bluuebunny/crossref_metadata_2025 huggingface dataset:
Anti-Carcinogenic Glucosinolates in Cruciferous Vegetables and Their Antagonistic Effects on Prevention of Cancers
Authors: Soundararajan Prabhakaran , Kim Jung Sun
Published: November 2018

Glucosinolates (GSL) are naturally occurring β-d-thioglucosides found across the cruciferous vegetables. Core structure formation and side-chain modifications lead to the synthesis of more than 200 types of GSLs in Brassicaceae. Isothiocyanates (ITCs) are chemoprotectives produced as the hydrolyzed product of GSLs by enzyme myrosinase. Benzyl isothiocyanate (BITC), phenethyl isothiocyanate (PEITC) and sulforaphane ([1-isothioyanato-4-(methyl-sulfinyl) butane], SFN) are potential ITCs with efficient therapeutic properties. Beneficial role of BITC, PEITC and SFN was widely studied against various cancers such as breast, brain, blood, bone, colon, gastric, liver, lung, oral, pancreatic, prostate and so forth. Nuclear factor-erythroid 2-related factor-2 (Nrf2) is a key transcription factor limits the tumor progression. Induction of ARE (antioxidant responsive element) and ROS (reactive oxygen species) mediated pathway by Nrf2 controls the activity of nuclear factor-kappaB (NF-κB). NF-κB has a double edged role in the immune system. NF-κB induced during inflammatory is essential for an acute immune process. Meanwhile, hyper activation of NF-κB transcription factors was witnessed in the tumor cells. Antagonistic activity of BITC, PEITC and SFN against cancer was related with the direct/indirect interaction with Nrf2 and NF-κB protein. All three ITCs able to disrupts Nrf2-Keap1 complex and translocate Nrf2 into the nucleus. BITC have the affinity to inhibit the NF-κB than SFN due to the presence of additional benzyl structure. This review will give the overview on chemo preventive of ITCs against several types of cancer cell lines. We have also discussed the molecular interaction(s) of the antagonistic effect of BITC, PEITC and SFN with Nrf2 and NF-κB to prevent cancer.
Multidisciplinary Investigations on Galphimia glauca: A Mexican Medicinal Plant with Pharmacological Potential
Authors: Sharma Ashutosh , Angulo-Bejarano Paola Isabel , Madariaga-Navarrete Alfredo , Oza Goldie , Iqbal Hafiz M. N. , Cardoso-Taketa Alexandre , Luisa Villarreal Maria
Published: November 2018

Galphimia glauca (Cav.) Kuntze is an important endemic plant species, which possesses many medicinal properties and has been used in the Mexican traditional medicine for its sedative, anxiolytic, anticonvulsant, antiasthmatic and antiallergic properties. The therapeutic properties of this plant are mainly due to the presence of diverse bioactive compounds such as flavonoids, triterpenoids, and phenolics. Several triterpenoids and flavonoids compounds have been isolated and identified. Modern studies have demonstrated many biological activities such as anti-inflammatory, antidiarrheal, gastroenteritis, antimalarial and cytotoxic activities. Nevertheless, many studies are restricted to the crude extract, and many bioactive compounds are yet to be identified and validated according to its traditional use. However, its commercial exploitation and use are highly limited due to the non-availability of enough plant material and lack of knowledge about its agronomical practices. Moreover, the misinterpretation and mislabeling of closely related species of the genus Galphimia Cav. as G. glauca or G. gracilis is a common problem for its rigorous scientific study and commercial exploitation. The present review provides comprehensive knowledge based on the available scientific literature. To the best of our knowledge, this is the first review on G. glauca. This comprehensive information will certainly provide a guide for the better understanding and utilization of G. glauca for its scientific and industrial exploitation.
Imidazo[1,2-a]quinoxalines Derivatives Grafted with Amino Acids: Synthesis and Evaluation on A375 Melanoma Cells
Authors: Chouchou Adrien , Patinote Cindy , Cuq Pierre , Bonnet Pierre-Antoine , Deleuze-Masquéfa Carine
Published: November 2018

Imiqualines (imidazoquinoxaline derivatives) are anticancer compounds with high cytotoxic activities on melanoma cell lines. The first generation of imiqualines, with two lead compounds (EAPB0203 and EAPB0503), shows remarkable in vitro (IC50 = 1 570 nM and IC50 = 200 nM, respectively, on the A375 melanoma cell line) and in vivo activity on melanoma xenografts. The second generation derivatives, EAPB02302 and EAPB02303, are more active, with IC50 = 60 nM and IC50 = 10 nM, respectively, on A375 melanoma cell line. The aim of this study was to optimize the bioavailability of imiqualine derivatives, without losing their intrinsic activity. For that, we achieved chemical modulation on the second generation of imiqualines by conjugating amino acids on position 4. A new series of twenty-five compounds was efficiently synthesized by using microwave assistance and tested for its activity on the A375 cell line. In the new series, compounds 11a, 9d and 11b show cytotoxic activities less than second generation compounds, but similar to that of the first generation ones (IC50 = 403 nM, IC50 = 128 nM and IC50 = 584 nM, respectively). The presence of an amino acid leads to significant enhancement of the water solubility for improved drugability.
Application of Glycation in Regulating the Heat-Induced Nanoparticles of Egg White Protein
Authors: Wang Chenying , Ren Xidong , Su Yujie , Yang Yanjun
Published: November 2018

Due to the poor thermal stability of egg white protein (EWP), important challenges remain regarding preparation of nanoparticles for EWP above the denaturation temperature at neutral conditions. In this study, nanoparticles were fabricated from conjugates of EWP and isomalto-oligosaccharide (IMO) after heating at 90 °C for 30 min. Meanwhile, the effects of protein concentration, temperature, pH, ionic strength and degree of glycation (DG) on the formation of nanoparticles from IMO-EWP were investigated. To further reveal the formation mechanism of the nanoparticles, structures, thermal denaturation properties and surface properties were compared between EWP and IMO-EWP conjugates. Furthermore, the emulsifying activity index (EAI) and the emulsifying stability index (ESI) of nanoparticles were determined. The results indicated that glycation enhanced thermal stability and net surface charge of EWP due to changes in the EWP structure. The thermal aggregation of EWP was inhibited significantly by glycation, and enhanced with a higher degree of glycation. Meanwhile, the nanoparticles (<200 nm in size) were obtained at pH 3.0, 7.0 and 9.0 in the presence of NaCl. The increased thermal stability and surface net negative charge after glycation contributed to the inhibition. The EAI and ESI of nanoparticles were increased nearly 3-fold and 2-fold respectively, as compared to unheated EWP.
A Retrospective Study on Dietary FODMAP Intake in Celiac Patients Following a Gluten-Free Diet
Authors: Roncoroni Leda , Elli Luca , Doneda Luisa , Bascuñán Karla A. , Vecchi Maurizio , Morreale Federico , Scricciolo Alice , Lombardo Vincenza , Pellegrini Nicoletta
Published: November 2018

Our aim was to evaluate the intake of foods containing fermentable oligo/di/mono-saccharides and polyols (FODMAP) as a possible factor that induces gastrointestinal symptoms in treated celiac disease (CD) patients. We collected seven-day weighed food records for 104 CD patients and 91 healthy volunteers. All evaluated food items were from sources with high and low content of FODMAP, which were divided into cereals and sweets, sweeteners and soft drinks, fruits, dried fruits, and vegetables. Nutrient intake was calculated using the food database of the European Institute of Oncology. The symptoms reported were assessed by a Rome IV Irritable bowel syndrome (IBS) diagnostic questionnaire and by specific questions for the evaluation of functional gastrointestinal disorders (FGIDs). The 12% of CD patients met IBS symptoms criteria as opposed to 6% of controls (p = 0.09) and 27% of patients reported FGIDs symptoms vs. 22% of healthy controls (p = 0.42). The intake by CD patients was significantly higher than healthy volunteers for: sweeteners and sugars with low content of FODMAP (p = 0.0007), fruits, dried fruits, and vegetables high in FODMAP (p = 0.003) and low in FODMAP (p = 0.04) when compared to controls. CD patients had a lower intake of cereals and sweets with a high content of FODMAP (p = 0.00001). Healthy volunteers consumed significantly higher alcoholic beverages and fats high in FODMAP (both p < 0.044). The mean daily intake of other food categories did not differ between both groups. Even though CD patients had a low intake of gluten-free cereals high in FODMAP, they still consumed a significant amount of fruits and vegetables high in FODMAP. The clinical effect of a concomitant gluten-free diet and low-FODMAP diet should be prospectively evaluated as a supportive therapy in CD patients.
Associations of Brain Reactivity to Food Cues with Weight Loss, Protein Intake and Dietary Restraint during the PREVIEW Intervention
Authors: Drummen Mathijs , Dorenbos Elke , Vreugdenhil Anita C. E. , Stratton Gareth , Raben Anne , Westerterp-Plantenga Margriet S. , Adam Tanja C.
Published: November 2018

The objective was to assess the effects of a weight loss and subsequent weight maintenance period comprising two diets differing in protein intake, on brain reward reactivity to visual food cues. Brain reward reactivity was assessed with functional magnetic resonance imaging in 27 overweight/obese individuals with impaired fasting glucose and/or impaired glucose tolerance (HOMA-IR: 3.7 ± 1.7; BMI: 31.8 ± 3.2 kg/m2; fasting glucose: 6.4 ± 0.6 mmol/L) before and after an 8-week low energy diet followed by a 2-year weight maintenance period, with either high protein (HP) or medium protein (MP) dietary guidelines. Brain reactivity and possible relationships with protein intake, anthropometrics, insulin resistance and eating behaviour were assessed. Brain reactivity, BMI, HOMA-IR and protein intake did not change differently between the groups during the intervention. In the whole group, protein intake during weight maintenance was negatively related to changes in high calorie images>low calorie images (H > L) brain activation in the superior/middle frontal gyrus and the inferior temporal gyrus (p < 0.005, corrected for multiple comparisons). H > L brain activation was positively associated with changes in body weight and body-fat percentage and inversely associated with changes in dietary restraint in multiple reward, gustatory and processing regions (p < 0.005, corrected for multiple comparisons). In conclusion, changes in food reward-related brain activation were inversely associated with protein intake and dietary restraint during weight maintenance after weight loss and positively associated with changes in body weight and body-fat percentage.
In Vitro and In Silico Analyses of Nicotine Release from a Gelisphere-Loaded Compressed Polymeric Matrix for Potential Parkinson’s Disease Interventions
Authors: Kumar Pradeep , Choonara Yahya E. , Du Toit Lisa C. , Singh Neha , Pillay Viness
Published: November 2018

This study aimed to develop a prolonged-release device for the potential site-specific delivery of a neuroprotective agent (nicotine). The device was formulated as a novel reinforced crosslinked composite polymeric system with the potential for intrastriatal implantation in Parkinson’s disease interventions. Polymers with biocompatible and bioerodible characteristics were selected to incorporate nicotine within electrolyte-crosslinked alginate-hydroxyethylcellulose gelispheres compressed within a release rate-modulating external polymeric matrix, comprising either hydroxypropylmethylcellulose (HPMC), polyethylene oxide (PEO), or poly(lactic-co-glycolic) acid (PLGA) to prolong nicotine release. The degradation and erosion studies showed that the produced device had desirable robustness with the essential attributes for entrapping drug molecules and retarding their release. Zero-order drug release was observed over 50 days from the device comprising PLGA as the external matrix. Furthermore, the alginate-nicotine interaction, the effects of crosslinking on the alginate-hydroxyethycellulose (HEC) blend, and the effects of blending PLGA, HPMC, and PEO on device performance were mechanistically elucidated using molecular modelling simulations of the 3D structure of the respective molecular complexes to predict the molecular interactions and possible geometrical orientation of the polymer morphologies affecting the geometrical preferences. The compressed polymeric matrices successfully retarded the release of nicotine over several days. PLGA matrices offered minimal rates of matrix degradation and successfully retarded nicotine release, leading to the achieved zero-order release for 50 days following exposure to simulated cerebrospinal fluid (CSF).
Therapeutic Effect and Metabolic Mechanism of A Selenium-Polysaccharide from Ziyang Green Tea on Chronic Fatigue Syndrome
Authors: Shao Changzhuan , Song Jing , Zhao Shanguang , Jiang Hongke , Wang Baoping , Chi Aiping
Published: November 2018

Ziyang green tea was considered a medicine food homology plant to improve chronic fatigue Ssyndrome (CFS) in China. The aim of this research was to study the therapeutic effect of selenium-polysaccharides (Se-TP) from Ziyang green tea on CFS and explore its metabolic mechanism. A CFS-rats model was established in the present research and Se-TP was administrated to evaluate the therapeutic effect on CFS. Some serum metabolites including blood urea nitrogen (BUN), blood lactate acid (BLA), corticosterone (CORT), and aldosterone (ALD) were checked. Urine metabolites were analyzed via gas chromatography-mass spectrometry (GC-MS). Multivariate statistical analysis was also used to check the data. The results selected biomarkers that were entered into the MetPA database to analyze their corresponding metabolic pathways. The results demonstrated that Se-TP markedly improved the level of BUN and CORT in CFS rats. A total of eight differential metabolites were detected in GC-MS analysis, which were benzoic acid, itaconic acid, glutaric acid, 4-acetamidobutyric acid, creatine, 2-hydroxy-3-isopropylbutanedioic acid, l-dopa, and 21-hydroxypregnenolone. These differential metabolites were entered into the MetPA database to search for the corresponding metabolic pathways and three related metabolic pathways were screened out. The first pathway was steroid hormone biosynthesis. The second was tyrosine metabolism, and the third was arginine-proline metabolism. The 21-hydroxypregnenolone level of rats in the CFS group markedly increased after the Se-TP administration. In conclusion, Se-TP treatments on CFS rats improved their condition. Its metabolic mechanism was closely related to that which regulates the steroid hormone biosynthesis.
Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things
Authors: Pan Qi , Wen Xiangming , Lu Zhaoming , Li Linpei , Jing Wenpeng
Published: November 2018

With the new advancements in flight control and integrated circuit (IC) technology, unmanned aerial vehicles (UAVs) have been widely used in various applications. One of the typical application scenarios is data collection for large-scale and remote sensor devices in the Internet of things (IoT). However, due to the characteristics of massive connections, access collisions in the MAC layer lead to high power consumption for both sensor devices and UAVs, and low efficiency for the data collection. In this paper, a dynamic speed control algorithm for UAVs (DSC-UAV) is proposed to maximize the data collection efficiency, while alleviating the access congestion for the UAV-based base stations. With a cellular network considered for support of the communication between sensor devices and drones, the connection establishment process was analyzed and modeled in detail. In addition, the data collection efficiency is also defined and derived. Based on the analytical models, optimal speed under different sensor device densities is obtained and verified. UAVs can dynamically adjust the speed according to the sensor device density under their coverages to keep high data collection efficiency. Finally, simulation results are also conducted to verify the accuracy of the proposed analytical models and show that the DSC-UAV outperforms others with the highest data collection efficiency, while maintaining a high successful access probability, low average access delay, low block probability, and low collision probability.
Investigation on the Influence of Humidity on Stimulated Brillouin Backscattering in Perfluorinated Polymer Optical Fibers
Authors: Schreier Andy , Liehr Sascha , Wosniok Aleksander , Krebber Katerina
Published: November 2018

In this paper perfluorinated graded-index polymer optical fibers are characterized with respect to the influence of relative humidity changes on spectral transmission absorption and Rayleigh backscattering. The hygroscopic and thermal expansion coefficient of the fiber are determined to be C H E = (7.4 ± 0.1) · 10 − 6 %r.h.−1 and C T E = (22.7 ± 0.3) · 10 − 6 K−1, respectively. The influence of humidity on the Brillouin backscattering power and linewidth are presented for the first time to our knowledge. The Brillouin backscattering power at a pump wavelength of 1319 nm is affected by temperature and humidity. The Brillouin linewidth is observed to be a function of temperature but not of humidity. The strain coefficient of the BFS is determined to be C S = (−146.5 ± 0.9) MHz/% for a wavelength of 1319 nm within a strain range from 0.1% to 1.5%. The obtained results demonstrate that the humidity-induced Brillouin frequency shift is predominantly caused by the swelling of the fiber over-cladding that leads to fiber straining.
A Non-Intrusive Approach for Indoor Occupancy Detection in Smart Environments
Authors: Abade Bruno , Perez Abreu David , Curado Marilia
Published: November 2018

Smart Environments try to adapt their conditions focusing on the detection, localisation, and identification of people to improve their comfort. It is common to use different sensors, actuators, and analytic techniques in this kind of environments to process data from the surroundings and actuate accordingly. In this research, a solution to improve the user’s experience in Smart Environments based on information obtained from indoor areas, following a non-intrusive approach, is proposed. We used Machine Learning techniques to determine occupants and estimate the number of persons in a specific indoor space. The solution proposed was tested in a real scenario using a prototype system, integrated by nodes and sensors, specifically designed and developed to gather the environmental data of interest. The results obtained demonstrate that with the developed system it is possible to obtain, process, and store environmental information. Additionally, the analysis performed over the gathered data using Machine Learning and pattern recognition mechanisms shows that it is possible to determine the occupancy of indoor environments.
A POSHE-Based Optimum Clip-Limit Contrast Enhancement Method for Ultrasonic Logging Images
Authors: Fu Qingqing , Zhang Zhengbing , Celenk Mehmet , Wu Aiping
Published: November 2018

Enabled by piezoceramic transducers, ultrasonic logging images often suffer from low contrast and indistinct local details, which makes it difficult to analyze and interpret geologic features in the images. In this work, we propose a novel partially overlapped sub-block histogram-equalization (POSHE)-based optimum clip-limit contrast enhancement (POSHEOC) method to highlight the local details hidden in ultrasonic well logging images obtained through piezoceramic transducers. The proposed algorithm introduces the idea of contrast-limited enhancement to modify the cumulative distribution functions of the POSHE and build a new quality evaluation index considering the effects of the mean gradient and mean structural similarity. The new index is designed to obtain the optimal clip-limit value for histogram equalization of the sub-block. It makes the choice of the optimal clip-limit automatically according to the input image. Experimental results based on visual perceptual evaluation and quantitative measures demonstrate that the proposed method yields better quality in terms of enhancing the contrast, emphasizing the local details while preserving the brightness and restricting the excessive enhancement compared with the other seven histogram equalization-based techniques from the literature. This study provides a feasible and effective method to enhance ultrasonic logging images obtained through piezoceramic transducers and is significant for the interpretation of actual ultrasonic logging data.
Selection and Characterization of Packaged FBG Sensors for Offshore Applications
Authors: Wu Lei , Maheshwari Muneesh , Yang Yaowen , Xiao Wensheng
Published: November 2018

With the development in the exploitation of maritime resources, the structural health monitoring (SHM) of offshore structures becomes necessary. This study focuses on addressing the practical issues of application of fiber Bragg grating (FBG) sensors for the SHM of offshore structures, in particular an FPSO (floating, production, storage, and offloading unit) vessel. Due to the harsh marine environment and tough working conditions, the FBG sensors must have sufficient protection and good repeatability for long-term monitoring. Thorough research has been conducted to identify the most suitable, commercially available protection packaging for FBG sensors for offshore applications. Further, the performance of the selected FBG sensor packaging is tested under conditions of strong sunlight, heavy rain, and salty water in order to emulate the marine environment. Moreover, the installation method of the packaged FBG sensors is equally important, as it ensures the repeatability and durability of the sensors for their long-term performance. It is shown that the packaged FBG sensors can be installed using resin-based epoxy to maintain the repeatability of the sensor over the long-term. Further, the packaged FBG sensors are installed and tested on a simple FPSO model. The experimental results under full load and ballast draft conditions show that the proposed FBG sensors are competent for the SHM of offshore structures.
Simultaneous All-Parameters Calibration and Assessment of a Stereo Camera Pair Using a Scale Bar
Authors: Sun Peng , Lu Nai-Guang , Dong Ming-Li , Yan Bi-Xi , Wang Jun
Published: November 2018

Highly accurate and easy-to-operate calibration (to determine the interior and distortion parameters) and orientation (to determine the exterior parameters) methods for cameras in large volume is a very important topic for expanding the application scope of 3D vision and photogrammetry techniques. This paper proposes a method for simultaneously calibrating, orienting and assessing multi-camera 3D measurement systems in large measurement volume scenarios. The primary idea is building 3D point and length arrays by moving a scale bar in the measurement volume and then conducting a self-calibrating bundle adjustment that involves all the image points and lengths of both cameras. Relative exterior parameters between the camera pair are estimated by the five point relative orientation method. The interior, distortion parameters of each camera and the relative exterior parameters are optimized through bundle adjustment of the network geometry that is strengthened through applying the distance constraints. This method provides both internal precision and external accuracy assessment of the calibration performance. Simulations and real data experiments are designed and conducted to validate the effectivity of the method and analyze its performance under different network geometries. The RMSE of length measurement is less than 0.25 mm and the relative precision is higher than 1/25,000 for a two camera system calibrated by the proposed method in a volume of 12 m × 8 m × 4 m. Compared with the state-of-the-art point array self-calibrating bundle adjustment method, the proposed method is easier to operate and can significantly reduce systematic errors caused by wrong scaling.
Student’s-t Mixture Regression-Based Robust Soft Sensor Development for Multimode Industrial Processes
Authors: Wang Jingbo , Shao Weiming , Song Zhihuan
Published: November 2018

Because of multiple manufacturing phases or operating conditions, a great many industrial processes work with multiple modes. In addition, it is inevitable that some measurements of industrial variables obtained through hardware sensors are incorrectly observed, recorded or imported into databases, resulting in the dataset available for statistic analysis being contaminated by outliers. Unfortunately, these outliers are difficult to recognize and remove completely. These process characteristics and dataset imperfections impose challenges on developing high-accuracy soft sensors. To resolve this problem, the Student’s-t mixture regression (SMR) is proposed to develop a robust soft sensor for multimode industrial processes. In the SMR, for each mixing component, the Student’s-t distribution is used instead of the Gaussian distribution to model secondary variables, and the functional relationship between secondary and primary variables is explicitly considered. Based on the model structure of the SMR, a computationally efficient parameter-learning algorithm is also developed for SMR. Results conducted on two cases including a numerical example and a real-life industrial process demonstrate the effectiveness and feasibility of the proposed approach.
Monitoring Fatigue Damage of Modular Bridge Expansion Joints Using Piezoceramic Transducers
Authors: Jiang Tianyong , Zhang Yaowen , Wang Lei , Zhang Liang , Song Gangbing
Published: November 2018

Modular bridge expansion joints (MBEJs) are commonly used in bridges and are often subjected to fatigue damages, which necessitate fatigue monitoring of MBEJs to ensure the reliable operation of the bridges. In this paper, a stress wave based active sensing approach using piezoceramic transducers is developed to monitor the fatigue damage of MBEJ. A MBEJ involves mainly center beam, edge beam, support bar, support box, sliding bearing, sliding spring, elastomeric strip seal, full-penetration weld and reinforcing plate. In practice, for a MBEJ, the part that is most prone to fatigue damage is the full-penetration weld between the center beam and the support bar. In this paper, a specimen, which is the full-scale center-beam/support-bar (CB/SB) assembly, was designed and fabricated to facilitate the experimental study. The assembly mainly includes center beam, support bar, reinforcing plate, and full-penetration weld. The lead zirconate titanate (PZT) transducer bonded on the support bar was used as the actuator and the PZT transducer mounted on the center beam was as the sensor. Dial indicators were utilized to measure the vertical displacement of the center beam. Two series of tests, including static test, and fatigue test, were performed on the specimen in an alternating fashion. Based on the number of cyclic loading, the experiment was divided into six different stages: 0th cycle (the healthy state), 0.8 million cycles, 1.6 million cycles, 2.4 million cycles, 3.2 million cycles, and 4 million cycles. The signals received by the PZT sensor were analyzed with the help of wavelet packet analysis. In addition, the structure stiffness also was considered as a comparative approach in this paper. Experimental results show that during the fatigue test, the structure stiffness decreases with the number of cycle loading. However, the method can only obtain the fatigue damage impact on the entire structure, and cannot determine the fatigue damage degree of a certain weld. On the other hand, the proposed method can accurately monitor the fatigue damage degree of full-penetration welds. The research results show that the developed piezoceramic enabled active sensing approach can monitor and estimate the fatigue damage in MBEJ in real-time.
LSRR-LA: An Anisotropy-Tolerant Localization Algorithm Based on Least Square Regularized Regression for Multi-Hop Wireless Sensor Networks
Authors: Zhao Wei , Shao Fei , Ye Song , Zheng Wei
Published: November 2018

As is well known, multi-hop range-free localization algorithms demonstrate pretty good performance in isotropic networks in which sensor nodes distribute evenly and densely. However, these algorithms are easily affected by network topology, causing a significant decrease in positioning accuracy. To improve the localization performance in anisotropic networks, this paper presents a multi-hop range-free localization algorithm based on Least Square Regularized Regression (LSRR). By building a mapping relationship between hop counts and real distances, we can regard the process of localization as a regularized regression. Firstly, the proximity information of the given network is measured. Then, a mapping model between the geographical distances and the hop distances is constructed by LSRR. Finally, each sensor node finds its own position via this mapping. The Average Localization Error (ALE) metric is used to evaluate the proposed method in our experiments, and results show that, compared with similar methods, our approach can effectively decrease the effect of anisotropy, thus considerably improving the positioning accuracy.
Reusability of SPE and Sb-modified SPE Sensors for Trace Pb(II) Determination
Authors: Finšgar Matjaž , Majer David , Maver Uroš , Maver Tina
Published: November 2018

In this work, unmodified screen-printed electrode (bare SPE) and Sb-film modified SPE (SbFSPE) sensors were employed for the analysis of trace amounts of Pb(II) in non-deaerated water solutions. The modified electrode was performed in situ in 0.5 mg/L Sb(III) and 0.01 M HCl. The methodology was validated for an accumulation potential of –1.1 V vs. Ag/AgCl and an accumulation time of 60 s. A comparative analysis of bare SPE and SbFSPE showed that the detection and quantification limits decrease for the bare SPE. The method with the bare SPE showed a linear response in the 69.8–368.4 µg/L concentration range, whereas linearity for the SbFSPE was in the 24.0–319.1 µg/L concentration range. This work also reports the reason why the multiple standard addition method instead of a linear calibration curve for Pb(II) analysis should be employed. Furthermore, the analytical method employing SbFSPE was found to be more accurate and precise compared to the use of bare SPE when sensors were employed for the first time, however this performance changed significantly when these sensors were reused in the same manner. Furthermore, electrochemical impedance spectroscopy was used for the first time to analyse the electrochemical response of sensors after being used for multiple successive analyses. Surface characterisation before and after multiple successive uses of bare SPE and SbFSPE sensors, with atomic force microscopy and field emission scanning electron microscopy, showed sensor degradation. The interference effect of Cd(II), Zn(II), As(III), Fe(II), Na(I), K(I), Ca(II), Mg(II), NO3–, Bi(III), Cu(II), Sn(II), and Hg(II) on the Pb(II) stripping signal was also studied. Finally, the application of SbFSPE was tested on a real water sample (from a local river), which showed high precision (RSD = 8.1%, n = 5) and accurate results.
Erratum: Zalameda, J. et al. Detection and Characterization of Damage in Quasi-Static Loaded Composite Structures using Passive Thermography. Sensors 2018, 18, 3562
Authors: Zalameda Joseph , Winfree William
Published: November 2018

The authors wish to correct Table 3 in their paper published in Sensors [...]
EmoTour: Estimating Emotion and Satisfaction of Users Based on Behavioral Cues and Audiovisual Data
Authors: Matsuda Yuki , Fedotov Dmitrii , Takahashi Yuta , Arakawa Yutaka , Yasumoto Keiichi , Minker Wolfgang
Published: November 2018

With the spread of smart devices, people may obtain a variety of information on their surrounding environment thanks to sensing technologies. To design more context-aware systems, psychological user context (e.g., emotional status) is a substantial factor for providing useful information in an appropriate timing. As a typical use case that has a high demand for context awareness but is not tackled widely yet, we focus on the tourism domain. In this study, we aim to estimate the emotional status and satisfaction level of tourists during sightseeing by using unconscious and natural tourist actions. As tourist actions, behavioral cues (eye and head/body movement) and audiovisual data (facial/vocal expressions) were collected during sightseeing using an eye-gaze tracker, physical-activity sensors, and a smartphone. Then, we derived high-level features, e.g., head tilt and footsteps, from behavioral cues. We also used existing databases of emotionally rich interactions to train emotion-recognition models and apply them in a cross-corpus fashion to generate emotional-state prediction for the audiovisual data. Finally, the features from several modalities are fused to estimate the emotion of tourists during sightseeing. To evaluate our system, we conducted experiments with 22 tourists in two different touristic areas located in Germany and Japan. As a result, we confirmed the feasibility of estimating both the emotional status and satisfaction level of tourists. In addition, we found that effective features used for emotion and satisfaction estimation are different among tourists with different cultural backgrounds.
Thermal Treatment of Aerosol Deposited NiMn2O4 NTC Thermistors for Improved Aging Stability
Authors: Schubert Michaela , Münch Christian , Schuurman Sophie , Poulain Véronique , Kita Jaroslaw , Moos Ralf
Published: November 2018

This paper examines the influence of a short-term thermal treatment of aerosol deposited negative temperature coefficient (NTC) thermistor films on the NTCR characteristics and their long-term stability with different electrode materials. An aerosol deposition of a spinel-based NiMn2O4 powder on alumina substrates with screen-printed AgPd and Au interdigital electrode structures was performed. The manufactured components of the typical size of 1206 were tempered in a moderate temperature range of 200 °C to 800 °C and aged for 1000 h at 125 °C in air. Based on R-T measurements in a high-precision silicone oil thermostat bath and high temperature XRD analyses, the influence of the thermal treatment was analyzed and discussed. A 60-min tempering at 400 °C proved to be optimal, as both the NTCR parameters and their ageing stability could be significantly improved. The findings are explained.
Probabilistic Forecasting of Nitrogen Dioxide Concentrations at an Urban Road Intersection
Authors: Kamińska Joanna A.
Published: November 2018

The concentration of nitrogen dioxide in the air along a major route in a large city is affected by very many factors, which are also interdependent. As an alternative to complicated deterministic models based on these complex processes, in this study a probabilistic model for predicting NO2 concentrations is proposed, using a simple accounting cluster-based method for determining probability distributions for tabulated values of ambient factors. Using the example of hourly values of NO2 concentration and data on wind speed and traffic flow for the main intersection in Wrocław (Poland), a model is constructed to predict the frequency of occurrence of concentrations in the form of a probability distribution, for given values of the input variables. The model was successfully verified on data for the first six months of 2018. A mean continuous rank probability score (CRPS) of 9.15 μg/m3 was obtained. In spite of the greater impact of traffic volume on urban NO2 concentrations, as measured by Pearson’s correlation coefficient, for instance, the model indicates that wind speed is also a very important factor—wind being the principal mechanism causing the evacuation of pollutants. This underlines the importance of sustainable city planning with regard to ensuring suitable conditions for the passage of air.
Biodiversity Observation for Land and Ecosystem Health (BOLEH): A Robust Method to Evaluate the Management Impacts on the Bundle of Carbon and Biodiversity Ecosystem Services in Tropical Production Forests
Authors: Kitayama Kanehiro , Fujiki Shogoro , Aoyagi Ryota , Imai Nobuo , Sugau John , Titin Jupiri , Nilus Reuben , Lagan Peter , Sawada Yoshimi , Ong Robert , Kugan Frederick , Mannan Sam
Published: November 2018

The Forest Stewardship Council (FSC) has initiated a new sustainability mechanism, the ecosystem-services certification. In this system, management entities who wish to be certified for the maintenance of ecosystem services (carbon, biodiversity, watershed, soil and recreational services) must verify that their activities have no net negative impacts on selected ecosystem service(s). Developing a robust and cost-effective measurement method is a key challenge for establishing a credible certification system. Using a single method to evaluate a bundle of ecosystem services will be more efficient in terms of transaction costs than using multiple methods. We tested the efficiency of a single method, “biodiversity observation for land and ecosystem health (BOLEH)”, to simultaneously evaluate biodiversity and carbon density on a landscape scale in FSC-certified tropical production forests in Sabah, Malaysia. In this method, forest intactness based on the tree-generic compositional similarity with that of a pristine forest was used as an index of biodiversity. We repeated BOLEH in 2009 and 2014 in these forests. Our analysis could detect significant spatiotemporal changes in both carbon and forest intactness during these five years, which reflected past logging intensities and current management regimes in these forests. Enhancement of these ecosystem services occurred in the forest where sustainable management with reduced-impact logging had long been implemented. In this paper, we describe the procedure of the BOLEH method, and results of the pilot test in these forests.
Construction and Simulation of Composite Measures and Condensation Model for Designing Probabilistic Computational Applications
Authors: Bagchi Susmit
Published: November 2018

The probabilistic algorithms are widely applied in designing computational applications such as distributed systems and probabilistic databases, to determine distributed consensus in the presence of random failures of nodes or networks. In distributed computing, symmetry breaking is performed by employing probabilistic algorithms. In general, probabilistic symmetry breaking without any bias is preferred. Thus, the designing of randomized and probabilistic algorithms requires modeling of associated probability spaces to generate control-inputs. It is required that discrete measures in such spaces are computable and tractable in nature. This paper proposes the construction of composite discrete measures in real as well as complex metric spaces. The measures are constructed on different varieties of continuous smooth curves having distinctive non-linear profiles. The compositions of discrete measures consider arbitrary functions within metric spaces. The measures are constructed on 1-D interval and 2-D surfaces and, the corresponding probability metric product is defined. The associated sigma algebraic properties are formulated. The condensation measure of the uniform contraction map is constructed as axioms. The computational evaluations of the proposed composite set of measures are presented.
The Augmented Approach towards Equilibrated Nexus Era into the Wireless Rechargeable Sensor Network
Authors: Ali Ahmad , Ming Yu , Chakraborty Sagnik , Iram Saima , Si Tapas
Published: November 2018

Present research in the domain of wireless sensor network (WSN) has unearthed that energy restraint of sensor nodes (SNs) encumbers their perpetual performance. Of late, the encroachment in the vicinity of wireless power transfer (WPT) technology has achieved pervasive consideration from both industry and academia to cater the sensor nodes (SNs) letdown in the wireless rechargeable sensor network (WRSNs). The fundamental notion of wireless power transfer is to replenish the energy of sensor nodes using a single or multiple wireless charging devices (WCDs). Herein, we present a jointly optimization model to maximize the charging efficiency and routing restraint of the wireless charging device (WCD). At the outset, we intend an unswerving charging path algorithm to compute the charging path of the wireless charging device. Moreover, Particle swarm optimization (PSO) algorithm has designed with the aid of a virtual clustering technique during the routing process to equilibrate the network lifetime. Herein clustering algorithm, the enduring energy of the sensor nodes is an indispensable parameter meant for the assortment of cluster head (CH). Furthermore, compare the proposed approach to corroborate its pre-eminence over the benchmark algorithm in diverse scenarios. The simulation results divulge that the proposed work is enhanced concerning the network lifetime, charging performance and the enduring energy of the sensor nodes.
Design of a New Variable Shewhart Control Chart Using Multiple Dependent State Repetitive Sampling
Authors: Aldosari Mansour Sattam , Aslam Muhammad , Khan Nasrullah , Jun Chi-Hyuck
Published: November 2018

In this paper, a new variable control chart is proposed using multiple dependent-state repetitive sampling by assuming that the data follows a normal distribution having a symmetry property. Its efficiency will be evaluated in terms of in-control and out-of-control average run lengths. The results showed that the proposed chart is better than the existing variable control chart to detect an early shift in the process. An industrial example is given to illustrate the proposed chart in the industry.
The Use of River Flow Discharge and Sediment Load for Multi-Objective Calibration of SWAT Based on the Bayesian Inference
Authors: Cheng Qin-Bo , Chen Xi , Wang Jiao , Zhang Zhi-Cai , Zhang Run-Run , Xie Yong-Yu , Reinhardt-Imjela Christian , Schulte Achim
Published: November 2018

The soil and water assessment tool (SWAT) is widely used to quantify the spatial and temporal patterns of sediment loads for watershed-scale management of sediment and nonpoint-source pollutants. However few studies considered the trade-off between flow and sediment objectives during model calibration processes. This study proposes a new multi-objective calibration method that incorporates both flow and sediment observed information into a likelihood function based on the Bayesian inference. For comparison, two likelihood functions, i.e., the Nash–Sutcliffe efficiency coefficient (NSE) approach that assumes model residuals follow the Gaussian distribution, and the BC-GED approach that assumes model residuals after Box–Cox transformation (BC) follow the generalized error distribution (GED), are applied for calibrating the flow and sediment parameters of SWAT with the water balance model and the variable source area concept (SWAT-WB-VSA) in the Baocun watershed, Eastern China. Compared with the single-objective method, the multi-objective approach improves the performance of sediment simulations without significantly impairing the performance of flow simulations, and reduces the uncertainty of flow parameters, especially flow concentration parameters. With the NSE approach, SWAT-WB-VSA captures extreme flood events well, but fails to mimic low values of river discharge and sediment load, possibly because the NSE approach is an informal likelihood function, and puts greater emphasis on high values. By contrast, the BC-GED approach approximates a formal likelihood function, and balances consideration of the high- and low- values. As a result, inferred results of the BC-GED method are more reasonable and consistent with the field survey results and previous related-studies. This method even discriminates the nonerodible characteristic of main channels.
Numerical Modeling of Flow Over a Rectangular Broad-Crested Weir with a Sloped Upstream Face
Authors: Jiang Lei , Diao Mingjun , Sun Haomiao , Ren Yu
Published: November 2018

The objective of this study was to evaluate the effect of the upstream angle on flow over a trapezoidal broad-crested weir based on numerical simulations using the open-source toolbox OpenFOAM. Eight trapezoidal broad-crested weir configurations with different upstream face angles (θ = 10°, 15°, 22.5°, 30°, 45°, 60°, 75°, 90°) were investigated under free-flow conditions. The volume-of-fluid (VOF) method and two turbulence models (the standard k-ε model and the SST k-w model) were employed in the numerical simulations. The numerical results were compared with the experimental results obtained from published papers. The root mean square error (RMSE) and the mean absolute percent error (MAPE) were used to evaluate the accuracy of the numerical results. The statistical results show that RMSE and MAPE values of the standard k-ε model are 0.35–0.67% and 0.50–1.48%, respectively; the RMSE and MAPE values of the SST k-w model are 0.25–0.66% and 0.55–1.41%, respectively. Additionally, the effects of the upstream face angle on the flow features, including the discharge coefficient and the flow separation zone, were also discussed in the present study.
Inter-Sectoral Linkage and External Trade Analysis for Virtual Water and Embodied Carbon Emissions in China
Authors: Huang Huiping , Li Xinsheng , Cao Lianhai , Jia Dongdong , Zhang Junlong , Wang Chunying , Han Yuping
Published: November 2018

In the globalized world, water utilization and carbon emissions are two important indicators for water and energy resources evaluation. This paper investigates the inter-sectoral linkage and external trade of virtual water (water embodied in products) and embodied carbon emissions in China based on input–output tables during 1997–2015. Results indicate that: inside China, agriculture, the electric and water industry are major virtual water suppliers, while heavy industrial sectors including the metal products industry, the petrochemical industry, other nonmetallic mineral products industry, and the mining industry are major embodied carbon emissions suppliers. China is the net exporter of virtual water (137.15 × 109 m3) and embodied carbon emissions (16.05 × 108 t). From the perspective of industrial chain, about 81% of virtual water export come from agriculture, the electric and water industry ultimately, and about 85% of embodied carbon emissions export come from the mining industry, the petrochemical industry, other nonmetallic mineral products industry, the metal products industry, and the electric and water industry ultimately.
Sur les indices des cristaux liquides : mesure par la méthode du prisme et étude théorique
Authors: Pellet Odette , Chatelain Pierre
Published: November 2018

Les indices de trois corps nématiques, mesurés par la méthode du prisme en fonction de la température et pour deux longueurs d'onde, sont donnés pour les phases cristal liquide et liquide isotrope dans la première partie de ce travail.

Dans la seconde partie les divers modes de calcul du champ de polarisation moléculaire sont discutés. Partant de ce que, dans le cristal liquide, il existe des domaines de l'ordre de 1/10 de µ dans lesquels les molécules sont très sensiblement parallèles les unes aux autres, une modification au calcul classique de Lorentz-Lorenz est apportée ; elle conduit à une meilleure vérification expérimentale des résultats théoriques.
La détermination des structures cristallines à partir du diagramme de Patterson
Authors: Clastre José , Gay Robert
Published: November 2018

On peut décomposer la recherche des structures cristallines en deux étapes : la détermination des positions atomiques, et l'identification des atomes pour chacunes de ces positions. On montre qu'il est possible de déterminer, d'une part les positions atomiques, d'autre part d'identifier les atomes directement à partir de la fonction de Patterson, sans la connaissance préalable des phases des facteurs de structure. On indique une méthode pratique permettant cette détermination.