Electronic transfer from aluminum into the core of gold nanoparticles capped with conjugated 2-naphthalenethiol

The electronic contact between a bulk metal and metal nanoparticles can be significantly different from that between two bulk metals due to the unique electronic structure in the nanometer size. In this work, the electronic contact between Au nanoparticles and Al is studied by X-ray photoelectron spectroscopy. Al is deposited on a layer of Au nanoparticles capped with conjugated 2-naphthalenethiol (Au-2NT NPs) in high vacuum by e-beam deposition at room temperature. The Au 4f X-ray photoelectron spectrum (XPS) significantly changes after the Al deposition. New XPS bands with higher binding energy appear. The angle dependence of the Au 4f XPS bands indicates that the electron transfer takes place at the contact between Al and Au-2NT NPs. In contrast, the Al deposition hardly changes the Au 4f XPS spectrum for Au nanoparticles capped with saturated 1-dodecanethiol. The effect of the Al deposition on the Au 4f XPS spectrum of Au nanoparticles capped with 2-naphthalenethiol is attributed to the electron transfer from Al through the conjugated 2-naphthalenehiol into the core of Au nanoparticles, as the Fermi energy of Al is higher than Au. This understanding on the contact between metal and metal nanoparticles provides guidance for the development of novel electronic devices.     

An online Bayesian filtering framework for Gaussian process regression: Application to global surface temperature analysis

Over the past centuries, global warming has gradually become one of the most significant issues in our life. Hence, it is crucial to analyze global surface temperature with an efficient and accurate model. Gaussian process (GP) is a popular nonparametric model, due to the power of Bayesian inference framework. However, the performance of GP is often deteriorated for large-scale data sets such as global surface temperature. In this work, we propose a novel online Bayesian filtering framework for large-scale GP regression. There are three contributions. Firstly, we develop a novel GP-based state space model to efficiently process data in a sequential manner. Secondly, based on our state space model, we design a marginalized particle filter to infer the latent function values and learn the model parameters online. It can efficiently reduce the computation burden of GP while improving the estimation accuracy in a recursive Bayesian inference framework. Finally, we successfully apply our approach to a number of synthetic data sets and the large-scale global surface temperature data set. The results show that our approach outperforms related GP variants, and it is an efficient and accurate expert system for global surface temperature analysis.     

An eye detection method robust to eyeglasses for mobile iris recognition

Finding the accurate position of an eye is crucial for mobile iris recognition system in order to extract the iris region quickly and correctly. Unfortunately, this is very difficult to accomplish when a person is wearing eyeglasses because of the interference from the eyeglasses. This paper proposes an eye detection method that is robust to eyeglass interference in mobile environment. The proposed method comprises two stages: eye candidate generation and eye validation. In the eye candidate generation stage, multi-scale window masks consisting of 2 × 3 subblocks are used to generate all image blocks possibly containing an eye image. In the ensuing eye validation stage, two methods are employed to determine which blocks actually contain true eye images and locate their precise positions as well: the first method searches for the glint of an NIR illuminator on the pupil region. If this first method fails, the next method computes the intensity difference between the assumed pupil and its surrounding region using multi-scale 3 × 3 window masks. Experimental results show that the proposed method detects the eye position more accurately and quickly than competing methods in the presence of interference from eyeglass frames.     

Metabolomics reveal that amino acids are the main contributors to antioxidant activity in wheat and rice gochujangs (Korean fermented red pepper paste)

Metabolite profiling of gochujangs (Korean fermented red pepper paste) produced from different kinds of raw materials (WG, wheat gochujang; RG, rice gochujang) was performed using gas chromatography time-of-flight mass spectrometry (GC–TOF-MS) and ultra-performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-Q-TOF-MS). Using principal component analysis (PCA), gochujang samples were differentiated based on the differences in starchy source and secondary materials used in their production. The content of amino acids and sugars was higher in WG, whereas the content of flavonoids, soyasaponins, and γ-aminobutyric acid (GABA) was higher in RG. The content of flavonoids and soyasaponins was related to the higher soybean koji content of RG. The level of antioxidant activity in WG was higher than that in RG and showed a strong positive correlation with amino acid content and a negative correlation with flavonoid content. Although the Trolox equivalent antioxidant capacity of flavonoids was only 10-fold higher than that of amino acids in an antioxidant activity assay, the total amino acid content was as much as several hundred fold higher than total flavonoid content in gochujang. This result suggests that the amino acids could be a main contributor to the antioxidant capacity in gochujang.     

Fabrication and operation of a 6 kWe class interconnector-type anode-supported tubular solid oxide fuel cell stack

A 6 kW class interconnector-type anode-supported tubular solid oxide fuel cell (ICT SOFC) stack is fabricated and operated in this study. An optimized current-collection method, which the method for current collection at the cathode using the winding method and is the method for the connection between cells using interconnect, is suggested to enhance the performance of the fabricated cell. That method can increase the current collection area because of usage of winding method for cell and make the connection between cells easy. The performance of a single cell with an effective electrode area of 205 cm² exhibits 51 W at 750 °C and 0.7 V. To assemble a 1 kW class stack, the prepared ICT SOFC cells are connected in series to 20 cells connected in parallel (20 cells in series × two in parallel, 20S2P). Four modules are assembled for a 6 kWe class stack. For one module, the prepared ICT SOFC cells are connected in series to 48 cells, in which one unit bundle consists of two cells connected in parallel. The performance of the stack in 3% humidified H₂ and air at 750 °C exhibits the maximum electrical power of 7425 W.     

Next viewing directions for the scanning of dental impressions

This paper proposes a scanning procedure for a structured light system (SLS) to measure dental impressions. Although increasing the number of scanning orientations may improve the quality of a scanned model, it is desirable to minimize the number of scanning operations to time and data storage. We attempt to reduce the number of scanning operations to the least number that will still acquire a complete model. The proposed procedure must resolve two sub-problems: (1) identification of missing areas from given range images, and (2) determination of the next viewing directions to fill those missing areas. If we consider range images as triangular meshes, the sub-problems can be solved by using well-known geometric algorithms. The triangular meshes, however, may consist of tens of millions of triangles, which require an unacceptably long time to compute. To cope with this problem, we propose two key ideas: (1) utilizing an inherent attribute of a range image, the map structure; (2) utilizing a graphics board to accelerate the evaluation of visibility. Our demonstration proves that the proposed approach improves the quality of scanned models and reduces the number of scanning operations.     

Bayes classifiers for imbalanced traffic accidents datasets

Traffic accidents data sets are usually imbalanced, where the number of instances classified under the killed or severe injuries class (minority) is much lower than those classified under the slight injuries class (majority). This, however, supposes a challenging problem for classification algorithms and may cause obtaining a model that well cover the slight injuries instances whereas the killed or severe injuries instances are misclassified frequently. Based on traffic accidents data collected on urban and suburban roads in Jordan for three years (2009–2011); three different data balancing techniques were used: under-sampling which removes some instances of the majority class, oversampling which creates new instances of the minority class and a mix technique that combines both. In addition, different Bayes classifiers were compared for the different imbalanced and balanced data sets: Averaged One-Dependence Estimators, Weightily Average One-Dependence Estimators, and Bayesian networks in order to identify factors that affect the severity of an accident. The results indicated that using the balanced data sets, especially those created using oversampling techniques, with Bayesian networks improved classifying a traffic accident according to its severity and reduced the misclassification of killed and severe injuries instances. On the other hand, the following variables were found to contribute to the occurrence of a killed causality or a severe injury in a traffic accident: number of vehicles involved, accident pattern, number of directions, accident type, lighting, surface condition, and speed limit. This work, to the knowledge of the authors, is the first that aims at analyzing historical data records for traffic accidents occurring in Jordan and the first to apply balancing techniques to analyze injury severity of traffic accidents.     

High yield strength bulk Ti based bimodal ultrafine eutectic composites with enhanced plasticity

Ti-based bulk metallic glass (BMGs) and their bimodal composites are linked with the pronounced strain hardening after yielding but with much low value of strength. Therefore, developing Ti-based alloys with high yield strength and high plasticity is the current challenge. Here, we report the synthesis of ultra-fine grained bulk (UFG) (Ti_0.705Fe_0.295)_100−xGa_x (0 ⩽ x ⩽ 2) bimodal eutectic composites with not only high strength and larger plasticity but also with high yield strength which is one of the important mechanical property for structural application. Reasonably high strength, high yield strength, strain to failure ratio, and enhanced plasticity of ∼7 ± 0.8% was observed in (Ti_70.5Fe_29.5)₉₈Ga₂ composite which is superior than Ti-based BMGs and bimodal composites. Modification of degree of eutectic structure refinement and volume fraction of constituent phases with the addition of Ga are the crucial factors in enhancing the mechanical properties of Ti–Fi–(Ga) composites.     

Optimized ellipsoid algorithm for LMI feasibility problems

Ellipsoid algorithm with deepest-cut method is presented for LMI(Linear Matrix Inequality) feasibility problems. The proposed algorithm removes more than half of the previous step’s ellipsoid to obtain faster convergence than the original ellipsoid method. The cutting-direction is also optimized to maximize the volume reduction ratio at each step.     

Electrical conduction mechanisms of CdTe quantum dots/p-si heterojunction

CdTe quantum dots (QDs) are prepared on p-Si substrates using thermal evaporation technique. Current–voltage (I–V) characteristics of Au/CdTe QDs/p-Si/Al heterojunction are measured in a temperature range 304–368 K. The results show that the device has a rectification behavior with a rectification ratio being 275 at ±1.5 V. We determine the electrical conduction mechanisms of the heterojunction. At forward voltages V<0.3 V, the thermionic emission becomes the main mechanism, where in this voltage range, it is possible to estimate the barrier height and the ideality factor. At a forward voltage range 0.5<V<0.9 V, the conduction mechanism turns into the space charge limited conduction which is dominated by an exponential trap distribution (TSCLC). Within this voltage range 0.5<V <0.9, the total density of the trap states is calculated. At forward voltages 0.95<V<1.5 V, Poole-Frenkel conduction mechanism fits well with the experimental data. It is found that there are two trap levels with zero fields of the activation energy which have values 0.16 and 0.46 eV. At the reverse applied voltages, it is also found that the main source of the reverse current is the generation-recombination through p-Si rather than through the interface of the thin film itself.