Deep neural networks have demonstrated the capability of solving classification problems using hierarchical models, and fuzzy image preprocessing has proven to be efficient in handling uncertainty ...found in images. This paper presents the combination of fuzzy image edge-detection and the usage of a convolutional neural network for a computer vision system to classify guitar types according to their body model. The focus of this investigation is to compare the effects of performing image-preprocessing techniques on raw data (non-normalized images) with different fuzzy edge-detection methods, specifically fuzzy Sobel, fuzzy Prewitt, and fuzzy morphological gradient, before feeding the images into a convolutional neural network to perform a classification task. We propose and compare two convolutional neural network architectures to solve the task. Fuzzy edge-detection techniques are compared against their classical counterparts (Sobel, Prewitt, and morphological gradient edge-detection) and with grayscale and color images in the RGB color space. The fuzzy preprocessing methodologies highlight the most essential features of each image, achieving favorable results when compared to the classical preprocessing methodologies and against a pre-trained model with both proposed models, as well as achieving a reduction in training times of more than 20% compared to RGB images.
Metal–organic frameworks that flex to undergo structural phase changes upon gas adsorption are promising materials for gas storage and separations, and achieving synthetic control over the pressure ...at which these changes occur is crucial to the design of such materials for specific applications. To this end, a new family of materials based on the flexible metal–organic framework Co(bdp) (bdp2– = 1,4-benzenedipyrazolate) has been prepared via the introduction of fluorine, deuterium, and methyl functional groups on the bdp2– ligand, namely, Co(F-bdp), Co(p-F2-bdp), Co(o-F2-bdp), Co(D4-bdp), and Co(p-Me2-bdp). These frameworks are isoreticular to the parent framework and exhibit similar structural flexibility, transitioning from a low-porosity, collapsed phase to high-porosity, expanded phases with increasing gas pressure. Powder X-ray diffraction studies reveal that fluorination of the aryl ring disrupts edge-to-face π–π interactions, which work to stabilize the collapsed phase at low gas pressures, while deuteration preserves these interactions and methylation strengthens them. In agreement with these observations, high-pressure CH4 adsorption isotherms show that the pressure of the CH4-induced framework expansion can be systematically controlled by ligand functionalization, as materials without edge-to-face interactions in the collapsed phase expand at lower CH4 pressures, while frameworks with strengthened edge-to-face interactions expand at higher pressures. Importantly, this work puts forth a general design strategy relevant to many other families of flexible metal–organic frameworks, which will be a powerful tool in optimizing these phase-change materials for industrial applications.
Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated ...because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., run‐up or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii) statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence, and uncertainties in an integrated and consistent probabilistic framework.
Key Points
PTHA quantifies the probability that different hazard intensity levels will be exceeded in a given time window at a specific place
PTHA is the first step toward tsunami risk assessment and risk reduction planning
A comprehensive review of PTHA is discussed for seismic and nonseismic tsunami sources with uncertainty quantification methods
Biofuel research that aims to optimize growth conditions in microalgae is critically important. Chlamydomonas reinhardtii is a green microalga that offers advantages for biofuel production research. ...This study compares the effects of nitrogen-, sulfur-, and nitrogen and sulfur- deprivations on the C. reinhardtii starchless mutant cc5373-sta6. Specifically, it compares growth, lipid body accumulation, and expression levels of acetyl-CoA carboxylase (ACC) and phosphoenolpyruvate carboxylase (PEPC). Among nutrient-deprived cells, TAP-S cells showed significantly higher total chlorophyll, cell density, and protein content at day 6 (p < 0.05). Confocal analysis showed a significantly higher number of lipid bodies in cells subjected to nutrient deprivation than in the control over the course of six days; N deprivation for six days significantly increased the size of lipid bodies (p < 0.01). In comparison with the control, significantly higher ACC expression was observed after 8 and 24 h of NS deprivation and only after 24 h with N deprivation. On the other hand, ACC and PEPC expression at 8 and 24 h of S deprivation was not significantly different from that in the control. A significantly lower PEPC expression was observed after 8 h of N and NS deprivation (p < 0.01), but a significantly higher PEPC expression was observed after 24 h (p < 0.01). Based on our findings, it would be optimum to cultivate cc5373-sta6 cells in nutrient deprived conditions (-N, -S or -NS) for four days; whereby there is cell growth, and both a high number of lipid bodies and a larger size of lipid bodies produced.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The air-free reaction of CoCl2 with 1,3,5-tri(1H-1,2,3-triazol-5-yl)benzene (H3BTTri) in N,N-dimethylformamide (DMF) and methanol leads to the formation of Co-BTTri (Co3(Co4Cl)3(BTTri)82·DMF), a ...sodalite-type metal–organic framework. Desolvation of this material generates coordinatively unsaturated low-spin cobalt(II) centers that exhibit a strong preference for binding O2 over N2, with isosteric heats of adsorption (Q st) of −34(1) and −12(1) kJ/mol, respectively. The low-spin (S = 1/2) electronic configuration of the metal centers in the desolvated framework is supported by structural, magnetic susceptibility, and computational studies. A single-crystal X-ray structure determination reveals that O2 binds end-on to each framework cobalt center in a 1:1 ratio with a Co–O2 bond distance of 1.973(6) Å. Replacement of one of the triazolate linkers with a more electron-donating pyrazolate group leads to the isostructural framework Co-BDTriP (Co3(Co4Cl)3(BDTriP)82·DMF; H3BDTriP = 5,5′-(5-(1H-pyrazol-4-yl)-1,3-phenylene)bis(1H-1,2,3-triazole)), which demonstrates markedly higher yet still fully reversible O2 affinities (Q st = −47(1) kJ/mol at low loadings). Electronic structure calculations suggest that the O2 adducts in Co-BTTri are best described as cobalt(II)–dioxygen species with partial electron transfer, while the stronger binding sites in Co-BDTriP form cobalt(III)–superoxo moieties. The stability, selectivity, and high O2 adsorption capacity of these materials render them promising new adsorbents for air separation processes.
The journal
Impact Factor
(IF) is not comparable among fields of science and social science because of systematic differences in publication and citation behaviour across disciplines. In this work, a ...decomposing of the field aggregate impact factor into five normally distributed variables is presented. Considering these factors, a principal component analysis is employed to find the sources of the variance in the
Journal Citation Reports
(
JCR
)
subject categories
of science and social science. Although publication and citation behaviour differs largely across disciplines, principal components explain more than 78 % of the total variance and the average number of references per paper is not the primary factor explaining the variance in impact factors across categories. The categories normalized impact factor based on the JCR subject category list is proposed and compared with the IF. This normalization is achieved by considering all the indexing categories of each journal. An empirical application, with one hundred journals in two or more subject categories of economics and business, shows that the
gap
between rankings is reduced around 32 % in the journals analyzed. This
gap
is obtained as the maximum distance among the ranking percentiles from all categories where each journal is included.
Quantitative assessment of key proteins that control the tumor-immune interface is one of the most formidable analytical challenges in immunotherapeutics. We developed a targeted MS platform to ...quantify programmed cell death-1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and programmed cell death 1 ligand 2 (PD-L2) at fmol/microgram protein levels in formalin fixed, paraffin-embedded sections from 22 human melanomas. PD-L1 abundance ranged 50-fold, from ∼0.03 to 1.5 fmol/microgram protein and the parallel reaction monitoring (PRM) data were largely concordant with total PD-L1-positive cell content, as analyzed by immunohistochemistry (IHC) with the E1L3N antibody. PD-1 was measured at levels up to 20-fold lower than PD-L1, but the abundances were not significantly correlated (r2 = 0.062, p = 0.264). PD-1 abundance was weakly correlated (r2 = 0.3057, p = 0.009) with the fraction of lymphocytes and histiocytes in sections. PD-L2 was measured from 0.03 to 1.90 fmol/microgram protein and the ratio of PD-L2 to PD-L1 abundance ranged from 0.03 to 2.58. In 10 samples, PD-L2 was present at more than half the level of PD-L1, which suggests that PD-L2, a higher affinity PD-1 ligand, is sufficiently abundant to contribute to T-cell downregulation. We also identified five branched mannose and N-acetylglucosamine glycans at PD-L1 position N192 in all 22 samples. Extent of PD-L1 glycan modification varied by ∼10-fold and the melanoma with the highest PD-L1 protein abundance and most abundant glycan modification yielded a very low PD-L1 IHC estimate, thus suggesting that N-glycosylation may affect IHC measurement and PD-L1 function. Additional PRM analyses quantified immune checkpoint/co-regulator proteins LAG3, IDO1, TIM-3, VISTA, and CD40, which all displayed distinct expression independent of PD-1, PD-L1, and PD-L2. Targeted MS can provide a next-generation analysis platform to advance cancer immuno-therapeutic research and diagnostics.
This study proposes an urban Bikeability Index (BI) to assess and prioritise bicycle infrastructure investments, and in turn, improve accessibility for cyclists. The contribution of this paper is ...twofold. First, we construct a BI that addresses particularities of the roads in cities of the Global South and considers the preferences, perceptions and socioeconomic characteristics by type of cyclist. Second, a tool is developed for decision-makers to prioritise investments in bicycle infrastructure, considering the estimated BI and expected cyclist flows. The methodology is structured into two stages. The first stage constructs a new BI following three steps. First, we select the most important factors and components related to biking behaviour. Second, we estimate weights for selected factors and components by using a discrete choice model to analyse users’ perceptions based on results from ranking surveys. Third, we estimate the BI by type of cyclist as a weighted additive function, which are equivalent to the probabilities calculated using the discrete choice model. The second stage proposes a direct demand model to prioritise bicycle infrastructure investments based on the estimation of BIs, and expected flows of cyclists. We applied the methodology to Barranquilla, Colombia and ranked different bicycle infrastructure investments for increasing bicycle demand in the city. The results suggest that even though primary roads are currently associated with low BI values due to high rates of road accidents, they tend to be preferred by cyclists. The presence of adequate bicycle infrastructure is the most crucial factor for people who frequently cycle for sport, while traffic safety and security are the most critical factors for those who cycle to work.
•Wind speed spatial resolution highly influences calculated wind power peaks and ramps.•Reduction of wind power generation uncertainties using statistical downscaling.•Publicly available dataset of ...wind power generation hourly time series at NUTS2.
The growing share of electricity production from solar and mainly wind resources constantly increases the stochastic nature of the power system. Modelling the high share of renewable energy sources – and in particular wind power – crucially depends on the adequate representation of the intermittency and characteristics of the wind resource which is related to the accuracy of the approach in converting wind speed data into power values. One of the main factors contributing to the uncertainty in these conversion methods is the selection of the spatial resolution. Although numerical weather prediction models can simulate wind speeds at higher spatial resolution (up to 1×1km) than a reanalysis (generally, ranging from about 25km to 70km), they require high computational resources and massive storage systems: therefore, the most common alternative is to use the reanalysis data. However, local wind features could not be captured by the use of a reanalysis technique and could be translated into misinterpretations of the wind power peaks, ramping capacities, the behaviour of power prices, as well as bidding strategies for the electricity market. This study contributes to the understanding what is captured by different wind speeds spatial resolution datasets, the importance of using high resolution data for the conversion into power and the implications in power system analyses. It is proposed a methodology to increase the spatial resolution from a reanalysis. This study presents an open access renewable generation time series dataset for the EU-28 and neighbouring countries at hourly intervals and at different geographical aggregation levels (country, bidding zone and administrative territorial unit), for a 30year period taking into account the wind generating fleet at the end of 2015.
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