Emotion Regulation and Spatial Memory

The emotion and memory has been studied for a long time, but the emotion was mostly induced before their main memory task and the relationship between emotion regulation and spatial memory was rarely studied. We conducted one hour experiment with university students for last one semester and analyzed using Excel 2016 in the correlation between emotion regulation self-report measures and spatial memory task accuracy. DERS supported our hypothesis weakly but ACS didn’t show the similar flow.This research was supported by the Undergraduate Research Opportunities Program (UROP) and Dr. Paul R. Schrater

Neurofeedback during Self-face Processing in Depressed versus Healthy Adolescents

Faculty advisor: Karina QuevedoThis research was supported by the Undergraduate Research Opportunities Program (UROP)

Perceived managerial and leadership effectiveness in a Korean context: An indigenous qualitative study

Multinational corporations (MNCs) across the world have sent an increasing number of managers abroad to leverage unprecedented opportunities in the era of globalization. However, their failure rate has been above 33% for decades, resulting in substantial costs (Puck, Kittler, & Wright, 2008). One of the primary reasons for this failure is a lack of understanding of the national and organizational cultures within the host countries (Festing & Maletzky, 2011). For example, while a number of MNCs have entered the Korean market, several such as Yahoo, Motorola, and Walmart have failed and withdrawn due to the companies’ lack of adjustment to the Korean cultural context (Choe, 2006; Woo, 2013). In spite of the significance of culturally embedded practices, most researchers who have explored management and leadership in Asian countries, whether they were Western or indigenous researchers, have implemented studies using extant Western management and leadership theories derived within the Western cultural context (Leung, 2007; Tsui, 2006). Numerous scholars have claimed that this could be problematic because the findings of such studies may not be applicable to non-Western countries (Li, 2012; Liden & Antonakis, 2009), and may fail to provide insights and understanding of novel contexts or to reveal indigenous aspects of management and leadership (Tsui, 2007). Consequently, there have been increasing calls for indigenous management and leadership research within Asian countries (see Li et al., 2014; Lyles, 2009; Tsui, 2004; Wolfgramm, Spiller, & Voyageur, 2014). Over the past 30 years, managerial effectiveness and leadership effectiveness have been substantially neglected areas of management research (Noordegraaf & Stewart, 2000; Yukl, Gordon, & Taber, 2002). In addition, there has been little agreement on what specific behaviors distinguish effective managers from ineffective ones. Furthermore, more research is needed to examine the managerial and leadership behaviors that are critical for shaping the performance of individuals, groups and organizations (see Borman & Brush, 1993; Cammock, Nilakant & Dakin, 1995; Mumford, 2011; Noordegraaf & Stewart, 2000; Yukl et al., 2002). While most of the research related to managerial and leadership effectiveness has been conducted in the U.S., the few notable non-U.S. studies include that of Cammock et al. (1995) in New Zealand who developed a behavioral lay model of managerial effectiveness using the repertory grid technique. Another notable exception is the cumulative series of perceived managerial and leadership effectiveness studies conducted by Hamlin with various indigenous co-researchers in Western and non-Western countries (see Hamlin & Patel, 2012; Ruiz, Wang, & Hamlin, 2013) using Flanagan’s (1954) critical incident technique (CIT)

A Novel Pear Scab (<i>Venturia nashicola</i>) Resistance Gene, <i>Rvn3</i>, from Interspecific Hybrid Pear (<i>Pyrus pyrifolia</i> × <i>P. communis</i>)

Asian pear scab is a fungal disease caused by Venturia nashicola. The identification of genes conferring scab resistance could facilitate the breeding of disease-resistant cultivars. Therefore, the present study aimed to identify a scab-resistance gene using an interspecific hybrid population ((Pyrus pyrifolia × P. communis) × P. pyrifolia). Artificial inoculation of V. nashicola was carried out for two years. The segregation ratio (1:1) of resistant to susceptible individuals indicated that resistance to V. nashicola was inherited from P. communis and controlled by a single dominant gene. Based on two years phenotypic data with the Kruskal–Wallis test and interval mapping, 12 common markers were significantly associated with scab resistance. A novel scab resistance gene, Rvn3, was mapped in linkage group 6 of the interspecific hybrid pear, and co-linearity between Rvn3 and one of the apple scab resistance genes, Rvi14, was confirmed. Notably, an insertion in pseudo-chromosome 6 of the interspecific hybrid cultivar showed homology with apple scab resistance genes. Hence, the newly discovered Rvn3 was considered an ortholog of the apple scab resistance gene. Since the mapping population used in the present study is a pseudo-BC1 population, pyramiding of multiple resistance genes to pseudo-BC1 could facilitate the breeding of pear cultivars with durable resistance

QTL Analysis and CAPS Marker Development Linked with Russet in Pear (<i>Pyrus</i> spp.)

The fruit skin types of pear (Pyrus spp.) are divided into russet, smooth, and intermediate. One of the important traits in pear breeding programs is russet on pear fruit skin because it affects the commercial value. In the present study, a high-density genetic linkage map of ‘Whangkeumbae’ (smooth) × ‘Minibae’ (russet) was constructed. In addition, quantitative trait loci (QTL) analysis was performed to identify russet related QTL and develop a cleaved amplified polymorphism sequence (CAPS) marker. Together with SNPs derived from Axiom Pear 70K Genotyping Array and genotyping-by-sequencing derived SNPs and SSRs generated in previous study, an integrated genetic linkage map of ‘Whangkeumbae’ × ‘Minibae’ was constructed. A total of 1263 markers were anchored in 17 linkage groups (LGs) with a total genetic distance of 1894.02 cM and an average marker density of 1.48 cM. The chromosome coverage of ‘Whangkeumbae’ × ‘Minibae’ map was improved because the SNPs derived from Axiom Pear 70K Genotyping Array were anchored. QTL analysis was performed using previous russet phenotype data evaluated with russet coverage and Hunter a. As a result of QTL analysis, russet coverage- and Hunter a-related QTLs were identified in LG8 of the ‘Whangkeumbae’ × ‘Minibae’ map, and SNPs located in the QTL region were heterozygous in the ‘Minibae’. Although the russet coverage- and Hunter a-related QTLs were commonly detected in LG8, the logarithm of odds values of SNPs in the QTL region were higher in QTL related to russet coverage than to Hunter a. The CAPS marker (CBp08ca01) was developed using an array SNP located in the russet coverage related QTL, and the genotype of CBp08ca01 showed a 1:1 ratio in ‘Whangkeumbae’ × ‘Minibae’ (χ2 = 0.65, p > 0.05). ‘Whangkeumbae’ and ‘Minibae’ were thought to have rr and Rr genotypes, respectively, and the genetic factors controlling the russet formation might be located in chromosome 8. The CBp08ca01 was able to select F1 individuals with less than 30% russet coverage. Thus, it will be a useful tool for marker-assisted selection in pears

Nanoporous Thin Films Based on Polylactide-Grafted Norbornene Copolymers

Thermally stable vinyl polymerized polynorbornene (PNB) is one of the challenging materials in porous low dielectric films for packaging applications. Nanoporous PNB thin films were obtained with poly(d,l-lactide) (PLA)-grafted norbornene copolymers. Thermally labile PLA chains act as pore generators in PNB films. Thermally stable PNB main chains were synthesized by Pd-catalyzed vinyl polymerization and PLA side chains were grafted onto the PNB main chains by ring opening polymerization. The brittle and poor processible properties of PNB could easily be controlled by the copolymerization with norbornene derivatives. In thin films, the PLA chains were found to thermally decompose at about 250 °C while the PNB matrix was stable during this pore generating process. The porosity of the porous PNB thin films could be controlled up to 18% with pore sizes below 5 nm range by varying the chain length of grafted PLA. Introduction of cross-linking epoxy groups onto the PNB main chains resulted in the formation of well-defined nanopores without any extensive pore collapse during the vitrification of the PNB matrix. Additionally, it is demonstrated that the photopatterning of the thin films could be achieved using photoinitiator.This work was financially supported by the Korea Science and Engineering Foundation (KOSEF) grant through the Acceleration Research (R17-2007-059-01000-0) and the NANO Systems Institute-National Core Research Center (R15-2003-032-02002-0) funded by the Korea Ministry of Education, Science and Technology (MEST). We also acknowledge the financial support from the Korean Ministry of Education, Science and Technology through the Brain Korea 21 Program at Seoul National University and the International Research Training Group (IRTG) (2006-IRTG-001) Mainz-Seoul Program jointly funded by the KOSEF of Korea and the Deutsche Forschungsgemeinschaft (DFG) of Germany. Additionally, this work was supported by the Ministry of Commerce, Industry and Energy (MOCIE)

Multichannel convolution neural network for gas mixture classification

Concomitant with people beginning to understand their legal rights or entitlement to complain, complaints of offensive odors and smell pollution have increased significantly. Consequently, monitoring gases and identifying their types and causes in real time has become a critical issue in the modern world. In particular, toxic gases that may be generated at industrial sites or odors in daily life consist of hybrid gases made up of various chemicals. Understanding the types and characteristics of these mixed gases is an important issue in many areas. However, mixed gas classification is challenging because the gas sensor arrays for mixed gases must process complex nonlinear high-dimensional data. In addition, obtaining sufficient training data is expensive. To overcome these challenges, this paper proposes a novel method for mixed gas classification based on analogous image representations with multiple sensor-specific channels and a convolutional neural network (CNN) classifier. The proposed method maps a gas sensor array into a multichannel image with data augmentation, and then utilizes a CNN for feature extraction from such images. The proposed method was validated using public mixture gas data from the UCI machine learning repository and real laboratory experiments. The experimental results indicate that it outperforms the existing classification approaches in terms of the balanced accuracy and weighted F1 scores. Additionally, we evaluated the performance of the proposed method in various experimental settings in terms of data representation, data augmentation, and parameter initialization, so that practitioners can easily apply it to artificial olfactory systems