Semi-Supervised First-Person Activity Recognition in Body-Worn Video

Body-worn cameras are now commonly used for logging daily life, sports, and law enforcement activities, creating a large volume of archived footage. This paper studies the problem of classifying frames of footage according to the activity of the camera-wearer with an emphasis on application to real-world police body-worn video. Real-world datasets pose a different set of challenges from existing egocentric vision datasets: the amount of footage of different activities is unbalanced, the data contains personally identifiable information, and in practice it is difficult to provide substantial training footage for a supervised approach. We address these challenges by extracting features based exclusively on motion information then segmenting the video footage using a semi-supervised classification algorithm. On publicly available datasets, our method achieves results comparable to, if not better than, supervised and/or deep learning methods using a fraction of the training data. It also shows promising results on real-world police body-worn video

Unsupervised Segmentation in Real-World Images via Spelke Object Inference

Self-supervised, category-agnostic segmentation of real-world images is a challenging open problem in computer vision. Here, we show how to learn static grouping priors from motion self-supervision by building on the cognitive science concept of a Spelke Object: a set of physical stuff that moves together. We introduce the Excitatory-Inhibitory Segment Extraction Network (EISEN), which learns to extract pairwise affinity graphs for static scenes from motion-based training signals. EISEN then produces segments from affinities using a novel graph propagation and competition network. During training, objects that undergo correlated motion (such as robot arms and the objects they move) are decoupled by a bootstrapping process: EISEN explains away the motion of objects it has already learned to segment. We show that EISEN achieves a substantial improvement in the state of the art for self-supervised image segmentation on challenging synthetic and real-world robotics datasets.Comment: 25 pages, 10 figure

Unifying (Machine) Vision via Counterfactual World Modeling

Leading approaches in machine vision employ different architectures for different tasks, trained on costly task-specific labeled datasets. This complexity has held back progress in areas, such as robotics, where robust task-general perception remains a bottleneck. In contrast, "foundation models" of natural language have shown how large pre-trained neural networks can provide zero-shot solutions to a broad spectrum of apparently distinct tasks. Here we introduce Counterfactual World Modeling (CWM), a framework for constructing a visual foundation model: a unified, unsupervised network that can be prompted to perform a wide variety of visual computations. CWM has two key components, which resolve the core issues that have hindered application of the foundation model concept to vision. The first is structured masking, a generalization of masked prediction methods that encourages a prediction model to capture the low-dimensional structure in visual data. The model thereby factors the key physical components of a scene and exposes an interface to them via small sets of visual tokens. This in turn enables CWM's second main idea -- counterfactual prompting -- the observation that many apparently distinct visual representations can be computed, in a zero-shot manner, by comparing the prediction model's output on real inputs versus slightly modified ("counterfactual") inputs. We show that CWM generates high-quality readouts on real-world images and videos for a diversity of tasks, including estimation of keypoints, optical flow, occlusions, object segments, and relative depth. Taken together, our results show that CWM is a promising path to unifying the manifold strands of machine vision in a conceptually simple foundation

Flavanone-rich citrus beverages counteract the transient decline in postprandial endothelial function in humans: a randomised, controlled, double-masked, cross-over intervention study

Specific flavonoid-rich foods/beverages are reported to exert positive effects on vascular function; however, data relating to effects in the postprandial state are limited. The present study investigated the postprandial, time-dependent (0–7 h) impact of citrus flavanone intake on vascular function. An acute, randomised, controlled, double-masked, cross-over intervention study was conducted by including middle-aged healthy men (30–65 years, n 28) to assess the impact of flavanone intake (orange juice: 128·9 mg; flavanone-rich orange juice: 272·1 mg; homogenised whole orange: 452·8 mg; isoenergetic control: 0 mg flavanones) on postprandial (double meal delivering a total of 81 g of fat) endothelial function. Endothelial function was assessed by flow-mediated dilatation (FMD) of the brachial artery at 0, 2, 5 and 7 h. Plasma levels of paringenin/hesperetin metabolites (sulphates and glucuronides) and nitric oxide species were also measured. All flavanone interventions were effective at attenuating transient impairments in FMD induced by the double meal (7 h post intake; P <0·05), but no dose–response effects were observed. The effects on FMD coincided with the peak of naringenin/hesperetin metabolites in circulation (7 h) and sustained levels of plasma nitrite. In summary, citrus flavanones are effective at counteracting the negative impact of a sequential double meal on human vascular function, potentially through the actions of flavanone metabolites on nitric oxide

Porphysome nanovesicles generated by porphyrin bilayers for use as multimodal biophotonic contrast agents

Optically active nanomaterials promise to advance a range of biophotonic techniques through nanoscale optical effects and integration of multiple imaging and therapeutic modalities. Here, we report the development of porphysomes; nanovesicles formed from self-assembled porphyrin bilayers that generated large, tunable extinction coefficients, structure-dependent fluorescence self-quenching and unique photothermal and photoacoustic properties. Porphysomes enabled the sensitive visualization of lymphatic systems using photoacoustic tomography. Near-infrared fluorescence generation could be restored on dissociation, creating opportunities for low-background fluorescence imaging. As a result of their organic nature, porphysomes were enzymatically biodegradable and induced minimal acute toxicity in mice with intravenous doses of 1,000 mg kg^(−1). In a similar manner to liposomes, the large aqueous core of porphysomes could be passively or actively loaded. Following systemic administration, porphysomes accumulated in tumours of xenograft-bearing mice and laser irradiation induced photothermal tumour ablation. The optical properties and biocompatibility of porphysomes demonstrate the multimodal potential of organic nanoparticles for biophotonic imaging and therapy

Distinct regulation of Ubc13 functions by the two ubiquitin-conjugating enzyme variants Mms2 and Uev1A

Ubc13, a ubiquitin-conjugating enzyme (Ubc), requires the presence of a Ubc variant (Uev) for polyubiquitination. Uevs, although resembling Ubc in sequence and structure, lack the active site cysteine residue and are catalytically inactive. The yeast Uev (Mms2) incites noncanonical Lys63-linked polyubiquitination by Ubc13, whereas the increased diversity of Uevs in higher eukaryotes suggests an unexpected complication in ubiquitination. In this study, we demonstrate that divergent activities of mammalian Ubc13 rely on its pairing with either of two Uevs, Uev1A or Mms2. Structurally, we demonstrate that Mms2 and Uev1A differentially modulate the length of Ubc13-mediated Lys63-linked polyubiquitin chains. Functionally, we describe that Ubc13–Mms2 is required for DNA damage repair but not nuclear factor κB (NF-κB) activation, whereas Ubc13–Uev1A is involved in NF-κB activation but not DNA repair. Our finding suggests a novel regulatory mechanism in which different Uevs direct Ubcs to diverse cellular processes through physical interaction and alternative polyubiquitination

Human malaria diagnosis using a single-step direct-PCR based on the Plasmodium cytochrome oxidase III gene

Background: Nested PCRs based on the Plasmodium 18s-rRNA gene have been extensively used for human malaria diagnosis. However, they are not practical when large quantities of samples need to be processed, further there have been challenges in the performance and when interpreting results, especially when submicroscopic infections are analysed. Here the use of "direct PCR" was investigated with the aim of improving diagnosis in the malaria elimination era.\ud \ud Methods: The performance of the Plasmodium cytochrome oxidase III gene (COX-III) based novel malaria detection strategies (direct nested PCR and direct single PCR) were compared using a 18s-rRNA direct nested PCR as a reference tool. Evaluations were based on sensitivity, specificity and the ability to detect mixed infections using control blood spot samples and field collected blood samples with final species diagnosis confirmation by sequencing.\ud \ud Results: The COX-III direct PCR (limit of detection: 0.6–2 parasites/μL) was more sensitive than the 18s-rRNA direct nested PCR (limit of detection: 2–10 parasites/μL). The COX-III direct PCR identified all 21 positive controls (no mixed infections detected) while the 18s-rRNA direct nested PCR identified 18/21 (including four mixed infections). Different concentrations of simulated mixed infections (Plasmodium vivax and Plasmodium falciparum) suggest that the COX-III direct PCR detects only the predominant species. When the 18s-rRNA direct nested PCR was used to detect Plasmodium in field collected bloods spots (n = 3833), there was discrepancy in the results from the genus PCR (16 % positive) and the species-specific PCR (5 % positive). Further, a large portion of a subset of these positive samples (93 % for genus and 60 % for P. vivax), did not align with Plasmodium sequences. In contrast, the COX-III direct PCR clearly identified (single bands confirmed with sequencing) 2 % positive Plasmodium samples including P. vivax, P. falciparum, Plasmodium malariae and Plasmodium ovale wallikeri.\ud \ud Conclusions: The COX-III single direct PCR is an alternative method for accurate detection of Plasmodium microscopic and submicroscopic infections in humans, especially when a large number of samples require screening. This PCR does not require DNA isolation, is sensitive, quick, produces confident/clear results, identifies all the Plasmodium species infecting humans, and is cost-effective.\u