Dynamic Adaptation on Non-Stationary Visual Domains

Domain adaptation aims to learn models on a supervised source domain that perform well on an unsupervised target. Prior work has examined domain adaptation in the context of stationary domain shifts, i.e. static data sets. However, with large-scale or dynamic data sources, data from a defined domain is not usually available all at once. For instance, in a streaming data scenario, dataset statistics effectively become a function of time. We introduce a framework for adaptation over non-stationary distribution shifts applicable to large-scale and streaming data scenarios. The model is adapted sequentially over incoming unsupervised streaming data batches. This enables improvements over several batches without the need for any additionally annotated data. To demonstrate the effectiveness of our proposed framework, we modify associative domain adaptation to work well on source and target data batches with unequal class distributions. We apply our method to several adaptation benchmark datasets for classification and show improved classifier accuracy not only for the currently adapted batch, but also when applied on future stream batches. Furthermore, we show the applicability of our associative learning modifications to semantic segmentation, where we achieve competitive results

Evaluation of Phage Display Discovered Peptides as Ligands for Prostate-Specific Membrane Antigen (PSMA)

The aim of this study was to identify potential ligands of PSMA suitable for further development as novel PSMA-targeted peptides using phage display technology. The human PSMA protein was immobilized as a target followed by incubation with a 15-mer phage display random peptide library. After one round of prescreening and two rounds of screening, high-stringency screening at the third round of panning was performed to identify the highest affinity binders. Phages which had a specific binding activity to PSMA in human prostate cancer cells were isolated and the DNA corresponding to the 15-mers were sequenced to provide three consensus sequences: GDHSPFT, SHFSVGS and EVPRLSLLAVFL as well as other sequences that did not display consensus. Two of the peptide sequences deduced from DNA sequencing of binding phages, SHSFSVGSGDHSPFT and GRFLTGGTGRLLRIS were labeled with 5-carboxyfluorescein and shown to bind and co-internalize with PSMA on human prostate cancer cells by fluorescence microscopy. The high stringency requirements yielded peptides with affinities KD∼1 μM or greater which are suitable starting points for affinity maturation. While these values were less than anticipated, the high stringency did yield peptide sequences that apparently bound to different surfaces on PSMA. These peptide sequences could be the basis for further development of peptides for prostate cancer tumor imaging and therapy. © 2013 Shen et al

NatCSNN: A Convolutional Spiking Neural Network for recognition of objects extracted from natural images

Biological image processing is performed by complex neural networks composed of thousands of neurons interconnected via thousands of synapses, some of which are excitatory and others inhibitory. Spiking neural models are distinguished from classical neurons by being biological plausible and exhibiting the same dynamics as those observed in biological neurons. This paper proposes a Natural Convolutional Neural Network (NatCSNN) which is a 3-layer bio-inspired Convolutional Spiking Neural Network (CSNN), for classifying objects extracted from natural images. A two-stage training algorithm is proposed using unsupervised Spike Timing Dependent Plasticity (STDP) learning (phase 1) and ReSuMe supervised learning (phase 2). The NatCSNN was trained and tested on the CIFAR-10 dataset and achieved an average testing accuracy of 84.7% which is an improvement over the 2-layer neural networks previously applied to this dataset.Comment: 12 page

A smoother end to the dark ages

Independent lines of evidence suggest that the first stars, which ended the cosmic dark ages, came in pairs, rather than singly. This could change the prevailing view that the early Universe had a Swiss-cheese-like appearance.Comment: Nature News and Views, April 7, 201

Parallel gene synthesis in a microfluidic device

The ability to synthesize custom de novo DNA constructs rapidly, accurately and inexpensively is highly desired by researchers, as synthetic genes and longer DNA constructs are enabling to numerous powerful applications in both traditional molecular biology and the emerging field of synthetic biology. However, the current cost of de novo synthesis—driven largely by reagent and handling costs—is a significant barrier to the widespread availability of such technology. In this work, we demonstrate, to our knowledge, the first gene synthesis in a microfluidic environment. The use of microfluidic technology greatly reduces reaction volumes and the corresponding reagent and handling costs. Additionally, microfluidic technology enables large numbers of complex reactions to be performed in parallel. Here, we report the fabrication of a multi-chamber microfluidic device and its use in carrying out the syntheses of several DNA constructs. Genes up to 1 kb in length were synthesized in parallel at minute starting oligonucleotide concentrations (10–25 nM) in four 500 nl reactors. Such volumes are one to two orders of magnitude lower than those utilized in conventional gene synthesis. The identity of all target genes was verified by sequencing, and the resultant error rate was determined to be 1 per 560 bases.Massachusetts Institute of Technology. Center for Bits and AtomsNational Science Foundation (U.S.) (CBA grant CCR-0122419

T-Helper Cell Cytokine Expression Profiling in Rheumatoid Arthritis Patients by Flow Cytometric Bead Array Analysis

Background: Rheumatoid arthritis (RA) is the most common chronic autoimmune disease affecting multiple joints. A chronic imbalance in cytokine production by T-helper (Th) cells is likely a key factor in RA development. Our objective was to profile the serum cytokine expression from three key Th cell types (Th1, Th2, and Th17) in RA patients in order to correlate the resulting cytokine expression profiles with RA activity. Material and Methods: From a population of RA patients (n = 71) and healthy controls (n = 18), the serum concentrations of seven cytokines (IL-2, IL-4, IL-6, IL-10, IL-17A, IFN-γ, and TNF-α) were analyzed by flow cytometric bead array (CBA). Results: The serum concentrations of all seven cytokines were significantly higher in RA patients than in healthy controls. Interestingly, the serum concentration profiles varied with the 28-joint Disease Activity Score (DAS28), a measure of RA activity derived from joint indices (tender joints and swollen joints count) and the erythrocyte sedimentation rate. In the high RA activity group (DAS28 > 5.1), all seven cytokines were significantly elevated. In the moderate RA activity group (DAS28 between 3.2 and 5.1), only IL-2, IL-6, IL-10, and IL-17A were significantly increased. In the low RA activity group (DAS28 ≤ 3.2), only IL-2, IL-4, and TNF-α were significantly elevated. Conclusions: The Th cell-derived cytokine expression profile significantly changes across varying levels of RA activity. Th1/Th17 cell-derived TNF-α and Th2 cell-derived IL-4 appear to play more important roles in the early stages of RA, while all seven cytokines derived from Th1, Th2, and Th17 cells (IL-2, IL-4, IL-6, IL-10, IL-17A, IFN-γ, and TNF-α) are overtly involved in the advanced stages of RA

Supersymmetric Intersecting Branes on the Waves

We construct a general family of supersymmetric solutions in time- and space-dependent wave backgrounds in general supergravity theories describing single and intersecting p-branes embedded into time-dependent dilaton-gravity plane waves of an arbitrary (isotropic) profile, with the brane world-volume aligned parallel to the propagation direction of the wave. We discuss how many degrees of freedom we have in the solutions. We also propose that these solutions can be used to describe higher-dimensional time-dependent "black holes", and discuss their property briefly.Comment: 12 pages, LaTe