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Monitoring the fuel moisture content (FMC) of 10 h dead vegetation is crucial for managing and mitigating the impact of wildland fires. The combination of in situ FMC observations, numerical weather prediction (NWP) models, and satellite retrievals has facilitated the development of machine learning (ML) models to estimate 10 h dead FMC retrievals over the contiguous US (CONUS). In this study, ML models were trained using variables from the National Water Model, the High-Resolution Rapid Refresh (HRRR) NWP model, and static surface properties, along with surface reflectances and land surface temperature (LST) retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on the Suomi-NPP satellite system. Extensive hyper-parameter optimization resulted in skillful FMC models compared to a daily climatography RMSE (+44%) and an hourly climatography RMSE (+24%). Notably, VIIRS retrievals played a significant role as predictors for estimating 10 h dead FMC, demonstrating their importance as a group due to their high band correlation. Conversely, individual predictors within the HRRR group exhibited relatively high importance according to explainability techniques. Removing both HRRR and VIIRS retrievals as model inputs led to a significant decline in performance, particularly with worse RMSE values when excluding VIIRS retrievals. The importance of the VIIRS predictor group reinforces the dynamic relationship between 10 h dead fuel, the atmosphere, and soil moisture. These findings underscore the significance of selecting appropriate data sources when utilizing ML models for FMC prediction. VIIRS retrievals, in combination with selected HRRR variables, emerge as critical components in achieving skillful FMC estimates.

Improving the precision and function of encapsulating three-dimensional (3D) DNA nanostructures via curved geometries could have transformative impacts on areas such as molecular transport, drug delivery, and nanofabrication. However, the addition of non-rasterized curvature escalates design complexity without algorithmic regularity, and these challenges have limited the ad hoc development and usage of previously unknown shapes. In this work, we develop and automate the application of a set of previously unknown design principles that now includes a multilayer design for closed and curved DNA nanostructures to resolve past obstacles in shape selection, yield, mechanical rigidity, and accessibility. We design, analyze, and experimentally demonstrate a set of diverse 3D curved nanoarchitectures, showing planar asymmetry and examining partial multilayer designs. Our automated design tool implements a combined algorithmic and numerical approximation strategy for scaffold routing and crossover placement, which may enable wider applications of general DNA nanostructure design for nonregular or oblique shapes.

Two isoforms of beta amyloid peptides, Ab40 and Ab42, differ from each other only in the last two amino acids, IA, at the end of Ab42. They, however, differ significantly in their ability in inducing Alzheimer's disease (AD). The rate curves of fibril growth of Ab40 and Ab42 and the effects of molecular crowding have been measured in in vitro experiments. These experimental curves, on the other hand, have been fitted in terms of rate constants for elementary reaction steps using rate equation approaches. Several sets of such rate parameters have been reported in the literature. Employing a recently developed stochastic kinetic method, implemented in a browser-based simulator, popsim, we study to reveal the differences in the kinetic behaviors implied by these sets of rate parameters. In particular, the stochastic method is used to distinguish the kinetic behaviors between Ab40 and Ab42 isoforms. As a result, we make general comments on the usefulness of these sets of rate parameters., To appear in the Journal of the Chinese Chemical Society

Purpose The purpose of this review article is to review the existing literature about the factors that impact stress in undergraduate students studying communication sciences and disorders (CSD). Current undergraduate students are more stressed than their predecessors and the body of literature about stressed students is growing. However, CSD students' experience may differ from their non-CSD peers and there is a dearth of literature about stressed CSD students, in particular. Method This is a narrative review of the literature about the factors that impact stress in undergraduate students studying CSD. The review is structured using the ecological systems theoretical framework with an emphasis on the microsystems that encompass the most salient factors related to undergraduate students' stress. Factors such as family influence (e.g., parenting style, parent education), peer support, faculty relationships, minority status, technology, and individual health behaviors were explored in the literature using electronic databases. Conclusions This review of the literature suggests that a myriad of microsystem factors contribute to the stress of undergraduate CSD students. Although the review focuses on microsystem factors that are closest to students, it is important to situate the results in context. The mental health of college students was on the decline before COVID-19, and as the economic and public health of the nation and world shift, the urgency to attend to our students increases. This review contributes to the greater understanding of CSD students' experiences that will inform programmatic and individual support.

PurposeSocial support may be provided by undergraduate students' family and friends and by other members of the campus community, including faculty. The purpose of this review article was to review the existing literature about the roles of faculty members as advisors, mentors, and gatekeepers who provide social support for undergraduate students. Social support is a buffer for stress, and current undergraduate students are more stressed than their predecessors.MethodThe study is a narrative review of the literature about faculty as advisors, mentors, and gatekeepers. The concept of social support and its relationship to students' stress is explored, followed by a discussion of faculty advisors' roles, knowledge, and skills and a synthesis of literature about prescriptive, developmental, praxis, and appreciative advising. A discussion of faculty as mentors who focus on students' experiences before, during, and after college and as gatekeepers who look for signs of students in distress concludes the review.ConclusionsFaculty may provide social support to students inside and outside the classroom as advisors, mentors, and gatekeepers. Assuming these roles means faculty must consider students as whole people who have needs and experiences beyond academics. Students' stress was clear in the literature before COVID-19, and their concerns and needs are exacerbated during the pandemic. Additional research is needed to identify effective advising and mentoring programs for communication sciences and disorders undergraduate students. Increased institutional support for and recognition of the time, resources, and training faculty need to serve in this expanded role is also critical as faculty members attempt to manage their own stress.

Investigation of protein self-assembly processes is important for understanding the growth processes of functional proteins as well as disease-causing amyloids. Inside cells, intrinsic molecular fluctuations are so high that they cast doubt on the validity of the deterministic rate-equation approach. Furthermore, the protein environments inside cells are often crowded with other macromolecules, with volume fractions of the crowders as high as 40%. We have developed a stochastic kinetic framework using Gillespie's algorithm for general systems undergoing particle self-assembly, including particularly protein aggregation at the cellular level. The effects of macromolecular crowding are investigated using models built on scaled-particle and transition-state theories. The stochastic kinetic method can be formulated to provide information on the dominating aggregation mechanisms in a method called reaction frequency (or propensity) analysis. This method reveals that the change of scaling laws related to the lag time can be directly related to the change in the frequencies of reaction mechanisms. Further examination of the time evolution of the fibril mass and length quantities unveils that maximal fluctuations occur in the periods of rapid fibril growth and the fluctuations of both quantities can be sensitive functions of rate constants. The presence of crowders often amplifies the roles of primary and secondary nucleation and causes shifting in the relative importance of elongation, shrinking, fragmentation, and coagulation of linear aggregates. We also show a dual effect of changing volume on the halftime of aggregation for ApoC2 which is reduced in the presence of crowders. A comparison of the results of stochastic simulations with those of rate equations gives us information on the convergence relation between them and how the roles of reaction mechanisms change as the system volume is varied.

Holographic cloud probes provide unprecedented information on cloud particle density, size and position. Each laser shot captures particles within a large volume, where images can be computationally refocused to determine particle size and shape. However, processing these holograms, either with standard methods or with machine learning (ML) models, requires considerable computational resources, time and occasional human intervention. ML models are trained on simulated holograms obtained from the physical model of the probe since real holograms have no absolute truth labels. Using another processing method to produce labels would be subject to errors that the ML model would subsequently inherit. Models perform well on real holograms only when image corruption is performed on the simulated images during training, thereby mimicking non-ideal conditions in the actual probe (Schreck et. al, 2022). Optimizing image corruption requires a cumbersome manual labeling effort. Here we demonstrate the application of the neural style translation approach (Gatys et. al, 2016) to the simulated holograms. With a pre-trained convolutional neural network (VGG-19), the simulated holograms are ``stylized'' to resemble the real ones obtained from the probe, while at the same time preserving the simulated image ``content'' (e.g. the particle locations and sizes). Two image similarity metrics concur that the stylized images are more like real holograms than the synthetic ones. With an ML model trained to predict particle locations and shapes on the stylized data sets, we observed comparable performance on both simulated and real holograms, obviating the need to perform manual labeling. The described approach is not specific to hologram images and could be applied in other domains for capturing noise and imperfections in observational instruments to make simulated data more like real world observations., Comment: 23 pages, 9 figures

Nucleic acid interactions under crowded environments are of great importance for biological processes and nanotechnology. However, the kinetics and thermodynamics of nucleic acid interactions in a crowded environment remain poorly understood. We use a coarse-grained model of DNA to study the kinetics and thermodynamics of DNA duplex and hairpin formation in crowded environments. We find that crowders can increase the melting temperature of both an 8-mer DNA duplex and a hairpin with a stem of 6-nt depending on the excluded volume fraction of crowders in solution and the crowder size. The crowding induced stability originates from the entropic effect caused by the crowding particles in the system. Additionally, we study the hybridization kinetics of DNA duplex formation and the formation of hairpin stems, finding that the reaction rate kon is increased by the crowding effect, while koff is changed only moderately. The increase in kon mostly comes from increasing the probability of reaching a transition state with one base pair formed. A DNA strand displacement reaction in a crowded environment is also studied with the model and we find that rate of toehold association is increased, with possible applications to speeding up strand displacement cascades in nucleic acid nanotechnology.

The final design process of the ITER EC upper launcher (UL) was carried out between 2011 and 2018 under a Grant agreement between the European Domestic Agency F4E and a consortium of European associations, namely KIT (D), SPC (CH), DIFFER (NL), IPP (D), CNR (I), and IPF (D). The final design is scheduled for 2019. The final design review (FDR) will be split into several review processes for dedicated sub-components. One of these sub-components is the structural system of the EC launcher. This article presents a brief overview on the final design status of the ITER EC UL structure of spring 2018, including the history of development since 2004. It highlights the most challenging design issues and debates demanding project management steps. The lesson learned in the technical development of the design will be discussed, in view of the design work for future fusion devices.

Today's college students are stressed ( Liu, Stevens, Wong, Yasui, & Chen, 2018 ), and stress may impact students' physical ( Doom & Haeffel, 2013 ) and mental health ( Baddeley, 2012 ; Liu et al., 2018 ). Purpose This mixed-methods study used a convergent parallel design to examine the stress experienced by undergraduate students who study communication sciences and disorders (CSD) at a private, Mid-Atlantic university. Method Eighty-seven students participated in the quantitative phase involving a survey (50.5% response rate), and 23 students participated in the qualitative phase involving focus groups (13% response rate). Research questions inquired about students' perceived stress levels, factors related to their stress, how they manage their stress, and students' knowledge and use of campus resources for support. Results Results suggest that CSD students are stressed, and primary factors related to stress include academic demands, graduate school admission, and financial concerns. Students manage their stress in various ways, including exercise, working hard to finish assignments, calling home, and relying on friends. However, CSD friendships are complicated by the intense competition for graduate seats, leaving students with reduced social support. Conclusion Given the complicated nature of CSD friendships, students report the need for increased community and support from CSD faculty.

This chapter will provide an overview of how characterizing free-energy landscapes can provide insights into the biophysical properties of DNA, as well as into the behaviour of the DNA assemblies used in the field of DNA nanotechnology. The landscapes for these complex systems are accessible through the use of accurate coarse-grained descriptions of DNA. Particular foci will be the landscapes associated with DNA self-assembly and mechanical deformation, where the latter can arise from either externally imposed forces or internal stresses., 20 pages, 5 figures

ITER will be equipped with four EC (Electron Cyclotron) Upper Launchers (UL) of 8 MW microwave power each with the aim to counteract plasma instabilities during operation. These launcher antennas will be installed into four upper ports of the ITER vacuum vessel. Beside their functional purpose the port plugs which are the structural system of the launchers, have to provide as much shielding as possible in order to protect adjacent components from neutrons and photons and to minimize the shutdown dose rate in the port interspace and the port cell, being located further back in the ITER Tokamak building. Thus appropriate shielding blocks shall be installed at proper positions inside the plug. In addition several structural components will be dressed up geometrically in order to provide maximum shielding capability. This paper presents the general design of the shielding elements and their technical integration into the EC Upper Launcher.

We show how coarse-grained modelling combined with umbrella sampling using distance-based order parameters can be applied to compute the free-energy landscapes associated with mechanical deformations of large DNA nanostructures. We illustrate this approach for the strong bending of DNA nanotubes and the potentially bistable landscape of twisted DNA origami sheets. The homogeneous bending of the DNA nanotubes is well described by the worm-like chain model; for more extreme bending the nanotubes reversibly buckle with the bending deformations localized at one or two "kinks". For a twisted one-layer DNA origami, the twist is coupled to the bending of the sheet giving rise to a free-energy landscape that has two nearly-degenerate minima that have opposite curvatures. By contrast, for a two-layer origami, the increased stiffness with respect to bending leads to a landscape with a single free-energy minimum that has a saddle-like geometry. The ability to compute such landscapes is likely to be particularly useful for DNA mechanotechnology and for understanding stress accumulation during the self-assembly of origamis into higher-order structures., Comment: main (17 pages, 7 figures); Supporting Information (14 pages, 11 figures)

The thermodynamics and kinetics of protein folding and protein aggregationin vivoare of great importance in numerous scientific areas including fundamental biophysics research, nanotechnology, and medicine. However, these processes remain poorly understood in bothin vivoandin vitrosystems. Here we extend an established model for protein aggregation that is based on the kinetic equations for the moments of the polymer size distribution by introducing macromolecular crowding particles into the model using scaled-particle and transition-state theories. The model predicts that the presence of crowders can either speed up, cause no change to, or slow down the progress of the aggregation compared to crowder-free solutions, in striking agreement with experimental results from nine different amyloid-forming proteins that utilized dextran as the crowder. These different dynamic effects of macromolecular crowding can be understood in terms of the change of excluded volume associated with each reaction step.

Nucleic acid interactions under crowded environments are of great importance for biological processes and nanotechnology. However, the kinetics and thermodynamics of nucleic acid interactions in a crowded environment remain poorly understood. We use a coarse-grained model of DNA to study the kinetics and thermodynamics of DNA duplex and hairpin formation in crowded environments. We find that crowders can increase the melting temperature of both an 8-mer DNA duplex and a hairpin with a stem of 6-nt depending on the excluded volume fraction of crowders in solution and the crowder size. The crowding induced stability originates from the entropic effect caused by the crowding particles in the system. Additionally, we study the hybridization kinetics of DNA duplex formation and the formation of hairpin stems, finding that the reaction ratekonis increased by the crowding effect, whilekoffis changed only moderately. The increase inkonmostly comes from increasing the probability of reaching a transition state with one base pair formed. A DNA strand displacement reaction in a crowded environment is also studied with the model and we find that rate of toehold association is increased, with possible applications to speeding up strand displacement cascades in nucleic acid nanotechnology.

[Image: see text] The problem of retrosynthetic planning can be framed as a one-player game, in which the chemist (or a computer program) works backward from a molecular target to simpler starting materials through a series of choices regarding which reactions to perform. This game is challenging as the combinatorial space of possible choices is astronomical, and the value of each choice remains uncertain until the synthesis plan is completed and its cost evaluated. Here, we address this search problem using deep reinforcement learning to identify policies that make (near) optimal reaction choices during each step of retrosynthetic planning according to a user-defined cost metric. Using a simulated experience, we train a neural network to estimate the expected synthesis cost or value of any given molecule based on a representation of its molecular structure. We show that learned policies based on this value network can outperform a heuristic approach that favors symmetric disconnections when synthesizing unfamiliar molecules from available starting materials using the fewest number of reactions. We discuss how the learned policies described here can be incorporated into existing synthesis planning tools and how they can be adapted to changes in the synthesis cost objective or material availability.

The present work introduces the first architectural energetics analysis of a medieval tumulus from the Eurasian/Pontic steppe. In contrast to New World earthworks, tumuli on the steppe were constructed 1) with sod taken from the environment immediately surrounding the construction site, 2) with the use of draft animals and metal tools, and 3) in identifiable phases as part of funerary rituals over a period of weeks or months. These variables introduce problems which are confronted through 1) the application of novel historically attested rates for construction and 2) the creation of new, replicable mathematical methods for modeling materials transport.

The prototypical photoinduced dissociation of Fe(CO)

Inspired by recent successes using single-stranded DNA tiles to produce complex structures, we develop a two-step coarse-graining approach that uses detailed thermodynamic calculations with oxDNA, a nucleotide-based model of DNA, to parametrize a coarser kinetic model that can reach the time and length scales needed to study the assembly mechanisms of these structures. We test the model by performing a detailed study of the assembly pathways for a two-dimensional target structure made up of 334 unique strands each of which are 42 nucleotides long. Without adjustable parameters, the model reproduces a critical temperature for the formation of the assembly that is close to the temperature at which assembly first occurs in experiments. Furthermore, the model allows us to investigate in detail the nucleation barriers and the distribution of critical nucleus shapes for the assembly of a single target structure. The assembly intermediates are compact and highly connected (although not maximally so), and classical nucleation theory provides a good fit to the height and shape of the nucleation barrier at temperatures close to where assembly first occurs.

Introduction: Disturbances of circadian rhythms occur in all episodes of bipolar disorder (BD). Lithium, as gold-standard in the maintenance treatment of BD, is known to influence circadian processes. Methods: In a pilot study lymphoblastoid cell lines (LCLs) were generated from 8 BD patients and 6 healthy controls. The LCLs were treated with lithiumchloride (LiCl) for 3 weeks. Cell cycles were then synchronized and expressional analysis by quantitative Real Time PCR was done. Results: BD and controls differed in the period length regarding DBP (albumin D-box binding protein) expression and DBP expression was also influenced by lithium treatment. Furthermore, baseline DBP expression was significantly different between non-treated BD and healthy controls. None of the other analyzed circadian genes showed to be influenced by chronic lithium treatment or to be differentially regulated due to the diagnosis. Discussion: We here show that chronic lithium treatment of LCLs leads to decreased expression of the clock gene DBP, rendering DBP a lithium-regulated gene. We could confirm the role of the circadian clock as well in lithium mode of action as in the pathomechanisms of BD although future studies with a greater number of participants and cell lines are needed.

As detailed structural characterizations of large complex DNA nanostructures are hard to obtain experimentally, particularly if they have substantial flexibility, coarse-grained modeling can potentially provide an important complementary role. Such modeling can provide a detailed view of both the average structure and the structural fluctuations, as well as providing insight into how the nanostructure's design determines its structural properties. Here, we present a case study of jointed DNA nanostructures using the oxDNA model. In particular, we consider archetypal hinge and sliding joints, as well as more complex structures involving a number of such coupled joints. Our results highlight how the nature of the motion in these structures can sensitively depend on the precise details of the joints. Furthermore, the generally good agreement with experiments illustrates the power of this approach and suggests the use of such modeling to prescreen the properties of putative designs.

We prove the hitherto hypothesized sequential dissociation of Fe(CO)5 in the gas phase upon photoexcitation at 266 nm via a singlet pathway with time-resolved valence and core-level photoelectron spectroscopy with an x-ray free-electron laser. Valence photoelectron spectra are used to identify free CO molecules and to determine the time constants of stepwise dissociation to Fe(CO)4 within the temporal resolution of the experiment and further to Fe(CO)3 within 3 ps. Fe 3p core-level photoelectron spectra directly reflect the singlet spin state of the Fe center in Fe(CO)5, Fe(CO)4, and Fe(CO)3 showing that the dissociation exclusively occurs along a singlet pathway without triplet-state contribution. Our results are important for assessing intra- and intermolecular relaxation processes in the photodissociation dynamics of the prototypical Fe(CO)5 complex in the gas phase and in solution, and they establish time-resolved core-level photoelectron spectroscopy as a powerful tool for determining the multiplicity of transition metals in photochemical reactions of coordination complexes.

We use Monte Carlo simulations and free-energy techniques to show that binary solutions of penta- and hexavalent two-dimensional patchy particles can form thermodynamically stable quasicrystals even at very narrow patch widths, provided their patch interactions are chosen in an appropriate way. Such patchy particles can be thought of as a coarse-grained representation of DNA multi-arm 'star' motifs, which can be chosen to bond with one another very specifically by tuning the DNA sequences of the protruding arms. We explore several possible design strategies and conclude that DNA star tiles that are designed to interact with one another in a specific but not overly constrained way could potentially be used to construct soft quasicrystals in experiment. We verify that such star tiles can form stable dodecagonal motifs using oxDNA, a realistic coarse-grained model of DNA.

Knots are some of the most remarkable topological features in nature. Self-assembly of knotted polymers without breaking or forming covalent bonds is challenging, as the chain needs to be threaded through previously formed loops in an exactly defined order. Here we describe principles to guide the folding of highly knotted single-chain DNA nanostructures as demonstrated on a nano-sized square pyramid. Folding of knots is encoded by the arrangement of modules of different stability based on derived topological and kinetic rules. Among DNA designs composed of the same modules and encoding the same topology, only the one with the folding pathway designed according to the ‘free-end' rule folds efficiently into the target structure. Besides high folding yield on slow annealing, this design also folds rapidly on temperature quenching and dilution from chemical denaturant. This strategy could be used to design folding of other knotted programmable polymers such as RNA or proteins., Driven by complementary base pairing, artificial single-chain DNA is capable of forming complex 3D architectures if an appropriate folding pathway can be realised. Here, the authors describe the design principles for rapidly folding structures, exemplified through fabrication of a nanosized square pyramid.

The surface of a ceramic substrate can be modified locally by introducing a second phase into a melt pool generated by a laser beam. CuO and WO"3 powders with nano-sized particles were used to laser-alloy alumina and a low-temperature co-fired ceramic (LTCC). A composite with complex multiphase microstructure was developed with particle agglomerates, small crystals as well as grains covered with reaction phase, in parts with typical length scales down to the submicron range. The geometry of the modified area could be controlled by the process parameters as well. A significant change of the thermal and electrical properties could be established for the laser-alloyed tracks in comparison with that of the ceramic substrate. The developed composites showed an electrical conductivity with a negative temperature coefficient for resistivity, i.e. resistivity decreases with increase in temperature, which is typical for semiconductors. An enhancement of thermal conductivity could be established as well. Especially for the WO"3 powder, it could be increased about 50% compared to the unmodified LTCC substrate.

ITER will be equipped with four EC (Electron Cyclotron) upper launchers of 8 MW microwave power each with the aim to counteract plasma instabilities during operation. The launcher antennas will be installed into four upper ports of the ITER vacuum vessel. All in-vessel microwave components of an EC antenna, comprising several sets of mirrors and waveguides are mounted into so-called upper port plugs. These are basically hollow casks which fit into the ports as cantilevered built-in components, forming thus integrated systems which guarantee optimum performance and simplify assembly and maintenance.

Advances in DNA nanotechnology have stimulated the search for simple motifs that can be used to control the properties of DNA nanostructures. One such motif, which has been used extensively in structures such as polyhedral cages, two-dimensional arrays, and ribbons, is a bulged duplex, that is two helical segments that connect at a bulge loop. We use a coarse-grained model of DNA to characterize such bulged duplexes. We find that this motif can adopt structures belonging to two main classes: one where the stacking of the helices at the center of the system is preserved, the geometry is roughly straight and the bulge is on one side of the duplex, and the other where the stacking at the center is broken, thus allowing this junction to act as a hinge and increasing flexibility. Small loops favor states where stacking at the center of the duplex is preserved, with loop bases either flipped out or incorporated into the duplex. Duplexes with longer loops show more of a tendency to unstack at the bulge and adopt an open structure. The unstacking probability, however, is highest for loops of intermediate lengths, when the rigidity of single-stranded DNA is significant and the loop resists compression. The properties of this basic structural motif clearly correlate with the structural behavior of certain nano-scale objects, where the enhanced flexibility associated with larger bulges has been used to tune the self-assembly product as well as the detailed geometry of the resulting nanostructures., 12 pages + 4 pages of supplemental materials

X-ray spectroscopy is a powerful tool to study the local charge distribution of chemical systems. Together with the liquid jet it becomes possible to probe chemical systems in their natural environment, the liquid phase. In this work, we present X-ray absorption (XA), X-ray emission (XE) and resonant inelastic X-ray scattering (RIXS) data of pure water and various salt solutions and show the possibilities these methods offer to elucidate the nature of ion-water interaction.

Laser-supported processes can be used to modify the electrical and thermal properties of ceramic substrates locally. These processes are characterized by a strong thermal interaction between the laser beam and the ceramic surface, which leads to localized melting. During the dynamic melting process, an additive material is injected into the melt pool in order to modify the physical properties. The heat and mass transfer during this dynamic melting and solidification process has been studied numerically in order to identify the dominating process parameters. Simulation tools based on a finite-volume method have been developed to describe the heat transfer, fluid flow, and phase change during the melting and solidification of the ceramic. The results of the calculation have been validated against experimental results.

Activation-induced cytidine deaminase (AID) is essential for somatic hypermutation (SHM) and class switch recombination (CSR) of immunoglobulin genes in antigen-dependent B-cell maturation. SHM is not restricted to immunoglobulin gene loci, raising the possibility of a function for AID in other cell types. In this study, it is shown that AID is expressed in spermatocytes in the human testis. AID was mostly cytoplasmic but nuclear AID was also observed in a proportion of cells, in keeping with the DNA deamination model of AID function. Intratubular germ cell neoplasia unclassified (IGCNU), the precursor lesion of testicular cancers, was AID-negative. Seminomas also lacked AID expression. Nuclear and cytoplasmic AID expression was observed in three of 32 mixed non-seminomatous germ cell tumours. The results provide evidence for a physiological role for AID outside the immune system. AID expression in spermatocytes points to a role in meiosis. It remains uncertain whether AID may also contribute to the genetic aberrations characteristically found in testicular germ cell tumours. The consistent absence of detectable AID expression in atypical spermatogonia of IGCNU and its rare expression in germ cell tumours suggest that continued expression of AID is not involved in the pathogenesis of germ cell tumours.

Laser supported processes can be used to modify the electrical and thermal properties of ceramic substrates locally. These processes are characterised by a strong thermal interaction between the laser beam and the ceramic surface which leads to localised melting. During the dynamic melting process an additive material is injected into the melt pool in order to modify the physical properties. The heat and mass transfer during this dynamic melting and solidification process has been studied numerically in order to identify the dominant process parameters. Simulation tools based on a finite volume method have been developed to describe the heat transfer, fluid flow and the phase change during the melting and solidification of the ceramic. The results of the calculation have been validated against experimental results.

Tribological properties of a system are very important for saving energy or increasing service life as in automotive industry. It is known that wear and friction behaviour is strongly influenced by the topography of the mated surfaces. In case of lubricated sliding contact the tribological properties can be improved by generating a defined surface structure in form of small channels or isolated pits. Depending on the structure it may act as a reservoir for the lubricant and hampers the drain of the lubricant. In addition, wear particles can be removed from the contact area and can be collected inside the structures. In the present paper, a Nd:YAG-laser was used to generate different structures on ceramic (Al 2 O 3 ) and steel (100Cr6) surfaces. Microchannels and micropits were generated onto an otherwise flat surface by a laser ablation process. Due to the high flexibility of the laser system, structural features such as size, density and orientation could be varied easily by changing the laser parameters. The effects of different topographies on friction and wear behaviour were examined using a cylinder/plate tribometer for lubricated and reversed sliding contact. Laser structured 100Cr6 and alumina surfaces mated to 100Cr6 cylinders showed that a reduction of friction could be achieved in comparison to the polished surfaces. Dependent on the kind of the surface structure the coefficient of friction could be reduced up to 30%, especially in the initial period of the tribological experiment. The results show that the laser technique is an effective tool to optimise the topography of tribological surfaces.

The objective of this work is the development of a laser-supported process that allows to modify the electric and thermal properties of ceramics on a local scale. The principle of the process is based on local melting of the ceramic by a CO 2 laser beam and application of an additive to the molten area on the surface. During solidification, a metal–ceramic composite is formed with modified material properties compared to the bulk material. Different alumina samples were treated with metal powders of tungsten, copper, and oxides of these metals. Scanning electron microscopy (SEM) and energy-dispersive X-ray microanalysis (EDX) analysis reveal that the physical and chemical properties of a peripheral zone are changed in the heated region down to a depth of approximately 500 μm. The resulting resistance of the laser tracks can be adjusted from semi-conducting to metallic behavior with a resistivity down to 2×10 −6 Ω/m. The modified ceramic can be used for heating elements working at operation temperatures of up to 1000 °C, high current resistance which can be loaded with current of up to 100 A.

A laser supported process has been developed to modify the electrical and thermal properties of ceramic substrates locally. This process is characterised by a strong thermal interaction between the laser beam and the ceramic surface which leads to localised melting. During the dynamic melting process an additional metallic material is introduced. After the solidification a metal-ceramic composite has been generated with different physical properties compared to the non-modified ceramic. The heat and mass transfer during this dynamic melting and solidification process has been studied experimentally and also numerically in order to identify the dominating process parameters. Simulation tools based on a finite element model have been developed to describe the heat transfer, fluid flow and the phase change during the melting and solidification of the ceramic. The results of the calculation have been validated against experimental results.

A laser supported process has been developed to modify the electrical and thermal properties of ceramic substrates locally. This process is characterized by a strong thermal interaction between the laser beam and the ceramic surface which leads to localized melting. During the dynamic melting process, an additional metallic material is introduced. After the solidification, a metal-ceramic composite has been generated with different physical properties compared to the non-modified ceramic. The heat and mass transfer during this dynamic melting and solidification process has been studied experimentally and also numerically in order to identify the dominating process parameters.

To simulate long time and length scale processes involving DNA it is necessary to use a coarse-grained description. Here we provide an overview of different approaches to such coarse graining, focussing on those at the nucleotide level that allow the self-assembly processes associated with DNA nanotechnology to be studied. OxDNA, our recently-developed coarse-grained DNA model, is particularly suited to this task, and has opened up this field to systematic study by simulations. We illustrate some of the range of DNA nanotechnology systems to which the model is being applied, as well as the insights it can provide into fundamental biophysical properties of DNA., 20 pages, 9 figures