This study explored mental workload recognition methods for carrier-based aircraft pilots utilising multiple sensor physiological signal fusion and portable devices. A simulation carrier-based aircraft flight experiment was designed, and subjective mental workload scores and electroencephalogram (EEG) and photoplethysmogram (PPG) signals from six pilot cadets were collected using NASA Task Load Index (NASA-TLX) and portable devices. The subjective scores of the pilots in three flight phases were used to label the data into three mental workload levels. Features from the physiological signals were extracted, and the interrelations between mental workload and physiological indicators were evaluated. Machine learning and deep learning algorithms were used to classify the pilots’ mental workload. The performances of the single-modal method and multimodal fusion methods were investigated. The results showed that the multimodal fusion methods outperformed the single-modal methods, achieving higher accuracy, precision, recall and F1 score. Among all the classifiers, the random forest classifier with feature-level fusion obtained the best results, with an accuracy of 97.69%, precision of 98.08%, recall of 96.98% and F1 score of 97.44%. The findings of this study demonstrate the effectiveness and feasibility of the proposed method, offering insights into mental workload management and the enhancement of flight safety for carrier-based aircraft pilots.

This study presents the black hole accretion history (BHAH) of obscured active galactic nuclei (AGNs) identified from the JWST CEERS survey by Chien et al. (2024) using mid-infrared (MIR) SED fitting. We compute black hole accretion rates (BHARs) to estimate the black hole accretion density (BHAD), ρLdisk, across 0 < z < 4.25. MIR luminosity functions (LFs) are also constructed for these sources, modeled with modified Schechter and double power law forms, and corresponding BHAD, ρLF, is derived by integrating the LFs and multiplying by the luminosity. Both ρLF extend to luminosities as lowas 107 L⊙, two orders of magnitude fainter than pre-JWST studies. Our results show that BHAD peaks between redshifts 1 and 3, with the peak varying by method and model, z ≃ 1 - 2 for ρLdisk and the double power law, and z ≃ 2 - 3 for the modified Schechter function. A scenario where AGN activity peaks before cosmic star formation would challenge existing black hole formation theories, but our present study, based on early JWST observations, provides an initial exploration of this possibility. At z ∼ 3, ρLF appears higher than X-ray estimates, suggesting that MIR observations are more effective in detecting obscured AGNs missed by X-ray observations. However, given the overlapping error bars, this difference remains within the uncertainties and requires confirmation with larger samples. These findings highlight the potential of JWST surveys to enhance the understanding of co-evolution between galaxies and AGNs.

Temporal variability and methodological differences in data normalization, among other factors, complicate effective trend analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wastewater surveillance data and its alignment with coronavirus disease 2019 (COVID-19) clinical outcomes. As there is no consensus approach for these analyses yet, this study explored the use of piecewise linear trend analysis (joinpoint regression) to identify significant trends and trend turning points in SARS-CoV-2 RNA wastewater concentrations (normalized and non-normalized) and corresponding COVID-19 case rates in the greater Las Vegas metropolitan area (Nevada, USA) from mid-2020 to April 2023. The analysis period was stratified into three distinct phases based on temporal changes in testing protocols, vaccination availability, SARS-CoV-2 variant prevalence, and public health interventions. While other statistical methodologies may require fewer parameter specifications, joinpoint regression provided an interpretable framework for characterization and comparison of trends and trend turning points, revealing sewershed-specific variations in trend magnitude and timing that also aligned with known variant-driven waves. Week-level trend agreement corroborated previous findings demonstrating a close relationship between SARS-CoV-2 wastewater surveillance data and COVID-19 outcomes. These findings guide future applications of advanced statistical methodologies and support the continued integration of wastewater-based epidemiology as a complementary approach to traditional COVID-19 surveillance systems.

The outer solar system is theoretically predicted to harbour an undiscovered planet, often referred to as Planet Nine. Simulations suggest that its gravitational influence could explain the unusual clustering of minor bodies in the Kuiper Belt. However, no observational evidence for Planet Nine has been found so far, as its predicted orbit lies far beyond Neptune, where it reflects only a faint amount of Sunlight. This work aims to find Planet Nine candidates by taking advantage of two far-infrared all-sky surveys, which are IRAS and AKARI. The epochs of these two surveys were separated by 23 years, which is large enough to detect Planet Nine’s ∼ 3′/year orbital motion. We use a dedicated AKARI Far-Infrared point source list for the purpose of our Planet Nine search — AKARI-FIS Monthly Unconfirmed Source List (AKARI-MUSL), which includes sources detected repeatedly only in hours timescale, but not after months. AKARI-MUSL is more advantageous than the AKARI Bright Source Catalogue (AKARI-BSC) for detecting moving and faint objects like Planet Nine with a twice-deeper flux detection limit. We search for objects that moved slowly between IRAS and AKARI detections given in the catalogues. First, we estimated the expected flux and orbital motion of Planet Nine by assuming its mass, distance, and effective temperature to ensure it can be detected by IRAS and AKARI, then applied the positional and flux selection criteria to narrow down the number of sources from the catalogues. Next, we produced all possible candidate pairs including one IRAS source and one AKARI source whose angular separations were limited between 42′ and 69.6′, corresponding to the heliocentric distance range of 500 – 700 AU and the mass range of 7 – 17M⊕. There are 13 candidate pairs obtained after the selection criteria. After image inspection, we found one good candidate, of which the IRAS source is absent from the same coordinate in the AKARI image after 23 years and vice versa. However, AKARI and IRAS detections are not enough to determine the full orbit of this candidate. This issue leads to the need for follow-up observations, which will determine the Keplerian motion of our Planet Nine candidate.

An unusual orbital element clustering of Kuiper belt objects (KBOs) has been observed. The most promising dynamic solution is the presence of a giant planet in the outer Solar system, Planet Nine. However, due to its extreme distance, intensive searches in optical have not been successful. We aim to find Planet Nine in the far-infrared, where it has the peak of the black body radiation, using the most sensitive all-sky far-infrared survey to date, AKARI. In contrast to optical searches, where the energy of reflected sunlight decreases by $d^{4}$, thermal radiation in the infrared decreases with the square of the heliocentric distance $d^{2}$. We search for moving objects in the AKARI Single Scan Detection List. We select sources from a promising region suggested by an N-body simulation from Millholland and Laughlin 2017: $30^{\circ}\lt$ R.A. $\lt50^{\circ}$ and $-20^{\circ}\lt$ Dec. $\lt20^{\circ}$. Known sources are excluded by cross-matching AKARI sources with 9 optical and infrared catalogues. Furthermore, we select sources with small background strength to avoid sources in the cirrus. Since Planet Nine is stationary in a timescale of hours but moves on a monthly scale, our primary strategy is to select slowly moving objects that are stationary in 24 h but not in six months, using multiple single scans by AKARI. The selected slowly moving AKARI sources are scrutinised for potential contamination from cosmic rays. Our analysis reveals two possible Planet Nine candidates whose positions and flux are within the theoretical prediction ranges. These candidates warrant further investigation through follow-up observations to confirm the existence and properties of Planet Nine.

The phenomenon of focusing of microwave beams in a plasma near a turning-point caustic is discussed by exploiting the analytical solution to the Gaussian beam-tracing equations in the two-dimensional (2-D) linear-layer problem. The location of maximum beam focusing and the beam width at that location are studied in terms of the beam initial conditions. This focusing must be taken into account to interpret Doppler backscattering (DBS) measurements. We find that the filter function that characterises the scattering intensity contribution along the beam path through the plasma is inversely proportional to the beam width, predicting enhanced scattering from the beam focusing region. We show that the DBS signal enhancement for decreasing incident angles between the beam path and the density gradient is due to beam focusing and not due to forward scattering, as was originally proposed by (Gusakov et al., (Plasma Phys. Contr. Fusion, vol. 56, 2014, p. 0250092014, 2017); Plasma Phys. Rep. vol. 43(6), 2017, pp. 605–613). The analytic beam model is used to predict the measurement of the $k_y$ density-fluctuation wavenumber power spectrum via DBS, showing that, in an NSTX-inspired example, the spectral exponent of the turbulent, intermediate-to-high $k_y$ density-fluctuation spectrum might be quantitatively measurable via DBS, but not the spectral peak corresponding to the driving scale of the turbulent cascade.

Manned lunar landers must ensure astronaut safety while enhancing payload capacity. Due to traditional landers being weak in high-impact energy absorb and heavy payload capacity, a Starship-type manned lunar lander is proposed in this paper. Firstly, a comprehensive analysis was conducted on the traditional cantilever beam cushioning mechanism for manned lander. Subsequently, a 26-ton manned lander and its landing mechanism were designed, and a rigid-flexible coupling dynamic analysis was performed on the compression process of the primary and auxiliary legs. Secondly, the landing performance of the proposed Starship-type manned lunar lander was compared with the traditional 14-ton manned lander in multiple landing conditions. The results indicate that under normal conditions, the largest acceleration of the proposed 26-ton Starship-type manned lander decreases more than 13.1%. It enables a significant increase in payload capacity while mitigating impact loads under various landing conditions.

Objectives/Goals: Engaging interest holders in research is increasingly common, and guidelines include creating engagement plans. A detailed plan may be especially helpful when researchers perceive engagement as difficult or less relevant. We tested whether a study’s translational stage or an investigator’s years of research experience affect their perceptions. Methods/Study Population: Since 2019, the Tufts Clinical and Translational Science Institute Pilot Studies Program required applicants to submit plans to engage interest holders. Applicants in three cohorts responded to a survey about this requirement, including perceived difficulty developing an engagement plan, perceived relevance of engagement, and self-reported years of research experience (≤5, 6–10, and ≥10 years). Two raters assigned translational stage(s) of proposed studies: T0 (basic science), T.5 (pre-clinical to initial human studies), and T1 through T4. Separate analyses were conducted when multistage studies were coded as the earliest vs. latest stage and for individual stage vs. groups of stages (T0/T.5/T1 vs. T2/T3/T4). The Fisher’s exact statistical test was used to assess associations between variables. Results/Anticipated Results: Analyses included 67 participants. Developing an engagement plan was perceived as more difficult for studies at earlier translational stages when those studies were coded as the earliest applicable stage. This significant association held both when stages were grouped as T0/T.5/T1 and T2/T3/T4 (P  =  .03) and when analyzed as a single stage (P  =  .01); however, when studies were coded as the latest applicable stage, there were no significant associations. Similarly, when multistage studies were coded as the earliest applicable stage, engagement was perceived as less relevant for early-stage studies when grouped (P  =  .04), but not for individual stages or when studies were coded as the latest applicable stage. No significant association between years of research experience and perceived difficulty was identified. Discussion/Significance of Impact: Results show that investigators conducting early-stage research perceive more difficulty engaging interest holders, aligning with prior qualitative studies. These investigators may need more evidence of the value added to early-stage studies, targeted and practical training, and funder requirements to establish a culture of engagement.

Brown dwarfs are failed stars with very low mass (13–75 Jupiter mass) and an effective temperature lower than 2 500 K. Their mass range is between Jupiter and red dwarfs. Thus, they play a key role in understanding the gap in the mass function between stars and planets. However, due to their faint nature, previous searches are inevitably limited to the solar neighbourhood (20 pc). To improve our knowledge of the low mass part of the initial stellar mass function and the star formation history of the Milky Way, it is crucial to find more distant brown dwarfs. Using James Webb Space Telescope (JWST) COSMOS-Web data, this study seeks to enhance our comprehension of the physical characteristics of brown dwarfs situated at a distance of kpc scale. The exceptional sensitivity of the JWST enables the detection of brown dwarfs that are up to 100 times more distant than those discovered in the earlier all-sky infrared surveys. The large area coverage of the JWST COSMOS-Web survey allows us to find more distant brown dwarfs than earlier JWST studies with smaller area coverages. To capture prominent water absorption features around 2.7 ${\unicode{x03BC}}$m, we apply two colour criteria, $\text{F115W}-\text{F277W}+1\lt\text{F277W}-\text{F444W}$ and $\text{F277W}-\text{F444W}\gt\,0.9$. We then select point sources by CLASS_STAR, FLUX_RADIUS, and SPREAD_MODEL criteria. Faint sources are visually checked to exclude possibly extended sources. We conduct SED fitting and MCMC simulations to determine their physical properties and associated uncertainties. Our search reveals 25 T-dwarf candidates and 2 Y-dwarf candidates, more than any previous JWST brown dwarf searches. They are located from 0.3 to 4 kpc away from the Earth. The spatial number density of 900–1 050 K dwarf is $(2.0\pm0.9) \times10^{-6}\text{ pc}^{-3}$, 1 050–1 200 K dwarf is $(1.2\pm0.7) \times10^{-6}\text{ pc}^{-3}$, and 1 200–1 350 K dwarf is $(4.4\pm1.3) \times10^{-6}\text{ pc}^{-3}$. The cumulative number count of our brown dwarf candidates is consistent with the prediction from a standard double exponential model. Three of our brown dwarf candidates were detected by HST, with transverse velocities $12\pm5$, $12\pm4$, and $17\pm6$ km s$^{-1}$. Along with earlier studies, the JWST has opened a new window of brown dwarf research in the Milky Way thick disk and halo.

Double-zero-event studies (DZS) pose a challenge for accurately estimating the overall treatment effect in meta-analysis (MA). Current approaches, such as continuity correction or omission of DZS, are commonly employed, yet these ad hoc methods can yield biased conclusions. Although the standard bivariate generalized linear mixed model (BGLMM) can accommodate DZS, it fails to address the potential systemic differences between DZS and other studies. In this article, we propose a zero-inflated bivariate generalized linear mixed model (ZIBGLMM) to tackle this issue. This two-component finite mixture model includes zero inflation for a subpopulation with negligible or extremely low risk. We develop both frequentist and Bayesian versions of ZIBGLMM and examine its performance in estimating risk ratios against the BGLMM and conventional two-stage MA that excludes DZS. Through extensive simulation studies and real-world MA case studies, we demonstrate that ZIBGLMM outperforms the BGLMM and conventional two-stage MA that excludes DZS in estimating the true effect size with substantially less bias and comparable coverage probability.

Matching-adjusted indirect comparison (MAIC) has been increasingly applied in health technology assessments (HTA). By reweighting subjects from a trial with individual participant data (IPD) to match the summary statistics of covariates in another trial with aggregate data (AgD), MAIC enables a comparison of the interventions for the AgD trial population. However, when there are imbalances in effect modifiers with different magnitudes of modification across treatments, contradictory conclusions may arise if MAIC is performed with the IPD and AgD swapped between trials. This can lead to the “MAIC paradox,” where different entities reach opposing conclusions about which treatment is more effective, despite analyzing the same data. In this paper, we use synthetic data to illustrate this paradox and emphasize the importance of clearly defining the target population in HTA submissions. Additionally, we recommend making de-identified IPD available to HTA agencies, enabling further indirect comparisons that better reflect the overall population represented by both IPD and AgD trials, as well as other relevant target populations for policy decisions. This would help ensure more accurate and consistent assessments of comparative effectiveness.

In scientific collaborations, technologies have broadened access to scarce scientific and engineering resources. While broader access is often applauded, little attention has been focused on the problem of efficient and equitable resource allocation. This paper presents laboratory experiments designed to compare different allocation mechanisms for access to joint research facilities. Specifically, we study the Vickrey-Clarke-Groves (VCG) auction, a simultaneous ascending auction (the Resource Allocation Design, RAD), and a mechanism based on submitted rankings (Knapsack). Experimental results show that RAD and VCG are both more efficient than Knapsack, while Knapsack achieves a more equal distribution of resources than RAD or VCG. The findings highlight the need for systematic exploration of allocation mechanisms within collaboratories.

Fast radio bursts (FRBs) are millisecond-duration radio waves from the Universe. Even though more than 50 physical models have been proposed, the origin and physical mechanism of FRB emissions are still unknown. The classification of FRBs is one of the primary approaches to understanding their mechanisms, but previous studies classified conventionally using only a few observational parameters, such as fluence and duration, which might be incomplete. To overcome this problem, we use an unsupervised machine-learning model, the Uniform Manifold Approximation and Projection to handle seven parameters simultaneously, including amplitude, linear temporal drift, time duration, central frequency, bandwidth, scaled energy, and fluence. We test the method for homogeneous 977 sub-bursts of FRB 20121102A detected by the Arecibo telescope. Our machine-learning analysis identified five distinct clusters, suggesting the possible existence of multiple different physical mechanisms responsible for the observed FRBs from the FRB 20121102A source. The geometry of the emission region and the propagation effect of FRB signals could also make such distinct clusters. This research will be a benchmark for future FRB classifications when dedicated radio telescopes such as the square kilometer array or Bustling Universe Radio Survey Telescope in Taiwan discover more FRBs than before.

In epidemiological investigations, pathogen genomics can provide insights and test epidemiological hypotheses that would not have been possible through traditional epidemiology. Tools to synthesize genomic analysis with other types of data are a key requirement of genomic epidemiology. We propose a new ‘phylepic’ visualization that combines a phylogenomic tree with an epidemic curve. The combination visually links the molecular time represented in the tree to the calendar time in the epidemic curve, a correspondence that is not easily represented by existing tools. Using an example derived from a foodborne bacterial outbreak, we demonstrated that the phylepic chart communicates that what appeared to be a point-source outbreak was in fact composed of cases associated with two genetically distinct clades of bacteria. We provide an R package implementing the chart. We expect that visualizations that place genomic analyses within the epidemiological context will become increasingly important for outbreak investigations and public health surveillance of infectious diseases.

Shark vertebrae and their centra (vertebral bodies) are high-performance structures able to survive millions of cycles of high amplitude strain despite lacking a repair mechanism for accumulating damage. Shark centra consist of mineralized cartilage, a biocomposite of bioapatite (bAp), and collagen, and the nanocrystalline bAp's contribution to functionality remains largely uninvestigated. Using the multiple detector energy-dispersive diffraction (EDD) system at 6-BM-B, the Advanced Photon Source, and 3D tomographic sampling, the 3D functionality of entire centra were probed. Immersion in ethanol vs phosphate-buffered saline produces only small changes in bAp d-spacing within a great hammerhead centrum. EDD mapping under in situ loading was performed an entire blue shark centrum, and 3D maps of bAp strain showed the two structural zones of the centrum, the corpus calcareum and intermedialia, contained opposite-signed strains approaching 0.5%, and application of ~8% nominal strain did not alter these strain magnitudes and their spatial distribution.