Image sensing with multilayer, nonlinear optical neural networks

Optical imaging is commonly used for both scientific and technological applications across industry and academia. In image sensing, a measurement, such as of an object's position, is performed by computational analysis of a digitized image. An emerging image-sensing paradigm breaks this delineation between data collection and analysis by designing optical components to perform not imaging, but encoding. By optically encoding images into a compressed, low-dimensional latent space suitable for efficient post-analysis, these image sensors can operate with fewer pixels and fewer photons, allowing higher-throughput, lower-latency operation. Optical neural networks (ONNs) offer a platform for processing data in the analog, optical domain. ONN-based sensors have however been limited to linear processing, but nonlinearity is a prerequisite for depth, and multilayer NNs significantly outperform shallow NNs on many tasks. Here, we realize a multilayer ONN pre-processor for image sensing, using a commercial image intensifier as a parallel optoelectronic, optical-to-optical nonlinear activation function. We demonstrate that the nonlinear ONN pre-processor can achieve compression ratios of up to 800:1 while still enabling high accuracy across several representative computer-vision tasks, including machine-vision benchmarks, flow-cytometry image classification, and identification of objects in real scenes. In all cases we find that the ONN's nonlinearity and depth allowed it to outperform a purely linear ONN encoder. Although our experiments are specialized to ONN sensors for incoherent-light images, alternative ONN platforms should facilitate a range of ONN sensors. These ONN sensors may surpass conventional sensors by pre-processing optical information in spatial, temporal, and/or spectral dimensions, potentially with coherent and quantum qualities, all natively in the optical domain

Generalized Gravi-Electromagnetism

A self consistant and manifestly covariant theory for the dynamics of four charges (masses) (namely electric, magnetic, gravitational, Heavisidian) has been developed in simple, compact and consistent manner. Starting with an invariant Lagrangian density and its quaternionic representation, we have obtained the consistent field equation for the dynamics of four charges. It has been shown that the present reformulation reproduces the dynamics of individual charges (masses) in the absence of other charge (masses) as well as the generalized theory of dyons (gravito - dyons) in the absence gravito - dyons (dyons). key words: dyons, gravito - dyons, quaternion PACS NO: 14.80H

Comparison of tumour-based (Petersen Index) and inflammation-based (Glasgow Prognostic Score) scoring systems in patients undergoing curative resection for colon cancer

After resection, it is important to identify colon cancer patients, who are at a high risk of recurrence and who may benefit from adjuvant treatment. The Petersen Index (PI), a prognostic model based on pathological criteria is validated in Dukes' B and C disease. Similarly, the modified Glasgow Prognostic Score (mGPS) based on biochemical criteria has also been validated. This study compares both the scores in patients undergoing curative resection of colon cancer. A total of 244 patients underwent elective resection between 1997 and 2005. The PI was constructed from pathological reports; the mGPS was measured pre-operatively. The median follow-up was 67 months (minimum 36 months) during which 109 patients died; 68 of them from cancer. On multivariate analysis of age, Dukes' stage, PI and mGPS, age (hazard ratio, HR, 1.74, P=0.001), Dukes' stage (HR, 3.63, P<0.001), PI (HR, 2.05, P=0.010) and mGPS (HR, 2.34, P<0.001) were associated independently with cancer-specific survival. Three-year cancer-specific survival rates for Dukes' B patients with the low-risk PI were 98, 92 and 82% for the mGPS of 0, 1 and 2, respectively (P<0.05). The high-risk PI population is small, in particular for Dukes' B disease (9%). The mGPS further stratifies those patients classified as low risk by the PI. Combining both the scoring systems could identify patients who have undergone curative surgery but are at high-risk of cancer-related death, therefore guiding management and trial stratification

Use of divalent metal ions in the DNA cleavage reaction of topoisomerase IV

It has long been known that type II topoisomerases require divalent metal ions in order to cleave DNA. Kinetic, mutagenesis and structural studies indicate that the eukaryotic enzymes utilize a novel variant of the canonical two-metal-ion mechanism to promote DNA scission. However, the role of metal ions in the cleavage reaction mediated by bacterial type II enzymes has been controversial. Therefore, to resolve this critical issue, this study characterized the DNA cleavage reaction of Escherichia coli topoisomerase IV. We utilized a series of divalent metal ions with varying thiophilicities in conjunction with oligonucleotides that replaced bridging and non-bridging oxygen atoms at (and near) the scissile bond with sulfur atoms. DNA scission was enhanced when thiophilic metal ions were used with substrates that contained bridging sulfur atoms. In addition, the metal-ion dependence of DNA cleavage was sigmoidal in nature, and rates and levels of DNA cleavage increased when metal ion mixtures were used in reactions. Based on these findings, we propose that topoisomerase IV cleaves DNA using a two-metal-ion mechanism in which one of the metal ions makes a critical interaction with the 3′-bridging atom of the scissile phosphate and facilitates DNA scission by the bacterial type II enzyme

Tips for implementing multigrid methods on domains containing holes

As part of our development of a computer code to perform 3D `constrained evolution' of Einstein's equations in 3+1 form, we discuss issues regarding the efficient solution of elliptic equations on domains containing holes (i.e., excised regions), via the multigrid method. We consider as a test case the Poisson equation with a nonlinear term added, as a means of illustrating the principles involved, and move to a "real world" 3-dimensional problem which is the solution of the conformally flat Hamiltonian constraint with Dirichlet and Robin boundary conditions. Using our vertex-centered multigrid code, we demonstrate globally second-order-accurate solutions of elliptic equations over domains containing holes, in two and three spatial dimensions. Keys to the success of this method are the choice of the restriction operator near the holes and definition of the location of the inner boundary. In some cases (e.g. two holes in two dimensions), more and more smoothing may be required as the mesh spacing decreases to zero; however for the resolutions currently of interest to many numerical relativists, it is feasible to maintain second order convergence by concentrating smoothing (spatially) where it is needed most. This paper, and our publicly available source code, are intended to serve as semi-pedagogical guides for those who may wish to implement similar schemes.Comment: 18 pages, 11 figures, LaTeX. Added clarifications and references re. scope of paper, mathematical foundations, relevance of work. Accepted for publication in Classical & Quantum Gravit

History and Class Consciousness 2.0: Georg Lukács in the age of digital capitalism and big data

This paper discusses the relevance of Georg Lukács’ 1923 book History and Class Consciousness in the context of digital capitalism. It does so by analysing how Lukács’ concepts of the dialectic of subject and object, ideology, reification, reified consciousness matter today in the context of big data and digital capitalism. The essay shows that History and Class Consciousness’ critique of reification, ideology, and reified consciousness remains highly topical in the age of digital capitalism and big data. Lukács’ analysis allows us to critically analyse how social media, big data, and various other Internet technologies are used as tools of reification. At the same time, Lukács reminds us that only human praxis can establish alternatives

Nonequilibrium Weak Processes in Kaon Condensation I --- Reaction rate for the thermal kaon process ---

We investigate the thermal kaon process,in which kaons are thermally produced via nucleon-nucleon collisions.This process is relevant to nonequilibrium dynamics of kaon condensation inside neutron stars.The reaction rates for these processes are calculated, and their temperature and density dependences are compared with those of other reaction rates.It is shown that the thermal kaon process is dominant over other relevant weak reactions throughout the nonequilibrium process, such as the kaon-induced Urca and the modified Urca reactions, and may control the entire evolution of the kaon condensate. The characteristic role of the soft and hard kaons during the evolution is explained, and implications for astrophysical phenomena are briefly discussed.Comment: 31 pages,incl.10 eps figures,RevTe

Novel cyclic di-GMP effectors of the YajQ protein family control bacterial virulence

Bis-(3 ',5 ') cyclic di-guanylate (cyclic di-GMP) is a key bacterial second messenger that is implicated in the regulation of many critical processes that include motility, biofilm formation and virulence. Cyclic di-GMP influences diverse functions through interaction with a range of effectors. Our knowledge of these effectors and their different regulatory actions is far from complete, however. Here we have used an affinity pull-down assay using cyclic di-GMP-coupled magnetic beads to identify cyclic di-GMP binding proteins in the plant pathogen Xanthomonas campestris pv. campestris (Xcc). This analysis identified XC_3703, a protein of the YajQ family, as a potential cyclic di-GMP receptor. Isothermal titration calorimetry showed that the purified XC_3703 protein bound cyclic di-GMP with a high affinity (K-d similar to 2 mu M). Mutation of XC_3703 led to reduced virulence of Xcc to plants and alteration in biofilm formation. Yeast two-hybrid and far-western analyses showed that XC_3703 was able to interact with XC_2801, a transcription factor of the LysR family. Mutation of XC_2801 and XC_3703 had partially overlapping effects on the transcriptome of Xcc, and both affected virulence. Electromobility shift assays showed that XC_3703 positively affected the binding of XC_2801 to the promoters of target virulence genes, an effect that was reversed by cyclic di-GMP. Genetic and functional analysis of YajQ family members from the human pathogens Pseudomonas aeruginosa and Stenotrophomonas maltophilia showed that they also specifically bound cyclic di-GMP and contributed to virulence in model systems. The findings thus identify a new class of cyclic di-GMP effector that regulates bacterial virulence

Systematic review of studies generating individual participant data on the efficacy of drugs for treating soil-transmitted helminthiases and the case for data-sharing

Preventive chemotherapy and transmission control (PCT) by mass drug administration is the cornerstone of the World Health Organization (WHO)’s policy to control soil-transmitted helminthiases (STHs) caused by Ascaris lumbricoides (roundworm), Trichuris trichiura (whipworm) and hookworm species (Necator americanus and Ancylostama duodenale) which affect over 1 billion people globally. Despite consensus that drug efficacies should be monitored for signs of decline that could jeopardise the effectiveness of PCT, systematic monitoring and evaluation is seldom implemented. Drug trials mostly report aggregate efficacies in groups of participants, but heterogeneities in design complicate classical meta-analyses of these data. Individual participant data (IPD) permit more detailed analysis of drug efficacies, offering increased sensitivity to identify atypical responses potentially caused by emerging drug resistance