Using combination of lifting wavelet and multiclass SVM based on global optimization class strategy for fault pattern identification

This paper presents a new method based on lifting wavelet for obtaining a fast multiclass SVM classification based on global optimization class strategy for fault diagnosis of roller bearing. Decision making was performed in two stages: feature extraction by computing the lifting wavelet coefficients and classification using the multiclass SVM classifiers trained on the extracted features. Experiments demonstrate that in comparison to discrete wavelet transform the lifting wavelet feature extraction can speed up the identification phase as well as achieve higher accuracy of multiclass SVM that is based on global optimization class strategy. Experimental results also reveal that the proposed multiclass SVM of global optimization is better than strategy of one against one and DAGSVM

Rare Copy Number Variations and Predictors in Children With Intellectual Disability and Epilepsy

Introduction: The concurrence of intellectual disability/global developmental delay and epilepsy (ID/GDD-EP) is very common in the pediatric population. The etiologies for both conditions are complex and largely unknown. The predictors of significant copy number variations (CNVs) are known for the cases with ID/GDD, but unknown for those with exclusive ID/GDD-EP. Importantly, the known predictors are largely from the same ethnic group; hence, they lack replication.Purpose: We aimed to determine and investigate the diagnostic yield of CNV tests, new causative CNVs, and the independent predictors of significant CNVs in Chinese children with unexplained ID/GDD-EP.Materials and methods: A total of 100 pediatric patients with unexplained ID/GDD-EP and 1,000 healthy controls were recruited. The American College of Medical Genetics guideline was used to classify the CNVs. Additionally, clinical information was collected and compared between those with significant and non-significant CNVs.Results: Twenty-eight percent of the patients had significant CNVs, 16% had variants of unknown significance, and 56% had non-significant CNVs. In total, 31 CNVs were identified in 28% (28/100) of cases: 25 pathogenic and 6 likely pathogenic. Eighteen known syndromes were diagnosed in 17 cases. Thirteen rare CNVs (8 novel and 5 reported in literature) were identified, of which three spanned dosage-sensitive genes: 19q13.2 deletion (ATP1A3), Xp11.4-p11.3 deletion (CASK), and 6q25.3-q25.3 deletion (ARID1B). By comparing clinical features in patients with significant CNVs against those with non-significant CNVs, a statistically significant association was found between the presence of significant CNVs and speech and language delay for those aged above 2 years and for those with facial malformations, microcephaly, congenital heart disease, fair skin, eye malformations, and mega cisterna magna. Multivariate logistic regression analysis allowed the identification of two independent significant CNV predictors, which are eye malformations and facial malformations.Conclusion: Our study supports the performance of CNV tests in pediatric patients with unexplained ID/GDD-EP, as there is high diagnostic yield, which informs genetic counseling. It adds 13 rare CNVs (8 novel), which can be accountable for both conditions. Moreover, congenital eye and facial malformations are clinical markers that can aid clinicians to understand which patients can benefit from the CNV testing and which will not, thus helping patients to avoid unnecessary and expensive tests

Using combination of lifting wavelet and multiclass SVM based on global optimization class strategy for fault pattern identification

This paper presents a new method based on lifting wavelet for obtaining a fast multiclass SVM classification based on global optimization class strategy for fault diagnosis of roller bearing. Decision making was performed in two stages: feature extraction by computing the lifting wavelet coefficients and classification using the multiclass SVM classifiers trained on the extracted features. Experiments demonstrate that in comparison to discrete wavelet transform the lifting wavelet feature extraction can speed up the identification phase as well as achieve higher accuracy of multiclass SVM that is based on global optimization class strategy. Experimental results also reveal that the proposed multiclass SVM of global optimization is better than strategy of one against one and DAGSVM

Protective Effects of a Rhodiola Crenulata Extract and Salidroside on Hippocampal Neurogenesis against Streptozotocin-Induced Neural Injury in the Rat

Previously we have demonstrated that a Rhodiola crenulata extract (RCE), containing a potent antioxidant salidroside, promotes neurogenesis in the hippocampus of depressive rats. The current study was designed to further investigate the protective effect of the RCE on neurogenesis in a rat model of Alzheimer's disease (AD) induced by an intracerebroventricular injection of streptozotocin (STZ), and to determine whether this neuroprotective effect is induced by the antioxidative activity of salidroside. Our results showed that pretreatment with the RCE significantly improved the impaired neurogenesis and simultaneously reduced the oxidative stress in the hippocampus of AD rats. In vitro studies revealed that (1) exposure of neural stem cells (NSCs) from the hippocampus to STZ strikingly increased intracellular reactive oxygen species (ROS) levels, induced cell death and perturbed cell proliferation and differentiation, (2) hydrogen peroxide induced similar cellular activities as STZ, (3) pre-incubation of STZ-treated NSCs with catalase, an antioxidant, suppressed all these cellular activities induced by STZ, and (4) likewise, pre-incubation of STZ-treated NSCs with salidroside, also an antioxidant, suppressed all these activities as catalase: reduction of ROS levels and NSC death with simultaneous increases in proliferation and differentiation. Our findings indicated that the RCE improved the impaired hippocampal neurogenesis in the rat model of AD through protecting NSCs by its main ingredient salidroside which scavenged intracellular ROS

Ni-based bimetallic heterogeneous catalysts for energy and environmental applications

Bimetallic catalysts have attracted extensive attention for a wide range of applications in energy production and environmental remediation due to their tunable chemical/physical properties. These properties are mainly governed by a number of parameters such as compositions of the bimetallic systems, their preparation method, and their morphostructure. In this regard, numerous efforts have been made to develop “designer” bimetallic catalysts with specific nanostructures and surface properties as a result of recent advances in the area of materials chemistry. The present review highlights a detailed overview of the development of nickel-based bimetallic catalysts for energy and environmental applications. Starting from a materials science perspective in order to obtain controlled morphologies and surface properties, with a focus on the fundamental understanding of these bimetallic systems to make a correlation with their catalytic behaviors, a detailed account is provided on the utilization of these systems in the catalytic reactions related to energy production and environmental remediation. We include the entire library of nickel-based bimetallic catalysts for both chemical and electrochemical processes such as catalytic reforming, dehydrogenation, hydrogenation, electrocatalysis and many other reactions

Graphene-Based Nanocomposites for Energy Storage

Since the first report of using micromechanical cleavage method to produce graphene sheets in 2004, graphene/graphene-based nanocomposites have attracted wide attention both for fundamental aspects as well as applications in advanced energy storage and conversion systems. In comparison to other materials, graphene-based nanostructured materials have unique 2D structure, high electronic mobility, exceptional electronic and thermal conductivities, excellent optical transmittance, good mechanical strength, and ultrahigh surface area. Therefore, they are considered as attractive materials for hydrogen (H2) storage and high-performance electrochemical energy storage devices, such as supercapacitors, rechargeable lithium (Li)-ion batteries, Li–sulfur batteries, Li–air batteries, sodium (Na)-ion batteries, Na–air batteries, zinc (Zn)–air batteries, and vanadium redox flow batteries (VRFB), etc., as they can improve the efficiency, capacity, gravimetric energy/power densities, and cycle life of these energy storage devices. In this article, recent progress reported on the synthesis and fabrication of graphene nanocomposite materials for applications in these aforementioned various energy storage systems is reviewed. Importantly, the prospects and future challenges in both scalable manufacturing and more energy storage-related applications are discussed

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

Measurement of ultra-high-energy diffuse gamma-ray emission of the Galactic plane from 10 TeV to 1 PeV with LHAASO-KM2A

The diffuse Galactic $\gamma$-ray emission, mainly produced via interactions between cosmic rays and the interstellar medium and/or radiation field, is a very important probe of the distribution, propagation, and interaction of cosmic rays in the Milky Way. In this work we report the measurements of diffuse $\gamma$-rays from the Galactic plane between 10 TeV and 1 PeV energies, with the square kilometer array of the Large High Altitude Air Shower Observatory (LHAASO). Diffuse emissions from the inner ($15^{\circ}<l<125^{\circ}$, $|b|<5^{\circ}$) and outer ($125^{\circ}<l<235^{\circ}$, $|b|<5^{\circ}$) Galactic plane are detected with $29.1\sigma$ and $12.7\sigma$ significance, respectively. The outer Galactic plane diffuse emission is detected for the first time in the very- to ultra-high-energy domain ($E>10$~TeV). The energy spectrum in the inner Galaxy regions can be described by a power-law function with an index of $-2.99\pm0.04$, which is different from the curved spectrum as expected from hadronic interactions between locally measured cosmic rays and the line-of-sight integrated gas content. Furthermore, the measured flux is higher by a factor of $\sim3$ than the prediction. A similar spectrum with an index of $-2.99\pm0.07$ is found in the outer Galaxy region, and the absolute flux for $10\lesssim E\lesssim60$ TeV is again higher than the prediction for hadronic cosmic ray interactions. The latitude distributions of the diffuse emission are consistent with the gas distribution, while the longitude distributions show clear deviation from the gas distribution. The LHAASO measurements imply that either additional emission sources exist or cosmic ray intensities have spatial variations.Comment: 12 pages, 8 figures, 5 tables; accepted for publication in Physical Review Letters; source mask file provided as ancillary fil

Does or did the supernova remnant Cassiopeia A operate as a PeVatron?

For decades, supernova remnants (SNRs) have been considered the prime sources of Galactic Cosmic rays (CRs). But whether SNRs can accelerate CR protons to PeV energies and thus dominate CR flux up to the knee is currently under intensive theoretical and phenomenological debate. The direct test of the ability of SNRs to operate as CR PeVatrons can be provided by ultrahigh-energy (UHE; $E_\gamma \geq 100$~TeV) $\gamma$-rays. In this context, the historical SNR Cassiopeia A (Cas A) is considered one of the most promising target for UHE observations. This paper presents the observation of Cas A and its vicinity by the LHAASO KM2A detector. The exceptional sensitivity of LHAASO KM2A in the UHE band, combined with the young age of Cas A, enabled us to derive stringent model-independent limits on the energy budget of UHE protons and nuclei accelerated by Cas A at any epoch after the explosion. The results challenge the prevailing paradigm that Cas A-type SNRs are major suppliers of PeV CRs in the Milky Way.Comment: 11 pages, 3 figures, Accepted by the APJ

Approaches in biotechnological applications of natural polymers

Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)