Miracle-dz/UniFAR-FTUs huggingface dataset:
Inference on volatility estimation with missing data: a functional data approach

This paper aims to investigate nonparametric estimation of the volatility component in a heteroscedastic scalar-on-function regression model when the underlying discrete-time process is ergodic and affected by a missing at random mechanism. First, we introduce a simplified estimator of the regression and volatility operators based on observed data only. We study their asymptotic properties, such as almost sure uniform consistency rate and asymptotic distribution. Then, the simplified estimators are used to impute the missing data in the original process in order to improve the estimation of the regression and volatility components. The asymptotic properties of the imputed estimators are also investigated. A numerical comparison between the estimators is discussed through simulated data. Finally, a real-data analysis is conducted to model the volatility of daily Brent crude oil returns using intraday, 1-minute frequency, natural gas returns.
Learner understanding of energy degradation

Learners' everyday ideas about energy often involve energy being "used up" or "wasted. " In physics, the concept of energy degradation can connect those ideas to the principle of energy conservation. Learners' spontaneous discussions about aspects of energy degradation motivated us to introduce new learning goals into our K-12 teacher professional development courses. One of our goals is for learners to recognize that since energy degradation is associated with the movement of some quantity towards equilibrium, the identification of energy as degraded or free depends on the choice of the objects involved. Another goal is for learners to recognize that overall energy degradation occurs. We find that teachers' discussions contain productive ideas about energy degradation that demonstrate progress towards our goals. These include (1) the idea that degraded energy can be made useful and (2) the idea that making energy useful requires either effort or energy relocation.
Logical Bias Learning for Object Relation Prediction

Scene graph generation (SGG) aims to automatically map an image into a semantic structural graph for better scene understanding. It has attracted significant attention for its ability to provide object and relation information, enabling graph reasoning for downstream tasks. However, it faces severe limitations in practice due to the biased data and training method. In this paper, we present a more rational and effective strategy based on causal inference for object relation prediction. To further evaluate the superiority of our strategy, we propose an object enhancement module to conduct ablation studies. Experimental results on the Visual Gnome 150 (VG-150) dataset demonstrate the effectiveness of our proposed method. These contributions can provide great potential for foundation models for decision-making.
Do the Benefits of Joint Models for Relation Extraction Extend to Document-level Tasks?

Two distinct approaches have been proposed for relational triple extraction - pipeline and joint. Joint models, which capture interactions across triples, are the more recent development, and have been shown to outperform pipeline models for sentence-level extraction tasks. Document-level extraction is a more challenging setting where interactions across triples can be long-range, and individual triples can also span across sentences. Joint models have not been applied for document-level tasks so far. In this paper, we benchmark state-of-the-art pipeline and joint extraction models on sentence-level as well as document-level datasets. Our experiments show that while joint models outperform pipeline models significantly for sentence-level extraction, their performance drops sharply below that of pipeline models for the document-level dataset.
On the Quantum Uncertainty of the Neutron Electric Dipole Moment

The continued interest in placing bounds on the neutron's Electric Dipole Moment (EDM) is due to the implications regarding the characteristics of the strong interaction and, in particular, its behavior under the CP symmetry. In this work, we discuss the apparent tension resulting from the discrepancy of about 13 orders of magnitude between the current bounds and the expected quantum uncertainty in the relevant quantity. We offer a resolution of the"puzzle"in terms of the notion of a weak measurement, using a version of the corresponding formalism adapted to consideration of the nEDM experiment at the Spallation Neutron Source at the Oak Ridge National Laboratory.
How much time does a photon spend as an atomic excitation before being transmitted?

When a single photon traverses a cloud of 2-level atoms, the average time it spends as an atomic excitation -- as measured by weakly probing the atoms -- can be shown to be the spontaneous lifetime of the atoms multiplied by the probability of the photon being scattered into a side mode. A tempting inference from this is that an average scattered photon spends one spontaneous lifetime as an atomic excitation, while photons that are transmitted spend zero time as atomic excitations. However, recent experimental work by some of us [PRX Quantum 3, 010314 (2022)] refutes this intuition. We examine this problem using the weak-value formalism and show that the time a transmitted photon spends as an atomic excitation is equal to the group delay, which can take on positive or negative values. We also determine the corresponding time for scattered photons and find that it is equal to the time delay of the scattered photon pulse, which consists of a group delay and a time delay associated with elastic scattering, known as the Wigner time delay. This work provides new insight into the complex and surprising histories of photons travelling through absorptive media.
Characterizing Semantic Ambiguity of the Materials Science Ontologies

Growth in computational materials science and initiatives such as the Materials Genome Initiative (MGI) and the European Materials Modelling Council (EMMC) has motivated the development and application of ontologies. A key factor has been increased adoption of the FAIR principles, making research data findable, accessible, interoperable, and reusable (Wilkinson et al. 2016). This paper characterizes semantic interoperability among a subset of materials science ontologies in the MatPortal repository. Background context covers semantic interoperability, ontological commitment, and the materials science ontology landscape. The research focused on MatPortal's two interoperability protocols: LOOM term matching and URI matching. Results report the degree of overlap and demonstrate the different types of ambiguity among ontologies. The discussion considers implications for FAIR and AI, and the conclusion highlight key findings and next steps.
NoxTrader: LSTM-Based Stock Return Momentum Prediction

— We introduce NoxTrader, which is designed for portfolio construction and trading execution, aims at generating profitable outcomes. The primary focus of NoxTrader is on stock market trading with an emphasis on cultivating moderate to long-term profits. The underlying learning process of NoxTrader hinges on the assimilation of insights gleaned from historical trading data, primarily hinging on time-series analysis due to the inherent nature of the employed dataset. We delineate the sequential progression encompassing data acquisition, feature engineering, predictive modeling, parameter configuration, establishment of a rigorous backtesting framework, and ultimately position NoxTrader as a testament to the prospective viability of algorithmic trading models within real-world trading scenarios.
Searching for new physics at $\mu\rightarrow e$ facilities with $\mu^+$ and $\pi^+$ decays at rest

We investigate the ability of $\mu\rightarrow e$ facilities, Mu2e and COMET, to probe, or discover, new physics with their detector validation datasets. The validation of the detector response may be performed using a dedicated run with $\mu^+$, collecting data below the Michel edge, $E_e\lesssim 52$ MeV; an alternative strategy using $\pi^+\rightarrow e^+ \nu_e$ may also be considered. We focus primarily on a search for a monoenergetic $e^+$ produced via two-body decays $\mu^+ \rightarrow e^+ X$ or $\pi^+\rightarrow e^+X$, with $X$ a light new physics particle. Mu2e can potentially explore new parameter space beyond present astrophysical and laboratory constraints for a set of well motivated models including: axion like particles with flavor violating couplings ($\mu^+ \rightarrow e^+ a$), massive $Z'$ bosons ($\mu^+ \rightarrow Z' e^+$), and heavy neutral leptons ($\pi^+\rightarrow e^+N$). The projected sensitivities presented herein can be achieved in a matter of days.
King of the Hill: A Novel Cybersecurity Competition for Teaching Penetration Testing

Cybersecurity competitions are an effective and engaging way to provide students with hands-on experience with real-world security practices. Unfortunately, existing competitions are ill-suited in giving students experience in penetration testing, because they tend to lack three key aspects: (1) pivoting across multiple machines, (2) developing or implanting custom software, and (3) giving students enough time to prepare for a lively in-class competition. In this paper, we present the design, implementation, and an initial run of King of the Hill (KotH) , an active learning cybersecurity competition designed to give students experience performing and defending against penetration testing. KotH competitions involve a sophisticated network topology that students must pivot through in order to reach high-value targets. When teams take control of a machine, they also take on the responsibility of running its critical services and defending it against other teams. Our preliminary results indicate that KotH gives students valuable and effective ﬁrst-hand experience with problems that professional penetration testers and network administrators face in real environments.
B RIDGING THE G AP B ETWEEN F OUNDATION M ODELS AND H ETEROGENEOUS F EDERATED L EARNING

Federated learning (FL) offers privacy-preserving decentralized machine learning, optimizing models at edge clients without sharing private data. Simultaneously, foundation models (FMs) have gained traction in the artificial intelligence (AI) community due to their exceptional performance across various tasks. However, integrating FMs into FL presents challenges, primarily due to their substantial size and intensive resource requirements. This is especially true when considering the resource heterogeneity in edge FL systems. We present an adaptive framework for Resource-aware Federated Foundation Models (RaFFM) to address these challenges. RaFFM introduces specialized model compression algorithms tailored for FL scenarios, such as salient parameter prioritization and highperformance subnetwork extraction. These algorithms enable dynamic scaling of given transformer-based FMs to fit heterogeneous resource constraints at the network edge during both FL’s optimization and deployment stages. Experimental results demonstrate that RaFFM shows significant superiority in resource utilization efficiency and uses fewer resources to deploy FMs to FL. Despite the lower resource consumption, target models optimized by RaFFM achieve performance on par with traditional FL methods applied to full-sized FMs. This is evident across tasks in both natural language processing and computer vision domains.
Siamese Representation Learning for Unsupervised Relation Extraction

Unsupervised relation extraction (URE) aims at discovering underlying relations between named entity pairs from open-domain plain text without prior information on relational distribution. Existing URE models utilizing contrastive learning, which attract positive samples and repulse negative samples to promote better separation, have got decent effect. However, fine-grained relational semantic in relationship makes spurious negative samples, damaging the inherent hierarchical structure and hindering performances. To tackle this problem, we propose Siamese Representation Learning for Unsupervised Relation Extraction -- a novel framework to simply leverage positive pairs to representation learning, possessing the capability to effectively optimize relation representation of instances and retain hierarchical information in relational feature space. Experimental results show that our model significantly advances the state-of-the-art results on two benchmark datasets and detailed analyses demonstrate the effectiveness and robustness of our proposed model on unsupervised relation extraction.
Nearest neighbor synthesis of CNOT circuits on general quantum architectures

In recent years, quantum computing has entered the Noisy Intermediate-Scale Quantum (NISQ). However, NISQ devices have inherent limitations in terms of connectivity and hardware noise, necessitating the transformation of quantum logic circuits for correct execution on NISQ chips. The synthesis of CNOT circuits considering physical constraints can transform quantum algorithms into low-level quantum circuits, which can be directly executed on physical chips. In the current trend, quantum chip architectures without Hamiltonian paths are gradually replacing architectures with Hamiltonian paths due to their scalability and low-noise characteristics. To this end, this paper addresses the nearest neighbor synthesis of CNOT circuits in the architecture with and without Hamiltonian paths, aiming to enhance the fidelity of the circuits after execution. Firstly, a key-qubit priority mapping model for the general architecture with and without Hamiltonian paths is proposed. Secondly, the initial mapping is further improved by using tabu search to reduce the number of CNOT gates after circuit synthesis and enhance its fidelity. Finally, the noise-aware CNOT circuit nearest neighbor synthesis algorithm for the general architecture is proposed based on the key-qubit priority mapping model. Experimental results show that the proposed method can enhance the fidelity of the CNOT circuit by about 64.7% on a real quantum computing device, achieving a significant optimization effect. Furthermore, the method can be extended to other circuits, thereby improving the overall performance of quantum computing on NISQ devices.
Atrial Fibrillation Recurrence in Patients With Transient New-Onset Atrial Fibrillation Detected During Hospitalization for Noncardiac Surgery or Medical Illness

BACKGROUND Atrial fibrillation (AF) is often detected for the first time in patients who are hospitalized for another reason. Long-term risks for AF recurrence in these patients are unclear. OBJECTIVE To estimate risk for AF recurrence in patients with new-onset AF during a hospitalization for noncardiac surgery or medical illness compared with a matched population without AF. DESIGN Matched cohort study. (ClinicalTrials.gov: NCT03221777). SETTING Three academic hospitals in Hamilton, Ontario, Canada. PARTICIPANTS The study enrolled patients hospitalized for noncardiac surgery or medical illness who had transient new-onset AF. For each participant, an age- and sex-matched control participant with no history of AF from the same hospital ward was recruited. All participants left the hospital in sinus rhythm. MEASUREMENTS 14-day electrocardiographic (ECG) monitor at 1 and 6 months and telephone assessment at 1, 6, and 12 months. The primary outcome was AF lasting at least 30 seconds on the monitor or captured by ECG 12-lead during routine care at 12 months. RESULTS Among 139 participants with transient new-onset AF (70 patients with medical illness and 69 surgical patients) and 139 matched control participants, the mean age was 71 years (SD, 10), the mean CHA2DS2-VASc score was 3.0 (SD, 1.5), and 59% were male. The median duration of AF during the index hospitalization was 15.8 hours (IQR, 6.4 to 49.6 hours). After 1 year, recurrent AF was detected in 33.1% (95% CI, 25.3% to 40.9%) of participants in the transient new-onset AF group and 5.0% (CI, 1.4% to 8.7%) of matched control participants; after adjustment for the number of ECG monitors worn and for baseline clinical differences, the adjusted relative risk was 6.6 (CI, 3.2 to 13.7). After exclusion of participants who had electrical or pharmacologic cardioversion during the index hospitalization (n = 40) and their matched control participants and limiting to AF events detected by the patch ECG monitor, recurrent AF was detected in 32.3% (CI, 23.1% to 41.5%) of participants with transient new-onset AF and 3.0% (CI, 0% to 6.4%) of matched control participants. LIMITATIONS Generalizability is limited, and the study was underpowered to evaluate subgroups and clinical predictors. CONCLUSION Among patients who have transient new-onset AF during a hospitalization for noncardiac surgery or medical illness, approximately 1 in 3 will have recurrent AF within 1 year. PRIMARY FUNDING SOURCE Peer-reviewed grants.
Taxonomy of the Archaeoglenes Biroi Species-Group (Tenebrionidae: Phrenapatinae: Archaeoglenini) with a Description of the New Species from the Moluccas

Abstract. A newly discovered species, Archaeoglenes borowieci sp. nov., is illustrated and described from the Moluccas (Indonesia). This new taxon is the first known anophthalmic representative of the genus. Based on the structure of the mouthparts (transverse mentum with truncate anterior margin; triangular and narrow submentum), pronotum (simple, without incision before anterior angle), and abdomen (wide and truncate intercoxal process), it is classified within the newly designated Archaeoglenes biroi species-group, which also groups: A. biroi Kaszab, 1982, A. caledonicus Kaszab, 1982, A. lawrencei Kaszab, 1982, A. solomonensis Lawrence, 1979, A. triplehorni Iwan & Kamiński, 2015. Additionally, the following synonymy is introduced: Archaeoglenes solomonensis Lawrence, 1979 (=Archaeoglenes greensladei Kaszab, 1982 syn. nov.).
What is an Optimal Policy in Time-Average MDP?

This paper discusses the notion of optimality for time-average MDPs. We argue that while most authors claim to use the "average reward" criteria, the notion that is implicitly used is in fact the notion of what we call Bellman optimality. We show that it does not coincide with other existing notions of optimality, like gain-optimality and bias-optimality but has strong connection with canonical-policies (policies that are optimal for any finite horizons) as well as value iteration and policy iterations algorithms.
Significance of the Radiocarbon Age and the Identification of the Fossil Wood under Lava Flows Erupted from Rishiri Volcano, Hokkaido, Japan

北海道北部, 利尻島において沓形溶岩流および野塚溶岩流の直下から木材遺体を採取し, その年代測定と樹種同定を行なった. 沓形溶岩流直下の木材遺体からは>37,320年BP, 野塚溶岩流直下の木材遺体からは28,230±1,020年BPの14C年代値が得られ, これらの値がそれぞれの溶岩流の噴出年代を示すと考えられる. 両地点における木材遺体を同定した結果, 野塚溶岩流直下のものはカラマツ属 Larix とトウヒ属 Picea, 沓形溶岩流直下のものはこれらの他にモミ属 Abies が含まれていた. 以上の結果から, 2つの溶岩流の噴出年代はこれまで考えられていたよりも古く, 最終氷期の約2. 8万年BPより前には, 火山体は少なくとも現在と同程度の高度にまで成長していたと考えられる. また, それぞれの溶岩流の噴出した時期には山麓で針葉樹が生育していたことが明らかになった.
Reducing Heavy-Traffic Response Time with Asymmetric Dispatching

Reducing mean response time has always been a desirable goal in queueing systems. If job sizes (a.k.a. service times) are known to the scheduler, the policy that minimizes mean response time of a single-server queue is SRPT (Shortest Remaining Processing Time). This is true even for queues that are part of a larger system, such as immediate-dispatch systems where jobs are sent to one of multiple single-server queues upon arrival.
The El Niño–southern oscillation and Antarctica

This paper reviews our understanding of how the effects of the El Niño–southern oscillation (ENSO) might be transmitted from the tropical Pacific Ocean to the Antarctic, and examines the evidence for such signals in the Antarctic meteorological, sea ice, ice core and biological records. Many scientific disciples concerned with the Antarctic require an understanding of how the climatic conditions in the tropical and mid‐latitude regions affect the Antarctic, and it is hoped that this review will aid their work.
A Window into Mammalian Basement Membrane Development: Insights from the mTurq2-Col4a1 Mouse Model

Basement membranes (BMs) are specialized sheets of extracellular matrix that underlie epithelial and endothelial tissues. BMs regulate traffic of cells and molecules between compartments, and participate in signaling, cell migration and organogenesis. The dynamics of mammalian BMs, however, are poorly understood, largely due to a lack of models in which core BM components are endogenously labelled. Here, we describe the mTurquoise2-Col4a1 mouse, in which we fluorescently tag collagen IV, the main component of BMs. Using an innovative Planar-Sagittal live imaging technique to visualize the BM of developing skin, we directly observe BM deformation during hair follicle budding and basal progenitor cell divisions. The BM’s inherent pliability enables dividing cells to remain attached to and deform the BM, rather than lose adhesion as generally thought. Using FRAP, we show BM collagen IV is extremely stable, even during periods of rapid epidermal growth. These findings demonstrate the utility of the mTurq2-Col4a1 mouse to shed new light on mammalian BM developmental dynamics.
Contact-FP: A Dimerization-Dependent Fluorescent Protein Toolkit for Visualizing Membrane Contact Site Dynamics

Membrane contact sites (MCSs) are sites of close apposition between two organelles used to exchange ions, lipids, and information. Cells respond to changing environmental or developmental conditions by modulating the number, extent, or duration of MCSs. Because of their small size and dynamic nature, tools to study the dynamics of MCSs in live cells have been limited. Dimerization-dependent fluorescent proteins (ddFPs) targeted to organelle membranes are an ideal tool for studying MCS dynamics because they reversibly interact to fluoresce specifically at the interface between two organelles. Here, we build on previous work using ddFPs as sensors to visualize the morphology and dynamics of MCSs. We engineered a suite of ddFPs called Contact-FP that targets ddFP monomers to lipid droplets (LDs), the endoplasmic reticulum (ER), mitochondria, peroxisomes, lysosomes, plasma membrane, caveolae, and the cytoplasm. We show that these probes correctly localize to their target organelles. Using LDs as a test case, we demonstrate that Contact-FP pairs specifically localize to the interface between two target organelles. Titration of LD-mitochondria ddFPs revealed that these sensors can be used at high concentrations to drive MCSs or can be titrated down to minimally perturb and visualize endogenous MCSs. We show that Contact-FP probes can be used to: (1) visualize LD-mitochondria MCS dynamics, (2) observe changes in LD-mitochondria MCS dynamics upon overexpression of PLIN5, a known LD-mitochondrial tether, and (3) visualize two MCSs that share one organelle simultaneously (e.g., LD-mitochondria and LD-ER MCSs). Contact-FP probes can be optimized to visualize MCSs between any pair of organelles represented in the toolkit.