The Effectiveness of Visualization Techniques for Supporting Decision-Making

Although visualization is beneficial for evaluating and communicating data, the efficiency of various visualization approaches for different data types is not always evident. This research aims to address this issue by investigating the usefulness of several visualization techniques for various data kinds, including continuous, categorical, and time-series data. The qualitative appraisal of each technique\u27s strengths, weaknesses, and interpretation of the dataset is investigated. The research questions include: which visualization approaches perform best for different data types, and what factors impact their usefulness? The absence of clear directions for both researchers and practitioners on how to identify the most effective visualization approach for a specific data type poses a significant research challenge. Our findings will help both professionals and researchers determine the most successful visualization approach for different data types, as well as identify topics for future study in the field of data visualization

Oxidation in Low Moisture Foods as a Function of Surface Lipids and Fat Content

Lipid oxidation is a major limitation to the shelf-life of low moisture foods and can lead to food waste. Little is known of whether the surface lipids in low moisture foods are more susceptible to oxidation since they are exposed to the environment. Therefore, the purpose of this research is to compare the rate of oxidation in surface and total lipids. Lipids in crackers were found to be in a heterogeneous matrix with proteins and starch, as determined by confocal microscopy. However, unlike spray-dried powders, both surface and interior lipids oxidized at similar rates, suggesting that the cracker matrix was not able to protect lipids from oxidation. Increasing the fat content of the crackers increased oxidation rates, which could be due to differences in the lipid structure or higher water activities in the high-fat crackers

MMSR: Multiple-Model Learned Image Super-Resolution Benefiting From Class-Specific Image Priors

Assuming a known degradation model, the performance of a learned image super-resolution (SR) model depends on how well the variety of image characteristics within the training set matches those in the test set. As a result, the performance of an SR model varies noticeably from image to image over a test set depending on whether characteristics of specific images are similar to those in the training set or not. Hence, in general, a single SR model cannot generalize well enough for all types of image content. In this work, we show that training multiple SR models for different classes of images (e.g., for text, texture, etc.) to exploit class-specific image priors and employing a post-processing network that learns how to best fuse the outputs produced by these multiple SR models surpasses the performance of state-of-the-art generic SR models. Experimental results clearly demonstrate that the proposed multiple-model SR (MMSR) approach significantly outperforms a single pre-trained state-of-the-art SR model both quantitatively and visually. It even exceeds the performance of the best single class-specific SR model trained on similar text or texture images.Comment: 5 pages, 4 figures, accepted for publication in IEEE ICIP 2022 Conferenc

Limiar entre a moda e a arte

As tendências de moda materializam-se e chegam aos consumidores, mas até lá passam por um processo criativo, que poderá ou não ser equiparado ao processo artístico? Sendo a moda concebida a partir do ensamento e leituras ou interpretações de seus criadores sobre o universo que o rodeia, poderá esta equiparar-se à arte ao traduzir as características do tempo em que foi criada? Será que estas vivem em esferas separadas, ou existe um diálogo permanente entre elas? Serão questões que tentaremos responder neste artigo, tentando analisar o limiar entre arte e moda

The Effect of Feeding Strategy on Butanol Production by Clostridium beijerinckii NCIMB 8052 Using Glucose and Xylose

We performed fed-batch fermentations of glucose and xylose mixtures producing butanol. Our aim was to develop a feeding strategy for coping with carbon catabolite repression (CCR) and sequential utilization problems as well as understanding the effect of feeding strategy on fermentation kinetics. Experimental results showed that fermenter 1 with only xylose as the initial carbon source could co-utilize sugars for all mixed sugar feeds. On the other hand, fermenter 2 with only glucose as the initial sugar showed sequential utilization. Xylose in fermenter 2 accumulated while glucose was present; it was only utilized after the glucose was completely exhausted. Besides the sugar utilization profile, the feeding strategy had an impact on the fermentation kinetics. Maximum specific growth rates were 0.68 h-1 and 0.94 h-1, for fermenter 1 and 2,respectively. Fermenter 1 produced 4.98 g/l butanol and yield was 0.28 g/g, while fermenter 2 produced 0.5 g/l butanol with a yield value of 0.05 g/g. Total sugar utilization was also higher for fermenter 1, 81 % and 46 % for fermenter 2. The feeding strategy we proposed showed that wild type Clostridium beijerinckii NCIMB 8052 can co-utilize glucose and xylose, and produce butanol. Our observation suggests that we can tackle sequential utilization problem and enhance fermentation process with the proposed feeding strategy without having to manipulate the strain.publishedVersio

Response Surface Methodology for Understanding Glucose and Xylose Utilization by Clostridium beijerinckii NCIMB 8052

We applied response surface methodology to understand the effect and extend of carbon catabolite repression (CCR) on growth of Clostridium beijerinckii NCIMB 8052 using xylose and glucose as representative lignocellulosic sugars. We performed batch growth experiments based on the central composite design with different concentrations of glucose and xylose, and estimated the respective growth rates as the response. Fitting the quadratic model with interaction coefficient to experimental data gave a good quality of fit (R-squared=0.939). We found that glucose is the most significant factor affecting the growth rate. Interaction between glucose and xylose is another highly significant factor. Response surface illustrated that increasing or decreasing both sugar concentrations at the same time results in a decreasing growth rate, and increasing either sugar concentration while decreasing the other sugar increases the growth rate. It is an important finding as it suggests that CCR can be not only from glucose on xylose but also from xylose on glucose. A transcriptional study will be necessary to understand the repression mechanism and to improve the utilization of sugars in mixed form, thus lignocellulosic fermentation processes.publishedVersio

Kinetic Study of Butanol Production from Mixtures of Glucose and Xylose and Investigation of Different Pre-growth Strategies

This study proposes a dynamic model that describes key characteristics of fermentative butanol production from glucose and xylose mixtures. The model has 12 parameters and incorporates noncompetitive inhibitory interaction between sugars as well as inhibitions due to high substrate and butanol concentrations. Different pre-growth strategies to achieve co-utilization of sugars were explored together with their effects on fermentation kinetics. Mixed sugar fermentation by the cultures pre-grown on a mixture of glucose and xylose showed a higher endurance to inhibition, a 2-fold increase in butanol production and a 1.5-fold increase in total sugar consumption compared to cultures pre-grown on xylose only. The average squared correlation coefficients (r2) between experimental observations and model predictions were 0.917 and 0.926 for fermentations done by the cultures pre-grown on xylose only, and pre-grown on a mixture of glucose and xylose, respectively. Sensitivity analysis on the model parameters revealed that the growth parameters were the most critical. The proposed model can serve as a basis for modeling of microbial butanol production from lignocellulosic biomass and be applied to other substrates and microorganisms. © 2019(32 refs)acceptedVersio

Identification and genetic characterization of Pseudomonas syringae pv. syringae from sweet cherry in Turkey

Pseudomonas syringae pv. syringae (Pss), which causes bacterial canker, is the most polyphagous bacterium in the P. syringae complex due to its broad host range. This pathogen is considered the major bacterial disease in cherry orchards. In this study, several samples were collected from infected sweet cherry trees in different locations of the Marmara region in Turkey between 2016-2018. Sixty-three isolates were identified as Pss by pathogenicity, LOPAT, GATTa, and MALDI-TOF MS tests. Total genomic DNA was extracted to confirm identity, followed by PCR amplification of syrB and cfl genes. Out of 63 isolates, 12 were randomly selected for Repetitive Element Sequence-based PCR (rep-PCR) and Multilocus Sequence Typing (MLST) analysis to gain insight into the relationships of those isolates. The cluster analysis of rep-PCR (ERIC-, REP- and BOX-PCR) could classify the isolates into two distinct clusters. Phylogenetic analysis was carried out to obtain the relation between isolates and the location.The MLST analysis of gyrB, rpoDp, rpoDs, and gltA genes allowed a clear allocation of the isolates into two separate main clusters. The relationship among the isolates were also evaluated by constructing a genealogical median-joining network (MJN). The isolates from six locations produced 11 haplotypes that were illustrated in the MJN. The results of this study proved that location could not be an indicator for showing the genetic diversity of Pss from cherry orchards. As the genetic variability of Pseudomonads has been demonstrated, the current study also showed high diversity among different isolates even within the populations. While more research is recommended, the results of this study contributed to a better understanding of the Pss evolutionary progress and genetic diversity of sweet cherry isolates

First Report of Bacterial Leaf Spot Caused by Xanthomonas arboricola Infecting Saucer Magnolia in Tennessee

[No Abstract Available

Perception-Distortion Trade-off in the SR Space Spanned by Flow Models

Flow-based generative super-resolution (SR) models learn to produce a diverse set of feasible SR solutions, called the SR space. Diversity of SR solutions increases with the temperature ($\tau$) of latent variables, which introduces random variations of texture among sample solutions, resulting in visual artifacts and low fidelity. In this paper, we present a simple but effective image ensembling/fusion approach to obtain a single SR image eliminating random artifacts and improving fidelity without significantly compromising perceptual quality. We achieve this by benefiting from a diverse set of feasible photo-realistic solutions in the SR space spanned by flow models. We propose different image ensembling and fusion strategies which offer multiple paths to move sample solutions in the SR space to more desired destinations in the perception-distortion plane in a controllable manner depending on the fidelity vs. perceptual quality requirements of the task at hand. Experimental results demonstrate that our image ensembling/fusion strategy achieves more promising perception-distortion trade-off compared to sample SR images produced by flow models and adversarially trained models in terms of both quantitative metrics and visual quality.Comment: 5 pages, 4 figures, accepted for publication in IEEE ICIP 2022 Conferenc