On the Green's matrices of strongly parabolic systems of second order

We establish existence and various estimates of fundamental matrices and Green's matrices for divergence form, second order strongly parabolic systems in arbitrary cylindrical domains under the assumption that solutions of the systems satisfy an interior H\"{o}lder continuity estimate. We present a unified approach valid for both the scalar and the vectorial cases.Comment: 33 page

Time-series implications of the permanent income hypothesis on durable goods consumption

Mankiw\u27s rational expectations-permanent income hypothesis (RE-PIH) model on consumer durable expenditures predicts that the change in durable expenditures should follow an MA (1) process. Empirical tests of this joint hypothesis, however, have been rejected using the postwar U.S. data. This thesis presents a time-series representation of the RE-PIH model that is capable of explaining the quarterly aggregated durable goods expenditure series. A novel feature of the analysis is that the observed infrequent purchases of durable goods by the consumers are incorporated into the model and that the time aggregation problem is explicitly addressed to investigate the aggregate dynamics of the durable expenditures. The time-series implication of the base model is that the change in durable expenditures is a function of the durable goods purchase interval. Mankiw\u27s MA (1) model is shown to be a special case where the purchase interval is one quarter. Estimation results show that the RE-PIH model is capable of explaining the quarterly aggregate dynamics of the consumer durable goods expenditures once the infrequent microeconomic action is incorporated into the model and the time aggregation problem is explicitly taken into account

Malware Visualization and Similarity via Tracking Binary Execution Path

Today, computer systems are widely and importantly used throughout society, and malicious codes to take over the system and perform malicious actions are continuously being created and developed. These malicious codes are sometimes found in new forms, but in many cases they are modified from existing malicious codes. Since there are too many threatening malicious codes that are being continuously generated for human analysis, various studies to efficiently detect, classify, and analyze are essential. There are two main ways to analyze malicious code. First, static analysis is a technique to identify malicious behaviors by analyzing the structure of malicious codes or specific binary patterns at the code level. The second is a dynamic analysis technique that uses virtualization tools to build an environment in a virtual machine and executes malicious code to analyze malicious behavior. The method used to analyze malicious codes in this paper is a static analysis technique. Although there is a lot of information that can be obtained from dynamic analysis, there is a disadvantage that it can be analyzed normally only when the environment in which each malicious code is executed is matched. However, since the method proposed in this paper tracks and analyzes the execution stream of the code, static analysis is performed, but the effect of dynamic analysis can be expected.The core idea of this paper is to express the malicious code as a 25 25 pixel image using 25 API categories selected. The interaction and frequency of the API is made into a 25 25 pixel image based on a matrix using RGB values. When analyzing the malicious code, the Euclidean distance algorithm is applied to the generated image to measure the color similarity, and the similarity of the mutual malicious behavior is calculated based on the final Euclidean distance value. As a result, as a result of comparing the similarity calculated by the proposed method with the similarity calculated by the existing similarity calculation method, the similarity was calculated to be 5-10% higher on average. The method proposed in this study spends a lot of time deriving results because it analyzes, visualizes, and calculates the similarity of the visualized sample. Therefore, it takes a lot of time to analyze a huge number of malicious codes. A large amount of malware can be analyzed through follow-up studies, and improvements are needed to study the accuracy according to the size of the data set

Omega-K Algorithm Using Plane Wave Approximation for Forward-Looking Imaging Radar

We propose an Omega-K algorithm that uses plane wave approximation for image formation in forward-looking imaging radar (FIRA) with the multi-input/double-output configuration. We assume that each of the transmitting antennas is located at the center of the receiving antenna array by applying a virtual antenna array. Then, we solve numerical equations in an approximation of the plane wave with the direction normal to the antenna array. Finally, we can obtain an image by proceeding with the following steps in order: the matched filtering, Stolt interpolation, two-dimensional inverse fast Fourier transform, phase compensation, image registration, and image merging. The performance of the proposed algorithm is verified through a simulation and a real experiment with neighboring targets. The results show that the proposed Omega-K algorithm with plane wave approximation can be successfully applied to FIRA systems with bistatic synthetic aperture radar configuration

Whole Genome Analysis of the Red-Crowned Crane Provides Insight into Avian Longevity

The red-crowned crane (Grus japonensis) is an endangered, large-bodied crane native to East Asia. It is a traditional symbol of longevity and its long lifespan has been confirmed both in captivity and in the wild. Lifespan in birds is known to be positively correlated with body size and negatively correlated with metabolic rate, though the genetic mechanisms for the red-crowned crane's long lifespan have not previously been investigated. Using whole genome sequencing and comparative evolutionary analyses against the grey-crowned crane and other avian genomes, including the long-lived common ostrich, we identified red-crowned crane candidate genes with known associations with longevity. Among these are positively selected genes in metabolism and immunity pathways (NDUFA5, NDUFA8, NUDT12, SOD3, CTH, RPA1, PHAX, HNMT, HS2ST1, PPCDC, PSTK CD8B, GP9, IL-9R, and PTPRC). Our analyses provide genetic evidence for low metabolic rate and longevity, accompanied by possible convergent adaptation signatures among distantly related large and long-lived birds. Finally, we identified low genetic diversity in the red-crowned crane, consistent with its listing as an endangered species, and this genome should provide a useful genetic resource for future conservation studies of this rare and iconic species

Depression and suicide risk prediction models using blood-derived multi-omics data

More than 300 million people worldwide experience depression; annually, ~800,000 people die by suicide. Unfortunately, conventional interview-based diagnosis is insufficient to accurately predict a psychiatric status. We developed machine learning models to predict depression and suicide risk using blood methylome and transcriptome data from 56 suicide attempters (SAs), 39 patients with major depressive disorder (MDD), and 87 healthy controls. Our random forest classifiers showed accuracies of 92.6% in distinguishing SAs from MDD patients, 87.3% in distinguishing MDD patients from controls, and 86.7% in distinguishing SAs from controls. We also developed regression models for predicting psychiatric scales with R2 values of 0.961 and 0.943 for Hamilton Rating Scale for Depression???17 and Scale for Suicide Ideation, respectively. Multi-omics data were used to construct psychiatric status prediction models for improved mental health treatment

Chromosome-scale assembly comparison of the Korean Reference Genome KOREF from PromethION and PacBio with Hi-C mapping information.

BACKGROUND:Long DNA reads produced by single-molecule and pore-based sequencers are more suitable for assembly and structural variation discovery than short-read DNA fragments. For de novo assembly, Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) are the favorite options. However, PacBio's SMRT sequencing is expensive for a full human genome assembly and costs more than $40,000 US for 30× coverage as of 2019. ONT PromethION sequencing, on the other hand, is 1/12 the price of PacBio for the same coverage. This study aimed to compare the cost-effectiveness of ONT PromethION and PacBio's SMRT sequencing in relation to the quality. FINDINGS:We performed whole-genome de novo assemblies and comparison to construct an improved version of KOREF, the Korean reference genome, using sequencing data produced by PromethION and PacBio. With PromethION, an assembly using sequenced reads with 64× coverage (193 Gb, 3 flowcell sequencing) resulted in 3,725 contigs with N50s of 16.7 Mb and a total genome length of 2.8 Gb. It was comparable to a KOREF assembly constructed using PacBio at 62× coverage (188 Gb, 2,695 contigs, and N50s of 17.9 Mb). When we applied Hi-C-derived long-range mapping data, an even higher quality assembly for the 64× coverage was achieved, resulting in 3,179 scaffolds with an N50 of 56.4 Mb. CONCLUSION:The pore-based PromethION approach provided a high-quality chromosome-scale human genome assembly at a low cost with long maximum contig and scaffold lengths and was more cost-effective than PacBio at comparable quality measurements