Miracle-dz/UniFAR-FTUs huggingface dataset:
Enzootic calcinosis in Toggenburg goats in New Zealand

ABSTRACT Case history Necropsies on Toggenburg goats culled from a small farm in the Manawatū district of New Zealand, performed at Massey University (Palmerston North, NZ) over a period of 29 years (1991–2019), revealed soft tissue mineralisation, particularly of cardiovascular tissues. The farm spans 10 acres and runs between 15 and 30 Toggenburg goats. The goats are predominantly on pasture comprising a variety of types. Pathological findings Necropsies were performed on all adult goats (n = 45) that died or were euthanised. Histopathology was performed on 42 goats (93%), of which 33 (73%) included sufficient tissues diagnostically relevant to soft tissue mineralisation. The most significant gross findings were in various arteries, with the aorta most commonly affected, followed by the heart and lungs. The aortic intima showed prominent, multifocal to coalescing, raised, wrinkled, white plaques. Microscopically there were multiphasic lesions of mineralisation, chondroid, and osseous metaplasia in the elastic arteries, aorta, heart and lungs. A lumbar vertebra from one goat had prominent, basophilic, fibrillar, tangled matrix lining Haversian canals and lamellae. Laboratory findings Blood samples were collected from 15 adult goats in the affected herd and from 10 adult Toggenburg goats from an unaffected herd. Samples were collected by jugular venipuncture at 2-month intervals for 12 months (April 2018–March 2019). Concentrations of calcium, phosphorus, 25-hydroxyvitamin D2 and D3 (25OHD2, 25OHD3) in serum were analysed. The concentration of total 25OHD in serum was 34.2 (95% CI = 18.9–49.4) nmol/L (p < 0.001) higher in goats from the affected herd than in goats from the unaffected herd. Serum 25OHD2 concentration was 46.2 (95% CI = 39.2–53.2) nmol/L higher (p < 0.001) in goats from the affected herd compared to the unaffected herd. Serum Ca concentrations in affected goats were 0.101 (95% CI = 0.005–0.196) mmol/L higher (p = 0.039) than unaffected goats, but remained within the reference range. There was no evidence of a difference in serum 25OHD3 and P concentration between the herds. Vegetation survey All paddocks on the property were surveyed every 2 months along evenly spaced line transects, and then further traversed perpendicularly to form a grid. No known calcinogenic species were identified. Known plant sources of vitamin D identified on the farm included mushrooms (species not defined), Dactylis glomerata, lichen, pine pollen, and algae. Diagnosis Soft tissue mineralisation and enzootic calcinosis. Clinical relevance Veterinarians are alerted to the possibility of either enzootic calcinosis in goats and the potential occurrence of calcinogenic plants in New Zealand; or chronic vitamin D toxicosis of non-plant origin.
Case Series of Soft Tissue Sarcoma Patients with Brain Metastasis with Implications from Genomic and Transcriptomic Analysis.

Purpose Brain metastasis rarely occurs in soft tissue sarcoma (STS). Here, we present five cases of STS with brain metastases with genetic profiles. Materials and Methods We included five patients from Seoul National University Hospital who were diagnosed with STS with metastasis to the brain. Tissue from the brain metastasis along with that from the primary site or other metastases were used for DNA and RNA sequencing to identify genetic profiles. Gene expression profiles were compared with sarcoma samples from The Cancer Genome Atlas (TCGA). Results The overall survival after diagnosis of brain metastasis ranged from 2.2 to 34.3 months. Comparison of mutational profiles between brain metastases and matched primary or other metastatic samples showed similar profiles. In two patients, copy number variation profiles between brain metastasis and other tumors showed several differences including MYCL, JUN, MYC and DDR2 amplification. Gene ontology analysis showed that the group of genes significantly highly expressed in the brain metastasis samples was enriched in the G-protein coupled receptor activity, structural constituent of chromatin, protein heterodimerization activity and binding of DNA, RNA, and protein. Gene set enrichment analysis showed enrichment in the pathway of neuroactive ligand receptor interaction and systemic lupus erythematosus. Conclusion The five patients had variable ranges of clinical courses and outcomes. Genomic and transcriptomic analysis of STS with brain metastasis implicate possible involvement of complex expression modification and epigenetic changes rather than the addition of single driver gene alteration.
Fully 3D-printed tortoise-like soft mobile robot with muti-scenario adaptability

Soft robotic systems are well suited to unstructured, dynamic tasks and environments, owing to their ability to adapt and conform without damaging themselves or their surroundings. These abilities are crucial in areas such as human-robot interaction, simplification of control system and weight reduction. At present, the existing soft mobile robots still have the disadvantages of single motion mode and application scenario, difficult manufacturing and low energy conversion efficiency. Based on the current shortcomings of soft robots, this paper designs and proposes a fully 3D-printed tortoise-like soft mobile robot with muti-scenarios adaptability. The robot uses a Bionic Tortoise Leg Actuator structure that enables simultaneous bending of the actuator in both directions, simplifying robot control and increasing the maximum bending angle achievable. In addition, a reconfiguration design solution has been proposed to enable the robot to implement two bionic modes for land and sea turtles, adapting to move on hard and soft surfaces and in water, enabling it to move in amphibious and complex environments. The performance of the pneumatic soft actuator is also improved by an improved Digital Light Processing method that enhances the maximum strain of the 3D printed soft material. The prototype was tested to give maximum movement speeds for different gaits and environments, demonstrating that the fully 3D printed tortoise-like soft-mobile robot designed in this paper is highly adaptable to multiple scenarios. The robot studied in this paper has a wide range of applications, with potential applications including navigation in a variety of domain environments, inspection of large underground oil and gas pipelines, and navigation in high temperature, high humidity and strong magnetic field environments or in military alert conditions.
Enabling Resource-Efficient AIoT System With Cross-Level Optimization: A Survey

The emerging field of artificial intelligence of things (AIoT, AI+IoT) is driven by the widespread use of intelligent infrastructures and the impressive success of deep learning (DL). With the deployment of DL on various intelligent infrastructures featuring rich sensors and weak DL computing capabilities, a diverse range of AIoT applications has become possible. However, DL models are notoriously resource-intensive. Existing research strives to realize near-/realtime inference of AIoT live data and low-cost training using AIoT datasets on resource-scare infrastructures. Accordingly, the accuracy and responsiveness of DL models are bounded by resource availability. To this end, the algorithm-system co-design that jointly optimizes the resource-friendly DL models and model-adaptive system scheduling improves the runtime resource availability and thus pushes the performance boundary set by the standalone level. Unlike previous surveys on resource-friendly DL models or hand-crafted DL compilers/frameworks with partially fine-tuned components, this survey aims to provide a broader optimization space for more free resource-performance tradeoffs. The cross-level optimization landscape involves various granularity, including the DL model, computation graph, operator, memory schedule, and hardware instructor in both on-device and distributed paradigms. Furthermore, due to the dynamic nature of AIoT context, which includes heterogeneous hardware, agnostic sensing data, varying user-specified performance demands, and resource constraints, this survey explores the context-aware inter-/intra-device controllers for automatic cross-level adaptation. Additionally, we identify some potential directions for resource-efficient AIoT systems. By consolidating problems and techniques scattered over diverse levels, we aim to help readers understand their connections and stimulate further discussions.
Bayesian inference of binary black holes with inspiral-merger-ringdown waveforms using two eccentric parameters

Orbital eccentricity is a crucial physical effect to unveil the origin of compact-object binaries detected by ground- and spaced-based gravitational-wave (GW) observatories. Here, we perform for the first time a Bayesian inference study of inspiral-merger-ringdown eccentric waveforms for binary black holes with non-precessing spins using two (instead of one) eccentric parameters: eccentricity and relativistic anomaly. We employ for our study the multipolar effective-one-body (EOB) waveform model SEOBNRv4EHM, and use initial conditions such that the eccentric parameters are specified at an orbit-averaged frequency. We show that this new parametrization of the initial conditions leads to a more efficient sampling of the parameter space. We also assess the impact of the relativistic-anomaly parameter by performing mock-signal injections, and we show that neglecting such a parameter can lead to significant biases in several binary parameters. We validate our model with mock-signal injections based on numerical-relativity waveforms, and we demonstrate the ability of the model to accurately recover the injected parameters. Finally, using standard stochastic samplers employed by the LIGO-Virgo-KAGRA Collaboration, we analyze a set of real GW signals observed by the LIGO-Virgo detectors during the first and third runs. We do not find clear evidence of eccentricity in the signals analyzed, more specifically we measure $e^{\text{GW150914}}_{\text{gw, 10Hz}}= 0.08^{+0.09}_{-0.06}$, $e^{\text{GW151226}}_{\text{gw, 20Hz}}= {0.04}^{+0.05}_{-0.04} $, and $e^{\text{GW190521}}_{\text{gw, 5.5Hz}}= 0.15^{+0.12}_{-0.12}$.
From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields

Recent years have seen vast progress in the development of machine learned force fields (MLFFs) based on ab-initio reference calculations. Despite achieving low test errors, the reliability of MLFFs in molecular dynamics (MD) simulations is facing growing scrutiny due to concerns about instability over extended simulation timescales. Our findings suggest a potential connection between robustness to cumulative inaccuracies and the use of equivariant representations in MLFFs, but the computational cost associated with these representations can limit this advantage in practice. To address this, we propose a transformer architecture called SO3krates that combines sparse equivariant representations (Euclidean variables) with a self-attention mechanism that separates invariant and equivariant information, eliminating the need for expensive tensor products. SO3krates achieves a unique combination of accuracy, stability, and speed that enables insightful analysis of quantum properties of matter on extended time and system size scales. To showcase this capability, we generate stable MD trajectories for flexible peptides and supra-molecular structures with hundreds of atoms. Furthermore, we investigate the PES topology for medium-sized chainlike molecules (e.g., small peptides) by exploring thousands of minima. Remarkably, SO3krates demonstrates the ability to strike a balance between the conflicting demands of stability and the emergence of new minimum-energy conformations beyond the training data, which is crucial for realistic exploration tasks in the field of biochemistry.
Nearly integrable flows and chaotic tangles in the Dimits shift regime of plasma edge turbulence

Transitionally turbulent flows frequently exhibit spatiotemporal intermittency, reflecting a complex interplay between driving forces, dissipation, and transport present in these systems. When this intermittency manifests as observable structures and patterns in the flow, the characterization of turbulence in these systems becomes challenging due to the nontrivial correlations introduced into the statistics of the turbulence by these structures. In this work, we use tools from dynamical systems theory to study intermittency in the Dimits shift regime of the flux-balanced Hasegawa–Wakatani (BHW) equations, which models a transitional regime of resistive drift-wave turbulence relevant to magnetically confined fusion plasmas. First, we show in direct numerical simulations that turbulence in this regime is dominated by strong zonal flows and coherent drift-wave vortex structures, which maintain a strong linear character despite their large amplitude. Using the framework of generalized Liouville integrability, we develop a theory of integrable Lagrangian flows in generic fluid and plasma systems and discuss how the observed zonal flows plus drift waves in the BHW system exhibit a form of “near-integrability” originating from a fluid element relabeling symmetry. We further demonstrate that the BHW flows transition from integrability to chaos via the formation of chaotic tangles in the aperiodic Lagrangian flow, and establish a direct link between the “lobes” associated with these tangles and intermittency in the observed turbulent dissipation. This illustrates how utilizing tools from deterministic dynamical systems theory to study convective nonlinearities can explain aspects of the intermittent spatiotemporal structure exhibited by the statistics of turbulent fields.
Are High-Temperature Molten Salts Reactive with Excess Electrons? Case of ZnCl2

New and exciting frontiers for the generation of safe and renewable energy have brought attention to molten inorganic salts of fluorides and chlorides. This is because high-temperature molten salts can act both as coolants and liquid fuel in next-generation nuclear reactors. Whereas research from a few decades ago suggests that salts are mostly unreactive to radiation, recent experiments hint at the fact that electrons generated in such extreme environments can react with the melt and form new species including nanoparticles. Our study probes the fate of an excess electron in molten ZnCl2 using first-principles molecular dynamics calculations. We find that on the time scale accessible to our study, an excess electron can be found in one of three states; the lowest-energy state can be characterized as a covalent Zn2Cl5•2– radical ion, the other two states are a solvated Zn•+ species (ZnCl3•2–) and a more delocalized species that still has some ZnCl3•2– character. Since for each of these, the singly occupied molecular orbital (SOMO) where the excess charge resides has a distinct and well-separated energy, the different species can in principle be characterized by their own electronic spectra. The study also sheds light onto what is commonly understood as the spectrum of a transient radical species which can be from the SOMO onto higher energy states or from the melt to pair with the excess electron leaving a hole in the liquid.
Fate of Chlorinated Compounds in a Sedimentary Fractured Rock Aquifer in South Central Wisconsin

A study was carried out in a sedimentary fractured rock site located in south central Wisconsin, US, which was impacted by DNAPL releases estimated to occur in the 1950’s and 1960’s. The majority of the DNAPL has accumulated in the upper portion of the Lone Rock Formation at a depth between 140 and 180 ft bgs referred as Layer 5 in this study. A groundwater VOC plume of more than 3km long has formed in this Layer. The DNAPL is mainly composed of 1,1,1-TCA, PCE, TCE and BTEX, while large amounts of biodegradation products such as cis-DCE and 1,1-DCA are present in the plume. Long term VOC data have been collected at the site and diverse geological and hydrogeological techniques have been applied to have a better understanding of the DNAPL history and behavior of the VOC plume. Evidence of biodegradation was also documented near the DNAPL source in these studies. The thesis objectives of the present study aimed first to have a better understanding of the long term contaminant distribution and degradation history at the site. This objective was accomplished reviewing the VOC historical concentration data collected from 1992 to 2006 in the wells tapping the most contaminated. hydrogeological unit in the bedrock (Layer 5) and in the overburden aquifer (referred as Layer 2). The second objective aimed to evaluate the current degree or extent of biodegradation of chlorinated compounds, which was accomplished evaluating the current groundwater redox conditions and using a combined analysis of VOC concentration and carbon isotope data collected in groundwater in September 2007. The historical data collected between1992 to 2006 showed the degradation of the VOC plume in Layer 5 was controlled by the availability of electron acceptors and redox conditions in the fracture bedrock aquifer. This pattern and the extension of the VOC
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank

Unbiased Learning to Rank (ULTR) aims to train unbiased ranking models from biased click logs, by explicitly modeling a generation process for user behavior and fitting click data based on examination hypothesis. Previous research found empirically that the true latent relevance is mostly recoverable through perfect click fitting. However, we demonstrate that this is not always achievable, resulting in a significant reduction in ranking performance. This research investigates the conditions under which relevance can be recovered from click data at a foundational level. We initially characterize a ranking model as identifiable if it can recover the true relevance up to a scaling transformation, a criterion sufficient for the pairwise ranking objective. Subsequently, we investigate an equivalent condition for identifiability, articulated as a graph connectivity test problem: the recovery of relevance is feasible if and only if the identifiability graph (IG), derived from the underlying structure of the dataset, is connected. The presence of a disconnected IG may lead to degenerate cases and suboptimal ranking performance. To tackle this challenge, we introduce two methods, namely node intervention and node merging, designed to modify the dataset and restore the connectivity of the IG. Empirical results derived from a simulated dataset and two real-world LTR benchmark datasets not only validate our proposed theorems but also demonstrate the effectiveness of our methods in alleviating data bias when the relevance model is unidentifiable.
Tomography of entangling two-qubit logic operations in exchange-coupled donor electron spin qubits

Scalable quantum processors require high-fidelity universal quantum logic operations in a manufacturable physical platform. Donors in silicon provide atomic size, excellent quantum coherence and compatibility with standard semiconductor processing, but no entanglement between donor-bound electron spins has been demonstrated to date. Here we present the experimental demonstration and tomography of universal 1- and 2-qubit gates in a system of two weakly exchange-coupled electrons, bound to single phosphorus donors introduced in silicon by ion implantation. We surprisingly observe that the exchange interaction has no effect on the qubit coherence. We quantify the fidelity of the quantum operations using gate set tomography (GST), and we use the universal gate set to create entangled Bell states of the electrons spins, with fidelity ~ 93%, and concurrence 0.91 +/- 0.08. These results form the necessary basis for scaling up donor-based quantum computers.
Arctic multilayered, mixed‐phase cloud processes revealed in millimeter‐wave cloud radar Doppler spectra

Cloud radar Doppler velocity spectra, lidar backscattering coefficients and depolarization ratios, and aircraft in situ measurements are used to investigate microphysical processes occurring in a case of multilayered, mixed‐phase clouds over the North Slope of Alaska. Some liquid‐cloud layers were observed to exist in well‐mixed atmospheric layers, but others were found in absolutely stable atmospheric layers. The observations suggest that strong cloud top cooling was necessary to produce the well‐mixed cloud layers; clouds shielded from radiative cooling by overlaying clouds more frequently existed in absolutely stable layers. The in situ measurements revealed that most liquid layers contained drizzle, the production process of which was shown from the radar and lidar measurements to have been interrupted only during heavier ice‐precipitation events. Different layers interacted with one another by changing the radiative heating profile and by precipitation which changed the growth paths available to cloud particles and even initiated new hydrometeor classes.
Gravitational Waves in the Circular Restricted Three Body Problem

The prospect of unprecedented high-quality data of gravitational waves in the upcoming decades demands a theoretical effort to optimally study and analyze the signals that next generation detectors will provide. Here we study the gravitational wave emission and related dynamics during the inspiralling phase of the Circular Restricted Three Body Problem, a modification of the conventional binary scenario in which a small third object co-rotates with the parent binary system. Specifically, we obtain analytic expressions for the emitted power, frequency variation and other dynamical variables that describe the evolution of the system. As a key highlight, we find that the presence of the third body actually slows down the coalescence of the binary, which can be partially interpreted as an effective rescaling of the binary's chirp-mass. Our analysis assumes semi-Keplerian orbits for the particles and a highly mass asymmetric parent binary needed for the stability of orbits.
SO2 as a possible proxy for volcanic ash in aviation hazard avoidance

Airborne volcanic ash poses a significant danger to aircraft, but is difficult to quantify accurately using satellite data, while sulphur dioxide is much easier to detect accurately, but is much less of a direct hazard to aviation. This paper investigates the reliability of using SO2 as a proxy for the location of volcanic ash, using an SO2 retrieval from the Infrared Atmospheric Sounding Interferometer (IASI) and ash detections from IASI and the Advanced Along Track Scanning Radiometer (AATSR). Using a numerical “missed ash fraction” applied to the eruptions of Eyjafjallajökull in 2010 and Puyehue‐Cordón Caulle in 2011 reveals that the SO2 flag typically misses ∼30% of the detectable ash. Furthermore, the missed ash fraction is found to be highly variable, both between the two eruptions and over the course of each eruption, with values of over 80% found on some days. The detection threshold of the AATSR ash flag is also investigated using radiative transfer calculations, allowing the threshold of the IASI flag to be inferred, and these are related to the ash contamination levels.
Antidepressant Use and Risk of Manic Episodes in Children and Adolescents With Unipolar Depression

Key Points Question Do pediatric patients diagnosed with unipolar depression who receive antidepressant treatment have an increased incidence of mania/hypomania compared with patients not treated with antidepressants? Findings In this cohort study including 43 677 children and adolescents diagnosed with unipolar depression, during a 12-week follow-up, patients treated with antidepressants did not have an increased incidence of mania/hypomania compared with patients who did not initiate antidepressant treatment. Hospitalizations, parental bipolar disorder, and use of antipsychotics and antiepileptics were the most important predictors of mania/hypomania by 12 weeks. Meaning This study found no evidence of treatment-emergent mania/hypomania in children and adolescents with unipolar depression.