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Spatial transcriptomics (ST) has emerged as a powerful technology for bridging histology imaging with gene expression profiling. However, its application has been limited by low throughput and the need for specialized experimental facilities. Prior works sought to predict ST from whole-slide histology images to accelerate this process, but they suffer from two major limitations. First, they do not explicitly model cell-cell interaction as they factorize the joint distribution of whole-slide ST data and predict the gene expression of each spot independently. Second, their encoders struggle with memory constraints due to the large number of spots (often exceeding 10,000) in typical ST datasets. Herein, we propose STFlow, a flow matching generative model that considers cell-cell interaction by modeling the joint distribution of gene expression of an entire slide. It also employs an efficient slide-level encoder with local spatial attention, enabling whole-slide processing without excessive memory overhead. On the recently curated HEST-1k and STImage-1K4M benchmarks, STFlow substantially outperforms state-of-the-art baselines and achieves over 18% relative improvements over the pathology foundation models. 

Nucleic acid-based drugs like aptamers have recently demonstrated great therapeutic potential. However, experimental platforms for aptamer screening are costly, and the scarcity of labeled data presents a challenge for supervised methods to learn protein-aptamer binding. To this end, we develop an unsupervised learning approach based on the predicted pairwise contact map between a protein and a nucleic acid and demonstrate its effectiveness in protein-aptamer binding prediction. Our model is based on FAFormer, a novel equivariant transformer architecture that seamlessly integrates frame averaging (FA) within each transformer block. This integration allows our model to infuse geometric information into node features while preserving the spatial semantics of coordinates, leading to greater expressive power than standard FA models. Our results show that FAFormer outperforms existing equivariant models in contact map prediction across three protein complex datasets, with over 10% relative improvement. Moreover, we curate five real-world protein-aptamer interaction datasets and show that the contact map predicted by FAFormer serves as a strong binding indicator for aptamer screening. 

We report the first observations of a long-duration very-high-energy (VHE; E>100 GeV) flare from BL Lacertae (VER J2202+422), taken with the Very Energetic Radiation Imaging Telescope Array System (VERITAS). On October 15, 2022, the Fermi-Large Area Telescope (LAT) detected elevated GeV activity originating from this blazar. This triggered a multiwavelength campaign, which includes observations from VERITAS, Swift, NuSTAR, and select optical and radio observatories. VERITAS observed the source for a total of ~9.8 hours between September 1, 2022 and December 1, 2022. An analysis of these data yields a ~28 sigma detection of the source. While previously observed VHE flares from BL Lacertae have lasted on time-scales of minutes to days, VERITAS continued to detect flaring activity from the source for over a month (~40 days) after the original flaring activity was detected with Fermi-LAT. Broadband spectral modeling shows that a synchrotron self-Compton (SSC) model with an external inverse-Compton (EC) component is preferred over a one-zone SSC model. 

Abstract The radio galaxy NGC 1275 is the brightest cluster galaxy in the Perseus Cluster. It is well studied across all wave bands, including very high-energy (VHE;E ≥ 100 GeV)γ-rays, and with radio observations over the last 20 yr tracking an unusual radio component, “C3.” NGC 1275 was observed in an exceptional VHE-flaring state between 2016 December 31 and 2017 January 3. The flare peak reached ∼1.5 Crab units as measured by the MAGIC observatory. We report on the observations of NGC 1275 conducted by VERITAS and multiwavelength data collected during this flaring state and, for context, data taken between 2009 and 2017 inclusively. VERITAS detected the declining state of the flare on 2017 January 2 (MJD 57755) and 3 (MJD 57756) at an average flux state of 0.5 Crab units. VERITAS spectra show an overall long-term trend of harder when brighter. During the flare, theγ-ray spectrum obtained from the combined Fermi-LAT, MAGIC, and VERITAS observations changes from a power law with an exponential cutoff on January 1 to a log-parabola on January 2. To study the evolution of the flare in more detail, multiband spectral energy distributions (SEDs) were constructed for the nights of 2017 January 1 and 2 corresponding to the shift from the peak to the decline of the flare. A blob-in-jet modeling of the SEDs results in support for a two-component model with aθ = 10^∘jet angle to the line of sight and theγ-ray emission zone located in the vicinity of the C3 radio component. 

Abstract Microquasars such as SS 433 are considered potential contributors to cosmic rays up to the knee of the cosmic-ray energy spectrum (∼4 PeV), where a transition in the dominant acceleration processes is expected. The SS 433 system, located within the W50 supernova remnant, is a Galactic microquasar with relativistic jets interacting with the surrounding medium over parsec scales, providing an example for studying jet-driven particle acceleration. A deep morphological and spectral study of SS 433 is performed using more than 150 hr of observations with VERITAS, sensitive toγ-ray energies >100 GeV. With an angular resolution better than 0 $\stackrel{\text{°}}{.}$ 1, extended TeVγ-ray emission is resolved from both the eastern and western jet lobes, located tens of parsecs from the central binary. The emission appears elongated along the jet axis and coincides with regions where the jets interact with the surrounding supernova remnant. No TeV emission is detected from the central binary, nor is significant emission observed between the central binary and the jet lobes. Phase-resolved analyses show no evidence for variability in the orbital or precessional phase, supporting a steady emission scenario. The observed morphology and spectra are consistent with scenarios where particles are accelerated in the lobes of the jets, possibly through shocks or alternative processes such as magnetic reconnection. The extended TeV emission from the jet lobes of SS 433 favors a leptonic origin in the VERITAS energy range, suggesting that any hadronic acceleration is subdominant. The results offer valuable constraints on how microquasar jets may contribute to the Galactic cosmic-ray population toward the knee. 

In this work, we propose a novel approach for the real-time estimation of chip-level spatial power maps for commercial Google Coral M.2 TPU chips based on a machine-learning technique for the first time. The new method can enable the development of more robust runtime power and thermal control schemes to take advantage of spatial power information such as hot spots that are otherwise not available. Different from the existing commercial multi-core processors in which real-time performance-related utilization information is available, the TPU from Google does not have such information. To mitigate this problem, we propose to use features that are related to the workloads of running different deep neural networks (DNN) such as the hyperparameters of DNN and TPU resource information generated by the TPU compiler. The new approach involves the offline acquisition of accurate spatial and temporal temperature maps captured from an external infrared thermal imaging camera under nominal working conditions of a chip. To build the dynamic power density map model, we apply generative adversarial networks (GAN) based on the workload-related features. Our study shows that the estimated total powers match the manufacturer's total power measurements extremely well. Experimental results further show that the predictions of power maps are quite accurate, with the RMSE of only 4.98\rm mW/mm^2, or 2.6\% of the full-scale error. The speed of deploying the proposed approach on an Intel Core i7-10710U is as fast as 6.9ms, which is suitable for real-time estimation. 

Abstract Significant gamma-ray emission between 1 TeV and 20 TeV from a point source, 1LHAASO J1219+2915, consistent with the location of the LINER/LLAGN galaxy NGC 4278 was recently reported by the Large High Altitude Air Shower Observatory (LHAASO) collaboration. These data were later split into active and quasi-quiet states, with most of the LHAASO significance coming from the active state (MJD 59449-59589). Subsequent analysis of Fermi-LAT and Swift-XRT observations have been used to explore the double-peaked broadband emission. Models of the spectral energy distribution (SED) are currently unconstrained due to the lack of contemporaneous multiwavelength data at either peak. Here, we report serendipitous observations of NGC 4278 with the Very Energetic Radiation Imaging Telescope Array System (VERITAS), made possible by the contemporaneous observations of the nearby blazars 1ES 1218+304, 1ES 1215+303, and W Comae, each of which are located within 2° of NGC 4278. VERITAS did not detect any gamma-ray emission, and a flux upper limit was calculated. The flux upper limits constrain the photon spectrum of the quasi-quiet period, and together with Fermi-LAT, indicate a peak in the SED between 100 GeV and 2 TeV. We present an interpretation of the broadband SED that is based on acceleration of protons in the corona of the active galactic nuclei, followed byp–γinteractions and optically thinγ-ray emission. Within this framework, the implied neutrino signal is slightly below the current sensitivity of IceCube.