Miracle-dz/UniFAR-FTUs huggingface dataset:
The oldest known clones of Salix herbacea growing in the Northern Apennines, Italy are at least 2000 years old.

PREMISE Dominant in many ecosystems around the world, clonal plants can reach considerable ages and sizes. Due to their modular growth patterns, individual clonal plants (genets) can consist of many subunits (ramets). Since single ramets do not reflect the actual age of genets, the ratio between genet size (radius) and longitudinal annual growth rate (LAGR) of living ramets is often used to approximate the age of clonal plants. However, information on how the LAGR changes along ramets and how LAGR variability may affect age estimates of genets is still limited. METHODS We assessed the variability of LAGR based on wood-section position along the ramets and on the duration of the growing season on three genetically distinct genets of Salix herbacea growing in the Northern Apennines (Italy). We compared genet ages estimated by dividing genet radius by the LAGRs of its ramets. RESULTS LAGR increased significantly from the stem apex to the root collar; indicating that ramet growth rate decreased with time. Furthermore, a difference of ca. 2 weeks in the onset of the growing period did not impact LAGR. Considering the high LAGR variability, we estimated that the three genets started to grow between ~2100 and ~7000 years ago, which makes them the oldest known clones of S. herbacea even considering the most conservative age estimate. CONCLUSIONS Our findings indicate that analyzing ramets at the root collar provides an integrative measurement of their overall LAGR, which is crucial for estimating the age of genets.
2-Furoic acid associated with the infection of nematodes by Dactylellina haptotyla and its biocontrol potential on plant root-knot nematodes

ABSTRACT Dactylellina haptotyla is a typical nematode-trapping fungus that has garnered the attention of many scholars for its highly effective lethal potential for nematodes. Secondary metabolites play an important role in D. haptotyla-nematode interactions, but which metabolites perform which function remains unclear. We report the metabolic functions based on high-quality, chromosome-level genome assembly of wild D. haptotyla YMF1.03409. The results indicate that a large variety of secondary metabolites and their biosynthetic genes were significantly upregulated during the nematode-trapping stage. In parallel, we identified that 2-furoic acid was specifically produced during nematode trapping by D. haptotyla YMF1.03409 and isolated it from fermentation production. 2-Furoic acid demonstrated strong nematicidal activity with an LD50 value of 55.05 µg/mL against Meloidogyne incognita at 48 h. Furthermore, the pot experiment showed that the number of galls of tomato root was significantly reduced in the experimental group treated with 2-furoic acid. The considerable increase in the 2-furoic acid content during the infection process and its virulent nematicidal activity revealed an essential synergistic effect during the process of nematode-trapping fungal infection. IMPORTANCE Dactylellina haptotyla have significant application potential in nematode biocontrol. In this study, we determined the chromosome-level genome sequence of D. haptotyla YMF1.03409 by long-read sequencing technology. Comparative genomic analysis identified a series of pathogenesis-related genes and revealed significant gene family contraction events during the evolution of D. haptotyla YMF1.03409. Combining transcriptomic and metabolomic data as well as in vitro activity test results, a compound with important application potential in nematode biocontrol, 2-furoic acid, was identified. Our result expanded the genetic resource of D. haptotyla and identified a previously unreported nematicidal small molecule, which provides new options for the development of plant biocontrol agents. Dactylellina haptotyla have significant application potential in nematode biocontrol. In this study, we determined the chromosome-level genome sequence of D. haptotyla YMF1.03409 by long-read sequencing technology. Comparative genomic analysis identified a series of pathogenesis-related genes and revealed significant gene family contraction events during the evolution of D. haptotyla YMF1.03409. Combining transcriptomic and metabolomic data as well as in vitro activity test results, a compound with important application potential in nematode biocontrol, 2-furoic acid, was identified. Our result expanded the genetic resource of D. haptotyla and identified a previously unreported nematicidal small molecule, which provides new options for the development of plant biocontrol agents.
Movement Artifact Suppression in Wearable Low-Density and Dry EEG Recordings Using Active Electrodes and Artifact Subspace Reconstruction

Wearable low-density dry electroencephalogram (EEG) headsets facilitate multidisciplinary applications of brain-activity decoding and brain-triggered interaction for healthy people in real-world scenarios. However, movement artifacts pose a great challenge to their validity in users with naturalistic behaviors (i.e., without highly controlled settings in a laboratory). High-precision, high-density EEG instruments commonly embed an active electrode infrastructure and/or incorporate an auxiliary artifact subspace reconstruction (ASR) pipeline to handle movement artifact interferences. Existing endeavors motivate this study to explore the efficacy of both hardware and software solutions in low-density and dry EEG recordings against non-tethered settings, which are rarely found in the literature. Therefore, this study employed a LEGO-like electrode-holder assembly grid to coordinate three 3-channel system designs (with passive/active dry vs. passive wet electrodes). It also conducted a simultaneous EEG recording while performing an oddball task during treadmill walking, with speeds of 1 and 2 KPH. The quantitative metrics of pre-stimulus noise, signal-to-noise ratio, and inter-subject correlation from the collected event-related potentials of 18 subjects were assessed. Results indicate that while treating a passive-wet system as benchmark, only the active-electrode design more or less rectified movement artifacts for dry electrodes, whereas the ASR pipeline was substantially compromised by limited electrodes. These findings suggest that a lightweight, minimally obtrusive dry EEG headset should at least equip an active-electrode infrastructure to withstand realistic movement artifacts for potentially sustaining its validity and applicability in real-world scenarios.
Analytical derivation of the Budyko curve based on rainfall characteristics and a simple evaporation model

The Budyko curve is often used to estimate the actual evaporation as a function of the aridity index in a catchment. Different empirical equations exist to describe this relationship; however, these equations have very limited physical background. The model concept presented in this paper is physically based and uses only measurable parameters. It makes use of two types of evaporation: interception and transpiration. It assumes that interception can be modeled as a threshold process on a daily time scale. If multiplied with the rainfall distribution function, integrated, and multiplied with the expected number of rain days per month, the monthly interception is obtained. In a similar way, the monthly interception can be upscaled to annual interception. Analogous to the interception process, transpiration can be modeled as a threshold process at a monthly time scale and can be upscaled by integration and multiplication with the expected number of rain months. The expected rain days per month are modeled in two ways: as a fixed proportion of the monthly rainfall and as a power function based on Markov properties of rainfall. The latter is solved numerically. It appears that on an annual basis the analytical model does not differ much from the numerical solution. Hence, the analytical model is used and applied on 10 locations in different climates. This paper shows that the empirical Budyko curve can be constructed on the basis of measurable parameters representing evaporation threshold values and the expected number of rain days and rain months and, in addition, a monthly moisture carryover amount for semiarid zones.
Heat sources and trigger mechanisms of exhumation of HP granulites in Variscan orogenic root

The structure of the Moldanubian domain is marked by felsic granulites of Ordovician protolith age forming the cores of domes that are separated from mid‐crustal Neoproterozoic and Palaeozoic metasedimentary rocks that occur in synclines by a late Ordovician to Silurian metabasic unit. Reflection and refraction seismic sections combined with gravity inversion modelling suggest the presence of a low density layer at the bottom of the crust (interpreted as felsic granulite) overlain by a denser layer (interpreted as amphibolite) with layers of intermediate density at the top (interpreted as metasedimentary rocks). It is proposed that the granulite domes surrounded by middle crustal rocks reflect transposed horizontal layering originally similar to that preserved in the deep crust and imaged by the geophysical surveys. This geological and geophysical structure is considered to be a result of Viséan gravity redistribution initiated by radioactive heating of felsic crust tectonically emplaced at the bottom of a Palaeozoic orogenic root. The radioactive layer with heat production of 4 μW m−3 corresponds geochemically and isotopically to Ordovician felsic metaigneous rocks of the Saxothuringian domain that have been emplaced at Moho depth under thickened crust during late Devonian–early Carboniferous continental subduction. Part of the continental crust continued to be subducted and produced fluids/low‐volume melts which directly contaminated and enriched the local lithospheric mantle by lithophile elements, most notably Cs, Rb, Li, Pb, U, Th and K. Thermal incubation of 10–15 Myr was sufficient to heat and convert the underplated felsic layer into granulites via dehydration melting and melt segregation. The process of melt loss was responsible for the removal of radioactive elements and for switching off the heat at the beginning of the exhumation process. At the same time, the metasomatized underlying mantle was heated producing characteristic ultrapotassic magmas. Gravitational instability was then induced by the density contrast between the light granulites and the overlaying denser mafic lower crustal layer and a viscosity drop related to thermal weakening and partial melting of the latter.
Clinical implications of recent studies using mtoR inhibitors to treat advanced hormone receptor-positive breast cancer

: Breast cancer is a leading cause of cancer-related death worldwide. Approximately 75% of breast cancer is hormone receptor-positive (HR + ) and is managed with endocrine therapies. However, relapse or disease progression caused by primary or acquired endocrine resistance is frequent. Phosphatidylinositol-3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR)-mediated signaling is one of the molecular mechanisms leading to endocrine resistance. mTOR inhibitors that target the PI3K/Akt/mTOR pathway are the first of the targeted therapies to be evaluated in clinical trials to overcome endocrine resistance. Although the clinical trial with temsirolimus, an mTOR inhibitor, did not show any benefit when compared with endocrine therapy alone, a Phase II clinical trial with sirolimus has been promising. Recently, everolimus was approved in combination with exemestane by the US Food and Drug Administration for treating postmenopausal women with advanced HR + breast cancer, based on the results of a Phase III trial. Therefore, everolimus represents the first and only targeted agent approved for combating endocrine resistance.
Spinal constructions for continuous type-space branching processes with interactions

We consider branching processes describing structured, interacting populations in continuous time. Dynamics of each individual's characteristics and branching properties can be influenced by the entire population. We propose a spinal construction, and establish a Girsanov-type result. By combining this result with the spinal decomposition, we derive a modified continuous-time version of the Kesten-Stigum theorem that incorporates interactions. Additionally, we propose an alternative simulation approach for stochastic size-dependent populations using appropriate spine constructions.
180$^\circ$-twisted bilayer ReSe$_2$ as an artificial noncentrosymmetric semiconductor

We have fabricated a 180$^\circ$-twisted bilayer ReSe$_2$ by stacking two centrosymmetric monolayer ReSe$_2$ flakes in opposite directions, which is expected to lose spatial inversion symmetry. By the second harmonic generation and angle-resolved photoemission spectroscopy, we successfully observed spatial inversion symmetry breaking and emergent band dispersions. The band calculation shows the finite lifting of spin degeneracy (~50 meV) distinct from natural monolayer and bilayer ReSe$_2$. Our results demonstrate that the spin-momentum locked state, which leads to spintronic functions and Berry-curvature-related phenomena, can be realized even with the stacking of centrosymmetric monolayers.
Development of a Whole-Body Work Imitation Learning System by a Biped and Bi-Armed Humanoid

Imitation learning has been actively studied in recent years. In particular, skill acquisition by a robot with a fixed body, whose root link position and posture and camera angle of view do not change, has been realized in many cases. On the other hand, imitation of the behavior of robots with floating links, such as humanoid robots, is still a difficult task. In this study, we develop an imitation learning system using a biped robot with a floating link. There are two main problems in developing such a system. The first is a teleoperation device for humanoids, and the second is a control system that can withstand heavy workloads and long-term data collection. For the first point, we use the whole body control device TABLIS. It can control not only the arms but also the legs and can perform bilateral control with the robot. By connecting this TABLIS with the high-power humanoid robot JAXON, we construct a control system for imi-tation learning. For the second point, we will build a system that can collect long-term data based on posture optimization, and can simultaneously move the robot's limbs. We combine high-cycle posture generation with posture optimization methods, including whole-body joint torque minimization and contact force optimization. We designed an integrated system with the above two features to achieve various tasks through imitation learning. Finally, we demonstrate the effectiveness of this system by experiments of manipulating flexible fabrics such that not only the hands but also the head and waist move simultaneously, manipulating objects using legs characteristic of humanoids, and lifting heavy objects that require large forces.
A Novel LC-MS/MS Method for Therapeutic Drug Monitoring of Baricitinib in Plasma of Pediatric Patients

Background: Janus kinase inhibitors are antirheumatic immunosuppressive drugs that target intracellular Janus kinases (JAKs). Baricitinib is a selective and reversible orally administered JAK1/JAK2 inhibitor approved for treating rheumatoid arthritis, atopic dermatitis, and alopecia areata in adult patients. Expanded access to baricitinib has been approved for treating pediatric patients affected by rare Mendelian autoinflammatory diseases with type I interferon-mediated damage. Knowledge of the pharmacokinetic properties and target plasma levels of baricitinib in pediatric patients is limited. In this study, a novel LC-MS/MS method for measuring baricitinib in plasma, validated according to the ICH M10 guidelines, is presented. Methods: Sample preparation was performed by adding 10 µL of IS working solution (150 ng/mL) and 200 µL of MeOH to each plasma sample. Chromatographic separation was conducted using a Thermo Scientific Accucore Polar Premium column (50 mm × 2.1 mm, i.d. 2.6 m). This method was applied to 7 real anonymous plasma samples obtained from pediatric patients treated with baricitinib at IRCCS Istituto Giannina Gaslini (Genoa, Italy). Patients of both sexes had a median age of 14 years (range, 10–17 years). Results: The LC-MS/MS method resulted linear over wide concentration ranges (1.024–100 ng/mL) and was accurate and reproducible in the absence of matrix effects, allowing for robust, specific, and rapid quantification of baricitinib from a low amount of plasma (50 µL). The plasma concentration of baricitinib in the samples of the patients, expressed as mean ± SD, was 11.25 ± 10.86 ng/mL. Conclusions: This novel LC-MS/MS method is suitable for the therapeutic drug monitoring of baricitinib and can help guide therapy optimization in pediatric patients.
K-Ar dating of lunar fines: Apollo 12, Apollo 14, and Luna 16

K-Ar ages were determined on a 6-in. double-focus mass spectrometer in fines of less than 1 mm from Apollo 14 and 16, and Luna 16 lunar soil samples. Age estimates of about 2.8 AE and about 4.0 AE are suggested for the two low-K components whose presence in the samples must be assumed to accommodate the age data. An average value of 0.1849 plus or minus 0.0008 was obtained for the Ar-18/Ar-36 ratio in the solar wind from ordinate intercept correlations for the Apollo 14 and Luna 16 samples. Cosmic ray exposure ages were close to 440 m.y. for both Apollo 14 samples and close to 840 m.y. for both Luna 16 samples.
Nonlinear response functions and disorder: the case of photogalvanic effect

We investigate the impact of impurity scattering on a generalized version of the circular photogalvanic effect (CPGE) in Weyl semimetals where the frequency detuning between the two orthogonally polarized beams is non-zero. Considering a minimal model with two Weyl nodes at different energies, we employ the self-consistent Born approximation (SCBA) to unravel the dependence of the associated complex correlation function on the strength of intra- and internode scattering, frequency detuning and energy difference between the two Weyl nodes. In the case of intranode scattering only, the optical response acquires Drude-like features, which we elucidate further by introducing an effective scattering strength. The Drude-like theory can even describe the response in presence of strong internode scattering if the latter has a fixed proportionality factor to the intranode scattering. By properly adjusting the frequency detuning, we also find the imaginary part of the response function to be reminiscent of a"quantized CPGE-like"form, although the real part of the response function is in general finite, and the total optical response oscillates with time due to the finite frequency offset. We finally conclude with an outlook on possible experimental consequences.
ObVi-SLAM: Long-Term Object-Visual SLAM

Robots responsible for tasks over long time scales must be able to localize consistently and scalably amid geometric, viewpoint, and appearance changes. Existing visual SLAM approaches rely on low-level feature descriptors that are not robust to such environmental changes and result in large map sizes that scale poorly over long-term deployments. In contrast, object detections are robust to environmental variations and lead to more compact representations, but most object-based SLAM systems target short-term indoor deployments with close objects. In this letter, we introduce ObVi-SLAM to overcome these challenges by leveraging the best of both approaches. ObVi-SLAM uses low-level visual features for high-quality short-term visual odometry; and to ensure global, long-term consistency, ObVi-SLAM builds an uncertainty-aware long-term map of persistent objects and updates it after every deployment. By evaluating ObVi-SLAM on data from 16 deployment sessions spanning different weather and lighting conditions, we empirically show that ObVi-SLAM generates accurate localization estimates consistent over long time scales in spite of varying appearance conditions.
Semantics-Driven Cloud-Edge Collaborative Inference A Case Study of License Plate Detection

With the proliferation of video data in smart city applications like intelligent transportation, efficient video analytics has become crucial but also challenging. This paper proposes a semantics-driven cloud-edge collaborative approach for accelerating video inference, using license plate recognition as a case study. The method separates semantics extraction and recognition, allowing edge servers to only extract visual semantics (license plate patches) from video frames and offload computation-intensive recognition to the cloud or neighboring edges based on load. This segmented processing coupled with a load-aware work distribution strategy aims to reduce end-to-end latency and improve throughput. Experiments demonstrate significant improvements in end-to-end inference speed (up to 5x faster), throughput (up to 9 FPS), and reduced traffic volumes (50% less) compared to cloud-only or edge-only processing, validating the efficiency of the proposed approach. The cloud-edge collaborative framework with semantics-driven work partitioning provides a promising solution for scaling video analytics in smart cities.
SAF-Net: Self-Attention Fusion Network for Myocardial Infarction Detection Using Multi-View Echocardiography

Myocardial infarction (MI) is a severe case of coronary artery disease (CAD) and ultimately, its detection is sub-stantial to prevent progressive damage to the myocardium. In this study, we propose a novel view-fusion model named self-attention fusion network (SAF-Net) to detect MI from multi-view echocardiography recordings. The proposed framework utilizes apical 2-chamber (A2C) and apical 4-chamber (A4C) view echocardiography recordings for classification. Three reference frames are extracted from each recording of both views and deployed pre-trained deep networks to extract highly representative features. The SAF-Net model utilizes a self-attention mechanism to learn dependencies in extracted feature vectors. The proposed model is computationally efficient thanks to its compact architecture having three main parts: a feature embedding to reduce dimensionality, self-attention for view-pooling, and dense layers for the classification. Experimental evaluation is performed using the HMC-QU-TAU11The benchmark HMC-QU-TAU dataset is publicly shared at the repository https://www.kaggle. com/aysendegerli/hmcqu-dataset. dataset which consists of 160 patients with A2C and A4C view echocardiography recordings. The proposed SAF-Net model achieves a high-performance level with 88.26% precision, 77.64% sensitivity, and 78.13% accuracy. The results demonstrate that SAF-Net model achieves the most accurate MI detection over multi-view echocardiography recordings.
Robust Internal Representations for Domain Generalization

This paper, which is part of the New Faculty Highlights Invited Speaker Program of AAAI'23, serves as a comprehensive survey of my research in transfer learning by utilizing embedding spaces. The work reviewed in this paper specifically revolves around the inherent challenges associated with continual learning and limited availability of labeled data. By providing an overview of my past and ongoing contributions, this paper aims to present a holistic understanding of my research, paving the way for future explorations and advancements in the field. My research delves into the various settings of transfer learning, including, few‐shot learning, zero‐shot learning, continual learning, domain adaptation, and distributed learning. I hope this survey provides a forward‐looking perspective for researchers who would like to focus on similar research directions.