Adversarial Learning for Intractable Problems

After intensive studies on basic problems such as classification and clustering, the machine learning community has reached a stage where many novel problems contain interrelated variables and the learning process usually contains complex inference sub-problems.  Graphical models such as Markov random field (MRF) and maximal marginal methods such as structured support vector machine (SVM-Struct) are popular choices for solving those problems.  Graphical models usually suffer great burden in computing the normalization term and marginal methods do not have Fisher consistency with many easy to use surrogate losses such as hinge loss. Adversarial learning has been proposed to overcome those shortcomings with additional benefits such as robust towards noises and easy adaptation to different problems. It has been proved to be advanced in both theoretically and practically on many problems that have exact solutions for the sub inference problem such as multiclass classification and multilabel prediction.   On the other hand, there are many even harder problems in which the inference part can be NP-hard. This means approximation has to be applied to produce an efficient solution. With the additional errors introduced to the computation process, the theoretical guarantees works on normal cases may no longer hold. In this work, we will explore the performance of adversarial learning on solving these kinds of hard problems.   We will focus on two problems.  The first one is multiclass classification with pairwise features. This problem represents a group of hard problems that are independently identically distributed (i. i. d) assumption of the data is broken.  The inference problem is equivalent to a multiway cut problem and it is NP-hard.  We applied adversarial learning on it and reformulated the sub-problem into an integer linear programming problem.  The second one is the weighted 3-dimensional matching problem which is also NP-hard.  This problem is one of the problems whose output has complex structures.  In this problem, we use a different way to solve it by reducing the problem to the marginal space and moving the NP hardness to the prediction stage.  We compared the results with state-of-art methods and got better results from adversarial learning for both of the problems. More work will be done to explore whether and how adversarial learning can make better use of inexact results to get to a good optimal point

Self-Assembly of Helical Polyacetylene Nanostructures on Carbon Nanotubes

The self-assembling of helical polyacetylene (PA) nanostructures on single-walled nanotubes (SWNT) is studied using molecular dynamics (MD) simulations. The results indicate that SWNT can activate and guide the polymer chains helically wrapping onto it through van der Waals interaction and the π–π stacking interaction between the polymer chain and the outer surface of SWNT. The effects of SWNT diameter, SWNT chirality, and PA chain length on the configuration of the nanostructure have been extensively examined. It is found that a DNA-like double helix of two PA chains appears when the diameter of SWNT is larger than about 13.56 Å, the SWNT chirality has a negligible effect on whether the helical process could happen, and the two PA chains can interact with each other and then influence the formation of the perfect double helix. The geometrical structures between PA and SWNT may trigger enormous interests in chemical functionalization and helical polymer synthesis, which may eventually be beneficial for fabricating nanoscale devices. In addition, the self-assembly process of helical nanostructures on SWNT may also be helpful for understanding biological systems at the molecular level and for developing new materials

DataSheet_1_Multi-omics profiling reveal responses of three major Dendrobium species from different growth years to medicinal components.docx

Dendrobium is a perennial herb found in Asia that is known for its medicinal and ornamental properties. Studies have shown that the stem is the primary medicinal component of Dendrobium spp. To investigate the effect of the species and age of Dendrobium (in years) on the content of its medicinal components, we collected the stems of 1-to-4-year-old D. officinale, D. moniliforme, and D. huoshanense, sequenced the transcriptome, metabolome, and microbiome, and analyzed the data in a comprehensive multi-omics study. We identified 10,426 differentially expressed genes (DEGs) with 644 differentially accumulated metabolites (DAMs) from 12 comparative groups and mapped the flavonoid pathway based on DEGs and DAMs. Transcriptomic and metabolomic data indicated a general trend of the accumulation of flavonoids exhibiting pharmacological effects in the three Dendrobium species. In addition, joint metabolome and microbiome analyses showed that actinobacteria was closely associated with flavonoid synthesis with increasing age. Our findings provide novel insights into the interactions of flavonoids of Dendrobium with the transcriptome and microbiome.</p

Surface Oxidized Cobalt-Phosphide Nanorods As an Advanced Oxygen Evolution Catalyst in Alkaline Solution

Electrochemical water splitting in alkaline solution plays a growing role in alternative energy devices due to the need for clean and sustainable energy. However, catalysts that are active for both hydrogen evolution and oxygen evolution reactions are rare. Herein, we demonstrate that cobalt phosphide (CoP), which was synthesized via the hydrothermal route and has been shown to have hydrogen evolution activity, is highly active for oxygen evolution. A current density of 10 mA cm^–2 was generated at an overpotential of only 320 mV in 1 M KOH for a CoP nanorod-based electrode (CoP NR/C), which was competitive with commercial IrO₂. The Tafel slope for CoP NR/C was only 71 mV dec^–1, and the catalyst maintained high stability during a 12 h test. This high activity was attributed to the formation of a thin layer of ultrafine crystalline cobalt oxide on the CoP surface

Sulfur-Doped Nickel Phosphide Nanoplates Arrays: A Monolithic Electrocatalyst for Efficient Hydrogen Evolution Reactions

Searching for cost-efficient electrocatalysts with high catalytic activity and stability for hydrogen generation by means of water electrolysis would make a great improvement on energy technologies field. Herein, we report high-performance hydrogen evolution reaction (HER) electrocatalysts based on sulfur-doped Ni₅P₄ nanoplate arrays grown on carbon paper (S–Ni₅P₄ NPA/CP). This ternary, robust, monolithic S–Ni₅P₄ NPA/CP exhibits remarkable performance for the HER compared to nickel phosphide and nickel sulfide catalysts. The S–Ni₅P₄ NPA/CP with ∼6% S presents the most promising behavior for water electrolysis applications. Specifically, it shows an onset potential of 6 mV, needing overpotentials (η) of 56 and 104 mV to attain current densities of 10 and 100 mA cm^–2 with a Tafel slope of 43.6 mV dec^–1. The turnover frequency of 6% S–Ni₅P₄ NPA/CP is about 0.11 s^–1 at overpotential of 100 mV, which is ca. 10 and 40 times that of Ni₅P₄ NPA/CP and NiS₂ NPA/CP, respectively. It also shows remarkable stability and durability in 0.5 M H₂SO₄ solution. The results indicate that S and P tune the electronic properties mutually and produce an active catalyst phase for the HER. Furthermore, the density functional theory calculations show that S–Ni₅P₄ NPA/CP exhibits only 0.04 eV of hydrogen adsorption free energy­(Δ<i>G</i>_H^*), which is more suitable than Pt (∼−0.09 eV). We propose that the S-doping not only restrains the surface oxidation and dissolution of S–Ni₅P₄ NPA/CP in acid solution but also reduces the Δ<i>G</i>_H^*. We believe that our work will provide a new strategy to design transition metal phosphide composite materials for practical applications in catalysis and energy fields

Novel Strategy for Preparing Dual-Modality Optical/PET Imaging Probes via Photo-Click Chemistry

Preparation of small molecule based dual-modality probes remains a challenging task due to the complicated synthetic procedure. In this study, a novel concise and generic strategy for preparing dual-modality optical/PET imaging probes via photo-click chemistry was developed, in which the diazole photo-click linker functioned not only as a bridge between the targeting-ligand and the PET imaging moiety, but also as the fluorophore for optical imaging. A dual-modality AE105 peptidic probe was successfully generated via this strategy and subsequently applied in the fluorescent staining of U87MG cells and the ⁶⁸Ga based PET imaging of mice bearing U87MG xenograft. In addition, dual-modality monoclonal antibody cetuximab has also been generated via this strategy and labeled with ⁶⁴Cu for PET imaging studies, broadening the application of this strategy to include the preparation of macromolecule based imaging probes

Expression of IL-4 and IL-5 by lung CD4⁺ cells in <i>Lilrb4^+/+</i> and <i>Lilrb4</i>^−/− mice.

<p>Mice were sensitized and challenged with OVA as described in the legend for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057007#pone-0057007-g002" target="_blank">Fig. 2</a>. After 18 h, lung mononuclear cells were obtained as described in the legend for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057007#pone-0057007-g001" target="_blank">Fig. 1</a>, and cells were analyzed by intracellular flow cytometry to determine the percentage, number, and MFI of IL-4 and IL-5 in CD4<b>⁺</b> cells. Data from representative experiments show dot plots for IL-4 and IL-5 (A); positivity was defined as cells that had fluorescence intensities greater than that of 99% of the same population of cells when stained with an equal amount of isotype control mAbs. Compiled data for IL-4 (B) and IL-5 (C) are expressed as mean ± SEM, <i>n</i> = 8.</p

Superior Selective CO₂ Adsorption of C₃N Pores: GCMC and DFT Simulations

Development of high-performance sorbents is extremely significant for CO₂ capture due to its increasing atmospheric concentration and impact on environmental degradation. In this work, we develop a new model of C₃N pores based on GCMC calculations to describe its CO₂ adsorption capacity and selectivity. Remarkably, it exhibits an outstanding CO₂ adsorption capacity and selectivity. For example, at 0.15 bar it shows exceptionally high CO₂ uptakes of 3.99 and 2.07 mmol/g with good CO₂/CO, CO₂/H₂, and CO₂/CH₄ selectivity at 300 and 350 K, separately. More importantly, this adsorbent also shows better water stability. Specifically, its CO₂ uptakes are 3.80 and 5.91 mmol/g for and 0.15 and 1 bar at 300 K with a higher water content. Furthermore, DFT calculations demonstrate that the strong interactions between C₃N pores and CO₂ molecules contribute to its impressive CO₂ uptake and selectivity, indicating that C₃N pores can be an extremely promising candidate for CO₂ capture

Expression of CCR7 on lung DCs in <i>Lilrb4^+/+</i> and <i>Lilrb4</i>^−/− mice.

<p>Mice were sensitized with OVA/LPS and challenged with AF-OVA as described in the legend for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057007#pone-0057007-g001" target="_blank">Fig. 1</a>. After 4 h, lung mononuclear cells were obtained as described in the legend for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057007#pone-0057007-g001" target="_blank">Fig. 1</a>, and CD11c^+/autofluorescence<b>⁻</b> cells were analyzed by flow cytometry for the percentage (<i>A</i>) and MFI (<i>B</i>) of CCR7 expression on AF-OVA<b>⁺</b> and AF-OVA<b>⁻</b> DCs. Fluorescence compensation was set for each color such that there was no cross-talk between detection channels. Data are expressed as mean ± SEM, <i>n</i> = 5.</p

Fluorine-Doped Carbon Blacks: Highly Efficient Metal-Free Electrocatalysts for Oxygen Reduction Reaction

For the goal of practical industrial development of fuel cells, inexpensive, sustainable, and high performance electrocatalysts for oxygen reduction reactions (ORR) are highly desirable alternatives to platinum (Pt) and other rare materials. In this work, sustainable fluorine (F)-doped carbon blacks (CB-F) as metal-free, low-cost, and high-performance electrocatalysts for ORR were synthesized for the first time. The performance (electrocatalytic activity, long-term operation stability, and tolerance to poisons) of the best one (BP-18F, based on Black Pearls 2000 (BP)) is on the same level as Pt-based or other best non-Pt-based catalysts in alkaline medium. The maximum power density of alkaline direct methanol fuel cell with BP-18F as the cathode (3 mg/cm²) is ∼15.56 mW/cm² at 60 °C, compared with a maximum of 9.44 mW/cm² for commercial Pt/C (3 mg_Pt/cm²). All these results unambiguously demonstrate that these sustainable CB-F catalysts are the most promising alternatives to Pt in an alkaline fuel cell. Since sustainable carbon blacks are 10 000 times less expensive and much more abundant than Pt or other rare materials, these CB-F electrocatalysts possess the best price/performance ratio for ORR to date