Search

Background: Chrysanthemum morifolium Ramat, a traditional Chinese medicine, has the effects on liver clearing, vision improving, and anti-inflammation. C. morifolium and probiotics have been individually studied for their beneficial effects on metabolic diseases. However, the underlying molecular mechanisms were not completely elucidated. This study aims to elucidate the potential molecular mechanisms of C. morifolium and probiotics combination (CP) on alleviating nonalcoholic fatty liver disease (NAFLD) and the dysregulation of glucose metabolism in high-fat diet (HFD)-fed mice. Methods: The therapeutic effect of CP on metabolism was evaluated by liver histology and serum biochemical analysis, as well as glucose tolerance test. The impact of CP on gut microbiota was analyzed by 16S rRNA sequencing and fecal microbiota transplantation. Hepatic transcriptomic analysis was performed with the key genes and proteins validated by RT-qPCR and western blotting. In addition, whole body Pparα knockout (Pparα−/−) mice were used to confirm the CP-mediated pathway. Results: CP supplementation ameliorated metabolic disorders by reducing body weight and hepatic steatosis, and improving glucose intolerance and insulin resistance in HFD fed mice. CP intervention mitigated the HFD-induced gut microbiota dysbiosis, which contributed at least in part, to the beneficial effect of improving glucose metabolism. In addition, hepatic transcriptomic analysis showed that CP modulated the expression of genes associated with lipid metabolism. CP downregulated the mRNA level of lipid droplet-binding proteins, such as Cidea and Cidec in the liver, leading to more substrates for fatty acid oxidation (FAO). Meanwhile, the expression of CPT1α, the rate-limiting enzyme of FAO, was significantly increased upon CP treatment. Mechanistically, though CP didn't affect the total PPARα level, it promoted the nuclear localization of PPARα, which contributed to the reduced expression of Cidea and Cidec, and increased expression of CPT1α, leading to activated FAO. Moreover, whole body PPARα deficiency abolished the anti-NAFLD effect of CP, suggesting the importance of PPARα in CP-mediated beneficial effect. Conclusion: This study revealed the hypoglycemic and hepatoprotective effect of CP by regulating gut microbiota composition and PPARα subcellular localization, highlighting its potential for therapeutic candidate for metabolic disorders. [ABSTRACT FROM AUTHOR]

Metal-supported solid oxide fuel cells have broad application prospects in distributed power generation, transportation, military, and other fields. The electrochemical performance of the cell is still a challenge in commercial applications. Regulating the anode microstructure and optimizing polarization characteristics are effective methods. In this study, atmospheric plasma spraying technology is chosen to prepare the Ni-Gd0.2Ce0.8O1.9(GDC) anodes using different low plasma powers (18, 21, 24 kW), which is cost-effective and efficient. The power effect on anode microstructure and electrochemical performance is investigated. The results show that as the plasma power decreases from 24 to 18 kW, the anode's gas permeability and three-phase reaction boundary (TPB) gradually increase. Reducing the spraying power can decrease polarization resistance and improve power density. The 18-kW anode exhibits the lowest polarization resistance and the best output performance. Open-circuit voltage and maximum power density are 1.03 V and 0.89 W cm−2 at 750 °C, respectively. The polarization resistance and total resistance are 0.19 and 0.40 Ω cm2, respectively. The experimental results prove that atmospheric plasma spraying can realize the rapid and low-cost anode preparation for high-performance MS-SOFC. [ABSTRACT FROM AUTHOR]

This paper discusses using ground-based imagery to determine the attitude of a flying projectile assuming prior knowledge of its external geometry. It presents a segmentation-based approach to follow the object and evaluates it quantitatively with simulated data and qualitatively with both simulated and real data. Two experimental cases are considered: One assumes reliable target distance measurement from an auxiliary range sensor, while the other assumes no range information. The results show that in the case of an unknown projectile–camera distance, with projectile dimensions of 1.378 m and 0.08 m in length and diameter, the estimated distance, in-plane location, and pitch angle accuracies are about 50 m, 0.15 m, and 6 degrees, respectively. Yaw angle estimation is ambiguous. In the second case, assuming that the projectile–camera distance is known resolves the ambiguity of yaw estimation, resulting in accuracies of about 0.15 m, 3 degrees, and 20 degrees for in-plane location, pitch, and yaw angles, respectively. These accuracies were normalized to a 1-km projectile–camera distance. [ABSTRACT FROM AUTHOR]

It is important for functional neurons of animals or human beings to adapt to external stimuli, such as sound, pressure, and light. Regarding this aspect, autaptic neuron enables itself to utilize historical information to modulate its instant dynamics, such that it may be able to behave adaptively. In this paper, a FitzHugh–Nagumo based autaptic neuron is employed to investigate the capability of a sound-sensitive neural circuit's adaptation and filtering to analog acoustic signals. Extensive simulations are performed for excitatory and inhibitory types of autaptic neurons. The results show that the time-delayed feedback of the excitatory chemical autapse can be tuned to play the role of a narrow-band filter in response to a broadband acoustic signal. While the excitatory chemical autaptic neuron cannot saturate its response amplitude due to its positive feedback gain, the inhibitory chemical autapse can drive the neuron's amplitude to converge as the intensity of external drive increases, which reveals the capability of adaptation. What's more, the inhibitory chemical autaptic neuron can also exhibit a novel bursting adaptation, in which the number of spikings contained in one bursting changes as the electrical activity evolves. For electrical autaptic neurons, it is also found that both time-delay feedback gains can effectively modulate the response of neuron to acoustic signal. While the variation of time-lags mainly changes the spiking rates of the excitatory electrical autaptic neuron, the feedback gain alters its response amplitude. Lastly, by carefully tuning the time-lags, the expected subthreshold dynamics for larger inhibitory feedback gains can be switched to nearby quasi-periodic firings, which implies a competing relation between the time-delays and the feedback gains in the spiking dynamics of the inhibitory electrical autaptic neurons. The diverse emerging phenomena are expected to facilitate the design of online or interactive learning artificial neural networks with these functional autaptic neurons. [ABSTRACT FROM AUTHOR]

Trading signal detection is a very popular yet challenging research topic in the financial investment area. This paper develops a novel method integrating piecewise linear representation (PLR), improved particle swarm optimization (IPSO) and a feature-weighted support vector machine (FW-WSVM) to analyze the nonlinear relationships between trading signals and the stock data hidden in historical data. First, PLR is applied to generate numerous trading points (valleys or peaks) based on the historical data. These turning points' prediction is formulated as a three-class classification problem. Then, IPSO is utilized to find the optimal parameters of FW-WSVM. Lastly, we conduct a series of comparative experiments between IPSO-FW-WSVM and PLR-ANN on 25 stocks with 2 different investment strategies. The experiment results show that our proposed method achieves higher prediction accuracy and profitability, which indicates the IPSO-FW-WSVM method is effective in the prediction of trading signals. [ABSTRACT FROM AUTHOR]

The corona virus pandemic has introduced limitations which were previously not a cause for concern. Chief among them are wearing face masks in public and constraints on the physical distance between people as an effective measure to reduce the virus spread. Visual surveillance systems, which are common in urban environments and initially commissioned for security surveillance, can be re-purposed to help limit the spread of COVID-19 and prevent future pandemics. In this work, we propose a novel integration technique for real-time pose estimation and multiple human tracking in a pedestrian setting, primarily for social distancing, using CCTV camera footage. Our technique promises a sizeable increase in processing speed and improved detection in very low-resolution scenarios. Using existing surveillance systems, pedestrian pose estimation, tracking and localization for social distancing (PETL4SD) is proposed for measuring social distancing, which combines the output of multiple neural networks aided with fundamental 2D/3D vision techniques. We leverage state-of-the-art object and pose estimation algorithms, combining their strengths, for increase in speed and improvement in detections. These detections are then tracked using a bespoke version of the FASTMOT algorithm. Temporal and analogous estimation techniques are used to deal with occlusions when estimating posture. Projective geometry along with the aforementioned posture tracking is then used to localize the pedestrians. Inter-personal distances are calculated and locally inspected to detect possible violations of the social distancing rules. Furthermore, a “smart violations detector” is employed which estimates if people are together based on their current actions and eliminates false social distancing violations within groups. Finally, distances are intuitively visualized with the right perspective. All implementation is in real time and is performed on Python. Experimental results are provided to validate our proposed method quantitatively and qualitatively on public domain datasets using only a single CCTV camera feed as input. Our results show our technique to outperform the baseline in speed and accuracy in low-resolution scenarios. The code of this work will be made publicly available on GitHub at . [ABSTRACT FROM AUTHOR]

Underwater acoustic vector sensors (UAVSs) are increasingly utilized for remote passive sonar detection, but the accuracy of direction-of-arrival (DOA) estimation remains a challenging problem, particularly under low signal-to-noise ratio (SNR) conditions and complex background noise. In this paper, a comprehensive theoretical analysis is conducted on UAVS signal preprocessing subjected to gain-phase uncertainties for average acoustic intensity measurement (AAIM) and complex acoustic intensity measurement (CAIM)-based vector DOA estimation, aiming to explain the theoretical restrictions of intensity-based vector acoustic preprocessing approaches. On this basis, a generalized vector acoustic preprocessing optimization model is established in which the principle can be described as "maximizing the denoising performance under the constraints of an equivalent amplitude-gain response and phase-bias response". A novel vector acoustic preprocessing method named linear matched stochastic resonance (LMSR) is proposed within the framework of matched stochastic resonance theory, which can naturally guarantee the linear gain-phase restrictions, as well achieving effective denoising performance. Numerical analyses demonstrate the superior vector DOA estimation performance of our proposed LMSR-AAIM and LMSR-CAIM methods in comparison to classical intensity-based AAIM and CAIM methods, especially under low-SNR conditions and non-Gaussian impulsive noise circumstances. Experimental verification conducted in the South China Sea further verifies its the effectiveness for practical application. This work can lay a solid foundation to break through the challenges of underwater remote vector acoustic DOA estimation under low-SNR conditions and complex ocean ambient noise and can provide important guidance for future research work. [ABSTRACT FROM AUTHOR]

• Proposing a new type of perforated-serrated fins. • Analyzing flow and heat transfer characteristics of cryogenic helium in serrated fin and perforated-serrated fin channels. • The thermo-hydraulic performance of perforated-serrated fins is significantly improved at 20 K and 77 K. • Effects of perforated position and fin porosity on the thermo-hydraulic performance are studied. Plate-fin heat exchangers (PFHEs) with serrated fins are commonly employed in cryogenic helium systems. To further improve the heat transfer performance and compactness of PFHEs, traditional serrated fins structure is optimized and a new type of perforated-serrated fins is proposed with each serrated fin perforated. Numerical simulations considering the influence of cryogenic conditions, using well-validated 3D models, are carried out. The results show that the heat transfer performance of optimized fins is improved. Compared with traditional serrated fins, Colburn j factor of perforated-serrated fins increases by 30.61–12.61 % at 20 K and by 16.71–2.9 % at 77 K. Although the flow performance of perforated-serrated fins is somewhat inferior, overall thermo-hydraulic performance is superior, particularly at low Reynolds numbers. The JF factor of perforated-serrated fins increases by 23.75–9.34 % at 20 K and by 11.04–3.3 % at 77 K. In addition, the effects of perforated position and fin porosity on thermo-hydraulic characteristics of perforated-serrated fins are obtained. For the design below 80 K PFHEs used in cryogenic helium systems, replacing traditional serrated fins with perforated-serrated fins may be worth considering to further improve overall thermo-hydraulic performance. [ABSTRACT FROM AUTHOR]

In order to provide production safety and determine the optimal ventilation scheme in coal mining, the mines should be classified by their gas emission and mine security rank. In this paper the three models of mine classification, mine insecurity, and the optimal ventilation required by the mine are established and solved by MatLab and Lingo software. In answer to question 1, firstly, the daily absolute gas emission amount and relative gas are evaluated by average values of absolute and relative gas emission rates. It is shown that average values distribution complies with the normal distribution and fluctuation around the stable value. Finally, according to the standard requirements, the mine is classified as a high gas mine. In answer to question 2, the relationship is established between the gas concentration and the lower limit of coal dust explosion concentration, and a specific function relationship between gas concentration and coal dust explosion concentration is obtained by logarithmic fitting. The fuzzy membership function is derived, and the fuzzy statistical evaluation model is established to evaluate the mine safely. The probability safety value calculated by MatLab software is 4.63 %. In answer to question 3, firstly, according to the relationship between gas concentration, coal dust concentration and ventilation speed, the minimum air volume actually required by the coal mining face under the condition of safe production is established. Through MatLab programming calculation, the minimum air volume of coal mining face 1 and face 2 is 385.10 and 531.08 m3/min, respectively. According to the diversion of the air volume of each working zone and the specific requirements for ventilation speed in each zone, a ventilation optimization model is established and solved by Lingo software. The calculated air volume of the local ventilator and the optimal (total) air volume required by the mine are 150 and 1491.18 m3/min, respectively. Finally, through the solution and analysis of the model, it is shown that the simulation method is reasonable and can produce reliable guidance for management of high-risk coal mining enterprises. [ABSTRACT FROM AUTHOR]

Video-based convolutional neural networks (CNNs) involve a large amount of training parameters, leading to the enormous computational complexity, which thereby delays the network convergence. Therefore, training successful CNN for action recognition rapidly is non-trivial. In this paper, a novel encoding called nonlinear gated channels unit (NGCU) is proposed to facilitate network training by encoding the global channel-level relationship. Based on this, nonlinear gated channels network (NGCN) is constructed for the end-to-end encoding, and the corresponding convergence performance is evaluated on the standard benchmarks UCF101 and HMDB51. Experimental results demonstrate that the proposed method is conducive to the convergence process of CNN based action recognition models. [ABSTRACT FROM AUTHOR]

Macrophage-mediated inflammation is a key pathophysiological component of cardiovascular diseases, but the underlying mechanisms by which the macrophage regulates inflammation have been unclear. In our study, we, for the first time, showed an endogenous sulfur dioxide (SO 2) production in RAW267.4 macrophages by using HPLC and SO 2 -specific fluorescent probe assays. Moreover, the endogenous SO 2 generating enzyme aspartate aminotransferase (AAT) was found to be expressed by the macrophages. Furthermore, we showed that AAT2 knockdown triggered spontaneous macrophage-mediated inflammation, as represented by the increased TNF-α and IL-6 levels and the enhanced macrophage chemotaxis; these effects could be reversed by the treatment with a SO 2 donor. Mechanistically, AAT2 knockdown activated the NF-κB signaling pathway in macrophages, while SO 2 successfully rescued NF-κB activation. In contrast, forced AAT2 expression reversed AngII-induced NF-κB activation and subsequent macrophage inflammation. Moreover, treatment with a SO 2 donor also alleviated macrophage infiltration in AngII-treated mouse hearts. Collectively, our data suggest that macrophage-derived SO 2 is an important regulator of macrophage activation and it acts as an endogenous "on-off switch" in the control of macrophage activation. This knowledge might enable a new therapeutic strategy for cardiovascular diseases. Image 1 • Endogenous SO 2 /aspartate aminotransferase pathway is present in macrophages. • Macrophage-derived SO 2 is a novel inflammation inhibitor. • SO 2 inhibits macrophage activation via NF-κB pathway. [ABSTRACT FROM AUTHOR]

Two recent reports suggested that the less common, less virulent enterococcal species, Enterococcus gallinarum and E. casseliflavus, with low-level vancomycin resistance due to chromosomally encoded vanC1 and vanC2/3, may influence host immunity. We reported that peri-transplant gut colonization with E. gallinarum and E. casseliflavus is associated with lower mortality after allogeneic hematopoietic cell transplantation (HCT). Because most acute leukemia patients undergoing HCT have received intensive chemotherapy (usually requiring prolonged hospitalization) for their underlying disease before HCT, we hypothesized that some may have acquired vanC-positive enterococci during chemotherapy. Therefore, we evaluated the presence of the vanC gene cluster using vanC1 and vanC2/3 qPCR in thrice-weekly collected stool samples from 20 acute leukemia patients undergoing intensive chemotherapy. We found that an unexpectedly large proportion of patients have detectable vanC1 and vanC2/3 (15% and 35%, respectively) in at least one stool sample. Comparing qPCR results with 16S rRNA gene sequencing results suggested that E. gallinarum may reach high abundances, potentially persisting into HCT and influencing transplant outcomes. [ABSTRACT FROM AUTHOR]

An ion imprinting polymer (IIP) electrochemical sensors based on chitosan-graphene oxide composites polymer modified glassy carbon electrode (CS/GO-IIP) was developed for the highly sensitive and selective detection of Cu (II) by the dip coating method. The Cu (II) ion-imprinted polymers were synthesized by chemically cross-linking with epichlorohydrin after the CS/GO/Cu (II) composite dropped on the glassy carbon electrode surface. The introduction of GO can improve the electrical conductivity of the electrode and amplify the electrochemical signal. The sensor was characterized by FT-IR, EDS, SEM, AFM, Raman spectroscopy and electrochemical measurements. Under the optimized conditions, a linear dependence was observed from 0.5 to 100 μmol/L with a detection limit of 0.15 μmol/L. The detection of Cu (II) was hardly interfered by the traditional metal cations. The CS/GO-IIP sensor showed excellent reproducibility via repetitive differential pulse anodic stripping voltammetry and the RSD was 3.3%. More importantly, the performance of CS/GO-IIP sensor was verified in tap and river water samples and has an acceptable recovery rates. [ABSTRACT FROM AUTHOR]

Abstract The fraction of interphase is an important microstructure parameter in the prediction of macroscopic properties of particulate composites. Currently, some researchers have presented theoretical and numerical investigations on the interphase fraction for spherical particle systems, and even quantify the influence of interphase fraction on the overall elastic and transport properties of particulate composites. However, the overlapping interphase fraction in polydisperse non-spherical particle systems is still an open issue. In this work, a generic theoretical model is formulated to derive the overlapping interphase fraction for polydisperse 2D non-circular and 3D non-spherical particle systems by means of the statistical geometry of composites. In this model, the morphology of interphase coated onto the surface of non-spherical particles can be characterized by circularity and sphericity of particles that are important parameters to describe the shape of particles. On the other hand, numerical simulations for the one-point probability function of interphase are presented to verify the proposed theoretical framework. In the numerical simulations, a novel algorithm is developed by reducing the problem of identifying the precise location between an arbitrary spatial point and interphase to the basic issue of finding the distance from the point to the surface of particles. If the distance is less than the interphase thickness, the point definitely locates inside interphase. In addition, the algorithm can be further used to detect the overlap between adjacent ellipsoidal particles (2D ellipses). Moreover, a variety of particle shapes (such as regular polygons and ellipses with the same circularity, and regular polyhedrons and ellipsoids with the same sphericity) are taken into account to generate particle packing structures. Then, the fraction of overlapping interphase in each packing structure is statistically obtained. Results show that statistical values are consistent with their theoretical values under the same conditions. This validates the reliability of the theoretical framework. Finally, the effects of particle size distributions and interphase thicknesses on the interphase fraction are investigated. It can be found that the interphase fraction increases with the increase of particle volume fraction, particle fineness and interphase thickness. [ABSTRACT FROM AUTHOR]

Abstract Convolutional Neural Networks (CNNs) have achieved great success for action recognition. Technically, extracting effective long-range temporal dynamics is critical for such temporal tasks. This paper proposes a temporal stochastic linear encoding (TSLE) to construct the global video representations for action recognition, which can be embedded inside of CNN as a layer. The advantages of temporal stochastic linear encoding networks (TSLEN) are: (a) Compared with algorithms focusing on the short-term motions it can implement an easy yet robust manipulation of long range temporal clues. (b) We propose an arbitrarily directional motion boundary (ADMB) unit, which can save the training time and hard disk space. (c) The proposed TSLE unit maps the highly-dimensional videos to the compact spatio-temporal representations. On the efficiency and recognition accuracy experimental results demonstrate that the proposed TSLENs achieve competitive performance among the effective algorithms. Highlights • The proposed TSLE network can implement an easy yet robust manipulation of long range temporal clues. • We propose an arbitrarily directional motion boundary (ADMB) units embodied inside of the CNN, which can save the training time and hard disk space. • We train the proposed TSLE networks on the large-scale Kinetics dataset, and with the obtained model we train the models on the UCF101 and HMDB51. • The proposed TSLE networks map a highly-dimensional video to a compact spatio-temporal representation. [ABSTRACT FROM AUTHOR]

Abstract In video recognition, rank-pooling operators are a type of models for sorting video sequences, which act on either the raw inputs or the intermediate feature maps of convolutional neural network (CNN). However, such models are currently restricted in the optimization of the linear ranking function by Rank-SVM and Rank-SVR. In this paper, we first propose a CNN architecture called RGB Rank Pooling Dynamic Network (RGB-RPDN), mapping a video to multiple frame-level dynamic spaces with the same size as the input. Importantly, a classical classification (e.g. FC, CNN) advanced in 2D image can be jointly positioned behind the generated representation for action classification, thus the joint architecture can be trained in an end-to-end manner. Second, we analyze how the flow-level evolution can be modeled by the hand-crafted rank-pooling machine, and extend the dynamic space of frame-level to that of flow-level by the Flow Rank Pooling Dynamic Network (Flow-RPDN). Third, equivalence relations between hand-crafted rank-pooling and RPDN are formulated, further the comparison of computing cost are qualitatively analyzed. Finally, the frame-level and flow-level pipelines are combined to achieve the final prediction by the late fusion. Specifically, with the models pre-trained on the large-scale Kinetics dataset, we train the two-stream RPDN on the UCF101 and HMDB51, where the parameters are initialized by the pre-trained models above. Experimental results demonstrate that the RPDN significantly improves the hand-crafted rank-pooling machines by a large margin of promotion, and achieves the correct rate of more excellent classification in action recognition. [ABSTRACT FROM AUTHOR]

In the present study, we hypothesized that the rumen bacterial and archaeal communities would change significantly over the transition period of dairy cows, mainly as an adaptation to the classical use of low-grain prepartum and high-grain postpartum diets. Bacterial 16S rRNA gene amplicon sequencing of rumen samples from 10 primiparous Holstein dairy cows revealed no changes over the transition period in relative abundance of genera such as Ruminococcus, Butyrivibrio, Clostridium, Coprococcus, and Pseudobutyrivibrio. However, other dominant genus-level taxa, such as Prevotella, unclassified Ruminococcaceae, and unclassified Succinivibrionaceae, showed distinct changes in relative abundance from the prepartum to the postpartum period. Overall, we observed individual fluctuation patterns over the transition period for a range of bacterial taxa that, in some cases, were correlated with observed changes in the rumen short-chain fatty acids profile. Combined results from clone library and terminalrestriction fragment length polymorphism (T-RFLP) analyses, targeting the methyl-coenzyme M reductase a-subunit (mcrA) gene, revealed a methanogenic archaeal community dominated by the Methanobacteriales and Methanomassiliicoccales orders, particularly the genera Methanobrevibacter, Methanosphaera, and Methanomassiliicoccus. As observed for the bacterial community, the T-RFLP patterns showed significant shifts in methanogenic community composition over the transition period. Together, the composition of the rumen bacterial and archaeal communities exhibited changes in response to particularly the dietary changes of dairy cows over the transition period. [ABSTRACT FROM AUTHOR]

Highly sensitive hydrogen sulfide (H 2 S) gas sensors were developed from a semiconducting heterostructure composed of CuO microspheres whose surface was modified with CuFe 2 O 4 nanoparticles. The CuO microspheres were fabricated utilizing a simple heating route carried out in a water bath, while CuFe 2 O 4 modification of CuO was carried out by a facile two-step method. The morphology and characteristics of the samples were examined by X-ray diffraction, scanning electron microscopy, transmission electron microscopy, energy dispersive X-ray spectroscopy, and inductively coupled plasma atomic emission spectrometry. The H 2 S gas sensing properties were examined at different operating temperatures, and their dependence on molar ratio of CuFe 2 O 4 to CuO was also investigated. Results showed that the response of the optimized CuFe 2 O 4 -modified CuO heterostructures to 10 ppm H 2 S gas was approximately 20 times higher than that of the initial CuO microspheres at the optimal operating temperature (240 °C). Moreover, a fast response/recovery was also noticed, and the mechanism for enhanced sensing properties of such heterostructures was thoroughly discussed. [ABSTRACT FROM AUTHOR]

The microstructure of the interfacial transition zone (ITZ) surrounding the aggregate in a cementitious composite is quite different from that of the bulk matrix, because of its distinct physical nature including relatively high porosity and low rigidity. The thickness and volume fraction of the ITZ play a major role in determining the transport and mechanical behavior of cementitious composites. However, the ITZ thickness may be overestimated when undertaking sectional plane analysis of these composites. Analysis of Platonic particles has previously shown that the sphericity of the particle is an important parameter in determining the overestimation of the ITZ thickness, but this raises the question of whether sphericity is sufficient to uniquely characterize the influence of aggregate shape. This paper investigates the influence of particle shape on overestimation of ITZ thickness for aggregate shapes which have the same sphericity values as Platonic particles; specifically, spheroids of differing geometries. A normal line sampling algorithm, which is designed to replicate the practical experimental process used in ITZ determination, is employed to obtain the apparent ITZ thickness. The influences of particle shape, sampling method and particle size distribution are investigated in terms of the overestimation of the ITZ volume fraction, and the effective diffusivity within three-phase composites, using the differential effective medium approximation. [ABSTRACT FROM AUTHOR]

A facile method was used to prepare Pd-doped CuO nanoflowers with various doping concentrations. The samples were characterized through X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDX), inductively coupled plasma atomic emission spectrometer (ICP-AES), and Brunauer – Emmett – Teller (BET) specific surface area analysis. The responses (R g /R a or R a /R g , where R g is the resistance in gas, and R a is the resistance in air) of such sensors exposed to 50 ppm CH 4 , NO 2 , C 2 H 5 OH, H 2 S, NH 3 , and H 2 were measured for comparison. For 1.25 wt% Pd-doped CuO nanoflowers, the response (R g /R a ) to 50 ppm H 2 S was 123.4 at 80 °C, which was significantly higher than that of pure CuO (R g /R a = 15.7). Furthermore, excellent stability and repeatability of the gas sensor were also demonstrated. The observed results clearly revealed that it is an important and facile approach to detect the H 2 S at low operating temperature for practical applications. [ABSTRACT FROM AUTHOR]

Dairy cows experience dramatic changes in host physiology from gestation to lactation period and dietary switch from high-forage prepartum diet to high-concentrate postpartum diet over the transition period (parturition +/- three weeks). Understanding the community structure and activity of the rumen microbiota and its associative patterns over the transition period may provide insight for e.g. improving animal health and production. In the present study, rumen samples from ten primiparous Holstein dairy cows were collected over seven weeks spanning the transition period. Total RNA was extracted from the rumen samples and cDNA thereof was subsequently used for characterizing the metabolically active bacterial (16S rRNA transcript amplicon sequencing) and archaeal (qPCR, T-RFLP and mcrA and 16S rRNA transcript amplicon sequencing) communities. The metabolically active bacterial community was dominated by three phyla, showing significant changes in relative abundance range over the transition period: Firmicutes (from prepartum 57% to postpartum 35%), Bacteroidetes (from prepartum 22% to postpartum 18%) and Proteobacteria (from prepartum 7% to postpartum 32%). For the archaea, qPCR analysis of 16S rRNA transcript number, revealed a significant prepartum to postpartum increase in Methanobacteriales, in accordance with an observed increase (from prepartum 80% to postpartum 89%) in relative abundance of 16S rRNA transcript amplicons allocated to this order. On the other hand, a significant prepartum to postpartum decrease (from 15% to 2%) was observed in relative abundance of Methanomassiliicoccales 16S rRNA transcripts. In contrast to qPCR analysis of the 16S rRNA transcripts, quantification of mcrA transcripts revealed no change in total abundance of metabolically active methanogens over the transition period. According to T-RFLP analysis of the mcrA transcripts, two Methanobacteriales genera, Methanobrevibacter and Methanosphaera (represented by the T-RFs 39 and 267 bp), represented more than 70% of the metabolically active methanogens, showing no significant changes over the transition period; minor T-RFs, likely to represent members of the order Methanomassiliicoccales and with a relative abundance below 5% in total, decreased significantly over the transition period. In accordance with the T-RFLP analysis, the mcrA transcript amplicon sequencing revealed Methanobacteriales to cover 99% of the total reads, dominated by the genera Methanobrevibacter (75%) and Methanosphaera (24%), whereas the Methanomassiliicoccales order covered only 0.2% of the total reads. In conclusion, the present study showed that the structure of the metabolically active bacterial and archaeal rumen communities changed over the transition period, likely in response to the dramatic changes in physiology and nutritional factors like dry matter intake and feed composition. It should be noted however that for the methanogens, the observed community changes were influenced by the analyzed gene (mcrA or 16S rRNA). [ABSTRACT FROM AUTHOR]

Interfacial transition zone (ITZ) between matrix and aggregate often plays a major role in transport and mechanical behaviors of cementitious composites as its physical nature of relatively high porosity and low rigidity. However, the ITZ thickness may be overestimated via sectional plane analysis technologies, this is attributed to a random sampling plane rarely passing through the normal to the surface of aggregates. So, it is necessary to quantify the overestimation degree of the ITZ thickness. In this study, a methodology to construct the ITZ layer around ellipsoidal aggregate particles is proposed. Then, a systematic line sampling algorithm is employed to obtain the statistical mean value of the ratio of the apparent to the actual ITZ thickness. The influence of aggregate shape and particle size distribution is discussed on the overestimations of the thickness and volume fraction of the ITZ, and the effective diffusivity of three-phase composites using the differential effective medium approximation. Results show that the aggregate shape has a significant impact on the apparent ITZ thickness, which mainly reflects in the sphericity of the aggregate shape. And the ranking of the overestimation of ITZ thickness, ITZ volume fraction and diffusivity for two types of spheroidal aggregate which have the same sphericity with the specified Platonic particle follow: Platonic particle > Oblate ellipsoid > Prolate ellipsoid. Sphericity is not a unique parameter characterizing the influence of particle shape on the overestimation degree of ITZ thickness. For quantification, other shape parameter needs to be developed in the future. We hope this article will be helpful to guide the practice of evaluating the contribution of aggregate particle shape to the ITZ microstructure and the influence of the ITZ on macroscopic performance of composite materials. [ABSTRACT FROM AUTHOR]

The interfacial transition zone (ITZ) between cement paste and aggregate is the weakest part of composites. To quantify the influence of the ITZ on macro-properties of composites, the ITZ area fraction should be considered. In this paper, apparent ITZ thickness around regular polygon and ellipse is determined by using a systematic line sampling algorithm. A generalized formula is proposed to obtain ITZ area fraction of concrete with 2D convex aggregates. Overestimation of ITZ area fraction and concrete diffusivity are calculated. Our study demonstrates that aggregate shape exerts an unneglectable impact on the ITZ thickness, and further on macro-properties of composites. [ABSTRACT FROM AUTHOR]

The interfacial transition zone (ITZ) between matrix and aggregate is a weak region because of its physical nature of relatively high porosity and low rigidity. ITZ microstructural configurations such as its thickness and volume fraction play an important role in transport and mechanical behaviours of cementitious composites. However, such ITZ characteristics are usually overestimated since random sampling planes from conventional sectional plane analysis technologies rarely pass through the normal to the surface of anisotropic aggregates. In this study, we first propose a normal line sampling (NLS) algorithm to evaluate the overestimation degrees of these microstructures for complex geometrical shaped aggregates like Platonic particles. The NLS algorithm applies the sampling lines along the normal of aggregate boundary at the given section plane that is significantly different from the previous methods in the literature. Then, the ITZ volume fraction can be determined by the ITZ thickness according to a generalized formula. We also extend these practical ITZ characteristics to estimate the effective diffusivity of cementitious composites by the classical effective medium approximation. The derived results show that the ratio of the apparent ITZ thickness to the actual ITZ thickness is dependent on the sphericity which is a shape descriptor of particles. Moreover, the overestimation degree of ITZ volume fraction and diffusivity of three-phase composites are governed by aggregate volume fraction, particle size distribution and particle shape. Finally, the results reflect that the aggregate shape has a significant effect on the apparent ITZ thickness, and the sampling process of ITZ thickness by using NLS algorithm is similar to the sampling techniques in experiment. [ABSTRACT FROM AUTHOR]

The present study looks for the feasibility of preparing UHPC with iron ore tailings (IOT for short) as fine aggregate. To enhance outstanding high performances, some influences on UHPC mortars were investigated such as different kinds of sands, different mix ratio of sands, and different largest particle size of fine aggregate. The results show that IOT have negligible poorer aggregate performance than silica sands but better than river sands. The strength of UHPC reaches the highest point when silica sands were instead 60% by IOT. As the largest particle size of fine aggregate is decreasing, the strength and frost resistance of UHPC were improved, but the liquidity was decreased. Micropowder of IOT affects the strength and the optimal content was 4%. [ABSTRACT FROM AUTHOR]

Introduction: Neurogenic pulmonary edema (NPE) is an acute and serious complication after subarachnoid hemorrhage (SAH) with high mortality. The present study aimed to test the therapeutic potential of brilliant blue G (BBG), a selective P2X purinoceptor 7 (P2X7R) antagonist, on NPE in a rat SAH model. Methods: SAH was induced by endovascular perforation. 86 Sprague-Dawley rats were randomly divided into sham, vehicle-, or BBG-treatment groups. Mortality, body weight, SAH grading, neurological deficits, NPE clinical symptoms, and pulmonary index were measured at 24 hours following SAH. Western blot, gelatin zymography, lung histopathology, and immunofluorescence staining were performed in the left lung lobe to explore the underlying mechanisms at 24 hours post-surgery. Results: The incidence of clinical symptoms was correlated with pulmonary index. P2X7R and the marker of alveolar type I epithelial cells (the mucin-type glycoprotein T1-α) immunoreactivities were generally co-localized. BBG administration decreased mature interleukin-1β, myeloperoxidase, and matrix metallopeptidase-9 activation, but increased tight junction proteins, such as ZO-1 and occludin, which ameliorated pulmonary edema via anti-inflammation and improved neurological deficits. Conclusion: P2X7R inhibition prevented NPE after SAH by attenuating inflammation. Thus, BBG is a potential therapeutic application for NPE after SAH and warrants further research. [ABSTRACT FROM AUTHOR]

Abstract: Polycrystalline La0.67A0.33MnO z (A=Ca, Sr) thin films with [202] preferred orientation were synthesized on amorphous quartz substrates by means of metal organic deposition (MOD) technology. The Curie temperature (T C ) and metal−insulator transition temperature (T p ) are 172K, 247K and 227K, 335K for La0.67Ca0.33MnO z (LCMO) film and La0.67Sr0.33MnO z (LSMO) film, respectively. The hysteresis and vertical anisotropy behaviors of MR are exhibited by the films below T C , which strongly relies on the magnetization process. The magnitude of these magnetotransport properties would decline with increasing temperature. The in-plane hysteric MR behaviors could be explained by multiple-domain model. For vertical anisotropy of MR, demagnetization effect plays an important role. Especially, compared to LCMO film, LSMO film still presents the above hysteretic MR effect and vertical anisotropic MR at RT due to its higher T C . [Copyright &y& Elsevier]

We propose a content-based 3-D mosaic (CB3M) representation for long video sequences of 3-D and dynamic urban scenes captured by a camera on a mobile platform. In the first phase, a set of parallel-perspective (pushbroom) mosaics with varying viewing directions is generated to capture both the 3-D and dynamic aspects of the scene under the camera coverage. In the second phase, a segmentation-based stereo matching algorithm is applied to extract parametric representations of the color, structure and motion of the dynamic and/or 3-D objects in urban scenes, where a lot of planar surfaces exist. Multiple pairs of stereo mosaics are used for facilitating reliable stereo matching, occlusion handling, accurate 3-D reconstruction, and robust moving target detection. CB3M is a highly compressed visual representation for a dynamic 3-D scene, and has object contents of both 3-D and motion information. Experimental results are given for various real video sequences of large-scale 3-D scenes. [ABSTRACT FROM PUBLISHER]

Abstract: A theoretical study on Ru-doped rutile SnO2(110) surface has been carried out by means of periodic density functional theory (DFT) at generalized gradient approximation (GGA-RPBE) level with a periodic supercell approach. Electronic structure analysis was performed based on the band structure and partial density of states. The results provide evidence that the electronic structures of SnO2(110) surface are modified by the surface Ru dopant, in which Ru 4d orbital are located at the edge of the band gap region. It is demonstrated that molecular oxygen adsorption characteristics on stoichiometric SnO2(110) surface are changed from endothermic to exothermic due to the existence of surface Ru dopant. The dissociative adsorption of molecular oxygen on the Ru5c/SnO2(110) surface is exothermic, which indicates that Ru could act as an active site to increase the oxygen atom species on SnO2(110) surface. Our present study reveals that the Ru dopant on surface is playing both electronic and chemical role in promoting the SnO2 gas-sensing property. [Copyright &y& Elsevier]

A stereo mosaic representation has been developed for fusing imaging data captured by sensors (cameras) in motion. In addition to providing a wide field of view, the multiperspective mosaics with various oblique views represent occlusion regions that cannot be achieved by using stationary sensors. One or multiple stereo pairs can be formed from mosaics with different oblique viewing angles and thus can be used for 3D viewing and 3D reconstruction. This approach has been applied to a number of important security and surveillance applications, including airborne surveillance, ground vehicle navigation, under-vehicle inspection, and 3D gamma-ray cargo inspection. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an investigation on the effect of Yb and Nd substituents on the piezoelectric properties and vibration velocity of 0.05Pb(Mn1/3Sb2/3)O3–0.95Pb(Zr0.52Ti0.48)O3 piezoelectric ceramics. The X-ray diffraction (XRD) measurements were performed on the doped samples and the results indicate that all the Yb-doped samples exhibit a single phase of perovskite structures in tetragonal symmetry and pyrochlore phases are found in specimens with high Nd dopant. The “soft” characteristic is improved by adding small amount of Yb2O3 and the optimum properties of Yb-doped PMSZ5 ceramics are achieved at x =2mol% (d 33 =390pC/N, ɛ r =1380, K p =0.61, tan δ =0.41%, Q m =800). Meanwhile, the piezoelectric properties of all Nd2O3-doped specimens are found deteriorating. Vibration velocity at ΔT =20°C, one of the most important factors for high-power piezoelectric application, is found as high as 1100mm/s for 2mol% Yb-doped specimens, which is about 2.7 times higher than that of the conventional hard PZT ceramics. [Copyright &y& Elsevier]

Abstract: In this paper we address the problem of fusing images from many video cameras or a moving video camera. The captured images have obvious motion parallax, but they will be aligned and integrated into a few mosaics with a large field-of-view (FOV) that preserve 3D information. We have developed a compact geometric representation that can re-organize the original perspective images into a set of parallel projections with different oblique viewing angles. In addition to providing a wide field of view, mosaics with various oblique views well represent occlusion regions that cannot be seen in a usual nadir view. Stereo mosaic pairs can be formed from mosaics with different oblique viewing angles. This representation can be used as both an advanced interface for interactive 3D video and a pre-processing step for 3D reconstruction. A ray interpolation approach for generating the parallel-projection mosaics is presented, and efficient 3D scene/object rendering based on multiple parallel-projection mosaics is discussed. Several real-world examples are provided, with applications ranging from aerial video surveillance/environmental monitoring, ground mobile robot navigation, to under-vehicle inspection. [Copyright &y& Elsevier]

Abstract: This paper presents a unified approach to automatically build dynamic and multi-resolution 360° panoramic (DMP) representations from image sequences captured by hand-held cameras mainly undertaking rotation and zooming for natural scenes with moving targets. A simple (yet stable) rigid motion model and a closed-loop-based mosaicing algorithm are proposed to generate cylindrical mosaics automatically. Multi-resolution representations are built for interesting areas by separating zooming sub-sequences from a pan/zoom sequence. Moving objects are detected and separated from images based on motion information, and then more accurate contours are extracted using a modified active contour algorithm. The DMP construction method is fast, robust, and automatic, achieving five frames per second for image sequences with 384×288 color images on a Pentium III 800MHz PC. The construction of the DMP representation can be used in virtual reality, video surveillance, and very low bit-rate video coding. [Copyright &y& Elsevier]

Environmental monitoring applications require seamless registration of optical data into large area mosaics that are geographically referenced to the world frame. Using frame-by-frame image registration alone, we can obtain seamless mosaics, but it will not exhibit geographical accuracy due to frame-to-frame error accumulation. On the other hand, the 3D geo-data from GPS, a laser profiler, an INS system provides a globally correct track of the motion without error propagation. However, the inherent (absolute) errors in the instrumentation are large for seamless mosaicing. The paper describes an effective two-track method for combining two different sources of data to achieve a seamless and geo-referenced mosaic, without 3D reconstruction or complex global registration. Experiments with real airborne video images show that the proposed algorithms are practical in important environmental applications. [ABSTRACT FROM AUTHOR]

This paper presents a Fourier-based approach for automatically constructing a 3D panoramic model of a natural scene from a video sequence. The video sequences could be captured by an unstabilized camera mounted on a moving platform on a common road surface. As the input of the algorithms, “seamles” panoramic view images (PVIs) and epipolar plane images (EPIs) are generated after image stabilization if the camera is unstabilized. A novel panoramic EPI analysis method is proposed that combines the advantages of both PVIs and EPIs efficiently in three important steps: locus orientation detection in the Fourier frequency domain, motion boundary localization in the spatio-temporal domain, and occlusion/resolution recovery only at motion boundaries. The Fourier energy-based approaches in literature were usually for low-level local motion analysis and are therefore not accurate for 3D reconstruction and are also computationally expensive. Our panoramic EPI analysis approach is both accurate and efficient for 3D reconstruction. Examples of layered panoramic representations for large-scale 3D scenes from real world video sequences are given. [ABSTRACT FROM AUTHOR]

Objective. To investigate the relationship of plasma homocysteine (Hcy) level to stroke and genetic factor to elevated plasma Hcy level. Methods. The plasma Hcy level was measured by capillary electrophoresis-ultraviolet detection and the gene polymorphism of N[sup 5], N[sup 10]-methylenetetrahydrofolate reductase (MTHFR) was studied with PCR-RFLP assay in 43 patients with cortical cerebral infarction and 42 healthy controls. Results. The plasma Hcy level of the patients (19.3 ± 6. 0 µ mol/L) was markedly higher than that of the controls (13.7 ± 5.4 µ mol/L) (t = 4. 16, P < 0.001). There are 3 genotypes, C/C, C/T and T/T, about base — variation of MTHFR gene at locus 677. The plasma Hcy level of the subjects with T/T genotype was higher than that of subjects with other genotypes. However, the frequencies of each genotype and allele were not significantly different between the patients and the controls. Conclusions. The elevated plasma Hcy level is a risk factor for atherothrombotic cerebral infarction, and is related to the C→T mutation at locus 677 of MTHFR gene. [ABSTRACT FROM AUTHOR]

This study integrates hollow microneedle arrays (HMNA) with a novel jellyfish-shaped electrochemical sensor for the detection of key biomarkers, including uric acid (UA), glucose, and pH, in artificial interstitial fluid. The jellyfish-shaped sensor displayed linear responses in detecting UA and glucose via differential pulse voltammetry (DPV) and chronoamperometry, respectively. Notably, the open circuit potential (OCP) of the system showed a linear variation with pH changes, validating its pH-sensing capability. The sensor system demonstrates exceptional electrochemical responsiveness within the physiological concentration ranges of these biomarkers in simulated epidermis sensing applications. The detection linear ranges of UA, glucose, and pH were 0~0.8 mM, 0~7 mM, and 4.0~8.0, respectively. These findings highlight the potential of the HMNA-integrated jellyfish-shaped sensors in real-world epidermal applications for comprehensive disease diagnosis and health monitoring. [ABSTRACT FROM AUTHOR]

Microneedles offer minimally invasive, user-friendly, and subcutaneously accessible transdermal drug delivery and have been widely investigated as an effective transdermal delivery system. Ibuprofen is a common anti-inflammatory drug to treat chronic inflammation. It is crucial to develop microneedle patches capable of efficiently delivering ibuprofen through the skin for the effective treatment of arthritis patients requiring repeated medication. In this study, the mechanical properties of a new type of polymer microneedle were studied by finite element analysis, and the experimental results showed that the microneedle could effectively deliver drugs through the skin. In addition, a high ibuprofen-loaded microneedle patch was successfully prepared by micromolding and subjected to evaluation of its infrared spectrum morphology and dissolve degree. The morphology of microneedles was characterized by scanning electron microscopy, and the mechanical properties were assessed using a built linear stretching system. In the in-vitro diffusion cell drug release test, the microneedle released 85.2 ± 1.52% (210 ± 3.7 μg) ibuprofen in the modified Franz diffusion within 4 h, exhibiting a higher drug release compared to other drug delivery methods. This study provides a portable, safe and efficient treatment approach for arthritis patients requiring daily repeated medication. [ABSTRACT FROM AUTHOR]

The bimetallic metal–organic frameworks (MOFs), Cu/Co-MOF, was synthesized through a solvothermal method and calcined to obtain CuO/Co3O4 composites. By adjusting the molar ratio between Cu and Co ions, a composite material of CuO/Co3O4 (Cu:Co = 1:1) was developed and showed excellent sensing capabilities, and the response reached as high as 196.3 for 10 ppm H2S detection. Furthermore, the optimal operating temperature as low as 40 °C was found. In comparison with the sensors prepared by pristine CuO and pristine Co3O4, the sensor based on CuO/Co3O4 composite exhibited a significant response. Additionally, the sensor can detect H2S gas down to 300 ppb. The gas sensing mechanism is discussed in depth from the perspective of p–p heterojunction formation between the p-type CuO and p-type Co3O4. The as-prepared CuO/Co3O4 composite-based sensor is expected to find practical application in the low-power monitoring of H2S. [ABSTRACT FROM AUTHOR]

The efficacy of therapeutics for acute promyelocytic leukemia (APL) has exhibited an increase in recent years. Only a few patients experience relapse, including extramedullary relapse, and in patients with extramedullary relapse, the central nervous system (CNS) is the most common site. To date, there is no expert consensus or clinical guidelines available for CNS relapse, at least to the best of our knowledge. The optimal therapeutic strategy and management options for these patients remain unclear. The present study reports the treatment of a patient with APL with multiple isolated relapses in the CNS. In addition, through a mini-review of the literature, the present study provides a summary of various reports of this disease and discusses possible treatment options for these patients. [ABSTRACT FROM AUTHOR]

Remote passive sonar detection with low-frequency band spectral lines has attracted much attention, while complex low-frequency non-Gaussian impulsive noisy environments would strongly affect the detection performance. This is a challenging problem in weak signal detection, especially for the high false alarm rate caused by heavy-tailed impulsive noise. In this paper, a novel matched stochastic resonance (MSR)-based weak signal detection model is established, and two MSR-based detectors named MSR-PED and MSR-PSNR are proposed based on a theoretical analysis of the MSR output response. Comprehensive detection performance analyses in both Gasussian and non-Gaussian impulsive noise conditions are presented, which revealed the superior performance of our proposed detector under non-Gasussian impulsive noise. Numerical analysis and application verification have revealed the superior detection performance with the proposed MSR-PSNR detector compared with energy-based detection methods, which can break through the high false alarm rate problem caused by heavy-tailed impulsive noise. For a typical non-Gasussian impulsive noise assumption with α = 1.5 , the proposed MSR-PED and MSR-PSNR can achieve approximately 16 dB and 22 dB improvements, respectively, in the detection performance compared to the classical PED method. For stronger, non-Gaussian impulsive noise conditions corresponding to α = 1 , the improvement in detection performance can be more significant. Our proposed MSR-PSNR methods can overcome the challenging problem of a high false alarm rate caused by heavy-tailed impulsive noise. This work can lay a solid foundation for breaking through the challenges of underwater passive sonar detection under non-Gaussian impulsive background noise, and can provide important guidance for future research work. [ABSTRACT FROM AUTHOR]

Visual impairment-related disabilities have become increasingly pervasive. Current reports estimate a total of 36 million persons with blindness and 217 million persons with moderate to severe visual impairment worldwide. Assistive technologies (AT), including text-to-speech software, navigational/spatial guides, and object recognition tools have the capacity to improve the lives of people with blindness and low vision. However, access to such AT is constrained by high costs and implementation barriers. More recently, expansive growth in mobile computing has enabled many technologies to be translated into mobile applications. As a result, a marketplace of accessibility apps has become available, yet no framework exists to facilitate navigation of this voluminous space. We developed the BLV (Blind and Low Vision) App Arcade: a fun, engaging, and searchable curated repository of app AT broken down into 11 categories spanning a wide variety of themes from entertainment to navigation. Additionally, a standardized evaluation metric was formalized to assess each app in five key dimensions: reputability, privacy, data sharing, effectiveness, and ease of use/accessibility. In this paper, we describe the methodological approaches, considerations, and metrics used to find, store and score mobile applications. The development of a comprehensive and standardized database of apps with a scoring rubric has the potential to increase access to reputable tools for the visually impaired community, especially for those in low- and middle-income demographics, who may have access to mobile devices but otherwise have limited access to more expensive technologies or services. A wide array of assistive mobile applications now serve as low cost, convenient, and effective alternatives to standard tools in the rehabilitation domain. Given an extensive (and growing) marketplace of assistive apps, we highlight the importance of developing standardized evaluation frameworks that serve to assess the merit, functionality, and accessibility of tools in respective rehabilitation fields. To provide an introduction to a novel resource accessible to the public to exhibit verified and reliable assistive apps for the visually impaired community, especially for those in low- and middle-income demographics who may not have access to common technologies and services. [ABSTRACT FROM AUTHOR]

A microstructure-guided diffusivity model of cement paste is devised to explore the dependence of the relative diffusivity on the microstructure evolutions of cement paste from fresh state via non-spherical cement particles hydration to hardened state. The microstructure-guided diffusivity model contains three main components: (1) the microstructure of fresh cement paste is generated to simulate the initial state of non-spherical cement particles in water; (2) a continuum-based hydration model of non-spherical cement particles (HYD-NSP) is proposed to describe the evolutions of various phases (hydration products and pores) from fresh state to hardened state; (3) a random walk model is implemented to the microstructures of hydrated cement paste digitalized at the resolution of 0.1 μm/voxel for the determination of relative diffusivity of cement paste. Although this study takes five kinds of Platonic particles and sphere as an introductory example, this microstructure-guided model is readily applicable to other complex microstructures induced by the hydration of non-spherical cement particles. Finally, we utilize the framework to evaluate the influence of the geometrical shape of cement particles on the hydrated microstructure and relative diffusivity of cement paste. Results shed light on that the relative diffusivity increases with the increase of sphericity as a shape descriptor of cement particle. This is due to the specific surface area decreasing with the increase of sphericity, resulting in less hydration products and more porosity, which ultimately increases the relative diffusivity. • Microstructure of fresh cement paste with non-spherical particles is generated. • A continuous-based hydration model of non-spherical cement particles is proposed. • Evolutions of hydration products and pores in hydrated cement paste are described. • A microstructure-guided diffusivity model of cement paste is devised. • Effect of cement shape on the hydrated microstructure and diffusivity is studied. [ABSTRACT FROM AUTHOR]

Focuses on an integrated omnidirectional view image analysis, to understand the outdoor road scene by a mobile robot, while highlighting a set of adaptive backpropagation networks. How the classification was performed; Analysis of internal representations of the networks; Information on the omni-view imaging sensor.

• CuO/CuFe 2 O 4 core-shell heterostructures were used to detect hydrogen sulfide. • At low operating temperatures, copper sulfide is irreversibly formed. • The material's conductivity is sharply increased by percolation. • Copper ferrite decoration delays percolation to higher gas concentrations. • The concentration range is relevant for human safety towards hydrogen sulfide. Toxic and corrosive H 2 S gas is detected using chemoresistive sensors based on CuO/CuFe 2 O 4 core-shell heterostructures, which are characterized by DC resistance measurements, scanning electron microscopy and energy-dispersive X-ray spectroscopy. Exposure to various test gases (CO, H 2 , NO 2 , VOCs) reveals low responses. However, unique reactivity towards H 2 S at low operating temperatures leads to accumulation of CuS clusters on the surface, which can connect to create a percolation path of high electric conductance. The core-shell heterostructures differ in their response to H 2 S, as the materials' shell (CuFe 2 O 4) partly converts incoming H 2 S to its combustion products, effectively reducing the amount of H 2 S reaching the core structures. This behavior was observed for both pulsed and continuous exposure to H 2 S, making it an inherent property of the examined core-shell heterostructures. SEM images and EDX spectra reveal that the phase transition with subsequent regeneration have a strong impact on the morphology of the functional layer. [ABSTRACT FROM AUTHOR]

Phototube can capture and transmit external illumination with high frequency into photocurrent in the nonlinear circuit, which can be tamed to produce the main dynamical properties of biological neurons. In fact, the involvement of functional electronic components can enhance the biophysical function of artificial neural circuits. In this paper, a photocell is connected to FitzHugh-Nagumo neural circuits, which can be excited by the photocurrent generated from the photocell. Furthermore, a memristor is proposed to couple two light-dependent neural circuits and the synchronization stability is investigated on the coupled dynamical systems by using standard scale transformation on the physical variables and parameters. It is found that phase synchronization and complete synchronization can be obtained by regulating the coupling channel connected by the memristor. The propagation and pumping of field energy are also calculated to predict the occurrence of synchronization. [ABSTRACT FROM AUTHOR]

As the soul of cement-based materials, hydration is a complex process involving many chemical reactions, which is one of the intrinsic driving forces for the evolution of the microstructure and macroscopic properties of cementitious composites. The predominant lines of previous researches on cement hydration models are dominated by spherical particles. However, the actual shape of cement grains is non-spherical. Herein, a continuous-based hydration model of non-spherical cement particles (HYD-NSP) is developed, in which the hydration kinetics strongly depend on the morphological features of cement grains. Subsequently, the proposed HYD-NSP model is validated by experimental results. By applying the HYD-NSP model, we further investigate the evolution of microstructures of cement paste including icosahedron-shaped cement grains over time. Results reveal that the influence of the shape of cement particles on the degree of hydration and the porosity of cement paste is mainly reflected by their specific surface area. Image 1 • A continuous-based hydration model of non-spherical cement particles is developed. • Hydration kinetics strongly depend on the morphological features of cement grains. • The proposed theoretical model is validated by experimental results. • The evolution of microstructures of cement paste is investigated by this model. [ABSTRACT FROM AUTHOR]

Superfluid helium has been used for cooling superconducting magnets in nuclear fusion and high energy physics. This paper presents a simplified final stage process of 1.8 K superfluid helium cryogenic system and its key component sub-atmospheric heat exchanger. Influence of variable thermal parameters of sub-atmospheric heat exchanger on the system performance is studied. The application of sub-atmospheric heat exchanger can increase refrigerating capacity by 61.34% under given conditions. The helically finned-tube heat exchanger (HFHE) is selected, and three-dimensional steady-state numerical simulations of flow and heat transfer performance have been carried out. Nu and f of tube side are 4.5-6 times higher and 95-97% lower than those of shell side, respectively. It is found that HFHE with low fin height and HFHE with filler (nylon rope) have better comprehensive heat transfer and flow performance, and PEC can reach 1.65 and 1.41 respectively under given conditions. [ABSTRACT FROM AUTHOR]