Optical focusing in scattering media with photoacoustic wavefront shaping (PAWS)

Controllable light delivery to the region of interest is essential to biomedical optical imaging methods like photoacoustic microscopy. It is, however, challenging beyond superficial depths in biological tissue (~1 mm beneath human skin) due to the strong scattering of light that scrambles the photon propagation paths. Recently, optical wavefront shaping has been proposed to modulate the incident light wavefront to compensate for the scattering-induced phase distortions, and consequentially, convey light optimally to a desired location behind or inside turbid media. To reach an optimum wavefront, a searching algorithm is usually required to optimize a feedback signal. In this work, we present our latest explorations, which use photoacoustic signals as the feedback to remotely and non-invasively guide the wavefront shaping process. Our method does not require direct optical access to the target region or the invasive embedding of fluorescence probes inside turbid media. Experimentally, we have demonstrated that diffuse light can be converged to the ultrasound focus by maximizing the amplitude of photoacoustic emissions from the intended absorbing site. Moreover, we show that wavefront-shaped light focusing can enhance existing optical imaging modalities like photoacoustic microscopy, in regard to signal-to-noise ratio, imaging depth, and potentially, resolution

BBReach: Tight and Scalable Black-Box Reachability Analysis of Deep Reinforcement Learning Systems

Reachability analysis is a promising technique to automatically prove or disprove the reliability and safety of AI-empowered software systems that are developed by using Deep Reinforcement Learning (DRL). Existing approaches suffer however from limited scalability and large overestimation as they must over-approximate the complex and almost inexplicable system components, namely deep neural networks (DNNs). In this paper we propose a novel, tight and scalable reachability analysis approach for DRL systems. By training on abstract states, our approach treats the embedded DNNs as black boxes to avoid the over-approximation for neural networks in computing reachable sets. To tackle the state explosion problem inherent to abstraction-based approaches, we devise a novel adjacent interval aggregation algorithm which balances the growth of abstract states and the overestimation caused by the abstraction. We implement a tool, called BBReach, and assess it on an extensive benchmark of control systems to demonstrate its tightness, scalability, and efficiency

Optimization and Abstraction: A Synergistic Approach for Analyzing Neural Network Robustness

In recent years, the notion of local robustness (or robustness for short) has emerged as a desirable property of deep neural networks. Intuitively, robustness means that small perturbations to an input do not cause the network to perform misclassifications. In this paper, we present a novel algorithm for verifying robustness properties of neural networks. Our method synergistically combines gradient-based optimization methods for counterexample search with abstraction-based proof search to obtain a sound and ({\delta}-)complete decision procedure. Our method also employs a data-driven approach to learn a verification policy that guides abstract interpretation during proof search. We have implemented the proposed approach in a tool called Charon and experimentally evaluated it on hundreds of benchmarks. Our experiments show that the proposed approach significantly outperforms three state-of-the-art tools, namely AI^2 , Reluplex, and Reluval

A prospective study of prognostic factors for duration of sick leave after endoscopic carpal tunnel release

<p>Abstract</p> <p>Background</p> <p>Endoscopic carpal tunnel release with a single portal technique has been shown to reduce sick leave compared to open carpal tunnel release, claiming to be a less invasive procedure and reducing scar tenderness leading to a more rapid return to work, and the purpose of this study was to identify prognostic factors for prolonged sick leave after endoscopic carpal tunnel release in a group of employed Danish patients.</p> <p>Methods</p> <p>The design was a prospective study including 75 employed patients with carpal tunnel syndrome operated with ECTR at two hospitals. The mean age was 46 years (SD 10.1), the male/female ratio was 0.42, and the mean preoperative duration of symptoms 10 months (range 6-12). Only 21 (28%) were unable to work preoperatively and mean sick leave was 4 weeks (range 1-4). At base-line and at the 3-month follow-up, a self-administered questionnaire was collected concerning physical, psychological, and social circumstances in relation to the hand problem. Data from a nerve conduction examination were collected at baseline and at the 3-month follow-up. Significant prognostic factors were identified through multiple logistic regression analysis.</p> <p>Results</p> <p>After the operation, the mean functional score was reduced from 2.3 to 1.4 (SD 0.8) and the mean symptom score from 2.9 to 1.5 (SD 0.7). The mean sick leave from work after the operation was 19.8 days (SD 14.3). Eighteen patients (24%) had more than 21 days of sick leave. Two patients (3%) were still unable to work after 3 months. Significant prognostic factors in the multivariate analysis for more than 21 days of postoperative sick leave were preoperative sick leave, blaming oneself for the hand problem and a preoperative distal motor latency.</p> <p>Conclusion</p> <p>Preoperative sick leave, blaming oneself for the hand problem, and a preoperative distal nerve conduction motor latency were prognostic factors for postoperative work absence of more than 21 days. Other factors may be important (clinical, demographic, economic, and workplace) in explaining the great variance in the results of sick leave after carpal tunnel release between studies from different countries.</p

Speckle-scale focusing in the diffusive regime with time reversal of variance-encoded light (TROVE)

Focusing of light in the diffusive regime inside scattering media has long been considered impossible. Recently, this limitation has been overcome with time reversal of ultrasound-encoded light (TRUE), but the resolution of this approach is fundamentally limited by the large number of optical modes within the ultrasound focus. Here, we introduce a new approach, time reversal of variance-encoded light (TROVE), which demixes these spatial modes by variance encoding to break the resolution barrier imposed by the ultrasound. By encoding individual spatial modes inside the scattering sample with unique variances, we effectively uncouple the system resolution from the size of the ultrasound focus. This enables us to demonstrate optical focusing and imaging with diffuse light at an unprecedented, speckle-scale lateral resolution of ~5 µm

Development and validation of an index of musculoskeletal functional limitations

BACKGROUND: While musculoskeletal problems are leading sources of disability, there has been little research on measuring the number of functionally limiting musculoskeletal problems for use as predictor of outcome in studies of chronic disease. This paper reports on the development and preliminary validation of a self administered musculoskeletal functional limitations index. METHODS: We developed a summary musculoskeletal functional limitations index based upon a six-item self administered questionnaire in which subjects indicate whether they are limited a lot, a little or not at all because of problems in six anatomic regions (knees, hips, ankles and feet, back, neck, upper extremities). Responses are summed into an index score. The index was completed by a sample of total knee replacement recipients from four US states. Our analyses examined convergent validity at the item and at the index level as well as discriminant validity and the independence of the index from other correlates of quality of life. RESULTS: 782 subjects completed all items of the musculoskeletal functional limitations index and were included in the analyses. The mean age of the sample was 75 years and 64% were female. The index demonstrated anticipated associations with self-reported quality of life, activities of daily living, WOMAC functional status score, use of walking support, frequency of usual exercise, frequency of falls and dependence upon another person for assistance with chores. The index was strongly and independently associated with self-reported overall health. CONCLUSION: The self-reported musculoskeletal functional limitations index appears to be a valid measure of musculoskeletal functional limitations, in the aspects of validity assessed in this study. It is useful for outcome studies following TKR and shows promise as a covariate in studies of chronic disease outcomes.National Institutes of Health (NIH P60 AR 47782; NIH K24 AR 02123

Metabolic Flux Analysis of Mitochondrial Uncoupling in 3T3-L1 Adipocytes

BACKGROUND:Increasing energy expenditure at the cellular level offers an attractive option to limit adiposity and improve whole body energy balance. In vivo and in vitro observations have correlated mitochondrial uncoupling protein-1 (UCP1) expression with reduced white adipose tissue triglyceride (TG) content. The metabolic basis for this correlation remains unclear. METHODOLOGY/PRINCIPAL FINDINGS:This study tested the hypothesis that mitochondrial uncoupling requires the cell to compensate for the decreased oxidation phosphorylation efficiency by up-regulating lactate production, thus redirecting carbon flux away from TG synthesis. Metabolic flux analysis was used to characterize the effects of non-lethal, long-term mitochondrial uncoupling (up to 18 days) on the pathways of intermediary metabolism in differentiating 3T3-L1 adipocytes. Uncoupling was induced by forced expression of UCP1 and chemical (FCCP) treatment. Chemical uncoupling significantly decreased TG content by ca. 35%. A reduction in the ATP level suggested diminished oxidative phosphorylation efficiency in the uncoupled adipocytes. Flux analysis estimated significant up-regulation of glycolysis and down-regulation of fatty acid synthesis, with chemical uncoupling exerting quantitatively larger effects. CONCLUSIONS/SIGNIFICANCE:The results of this study support our hypothesis regarding uncoupling-induced redirection of carbon flux into glycolysis and lactate production, and suggest mitochondrial proton translocation as a potential target for controlling adipocyte lipid metabolism

Recommender Systems

The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has a great scientific depth and combines diverse research fields which makes it of interests for physicists as well as interdisciplinary researchers.Comment: 97 pages, 20 figures (To appear in Physics Reports