Miracle-dz/UniFAR-FTUs huggingface dataset:
A Brief Review of Single Event Burnout Failure Mechanisms and Design Tolerances of Silicon Carbide MOSFETs

Radiation hardening of the MOSFET is of the highest priority for sustaining high-power systems in the space radiation environment. SiC-based power electronics are being looked at as a strong alternative for high power spaceborne power electronic systems. The SiC MOSFET has been shown to be most prone to SEB of the radiation effects. The knowledge of SiC MOSFET device degradation and failure mechanisms are reviewed. Additionally, the viability of rad-tolerant SiC MOSFET designs and the methods of SEB simulation are evaluated. A merit system is proposed to consider the performance of radiation tolerance and nominal electrical performance. Criteria needed for high-fidelity SEB simulation are also reviewed. This paper stands as a necessary analytical review to intercede the development of rad-hard power devices for space and extreme environment applications.
On the Evolution of Knowledge Graphs: A Survey and Perspective

Knowledge graphs (KGs) are structured representations of diversified knowledge. They are widely used in various intelligent applications. In this article, we provide a comprehensive survey on the evolution of various types of knowledge graphs (i.e., static KGs, dynamic KGs, temporal KGs, and event KGs) and techniques for knowledge extraction and reasoning. Furthermore, we introduce the practical applications of different types of KGs, including a case study in financial analysis. Finally, we propose our perspective on the future directions of knowledge engineering, including the potential of combining the power of knowledge graphs and large language models (LLMs), and the evolution of knowledge extraction, reasoning, and representation.
Data-driven mode shape selection and model-based vibration suppression of 3-RRR parallel manipulator with flexible actuation links

The mode shape function is difficult to determine in modeling manipulators with flexible links using the assumed mode method. In this paper, for a planar 3-RRR parallel manipulator with flexible actuation links, we provide a data-driven method to identify the mode shape of the flexible links and propose a model-based controller for the vibration suppression. By deriving the inverse kinematics of the studied mechanism in analytical form, the dynamic model is established by using the assumed mode method. To select the mode shape function, the software of multi-body system dynamics is used to simulate the dynamic behavior of the mechanism, and then the data-driven method which combines the DMD and SINDy algorithms is employed to identify the reasonable mode shape functions for the flexible links. To suppress the vibration of the flexible links, a state observer for the end-effector is constructed by a neural network, and the model-based control law is designed on this basis. In comparison with the model-free controller, the proposed controller with developed dynamic model has promising performance in terms of tracking accuracy and vibration suppression.
LaTeX: Language Pattern-aware Triggering Event Detection for Adverse Experience during Pandemics

The COVID-19 pandemic has accentuated socioeconomic disparities across various racial and ethnic groups in the United States. While previous studies have utilized traditional survey methods like the Household Pulse Survey (HPS) to elucidate these disparities, this paper explores the role of social media platforms in both highlighting and addressing these challenges. Drawing from real-time data sourced from Twitter, we analyzed language patterns related to four major types of adverse experiences: loss of employment income (LI), food scarcity (FS), housing insecurity (HI), and unmet needs for mental health services (UM). We first formulate a sparsity optimization problem that extracts low-level language features from social media data sources. Second, we propose novel constraints on feature similarity exploiting prior knowledge about the similarity of the language patterns among the adverse experiences. The proposed problem is challenging to solve due to the non-convexity objective and non-smoothness penalties. We develop an algorithm based on the alternating direction method of multipliers (ADMM) framework to solve the proposed formulation. Extensive experiments and comparisons to other models on real-world social media and the detection of adverse experiences justify the efficacy of our model.
DeepQTest: Testing Autonomous Driving Systems with Reinforcement Learning and Real-world Weather Data

Autonomous driving systems (ADSs) are capable of sensing the environment and making driving decisions autonomously. These systems are safety-critical, and testing them is one of the important approaches to ensure their safety. However, due to the inherent complexity of ADSs and the high dimensionality of their operating environment, the number of possible test scenarios for ADSs is infinite. Besides, the operating environment of ADSs is dynamic, continuously evolving, and full of uncertainties, which requires a testing approach adaptive to the environment. In addition, existing ADS testing techniques have limited effectiveness in ensuring the realism of test scenarios, especially the realism of weather conditions and their changes over time. Recently, reinforcement learning (RL) has demonstrated great potential in addressing challenging problems, especially those requiring constant adaptations to dynamic environments. To this end, we present DeepQTest, a novel ADS testing approach that uses RL to learn environment configurations with a high chance of revealing abnormal ADS behaviors. Specifically, DeepQTest employs Deep Q-Learning and adopts three safety and comfort measures to construct the reward functions. To ensure the realism of generated scenarios, DeepQTest defines a set of realistic constraints and introduces real-world weather conditions into the simulated environment. We employed three comparison baselines, i.e., random, greedy, and a state-of-the-art RL-based approach DeepCOllision, for evaluating DeepQTest on an industrial-scale ADS. Evaluation results show that DeepQTest demonstrated significantly better effectiveness in terms of generating scenarios leading to collisions and ensuring scenario realism compared with the baselines. In addition, among the three reward functions implemented in DeepQTest, Time-To-Collision is recommended as the best design according to our study.
Audiomagnetotelluric data and preliminary two-dimensional models from Spring, Dry Lake, and Delamar Valleys, Nevada

7 Introduction . 7 Audiomagnetotelluric Method.9 Audiomagnetotelluric Data . 10 Two-Dimensional Inverse Modeling . 11 Audiomagnetotelluric Surveys and Results.12 Spring Valley.13 Profiles AQDCT, SVNN Southeastern Spring Valley . 13 Profiles SVN0, SVNP, SVNQ -The Troughs . 14 Delamar Valley.15 Profiles DELA1 and DELA5 . 15 Dry Lake Valley.16 Profiles DLV1, DLV2, DLV3, DLV4, DLV5, DLV8, and DLV24.16 Acknowledgments.19 References Cited . 19 Figures Figure 1. Topographic map of southern Spring Valley, Nev. , showing location of audiomagnetotelluric profiles in red. Profiles shown in blue were collected prior to May 2007 and are presented in McPhee and others, 2006, 2007. 22 Figure 2. Topographic map of Delamar Valley, Nev. , showing location of audiomagnetotelluric profiles in red. 23 Figure 3. Topographic map of Dry Lake Valley, Nev. , showing audiomagnetotelluric profiles in red. 24 Figure 4. Two-dimensional inverse model computed from the transverse magnetic-mode data along profile AQDCT in Spring Valley, Nev. 25 Figure 5. Pseudosections of observed data and model response for the apparent resistivity and phase along profile AQDCT in Spring Valley, Nev. 26 Figure 6. Two-dimensional inverse model computed from the transverse magnetic-mode data along profile SVNN in Spring Valley, Nev. 27 Figure 7. Pseudosections of observed data and model response for the apparent resistivity and phase along profile SVNN in Spring Valley, Nev. 28 Figure 8. Two-dimensional inverse model computed from the transverse magnetic-mode data along profile SVNO in Spring Valley, Nev. 29 Figure 9. Pseudosections of observed data and model response for the apparent resistivity and phase along profile SVNO in Spring Valley, Nev. 30 Figure 10. Two-dimensional inverse model computed from the transverse magneticmode data along profile SVNP in Spring Valley, Nev. 31 Figure 11. Pseudosections of observed data and model response for the apparent resistivity and phase along profile SVNP in Spring Valley, Nev. 32 Figure 12. Two-dimensional inverse model computed from the transverse electricand transverse magnetic-mode data along profile SVNQ in Spring Valley, Nev. 33
Adaptive finite element approximation of bilinear optimal control with fractional Laplacian

We investigate the application of a posteriori error estimates to a fractional optimal control problem with pointwise control constraints. Specifically, we address a problem in which the state equation is formulated as an integral form of the fractional Laplacian equation, with the control variable embedded within the state equation as a coefficient. We propose two distinct finite element discretization approaches for an optimal control problem. The first approach employs a fully discrete scheme where the control variable is discretized using piecewise constant functions. The second approach, a semi-discrete scheme, does not discretize the control variable. Using the first-order optimality condition, the second-order optimality condition, and a solution regularity analysis for the optimal control problem, we devise a posteriori error estimates. We subsequently demonstrate the reliability and efficiency of the proposed error estimators. Based on the established error estimates framework, an adaptive refinement strategy is developed to help achieve the optimal convergence rate. The effectiveness of the refinement strategy is verified by numerical experiments.
The elemental composition of Almahata Sitta

Abstract– We quantified up to 60 elements in four individual fragments (#4, #7, #15, and #47) of the Almahata Sitta meteorite, which entered Earth’s atmosphere on October 7, 2008. Almahata Sitta is indisputably the product of fragments of asteroid 2008 TC3 surviving passage through Earth’s atmosphere. Each of the four analyzed fragments has a ureilitic composition based on comparisons with literature data. The analyzed fragments represent each of the major lithologies of Almahata Sitta. Highly refractory siderophile elements are similarly enriched in all fragments of Almahata Sitta, while volatile elements show more compositional variability. The abundances of rare earth elements (REE) only reach CI values in the case of a single Almahata Sitta fragment (#15). More typically, REE abundances in Almahata Sitta are between 0.01 and 0.3 × CI. None of the fragments displays the classic V‐shaped REE pattern that are often found in ureilites. Given that Almahata Sitta was collected shortly after its fall, these REE compositional results indicate that the V‐shaped REE pattern found in many ureilites may be a result of extended terrestrial residence times.
44Ca/42Ca and 143Nd/144Nd isotope variations in Cretaceous–Eocene Tethyan francolites and their bearing on phosphogenesis in the southern Tethys

Measurements of 4 4 Ca/ 4 2 Ca and 1 4 3 Nd/ 1 4 4 Nd isotope ratios in carbonate fluorapatite (CFA) through the Aptian-Eocene section of the Negev (Israel), together with quantified rates of P and Ca accumulation and bulk sedimentation, permit an examination of the relationships of these five factors to Tethyan phosphogenesis. The data provide an Aptian-Eocene (ca. 70 Ma) record of the Ca isotope composition of 35 CFA samples (24 of which were also analyzed for Nd isotopes), representing 11 time-stratigraphic phosphate horizons within the sequence. The δ 4 4 Ca values are significantly lower in the Aptian-Albian samples (δ 4 4 Ca = -0.11‰ to -0.06‰) than in the Campanian-Eocene samples (δ 4 4 Ca = +0.22‰ to +0.42‰), whereas the e N d (Τ) values increase from continental crust like in the Aptian-Albian [e N d ( T ) = -10.9] to more radiogenic, Pacific-like [e N d ( T ) = -6.6 to -6.1] in the Campanian. Both peaks of δ 4 4 Ca and e N d ( T ) in the Campanian coincide with the peak of Tethyan phosphogenesis in the Negev, which is marked by a sharp increase of P accumulation rates (from <200 μmol.cm - 2 .k.y. - 1 in pre-Campanian time to ∼1700 μmol.cm - 2 .k.y. - 1 in the Campanian) and a decrease in rates of Ca accumulation and bulk sedimentation. The coincident increases of δ 4 4 Ca and e N d ( T ) values and P accumulation rates in the Negev area during the Campanian suggest that they are related in this time interval and were induced by the global Late Cretaceous sea-level rise and increasing circumequatorial Tethyan flow.
IS M ORE : O N THE F EATURE R EDUNDANCY OF P RETRAINED M ODELS W HEN T RANSFERRING TO F EW - SHOT T ASKS

Transferring a pretrained model to a downstream task can be as easy as conducting linear probing with target data, that is, training a linear classifier upon frozen features extracted from the pretrained model. As there may exist significant gaps between pretraining and downstream datasets, one may ask whether all dimensions of the pretrained features are useful for a given downstream task. We show that, for linear probing, the pretrained features can be extremely redundant when the downstream data is scarce, or few-shot. For some cases such as 5-way 1-shot tasks, using only 1% of the most important feature dimensions is able to recover the performance achieved by using the full representation. Interestingly, most dimensions are redundant only under few-shot settings and gradually become useful when the number of shots increases, suggesting that feature redundancy may be the key to characterizing the “few-shot” nature of few-shot transfer problems. We give a theoretical understanding of this phenomenon and show how dimensions with high variance and small distance between class centroids can serve as confounding factors that severely disturb classification results under few-shot settings. As an attempt at solving this problem, we find that the redundant features are difficult to identify accurately with a small number of training samples, but we can instead adjust feature magnitude with a soft mask based on estimated feature importance. We show that this method can generally improve few-shot transfer performance across various pretrained models and downstream datasets.
Detecting Lane Departure Based on GIS Using DGPS

This paper proposes a method utilizing Differential Global Position System (DGPS) with Real-Time Kinematic (RTK) and pre-built Geo-graphic Information System (GIS) to detect lane departure of a vehicle. The position of a vehicle measured by DGPS with RTK has 18 cm-level accuracy. The preconditioned GIS data giving accurate position information of the traffic lanes is used to set up coordinate system and to enable fast calculation of the relative position of the vehicle within the traffic lanes. This relative position can be used for safe driving by preventing the vehicle from departing lane carelessly. The proposed system can be a key component in functions such as vehicle guidance, driver alert and assistance, and the smart highway that eventually enables autonomous driving supporting system. Experimental results show the ability of the system to meet the accuracy and robustness to detect lane departure of a vehicle at high speed.
Environmental Sources of Fecal Bacteria

Despite regulatory requirements for treating wastewater to reduce microbial pollutants prior to release into waterways, frequent beach closures or advisories as a result of elevated fecal indicator bacteria (FIB; e.g., Escherichia coli and enterococci) have been a chronic problem at many recreational locations. This chapter provides a review of the research on environmental occurrences of FIB in a variety of terrestrial and aquatic habitats under different geographic and climatic conditions, and discusses how these external sources may affect surface water quality. FIB are usually retained in the upper layer of soil depending on soil type, temperature, rate of water flow, and other environmental variables. Several microbial source tracking studies have identified wildlife as an important nonpoint source of FIB; however, identifying and partitioning these contaminants by source has been challenging. Future research on colonization potential, growth requirements, microbial interactions, and population genetics, can shed more light on FIB occurrence in natural environments. The persistence and potential growth of indicator bacteria in sediments and soils likely have a serious impact on recreational water quality by elevating bacterial counts through resuspension and surface runoff. Since large quantities of wastes generated from animal husbandry activities, such as poultry, dairy, and swine production, are often spread over the land as a fertilizer, these processes may result in an increase of microbial contaminants in the soil that, in turn, could potentially affect the quality of nearby water bodies.
Regeneration of neuromuscular synapses after acute and chronic denervation by inhibiting the gerozyme 15-prostaglandin dehydrogenase

To date, there are no approved treatments for the diminished strength and paralysis that result from the loss of peripheral nerve function due to trauma, heritable neuromuscular diseases, or aging. Here, we showed that denervation resulting from transection of the sciatic nerve triggered a marked increase in the prostaglandin-degrading enzyme 15-hydroxyprostaglandin dehydrogenase (15-PGDH) in skeletal muscle in mice, providing evidence that injury drives early expression of this aging-associated enzyme or gerozyme. Treating mice with a small-molecule inhibitor of 15-PGDH promoted regeneration of motor axons and formation of neuromuscular synapses leading to an acceleration in recovery of force after an acute nerve crush injury. In aged mice with chronic denervation of muscles, treatment with the 15-PGDH inhibitor increased motor neuron viability and restored neuromuscular junctions and function. These presynaptic changes synergized with previously reported muscle tissue remodeling to result in a marked increase in the strength of aged muscles. We further found that 15-PGDH aggregates defined the target fibers that are histopathologic hallmarks of human neurogenic myopathies, suggesting that the gerozyme may be involved in their etiology. Our data suggest that inhibition of 15-PGDH may constitute a therapeutic strategy to physiologically boost prostaglandin E2, restore neuromuscular connectivity, and promote recovery of strength after acute or chronic denervation due to injury, disease, or aging. Description Inhibition of the gerozyme 15-PGDH promotes peripheral nerve regeneration and restoration of damaged neuromuscular synapses in injured or aged mice. Editor’s summary Skeletal muscle denervation, which can occur because of disease, trauma or disuse, results in muscle weakness and atrophy, with no available treatments to promote axon regeneration or to restore neuromuscular junctions (NMJs). Here, Bakooshli, Wang, and colleagues found that 15-prostaglandin dehydrogenase (15-PGDH), which accumulates with age and promotes muscle atrophy, markedly increased in denervated mouse myofibers and aggregated in ‘target fibers, hallmarks of chronic nerve damage in human myogenic neuropathies. In a mouse model of sciatic nerve crush injury, small molecule inhibition of 15-PGDH promoted motor axon regeneration and NMJ restoration, leading to improvement in muscle force 14 days after injury. In aged mice, treatment improved NMJ number and morphology and elicited a pro-regenerative response in motor neurons, suggesting that 15-PGDH may be a therapeutic target for neuromuscular recovery after denervation. —Melissa L. Norton
Emergence and genomic insights of non-pandemic O1 Vibrio cholerae in Zhejiang, China

ABSTRACT Vibrio cholerae O1 has caused cholera pandemics. Non-pandemic V. cholerae O1 strains, which are genetically distinctive from the pandemic clones, have been isolated from both human infections and the environment. We aimed to better understand the non-pandemic O1 strains and their pandemic potential. We sequenced 109 non-pandemic O1 isolates from Zhejiang, China (from 1963 to 1996) and compared them with 62 publicly available non-pandemic O1 genomes. The isolates from Zhejiang can be classified into three lineages (L1–L3). All grouped together with L3 sharing the most recent common ancestor with the pandemic clones. L2 and L3 emerged in the 1960s while L1 emerged in the 1970s. L1 and L2 disappeared after the 1990s, but L3 persisted until recently. All isolates contained the type VI secretion system. The Vibrio pathogenicity island was present in all L3 isolates, whereas the type III secretion system was present in all L1 isolates. L2 did not carry any unique virulence genes. An intact CTXφ was present in only two L3 isolates. An intact Vibrio seventh pandemic island 1 was present in only three L3 isolates. The blaCARB-7 gene was identified in 96.3% of L2 isolates. Each of the non-pandemic O1 lineages has unique properties contributing to their capacity to cause disease. Our findings offer new insight into the evolution of O1 V. cholerae for cholera prevention and control. IMPORTANCE It is well recognized that only Vibrio cholerae O1 causes cholera pandemics. However, not all O1 strains cause pandemic-level disease. In this study, we analyzed non-pandemic O1 V. cholerae isolates from the 1960s to the 1990s from China and found that they fell into three lineages, one of which shared the most recent common ancestor with pandemic O1 strains. Each of these non-pandemic O1 lineages has unique properties that contribute to their capacity to cause cholera. The findings of this study enhanced our understanding of the emergence and evolution of both pandemic and non-pandemic O1 V. cholerae. It is well recognized that only Vibrio cholerae O1 causes cholera pandemics. However, not all O1 strains cause pandemic-level disease. In this study, we analyzed non-pandemic O1 V. cholerae isolates from the 1960s to the 1990s from China and found that they fell into three lineages, one of which shared the most recent common ancestor with pandemic O1 strains. Each of these non-pandemic O1 lineages has unique properties that contribute to their capacity to cause cholera. The findings of this study enhanced our understanding of the emergence and evolution of both pandemic and non-pandemic O1 V. cholerae.
Sieben auf einen Streich: Neuroprotektive (Mikro-)Nährstoffe als kognitive Enhancer

Zusammenfassung Eine optimale kognitive Leistungsfähigkeit ist in allen Lebensphasen für die Vitalität von hohem Stellenwert. Insb. in der Kindheit und im Adoleszentenalter haben Ernährungseinflüsse entscheidenden Einfluss auf die Hirnentwicklung und kognitive Leistungsfähigkeit. Mikronährstoffe spielen daher nicht nur eine essenzielle Rolle für die allgemeine Zellentwicklung und Zellfunktion, sondern auch bei zahlreichen neurologischen Funktionen, wie der Neurotransmittersynthese, Myelogenese sowie der Bildung von Neurotrophinen. Eine adäquate diätetische Versorgung mit gehirnaktiven (Mikro-)Nährstoffen wie Vitaminen, Mineralien und ω-3-Fettsäuren ist daher bei Schulkindern von elementarer Bedeutung für eine gesunde Hirnentwicklung.