Counting statistics based on the analytic solutions of the differential-difference equation for birth-death processes

Birth-death processes take place ubiquitously throughout the universe. In general, birth and death rates depend on the system size (corresponding to the number of products or customers undergoing the birth-death process) and thus vary every time birth or death occurs, which makes fluctuations in the rates inevitable. The differential-difference equation governing the time evolution of such a birth-death process is well established, but it resists solving for a non-asymptotic solution. In this work, we present the analytic solution of the differential-difference equation for birth-death processes without approximation. The time-dependent solution we obtain leads to an analytical expression for counting statistics of products (or customers). We further examine the relationship between the system size fluctuations and the birth and death rates, and find that statistical properties (variance subtracted by mean) of the system size are determined by the mean death rate as well as the covariance of the system size and the net growth rate (i.e., the birth rate minus the death rate). This work suggests a promising new direction for quantitative investigations into birth-death processes

Study on Moth Diversity in islands and land borders, in the southwest area of Korean Peninsula

AbstractIn order to investigate moth diversity in the bordering islands and inland in the southwest area of Korean Peninsula, a total of 1,127 individuals of 270 species from 214 genera, 16 families, 1 order were collected from four inland sites and four island sites near Mokpo, at the southern end of the Korean Peninsula from April to October of 2009. According to the analysis of the collected moths, Noctuidae with its 102 species were the most frequently collected order and followed by Geometridae and Pyralidae. Among the 5 regions studied every month (Yangeulsan (Mt.), Oedaldo, Yudalsan (Mt.), Ibamsan (Mt.), Seungdalsan (Mt.)), Mt. Seungdalsan showed the highest species diversity with 129 species from 452 moths collected, followed by decreasing order of Yangeulsan at 70 species from 139 moths, Ibamsan at 59 species from 116 moths, Oedaldo at 58 species from 133 moths and Yudalsan of 48 species from 125 moths. In the three regions in which samples were taken once, Dalido showed the highest figure at 49 species from 98 moths collected, followed by Gohado at 23 species from 37 moths and Heosado at 14 species from 27 moths

Adaptive Noise Reduction Algorithm to Improve R Peak Detection in ECG Measured by Capacitive ECG Sensors

Electrocardiograms (ECGs) can be conveniently obtained using capacitive ECG sensors. However, motion noise in measured ECGs can degrade R peak detection. To reduce noise, properties of reference signal and ECG measured by the sensors are analyzed and a new method of active noise cancellation (ANC) is proposed in this study. In the proposed algorithm, the original ECG signal at QRS interval is regarded as impulsive noise because the adaptive filter updates its weight as if impulsive noise is added. As the proposed algorithm does not affect impulsive noise, the original signal is not reduced during ANC. Therefore, the proposed algorithm can conserve the power of the original signal within the QRS interval and reduce only the power of noise at other intervals. The proposed algorithm was verified through comparisons with recent research using data from both indoor and outdoor experiments. The proposed algorithm will benefit a noise reduction of noisy biomedical signal measured from sensors.11Ysciescopu

Effect of laser-dimpled titanium surfaces on attachment of epithelial-like cells and fibroblasts.

PurposeThe objective of this study was to conduct an in vitro comparative evaluation of polished and laserdimpled titanium (Ti) surfaces to determine whether either surface has an advantage in promoting the attachment of epithelial-like cells and fibroblast to Ti.Materials and methodsForty-eight coin-shaped samples of commercially pure, grade 4 Ti plates were used in this study. These discs were cleaned to a surface roughness (Ra: roughness centerline average) of 180 nm by polishing and were divided into three groups: SM (n=16) had no dimples and served as the control, SM15 (n=16) had 5-µm dimples at 10-µm intervals, and SM30 (n=16) had 5-µm dimples at 25-µm intervals in a 2 × 4 mm(2) area at the center of the disc. Human gingival squamous cell carcinoma cells (YD-38) and human lung fibroblasts (MRC-5) were cultured and used in cell proliferation assays, adhesion assays, immunofluorescent staining of adhesion proteins, and morphological analysis by SEM. The data were analyzed statistically to determine the significance of differences.ResultsThe adhesion strength of epithelial cells was higher on Ti surfaces with 5-µm laser dimples than on polished Ti surfaces, while the adhesion of fibroblasts was not significantly changed by laser treatment of implant surfaces. However, epithelial cells and fibroblasts around the laser dimples appeared larger and showed increased expression of adhesion proteins.ConclusionThese findings demonstrate that laser dimpling may contribute to improving the periimplant soft tissue barrier. This study provided helpful information for developing the transmucosal surface of the abutment

RCM-Fusion: Radar-Camera Multi-Level Fusion for 3D Object Detection

While LiDAR sensors have been succesfully applied to 3D object detection, the affordability of radar and camera sensors has led to a growing interest in fusiong radars and cameras for 3D object detection. However, previous radar-camera fusion models have not been able to fully utilize radar information in that initial 3D proposals were generated based on the camera features only and the instance-level fusion is subsequently conducted. In this paper, we propose radar-camera multi-level fusion (RCM-Fusion), which fuses radar and camera modalities at both the feature-level and instance-level to fully utilize radar information. At the feature-level, we propose a Radar Guided BEV Encoder which utilizes radar Bird's-Eye-View (BEV) features to transform image features into precise BEV representations and then adaptively combines the radar and camera BEV features. At the instance-level, we propose a Radar Grid Point Refinement module that reduces localization error by considering the characteristics of the radar point clouds. The experiments conducted on the public nuScenes dataset demonstrate that our proposed RCM-Fusion offers 11.8% performance gain in nuScenes detection score (NDS) over the camera-only baseline model and achieves state-of-the-art performaces among radar-camera fusion methods in the nuScenes 3D object detection benchmark. Code will be made publicly available.Comment: 10 pages, 5 figure

Zero-frequency Bragg gap by spin-harnessed metamaterial

The Bragg gap that stops wave propagation may not be formed from zero or a very low frequency unless the periodicity of a periodic system is unrealistically large. Accordingly, the Bragg gap has been considered to be inappropriate for low frequency applications despite its broad bandwidth. Here, we report a new mechanism that allows formation of the Bragg gap starting from a nearly zero frequency. The mechanism is based on the finding that if additional spin motion is coupled with the longitudinal motion of a mass of a diatomic mechanical periodic system, the Bragg gap starting from a nearly zero frequency can be formed. The theoretical analysis shows that the effective mass and stiffness at the band gap frequencies are all positive, confirming that the formed stop band is a Bragg gap. The periodic system is realized by a spin-harnessed metamaterial which incorporates unique linkage mechanisms. The numerical and experimental validation confirmed the formation of the low-frequency Bragg gap. The zero-frequency Bragg gap is expected to open a new way to control hard-to-shield low-frequency vibration and noise

Sequence-to-Sequence Prediction of Vehicle Trajectory via LSTM Encoder-Decoder Architecture

In this paper, we propose a deep learning based vehicle trajectory prediction technique which can generate the future trajectory sequence of surrounding vehicles in real time. We employ the encoder-decoder architecture which analyzes the pattern underlying in the past trajectory using the long short-term memory (LSTM) based encoder and generates the future trajectory sequence using the LSTM based decoder. This structure produces the $K$ most likely trajectory candidates over occupancy grid map by employing the beam search technique which keeps the $K$ locally best candidates from the decoder output. The experiments conducted on highway traffic scenarios show that the prediction accuracy of the proposed method is significantly higher than the conventional trajectory prediction techniques

The Fruit Hull of Gleditsia sinensis

Lung cancer has substantial mortality worldwide, and chemotherapy is a routine regimen for the treatment of patients with lung cancer, despite undesirable effects such as drug resistance and chemotoxicity. Here, given a possible antitumor effect of the fruit hull of Gleditsia sinensis (FGS), we tested whether FGS enhances the effectiveness of cis-diammine dichloridoplatinum (II) (CDDP), a chemotherapeutic drug. We found that CDDP, when administered with FGS, significantly decreased the viability and increased the apoptosis and cell cycle arrest of Lewis lung carcinoma (LLC) cells, which were associated with the increase of p21 and decreases of cyclin D1 and CDK4. Concordantly, when combined with FGS, CDDP significantly reduced the volume and weight of tumors derived from LLC subcutaneously injected into C57BL/6 mice, with concomitant increases of phosphor-p53 and p21 in tumor tissue. Together, these results show that FGS could enhance the antitumor activity of CDDP, suggesting that FGS can be used as a complementary measure to enhance the efficacy of a chemotherapeutic agent such as CDDP

Size distributions of atmospheric particulate matter and associated trace metals in the multi-industrial city of Ulsan, Korea

Particulate matter (PM) was collected using micro-orifice uniform deposit impactors from a residential (RES) site and an industrial (IND) site in Ulsan, South Korea, in September-October 2014. The PM samples were measured based on their size distributions (11 stages), ranging from 0.06 ??m to over 18.0 ??m. Nine trace metals (As, Se, Cr, V, Cd, Pb, Ba, Sb, and Zn) associated with PM were analyzed. The PM samples exhibited weak bimodal distributions irrespective of sampling sites and events, and the mean concentrations of total PM (TPM) measured at the IND site (56.7 ??g/m3) was higher than that measured at the RES site (38.2 ??g/m3). The IND site also showed higher levels of nine trace metals, reflecting the influence of industrial activities and traffic emissions. At both sites, four trace metals (Ba, Zn, V, and Cr) contributed to over 80% of the total concentrations in TPM. The modality of individual trace metals was not strong except for Zn; however, the nine trace metals in PM2.5 and PM10 accounted for approximately 50% and 90% of the total concentrations in TPM, respectively. This result indicates that the size distributions of PM and trace metals are important to understand how respirable PM affects public health

OASIS: Online Application for the Survival Analysis of Lifespan Assays Performed in Aging Research

Aging is a fundamental biological process. Characterization of genetic and environmental factors that influence lifespan is a crucial step toward understanding the mechanisms of aging at the organism level. To capture the different effects of genetic and environmental factors on lifespan, appropriate statistical analyses are needed.We developed an online application for survival analysis (OASIS) that helps conduct various novel statistical tasks involved in analyzing survival data in a user-friendly manner. OASIS provides standard survival analysis results including Kaplan-Meier estimates and mean/median survival time by taking censored survival data. OASIS also provides various statistical tests including comparison of mean survival time, overall survival curve, and survival rate at specific time point. To visualize survival data, OASIS generates survival and log cumulative hazard plots that enable researchers to easily interpret their experimental results. Furthermore, we provide statistical methods that can analyze variances among survival datasets. In addition, users can analyze proportional effects of risk factors on survival.OASIS provides a platform that is essential to facilitate efficient statistical analyses of survival data in the field of aging research. Web application and a detailed description of algorithms are accessible from http://sbi.postech.ac.kr/oasis