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Machine learning (ML) inference serving systems host deep neural network (DNN) models and schedule incoming inference requests across deployed GPUs. However, limited support for task prioritization and insufficient latency estimation under concurrent execution may restrict their applicability in on-premises scenarios. We present \emph{Strait}, a serving system designed to enhance deadline satisfaction for dual-priority inference traffic under high GPU utilization. To improve latency estimation, Strait models potential contention during data transfer and accounts for kernel execution interference through an adaptive prediction model. By drawing on these predictions, it performs priority-aware scheduling to deliver differentiated handling. Evaluation results under intense workloads suggest that Strait reduces deadline violations for high-priority tasks by 1.02 to 11.18 percentage points while incurring acceptable costs on low-priority tasks. Compared to software-defined preemption approaches, Strait also exhibits more equitable performance.
Background/Objective: Vitamin D deficiency (serum 25-hydroxyvitamin D [25(OH)D] concentration <50 nmol/L) is prevalent among Aboriginal and Torres Strait Islander peoples in Australia. Alternative to sun exposure (the primary source of vitamin D), vitamin D can also be obtained from food (e.g., fish, eggs, and meat) and supplements. However, vitamin D intake among Aboriginal and Torres Strait Islander peoples is currently unknown. We aimed to provide the first quantification of vitamin D intake using nationally representative data from Aboriginal and Torres Strait Islander peoples. Methods: We used food consumption data collected in the 2012-2013 National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (n = 4,109) and vitamin D food composition data to quantify mean absolute vitamin D intake by sex, age group, and remoteness of location. Differences in mean vitamin D intake between sexes and between remoteness of location were assessed using the 95% confidence interval (95% CI). Results: The mean (standard deviation (SD)) vitamin D intake among Aboriginal and Torres Strait Islander peoples was 2.9 (3.0) μg/day. Males had a statistically significantly
The Atlantic Meridional Overturning Circulation (AMOC) is a major tipping element in the present-day climate, and could potentially collapse under sufficient freshwater or CO2-forcing. While the effect of the Bering Strait on AMOC stability has been well studied, it is unknown whether a constructed closure of this Strait can prevent an AMOC collapse under climate change. Here, we show in an Earth system Model of Intermediate Complexity that an artificial closure of the Strait can extend the safe carbon budget of the AMOC, provided that the AMOC is strong enough at the closure time. Specifically, for this model, an equilibrium AMOC with a reduction below (6.1 +/- 0.5)% from pre-industrial has an additional budget up to 500PgC given a sufficiently early closure, while for a weaker AMOC a closure reduces this budget. This indicates that constructing this closure could be a feasible climate intervention strategy to prevent an AMOC collapse.
Although previous observational studies have shown associations between serum 25-hydroxyvitamin D (25(OH)D) concentration and metabolic syndrome, this association has not yet been investigated among Aboriginal and Torres Strait Islander peoples. We aimed to investigate the association between serum 25(OH)D concentration and metabolic syndrome and its risk factors in this population group. We used cross-sectional data from the 2012-2013 Australian Aboriginal and Torres Strait Islander Health Survey. Metabolic syndrome is defined as having 3 or more risk factors: elevated waist circumference, elevated triglycerides, low high-density lipoprotein (HDL) cholesterol, elevated blood pressure, or elevated fasting blood glucose. We used binomial logistic regression to test associations between serum 25(OH)D concentration and metabolic syndrome, and multiple linear regression to test associations between serum 25(OH)D concentration and each risk factor. We included the following covariates: age, sex, smoking status, education level, socio-economic status, remoteness of location, season, and body mass index (BMI). After adjusting for covariates, we found that each 10 nmol/L increase in serum
Accurate recognition of vessel types from Automatic Identification System (AIS) tracks is essential for safety oversight and combating illegal, unreported, and unregulated (IUU) activity. This paper presents a strait-scale, machine-learning pipeline that classifies moving vessels using only AIS data. We analyze eight days of historical AIS from the Danish Maritime Authority covering the Bornholm Strait in the Baltic Sea (January 22-30, 2025). After forward/backward filling voyage records, removing kinematic and geospatial outliers, and segmenting per-MMSI tracks while excluding stationary periods ($\ge 1$ h), we derive 31 trajectory-level features spanning kinematics (e.g., SOG statistics), temporal, geospatial (Haversine distances, spans), and ship-shape attributes computed from AIS A/B/C/D reference points (length, width, aspect ratio, bridge-position ratio). To avoid leakage, we perform grouped train/test splits by MMSI and use stratified 5-fold cross-validation. Across five classes (cargo, tanker, passenger, high-speed craft, fishing; N=1{,}910 trajectories; test=382), tree-based models dominate: a Random Forest with SMOTE attains 92.15% accuracy (macro-precision 94.11%, macro-
Background: Low vitamin D intake and high prevalence of vitamin D deficiency (serum 25-hydroxyvitamin D concentration < 50 nmol/L) among Aboriginal and Torres Strait Islander peoples highlight a need for public health strategies to improve vitamin D status. As few foods contain naturally occurring vitamin D, fortification strategies may be needed to improve vitamin D intake and status among Aboriginal and Torres Strait Islander peoples. Objective: We aimed to model vitamin D food fortification scenarios among Aboriginal and Torres Strait Islander peoples. Methods: We used nationally representative food consumption data (n=4,109) and vitamin D food composition data to model four food fortification scenarios. The modelling for Scenario 1 included foods and maximum vitamin D concentrations permitted for fortification in Australia: i) dairy products and alternatives, ii) butter/margarine/oil spreads, iii) formulated beverages, and iv) selected ready-to-eat breakfast cereals. The modelling for Scenarios 2a-c included some vitamin D concentrations higher than permitted in Australia; Scenario 2c included bread, which is not permitted for vitamin D fortification in Australia. Scenario 2
Objective: To investigate the association between serum 25-hydroxyvitamin D [25(OH)D] concentration and mental health, measured using the Kessler Psychological Distress Scale 5 (K5), among Aboriginal and Torres Strait Islander Peoples. Methods: We used cross-sectional data from the 2012-2013 Australian Aboriginal and Torres Strait Islander Health Survey. Multiple linear regression was used to test the association between serum 25(OH)D concentration and K5, adjusting for age, sex, education, remoteness, socioeconomic status, season of blood collection, smoking, and alcohol intake (n = 1,983). We also stratified the analysis by sex and by remoteness. Results: There was no statistically significant association between serum 25(OH) concentration and K5 in the total population, nor when stratified by sex. When stratified by remoteness, higher serum 25(OH)D concentration was statistically significantly associated with lower K5 scores among those living remotely (adjusted \b{eta}: -0.18; 95% CI: -0.35, -0.01). Conclusions: Serum 25(OH)D concentration was inversely associated with psychological distress only among those living remotely. Implications for Public Health: Given the prevalence
We propose Stratified Image Transformer(StraIT), a pure non-autoregressive(NAR) generative model that demonstrates superiority in high-quality image synthesis over existing autoregressive(AR) and diffusion models(DMs). In contrast to the under-exploitation of visual characteristics in existing vision tokenizer, we leverage the hierarchical nature of images to encode visual tokens into stratified levels with emergent properties. Through the proposed image stratification that obtains an interlinked token pair, we alleviate the modeling difficulty and lift the generative power of NAR models. Our experiments demonstrate that StraIT significantly improves NAR generation and out-performs existing DMs and AR methods while being order-of-magnitude faster, achieving FID scores of 3.96 at 256*256 resolution on ImageNet without leveraging any guidance in sampling or auxiliary image classifiers. When equipped with classifier-free guidance, our method achieves an FID of 3.36 and IS of 259.3. In addition, we illustrate the decoupled modeling process of StraIT generation, showing its compelling properties on applications including domain transfer.
Using Lagrangian methods we analyze a 20-year-long estimate of water flux through the Kamchatka Strait in the northern North Pacific based on AVISO velocity field. It sheds new light on the flux pattern and its variability on annual and monthly time scales. Strong seasonality in surface outflow through the strait could be explained by temporal changes in the wind stress over the northern and western Bering Sea slopes. Interannual changes in a surface outflow through the Kamchatka Strait correlate significantly with the Near Strait inflow and Bering Strait outflow. Enhanced westward surface flow of the Alaskan Stream across the $174^\circ$ E section in the northern North Pacific is accompanied by an increased inflow into the Bering Sea through the Near Strait. In summer, the surface flow pattern in the Kamchatka Strait is determined by passage of anticyclonic and cyclonic mesoscale eddies. The wind stress over the Bering basin in winter - spring is responsible for eddy generation in the region.
The Strait of Gibraltar is a region characterized by intricate oceanic sub-mesoscale features, influenced by topography, tidal forces, instabilities, and nonlinear hydraulic processes, all governed by the nonlinear equations of fluid motion. In this study, we aim to uncover the underlying physics of these phenomena within 3D MIT general circulation model simulations, including waves, eddies, and gyres. To achieve this, we employ Dynamic Mode Decomposition (DMD) to break down simulation snapshots into Koopman modes, with distinct exponential growth/decay rates and oscillation frequencies. Our objectives encompass evaluating DMD's efficacy in capturing known features, unveiling new elements, ranking modes, and exploring order reduction. We also introduce modifications to enhance DMD's robustness, numerical accuracy, and robustness of eigenvalues. DMD analysis yields a comprehensive understanding of flow patterns, internal wave formation, and the dynamics of the Strait of Gibraltar, its meandering behaviors, and the formation of a secondary gyre, notably the Western Alboran Gyre, as well as the propagation of Kelvin and coastal-trapped waves along the African coast. In doing so, it si
This paper analyzes the availability and accuracy of coastal altimetry sea level products in the Strait of Gibraltar. All possible repeats of two sections of the Envisat and AltiKa ground-tracks were used in the eastern and western portions of the strait. For Envisat, along-track sea level anomalies (SLAs) at 18-Hz posting rate were computed using ranges from two sources, namely, the official SGDRs and the outputs of a coastal waveform retracker, the ALES retracker; in addition, SLAs at 1 Hz were obtained from CTOH, France. For AltiKa, along-track SLA at 40 Hz was also computed both from SGDR and ALES ranges. The quality of these altimeter products was validated using two tide gauges located on the southern coast of Spain. We observed an improvement of about 20% in the accuracy of the Envisat SLAs from ALES compared to the standard (SGDR) and the reprocessed CTOH data sets. AltiKa shows higher accuracy, with no significant differences between SGDR and ALES.
The cross-strait relationship between China and Taiwan is marked by increasing hostility around potential reunification. We analyze an unattributed bot network and how repeater bots engaged in an influence campaign against Taiwan following US House Speaker Nancy Pelosi's visit to Taiwan in 2022. We examine the message amplification tactics employed by four key bot sub-communities, the widespread dissemination of information across multiple platforms through URLs, and the potential targeted audiences of this bot network. We find that URL link sharing reveals circumvention around YouTube suspensions, in addition to the potential effectiveness of algorithmic bot connectivity to appear less bot-like, and detail a sequence of coordination within a sub-community for message amplification. We additionally find the narratives and targeted audience potentially shifting after account activity discrepancies, demonstrating how dynamic these bot networks can operate.
In this work, we retracked altimeter waveforms of ESA satellites. ERS2 RA and Envisat RA2 from descending track 0360 over the eastern side of the Strait of Gibraltar using the Adaptive Leading Edge Subwaveform ALES retracker.
We present Cassini VIMS observations of sun glitter -- wave-induced reflections from a liquid surface offset from a specular point -- on Kraken Mare. Sun glitter reveals rough sea surfaces around Kraken Mare, namely the coasts and narrow straits. The sun glitter observations indicate wave activity driven by the winds and tidal currents in Kraken Mare during northern summer. T104 Cassini VIMS observations show three sun glitter features in Bayta Fretum indicative of variegated wave fields. We cannot uniquely determine one source for the coastal Bayta waves, but we lean toward the interpretation of surface winds, because tidal currents should be too weak to generate capillary-gravity waves in Bayta Fretum. T105 and T110 observations reveal wave fields in the straits of Seldon Fretum, Lulworth Sinus, and Tunu Sinus that likely originate from the constriction of tidal currents. Coastlines of Bermoothes and Hufaidh Insulae adjoin rough sea surfaces, suggesting a complex interplay of wind-roughened seas and localized tidal currents. Bermoothes and Hufaidh Insulae may share characteristics of either the Torres Strait off Australia or the Aland region of Finland, summarized as an island-de
English: To the Meriam Mir people of Mer (Murray Island) in the eastern Torres Strait, bright meteors are an important element of death customs and beliefs. We draw from a combination of ethno-historic studies and interviews with Meriam elders to understand the role of bright meteors (Maier) in Torres Strait traditions relating to spiritual elements of death rites using a framework of symbolic anthropology. We find that bright meteors serve as symbolic representations of death and mortuary purification practices and show how the physical properties of meteors are incorporated in ritual, belief, spirituality, and custom. Meriam Mir: Meriamgize maier oditautlare nade eud onagri a mokakalam eud kerker. Kemerkemer daratkapda kikem kerkerira pardar, dorge a oka nako Torres Straitge eud tonar bud ueplare. Debe bibi maieride onatager eud ia onagri a nalu tonar able maierira seri/kakaper a dum able tonar umerem a simir akedrem.
This study attempts to investigate cross-strait variations on two typical synonymous loanwords in Chinese, i.e. xie2shang1 and tan2pan4, drawn on MARVS theory. Through a comparative analysis, the study found some distributional, eventual, and contextual similarities and differences across Taiwan and Mainland Mandarin. Compared with the underused tan2pan4, xie2shang1 is significantly overused in Taiwan Mandarin and vice versa in Mainland Mandarin. Additionally, though both words can refer to an inchoative process in Mainland and Taiwan Mandarin, the starting point for xie2shang1 in Mainland Mandarin is somewhat blurring compared with the usage in Taiwan Mandarin. Further on, in Taiwan Mandarin, tan2pan4 can be used in economic and diplomatic contexts, while xie2shang1 is used almost exclusively in political contexts. In Mainland Mandarin, however, the two words can be used in a hybrid manner within political contexts; moreover, tan2pan4 is prominently used in diplomatic contexts with less reference to economic activities, while xie2sahng1 can be found in both political and legal contexts, emphasizing a role of mediation.
Multi-cause observational studies contain information about unmeasured confounding through the dependence structure among causes. However, literal imputation of the unobserved confounder is often more complex than learning a lower-dimensional substitute score that preserves the shared assignment variation needed for stable causal adjustment. The deconfounder (Wang and Blei, 2019) and related substitute confounder methods exploit this idea, but flexible assignment models can fit the joint distribution of the causes while producing scores that over-encode the treatment vector, collapse overlap, or capture single-cause variation. We develop a Bayesian factor assignment framework for learning sparse substitute confounders that retain coarse multi-cause dependence with shrinkage priors. The theory is stated at the level of posterior concentration, factor score contraction, and overlap-preserving assignment geometry and therefore does not rely on a particular shrinkage prior. Under these conditions, the proposed regression-adjusted estimators are consistent for mean potential outcomes when the corresponding latent variable identification assumptions hold. Shrinkage priors provide a natur
Shapes of objects in images are often complex, high-dimensional, and vary in ways not captured by standard Euclidean geometry and statistics. Statistical shape analysis encompasses methods for flexible and interpretable measurement of intrinsic shape and shape variability in geometric objects. Elastic Shape Analysis (ESA) is one such method that measures shape differences between objects, represented by contours, in a way that is invariant to rotation, scale, translation, and parameterization. Although ESA is useful for quantifying shape of objects in many image applications, formal methods for statistical inference in image-based ESA remain limited. This work introduces a hypothesis test procedure based on empirical confidence intervals for the elastic shape distance (ESD) between a proposed underlying true shape and an estimated shape. The confidence intervals are created using a bootstrap procedure for non-smooth functionals, which accounts for the non-differentiability of the ESD. The effectiveness of the method is illustrated through both numerical studies and real world image examples from inertial confinement fusion (ICF).
AI is increasingly being used to assist fraud and cybercrime. However, it is unclear the extent to which current large language models can provide useful information for complex criminal activity. Working with law enforcement and policy experts, we developed multi-turn evaluations for three fraud and cybercrime scenarios (romance scams, CEO impersonation, and identity theft). Our evaluations focus on text-to-text interactions. In each scenario, we evaluate whether models provide actionable assistance beyond information typically available on the web, as assessed by domain experts. We do so in ways designed to resemble real-world misuse, such as breaking down requests for fraud into a sequence of seemingly benign queries. We found that (1) current large language models provide minimal actionable information for fraud and cybercrime without the use of advanced jailbreaking techniques, (2) model safeguards have significant impact on the provision of information, with the two open-weight large language models fine-tuned to remove safety guardrails providing the most actionable and useful responses, and (3) decomposing requests into benign-seeming queries elicited more assistance than e
We propose causal effect estimators based on empirical Fréchet means and operator-valued kernels, tailored to functional data spaces. These methods address the challenges of high-dimensionality, sequential ordering, and model complexity while preserving robustness to treatment misspecification. Using structural assumptions, we obtain compact representations of potential outcomes, enabling scalable estimation of causal effects over time and across covariates. We provide both theoretical, regarding the consistency of functional causal effects, as well as empirical comparison of a range of proposed causal effect estimators. Applications to binary treatment settings with functional outcomes illustrate the framework's utility in biomedical monitoring, where outcomes exhibit complex temporal dynamics. Our estimators accommodate scenarios with registered covariates and outcomes, aligning them to the Fréchet means, as well as cases requiring higher-order representations to capture intricate covariate-outcome interactions. These advancements extend causal inference to dynamic and non-linear domains, offering new tools for understanding complex treatment effects in functional data settings.