bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effects of Pavement Types on Soil Bacterial Communities across Different Depths
Authors: Yu Weiwei , Hu Yinhong , Cui Bowen , Chen Yuanyuan , Wang Xiaoke
Published: May 2019

Pavements have remarkable effects on topsoil micro-organisms, but it remains unclear how subsoil microbial communities respond to pavements. In this study, ash trees (Fraxinus Chinensis) were planted on pervious pavement (PP), impervious pavement (IPP), and non-pavement (NP) plots. After five years, we determined the soil bacterial community composition and diversity by high-throughput sequencing of the bacterial 16S rRNA gene. The results of our field experiment reveal that the presence of pavement changed soil bacterial community composition and decreased the Shannon index, but had no impact on the Chao 1 at the 0–20 cm layer. However, we achieved the opposite result at a depth of 20–80 cm. Furthermore, there was a significant difference in bacterial community composition using the Shannon index and the Chao 1 at the 80–100 cm layer. Soil total carbon (TC), total nitrogen (TN), available phosphorus (AP), NO3−-N, and available potassium (AK) were the main factors that influenced soil bacterial composition and diversity across different pavements. Soil bacterial composition and diversity had no notable difference between PP and IPPs at different soil layers. Our results strongly indicate that pavements have a greater impact on topsoil bacterial communities than do subsoils, and PPs did not provide a better habitat for micro-organisms when compared to IPPs in the short term.
Fish and Meat Intake, Serum Eicosapentaenoic Acid and Docosahexaenoic Acid Levels, and Mortality in Community-Dwelling Japanese Older Persons
Authors: Otsuka Rei , Tange Chikako , Nishita Yukiko , Tomida Makiko , Kato Yuki , Imai Tomoko , Ando Fujiko , Shimokata Hiroshi
Published: May 2019

The associations between meat/fish consumption, docosahexaenoic acid (DHA)/eicosapentaenoic acid (EPA) intakes, and blood DHA/EPA levels, and mortality in Japan were examined as part of the National Institute for Longevity Sciences-Longitudinal Study of Aging: 520 men and 534 women (60–79 years at baseline) were followed from 1997–2017. Nutritional intakes were assessed using a 3-day dietary record and fasting venous blood samples were collected. Serum EPA/DHA concentrations, the EPA/arachidonic acid (ARA) ratio, EPA/DHA intakes, and fish/meat intakes were examined in tertiles as indicator variables, and hazard ratios (HR) were calculated to compare the risk of death across tertiles controlling for sex, age, body mass index, smoking status, alcohol drinking, physical activity, education, employment, and history of diseases. During follow-up (mean 11.7 years), 422 subjects (40.4%) died. The multivariate-adjusted HR for all-cause mortality in subjects in the highest tertile of serum DHA and EPA/ARA ratio was 0.73 (95% confidence intervals (CI): 0.53–0.99) and 0.71 (95% CI: 0.53–0.96) compared with subjects in the lowest tertile, respectively (trend p < 0.05). There were no significant associations between mortality and serum EPA/ARA and DHA/EPA intakes. An increased serum DHA level or EPA/ARA ratio might be recommended for longevity to Japanese community dwellers.
Oral Administration of Porphyromonas gingivalis, a Major Pathogen of Chronic Periodontitis, Promotes Resistance to Paclitaxel in Mouse Xenografts of Oral Squamous Cell Carcinoma
Authors: Song Jae Min , Woo Bok Hee , Lee Ji Hye , Yoon Sanggyeong , Cho Youngseuk , Kim Yong-Deok , Park Hae Ryoun
Published: May 2019

Chemotherapy is not a first-line therapy for oral squamous cell carcinoma (OSCC), which is the most common type of oral cancer, because most OSCC shows resistance to chemotherapeutic reagents. Inflammatory signals are suggested to be associated with chemoresistance as well as carcinogenesis in many different cancers, and thus chronic periodontitis, the most common chronic inflammatory disease of the oral cavity, could modulate responsiveness to chemotherapeutic agents used against oral cancer. This study was performed to define the role of chronic periodontitis in oral cancer progression and to determine the responsiveness of oral cancer to a chemotherapeutic reagent. First, we quantified the tumor growth rate and changes in serum cytokine profiles of mice administered Porphyromonas gingivalis, a major pathogen of chronic periodontitis. Compared with uninfected mice, the mice that were chronically administered P. gingivalis showed increased resistance to paclitaxel and a decreased tumor growth rate. In addition, P. gingivalis-treated mice exhibited higher serum levels of interleukin-6 (IL-6) than uninfected mice. Furthermore, the sensitivity of tumor xenografts to paclitaxel in mice administered P. gingivalis was dramatically increased when the mice were administered ibuprofen, an anti-inflammatory drug which supports the modulatory effect of periodontal pathogen-induced inflammation in chemoresistance.
Plant Proteomic Research 2.0: Trends and Perspectives
Authors: Komatsu Setsuko
Published: May 2019

Plants being sessile in nature are constantly exposed to environmental challenges resulting in substantial yield loss [...]
Fragment-Based Ligand-Protein Contact Statistics: Application to Docking Simulations
Authors: Macari Gabriele , Toti Daniele , Del Moro Carlo , Polticelli Fabio
Published: May 2019

In this work, the information contained in the contacts between fragments of small-molecule ligands and protein residues has been collected and its exploitability has been verified by using the scoring of docking simulations as a test case for bringing about a proof of concept. Contact statistics between small-molecule fragments and binding site residues were collected and analyzed using a dataset composed of 200,000+ binding sites and associated ligands, derived from the database of the LIBRA ligand binding site recognition software, as a starting point. The fragments were generated by applying the decomposition algorithm implemented in BRICS. A simple “potential” based on the contact frequencies was tested against the CASF-2013 benchmark; its performance was then evaluated through the rescoring of docking poses generated for the DUD-E dataset. The results obtained indicate that this approach, its simplicity notwithstanding, yields promising results that are comparable, and in some cases, superior, to those obtained with other, more complex scoring functions.
Mechanism of CK2.3, a Novel Mimetic Peptide of Bone Morphogenetic Protein Receptor Type IA, Mediated Osteogenesis
Authors: Vrathasha Vrathasha , Weidner Hilary , Nohe Anja
Published: May 2019

Background: Osteoporosis is a degenerative skeletal disease with a limited number of treatment options. CK2.3, a novel peptide, may be a potential therapeutic. It induces osteogenesis and bone formation in vitro and in vivo by acting downstream of BMPRIA through releasing CK2 from the receptor. However, the detailed signaling pathways, the time frame of signaling, and genes activated remain largely unknown. Methods: Using a newly developed fluorescent CK2.3 analog, specific inhibitors for the BMP signaling pathways, Western blot, and RT-qPCR, we determined the mechanism of CK2.3 in C2C12 cells. We then confirmed the results in primary BMSCs. Results: Using these methods, we showed that CK2.3 stimulation activated OSX, ALP, and OCN. CK2.3 stimulation induced time dependent release of CK2β from BMPRIA and concurrently CK2.3 colocalized with CK2α. Furthermore, CK2.3 induced BMP signaling depends on ERK1/2 and Smad1/5/8 signaling pathways. Conclusion: CK2.3 is a novel peptide that drives osteogenesis, and we detailed the molecular sequence of events that are triggered from the stimulation of CK2.3 until the induction of mineralization. This knowledge can be applied in the development of future therapeutics for osteoporosis.
MST1 Regulates Neuronal Cell Death via JNK/Casp3 Signaling Pathway in HFD Mouse Brain and HT22 Cells
Authors: Khan Mehtab , Rutten Bart P. F. , Kim Myeong Ok
Published: May 2019

Oxidative stress has been considered as the main mediator in neurodegenerative diseases. A high-fat diet (HFD) and metabolic diseases result in oxidative stress generation, leading to various neurodegenerative diseases via molecular mechanisms that remain largely unknown. Protein kinases play an important role in the homeostasis between cell survival and cell apoptosis. The mammalian sterile 20-like kinase-1 (MST1) protein kinase plays an important role in cellular apoptosis in different organ systems, including the central nervous system. In this study, we evaluated the MST1/c-Jun N-terminal kinase (JNK) dependent oxidative damage mediated cognitive dysfunction in HFD-fed mice and stress-induced hippocampal HT22 (mice hippocampal) cells. Our Western blot and immunofluorescence results indicate that HFD and stress-induced hippocampal HT22 cells activate MST1/JNK/Caspase-3 (Casp-3) signaling, which regulates neuronal cell apoptosis and beta-amyloid-cleaving enzyme (BACE1) expression and leads to impaired cognition. Moreover, MST1 expression inhibition by shRNA significantly reduced JNK/Casp-3 signaling. Our in vivo and in vitro experiments mimicking metabolic stress, such as a high-fat diet, hyperglycemia, and an inflammatory response, determined that MST1 plays a key regulatory role in neuronal cell death and cognition, suggesting that MST1 could be a potential therapeutic target for numerous neurodegenerative diseases.
Molecular and Cellular Mechanisms Underlying Somatostatin-Based Signaling in Two Model Neural Networks, the Retina and the Hippocampus
Authors: Cammalleri Maurizio , Bagnoli Paola , Bigiani Albertino
Published: May 2019

Neural inhibition plays a key role in determining the specific computational tasks of different brain circuitries. This functional “braking” activity is provided by inhibitory interneurons that use different neurochemicals for signaling. One of these substances, somatostatin, is found in several neural networks, raising questions about the significance of its widespread occurrence and usage. Here, we address this issue by analyzing the somatostatinergic system in two regions of the central nervous system: the retina and the hippocampus. By comparing the available information on these structures, we identify common motifs in the action of somatostatin that may explain its involvement in such diverse circuitries. The emerging concept is that somatostatin-based signaling, through conserved molecular and cellular mechanisms, allows neural networks to operate correctly.
Epigenetic Mechanisms in Hepatic Stellate Cell Activation During Liver Fibrosis and Carcinogenesis
Authors: Barcena-Varela Marina , Colyn Leticia , Fernandez-Barrena Maite G.
Published: May 2019

Liver fibrosis is an essential component of chronic liver disease (CLD) and hepatocarcinogenesis. The fibrotic stroma is a consequence of sustained liver damage combined with exacerbated extracellular matrix (ECM) accumulation. In this context, activation of hepatic stellate cells (HSCs) plays a key role in both initiation and perpetuation of fibrogenesis. These cells suffer profound remodeling of gene expression in this process. This review is focused on the epigenetic alterations participating in the transdifferentiation of HSCs from the quiescent to activated state. Recent advances in the field of DNA methylation and post-translational modifications (PTM) of histones (acetylation and methylation) patterns are discussed here, together with altered expression and activity of epigenetic remodelers. We also consider recent advances in translational approaches, including the use of epigenetic marks as biomarkers and the promising antifibrotic properties of epigenetic drugs that are currently being used in patients.
Adjoint-Based Multi-Point and Multi-Objective Optimization of a Turbocharger Radial Turbine
Authors: Mueller Lasse , Verstraete Tom
Published: May 2019

This paper presents a gradient-based design optimization of a turbocharger radial turbine for automotive applications. The aim is to improve both the total-to-static efficiency and the moment of inertia of the turbine wheel. The search for the optimal designs is accomplished by a high-fidelity adjoint-based optimization framework using a fast sequential quadratic programming algorithm. The proposed method is able to produce improved Pareto-optimal designs, which are trade-offs between the two competing objectives, in only a few iterations. This is realized by redesigning the blade shape and the meridional flow channel for the respective target while satisfying imposed aerodynamic constraints. Furthermore, a comparative study with an evolutionary algorithm suggests that the gradient-based method has found the global Pareto front at a computational cost which is about one order of magnitude lower.
Scratching Cu|Au Nanolaminates
Authors: Gola Adrien , Pastewka Lars
Published: May 2019

We used molecular dynamics simulations to study the scratching of Cu|Au nanolaminates of 5 nm layer thickness with a nanoscale indenter of 15 nm radius at normal forces between 0.5 μ N and 2 μ N. Our simulations show that Au layers wear quickly while Cu layers are more resistant to wear. Plowing was accompanied by the roughening of the Cu|Au heterointerface that lead to the folding of the nanolaminate structure at the edge of the wear track. Our explorative simulations hint at the complex deformation processes occurring in nanolaminates under tribological load.
Photocatalytic Microporous Membrane against the Increasing Problem of Water Emerging Pollutants
Authors: Martins Pedro M. , Ribeiro Joana M. , Teixeira Sara , Petrovykh Dmitri. Y. , Cuniberti Gianaurelio , Pereira Luciana , Lanceros-Méndez Senentxu
Published: May 2019

Emerging pollutants are an essential class of recalcitrant contaminants that are not eliminated from water after conventional treatment. Here, a photocatalytic microporous membrane based on polyvinylidene difluoride-co-trifluoroethylene (PVDF−TrFE) with immobilised TiO2 nanoparticles, prepared by solvent casting, was tested against representative emerging pollutants. The structure and composition of these polymeric membranes were characterized by scanning electron microscopy, energy dispersive X-ray spectroscopy, Fourier-transform infrared spectroscopy, porosimetry, and contact angle goniometry. The nanocomposites exhibited a porous structure with a uniform distribution of TiO2 nanoparticles. The addition of TiO2 did not change the structure of the polymeric matrix; however, it increased the wettability of the nanocomposite. The nanocomposites degraded 99% of methylene blue (MB), 95% of ciprofloxacin (CIP), and 48% of ibuprofen (IBP). The microporous nanocomposite exhibited no photocatalytic efficiency loss after four use cycles, corresponding to 20 h of UV irradiation. The reusability of this system confirms the promising nature of polymer nanocomposites as the basis for cost-effective and scalable treatments of emerging pollutants.
Effects of Machining Velocity on Ultra-Fine Grained Al 7075 Alloy Produced by Cryogenic Temperature Large Strain Extrusion Machining
Authors: Yin Xiaolong , Chen Haitao , Deng Wenjun
Published: May 2019

In this study, cryogenic temperature large strain extrusion machining (CT-LSEM) as a novel severe plastic deformation (SPD) method for producing ultra-fine grained (UFG) microstructure is investigated. Solution treated Al 7075 alloy was subjected to CT-LSEM, room temperature (RT) LSEM, as well as CT free machining (CT-FM) with different machining velocities to study their comparative effects. The microstructure evolution and mechanical properties were characterized by differential scanning calorimetry (DSC), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Vickers hardness measurements. It is observed that the hardness of the sample has increased from 105 HV to 169 HV and the chip can be fully extruded under CT-LSEM at the velocity of 5.4 m/min. The chip thickness and hardness decrease with velocity except for RT-LSEM at the machining velocity of 21.6 m/min, under which the precipitation hardening exceeds the softening effect. The constraining tool and processing temperature play a significant role in chip morphology. DSC analysis suggests that the LSEM process can accelerate the aging kinetics of the alloy. A higher dislocation density, which is due to the suppression of dynamic recovery, contributes to the CT-LSEM samples, resulting in greater hardness than the RT-LSEM samples.
An Optimized Network Representation Learning Algorithm Using Multi-Relational Data
Authors: Ye Zhonglin , Zhao Haixing , Zhang Ke , Zhu Yu , Wang Zhaoyang
Published: May 2019

Representation learning aims to encode the relationships of research objects into low-dimensional, compressible, and distributed representation vectors. The purpose of network representation learning is to learn the structural relationships between network vertices. Knowledge representation learning is oriented to model the entities and relationships in knowledge bases. In this paper, we first introduce the idea of knowledge representation learning into network representation learning, namely, we propose a new approach to model the vertex triplet relationships based on DeepWalk without TransE. Consequently, we propose an optimized network representation learning algorithm using multi-relational data, MRNR, which introduces the multi-relational data between vertices into the procedures of network representation learning. Importantly, we adopted a kind of higher order transformation strategy to optimize the learnt network representation vectors. The purpose of MRNR is that multi-relational data (triplets) can effectively guide and constrain the procedures of network representation learning. The experimental results demonstrate that the proposed MRNR can learn the discriminative network representations, which show better performance on network classification, visualization, and case study tasks compared to the proposed baseline algorithms in this paper.
Renieramycin T Induces Lung Cancer Cell Apoptosis by Targeting Mcl-1 Degradation: A New Insight in the Mechanism of Action
Authors: Petsri Korrakod , Chamni Supakarn , Suwanborirux Khanit , Saito Naoki , Chanvorachote Pithi
Published: May 2019

Among malignancies, lung cancer is the major cause of cancer death. Despite the advance in lung cancer therapy, the five-year survival rate is extremely restricted due to therapeutic failure and disease relapse. Targeted therapies selectively inhibiting certain molecules in cancer cells have been accepted as promising ways to control cancer. In lung cancer, evidence has suggested that the myeloid cell leukemia 1 (Mcl-1) protein, an anti-apoptotic member of the Bcl-2 family, is a target for drug action. Herein, we report the Mcl-1 targeting activity of renieramycin T (RT), a marine-derived tetrahydroisoquinoline alkaloid that was isolated from the Thai blue sponge Xestospongia sp. RT was shown to be dominantly toxic to lung cancer cells compared to the normal cells in the lung. The cytotoxicity of this compound toward lung cancer cells was mainly exerted through apoptosis induction. For the mechanism of action, we found that RT mediated activation of p53 protein and caspase-9 and -3 activations. While others Bcl-2 family proteins (Bcl-2, Bak, and Bax) were minimally changed in response to RT, Mcl-1 protein was dramatically diminished. We further performed the cycloheximide experiment and found that the half-life of Mcl-1 was significantly shortened by RT treatment. When MG132, a potent selective proteasome inhibitor, was utilized, it could restore the Mcl-1 level. Furthermore, immunoprecipitation analysis revealed that RT significantly increased the formation of Mcl-1-ubiquitin complex compared to the non-treated control. In conclusion, we report the potential apoptosis induction of RT with a mechanism of action involving the targeting of Mcl-1 for ubiquitin-proteasomal degradation. As Mcl-1 is critical for cancer cell survival and chemotherapeutic failure, this novel information regarding the Mcl-1-targeted compound would be beneficial for the development of efficient anti-cancer strategies or targeted therapies.
The Landscape of Chronic Pain: Broader Perspectives
Authors: Johnson Mark I.
Published: May 2019

Chronic pain is a global health concern. This special issue on matters related to chronic pain aims to draw on research and scholarly discourse from an eclectic mix of areas and perspectives. The purpose of this non-systematic topical review is to précis an assortment of contemporary topics related to chronic pain and its management to nurture debate about research, practice and health care policy. The review discusses the phenomenon of pain, the struggle that patients have trying to legitimize their pain to others, the utility of the acute–chronic dichotomy, and the burden of chronic pain on society. The review describes the introduction of chronic primary pain in the World Health Organization’s International Classification of Disease, 11th Revision and discusses the importance of biopsychosocial approaches to manage pain, the consequences of overprescribing and shifts in service delivery in primary care settings. The second half of the review explores pain perception as a multisensory perceptual inference discussing how contexts, predictions and expectations contribute to the malleability of somatosensations including pain, and how this knowledge can inform the development of therapies and strategies to alleviate pain. Finally, the review explores chronic pain through an evolutionary lens by comparing modern urban lifestyles with genetic heritage that encodes physiology adapted to live in the Paleolithic era. I speculate that modern urban lifestyles may be painogenic in nature, worsening chronic pain in individuals and burdening society at the population level.
Neck Circumference and Its Association with Cardiometabolic Risk Factors in Pediatric Population
Authors: González-Cortés Carlos Adrián , Téran-García Margarita , Luevano-Contreras Claudia , Portales-Pérez Diana Patricia , Vargas-Morales Juan Manuel , Cubillas-Tejeda Ana Cristina , Cossío-Torres Patricia Elizabeth , Aradillas-García Celia
Published: May 2019

Background and objectives: To identify the relationship between neck circumference (NC) and cardiometabolic risk factors in children. Materials and Methods: Children and adolescents 6–18 years old (n = 548) from five counties of San Luis Potosí, México were included. Data was collected for biological markers (glucose and lipid profile) and anthropometric and clinical measurements—weight, height, NC, waist circumference (WC), and blood pressure (BP). Body mass index (BMI) was calculated using Quetelet formula (kg/m2). Descriptive analysis, correlation tests, and receiver operating characteristic (ROC) analysis were performed. Results: NC was highly correlated with BMI and WC in both genders (p <0.0001). The most frequent risk factor was high BMI (38.7%). Sensitivity and specificity analysis of NC and high BMI showed an area under the ROC curve of 0.887. Conclusions: According to our findings, NC is a simple, low-cost, and non-invasive measurement, which has a high association with high BMI and increased WC.
Computational Screening and Analysis of Lung Cancer Related Non-Synonymous Single Nucleotide Polymorphisms on the Human Kirsten Rat Sarcoma Gene
Authors: Wang Qiankun , Mehmood Aamir , Wang Heng , Xu Qin , Xiong Yi , Wei Dong-Qing
Published: May 2019

The human KRAS (Kirsten rat sarcoma) is an oncogene, involved in the regulation of cell growth and division. The mutations in the KRAS gene have the potential to cause normal cells to become cancerous in human lungs. In the present study, we focus on non-synonymous single nucleotide polymorphisms (nsSNPs), which are point mutations in the DNA sequence leading to the amino acid variants in the encoded protein. To begin with, we developed a pipeline to utilize a set of computational tools in order to obtain the most deleterious nsSNPs (Q22K, Q61P, and Q61R) associated with lung cancer in the human KRAS gene. Furthermore, molecular dynamics simulation and structural analyses of the 3D structures of native and mutant proteins confirmed the impact of these nsSNPs on the stability of the protein. Finally, the experimental results demonstrated that the structural stability of the mutant proteins was worse than that of the native protein. This study provides significant guidance for narrowing down the number of KRAS mutations to be screened as potential diagnostic biomarkers and to better understand the structural and functional mechanisms of the KRAS protein.
Trimethyl Chitosan/Siloxane-Hybrid Coated Fe3O4 Nanoparticles for the Uptake of Sulfamethoxazole from Water
Authors: Soares Sofia F. , Fernandes Tiago , Trindade Tito , Daniel-da-Silva Ana L.
Published: May 2019

The presence of several organic contaminants in the environment and aquatic compartments has been a matter of great concern in the recent years. To tackle this problem, new sustainable and cost-effective technologies are needed. Herein we describe magnetic biosorbents prepared from trimethyl chitosan (TMC), which is a quaternary chitosan scarcely studied for environmental applications. Core@shell particles comprising a core of magnetite (Fe3O4) coated with TMC/siloxane hybrid shells (Fe3O4@SiO2/SiTMC) were successfully prepared using a simple one-step coating procedure. Adsorption tests were conducted to investigate the potential of the coated particles for the magnetically assisted removal of the antibiotic sulfamethoxazole (SMX) from aqueous solutions. It was found that TMC-based particles provide higher SMX adsorption capacity than the counterparts prepared using pristine chitosan. Therefore, the type of chemical modification introduced in the chitosan type precursors used in the surface coatings has a dominant effect on the sorption efficiency of the respective final magnetic nanosorbents.
Infections with Carbapenem-Resistant Gram-Negative Bacteria are a Serious Problem Among Critically Ill Children: A Single-Centre Retrospective Study
Authors: Aygun Fatih , Aygun Fatma Deniz , Varol Fatih , Durak Cansu , Çokuğraş Haluk , Camcıoğlu Yıldız , Çam Halit
Published: May 2019

Children in paediatric intensive care units (PICUs) are vulnerable to infections because invasive devices are frequently used during their admission. We aimed to determine the prevalence, associated factors, and prognosis of infections in our PICU. This retrospective study evaluated culture results from 477 paediatric patients who were treated in the PICU between January 2014 and March 2019. Ninety patients (18.9%) had bacterial infections, with gram-negative bacteria being the predominant infectious agents. Culture-positive patients were younger than culture-negative patients, and age was related to mortality and various clinical factors. Culture-positive bacterial infections in the PICU were associated with increased use of invasive mechanical ventilation (odds ratio(OR); 2.254), red blood cell (RBC) transfusions (OR:2.624), and inotropic drugs (OR:2.262). Carbapenem resistance was found in approximately one-third of gram-negative bacteria, and was most common in tracheal aspirate specimens and cases involving Klebsiella spp. Total parenteral nutrition was a significant risk factor (OR:5.870). Positive blood culture results were associated with poorer patient survival than other culture results. These findings indicate that infections, especially those involving carbapenem-resistant bacteria, are an important issue when treating critically ill children.
Highly Porous Graphitic Activated Carbons from Lignite via Microwave Pretreatment and Iron-Catalyzed Graphitization at Low-Temperature for Supercapacitor Electrode Materials
Authors: Liu Dongdong , Zhao Xiaoman , Su Rui , Hao Zhengkai , Jia Boyin , Li Song , Dong Liangjie
Published: May 2019

At present, the preparation of highly porous graphitic activated carbons (HPGACs) using the usual physical and chemical activation methods has met a bottleneck. In this study, HPGACs are directly synthesized from lignite at 900 °C. The whole process is completed by a microwave pretreatment, a graphitization conversion of the carbon framework at a low temperature using a small amount of FeCl3 (10–30 wt%), and a subsequent physical activation using CO2. Consequently, the dispersed and mobile iron species, in the absence of oxygen functional groups (removed during the microwave pretreatment), can greatly promote catalytic graphitization during pyrolysis, and, as an activating catalyst, can further facilitate the porosity development during activation. The as-obtained AC-2FeHLH-5-41.4(H) presents a low defect density, high purity, and specific surface area of 1852.43 m2 g−1, which is far greater than the AC-HLH-5-55.6(H) obtained solely by physical activation. AC-2FeHLH-5-41.4(H) as a supercapacitor electrode presents an excellent performance in the further electrochemical measurements. Such a convenient and practical method with low cost proves a scalable method to prepare HPGACs from a wide range of coal/biomass materials for industrial scale-up and applications.
High-Speed Ship Detection in SAR Images Based on a Grid Convolutional Neural Network
Authors: Zhang Tianwen , Zhang Xiaoling
Published: May 2019

As an active microwave sensor, synthetic aperture radar (SAR) has the characteristic of all-day and all-weather earth observation, which has become one of the most important means for high-resolution earth observation and global resource management. Ship detection in SAR images is also playing an increasingly important role in ocean observation and disaster relief. Nowadays, both traditional feature extraction methods and deep learning (DL) methods almost focus on improving ship detection accuracy, and the detection speed is neglected. However, the speed of SAR ship detection is extraordinarily significant, especially in real-time maritime rescue and emergency military decision-making. In order to solve this problem, this paper proposes a novel approach for high-speed ship detection in SAR images based on a grid convolutional neural network (G-CNN). This method improves the detection speed by meshing the input image, inspired by the basic thought of you only look once (YOLO), and using depthwise separable convolution. G-CNN is a brand new network structure proposed by us and it is mainly composed of a backbone convolutional neural network (B-CNN) and a detection convolutional neural network (D-CNN). First, SAR images to be detected are divided into grid cells and each grid cell is responsible for detection of specific ships. Then, the whole image is input into B-CNN to extract features. Finally, ship detection is completed in D-CNN under three scales. We experimented on an open SAR Ship Detection Dataset (SSDD) used by many other scholars and then validated the migration ability of G-CNN on two SAR images from RadarSat-1 and Gaofen-3. The experimental results show that the detection speed of our proposed method is faster than the existing other methods, such as faster-regions convolutional neural network (Faster R-CNN), single shot multi-box detector (SSD), and YOLO, under the same hardware environment with NVIDIA GTX1080 graphics processing unit (GPU) and the detection accuracy is kept within an acceptable range. Our proposed G-CNN ship detection system has great application values in real-time maritime disaster rescue and emergency military strategy formulation.
Controlling the Flight of a Drone and Its Camera for 3D Reconstruction of Large Objects
Authors: Mentasti Simone , Pedersini Federico
Published: May 2019

In this paper we present a simple stand-alone system performing the autonomous acquisition of multiple pictures all around large objects, i.e., objects that are too big to be photographed from any side just with a camera held by hand. In this approach, a camera carried by a drone (an off-the-shelf quadcopter) is employed to carry out the acquisition of an image sequence representing a valid dataset for the 3D reconstruction of the captured scene. Both the drone flight and the choice of the viewpoints for shooting a picture are automatically controlled by the developed application, which runs on a tablet wirelessly connected to the drone, and controls the entire process in real time. The system and the acquisition workflow have been conceived with the aim to keep the user intervention minimal and as simple as possible, requiring no particular skill to the user. The system has been experimentally tested on several subjects of different shapes and sizes, showing the ability to follow the requested trajectory with good robustness against any flight perturbations. The collected images are provided to a scene reconstruction software, which generates a 3D model of the acquired subject. The quality of the obtained reconstructions, in terms of accuracy and richness of details, have proved the reliability and efficacy of the proposed system.
A Broadband Mid-Infrared Trace Gas Sensor Using Supercontinuum Light Source: Applications for Real-Time Quality Control for Fruit Storage
Authors: Eslami Jahromi Khalil , Pan Qing , Khodabakhsh Amir , Sikkens Cor , Assman Paul , Cristescu Simona M. , Moselund Peter M. , Janssens Maxime , Verlinden Bert E. , Harren Frans J. M.
Published: May 2019

We present a fully integrated and transportable multi-species trace gas sensor based on a mid-infrared (MIR) supercontinuum light source. The high brightness (surpassing synchrotron) and ultra-broad spectral bandwidth (2–4 μm) of this light source allows simultaneous detection of multiple broadband absorbing gas species. High sensitivity in the sub-ppmv level has been achieved by utilizing an astigmatic multipass cell. A grating-based spectrometer at a scanning rate of 20 Hz is developed employing a balanced detection scheme. A multi-component global fitting algorithm is implemented into a central LabVIEW program to perform real-time data analysis. The obtained concentration values are validated by the standard gas chromatography mass spectrometry (GC-MS) method. Field application of the sensor for quality control of stored fruits at a small scale is demonstrated, involving the detection of ethylene, ethanol, ethyl acetate, acetaldehyde, methanol, acetone, and water simultaneously. The sensor also shows promising potentials for other applications, such as environmental monitoring and biomedical research.
Fluid Sensing Using Quartz Tuning Forks—Measurement Technology and Applications
Authors: Voglhuber-Brunnmaier Thomas , Niedermayer Alexander O. , Feichtinger Friedrich , Jakoby Bernhard
Published: May 2019

We provide an overview of recent achievements using quartz tuning forks for sensing liquid viscosity and density. The benefits of using quartz crystal tuning forks (QTFs) over other sensors are discussed on the basis of physical arguments and issues arising in real world applications. The path to highly accurate and robust measurement systems is described and a recently devised system considering these findings is presented. The performance of the system is analyzed for applications such as the mixing ratio measurement of fuels, diesel-soot contamination for engine oil condition monitoring, and particle size characterization in suspensions. It is concluded that using properly designed systems enables a variety of applications in industry and research.
A Robust Diffusion Minimum Kernel Risk-Sensitive Loss Algorithm over Multitask Sensor Networks
Authors: Li Xinyu , Shi Qing , Xiao Shuangyi , Duan Shukai , Chen Feng
Published: May 2019

Distributed estimation over sensor networks has attracted much attention due to its various applications. The mean-square error (MSE) criterion is one of the most popular cost functions used in distributed estimation, which achieves its optimality only under Gaussian noise. However, impulsive noise also widely exists in real-world sensor networks. Thus, the distributed estimation algorithm based on the minimum kernel risk-sensitive loss (MKRSL) criterion is proposed in this paper to deal with non-Gaussian noise, particularly for impulsive noise. Furthermore, multiple tasks estimation problems in sensor networks are considered. Differing from a conventional single-task, the unknown parameters (tasks) can be different for different nodes in the multitask problem. Another important issue we focus on is the impact of the task similarity among nodes on multitask estimation performance. Besides, the performance of mean and mean square are analyzed theoretically. Simulation results verify a superior performance of the proposed algorithm compared with other related algorithms.
Entry Aggregation and Early Match Using Hidden Markov Model of Flow Table in SDN
Authors: Wang Cheng , Youn Hee Yong
Published: May 2019

The usage of multiple flow tables (MFT) has significantly extended the flexibility and applicability of software-defined networking (SDN). However, the size of MFT is usually limited due to the use of expensive ternary content addressable memory (TCAM). Moreover, the pipeline mechanism of MFT causes long flow processing time. In this paper a novel approach called Agg-ExTable is proposed to efficiently manage the MFT. Here the flow entries in MFT are periodically aggregated by applying pruning and the Quine–Mccluskey algorithm. Utilizing the memory space saved by the aggregation, a front-end ExTable is constructed, keeping popular flow entries for early match. Popular entries are decided by the Hidden Markov model based on the match frequency and match probability. Computer simulation reveals that the proposed scheme is able to save about 45% of space of MFT, and efficiently decrease the flow processing time compared to the existing schemes.
Residual Motion Error Correction with Backprojection Multisquint Algorithm for Airborne Synthetic Aperture Radar Interferometry
Authors: Xie Pengfei , Zhang Man , Zhang Lei , Wang Guanyong
Published: May 2019

For airborne interferometric synthetic aperture radar (InSAR) data processing, it is essential to achieve precise motion compensation to obtain high-quality digital elevation models (DEMs). In this paper, a novel InSAR motion compensation method is developed, which combines the backprojection (BP) focusing and the multisquint (MSQ) technique. The algorithm is two-fold. For SAR image focusing, BP algorithm is applied to fully use the navigation information. Additionally, an explicit mathematical expression of residual motion error (RME) in the BP image is derived, which paves a way to integrating the MSQ algorithm in the azimuth spatial wavenumber domain for a refined RME correction. It is revealed that the proposed backprojection multisquint (BP-MSQ) algorithm exploits the motion error correction advantages of BP and MSQ simultaneously, which leads to significant improvements of InSAR image quality. Simulation and real data experiments are employed to illustrate the effectiveness of the proposed algorithm.
Novel Unconventional-Active-Jamming Recognition Method for Wideband Radars Based on Visibility Graphs
Authors: Du Congju , Tang Bin
Published: May 2019

Radar unconventional active jamming, including unconventional deceptive jamming and barrage jamming, poses a serious threat to wideband radars. This paper proposes an unconventional-active-jamming recognition method for wideband radar. In this method, the visibility algorithm of converting the radar time series into graphs, called visibility graphs, is first given. Then, the visibility graph of the linear-frequency-modulation (LFM) signal is proved to be a regular graph, and the rationality of extracting features on visibility graphs is theoretically explained. Therefore, four features on visibility graphs, average degree, average clustering coefficient, Newman assortativity coefficient, and normalized network-structure entropy, are extracted from visibility graphs. Finally, a random-forests (RF) classifier is chosen for unconventional-active-jamming recognition. Experiment results show that recognition probability was over 90% when the jamming-to-noise ratio (JNR) was above 0 dB.
An Improved Roadside Parking Space Occupancy Detection Method Based on Magnetic Sensors and Wireless Signal Strength
Authors: Lou Liangliang , Zhang Jinyi , Xiong Yong , Jin Yanliang
Published: May 2019

Smart Parking Management Systems (SPMSs) have become a research hotspot in recent years. Many researchers are focused on vehicle detection technology for SPMS which is based on magnetic sensors. Magnetism-based wireless vehicle detectors (WVDs) integrate low-power wireless communication technology, which improves the convenience of construction and maintenance. However, the magnetic signals are not only susceptible to the adjacent vehicles, but also affected by the magnetic signal dead zone of high-chassis vehicles, resulting in a decrease in vehicle detection accuracy. In order to improve the vehicle detection accuracy of the magnetism-based WVDs, the paper introduces an RF-based vehicle detection method based on the characteristics analysis of received signal strengths (RSSs) generated by the wireless transceivers. Since wireless transceivers consume more energy than magnetic sensors, the proposed RF-based method is only activated to extract the data characteristics of RSSs to further judge the states of vehicles when the data feature of magnetic signals is not sufficient to provide accurate judgment on parking space status. The proposed method was evaluated in an actual roadside parking lot and experimental results show that when the sampling rate of magnetic sensor is 1 Hz, the vehicle detection accuracy is up to 99.62%. Moreover, compared with machine-learning-based vehicle detection method, the experimental results show that our method has achieved a good compromise between detection accuracy and power consumption.
Collaborative Concession in Food Movement Networks: The Uneven Relations of Resource Mobilization
Authors: Sbicca Joshua , Luxton India , Hale James , Roeser Kassandra
Published: May 2019

How do food movements prioritize and work to accomplish their varied and often conflicting social change goals at the city scale? Our study investigates the Denver food movement with a mixed methods social network analysis to understand how organizations navigate differences in power and influence vis-à-vis resource exchange. We refer to this uneven process with the analytical concept of “collaborative concession”. The strategic resource mobilization of money, land, and labor operates through certain collaborative niches, which constitute the priorities of the movement. Among these are poverty alleviation and local food production, which are facilitated by powerful development, education, and health organizations. Therefore, food movement networks do not offer organizations equal opportunity to carry out their priorities. Concession suggests that organizations need to lose something to gain something. Paradoxically, collaboration can produce a resource gain. Our findings provide new insights into the uneven process by which food movement organizations—and city-wide food movements overall—mobilize.
Combined Effects of the Surface Urban Heat Island with Landscape Composition and Configuration Based on Remote Sensing: A Case Study of Shanghai, China
Authors: Du Hongyu , Ai Jinquan , Cai Yongli , Jiang Hong , Liu Pudong
Published: May 2019

Rapid urbanization leads to changes in surface coverage and landscape patterns. This results in urban heat island (UHI) effects and a series of negative ecological consequences. Considering this concern and taking Shanghai as an example, this paper concentrates on the effects of surface coverage and landscape patterns on urban land surface temperature (LST). The research is based on quantitative retrieval of remote sensing data with consideration of methods in multiple disciplines, including landscape ecology, geographic information systems, and statistical analysis. It concludes that, over time, the thermal environment of Shanghai is becoming critical. The average LST ranking of different surface coverage is as follows: Construction land (CL) > bare land (BL) > green land (GL) > agricultural land (AL) > water body (WB). LST varies significantly with the type of surface coverage. CL contributes the most to the UHI, while WB and GL have obvious mitigation effects on the UHI. The large area, low degree of landscape fragmentation, and complex outlines lead to low LST rankings for GL, WB, and AL and a high LST ranking for CL. The conclusions indicate that CL should be broken down by GL and WB into discrete pieces to effectively mitigate UHI effects. The research reveals UHI features and changes in Shanghai over the years and provides practical advice that can be used by urban planning authorities to mitigate UHI.
Sustainable Intensification with Cereal-Legume Intercropping in Eastern and Southern Africa
Authors: Kiwia Abednego , Kimani David , Harawa Rebbie , Jama Bashir , Sileshi Gudeta W.
Published: May 2019

Much research has been conducted on cereal-legume intercropping as a sustainable intensification (SI) practice in Eastern and Southern Africa (ESA). However, the role of inorganic fertilizers in sustainably intensifying intercropping systems has not been systematically analyzed. Therefore, the objective of the present analysis was to assess the role of inorganic fertilizer use in cereal-pigeonpea (Cajanus cajan) intercropping in terms of SI indicators, namely, yield, production risks, input use efficiency, and economic returns. The data used for this analysis were gathered from over 900 on-farm trials across Kenya, Tanzania, and Mozambique. All SI indicators assessed showed that intercropping combined with application of small amounts of inorganic fertilizers is superior to unfertilized intercrops. Fertilizer application in the intercropping system improved cereal yields by 71–282% and pigeon pea yields by 32–449%, increased benefit–cost ratios by 10–40%, and reduced variability in cereal yields by 40–56% and pigeonpea yields by 5–52% compared with unfertilized intercrops. Improved yields and reduced variability imply lowering farmers’ risk exposure and improved credit rating, which could enhance access to farm inputs. We conclude that the strategic application of small amounts of inorganic fertilizers is essential for the productivity and economic sustainability of cereal-pigeonpea intercropping under smallholder farming in ESA.
Application of the Bipolar Neutrosophic Hamacher Averaging Aggregation Operators to Group Decision Making: An Illustrative Example
Authors: Jamil Muhammad , Abdullah Saleem , Yaqub Khan Muhammad , Smarandache Florentin , Ghani Fazal
Published: May 2019

The present study aims to introduce the notion of bipolar neutrosophic Hamacher aggregation operators and to also provide its application in real life. Then neutrosophic set (NS) can elaborate the incomplete, inconsistent, and indeterminate information, Hamacher aggregation operators, and extended Einstein aggregation operators to the arithmetic and geometric aggregation operators. First, we give the fundamental definition and operations of the neutrosophic set and the bipolar neutrosophic set. Our main focus is on the Hamacher aggregation operators of bipolar neutrosophic, namely, bipolar neutrosophic Hamacher weighted averaging (BNHWA), bipolar neutrosophic Hamacher ordered weighted averaging (BNHOWA), and bipolar neutrosophic Hamacher hybrid averaging (BNHHA) along with their desirable properties. The prime gain of utilizing the suggested methods is that these operators progressively provide total perspective on the issue necessary for the decision makers. These tools provide generalized, increasingly exact, and precise outcomes when compared to the current methods. Finally, as an application, we propose new methods for the multi-criteria group decision-making issues by using the various kinds of bipolar neutrosophic operators with a numerical model. This demonstrates the usefulness and practicality of this proposed approach in real life.