28 research outputs found
Student-parents' Perspectives and Challenges of Online Learning During the Covid-19 Pandemic: A Quantitative Study
No full textAbstract: The Covid-19 pandemic forced educational institutions to shut down. Just like a damsel in distress, the educational system needed a knight in shining armor, and so online learning comes to the rescue. Online learning rescued many countries from academic freeze during this global pandemic. This present study will explore the perception and challenges of student-parents in online learning during this global pandemic. Perspectives and challenges were also examined in terms gender. Lastly, it is also explored if there is a relationship between the student-parent’s perspectives and challenges. Results shows that student-parents have neither positive or negative perception about online learning and that they experience moderate challenges in this learning setup. However, comparing the means between males and females, it is revealed that females are more challenge with this online learning set-up than males with a mean difference of 0.28. In terms of relationship between the student-parents’ perspectives and challenges of online learning, the results revealed that respondents’ challenges of online learning do not have association with their perspectives.
Keywords: Challenges of Online Learning, Covid-19 Pandemic, Student-parents’ Perspectives.
Title: Student-parents’ Perspectives and Challenges of Online Learning During the Covid-19 Pandemic: A Quantitative Study
Author: Ina Mae B. Factor
International Journal of Recent Research in Social Sciences and Humanities (IJRRSSH)
ISSN 2349-7831
Vol. 9, Issue 2, April 2022 - June 2022
Page No: 165-175
Paper Publications
Website: www.paperpublications.org
Published Date: 19-May-2022
DOI: https://doi.org/10.5281/zenodo.6562740
Paper Download Link (Source):
https://www.paperpublications.org/upload/book/Student-parents’%20Perspectives-19052022-1.pdfInternational Journal of Recent Research in Social Sciences and Humanities (IJRRSSH)
ISSN 2349-7831
Paper Publications
Website: www.paperpublications.or
A hybrid metaheuristic approach using random forest and particle swarm optimization to study and evaluate backbreak in open-pit blasting
No full textBackbreak is a rock fracture problem that exceeds the limits of the last row of holes in an explosion operation. Excessive backbreak increases operational costs and also poses a threat to mine safety. In this regard, a new hybrid intelligence approach based on random forest (RF) and particle swarm optimization (PSO) is proposed for predicting backbreak with high accuracy to reduce the unsolicited phenomenon induced by backbreak in open-pit blasting. A data set of 234 samples with six input parameters including special drilling (SD), spacing (S), burden (B), hole length (L), stemming (T) and powder factor (PF) and one output parameter backbreak (BB) is set up in this study. Seven input combinations (one with six parameters, six with five parameters) are built to generate the optimal prediction model. The PSO algorithm is integrated with the RF algorithm to find the optimal hyper-parameters of each model and the fitness function, which is the mean absolute error (MAE) of ten cross-validations. The performance capacities of the optimal models are assessed using MAE, root-mean-square error (RMSE), Pearson correlation coefficient (R2) and mean absolute percentage error (MAPE). Findings demonstrated that the PSO–RF model combining L–S–B–T–PF with MAE of 0.0132 and 0.0568, RMSE of 0.0811 and 0.1686, R2 of 0.9990 and 0.9961 and MAPE of 0.0027 and 0.0116 in training and testing phases, respectively, has optimal prediction performance. The optimal PSO–RF models were compared with the classical artificial neural network, RF, genetic programming, support vector machine and convolutional neural network models and show that the PSO–RF model has superiority in predicting backbreak. The Gini index of each input variable has also been calculated in the RF model, which was 31.2 (L), 23.1 (S), 27.4 (B), 36.6 (T), 23.4 (PF) and 16.9 (SD), respectively. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature
The effect of Kappaphycus alvarezii active fraction on oxidative stress and inflammation in streptozotocin and nicotinamide-induced diabetic rats
No full textBackground: High glucose concentration increases the glycation process which leads to oxidative stress and inflammation, that can cause complications in diabetes. Several medicinal plants have been used in the treatment of diabetes and its complications. One of them is Kappaphycus alvarezii, an algae that has known antidiabetic abilities. This study aimed to examine the effect of K. alvarezii active fraction on plasma hydrogen peroxide (H2O2) and Tumor Necrosis Factor α (TNFα) levels, renal NADPH oxidase 4 (NOX4) and Nuclear Factor κ B (NFκB) gene expressions. Methods: Active fraction was obtained from bioassay-guided fractionation with antiglycation ability. In vivo study was performed on twenty Wistar male rats. The level of H2O2 was measured using H2O2 Assay Kit, the Optical Density value measured using spectrophotometer at a wavelength of 405 nm. Plasma TNFα level was measured using ELISA. Renal NOX4 and NFκB gene expression was analyzed using qPCR. Results: Active fraction significantly reduced plasma H2O2 but not TNFα levels. Furthermore, renal NOX4 gene expression was lower in the diabetic rat group treated with active fraction compared to the untreated group but not NFκB gene expression. Conclusions: K. alvarezii active fraction has an activity to reduce plasma H2O2 as well as renal NOX4 gene expression. Therefore, this fraction could be developed as a potential candidate for diabetes treatment through oxidative stress mechanisms. © 2022, The Author(s)
Identification and functional analysis of Joka2, a tobacco member of the family of selective autophagy cargo receptors
No full textTwo main mechanisms of protein turnover exist in eukaryotic cells: the ubiquitin-proteasome system and the autophagylysosomal pathway. Autophagy is an emerging important constituent of many physiological and pathological processes, such as response to nutrient deficiency, programmed cell death and innate immune response. In mammalian cells the selectivity of autophagy is ensured by the presence of cargo receptors, such as p62/SQSTM1 and NBR1, responsible for sequestration of the ubiquitinated proteins. In plants no selective cargo receptors have been identified yet. The
present report indicates that structural and functional homologs of p62 and NBR1 proteins exist in plants. The tobacco protein, named Joka2, has been identified in yeast two-hybrid search as a binding partner of a small coiled-coil protein, a member of UP9/LSU family of unknown function, encoded by the UP9C gene strongly and specifically induced during sulfur deficiency. The typical domains of p62 and NBR1 are conserved in Joka2. Similarly to p62, Joka2-YFP has dual
localization (cytosolic speckles and the nucleus); it forms homodimers and interacts with a member of the ATG8 family.
Increased expression of Joka2 and ATG8f was observed in roots of tobacco plants grown for two days in nutrient-deficient conditions. Constitutive ectopic expression of Joka2-YFP in tobacco resulted in attenuated response (manifested by lesser yellowing of the leaves) to nutrient deficiency. In conclusion, Joka2, and presumably the process of selective autophagy, might constitute an important part of plant response to environmental stresses
SOME REFLECTIONS ON CLIMATE CHANGE, GREEN GROWTH ILLUSIONS AND DEVELOPMENT SPACE
No full textMany economists and policy makers advocate a fundamental shift towards “green growth” as the new, qualitatively-different growth paradigm, based on enhanced material/resource/energy efficiency and drastic changes in the energy mix. “Green growth” may work well in creating new growth impulses with reduced environmental load and facilitating related technological and structural change. But can it also mitigate climate change at the required scale (i.e. significant, absolute and permanent decline of GHG emissions at global level) and pace? This paper argues that growth, technological, population-expansion and governance constraints as well as some key systemic issues cast a very long shadow on the “green growth” hopes. One should not deceive oneself into believing that such evolutionary (and often reductionist) approach will be sufficient to cope with the complexities of climate change. It may rather give much false hope and excuses to do nothing really fundamental that can bring about a U-turn of global GHG emissions. The proponents of a resource efficiency revolution and a drastic change in the energy mix need to scrutinize the historical evidence, in particular the arithmetic of economic and population growth. Furthermore, they need to realize that the required transformation goes beyond innovation and structural changes to include democratization of the economy and cultural change. Climate change calls into question the global equality of opportunity for prosperity (i.e. ecological justice and development space) and is thus a huge developmental challenge for the South and a question of life and death for some developing countries (who increasingly resist the framing of climate protection versus equity).
DeepBacs – Mixed segmentation dataset and StarDist model
No full textMixed training and test images of S. aureus, E. coli and B. subtilis for cell segmentation using StarDist, as well as the trained StarDist model.
Additional information can be found on this github wiki.
Data type: Paired bright field / fluorescence and segmented mask images
Microscopy data type: 2D widefield images; DIC and fluorescence for S. aureus, bright field images for E. coli, and fluorescence images for B. subtilis
Microscopes:
S. aureus:
GE HealthCare Deltavision OMX system (with temperature and humidity control, 37°C) equipped with an Olympus 60x 1.42NA Oil immersion objective and 2 PCO Edge 5.5 sCMOS cameras (one for DIC, one for fluorescence)
E.coli:
Nikon Eclipse Ti-E equipped with an Apo TIRF 1.49NA 100x oil immersion objective
B. subtilis:
Custom-built 100x inverted microscope bearing a 100x TIRF objective (Nikon CFI Apochromat TIRF 100XC Oil); images were captured on a Prime BSI sCMOS camera (Teledyne Photometrics)
Cell types: S. aureus strain JE2, E. coli MG1655 (CGSC #6300) and B. subtilis strain SH130; all grown under agarose pads
File format: .tif (8-bit and 16-bit)
Image size: 512 x 512 px² @ 80 nm pixel size (S. aureus); 1024 x 1024 px² @ 79 nm pixel size (E. coli); 1024 x 1024 px² @ 65 nm pixel size (B. subtilis)
Image preprocessing:
S. aureus:
Raw images were manually annotated by drawing ellipses in the NR fluorescence image and segmented images were created using the LOCI plugin (“ROI Map”). For training, images and masks were quartered into four 256 x 256 px² patches.
E. coli:
Raw images were recorded in 16-bit mode (image size 512x512 px² @ 158 nm/px). Images were upscaled with a factor of 2 (no interpolation) to enable generation of higher-quality segmentation masks.
B. subtilis:
Images were denoised using PureDenoise and resulting 32-bit images were converted into 8-bit images after normalizing to 1% and 99.98% percentiles. Images were manually annotated using the Labkit Fiji plugin
StarDist model:
The StarDist 2D model was generated using the ZeroCostDL4Mic platform (Chamier et al., 2021). It was trained from scratch for 200 epochs (120 steps/epoch) on 155 paired image patches (image dimensions: (1024, 1024), patch size: (256,256)) with a batch size of 4, 10% validation data, 64 rays on grid 2, a learning rate of 0.0003 and a mae loss function, using the StarDist 2D ZeroCostDL4Mic notebook (v 1.12.2). Key python packages used include tensorflow (v 0.1.12), Keras (v 2.3.1), csbdeep (v 0.6.1), numpy (v 1.19.5), cuda (v 11.0.221). The training was accelerated using a Tesla P100GPU. The dataset was augmented by a factor of 3.
The model weights can be used in the ZeroCostDL4Mic StarDist 2D notebook, the StarDist Fiji plugin or the TrackMate Fiji plugin (v7+).
Author(s): Christoph Spahn1,2, Mike Heilemann1,3, Mia Conduit4, Séamus Holden4,5, Pedro Matos Pereira6,7, Mariana Pinho6,8
Contact email: [email protected], [email protected], [email protected] and [email protected]
Affiliation(s):
1) Institute of Physical and Theoretical Chemistry, Max-von-Laue Str. 7, Goethe-University Frankfurt, 60439 Frankfurt, Germany
2) ORCID: 0000-0001-9886-2263
3) ORCID: 0000-0002-9821-3578
4) Centre for Bacterial Cell Biology, Biosciences Institute, Newcastle University, NE2 4AX UK
5) ORCID: 0000-0002-7169-907X
6) Bacterial Cell Biology, Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal
7) ORCID: 0000-0002-1426-9540
8) ORCID: 0000-0002-7132-884
"Disney is the Tiffany’s and I am the Woolworth's of the business": A critical re-analysis of the business philosophies, production values and studio practices of animator-producer Paul Houlton Terry
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Animator-producer Paul Houlton Terry has been portrayed as having little passion for the animation he produced and being more concerned with making a profit than producing entertaining cartoons with high production values. The purpose of the dissertation is to re-evaluate Terry‘s legacy to animated cartooning by analyzing his business philosophies, production values, and studio practices.
Application of four psychodynamic factors to the early life and career of Terry, 1887-1929, found that his economic decision making was characterized by: an external locus of control, risk-averse financial behaviour, extreme saving behaviour through precaution, and shrewd money management practices. Based on Terry‘s historical responses to twelve major economic, technological, or institutional forces of change for the period 1929-1955, the psychodynamic factors were found to provide accurate explanations for his studio practices and production decisions.
There was no evidence to support the conclusion that three early career disappointments undermined Terry‘s intrinsic motivation to create animated cartoons. Rather, Terry‘s lack of risk taking, external locus of control, tight studio production schedule, desire to compete with neighbour studio Fleischer, difficulty in separating financial rewards from creative processes in animation, and practice of undertaking surveillance measures on staff may have undermined his and his studio‘s creativity. Archival research found Terry to possess strong passions for and to have made significant creative contributions to the field of animation.
Biographical research found that Terry retained a stable nucleus of highly talented artists who dedicated a significant portion of their working careers to the studio. An analysis of the cel aesthetics of a random sample of animated cartoons produced during the years 1930-1955 found that Terry created animated cartoons with above average cel aesthetics when compared to the other studios thereby supporting an inference that Terry was motivated to producing quality crafted animation. Further research is suggested into the role psychodynamic factors and economic decision-making play in the film production process and a clarification of Terry‘s legacy to the field of animated cartoons
A unified meta-ecosystem dynamics model: Integrating herbivore-plant subwebs with the intermittent upwelling hypothesis
No full textDetermining the relative influence of biotic and abiotic processes in structuring communities at local to large spatial scales is best understood using a biogeographic comparative-experimental approach. Using this approach, previous work suggests that intertidal community dynamics (top-down and bottom-up effects) vary unimodally along an upwelling-based productivity gradient, termed the Intermittent Upwelling Hypothesis (IUH). Evidence consistent with the IUH comes from the sessile invertebrate/predator (SIP) subweb in certain rocky intertidal communities, but whether this pattern extends to macrophyte/herbivore (MH) subwebs is unknown. Here we ask: Are MH subwebs also structured as predicted by the IUH? What is the relative importance of herbivory and predation in structuring these communities? Under what conditions do ecological subsidies like nutrients or propagule production drive community dynamics? And are omnivorous interactions important? We hypothesize that MH subwebs are driven by a new construct, the Grazing-Weakening Hypothesis (GWH), which states that MH interactions weaken monotonically with increasing nutrients, with strong (weak) herbivory and low (high) macrophyte productivity at low (high) nutrients. We explored local-to-large spatial scale dynamics of both subwebs using a biogeographic comparative-experimental factorial field experiment testing joint and separate effects of herbivores and predators between two continents. Experiments at ten sites ranging across from persistent upwelling to persistent downwelling regimes ran for 26-29 months in Oregon and California, and New Zealand South Island. For the MH subweb, results were consistent with the GWH: herbivory declined and macrophytes increased with increasing nutrients. As expected, results for the SIP subweb were consistent with the IUH: predator effect size was unimodally related to upwelling. Overall, herbivory explained more variation in community structure than did predation, especially in New Zealand. Omnivory was weak, sessile invertebrates outcompeted macrophytes, and ocean-driven subsidies provided the basic template driving ecosystem dynamics. We propose a unified Meta-Ecosystem Dynamics Model (MEcoDynaMo) combining MH and SIP results: with increased upwelling, sessile invertebrates and underlying dynamics vary unimodally (as in the IUH), while herbivory decreases and macrophytes generally increase. While this model was based on research in temperate ecosystems varying in upwelling regime, its wider applicability remains to be tested.Excel or similar spreadsheet.Funding provided by: David and Lucile Packard FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000008Award Number: Funding provided by: Gordon and Betty Moore FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000936Award Number: Funding provided by: Andrew W. Mellon FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000873Award Number: Funding provided by: Wayne and Gladys Valley FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100001370Award Number:Study Systems
Research was done on wave-exposed rocky benches on the OR and northern CA coast located in the California Current Large Marine Ecosystem (LME), and NZ, located in the New Zealand Shelf Large Marine Ecosystem (Fig. 2). Experiments were done in OR and NZ, and supplementary data on nutrients and macrophyte cover were obtained in CA by the PISCO consortium. Tidal ranges were 3.0 to 3.5 m in OR and CA and 2.1 (east coast) to 3.4 m (west coast) in NZ (Appendix S1: Table S1). OR/CA experiences mixed semi-diurnal tides (i.e., successive low or high tides are of unequal height, with one "good" low tide per day during spring tide periods), while NZ tides are semi-diurnal (daily low and high tides are of similar height). Except for Nine-Mile Beach in NZ, sites used in this study have lengthy histories of continuous ecological research, beginning in 1983 in OR, the 1990s in CA, and 1994 in NZ.
Environment
Experiments in NZ and OR were conducted between October 2004 to October 2007 and May 2005 to August 2007, respectively. CA and NZ data on nutrients and chlorophyll-a were obtained in 1999-2002 and have been collected in OR continuously since 1999. The research included environmental and ecological measurements and identically designed and conducted experiments in both LMEs, with initiation offset by 6 months so that each was begun in the respective spring in each LME (Appendix S2: Fig. S1).
Upwelling Regimes and Shelf Width. Oceanic conditions in the two LMEs have been detailed elsewhere (e.g., Menge et al., 1997, 1999, 2003, 2011, 2015; Menge & Menge, 2013; Schiel, 2004, 2011; Stevens et al. 2021). Briefly, the OR/CA coast is characterized by intermittent upwelling, with a reversing, conveyor belt-like cross-shelf flow pattern (Appendix S1: Table S2). Upwelling events typically deliver temporally varying pulses of cold, nutrient-rich water nearshore and then via subsequent cross-shore flows to offshore shelf waters, while the alternating downwelling-driven events deliver warmed, nutrient-poor surface waters to the nearshore. Periods between upwelling cessation and downwelling onset are termed "relaxations" and are also conditions that can deliver materials to the coast as the uneven sea level generated by upwelling processes evens up with shoreward water movement. In this study, upwelling was stronger at southern OR and CA sites, and weaker at the four central OR sites.
Coastal currents interact with shelf width to modify retention of subsidies along the coast (Kirincich et al., 2005). The shelf is relatively wide in the Cape Perpetua (CP) or "central" region (sites SH and TK) and relatively narrow at all other sites (Menge et al., 2015), generating weak and retentive currents in the CP region and stronger, less retentive offshore currents elsewhere (see bathymetry in Fig. 2).
In NZ, East coast sites are dominated by persistent downwelling while West coast sites experience intermittent upwelling (Menge et al., 2003; Appendix S1: Table S2). Shelf width also differs between coasts, narrow at the East coast sites and wide at the West coast sites (Menge et al., 2003). It thus seems likely that the West coast sites have retentive oceanic regimes for the same reason those at CP; the wide shelf likely weakens upwelling currents. On the East coast, downwelling flows occur shoreward, so would also transport particles toward the coast, at least in surface waters.
We quantified upwelling regimes using two measures, a high resolution (to 0.25o [28 km] latitude) dataset used in analyses of OR and NZ data in which we used the Ekman cross-shelf transport component (e.g., see Close et al. 2020), and in analyses including CA data, the globally available Bakun upwelling index (Bakun, 1975). Units of both are m3 water * sec-1 * 100m of coastline. These metrics were highly correlated (p < 0.0001, adj. R2 = 0.92) indicating using these alternatives should give comparable results. Although an updated upwelling index (CUTI, Jacox et al., 2016) is available for California Current sites, it has not yet been extended to NZ. We calculated the monthly average upwelling index at each site for the period of study in each LME. Upwelling intermittency was calculated as in Menge & Menge (2013; p. 290 and Appendix B: Figs. B2, B3) and shelf width was determined as detailed in Menge et al. (2015) for both OR and NZ. Data for 100m isobaths were obtained using the ETOPO1 database (see Appendix S1: Table S2)
Water Temperature. Seawater temperature was quantified using Onset HOBO TidBit ® (Onset Computer Corp., Bourne, MA, USA) replicate temperature loggers (n = 2 or 3) placed in situ in the low intertidal zone at each site. Loggers recorded at 15-minute (OR) to hourly (NZ) intervals, which were averaged to daily, then to monthly values for analysis. We used a detiding program (Menge et al., 2003) to separate air from water temperatures (hereafter termed intertidal sea surface temperature or ISST).
Nutrients and Phytoplankton. Nutrients (NO3 + NO2) and phytoplankton (proxied by Chlorophyll-a, hereafter Chl-a) were quantified using replicate (n = 3-5) bottle samples taken during low tides (see details in Menge et al. 1997, 1999, 2003, 2015). We used data averaged across upwelling months in OR (April-September in OR, October-March in NZ). Nutrient data were only available from 1999-2002 for NZ so we limited our comparisons of nutrients to upwelling months in those years in both NZ and OR.
Prey Recruitment. We considered prey recruitment to be an external (environmental) input in our analyses (see below). We quantified barnacle and mussel recruitment using standard collectors to test for associations between recruitment and experimental communities. Barnacle recruitment was determined using 10 x 10 cm PVC plates covered with Saf-T-Walk ® (3M), a rubbery rugose tape used as an anti-slip surface on boats. Such collectors have been widely used (e.g., Farrell et al., 1991; Broitman et al., 2008; Dudas et al., 2009; Menge, 1992; Menge et al., 1999, 2003, 2010, 2011, 2015; Menge & Menge, 2013, 2019; Navarrete et al., 2005, 2008; Pfaff et al., 2011, 2015), and provide an index of barnacle recruitment. Mussel recruitment was similarly determined using plastic mesh balls (Tuffies), also in wide use (references in previous sentence). Collectors (n = 5 replicates each) were placed in the lower mid intertidal zone near the experiments at all sites in both LMEs and replaced monthly in OR and monthly to quarterly in NZ. Samples were processed in the laboratory by counting recruits under a microscope. Barnacle recruits could usually be identified to species, but Oregon mussel recruits were difficult to identify to species so likely included both Mytilus californianus and M. trossulus. New Zealand mussel recruits of P. canaliculus and A. ater maioriensis were distinguishable but M. galloprovincialis and Xenostrobus pulex are very similar. In analyses, we combined all acorn barnacle and mussel recruits as "barnacle recruits" and "mussel recruits", respectively. We used data from the recruitment seasons (~April-November in OR, October-March in NZ) for 2003 through 2006.
Similar Biota and Functional Roles among Systems
The biota in each LME consisted of similar groups including some of the same genera, but few species occurred in both LMEs (Appendix S1: Table S3). Each LME had similar functional groups of macrophytes, sessile invertebrates (mytilid mussels, acorn and stalked barnacles), grazing herbivores (limpets and chitons), and predators (whelks, and sea stars). Further, each functional group consisted of morphologically similar species; both LMEs had larger and smaller species of mussels and barnacles, limpets and whelks of similar size and appearance, and similar apex sea star predators known to be dietary generalists and to consume similar prey (for details see Paine, 1971; Menge et al., 1994, 1999, 2003; Navarrete & Menge, 1996; Schiel, 2004, 2011; Novak, 2010, 2013). A few taxa occurred in, or were abundant in, one system but not the other. For example (1) surfgrass (e.g., Phyllospadix spp.) does not occur in NZ (but did not colonize our OR plots); (2) gooseneck barnacles Pollicipes polymerus are abundant in OR, but comparable stalked barnacles Calantica villosa and C. spinosa were sparse at NZ sites and mostly restricted to cryptic habitats; (3) the large chiton Katharina tunicata is abundant in OR but similar-sized chitons (e.g., Eudoxochiton nobilis) were sparse at our NZ sites; and (4) herbivorous fish and crabs can have effects at some sites in NZ (e.g., Rilov & Schiel, 2006; Taylor & Schiel, 2010). We have never observed crabs at our NZ sites, nor have we seen evidence of their activity or that of fish (e.g., broken or cracked mussel shells or bitten off barnacles), so feel it unlikely they had effects in our experiments. Crabs are sparse at our OR/CA sites, and possible fish predators seem restricted to calmer waters, and again, we've seen no signs of predation by these taxa at our sites. Despite these differences, the similarities remain striking and researchers familiar with one system quickly become comfortable working in the other.
In this study, because few species occurred in both systems, we focused on interactions at the functional-group or "trait-based" level. The taxa listed in Appendix S1: Table S3 were sorted into ten functional groups including crustose algae, filamentous algae, turf-forming algae, blade-forming algae, large brown algae, chthamaloid barnacles, balanoid barnacles, gooseneck barnacles, mussels and "other" (consisting mostly of sea anemones).
Community Patterns among Upwelling Regimes
Abundances. To provide the broader community context for the experiments, at all sites we quantified community structure, defined as abundance of sessile and mobile species, using three methods. In NZ, we conducted horizontal (i.e., parallel to the water's edge) transect-quadrat surveys for sessile organisms and small mobile organisms (e.g., Menge, 1976; Lubchenco & Menge, 1978). In OR and CA, we conducted vertical transect-quadrat surveys (i.e., perpendicular to water's edge, spanning the intertidal zones). In the horizontal transect-quadrat method, 0.25 m2 quadrats divided into 0.04 m2 subquadrats were placed at three-meter intervals along 30 m transect tapes placed in the center of the low-mid zone (i.e., the ~ 1 m-wide zone just below mussel beds) parallel to the water's edge. Abundance, quantified as percent cover of all sessile taxa, was estimated from photographs using the subquadrats (each covering 4% of the 100% of the quadrat area) as a guide to facilitate abundance scaling to the 1% level. Mobile organisms were then counted in each 0.25 m2 quadrat to provide density estimates. Mobile organism abundance estimates in vertical transect-quadrat photographic surveys (OR, CA) were done similarly; although transects ran from the low-mid zone to the high zone, we used only data from the low zone (i.e., the ~ 1 meter below the mussel bed). In OR and NZ, we also used larger belt transects in areas of sea star habitat (typically just below mussel beds or in channels) to quantify sea star abundance (e.g., Menge et al., 2011, 2016). Belt transects consisted of replicated 2 x 10 or 2 x 5 m plots placed parallel to the water's edge in which all sea stars were counted, weighed and measured. Here we present averages of percent cover data across 2015-2020 (6 surveys, OR and CA) and 1995-2016 (11 surveys, NZ), small mobile species (including limpets and chitons) density data from 2006-2016 (11 surveys, OR) and 2008-2016 (3 surveys, NZ), and sea star density data from 2005-07 (3 surveys, OR), and 2000-2019 (4 surveys, NZ).
Limpet Size. Because herbivore size could be related to herbivore impact as well as herbivore density, we quantified limpet size using two methods. In NZ, we measured species-specific limpet length directly in the field at each site using rulers and calipers. All accessible limpets (some were in crevices) in the vicinity of each transect were measured with the goal of measuring at least 200 individuals of each species. In OR, we measured limpets in photographs of experimental treatments (see below) using rulers placed at the edge of each plot as a scale. We used photographs taken in the second year of the experiment (i.e., after limpets recolonizing plots had grown to sizes like those of limpets in the vicinity) to ensure that sizes were representative.
Comparative Experiments Testing Top-Down Control Among Upwelling Regimes
Experimental Timing. In OR, the experiments testing predator x herbivore effects started in May 2005 at six sites, two each in three regions (from north to south, Capes Foulweather [hereafter northern region], Perpetua [central region], and Blanco [southern region]. In NZ, experiments began in October 2004 at four sites, two each on East and West coasts. Depending on the site, and how quickly an endpoint was reached (i.e., when little change occurred during several consecutive monitoring visits), experiments ran for 21-26 months in OR and 22-29 months in NZ (Appendix S2: Fig. S1). Although sampling was often monthly, for easier analysis and comparison, we averaged samples by season (termed a "sample period") in each LME with OR sample periods lagged 6 calendar months after NZ sample periods. In sample periods 2-7, seasons were summer, fall, winter, spring, summer and fall. Because recovery was slow on the NZ East coast, the last two sample periods (8 and 9) were six and 12 months long (Appendix S2: Fig. S1).
Experimental Design. All experiments were established in the lower-mid zone, transitional between typically mussel-dominated mid zones and algal-dominated low zones. Plots ranged in tidal height from about 0.8 to 1.8 m (Appendix S1: Table S1). Reflecting the different tidal range between NZ east and west coasts, experiment heights were slightly lower at east than at west coast sites (Appendix S1: Table S1). The basic unit was a 25 x 25 cm square experimental plot, which was cleared of all biota using scrapers and wire brushes. Oven cleaner (NaOH) was then applied to remove most remaining algal and animal tissue. Treatments were (1) controls that allowed herbivore and predator access (abbreviated = +H+P), (2) predator exclusion (herbivores present, predators absent = +H-P), (3) herbivore exclusion (herbivores absent, predators present = -H+P), and (4) consumer exclusion (herbivores absent, predators absent = -H-P). Three control treatments, all +H+P, were included. To control for stainless-steel fences and antifouling paint (see below), we used partial (two-sided) fence controls (FC) and partial (strips with gaps) paint control barriers (PC). Plots with stainless steel lag screws at each corner served as marked plot controls (MP). MPs, FCs, and PCs allowed entry by limpets, chitons, whelks, sea stars, and crabs. The efficacy of the paint exclusion and fence methods to exclude or allow entry by limpets, the main herbivore group, was high (Appendix S2: Figs. S2, S3). Limpets were abundant in control (+H+P) and predator effect treatments (+H-P), and low in herbivore effect and consumer effect treatments (–H+P and –H-P). The design was blocked, with each block including all treatments, and with five replicate blocks per site. Blocks were spaced out on the shore, with 3-10 meters between each block.
Predator effects (+H-P) were tested by fastening four-sided stainless steel mesh fences or "open cages." Fences hindered entry by certain benthic predators (whelks, sea stars; but not crabs or fish) but allowed grazers (limpets, chitons) to enter (by crawling underneath cage edges) or recruit to the cages. Those few whelks entering cages (species shown in Appendix S1: Table S3) were removed at each monitoring visit. The only sea stars found in OR cages were one Pisaster ochraceus at SH (once), and occasional Leptasterias sp. at FC. No sea stars were found in NZ cages during monitoring visits.
Herbivore effects (-H+P) were tested by attaching a 3-5 cm wide strip of Z-Spar® (Pettit Paint A-788 Splash Zone marine epoxy) around each plot, smoothing the edges to ensure a continuous smooth surface was available to grazers, and applying a layer of copper-based antifouling paint (Coastal Copper 250 Ablative Antifouling Bottom Paint, 1st Marine Products) (e.g., Fig. 3). Prior research has shown that this effectively excludes limpets but does not impede whelks, sea stars, or crabs (Cubit, 1984; Menge, 2000; Freidenburg et al., 2007; Guerry, 2008; Guerry et al., 2009; Guerry & Menge, 2017). Herbivorous snails (e.g., species shown in Appendix S1: Table S3) are also not deterred by the paint, but at all OR and NZ sites were either sparse (Tegula, Lunella, Melagraphia, Diloma) and/or very small and unlikely to have much effect (littorines, Risselopsis). Consumer effects (-H-P) were tested by combining paint strips and stainless-steel fences (e.g., Fig. 3). Fences were attached to the rock and then surrounded by the Z-spar/paint barriers.
After initiation, abundances in plots were determined visually in the field or photographically during each monitoring visit by the senior author. Because prior experiments showed that changes typically were initially rapid and slowed over time, the frequency of visits varied, ranging from monthly during the first months of the experiment and extending to three (OR) to twelve (NZ) months. During monitoring visits, we removed invading grazers or predators from exclusion plots, repainted barriers as needed, and repaired damaged cages. In total, we analyzed 4,711 samples across all combinations of LME (n = 2) x Region (n = 5) x Site (n = 2 per region) x Treatments (n = 6) x Replicates (n = 5) x Sample dates (7 to 9 in NZ, 17 to 19 in OR, depending on region).
Data Analysis
To organize our results and categorize datasets, we have assembled each according to region, inclusive dates, the sites used, and in which figure(s) and/or table(s) analyses each dataset was used into Table 1. The table heading lists all sites used including core sites in each region and sites from which supplementary data were collected.
Data were analyzed using JMP v16.1.0 (SAS Institute, Inc., 2021), PRIMER 7, and PERMANOVA+ for PRIMER (Anderson & Gorley, 2008). We used natural log-transformed data (ln (x+1)) in JMP analyses and square root transformations in PRIMER analyses. We chose not to use arc-sine transformations because percent covers could range >100% due to algal layering or overgrowth. Factors in the PERMANOVA model included the nested spatial effects crossed with the time and treatment effects, including LME (large scale effects of OR and NZ as a random factor), region ne
Applications of neural network on the predictions of interference effect on design wind load of different geometry building
No full text碩士現代社會的都會區由於可利用的土地與空間有限且日漸減少的情況下，都市往上發展，興建高層建築成為不可避免的趨勢。由於高層建築相對於低矮建築來說勁度較低，且當建築物愈接近地面因地表粗糙度的關係所受到風力較小，因此愈高的建築物所受到的風力會愈大，所以在設計時就必須考慮到風力對高層建築物的影響。而在高樓林立之現今大都市中，除了單棟建築的風力之外，相鄰建築物間之風力交互作用也成為一個重要的問題，影響高層建築物間干擾效應的參數很多，如上游流場、建築物間的距離及主建物及干擾建物的尺寸等。
本文的風洞實驗數據顯示，在權重干擾指標部分，干擾指數會隨著建物高度而增大，因此可知當主建物與干擾建物相同時，其高寬比愈大所產生的干擾效應也會隨著增大。
本文主要是利用類神經網路對目前已有的干擾效應資料庫來進行干擾係數的預測，最後再利用所預測的干擾係數來計算出設計風載重。研究使用的類神經網路為輻狀基底函數類神經網路，其主要架構分為輸入層、一層隱藏層及輸出層，在使用遞增式的方法選取出中心點後透過隱藏層中的輻狀基底函數來尋求出網路模式。
由本文的結果得知，在訓練資料的預測方面絕大多數的誤差都低於3%，僅有少數幾點偏高一些，但仍然都在5%以下，在預測資料上，A(α=0.32)、B(α=0.25)、C(α=0.15)三個地況中，除了C地況在順風向動態背景方面平均誤差較高外，其餘在靜態及動態背景部份平均誤差皆低於7%，動態共振部份A、B地況介於7~12%之間，但在最複雜的C地況則大多介於15~22%之間，因此在共振部份的預測仍需加強。Tall building plays an important role in the city development due to the limited land, and the interference effects from the adjacent buildings cannot be ignored. Due to the complexity of the interference phenomenon, the building interference phenomenon is too complicated a problem for traditional engineering approaches. A more sensible way to deal with this problem would be using good quality aerodynamic database with IT techniques such as neural network. The aim of this thesis is to construct an aerodynamic database on building interference that can be used together with the wind code or/and single building’s aerodynamic database for wind resistant design of tall buildings.
Through the comparison of the weighted interference index, the results of wind tunnel experiments indicate, that the interference effects increase with buildings aspect ratio.
In this study the Artificial Neural Network technique was applied on an existing limited aerodynamic database to predict tall buildings’ interference factor (IF), and use the result to calculate design wind load. The ANN model is radial basis function (RBF) neural network, and the framework includes input layer, a single hidden layer and output layer. By centers and radial basis function in the hidden layer to create a neural network. The results indicate that, in the training phase, the error almost can smaller than 3%, in the predicting phase, except acrosswind background part in terrain C ,the static part and background part in all terrain are less than 7%. The resonant part in terrain A&B are within 7% to 12%. However, in terrain C the error of resonant part can be as large as 15% to 22%. In other words the resonant part need to be further improved.目錄
第一章 緒論 …………………………………………………… 1
1.1 研究動機………………………………………………… 1
1.2 研究方法………………………………………………… 2
1.3 研究內容………………………………………………… 3
1.4 論文架構………………………………………………… 4
第二章 文獻回顧 ……………………………………………… 6
2.1 大氣邊界層與流場之模………………………………… 6
2.2 雷諾數效………………………………………………… 7
2.3 風洞實驗之阻塞效應 ………………………………… 8
2.4 力平衡儀之風洞量測 ………………………………… 8
2.5 干擾效應對順風向的影響……………………………… 9
2.5.1 干擾效應對順風向風力頻譜之影響 ………………… 9
2.5.2 干擾效應對順風向風力係數之影響 ………………… 9
2.6 干擾效應對橫風向的影響 …………………………… 10
2.6.1 干擾效應對橫風向風力頻譜之影響 ………………… 10
2.6.2 干擾效應對橫風向風力係數之影響 ………………… 10
2.7 干擾係數………………………………………………… 11
2.7.1 順風向靜態 …………………………………………… 11
2.7.2 順風向動態 …………………………………………… 12
2.7.3 橫風向動態 …………………………………………… 12
2.8 高樓風載重各分量之相關性…………………………… 13
2.9 干擾係數之預測………………………………………… 13
2.9.1 類神經網路 …………………………………………… 13
2.9.2 利用類神經網路預測干擾係數 ……………………… 14
第三章 理論背景 ……………………………………………… 15
3.1 大氣邊界層流場特性概述……………………………… 15
3.1.1 平均風速剖面 ………………………………………… 15
3.1.2 紊流強度 ……………………………………………… 17
3.1.3 紊流長度尺度 ………………………………………… 18
3.1.4 擾動風速頻譜 ………………………………………… 19
3.2 鈍體氣動力現象………………………………………… 20
3.3 結構物風載重…………………………………………… 22
3.3.1 順風向風力作用 ……………………………………… 22
3.3.2 橫風向風力作用 ……………………………………… 23
3.4 高頻力平衡儀…………………………………………… 24
3.4.1 力平衡儀量測架構 …………………………………… 24
3.4.2 力平衡儀量測基本原理 ……………………………… 25
3.4.3 實驗中使用之公式推導 ……………………………… 27
3.5 干擾效應………………………………………………… 31
3.5.1 干擾係數 ……………………………………………… 31
3.5.2 干擾效應下的設計風載重 …………………………… 32
3.5.3 干擾指標 (Interference Index)…………………… 32
3.6 類神經網路……………………………………………… 33
3.6.1 輻狀基底函數類神經網路 …………………………… 33
第四章 實驗設置與數據處理 ………………………………… 36
4.1 干擾效應實驗及資料庫說明…………………………… 36
4.1.1 風洞設備 ……………………………………………… 36
4.1.2 大氣邊界層流場之模擬 ……………………………… 36
4.1.3 風速量測 ……………………………………………… 38
4.1.4 風力量測 ……………………………………………… 38
4.1.5 六軸力平衡儀之描述 ………………………………… 39
4.1.6 力平衡儀量測系列之架設 …………………………… 39
4.1.7 改變干擾建築物高度比及寬度比系列 ……………… 39
4.1.8 改變主要量測建築物斷面系列 ……………………… 41
4.1.9 實驗座標系統 ………………………………………… 42
4.2 類神經網路主題說明…………………………………… 44
4.2.1 輻狀基底函數類神經網路架構 ……………………… 44
4.2.2 使用參數及資料庫之訂定 …………………………… 44
第五章 實驗結果與討論 ……………………………………… 50
5.1 資料庫內容之說明……………………………………… 51
5.2 類神經網路預測………………………………………… 52
5.2.1 類神經網路模式的建立 ……………………………… 52
5.2.2 干擾係數預測點資料之分佈與預測 ………………… 59
5.2.3 設計風載重 …………………………………………… 67
5.3 干擾效應實驗結果之探討……………………………… 83
5.3.1 C地況之干擾效應探討 ……………………………… 83
5.3.2 B地況之干擾效應探討 ……………………………… 84
5.3.3 A地況之干擾效應探討 ……………………………… 86
第六章 結論與建議 …………………………………………… 88
6.1 結論……………………………………………………… 88
6.2 建議……………………………………………………… 89
第七章 參考文獻 ……………………………………………… 90
圖目錄
圖(3-1) m隨Zo遞增之關係圖-------------------------------- 94
圖(3-2) 鈍體分離流及渦漩示意圖--------------------------- 94
圖(3-3) 實驗模型之座標軸及0度角定義圖-------------------- 95
圖(3-4) 模型與力平衡儀之動力反應頻譜轉換圖--------------- 96
圖(3-5) 輻狀基底函數類神經網路架構----------------------- 34
圖(4-1) 淡江大學結構氣動力風洞實驗室平面圖--------------- 97
圖(4-2) 地況A、B、C之(1)平均風速(2)紊流強度(3)長度尺度 剖面----------- 98
圖(4-3) 決定擾流板之高度與寬度之經驗曲線圖--------------- 99
圖(4-4) 地況C與地況A之邊界層模擬圖---------------------- 100
圖(4-5) 地況A、B、C之錐形擾流板設計尺寸圖--------------- 101
圖(4-6) 模擬邊界層流場之粗糙元素尺寸圖------------------ 103
圖(4-7) 淡江大學邊界層一號風洞實驗室內部設置圖---------- 104
圖(4-8) 本實驗所採用之力平衡儀各構件圖------------------ 104
圖(4-9) 改變干擾建物高寬比系列--------------------------- 40
圖(4-10) 改變主要建物與干擾建物高寬比系列---------------- 41
圖(4-11) 干擾效應113點實驗座標系統圖--------------------- 42
圖(4-12) 干擾效應84點實驗座標系統圖---------------------- 43
圖(4-13) 干擾效應24點實驗座標系統圖---------------------- 43
圖(5-1) C地況實驗與預測值的比較-------------------------- 60
圖(5-2) C地況類神經網路干擾係數預測之絕對誤差------------ 61
圖(5-3) C地況忽略共振部份實驗與預測值比較---------------- 62
圖(5-4) B地況實驗與預測值的比較-------------------------- 63
圖(5-5) B地況類神經網路干擾係數預測之絕對誤差------------ 64
圖(5-6) B地況忽略共振部份實驗與預測值比較---------------- 65
圖(5-7) A地況實驗與預測值的比較-------------------------- 66
圖(5-8) A地況類神經網路干擾係數預測之絕對誤差------------ 66
圖(5-9) A地況忽略共振部份實驗與預測值比較---------------- 67
圖(5-10) C地況無因次化頻率0.2順風向預測干擾係數與設計風載重誤差比較-68
圖(5-11) C地況無因次化頻率0.2橫風向預測干擾係數與設計風載重誤差比較-69
圖(5-12) C地況無因次化頻率0.2實驗、預測及單棟設計風載重之比較----------70
圖(5-13) C地況無因次化頻率0.3順風向預測干擾係數與設計風載重誤差比較-71
圖(5-14) C地況無因次化頻率0.3橫風向預測干擾係數與設計風載重誤差比較-71
圖(5-15) C地況無因次化頻率0.3實驗、預測及單棟設計風載重之比較----------73
圖(5-16) B地況無因次化頻率0.2順風向預測干擾係數與設計風載重誤差比較-74
圖(5-17) B地況無因次化頻率0.2橫風向預測干擾係數與設計風載重誤差比較-74
圖(5-18) B地況無因次化頻率0.2實驗、預測及單棟設計風載重之比較----------75
圖(5-19) B地況無因次化頻率0.3順風向預測干擾係數與設計風載重誤差比較-76
圖(5-20) B地況無因次化頻率0.3橫風向預測干擾係數與設計風載重誤差比較-76
圖(5-21) B地況無因次化頻率0.3實驗、預測及單棟設計風載重之比較----------77
圖(5-22) A地況無因次化頻率0.2順風向預測干擾係數與設計風載重誤差比較-79
圖(5-23) A地況無因次化頻率0.2橫風向預測干擾係數與設計風載重誤差比較-79
圖(5-24) A地況無因次化頻率0.2實驗、預測及單棟設計風載重之比較----------80
圖(5-25) A地況無因次化頻率0.3順風向預測干擾係數與設計風載重誤差比較-81
圖(5-26) A地況無因次化頻率0.3橫風向預測干擾係數與設計風載重誤差比較-81
圖(5-27) A地況無因次化頻率0.3實驗、預測及單棟設計風載重之比較----------82
圖(5-28) BH2-BH2順風向平均風力干擾係數(等值線圖)-------- 105
圖(5-29) BH2-BH2順風向平均風力干擾係數(分佈圖)---------- 105
圖(5-30) BH2-BH2順風向背景部份干擾係數(等值線圖)-------- 105
圖(5-31) BH2-BH2順風向背景部份干擾係數(分佈圖)---------- 106
圖(5-32) BH2-BH2橫風向背景部份干擾係數(等值線圖)-------- 106
圖(5-33) BH2-BH2橫風向背景部份干擾係數(分佈圖)---------- 106
圖(5-34) BH2-BH2無因次化頻率0.2順風向共振干擾係數(等值線圖)----------- 107
圖(5-35) BH2-BH2無因次化頻率0.2順風向共振干擾係數(分佈圖)-------------- 107
圖(5-36) BH2-BH2無因次化頻率0.2橫風向共振干擾係數(等值線圖)----------- 107
圖(5-37) BH2-BH2無因次化頻率0.2橫風向共振干擾係數(分佈圖)-------------- 108
圖(5-38) BH2-BH2無因次化頻率0.3順風向共振干擾係數(等值線圖)----------- 108
圖(5-39) BH2-BH2無因次化頻率0.3順風向共振干擾係數(分佈圖)-------------- 108
圖(5-40) BH2-BH2無因次化頻率0.3橫風向共振干擾係數(等值線圖)----------- 109
圖(5-41) BH2-BH2無因次化頻率0.3橫風向共振干擾係數(分佈圖)-------------- 109
圖(5-42) BH3-BH3順風向平均風力干擾係數(等值線圖)-------- 110
圖(5-43) BH3-BH3順風向平均風力干擾係數(分佈圖)---------- 110
圖(5-44) BH3-BH3順風向背景部份干擾係數(等值線圖)-------- 110
圖(5-45) BH3-BH3順風向背景部份干擾係數(分佈圖)---------- 111
圖(5-46) BH3-BH3橫風向背景部份干擾係數(等值線圖)-------- 111
圖(5-47) BH3-BH3橫風向背景部份干擾係數(分佈圖)---------- 111
圖(5-48) BH3-BH3無因次化頻率0.2順風向共振干擾係數(等值線圖)----------- 112
圖(5-49) BH3-BH3無因次化頻率0.2順風向共振干擾係數(分佈圖)-------------- 112
圖(5-50) BH3-BH3無因次化頻率0.2橫風向共振干擾係數(等值線圖)----------- 112
圖(5-51) BH3-BH3無因次化頻率0.2橫風向共振干擾係數(分佈圖)-------------- 113
圖(5-52) BH3-BH3無因次化頻率0.3順風向共振干擾係數(等值線圖)----------- 113
圖(5-53) BH3-BH3無因次化頻率0.3順風向共振干擾係數(分佈圖)-------------- 113
圖(5-54) BH3-BH3無因次化頻率0.3橫風向共振干擾係數(等值線圖)----------- 114
圖(5-55) BH3-BH3無因次化頻率0.3橫風向共振干擾係數(分佈圖)-------------- 114
圖(5-56) BH4-BH4順風向平均風力干擾係數(等值線圖)-------- 115
圖(5-57) BH4-BH4順風向平均風力干擾係數(分佈圖)---------- 115
圖(5-58) BH4-BH4順風向背景部份干擾係數(等值線圖)-------- 115
圖(5-59) BH4-BH4順風向背景部份干擾係數(分佈圖)---------- 116
圖(5-60) BH4-BH4橫風向背景部份干擾係數(等值線圖)-------- 116
圖(5-61) BH4-BH4橫風向背景部份干擾係數(分佈圖)---------- 116
圖(5-62) BH4-BH4無因次化頻率0.2順風向共振干擾係數(等值線圖)----------- 117
圖(5-63) BH4-BH4無因次化頻率0.2順風向共振干擾係數(分佈圖)-------------- 117
圖(5-64) BH4-BH4無因次化頻率0.2橫風向共振干擾係數(等值線圖)----------- 117
圖(5-65) BH4-BH4無因次化頻率0.2橫風向共振干擾係數(分佈圖)-------------- 118
圖(5-66) BH4-BH4無因次化頻率0.3順風向共振干擾係數(等值線圖)----------- 118
圖(5-67) BH4-BH4無因次化頻率0.3順風向共振干擾係數(分佈圖)-------------- 118
圖(5-68) BH4-BH4無因次化頻率0.3橫風向共振干擾係數(等值線圖)----------- 119
圖(5-69) BH4-BH4無因次化頻率0.3橫風向共振干擾係數(分佈圖)-------------- 119
圖(5-70) BH5-BH5順風向平均風力干擾係數(等值線圖)-------- 120
圖(5-71) BH5-BH5順風向平均風力干擾係數(分佈圖)---------- 120
圖(5-72) BH5-BH5順風向背景部份干擾係數(等值線圖)-------- 120
圖(5-73) BH5-BH5順風向背景部份干擾係數(分佈圖)---------- 121
圖(5-74) BH5-BH5橫風向背景部份干擾係數(等值線圖)-------- 121
圖(5-75) BH5-BH5橫風向背景部份干擾係數(分佈圖)---------- 121
圖(5-76) BH5-BH5無因次化頻率0.2順風向共振干擾係數(等值線圖)----------- 122
圖(5-77) BH5-BH5無因次化頻率0.2順風向共振干擾係數(分佈圖)-------------- 122
圖(5-78) BH5-BH5無因次化頻率0.2橫風向共振干擾係數(等值線圖)----------- 122
圖(5-79) BH5-BH5無因次化頻率0.2橫風向共振干擾係數(分佈圖)-------------- 123
圖(5-80) BH5-BH5無因次化頻率0.3順風向共振干擾係數(等值線圖)----------- 123
圖(5-81) BH5-BH5無因次化頻率0.3順風向共振干擾係數(分佈圖)-------------- 123
圖(5-82) BH5-BH5無因次化頻率0.3橫風向共振干擾係數(等值線圖)----------- 124
圖(5-83) BH5-BH5無因次化頻率0.3橫風向共振干擾係數(分佈圖)-------------- 124
圖(5-84) BH6-BH6順風向平均風力干擾係數(等值線圖)-------- 125
圖(5-85) BH6-BH6順風向平均風力干擾係數(分佈圖)---------- 125
圖(5-86) BH6-BH6順風向背景部份干擾係數(等值線圖)-------- 125
圖(5-87) BH6-BH6順風向背景部份干擾係數(分佈圖)---------- 126
圖(5-88) BH6-BH6橫風向背景部份干擾係數(等值線圖)-------- 126
圖(5-89) BH6-BH6橫風向背景部份干擾係數(分佈圖)---------- 126
圖(5-90) BH6-BH6無因次化頻率0.2順風向共振干擾係數(等值線圖)----------- 127
圖(5-91) BH6-BH6無因次化頻率0.2順風向共振干擾係數(分佈圖)-------------- 127
圖(5-92) BH6-BH6無因次化頻率0.2橫風向共振干擾係數(等值線圖)----------- 127
圖(5-93) BH6-BH6無因次化頻率0.2橫風向共振干擾係數(分佈圖)-------------- 128
圖(5-94) BH6-BH6無因次化頻率0.3順風向共振干擾係數(等值線圖)----------- 128
圖(5-95) BH6-BH6無因次化頻率0.3順風向共振干擾係數(分佈圖)-------------- 128
圖(5-96) BH6-BH6無因次化頻率0.3橫風向共振干擾係數(等值線圖)----------- 129
圖(5-97) BH6-BH6無因次化頻率0.3橫風向共振干擾係數(分佈圖)-------------- 129
圖(5-98) BH2-BH2順風向平均風力干擾係數(等值線圖)-------- 130
圖(5-99) BH2-BH2順風向平均風力干擾係數(分佈圖)---------- 130
圖(5-100) BH2-BH2順風向背景部份干擾係數(等值線圖)------- 130
圖(5-101) BH2-BH2順風向背景部份干擾係數(分佈圖)--------- 131
圖(5-102) BH2-BH2橫風向背景部份干擾係數(等值線圖)------- 131
圖(5-103) BH2-BH2橫風向背景部份干擾係數(分佈圖)--------- 131
圖(5-104) BH2-BH2無因次化頻率0.2順風向共振干擾係數(等值線圖)--------- 132
圖(5-105) BH2-BH2無因次化頻率0.2順風向共振干擾係數(分佈圖)------------ 132
圖(5-106) BH2-BH2無因次化頻率0.2橫風向共振干擾係數(等值線圖)--------- 132
圖(5-107) BH2-BH2無因次化頻率0.2橫風向共振干擾係數(分佈圖)------------ 133
圖(5-108) BH2-BH2無因次化頻率0.3順風向共振干擾係數(等值線圖)--------- 133
圖(5-109) BH2-BH2無因次化頻率0.3順風向共振干擾係數(分佈圖)------------ 133
圖(5-110) BH2-BH2無因次化頻率0.3橫風向共振干擾係數(等值線圖)--------- 134
圖(5-111) BH2-BH2無因次化頻率0.3橫風向共振干擾係數(分佈圖)------------ 134
圖(5-112) BH3-BH3順風向平均風力干擾係數(等值線圖)------- 135
圖(5-113) BH3-BH3順風向平均風力干擾係數(分佈圖)--------- 135
圖(5-114) BH3-BH3順風向背景部份干擾係數(等值線圖)------- 135
圖(5-115) BH3-BH3順風向背景部份干擾係數(分佈圖)--------- 136
圖(5-116) BH3-BH3橫風向背景部份干擾係數(等值線圖)------- 136
圖(5-117) BH3-BH3橫風向背景部份干擾係數(分佈圖)--------- 136
圖(5-118) BH3-BH3無因次化頻率0.2順風向共振干擾係數(等值線圖)--------- 137
圖(5-119) BH3-BH3無因次化頻率0.2順風向共振干擾係數(分佈圖)------------ 137
圖(5-120) BH3-BH3無因次化頻率0.2橫風向共振干擾係數(等值線圖)--------- 137
圖(5-121) BH3-BH3無因次化頻率0.2橫風向共振干擾係數(分佈圖)------------ 138
圖(5-122) BH3-BH3無因次化頻率0.3順風向共振干擾係數(等值線圖)--------- 138
圖(5-123) BH3-BH3無因次化頻率0.3順風向共振干擾係數(分佈圖)------------ 138
圖(5-124) BH3-BH3無因次化頻率0.3橫風向共振干擾係數(等值線圖)--------- 139
圖(5-125) BH3-BH3無因次化頻率0.3橫風向共振干擾係數(分佈圖)------------ 139
圖(5-126) BH4-BH4順風向平均風力干擾係數(等值線圖)------- 140
圖(5-127) BH4-BH4順風向平均風力干擾係數(分佈圖)--------- 140
圖(5-128) BH4-BH4順風向背景部份干擾係數(等值線圖)------- 140
圖(5-129) BH4-BH4順風向背景部份干擾係數(分佈圖)--------- 141
圖(5-130) BH4-BH4橫風向背景部份干擾係數(等值線圖)------- 141
圖(5-131) BH4-BH4橫風向背景部份干擾係數(分佈圖)--------- 141
圖(5-132) BH4-BH4無因次化頻率0.2順風向共振干擾係數(等值線圖)--------- 142
圖(5-133) BH4-BH4無因次化頻率0.2順風向共振干擾係數(分佈圖)------------ 142
圖(5-134) BH4-BH4無因次化頻率0.2橫風向共振干擾係數(等值線圖)--------- 142
圖(5-135) BH4-BH4無因次化頻率0.2橫風向共振干擾係數(分佈圖)------------ 143
圖(5-136) BH4-BH4無因次化頻率0.3順風向共振干擾係數(等值線圖)--------- 143
圖(5-137) BH4-BH4無因次化頻率0.3順風向共振干擾係數(分佈圖)------------ 143
圖(5-138) BH4-BH4無因次化頻率0.3橫風向共振干擾係數(等值線圖)--------- 144
圖(5-139) BH4-BH4無因次化頻率0.3橫風向共振干擾係數(分佈圖)------------ 144
圖(5-140) BH5-BH5順風向平均風力干擾係數(等值線圖)------- 145
圖(5-141) BH5-BH5順風向平均風力干擾係數(分佈圖)--------- 145
圖(5-142) BH5-BH5順風向背景部份干擾係數(等值線圖)------- 145
圖(5-143) BH5-BH5順風向背景部份干擾係數(分佈圖)--------- 146
圖(5-144) BH5-BH5橫風向背景部份干擾係數(等值線圖)------- 146
圖(5-145) BH5-BH5橫風向背景部份干擾係數(分佈圖)--------- 146
圖(5-146) BH5-BH5無因次化頻率0.2順風向共振干擾係數(等值線圖)--------- 147
圖(5-147) BH5-BH5無因次化頻率0.2順風向共振干擾係數(分佈圖)------------ 147
圖(5-148) BH5-BH5無因次化頻率0.2橫風向共振干擾係數(等值線圖)--------- 147
圖(5-149) BH5-BH5無因次化頻率0.2橫風向共振干擾係數(分佈圖)------------ 148
圖(5-150) BH5-BH5無因次化頻率0.3順風向共振干擾係數(等值線圖)--------- 148
圖(5-151) BH5-BH5無因次化頻率0.3順風向共振干擾係數(分佈圖)------------ 148
圖(5-152) BH5-BH5無因次化頻率0.3橫風向共振干擾係數(等值線圖)--------- 149
圖(5-153) BH5-BH5無因次化頻率0.3橫風向共振干擾係數(分佈圖)------------ 149
圖(5-154) BH6-BH6順風向平均風力干擾係數(等值線圖)------- 150
圖(5-155) BH6-BH6順風向平均風力干擾係數(分佈圖)--------- 150
圖(5-156) BH6-BH6順風向背景部份干擾係數(等值線圖)------- 150
圖(5-157) BH6-BH6順風向背景部份干擾係數(分佈圖)--------- 151
圖(5-158) BH6-BH6橫風向背景部份干擾係數(等值線圖)------- 151
圖(5-159) BH6-BH6橫風向背景部份干擾係數(分佈圖)--------- 151
圖(5-160) BH6-BH6無因次化頻率0.2順風向共振干擾係數(等值線圖)--------- 152
圖(5-161) BH6-BH6無因次化頻率0.2順風向共振干擾係數(分佈圖)------------ 152
圖(5-162) BH6-BH6無因次化頻率0.2橫風向共振干擾係數(等值線圖)--------- 152
圖(5-163) BH6-BH6無因次化頻率0.2橫風向共振干擾係數(分佈圖)------------ 153
圖(5-164) BH6-BH6無因次化頻率0.3順風向共振干擾係數(等值線圖)--------- 153
圖(5-165) BH6-BH6無因次化頻率0.3順風向共振干擾係數(分佈圖)------------ 153
圖(5-166) BH6-BH6無因次化頻率0.3橫風向共振干擾係數(等值線圖)--------- 154
圖(5-167) BH6-BH6無因次化頻率0.3橫風向共振干擾係數(分佈圖)------------ 154
圖(5-168) BH2-BH2順風向平均風力干擾係數(等值線圖)------- 155
圖(5-169) BH2-BH2順風向平均風力干擾係數(分佈圖)--------- 155
圖(5-170) BH2-BH2順風向背景部份干擾係數(等值線圖)------- 155
圖(5-171) BH2-BH2順風向背景部份干擾係數(分佈圖)--------- 156
圖(5-172) BH2-BH2橫風向背景部份干擾係數(等值線圖)------- 156
圖(5-173) BH2-BH2橫風向背景部份干擾係數(分佈圖)--------- 156
圖(5-174) BH2-BH2無因次化頻率0.2順風向共振干擾係數(等值線圖)--------- 157
圖(5-175) BH2-BH2無因次化頻率0.2順風向共振干擾係數(分佈圖)------------ 157
圖(5-176) BH2-BH2無因次化頻率0.2橫風向共振干擾係數(等值線圖)--------- 157
圖(5-177) BH2-BH2無因次化頻率0.2橫風向共振干擾係數(分佈圖)------------ 158
圖(5-178) BH2-BH2無因次化頻率0.3順風向共振干擾係數(等值線圖)--------- 158
圖(5-179) BH2-BH2無因次化頻率0.3順風向共振干擾係數(分佈圖)------------ 158
圖(5-180) BH2-BH2無因次化頻率0.3橫風向共振干擾係數(等值線圖)--------- 159
圖(5-181) BH2-BH2無因次化頻率0.3橫風向共振干擾係數(分佈圖)------------ 159
圖(5-182) BH3-BH3順風向平均風力干擾係數(等值線圖)------- 160
圖(5-183) BH3-BH3順風向平均風力干擾係數(分佈圖)--------- 160
圖(5-184) BH3-BH3順風向背景部份干擾係數(等值線圖)------- 160
圖(5-185) BH3-BH3順風向背景部份干擾係數(分佈圖)--------- 161
圖(5-186) BH3-BH3橫風向背景部份干擾係數(等值線圖)------- 161
圖(5-187) BH3-BH3橫風向背景部份干擾係數(分佈圖)--------- 161
圖(5-188) BH3-BH3無因次化頻率0.2順風向共振干擾係數(等值線圖)--------- 162
圖(5-189) BH3-BH3無因次化頻率0.2順風向共振干擾係數(分佈圖)------------ 162
圖(5-190) BH3-BH3無因次化頻率0.2橫風向共振干擾係數(等值線圖)--------- 162
圖(5-191) BH3-BH3無因次化頻率0.2橫風向共振干擾係數(分佈圖)------------ 163
圖(5-192) BH3-BH3無因次化頻率0.3順風向共振干擾係數(等值線圖)--------- 163
圖(5-193) BH3-BH3無因次化頻率0.3順風向共振干擾係數(分佈圖)------------ 163
圖(5-194) BH3-BH3無因次化頻率0.3橫風向共振干擾係數(等值線圖)--------- 164
圖(5-195) BH3-BH3無因次化頻率0.3橫風向共振干擾係數(分佈圖)------------ 164
圖(5-196) BH4-BH4順風向平均風力干擾係數(等值線圖)------- 165
圖(5-197) BH4-BH4順風向平均風力干擾係數(分佈圖)--------- 165
圖(5-198) BH4-BH4順風向背景部份干擾係數(等值線圖)------- 165
圖(5-199) BH4-BH4順風向背景部份干擾係數(分佈圖)--------- 166
圖(5-200) BH4-BH4橫風向背景部份干擾係數(等值線圖)------- 166
圖(5-201) BH4-BH4橫風向背景部份干擾係數(分佈圖)--------- 166
圖(5-202) BH4-BH4無因次化頻率0.2順風向共振干擾係數(等值線圖)--------- 167
圖(5-203) BH4-BH4無因次化頻率0.2順風向共振干擾係數(分佈圖)------------ 167
圖(5-204) BH4-BH4無因次化頻率0.2橫風向共振干擾係數(等值線圖)--------- 167
圖(5-205) BH4-BH4無因次化頻率0.2橫風向共振干擾係數(分佈圖)------------ 168
圖(5-206) BH4-BH4無因次化頻率0.3順風向共振干擾係數(等值線圖)--------- 168
圖(5-207) BH4-BH4無因次化頻率0.3順風向共振干擾係數(分佈圖)------------ 168
圖(5-208) BH4-BH4無因次化頻率0.3橫風向共振干擾係數(等值線圖)--------- 169
圖(5-209) BH4-BH4無因次化頻率0.3橫風向共振干擾係數(分佈圖)------------ 169
圖(5-210) BH5-BH5順風向平均風力干擾係數(等值線圖)------- 170
圖(5-211) BH5-BH5順風向平均風力干擾係數(分佈圖)--------- 170
圖(5-212) BH5-BH5順風向背景部份干擾係數(等值線圖)------- 170
圖(5-213) BH5-BH5順風向背景部份干擾係數(分佈圖)--------- 171
圖(5-214) BH5-BH5橫風向背景部份干擾係數(等值線圖)------- 171
圖(5-215) BH5-BH5橫風向背景部份干擾係數(分佈圖)--------- 171
圖(5-216) BH5-BH5無因次化頻率0.2順風向共振干擾係數(等值線圖)--------- 172
圖(5-217) BH5-BH5無因次化頻率0.2順風向共振干擾係數(分佈圖)------------ 172
圖(5-218) BH5-BH5無因次化頻率0.2橫風向共振干擾係數(等值線圖)--------- 172
圖(5-219) BH5-BH5無因次化頻率0.2橫風向共振干擾係數(分佈圖)------------ 173
圖(5-220) BH5-BH5無因次化頻率0.3順風向共振干擾係數(等值線圖)--------- 173
圖(5-221) BH5-BH5無因次化頻率0.3順風向共振干擾係數(分佈圖)------------ 173
圖(5-222) BH5-BH5無因次化頻率0.3橫風向共振干擾係數(等值線圖)--------- 174
圖(5-223) BH5-BH5無因次化頻率0.3橫風向共振干擾係數(分佈圖)------------ 174
圖(5-224) BH6-BH6順風向平均風力干擾係數(等值線圖)------- 175
圖(5-225) BH6-BH6順風向平均風力干擾係數(分佈圖)--------- 175
圖(5-226) BH6-BH6順風向背景部份干擾係數(等值線圖)------- 175
圖(5-227) BH6-BH6順風向背景部份干擾係數(分佈圖)--------- 176
圖(5-228) BH6-BH6橫風向背景部份干擾係數(等值線圖)------- 176
圖(5-229) BH6-BH6橫風向背景部份干擾係數(分佈圖)--------- 176
圖(5-230) BH6-BH6無因次化頻率0.2順風向共振干擾係數(等值線圖)--------- 177
圖(5-231) BH6-BH6無因次化頻率0.2順風向共振干擾係數(分佈圖)------------ 177
圖(5-232) BH6-BH6無因次化頻率0.2橫風向共振干擾係數(等值線圖)--------- 177
圖(5-233) BH6-BH6無因次化頻率0.2橫風向共振干擾係數(分佈圖)------------ 178
圖(5-234) BH6-BH6無因次化頻率0.3順風向共振干擾係數(等值線圖)--------- 178
圖(5-235) BH6-BH6無因次化頻率0.3順風向共振干擾係數(分佈圖)------------ 178
圖(5-236) BH6-BH6無因次化頻率0.3橫風向共振干擾係數(等值線圖)--------- 179
圖(5-237) BH6-BH6無因次化頻率0.3橫風向共振干擾係數(分佈圖)------------ 179
表目錄
表(3-1) 指數律參數建議值----------------------------------16
表(3-2) 對數律參數建議值----------------------------------17
表(3-3) 常用β值與 的關係---------------------------------18
表(3-4) 各型式之輻狀基底函數------------------------------35
表(4-1) 改變寬度比系列模型尺寸----------------------------40
表(4-2) 改變高度比系列模型尺寸----------------------------41
表(4-3) 改變主要建築物與干擾建物系列模型尺寸--------------41
表(4-4) A地況干擾效應資料庫-------------------------------45
表(4-5) B地況干擾效應資料庫-------------------------------45
表(4-6) C地況干擾效應資料庫-------------------------------46
表(4-7) A地況，預測點為BH2-BH2，干擾效應(篩選)資料庫------46
表(4-8) A地況，預測點為BH3-BH3，干擾效應(篩選)資料庫------46
表(4-9) A地況，預測點為BH4-BH4，干擾效應(篩選)資料庫------46
表(4-10) A地況，預測點為BH5-BH5，干擾效應(篩選)資料庫-----47
表(4-11) A地況，預測點為BH6-BH6，干擾效應(篩選)資料庫-----47
表(4-12) B地況，預測點為BH2-BH2，干擾效應(篩選)資料庫-----47
表(4-13) B地況，預測點為BH3-BH3，干擾效應(篩選)資料庫-----47
表(4-14) B地況，預測點為BH4-BH4，干擾效應(篩選)資料庫-----47
表(4-15) B地況，預測點為BH5-BH5，干擾效應(篩選)資料庫-----48
表(4-16) B地況，預測點為BH6-BH6，干擾效應(篩選)資料庫-----48
表(4-17) C地況，預測點為BH2-BH2，干擾效應(篩選)資料庫-----48
表(4-18) C地況，預測點為BH3-BH3，干擾效應(篩選)資料庫-----48
表(4-19) C地況，預測點為BH4-BH4，干擾效應(篩選)資料庫-----48
表(4-20) C地況，預測點為BH5-BH5，干擾效應(篩選)資料庫-----49
表(4-21) C地況，預測點為BH6-BH6，干擾效應(篩選)資料庫-----49
表(5-1) 實驗室資料庫A、B、C地況數據列表-------------------51
表(5-2) C地況各項輸出變數之分散參數與MAE(完整資料庫)------50
表(5-3) B地況各項輸出變數之分散參數與MAE(完整資料庫)------50
表(5-4) A地況各項輸出變數之分散參數與MAE(完整資料庫)------50
表(5-5) C地況BH2各項輸出變數之MAE(篩選資料庫)-------------54
表(5-6) C地況BH3各項輸出變數之MAE(篩選資料庫)-------------54
表(5-7) C地況BH4各項輸出變數之MAE(篩選資料庫)-------------54
表(5-8) C地況BH5各項輸出變數之MAE(篩選資料庫)-------------55
表(5-9) C地況BH6各項輸出變數之MAE(篩選資料庫)-------------55
表(5-10) B地況BH2各項輸出變數之MAE(篩選資料庫)------------55
表(5-11) B地況BH3各項輸出變數之MAE(篩選資料庫)------------56
表(5-12) B地況BH4各項輸出變數之MAE(篩選資料庫)------------56
表(5-13) B地況BH5各項輸出變數之MAE(篩選資料庫)------------56
表(5-14) B地況BH6各項輸出變數之MAE(篩選資料庫)------------57
表(5-15) A地況BH2各項輸出變數之MAE(篩選資料庫)------------57
表(5-16) A地況BH3各項輸出變數之MAE(篩選資料庫)------------57
表(5-17) A地況BH4各項輸出變數之MAE(篩選資料庫)------------58
表(5-18) A地況BH5各項輸出變數之MAE(篩選資料庫)------------58表(5-19) A地況BH6各項輸出變數之MAE(篩選資料庫)------------58
表(5-19) A、B、C地況類神經網路預測資料點及干擾建築物組合--60
表(5-20) 干擾指數-WII (Terrain A)-------------------------93
表(5-21) 干擾指數-WII (Terrain B)-------------------------93
表(5-22) 干擾指數-WII (Terrain C)-------------------------93學號: 696380418, 學年度: 9
0006
No full textDAILY PALO ALTO TIMES. WEDNESDAY. SEPTEMBER 19.1917.
The Lure of Low Prices
In DYEING and CLEANING Means Trouble
TOO kmow aad -WK know tbat price* oa sll materials nsed tn tha
process ot Dyeing inti a*-ultc ar* asray ap*. IT MEANS MTJBSTt-
TCTION, a "had odor" and parhapa th* rata ol garaaata sooner or'
The F. THOMAS Parisian
DyeinfJ and Cleaning Works
H»t. . npauuo. of arte Ot rear, toe
AT MODERATE PRICES. '
.1. ALMA ST.. PALO Aim).
look tee tb. -OOLD HBAII* oo I
OX OF WORK
PHOSB SIT
THIS IS A NEW FLAG OF THE FRES
Miss Alice Diaz
Indoor uid Outdoor Studio 55 Kingiley Avenue,
Dane* radiate, coaching of tha danoa In plsys, ps(jeanta, psntomimes,
rhythmic dancln*** for child*-*,-., girt a, woman; coschln-j In social dancing- Further information may b* obtained by addrsstln-j Mlaa Dlax,
or tcltphonlno Palo Alto Sll
HEADQUARTERS FOR
Mineral and Aerated
Waters
SchwcTO*'. tUrsijaartll.
ApoUla-Wl.
IW-tu, ottete. A*.
iunl«t
Cllwjoot CI.*. OlB^r Al.
tWs*
SbaaU Gloter AM -
Poised
Hi,*, nool Roe.
- Hactocar Klssl^n.
Issesmaeerf sseet
vidgr Pimn.i
Crap. Jnlf.
WUl. Rock
UTS 1-ISEAPPI.E JTICB—Apoollaln. set nlwlua,
tbem wwadsjs.
Earle & Co. Grocers
Phone. 837 and 838
Masonic Temple Bldg
LET US FIGURE
with you on your bleycla rspalrln-r.
Our price* an ressonabje. W*
guarantee ottry Job.
PIERCE, COLUMBIA AND INDIAN
OICYCLES* ON EASY PAYMENTS
Indian Cyclery
67B EMERSON STREBT
Boon this flat will ba own la tb* bsrbors of th* world tn dettano* of tba
D boat It la th* emblem adopted fay th* United State* ahlpplng board.
MAE MARSH STAR IN
••POLLY OF THE CIRCUS"
roily of the Circus." a tnmendoua
Ootdwyn picture from Msr*rar*t
Mayo ■ gnat play, with famous little
Wae Marsh a* It. star, will be ahown
next Sunday and Monday at th* Varsity TheaUr.
This plctnn ta the tint release of
Ooldwya Picture* Corporation, formed
by Samuel Oold&ah tn aasodatlon with
Edgar Selwyn, Margaret Mayo, Archi
bald Selwyn and a brilliant group of
author-* and playwrights.
Th* story of Polly, which haa bean
given a tremendous production In Its
plctnrised Jonn. ts that ot a motherless girl of the circus, and ot th* part
she play* In the drams of Ufa In a
small Anwricah Tillage. It ts a romance of tb* sawdust ring and haa
been termed "The Classic -of the Big
To***.**
Polly is hurt while doing h«r act,
and Is taken to tha hone of th* local
minister to be cared for. Here a pretty romaneo bods, but before It blooms
it is Interrupt---] by th* gossip oft tba
TQUgen, and Polly goaa back to th*
circa*, Bat tha circus comes hack another rear and Polly and tba mlnlstar
plck up th* threads ot lh*lr romaneo
In a dramatic climax.
Tb* picture la filled with realistic
soon** of circus life, tb* moat thrilling
of which la a fin tn th* big taat" and
tb* stamped* of tha audio*.**-!. It re-
qolrtd a fully equipped circus to produce thla realism, and you an permitted to aaa a complete circus performance oa the screen; th* arrival of
a circus In the town at daybreak, tha
gnat str<*ot parade, th* departun ln
th* black of night. Th* greatest liorso-
raea sceue ever put on the screen la another of the thrilling Incidents of this
remarkable picture.
A Lady en Trial.
"Shall 1 rive tbe Jury tb* dot-uts-tnts
tn tb* eater* Inquired a bailiff.
"Wbat ban tb* documents got to do
wltb their declsk»*r sasppad the *ar-
cast I-.' Juilgr. "'Just gin NCh of 'em
a photo of tha fair (WfndauLH-Pltt>-
tmrgh Post.
IU MlMtsn.
"An yon going to earthf asked tb*
star of the furor!.
"Tea.** replied the e-oaa-K, "and wbeo
I nt tben 1 wtll a tall unfold."-Bat-
It mor* A merles a.
GENUINE LEATHER
Studebaker bodlet ara uphohteredVith genuine leather,
snd it i» of high grade quality—the ume that you find on
can costing from 50000 to ?i-ooaoo more than Studebaker can.
It Is toft, pliable, durable, f-ut colored, and It wUl not
work off, icate, crumble or check, we describf this
leather to you because It shows the quality of materia!
Ibat Studebaker tuei In the construction of Its car.
Baptaat ha* not been spared to cheapen tha car In
any particular. It b distinctly a high-grade, fine automobile. Your comfort, your safety, your pride, hav*
aU been considered In the design ana construction of
both the FOUR tad SIX
It costs only a little mora to obtain th* quality that
yon find In Studebaker earn ud this quality ii the
.thing that glvei you real economy. "It b better to pay
a little more and get th* BEST?
UNIVERSITY GARAGE
11. P. Wm. Brockmwn, Prop.
328 University Ave.
Phone Palo Alto 241 . Palo Alto, Cal.
Inside and Out
Merc exterior., superiority in clothing can no
more accomplish satisfaction than can a marble facade make a fine
structure.* The merit of
High Art
Clothes
Made by Strouse & Bros.
Inc., Baltimore, Md.
is more than, skin deep.
Added to the well known
high quality of fabric
and tailoring in these
clothes is lhat big factor
of lining and trimmings.
Be introspective—look beneath, the surface for
the quality of your fall suit. "High Art Clothes"
measure up t,, the most exacting specifications.
Prices 17.50, 22.50 The Suit
ANNOUNCEMENT
We beg to announce the arrival of our coats and one-
piece dresses for fall—authentic styles that are to be
worn by those that know—high grade suits in merveil-
lieux, diagonal and calamine serges.
PRICES PROM 22.50
Cretonne and Kindred
Materials
sm'h as Linestra. Belgian Cloth, Khedive Cloth, Geneva
Ciotti, Shakari, Mercerized Repp. Rc^wildering array of
m.-irveln-js'color schemes lhat defy description—for draperies hangings, knitting bags and pillows; 33 to 50 inches
with-, from 25c to-152 a vard. * -- '
Knitted Underwear
Our fall shipment of the
famous "Merode" underwear is being unpacked
now. It comprises cotton,
cotton and wool, all wool
and silk and wool, represented in all the different
weights made. Vests 75c
up. Tights 75c up. Union
suits 6.75 ,-r*-y
USest
to 2.50 to $12 .
MEN'S STORE
UNIVERSITY AVE.. ANp HIGH STREET
PHONE 458R
SOLE AGENTS
Kayser's Gloves and Underwear
Ladies Home Journal Patterns 10c, 15c
Pleating, Picoting, Hemstitching, etc
Royal Worcester Corsets , Buttons of every style and color made to
Cash's Woven Letters order
Merode Underwear
Redfern Corsets
Warner's Corsets
Bon Ton Corsets
WOMEN'S STORE
UNIVERSITY AVE. AND EMERSON ST.
PHONE 458W
