Automated mixed traffic vehicle control and scheduling study

The operation and the expected performance of a proposed automatic guideway transit system which uses low speed automated mixed traffic vehicles (AMTVs) were analyzed. Vehicle scheduling and headway control policies were evaluated with a transit system simulation model. The effect of mixed traffic interference on the average vehicle speed was examined with a vehicle pedestrian interface model. Control parameters regulating vehicle speed were evaluated for safe stopping and passenger comfort. Some preliminary data on the cost and operation of an experimental AMTV system are included. These data were the result of a separate task conducted at JPL, and were included as background information

Let’s makan!: Savoring Singapore’s culinary heritage in hotel restaurants

Eating is a national pastime in Singapore and food features strongly in many aspects of the city-state’s social and cultural landscape. Culinaria and gastronomy can be significant features of a destination and they allow tourists to experience local cultures, heritage and lifestyles. Street (hawker) food in Singapore offers a unique opportunity for visitors to sample popular local dishes conveniently and economically, whilst experiencing a vibrant taste of the colloquial way of life through eating and socializing with the locals. Many hotels in Singapore also commonly feature local signature dishes in their menu and foodservice outlets. This study aims to explore the role of street (hawker) food and local cuisine as a tourism and cultural resource within the Asian hospitality context. It investigates the phenomenon of Asian street food and traditional cuisines served in international chain hotels, specifically from a hotel and destination branding perspective, with a particular example of Singapore as a tourist destination. Keywords: Street Food, Asian Cuisine, Hotel Restaurants, Food Heritage, Brand Identit

Technical Note: Community of bacteria attached on the PVDF MF membrane surface fouled from drinking water treatment, in Seoul, Korea

Alpha, beta, and gamma proteobacteria comprise approximately 68, 16, and 7% of all identified bacteria. In this study, bacterial communities that had fouled polyvinylidene fluoride microfiltration membranes, which are used for drinking water treatment, over an 18 month period were analyzed using the 16s rRNA gene clone library method. The alpha, beta, and gamma proteobacteria were composed of mainly Bradyrhizobium and Rhodopseudomonas, Ralstonia, and Legionella, respectively. The presence of a relatively high amount of alpha proteobacteria was due to the oligotrophic condition of the drinking water source, the Han River, tested in this specific case study. The second most prominent bacteria community was the beta proteobacteria, which are typically found in a freshwater environment. This finding supports the notion that the drinking water source was relatively clean. Analyses of the organic foulants indicated that they were most likely from extra cellular polymers and/or cell fractured chemicals from bacteria or micro-organisms, as identified using organic characterizing tools, including 3-D fluorescence excitation-emission matrix and Fourier transform IR analyses.clos

Using Growing Self-Organising Maps to Improve the Binning Process in Environmental Whole-Genome Shotgun Sequencing

Metagenomic projects using whole-genome shotgun (WGS) sequencing produces many unassembled DNA sequences and small contigs. The step of clustering these sequences, based on biological and molecular features, is called binning. A reported strategy for binning that combines oligonucleotide frequency and self-organising maps (SOM) shows high potential. We improve this strategy by identifying suitable training features, implementing a better clustering algorithm, and defining quantitative measures for assessing results. We investigated the suitability of each of di-, tri-, tetra-, and pentanucleotide frequencies. The results show that dinucleotide frequency is not a sufficiently strong signature for binning 10 kb long DNA sequences, compared to the other three. Furthermore, we observed that increased order of oligonucleotide frequency may deteriorate the assignment result in some cases, which indicates the possible existence of optimal species-specific oligonucleotide frequency. We replaced SOM with growing self-organising map (GSOM) where comparable results are obtained while gaining 7%–15% speed improvement

Binning sequences using very sparse labels within a metagenome

<p>Abstract</p> <p>Background</p> <p>In metagenomic studies, a process called binning is necessary to assign contigs that belong to multiple species to their respective phylogenetic groups. Most of the current methods of binning, such as BLAST, <it>k</it>-mer and PhyloPythia, involve assigning sequence fragments by comparing sequence similarity or sequence composition with already-sequenced genomes that are still far from comprehensive. We propose a semi-supervised seeding method for binning that does not depend on knowledge of completed genomes. Instead, it extracts the flanking sequences of highly conserved 16S rRNA from the metagenome and uses them as seeds (labels) to assign other reads based on their compositional similarity.</p> <p>Results</p> <p>The proposed seeding method is implemented on an unsupervised Growing Self-Organising Map (GSOM), and called Seeded GSOM (S-GSOM). We compared it with four well-known semi-supervised learning methods in a preliminary test, separating random-length prokaryotic sequence fragments sampled from the NCBI genome database. We identified the flanking sequences of the highly conserved 16S rRNA as suitable seeds that could be used to group the sequence fragments according to their species. S-GSOM showed superior performance compared to the semi-supervised methods tested. Additionally, S-GSOM may also be used to visually identify some species that do not have seeds.</p> <p>The proposed method was then applied to simulated metagenomic datasets using two different confidence threshold settings and compared with PhyloPythia, <it>k</it>-mer and BLAST. At the reference taxonomic level Order, S-GSOM outperformed all <it>k</it>-mer and BLAST results and showed comparable results with PhyloPythia for each of the corresponding confidence settings, where S-GSOM performed better than PhyloPythia in the ≥ 10 reads datasets and comparable in the ≥ 8 kb benchmark tests.</p> <p>Conclusion</p> <p>In the task of binning using semi-supervised learning methods, results indicate S-GSOM to be the best of the methods tested. Most importantly, the proposed method does not require knowledge from known genomes and uses only very few labels (one per species is sufficient in most cases), which are extracted from the metagenome itself. These advantages make it a very attractive binning method. S-GSOM outperformed the binning methods that depend on already-sequenced genomes, and compares well to the current most advanced binning method, PhyloPythia.</p

Optimization of sub-critical water extraction (SWE) of lipid and eicosapentaenoic acid (EPA) from Nannochloropsis gaditana

Microalgae are a promising source of omega-3. The purpose of this study was to extract lipid with a relatively high content of eicosapentaenoic acid (EPA) from Nannochloropsis gaditana using subcritical water extraction (SWE). The effects of different temperatures (156.1-273.9°C), extraction times (6.6-23.4 minutes), and biomass loadings (33-117 g algae/L) on the extraction yield were studied. From the optimization study using central composite design (CCD), quadratic models generated for lipid yield and EPA composition were considered to be significant models (p < 0.05). The predictive equations were also formed for lipid yield and EPA composition. The predicted optimum lipid yield and EPA composition at 236.54°C, 13.95 minutes, and 60.50 g algae/L were 18.278 wt% of total biomass and 14.036 wt% of total fatty acid methyl ester (FAME), respectively

Lensed CMB power spectra from all-sky correlation functions

Weak lensing of the CMB changes the unlensed temperature anisotropy and polarization power spectra. Accounting for the lensing effect will be crucial to obtain accurate parameter constraints from sensitive CMB observations. Methods for computing the lensed power spectra using a low-order perturbative expansion are not good enough for percent-level accuracy. Non-perturbative flat-sky methods are more accurate, but curvature effects change the spectra at the 0.3-1% level. We describe a new, accurate and fast, full-sky correlation-function method for computing the lensing effect on CMB power spectra to better than 0.1% at l<2500 (within the approximation that the lensing potential is linear and Gaussian). We also discuss the effect of non-linear evolution of the gravitational potential on the lensed power spectra. Our fast numerical code is publicly available.Comment: 16 pages, 4 figures. Changes to match PRD version including new section on non-linear corrections. CAMB code available at http://camb.info

Light, medium-weight or heavy? The nature of the first supermassive black hole seeds

Observations of hyper-luminous quasars at $z>6$ reveal the rapid growth of supermassive black holes (SMBHs $>10^9 \rm M_{\odot}$) whose origin is still difficult to explain. Their progenitors may have formed as remnants of massive, metal free stars (light seeds), via stellar collisions (medium-weight seeds) and/or massive gas clouds direct collapse (heavy seeds). In this work we investigate for the first time the relative role of these three seed populations in the formation of $z>6$ SMBHs within an Eddington-limited gas accretion scenario. To this aim, we implement in our semi-analytical data-constrained model a statistical description of the spatial fluctuations of Lyman-Werner (LW) photo-dissociating radiation and of metal/dust enrichment. This allows us to set the physical conditions for BH seeds formation, exploring their relative birth rate in a highly biased region of the Universe at $z>6$. We find that the inclusion of medium-weight seeds does not qualitatively change the growth history of the first SMBHs: although less massive seeds ($<10^3 \rm M_\odot$) form at a higher rate, the mass growth of a $\sim 10^9 \rm M_\odot$ SMBH at $z<15$ is driven by efficient gas accretion (at a sub-Eddington rate) onto its heavy progenitors ($10^5 \rm M_\odot$). This conclusion holds independently of the critical level of LW radiation and even when medium-weight seeds are allowed to form in higher metallicity galaxies, via the so-called super-competitive accretion scenario. Our study suggests that the genealogy of $z \sim 6$ SMBHs is characterized by a rich variety of BH progenitors, which represent only a small fraction ($< 10 - 20\%$) of all the BHs that seed galaxies at $z > 15$.Comment: (21 pages, 18 figures, 2 tables. Accepted for publication in MNRAS

Autonomic Nervous System characterization in hyperbaric environments considering respiratory component and non-linear analysis of Heart Rate Variability

Objectives: an evaluation of Principal Dynamic Mode (PDM) and Orthogonal Subspace Projection (OSP) methods to characterize the Autonomic Nervous System (ANS) response in three different hyperbaric environments was performed. Methods: ECG signals were recorded in two different stages (baseline and immersion) in three different hyperbaric environments: (a) inside a hyperbaric chamber, (b) in a controlled sea immersion, (c) in a real reservoir immersion. Time-domain parameters were extracted from the RR series of the ECG. From the Heart Rate Variability signal (HRV), classic Power Spectral Density (PSD), PDM (a non-linear analysis of HRV which is able to separate sympathetic and parasympathetic activities) and OSP (an analysis of HRV which is able to extract the respiratory component) methods were used to assess the ANS response. Results: PDM and OSP parameters follows the same trend when compared to the PSD ones for the hyperbaric chamber dataset. Comparing the three hyperbaric scenarios, significant differences were found: i) heart rate decreased and RMSSD increased in the hyperbaric chamber and the controlled dive, but they had the opposite behavior during the uncontrolled dive; ii) power in the OSP respiratory component was lower than power in the OSP residual component in cases a and c; iii) PDM and OSP methods showed a significant increase in sympathetic activity during both dives, but parasympathetic activity increased only during the uncontrolled dive. Conclusions: PDM and OSP methods could be used as an alternative measurement of ANS response instead of the PSD method. OSP results indicate that most of the variation in the heart rate variability cannot be described by changes in the respiration, so changes in ANS response can be assigned to other factors. Time-domain parameters reflect vagal activation in the hyperbaric chamber and in the controlled dive because of the effect of pressure. In the uncontrolled dive, sympathetic activity seems to be dominant, due to the effects of other factors such as physical activity, the challenging environment, and the influence of breathing through the scuba mask during immersion. In sum, a careful description of the changes in all the possible factors that could affect the ANS response between baseline and immersion stages in hyperbaric environments is needed for better interpretation of the results

Delayed degradation of chlorophylls and photosynthetic proteins in Arabidopsis autophagy mutants during stress-induced leaf yellowing

Under mild abiotic-stress conditions, Arabidopsis atg mutants showed a functional stay-green phenotype which is probably caused by the lack of chloroplastic autophagy and the retrograde regulation of senescence-associated gene expressio