The annual nitrogen (N) production from livestock manure is comparable to that of synthetic N fertilizers used globally in croplands. Despite its recognized value for crop nutrition, current inefficient manure application contributes ∼10% to global anthropogenic greenhouse gas (GHG) emissions. Addressing this challenge, we investigated semiliquid manure slurry, which in some regions provides up to half of the N supplied to crops. Using meta-analysis and machine learning methodology, we predicted agricultural and environmental impacts of slurry use in different climate scenarios based on 1952 paired observations in global field experiments. Current suboptimal uses of slurry generate 7% (0.1 Tg N) higher nitrous oxide emissions than synthetic fertilizers. Under future warming scenarios and without optimization, these emissions are projected to increase by an additional 3-5% (∼0.2 Tg N) and total noncarbon dioxide (CO2) GHG emissions by 30% (600 Tg CO2 equivalents year-1). Current evidence identifies the combination of subsurface slurry application and nitrification inhibitors as an effective optimization strategy. This strategy may reduce non-CO2 GHG emissions by 30%, equivalent to an 8% reduction in the total agricultural GHG emissions. We estimated that this optimization, combined with a favorable slurry N-to-total N ratio, has the technological potential to increase global cereal production by up to 20% and restore organic carbon stocks in topsoil by 5% (3400 Tg carbon). Thus, optimizing slurry use should be a priority, as it contributes to climate change mitigation, food security, and soil fertility.

Most of the intracyclic variability in the large-scale solar magnetic field comes from the equatorial dipole component of the solar magnetic field. The equatorial dipole component is highly sensitive to the longitude distribution of the active regions. We quantify the effect of individual active regions on the large-scale solar magnetic field of the solar cycle 24. We study the effect of the longitude distribution of active regions on the strength of the large-scale dipole component. We used a surface flux transport (SFT) model to simulate the evolution of individual active regions and quantified their effect on the large-scale magnetic field using the recently developed vector sum method. We took advantage of the longitudinal translational invariance of the SFT model and compared the observed solar cycle 24 to the 10 000 simulations of the solar cycle 24 using randomized longitudinal source locations, but otherwise identical flux emergence. We find that taking into account both the axial and equatorial components of the vector sum characterizing the global solar magnetic field sets better constraints on the parameter space of the SFT model than, for example, using the axial dipole moment alone as an optimization metric. We studied the maximum of cycle 24 and identified the recurrent and localized flux emergence in the southern hemisphere as the main culprit behind the rapid strengthening of the large-scale magnetic field in late 2014. We find that during the declining phase of the solar cycle, the strength of the large-scale magnetic field stayed above the median level of randomized simulations (p $<$ 0.027) for 42 subsequent rotations (from September 2014 to November 2017). This indicates that the longitudinal distribution of active regions is not random and, rather, that it demonstrates a tendency for some regions to emerge at longitudes where their equatorial components reinforce the large-scale equatorial field.

The pathophysiology of functional neurological disorders (FND) has been discussed to include dysfunctions in interoception, the modality about perceiving and processing internal bodily signals. However, findings on abnormal interoception in FND have been inconsistent and mainly limited to measures of accuracy and self-report. Interoceptive neuronal markers have only been investigated in specific symptoms, and interoceptive attentional modulation has been completely overlooked. In a cohort of patients with mixed FND (N = 44) and sex- and age-matched healthy controls (N = 48), we set out to assess first, interoceptive accuracy with an adapted version of the heartbeat counting task; secondly, interoceptive self-report with two different questionnaires (Multidimensional Assessment of Interoceptive Awareness and Interoceptive Accuracy Scale) and thirdly, neuronal trait markers under attention modulation by measuring heartbeat-evoked potentials, the neurophysiological signal related to the heartbeat. We searched for group differences (FND versus controls) across two attentional conditions, by asking participants to either focus on their heartbeat (i.e. interoceptive condition) or an external sound (i.e. exteroceptive control condition). Cardiac covariates (heart rate and heartrate variability or normalized electrocardiac amplitude) were included in the analysis as control. Patients with FND scored lower in both interoceptive self-report questionnaires (P < 0.020), reported higher difficulty concerning the focus towards their heartbeat (P = 0.004), while no significant difference was found in interoceptive accuracy using the heartbeat counting task (P = 0.060). Global field analyses revealed short intervals of a group-by-condition interaction in global field power (285–298 ms) and topographical differences (310–321 ms) confirming that patients with FND have lower overall activity and frontal deactivation during the interoceptive condition. Preselected electrodes for a targeted analysis of the heartbeat-evoked potential based on earlier work revealed a medium effect size attenuation at the frontal-lateralized F8 electrode at 250–595 ms following R-peak for patients with FND (P = 0.028), surviving correction for cardiac covariates. Exploratory analyses further identified an earlier difference at F1 (185–210 ms post-R-peak) in FND patients for interoceptive attention (P = 0.001), also surviving covariate control. While behavioural interoceptive accuracy was marginally preserved, these findings indicate overall altered interoceptive processing in FND, characterized by reduced self-report and difficulty to focus on cardiac signals, along with attenuated neural processes, especially in frontal-lateralized regions that further depend on attentional mechanisms. By identifying objective neural markers of interoceptive dysfunction in FND, this study highlights the involvement of interoception in a multidimensional assessment including the relevance of attention.

Rapid prediction of 3D global residual stress field in metal workpieces manufactured by directed energy deposition using graph attention networks

GMSR: Gradient-integrated mamba for spectral reconstruction from RGB images.

Currently, research on cherry detection and recognition is relatively limited, and existing methods for agricultural product inspection often suffer from slow speed and low classification accuracy. To address these issues, this paper introduces an improved YOLOv11n-based model for detecting cherry ripeness, designed to enhance both the accuracy and efficiency of identifying cherries at different maturity stages. First, improvements were made to the backbone network of the YOLOv11n model by replacing the original backbone with ConvNeXtv2. This replacement achieved a broader global receptive field and enhanced multi-scale learning, which helped reduce computational costs and significantly improve efficiency while maintaining high performance. Second, a DCNv4 convolution module—an advanced convolutional layer with adaptive receptive fields—was added to the neck of the model. The neck is an intermediate stage that combines features from different layers, and the DCNv4 adapts the receptive field to help accurately locate occluded cherries of any shape and scale. This improves detection performance for small cherries without increasing computational complexity. Finally, the convolutional attention module CBAM was introduced. CBAM adaptively focuses on important image features while suppressing irrelevant background by using both channel and spatial attention mechanisms. Together, these additions significantly improve cherry detection accuracy and robustness. Our experimental results show that the improved M-YOLOv11n algorithm achieved a 4.84% increase in mAP@50 compared to the original YOLOv11n model. Precision and recall also improved by 1.25% and 0.4%, respectively. Overall, the enhanced model outperformed not only its base version but also the YOLOv5n and YOLOv8n models. Compared to multi-stage models, the proposed model demonstrates superior accuracy, speed, and reduced computational requirements. This improvement enables more efficient and precise identification of cherry ripeness, thereby enhancing the efficiency of cherry harvesting and facilitating optimal harvest timing. These advancements support the optimization of storage and transportation conditions for cherries and provide robust technical support for intelligent orchard management and the advancement of automated fruit sorting systems.

This study investigates the influence mechanism of key factors on the heating value of syngas during underground coal gasification (UCG) and proposes an optimization path for enhanced energy conversion efficiency based on typical global field test data. Integrating data review and pattern analysis, it systematically explores the influence of core factors, including coal seam characteristics, reactor structure, and gasification agent ratio. It is found that the relationship between syngas heating value and coal rank is not simply linear, with representative heating values ranging from 4.13 to 11.96 MJ/m3. Medium-rank coal, characterized by “medium volatile matter and low ash content”, yields high-heating-value syngas when paired with air/steam as the gasification agent. Shaftless reactor structures demonstrate superior overall performance compared to shaft-based designs, with the representative heating value improving from 3.83 MJ/m3 to 7.8 MJ/m3. The combination of U-shaped horizontal wells with the Controlled Retracting Injection Point (CRIP) technology improves the heating value. Effective control over the syngas heating value can be achieved by optimized composition and ratio of the gasification agent, with representative value of 9.10 MJ/m3 in oxygen-enriched steam gasification compared to 4.28 MJ/m3 in air gasification. Based on an evaluation of data fluctuation characteristics, the significance ranking of the factors is as follows: gasification agent, coal rank, and reactor structure. Consequently, an engineering optimization path for enhancing UCG syngas heating value is proposed: prioritize optimizing the composition and ratio of the gasification agent as the primary means of heating value control; on this basis, rationally select coal rank resources, focusing on process compatibility to mitigate performance fluctuations; and then incorporate advanced reactor structures to construct a synergistic and efficient gasification system. This research can provide theoretical support and data references for engineering site selection, process design, and operational control of UCG projects.

Abstract This paper explains how corporate and organizational professionals reach top positions, emphasizing organizational careers—the history of organizational experiences throughout an individual’s work life—as a key status dynamic. Trajectories to the top traverse not only in-house career ladders but operate across multiple status orders, specifically as exchanges between hierarchical status (rank within an organization) and organizational status (rank of an organization in the field). I theorize three ideal-type trajectories to the top: fidelity (hierarchical status accumulation in high-status organizations), conversion (trading organizational for hierarchical status), and regulatory capital (exploiting regulatory knowledge and networks for high-status positions). Analysing a novel database of elite careers in the global tax field—a domain marked by corporate and organizational professionalism—I find evidence for the centrality of these three trajectories, with their distribution marked by both general and field-specific dynamics, notably the power of the Big Four firms and the distinctive importance of regulatory experience. Conceptually, the study extends research on contemporary knowledge-based professionals by specifying and showing how status dynamics vary across career pathways and fields; methodologically, it advances a personnel-flow-based measure of organizational status that is applicable across heterogeneous fields.

Synthetic aperture radar (SAR), with its all-weather and all-day observation capabilities, plays a significant role in the field of remote sensing. However, due to the unique imaging mechanism of SAR, its interpretation is challenging. Translating SAR images into optical remote sensing images has become a research hotspot in recent years to enhance the interpretability of SAR images. This paper proposes a deep learning-based method for SAR-to-optical remote sensing image translation. The network comprises three parts: a global representor, a generator with cascaded multi-head attention, and a multi-scale discriminator. The global representor, built upon InternImage with deformable convolution v3 (DCNv3) as its core operator, leverages its global receptive field and adaptive spatial aggregation capabilities to extract global semantic features from SAR images. The generator follows the classic “encoder-bottleneck-decoder” structure, where the encoder focuses on extracting local detail features from SAR images. The cascaded multi-head attention module within the bottleneck layer optimizes local detail features and facilitates feature interaction between global semantics and local details. The discriminator adopts a multi-scale structure based on the local receptive field PatchGAN, enabling joint global and local discrimination. Furthermore, for the first time in SAR image translation tasks, structural similarity index metric (SSIM) loss is combined with adversarial loss, perceptual loss, and feature matching loss as the loss function. A series of experiments demonstrate the effectiveness and reliability of the proposed method. Compared to mainstream image translation methods, our method ultimately generates higher-quality optical remote sensing images that are semantically consistent, texturally authentic, clearly detailed, and visually reasonable appearances.

ABSTRACT Increasing evidence suggests that transcranial direct current stimulation (tDCS) can enhance language outcomes in people with post-stroke aphasia. However, the neurophysiological mechanisms underlying these behavioral improvements remain insufficiently characterized. This crossover feasibility study examined the clinical and technical viability of integrating transcranial magnetic stimulation with electroencephalography (TMS–EEG) to characterize cortical excitability and network dynamics before and after real and sham tDCS in individuals with chronic post-stroke non-fluent aphasia. Eight participants were enrolled; four completed the full protocol, while four discontinued due to scheduling or technical constraints. The completers underwent eight weeks of anodal tDCS and language exercises. They tolerated the combined procedures well, with full adherence, no adverse events, and good-quality TMS–EEG recordings, confirming the protocol’s feasibility. Cortical responses were quantified using global and local mean field power (GMFP, LMFP) and a regional complexity index. Behaviorally, modest language improvements were observed in two participants with Broca’s aphasia. Neurophysiologically, heterogeneous modulations of cortical reactivity were observed across cases. These findings indicate that this multimodal protocol can be practically and safely implemented, with no adverse effects observed, while also underscoring logistical, technical, and clinical considerations for larger-scale studies designed to elucidate the neurophysiological mechanisms supporting tDCS-driven language recovery.

The Gravity Recovery and Climate Experiment (GRACE) tracks drought events by detecting changes in the global gravitational field and capturing abnormal information on the reserves of surface water, soil water, and groundwater, which makes it possible for a more comprehensive and unified global and regional monitoring of groundwater drought. This study adopted the gravity satellite GRACE data and combined it with the hydrological model dataset. Additionally, we assessed the temporal evolution and spatial pattern of groundwater drought in the Yangtze River Basin (YRB) and its sub-basins from 2003 to 2022, determined the change points of the hidden seasonal and trend components in groundwater drought, and identified the direct/indirect driving contributions of the main climatic and circulation factors to groundwater drought. The results show that (1) as a normalized index, the groundwater drought index (GDI) can reflect direct evidence of any surplus and deficit in groundwater availability. During the study period, the minimum value (−1.66) of the GDI occurred in July 2020 (severe drought). (2) The average value of GDI in the entire basin ranged from −1.66 (severe drought) to 0.52 (no drought). (3) The average Zs values (Mann–Kendall Z-statistic) of GDI were −0.23, −0.16, −0.43, and 0.14, respectively, and the proportions of areas with aggravated drought reached 65.21%, 61.05%, 89.70% and 43.67%, respectively. (4) Partial wavelet coherence analysis can simultaneously reveal the local correlations of time series at different time scales and frequencies. Based on partial wavelet analysis, precipitation was the best factor for explaining the dynamic changes in groundwater drought. (5) The North Pacific Index (NPI), the Pacific/North American Index (PNA), and the Sunspot Index (SSI) can serve as the main predictors that can effectively capture the drought changes in groundwater in the YRB. The GRACE satellite can provide a new tool for monitoring, tracking, and assessing groundwater drought situations, which is of great significance for guiding the development of the drought early warning system in the YRB and effectively preventing and responding to drought disasters.

As a bridge connecting processes in the Earth’s interior and the superficial lithosphere, distribution characteristics of global stress fields could benefit the verification of geodynamical models and reflect spatial variations of lithospheric strength. Numerical simulation of the global stress field could provide the temporal evolution process of the stress fields, and reveal the dynamic process of accumulation and release of the in situ stress fields as well as the quantitative relationship between force sources and the stress fields, which could compensate for the sparsity and insufficient representativeness of in situ stress observation data. To advance the investigation on the global stress fields, we review the state-of-the-art progress of numerical simulation tools for global stress fields and their applications, and show the existing problems as well as future trends.

Abstract Although Mars lacks an intrinsic global dipole magnetic field, the existence of crustal magnetic anomalies in the southern hemisphere causes the Martian magnetosphere to have the hybrid characteristics combining Venus‐like induced and Earth‐like intrinsic types. However, the influence of the crustal fields on shaping the Martian dayside magnetosphere remains ambiguous. To explore this, an entirely induced magnetosphere and a hybrid magnetosphere are obtained from a Hall‐magnetohydrodynamic model without and with the consideration of the crustal fields under average solar wind conditions. Simulation results reveal that the presence of the crustal fields typically enhances and twists magnetic field and associated current within the Martian hybrid magnetosphere. Accordingly, the crustal fields significantly augment the intensity of motional and Hall electric fields, from which ions tend to acquire considerably additional energy for escape. These findings provide valuable insights into the structuring of the Martian hybrid magnetosphere under the impact of the crustal fields.

BACKGROUND: The current study aimed to characterize aging-related cortical changes in spatial hearing using electroencephalographic (EEG) recordings evoked in response to spatial deviants (virtual acoustic stimuli). METHODS: A group comparison design was used in the present study. A 3-stimulus oddball paradigm containing 2 deviant stimuli and 1 standard was used to obtain P300 recordings from 64 scalp electrodes. The offline processed EEG data for spatial deviants were compared across age groups using global field power (GFP) and topographic pattern analyses. P300 was recorded on 3 groups of normal hearing listeners: 10 young adults (31-40 years), 12 middle-aged adults (41-50 years), and 13 elderly adults (51-65 years). RESULTS: Group differences were evident on GFP, with the elderly adults manifesting larger GFP at the N1 and P3 regions. Further pattern analyses marked the extinction and emergence of new scalp topographies in the elderly and middle-aged groups starting from 130 ms and lasting until 800 ms. CONCLUSION: The study provides support for aging-related deterioration in inhibitory control over neural coding of space, which becomes apparent from 130 ms poststimulus presentation.Cite this article as: Nisha KV, , Kappadi SS, Nisha KV; Uppunda AK. Impact of aging on attentional networks in cortical coding of auditory space. J Int Adv Otol. 2025, 21, 1765, doi:10.5152/jiao.2024.241765.

ABSTRACTUnderstanding how individuals segment complex natural scenes into perceptual segments is essential for explaining both typical and atypical sensory processing. In Autism Spectrum Disorder (ASD), differences in visual segmentation and integration are widely documented. However, existing paradigms often rely on simplified stimuli and do not capture the dynamic, naturalistic processes underlying real world scene segmentation. To overcome those limitations, in this work we present a novel, multimodal experimental framework. The framework combines precisely timed, trial-based perceptual measurements with electroencephalography (EEG) to examine how neural activity aligns temporally with segmentation decisions and with eye-tracking to examine visual exploration strategies and attention allocation. Neurotypical (NT) participants and participants with ASD aged 16 years and above viewed natural scenes and textures and indicated whether two cued image regions belonged to the same or different perceptual segments. Responses to multiple pairs of cues enabled the estimation of subjectively perceived segmentation maps and the associated uncertainty. Across NT and ASD populations, we analyzed segmentation maps, reaction time distributions, gaze profiles, and trial-aligned neural responses. Behavioral results revealed slower and more idiosyncratic segmentation patterns in ASD. Eye-tracking analyses also demonstrated distinct gaze patterns suggesting broader exploration of the images during early viewing. EEG analyses demonstrated delayed and more diffuse occipital activation in ASD, accompanied by reduced global field power at several key time windows spanning stimulus presentation. Together, these findings establish a reproducible method for studying the temporal and spatial components of natural scene segmentation and indicate meaningful behavioral and neural distinctions in ASD. This framework provides a methodological bridge between controlled experimental stimuli and real-world perception in both neurotypical and neurodivergent populations.

Steady-state solutions to the Navier-Stokes equations are a valuable tool for constructing quasi-steady models of the solar wind and exploring the various factors that affect the fluxes of mass, energy, and momentum into the heliosphere. These models typically omit the effects of viscosity, which is assumed to be negligible under most coronal and heliospheric conditions; however, the inviscid Navier-Stokes equations are known to admit solutions that are singular at the sonic point, where the solar wind speed becomes equal to the relevant acoustic speed. Consequently, inviscid solar wind models require special treatment of the solution near the sonic points, and this has proven to be a significant impediment to efficient modeling of the solar wind. In this paper we revisit the governing hydrodynamic equations for the expanding solar wind, with the inclusion of the viscous stress as defined by the classical (Newtonian) closure, and we show how this inclusion eliminates the singularities that emerge from the inviscid equations. This result has been previously reported and used to generate steady-state solar wind profiles from initial conditions in the asymptotic limit (outside of the Sun's gravitational well); however, those studies did not include realistic treatments of the inner corona, and generally rejected the prospect of extrapolating solutions outward from the Sun into the heliosphere, which they deemed to be computationally unfeasible. Our aim, therefore, is to expand this method to include external heating and optically thin radiative losses and show that solutions can be computed outward from initial conditions near the solar surface, thereby capturing the entire range of scales from below the transition region to the outer heliosphere in a single solution. Our the steady-state, field aligned Navier-Stokes equations as a system of five coupled, first order, ordinary differential equations (ODEs) describing the spatial evolution of the mass density, pressure, speed, conductive heat flux, and viscous stress. These equations were then solved approach was to cast using conventional methods, without any special treatment of the governing equations in the vicinity of the sonic point. Physically meaningful solutions were identified by varying the initial conditions at the lower boundary until the solution obtained the correct asymptotic form, which we derived for the particular closures that we employed. The representative solutions that we present here demonstrate the utility and efficiency of this extrapolation method, which is considerably more realistic than commonly used analytical or empirical models. This method provides a direct approach to generating accurate solar wind profiles subject to motivated initial conditions near the solar surface, at a fraction of the computational cost of comparable relaxation-based models. The this method can be used to initialize time-dependent simulations, to large families of steady-state solutions that can then be used to populate the hydrodynamic variables along individual magnetic field lines in , observationally solutions obtained from generate global magnetic field models and to explore how the properties of the quasi-steady solar wind are affected by changes in magnetic geometry and different coronal heating models.

ABSTRACT Clinical relevance Quantitative analysis of macular capillary plexuses using optical coherence tomography angiography (OCTA) may improve diagnosis and monitoring of glaucoma. Identifying vascular patterns linked to localised and global visual field loss could enhance clinical decision-making and understanding of disease mechanisms. Purpose To investigate the relationship between macular vessel density, measured by OCTA, and visual field loss quantified by pattern standard deviation and mean deviation; and to determine whether perfusion metrics from the superficial and deep capillary plexus correlate with functional deficits using OCTA and visual field analysis. Methods This cross-sectional study included 114 participants: 38 with glaucoma, 38 glaucoma suspects, and 38 healthy controls. Macular vessel density of the superficial and deep capillary plexus was measured using 6 × 6 mm OCTA scans, while functional loss was assessed with Humphrey visual field parameters including pattern standard deviation, mean deviation, and the visual field index. Linear regression was performed to analyse associations between vascular metrics, visual field indices, and structural measures such as retinal nerve fibre layer and ganglion cell complex thickness. Results Deep capillary plexus vessel density showed strong correlations with global functional loss (mean deviation, R² = 0.88, p < 0.001) and focal loss (pattern standard deviation, R² = 0.83, p < 0.001). Superficial capillary plexus vessel density was significantly associated with pattern standard deviation (R² = 0.51, p < 0.001). Glaucoma eyes showed higher pattern standard deviation (7.87 ± 3.11) than suspects (2.76 ± 1.45) and controls (2.37 ± 0.67) (p < 0.001), along with reduced macular perfusion in both plexuses. Conclusion Macular vessel density, particularly in the deep capillary plexus, is strongly associated with focal and global visual field loss in glaucoma. Superficial plexus metrics show a moderate but significant correlation with focal loss, supporting OCTA as a non-invasive biomarker for early glaucoma detection and monitoring.

The output mitral cells (MCs) and tufted cells (TCs) of the mammalian olfactory bulb (OB) are coupled through both chemical mechanisms as well as gap junctions that are mediated by connexin 36 (Cx36). Here, we tested both behavioural and physiological effects of eliminating gap junctions in knockout (KO) mice with homozygous deletions of Cx36. In a go/no-go associative learning task, Cx36 KO mice were found to display reduced discrimination capabilities when presented with pairs of stimuli that included a monomolecular odour and mixtures that had the same monomolecular odour and a small amount of a structurally similar odour. The impairments did not occur for less similar odour pairs, suggesting that Cx36 KO mice have olfactory processing deficits that are specific to fine odour discrimination. In physiological recordings in OB slices from Cx36 KO mice, MCs displayed reduced excitation in response to electrical stimulation of sensory afferents, both single stimulus pulses as well as a theta burst pattern designed to mimic sniffing. The reduction in MC excitatory current was most prominent for late portions of their response, 300ms after single stimulus pulses or following all theta bursts that came after the first. More global local field potentials recorded in OB glomeruli were largely unaffected by Cx36 KO. We suggest that the KO-induced impairments in fine odour discrimination could be linked to reduced late-phase MC excitation because of the longer time that mice require to make difficult odour discriminations. KEY POINTS: The output mitral cells (MCs) of the olfactory bulb (OB) engage in strong electrical coupling via connexin 36 (Cx36)-mediated gap junctions. However, the behavioural and physiological relevance of these gap junctions is not well understood. In studies conducted in Cx36 knockout (KO) mice, we found impaired odour discrimination vs. wild-type mice in a go/no-go associative learning task, although deficits only occurred with the most difficult tasks involving odour mixtures. These results provide the first evidence to date of olfactory behavioural deficits in Cx36 KO mice. In OB slices, Cx36 KO reduced excitatory responses in MCs to electrical stimulation of sensory afferents, but only during latter stages of the response. We suggest that KO-induced impairments in fine odour discrimination could be linked to reduced late-phase MC excitation because of the longer time that mice require to make difficult odour discriminations.

An isotropic vector of a given quadratic form is a nonzero vector where the form vanishes. Geometrically, it is a vector that is self-orthogonal with respect to this form. On the other hand, from the arithmetical point of view, an isotropic vector forms a solution to a multivariate quadratic equation. The problem of constructing isotropic vectors is one of the leading forces in the computational theory of quadratic forms. In this paper, we present algorithms for finding isotropic vectors of quadratic forms (of any dimension) over an arbitrary global field of characteristic distinct from 2 2 .

Weight bias is a social justice issue that manifests in social and health inequities, affecting the lives of millions of individuals globally. Although weight bias research has increased over the last two decades, it remains pervasive, and more work is needed to establish effective strategies to reduce it. The 2024 International Weight Bias Summit aimed to collaboratively identify future research directions for prioritization as well as perceived barriers in the global field of weight bias and stigma. This paper presents the primary findings from the Summit. Experts in weight bias (N = 33 researchers, clinicians, representatives of professional/national organizations with interests in weight bias and stigma, and individuals with lived experiences) from across North and Latin America, Europe, and Australia attended the two-day Summit. Attendees participated in semi-structured small group discussions using the Nominal Group Technique (NGT). Notes were collected from all discussions and thematically analyzed to identify the most prominent research directions and barriers that emerged from the Summit. Experts identified six key research directions (presented without hierarchical ranking): (1) consequences of weight bias, (2) conceptual and methodological clarity, (3) diversity in sampling, cultures, and settings, (4) interventions, (5) policy, and (6) implementation science. Three key barriers were also identified in weight bias and stigma research: (1) widespread misconceptions and lack of recognition of weight bias as a legitimate issue, (2) funding challenges, and (3) lack of collaborations and working in silos. Experts identified six critical research directions that should be prioritized to advance weight bias and stigma research and drive meaningful progress. Continued international collaboration was recognized as essential to driving this work forward.