bluuebunny/crossref_metadata_2025 huggingface dataset:
The Anti-Aging Potential of Neohesperidin and Its Synergistic Effects with Other Citrus Flavonoids in Extending Chronological Lifespan of Saccharomyces Cerevisiae BY4742
Authors: Guo Chunxia , Zhang Hua , Guan Xin , Zhou Zhiqin
Published: November 2019

The anti-aging activity of many plant flavonoids, as well as their mechanisms of action, have been explored in the current literature. However, the studies on the synergistic effects between the different flavonoid compounds were quite limited in previous reports. In this study, by using a high throughput assay, we tested the synergistic effects between different citrus flavonoids throughout the yeast’s chronological lifespan (CLS). We studied the effect of four flavonoid compounds including naringin, hesperedin, hesperitin, neohesperidin, as well as their different combinations on the CLS of the yeast strain BY4742. Their ROS scavenging ability, in vitro antioxidant activity and the influence on the extracellular pH were also tested. The results showed that neohesperidin extended the yeast’s CLS in a concentration-dependent manner. Especially, we found that neohesperidin showed great potential in extending CLS of budding yeast individually or synergistically with hesperetin. The neohesperidin exhibited the strongest function in decreasing the reactive oxygen species (ROS) accumulation in yeast. These findings clearly indicated that neohesperidin is potentially an anti-aging citrus flavonoid, and its synergistic effect with other flavonoids on yeast’s CLS will be an interesting subject for future research of the anti-aging function of citrus fruits.
Synthesis and Anticancer Activity of CDDO and CDDO-Me, Two Derivatives of Natural Triterpenoids
Authors: Borella Rebecca , Forti Luca , Gibellini Lara , De Gaetano Anna , De Biasi Sara , Nasi Milena , Cossarizza Andrea , Pinti Marcello
Published: November 2019

Triterpenoids are natural compounds synthesized by plants through cyclization of squalene, known for their weak anti-inflammatory activity. 2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oic acid (CDDO), and its C28 modified derivative, methyl-ester (CDDO-Me, also known as bardoxolone methyl), are two synthetic derivatives of oleanolic acid, synthesized more than 20 years ago, in an attempt to enhance the anti-inflammatory behavior of the natural compound. These molecules have been extensively investigated for their strong ability to exert antiproliferative, antiangiogenic, and antimetastatic activities, and to induce apoptosis and differentiation in cancer cells. Here, we discuss the chemical properties of natural triterpenoids, the pathways of synthesis and the biological effects of CDDO and its derivative CDDO-Me. At nanomolar doses, CDDO and CDDO-Me have been shown to protect cells and tissues from oxidative stress by increasing the transcriptional activity of the nuclear factor (erythroid-derived 2)-like 2 (Nrf2). At doses higher than 100 nM, CDDO and CDDO-Me are able to modulate the differentiation of a variety of cell types, both tumor cell lines or primary culture cell, while at micromolar doses these compounds exert an anticancer effect in multiple manners; by inducing extrinsic or intrinsic apoptotic pathways, or autophagic cell death, by inhibiting telomerase activity, by disrupting mitochondrial functions through Lon protease inhibition, and by blocking the deubiquitylating enzyme USP7. CDDO-Me demonstrated its efficacy as anticancer drugs in different mouse models, and versus several types of cancer. Several clinical trials have been started in humans for evaluating CDDO-Me efficacy as anticancer and anti-inflammatory drug; despite promising results, significant increase in heart failure events represented an obstacle for the clinical use of CDDO-Me.
Improving Water Permeability of Hydrophilic PVDF Membrane Prepared via Blending with Organic and Inorganic Additives for Humic Acid Separation
Authors: Arahman Nasrul , Mulyati Sri , Fahrina Afrillia , Muchtar Syawaliah , Yusuf Mukramah , Takagi Ryosuke , Matsuyama Hideto , Nordin Nik Abdul Hadi , Bilad Muhammad Roil
Published: November 2019

The removal of impurities from water or wastewater by the membrane filtration process has become more reliable due to good hydraulic performance and high permeate quality. The filterability of the membrane can be improved by having a material with a specific pore structure and good hydrophilic properties. This work aims at preparing a polyvinylidene fluoride (PVDF) membrane incorporated with phospholipid in the form of a 2-methacryloyloxyethyl phosphorylcholine, polymeric additive in the form of polyvinylpyrrolidone, and its combination with inorganic nanosilica from a renewable source derived from bagasse. The resulting membrane morphologies were analyzed by using scanning electron microscopy. Furthermore, atomic force microscopy was performed to analyze the membrane surface roughness. The chemical compositions of the resulting membranes were identified using Fourier transform infrared. A lab-scale cross-flow filtration system module was used to evaluate the membrane’s hydraulic and separation performance by the filtration of humic acid (HA) solution as the model contaminant. Results showed that the additives improved the membrane surface hydrophilicity. All modified membranes also showed up to five times higher water permeability than the pristine PVDF, thanks to the improved structure. Additionally, all membrane samples showed HA rejections of 75–90%.
Dicentrine Potentiates TNF-α-Induced Apoptosis and Suppresses Invasion of A549 Lung Adenocarcinoma Cells via Modulation of NF-κB and AP-1 Activation
Authors: Ooppachai Chanatip , Limtrakul (Dejkriengkraikul) Pornngarm , Yodkeeree Supachai
Published: November 2019

Numerous studies have indicated that tumor necrosis factor-alpha (TNF-α) could induce cancer cell survival and metastasis via activation of transcriptional activity of NF-κB and AP-1. Therefore, the inhibition of TNF-α-induced NF-κB and AP-1 activity has been considered in the search for drugs that could effectively treat cancer. Dicentrine, an aporphinic alkaloid, exerts anti-inflammatory and anticancer activities. Therefore, we investigated the effects of dicentrine on TNF-α-induced tumor progression in A549 lung adenocarcinoma cells. Our results demonstrated that dicentrine effectively sensitizes TNF-α-induced apoptosis in A549 cells when compared with dicentrine alone. In addition, dicentrine increases caspase-8, -9, -3, and poly (ADP-ribose) polymerase (PARP) activities by upregulating the death-inducing signaling complex and by inhibiting the expression of antiapoptotic proteins including cIAP2, cFLIP, and Bcl-XL. Furthermore, dicentrine inhibits the TNF-α-induced A549 cells invasion and migration. This inhibition is correlated with the suppression of invasive proteins in the presence of dicentrine. Moreover, dicentrine significantly blockes TNF-α-activated TAK1, p38, JNK, and Akt, leading to reduced levels of the transcriptional activity of NF-κB and AP-1. Taken together, our results suggest that dicentrine could enhance TNF-α-induced A549 cell death by inducing apoptosis and reducing cell invasion due to, at least in part, the suppression of TAK-1, MAPK, Akt, AP-1, and NF-κB signaling pathways.
DNA-Templated Fluorescent Nanoclusters for Metal Ions Detection
Authors: Song Chunxia , Xu Jingyuan , Chen Ying , Zhang Liangliang , Lu Ying , Qing Zhihe
Published: November 2019

DNA-templated fluorescent nanoclusters (NCs) have attracted increasing research interest on account of their prominent features, such as DNA sequence-dependent fluorescence, easy functionalization, wide availability, water solubility, and excellent biocompatibility. Coupling DNA templates with complementary DNA, aptamers, G-quadruplex, and so on has generated a large number of sensors. Additionally, the preparation and applications of DNA-templated fluorescent NCs in these sensing have been widely studied. This review firstly focuses on the properties of DNA-templated fluorescent NCs, and the synthesis of DNA-templated fluorescent NCs with different metals is then discussed. In the third part, we mainly introduce the applications of DNA-templated fluorescent NCs for sensing metal ions. At last, we further discuss the future perspectives of DNA-templated fluorescent NCs in the synthesis and sensing metal ions in the environmental and biological fields.
Single Production of Kojic Acid by Aspergillus flavus and the Revision of Flufuran
Authors: Ola Antonius R. B. , Metboki Gema , Lay Caterina S. , Sugi Yoseph , Rozari Philipi De , Darmakusuma Dodi , Hakim Euis Holisotan
Published: November 2019

Timor Island is very hot and dry due to the high intensity of sunlight experienced throughout the year. The endophytic fungi Aspergillus flavus had been isolated from medicinal plants such as Catharanthus roseus, Annona squamosa and Curcuma xanthorisa. The endophytic fungi A. flavus from each plant was cultivated on solid rice media and then analyzed for its capability for producing kojic acid. The production of kojic acid was analyzed by HPLC; the highest amount of kojic acid was observed from the endophytic fungi A. flavus, isolated from the stem of Catharanthus roseus, followed by A. flavus from Annona squamosa and Curcuma xanthorisa. Simple VLC fractionation of the extract of A. flavus from C.roseus led to the isolation of around 11.1 g of pure kojic acid. The structure of kojic acid (1) was confirmed by NMR and MS spectroscopic data. A comparison of the NMR data with the literature supported the revision of the natural product flufuran to kojic acid. To the best of our knowledge, this is the first report of a strain of endophytic fungi producing only kojic acid without any other toxic metabolites such as alfatoxins. Therefore, this Aspergillus flavus strain can be applied as a potential producer of kojic acid for industrial use.
Adherence to the Mediterranean Diet and Its Association with Body Composition and Physical Fitness in Spanish University Students
Authors: Cobo-Cuenca Ana Isabel , Garrido-Miguel Miriam , Soriano-Cano Alba , Ferri-Morales Asunción , Martínez-Vizcaíno Vicente , Martín-Espinosa Noelia María
Published: November 2019

The aims of this study were to assess the association of adherence to the Mediterranean diet (MD) with physical fitness and body composition in Spanish university students and to determine the ability to predict the MD adherence of each Mediterranean Diet Adherence Screener (MEDAS) item. A cross-sectional study was performed involving 310 first-year university students. Adherence to the MD was evaluated with MEDAS-14 items. Anthropometric variables, body composition, and physical fitness were assessed. Muscle strength was determined based on handgrip strength and the standing long jump test. Cardiorespiratory fitness (CRF) was measured using the Course–Navette test. Only 24% of the university students had good adherence to the MD. The ANCOVA models showed a significant difference between participants with high adherence to the MD and those with medium and low adherence in CRF (p = 0.017) and dynamometry (p = 0.005). Logistic binary regression showed that consuming >2 vegetables/day (OR = 20.1; CI: 10.1–30.1; p < 0.001), using olive oil (OR = 10.6; CI: 1.4–19.8; p = 0.021), consuming <3 commercial sweets/week (OR = 10.1; IC: 5.1–19.7; p < 0.001), and consuming ≥3 fruits/day (OR = 8.8; CI: 4.9–15.7; p < 0.001) were the items most associated with high adherence to the MD. In conclusion, a high level of adherence to the MD is associated with high-level muscular fitness and CRF in Spanish university students.
Vitamin D Levels in Women with Polycystic Ovary Syndrome: A Population-Based Study
Authors: Lumme Johanna , Sebert Sylvain , Pesonen Paula , Piltonen Terhi , Järvelin Marjo-Riitta , Herzig Karl-Heinz , Auvinen Juha , Ojaniemi Marja , Niinimäki Maarit
Published: November 2019

Background: Conflicting evidence supports a role for vitamin D in women with reproductive disorders such as polycystic ovary syndrome (PCOS) but studies on large, unselected populations have been lacking. Methods: We conducted a general population-based study from the prospective Northern Finland Birth Cohort 1966 (NFBC1966). Serum 25-hydroksyvitamin D (25(OH)D) levels were evaluated in women with self-reported PCOS (n = 280) versus non-symptomatic controls (n = 1573) at the age of 31 with wide range of endocrine and metabolic confounders. Results: The levels of 25(OH)D were similar among women with and without self-reported PCOS (50.35 vs. 48.30 nmol/L, p = 0.051). Women with self-reported PCOS presented with a higher body mass index (BMI), increased insulin resistance, and low-grade inflammation and testosterone levels compared to controls. The adjusted linear regression model showed a positive association between total 25(OH)D levels in self-reported PCOS (β = 2.46, 95% confidence interval (CI) 0.84 to 4.08, p = 0.003). The result remained after adjustment for BMI, testosterone, homeostatic model assessment of insulin resistance (HOMA-IR), and high-sensitivity C-reactive protein (hs-CRP) levels. Conclusion: In this population-based setting, PCOS was associated with higher vitamin D levels when adjusting for confounding factors, without distinct beneficial effects on metabolic derangements.
Immunohistochemical Expression Patterns of Inflammatory Cells Involved in Chronic Hyperplastic Candidosis
Authors: Williams Ailish , Williams David , Rogers Helen , Wei Xiaoqing , Lewis Michael , Wozniak Sue , Farnell Damian , Jones Adam
Published: November 2019

The profile of the inflammatory cell infiltrate in chronic hyperplastic candidosis (CHC) was determined in oral mucosal biopsies by immunohistochemistry. One tonsillar tissue section was included as an immunohistochemistry control, whilst squamous papilloma (n = 4) with secondary Candida infection was used as Candida controls. Oral lichen planus tissues (n = 10) provided negative controls for Candida presence, as well as positive controls for inflammation. Immunohistochemistry employed antibodies specific for CD3+ (T lymphocytes), CD4+ (T helper cells), CD8+ (cytotoxic T cells), and CD20+ (B lymphocytes). Manual counting of stained cells from digitised images determined the proportion of each cell type relative to the total number of cells, and these were assessed in the mucosa, the epithelium, and the lamina propria. The mean proportion of CD3+ cells was significantly higher than CD20+ cells in all tissue types. For CHC, the mean proportion of CD3+ cells in entire tissues was 15.6%, with the highest proportion in the lamina propria (32.6%) compared with the epithelium (3.9%). CD20+ cells were in much lower proportions (1.8%) in CHC, with the highest proportion (3.6%) in the lamina propria. T lymphocytes were predominately CD4+ cells (9.0%) compared with CD8+ cells (4.4%). CD4+ cells were most prevalent in the lamina propria (23.1%) compared with the epithelium (mean = 3.2%). From these results, it was concluded that the immune response invoked by Candida in CHC is primarily driven by the T helper cells.
Quantification of Enterocytozoon hepatopenaei (EHP) in Penaeid Shrimps from Southeast Asia and Latin America Using TaqMan Probe-Based Quantitative PCR
Authors: Piamsomboon Patharapol , Choi Seong-Kyoon , Hanggono Bambang , Nuraini Yani Lestari , Wati Fatma , Tang Kathy F. J. , Park Song , Kwak Dongmi , Rhee Man Hee , Han Jee Eun , Kim Ji Hyung
Published: November 2019

We developed a qPCR assay based on the β-tubulin gene sequence for the shrimp microsporidian parasite Enterocytozoon hepatopenaei (EHP). This assay reacted with the hepatopancreas (HP) of EHP-infected shrimps, and the highest copy numbers were found in HP and feces samples from Southeast Asian countries (106–108 copies mg−1), while HP samples from Latin America, Artemia, and EHP-contaminated water showed lower amounts (101–103 copies mg−1 or mL−1 of water). No false positive was found with the normal shrimp genome, live feeds, or other parasitic diseases. This tool will facilitate the management of EHP infection in shrimp farms.
The Development and Characterization of Near-Isogenic and Pyramided Lines Carrying Resistance Genes to Brown Planthopper with the Genetic Background of Japonica Rice (Oryza sativa L.)
Authors: Nguyen Cuong D. , Verdeprado Holden , Zita Demeter , Sanada-Morimura Sachiyo , Matsumura Masaya , Virk Parminder S. , Brar Darshan S. , Horgan Finbarr G. , Yasui Hideshi , Fujita Daisuke
Published: November 2019

The brown planthopper (BPH: Nilaparvata lugens Stål.) is a major pest of rice, Oryza sativa, in Asia. Host plant resistance has tremendous potential to reduce the damage caused to rice by the planthopper. However, the effectiveness of resistance genes varies spatially and temporally according to BPH virulence. Understanding patterns in BPH virulence against resistance genes is necessary to efficiently and sustainably deploy resistant rice varieties. To survey BPH virulence patterns, seven near-isogenic lines (NILs), each with a single BPH resistance gene (BPH2-NIL, BPH3-NIL, BPH17-NIL, BPH20-NIL, BPH21-NIL, BPH32-NIL and BPH17-ptb-NIL) and fifteen pyramided lines (PYLs) carrying multiple resistance genes were developed with the genetic background of the japonica rice variety, Taichung 65 (T65), and assessed for resistance levels against two BPH populations (Hadano-66 and Koshi-2013 collected in Japan in 1966 and 2013, respectively). Many of the NILs and PYLs were resistant against the Hadano-66 population but were less effective against the Koshi-2013 population. Among PYLs, BPH20+BPH32-PYL and BPH2+BPH3+BPH17-PYL granted relatively high BPH resistance against Koshi-2013. The NILs and PYLs developed in this research will be useful to monitor BPH virulence prior to deploying resistant rice varieties and improve rice’s resistance to BPH in the context of regionally increasing levels of virulence.
Analysis of Parameters for the Accurate and Fast Estimation of Tree Diameter at Breast Height Based on Simulated Point Cloud
Authors: Wang Pei , Gan Xiaozheng , Zhang Qing , Bu Guochao , Li Li , Xu Xiuxian , Li Yaxin , Liu Zichu , Xiao Xiangming
Published: November 2019

Terrestrial laser scanning (TLS) is a high-potential technology in forest surveys. Estimating the diameters at breast height (DBH) accurately and quickly has been considered a key step in estimating forest structural parameters by using TLS technology. However, the accuracy and speed of DBH estimation are affected by many factors, which are classified into three groups in this study. We adopt an additive error model and propose a simple and common simulation method to evaluate the impacts of three groups of parameters, which include the range error, angular errors in the vertical and horizontal directions, angular step width, trunk distance, slice thickness, and real DBH. The parameters were evaluated statistically by using many simulated point cloud datasets that were under strict control. Two typical circle fitting methods were used to estimate DBH, and their accuracy and speed were compared. The results showed that the range error and the angular error in horizontal direction played major roles in the accuracy of DBH estimation, the angular step widths had a slight effect in the case of high range accuracy, the distance showed no relationship with the accuracy of the DBH estimation, increasing the scanning angular width was relatively beneficial to the DBH estimation, and the algebraic circle fitting method was relatively fast while performing DBH estimation, as is the geometrical method, in the case of high range accuracy. Possible methods that could help to obtain accurate and fast DBH estimation results were proposed and discussed to optimize the design of forest inventory experiments.
Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia)
Authors: Dandridge Chelsea , Lakshmi Venkat , Bolten John , Srinivasan Raghavan
Published: November 2019

Satellite-based precipitation is an essential tool for regional water resource applications that requires frequent observations of meteorological forcing, particularly in areas that have sparse rain gauge networks. To fully realize the utility of remotely sensed precipitation products in watershed modeling and decision-making, a thorough evaluation of the accuracy of satellite-based rainfall and regional gauge network estimates is needed. In this study, Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42 v.7 and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily rainfall estimates were compared with daily rain gauge observations from 2000 to 2014 in the Lower Mekong River Basin (LMRB) in Southeast Asia. Monthly, seasonal, and annual comparisons were performed, which included the calculations of correlation coefficient, coefficient of determination, bias, root mean square error (RMSE), and mean absolute error (MAE). Our validation test showed TMPA to correctly detect precipitation or no-precipitation 64.9% of all days and CHIRPS 66.8% of all days, compared to daily in-situ rainfall measurements. The accuracy of the satellite-based products varied greatly between the wet and dry seasons. Both TMPA and CHIRPS showed higher correlation with in-situ data during the wet season (June–September) as compared to the dry season (November–January). Additionally, both performed better on a monthly than an annual time-scale when compared to in-situ data. The satellite-based products showed wet biases during months that received higher cumulative precipitation. Based on a spatial correlation analysis, the average r-value of CHIRPS was much higher than TMPA across the basin. CHIRPS correlated better than TMPA at lower elevations and for monthly rainfall accumulation less than 500 mm. While both satellite-based products performed well, as compared to rain gauge measurements, the present research shows that CHIRPS might be better at representing precipitation over the LMRB than TMPA.
Deep Learning-Generated Nighttime Reflectance and Daytime Radiance of the Midwave Infrared Band of a Geostationary Satellite
Authors: Kim Yerin , Hong Sungwook
Published: November 2019

Midwave infrared (MWIR) band of 3.75 μm is important in satellite remote sensing in many applications. This band observes daytime reflectance and nighttime radiance according to the Earth’s and the Sun’s effects. This study presents an algorithm to generate no-present nighttime reflectance and daytime radiance at MWIR band of satellite observation by adopting the conditional generative adversarial nets (CGAN) model. We used the daytime reflectance and nighttime radiance data in the MWIR band of the meteoritical imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), as well as in the longwave infrared (LWIR; 10.8 μm) band of the COMS/MI sensor, from 1 January to 31 December 2017. This model was trained in a size of 1024 × 1024 pixels in the digital number (DN) from 0 to 255 converted from reflectance and radiance with a dataset of 256 images, and validated with a dataset of 107 images. Our results show a high statistical accuracy (bias = 3.539, root-mean-square-error (RMSE) = 8.924, and correlation coefficient (CC) = 0.922 for daytime reflectance; bias = 0.006, RMSE = 5.842, and CC = 0.995 for nighttime radiance) between the COMS MWIR observation and artificial intelligence (AI)-generated MWIR outputs. Consequently, our findings from the real MWIR observations could be used for identification of fog/low cloud, fire/hot-spot, volcanic eruption/ash, snow and ice, low-level atmospheric vector winds, urban heat islands, and clouds.
Continuous Monitoring of Differential Reflectivity Bias for C-Band Polarimetric Radar Using Online Solar Echoes in Volume Scans
Authors: Chu Zhigang , Liu Wei , Zhang Guifu , Kou Leilei , Li Nan
Published: November 2019

The measurement error of differential reflectivity (ZDR), especially systematic ZDR bias, is a fundamental issue for the application of polarimetric radar data. Several calibration methods have been proposed and applied to correct ZDR bias. However, recent studies have shown that ZDR bias is time-dependent and can be significantly different on two adjacent days. This means that the frequent monitoring of ZDR bias is necessary, which is difficult to achieve with existing methods. As radar sensitivity has gradually been enhanced, large amounts of online solar echoes have begun to be observed in volume-scan data. Online solar echoes have a high frequency, and a known theoretical value of ZDR (0 dB) could thus allow the continuous monitoring of ZDR bias. However, online solar echoes are also affected by low signal-to-noise ratio and precipitation attenuation for short-wavelength radar. In order to understand the variation of ZDR bias in a C-band polarimetric radar at the Nanjing University of Information Science and Technology (NUIST-CDP), we analyzed the characteristics of online solar echoes from this radar, including the daily frequency of occurrence, the distribution along the radial direction, precipitation attenuation, and fluctuation caused by noise. Then, an automatic method based on online solar echoes was proposed to monitor the daily ZDR bias of the NUIST-CDP. In the proposed method, a one-way differential attenuation correction for solar echoes and a maximum likelihood estimation using a Gaussian model were designed to estimate the optimal daily ZDR bias. The analysis of three months of data from the NUIST-CDP showed the following: (1) Online solar echoes occurred very frequently regardless of precipitation. Under the volume-scan mode, the average number of occurrences was 15 per day and the minimum number was seven. This high frequency could meet the requirements of continuous monitoring of the daily ZDR bias under precipitation and no-rain conditions. (2) The result from the proposed online solar method was significantly linearly correlated with that from the vertical pointing method (observation at an elevation angle of 90°), with a correlation coefficient of 0.61, suggesting that the proposed method is feasible. (3) The day-to-day variation in the ZDR bias was relatively large, and 32% of such variations exceeded 0.2 dB, meaning that a one-time calibration was not representative in time. Accordingly, continuous calibration will be necessary. (4) The ZDR bias was found to be largely influenced by the ambient temperature, with a large negative correlation between the ZDR bias and the temperature.
Detection of Crack Initiation and Growth Using Fiber Bragg Grating Sensors Embedded into Metal Structures through Ultrasonic Additive Manufacturing
Authors: Chilelli Sean K. , Schomer John J. , Dapino Marcelo J.
Published: November 2019

Structural health monitoring (SHM) is a rapidly growing field focused on detecting damage in complex systems before catastrophic failure occurs. Advanced sensor technologies are necessary to fully harness SHM in applications involving harsh or remote environments, life-critical systems, mass-production vehicles, robotic systems, and others. Fiber Bragg Grating (FBG) sensors are attractive for in-situ health monitoring due to their resistance to electromagnetic noise, ability to be multiplexed, and accurate real-time operation. Ultrasonic additive manufacturing (UAM) has been demonstrated for solid-state fabrication of 3D structures with embedded FBG sensors. In this paper, UAM-embedded FBG sensors are investigated with a focus on SHM applications. FBG sensors embedded in an aluminum matrix 3 mm from the initiation site are shown to resolve a minimum crack length of 0.286 ± 0.033 mm and track crack growth until near failure. Accurate crack detection is also demonstrated from FBGs placed 6 mm and 9 mm from the crack initiation site. Regular acrylate-coated FBG sensors are shown to repeatably work at temperatures up to 300 ∘ C once embedded with the UAM process.
Magnetic-based Soft Tactile Sensors with Deformable Continuous Force Transfer Medium for Resolving Contact Locations in Robotic Grasping and Manipulation
Authors: Mohammadi Alireza , Xu Yangmengfei , Tan Ying , Choong Peter , Oetomo Denny
Published: November 2019

The resolution of contact location is important in many applications in robotics and automation. This is generally done by using an array of contact or tactile receptors, which increases cost and complexity as the required resolution or area is increased. Tactile sensors have also been developed using a continuous deformable medium between the contact and the receptors, which allows few receptors to interpolate the information among them, avoiding the weakness highlighted in the former approach. The latter is generally used to measure contact force intensity or magnitude but rarely used to identify the contact locations. This paper presents a systematic design and characterisation procedure for magnetic-based soft tactile sensors (utilizing the latter approach with the deformable contact medium) with the goal of locating the contact force location. This systematic procedure provides conditions under which design parameters can be selected, supported by a selected machine learning algorithm, to achieve the desired performance of the tactile sensor in identifying the contact location. An illustrative example, which combines a particular sensor configuration (magnetic hall effect sensor as the receptor, a selected continuous medium and a selected sensing resolution) and a specific data-driven algorithm, is used to illustrate the proposed design procedure. The results of the illustrative example design demonstrates the efficacy of the proposed design procedure and the proposed sensing strategy in identifying a contact location. The resulting sensor is also tested on a robotic hand (Allegro Hand, SimLab Co) to demonstrate its application in real-world scenarios.
A Dual Neural Architecture Combined SqueezeNet with OctConv for LiDAR Data Classification
Authors: Wang Aili , Wang Minhui , Jiang Kaiyuan , Cao Mengqing , Iwahori Yuji
Published: November 2019

Light detection and ranging (LiDAR) is a frequently used technique of data acquisition and it is widely used in diverse practical applications. In recent years, deep convolutional neural networks (CNNs) have shown their effectiveness for LiDAR-derived rasterized digital surface models (LiDAR-DSM) data classification. However, many excellent CNNs have too many parameters due to depth and complexity. Meanwhile, traditional CNNs have spatial redundancy because different convolution kernels scan and store information independently. SqueezeNet replaces a part of 3 × 3 convolution kernels in CNNs with 1 × 1 convolution kernels, decomposes the original one convolution layer into two layers, and encapsulates them into a Fire module. This structure can reduce the parameters of network. Octave Convolution (OctConv) pools some feature maps firstly and stores them separately from the feature maps with the original size. It can reduce spatial redundancy by sharing information between the two groups. In this article, in order to improve the accuracy and efficiency of the network simultaneously, Fire modules of SqueezeNet are used to replace the traditional convolution layers in OctConv to form a new dual neural architecture: OctSqueezeNet. Our experiments, conducted using two well-known LiDAR datasets and several classical state-of-the-art classification methods, revealed that our proposed classification approach based on OctSqueezeNet is able to provide competitive advantages in terms of both classification accuracy and computational amount.
A Systematic Review of Detecting Sleep Apnea Using Deep Learning
Authors: Mostafa Sheikh Shanawaz , Mendonça Fábio , G. Ravelo-García Antonio , Morgado-Dias Fernando
Published: November 2019

Sleep apnea is a sleep related disorder that significantly affects the population. Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an expert technician is needed to score. Numerous researchers have proposed and implemented automatic scoring processes to address these issues, based on fewer sensors and automatic classification algorithms. Deep learning is gaining higher interest due to database availability, newly developed techniques, the possibility of producing machine created features and higher computing power that allows the algorithms to achieve better performance than the shallow classifiers. Therefore, the sleep apnea research has currently gained significant interest in deep learning. The goal of this work is to analyze the published research in the last decade, providing an answer to the research questions such as how to implement the different deep networks, what kind of pre-processing or feature extraction is needed, and the advantages and disadvantages of different kinds of networks. The employed signals, sensors, databases and implementation challenges were also considered. A systematic search was conducted on five indexing services from 2008–2018. A total of 255 papers were found and 21 were selected by considering the inclusion and exclusion criteria, using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach.
Modeling Indoor Relative Humidity and Wood Moisture Content as a Proxy for Wooden Home Fire Risk
Authors: Log Torgrim
Published: November 2019

Severe wooden home conflagrations have previously been linked to the combination of very dry indoor climate in inhabited buildings during winter time, resulting in rapid fire development and strong winds spreading the fire to neighboring structures. Knowledge about how ambient conditions increase the fire risk associated with dry indoor conditions is, however, lacking. In the present work, the moisture content of indoor wooden home wall panels was modeled based on ambient temperature and relative humidity recorded at meteorological stations as the climatic boundary conditions. The model comprises an air change rate based on ambient and indoor (22 °C) temperatures, indoor moisture sources and wood panel moisture sorption processes; it was tested on four selected homes in Norway during the winter of 2015/2016. The results were compared to values recorded by indoor relative humidity sensors in the homes, which ranged from naturally ventilated early 1900s homes to a modern home with balanced ventilation. The modeled indoor relative humidity levels during cold weather agreed well with recorded values to within 3% relative humidity (RH) root mean square deviation, and thus provided reliable information about expected wood panel moisture content. This information was used to assess historic single home fire risk represented by an estimated time to flashover during the studied period. Based on the modelling, it can be concluded that three days in Haugesund, Norway, in January 2016 were associated with very high conflagration risk due to dry indoor wooden materials and strong winds. In the future, the presented methodology may possibly be based on weather forecasts to predict increased conflagration risk a few days ahead. This could then enable proactive emergency responses for improved fire disaster risk management.
Experimental Validation of Slip-Forming Using Ultrasonic Sensors
Authors: Yoon Hyejin , Kim Young Jin , Chin Won Jong , Kang Jun Won , Koh Hyun-Moo
Published: November 2019

Slip-forming in concrete construction enables the continuous placement of concrete using a climbing form, the efficiency of which depends on appropriate slip-up timing. This implies the importance of knowing accurately the development of concrete strength over time, which has been assessed manually to date in construction fields. This paper presents a method for automating the slip-forming process by determining the optimal slip-up time using the in-situ strength of concrete. The strength of concrete is evaluated by a formula relating the strength to the surface wave velocity measured with ultrasonic sensors. Specifically, this study validates the applicability of the slip-form system with ultrasonic sensors for continuously monitoring the hardening of concrete through its application in several construction sites. To this end, a slip-form system with a pair of ultrasonic modules at the bottom of the panel was tested and the time variation of surface wave velocity in the concrete material was monitored during the slip-forming process. The results show that the proposed method can provide the optimal slip-up time of the form to automate the slip-forming process. This approach is expected to apply to other construction technologies that required the continuous monitoring of concrete strength for construction efficiency as well as quality maintenance.
Maximum Power Point Tracking of Photovoltaic System Based on Reinforcement Learning
Authors: Chou Kuan-Yu , Yang Shu-Ting , Chen Yon-Ping
Published: November 2019

The maximum power point tracking (MPPT) technique is often used in photovoltaic (PV) systems to extract the maximum power in various environmental conditions. The perturbation and observation (P&O) method is one of the most well-known MPPT methods; however, it may face problems of large oscillations around maximum power point (MPP) or low-tracking efficiency. In this paper, two reinforcement learning-based maximum power point tracking (RL MPPT) methods are proposed by the use of the Q-learning algorithm. One constructs the Q-table and the other adopts the Q-network. These two proposed methods do not require the information of an actual PV module in advance and can track the MPP through offline training in two phases, the learning phase and the tracking phase. From the experimental results, both the reinforcement learning-based Q-table maximum power point tracking (RL-QT MPPT) and the reinforcement learning-based Q-network maximum power point tracking (RL-QN MPPT) methods have smaller ripples and faster tracking speeds when compared with the P&O method. In addition, for these two proposed methods, the RL-QT MPPT method performs with smaller oscillation and the RL-QN MPPT method achieves higher average power.
Impact of Seasonal Changes of Precipitation and Air Temperature on Clay Excavation
Authors: Težak Denis , Soldo Božo , Đurin Bojan , Kranjčić Nikola
Published: November 2019

Excavation of clay soil is one of the most important economic branches in the northern part of Croatia. The impact of clay soil in Croatia compared to the global exploitation fields of clay soil is negligible. Modern methods of clay excavation during winter months due to negligible amounts are not profitable. Therefore, it is important to optimize clay soil excavation throughout the year to increase the efficiency of exploitation and increase profits. In the case of large amounts of precipitation (rain), clay absorbs water and becomes grain. For this reason, access to the exploitation field and excavation itself becomes impossible. Air temperature also plays an important role in excavation. Long-lasting low air temperatures below 0 °C during the winter months result in clay frost. As a result, excavation cannot occur at that time. The paper describes a new method of modeling the precipitation and air temperature on the exploitation fields of clay in Northwest Croatia on the exploitation fields of Cukavec and Cukavec II. The method involves the calculation of the drought index and use of the rescaled adjusted partial sums (RAPS) statistical method and its application on a time series of total daily precipitation and average daily temperatures as a climatic indicator of any observed area. Using this process, it is possible to determine the time period of the year when clay soil can be excavated.
Air Pollutant Emissions from Vehicles and Their Abatement Scenarios: A Case Study of Chengdu-Chongqing Urban Agglomeration, China
Authors: Song Xiaowei , Hao Yongpei , Zhu Xiaodong
Published: November 2019

Vehicular emissions have become one of the important sources of air pollution, and their effective control is essential to protect the environment. The Chengdu-Chongqing Urban Agglomeration (CCUA), a less developed area located in the southwest of China with higher vehicle population and special topographic features, was selected as the research area. The aims of this study were to establish multi-year vehicular emission inventories for ten important air pollutants in this area and to analyze emission control policy scenarios based on the inventories. The results showed that the ten vehicular pollutant emissions had differences during the past decade, and CO2 and NH3 increased markedly between 1999 and 2015. Chengdu and Chongqing were the dominant contributors of vehicular emissions in the CCUA. Eight scenarios based on these inventories were designed and the alternative energy replacement scenario was studied from the life-cycle perspective. Compared with the business as usual scenario, elimination of substandard vehicles scenario is the most effective policy to control NOx, PM2.5, PM10, and CH4 emissions; the radical alternative energy replacement scenario could decrease the vehicular NMVOC, CO2, N2O, and NH3 emissions; the elimination of motorcycles scenario could decrease the vehicular CO emissions; and the raising fuel standards scenario could reduce vehicular SO2 emissions significantly (by 94.81%). The radical integrated scenario (combining all of the reduction control measures mentioned above) would achieve the maximum emission reduction of vehicular pollutants CO, NMVOC, NOx, PM2.5, PM10, CO2, N2O, and NH3 compared with any scenario alone.
Comparisons between Aquaponic and Conventional Hydroponic Crop Yields: A Meta-Analysis
Authors: Ayipio Emmanuel , Wells Daniel E. , McQuilling Alyssa , Wilson Alan E.
Published: November 2019

Aquaponic is a relatively new system of farming, which has received much research attention due to its potential for sustainability. However, there is no consensus on comparability between crop yields obtained from aquaponics (AP) and conventional hydroponics (cHP). Meta-analysis was used to synthesize the literature on studies that compared crop yields of AP and cHP. Factors responsible for differences were also examined through subgroup analysis. A literature search was conducted in five databases with no time restriction in order to capture any publication on AP and cHP crop yield comparisons. The search was, however, limited to journal and conference articles published in English. Study characteristics and outcome measures of food crops were extracted. A natural log response ratio effect size measure was used to transform study outcomes. An unweighted meta-analysis was conducted through bootstrapping to calculate overall effect size and its confidence interval. Between-study heterogeneity (I2) was estimated using a random effects model. Subgroup and meta-regression were used to assess moderators, in an attempt to explain heterogeneity in the effect size. The results showed that although crop yield in AP was lower than conventional cHP, the difference was not statistically significant. However, drawing conclusions on the overall effect size must be done with caution due to the use of unweighted meta-analysis. There were statistically significant effects of aquatic organism, hydroponic system type, and nutrient supplementation used in the studies on crop yield comparisons. Nutrient supplementation, particularly, led to on average higher crop yield in AP relative to cHP. These findings are a vital information source for choosing factors to include in an AP study. These findings also synthesize the current trends in AP crop yields in comparison with cHP.
Understanding Resource Consumption in the Home, Community and Society through Behaviour and Social Practice Theories
Authors: Breadsell Jessica K. , Eon Christine , Morrison Gregory M.
Published: November 2019

The practices and behaviours of individuals influences resource consumption at many scales and are shaped by a multitude of psychological, social, and technical factors. This conceptual paper examines the differences between socio-psychological and social practice theories, building on the Chalk and Cheese debate in the literature. Insight is provided into their potential value in understanding resource consumption studies at different scales: the individual, the home, community, and societal. Each theory has its own qualitative and quantitative methods which allude to different conclusions and recommendations for resource consumption initiatives. We review the debate surrounding the application of both theories, adding our voice to the potential for both theories to be used at different scales and for different time periods, along with comments on the interlocking nature of practices. Design and technology changes can lead to quicker changes in behaviour and practices, whereby socio-psychological theories offer insights into changes in mind frame, values, and social norms.
Assessment of Ecosystem Service Values of Urban Parks in Improving Air Quality: A Case Study of Wuhan, China
Authors: Xie Qijiao , Yue Yang , Sun Qi , Chen Si , Lee Soo-Beom , Kim Seong Wook
Published: November 2019

Assessing ecosystem service values of urban parks can promote understanding of urban green space protection and management. In this study, ecosystem services of air quality purification from 40 sample parks with different areas and land cover compositions were assessed based on literature records and high-resolution images. Six typical ecological benefits of CO2 sequestration, O2 generation, air temperature amelioration, SO2 removal, NOx removal, and dust interception were estimated. The results showed similar proportions of different ecosystem service values to total. The ecological services of CO2 sequestration and O2 generation contributed the majority of total ecosystem service value, with percentages ranging from 69.34% to 73.76% and from 20.52% to 21.71%, respectively. There was very wide variation of ecosystem service values among urban parks. Multivariate regression between ecosystem service values and spatial characteristics of urban parks revealed that park areas of forest and water played a vital role in service value. For a given park, the total service value could be increased by up to 600% if the park was redesigned with consideration of land cover composition. This study provides sound scientific information for urban planners and greening designers to optimize urban park layout.
ASSESSMENT OF THE PRODUCTIVITY AND QUALITY OF VARIETIES AND PROMISING HYBRIDS OF POTATO IN THE CONTEXT OF THE CENTRAL REGION OF THE RUSSIAN FEDERATION
Authors: Shabanov Adam , Kiselev Aleksander , Fedotova Ludmila , Timoshina Nataliya , Knyazeva Elena
Published: November 2019

The article presents the results of the evaluation of promising varieties and hybrids 59 potatoes different ripeness on productivity, biochemical indicators and canteens qualities of tubers. Highlighted the varieties and hybrids with yield levels over 40 t/ha. Identified by their culinary type and intended use of the product.
Ahkâm Âyetlerinin Tefsîrinde Mezhebe Bağlılık (Beydâvî ve Nesefî Örneği)
Authors: BAĞIŞ Mehmet
Published: November 2019

Kur’ân-ı
Kerîm, kulların dünyevî ve uhrevî maslahatlarına yönelik birtakım fıkhî
hükümler içermektedir. Tefsir kaynaklarımıza bakıldığında, Kur’ân’daki
hükümlerle ilgili âyetleri özel olarak ele alan ve fıkhî mezheplerin de
görüşlerine değinmek suretiyle bu gibi âyetlerin tefsirini yapan birçok eser
bulunmaktadır. “Ahkâm Âyetlerinin Tefsirinde Mezhebe Bağlılık (Beydâvî ve Nesefî Örneği)” adlı bu çalışmamızda Beydâvî ve
Nesefî’nin, özellikle fürû-ı fıkıhla ilgili meselelerde ahkâm âyetlerini tefsir
etme metotları üzerinde durulmuş, benzer ve farklı yönleri ortaya konulmaya
çalışılmıştır. İki müfessir de kendi tefsirlerinde bu gibi konuları işlerken,
genellikle müntesibi oldukları mezheplerinin görüşlerini tercih etmişlerdir. Bu
görüşlerini ispatlamak maksadıyla da âyetlerden, hadislerden, icmâdan, kıyastan
ve itibar edilen diğer delillerden yararlanmışlardır. Hem Beydâvî’nin
Envârü’t-Tenzîl’inde hem de Nesefî’nin Medârikü’t- Tenzîl’inde ilk bakışta göze
çarpan bir durum da bu iki tefsir eserinde Arap dili tahlillerine, belâgat
inceliklerine ve ara sıra cahiliye şiirinden istişhatlara yer verilmesidir. İki
tefsir eserinde mevcut olan bu ortak özellik, ahkâm âyetlerinin tefsirinde de
görülmektedir. Çalışmada; Besmele’nin Kur’ân’dan bir âyet olup olmadığı
meselesi, kasr-ı salât, nikâh akdinde velî şartı ve kuru’ meselesi gibi
konular, Beydâvî ve Nesefî tefsirleri ekseninde detaylı olarak incelenmiştir.