Modeling Autoregressive Models in Cool Island Effects associated with Remote Telemeter Technology (ASTER) in Taiwan: A GIS Approach

AbstractA microclimate is the unique climate of a small-scale region, such as a field or parts of urban or rural areas. The weather variables in a microclimate include temperature, wind, humidity, land forms, and water regimes. In Northern Taiwan's Taoyuan County, irrigation ponds take a long time to heat up during the summer months, keeping these rural areas cooler than surrounding urbanized areas. Based on Geographic Information System (GIS) layers associated with Digital Terrain Modeling (DTM), along with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images, this paper examines temperature variables in four counties/cities in Taiwan for the past century. Urban development is found to have contributed to temperature increases, but an understanding of the cooling mechanism is still incomplete. Temperatures in the Taoyuan tableland have declined, at odds with trends in other areas in Taiwan as well as on a global scale. In Taoyuan, the Times-Series Regression Model was used to extrapolated a downward trend from a mean current temperature of 21.3°C currently down to 19.72°C in 2099, assuming the area of irrigation ponds remain unchanged

Bearing fault feature extraction method based on complete ensemble empirical mode decomposition with adaptive noise

As an important part of rotating machinery, bearings play an important role in large-scale mechanical equipment. Abnormal bearing conditions may cause the machine to malfunction, or even evolve into a serious accident. Therefore, the accurate and timely fault diagnosis of the bearing is of great significance. Based on EMD, this paper introduces the working principles and characteristics of EEMD and CEEMDAN, respectively. Then the signal was decomposed by EEMD and CEEMDAN respectively. The simulation results show that CEEMDAN has better effect on signal decomposition. Then, comparing the effect of CEEMDAN and EEMD on bearing fault feature frequency extraction, the experiment proves that CEEMDAN has a better ability to preserve original signal and eliminate noise than EEMD method, and can extract bearing fault feature more accurately and timely

Anti-cancer natural products isolated from chinese medicinal herbs

In recent years, a number of natural products isolated from Chinese herbs have been found to inhibit proliferation, induce apoptosis, suppress angiogenesis, retard metastasis and enhance chemotherapy, exhibiting anti-cancer potential both in vitro and in vivo. This article summarizes recent advances in in vitro and in vivo research on the anti-cancer effects and related mechanisms of some promising natural products. These natural products are also reviewed for their therapeutic potentials, including flavonoids (gambogic acid, curcumin, wogonin and silibinin), alkaloids (berberine), terpenes (artemisinin, β-elemene, oridonin, triptolide, and ursolic acid), quinones (shikonin and emodin) and saponins (ginsenoside Rg3), which are isolated from Chinese medicinal herbs. In particular, the discovery of the new use of artemisinin derivatives as excellent anti-cancer drugs is also reviewed

Trends and Patterns of Disparities in Burden of Lung Cancer in the United States, 1974-2015

Background: Although lung cancer incidence and mortality have been declining since the 1990s, the extent to which such progress has been made is unequal across population segments. Updated epidemiologic data on trends and patterns of disparities are lacking.Methods: Data on lung cancer cases and deaths during 1974 to 2015 were extracted from the Surveillance, Epidemiology, and End Results program. Age-standardized lung cancer incidence and mortality and their annual percent changes were calculated by histologic types, demographic variables, and tumor characteristics.Results: Lung cancer incidence decreased since 1990 (1990 to 2007: annual percent change, −0.9 [95% CI, −1.0%, −0.8%]; 2007 to 2015: −2.6 [−2.9%, −2.2%]). Among adults aged between 20 and 39 years, a higher incidence was observed among females during 1995 to 2011, after which a faster decline in female lung cancer incidence (males: −2.5% [−2.8%, −2.2%]; females: −3.1% [−4.7%, −1.5%]) resulted in a lower incidence among females. The white population had a higher incidence than the Black population for small cell carcinoma since 1987. Black females were the only group whose adenocarcinoma incidence plateaued since 2012 (−5.0% [−13.0%, 3.7%]). A higher incidence for squamous cell carcinoma was observed among Black males and females than among white males and females during 1974 to 2015. After circa 2005, octogenarians and older patients constituted the group with the highest lung cancer incidence. Incidence for localized and AJCC/TNM stage I lung cancer among octogenarians and older patients plateaued since 2009, while mortality continued to rise (localized: 1.4% [0.6%, 2.1%]; stage I: 6.7% [4.5%, 9.0%]).Conclusions: Lung cancer disparities prevail across population segments. Our findings inform effective approaches to eliminate lung cancer disparities by targeting at-risk populations

Environmental literacy on ecotourism: a study on student knowledge, attitude, and behavioral intentions in China and Taiwan

This study aims to gain further insights to Chinese and Taiwanese university students’ environmental literacy on ecotourism. A structural equation model is developed and validated in an effort to explore the differences between Chinese and Taiwanese university students in terms of their environmental knowledge, environmental attitude, and behavioral intentions. The results showed that the ecotourism perception of Chinese and Taiwanese university students affect their behavioral intentions. Chinese university students exhibited a higher correlation between ecotourism knowledge and behavioral intentions than their Taiwanese counterparts. The findings also revealed differences between the Chinese and Taiwanese students in their perception of ecotourism, and this disparity was particularly evident with regards to how ecotourism should be governed. A moderate difference in ecotourism behavioral intentions was also identified, in which Taiwanese university students were less likely to engage in self-empowerment or private empowerment, to be more educated in the field of ecotourism than their Chinese counterparts

Temporal and Spatial Dynamics of Carbon Fixation by Moso Bamboo (Phyllostachys pubescens) in Subtropical China

To study the temporal and spatial dynamics of carbon fixation by Moso bamboo (Phyllostachys pubescens) in subtropical China, carbon fixation of leaves within the canopy of P. pubescens was measured with a LI-6400 portable photosynthesis system. The results showed that the capability of carbon fixation of P. pubescens leaves had obvious temporal and spatial dynamic variations. It was revealed that there were two peak periods and two low periods in the season variation of carbon fixation capability. Data also revealed that the capability of carbon fixation by five-year-old P. pubescens was more than that of one-year-old and three-year-old. Daily and seasonal carbon fixation showed a negative correlation with the CO2 concentration. The temporal and spatial dynamics of carbon fixation by P. pubescens described above provided a scientific basis for development of technologies in bamboo timber production

Blood DNA methylation sites predict death risk in a longitudinal study of 12,300 individuals

This is the final version. Available on open access from Impact Journals via the DOI in this recordDNA methylation has fundamental roles in gene programming and aging that may help predict mortality. However, no large-scale study has investigated whether site-specific DNA methylation predicts all-cause mortality. We used the Illumina-HumanMethylation450-BeadChip to identify blood DNA methylation sites associated with all-cause mortality for 12, 300 participants in 12 Cohorts of the Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium. Over an average 10-year follow-up, there were 2,561 deaths across the cohorts. Nine sites mapping to three intergenic and six gene-specific regions were associated with mortality (P < 9.3x10-7) independently of age and other mortality predictors. Six sites (cg14866069, cg23666362, cg20045320, cg07839457, cg07677157, cg09615688)-mapping respectively to BMPR1B, MIR1973, IFITM3, NLRC5, and two intergenic regions-were associated with reduced mortality risk. The remaining three sites (cg17086398, cg12619262, cg18424841)-mapping respectively to SERINC2, CHST12, and an intergenic region-were associated with increased mortality risk. DNA methylation at each site predicted 5%-15% of all deaths. We also assessed the causal association of those sites to age-related chronic diseases by using Mendelian randomization, identifying weak causal relationship between cg18424841 and cg09615688 with coronary heart disease. Of the nine sites, three (cg20045320, cg07839457, cg07677157) were associated with lower incidence of heart disease risk and two (cg20045320, cg07839457) with smoking and inflammation in prior CHARGE analyses. Methylation of cg20045320, cg07839457, and cg17086398 was associated with decreased expression of nearby genes (IFITM3, IRF, NLRC5, MT1, MT2, MARCKSL1) linked to immune responses and cardiometabolic diseases. These sites may serve as useful clinical tools for mortality risk assessment and preventative care

Feature Flow: In-network Feature Flow Estimation for Video Object Detection

Optical flow, which expresses pixel displacement, is widely used in many computer vision tasks to provide pixel-level motion information. However, with the remarkable progress of the convolutional neural network, recent state-of-the-art approaches are proposed to solve problems directly on feature-level. Since the displacement of feature vector is not consistent to the pixel displacement, a common approach is to:forward optical flow to a neural network and fine-tune this network on the task dataset. With this method,they expect the fine-tuned network to produce tensors encoding feature-level motion information. In this paper, we rethink this de facto paradigm and analyze its drawbacks in the video object detection task. To mitigate these issues, we propose a novel network (IFF-Net) with an \textbf{I}n-network \textbf{F}eature \textbf{F}low estimation module (IFF module) for video object detection. Without resorting pre-training on any additional dataset, our IFF module is able to directly produce \textbf{feature flow} which indicates the feature displacement. Our IFF module consists of a shallow module, which shares the features with the detection branches. This compact design enables our IFF-Net to accurately detect objects, while maintaining a fast inference speed. Furthermore, we propose a transformation residual loss (TRL) based on \textit{self-supervision}, which further improves the performance of our IFF-Net. Our IFF-Net outperforms existing methods and sets a state-of-the-art performance on ImageNet VID

Online active proposal set generation for weakly supervised object detection

To reduce the manpower consumption on box-level annotations, many weakly supervised object detection methods which only require image-level annotations, have been proposed recently. The training process in these methods is formulated into two steps. They firstly train a neural network under weak supervision to generate pseudo ground truths (PGTs). Then, these PGTs are used to train another network under full supervision. Compared with fully supervised methods, the training process in weakly supervised methods becomes more complex and time-consuming. Furthermore, overwhelming negative proposals are involved at the first step. This is neglected by most methods, which makes the training network biased towards to negative proposals and thus degrades the quality of the PGTs, limiting the training network performance at the second step. Online proposal sampling is an intuitive solution to these issues. However, lacking of adequate labeling, a simple online proposal sampling may make the training network stuck into local minima. To solve this problem, we propose an Online Active Proposal Set Generation (OPG) algorithm. Our OPG algorithm consists of two parts: Dynamic Proposal Constraint (DPC) and Proposal Partition (PP). DPC is proposed to dynamically determine different proposal sampling strategies according to the current training state. PP is used to score each proposal, part proposals into different sets and generate an active proposal set for the network optimization. Through experiments, our proposed OPG shows consistent and significant improvement on both datasets PASCAL VOC 2007 and 2012, yielding comparable performance to the state-of-the-art results.Ministry of Education (MOE)Nanyang Technological UniversitySubmitted/Accepted versionThis work is partly supported by an NTU, Singapore Start-up Grant (04INS000338C130) and MOE, Singapore Tier-1 research grants: RG28/18 (S) and RG22/19 (S)