Search Results (7)

The reduction of urban congestion represents one of the main challenges for increasing sustainability. This implies the necessity to increase our knowledge of urban mobility and traffic. The fundamental diagram (FD) is a possible tool for analyzing the traffic conditions on an urban road link. FD is commonly associated with the links of a transport network, but it has recently been extended to the whole transport network and named the network macroscopic fundamental diagram (NMFD). When used at the link or network level, the FD is important for supporting the simulation, design, planning, and control of the transport system. Recently, floating car data (FCD), which are based on vehicles’ trajectories using GPS, are able to provide the trajectories of a number of vehicles circulating on the network. The objective of this paper is to integrate FCD with traffic data obtained from traditional loop-detector technology for building FDs. Its research contribution concerns the proposal of a methodology for the extraction of speed data from taxi FCD, corresponding to a specific link section, and the calibration of FDs from FCD and loop detector data. The methodology has been applied to a real case in the city of Santander. The first results presented are encouraging, supporting the paper’s thesis that FCD can be integrated with data obtained from loop detectors to build FD. Full article

In nanofluidics, surface control is a critical technology because nanospaces are surface-governed spaces as a consequence of their extremely high surface-to-volume ratio. Various surface patterning methods have been developed, including patterning on an open substrate and patterning using a liquid modifier in microchannels. However, the surface patterning of a closed nanochannel is difficult. In addition, the surface evaluation of closed nanochannels is difficult because of a lack of appropriate experimental tools. In this study, we verified the surface patterning of a closed nanochannel by vacuum ultraviolet (VUV) light and evaluated the surface using streaming-current measurements. First, the C₁₈ modification of closed nanochannels was confirmed by Laplace pressure measurements. In addition, no streaming-current signal was detected for the C₁₈-modified surface, confirming the successful modification of the nanochannel surface with C₁₈ groups. The C₁₈ groups were subsequently decomposed by VUV light, and the nanochannel surface became hydrophilic because of the presence of silanol groups. In streaming-current measurements, the current signals increased in amplitude with increasing VUV light irradiation time, indicating the decomposition of the C₁₈ groups on the closed nanochannel surfaces. Finally, hydrophilic/hydrophobic patterning by VUV light was performed in a nanochannel. Capillary filling experiments confirmed the presence of a hydrophilic/hydrophobic interface. Therefore, VUV patterning in a closed nanochannel was demonstrated, and the surface of a closed nanochannel was successfully evaluated using streaming-current measurements. Full article

In microfluidics, especially in nanofluidics, nanochannels with functionalized surfaces have recently attracted attention for use as a new tool for the investigation of chemical reaction fields. Molecules handled in the reaction field can reach the single–molecule level due to the small size of the nanochannel. In such surroundings, contamination of the channel surface should be removed at the single–molecule level. In this study, it was assumed that metal materials could contaminate the nanochannels during the fabrication processes; therefore, we aimed to develop metal-free fabrication processes. Fused silica channels 1000 nm-deep were conventionally fabricated using a chromium mask. Instead of chromium, electron beam resists more than 1000 nm thick were used and the lithography conditions were optimized. From the results of optimization, channels with 1000 nm scale width and depth were fabricated on fused silica substrates without the use of a chromium mask. In nanofluidic experiments, an oxidation reaction was observed in a device fabricated by conventional fabrication processes using a chromium mask. It was found that Cr⁶⁺ remained on the channel surfaces and reacted with chemicals in the liquid phase in the extended nanochannels; this effect occurred at least to the micromolar level. In contrast, the device fabricated with metal-free processes was free of artifacts induced by the presence of chromium. The developed fabrication processes and results of this study will be a significant contribution to the fundamental technologies employed in the fields of microfluidics and nanofluidics. Full article

In many types of music, percussion plays an essential role to establish the rhythm and the groove of the music. Algorithms that can decompose the percussive signal into its constituent components would therefore be very useful, as they would enable many analytical and creative applications. This paper describes a method for the unsupervised decomposition of percussive recordings, building on the non-negative matrix factor deconvolution (NMFD) algorithm. Given a percussive music recording, NMFD discovers a dictionary of time-varying spectral templates and corresponding activation functions, representing its constituent sounds and their positions in the mix. We observe, however, that the activation functions discovered using NMFD do not show the expected impulse-like behavior for percussive instruments. We therefore enforce this behavior by specifying that the activations should take on binary values: either an instrument is hit, or it is not. To this end, we rewrite the activations as the output of a sigmoidal function, multiplied with a per-component amplitude factor. We furthermore define a regularization term that biases the decomposition to solutions with saturated activations, leading to the desired binary behavior. We evaluate several optimization strategies and techniques that are designed to avoid poor local minima. We show that incentivizing the activations to be binary indeed leads to the desired impulse-like behavior, and that the resulting components are better separated, leading to more interpretable decompositions. Full article

Nanofluidic devices have offered us fascinating analytical platforms for chemical and bioanalysis by exploiting unique properties of liquids and molecules confined in nanospaces. The increasing interests in nanofluidic analytical devices have triggered the development of new robust and sensitive detection techniques, especially label-free ones. IR absorption spectroscopy is one of the most powerful biochemical analysis methods for identification and quantitative measurement of chemical species in the label-free and non-invasive fashion. However, the low sensitivity and the difficulties in fabrication of IR-compatible nanofluidic devices are major obstacles that restrict the applications of IR spectroscopy in nanofluidics. Here, we realized the bonding of CaF₂ and SiO₂ at room temperature and demonstrated an IR-compatible nanofluidic device that allowed the IR spectroscopy in a wide range of mid-IR regime. We also performed the integration of metal-insulator-metal perfect absorber metamaterials into nanofluidic devices for plasmon-enhanced infrared absorption spectroscopy with ultrahigh sensitivity. This study also shows a proof-of-concept of the multi-band absorber by combining different types of nanostructures. The results indicate the potential of implementing metamaterials in tracking several characteristic molecular vibrational modes simultaneously, making it possible to identify molecular species in mixture or complex biological entities. Full article

Nanofluidics, a discipline of science and engineering of fluids confined to structures at the 1–1000 nm scale, has experienced significant growth over the past decade. Nanofluidics have offered fascinating platforms for chemical and biological analyses by exploiting the unique characteristics of liquids and molecules confined in nanospaces; however, the difficulty to detect molecules in extremely small spaces hampers the practical applications of nanofluidic devices. Laser-induced fluorescence microscopy with single-molecule sensitivity has been so far a major detection method in nanofluidics, but issues arising from labeling and photobleaching limit its application. Recently, numerous label-free detection methods have been developed to identify and determine the number of molecules, as well as provide chemical, conformational, and kinetic information of molecules. This review focuses on label-free detection techniques designed for nanofluidics; these techniques are divided into two groups: optical and electrical/electrochemical detection methods. In this review, we discuss on the developed nanofluidic device architectures, elucidate the mechanisms by which the utilization of nanofluidics in manipulating molecules and controlling light–matter interactions enhances the capabilities of biological and chemical analyses, and highlight new research directions in the field of detections in nanofluidics. Full article

Semi-Nonnegative Matrix Factorization (Semi-NMF), as a variant of NMF, inherits the merit of parts-based representation of NMF and possesses the ability to process mixed sign data, which has attracted extensive attention. However, standard Semi-NMF still suffers from the following limitations. First of all, Semi-NMF fits data in a Euclidean space, which ignores the geometrical structure in the data. What’s more, Semi-NMF does not incorporate the discriminative information in the learned subspace. Last but not least, the learned basis in Semi-NMF is unnecessarily part based because there are no explicit constraints to ensure that the representation is part based. To settle these issues, in this paper, we propose a novel Semi-NMF algorithm, called Group sparsity and Graph regularized Semi-Nonnegative Matrix Factorization with Discriminability (GGSemi-NMFD) to overcome the aforementioned problems. GGSemi-NMFD adds the graph regularization term in Semi-NMF, which can well preserve the local geometrical information of the data space. To obtain the discriminative information, approximation orthogonal constraints are added in the learned subspace. In addition, ${\ell }_{21}$ norm constraints are adopted for the basis matrix, which can encourage the basis matrix to be row sparse. Experimental results in six datasets demonstrate the effectiveness of the proposed algorithms. Full article