Visible Layer Research Articles

Cu2FeSnS4 decorated Ni-TiO2 nanorods heterostructured photoanode for enhancing water splitting performance

Earth-abundant and visible light sensitive Cu2FeSnS4 layer is decorated on Ni-TiO2 nanorods (CFTS/Ni-TiO2 NRs) using wet chemical approach. First, Ni doping is performed on hydrothermally grown TiO2 nanorods to achieve Ni on the surface of TiO2. After surface doping of Ni, the bandgap of TiO2 nanorod films changes from 3.0 eV to 2.79 eV. Once the layer of Cu2FeSnS4 is decorated on the Ni doped TiO2 nanorods the absorption edge of the photoanode further shifted toward lower energy. Mott-Schottky analysis revealed more than 3-fold increase in photogenerated charge carrier density in CFTS/Ni-TiO2 NRs. This heterostructured photoanodes demonstrated a significant increase in photocurrent from 0.730 mA/cm2 to 2.09 mA/cm2 (at 1.23 V vs RHE). The lifetime of photo-generated charge carriers also improves from 10.87 s to 15.36 s for CFTS/Ni-TiO2 NRs as compared to TiO2 NRs. The CFTS/Ni-TiO2 NRs exhibit excellent photoelectrochemical properties with high stability, hence this heterostructure can be a potential candidate for solar energy device applications.

Near-Field Radiant Heat Flux from Open-Air Gasoline and Diesel Pool Fires: Modified Point Source and Discretized Solid Flame Models

This paper proposes novel modifications to existing solid flame and point source models to better predict the spatial contour of near-field, steady-state radiant heat flux from large circular pool fires (with diameters ranging from 1 m to 20 m) with gasoline and diesel fuel. The proposed models account for partial smoke obscuration of the flames, and the emissive power of the visible flame layer is calculated via a radiative fraction of the fire’s heat release rate as a function of the pool size. The modified discretized solid flame model uses a cylinder + cone shape combination whose surfaces are discretized to enable a flexible summation of total radiative energy emission. The modified point source model places its radiating point at the mid-height of the visible flame layer to capture the location of maximum radiation intensity. Predictions from both proposed models are benchmarked against available data from pool fire experiments, calibrated against computational fluid dynamic simulations, and compared with existing analytical solutions for a range of pool fire diameters at varying standoffs and gauge heights. The results demonstrate that the proposed models can effectively predict the spatial contour and peak value of radiant heat flux on nearby targets (i.e., at distances less than 2.5 times the pool diameter) with low computational effort.

Land-sea correlations in the Eastern Mediterranean region over the past c. 800 kyr based on macro- and cryptotephras from ODP Site 964 (Ionian Basin)

Direct correlations between terrestrial and marine climate-proxy records are essential in order to determine potential lead/lag relationships in the response of the terrestrial and marine realms to climate forcing. In the Eastern Mediterranean region, such land-sea correlations have not yet been established beyond c. 200 ka. To explore the potential of tephra layers for Late and Middle Pleistocene land-sea correlations in the Eastern Mediterranean region, we have revisited yet unconfirmed tephra layers previously reported from Ocean Drilling Program (ODP) Site 964 (Ionian Basin) for the past c. 800 kyr in order to identify their origin and examine potential terrestrial counterparts. Using major- and trace-element glass analyses, we confirmed the presence of seven visible tephra layers with ages from 623 to 38 ka. These tephra layers represent known tephra isochrons from Italian volcanic centers (Y-5, Y-7, X-6, and V-0) and three yet unknown eruptions from Etna (623 ka), the Campanian Volcanic Zone (CVZ; 238 ka), and Pantelleria (238 ka). Because the majority of the previously reported tephra layers from ODP Site 964 were identified as clastic layers of non-volcanic origin, cryptotephra analyses were carried out for cores spanning Marine Isotope Stages (MIS) 13 to 9 (500–320 ka). This effort yielded 19 cryptotephra layers originating from Santorini volcano, the CVZ, possibly Roccamonfina volcano, and an undefined source in either the Aeolian Islands or the South Aegean Volcanic Arc. Two tephra layers are correlated with potential equivalents from terrestrial archives on the Italian and Balkan Peninsulas, including tephra isochrons SC5/A7/OH-DP-1966 (c. 493 ka; Mercure basin, Acerno basin, and Lake Ohrid) and TP09–65.95 (c. 359 ka; Tenaghi Philippon) that represent an unknown eruption of Roccamonfina and the Cape Therma 1 eruption of Santorini, respectively. Direct linking of the marine record from ODP Site 964 with the terrestrial records from Tenaghi Philippon, Lake Ohrid, and the Acerno basin via tephra tie points allowed us to circumvent shortcomings of the individual age models, and to obtain a comprehensive picture of climate variability in the greater Eastern Mediterranean region for the MIS 13–9 interval.

Combined use of infrared imaging techniques for the study of underlying features in the Santa Maria in Cosmedin altarpiece

This paper presents a study carried out on the painted altarpiece preserved inside the Basilica of Santa Maria in Cosmedin, Rome, by combining three imaging techniques operating in the near‐ and mid‐infrared spectral ranges. The altarpiece has several pictorial layers and restorations, which have superimposed over time for stylistic adjustment and conservative purposes up to its present appearance. The results obtained in this study enable the detection of damage to the wooden support and the identification of pictorial features buried beneath the visible paint layer, thus providing significant information on the historical and artistic characterization of the artefact.

Infrared and visible image fusion based on weighted variance guided filter and image contrast enhancement

With extraordinary advances in sensor technology, infrared and visible image fusion has been widely used in both military and civilian applications. In this paper, we propose a novel image fusion method based on decomposition and division based strategy. The proposed method improves the guided filter to better decompose images and restrict artifacts around image boundaries. Furthermore, because the quality of visible images is easily affected by low light conditions and noises, it is necessary to enhance the contrast of visible images to improve the visual quality before applying image fusion. Subsequently, we divide the infrared and visible image into several sub-images in vertical direction, because there is more similar image content in this direction such as the sky and land. Additionally, each sub-image is decomposed into a base layer and a detail layer. Different from previous methods, the fusion in our proposed method is executed by two different strategies, one takes the sub infrared base layer as the main image to get the fusion result, while the other one takes the sub visible base layer as the main image, and two different sub-fusion results are obtained. We also propose a new fusion strategy called gradient-brightness criterion to adaptively output the final fused image. As a result, the fused image preserves more details of visible image and clearer infrared objects at the same time, which is well suited for human visual perception. Experimental results indicate that our proposed method achieves a superior performance compared with previous fusion methods in both subjective and objective assessments.

Visibility Layers: A Framework for Facing the Complexity of the Gender Gap in Wikipedia Content

Visibility Layers: A Framework for Facing the Complexity of the Gender Gap in Wikipedia Content

Assessment of the Impact of Trace Elements in FAME Biodiesel on Diesel Oxidation Catalyst Activity after Full Lifetime of Operation in A Heavy-Duty Truck

Fatty acid methyl ester (FAME) biodiesel contains some trace amounts of Na, K, P, Ca, and Mg. Our objective was to investigate whether the presence of such elements can poison a diesel oxidation catalyst that has been used for an entire regulatory lifetime in a heavy-duty truck fueled by FAME biodiesel. The investigated vehicle-aged catalyst contained high loadings of S, P, and Na, as well as a visible layer of soot. Activity in the NO oxidation reaction was severely decreased compared to a fresh catalyst of the same type, while the CO and C3H6 oxidation reactions were less affected. Subsequent selective trace element removal procedures, followed by activity tests, were used to decouple the effect of different poisons. Sintering was observed to be the main cause of catalyst deactivation. Of the trace elements present on the catalyst, P had the greatest effect on catalyst activity, while the other trace elements had little effect.

Computational and experimental evaluation of view out according to European Standard EN17037

This paper presents an experimental evaluation of view out based on EN17037:2018 Daylight in Buildings within an educational building. The primary motivation to conduct the research was an introduction of a view out appraisal criteria by the mentioned standard. The study gives insights into the following: (i) the use of computational evaluation of an outside view according to the EN17037 criteria (ii) the use of the direct simultaneous questionnaire to assess the view out (iii) a description of the relationships between the normative criteria and users' subjective assessments of view out, and (iv) the link between the quantitative and qualitative parameters of the evaluation of view out. The study was conducted using a three step approach: S1 – a computational evaluation of the outside view according to the standard's recommendations: distance to the nearest obstacle, number of visible layers and angle of the view; S2 – a view out evaluation based on a direct questionnaire in the selected indoor spaces under various daylight conditions; S3 – analysis and comparison of the results. The data was collected in 2019 and 2020 with 169 evaluations from volunteering architecture students. The key findings are: (i) the outcome of the subjective participants' evaluation of the view out differs from the results generated through computational simulations based on the EN17037 ratings (ii) similar results were recorded in reference to the estimation of the layers of the view, and (iii) the responders rated the view out one rank lower than the computational evaluation suggests.

Supervised Deep Belief Network for Quality Prediction in Industrial Processes

Deep belief network (DBN) has recently been applied for soft sensor modeling with its excellent feature representation capacity. However, DBN cannot guarantee that the extracted features are quality-related and beneficial for further quality prediction. To solve this problem, a novel supervised DBN (SDBN) is proposed in this article by introducing the quality information into the training phase. SDBN consists of multiple supervised restricted Boltzmann machines (SRBMs) with a stacked structure. In each SRBM, the quality variables are added to the visible layer for network pretraining and feature learning. Thus, the pretrained weights can act as better initializations for the whole network for fine-tuning. Moreover, it can ensure that the learned features are largely quality-related for soft sensor. Finally, the SDBN-based soft sensor model is applied to two industrial plants of a debutanizer column and a hydrocracking process for quality prediction.

Color image encryption via Hénon-zigzag map and chaotic restricted Boltzmann machine over Blockchain

A color image encryption algorithm using the Hénon-zigzag map and chaotic restricted Boltzmann machine (CRBM) is proposed in this paper. The proposed pseudo-random number generator, chaotic restricted Boltzmann machine (CRBM), can simultaneously generate three pseudo-random number sequences. The algorithm includes the permutation phase and the diffusion phase. In the Hénon-zigzag map-based permutation phase, zigzag map is used to modulate two pseudo-random number sequences generated by Hénon map to obtain two new pseudo-random number sequences. The mixing of these two chaotic maps makes the security of the permutation phase significantly improve. Subsequently the two pseudo-random number sequences are used for row permutation and column permutation, respectively. In the diffusion phase, through multiple iterations of CRBM of the 3 × 3 architecture, three pseudo-random number sequences are generated by the state values of three neurons in the visible layer. Then these three pseudo-random number sequences are used for bitxor operation with the R, G and B components of the scrambled image, respectively. A series of numerical experiments and analyses on encrypted images prove that the proposed algorithm is more secure than state-of-the-art algorithms. Furthermore, based on the combined use of blockchain and the proposed algorithm, a novel image encryption/decryption system is proposed. The system has two features: asymmetric encryption/decryption of images and authoritative verification of the integrity of encrypted images. It may provide a better understanding of blockchain in digital image encryption.

Surface Activation of Polylactic Acid-Based Wood-Plastic Composite by Atmospheric Pressure Plasma Treatment.

Wood-plastic composite (WPC) based on a polylactic acid (PLA) matrix is a promising material since it is biobased, degradable, sustainable, and 3D printable. However, due to its coloring, visible layers after 3D-printing, and small build volumes of these printers, a coating or gluing of parts might be required. This study investigates the influence of a dielectric barrier discharge (DBD) plasma treatment of PLA-based WPC to activate the surface and improve, e.g., coating capabilities. X-ray photoelectron spectroscopy (XPS) measurements showed the oxidation of the surface due to the formation of carbonyl and carboxyl groups. Laser scanning microscopy revealed a surface roughening after the treatment. Contact angles of water and diiodomethane decreased significantly after the plasma treatment and the consecutively calculated surface free energy increased. Finally, two practical adhesion tests revealed an improvement of the applied acrylic dispersion coating’s adhesion to the WPC surface: The assigned cross-cut class improved, and the pull-off strength increased from 1.4 to 2.3 N/mm2.

VOLCORE, a global database of visible tephra layers sampled by ocean drilling

The VOLCORE (Volcanic Core Records) database is a collection of 34,696 visible tephra (volcanic ash and lithological or grain size variations) occurrences reported in the initial reports volumes of all of the Deep Sea Drilling Project (DSDP; 1966–1983), the Ocean Drilling Program (ODP; 1983–2003), the Integrated Ocean Drilling Program (IODP; 2003–2013) and the International Ocean Discovery Program (IODP; 2013-present) up to and including IODP Expedition 381. The combined international ocean drilling programmes (OD) have locations with global coverage. Cored tephra layers and tephra-bearing sediments span timescales from recent to ~150 million years in age. This database is a collection of information about reported visible tephra layers entirely or predominantly composed of volcanic ash. Data include the depth below sea floor, tephra thickness, location, and any reported comments. An approximate age was estimated for most (29,493) of the tephra layers using published age-depth models. The database can be used as a starting point for studies of tephrochronology, volcanology, geochemistry, studies of sediment transport and palaeoclimatology.

Rapid carbon accumulation in a peatland following Late Holocene tephra deposition, New Zealand

Contemporary measurements of carbon (C) accumulation rates in peatlands around the world often show the C sink to be stronger on average than at times in the past. Alteration of global nutrient cycles could be contributing to elevated carbon accumulation in the present day. Here we examine the effect of volcanic inputs of nutrients on peatland C accumulation in Moanatuatua Bog, New Zealand, by examining a high-resolution Late Holocene C accumulation record during which powerful volcanic eruptions occurred, depositing two visible rhyolitic tephra layers (Taupo, 232 ± 10 CE; Kaharoa, 1314 ± 12 CE). Carbon accumulation rates since c. 50 CE, well before any human presence, increased from a background rate of 23 g C m−2 yr−1 up to 110 g C m−2 yr−1 following the deposition of the Taupo Tephra, and 84 g C m−2 yr−1 following the deposition of the Kaharoa Tephra. Smaller but nevertheless marked increases in C accumulation additionally occurred in association with the deposition of three andesitic-dacitic cryptotephras (each ≤ ∼1 mm thick) of the Tufa Trig Formation between the Taupo and Kaharoa events. These five periods of elevated C uptake, especially those associated with the relatively thick Taupo and Kaharoa tephras, were accompanied by shifts in nutrient stoichiometry, indicating that there was greater availability of phosphorus (P) relative to nitrogen (N) and C during the period of high C uptake. Such P was almost certainly derived from volcanic sources, with P being present in the volcanic glass at Moanatuatua, and many of the eruptions described being associated with the local deposition of the P rich mineral apatite. We found peatland C accumulation to be tightly coupled to N and P accumulation, suggesting nutrient inputs exert a strong control on rates of peat accumulation. Nutrient stoichiometry indicated a strong ability to recover P within the ecosystem, with C:P ratios being higher than most other peatlands in the literature. We conclude that nutrient inputs, deriving from volcanic eruptions, have been very important for C accumulation rates in the past. Therefore, the elevated nutrient inputs occurring in the present day could offer a more plausible explanation, as opposed to a climatic component, for observed high contemporary C accumulation in New Zealand peatlands.

Coupling TiO2 nanorods with g‐CN using modified physical vapor deposition for efficient photoelectrochemical water oxidation

AbstractThe core‐shell TiO2@g‐CN nanorods arrays were constructed directly on fluorine‐doped tin oxide grass using vacuum magnetic filtered arc ion plating. The unique structure combines both advantages from TiO2 as an effective electron‐transfer layer and graphic carbon nitride (g‐CN) with a proper band gap serving as visible light absorption layer. Under 100 mW/cm2 (AM 1.5G) light illumination, the optimal TiO2@g‐CN produces a photocurrent density of 0.91 mA/cm2 at 1.23 V vs reversible hydrogen electrode, which is 2.1 times of the bare TiO2 (0.43 mA/cm2) obtained at the same potential. The improved photoelectrochemical performance is mainly attributed from the improved charge separation and transport within the heterojunction as well as the enhanced light absorption.

Predictive ARIMA Model for coronal index solar cyclic data

Many solar activities, e.g. sunspots, Mg II indices, coronal index of solar activity, etc., are produced by solar magnetic fields that affect both, the solar atmosphere and heliosphere, including the terrestrial environment. The atmosphere of the sun is recognized by photosphere, as a visible solar disk and layers above it: chromosphere, transition zone and corona. The nature of solar activity can be, in the emission solar corona, recognized by the coronal index of solar activity (CI). Its dataset in the period 1944–2009 will be used to test the ARIMA model. Based on the minimum AIC and BIC values, ARIMA(1,0,1) model is selected for each CI cycle and total dataset. The quality of the selected model is endorsed by (RMSE, MAPE, & FPE). The behaviour of the observed (original) CI cycle with predictive CI cycle shows a strong correlation, of more than 0.8 between actual and predictive CI cycles, which is a predictive power of ARIMA(1,0,1) model. Further model persistency estimated by Hurst exponent (smoothness) with the help of fractal dimension (complexity). All predictive CI cycles show persistence and positively correlated, the total dataset equation is given as X(t) – 0.977(t-1) = Z(t) - 0.546(t-1). • The purpose of the paper to understand the search of model for coronal index solar data. • By using of model predict the CI cycles. • Check the appropriateness of predicted cycle with original cycle by selected model. • After all persistency of the original and predictive data obtained by Hurst & fractal dimension.

Machine learning holographic mapping by neural network renormalization group

The authors design a machine learning scheme to explore problems in quantum field theory. The method relies in providing quantum field theory as a visible layer of the machine, living on the boundary, and results in a dual theory that governs its hidden variables

Biomimetic hybrid membranes with covalently anchored chitosan – Material design, transport and separation

New hybrid membrane was inspired by biomimicking the water harvesting system in the back of fogstand beetle. Therefore, efficient hydrophobic material with hydrophilic chitosan (CS) islands was produced by the covalent attachment of chitosan to the hydrophobic surface of PVDF membranes. The attachment of CS molecules allows upgrading the membrane permeability and antifouling properties. Employing the “grafting to” approach, CS was anchored to pre-activated PVDF-membranes by urea linker via silanization. Materials were used for different separation processes, including membrane distillation (MD) for the removal of hazardous volatile organic compounds, desalination, and concentration of raw juices. Material physiochemical features, wettability, stability, tribology, and morphology, were assessed with respect to transport and separation. The hybrid-material possessed improved thermal stability and water resistance. The process separation index increased from ~6.8 kg m−2 h−1 to 90 kg m−2 h−1 for pristine and hybrid-material, respectively. During the juice concentration, the normalized flux decline for pristine was ~50%, whereas for hybrid material below 10%. On the pristine material, a visible layer of foulant was found after the separation, whereas the hybrid membrane shows a relatively clean surface. The developed strategy offers several distinct advantages for generating new materials having potential applications in water oil separation and wastewater treatment.

An Improved Deep Belief Network for Chinese Emergency Recognition

Aiming at the defects that the RBM module in DBN can only re-represent information but cannot extract information features, and can only handle one-dimensional data, the DBN network is improved, and a Conv-DBN model is proposed to recognize emergencies. First, the text corpus is preprocessed, and the word vector matrix generated by Word2Vec is used as input, and then the word vector features are extracted through the visible layer integrated into the convolution operation. Word vector features are used as the input of the next layer. Finally, every layers are fine-tuned through back-propagation at the top layer. The softmax function is used to activate, and the recognition result is output. Simulation results show that the method proposed in this paper has improved accuracy and recall, and F value is better than other methods.

Teething during sleep: Ultrastructural analysis of pharyngeal muscle and cuticular grinder during the molt in Caenorhabditis elegans.

Complex extracellular structures exist throughout phylogeny, but the dynamics of their formation and dissolution are often opaque. One example is the pharyngeal grinder of the nematode Caenorhabditis elegans, an extracellular structure that ruptures bacteria during feeding. During each larval transition stage, called lethargus, the grinder is replaced with one of a larger size. Here, we characterize at the ultrastructural level the deconstruction of the larval grinder and the construction of the adult grinder during the fourth larval stage (L4)-to-adult transition. Early in L4 lethargus, pharyngeal muscle cells trans-differentiate from contractile to secretory cells, as evidenced by the appearance of clear and dense core vesicles and disruptions in sarcomere organization. This is followed, within minutes, by the dissolution of the L4 grinder and the formation and maturation of the adult grinder. Components of the nascent adult grinder are deposited basally, and are separated from the dissolving larval grinder by a visible apical layer. The complete grinder is a lamellated extracellular matrix comprised of five layers. Following grinder formation, pharyngeal muscle cells regain ultrastructural contractile properties, and muscle contractions resume. Our findings add to our understanding of how complex extracellular structures assemble and dissemble.

Entropy, Free Energy, and Work of Restricted Boltzmann Machines.

A restricted Boltzmann machine is a generative probabilistic graphic network. A probability of finding the network in a certain configuration is given by the Boltzmann distribution. Given training data, its learning is done by optimizing the parameters of the energy function of the network. In this paper, we analyze the training process of the restricted Boltzmann machine in the context of statistical physics. As an illustration, for small size bar-and-stripe patterns, we calculate thermodynamic quantities such as entropy, free energy, and internal energy as a function of the training epoch. We demonstrate the growth of the correlation between the visible and hidden layers via the subadditivity of entropies as the training proceeds. Using the Monte-Carlo simulation of trajectories of the visible and hidden vectors in the configuration space, we also calculate the distribution of the work done on the restricted Boltzmann machine by switching the parameters of the energy function. We discuss the Jarzynski equality which connects the path average of the exponential function of the work and the difference in free energies before and after training.