ORCID

Attenuation bias—the systematic underestimation of regression coefficients due to measurement errors in input variables—affects astronomical data-driven models. For linear regression, this problem was solved by treating the true input values as latent variables to be estimated alongside model parameters. In this paper, we show that neural networks suffer from the same attenuation bias and that the latent variable solution generalizes directly to neural networks. We introduce LatentNN, a method that jointly optimizes network parameters and latent input values by maximizing the joint likelihood of observing both inputs and outputs. We demonstrate the correction on one-dimensional regression, multivariate inputs with correlated features, and stellar spectroscopy applications. LatentNN reduces attenuation bias across a range of signal-to-noise ratios where standard neural networks show large bias. This provides a framework for improved neural network inference in the low signal-to-noise regime characteristic of astronomical data. This bias correction is most effective when measurement errors are less than roughly half the intrinsic data range; in the regime of very low signal-to-noise and few informative features. Code is available at https://github.com/tingyuansen/LatentNN.

In the flash-grab effect, an object flashed on a moving background appears to be shifted in the direction of the motion. The same background motion also distorts the flashed object's perceived shape. An even greater shift in the perceived location is produced by the frame effect, raising the question of whether it also produces a shape distortion. This phenomenon is important because the frame effect has been linked to perceptual stabilization during eye movements where the whole visual field acts as the frame. We found that, unlike the flash-grab case, shape was preserved for the frame effect to a much greater extent than for the flash-grab. Next, we tested the extent to which shape distortions could be predicted from the size of the shifts in position of individual shape elements. We found that observed distortions were weaker than predicted distortions for the frame effect, but stronger for the flash-grab stimulus. Finally, we examined whether the greater shape distortion for the flash-grab was due to the nature of the background motion (rotation vs. translation) or the aperture within which the background motion was presented (circular vs. rectangular). We found that both factors contributed to greater shape distortion. Our findings show that motion-induced shape distortions are not solely based on the individual position shifts of the shape elements when tested in isolation. The shape preservation for the frame effect may be achieved through engaging shape-based mechanisms tuned to the dynamics of saccadic eye movements.

As communities increasingly aim to understand and demonstrate how their data repositories support the FAIR Principles, decision-makers need tools that provide a clear, actionable snapshot. This paper introduces FIP Check, a rubric-based tool for assessing FAIR Implementation Profiles (FIPs) through a structured assessment of FAIR Enabling Resources (FERs). Built on the FIP ontology, the FIP Check brings three key innovations to FAIR assessment. First, it enables granular and practical evaluation by using a FAIR Principle-aligned rubric to assess individual FERs. Second, it measures partial FAIRness through a progressive scoring scale that captures varying levels of FAIR alignment, offering constructive, context-aware feedback rather than purely binary results. Additionally, this tool complements existing FAIR assessment tools by focusing on FERs as the units of assessment rather than on entire repositories or datasets. Third, it ensures transparent and inspectable balance by embedding expert-informed assessments within a standardized rubric and making all scoring decisions directly visible. FIP Check was piloted across seven biomedical data repositories, testing its utility in identifying strengths and actionable gaps, and supporting more informed FAIR improvement efforts. It enables communities to assess their current practices and plan targeted enhancements. By providing detailed insights into how individual FERs contribute to FIP’s FAIR alignment, the FIP Check transforms the FAIR Principles from abstract ideals into practical guidance that support strategic alignment, foster shared understanding, and encourage repository owners to see their resources not only as providers of data, but as infrastructure components.

El estudio evalúa la relación entre sostenibilidad (GRI100–400), equidad de género y desempeño financiero en diez empresas chilenas listadas (2020–2023). Mediante regresiones de panel (efectos fijos, aleatorios y PCSE) sobre MN, ROA y ROE, se halló una débil asociación positiva de GRI200 con el margen neto y de la presencia femenina en directorios con la rentabilidad; los demás indicadores presentan efectos heterogéneos según modelo y métrica. Concluimos resaltando la pertinencia de políticas corporativas inclusivas y transparentes.

Real-time traffic congestion is a challenging problem in smartcities. An Intelligent Transportation System (ITS) is a big data application integrating sensor hardware and network technologies, which can intelligently capture traffic information, efficiently transform data into knowledge, and organize and manage transportation resources. Urban Traffic Control (UTC) is a critical component of ITS, analyzing real-time traffic information and coordinating traffic signal timing plans to optimize traffic network performance and improve vehicle travel speeds. However, traditional UTC based on centralized architecture would be challenged in data transmission, architecture malfunctions, system bottlenecks, etc. As a solution, the multi-Agent based RTC (ATC) with smart intersections is proposed. Additionally, more comprehensive traffic data can be captured with advanced detection techniques, and Regional Traffic Control (RTC) systems can be designed with advanced optimal control algorithms. Digital Banking (DB) Infrastructures powered with AI can be trained on historical data to simulate human understanding of patterns and trends when leveraging custom models tuned to understand banking transactions. Integrating artificial intelligence (AI) and automation into the digital banking infrastructure can result in a stable pipeline implementation of sorting transactions data for anomalies per the bank thresholds. Moreover, with the integration of AI systems, captured data can be analysed to study the traffic characteristics of the bank and determine how efficiently it is working. AI can also be used to examine this data, identify problematic data, perform risk prediction, timely tracking, and further determine whether it fits the standards of bank transactions. AI can warn of difficulties in bank transactions. When an unauthorised transaction is detected, that transaction can be prohibited in real-time. Furthermore, it can help to significantly increase banks' risk management levels, improved efficiency and a near-zero error output requirement of regular activity.

Abstract The new minerals auropolybasite, ideally Ag15AuSb2S11, and auropearceite, ideally Ag15AuAs2S11, were found at the Šibeničný vrch near Nová Baňa in Slovakia. They were found as anhedral grains up to 0.2 mm in size, usually rimmed by acanthite. Both new minerals are associated with acanthite, argentopolybasite, argentopearceite, pyrargyrite, proustite, stephanite, selenostephanite, rozhdestvenskayaite-(Zn), zvěstovite-(Zn), zvěstovite-(Fe), naumannite, Au-Ag alloys, uytenbogaardtite, iodargyrite, and bromargyrite. They are dark grey to black, opaque, with a black streak and metallic luster. The Mohs hardness is ∼3. They are brittle with no observable cleavage and with a conchoidal fracture. The calculated densities are 6.622 g/cm3 for auropolybasite and 6.606 g/cm3 for auropearceite. In reflected light, auropolybasite and auropearceite are gray with a bluish tint, no observable bireflectance, and very weak pleochroism. They show moderate anisotropy in crossed polars with weak greenish and green-blue tints. The reflectance values for wavelengths recommended by the Commission on Ore Mineralogy of the IMA are (Rmin/Rmax, %): 33.5/31.6 (470 nm), 32.9/31.1 (546 nm), 32.1/30.6 (589 nm), and 30.2/29.3 (650 nm) for auropolybasite and 30.6/29.8 (470 nm), 30.3/29.2 (546 nm), 29.7/28.7 (589 nm), and 28.1/27.4 (650 nm) for auropearceite. The empirical formula (based on 29 apfu) for auropolybasite is Ag15.27Au0.84(Sb1.51As0.46)Σ1.97(S10.55Se0.30Cl0.06)Σ10.91 and that for auropearceite is Ag15.84Au0.88(As1.33Sb0.44)Σ1.76(S10.46Se0.05Te0.01)Σ10.52. The ideal end-member formulas are Ag15AuSb2S11 for auropolybasite and Ag15AuAs2S11 for auropearceite. Their symmetry is trigonal, space group P321. Latice parameters for auropolybasite are: a = 15.1091(5) Å, c = 12.1518(5) Å, V = 2402.42(15) Å3, Z = 4, and those for auropearceite are: a = 14.995(3) Å, c = 12.115(2) Å, V = 2359.3(8) Å3, Z = 4. Crystal-structure analysis of auropolybasite confirmed that its atomic arrangement is isotypic to that of the other members of the polybasite group and it is isostructural with auropearceite. These minerals formed in the waning stages of epithermal systems, where reduced, S-rich, low-salinity fluids transported Au, Ag, Sb, and As as thiocomplexes. These fluids were unable to transport Cu, Pb, and Zn, thus explaining the chemical composition of these minerals and the entire mineral assemblage.

Periods of civil unrest pose significant operational and security challenges to those seeking to provide emergency care to patients. For emergency departments (EDs) and their staff, effectively operating in this potentially hostile environment requires careful planning. Understanding the challenges posed during periods of civil unrest is paramount for emergency medicine staff and emergency planners to ensure continuity of care. To provide ED and hospital staff with an understanding of the challenges faced during periods of civil unrest and to offer recommendations to maintain safety and operational viability. Preplanning before any anticipated civil unrest is essential to a well-coordinated response. During the period of civil unrest, maintaining effective communication between command elements and clinicians in the ED is vital to ensure bidirectional sharing of information. Deviations from normal operating procedures should be expected and relayed to clinicians as quickly as possible. Similarly, staff may need to shelter in place or relocate to a more secure area within the hospital. Civil unrest is highly dynamic, and hospital leadership must follow developments closely to protect staff and facilities. This review provides ED and hospital staff with an understanding of the significant challenges during periods of civil unrest.

Intensity interferometry (II) offers a powerful means to observe stellar objects with a high resolution. In this work, we demonstrate that II can also probe internal stellar kinematics by revealing a time-asymmetric Hanbury Brown and Twiss (HBT) effect, causing a measurable shift in the temporal correlation peak away from zero delay. We develop numerical models to simulate this effect for two distinct astrophysical scenarios: an emission-line circumstellar disk and an absorption-line binary system. Our simulations reveal a clear sensitivity of this temporal asymmetry to the system’s inclination angle, velocity symmetry, and internal dynamics. This suggests that, with sufficiently high time resolution, II can be used to extract quantitative information about internal kinematics, offering a new observational window on stellar dynamics.

There are no consensus guidelines demonstrating that early venous thromboembolism prophylaxis (VTEP) is safe in patients with traumatic brain injury (TBI) who undergo neurosurgical interventions. We hypothesized that early initiation of VTEP in patients with TBI would decrease the incidence of venous thromboembolism (VTE) and intracranial hemorrhage expansion (ICHE). This was a retrospective single-center study of adult patients with TBI who underwent neurosurgical intervention from 2012 to 2023 at a level 1 trauma center. Early (72 hours or less) and late (more than 72 hours) VTEP initiation after neurosurgery were compared. Outcomes were VTE, ICHE, and mortality. A Cox proportional hazard regression was completed comparing late and early and VTEP vs No VTEP groups. Of 845 patients, 618 received VTEP, 180 received VTEP within 72 hours and 438 received VTEP more than 72 hours after neurosurgical intervention. There were no differences in age, race, sex, Abbreviated Injury Scale head score, or comorbidities. There was no difference in VTE (hazard ratio [HR] 1.38, 95% CI 0.39 to 4.84, p = 0.62). The Late cohort had lower odds of ICHE (HR 0.53, 95% CI 0.28 to 0.99, p = 0.05) and mortality (HR 0.04, 95% CI 0.24 to 0.80, p = 0.007). Increased risk of VTE of 50% with each missed dose was seen up to 3 missed doses (odds ratio 1.52, 95% CI 0.64 to 3.40, p = 0.31). Although VTE rates were similar between early and late chemoprophylaxis initiation in patients with TBI who underwent neurosurgical intervention, the late cohort had lower mortality and risk of ICHE. Missed doses had an increased risk of VTE.