging from 0.1 to 3.4 mm/yr over the Late Pleistocene.
We find that, during times of weak monsoon intensity, the moderately steep areas (hillslope angles of 27 +/- 13 degrees) erode at lower rates of 0.1-0.4 mm/yr compared to steeper (>40 degrees) crestal regions of the Dhauladhar Range that erode at 0.8-1.3 mm/yr.
In contrast, during several millennia of stronger monsoon intensity, both the moderately steep and high slope areas record higher erosion rates (>1-3.4 mm/yr). Lithological clast-count analysis shows that this increase of erosion is focused in the moderately steep areas, where Lesser Himalayan rocks are exposed.
Our data thus highlight the highly non-linear response of climatic forcing on landscape evolution and suggest complex depositional processes and sedimentary signals in downstream areas. (C) 2021 Elsevier B.V. All rights reserved.
The current study examined the impact of the Good Behavior Game (GBG) on the academic engagement (AE) and disruptive behavior (DB) of at-risk students' in a German inclusive primary school sample using behavioral progress monitoring.
A multiple baseline design across participants was employed to evaluate the effects of the GBG on 35 primary school students in seven classrooms from grade 1 to 3 (M-age = 8.01 years, SDage = 0.81 years).
The implementation of the GBG was randomly staggered by 2 weeks across classrooms. Teacher-completed Direct Behavior Rating (DBR) was applied to measure AE and DB. We used piecewise regression and a multilevel extension to estimate the individual case-specific treatment effects as well as the generalized effects across cases.
Piecewise regressions for each case showed significant immediate treatment effects for the majority of participants (82.86%) for one or both outcome measures.
The multilevel approach revealed that the GBG improved at-risk students' classroom behaviors generally with a significant immediate treatment effect across cases (for AE, B = 0.74, p < 0.001; for DB, B = -1.29, p < 0.001).
The moderation between intervention effectiveness and teacher ratings of students' risks for externalizing psychosocial problems was significant for DB (B = -0.07, p = 0.047) but not for AE.
Findings are consistent with previous studies indicating that the GBG is an appropriate classroom-based intervention for at-risk students and expand the literature regarding differential effects for affected students.
In addition, the study supports the relevance of behavioral progress monitoring and data-based decision-making in inclusive schools in order to evaluate the effectiveness of the GBG and, if necessary, to modify the intervention for individual students or the whole group.