Minimum Distance Testing and Top Income Shares in Korea

We study Kolmogorov-Smirnov goodness of fit tests for evaluating distributional hypotheses where unknown parameters need to be fitted. Following work of Pollard (1979), our approach uses a Cramér-von Mises minimum distance estimator for parameter estimation. The asymptotic null distribution of the resulting test statistic is represented by invariance principle arguments as a functional of a Brownian bridge in a simple regression format for which asymptotic critical values are readily delivered by simulations. Asymptotic power is examined under fixed and local alternatives and finite sample performance of the test is evaluated in simulations. The test is applied to measure top income shares using Korean income tax return data over 2007 to 2012. When the data relate to the upper 0.1% or higher tail of the income distribution, the conventional assumption of a Pareto tail distribution cannot be rejected. But the Pareto tail hypothesis is rejected for the top 1.0% or 0.5% incomes at the 5% significance level

Automatic Three-Dimensional Cephalometric Annotation System Using Three-Dimensional Convolutional Neural Networks

Background: Three-dimensional (3D) cephalometric analysis using computerized tomography data has been rapidly adopted for dysmorphosis and anthropometry. Several different approaches to automatic 3D annotation have been proposed to overcome the limitations of traditional cephalometry. The purpose of this study was to evaluate the accuracy of our newly-developed system using a deep learning algorithm for automatic 3D cephalometric annotation. Methods: To overcome current technical limitations, some measures were developed to directly annotate 3D human skull data. Our deep learning-based model system mainly consisted of a 3D convolutional neural network and image data resampling. Results: The discrepancies between the referenced and predicted coordinate values in three axes and in 3D distance were calculated to evaluate system accuracy. Our new model system yielded prediction errors of 3.26, 3.18, and 4.81 mm (for three axes) and 7.61 mm (for 3D). Moreover, there was no difference among the landmarks of the three groups, including the midsagittal plane, horizontal plane, and mandible (p>0.05). Conclusion: A new 3D convolutional neural network-based automatic annotation system for 3D cephalometry was developed. The strategies used to implement the system were detailed and measurement results were evaluated for accuracy. Further development of this system is planned for full clinical application of automatic 3D cephalometric annotation

Production of 2,3-butanediol from glucose and cassava hydrolysates by metabolically engineered industrial polyploid Saccharomyces cerevisiae

Background 2,3-Butanediol (2,3-BDO) is a valuable chemical for industrial applications. Bacteria can produce 2,3-BDO with a high productivity, though most of their classification as pathogens makes them undesirable for the industrial-scale production. Though Saccharomyces cerevisiae (GRAS microorganism) was engineered to produce 2,3-BDO efficiently in the previous studies, their 2,3-BDO productivity, yield, and titer were still uncompetitive compared to those of bacteria production. Thus, we propose an industrial polyploid S. cerevisiae as a host for efficient production of 2,3-BDO with high growth rate, rapid sugar consumption rate, and resistance to harsh conditions. Genetic manipulation tools for polyploid yeast had been limited; therefore, we engineered an industrial polyploid S. cerevisiae strain based on the CRISPR-Cas9 genome-editing system to produce 2,3-BDO instead of ethanol. Results Endogenous genes coding for pyruvate decarboxylase and alcohol dehydrogenase were partially disrupted to prevent declined growth rate and C2-compound limitation. A bacterial 2,3-BDO-producing pathway was also introduced in engineered polyploid S. cerevisiae. A fatal redox imbalance was controlled through the heterologous NADH oxidase from Lactococcus lactis during the 2,3-BDO production. The resulting strain (YG01_SDBN) still retained the beneficial traits as polyploid strains for the large-scale fermentation. The combination of partially disrupted PDC (pyruvate decarboxylase) and ADH (alcohol dehydrogenase) did not cause the severe growth defects typically found in all pdc- or adh-deficient yeast. The YG01_SDBN strain produced 178 g/L of 2,3-BDO from glucose with an impressive productivity (2.64 g/L h). When a cassava hydrolysate was used as a sole carbon source, this strain produced 132 g/L of 2,3-BDO with a productivity of 1.92 g/L h. Conclusions The microbial production of 2,3-BDO has been limited to bacteria and haploid laboratorial S. cerevisiae strains. This study suggests that an industrial polyploid S. cerevisiae (YG01_SDBN) can produce high concentration of 2,3-BDO with various advantages. Integration of metabolic engineering of the industrial yeast at the gene level with optimization of fed-batch fermentation at the process scale resulted in a remarkable achievement of 2,3-BDO production at 178 g/L of 2,3-BDO concentration and 2.64 g/L h of productivity. Furthermore, this strain could make a bioconversion of a cassava hydrolysate to 2,3-BDO with economic and environmental benefits. The engineered industrial polyploid strain could be applicable to production of biofuels and biochemicals in large-scale fermentations particularly when using modified CRISPR-Cas9 tools.This study is funded by National Research Foundation of Korea (2011-0031359)

Folding machineries displayed on a cation-exchanger for the concerted refolding of cysteine- or proline-rich proteins

<p>Abstract</p> <p>Background</p> <p><it>Escherichia coli </it>has been most widely used for the production of valuable recombinant proteins. However, over-production of heterologous proteins in <it>E. coli </it>frequently leads to their misfolding and aggregation yielding inclusion bodies. Previous attempts to refold the inclusion bodies into bioactive forms usually result in poor recovery and account for the major cost in industrial production of desired proteins from recombinant <it>E. coli</it>. Here, we describe the successful use of the immobilized folding machineries for <it>in vitro </it>refolding with the examples of high yield refolding of a ribonuclease A (RNase A) and cyclohexanone monooxygenase (CHMO).</p> <p>Results</p> <p>We have generated refolding-facilitating media immobilized with three folding machineries, mini-chaperone (a monomeric apical domain consisting of residues 191–345 of GroEL) and two foldases (DsbA and human peptidyl-prolyl <it>cis-trans </it>isomerase) by mimicking oxidative refolding chromatography. For efficient and simple purification and immobilization simultaneously, folding machineries were fused with the positively-charged consecutive 10-arginine tag at their C-terminal. The immobilized folding machineries were fully functional when assayed in a batch mode. When the refolding-facilitating matrices were applied to the refolding of denatured and reduced RNase A and CHMO, both of which contain many cysteine and proline residues, RNase A and CHMO were recovered in 73% and 53% yield of soluble protein with full enzyme activity, respectively.</p> <p>Conclusion</p> <p>The refolding-facilitating media presented here could be a cost-efficient platform and should be applicable to refold a wide range of <it>E. coli </it>inclusion bodies in high yield with biological function.</p

Molecular cloning and biochemical characterization of a novel erythrose reductase from Candida magnoliae JH110

<p>Abstract</p> <p>Background</p> <p>Erythrose reductase (ER) catalyzes the final step of erythritol production, which is reducing erythrose to erythritol using NAD(P)H as a cofactor. ER has gained interest because of its importance in the production of erythritol, which has extremely low digestibility and approved safety for diabetics. Although ERs were purified and characterized from microbial sources, the entire primary structure and the corresponding DNA for ER still remain unknown in most of erythritol-producing yeasts. <it>Candida magnoliae </it>JH110 isolated from honeycombs produces a significant amount of erythritol, suggesting the presence of erythrose metabolizing enzymes. Here we provide the genetic sequence and functional characteristics of a novel NADPH-dependent ER from <it>C. magnoliae </it>JH110.</p> <p>Results</p> <p>The gene encoding a novel ER was isolated from an osmophilic yeast <it>C. magnoliae </it>JH110. The ER gene composed of 849 nucleotides encodes a polypeptide with a calculated molecular mass of 31.4 kDa. The deduced amino acid sequence of ER showed a high degree of similarity to other members of the aldo-keto reductase superfamily including three ER isozymes from <it>Trichosporonoides megachiliensis </it>SNG-42. The intact coding region of ER from <it>C. magnoliae </it>JH110 was cloned, functionally expressed in <it>Escherichia coli </it>using a combined approach of gene fusion and molecular chaperone co-expression, and subsequently purified to homogeneity. The enzyme displayed a temperature and pH optimum at 42°C and 5.5, respectively. Among various aldoses, the <it>C. magnoliae </it>JH110 ER showed high specific activity for reduction of erythrose to the corresponding alcohol, erythritol. To explore the molecular basis of the catalysis of erythrose reduction with NADPH, homology structural modeling was performed. The result suggested that NADPH binding partners are completely conserved in the <it>C. magnoliae </it>JH110 ER. Furthermore, NADPH interacts with the side chains Lys252, Thr255, and Arg258, which could account for the enzyme's absolute requirement of NADPH over NADH.</p> <p>Conclusions</p> <p>A novel ER enzyme and its corresponding gene were isolated from <it>C. magnoliae </it>JH110. The <it>C. magnoliae </it>JH110 ER with high activity and catalytic efficiency would be very useful for <it>in vitro </it>erythritol production and could be applied for the production of erythritol in other microorganisms, which do not produce erythritol.</p

EFFECTS OF MO, CR, AND V ADDITIONS ON TENSILE AND CHARPY IMPACT PROPERTIES OF API X80 PIPELINE STEELS

In this study, four API X80 pipeline steels were fabricated by varying Mo, Cr, and V additions, and their microstructures and crystallographic orientations were analyzed to investigate the effects of their alloying compositions on tensile properties and Charpy impact properties. Because additions of Mo and V promoted the formation of fine acicular ferrite (AF) and granular bainite (GB) while prohibiting the formation of coarse GB, they increased the strength and upper-shelf energy (USE) and decreased the energy transition temperature (ETT). The addition of Cr promoted the formation of coarse GB and hard secondary phases, thereby leading to an increased effective grain size, ETT, and strength, and a decreased USE. The addition of V resulted in a higher strength, a higher USE, a smaller effective grain size, and a lower ETT, because it promoted the formation of fine and homogeneous of AF and GB. The steel that contains 0.3 wt pct Mo and 0.06 wt pct V without Cr had the highest USE and the lowest ETT, because its microstructure was composed of fine AF and GB while its maintained excellent tensile properties.X1126sciescopu

An unusual cause of duodenal perforation due to a lollipop stick

Children have a natural tendency to explore objects with their mouths; this can result in the swallowing of foreign objects. Most ingested foreign bodies pass uneventfully through the gastrointestinal tract. However, some foreign bodies cause obstruction or perforation of the gastrointestinal tract, requiring surgical intervention. Perforation of the gastrointestinal tract may be associated with considerable morbidity and mortality. The most common sites of intestinal foreign body perforation are the ileocecal and rectosigmoid regions. Foreign body perforation of the duodenum is relatively uncommon. We report the first Korean case of duodenal perforation by an ingested 8-cm lollipop stick. Lollipops are popular with the children and fairly accessible to them, as most parents are not aware of their potential harm. Pediatric clinicians should be aware of the risks associated with lollipop stick ingestion. Our report also describes the feasibility and safety of laparoscopic diagnosis and management of pediatric patients with peritonitis induced by the ingestion of foreign bodies

Convolution channel separation and frequency sub-bands aggregation for music genre classification

In music, short-term features such as pitch and tempo constitute long-term semantic features such as melody and narrative. A music genre classification (MGC) system should be able to analyze these features. In this research, we propose a novel framework that can extract and aggregate both short- and long-term features hierarchically. Our framework is based on ECAPA-TDNN, where all the layers that extract short-term features are affected by the layers that extract long-term features because of the back-propagation training. To prevent the distortion of short-term features, we devised the convolution channel separation technique that separates short-term features from long-term feature extraction paths. To extract more diverse features from our framework, we incorporated the frequency sub-bands aggregation method, which divides the input spectrogram along frequency bandwidths and processes each segment. We evaluated our framework using the Melon Playlist dataset which is a large-scale dataset containing 600 times more data than GTZAN which is a widely used dataset in MGC studies. As the result, our framework achieved 70.4% accuracy, which was improved by 16.9% compared to a conventional framework

Integrated Parameter-Efficient Tuning for General-Purpose Audio Models

The advent of hyper-scale and general-purpose pre-trained models is shifting the paradigm of building task-specific models for target tasks. In the field of audio research, task-agnostic pre-trained models with high transferability and adaptability have achieved state-of-the-art performances through fine-tuning for downstream tasks. Nevertheless, re-training all the parameters of these massive models entails an enormous amount of time and cost, along with a huge carbon footprint. To overcome these limitations, the present study explores and applies efficient transfer learning methods in the audio domain. We also propose an integrated parameter-efficient tuning (IPET) framework by aggregating the embedding prompt (a prompt-based learning approach), and the adapter (an effective transfer learning method). We demonstrate the efficacy of the proposed framework using two backbone pre-trained audio models with different characteristics: the audio spectrogram transformer and wav2vec 2.0. The proposed IPET framework exhibits remarkable performance compared to fine-tuning method with fewer trainable parameters in four downstream tasks: sound event classification, music genre classification, keyword spotting, and speaker verification. Furthermore, the authors identify and analyze the shortcomings of the IPET framework, providing lessons and research directions for parameter efficient tuning in the audio domain.Comment: 5 pages, 3 figures, submit to ICASSP202