bluuebunny/crossref_metadata_2025 huggingface dataset:
Melatonin: A Versatile Protector against Oxidative DNA Damage
Authors: Galano Annia , Tan Dun-Xian , Reiter Russel
Published: February 2018

Oxidative damage to DNA has important implications for human health and has been identified as a key factor in the onset and development of numerous diseases. Thus, it is evident that preventing DNA from oxidative damage is crucial for humans and for any living organism. Melatonin is an astonishingly versatile molecule in this context. It can offer both direct and indirect protection against a wide variety of damaging agents and through multiple pathways, which may (or may not) take place simultaneously. They include direct antioxidative protection, which is mediated by melatonin’s free radical scavenging activity, and also indirect ways of action. The latter include, at least: (i) inhibition of metal-induced DNA damage; (ii) protection against non-radical triggers of oxidative DNA damage; (iii) continuous protection after being metabolized; (iv) activation of antioxidative enzymes; (v) inhibition of pro-oxidative enzymes; and (vi) boosting of the DNA repair machinery. The rather unique capability of melatonin to exhibit multiple neutralizing actions against diverse threatening factors, together with its low toxicity and its ability to cross biological barriers, are all significant to its efficiency for preventing oxidative damage to DNA.
Calycophyllum spruceanum (Benth.), the Amazonian “Tree of Youth” Prolongs Longevity and Enhances Stress Resistance in Caenorhabditis elegans
Authors: Peixoto Herbenya , Roxo Mariana , Koolen Hector , Da Silva Felipe , Silva Emerson , Braun Markus , Wang Xiaojuan , Wink Michael
Published: February 2018

The tree popularly known in Brazil as mulateiro or pau-mulato (Calycophyllum spruceanum (Benth.) K. Schum.) is deeply embedded in the herbal medicine of the Amazon region. Different preparations of the bark are claimed to have anti-aging, antioxidant, antimicrobial, emollient, wound healing, hemostatic, contraceptive, stimulant, and anti-diabetic properties. The current study aims to provide the first step towards a science-based evidence of the beneficial effects of C. spruceanum in the promotion of longevity and in the modulation of age-related markers. For this investigation, we used the model system Caenorhabditis elegans to evaluate in vivo antioxidant and anti-aging activity of a water extract from C. spruceanum. To chemically characterize the extract, HPLC MS (High Performance Liquid Chromatography Mass Spectrometry)/MS analyses were performed. Five secondary metabolites were identified in the extract, namely gardenoside, 5-hydroxymorin, cyanidin, taxifolin, and 5-hydroxy-6-methoxycoumarin-7-glucoside. C. spruceanum extract was able to enhance stress resistance and to extend lifespan along with attenuation of aging-associated markers in C. elegans. The demonstrated bioactivities apparently depend on the DAF-16/FOXO pathway. The data might support the popular claims of mulateiro as the “tree of youth”, however more studies are needed to clarify its putative benefits to human health.
Electrospun CuO-Nanoparticles-Modified Polycaprolactone @Polypyrrole Fibers: An Application to Sensing Glucose in Saliva
Authors: Xu Ting , Jin Wen , Wang Zhenzhen , Cheng Haiyan , Huang Xinhua , Guo Xiaoyu , Ying Ye , Wu Yiping , Wang Feng , Wen Ying , Yang Haifeng
Published: February 2018

A non-invasive method for detecting glucose is pursued by millions of diabetic patients to improve their personal management of blood glucose. In this work, a novel CuO nanoparticles (NPs) decorated polycaprolactone@polypyrrole fibers modified indium-tin oxide (denoted as CuO/PCL@PPy/ITO) electrode has been fabricated by electrospinning combined with the electrodeposition method for non-enzymatic detection of glucose in saliva fluid. The electrospun composite fibers exhibit high sensitivity for the glucose detection. The synergistic effect between CuO and PPy together with the unique three-dimensional net structure contributes the reliable selectivity, good test repeatability, large-scale production reproducibility in massive way, the reasonable stability and a high catalytic surface area to the sensor. Quantitative detection of glucose is determined in the linear range from 2 μM to 6 mM and the lowest detection limit is 0.8 μM. The CuO/PCL@PPy/ITO electrode shows potential for the non-invasive detection of salivary glucose.
Mechanistic Pathways Underlying the Antihypertensive Effect of Fermented Milk with Lactococcus lactis NRRL B-50571 in Spontaneously Hypertensive Rats
Authors: Beltrán-Barrientos Lilia , Hernández-Mendoza Adrián , González-Córdova Aarón , Astiazarán-García Humberto , Esparza-Romero Julián , Vallejo-Córdoba Belinda
Published: February 2018

It has been reported that fermented milk (FM) with Lactococcus lactis NRRL B-50571 had an antihypertensive effect in spontaneously hypertensive rats (SHR) and prehypertensive subjects. Therefore, the objective of the present study was to evaluate the possible mechanisms involved (angiotensin converting enzyme inhibition (ACEI), enhancement of nitric oxide production, antioxidant activity and opioid effect), in the antihypertensive effect of FM with SHR. First, twenty one SHR were randomized into three groups to either receive in a single-oral dose of purified water (negative control), FM, or naloxone (opioid receptor antagonist) + FM. In a parallel study, twenty seven SHR were randomized into three groups to either receive ad libitum purified water (negative control), Captopril or FM. After six weeks of treatment ACEI activity, enhancement of nitric oxide production, and antioxidant activity were evaluated in plasma. Results indicated that opioid receptors were not involved in the hypotensive effect of FM. However, ACEI activity (94 U/L), the oxidative stress index (malondialdehyde/catalase + glutathione peroxidase) 0.9, and nitric oxide in plasma (4.4 ± 1.3 U/L), were significantly different from the negative control, and not significantly different from the Captopril group. Thus, these results suggested that these mechanisms are involved in the hypotensive effect of FM.
Impact of Genetic Variants on the Individual Potential for Body Fat Loss
Authors: Cha Soyeon , Kang Joon , Lee Jae-Hak , Kim Jinki , Kim Heewon , Yang Yoon , Park Woong-Yang , Kim Jinho
Published: February 2018

The past decade has witnessed the discovery of obesity-related genetic variants and their functions through genome-wide association studies. Combinations of risk alleles can influence obesity phenotypes with different degrees of effectiveness across various individuals by interacting with environmental factors. We examined the interaction between genetic variation and changes in dietary habits or exercise that influences body fat loss from a large Korean cohort (n = 8840). Out of 673 obesity-related SNPs, a total of 100 SNPs (37 for carbohydrate intake; 19 for fat intake; 44 for total calories intake; 25 for exercise onset) identified to have gene-environment interaction effect in generalized linear model were used to calculate genetic risk scores (GRS). Based on the GRS distribution, we divided the population into four levels, namely, “very insensitive”, “insensitive”, “sensitive”, and “very sensitive” for each of the four categories, “carbohydrate intake”, “fat intake”, “total calories intake”, and “exercise”. Overall, the mean body fat loss became larger when the sensitivity level was increased. In conclusion, genetic variants influence the effectiveness of dietary regimes for body fat loss. Based on our findings, we suggest a platform for personalized body fat management by providing the most suitable and effective nutrition or activity plan specific to an individual.
Low Transfer of Tacrolimus and Its Metabolites into Colostrum of Graft Recipient Mothers
Authors: Kociszewska-Najman Bozena , Mazanowska Natalia , Pietrzak Bronislawa , Paczek Leszek , Szpotanska-Sikorska Monika , Schreiber-Zamora Joanna , Hryniewiecka Ewa , Zochowska Dorota , Samborowska Emilia , Dadlez Michal , Wielgos Miroslaw
Published: February 2018

Currently, the majority of neonates born to organ recipient mothers on chronic immunosuppressive therapy are formula fed. However, over the past few years, evidence has grown, suggesting that breastfeeding might be possible and beneficial. We designed a study assessing the transfer of tacrolimus into the colostrum of posttransplant mothers. We assessed the amount of tacrolimus and its metabolites, M-1 and M-3, that would be ingested by the breastfed neonates. Concentrations of tacrolimus and its metabolites were measured in colostrum from 14 posttransplant mothers as well as in venous cord blood and venous blood of the neonates. Test material analysis was performed by liquid chromatography coupled with mass spectrometry (LC/MS). The amount of ingested formula was registered, which allowed for estimation of the amount of tacrolimus and its metabolites that would be ingested by breastfed infants. The mean amount of tacrolimus that would be ingested by the neonates in maternal milk was 151.4 ng/kg/24 h (standard deviation SD ± 74.39); metabolite M-1: 23.80 ng/kg/24 h (SD ± 14.53); and metabolite M-3: 13.25 ng/kg/24 h (SD ± 9.05). The peak level of tacrolimus and metabolite M-1 in colostrum was noted 8 h after an oral dose (3.219 ng/mL SD ± 2.22 and 0.56 ng/mL SD ± 0.60, respectively) and metabolite M-3 after 6 h (0.29 ng/mL SD ± 0.22). Low concentrations of tacrolimus and its metabolites, M-1 and M-3, in colostrum show that neonates will ingest trace amounts of the drug. Further studies are required to fully assess the safety of breastfeeding by posttransplant mothers.
Effects of a Carob-Pod-Derived Sweetener on Glucose Metabolism
Authors: Lambert Carmen , Cubedo Judit , Padró Teresa , Vilahur Gemma , López-Bernal Sergi , Rocha Milagros , Hernández-Mijares Antonio , Badimon Lina
Published: February 2018

Background: Patients with type 2 diabetes mellitus (T2DM) have a higher incidence of cardiovascular (CV) events. The ingestion of high-glycemic index (GI) diets, specially sweetened beverage consumption, has been associated with the development of T2DM and CV disease. Objective: We investigated the effects of the intake of a sweetened beverage, obtained from natural carbohydrates containing pinitol (PEB) compared to a sucrose-enriched beverage (SEB) in the context of impaired glucose tolerance (IGT) and diabetes. Methods: The study was divided in three different phases: (1) a discovery phase where the plasma proteomic profile was investigated by 2-DE (two-dimensional electrophoresis) followed by mass spectrometry (matrix-assisted laser desorption/ionization time-of-flight—MALDI-TOF/TOF) in healthy and IGT volunteers; (2) a verification phase where the potential mechanisms behind the observed protein changes were investigated in the discovery cohort and in an additional group of T2DM volunteers; and (3) the results were validated in a proof-of-concept interventional study in an animal model of diabetic rats with complementary methodologies. Results: Six weeks of pinitol-enriched beverage (PEB) intake induced a significant increase in two proteins involved in the insulin secretion pathway, insulin-like growth factor acid labile subunit (IGF1BP-ALS; 1.3-fold increase; P = 0.200) and complement C4A (1.83-fold increase; P = 0.007) in IGT subjects but not in healthy volunteers. Changes in C4A were also found in the serum samples of Zucker diabetic fatty (ZDF) rats after four weeks of PEB intake compared to basal levels (P = 0.042). In addition, an increased expression of the glucose transporter-2 (GLUT2) gene was observed in the jejunum (P = 0.003) of inositol-supplemented rats when compared to sucrose supplementation. This change was correlated with the observed change in C4A (P = 0.002). Conclusions: Our results suggest that the substitution of a common sugar source, such as sucrose, by a naturally-based, pinitol-enriched beverage induces changes in the insulin secretion pathway that could help to reduce blood glucose levels by protecting β-cells and by stimulating the insulin secretion pathway. This mechanism of action could have a relevant role in the prevention of insulin resistance and diabetes progression.
Soluble CD14 as a Diagnostic Biomarker for Smear-Negative HIV-Associated Tuberculosis
Authors: Liu Yanyan , Ndumnego Okechukwu , Chen Tingting , Kim Ryung , Jenny-Avital Elizabeth , Ndung’u Thumbi , Wilson Douglas , Achkar Jacqueline
Published: February 2018

Sputum smear-negative HIV-associated active tuberculosis (TB) is challenging to diagnose. CD14 is a pattern recognition receptor that is known to mediate monocyte activation. Prior studies have shown increased levels of soluble CD14 (sCD14) as a potential biomarker for TB, but little is known about its value in detecting smear-negative HIV-associated TB. We optimized a sandwich ELISA for the detection of sCD14, and tested sera from 56 smear-negative South African (39 culture-positive and 17 culture-negative) HIV-infected pulmonary TB patients and 24 South African and 43 US (21 positive and 22 negative for tuberculin skin test, respectively) HIV-infected controls. SCD14 concentrations were significantly elevated in smear-negative HIV-associated TB compared with the HIV-infected controls (p < 0.0001), who had similar concentrations, irrespective of the country of origin or the presence or absence of latent M. tuberculosis infection (p = 0.19). The culture-confirmed TB group had a median sCD14 level of 2199 ng/mL (interquartile range 1927–2719 ng/mL), versus 1148 ng/mL (interquartile range 1053–1412 ng/mL) for the South African controls. At a specificity of 96%, sCD14 had a sensitivity of 95% for culture-confirmed smear-negative TB. These data indicate that sCD14 could be a highly accurate biomarker for the detection of HIV-associated TB.
Glycosaminoglycans and Proteoglycans
Authors: Pomin Vitor , Mulloy Barbara
Published: February 2018

In this editorial to MDPI Pharmaceuticals special issue “Glycosaminoglycans and Proteoglycans” we describe in outline the common structural features of glycosaminoglycans and the characteristics of proteoglycans, including the intracellular proteoglycan, serglycin, cell-surface proteoglycans, like syndecans and glypicans, and the extracellular matrix proteoglycans, like aggrecan, perlecan, and small leucine-rich proteoglycans. The context in which the pharmaceutical uses of glycosaminoglycans and proteoglycans are presented in this special issue is given at the very end.
Chitosan Based Self-Assembled Nanoparticles in Drug Delivery
Authors: Quiñones Javier Pérez , Peniche Hazel , Peniche Carlos
Published: February 2018

Chitosan is a cationic polysaccharide that is usually obtained by alkaline deacetylation of chitin poly(N-acetylglucosamine). It is biocompatible, biodegradable, mucoadhesive, and non-toxic. These excellent biological properties make chitosan a good candidate for a platform in developing drug delivery systems having improved biodistribution, increased specificity and sensitivity, and reduced pharmacological toxicity. In particular, chitosan nanoparticles are found to be appropriate for non-invasive routes of drug administration: oral, nasal, pulmonary and ocular routes. These applications are facilitated by the absorption-enhancing effect of chitosan. Many procedures for obtaining chitosan nanoparticles have been proposed. Particularly, the introduction of hydrophobic moieties into chitosan molecules by grafting to generate a hydrophobic-hydrophilic balance promoting self-assembly is a current and appealing approach. The grafting agent can be a hydrophobic moiety forming micelles that can entrap lipophilic drugs or it can be the drug itself. Another suitable way to generate self-assembled chitosan nanoparticles is through the formation of polyelectrolyte complexes with polyanions. This paper reviews the main approaches for preparing chitosan nanoparticles by self-assembly through both procedures, and illustrates the state of the art of their application in drug delivery.
Butyl Rubber Nanocomposites with Monolayer MoS2 Additives: Structural Characteristics, Enhanced Mechanical, and Gas Barrier Properties
Authors: Tsai Chi-Yang , Lin Shuian-Yin , Tsai Hsieh-Chih
Published: February 2018

Emerging two-dimensional (2D) materialsm, such as molybdenum disulfide (MoS2), offer opportunities to tailor the mechanical and gas barrier properties of polymeric materials. In this study, MoS2 was exfoliated to monolayers by modification with ethanethiol and nonanethiol. The thicknesses of resulting MoS2 monolayers were 0.7 nm for MoS2-ethanethiol and 1.1 nm for MoS2-nonanethiol. MoS2 monolayers were added to chlorobutyl rubber to prepare MoS2-butyl rubber nanocomposites at concentrations of 0.5, 1, 3, and 5 phr. The tensile stress showed a maximum enhancement of about 30.7% for MoS2-ethanethiol-butyl rubber and 34.8% for MoS2-nonanethiol-butyl rubber when compared to pure chlorobutyl rubber. In addition, the gas barrier properties were increased by 53.5% in MoS2-ethanethiol-butyl rubber and 49.6% in MoS2-nonanethiol-butyl rubber. MoS2 nanosheets thus enhanced the mechanical and gas barrier properties of chlorobutyl rubber. The nanocomposites that are presented here may be used to manufacture pharmaceutical stoppers with high mechanical and gas barrier properties.
Hydrogen-Deuterium Exchange Profiles of Polyubiquitin Fibrils
Authors: Morimoto Daichi , Nishizawa Ryo , Walinda Erik , Takashima Shingo , Sugase Kenji , Shirakawa Masahiro
Published: February 2018

Ubiquitin and its polymeric forms are conjugated to intracellular proteins to regulate diverse intracellular processes. Intriguingly, polyubiquitin has also been identified as a component of pathological protein aggregates associated with Alzheimer’s disease and other neurodegenerative disorders. We recently found that polyubiquitin can form amyloid-like fibrils, and that these fibrillar aggregates can be degraded by macroautophagy. Although the structural properties appear to function in recognition of the fibrils, no structural information on polyubiquitin fibrils has been reported so far. Here, we identify the core of M1-linked diubiquitin fibrils from hydrogen-deuterium exchange experiments using solution nuclear magnetic resonance (NMR) spectroscopy. Intriguingly, intrinsically flexible regions became highly solvent-protected in the fibril structure. These results indicate that polyubiquitin fibrils are formed by inter-molecular interactions between relatively flexible structural components, including the loops and edges of secondary structure elements.
Design of an Embedded Multi-Camera Vision System—A Case Study in Mobile Robotics
Authors: Costa Valter , Cebola Peter , Sousa Armando , Reis Ana
Published: February 2018

The purpose of this work is to explore the design principles for a Real-Time Robotic Multi Camera Vision System, in a case study involving a real world competition of autonomous driving. Design practices from vision and real-time research areas are applied into a Real-Time Robotic Vision application, thus exemplifying good algorithm design practices, the advantages of employing the “zero copy one pass” methodology and associated trade-offs leading to the selection of a controller platform. The vision tasks under study are: (i) recognition of a “flat” signal; and (ii) track following, requiring 3D reconstruction. This research firstly improves the used algorithms for the mentioned tasks and finally selects the controller hardware. Optimization for the shown algorithms yielded from 1.5 times to 190 times improvements, always with acceptable quality for the target application, with algorithm optimization being more important on lower computing power platforms. Results also include a 3-cm and five-degree accuracy for lane tracking and 100% accuracy for signalling panel recognition, which are better than most results found in the literature for this application. Clear results comparing different PC platforms for the mentioned Robotic Vision tasks are also shown, demonstrating trade-offs between accuracy and computing power, leading to the proper choice of control platform. The presented design principles are portable to other applications, where Real-Time constraints exist.
Assessing the Defoliation of Pine Forests in a Long Time-Series and Spatiotemporal Prediction of the Defoliation Using Landsat Data
Authors: Zhu Chenghao , Zhang Xiaoli , Zhang Ning , Hassan Mohammed , Zhao Lin
Published: February 2018

Pine forests (Pinus tabulaeformis) have been in danger of defoliation by a caterpillar in the west Liaoning province of China for more than thirty years. This paper aims to assess and predict the degree of damage to pine forests by using remote sensing and ancillary data. Through regression analysis of the pine foliage remaining ratios of field plots with several vegetation indexes of Landsat data, a feasible inversion model was obtained to detect the degree of damage using the Normalized Difference Infrared Index of 5th band (NDII5). After comparing the inversion result of the degree of damage to the pine in 29 years and the historical damage record, quantized results of damage assessment in a long time-series were accurately obtained. Based on the correlation analysis between meteorological variables and the degree of damage from 1984 to 2015, the average degree of damage was predicted in temporal scale. By adding topographic and other variables, a linear prediction model in spatiotemporal scale was constructed. The spatiotemporal model was based on 5015 public pine points for 24 years and reached 0.6169 in the correlation coefficient. This paper provided a feasible and quantitative method in the spatiotemporal prediction of forest pest occurrence by remote sensing.
Empirical Algorithm for Significant Wave Height Retrieval from Wave Mode Data Provided by the Chinese Satellite Gaofen-3
Authors: Wang He , Wang Jing , Yang Jingsong , Ren Lin , Zhu Jianhua , Yuan Xinzhe , Xie Chunhua
Published: February 2018

Gaofen-3 (GF-3), the first Chinese civil C-band synthetic aperture radar (SAR), was successfully launched by the China Academy of Space Technology on 10 August 2016. Among its 12 imaging modes, wave mode is designed to monitor the ocean surface waves over the open ocean. An empirical retrieval algorithm of significant wave height (SWH), termed Quad-Polarized C-band WAVE algorithm for GF-3 wave mode (QPCWAVE_GF3), is developed for quad-polarized SAR measurements from GF-3 in wave mode. QPCWAVE_GF3 model is built using six SAR image and spectrum related parameters. Based on a total of 2576 WaveWatch III (WW3) and GF-3 wave mode match-ups, 12 empirical coefficients of the model are determined for 6 incidence angle modes. The validation of the QPCWAVE_GF3 model is performed through comparisons against independent WW3 modelling hindcasts, and observations from altimeters and buoys from January to October in 2017. The assessment shows a good agreement with root mean square error from 0.5 m to 0.6 m, and scatter index around 20%. In particular, applications of the QPCWAVE_GF3 model in SWH estimation for two storm cases from GF-3 data in wave mode and Quad-Polarization Strip I mode are presented respectively. Results indicate that the proposed algorithm is suitable for SWH estimation from GF-3 wave mode and is promising for other similar data.
User Access Management Based on Network Pricing for Social Network Applications
Authors: Lin Fuhong , Pang Zhibo , Ma Xingmin , Gu Qing
Published: February 2018

Social applications play a very important role in people’s lives, as users communicate with each other through social networks on a daily basis. This presents a challenge: How does one receive high-quality service from social networks at a low cost? Users can access different kinds of wireless networks from various locations. This paper proposes a user access management strategy based on network pricing such that networks can increase its income and improve service quality. Firstly, network price is treated as an optimizing access parameter, and an unascertained membership algorithm is used to make pricing decisions. Secondly, network price is adjusted dynamically in real time according to network load. Finally, selecting a network is managed and controlled in terms of the market economy. Simulation results show that the proposed scheme can effectively balance network load, reduce network congestion, improve the user's quality of service (QoS) requirements, and increase the network’s income.
Towards an Iterated Game Model with Multiple Adversaries in Smart-World Systems
Authors: He Xiaofei , Yang Xinyu , Yu Wei , Lin Jie , Yang Qingyu
Published: February 2018

Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT) (smart cities, smart grid, smart transportation, etc.) and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the development of a specific defensive strategy to deal with specific, often singular threats. In this paper, we address the issue of coalitional attacks, which can be launched by multiple adversaries cooperatively against the smart-world system such as smart cities. Particularly, we propose a game-theory based model to capture the interaction among multiple adversaries, and quantify the capacity of the defender based on the extended Iterated Public Goods Game (IPGG) model. In the formalized game model, in each round of the attack, a participant can either cooperate by participating in the coalitional attack, or defect by standing aside. In our work, we consider the generic defensive strategy that has a probability to detect the coalitional attack. When the coalitional attack is detected, all participating adversaries are penalized. The expected payoff of each participant is derived through the equalizer strategy that provides participants with competitive benefits. The multiple adversaries with the collusive strategy are also considered. Via a combination of theoretical analysis and experimentation, our results show that no matter which strategies the adversaries choose (random strategy, win-stay-lose-shift strategy, or even the adaptive equalizer strategy), our formalized game model is capable of enabling the defender to greatly reduce the maximum value of the expected average payoff to the adversaries via provisioning sufficient defensive resources, which is reflected by setting a proper penalty factor against the adversaries. In addition, we extend our game model and analyze the extortion strategy, which can enable one participant to obtain more payoff by extorting his/her opponents. The evaluation results show that the defender can combat this strategy by encouraging competition among the adversaries, and significantly suppress the total payoff of the adversaries via setting the proper penalty factor.
Integrated Affinity Biosensing Platforms on Screen-Printed Electrodes Electrografted with Diazonium Salts
Authors: Yáñez-Sedeño Paloma , Campuzano Susana , Pingarrón José M.
Published: February 2018

Adequate selection of the electrode surface and the strategies for its modification to enable subsequent immobilization of biomolecules and/or nanomaterials integration play a major role in the performance of electrochemical affinity biosensors. Because of the simplicity, rapidity and versatility, electrografting using diazonium salt reduction is among the most currently used functionalization methods to provide the attachment of an organic layer to a conductive substrate. This particular chemistry has demonstrated to be a powerful tool to covalently immobilize in a stable and reproducible way a wide range of biomolecules or nanomaterials onto different electrode surfaces. Considering the great progress and interesting features arisen in the last years, this paper outlines the potential of diazonium chemistry to prepare single or multianalyte electrochemical affinity biosensors on screen-printed electrodes (SPEs) and points out the existing challenges and future directions in this field.
Object-Oriented Hierarchy Radiation Consistency for Different Temporal and Different Sensor Images
Authors: Su Nan , Yan Yiming , Zhao Chunhui , Wang Liguo
Published: February 2018

In the paper, we propose a novel object-oriented hierarchy radiation consistency method for dense matching of different temporal and different sensor data in the 3D reconstruction. For different temporal images, our illumination consistency method is proposed to solve both the illumination uniformity for a single image and the relative illumination normalization for image pairs. Especially in the relative illumination normalization step, singular value equalization and linear relationship of the invariant pixels is combined used for the initial global illumination normalization and the object-oriented refined illumination normalization in detail, respectively. For different sensor images, we propose the union group sparse method, which is based on improving the original group sparse model. The different sensor images are set to a similar smoothness level by the same threshold of singular value from the union group matrix. Our method comprehensively considered the influence factors on the dense matching of the different temporal and different sensor stereoscopic image pairs to simultaneously improve the illumination consistency and the smoothness consistency. The radiation consistency experimental results verify the effectiveness and superiority of the proposed method by comparing two other methods. Moreover, in the dense matching experiment of the mixed stereoscopic image pairs, our method has more advantages for objects in the urban area.
Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management
Authors: Silva Bhagya , Khan Murad , Han Kijun
Published: February 2018

The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.
An Amperometric Biosensor for the Determination of Bacterial Sepsis Biomarker, Secretory Phospholipase Group 2-IIA Using a Tri-Enzyme System
Authors: Nik Mansor Nik , Leong Tan , Safitri Eka , Futra Dedi , Ahmad Nurul , Nasuruddin Dian , Itnin Azlin , Zaini Ida , Arifin Khaizurin , Heng Lee , Hassan Nurul
Published: February 2018

A tri-enzyme system consisting of choline kinase/choline oxidase/horseradish peroxidase was used in the rapid and specific determination of the biomarker for bacterial sepsis infection, secretory phospholipase Group 2-IIA (sPLA2-IIA). These enzymes were individually immobilized onto the acrylic microspheres via succinimide groups for the preparation of an electrochemical biosensor. The reaction of sPLA2-IIA with its substrate initiated a cascading enzymatic reaction in the tri-enzyme system that led to the final production of hydrogen peroxide, which presence was indicated by the redox characteristics of potassium ferricyanide, K3Fe(CN)6. An amperometric biosensor based on enzyme conjugated acrylic microspheres and gold nanoparticles composite coated onto a carbon-paste screen printed electrode (SPE) was fabricated and the current measurement was performed at a low potential of 0.20 V. This enzymatic biosensor gave a linear range 0.01–100 ng/mL (R2 = 0.98304) with a detection limit recorded at 5 × 10−3 ng/mL towards sPLA2-IIA. Moreover, the biosensor showed good reproducibility (relative standard deviation (RSD) of 3.04% (n = 5). The biosensor response was reliable up to 25 days of storage at 4 °C. Analysis of human serum samples for sPLA2-IIA indicated that the biosensor has potential for rapid bacterial sepsis diagnosis in hospital emergency department.
An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments
Authors: Lemos Marcus , Filho Raimir , Rabêlo Ricardo , De Carvalho Carlos , Mendes Douglas , Costa Valney
Published: February 2018

Virtual sensors provisioning is a central issue for sensors cloud middleware since it is responsible for selecting physical nodes, usually from Wireless Sensor Networks (WSN) of different owners, to handle user’s queries or applications. Recent works perform provisioning by clustering sensor nodes based on the correlation measurements and then selecting as few nodes as possible to preserve WSN energy. However, such works consider only homogeneous nodes (same set of sensors). Therefore, those works are not entirely appropriate for sensor clouds, which in most cases comprises heterogeneous sensor nodes. In this paper, we propose ACxSIMv2, an approach to enhance the provisioning task by considering heterogeneous environments. Two main algorithms form ACxSIMv2. The first one, ACASIMv1, creates multi-dimensional clusters of sensor nodes, taking into account the measurements correlations instead of the physical distance between nodes like most works on literature. Then, the second algorithm, ACOSIMv2, based on an Ant Colony Optimization system, selects an optimal set of sensors nodes from to respond user’s queries while attending all parameters and preserving the overall energy consumption. Results from initial experiments show that the approach reduces significantly the sensor cloud energy consumption compared to traditional works, providing a solution to be considered in sensor cloud scenarios.
A Novel Adaptively-Robust Strategy Based on the Mahalanobis Distance for GPS/INS Integrated Navigation Systems
Authors: Jiang Chen , Zhang Shu-Bi
Published: February 2018

As an optimal estimation method, the Kalman filter is the most frequently-used data fusion strategy in the field of dynamic navigation and positioning. Nevertheless, the abnormal model errors seriously degrade performance of the conventional Kalman filter. The adaptive Kalman filter was put forward to control the influences of model errors. However, the adaptive Kalman filter based on the predicted residuals (innovation vector) requires reliable observation information, and its performance is significantly affected by outliers in the measurements. In this paper, a novel adaptively-robust strategy based on the Mahalanobis distance is proposed to weaken the effects of abnormal model deviations and outliers in the measurements. In the proposed scheme, the judging index is defined based on the Mahalanobis distance, and the adaptively-robust filtering is performed when the observations are reliable, otherwise, the robust filtering is performed based on the robust estimation method. Various experiments with the actual data of GPS/INS integrated navigation systems are implemented to examine validity of the proposed scheme. Results show that both the influences of model deviations and outliers are weakened effectively by using the proposed adaptive robust filtering scheme. Moreover, the proposed scheme is easy to implement with a reasonable calculation burden.
Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors
Authors: Nguyen Dat Tien , Pham Tuyen Danh , Baek Na Rae , Park Kang Ryoung
Published: February 2018

Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases.
A Micro-Damage Detection Method of Litchi Fruit Using Hyperspectral Imaging Technology
Authors: Xiong Juntao , Lin Rui , Bu Rongbin , Liu Zhen , Yang Zhengang , Yu Lianyi
Published: February 2018

The non-destructive testing of litchi fruit is of great significance to the fresh-keeping, storage and transportation of harvested litchis. To achieve quick and accurate micro-damage detection, a non-destructive grading test method for litchi fruits was studied using 400–1000 nm hyperspectral imaging technology. The Huaizhi litchi was chosen in this study, and the hyperspectral data average for the region of interest (ROI) of litchi fruit was extracted for spectral data analysis. Then the hyperspectral data samples of fresh and micro-damaged litchi fruits were selected, and a partial least squares discriminant analysis (PLS-DA) was used to establish a prediction model for the realization of qualitative analysis for litchis with different qualities. For the external validation set, the mean per-type recall and precision were 94.10% and 93.95%, respectively. Principal component analysis (PCA) was used to determine the sensitive wavelength for recognition of litchi quality characteristics, with the results of wavelengths corresponding to the local extremum for the weight coefficient of PC3, i.e., 694, 725 and 798 nm. Then the single-band images corresponding to each sensitive wavelength were analyzed. Finally, the 7-dimension features of the PC3 image were extracted using the Gray Level Co-occurrence Matrix (GLCM). Through image processing, least squares support vector machine (LS-SVM) modeling was conducted to classify the different qualities of litchis. The model was validated using the experiment data, and the average accuracy of the validation set was 93.75%, while the external validation set was 95%. The results indicate the feasibility of using hyperspectral imaging technology in litchi postpartum non-destructive detection and classification.
Numerical Study and Optimisation of a Novel Single-Element Dual-Frequency Ultrasound Transducer
Authors: Sun Changhe , Jiang Senlin , Liu Yufei
Published: February 2018

A dual-frequency ultrasound transducer (DFUT) is usually preferred for its numerous advantageous applications, especially in biomedical imaging and sensing. However, most of DFUTs are based on the combination of fundamental and harmonic operations, or integration of multiple different single-frequency ultrasound transducers, hindering perfect beam alignment and acoustic impedance matching. A novel single-element DFUT has been proposed in this paper. A small piezoelectric membrane is used as the high-frequency ultrasound transducer, which is stacked on a large non-piezoelectric elastic membrane with a groove used as the low-frequency capacitive ultrasound transducer. Such a capacitive-piezoelectric hybrid structure is theoretically analysed in details, based on the electrostatic attraction force and converse piezoelectric effect. Both the low and high resonance frequencies are independently derived, with a maximum deviation of less than 4% from the finite element simulations. Besides, a lumped-parameter equivalent circuit model of combining both the capacitive and piezoelectric ultrasound transducers was also described. Based on our dual-frequency structure design, a high-to-low frequency ratio of about 2 to more than 20 could be achieved, with easy and independent controllability of two frequencies, and the high-frequency operation shows at least an order-of-magnitude displacement sensitivity improvement compared with the conventional harmonic operations.
EEMD-Based Steady-State Indexes and Their Applications to Condition Monitoring and Fault Diagnosis of Railway Axle Bearings
Authors: Yi Cai , Wang Dong , Fan Wei , Tsui Kwok-Leung , Lin Jianhui
Published: February 2018

Railway axle bearings are one of the most important components used in vehicles and their failures probably result in unexpected accidents and economic losses. To realize a condition monitoring and fault diagnosis scheme of railway axle bearings, three dimensionless steadiness indexes in a time domain, a frequency domain, and a shape domain are respectively proposed to measure the steady states of bearing vibration signals. Firstly, vibration data collected from some designed experiments are pre-processed by using ensemble empirical mode decomposition (EEMD). Then, the coefficient of variation is introduced to construct two steady-state indexes from pre-processed vibration data in a time domain and a frequency domain, respectively. A shape function is used to construct a steady-state index in a shape domain. At last, to distinguish normal and abnormal bearing health states, some guideline thresholds are proposed. Further, to identify axle bearings with outer race defects, a pin roller defect, a cage defect, and coupling defects, the boundaries of all steadiness indexes are experimentally established. Experimental results showed that the proposed condition monitoring and fault diagnosis scheme is effective in identifying different bearing health conditions.
Fast Detection of Copper Content in Rice by Laser-Induced Breakdown Spectroscopy with Uni- and Multivariate Analysis
Authors: Liu Fei , Ye Lanhan , Peng Jiyu , Song Kunlin , Shen Tingting , Zhang Chu , He Yong
Published: February 2018

Fast detection of heavy metals is very important for ensuring the quality and safety of crops. Laser-induced breakdown spectroscopy (LIBS), coupled with uni- and multivariate analysis, was applied for quantitative analysis of copper in three kinds of rice (Jiangsu rice, regular rice, and Simiao rice). For univariate analysis, three pre-processing methods were applied to reduce fluctuations, including background normalization, the internal standard method, and the standard normal variate (SNV). Linear regression models showed a strong correlation between spectral intensity and Cu content, with an R 2 more than 0.97. The limit of detection (LOD) was around 5 ppm, lower than the tolerance limit of copper in foods. For multivariate analysis, partial least squares regression (PLSR) showed its advantage in extracting effective information for prediction, and its sensitivity reached 1.95 ppm, while support vector machine regression (SVMR) performed better in both calibration and prediction sets, where R c 2 and R p 2 reached 0.9979 and 0.9879, respectively. This study showed that LIBS could be considered as a constructive tool for the quantification of copper contamination in rice.
Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach
Authors: Paiva Joana S. , Ribeiro Rita S. R. , Cunha João P. S. , Rosa Carla C. , Jorge Pedro A. S.
Published: February 2018

Recent trends on microbiology point out the urge to develop optical micro-tools with multifunctionalities such as simultaneous manipulation and sensing. Considering that miniaturization has been recognized as one of the most important paradigms of emerging sensing biotechnologies, optical fiber tools, including Optical Fiber Tweezers (OFTs), are suitable candidates for developing multifunctional small sensors for Medicine and Biology. OFTs are flexible and versatile optotools based on fibers with one extremity patterned to form a micro-lens. These are able to focus laser beams and exert forces onto microparticles strong enough (piconewtons) to trap and manipulate them. In this paper, through an exploratory analysis of a 45 features set, including time and frequency-domain parameters of the back-scattered signal of particles trapped by a polymeric lens, we created a novel single feature able to differentiate synthetic particles (PMMA and Polystyrene) from living yeasts cells. This single statistical feature can be useful for the development of label-free hybrid optical fiber sensors with applications in infectious diseases detection or cells sorting. It can also contribute, by revealing the most significant information that can be extracted from the scattered signal, to the development of a simpler method for particles characterization (in terms of composition, heterogeneity degree) than existent technologies.
Why the Wind Curtailment of Northwest China Remains High
Authors: Luo Guoliang , Dan Erli , Zhang Xiaochun , Guo Yiwei
Published: February 2018

The total grid-connected installed capacity of wind power in northwest China has grown from 16,260 MW in 2013 to 43,290 MW in 2016; an increase of 88.7% each year. However, this region has suffered from increasingly serious wind curtailment since 2014, and the wind curtailment amount accounts for nearly a half of China’s total. The wind curtailment rate of Gansu Province, Xinjiang Uygur Autonomous Region and Ningxia Hui Autonomous Region in this area has increased and remains high. This paper constructs an analytical model to explore the reasons of the high wind curtailment of these three provinces from the four aspects of the wind power supply capacity, demand, grid transmission capacity, power system flexibility and market mechanism and laws. The results show that the relationship between the wind energy distribution and supply and the local load is incompatible, which is the source causing the high wind curtailment in northwest China. On the one hand, the game between the local government and developers has driven the development of wind power bases. On the other hand, the electricity sector is growing slowly and oversupply of electricity is seen in many areas of China. The wind power grid of northwest China not only faces limit of grid transmission capacity, but also constraint of insufficient flexibility of the electricity system. Presently, China has not set up a market mechanism and subsidy mechanism for the peak load adjustment, thus the thermal power companies lack motivation to voluntarily adjust the peak load. Moreover, the regional segregation and market barriers are also obstacles for the wind power outward transmission.