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Single-molecule junctions - nanoscale systems where a molecule is connected to metallic electrodes - offer a unique platform for studying charge, spin and energy transport in non-equilibrium many-body quantum systems, with few parallels in other areas of condensed matter physics. Over the past decades, these systems have revealed a wide range of remarkable quantum phenomena, including quantum interference, non-equilibrium spin-crossover, diode-like behavior, or chiral-induced spin selectivity, among many others. To develop a detailed understanding, it turned out essential to have available ab initio-based tools for accurately describing quantum transport in such systems. They need to be capable of capturing the intricate electronic structure of molecules, sometimes in the presence of electron-electron or electron-phonon interactions, in out-of-equilibrium environments. Such tools are indispensable also for experimentally observed phenomena explained in terms of parametrized tight-binding models for the quantum transport problem. While FHI-aims also offers specialized transport routines, e.g. for chemically functionalized nanotubes or nanotube networks, our focus in this section is on the AITRANSS package designed for simulations of single-molecule transport. AITRANSS is an independent post-processing tool that combined with FHI-aims enables the calculation of electronic transport properties, as well as atom-projected density of states, spin properties and the simulation of scanning tunneling microscope images in molecular junctions. Pilot versions of the code extend some of these capabilities to non-linear transport in the applied bias, with plans to include these features in future releases of the package., Comment: 7 pages, 2 figures. This is a contribution/chapter to the upcoming "Roadmap on Advancements of the FHI-aims Software Package"

Osteochondrodysplasia, affecting 2-3% of newborns globally, is a group of bone and cartilage disorders that often result in head malformations, contributing to childhood morbidity and reduced quality of life. Current research on this disease using mouse models faces challenges since it involves accurately segmenting the developing cartilage in 3D micro-CT images of embryonic mice. Tackling this segmentation task with deep learning (DL) methods is laborious due to the big burden of manual image annotation, expensive due to the high acquisition costs of 3D micro-CT images, and difficult due to embryonic cartilage's complex and rapidly changing shapes. While DL approaches have been proposed to automate cartilage segmentation, most such models have limited accuracy and generalizability, especially across data from different embryonic age groups. To address these limitations, we propose novel DL methods that can be adopted by any DL architectures -- including CNNs, Transformers, or hybrid models -- which effectively leverage age and spatial information to enhance model performance. Specifically, we propose two new mechanisms, one conditioned on discrete age categories and the other on continuous image crop locations, to enable an accurate representation of cartilage shape changes across ages and local shape details throughout the cranial region. Extensive experiments on multi-age cartilage segmentation datasets show significant and consistent performance improvements when integrating our conditional modules into popular DL segmentation architectures. On average, we achieve a 1.7% Dice score increase with minimal computational overhead and a 7.5% improvement on unseen data. These results highlight the potential of our approach for developing robust, universal models capable of handling diverse datasets with limited annotated data, a key challenge in DL-based medical image analysis.

Accurate prediction of electronic and optical excitations in van der Waals (vdW) materials is a long-standing challenge for density functional theory. The recently proposed Wannier-localized optimally-tuned screened range-separated hybrid (WOT-SRSH) functional has proven successful in non-empirical determination of electronic band gaps and optical absorption spectra for various covalent and ionic crystals. However, for vdW materials the tuning of the material- and structure-dependent functional parameters has, until now, only been attained semi-empirically. Here, we present a non-empirical WOT-SRSH approach applicable to vdW materials, with the optimal functional parameters transferable between monolayer and bulk. We apply this methodology to prototypical vdW materials: black phosphorus, molybdenum disulfide, and hexagonal boron nitride (in the latter case including zero-point renormalization). We show that the WOT-SRSH approach consistently achieves accuracy levels comparable to experiments and ab initio many-body perturbation theory (MBPT) calculations for band structures and optical absorption spectra, both on its own and as an optimal starting point for MBPT calculations., Comment: 11 pages + 4 figures; Supporting Information (15 pages + 2 figures)

An ultra-compact wearable antenna, for electronic travel aid (ETA) applications, is presented. An AMC-backed twin arrow antenna, operative in the 24.05-24.25 GHz frequency band, has been designed for imaging systems supporting ETA. Artificial Magnetic Conductor (AMC) is combined with the antenna with the aim of reducing the backward radiation to the wearing person while improving its radiation properties and bandwidth, all this without increasing the initial area of the antenna. Prototypes of the AMC-antenna have been fabricated and measured. In order to test its performance for the application, imaging have been conducted by means of synthetic aperture radar (SAR) techniques by placing the antenna in the arm of a user to take advantage of natural body movement. Electromagnetic images have been obtained and the target has been identified, demonstrating the suitability of the AMC-antenna for the ETA system.

The use of electric fields applied across magnetic heterojunctions that lack spatial inversion symmetry has been previously proposed as a non-magnetic mean of controlling localized magnetic moments through spin-orbit torques (SOT). The implementation of this concept at the single-molecule level has remained a challenge, however. Here, we present first-principle calculations of SOT in a single-molecule junction under bias and beyond linear response. Employing a self-consistency scheme invoking density functional theory and non-equilibrium Green's function theory, we compute the current-induced SOT. Responding to this torque, a localized magnetic moment can tilt. Within the linear regime our quantitative estimates for the SOT in single-molecule junctions yield values similar to those known for magnetic interfaces. Our findings contribute to an improved microscopic understanding of SOT in single molecules., Comment: 7 pages + 5 figures; Supporting Information (16 pages + 3 figures)

Plankton recognition provides novel possibilities to study various environmental aspects and an interesting real-world context to develop domain adaptation (DA) methods. Different imaging instruments cause domain shift between datasets hampering the development of general plankton recognition methods. A promising remedy for this is DA allowing to adapt a model trained on one instrument to other instruments. In this paper, we present a new DA dataset called DAPlankton which consists of phytoplankton images obtained with different instruments. Phytoplankton provides a challenging DA problem due to the fine-grained nature of the task and high class imbalance in real-world datasets. DAPlankton consists of two subsets. DAPlankton_LAB contains images of cultured phytoplankton providing a balanced dataset with minimal label uncertainty. DAPlankton_SEA consists of images collected from the Baltic Sea providing challenging real-world data with large intra-class variance and class imbalance. We further present a benchmark comparison of three widely used DA methods.

Simultaneous multithreading processors improve throughput over single-threaded processors thanks to sharing internal core resources among instructions from distinct threads. However, resource sharing introduces inter-thread interference within the core, which has a negative impact on individual application performance and can significantly increase the turnaround time of multi-program workloads. The severity of the interference effects depends on the competing co-runners sharing the core. Thus, it can be mitigated by applying a thread-to-core allocation policy that smartly selects applications to be run in the same core to minimize their interference. This paper presents SYNPA, a simple approach that dynamically allocates threads to cores in an SMT processor based on their run-time dynamic behavior. The approach uses a regression model to select synergistic pairs to mitigate intra-core interference. The main novelty of SYNPA is that it uses just three variables collected from the performance counters available in current ARM processors at the dispatch stage. Experimental results show that SYNPA outperforms the default Linux scheduler by around 36%, on average, in terms of turnaround time in 8-application workloads combining frontend bound and backend bound benchmarks., Comment: 11 pages, 9 figures

Using both time-dependent density functional theory (TDDFT) and the ``single-shot" $GW$ plus Bethe-Salpeter equation ($GW$-BSE) approach, we compute optical band gaps and optical absorption spectra from first principles for eight common binary and ternary closed-shell metal oxides (MgO, Al$_2$O$_3$, CaO, TiO$_2$, Cu$_2$O, ZnO, BaSnO$_3$, and BiVO$_4$), based on the non-empirical Wannier-localized optimally-tuned screened range-separated hybrid functional. Overall, we find excellent agreement between our TDDFT and $GW$-BSE results and experiment, with a mean absolute error less than 0.4 eV, including for Cu$_2$O and ZnO, traditionally considered to be challenging for both methods.

Global change is predicted to induce shifts in anuran acoustic behavior, which can be studied through passive acoustic monitoring (PAM). Understanding changes in calling behavior requires the identification of anuran species, which is challenging due to the particular characteristics of neotropical soundscapes. In this paper, we introduce a large-scale multi-species dataset of anuran amphibians calls recorded by PAM, that comprises 27 hours of expert annotations for 42 different species from two Brazilian biomes. We provide open access to the dataset, including the raw recordings, experimental setup code, and a benchmark with a baseline model of the fine-grained categorization problem. Additionally, we highlight the challenges of the dataset to encourage machine learning researchers to solve the problem of anuran call identification towards conservation policy. All our experiments and resources can be found on our GitHub repository https://github.com/soundclim/anuraset.

The accurate description of electronic properties and optical absorption spectra is a long-standing challenge for density functional theory. Recently, the introduction of screened range-separated hybrid (SRSH) functionals for solid-state materials has allowed for the calculation of fundamental band gaps and optical absorption spectra that are in very good agreement with many-body perturbation theory. However, since solid-state SRSH functionals are typically tuned to reproduce the properties of bulk phases, their transferability to low-dimensional structures, which experience substantially different screening than in the bulk, remains an open question. In this work, we explore the transferability of SRSH functionals to several prototypical van der Waals materials, including transition-metal sulfides and selenides, indium selenide, black phosphorus, and hexagonal boron nitride. Considering the bulk and a monolayer of these materials as limiting cases, we show that the parameters of the SRSH functional can be determined systematically, using only the band-edge quasiparticle energies of these extremal structural phases as fitting targets. The resulting SRSH functionals can describe both electronic bandstructures and optical absorption spectra with accuracy comparable to more demanding ab initio many-body perturbation theory (GW and Bethe-Salpeter equation) approaches. Selected examples also demonstrate that the SRSH parameters, obtained from the bulk and monolayer reference structures, display good accuracy for bandstructures and optical spectra of bilayers, indicating a degree of transferability that is independent of the fitting procedure., Comment: 14 pages + 8 figures; Supporting Information (21 pages + 18 figures)

The impact of exposure to astrophysical ionizing radiation on astronaut health is one of the main concerns in planning crewed missions to Mars. Astronauts will be exposed to energetic charged particles from Galactic and Solar origin for a prolonged period with little protection from a thin spacecraft shield in transit and from the rarefied Martian atmosphere when on the surface. Adverse impacts on astronaut health include, for example, Acute Radiation Syndrome, damage to the nervous system, and increased cancer risk. We rely on medical studies to assess the impact of enhanced radiation dose levels on various physiological systems and the overall health of astronauts. Using a combination of radiation measurements and numerical modeling with the GEANT4 package, we calculate the distribution of radiation dose in various human body organs for various expected scenarios simulated with a model human phantom. We suggest mitigation strategies, such as improved ways of shielding and dietary supplements, and make recommendations for the safety of astronauts in future crewed missions to Mars., Comment: Under Review