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Real-time object localization on edge devices is fundamental for numerous applications, ranging from surveillance to industrial automation. Traditional frameworks, such as object detection, segmentation, and keypoint detection, struggle in resource-constrained environments, often resulting in substantial target omissions. To address these challenges, we introduce OCDet, a lightweight Object Center Detection framework optimized for edge devices with NPUs. OCDet predicts heatmaps representing object center probabilities and extracts center points through peak identification. Unlike prior methods using fixed Gaussian distribution, we introduce Generalized Centerness (GC) to generate ground truth heatmaps from bounding box annotations, providing finer spatial details without additional manual labeling. Built on NPU-friendly Semantic FPN with MobileNetV4 backbones, OCDet models are trained by our Balanced Continuous Focal Loss (BCFL), which alleviates data imbalance and focuses training on hard negative examples for probability regression tasks. Leveraging the novel Center Alignment Score (CAS) with Hungarian matching, we demonstrate that OCDet consistently outperforms YOLO11 in object center detection, achieving up to 23% higher CAS while requiring 42% fewer parameters, 34% less computation, and 64% lower NPU latency. When compared to keypoint detection frameworks, OCDet achieves substantial CAS improvements up to 186% using identical models. By integrating GC, BCFL, and CAS, OCDet establishes a new paradigm for efficient and robust object center detection on edge devices with NPUs. The code is released at https://github.com/chen-xin-94/ocdet.

This paper presents a conceptual exploration of how Digital Learning Platforms (DLPs) can be utilized to investigate the impact of language clarity, precision, engagement, and contextual relevance on mathematics learning from word problems. Focusing on three distinct DLPs--ASSISTments/E-TRIALS, MATHia/UpGrade, and Canvas/Terracotta--we propose hypothetical studies aimed at uncovering how nuanced language modifications can enhance mathematical understanding and engagement. While these studies are illustrative in nature, they provide a blueprint for researchers interested in leveraging DLPs for empirical investigation so that future investigators gain a better understanding of the emerging infrastructure for research in DLPs and the opportunities provided by them. In highlighting three distinct implementations of the same core research question, we reveal both commonalities as well as differences in how different educational technologies might build evidence, offering a unique opportunity to advance the field of math education and other education research fields.

This paper presents a software component that generates a user interface structure for populating a domain ontology. The core of this work is an algorithm that takes an ontology and returns a structure describing the user interface. The component also provides functions for populating the ontology and editing existing individuals. Unlike previous approaches, this method can be implemented without any configuration. Additionally, it offers an easy-to-use configuration mechanism that allows irrelevant classes to be hidden and automatically populated. What distinguishes this work is that, instead of exploring the ontology using syntactic methods or queries, our algorithm employs services that implement description logic inference mechanisms. This work illustrates the proposed approach using the well-known wine ontology.

We consider the design of cascaded diffractive optical elements (DOEs) for generating specified intensity distributions for several incident beams with different wavelengths. For each incident beam with a given wavelength, the cascaded DOE forms a different specified intensity distribution. The problem of DOE design is formulated as the problem of minimizing a functional that depends on the functions of diffractive microrelief height of the cascaded DOE and represents the deviations of the intensity distributions generated at the operating wavelengths from the specified ones. Explicit expressions are obtained for the derivatives of the functional, and on this basis, a gradient method for calculating a cascaded DOE is formulated. The proposed gradient method is used for the calculation of cascaded DOEs focusing radiation of three different wavelengths into different areas. In particular, the calculation of a cascaded DOE generating a complex color image of parrots is considered. The presented numerical simulation results demonstrate high performance of the proposed method., Comment: 11 pages, 7 figures

We consider the problem of designing a diffractive neural network (DNN) consisting of a set of sequentially placed phase diffractive optical elements (DOEs) and intended for the optical solution of several given classification problems at different operating wavelengths, so that each classification problem is solved at the corresponding wavelength. The problem of calculating the DNN is formulated as the problem of minimizing a functional that depends on the functions of the diffractive microrelief height of the DOEs constituting the DNN and represents the error in solving the given classification problems at the operating wavelengths. We obtain explicit and compact expressions for the derivatives of this functional and, using them, formulate a gradient method for the DNN calculation. Using this method, we design DNNs for solving the following three classification problems at three different wavelengths: the problem of classifying handwritten digits from the MNIST database, the problem of classifying fashion products from the Fashion MNIST database, and the problem of classifying ten handwritten letters from the EMNIST database. The presented simulation results of the designed DNNs demonstrate high performance of the proposed method., Comment: 19 pages, 11 figures

A wide range of practically important problems is nowadays efficiently solved using artificial neural networks. This gave momentum to intensive development of their optical implementations, among which, the so-called diffractive neural networks (DNNs) constituted by a set of phase diffractive optical elements (DOEs) attract considerable research interest. In the practical implementation of DNNs, one of the standing problems is the requirement for high positioning accuracy of the DOEs. In this work, we address this problem and propose a method for the design of DNNs for image classification, which takes into account the positioning errors (transverse shifts) of the DNN elements. In the method, the error of solving the classification problem is represented by a functional depending on the phase functions of the DOEs and on random vectors describing their transverse shifts. The mathematical expectation of this functional is used as an error functional in the gradient method for calculating the DNN taking into account the transverse shifts of the DOEs. It is shown that the calculation of the derivatives of this functional corresponds to the DNN training method, in which the DOEs have random transverse shifts. Using the proposed gradient method, DNNs are designed that are robust to transverse shifts of the DOEs and enable solving the problem of classifying handwritten digits at a visible wavelength. Numerical simulations demonstrate good performance of the designed DNNs at transverse shifts of up to 17 wavelengths., Comment: 16 pages, 7 figures, 2 tables

We present an educational escape room in physics (ERP) covering the main disciplines of physics as taught in the education of neighboring sciences, in this case veterinary medicine, extended by a European board game system of victory points (VP). The puzzles in physics are mandatory to master the ERP requiring to be solved in a sequential order. In our study, we show the growth of knowledge by knowledge-transfer cards separated into disciplines of physics as demonstrated by critical exemplary questions of test groups. Tactical secondary puzzles, the so called \textit{Eurogame puzzles} (EPs), are able to be solved in parallel in any arbitrary and independent sequence, allowing a self-adjusted challenge autolevelled by the students by choice. The motivation is improved by a scoring list to solve, at least, a few optional EPs as additional game-like adventure and challenge collecting VP. A second part of the study demonstrates the attraction of the introduced European board game concept as an important tool for gamificiation and open-by-choice EPs not being necessarily related to physics directly. EPs are able to smooth the contrast of playing games and learning, providing an additional bridge to overcome the fear of physics. A strong advantage is the flexibility of the European board concept, choosing from a broad range of optional EPs to fascinate and motivate students taking into account individual preferences improving escape rooms by decision-making skills. The concept is able be applied to every escape room independent of the taught subject or topic., Comment: 20 pages, 9 figures

This vision paper introduces a pioneering data lake architecture designed to meet Life \& Earth sciences' burgeoning data management needs. As the data landscape evolves, the imperative to navigate and maximize scientific opportunities has never been greater. Our vision paper outlines a strategic approach to unify and integrate diverse datasets, aiming to cultivate a collaborative space conducive to scientific discovery.The core of the design and construction of a data lake is the development of formal and semi-automatic tools, enabling the meticulous curation of quantitative and qualitative data from experiments. Our unique ''research-in-the-loop'' methodology ensures that scientists across various disciplines are integrally involved in the curation process, combining automated, mathematical, and manual tasks to address complex problems, from seismic detection to biodiversity studies. By fostering reproducibility and applicability of research, our approach enhances the integrity and impact of scientific experiments. This initiative is set to improve data management practices, strengthening the capacity of Life \& Earth sciences to solve some of our time's most critical environmental and biological challenges.

This paper proposes a Researcher-in-the-Loop (RITL) guided content curation approach for quanti-qualitative research methods that uses a version control system based on consensus. The paper introduces a workflow for quanti-qualitative research processes that produces and consumes content versions through collaborative phases validated through consensus protocols performed by research teams. We argue that content versioning is a critical component that supports the research process's reproducibility, traceability, and rationale. We propose a curation framework that provides methods, protocols, and tools for supporting the RITL approach to managing the content produced by quanti-qualitative methods. The paper reports a validation experiment using a use case about the study on disseminating political statements in graffiti.

Detailed measurements of the spectral structure of cosmic-ray electrons and positrons from 10.6 GeV to 7.5 TeV are presented from over 7 years of observations with the CALorimetric Electron Telescope (CALET) on the International Space Station. Because of the excellent energy resolution (a few percent above 10 GeV) and the outstanding e/p separation (10$^5$), CALET provides optimal performance for a detailed search of structures in the energy spectrum. The analysis uses data up to the end of 2022, and the statistics of observed electron candidates has increased more than 3 times since the last publication in 2018. By adopting an updated boosted decision tree analysis, a sufficient proton rejection power up to 7.5 TeV is achieved, with a residual proton contamination less than 10%. The observed energy spectrum becomes gradually harder in the lower energy region from around 30 GeV, consistently with AMS-02, but from 300 to 600 GeV it is considerably softer than the spectra measured by DAMPE and Fermi-LAT. At high energies, the spectrum presents a sharp break around 1 TeV, with a spectral index change from -3.15 to -3.91, and a broken power law fitting the data in the energy range from 30 GeV to 4.8 TeV better than a single power law with 6.9 sigma significance, which is compatible with the DAMPE results. The break is consistent with the expected effects of radiation loss during the propagation from distant sources (except the highest energy bin). We have fitted the spectrum with a model consistent with the positron flux measured by AMS-02 below 1 TeV and interpreted the electron + positron spectrum with possible contributions from pulsars and nearby sources. Above 4.8 TeV, a possible contribution from known nearby supernova remnants, including Vela, is addressed by an event-by-event analysis providing a higher proton-rejection power than a purely statistical analysis., Comment: main text: 7 pages, 4 figures; supplemental material: 10 pages, 8 figures, 1 table

We present the observation of a charge-sign dependent solar modulation of galactic cosmic rays (GCRs) with the CALorimetric Electron Telescope onboard the International Space Station over 6 yr, corresponding to the positive polarity of the solar magnetic field. The observed variation of proton count rate is consistent with the neutron monitor count rate, validating our methods for determining the proton count rate. It is observed by the CALorimetric Electron Telescope that both GCR electron and proton count rates at the same average rigidity vary in anticorrelation with the tilt angle of the heliospheric current sheet, while the amplitude of the variation is significantly larger in the electron count rate than in the proton count rate. We show that this observed charge-sign dependence is reproduced by a numerical ``drift model'' of the GCR transport in the heliosphere. This is a clear signature of the drift effect on the long-term solar modulation observed with a single detector., Comment: main text: 6 pages, 3 figures, supplemental material: 8 pages, 3 figures, 1 table

We present the results of a direct measurement of the cosmic-ray helium spectrum with the CALET instrument in operation on the International Space Station since 2015. The observation period covered by this analysis spans from October 13, 2015 to April 30, 2022 (2392 days). The very wide dynamic range of CALET allowed to collect helium data over a large energy interval, from ~40 GeV to ~250 TeV, for the first time with a single instrument in Low Earth Orbit. The measured spectrum shows evidence of a deviation of the flux from a single power-law by more than 8$\sigma$ with a progressive spectral hardening from a few hundred GeV to a few tens of TeV. This result is consistent with the data reported by space instruments including PAMELA, AMS-02, DAMPE and balloon instruments including CREAM. At higher energy we report the onset of a softening of the helium spectrum around 30 TeV (total kinetic energy). Though affected by large uncertainties in the highest energy bins, the observation of a flux reduction turns out to be consistent with the most recent results of DAMPE. A Double Broken Power Law (DBPL) is found to fit simultaneously both spectral features: the hardening (at lower energy) and the softening (at higher energy). A measurement of the proton to helium flux ratio in the energy range from 60 GeV/n to about 60 TeV/n is also presented, using the CALET proton flux recently updated with higher statistics.

We present the measurement of the energy dependence of the boron flux in cosmic rays and its ratio to the carbon flux \textcolor{black}{in an energy interval from 8.4 GeV$/n$ to 3.8 TeV$/n$} based on the data collected by the CALorimetric Electron Telescope (CALET) during $\sim 6.4$ years of operation on the International Space Station. An update of the energy spectrum of carbon is also presented with an increase in statistics over our previous measurement. The observed boron flux shows a spectral hardening at the same transition energy $E_0 \sim 200$ GeV$/n$ of the C spectrum, though B and C fluxes have different energy dependences. The spectral index of the B spectrum is found to be $\gamma = -3.047\pm0.024$ in the interval $25 < E < 200$ GeV$/n$. The B spectrum hardens by $\Delta \gamma_B=0.25\pm0.12$, while the best fit value for the spectral variation of C is $\Delta \gamma_C=0.19\pm0.03$. The B/C flux ratio is compatible with a hardening of $0.09\pm0.05$, though a single power-law energy dependence cannot be ruled out given the current statistical uncertainties. A break in the B/C ratio energy dependence would support the recent AMS-02 observations that secondary cosmic rays exhibit a stronger hardening than primary ones. We also perform a fit to the B/C ratio with a leaky-box model of the cosmic-ray propagation in the Galaxy in order to probe a possible residual value $\lambda_0$ of the mean escape path length $\lambda$ at high energy. We find that our B/C data are compatible with a non-zero value of $\lambda_0$, which can be interpreted as the column density of matter that cosmic rays cross within the acceleration region., Comment: main text: 7 pages, 3 figures; supplemental material: 13 pages, 8 figures, 3 tables

The efficient control of a large number of qubits is one of most challenging aspects for practical quantum computing. Current approaches in solid-state quantum technology are based on brute-force methods, where each and every qubit requires at least one unique control line, an approach that will become unsustainable when scaling to the required millions of qubits. Here, inspired by random access architectures in classical electronics, we introduce the shared control of semiconductor quantum dots to efficiently operate a two-dimensional crossbar array in planar germanium. We tune the entire array, comprising 16 quantum dots, to the few-hole regime and, to isolate an unpaired spin per dot, we confine an odd number of holes in each site. Moving forward, we establish a method for the selective control of the quantum dots interdot coupling and achieve a tunnel coupling tunability over more than 10 GHz. The operation of a quantum electronic device with fewer control terminals than tunable experimental parameters represents a compelling step forward in the construction of scalable quantum technology., Comment: 33 pages including supplementary information

A precise measurement of the cosmic-ray proton spectrum with the Calorimetric Electron Telescope (CALET) is presented in the energy interval from 50 GeV to 60 TeV, and the observation of a softening of the spectrum above 10 TeV is reported. The analysis is based on the data collected during $\sim$6.2 years of smooth operations aboard the International Space Station and covers a broader energy range with respect to the previous proton flux measurement by CALET, with an increase of the available statistics by a factor of $\sim$2.2. Above a few hundred GeV we confirm our previous observation of a progressive spectral hardening with a higher significance (more than 20 sigma). In the multi-TeV region we observe a second spectral feature with a softening around 10 TeV and a spectral index change from =2.6 to -2.9 consistently, within the errors, with the shape of the spectrum reported by DAMPE. We apply a simultaneous fit of the proton differential spectrum which well reproduces the gradual change of the spectral index encompassing the lower energy power-law regime and the two spectral features observed at higher energies., Comment: main text: 8 pages, 5 figures, supplemental material: 9 pages, 7 figures, 1 table, marked as a PRL Editor's Suggestion

Position detection of hydraulic cylinder pistons is crucial for numerous industrial automation applications. A typical traditional method is to excite electromagnetic waves in the cylinder structure and analytically solve the piston position based on the scattering parameters measured by a sensor. The core of this approach is a physical model that outlines the relationship between the measured scattering parameters and the targeted piston position. However, this physical model has shortcomings in accuracy and adaptability, especially in extreme conditions. To address these limitations, we propose machine learning and deep learning-based methods to learn the relationship directly in a data-driven manner. As a result, all deep learning models in this paper consistently outperform the physical one by a large margin. We further deliberate on the choice of models based on domain knowledge and provide in-depth analyses combining model performance with real-world physical characteristics. Specifically, we use Convolutional Neural Network (CNN) to discover local interactions of input among adjacent frequencies, apply Complex-Valued Neural Network (CVNN) to exploit the complex-valued nature of electromagnetic scattering parameters, and introduce a novel technique named Frequency Encoding to add weighted frequency information to the model input. The combination of these techniques results in our best-performing model, a complex-valued CNN with Frequency Encoding, which exhibits substantial improvement in accuracy with an error reduction of 1/12 compared to the traditional physical model., Comment: 19 pages, 10 figures

The CALorimetric Electron Telescope (CALET) on the International Space Station (ISS) consists of a high-energy cosmic ray CALorimeter (CAL) and a lower-energy CALET Gamma ray Burst Monitor (CGBM). CAL is sensitive to electrons up to 20 TeV, cosmic ray nuclei from Z = 1 through Z $\sim$ 40, and gamma rays over the range 1 GeV - 10 TeV. CGBM observes gamma rays from 7 keV to 20 MeV. The combined CAL-CGBM instrument has conducted a search for gamma ray bursts (GRBs) since Oct. 2015. We report here on the results of a search for X-ray/gamma ray counterparts to gravitational wave events reported during the LIGO/Virgo observing run O3. No events have been detected that pass all acceptance criteria. We describe the components, performance, and triggering algorithms of the CGBM - the two Hard X-ray Monitors (HXM) consisting of LaBr$_{3}$(Ce) scintillators sensitive to 7 keV to 1 MeV gamma rays and a Soft Gamma ray Monitor (SGM) BGO scintillator sensitive to 40 keV to 20 MeV - and the high-energy CAL consisting of a CHarge-Detection module (CHD), IMaging Calorimeter (IMC), and fully active Total Absorption Calorimeter (TASC). The analysis procedure is described and upper limits to the time-averaged fluxes are presented., Comment: 27 pages, 10 figures. Accepted for publication in ApJ

The relative abundance of cosmic ray nickel nuclei with respect to iron is by far larger than for all other trans-iron elements, therefore it provides a favorable opportunity for a low background measurement of its spectrum. Since nickel, as well as iron, is one of the most stable nuclei, the nickel energy spectrum and its relative abundance with respect to iron provide important information to estimate the abundances at the cosmic ray source and to model the Galactic propagation of heavy nuclei. However, only a few direct measurements of cosmic-ray nickel at energy larger than $ \sim$ 3 GeV/n are available at present in the literature and they are affected by strong limitations in both energy reach and statistics. In this paper we present a measurement of the differential energy spectrum of nickel in the energy range from 8.8 to 240 GeV/n, carried out with unprecedented precision by the Calorimetric Electron Telescope (CALET) in operation on the International Space Station since 2015. The CALET instrument can identify individual nuclear species via a measurement of their electric charge with a dynamic range extending far beyond iron (up to atomic number $ Z $ = 40). The particle's energy is measured by a homogeneous calorimeter (1.2 proton interaction lengths, 27 radiation lengths) preceded by a thin imaging section (3 radiation lengths) providing tracking and energy sampling. This paper follows our previous measurement of the iron spectrum [O. Adriani et al., Phys. Rev. Lett. 126, 241101 (2021).], and it extends our investigation on the energy dependence of the spectral index of heavy elements. It reports the analysis of nickel data collected from November 2015 to May 2021 and a detailed assessment of the systematic uncertainties. In the region from 20 to 240 GeV$ /n $ our present data are compatible within the errors with a single power law with spectral index $ -2.51 \pm 0.07 $., Comment: main text: 8 pages, 4 figures; supplemental material: 8 pages, 9 figures, 1 table. arXiv admin note: text overlap with arXiv:2106.08036

This report examines the meaning and impact of the digital divide -- the gap between those who can and cannot access the Internet -- on college students during the COVID-19 emergency shift to remote learning. The assessment is based on several national surveys conducted in the spring or summer of 2020, as well as results from a large-scale survey the authors conducted at Indiana University and The Ohio State University during the same time period. Key findings reveal the prevalence of inadequate technology, the relationship between inadequate technology and student success, and college and state approaches to supporting students with inadequate technology during the emergency transition. [At Indiana University, this research was sponsored by Schmidt Futures and by the Office of the Vice President for Research at Indiana University. At Ohio State, this research was supported by the Office of Student Academic Success, the Office of Student Life, and the Drake Institute for Teaching and Learning.]

Focusing on the electron and positron spectrum measured with CALET, which shows characteristic structures, we calculate flux contributions of cosmic rays escaped from supernova remnants, which were randomly born. We adopt a Monte Carlo method to take into account the stochastic property of births of nearby sources. We find that without a complicated energy dependence of the diffusion coefficient, simple power-law diffusion coefficients can produce spectra similar to the CALET spectrum even with a dispersion in the injection index. The positron component measured with AMS-02 is consistent with a bump-like structure around 300 GeV in the CALET spectrum. One to three nearby supernovae can contribute up to a few tens of percent of the CALET flux at 2--4 TeV, ten or more unknown and distant ($\gtrsim 500$ pc) supernovae account for the remaining several tens of percent of the flux. The CALET spectrum, showing a sharp drop at $\sim 1$ TeV, allows for a contribution of cosmic rays from an extraordinary event which occured $\sim 400$ kyr ago. This type of event releases electrons/positrons with a total energy more than 10 times the average energy for usual supernovae, and its occurrence rate is lower than $1/300$ of the usual supernova rate., Comment: 10 pages, 10 figures

For researchers seeking to improve education, a common goal is to identify teaching practices that have causal benefits in classroom settings. To test whether an instructional practice exerts a causal influence on an outcome measure, the most straightforward and compelling method is to conduct an experiment. While experimentation is common in laboratory studies of learning, experimentation is increasingly rare in classroom settings, and to date, researchers have argued it is prohibitively expensive and difficult to conduct experiments on education in situ. To address this challenge, we present Terracotta (Tool for Education Research with RAndomized COnTrolled TriAls), an open-source web application that integrates with a learning management system to provide a comprehensive experimental research platform within an online class site. Terracotta automates randomization, informed consent, experimental manipulation of different versions of learning activities, and export of de-identified research data. Here we describe these features, and the results of a live classroom demonstration study using Terracotta, a preregistered replication of McDaniel et al. ("Journal of Applied Research in Memory and Cognition," 1(1), 18-26, 2012). Using Terracotta, we experimentally manipulated online review assignments so that consenting students alternated, on a weekly basis, between taking multiple-choice quizzes (retrieval practice) and reading answers to these quizzes (restudy). Students' performance on subsequent exams was significantly improved for items that had been in retrieval practice review assignments. This successful replication demonstrates that Terracotta can be used to experimentally manipulate consequential aspects of students' experiences in education settings. [This is online version of an article published in "Behavior Research Methods."]