Search

A novel strategy for the stereospecific Pd-catalyzed acylative cross-coupling of enantiomerically enriched alkylboron compounds has been developed. The protocol features an extremely high level of enantiospecificity to allow facile access to synthetically challenging and valuable chiral ketones and carboxylic acid derivatives. The use of a sterically encumbered and electron-rich phosphine ligand proved to be crucial for the success of the reaction. Furthermore, based on experimental and computational studies, a unique mechanism for the transmetalation of the C(sp3)-based organoboron reagent has been identified. Furthermore, based on experimental and computational studies, a unique mechanism for the transmetalation of the C(sp3)-based organoboron reagent has been identified.

Genetic and medical insights from studies on cardioprotective phenotypes aid the development of novel therapeutics. This study identified genetic variants associated with supernormal coronary arteries using genome-wide association study data and the corresponding genes based on expression quantitative trait loci (eQTL).Study participants were selected from two Korean cohorts according to inclusion criteria that included males with high cardiovascular risk (Framingham risk score ≥ 14, 10-year risk ≥ 16%) but with normal coronary arteries (supernormal group) or coronary artery disease (control group). After screening 12,309 individuals, males meeting the supernormal phenotype (n=72) and age-matched controls (n=94) were enrolled. Genetic variants associated with the supernormal phenotype were identified using Firth's logistic regression, and eQTL was used to evaluate whether the identified variants influence the expression of particular genes in human tissues.Approximately 5 million autosomal variants were tested for association with the supernormal phenotype, and 10 independent loci suggestive of supernormal coronary arteries (p＜5.0 ×10This study identified genetic variants and eQTL genes associated with supernormal coronary arteries. These results suggest candidate genes representing potential therapeutic targets for coronary artery disease.

Subjective well-being (SWB) has been explored in European ancestral populations; however, whether the SWB genetic architecture is shared across populations remains unclear. We conducted a cross-population genome-wide association study for SWB using samples from Korean (n = 110,919) and European (n = 563,176) ancestries. Five ancestry-specific loci and twelve cross-ancestry significant genomic loci were identified. One novel locus (rs12298541 near HMGA2) associated with SWB was also identified through the European meta-analysis. Significant cross-ancestry genetic correlation for SWB between samples was observed. Polygenic risk analysis in an independent Korean cohort (n = 22,455) demonstrated transferability between populations. Significant correlations between SWB and major depressive disorder, and significant enrichment of central nervous system-related polymorphisms heritability in both ancestry populations were found. Hence, large-scale cross-ancestry genome-wide association studies can advance our understanding of SWB genetic architecture and mental health.

Variation in skin pigmentation can be affected by both environmental factors and intrinsic factors such as age, gender, and genetic variation. Recent GWASs revealed that genetic variants of genes functionally related to a pigmentation pathway were associated with skin pigmentary traits. However, these GWASs focused on populations with European ancestry, and only a few studies have been performed on Asian populations, limiting our understanding of the genetic basis of skin pigmentary traits in Asians. To evaluate the genetic variants associated with facial pigmented spots, we conducted a GWAS analysis of objectively measured facial pigmented spots in 17,019 Korean women. This large-scale GWAS identified several genomic loci that were significantly associated with facial pigmented spots (five previously reported loci and two previously unreported loci, to our knowledge), which were detected by UV light: BNC2 at 9p22 (rs16935073; P-value = 2.11 × 10−46), PPARGC1B at 5q32 (rs32579; P-value = 9.04 × 10−42), 10q26 (rs11198112; P-value = 9.66 × 10−38), MC1R at 16q24 (rs2228479; P-value = 6.62 × 10−21), lnc01877 at 2q33 (rs12693889; P-value = 1.59 × 10−11), CDKN2B-AS1 at 9p21 (rs643319; P-value = 7.76 × 10−9), and MFSD12 at 19p13 (rs2240751; P-value = 9.70 × 10−9). Further functional characterization of the candidate genes needs to be done to fully evaluate their contribution to facial pigmented spots.

In this paper, we consider mimicking fictional characters as a promising direction for building engaging conversation models. To this end, we present a new practical task where only a few utterances of each fictional character are available to generate responses mimicking them. Furthermore, we propose a new method named Pseudo Dialog Prompting (PDP) that generates responses by leveraging the power of large-scale language models with prompts containing the target character's utterances. To better reflect the style of the character, PDP builds the prompts in the form of dialog that includes the character's utterances as dialog history. Since only utterances of the characters are available in the proposed task, PDP matches each utterance with an appropriate pseudo-context from a predefined set of context candidates using a retrieval model. Through human and automatic evaluation, we show that PDP generates responses that better reflect the style of fictional characters than baseline methods., NAACL2022 (Short)

Increased serum uric acid (SUA) levels cause gout and are associated with multiple diseases, including chronic kidney disease. Previous genome-wide association studies (GWAS) have identified more than 180 loci that contribute to SUA levels. Here, we investigated genetic determinants of SUA level in the Korean population. We conducted a GWAS for SUA in 6,881 Korean individuals, calculated polygenic risk scores (PRSs) for common variants, and validated the association of low-frequency variants and PRS with SUA levels in 3,194 individuals. We identified two low-frequency and six common independent variants associated with SUA. Despite the overall similar effect sizes of variants in Korean and European populations, the proportion of variance for SUA levels explained by the variants was greater in the Korean population. A rare, nonsense variant SLC22A12 p.W258X showed the most significant association with reduced SUA levels, and PRSs of common variants associated with SUA levels were significant in multiple Korean cohorts. Interestingly, an East Asian-specific missense variant (rs671) in ALDH2 displayed a significant association on chromosome 12 with the SUA level. Further genetic epidemiological studies on SUA are needed in ethnically diverse cohorts to investigate rare or low-frequency variants and determine the influence of genetic and environmental factors on SUA.

When there is a mismatch between the target identity and the driver identity, face reenactment suffers severe degradation in the quality of the result, especially in a few-shot setting. The identity preservation problem, where the model loses the detailed information of the target leading to a defective output, is the most common failure mode. The problem has several potential sources such as the identity of the driver leaking due to the identity mismatch, or dealing with unseen large poses. To overcome such problems, we introduce components that address the mentioned problem: image attention block, target feature alignment, and landmark transformer. Through attending and warping the relevant features, the proposed architecture, called MarioNETte, produces high-quality reenactments of unseen identities in a few-shot setting. In addition, the landmark transformer dramatically alleviates the identity preservation problem by isolating the expression geometry through landmark disentanglement. Comprehensive experiments are performed to verify that the proposed framework can generate highly realistic faces, outperforming all other baselines, even under a significant mismatch of facial characteristics between the target and the driver., In AAAI 2020

Exemplar-based generative models for open-domain conversation produce responses based on the exemplars provided by the retriever, taking advantage of generative models and retrieval models. However, they often ignore the retrieved exemplars while generating responses or produce responses over-fitted to the retrieved exemplars. In this paper, we argue that these drawbacks are derived from the one-to-many problem of the open-domain conversation. When the retrieved exemplar is relevant to the given context yet significantly different from the gold response, the exemplar-based generative models are trained to ignore the exemplar since the exemplar is not helpful for generating the gold response. On the other hand, when the retrieved exemplar is lexically similar to the gold response, the generative models are trained to rely on the exemplar highly. Therefore, we propose a training method selecting exemplars that are semantically relevant to the gold response but lexically distanced from the gold response to mitigate the above disadvantages. In the training phase, our proposed training method first uses the gold response instead of dialogue context as a query to select exemplars that are semantically relevant to the gold response. And then, it eliminates the exemplars that lexically resemble the gold responses to alleviate the dependency of the generative models on that exemplars. The remaining exemplars could be irrelevant to the given context since they are searched depending on the gold response. Thus, our proposed training method further utilizes the relevance scores between the given context and the exemplars to penalize the irrelevant exemplars. Extensive experiments demonstrate that our proposed training method alleviates the drawbacks of the existing exemplar-based generative models and significantly improves the performance in terms of appropriateness and informativeness.

ImportancePolygenic risk scores (PRSs), which aggregate the genetic effects of single-nucleotide variants identified in genome-wide association studies (GWASs), can help distinguish individuals at a high genetic risk for Alzheimer disease (AD). However, genetic studies have predominantly focused on populations of European ancestry.ObjectiveTo evaluate the transferability of a PRS for AD in the Korean population using summary statistics from a prior GWAS of European populations.Design, Setting, and ParticipantsThis cohort study developed a PRS based on the summary statistics of a large-scale GWAS of a European population (the International Genomics of Alzheimer Project; 21 982 AD cases and 41 944 controls). This PRS was tested for an association with AD dementia and its related phenotypes in 1634 Korean individuals, who were recruited from 2013 to 2019. The association of a PRS based on a GWAS of a Japanese population (the National Center for Geriatrics and Gerontology; 3962 AD cases and 4074 controls) and a transancestry meta-analysis of European and Japanese GWASs was also evaluated. Data were analyzed from December 2020 to June 2021.Main Outcomes and MeasuresRisk of AD dementia, amnestic mild cognitive impairment (aMCI), earlier symptom onset, and amyloid β deposition (Aβ).ResultsA total of 1634 Korean patients (969 women [59.3%]), including 716 individuals (43.6%) with AD dementia, 222 (13.6%) with aMCI, and 699 (42.8%) cognitively unimpaired controls, were analyzed in this study. The mean (SD) age of the participants was 71.6 (9.0) years. Higher PRS was associated with a higher risk of AD dementia independent of APOE ɛ4 status in the Korean population (OR, 1.95; 95% CI, 1.40-2.72; P APOE ɛ4 status. The PRS based on a transancestry meta-analysis of data sets comprising 2 distinct ancestries showed a slightly improved accuracy.Conclusions and RelevanceIn this cohort study, a PRS derived from a European GWAS identified individuals at a high risk for AD dementia in the Korean population. These findings emphasize the transancestry transferability and clinical value of PRSs and suggest the importance of enriching diversity in genetic studies of AD.

All-solid-state batteries (ASSBs) offer a fundamental solution to mitigate the safety and reliability issues of conventional lithium-ion batteries utilizing flammable liquid electrolytes. However, interfacial resistances between the cathode materials and solid electrolytes, which originate from poor solid-solid contacts and detrimental interfacial reactions, limit the electrochemical performances of ASSBs. Recently, various approaches have been developed to realize high-capacity composite cathodes with improved cycling stability. For example, single-crystal LiNi0.8Co0.1Mn0.1O2 (NCM811) has been reported to mitigate the capacity fading resulting from cracking of commonly adopted multi-crystal NCM811. Also, halide-type solid electrolytes are reported to exhibit high Li-ion conductivity and electrochemical stability with NCM. In this work, we systematically study the interfacial and charge-transport impedances of NCM composite cathodes with halide solid electrolytes. The composite cathodes comprising single- or multi-crystal NCM811 and Li6PS5Cl or Li3InCl6 (and conductive agents) are fabricated to characterize their electrochemical impedance behaviors. In particular, we analyze the evolution of the interfacial and charge-transport impedances during charge–discharge cycling based on a multi-rail transmission line model combined with interfacial reactions. In addition, we investigate the chemical, electrochemical, and mechanical degradations of composite cathodes using various analytical tools to elucidate performance-determining factors of ASSBs.

Background and objectives: Parkinson’s disease (PD) and schizophrenia often share symptomatology. Psychotic symptoms are prevalent in patients with PD, and similar motor symptoms with extrapyramidal signs are frequently observed in antipsychotic-naïve patients with schizophrenia as well as premorbid families. However, few studies have examined the relationship between PD and schizophrenia. We performed this study to evaluate whether genetic variants which increase PD risk influence the risk of developing schizophrenia, and vice versa. Materials and Methods: Two-sample Mendelian randomization (TSMR) with summary statistics from large-scale genome-wide association studies (GWAS) was applied. Summary statistics were extracted for these instruments from GWAS of PD and schizophrenia, Results: We found an increase in the risk of schizophrenia per one-standard deviation (SD) increase in the genetically-predicted PD risk (inverse-variance weighted method, odds ratio = 1.10, 95% confidence interval, 1.05−1.15, p = 3.49 × 10−5). The association was consistent in sensitivity analyses, including multiple TSMR methods, analysis after removing outlier variants with potential pleiotropic effects, and analysis after applying multiple GWAS subthresholds. No relationships were evident between PD and smoking or other psychiatric disorders, including attention deficit hyperactivity disorder, autism spectrum disorder, bipolar affective disorder, major depressive disorder, Alzheimer’s disease, or alcohol dependence. However, we did not find a reverse relationship, genetic variants increasing schizophrenia risk did not alter the risk of PD, Conclusions: Overall, our findings suggest that increased genetic risk of PD can be associated with increased risk of schizophrenia. This association supports the intrinsic nature of the psychotic symptom in PD rather than medication or environmental effects. Future studies for possible comorbidities and shared genetic structure between the two diseases are warranted.

This paper presents a widely adaptive time-delayed control (WATDC) without imposing any restrictions on allowable control gains to make the most of the advantages of time-delayed control (TDC) and, then, applies the WATDC to robot manipulators. Since the proposed WATDC can provide arbitrarily high gains by using the time-varying bounds of time-delayed estimation errors, it has a room for improving the tracking performance and robustness of the existing stabilizing TDCs that have narrow range of control gains depending on system parameters comprising the inertia of a robot manipulator. Furthermore, the proposed WATDC employs a fast adaptive law to generate wide-ranging and well-timed control gains that depend on the magnitude of tracking errors. In other words, timely adaptation over a wide range of control gains makes the WATDC provide suitable control effort for desirable output responses. Additionally, to suppress unfavorable inherent time-delayed estimation errors arising from one sample delayed measurements, the proposed WATDC works together with a sliding-mode control that has switching gains based on the time-varying bounds of time-delayed estimation errors. In simulations and experiments with robot manipulators, the proposed WATDC has better tracking performance and robustness than the existing TDCs due to a wide range of adaptive control gains and the time-delayed-estimation-error-dependent switching gains.

In this study, we have analyzed the optimal bias condition of dummy WL for the sub-block gate induced drain leakage (GIDL) erase operation in 16-layer 3D NAND flash memory. Three-dimensional NAND flash memory performs an erase operation in units of pages. Increasing the number of stacks increases the number of cells that are erased at one time, which can lead to undesirable durability degradation. In this case, the sub-block erase operation can reduce the burden on the cell by up to half, due to the erase operation. The distribution of the hole density (hDensity) and the potential, according to VDummy, was analyzed when block1 and block2 were erased by setting WL0:WL7 to block1, WL9:WL15 to block2, and WL8 to dummy WL. For the simulation results, block1 showed an optimal distribution of hDensity and potential in the order of 20 V, floating, and 0 V. In block2, the optimal distribution of hDensity was shown in the order of 20 V, floating, and 0 V, with the optimal distribution of the potential in the order of floating and 0 V.

The current evaluation protocol of long-tailed visual recognition trains the classification model on the long-tailed source label distribution and evaluates its performance on the uniform target label distribution. Such protocol has questionable practicality since the target may also be long-tailed. Therefore, we formulate long-tailed visual recognition as a label shift problem where the target and source label distributions are different. One of the significant hurdles in dealing with the label shift problem is the entanglement between the source label distribution and the model prediction. In this paper, we focus on disentangling the source label distribution from the model prediction. We first introduce a simple but overlooked baseline method that matches the target label distribution by post-processing the model prediction trained by the cross-entropy loss and the Softmax function. Although this method surpasses state-of-the-art methods on benchmark datasets, it can be further improved by directly disentangling the source label distribution from the model prediction in the training phase. Thus, we propose a novel method, LAbel distribution DisEntangling (LADE) loss based on the optimal bound of Donsker-Varadhan representation. LADE achieves state-of-the-art performance on benchmark datasets such as CIFAR-100-LT, Places-LT, ImageNet-LT, and iNaturalist 2018. Moreover, LADE outperforms existing methods on various shifted target label distributions, showing the general adaptability of our proposed method., Comment: CVPR 2021

Occupational attainment, which represents middle-age cognitive activities, is a known proxy marker of cognitive reserve for Alzheimer's disease. Previous genome-wide association studies have identified numerous genetic variants and revealed the genetic architecture of educational attainment, another marker of cognitive reserve. However, the genetic architecture and heritability for occupational attainment remain elusive. We performed a large-scale genome-wide association study of occupational attainment with 248 847 European individuals from the UK Biobank using the proportional odds logistic mixed model method. In this analysis, we defined occupational attainment using the classified job levels formulated in the UK Standard Occupational Classification system considering the individual professional skill and academic level. We identified 30 significant loci (P < 5 × 10−8); 12 were novel variants, not associated with other traits. Among them, four lead variants were associated with genes expressed in brain tissues by expression quantitative trait loci mapping from 10 brain regions: rs13002946, rs3741368, rs11654986 and rs1627527. The single nucleotide polymorphism-based heritability was estimated to be 8.5% (standard error of the mean = 0.004) and partitioned heritability was enriched in the CNS and brain tissues. Genetic correlation analysis showed shared genetic backgrounds between occupational attainment and multiple traits, including education, intelligence, leisure activities, life satisfaction and neuropsychiatric disorders. In two-sample Mendelian randomization analysis, we demonstrated that high occupation levels were associated with reduced risk for Alzheimer's disease [odds ratio (OR) = 0.78, 95% confidence interval (CI) = 0.65–0.92 in inverse variance weighted method; OR = 0.73, 95% CI = 0.57–0.92 in the weighted median method]. This causal relationship between occupational attainment and Alzheimer's disease was robust in additional sensitivity analysis that excluded potentially pleiotropic single nucleotide polymorphisms (OR = 0.72, 95% CI = 0.57–0.91 in the inverse variance weighted method; OR = 0.72, 95% CI = 0.53–0.97 in the weighted median method). Multivariable Mendelian randomization confirmed that occupational attainment had an independent effect on the risk for Alzheimer’s disease even after taking educational attainment into account (OR = 0.72, 95% CI = 0.54–0.95 in the inverse variance weighted method; OR = 0.68, 95% CI = 0.48–0.97 in the weighted median method). Overall, our analyses provide insights into the genetic architecture of occupational attainment and demonstrate that occupational attainment is a potential causal protective factor for Alzheimer's disease as a proxy marker of cognitive reserve.

Despite the remarkable performance of large-scale generative models in open-domain conversation, they are known to be less practical for building real-time conversation systems due to high latency. On the other hand, retrieval models could return responses with much lower latency but show inferior performance to the large-scale generative models since the conversation quality is bounded by the pre-defined response set. To take advantage of both approaches, we propose a new training method called G2R (Generative-to-Retrieval distillation) that preserves the efficiency of a retrieval model while leveraging the conversational ability of a large-scale generative model by infusing the knowledge of the generative model into the retrieval model. G2R consists of two distinct techniques of distillation: the data-level G2R augments the dialogue dataset with additional responses generated by the large-scale generative model, and the model-level G2R transfers the response quality score assessed by the generative model to the score of the retrieval model by the knowledge distillation loss. Through extensive experiments including human evaluation, we demonstrate that our retrieval-based conversation system trained with G2R shows a substantially improved performance compared to the baseline retrieval model while showing significantly lower inference latency than the large-scale generative models., Comment: EMNLP21-Findings

Saliency Map, the gradient of the score function with respect to the input, is the most basic technique for interpreting deep neural network decisions. However, saliency maps are often visually noisy. Although several hypotheses were proposed to account for this phenomenon, there are few works that provide rigorous analyses of noisy saliency maps. In this paper, we firstly propose a new hypothesis that noise may occur in saliency maps when irrelevant features pass through ReLU activation functions. Then, we propose Rectified Gradient, a method that alleviates this problem through layer-wise thresholding during backpropagation. Experiments with neural networks trained on CIFAR-10 and ImageNet showed effectiveness of our method and its superiority to other attribution methods., Comment: Accepted at the 2019 ICCV Workshop on Interpreting and Explaining Visual AI Models (VXAI 2019)

Keyword spotting (KWS) plays a critical role in enabling speech-based user interactions on smart devices. Recent developments in the field of deep learning have led to wide adoption of convolutional neural networks (CNNs) in KWS systems due to their exceptional accuracy and robustness. The main challenge faced by KWS systems is the trade-off between high accuracy and low latency. Unfortunately, there has been little quantitative analysis of the actual latency of KWS models on mobile devices. This is especially concerning since conventional convolution-based KWS approaches are known to require a large number of operations to attain an adequate level of performance. In this paper, we propose a temporal convolution for real-time KWS on mobile devices. Unlike most of the 2D convolution-based KWS approaches that require a deep architecture to fully capture both low- and high-frequency domains, we exploit temporal convolutions with a compact ResNet architecture. In Google Speech Command Dataset, we achieve more than \textbf{385x} speedup on Google Pixel 1 and surpass the accuracy compared to the state-of-the-art model. In addition, we release the implementation of the proposed and the baseline models including an end-to-end pipeline for training models and evaluating them on mobile devices., In INTERSPEECH 2019

In this study, Apriori algorithm was employed to genetic sequence patterns of Aedes albopictus (Asian tiger mosquito, Skuse, Dengue fever vector) in native and invasive ranges. It has spread widely across the world from its native region, South-east Asian countries, to every continent except Antarctica. To find the congruity of the species and their origins, I decided to compare them. To analyze the short-term genetic mutations, mtDNA was used to derive the pattern

This paper deals with a real-time panorama algorithm for mobile camera systems. The proposed system generates the panoramic images and shows the intermediate results simultaneously on the mobile display. The proposed panorama system consists of feature point extraction, feature tracking, rotation matrix estimation, and image warping onto cylindrical surface. Feature points are extracted by fast Hessian detector in the low resolution and corner detector in the high resolution. Then, the feature points are tracked by matching between input frame and synthesized panorama image. The camera motion is modeled as a rotation matrix which is estimated using the tracked feature points. For realtime operation of panoramic image synthesis, we propose a method to estimate the rotation matrix using non-iterative least square method. We project the feature points of image onto the unit sphere surface in the world coordinates. This enables us to estimate the parameters of rotation matrix as the linear and non-iterative problem. Finally, we project the input frames onto panorama surface using the rotation matrix. We also implement a real-time display interface to show the intermediate panorama results while panorama image is being generated. Thus, the proposed panorama system paints the panorama canvas with real images. According to the experiments in the mobile systems such as mobile phone and tablet PC, the proposed system works well to generate the panoramic images in real-time.