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Virtual reality allows creating highly immersive visual and auditory experiences, making users feel physically present in the environment. This makes it an ideal platform to simulate dangerous scenarios, including fire evacuation, and study human behaviour without exposing users to harmful elements. However, human perception of the surroundings is based on the integration of multiple sensory cues (visual, auditory, tactile, or/and olfactory) present in the environment. When some of the sensory stimuli are missing in the virtual experience, it can break the illusion of being there in the environment and could lead to actions that deviate from normal behaviour. In this work, we added an olfactory cue in a well-documented historic hotel fire scenario that was recreated in VR, and examined the effects of the olfactory cue on human behaviour. We conducted a between subject study on 40 naive participants. Our results show that the addition of the olfactory cue could increase behavioural realism. We found that 80% of the studied actions for the VR with olfactory cue condition matched the ones performed by the survivors. In comparison, only 40% of the participants' actions for VR only condition were similar to the survivors., Comment: Accepted at IEEE International Symposium on Mixed and Augmented Reality (ISMAR) 2023, 9 pages

We combine X-ray-specific tracer particles, a photon counting detector, and a liquid metal jet anode X-ray source to achieve $O$(1 kHz) X-ray imaging speeds in the laboratory, 15$\times$ faster than previous comparable studies with $O$(50 $\mu$m) tracers. To examine the limits of this measurement technique we conduct three experiments: 2D and 3D X-ray particle velocimetry (XPV) of Poiseuille pipe flow, 3D XPV of flow around a Taylor bubble, and 3D scalar mixing with a laminar jet. These experiments demonstrate the performance improvement achievable by combining the aforementioned elements, the applicability to multiphase flows and deforming systems, and the potential to capture scalar and vector quantities simultaneously. Most importantly, these experiments are conducted with a laboratory-scale system, showing that in-lab X-ray particle velocimetry techniques are now becoming usable for a wider range of flows of interest. Furthermore, the design of XPV experiments is discussed to clarify the trade offs between achievable imaging speed, domain size and spatiotemporal resolution.

Real-time forecasting of travel demand during wildfire evacuations is crucial for emergency managers and transportation planners to make timely and better-informed decisions. However, few studies focus on accurate travel demand forecasting in large-scale emergency evacuations. Therefore, this study develops and tests a new methodological framework for modeling trip generation in wildfire evacuations by using (a) large-scale GPS data generated by mobile devices and (b) state-of-the-art AI technologies. The proposed methodology aims at forecasting evacuation trips and other types of trips. Based on the travel demand inferred from the GPS data, we develop a new deep learning model, i.e., Situational-Aware Multi-Graph Convolutional Recurrent Network (SA-MGCRN), along with a model updating scheme to achieve real-time forecasting of travel demand during wildfire evacuations. The proposed methodological framework is tested in this study for a real-world case study: the 2019 Kincade Fire in Sonoma County, CA. The results show that SA-MGCRN significantly outperforms all the selected state-of-the-art benchmarks in terms of prediction performance. Our finding suggests that the most important model components of SA-MGCRN are evacuation order/warning information, proximity to fire, and population change, which are consistent with behavioral theories and empirical findings.

Dielectrophoresis is an electric field-based technique for moving neutral particles through a fluid. When used for particle separation, dielectrophoresis has many advantages compared to other methods, providing label-free operation with greater control of the separation forces. In this paper, we design, build, and test a low-voltage dielectrophoretic device using a 3D printing approach. This lab-on-a-chip device fits on a microscope glass slide and incorporates microfluidic channels for particle separation. First, we use multiphysics simulations to evaluate the separation efficiency of the prospective device and guide the design process. Second, we fabricate the device in PDMS (polydimethylsiloxane) by using 3D-printed moulds that contain patterns of the channels and electrodes. The imprint of the electrodes is then filled with silver conductive paint, making a 9 pole comb electrode. Lastly, we evaluate the separation efficiency of our device by introducing a mixture of 3 $\mu$m and 10 $\mu$m polystyrene particles and tracking their progression. Our device is able to efficiently separate these particles when the electrodes are energized with $\pm$12 V at 75 kHz. Overall, our method allows the fabrication of cheap and effective dielectrophoretic microfluidic devices using commercial off-the-shelf equipment., Comment: 1 supporting information file

With increased frequency and intensity due to climate change, wildfires have become a growing global concern. This creates severe challenges for fire and emergency services as well as communities in the wildland-urban interface (WUI). To reduce wildfire risk and enhance the safety of WUI communities, improving our understanding of wildfire evacuation is a pressing need. To this end, this study proposes a new methodology to analyze human behavior during wildfires by leveraging a large-scale GPS dataset. This methodology includes a home-location inference algorithm and an evacuation-behavior inference algorithm, to systematically identify different groups of wildfire evacuees (i.e., self-evacuee, shadow evacuee, evacuee under warning, and ordered evacuee). We applied the methodology to the 2019 Kincade Fire in Sonoma County, CA. We found that among all groups of evacuees, self-evacuees and shadow evacuees accounted for more than half of the evacuees during the Kincade Fire. The results also show that inside of the evacuation warning/order zones, the total evacuation compliance rate was around 46% among all the categorized people. The findings of this study can be used by emergency managers and planners to better target public outreach campaigns, training protocols, and emergency communication strategies to prepare WUI households for future wildfire events.

Trans-splicing of leader sequences onto the 59ends of mRNAs is a widespread phenomenon in protozoa, nematodes and some chordates. Using parallel sequencing we have developed a method to simultaneously map 59splice sites and analyze the corresponding gene expression profile, that we term spliced leader trapping (SLT). The method can be applied to any organism with a sequenced genome and trans-splicing of a conserved leader sequence. We analyzed the expression profiles and splicing patterns of bloodstream and insect forms of the parasite Trypanosoma brucei. We detected the 59splice sites of 85% of the annotated protein-coding genes and, contrary to previous reports, found up to 40% of transcripts to be differentially expressed. Furthermore, we discovered more than 2500 alternative splicing events, many of which appear to be stage-regulated. Based on our findings we hypothesize that alternatively spliced transcripts present a new means of regulating gene expression and could potentially contribute to protein diversity in the parasite. The entire dataset can be accessed online at TriTrypDB or through: http://splicer.unibe.ch/., Comment: 13 pages, 8 figures

Motorized rotation mounts and stages are versatile instruments that introduce computer control to optical systems, enabling automation and scanning actions. They can be used for intensity control and position adjustments, etc. However, these rotation mounts come with a hefty price tag, and this limits their use. This work shows how to build two different types of motorized rotation mounts for 1" optics, using a 3D printer and off-the-shelf components. The first is intended for reflective elements, like mirrors and gratings, and the second for transmissive elements, like polarizers and retarders. We evaluate and compare their performance to commercial systems based on velocity, resolution, accuracy, backlash, and axis wobble. Also, we investigate the angular stability using Allan variance analysis. The results show that our mounts perform similar to systems costing more than 2000 Euro, while also being quick to build and costing less than 200 Euro. As a proof of concept, we show how to control lasers used in an optical tweezers and Raman spectroscopy setup. When used for this, the 3D printed motorized rotational mounts provide intensity control with a resolution of $0.03$ percentage points or better.

The formation of biomolecular condensates inside cells often involve intrinsically disordered proteins (IDPs), and several of these IDPs are also capable of forming droplet-like dense assemblies on their own, through liquid-liquid phase separation. When modelings thermodynamic phase changes, it is well-known that finite-size scaling analysis can be a valuable tool. However, to our knowledge, this approach has not been applied before to the computationally challenging problem of modeling sequence-dependent biomolecular phase separation. Here, we implement finite-size scaling methods to investigate the phase behavior of two 10-bead sequences in a continuous hydrophobic/polar protein model. Combined with reversible explicit-chain Monte Carlo simulations of these sequences, finite-size scaling analysis turns out to be both feasible and rewarding, despite relying on theoretical results for asymptotically large systems. While both sequences form dense clusters at low temperature, this analysis shows that only one of them undergoes liquid-liquid phase separation. Furthermore, the transition temperature at which droplet formation sets in, is observed to converge slowly with system size, so that even for our largest systems the transition is shifted by about 8%. Using finite-size scaling analysis, this shift can be estimated and corrected for., Comment: 18 pages, 8 figures, to appear in Physical Review E

The Hesperos mission proposed in this paper is a mission to Venus to investigate the interior structure and the current level of activity. The main questions to be answered with this mission are whether Venus has an internal structure and composition similar to Earth and if Venus is still tectonically active. To do so the mission will consist of two elements: an orbiter to investigate the interior and changes over longer periods of time and a balloon floating at an altitude between 40 and 60\~km to investigate the composition of the atmosphere. The mission will start with the deployment of the balloon which will operate for about 25 days. During this time the orbiter acts as a relay station for data communication with Earth. Once the balloon phase is finished the orbiter will perform surface and gravity gradient mapping over the course of 7 Venus days. This mission proposal is the result of the Alpbach Summer School and the post-Alpbach week., Comment: The article was submitted to Advances in Space Research in November 2016. It was accepted with major revisions. Due to unavailability of the team after the end of the project, the paper wasn't fully revised and the submission was withdrawn. The current version includes most of the revisions

We use Markov state models (MSMs) to analyze the dynamics of a $\beta$-hairpin-forming peptide in Monte Carlo (MC) simulations with interacting protein crowders, for two different types of crowder proteins [bovine pancreatic trypsin inhibitor (BPTI) and GB1]. In these systems, at the temperature used, the peptide can be folded or unfolded and bound or unbound to crowder molecules. Four or five major free-energy minima can be identified. To estimate the dominant MC relaxation times of the peptide, we build MSMs using a range of different time resolutions or lag times. We show that stable relaxation-time estimates can be obtained from the MSM eigenfunctions through fits to autocorrelation data. The eigenfunctions remain sufficiently accurate to permit stable relaxation-time estimation down to small lag times, at which point simple estimates based on the corresponding eigenvalues have large systematic uncertainties. The presence of the crowders have a stabilizing effect on the peptide, especially with BPTI crowders, which can be attributed to a reduced unfolding rate $k_\text{u}$, while the folding rate $k_\text{f}$ is left largely unchanged., Comment: 18 pages, 6 figures

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