Search

Most learning algorithms for deep neural networks (DNNs) employ gradient descent or block coordinate descent, which involves the direct application of a non-linear activation function throughout the course of optimization, such that only the input and output of the activation function are optimized. By contrast, the “un-rectifying” technique expresses a non-linear point-wise (non-smooth) activation function as a data-dependent variable (activation variable), which means that the activation variable along with its input and output can all be employed in optimization. The fact that the ReLU network in this study was un-rectified means that the activation functions could be replaced with data-dependent activation variables in the form of equations and equality constraints. The discrete nature of activation variables associated with un-rectifying ReLUs allows the reformulation of deep learning problems as problems of combinatorial optimization. However, we demonstrate that the optimal solution to a combinatorial optimization problem can be preserved by relaxing the discrete domains of activation variables to closed intervals in a real domain. We also demonstrate it is possible to optimize a network based on the augmented Lagrangian approach. This means that our method could theoretically achieve global convergence where all limit points are critical points of the learning problem. In experiments and comparisons with other methods addressing classification and compressed sensing recovery problems, the proposed approach makes it easier to learn a network to a given degree of accuracy within a small number of epochs. [ABSTRACT FROM AUTHOR]

Extracting multiple unknown sources from a single observation of a single-channel is an ill-posed problem encountered in a variety of applications. This paper characterizes the ambiguity of solutions to the source separation problem, and then proposes a novel adaptive-operator-based approach to deriving solutions based on a combination of separation operators and domain-specific knowledge related to sources. The proposed scheme involves transforming the original problem into a new problem, in which data-dependent operators and the unknown sources are variables to be optimized. We demonstrate that a solution to the proposed optimization problem must reside in the null spaces of the operators, and any such solution also provides an optimal value to the original problem. We then demonstrate the applicability of the proposed method to the separation of sparse sources as well as AM-FM sources. Note that the proposed scheme outperformed corresponding state-of-the-art methods in noiseless as well as noisy environments. Finally, we demonstrate the efficacy of the proposed scheme in separation tasks based on real-world ECG data (i.e., extracting fetal ECG signals from noisy observations in which maternal and fetal ECGs recordings are superimposed) and electrical data (i.e.,separating singularities from harmonic components in an observation of noisy data related to surges in electrical current). [ABSTRACT FROM AUTHOR]

Genus Pleurotus spp. contains many edible fungi with high nutritional value, medicinal value, and ease of growth. Cultivation of Pleurotus faces many problems including poor quality of mushroom spawn, low biological efficiency, and slow growth. In this study, we performed species identification using ITS marker and antioxidant capacity evaluation on 27 Pleurotus mycelia strains from MARDI's mushroom bank. Furthermore, important characteristics such as biological efficiency, complete growth, and antioxidant capacity were evaluated for 10 selected fruiting bodies of Pleurotus pulmonarius. Strain MP34 was the most suitable strain for commercial production, whereas mycelial strain MP42, MP52, and MP28 were suitable for the extraction of biologically active compounds. Our findings contributed and identified high‐quality strains for the local Malaysian mushroom farmers. Future studies will focus on parameters such as substrate and supplements selection and bag preparation for the improvement of Pleurotus cultivation. Novelty impact statement: This study evaluated the potential of using ITS markers and antioxidant profiling to identify high‐quality Pleurotus strain, which can be subsequently used for the quality control of Pleurotus mycelia culture in the mushroom bank and even by the farmer. [ABSTRACT FROM AUTHOR]

Frames are the foundation of the linear operators used in the decomposition and reconstruction of signals, such as the discrete Fourier transform, Gabor, wavelets, and curvelet transforms. The emergence of sparse representation models has shifted the emphasis in frame theory toward sparse-norm minimization problems. In this paper, we apply frame theory to the sparse representation of signals, wherein a frame is used for synthesis dictionary and a dual frame is used for analysis dictionary. Our objective was to formulate a novel dual-frame design in which the sparse vector obtained through the decomposition of any signal is also the sparse solution representing signals based on a reconstruction frame. Our findings demonstrate that this type of dual frame cannot be constructed for overcomplete frames, thereby precluding the use of any linear analysis operator to derive the sparse synthesis coefficient for signal representation. We also developed a novel dictionary learning algorithm (called Parseval K-SVD) to learn a tight-frame dictionary with normalized atoms. We then dealt with the problem of signal representation using frames from the analysis and synthesis perspective to derive optimization formulations for problems pertaining to image recovery. Our preliminary results demonstrate that the images recovered using this approach are correlated with the frame bounds of dictionaries, thereby demonstrating the importance of using different dictionaries for different applications. [ABSTRACT FROM AUTHOR]

The reactivity of the >CH and >NH groups of barbituric acid (BTA) toward the two terminal -C=C- groups of N,N'-bismaleimide-4,4′-diphenylmethane (BMI) was studied with the aid of three model compounds (N-phenylmaleimide (PMI) containg one -C=C- group, 1,3-dimethylbarbituric acid (1,3DMBTA) containing 1 >CH group and 5,5-dimethylbarbituric acid (5,5DMBTA) containing 2 >NH groups per molecule) and a molecular probe (hydroquinone (HQ)) that was capable of detecting free radical polymerization. Kinetics studies (DSC) and molecular structure characterization (H-NMR) showed that it was the >CH group of BTA that predominated in the isothermal polymerization of BMI with BTA in N-methyl-2-pyrrolidone in the temperature range 373-403 K. On the contrary, the 2 >NH groups of BTA did not contribute to polymerization of BMI with BTA to an appreciate extent. [ABSTRACT FROM AUTHOR]

From the perspective of the Bayesian approach, the denoising problem is essentially a prior probability modeling and estimation task. In this paper, we propose an approach that exploits a hidden Bayesian network, constructed from wavelet coefficients, to model the prior probability of the original image. Then, we use the belief propagation (BP) algorithm, which estimates a coefficient based on all the coefficients of an image, as the maximum-a-posterior (MAP) estimator to derive the denoised wavelet coefficients. We show that if the network is a spanning tree, the standard BP algorithm can perform MAP estimation efficiently. Our experiment results demonstrate that, in terms of the peak-signal-to-noise-ratio and perceptual quality, the proposed approach outperforms state-of-the-art algorithms on several images, particularly in the textured regions, with various amounts of white Gaussian noise. [ABSTRACT FROM PUBLISHER]

Homogeneous catalysts PtCl2[5,5′-bis-(n-ClCF2(CF2)3CH2OCH2)-2,2′-bpy] (2A) and PtCl2[5,5′-bis-(n-HCF2(CF2)3CH2OCH2)-2,2′-bpy] (2B), which contained short fluorous chains, were synthesized and used in catalysis of hydrosilylation of alkynes. In these reactions the thermomorphic mode was effectively used to recover these catalysts from the reaction mixture up to eight cycles by taking advantage of heterogeneous phase separation at ice temperature. This kind of catalysis had previously been observed in fluorous catalysts of platinum containing about 50% F-content, but in this work the percentage of F-content is decreased to only about 30%, by which we termed them as "very light fluorous". Our new type of catalyst with limited number of F-content is considered as the important discovery in the fluorous technology field as the reduced number of fluorine atoms will help to be able to comply the EPA 8-carbon rule. The metal leaching after the reaction has been examined by ICP-MS, and the testing results show the leaching of residual metal to be minimal. Additionally, comparing these results to our previous work, fluorous chain assisted selectivity has been observed when different fluorous chain lengths of the catalysts are used. It has been found that there exists fluorous chain assisted better selectivity towards β-(E) form in the Pt-catalyzed hydrosilylation of non-symmetric terminal alkyne when the Pt catalyst contains short fluorous chain (i.e., 4 Cs). Phenyl acetylenes showed the opposite regioselectivity due to pi-pi interaction while using the same catalyst via Markovnikov's addition to form terminal vinyl silane, which is then a major product for Pt-catalyzed hydrosilylation of terminal aryl acetylene with triethylsilane. Finally, the kinetic studies indicate that the insertion of alkyne into the Pt-H bond is the rate-determining step. [ABSTRACT FROM AUTHOR]

The objective of this study was to synthesize the 9-/13-position substituted berberine derivatives and evaluate their cytotoxic and photocytotoxic effects against three human cancer cell lines. Among all the synthesized compounds, 9-O-dodecyl- (5e), 13-dodecyl- (6e), and 13-O-dodecyl-berberine (7e) exhibited stronger growth inhibition against three human cancer cell lines, (HepG2, HT-29 and BFTC905), in comparison with structurally related berberine (1). These three compounds also showed the photocytotoxicity in human cancer cells in a concentration-dependent and light dose-dependent manner. Through flow cytometry analysis, we found out a lipophilic group at the 9-/13-position of berberine may have facilitated its penetration into test cells and hence enhanced its photocytotoxicity on the human liver cancer cell HepG2. Further, in cell cycle analysis, 5e, 6e, and 7e induced HepG2 cells to arrest at the S phase and caused apoptosis upon irradiation. In addition, photodynamic treatment of berberine derivatives 5e, 6e, and 7e again showed a significant photocytotoxic effects on HepG2 cells, induced remarkable cell apoptosis, greatly increased intracellular ROS level, and the loss of mitochondrial membrane potential. These results over and again confirmed that berberine derivatives 5e, 6e, and 7e greatly enhanced photocytotoxicity. Taken together, the test data led us to conclude that berberine derivatives with a dodecyl group at the 9-/13-position could be great candidates for the anti-liver cancer medicines developments. [ABSTRACT FROM AUTHOR]