cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Landslide susceptibility of the Prato–Pistoia–Lucca provinces, Tuscany, Italy
Creators: name: Segoni, Samuele
name: Tofani, Veronica
name: Lagomarsino, Daniela
name: Moretti, Sandro
Publisher: name: Taylor & Francis
Year: 2016
Subjects: subject: Medicine
subject: Neuroscience
subject: Biotechnology
subject: Ecology
subject: FOS: Biological sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: Cancer
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: Plant Biology
subject: Computational Biology

description: We mapped landslide susceptibility in the provinces of Lucca, Pistoia and Prato (central Italy), a 3103 km2 territory that approximately corresponds to the portion of Tuscany principally affected by landslides. We used a methodology based on a treebagger random forest. The input parameters used for the susceptibility assessment are curvature, flow accumulation, topographic wetness index, elevation, profile curvature, planar curvature, slope gradient, aspect, land use and lithology. The map was validated providing satisfactory results (AUC = 0.84). The map classifies the study area into four susceptibility classes that identify areas with different probabilities of being affected by landslides. The Main Map represents a useful instrument to assist land planning, development of mitigation measures and landslide risk management. Moreover, it could be used in further research addressing quantitative hazard and risk assessment.
Analysis and design of two-dimensional compound metallic metagratings using an analytical method
Creators: name: Rahmanzadeh, Mahdi
name: Khavasi, Amin
Publisher: name: arXiv
Year: 2021
Subjects: subject: Classical Physics (physics.class-ph)
subject: Optics (physics.optics)
subject: FOS: Physical sciences

description: The recently proposed concept of metagrating enables wavefront manipulation of electromagnetic (EM) waves with unitary efficiency and relatively simple fabrication requirements. Herein, two-dimensional (2D) metagratings composed of a 2D periodic array of rectangular holes in a metallic medium are proposed for diffraction pattern control. We first present an analytical method for diffraction analysis of 2D compound metallic metagrating (a periodic metallic structure with more than one rectangular hole in each period). Closed-form and analytical expressions are presented for the reflection coefficients of diffracted orders for the first time. Next, we verify the proposed method's results against full-wave simulations and demonstrate their excellent agreement. As a proof of principle, two applications are presented using the proposed analytical method. The first application is a perfect out-of-plane reflector that transfers a normal transverse-magnetic (TM) polarized plane wave to an oblique transverse-electric (TE) polarized plane wave in the $y-z$ plane. The second one is a five-channel beam splitter with an arbitrary power distribution between channels. Using the proposed analytical method, we designed these metagratings without requiring even a single optimization in a full-wave solver. The performance of the designed metagratings is better than previously reported structures in terms of power efficiency and relative distribution error. Our analytical results reveals that 2D metagratings can be used for manipulating EM waves in the plane and out of the plane of incidence with very high efficiency, thereby leading to extensive applications in a wide range of frequencies from microwave to terahertz (THz) regimes.
Metamodeling approaches to help designing vegetative filter strips and improve the water quality
Creators: name: Lauvernet, Claire
name: Helbert, Céline
name: Xujia, Zhu
name: Sudret, Bruno
Publisher: name: ETH Zurich
Year: 2022

description: Significant amounts of pollutant are measured in surface water, their presence due in part to the use of pesticides in agriculture. One solution to limit pesticide transfer by surface runoff is to implement vegetative filter strips (VFS) along rivers. The sizing of these strips is a major issue, with influencing factors that include local conditions (climate, soil, etc.). The BUVARD modeling toolkit was developed to design VFSs throughout France according to these properties. This toolkit includes the numerical model VFSMOD, which quantifies dynamic effects of VFS site-specific pesticide mitigation efficiency. However, the toolkit is quite complex to use with many input uncertain parameters (quantitative - such as the slope, the Curve Number - or qualitative -such as the soil type or the rainfall event), making it not easy to use for risk management.

In this study, a metamodeling (or model dimension reduction) approach is proposed to ease the use of BUVARD and to help users design VFSs that are adapted to specific contexts. Different reduced models, or surrogates, are compared, based on Bayesian learning approaches or not: Polynomial Chaos Expansions, Mixed-kriging, and Deep-GP. Mixed-kriging is a kriging method that was implemented with a covariance kernel for a mixture of qualitative and quantitative inputs. Kriging and Deep-GP are built by couple of modalities and PCE and Mixed-kriging are built considering mixed quantitative and qualitative variables. As a last step, Finally, we perform a global sensitivity analysis with the help of the two surrogate models with the best accuracy. The results show that they give the same ranking of the importance of the input parameters.

The metamodel is a simple way to provide a relevant first guess to help design the pollution reduction device. In addition, the surrogate model is a relevant uncertainty tool, to visualize the impact that lack of knowledge of some parameters of filter efficiency can have when performing risk analysis and management.
description: EGUsphere
Tree water-use recovery after drought-intermittent rainfall events
Creators: name: Shekhar, Ankit
name: Paul-Limoges, Eugénie
name: Zweifel, Roman
name: Buchmann, Nina
name: Gharun, Mana
Publisher: name: ETH Zurich
Year: 2022

description: Short drought-intermittent rainfall (SDIR) events, i.e., short rainfall events after long dry spells, typically re-wet top few centimeters of soil layer and often has little impact on the water balance of the ecosystem. Nevertheless, these SDIR events could provide the much-needed short-term water supply during dry spells to the terrestrial ecosystem, especially trees. An efficient use of these SDIR events could provide the trees with a buffer to withstand longer drought conditions, which will become more frequent and intense with the upcoming changes in climate.

This study aims to quantify the tree water use (TWU) recovery in terms of sapflow recovery following SDIR events across multiple global forest sites (35 sites) spanning over 250 site-years. SDIR events are identified probabilistically as rainfall periods (1-2 days with daily rainfall < 75th percentile) occurring after an extreme dry spell (> 90th percentile of dry spell duration) during the growing season. For each tree, TWU recovery (RTWU) is estimated based on percentage increase in sapflow rate after the SDIR event (Sa), compared to before the SDIR event (Sb), and standardized by seasonal maximum sapflow (Smax). The inter-species RTWU and intra-species RTWU relationship with tree allometry (height and diameter) is used to explain the recovery rates. The main hypothesis tested here is that the intra-species differences in RTWU are positively related to tree size due to better root development in larger trees. The understanding of RTWU provides a new axis to understand and predict tree recovery after drought events.
description: EGUsphere
Improving the accuracy of rapid Earth Orientation Parameters with the "ResLearner" machine learning method
Creators: name: Kiani Shahvandi, Mostafa
name: Dill, Robert
name: Dobslaw, Henryk
name: Mishra, Siddhartha
name: Soja, Benedikt
Publisher: name: ETH Zurich
Year: 2023

description: Determination of Earth Orientation Parameters (EOP) with utmost accuracy requires the combination of various data sources from different space geodetic techniques, some of which requiring long processing time. This results in a latency of up to several weeks by which the so-called final EOP are released. Since some of the important applications, including satellite navigation and orientation of deep space telescopes, require instantaneous EOP information, the so-called rapid determination and also prediction of EOP are needed. International Earth Rotation and Reference Systems Service (IERS) provides rapid EOP by using the most recent Global Positioning System (GPS) and Very Long Baseline Interferometry (VLBI) 24-hour and intensive sessions data. However, there are some discrepancies between these rapid data and the final, most accurate EOP. In order to reduce these discrepancies and achieve more accurate rapid EOP, we focus on applying machine learning algorithms for polar motion components (xp, yp) and dUT1=UT1-UTC. We focus on a window of 63 days with 31 day predictions to the past and 31 day predictions to the future.

We devise a new algorithm called ResLearner, which is a machine learning method based on multilayer perceptrons trying to learn the differences between rapid and final EOP data. We use informative features such as Effective Angular Momentum (EAM) data (both the observations provided by GFZ and the 14-day forecasts provided by ETH Zurich), tides, Liouville equation for (xp, yp), and a linear relation between dUT1 and the axial components of EAM.
We use ResLearner in the context of Deep Ensembles in order to derive the uncertainty in the estimations. We also address the so-called unmixing and self-calibration problems. The former enables us to unravel the causes behind the discrepancies between rapid and final EOP as provided by IERS, while the latter could help us reduce these erroneous effects. 

We train the algorithms on both the IERS and Jet Propulsion Laboratory (JPL) final EOP data. Our ResLearner method can consistently reduce the discrepancies between rapid and final EOP across all days. The improvement in accuracy is up to 55%. We observe some unexpected behaviour related to day 0 of prediction, in which the accuracy of the IERS is significantly better than the immediately preceding or following values. Our unmixing algorithm shows that this behaviour is probably related to erroneous, non-linear effects of EAM at day 0, and also semi-diurnal, diurnal, long-period retrograde and prograde, and zonal tides. Using our self-calibration algorithm for EAM, we can slightly improve the prediction performance by up to 14%.

Finally, we provide the improved rapid EOP data publicly, operationally, and on a daily basis, on the ETH Zurich prediction center website at https://gpc.ethz.ch/EOP/Rapid/
description: EGUsphere
QU-net++: Image Quality Detection Framework for Segmentation of Medical 3D Image Stacks
Creators: name: Roychowdhury, Sohini
Publisher: name: arXiv
Year: 2021
Subjects: subject: Image and Video Processing (eess.IV)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: Automated segmentation of pathological regions of interest aids medical image diagnostics and follow-up care. However, accurate pathological segmentations require high quality of annotated data that can be both cost and time intensive to generate. In this work, we propose an automated two-step method that detects a minimal image subset required to train segmentation models by evaluating the quality of medical images from 3D image stacks using a U-net++ model. These images that represent a lack of quality training can then be annotated and used to fully train a U-net-based segmentation model. The proposed QU-net++ model detects this lack of quality training based on the disagreement in segmentations produced from the final two output layers. The proposed model isolates around 10% of the slices per 3D image stack and can scale across imaging modalities to segment cysts in OCT images and ground glass opacity (GGO) in lung CT images with Dice scores in the range 0.56-0.72. Thus, the proposed method can be applied for cost effective multi-modal pathology segmentation tasks.
description: 4 pages, 7 figures, 1 Table
Automatic MTM-Transcription in Virtual Reality Using the Digital Twin of a Workplace
Creators: name: Andreopoulos, Emmanouil
name: Gorobets, Valentina
name: Kunz, Andreas
Publisher: name: ETH Zurich
Year: 2022
Subjects: subject: Virtual Reality (VR)
subject: MTM
subject: Workplace Optimization

description: Despite the high level of automation in industrial production, manual operations still play an important role and contribute significantly to the overall production costs. For the evaluation of these manual processes the ``Methods-Time Measurement'' (MTM) is widely used. This method is applied to real workplaces or mock-ups thereof, while also Virtual Reality (VR) can be used for the representation of such workplaces. However, the evaluation of the workers' performed actions is still done manually, which is a time-consuming and error-prone process. This paper introduces an approach to automatically detect full-body actions of users in VR and consequently derive the appropriate MTM values, without knowledge of a pre-existing workplan. The detection algorithm that was developed is explained in detail and its performance is analyzed through a user study with 30 participants.
description: Research Square
Impact of erroneous station coordinates on the estimation of UT1-UTC with VLBI Intensive sessions
Creators: name: Kern, Lisa
name: Schartner, Matthias
name: Böhm, Johannes
name: Böhm, Sigrid
name: Nothnagel, Axel
name: Soja, Benedikt
Publisher: name: ETH Zurich
Year: 2022

description: So-called Intensives are one-hour-long VLBI sessions including mostly two stations, which are routinely observed to derive the Earth's phase of rotation expressed through the parameter UT1-UTC. Due to the limitation in time and participating stations, only a few parameters of interest can be estimated during the analysis, whereas others are fixed to their a priori values, such as the remaining Earth orientation parameters, as well as station and source coordinates. 

It is common knowledge that the impact of errors in the a priori station coordinates on the UT1-UTC results changes depending on the location, orientation and length of the baseline. In this presentation, we examine these effects for the first time in a systematic way covering the whole Earth. We performed Monte-Carlo simulations (MCS) with realistic noise models for a global 10° grid of artificial VGOS stations. The grid covers latitudes of -80° to 80° and longitudes of 0° to 180°. All possible and unambiguous baselines between these artificial telescopes are investigated. For every baseline, monthly schedules were generated over one year to eliminate source selection effects. In the MCS, the station coordinates are compromised with an error of 5 mm in either North-South, East-West or Up-Down direction. 

Thereby, we demonstrate that errors along the East-West direction tend to be less critical for long East-West baselines compared to errors in North-South direction. Furthermore, we show that errors in the station height are less critical compared to errors in North-South or East-West direction. The simulation results show that investigations of suitable locations for additional radio telescopes for UT1-UTC Intensive sessions cannot be selected by investigations in analytical equations such as the partial derivatives of the parameters alone but need more sophisticated analyses of error propagation.
description: EGUsphere
Uncertainty in Grain Size Estimations of Volatiles on Trans-Neptunian Objects (TNOs) and Kuiper Belt Objects (KBOs)
Creators: name: Emran, A.
name: Chevrier, V. F.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Earth and Planetary Astrophysics (astro-ph.EP)
subject: FOS: Physical sciences

description: We analyze the uncertainty in grain size estimation of pure methane (CH4) and nitrogen saturated with methane (N2:CH4) ices, the most abundant volatile materials on trans-Neptunian objects (TNOs) and Kuiper belt objects (KBOs). We compare the single scattering albedo, which determines the grain size estimation of outer solar system regolith (Hansen, 2009), of these ices using the Mie scattering model and two other Hapke approximations (Hapke, 1993) in radiative transfer scattering models (RTM) at near-infrared (NIR) wavelengths (1-5 $μ$m). The equivalent slab (Hapke Slab) approximation model predicts results much closer to Mie scattering over the NIR wavelengths at a wide range of grain sizes. In contrast, even though the internal scattering model (ISM) predicts an approximate particle diameter close to the Mie model for particles with a 10 $μ$m radii, it exhibits higher discrepancies in the predicted estimation for larger grain sizes (e.g., 100 and 1000 $μ$m radii). Owing to the Rayleigh effect on single-scattering properties, neither Hapke approximate models could predict an accurate grain size estimation for the small particles (radii $\leq$ 5 $μ$m). We recommend that future studies should favor the equivalent slab approximation when employing RTMs for estimating grain sizes of the vast number of TNOs and KBOs in the outer solar system.
description: 11 pages, 4 figures, 1 table. Submitted to AJ
Reinforcement Learning-based Human Operator Decision Support Agent for Highly Transient Industrial Processes
Creators: name: Ruan, Jianqi
Publisher: name: Purdue University Graduate School
Year: 2024
Subjects: classificationCode: 401799
subject: Mechanical engineering not elsewhere classified

description: Most industrial processes are not fully-automated. Although reference tracking can be handled by low-level controllers, initializing and adjusting the reference, or setpoint, values, are commonly tasks assigned to human operators. A major challenge that arises, though, is control policy variation among operators which in turn results in inconsistencies in the final product. In order to guide operators to pursue better and more consistent performance, researchers have explored the optimal control policy through different approaches. Although in different applications, researchers use different approaches, an accurate process model is still crucial to the approaches. However, for a highly transient process (e.g., the startup of a manufacturing process), modeling can be challenging and inaccurate, and approaches highly relying on a process model may not work well. One example is process startup in a twin-roll steel strip casting process and motivates this work.
 In this dissertation, I propose three offline reinforcement learning (RL) algorithms which require the RL agent to learn a control policy from a fixed dataset that is pre-collected by human operators during operations of the twin-roll casting process. Compared to existing offline RL algorithms, the proposed algorithms focus on exploiting the best control policy used by human operators rather than exploring new control policies constrained by the existing policies. In addition, in existing offline RL algorithms, there is not enough consideration of the imbalanced dataset problem. In the second and the third proposed algorithms, I leverage the idea of cost sensitive learning to incentivize the RL agent to learn the most valuable control policy, rather than the most common one represented in the dataset. In addition, since the process model is not available, I propose a performance metric that does not require a process model or simulator for agent testing. The third proposed algorithm is compared with benchmark offline RL algorithms and achieves better and more consistent performance.
Investigation of the falling asleep dynamics and its closed-loop augmentation strategy
Creators: name: Li, Junheng
Publisher: name: Imperial College London
Year: 2023

description: Sleep onset insomnia is a common sleep disturbance, particularly in the pathological ageing pop- ulation such as patients with neurodegenerative diseases and dementia. The bi-directional rela- tionship between sleep disorders and neurodegeneration makes it a novel early-stage treatment venue. Pharmacological treatments for insomnia often cause side effects and fail to show cog- nitive benefits. Novel neuromodulatory approaches, especially phase-synchronised closed-loop auditory stimulation targeting neural oscillations, have been promising candidates for enhancing deep sleep, but are yet to be explored for augmenting sleep onset. Standard sleep staging has poor temporal resolution and bad matches to subjective experi- ence, especially for patients with sleep-onset insomnia. Therefore, a better understanding of the falling asleep dynamics outside the sleep staging is necessary for better outcome measurements and closed-loop control. This thesis aims to study the falling asleep brain dynamics measured via electroencephalogram (EEG) on large sleep datasets and test the feasibility of using closed-loop auditory stimulation to augment the process. I first developed a novel feature-based statisti- cal learning approach to explore the EEG dynamics and identified several whole-brain EEG biomarkers for distinguishing the wakefulness and sleep onset states. Combined with the dy- namical systems theory, I then built a functional model to describe the continuous falling asleep transition dynamics as a catastrophic bifurcation process. Additionally, I explored the regional brain dynamics and their interactions during the falling asleep process, which provided further insights into sleep initiation. Lastly, I present a nap study to test the feasibility of phase-synchronised auditory stimulation in augmenting falling asleep, using the EEG biomarkers identified as outcome measurements. I also tested the effect of auditory-intervened naps on memory functions. The results showed a weak positive effect on associative memory. Further refined analyses are necessary to reveal mechanistic insights and guide future experimental explorations for a personalised stimulation design.
Pattern of flower size variation along an altitudinal gradient differs between Impatiens textori and Impatiens noli-tangere
Creators: name: Hattori, Mitsuru
name: Nagano, Yusuke
name: Shinohara, Yoshinori
name: Itino, Takao
Publisher: name: Taylor & Francis
Year: 2016
Subjects: subject: Evolutionary Biology
subject: FOS: Biological sciences
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: Ecology
subject: Marine Biology
subject: Plant Biology

description: Studies of factors influencing spatial variation in flower size offer insights into floral evolution. We investigated altitudinal variations in five flower dimensions of two native Japanese Impatiens species (I. textori and I. noli-tangere) and their interactions with their faunal visitors. These two species have similar floral traits, including flower shape, flowering time, and pollinator species; both species are pollinated mainly by Bombus diversus. In I. textori, all measured flower dimensions were negatively correlated with altitude. In contrast, in I. noli-tangere, no measured flower dimensions correlated with altitude. Thus, the altitudinal pattern of flower size variation differed between these congeneric co-habiting herbaceous plant species. The different patterns suggest that the factors (e.g. altitudinal variations of abiotic factors) that cause variation of flower size differ between these two Impatiens species even though focal species have similar floral traits (e.g. flower shape, flowering time, and pollinator species).
Hydrogen isotopes from lipid biomarkers record eutrophication induced changes in algal community assemblages
Creators: name: Ladd, S. Nemiah
name: Nelson, Daniel B.
name: Matthews, Blake
name: Dyer, Shannon
name: Narwani, Anita
name: Dubois, Nathalie
name: Schubert, Carsten
Publisher: name: ETH Zurich
Year: 2022

description: Phytoplankton are an important biogeochemical force, collectively impacting nutrient cycling as well as atmospheric and aquatic chemistry. However, it remains challenging to reconstruct changes in algal productivity and community assembly throughout the geologic past. Here, we lay the foundation for a sensitive proxy of past algal ecology based on compound-specific hydrogen isotope compositions (δ2H values) of common algal lipids. While such measurements have previously been used as indicators of water hydrogen isotope ratios, our results from laboratory cultures and experimental ponds demonstrate that changes in the δ2H values of ubiquitous lipids such as palmitic acid associated with taxonomic changes are an order of magnitude greater than those caused by hydrologic change. These results indicate that δ2H values of algal lipids, and the relative offset of these values among different compounds, can be used to reconstruct past changes in algal community assemblages, including those driven by changes in nutrient supply.

We apply this approach to a ~180 year sedimentary record from Lake Greifen, a lake in the central Swiss Plateau that underwent well-documented eutrophication and partial recovery in the second half of the 20th century. As total phosphorus concentrations in the lake increased from > 100 mg/L to ~ 500 mg/L in the 1950s-1970s, palmitic acid d2H values increased by 40 ‰ and phytol δ2H values by 20 ‰;  δ2H values of both compounds subsequently declined with total P following maximum values in the early 1980s. During this entire time interval, mean annual precipitation δ2H values fluctuated within a ~10 ‰ range and are not correlated with the changes in lipid δ2H values. Additionally, the decline in lipid δ2H values is correlated with declining relative abundance of green algae as the eutrophication pressure on Lake Greifen receded in the past decades. This correlation matches the prediction from our culturing and mesocosm results, where green algae produced exceptionally 2H-enriched fatty acids, and indicates that lipid δ2H can be applied to reconstruct nutrient induced shifts in algal populations.
description: EGUsphere
Dispersive optical systems for scalable Raman driving of hyperfine qubits
Creators: name: Levine, Harry
name: Bluvstein, Dolev
name: Keesling, Alexander
name: Wang, Tout T.
name: Ebadi, Sepehr
name: Semeghini, Giulia
name: Omran, Ahmed
name: Greiner, Markus
name: Vuletić, Vladan
name: Lukin, Mikhail D.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Hyperfine atomic states are among the most promising candidates for qubit encoding in quantum information processing. In atomic systems, hyperfine transitions are typically driven through a two-photon Raman process by a laser field which is amplitude modulated at the hyperfine qubit frequency. Here, we introduce a new method for generating amplitude modulation by phase modulating a laser and reflecting it from a highly dispersive optical element known as a chirped Bragg grating (CBG). This approach is passively stable, offers high efficiency, and is compatible with high-power laser sources, enabling large Rabi frequencies and improved quantum coherence. We benchmark this new approach by globally driving an array of $\sim 300$ neutral $^{87}$Rb atomic qubits trapped in optical tweezers, and obtain Rabi frequencies of 2 MHz with photon-scattering error rates of $< 2 \times 10^{-4}$ per $π$-pulse. This robust approach can be directly integrated with local addressing optics in both neutral atom and trapped ion systems to facilitate high-fidelity single-qubit operations for quantum information processing.
description: 15 pages, 6 figures
Animations of uncertainty growth rates from operational ensemble prediction systems, for the time period 20 November 2020 – 10 March 2021
Creators: name: Rodwell, Mark
name: Wernli, Heini
Publisher: name: ETH Zurich
Year: 2023

description: These animations show so-called Lagrangian growth rates (LGR) of forecast uncertainty based on operational ensemble prediction systems. The first animation shows LGR of potential vorticity on 315 K from the ECMWF ensemble data assimilation background forecasts, and the second animation shows LGR of geopotential height at 250 hPa from four TIGGE ensemble systems (ECMWF, JMA, NCEP and UKMO). Animations show hourly fields over the North Atlantic region for the period 20 November 2020 – 10 March 2021.
The dorsal column nuclei scales mechanical allodynia during neuropathic pain
Creators: name: Upadhyay, Aman A.
Publisher: name: No Publisher Supplied
Year: 2024

description: Our ability to sense touch is vital for the navigation of our sensory environment. However, pathological conditions such as neuropathic pain can cause increased sensitivity to innocuous stimuli, and even allows for light, innocuous stimuli to elicit painful responses, known as mechanical allodynia. In normal conditions, a key pathway for the transmission of innocuous tactile information is the dorsal column nuclei (DCN), which are responsible for conveying peripheral low-threshold stimuli to the brain. Although other key regions of the central nervous system have been implicated in mediating tactile hypersensitivity and allodynia during neuropathic pain, the DCN have been largely understudied in this context, despite having a role in normal tactile sensation. Here, we identify that the DCN undergoes molecular and functional changes during neuropathic pain which contribute to a hyperactive environment, particularly during tactile stimulation. Based on this, we hypothesized that DCN circuits are hyperactive during neuropathic pain. We performed slice electrophysiology on DCN neurons and found that DCN neurons are not hyperexcitable during neuropathic pain, but have altered inputs from the periphery and spinal cord which may enhance recruitment of DCN neurons during sensory stimulation. Based on these results, we next explored the functional role of the DCN output to the thalamus, which is a key component of tactile sensation, in the context of neuropathic pain. Using chemogenetics for neuronal manipulation, we found that DCN neurons projecting to the thalamus are important for maintaining touch sensitivity, but do not affect noxious mechanical or thermal sensitivity. Lastly, we propose that the presence of local inhibitory neurons in the DCN confer the ability to scale up or scale down tactile sensitivity. Our results suggest that chemogenetic or optogenetic manipulation of DCN inhibition is able to bidirectionally scale tactile sensitivity: reduction of DCN inhibition artificially generates phenotypes of neuropathic pain, while suppression of DCN circuits during neuropathic pain is able to reduce tactile hypersensitivity, suggesting an underexplored area of interest for studying mechanisms and treatments of mechanical allodynia. Together, this data suggests that in addition to established mechanisms of mechanical allodynia, the DCN likely contributes in part to altered tactile signaling during neuropathic pain, with local inhibition as a key modulator of tactile sensitivity.
On type 0 string theory in solvable RR backgrounds
Creators: name: Skrzypek, Torben
name: Tseytlin, Arkady A.
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: Motivated by a possibility of solving non-supersymmetric type 0 string theory in $AdS_5 \times S^5$ background using integrability, we revisit the construction of type 0 string spectrum in some solvable examples of backgrounds with RR fluxes that are common to type IIB and type 0B theories. The presence of RR fluxes requires the use of a Green-Schwarz description for type 0 string theory. Like in flat space, the spectrum of type 0 theory can be derived from the type II theory spectrum by a $(-1)^F$ orbifolding, i.e. combining the untwisted sector where GS fermions are periodic with the twisted sector where GS fermions are antiperiodic (and projecting out all spacetime fermionic states). This construction of the type 0 spectrum may also be implemented using a Melvin background that allows to continuously interpolate between the type II and type 0 theories. As an illustration, we discuss the type 0B spectrum in the pp-wave background which is the Penrose limit of $AdS_5 \times S^5$ with RR 5-form flux and also in the pp-wave background which is the Penrose limit of $AdS_3 \times S^3 \times T^4$ supported by mixed RR and NSNS 3-form fluxes. We show that increasing the strength of the RR flux increases the value of the effective normal ordering constant (which determines the mass of the type 0 tachyon) and thus effectively decreases the momentum-space domain of instability of the ground state. We also comment on the semiclassical sector of states of type 0B theory in $AdS_5 \times S^5$.
description: 28 pages, 3 figures; v3: minor comments added
Frame-Capture-Based CSI Recomposition Pertaining to Firmware-Agnostic WiFi Sensing
Creators: name: Hanahara, Ryosuke
name: Itahara, Sohei
name: Yamashita, Kota
name: Koda, Yusuke
name: Taya, Akihito
name: Nishio, Takayuki
name: Yamamoto, Koji
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (cs.LG)
subject: Signal Processing (eess.SP)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: With regard to the implementation of WiFi sensing agnostic according to the availability of channel state information (CSI), we investigate the possibility of estimating a CSI matrix based on its compressed version, which is known as beamforming feedback matrix (BFM). Being different from the CSI matrix that is processed and discarded in physical layer components, the BFM can be captured using a medium-access-layer frame-capturing technique because this is exchanged among an access point (AP) and stations (STAs) over the air. This indicates that WiFi sensing that leverages the BFM matrix is more practical to implement using the pre-installed APs. However, the ability of BFM-based sensing has been evaluated in a few tasks, and more general insights into its performance should be provided. To fill this gap, we propose a CSI estimation method based on BFM, approximating the estimation function with a machine learning model. In addition, to improve the estimation accuracy, we leverage the inter-subcarrier dependency using the BFMs at multiple subcarriers in orthogonal frequency division multiplexing transmissions. Our simulation evaluation reveals that the estimated CSI matches the ground-truth amplitude. Moreover, compared to CSI estimation at each individual subcarrier, the effect of the BFMs at multiple subcarriers on the CSI estimation accuracy is validated.
Exploring Diagram and Video-Based OOP Exercises to Counter LLM Over-Reliance - Vision Experiments
Creators: name: Cipriano, Bruno Pereira
name: Alves, Pedro
name: Denny, Paul
Publisher: name: Zenodo
Year: 2024

description: The file contains a set of experiments performed with GPT-4 and Bard in order to determine how capable they are of solving digram-based Object-Oriented Programming exercises.

These experiments were published in a paper accepted into the EC-TEL 2024 conference.
Surrogate models for quantum spin systems based on reduced order modeling
Creators: name: Herbst, Michael F.
name: Wessel, Stefan
name: Rizzi, Matteo
name: Stamm, Benjamin
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: We present a methodology to investigate phase-diagrams of quantum models based on the principle of the reduced basis method (RBM). The RBM is built from a few ground-state snapshots, i.e., lowest eigenvectors of the full system Hamiltonian computed at well-chosen points in the parameter space of interest. We put forward a greedy-strategy to assemble such small-dimensional basis, i.e., to select where to spend the numerical effort needed for the snapshots. Once the RBM is assembled, physical observables required for mapping out the phase-diagram (e.g., structure factors) can be computed for any parameter value with a modest computational complexity, considerably lower than the one associated to the underlying Hilbert space dimension. We benchmark the method in two test cases, a chain of excited Rydberg atoms and a geometrically frustrated antiferromagnetic two-dimensional lattice model, and illustrate the accuracy of the approach. In particular, we find that the ground-manifold can be approximated to sufficient accuracy with a moderate number of basis functions, which increases very mildly when the number of microscopic constituents grows - in stark contrast to the exponential growth of the Hilbert space needed to describe each of the few snapshots. A combination of the presented RBM approach with other numerical techniques circumventing even the latter big cost, e.g., Tensor Network methods, is a tantalising outlook of this work.
The strong couplings of massive Yang-Mills theory
Creators: name: Hell, Anamaria
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: We study the massive Yang-Mills theory in which the mass term is added by hand. The standard perturbative approach suggests that the massless limit of this theory is not smooth. We confirm that this issue is related to the existence of additional degrees of freedom, which are absent in the massless theory. Nevertheless, we show that the longitudinal modes become strongly coupled at the Vainshtein scale, which coincides with the scale of the unitarity violation. Beyond this scale, they decouple from the remaining degrees of freedom, and the massless theory is restored up to small corrections. From here, it follows that the apparent discontinuity in the massless limit is only an artefact of the perturbation theory. The massless limit of massive Yang-Mills theory is smooth, as originally proposed by A. I. Vainshtein and I. B. Khriplovich.
description: 23 pages
Efficient computations of continuous action densities of states for lattice models
Creators: name: Lucini, Biagio
name: Francesconi, Olmo
name: Holzmann, Markus
name: Lancaster, David
name: Rago, Antonio
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Lattice (hep-lat)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: The Logarithmic Linear Relaxation (LLR) algorithm is an efficient method for computing densities of states for systems with a continuous spectrum. A key feature of this method is exponential error reduction, which allows us to evaluate the density of states of a system over hundreds of thousands of orders of magnitude with a fixed level of relative accuracy. As a consequence of exponential error reduction, the LLR method provides a robust alternative to traditional Monte Carlo calculations in cases in which states suppressed by the Boltzmann weight play nevertheless a relevant role, e.g., as transition regions between dominant configuration sets. After reviewing the algorithm, we will show an application in U(1) Lattice Gauge Theory that has enabled us to obtain the most accurate estimate of the critical coupling with modest computational resources, defeating exponential tunneling times between metastable vacua. As a further showcase, we will then present an application of the LLR method to the decorrelation of the topological charge in SU(3) Lattice Gauge Theory near the continuum limit. Finally, we will review in general applications of the LLR algorithm to systems affected by a strong sign problem and discuss the case of the Bose gas at finite chemical potential.
description: 6 pages, 3 figures. Talk presented by B. Lucini at the XXXII IUPAP Conference on Computational Physics 21, Coventry, UK, 1-5 August 2021
An accurate, robust, and efficient finite element framework for anisotropic, nearly and fully incompressible elasticity
Creators: name: Karabelas, Elias
name: Gsell, Matthias A. F.
name: Haase, Gundolf
name: Plank, Gernot
name: Augustin, Christoph M.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Numerical Analysis (math.NA)
subject: Applied Physics (physics.app-ph)
subject: FOS: Mathematics
subject: FOS: Physical sciences

description: Fiber-reinforced soft biological tissues are typically modeled as hyperelastic, anisotropic, and nearly incompressible materials. To enforce incompressibility a multiplicative split of the deformation gradient into a volumetric and an isochoric part is a very common approach. However, due to the high stiffness of anisotropic materials in the preferred directions, the finite element analysis of such problems often suffers from severe locking effects and numerical instabilities. In this paper, we present novel methods to overcome locking phenomena for anisotropic materials using stabilized P1-P1 elements. We introduce different stabilization techniques and demonstrate the high robustness and computational efficiency of the chosen methods. In several benchmark problems we compare the approach to standard linear elements and show the accuracy and versatility of the methods to simulate anisotropic, nearly and fully incompressible materials. We are convinced that this numerical framework offers the possibility to accelerate accurate simulations of biological tissues, enabling patient-specfic parameterization studies, which require numerous forward simulations.
description: This research has received funding from the European Union's Horizon 2020 research and innovation programme under the ERA-NET co-fund action No. 680969 (ERA-CVD SICVALVES) funded by the Austrian Science Fund (FWF), Grant I 4652-B
An evaluation of multiplex bead-based analysis of cytokines and soluble proteins in archived lithium heparin plasma, EDTA plasma and serum samples
Creators: name: Brøndum, Line
name: Sørensen, Brita Singers
name: Eriksen, Jesper Grau
name: Mortensen, Lise Saksø
name: Lønbro, Simon
name: Overgaard, Jens
name: Alsner, Jan
Publisher: name: Taylor & Francis
Year: 2016
Subjects: subject: Biophysics
subject: Biochemistry
subject: 29999 Physical Sciences not elsewhere classified
subject: FOS: Physical sciences
subject: Medicine
subject: Cell Biology
subject: Physiology
subject: FOS: Biological sciences
subject: Ecology
subject: Immunology
subject: FOS: Clinical medicine
subject: 111714 Mental Health
subject: FOS: Health sciences

description: Objective: To assess the usability of archived plasma and serum by multiplex (Luminex) analysis of circulating proteins (analytes) by evaluating the day to day variation, the effect of several freeze-thaw cycles, and the influence of the media and choice of anticoagulant. Methods: Nineteen analytes in plasma and serum from 86 head and neck cancer patients and 33 controls were evaluated: EGFR, leptin, OPN, VEGFR-1, VEGFR-2, IL-2, IL-13, PDGF-bb, TNF, PAI-1, SDF-1a, IL-4, IL-6, IL-8, eotaxin, G-CSF, VEGF, GRO-a, and HGF. Results: The correlation between measurements of the same samples analyzed on different dates was reasonable. However, samples run on different dates could exhibit different absolute values. The 75th percentile of the fold differences for samples run on different dates was 2.2. No significant difference was found between one and four freeze-thaw cycles (except for HGF), and the correlation was high. We found significant differences in mean concentrations of the majority of analytes in different media and with different anticoagulants. Only the following analytes did not show difference in mean concentrations: EDTA plasma vs. serum: leptin and VEGFR-2, LH plasma vs. serum: IL-2, IL-13, and VEGF, LH plasma levels vs. EDTA plasma: IL-2 and IL-4. Conclusion: Stored serum, LH plasma, and EDTA plasma from clinical trials can be used for analysis of circulating cytokines and proteins. Variations in measurements occur, but are within reasonable ranges. The optimal type of media depends on the analytes, as different analytes have low number of measurements below the lower limit of quantification and higher dynamic ranges in different media.
Outdoor yoga pose 3
Creators: name: Marsh, Andrew
Publisher: name: figshare
Year: 2016
Subjects: subject: 111002 Clinical Nursing: Primary (Preventative)
subject: FOS: Health sciences
subject: 110499 Complementary and Alternative Medicine not elsewhere classified
subject: FOS: Clinical medicine
subject: 110602 Exercise Physiology
subject: Health Care
subject: 111712 Health Promotion
subject: 110699 Human Movement and Sports Science not elsewhere classified

description: Yoga outdoors. Photo for OM Yoga Magazine.
Simulation of absorption spectra of molecular aggregates: a Hierarchy of Stochastic Pure States approach
Creators: name: Chen, Lipeng
name: Bennett, Doran I. G.
name: Eisfeld, Alexander
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: The simulation of spectroscopic observables for molecular aggregates with strong and structured coupling of electronic excitation to vibrational degrees of freedom is an important but challenging task. The hierarchy of pure states (HOPS) provides a formally exact solution based on local, stochastic trajectories. Exploiting the localization of HOPS for the simulation of absorption spectra in large aggregares requires a formulation in terms of normalized trajectories. Here we provide a normalized dyadic equation where the ket- and bra-states are propagated in different electronic Hilbert spaces. This work opens the door to apply adaptive HOPS methods for the simulation of absorption spectra and also to a formulation for non-linear spectroscopy that is perturbative with respect to interactions with the electric field.
Earth as an Exoplanet: Investigating Earth's Time Variable Thermal Emission and its Atmospheric Seasonality using Disk-Integrated Satellite Observations
Creators: name: Mettler, Jean-Noël
name: Quanz, Sascha Patrick
name: Helled, Ravit
Publisher: name: ETH Zurich
Year: 2022

description: American Astronomical Society Meeting Abstracts, 54 (5)
description: AASTCS 9: Exoplanets IV Abstracts
The universal algebra of the electromagnetic field III. Static charges and emergence of gauge fields
Creators: name: Buchholz, Detlev
name: Ciolli, Fabio
name: Ruzzi, Giuseppe
name: Vasselli, Ezio
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mathematical Physics (math-ph)
subject: High Energy Physics - Theory (hep-th)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: A universal C*-algebra of gauge invariant operators is presented, describing the electromagnetic field as well as operations creating pairs of static electric charges having opposite signs. Making use of Gauss' law, it is shown that the string-localized operators, which necessarily connect the charges, induce outer automorphisms of the algebra of the electromagnetic field. Thus they carry additional degrees of freedom which cannot be created by the field. It reveals the fact that gauge invariant operators encode information about the presence of non-observable gauge fields underlying the theory. Using the Gupta-Bleuler formalism, concrete implementations of the outer automorphisms by exponential functions of the gauge fields are presented. These fields also appear in unitary operators inducing the time translations in the resulting representations of the universal algebra.
description: 14 pages, no figures