GOGGLES: Automatic Image Labeling with Affinity Coding

Generating large labeled training data is becoming the biggest bottleneck in building and deploying supervised machine learning models. Recently, the data programming paradigm has been proposed to reduce the human cost in labeling training data. However, data programming relies on designing labeling functions which still requires significant domain expertise. Also, it is prohibitively difficult to write labeling functions for image datasets as it is hard to express domain knowledge using raw features for images (pixels). We propose affinity coding, a new domain-agnostic paradigm for automated training data labeling. The core premise of affinity coding is that the affinity scores of instance pairs belonging to the same class on average should be higher than those of pairs belonging to different classes, according to some affinity functions. We build the GOGGLES system that implements affinity coding for labeling image datasets by designing a novel set of reusable affinity functions for images, and propose a novel hierarchical generative model for class inference using a small development set. We compare GOGGLES with existing data programming systems on 5 image labeling tasks from diverse domains. GOGGLES achieves labeling accuracies ranging from a minimum of 71% to a maximum of 98% without requiring any extensive human annotation. In terms of end-to-end performance, GOGGLES outperforms the state-of-the-art data programming system Snuba by 21% and a state-of-the-art few-shot learning technique by 5%, and is only 7% away from the fully supervised upper bound.Comment: Published at 2020 ACM SIGMOD International Conference on Management of Dat

Computational exploration of the chemical structure space of possible reverse tricarboxylic acid cycle constituents

The reverse tricarboxylic acid (rTCA) cycle has been explored from various standpoints as an idealized primordial metabolic cycle. Its simplicity and apparent ubiquity in diverse organisms across the tree of life have been used to argue for its antiquity and its optimality. In 2000 it was proposed that chemoinformatics approaches support some of these views. Specifically, defined queries of the Beilstein database showed that the molecules of the rTCA are heavily represented in such compound databases. We explore here the chemical structure space, e.g. the set of organic compounds which possesses some minimal set of defining characteristics, of the rTCA cycle's intermediates using an exhaustive structure generation method. The rTCA's chemical space as defined by the original criteria and explored by our method is some six to seven times larger than originally considered. Acknowledging that each assumption in what is a defining criterion making the rTCA cycle special limits possible generative outcomes, there are many unrealized compounds which fulfill these criteria. That these compounds are unrealized could be due to evolutionary frozen accidents or optimization, though this optimization may also be for systems-level reasons, e.g., the way the pathway and its elements interface with other aspects of metabolism

Exact results for some Madelung type constants in the finite-size scaling theory

A general formula is obtained from which the madelung type constant: $$C(d|\nu)=\int_0^\infty dx x^{d/2-\nu-1}[(\sum_{l=-\infty}^\infty e^{-xl^2})^d-1-(\frac\pi x)^{d/2}]$$ extensively used in the finite-size scaling theory is computed analytically for some particular cases of the parameters $d$ and $\nu$. By adjusting these parameters one can obtain different physical situations corresponding to different geometries and magnitudes of the interparticle interaction.Comment: IOP- macros, 5 pages, replaced with amended version (1 ref. added

Regulation of CD4+NKG2D+ Th1 cells in patients with metastatic melanoma treated with sorafenib : role of IL-15Rα and NKG2D triggering

Beyond cancer-cell intrinsic factors, the immune status of the host has a prognostic impact on patients with cancer and influences the effects of conventional chemotherapies. Metastatic melanoma is intrinsically immunogenic, thereby facilitating the search for immune biomarkers of clinical responses to cytotoxic agents. Here, we show that a multi-tyrosine kinase inhibitor, sorafenib, upregulates interleukin (IL)-15Rα in vitro and in vivo in patients with melanoma, and in conjunction with natural killer (NK) group 2D (NKG2D) ligands, contributes to the Th1 polarization and accumulation of peripheral CD4+NKG2D+ T cells. Hence, the increase of blood CD4+NKG2D+ T cells after two cycles of sorafenib (combined with temozolomide) was associated with prolonged survival in a prospective phase I/II trial enrolling 63 patients with metastatic melanoma who did not receive vemurafenib nor immune checkpoint-blocking antibodies. In contrast, in metastatic melanoma patients treated with classical treatment modalities, this CD4+NKG2D+ subset failed to correlate with prognosis. These findings indicate that sorafenib may be used as an "adjuvant" molecule capable of inducing or restoring IL-15Rα/IL-15 in tumors expressing MHCclass I-related chain A/B (MICA/B) and on circulating monocytes of responding patients, hereby contributing to the bioactivity of NKG2D+ Th1 cells.peer-reviewe

The Intervention of Adult Education in Surface Water Pollution in the Niger-Delta Region of Nigeria

Surface water is undoubtedly one of the most precious natural resources that exist on our planet. The most unfortunate circumstances that man has found himself in, is the pollution of surface water bodies. In the past, the quest for wealth and to satisfy human wants and needs, man has hampered and greatly polluted the environment in which he lives in. The vulnerability of surface water in the Niger-Delta Region of Nigeria to frequent oil spills and has other pollutants have had negative effects on the fragile mangrove ecosystem, wildlife, aquatic resources and most importantly on man. It is in this regard that the intervention of adult education came into being to see that the problems of surface water pollution in the Niger Delta Region is being addressed through its various programmes such as literacy,  vocational/functional literacy programmes, community education, continuing education

Possibility of the new type phase transition

The scalar field theory and the scalar electrodynamics quantized in the flat gap are considered. The dynamical effects arising due to the boundary presence with two types of boundary conditions (BC) satisfied by scalar fields are studied. It is shown that while the Neumann BC lead to the usual scalar field mass generation, the Dirichlet BC give rise to the dynamical mechanism of spontaneous symmetry breaking. Due to the later, there arises the possibility of the new type phase transition from the normal to spontaneously broken phase. The decreasing in the characteristic size of the quantization region (the gap size here) and increasing in the temperature compete with each other, tending to transport the system in the spontaneously broken and in the normal phase, respectively. The system evolves with a combined parameter, simultaneously reflecting the change in temperature and in the size. As a result, at the critical value of this parameter there occurs the phase transition from the normal phase to the spontaneously broken one. In particular, the usual massless scalar electrodynamics transforms to the Higgs model

The Lipopolysaccharide Export Pathway in Escherichia coli: Structure, Organization and Regulated Assembly of the Lpt Machinery

The bacterial outer membrane (OM) is a peculiar biological structure with a unique composition that contributes significantly to the fitness of Gram-negative bacteria in hostile environments. OM components are all synthesized in the cytosol and must, then, be transported efficiently across three compartments to the cell surface. Lipopolysaccharide (LPS) is a unique glycolipid that paves the outer leaflet of the OM. Transport of this complex molecule poses several problems to the cells due to its amphipatic nature. In this review, the multiprotein machinery devoted to LPS transport to the OM is discussed together with the challenges associated with this process and the solutions that cells have evolved to address the problem of LPS biogenesis

Read for the Stars

Since this is a literacy narrative, most of my writing process involved self-reflection and recollection of my earliest literacy memories. At times, this was difficult, because I had some disjointed or unrelated memories which were difficult to put into a cohesive narrative. I had only one draft of this paper, but after a peer review session in my ENG 100 class, I made revisions for clarification purposes and to correct some minor grammatical oversights

Evaluation of Methods for Gene Selection in Melanoma Cell Lines

A major objective in microarray experiments is to identify a panel of genes that are associated with a disease outcome or trait. Many statistical methods have been proposed for gene selection within the last fifteen years. While the comparison of some of these methods has been done, most of them concentrated on finding gene signatures based on two groups. This study evaluates four gene selection methods when the outcome of interested is continuous in nature. We provide a comparative review of four methods: the Statistical Analysis of Microarrays (SAM), the Linear Models for Microarray Analysis (LIMMA), the Lassoed Principal Components (LPC), and the Quantitative Trait Analysis (QTA). Comparison is based on the power to identify differentially expressed genes, the predictive ability of the genelists for a continuous outcome (G2 checkpoint function), and the prognostic properties of the genelists for distant metastasis-free survival. A simulated dataset and a publicly available melanoma cell lines dataset are used for simulations and validation, respectively. A primary melanoma dataset is used for assessment of prognosis. No common genes were found among the genelists from the four methods. While the SAM was generally the best in terms of power, the QTA genelist performed the best in the prediction of the G2 checkpoint function. Identification of genelists depends on the choice of the gene selection method. The QTA method would be preferred over the other approaches in predicting a quantitative outcome in melanoma research. We recommend the development of more robust statistical methods for differential gene expression analysis