Generation Of Different Types Research Articles

Development of large-scale synthetic 3D point cloud datasets for vision-based bridge structural condition assessment

Visual recognition of 3D point cloud data of bridge inspection scenes is a key step in automating the visual inspection process, which is currently largely manual and inefficient. To alleviate the lack of large-scale annotated point cloud datasets for training such 3D visual recognition algorithms, this research investigates an approach for developing large-scale synthetic point cloud datasets. The proposed approach proceeds in four steps: (1) random generation of different types of bridges in computer graphics environments; (2) sampling of camera trajectories that represent data collection scenarios during bridge inspection; (3) 3D reconstruction using Structure from Motion (SfM) applied to rendered synthetic images; (4) automated annotation of the reconstructed point cloud using ground truth masks obtained with synthetic images. Besides, this research proposes to store point uncertainty information defined by the error between the ground truth depth and the depth calculated from the SfM results. Prior to training, thresholds can be applied to this uncertainty information to control the levels of outliers in the dataset. This research demonstrates the proposed approach by generating point cloud datasets for two data collection scenarios. The effectiveness of the generated datasets is investigated by training 3D semantic segmentation algorithms and evaluating the performance on real and synthetic point cloud data. The proposed approach for point cloud dataset generation will facilitate the development of generalizable and high level-of-detail 3D recognition algorithms toward autonomous bridge inspection.

Recreational Ecosystem Services in the Qinghai–Tibet Plateau National Park Group: Mapping, Monetization, and Evaluation

Recreational Ecosystem Services in the Qinghai–Tibet Plateau National Park Group: Mapping, Monetization, and Evaluation

Алгоритми стабілізації швидкості обертів ротора Дар’є вітро-енергетичної установки, керованого змінами довжини лопатей

The world’s power engineering features ever increasing attention to the development of renewable power sources. Difficulties in provision with traditional energy sources (gas, coal, and oil products) and the global trends of transition to green sources call for replacing the traditional sources with new ones. Among the alternative energy sources, wind power plants (WPPs) installed in suitable territories have received widespread use. Modern WPPs are of two types: vertical- and horizontal-axis ones. Vertical-axis WPPs, as distinct from horizontal-axis ones, have a number of specific advantages, such as, for example, insensitivity to wind direction changes, which significantly simplify the WPP design and increase the WPP reliability. Both WPP types are dynamically complex systems, which operate in different regimes depending on their dynamic and technological features. The task of matching these features is assigned to control systems, which control the rotor operation using additional devices, for example, generators of different types. For horizontal-axis WPPs, approaches to the solution of a number of system control problems have been developed on the basis of the principle of swept area variation. The development of a similar approach for vertical-axis WPPs seems to be an important and promising task. The goal of this paper is to develop efficient algorithms of WPP rotor speed stabilization using the principle of swept area variation, namely, telescopic blades. The problem is solved using methods of the classical automatic control theory and mathematical simulation. The novelty lies in extending the concept of control by swept area variation to Darrieus vertical-axis WPPs, synthesizing efficient algorithms for stabilizing the rotor speed of Darrieus vertical-axis WPPs controlled by blade length variation, and determining conditions for their stability. The algorithms may be used in substantiating design solutions for Darrieus rotor vertical-axis WPPs.

Neurons and astrocytes derived from human iPSCs to model Alzheimer´s disease

AbstractBackgroundAlzheimer’s disease (AD) is characterized by presenting a complex pathology, not fully resolved yet. This fact, together with the lack of reliable models, has impeded the development of effective therapies. Recently, several studies have shown that functional glial cell defects have a key role in the pathology of AD. However, this glial dysfunction, currently, cannot be correctly modeled using the available animal models, so we hypothesized that cells derived from Alzheimer’s patients can serve as a better platform for studying the disease. In this sense, human pluripotent stem cells (hPSC) allow the generation of different types of neural cells, which can be used for disease modeling, identification of new targets and drugs development.MethodWe have a collection of hiPSCs derived from patients with sporadic forms of AD stratified based on APOE genotype. We have differentiated these cells towards neural cells and mature them to neurons or astrocytes using a serum‐free approach, to assess intrinsic differences between those derived from AD patients or healthy controls.ResultWe have implemented a serum‐free approach and generated neural precursors and astrocytes from all the lines tested. We observe differences at the phenotypic level and a reduced capacity to differentiate towards neural lineage in those lines derived from APOE4 carriers.ConclusionOur preliminary data suggest intrinsic differences in the neural differentiation capacity between cell lines derived from APOE4 or APOE3 carrier subjects. Further experiments would contribute to elucidate novel pathogenic pathways associated with neurodegeneration and susceptible of therapeutic modulation, likely contributing to the development of new effective drugs against AD.Acknowledgments: This study was supported by Instituto de Salud Carlos III (ISCiii) of Spain, co‐financed by FEDER funds from European Union, through grants PI21/00915 (to AG) and PI21/00914 (to JV); by Junta de Andalucia through Consejería de Economía y Conocimiento grants UMA20‐FEDERJA‐048 (to JAGL), PY18‐RT‐2233 (to AG) and US‐1262734 (to JV) co‐financed by Programa Operativo FEDER 2014‐2020, University of Malaga (B1‐2020_04) to JAGL and Programa Operativo de Empleo Juvenil SNGJ4‐11 to LCP.

N-linked glycans: an underappreciated key determinant of T cell development, activation, and function.

N-linked glycosylation is a post-translational modification that results in the decoration of newly synthesized proteins with diverse types of oligosaccharides that originate from the amide group of the amino acid asparagine. The sequential and collective action of multiple glycosidases and glycosyltransferases are responsible for determining the overall size, composition, and location of N-linked glycans that become covalently linked to an asparagine during and after protein translation. A growing body of evidence supports the critical role of N-linked glycan synthesis in regulating many features of T cell biology, including thymocyte development and tolerance, as well as T cell activation and differentiation. Here, we provide an overview of how specific glycosidases and glycosyltransferases contribute to the generation of different types of N-linked glycans and how these post-translational modifications ultimately regulate multiple facets of T cell biology.

Histological characterization of the human masticatory oral mucosa. A histochemical and immunohistochemical study.

Histology of human oral mucosa is closely related with its function and anatomical location, and a proper characterization of the human masticatory oral mucosa could be very useful in periodontal pathology. In the present work, we have carried out a comprehensive study in order to determine the main histological features of parakeratinized (POM) and orthokeratinized (OOM) masticatory human oral mucosa using light and electron microscopy. To perform this, we have used several histological, histochemical and immunohistochemical methods to detect key markets at the epithelial, basement membrane and connective tissue levels. Our results demonstrated that POM and OOM share many histological similarities, as expected. However, important differences were observed at the epithelial layer of POM, that was significantly thicker than the epithelial layer found in OOM, especially due to a higher number of cells at the stratum spinosum. The expression pattern of CK10 and filaggrin revealed intense signal expression in OOM as compared to POM. Collagen and proteoglycans were more abundant in OOM stroma than in POM. No differences were found for blood vessels and basement membrane. These results may contribute to a better understanding of the pathological conditions affecting the human masticatory oral mucosa. In addition, these findings could be useful for the generation of different types of oral mucosa by tissue engineering techniques. Microscopical features of parakeratinized and orthokeratinized masticatory human oral mucosa showed important differences at both, epithelial and stromal levels. Parakeratinized masticatory human oral mucosa exert thicker epithelial layer, especially, at the stratum spinosum in comparison to orthokeratinized human oral mucosa. Cytokeratin 10 and filaggrin human epithelial markers were intensively expressed in orthokeratinized masticatory human oral mucosa in comparison to parakeratinized masticatory human oral mucosa. At the stromal level, orthokeratinized masticatory human oral mucosa exhibit higher levels of collagen and proteoglycans than parakeratinized masticatory oral mucosa. The deep knowledge of histological features of masticatory oral mucosa could lead to a better understanding of oral mucosa pathology and advanced treatments.

Unraveling the Challenges of Oxidative Stability and Methods for Assessing Oxidation of Commercial Oils: A Review

Edible oils are among the most crucial nutritional constituents as these are utilized for frying or cuisine. Though, these oils are prone towards oxidative deterioration from manufacturing to transportation due to environmental exposure as well as storage conditions which result in generation of different types of oxidation products. The generation of primary and secondary products result in harmful impacts on human health and may also result in cardiovascular diseases in consumers. The mechanism of oxidative deterioration cannot be assessed easily due to complexity of the reaction under which it may take place. Different types of approaches have been proposed to determine the products generated as a result of oxidation so that safety for their user can be assured. Different types of analytical techniques can be employed in addition to chemical methods so that analysis of oxidative deterioration can be done completely. The proposed study is aimed to assess the oxidative stability of oils in addition to the factors which can influence oxidation of these oils under different conditions. This review also summarize the classical and advanced state of the art analytical techniques which has recently been developed in different possible ways and effectively can be employed for analysis of oxidative deterioration of edible oils. This article possibly will oblige as a reference in the assortment, establishing, and enhancement of approaches for investigating the oxidative stability of edible oil.

Gold Nanomaterial‐Based Optical Modulators for Wideband Pulse Laser Generation

Pulsed lasers have wide applications in several fields, such as basic research, telecommunications, and industrial materials processing. A saturable absorber (SA) is a key component for pulse laser generation. However, the current SAs exhibit certain limitations. Hence, developing new nonlinear optical materials as SAs for pulse lasers generation is significantly important in ultrafast photonics and related applications. Metallic nanomaterials have attracted considerable attention because of their higher nonlinearity coefficients and wideband nonlinear response, which are induced by the surface plasmon resonance (SPR) effect. The SPR effect depends on the size and morphology of materials. Thus, the nonlinear optical absorption effect of gold nanomaterials for pulse laser generation must be explored. In this review, the optical properties of gold nanomaterials are introduced, including SPR absorption, photoluminescence properties, and surface‐enhanced Raman scattering effect. Then, the synthesis and characterization of different gold nanomaterials are reviewed. Subsequently, the nonlinear optical characteristics and devices based on gold nanomaterials are also introduced. Furthermore, the generation of different types of lasers using gold nanomaterial‐based devices is also reviewed. A comparison between gold nanomaterials and other SA materials is presented. Finally, the conclusion and outlook on gold nanomaterial‐based nonlinear optical devices are presented.

4-F-PCP, a Novel PCP Analog Ameliorates the Depressive-Like Behavior of Chronic Social Defeat Stress Mice via NMDA Receptor Antagonism.

Major depressive disorder is a leading cause of disability in more than 280 million people worldwide. Monoamine-based antidepressants are currently used to treat depression, but delays in treatment effects and lack of responses are major reasons for the need to develop faster and more efficient antidepressants. Studies show that ketamine (KET), a PCP analog, produces antidepressant effects within a few hours of administration that lasts up to a week. However, the use of KET has raised concerns about side effects, as well as the risk of abuse. 4 -F-PCP analog is a novel PCP analog that is also an NMDA receptor antagonist, structurally similar to KET, and might potentially elicit similar antidepressant effects, however, there has been no study on this subject yet. Herein, we investigate whether 4-F-PCP displays antidepressant effects and explored their potential therapeutic mechanisms. 4-F-PCP at 3 and 10 mg/kg doses showed antidepressant-like effects and repeated treatments maintained its effects. Furthermore, treatment with 4-F-PCP rescued the decreased expression of proteins most likely involved in depression and synaptic plasticity. Changes in the excitatory amino acid transporters (EAAT2, EAAT3, EAAT4) were also seen following drug treatment. Lastly, we assessed the possible side effects of 4-F-PCP after long-term treatment (up to 21 days). Results show that 4-F-PCP at 3 mg/kg dose did not alter the cognitive function of mice. Overall, current findings provide significant implications for future research not only with PCP analogs but also on the next generation of different types of antidepressants.

Generation of soliton molecules in mode-locked erbium-doped fiber laser by InSb saturable absorber

Conventional solitons (CSs), and soliton molecules (SMs) consisting of two and three CSs in a passively mode-locked erbium-doped fiber (EDF) laser based on InSb saturable absorber (SA) are demonstrated. The InSb SA coated on tapered single-mode fibers by magnetron-sputtering deposition (MSD) method possesses linear transmittance of 93.39 %, modulation depth of 2.8 %, and saturation peak power of 3.18 W, respectively. In the CSs operation, the oscillating wavelength is centered at 1570.38 nm with pulse duration of 540.74 fs, pulse repetition rate of 28.38 MHz and maximum average output power of 5.51 mW. In the SMs operation, tight bound SMs consisting of two solitons, and loose bound SMs consisting of two and three solitons are achieved and analyzed in detail. It’s concluded that the initial temporal separation between neighboring solitons (TSNS) is totally decided by the cavity parameters. In the formed SMs, the ratio of TSNS to soliton pulse duration can even be as large as several hundreds of times. The adoption of real SA is more advantageous than effective one to realize the modulation of initial TSNS and hence facilitates the generation of different types of SMs. The work, for the first time, verifies the feasibility and stability of SMs generation by InSb-based SA, which not only enriches the insight of InSb two-dimensional (2D) materials, but also achieves an in-depth understanding of SMs.

Effective hydrolysis for waste plant biomass impacts sustainable fuel and reduced air pollution generation: A comprehensive review

Among various natural biowastes availability in the environment, agricultural residues showed great impacts. It is due to huge availability and cheap carbon source, creating big challenges for their utility and systematic reduction. Objective of this review is to address the waste biomass availability and huge quantities issues and also put effort to minimize this nutrient load via biotransforming into value-added products. Different wastes (organic/inorganic) generation with their negative issues are due to numbers of developmental and social activities, reported. Currently, various efforts are found for these wastes minimization via generation of different types of value-added products (biogas, bioH2, alcoholic fuel, organic acids and others products) and these wastes in municipal cities are also reported with production of advanced biofuels as promising outcomes. For hydrolysis of complex organic resources including lignocellulosic biomasses, physicochemical, structural or compositional changes are needed that aid in conversion into sugar and organic compounds such as biofuels. So, efficient and effective pretreatment processes selection (physical, biological, chemical or combined one) is critical to achieve these hydrolysis goals and resultant cellulose or hemicellulose components can be accessible by biological catalysis. These can achieve final hydrolysis and fermentative or monomer sugars. And later, synthesis of fuels or value-added products during microbial fermentation or biotransformation processes can be achieved. This review discusses pretreatment techniques for improved hydrolysis for fermentative sugar with emphasis on reduced quantities of toxic compounds (furfural compound) in hydrolyzed biomasses. Minimum deterioration fuel economy also reported with production of different bioproducts including biofuels. Additionally, impacts of toxic products and gasses emission are also discussed with their minimization.

Tailoring the phase evolution of molybdenum-based nanocrystals in carbon nanofibers for enhanced performance of lithium-ion batteries

The design and development of flexible and free-standing molybdenum (Mo)-based composite nanomaterials have aroused intensive attention in the fields of electrocatalysis, energy storage, and wearable electronics. In this study, novel nanocomposite membranes constructed with Mo-based compound nanocrystals loaded carbon nanofibers (CNFs) were successfully generated by a combination of electrospinning molybdenum acetylacetone-contained polyacrylonitrile (PAN) solution and subsequent annealing process from 580 to 900 ºC. The relationship and mechanisms between the generation of different types of Mo-based nanocrystals and the annealing temperature were systematically explored. It was found that MoO2 nanocrystals were formed when the annealing temperature was 580 °C. With the temperature increasing, Mo2N nanocrystals began to form due to the reaction between the formed MoO2 and the N atoms in the PAN macromolecules. At higher temperature like 669 °C, Mo2C nanocrystals started to form due to the reaction between Mo2N and C atoms in the carbonized PAN macromolecules, and single-phase Mo2C nanocrystals were produced in CNFs at 900 ºC. Then, a series of flexible CNF-based nanocomposite membranes embedded with various different types of Mo-based compound nanocrystals were generated by effectively controlling the annealing temperature, which were all utilized as anodes for the construction of lithium-ion batteries. Electrochemical measurements showed that the anode materials annealed at 600 oC possessed the highest specific capacity, which were due to the high theoretical specific capacity of MoO2 and significantly improved conductivity of Mo2N. Moreover, all the as-developed electrodes exhibited excellent cycling stability during the charge-discharge process. The present study provides a facile and broadly-applicable routine to tailor the component, structure, and electrochemical properties of Mo-based nanocrystals in CNFs, which finds huge application potential in the fields of various flexible electrochemical devices.

Generating Unit Tests for Documentation

Software projects capture redundant information in various kinds of artifacts, as specifications from the source code are also tested and documented. Such redundancy provides an opportunity to reduce development effort by supporting the joint generation of different types of artifacts. We introduce a tool-supported technique, called DScribe, that allows developers to combine unit test and documentation templates, and to invoke these templates to generate documentation and unit tests. DScribe supports the detection and replacement of outdated documentation, and the use of templates can encourage extensive test suites with a consistent style. Our evaluation of 835 specifications revealed that 85 percent were not tested or correctly documented, and DScribe could be used to automatically generate 97 percent of the tests and documentation. An additional study revealed that tests generated by DScribe are more focused and readable than those written by human testers or generated by state-of-the-art automated techniques.

Real-time observation of dissipative multi-soliton complexes in a net-normal dispersion fiber laser

Recent progress in real-time measurement technology makes it possible to spectrally characterize multi-soliton complexes. Here, we report on real-time observation to the multi-pulse structures in a net-normal dispersion mode-locked fiber laser. With careful adjustment of cavity parameters, several kinds of multi-soliton complexes, such as the coexistence of soliton singlet and soliton molecule, as well as the coexistence of different types of soliton molecules, are realized in the experiment. Real-time spectral information of each pulse under multi-soliton states can be well resolved with the dispersive Fourier transformation technique, which is markedly different from the results measured by conventional measurement instruments. Note that this is the first reported the simultaneous generation of different types of soliton molecules in a fiber laser to our best knowledge. The findings help to understand the complicated dynamics of the coexisting pattern between different kinds of dissipative solitons.

Performance improvement of shunt active power filter based on indirect control with a new robust phase-locked loop

Introduction. Since the development of the first active power filter (APF) in 1976, many efforts have been focused on improving the performances of the APF control as the number of different nonlinear loads has continued to increase. These nonlinear loads have led to the generation of different types of current harmonics, which requires more advanced controls, including robustness, to get an admissible total harmonic distortion (THD) in the power system. Purpose. The purpose of this paper is to develop a robust phase-locked loop (PLL) based on particle swarm optimization-reference signal tracking (PSO-RST) controller for a three phase three wires shunt active power filter control. Methodology. A robust PLL based on PSO-RST controller insert into the indirect d-q control of a shunt active power filter was developed. Results. Simulation results performed under the MATLAB/SimPowerSystem environment show a higher filtering quality and a better robustness compared to the classical d-q controls. Originality. Conventional PLLs have difficulty determining the phase angle of the utility voltage sources when grid voltage is distorted. If this phase angle is incorrectly determined, this leads to a malfunction of the complete control of the active power filters. This implies a bad compensation of the current harmonics generated by the nonlinear loads. To solve this problem we propose a robust and simple PLL based on PSO-RST controller to eliminate the influence of the voltage harmonics. Practical value. The proposed solution can be used to improve the functioning of the shunt active power filter and to reduce the amount of memory implementation.

A Brief Review on Evaluation and Exploration of Antioxidant Activity of Mango Ginger

Many free radicals are generates in the human body due to metabolic processes and in order to counteract the harmful effects of these antioxidants, human body has a complex system of natural enzymatic and non-enzymatic antioxidant defenses or mechanisms. These free radicals are mainly responsible for generation of different types of diseases and disorders. Hence protection of body against free radical is important and which can also be done by taking diet with maximum antioxidants. Naturally occurring antioxidant are very important in preventing body from various free radicals. Many medicinal plants and their extracts have been reported for potential anti-oxidant activity. Curcuma amada Roxb (Mango Ginger) is the most important genera come under the Zingiberaceae family. Chemically it has reported for the presence of wide range of phytoconstituents which include the flavonoids, terpenoids, tannins steroids, alkaloids, glycosides and essential oils. Due to presence of wide variety of phytoconstituents plant has very well traditional value reported for pharmacological significance for a variety of ailments. It effectively treats skin allergies, stomach problems, and high blood cholesterol and has been reported for antioxidant properties. In the present review work various research articles published on antioxidant activity of Mango Ginger Have been collected from various journal site and databases and explored systematically

Flow kinematics in the generation of different types of green water events with incident wave trains

Various types of green water events, generated with incident wave trains, have been identified in experimental research, but experimental analysis of their kinematics is still required to improve comparisons of analytical and numerical models. This paper presents an experimental investigation of the kinematics of consecutive green water events generated with incident wave trains, particularly during their formation and interaction with the bow of a fixed structure. These events include Plunging-Dam-Break (PDB) and Hammer-Fist (HF) types of green water. The kinematics of the latter has not been explored experimentally before. The experiments were carried out in a wave flume, considering incident waves trains of different steepness. Particle Image Velocimetry (PIV) methods were used to study the flow kinematics. The role of flow velocity during the formation of a representative PDB and a HF green water event was investigated in detail. Then, the averaged velocities of the initial stages of green water were compared for all the wave trains considered. For most the events, the shipping water tends to accelerate horizontally over the deck since it crosses the deck, where horizontal velocities close to zero are observed. Results suggest that PDB events have lower run-up velocities than HF events, but higher water-on-deck velocities. The analysis presented here may be useful for engineering purposes, in the validation of analytical and numerical methods. A database with results of the events investigated is available for interested readers.

DisenCite: Graph-Based Disentangled Representation Learning for Context-Specific Citation Generation

Citing and describing related literature are crucial to scientific writing. Many existing approaches show encouraging performance in citation recommendation, but are unable to accomplish the more challenging and onerous task of citation text generation. In this paper, we propose a novel disentangled representation based model DisenCite to automatically generate the citation text through integrating paper text and citation graph. A key novelty of our method compared with existing approaches is to generate context-specific citation text, empowering the generation of different types of citations for the same paper. In particular, we first build and make available a graph enhanced contextual citation dataset (GCite) with 25K edges in different types characterized by citation contained sections over 4.8K research papers. Based on this dataset, we encode each paper according to both textual contexts and structure information in the heterogeneous citation graph. The resulted paper representations are then disentangled by the mutual information regularization between this paper and its neighbors in graph. Extensive experiments demonstrate the superior performance of our method comparing to state-of-the-art approaches. We further conduct ablation and case studies to reassure that the improvement of our method comes from generating the context-specific citation through incorporating the citation graph.

DVGfinder: A Metasearch Tool for Identifying Defective Viral Genomes in RNA-Seq Data.

The generation of different types of defective viral genomes (DVG) is an unavoidable consequence of the error-prone replication of RNA viruses. In recent years, a particular class of DVGs, those containing long deletions or genome rearrangements, has gain interest due to their potential therapeutic and biotechnological applications. Identifying such DVGs in high-throughput sequencing (HTS) data has become an interesting computational problem. Several algorithms have been proposed to accomplish this goal, though all incur false positives, a problem of practical interest if such DVGs have to be synthetized and tested in the laboratory. We present a metasearch tool, DVGfinder, that wraps the two most commonly used DVG search algorithms in a single workflow for the identification of the DVGs in HTS data. DVGfinder processes the results of ViReMa-a and DI-tector and uses a gradient boosting classifier machine learning algorithm to reduce the number of false-positive events. The program also generates output files in user-friendly HTML format, which can help users to explore the DVGs identified in the sample. We evaluated the performance of DVGfinder compared to the two search algorithms used separately and found that it slightly improves sensitivities for low-coverage synthetic HTS data and DI-tector precision for high-coverage samples. The metasearch program also showed higher sensitivity on a real sample for which a set of copy-backs were previously validated.

Network topological determinants of pathogen spread

How do we best constrain social interactions to decrease transmission of communicable diseases? Indiscriminate suppression is unsustainable long term and presupposes that all interactions carry equal importance. Instead, transmission within a social network has been shown to be determined by its topology. In this paper, we deploy simulations to understand and quantify the impact on disease transmission of a set of topological network features, building a dataset of 9000 interaction graphs using generators of different types of synthetic social networks. Independently of the topology of the network, we maintain constant the total volume of social interactions in our simulations, to show how even with the same social contact some network structures are more or less resilient to the spread. We find a suitable intervention to be specific suppression of unfamiliar and casual interactions that contribute to the network’s global efficiency. This is, pathogen spread is significantly reduced by limiting specific kinds of contact rather than their global number. Our numerical studies might inspire further investigation in connection to public health, as an integrative framework to craft and evaluate social interventions in communicable diseases with different social graphs or as a highlight of network metrics that should be captured in social studies.