bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplemental Retinal Carotenoids Enhance Memory in Healthy Individuals with Low Levels of Macular Pigment in A Randomized, Double-Blind, Placebo-Controlled Clinical Trial
Authors: Power Rebecca , Coen Robert F. , Beatty Stephen , Mulcahy Riona , Moran Rachel , Stack Jim , Howard Alan N. , Nolan John M.
Published: January 2018

Background:

There is a biologically plausible rationale whereby the dietary carotenoids lutein (L), zeaxanthin (Z), and meso-zeaxanthin (MZ), which are collectively referred to as macular pigment (MP) in the central retina (macula), support the maintenance of cognition via their antioxidant and anti-inflammatory properties.

Objective:

To investigate the impact of supplemental L, Z, and MZ on memory, executive function, and verbal fluency among healthy individuals with low MP levels.

Methods:

In this double-blind, placebo-controlled, randomized clinical trial, subjects ( n = 91; mean±SD age = 45.42±12.40; % male = 51.6) consumed a daily formulation of 10 mg L, 10 mg MZ, and 2 mg Z ( n = 45) or placebo ( n = 46) for 12 months. Cognitive domains assessed included verbal and visual learning, immediate and delayed memory, executive function, and verbal fluency. MP and serum carotenoid concentrations of L, Z, and MZ were also measured.

Results:

Following 12-month supplementation, individuals in the active group exhibited statistically significant improvements in memory when compared to the placebo group (paired associated learning [PAL] memory score [rANOVA, p = 0.009]; PAL errors [rANOVA, p = 0.017]). Furthermore, the observed reduction in the number of errors made in the PAL task among those in the intervention group was positively and significantly related to observed increases in MP volume ( p = 0.005) and observed increases in serum concentrations of L ( p = 0.009).

Conclusion:

This randomized, double-blind, placebo-controlled clinical trial demonstrates a memory-enhancing effect of daily supplementation with L, Z, and MZ in healthy subjects with low MP at baseline. The implications of these findings for intellectual performance throughout life, and for risk of cognitive decline in later life, warrant further study.
Apparent Cognitive Decline as Revealed by an Executive Function Test within a Cohort of Elderly Individuals Self-Reporting Normal Cognitive Performance
Authors: Shea Thomas B. , Remington Ruth
Published: January 2018

Alzheimer’s disease (AD) can be preceded by subtle memory decline that can last a decade or more before progressing to what would be diagnosed as the mild cognitive impairment stage. During this early stage of decline, individuals and even their caregivers can fail to perceive any serious difficulty or need to consult a physician. Herein, we present evidence in support of these concerns, and demonstrate how this can interfere not only with clinical trials of AD but also those involving cognitive performance of elderly individuals without intentional reference to AD.
Fuzzy-Bayesian-network-based Safety Risk Analysis in Railway Passenger Transport
Authors: Sun Dongye , Jia Yuanhua , Yang Yang , Li Huanan , Zhao Liping
Published: January 2018

This study presents a fuzzy Bayesian network (FBN) method to analyze the influence on the safety risk of railway passenger transport applying different risk control strategies. Based on the fuzzy probability of the basic event determined by the expert group decision method, the proposed FBN method can reasonably predict the probability of railway passenger safety risk. It is also proven that control the risk in the safety management of railway passenger transport will be the most effective way to reduce the risk probability of the railway passenger transport safety.
Novell Application of CFD for Rocket Engine Nozzle Optimization
Authors: Jéger Csaba , Veress Árpád
Published: January 2018

Numerical analyses, validation and geometric optimization of a converging-diverging nozzle flows has been established in the present work. The optimal nozzle contour for a given nozzle pressure ratio and length yields the largest obtainable thrust for the conditions and thus minimises the losses. Application of such methods reduces the entry cost to the market, promote innovation and accelerate the development processes. A parametric geometry, numerical mesh and simulation model is constructed first to solve the problem. The simulation model is then validated by using experimental and computational data. The optimizations are completed for conical and bell shaped nozzles also to find the suitable nozzle geometries for the given conditions. Results are in good agreement with existing nozzle flow fields. The optimization loop described and implemented here can be used in the all similar situations and can be the basis of an improved nozzle geometry optimization procedure by means of using a multiphysics system to generate the final model with reduced number sampling phases.
Chemical and Biological Investigations of Cerbera odollam Gaertn
Authors: Rahman Monica Sharfin , Faisal Adnan , Hasan Choudhury Mahmood , Ahsan Monira , Masud Mohammad Mehedi
Published: January 2018

The present article describes the isolation and characterization of secondary metabolites from the leaves of Cerbera odollam as well as bioactivities of the crude methanolic extract and its petroleum ether (PE), carbon tetrachloride (CTC), chloroform (CF) and aqueous (AQ) soluble fractions. In this investigation, successive chromatographic separation and purification yielded β-amyrin (CO-01), lupeol (CO-02), β-sitostenone (CO-03) and triticusterol (CO-04). The study also indicated the antioxidant, cytotoxic, antimicrobial, membrane stabilizing activities and poor thrombolytic activities. Thus, the present study endeavors to provide scientific basis to establish Cerbera odollam as a potential medicinal plant.Dhaka Univ. J. Pharm. Sci. 16(2): 179-186, 2017 (December)
Bioactivities of Digera muricata (L.) Mart. Available in Bangladesh
Authors: Miah Mohammad Mohasin , Das Pritom , Mridha Shakil Ahammad , Kuddus Md Ruhul , Rashid Mohammad A
Published: January 2018

Abstract not availableDhaka Univ. J. Pharm. Sci. 16(2): 251-254, 2017 (December)
Bacterial Proteases as Thrombolytics and Fibrinolytics
Authors: Akhtar Taqiyah , Hoq Md Mozammel , Mazid Md Abdul
Published: January 2018

Proteases regulate important pathophysiological processes in human body such as homeostasis, blood   coagulation, fibrinolysis, tumor progression, etc. These biological effects of proteases largely attribute to their   applicability as therapeutic agents. Imbalance in blood coagulation and fibrinolysis, two important physiological   processes in human body, leads to thrombosis, a leading cause of cardiovascular complications including myocardial   infarction, stroke, etc. The enzymes used to dissolve thrombus (blood clot) are known as thrombolytic agents and   among them, the enzymes involving hydrolysis of fibrin called fibrinolytic agents. Thrombolytic agents can be   classified according to generation, mechanism of action, source and active site of the enzymes. Among the   commercially available thrombolytic agents, uPA and tPA are generally safe but are very expensive. On the other   hand, the bacterial streptokinase is a relatively cheap thrombolytic agent but causes undesirable side effects such as   bleeding complications. For this reason, worldwide research for potent thrombolytic agents to prevent and treat   cardiovascular diseases have been continuing. Microbes are considered as a potential source of as well as safe vectors   for expressing thrombolytic and fibrinolytic enzymes. Bacilli are one of the largest groups for this purpose. They   have been collected from different traditional fermented foods or have been produced by solid state fermentation   using appropriate nutrient substrates including different agro-industrial wastes such as rice straw, molasses, soybean   curd residues, etc. This review focuses on different bacterial proteases reported to have potential thrombolytic and   fibrinolytic activities.Dhaka Univ. J. Pharm. Sci. 16(2): 255-269, 2017 (December)
An Ensemble Classifier with Random Projection for Predicting Protein–Protein Interactions Using Sequence and Evolutionary Information
Authors: Song Xiao-Yu , Chen Zhan-Heng , Sun Xiang-Yang , You Zhu-Hong , Li Li-Ping , Zhao Yang
Published: January 2018

Identifying protein–protein interactions (PPIs) is crucial to comprehend various biological processes in cells. Although high-throughput techniques generate many PPI data for various species, they are only a petty minority of the entire PPI network. Furthermore, these approaches are costly and time-consuming and have a high error rate. Therefore, it is necessary to design computational methods for efficiently detecting PPIs. In this study, a random projection ensemble classifier (RPEC) was explored to identify novel PPIs using evolutionary information contained in protein amino acid sequences. The evolutionary information was obtained from a position-specific scoring matrix (PSSM) generated from PSI-BLAST. A novel feature fusion scheme was then developed by combining discrete cosine transform (DCT), fast Fourier transform (FFT), and singular value decomposition (SVD). Finally, via the random projection ensemble classifier, the performance of the presented approach was evaluated on Yeast, Human, and H. pylori PPI datasets using 5-fold cross-validation. Our approach achieved high prediction accuracies of 95.64%, 96.59%, and 87.62%, respectively, effectively outperforming other existing methods. Generally speaking, our approach is quite promising and supplies a practical and effective method for predicting novel PPIs.
Evaluation of the Simultaneous Production of Xylitol and Ethanol from Sisal Fiber
Authors: Damião Xavier Franklin , Santos Bezerra Gustavo , Florentino Melo Santos Sharline , Sousa Conrado Oliveira Líbia , Luiz Honorato Silva Flávio , Joice Oliveira Silva Aleir , Maria Conceição Marta
Published: January 2018

Recent years have seen an increase in the use of lignocellulosic materials in the development of bioproducts. Because sisal fiber is a low cost raw material and is readily available, this work aimed to evaluate its hemicellulose fraction for the simultaneous production of xylitol and ethanol. The sisal fiber presented a higher hemicellulose content than other frequently-employed biomasses, such as sugarcane bagasse. A pretreatment with dilute acid and low temperatures was conducted in order to obtain the hemicellulose fraction. The highest xylose contents (0.132 g·g−1 of sisal fiber) were obtained at 120 °C with 2.5% (v/v) of sulfuric acid. The yeast Candida tropicalis CCT 1516 was used in the fermentation. In the sisal fiber hemicellulose hydrolysate, the maximum production of xylitol (0.32 g·g−1) and of ethanol (0.27 g·g−1) was achieved in 60 h. Thus, sisal fiber presents as a potential biomass for the production of ethanol and xylitol, creating value with the use of hemicellulosic liquor without detoxification and without the additional steps of alkaline pretreatment.
Targeting Pancreatic Cancer Cell Plasticity: The Latest in Therapeutics
Authors: Smigiel Jacob , Parameswaran Neetha , Jackson Mark
Published: January 2018

Mortality remains alarmingly high for patients diagnosed with pancreatic ductal adenocarcinoma (PDAC), with 93% succumbing to the disease within five years. The vast majority of PDAC cases are driven by activating mutations in the proto-oncogene KRAS, which results in constitutive proliferation and survival signaling. As efforts to target RAS and its downstream effectors continue, parallel research aimed at identifying novel targets is also needed in order to improve therapeutic options and efficacy. Recent studies demonstrate that self-renewing cancer stem cells (CSCs) contribute to metastatic dissemination and therapy failure, the causes of mortality from PDAC. Here, we discuss current challenges in PDAC therapeutics, highlight the contribution of mesenchymal/CSC plasticity to PDAC pathogenesis, and propose that targeting the drivers of plasticity will prove beneficial. Increasingly, intrinsic oncogenic and extrinsic pro-growth/survival signaling emanating from the tumor microenvironment (TME) are being implicated in the de novo generation of CSC and regulation of tumor cell plasticity. An improved understanding of key regulators of PDAC plasticity is providing new potential avenues for targeting the properties associated with CSC (including enhanced invasion and migration, metastatic outgrowth, and resistance to therapy). Finally, we describe the growing field of therapeutics directed at cancer stem cells and cancer cell plasticity in order to improve the lives of patients with PDAC.
Stacked Wire Mesh Monoliths for the Simultaneous Abatement of VOCs and Diesel Soot
Authors: Godoy María , Banús Ezequiel , Sanz Oihane , Montes Mario , Miró Eduardo , Milt Viviana
Published: January 2018

Structured catalysts based on Pt,CeO2 deposited on stainless steel wire meshes were developed to build catalytic cartridges for the treatment of diesel exhaust gases. The cartridges were tested for the simultaneous combustion of volatile organic compounds (VOCs) and soot. To this end, n-hexane, acetyl acetate, and toluene were selected as probe molecules. Each of them were loaded together with real soot into the cartridges showing that while VOCs abatement takes place between 200 °C and 350 °C, soot combustion occurs in the 300–500 °C temperature range with an average maximum combustion rate at 420 °C. The catalytic cartridges were characterized by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and Brunauer-Emmett-Teller (BET) techniques. The mechanical stability of the coatings was confirmed by the ultrasound method. Air permeability of the cartridges prepared with different mesh sizes was also measured and the results were correlated using the Payri equation.
Synthesis of Three-Dimensionally Ordered Macroporous NiCe Catalysts for Oxidative Dehydrogenation of Propane to Propene
Authors: Fang Kegong , Liu Lulu , Zhang Mingwei , Zhao Lu , Zhou Juan , Li Wenbin , Mu Xiaoliang , Yang Cheng
Published: January 2018

Three-dimensionally ordered macroporous (3DOM) NiCe catalysts with different Ni/Ce molar ratio were fabricated using the colloidal crystal templating method. The physic-chemical properties of the samples were characterized by various techniques, including N2 adsorption–desorption, X-ray diffraction (XRD), transmission electron microscopy (TEM), Raman, and H2-temperature-programmed reduction (TPR) characterizations. The results revealed that the 3DOM NiCe samples preserved the three-dimensionally ordered macroporous channels with interlinked micro- or mesoporous structure and highly dispersed nickel oxide species in the framework upon different amount of nickel incorporation. In the evaluation of the oxidative dehydrogenation (ODH) of propane, the 3DOM NiCe catalysts exhibited higher selectivity and yield to propene than the amorphous NiCe catalyst. An optimum yield of propene of 11.9% with the 30.3% propane conversion at 375 °C was obtained over the 3DOM 2NiCe catalyst. Combining XRD, TPR, and Raman analysis, it could be found that the nickel incorporation in CeO2 lattice produced a high concentration of oxygen vacancies that were the active sites for the oxidative dehydrogenation of propane. Besides this, the 3DOM structure promoted the rapid diffusion of the reactants and products—favorable for the generation of propene in the ODH of propane.
Neurological Respiratory Failure
Authors: Rudrappa Mohan , Kokatnur Laxmi , Chernyshev Oleg
Published: January 2018

West Nile virus infection in humans is mostly asymptomatic. Less than 1% of neuro-invasive cases show a fatality rate of around 10%. Acute flaccid paralysis of respiratory muscles leading to respiratory failure is the most common cause of death. Although the peripheral nervous system can be involved, isolated phrenic nerve palsy leading to respiratory failure is rare and described in only two cases in the English literature. We present another case of neurological respiratory failure due to West Nile virus-induced phrenic nerve palsy. Our case reiterates the rare, but lethal, consequences of West Nile virus infection, and the increase of its awareness among physicians.
Laboratory Investigation of Flow Paths in 3D Self-Affine Fractures with Lattice Boltzmann Simulations
Authors: Li Jiawei , Cherubini Claudia , Galindo Torres Sergio , Li Zi , Pastore Nicola , Li Ling
Published: January 2018

In this study, laboratory experiments and simulations have been conducted to investigate single water phase flow through self-affine rough fractures. It is the first time that 3D printing technology is proposed for the application of generating self-affine rough fractures. The experimental setup was designed to measure the water volume by dividing the discharging surface into five sections with equal distances under constant injection flow rates. Water flow through self-affine rough fractures was simulated numerically by using the Lattice Boltzmann method (LBM). An agreement between the experimental data and the numerical simulation results was achieved. The fractal dimension is positively correlated to fracture surface roughness and the fracture inclination represents the gravity force acting on the water flow. The influences of fracture inclinations, fractal dimensions, and mismatch wavelengths were studied and analyzed, with an emphasis on flow paths through a self-affine rough fracture. Different values of fractal dimensions, fracture inclinations, and mismatch wavelengths result in small changes of flow rates from five sections of discharging surface. However, the section of discharging surface with the largest flow rate remains constant. In addition, it is found that the gravity force can affect flow paths. Combined with the experimental data, the simulation results are used to explain the preferential flow paths through fracture rough surfaces from a new perspective. The results may enhance our understanding of fluid flow through fractures and provide a solid background for further research in the areas of energy exploration and production.
Identifying Green Infrastructure as a Basis for an Incentive Mechanism at the Municipality Level in Biscay (Basque Country)
Authors: Rodríguez-Loinaz Gloria , Peña Lorena , Palacios-Agundez Igone , Ametzaga Ibone , Onaindia Miren
Published: January 2018

The contributions of green infrastructure (GI) to human well-being have been widely recognised; however, pathways for its systematic implementation are missing. Local governments can play a crucial role in the conservation of GI, and a formal recognition of this role in budgeting systems would foster the inclusion of GI in their agenda. The aim of this study is to identify the principal components of GI at the local level to form a basis for a compensatory economic scheme. We identified the principal components of GI based on the mapping of biodiversity conservation and ecosystem services provision. Furthermore, we analysed the potentiality of an incentive mechanism to promote GI based on the protection status of GI. Finally, an incentive mechanism to promote GI at the municipality level was proposed. The results showed that the GI of Biscay is mainly composed of the natural forests presented in the area, and that 50% of the principal components of the GI are not protected. Furthermore, one third of the protected principal components of the GI only has protection at the municipality level. So, we propose a Payment for Ecosystem Services (PES)-like scheme at the municipality level based on the cover of natural forests, where the objective is the conservation and promotion of the GI.
Structural and Evolutionary Relationships in the Giant Sex Chromosomes of Three Microtus Species
Authors: Lamelas Luz , Arroyo María , Fernández Francisco , Marchal Juan , Sánchez Antonio
Published: January 2018

The genus Microtus has high karyotypic diversity. The existence of notable differences in the length of its sex chromosomes contributes to this variation. Variations in size are attributed to the enlargement of their heterochromatin content, which is of such magnitude in some species that they are referred to as “giant sex chromosomes”. Here, we perform an intra- and interspecific analysis of the molecular composition of the heterochromatic blocks in three species with giant sex chromosomes (Microtus chrotorrhinus, M. cabrerae and M. agrestis). Our results show that the heterochromatic content is very similar in both the X and Y chromosomes of M. chrotorrhinus, and that their molecular composition is more closely related to the heterochromatic blocks of M. agrestis than to the sex heterochromatin of M. cabrerae; however, species-specific differences do clearly exist. Interestingly, the euchromatic regions of the X chromosome of all three of these species share a homologous region composed of heterochromatic-related sequences. Our results therefore reinforce the idea that certain similarities in the original organization of these X chromosomes could have facilitated their later enlargement.
The Landscape of Small Non-Coding RNAs in Triple-Negative Breast Cancer
Authors: Guo Yan , Yu Hui , Wang Jing , Sheng Quanhu , Zhao Shilin , Zhao Ying-Yong , Lehmann Brian
Published: January 2018

Triple-negative breast cancer (TNBC) is an operational term for breast cancers lacking targetable estrogen receptor expression and HER2 amplifications. TNBC is, therefore, inherently heterogeneous, and is associated with worse prognosis, greater rates of metastasis, and earlier onset. TNBC displays mutational and transcriptional diversity, and distinct mRNA transcriptional subtypes exhibiting unique biology. High-throughput sequencing has extended cancer research far beyond protein coding regions that include non-coding small RNAs, such as miRNA, isomiR, tRNA, snoRNAs, snRNA, yRNA, 7SL, and 7SK. In this study, we performed small RNA profiling of 26 TNBC cell lines, and compared the abundance of non-coding RNAs among the transcriptional subtypes of triple negative breast cancer. We also examined their co-expression pattern with corresponding mRNAs. This study provides a detailed description of small RNA expression in triple-negative breast cancer cell lines that can aid in the development of future biomarker and novel targeted therapies.
Meteorological Patterns Linked to Landslide Triggering in Asturias (NW Spain): A Preliminary Analysis
Authors: Valenzuela Pablo , Iglesias Miguel , Domínguez-Cuesta María , Mora García Manuel
Published: January 2018

Asturias is one of the most landslide prone areas in the north of Spain. Most landslides are linked to intense and continue rainfall events, especially between October and May. This fact points out precipitation as the main triggering factor in the study area. Thirteen rainfall episodes that caused 1064 landslides between 2008 and 2016 have been selected for its study. Landslide records come from the Principality of Asturias Landslide Database (BAPA) and meteorological data from the Spanish Meteorological Agency (AEMET). Meteorological conditions which took place during each period have been characterized by using NCEP/NCAR Reanalysis data. Four main landslide-triggering meteorological patterns have been identified for the Asturian territory: Strong Atlantic Anticyclone pattern (SAA), Atlantic Depression pattern (AD), Anticyclonic ridge pattern (AR) and Cut-off Low pattern (CL).
Antimacrofouling Efficacy of Innovative Inorganic Nanomaterials Loaded with Booster Biocides
Authors: Gutner-Hoch Eldad , Martins Roberto , Oliveira Tania , Maia Frederico , Soares Amadeu , Loureiro Susana , Piller Chen , Preiss Iris , Weis Michal , Larroze Severine , Teixeira Tania , Tedim João , Benayahu Yehuda
Published: January 2018

The application of nano-structured compounds has been increasing rapidly in recent years, in several fields. The use of engineered nano-materials as carriers of antifouling compounds is just beginning and already reveals clear advantages compared to bulk active compounds, such as slowed and controlled release, novel functionality, and high loading capacity. This present study assesses the antifouling efficacy of two nanostructured materials, spherical mesoporous silica nanocapsules (SiNC) and Zn-Al layered double hydroxides (LDH), loaded with two commercial biocides, zinc prithione (ZnPT) and copper pyrithione (CuPT). The study used adult mussels from three geographical regions, the Atlantic Ocean, Mediterranean Sea, and the Red Sea, to examine the efficacy of the innovative compounds. The efficacy of these compounds on larvae of the bryozoan Bugula neritina from the Mediterranean Sea and the Red Sea was also examined. The results of this study demonstrated the environmentally friendly properties of unloaded LDH against the two-model systems, adult mussels or bryozoan larvae. ZnPT entrapped in LDH demonstrated the most effective antifouling compound against the two model systems. A comparison of the impact of the two compounds on macrofouling organisms from the different marine habitats examined in this study indicates a distinction associated with the organisms’ different ecosystems. The Red Sea mussels and bryozoans, representing a tropical marine ecosystem, yielded the highest efficacy values among tested Atlantic Ocean and Mediterranean Sea mussels and bryozoans.
Inferring Missing Climate Data for Agricultural Planning Using Bayesian Networks
Authors: Lara-Estrada Leonel , Rasche Livia , Sucar L. , Schneider Uwe
Published: January 2018

Climate data availability plays a key role in development processes of policies, services, and planning in the agricultural sector. However, data at the spatial or temporal resolution required is often lacking, or certain values are missing. In this work, we propose to use a Bayesian network approach to generate data for missing variables. As a case study, we use relative humidity, which is an important indicator of land suitability for coffee production. For the model, we first extracted climate data for the variables precipitation, maximum and minimum air temperature, wind speed, solar radiation and relative humidity from the surface reanalysis dataset Climate Forecast System Reanalysis. We then used machine learning algorithms to define the model structure and parameters from the relationships of the variables found in the dataset. Precipitation, maximum and minimum air temperature, wind speed, and solar radiation are then used as proxy variables to infer missing values for monthly relative humidity and relative humidity for the driest month. For this, we used both complete and incomplete initial data. In both scenarios of data availability, the comparison of estimated and measured values of relative humidity shows a high level of agreement. We conclude that using Bayesian Networks is a practical solution to estimate relative humidity for coffee agricultural planning.
Anchoring ZnO Nanoparticles in Nitrogen-Doped Graphene Sheets as a High-Performance Anode Material for Lithium-Ion Batteries
Authors: Yuan Guanghui , Xiang Jiming , Jin Huafeng , Wu Lizhou , Jin Yanzi , Zhao Yan
Published: January 2018

A novel binary nanocomposite, ZnO/nitrogen-doped graphene (ZnO/NG), is synthesized via a facile solution method. In this prepared ZnO/NG composite, highly-crystalline ZnO nanoparticles with a size of about 10 nm are anchored uniformly on the N-doped graphene nanosheets. Electrochemical properties of the ZnO/NG composite as anode materials are systematically investigated in lithium-ion batteries. Specifically, the ZnO/NG composite can maintain the reversible specific discharge capacity at 870 mAh g−1 after 200 cycles at 100 mA g−1. Besides the enhanced electronic conductivity provided by interlaced N-doped graphene nanosheets, the excellent lithium storage properties of the ZnO/NG composite can be due to nanosized structure of ZnO particles, shortening the Li+ diffusion distance, increasing reaction sites, and buffering the ZnO volume change during the charge/discharge process.
On the Mn–C Short-Range Ordering in a High-Strength High-Ductility Steel: Small Angle Neutron Scattering and Ab Initio Investigation
Authors: Song Wenwen , Bogdanovski Dimitri , Yildiz Ahmet , Houston Judith , Dronskowski Richard , Bleck Wolfgang
Published: January 2018

The formation of Mn–C short-range ordering (SRO) has a great influence on the mechanical properties of high-Mn steels. In the present work, the formation of Mn–C SRO during recrystallization of an X60Mn18 steel was investigated by means of a combined study employing small angle neutron scattering (SANS) and ab initio ground-state energy calculations based on density-functional theory. The SANS measurements prove the presence of Mn–C SRO in the recrystallization annealed X60Mn18 steel and indicate the evolution of the SRO during recrystallization. The results show that with the increase in annealing time, the mean size of the Mn–C SRO decreases, whereas the number density increases. The ab initio calculations well describe the energetically favored condition of Mn–C SRO and provide the theoretical explanation of the clustering formation and evolution in the X60Mn18 steel. The stress-strain curve of the X60Mn18 steel exhibits a high strain-hardening rate and the plastic deformation is characterized with a series of serrations during a uniaxial tensile test. In the end, the correlation between Mn–C SRO and the serrated flow of high-Mn steels is further discussed.
Monitoring Reaction Paths Using Vibrational Spectroscopies: The Case of the Dehydrogenation of Propane toward Propylene on Pd-Doped Cu(111) Surface
Authors: Hu Wei , Cao Xinrui
Published: January 2018

Monitoring reaction paths is not only a fundamental scientific issue but also helps us to understand and optimize the catalytic process. Infrared (IR) and Raman spectroscopies are powerful tools for detecting particular molecules or intermediate products as a result of their ability to provide the molecular “finger-print”. However, theoretical modeling for the vibrational spectra of molecular adsorbates on metallic surfaces is a long-standing challenge, because accurate descriptions of the electronic structure for both the metallic substrates and adsorbates are required. In the present work, we applied a quasi-analytical IR and Raman simulation method to monitor the dehydrogenation of propane towards propylene on a Pd-doped Cu(111) surface in real-time. Different Pd ensembles were used to construct the single-atom catalyst (SAC). We found that the number of sublayer Pd atoms could only affect the intensity of the peak rather than the peak position on the vibrational spectra. However, with the dehydrogenation reaction proceeding, both IR and Raman spectra were changed greatly, which indicates that every reaction step can be distinguished from the point of view of vibrational spectroscopies. Additionally, we found that the catalytic process, which starts from different initial states, shows different spectral profiles. The present results suggest that the vibrational spectroscopies obtained by the high-precision simulations pave the way for identifying different catalytic reaction paths.
Optimization of Fermentation Conditions and Bench-Scale for Improvement of a Novel Glycoprotein GP-1 Production by Streptomyces kanasenisi ZX01
Authors: Zhou Yong , Zhou Xin , Yu Dai-Lin , Sang Bu , Feng Jun-Tao , Han Li-Rong , Zhang Xing
Published: January 2018

GP-1 is a novel glycoprotein produced by Streptomyces kanasenisi ZX01 that was isolated from soil near Kanas Lake with significant bioactivity against tobacco mosaic virus. However, extremely low fermentation production has largely hindered further research and market applications on glycoprotein GP-1. In this study, response surface methodology was used to optimize fermentation conditions in a shake flask for higher glycoprotein GP-1 production. When the optimized fermentation conditions were inoculum volume of 6%, initial pH of 6.5, and rotating speed of 150 rpm, glycoprotein GP-1 production could reach 0.9253 mg/L, which was increased by 52.14% compared to the original conditions. In addition, scale-up fermentation was conducted in a 5-L bioreactor to preliminarily explore the feasibility for mass production of glycoprotein GP-1 in a large fermentor, obtaining GP-1 production of 2.54 mg/L under the same conditions, which was 2.75 times higher than the production obtained from a shake flask of 0.9253 mg/L. This work will be helpful to improve GP-1 production on a large scale and lay the foundations for developing it as a novel agent against plant virus.
Eating Patterns in Patients with Compensated Cirrhosis: A Case-Control Study
Authors: Buscail Camille , Bourcier Valérie , Fezeu Léopold , Roulot Dominique , Brulé Séverine , Ben-Abdesselam Zahia , Cagnot Carole , Hercberg Serge , Nahon Pierre , Ganne-Carrié Nathalie , Julia Chantal
Published: January 2018

Background: There is growing evidence suggesting that maintaining an adequate nutritional status for patients with liver cirrhosis (LC) is relevant to prevent complications. The present study aimed to describe dietary behaviours of patients with compensated and non-complicated LC and comparing them with those of subjects from the general population. Methods: In this case-control study, patients were volunteers enrolled in the ALICIR (ALImentation et CIRrhose) study, an observational survey nested in two French prospective cohorts of patients with biopsy-proven compensated cirrhosis related either to excessive alcohol consumption (CIRRAL) or to hepatitis B or C virus infection (CirVir). Controls were selected from the NutriNet-Santé cohort. Dietary data were collected through a semi quantitative food frequency questionnaire. Dietary and nutritional data were compared using multi-adjusted paired Student’s tests. Results: Between June 2014 and February 2016, 174 patients of CirVir (N = 97) or CIRRAL (N = 77) were matched with 348 controls from the NutriNet-Santé cohort, according to gender, age, BMI and educational level. Compared to controls, patients (mean ± SD) consumed more sodas (236.0 ± 29.8 mL vs. 83.0 ± 33.0 mL) and water (1787.6 ± 80.6 mL vs. 933.6 ± 85.3 mL), and lower amounts of salty snacks (4.2 ± 1.42 g vs. 9.0 ± 1.6 g) and alcoholic beverages (71.8 ± 23.4 g vs. 151.2 ± 25.9 g), with all p values < 0.0001. Dietary behaviours differed according to LC aetiology. Conclusions: Dietary behaviour of patients significantly differed from subjects from the general population.
Physical Activity, Physical Fitness, Body Composition, and Nutrition Are Associated with Bone Status in University Students
Authors: Hervás Gotzone , Ruiz-Litago Fátima , Irazusta Jon , Fernández-Atutxa Ainhoa , Fraile-Bermúdez Ana , Zarrazquin Idoia
Published: January 2018

Understanding the modifiable factors that improve and maximize peak bone mass at an early age is necessary to design more effective intervention programs to prevent osteoporosis. To identify these modifiable factors, we analyzed the relationship of physical activity (PA), physical fitness, body composition, and dietary intake with bone stiffness index (SI), measured by quantitative ultrasonometry in young university students (18–21 years). Moderate-to-vigorous PA (MVPA) was the strongest predictor of SI (β = 0.184; p = 0.035). SI was most closely related with very vigorous PA in males (β = 0.288; p = 0.040) and with the number of steps/day in females (β = 0.319; p = 0.002). An association between thigh muscle and SI was consistent in both sexes (β = 0.328; p < 0.001). Additionally, extension maximal force was a bone SI predictor factor in females (β = 0.263; p = 0.016) independent of thigh muscle perimeter. Calcium intake was the only nutrition parameter that had a positive relationship with SI (R = 0.217; p = 0.022). However, it was not included as a predictor for SI in our regression models. This study identifies predictors of bone status in each sex and indicates that muscle and bone interrelate with PA and fitness in young adults.
Validity of Predictive Equations for Resting Energy Expenditure Developed for Obese Patients: Impact of Body Composition Method
Authors: Achamrah Najate , Jésus Pierre , Grigioni Sébastien , Rimbert Agnès , Petit André , Déchelotte Pierre , Folope Vanessa , Coëffier Moïse
Published: January 2018

Predictive equations have been specifically developed for obese patients to estimate resting energy expenditure (REE). Body composition (BC) assessment is needed for some of these equations. We assessed the impact of BC methods on the accuracy of specific predictive equations developed in obese patients. REE was measured (mREE) by indirect calorimetry and BC assessed by bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA). mREE, percentages of prediction accuracy (±10% of mREE) were compared. Predictive equations were studied in 2588 obese patients. Mean mREE was 1788 ± 6.3 kcal/24 h. Only the Müller (BIA) and Harris & Benedict (HB) equations provided REE with no difference from mREE. The Huang, Müller, Horie-Waitzberg, and HB formulas provided a higher accurate prediction (>60% of cases). The use of BIA provided better predictions of REE than DXA for the Huang and Müller equations. Inversely, the Horie-Waitzberg and Lazzer formulas provided a higher accuracy using DXA. Accuracy decreased when applied to patients with BMI ≥ 40, except for the Horie-Waitzberg and Lazzer (DXA) formulas. Müller equations based on BIA provided a marked improvement of REE prediction accuracy than equations not based on BC. The interest of BC to improve REE predictive equations accuracy in obese patients should be confirmed.
Factors Associated with Binge Eating Behavior among Malaysian Adolescents
Authors: Gan Wan , Mohamad Normasliana , Law Leh
Published: January 2018

Although there are numerous studies on binge eating behavior in the Western countries, studies on this behavior in Malaysia are still limited. Therefore, this cross-sectional study aimed to determine the risk factors associated with binge eating behavior among adolescents in Malaysia. The study included 356 adolescents (42.7% males and 57.3% females), aged 13 to 16 years. They completed a self-administered questionnaire on demographic and socioeconomic backgrounds, frequency of family meals, family meal environments, family cohesion, perception of body size, self-esteem, depressive symptoms, perfectionistic self-presentation, and binge eating behavior. Furthermore, their weight, height, and waist circumference were measured. It was found that 14.0% of the participants engaged in binge eating behavior (15.2% in females and 12.5% in males). Additionally, it was identified that high levels of depressive symptoms, high levels of body dissatisfaction, poor family cohesion, and low self-esteem were significantly contributed to binge eating behavior after controlling for sex (adjusted R2 = 0.165, F = 15.056, p < 0.001). The findings may suggest that improving the relationships between family members, along with eliminating adolescents’ negative emotions could help in the prevention of binge eating behavior among adolescents. The identified modifiable risk factors should be incorporated into binge eating preventive programs to increase the effectiveness of the programs.
Advances in Non-Destructive Early Assessment of Fruit Ripeness towards Defining Optimal Time of Harvest and Yield Prediction—A Review
Authors: Li Bo , Lecourt Julien , Bishop Gerard
Published: January 2018

Global food security for the increasing world population not only requires increased sustainable production of food but a significant reduction in pre- and post-harvest waste. The timing of when a fruit is harvested is critical for reducing waste along the supply chain and increasing fruit quality for consumers. The early in-field assessment of fruit ripeness and prediction of the harvest date and yield by non-destructive technologies have the potential to revolutionize farming practices and enable the consumer to eat the tastiest and freshest fruit possible. A variety of non-destructive techniques have been applied to estimate the ripeness or maturity but not all of them are applicable for in situ (field or glasshouse) assessment. This review focuses on the non-destructive methods which are promising for, or have already been applied to, the pre-harvest in-field measurements including colorimetry, visible imaging, spectroscopy and spectroscopic imaging. Machine learning and regression models used in assessing ripeness are also discussed.
Influence of Temperature on the Mechanical Properties and Reactive Behavior of Al-PTFE under Quasi-Static Compression
Authors: Wang Huai-Xi , Fang Xiang , Feng Bin , Gao Zhen-Ru , Wu Shuang-Zhang , Li Yu-Chun
Published: January 2018

Al-PTFE (aluminum-polytetrafluoroethylene) is a typical kind of Reactive Material (RM), which has a variety of potential applications in weapon systems. In this paper, quasi-static compression experiments were carried out for a pressed and sintered mixture of Al and PTFE powders using a microcomputer-controlled electronic universal testing machine. The results show that both the mechanical property and reactive behavior of Al-PTFE are strongly temperature-dependent. The material undergoes a brittle-ductile transition associated with a temperature-induced crystalline phase transformation of the PTFE matrix. At low temperatures (−18, 0, and 16 °C), samples of Al-PTFE failed with shear crack and no reaction was observed. As the temperature increased (22, 35, and 80 °C), Al-PTFE exhibited a high toughness and violent reaction occurred in all of the tested samples. Scanning electron microscope observations showed different fracture mechanisms of the PTFE matrix and the increase in toughness was due to the formation of PTFE fibrils which could dissipate energy and bridge crack plane during plastic deformation.
Intercalation Polymerization Approach for Preparing Graphene/Polymer Composites
Authors: Guo Yifan , Peng Fuxi , Wang Huagao , Huang Fei , Meng Fanbin , Hui David , Zhou Zuowan
Published: January 2018

The rapid development of society has promoted increasing demand for various polymer materials. A large variety of efforts have been applied in order for graphene strengthened polymer composites to satisfy different requirements. Graphene/polymer composites synthesized by traditional strategies display some striking defects, like weak interfacial interaction and agglomeration of graphene, leading to poor improvement in performance. Furthermore, the creation of pre-prepared graphene while being necessary always involves troublesome processes. Among the various preparation strategies, an appealing approach relies on intercalation and polymerization in the interlayer of graphite and has attracted researchers’ attention due to its reliable, fast and simple synthesis. In this review, we introduce an intercalation polymerization strategy to graphene/polymer composites by the intercalation of molecules/ions into graphite interlayers, as well as subsequent polymerization. The key point for regulating intercalation polymerization is tuning the structure of graphite and intercalants for better interaction. Potential applications of the resulting graphene/polymer composites, including electrical conductivity, electromagnetic absorption, mechanical properties and thermal conductivity, are also reviewed. Furthermore, the shortcomings, challenges and prospects of intercalation polymerization are discussed, which will be helpful to researchers working in related fields.
Weighting of Multi-GNSS Observations in Real-Time Precise Point Positioning
Authors: Kazmierski Kamil , Hadas Tomasz , Sośnica Krzysztof
Published: January 2018

The combination of Global Navigation Satellite Systems (GNSS) may improve the accuracy and precision of estimated coordinates, as well as the convergence time of Precise Point Positioning (PPP) solutions. The key conditions are the correct functional model and the proper weighting of observations, for which different characteristics of multi-GNSS signals should be taken into account. In post-processing applications, the optimum stochastic model can be obtained through the analysis of post-fit residuals, but for real-time applications the stochastic model has to be defined in advanced. We propose five different weighting schemes for the GPS + GLONASS + Galileo + BeiDou combination, including two schemes with no intra-system differences, and three schemes that are based on signal noise and/or quality of satellite orbits. We perform GPS-only and five multi-GNSS solutions representing each weighting scheme. We analyze formal errors of coordinates, coordinate repeatability, and solution convergence time. We found that improper or equal weighting may improve formal errors but decreases coordinate repeatability when compared to the GPS-only solution. Intra-system weighting based on satellite orbit quality allows for a reduction of formal errors by 40%, for shortening convergence time by 40% and 47% for horizontal and vertical components, respectively, as well as for improving coordinate repeatability by 6%.
Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study
Authors: Berger Katja , Atzberger Clement , Danner Martin , D’Urso Guido , Mauser Wolfram , Vuolo Francesco , Hank Tobias
Published: January 2018

Upcoming satellite hyperspectral sensors require powerful and robust methodologies for making optimum use of the rich spectral data. This paper reviews the widely applied coupled PROSPECT and SAIL radiative transfer models (PROSAIL), regarding their suitability for the retrieval of biophysical and biochemical variables in the context of agricultural crop monitoring. Evaluation was carried out using a systematic literature review of 281 scientific publications with regard to their (i) spectral exploitation, (ii) vegetation type analyzed, (iii) variables retrieved, and (iv) choice of retrieval methods. From the analysis, current trends were derived, and problems identified and discussed. Our analysis clearly shows that the PROSAIL model is well suited for the analysis of imaging spectrometer data from future satellite missions and that the model should be integrated in appropriate software tools that are being developed in this context for agricultural applications. The review supports the decision of potential users to employ PROSAIL for their specific data analysis and provides guidelines for choosing between the diverse retrieval techniques.
Small Imaging Depth LIDAR and DCNN-Based Localization for Automated Guided Vehicle
Authors: Ito Seigo , Hiratsuka Shigeyoshi , Ohta Mitsuhiko , Matsubara Hiroyuki , Ogawa Masaru
Published: January 2018

We present our third prototype sensor and a localization method for Automated Guided Vehicles (AGVs), for which small imaging LIght Detection and Ranging (LIDAR) and fusion-based localization are fundamentally important. Our small imaging LIDAR, named the Single-Photon Avalanche Diode (SPAD) LIDAR, uses a time-of-flight method and SPAD arrays. A SPAD is a highly sensitive photodetector capable of detecting at the single-photon level, and the SPAD LIDAR has two SPAD arrays on the same chip for detection of laser light and environmental light. Therefore, the SPAD LIDAR simultaneously outputs range image data and monocular image data with the same coordinate system and does not require external calibration among outputs. As AGVs travel both indoors and outdoors with vibration, this calibration-less structure is particularly useful for AGV applications. We also introduce a fusion-based localization method, named SPAD DCNN, which uses the SPAD LIDAR and employs a Deep Convolutional Neural Network (DCNN). SPAD DCNN can fuse the outputs of the SPAD LIDAR: range image data, monocular image data and peak intensity image data. The SPAD DCNN has two outputs: the regression result of the position of the SPAD LIDAR and the classification result of the existence of a target to be approached. Our third prototype sensor and the localization method are evaluated in an indoor environment by assuming various AGV trajectories. The results show that the sensor and localization method improve the localization accuracy.