Photoelectric response of Schottky barrier in La0.7 Ca0.3 Mn O3 Nb:SrTi O3 heterojunctions

Heterojunctions composed of La0.7 Ca0.3 Mn O3 and 0.05 wt % Nb-doped SrTi O3 were fabricated using pulse laser deposition. The current-voltage characteristics of such heterojunctions can be described by tunneling with an effective Schottky barrier. These junctions showed significant response to ultraviolet and visible light. Band-to-band and internal photoemission were characterized by photoelectric experiments. A quantum efficiency of about 86% was observed at an incident energy of ∼3.95 eV, which corresponds to the band-to-band excitation of electrons in Nb:SrTi O3. From the internal photoemission, the height of Schottky barrier was determined as 1.64 eV. © 2008 American Institute of Physics.published_or_final_versio

Pharmacological Effects of Active Compounds on Neurodegenerative Disease with Gastrodia and Uncaria Decoction, a Commonly Used Poststroke Decoction

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Classical and reactive molecular dynamics: Principles and applications in combustion and energy systems

Molecular dynamics (MD) has evolved into a ubiquitous, versatile and powerful computational method for fundamental research in science branches such as biology, chemistry, biomedicine and physics over the past 60 years. Powered by rapidly advanced supercomputing technologies in recent decades, MD has entered the engineering domain as a first-principle predictive method for material properties, physicochemical processes, and even as a design tool. Such developments have far-reaching consequences, and are covered for the first time in the present paper, with a focus on MD for combustion and energy systems encompassing topics like gas/liquid/solid fuel oxidation, pyrolysis, catalytic combustion, heterogeneous combustion, electrochemistry, nanoparticle synthesis, heat transfer, phase change, and fluid mechanics. First, the theoretical framework of the MD methodology is described systemically, covering both classical and reactive MD. The emphasis is on the development of the reactive force field (ReaxFF) MD, which enables chemical reactions to be simulated within the MD framework, utilizing quantum chemistry calculations and/or experimental data for the force field training. Second, details of the numerical methods, boundary conditions, post-processing and computational costs of MD simulations are provided. This is followed by a critical review of selected applications of classical and reactive MD methods in combustion and energy systems. It is demonstrated that the ReaxFF MD has been successfully deployed to gain fundamental insights into pyrolysis and/or oxidation of gas/liquid/solid fuels, revealing detailed energy changes and chemical pathways. Moreover, the complex physico-chemical dynamic processes in catalytic reactions, soot formation, and flame synthesis of nanoparticles are made plainly visible from an atomistic perspective. Flow, heat transfer and phase change phenomena are also scrutinized by MD simulations. Unprecedented details of nanoscale processes such as droplet collision, fuel droplet evaporation, and CO2 capture and storage under subcritical and supercritical conditions are examined at the atomic level. Finally, the outlook for atomistic simulations of combustion and energy systems is discussed in the context of emerging computing platforms, machine learning and multiscale modelling

The effects of dynamic compression on the development of cartilage grafts engineered using bone marrow and infrapatellar fat pad derived stem cells.

Bioreactors that subject cell seeded scaffolds or hydrogels to biophysical stimulation have been used to improve the functionality of tissue engineered cartilage and to explore how such constructs might respond to the application of joint specific mechanical loading. Whether a particular cell type responds appropriately to physiological levels of biophysical stimulation could be considered a key determinant of its suitability for cartilage tissue engineering applications. The objective of this study was to determine the effects of dynamic compression on chondrogenesis of stem cells isolated from different tissue sources. Porcine bone marrow (BM) and infrapatellar fat pad (FP) derived stem cells were encapsulated in agarose hydrogels and cultured in a chondrogenic medium in free swelling (FS) conditions for 21 d, after which samples were subjected to dynamic compression (DC) of 10% strain (1 Hz, 1 h d(-1)) for a further 21 d. Both BM derived stem cells (BMSCs) and FP derived stem cells (FPSCs) were capable of generating cartilaginous tissues with near native levels of sulfated glycosaminoglycan (sGAG) content, although the spatial development of the engineered grafts strongly depended on the stem cell source. The mechanical properties of cartilage grafts generated from both stem cell sources also approached that observed in skeletally immature animals. Depending on the stem cell source and the donor, the application of DC either enhanced or had no significant effect on the functional development of cartilaginous grafts engineered using either BMSCs or FPSCs. BMSC seeded constructs subjected to DC stained less intensely for collagen type I. Furthermore, histological and micro-computed tomography analysis showed mineral deposition within BMSC seeded constructs was suppressed by the application of DC. Therefore, while the application of DC in vitro may only lead to modest improvements in the mechanical functionality of cartilaginous grafts, it may play an important role in the development of phenotypically stable constructs.Funding was provided by the European Research Council Starter Grant (StemRepair—Project number 258463) and a SFI President of Ireland Young Researcher Award (08/Y15/B1336)

Experimental and numerical study on soot formation in laminar diffusion flames of biodiesels and methyl esters

Biodiesel and blends with petroleum diesel are promising renewable alternative fuels for engines. In the present study, the soot concentration generated from four biodiesels, two pure methyl esters, and their blends with petroleum diesel are measured in a series of fully pre-vapourised co-flow diffusion flames. The experimental measurements are conducted using planar laser induced-incandescence (LII) and laser extinction optical methods. The results show that the maximum local soot volume fractions of neat biodiesels are 24.4% - 41.2% of pure diesel, whereas the mean soot volume fraction of neat biodiesel cases was measured as 11.3% - 21.3% of pure diesel. The addition of biodiesel to diesel not only reduces the number of inception particles, but also inhibits their surface growth. The discretised population balance modelling of a complete set of soot processes is employed to compute the 2D soot volume fraction and size distribution across the tested flames. The results show that the model also demonstrates a reduction of both soot volume fraction and primary particle size by adding biodiesel fuels. However, it is not possible to clearly determine which factors are responsible for the reduction from the comparison alone. Moreover, analysis of the discrepancies between numerical and experimental results for diesel and low-blending cases offers an insight for the refinement of soot formation modelling of combustion with large-molecule fuels.Bo Tian is supported by the fellowship provided by ZEPI. C. T. Chong is supported by the Newton Advanced Fellowship of the Royal Society (NA160115). Anxiong Liu gratefully acknowledges the financial support of the Chinese Scholarship Council (CSC) and the EPSRC grant No. EP/S012559/1

Experimental and numerical study on soot formation in laminar diffusion flames of biodiesels and methyl esters

Biodiesel and blends with petroleum diesel are promising renewable alternative fuels for engines. In the present study, the soot concentration generated from four biodiesels, two pure methyl esters, and their blends with petroleum diesel are measured in a series of fully pre-vapourised co-flow diffusion flames. The experimental measurements are conducted using planar laser induced-incandescence (LII) and laser extinction optical methods. The results show that the maximum local soot volume fractions of neat biodiesels are 24.4% - 41.2% of pure diesel, whereas the mean soot volume fraction of neat biodiesel cases was measured as 11.3% - 21.3% of pure diesel. The addition of biodiesel to diesel not only reduces the number of inception particles, but also inhibits their surface growth. The discretised population balance modelling of a complete set of soot processes is employed to compute the 2D soot volume fraction and size distribution across the tested flames. The results show that the model also demonstrates a reduction of both soot volume fraction and primary particle size by adding biodiesel fuels. However, it is not possible to clearly determine which factors are responsible for the reduction from the comparison alone. Moreover, analysis of the discrepancies between numerical and experimental results for diesel and low-blending cases offers an insight for the refinement of soot formation modelling of combustion with large-molecule fuels.Bo Tian is supported by the fellowship provided by ZEPI. C. T. Chong is supported by the Newton Advanced Fellowship of the Royal Society (NA160115). Anxiong Liu gratefully acknowledges the financial support of the Chinese Scholarship Council (CSC) and the EPSRC grant No. EP/S012559/1

Validation of the Alzheimer's disease-resemblance atrophy index in classifying and predicting progression in Alzheimer's disease

BACKGROUND: Automated tools for characterising dementia risk have the potential to aid in the diagnosis, prognosis, and treatment of Alzheimer’s disease (AD). Here, we examined a novel machine learning-based brain atrophy marker, the AD-resemblance atrophy index (AD-RAI), to assess its test-retest reliability and further validate its use in disease classification and prediction. METHODS: Age- and sex-matched 44 probable AD (Age: 69.13 ± 7.13; MMSE: 27–30) and 22 non-demented control (Age: 69.38 ± 7.21; MMSE: 27–30) participants were obtained from the Minimal Interval Resonance Imaging in Alzheimer’s Disease (MIRIAD) dataset. Serial T1-weighted images (n = 678) from up to nine time points over a 2-year period, including 179 pairs of back-to-back scans acquired on same participants on the same day and 40 pairs of scans acquired at 2-week intervals were included. All images were automatically processed with AccuBrain® to calculate the AD-RAI. Its same-day repeatability and 2-week reproducibility were first assessed. The discriminative performance of AD-RAI was evaluated using the receiver operating characteristic curve, where DeLong’s test was used to evaluate its performance against quantitative medial temporal lobe atrophy (QMTA) and hippocampal volume adjusted by intracranial volume (ICV)-proportions and ICV-residuals methods, respectively (HVR and HRV). Linear mixed-effects modelling was used to investigate longitudinal trajectories of AD-RAI and baseline AD-RAI prediction of cognitive decline. Finally, the longitudinal associations between AD-RAI and MMSE scores were assessed. RESULTS: AD-RAI had excellent same-day repeatability and excellent 2-week reproducibility. AD-RAI’s AUC (99.8%; 95%CI = [99.3%, 100%]) was equivalent to that of QMTA (96.8%; 95%CI = [92.9%, 100%]), and better than that of HVR (86.8%; 95%CI = [78.2%, 95.4%]) or HRV (90.3%; 95%CI = [83.0%, 97.6%]). While baseline AD-RAI was significantly higher in the AD group, it did not show detectable changes over 2 years. Baseline AD-RAI was negatively associated with MMSE scores and the rate of the change in MMSE scores over time. A negative longitudinal association was also found between AD-RAI values and the MMSE scores among AD patients CONCLUSIONS: The AD-RAI represents a potential biomarker that may support AD diagnosis and be used to predict the rate of future cognitive decline in AD patients

Wave attenuation at a salt marsh margin: A case study of an exposed coast on the Yangtze estuary

To quantify wave attenuation by (introduced) Spartina alterniflora vegetation at an exposed macrotidal coast in the Yangtze Estuary, China, wave parameters and water depth were measured during 13 consecutive tides at nine locations ranging from 10 m seaward to 50 m landward of the low marsh edge. During this period, the incident wave height ranged from <0.1 to 1.5 m, the maximum of which is much higher than observed in other marsh areas around the world. Our measurements and calculations showed that the wave attenuation rate per unit distance was 1 to 2 magnitudes higher over the marsh than over an adjacent mudflat. Although the elevation gradient of the marsh margin was significantly higher than that of the adjacent mudflat, more than 80% of wave attenuation was ascribed to the presence of vegetation, suggesting that shoaling effects were of minor importance. On average, waves reaching the marsh were eliminated over a distance of similar to 80 m, although a marsh distance of >= 100 m was needed before the maximum height waves were fully attenuated during high tides. These attenuation distances were longer than those previously found in American salt marshes, mainly due to the macrotidal and exposed conditions at the present site. The ratio of water depth to plant height showed an inverse correlation with wave attenuation rate, indicating that plant height is a crucial factor determining the efficiency of wave attenuation. Consequently, the tall shoots of the introduced S. alterniflora makes this species much more efficient at attenuating waves than the shorter, native pioneer species in the Yangtze Estuary, and should therefore be considered as a factor in coastal management during the present era of sea-level rise and global change. We also found that wave attenuation across the salt marsh can be predicted using published models when a suitable coefficient is incorporated to account for drag, which varies in place and time due to differences in plant characteristics and abiotic conditions (i.e., bed gradient, initial water depth, and wave action).

Microbial fuel cells: a green and alternative source for bioenergy production

Microbial fuel cell (MFC) represents one of the green technologies for the production of bioenergy. MFCs using microalgae produce bioenergy by converting solar energy into electrical energy as a function of metabolic and anabolic pathways of the cells. In the MFCs with bacteria, bioenergy is generated as a result of the organic substrate oxidation. MFCs have received high attention from researchers in the last years due to the simplicity of the process, the absence in toxic by-products, and low requirements for the algae growth. Many studies have been conducted on MFC and investigated the factors affecting the MFC performance. In the current chapter, the performance of MFC in producing bioenergy as well as the factors which influence the efficacy of MFCs is discussed. It appears that the main factors affecting MFC’s performance include bacterial and algae species, pH, temperature, salinity, substrate, mechanism of electron transfer in an anodic chamber, electrodes materials, surface area, and electron acceptor in a cathodic chamber. These factors are becoming more influential and might lead to overproduction of bioenergy when they are optimized using response surface methodology (RSM)