The origin, evolution, and application of the megapolitan area concept

Robert E. Lang,임재원,Karen A. Danielsen 서울시립대학교 도시과학연구원 2020 도시과학국제저널 Vol.24 No.1

The article explores the origin and evolution of the ‘megapolitan concept', the idea of a super-sized region that began in 1961 in Jean Gottmann's ‘megalopolis,' which he developed to explain large-scale urbanization in the Northeastern U.S. Jerome Picard, a researcher at the Urban Land Institute took up the megalopolis idea in 1967 and applied it to the entire U.S. and projected large-scale urban growth to 2000. The Regional Plan Association (RPA) also applied the megalopolis concept to The Second Regional Plan for New York in 1968. Lang in 2000s, then working with his colleagues at Virginia Tech developed the megapolitan concept and definition-in part to differential the concept from work being done by the University of Pennsylvania for RPA. Lang defined ‘megapolitan clusters’ as multiple megapolitan areas that are networked either by commuting, logistics, or dense air links, but where there is no more than three times the distance used to define a Megapolitan Area between anchor metropolitan areas at their furthest distance. The recent evolution of megapolitan area and megapolitan cluster concepts by Lang and the colleagues is applied to a series of projects, including ‘Sun Corridor’ in 2006 (Phoenix-Tucson) and the Southwest Triangle (SoCal-Sun Corridor-Las Vegas) in 2014. The article ends with the future application of megapolitan area concept in the rapidly growing Southwest Triangle megapolitan cluster.

A Robust Method for Speech Replay Attack Detection

( Lang Lin ),( Rangding Wang ),( Diqun Yan ),( Li Dong ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.1

Spoofing attacks, especially replay attacks, pose great security challenges to automatic speaker verification (ASV) systems. Current works on replay attacks detection primarily focused on either developing new features or improving classifier performance, ignoring the effects of feature variability, e.g., the channel variability. In this paper, we first establish a mathematical model for replay speech and introduce a method for eliminating the negative interference of the channel. Then a novel feature is proposed to detect the replay attacks. To further boost the detection performance, four post-processing methods using normalization techniques are investigated. We evaluate our proposed method on the ASVspoof 2017 dataset. The experimental results show that our approach outperforms the competing methods in terms of detection accuracy. More interestingly, we find that the proposed normalization strategy could also improve the performance of the existing algorithms.

An algorithm for labia minora reduction based on a review of anatomical, configurational, and individual considerations

Lange Maurits DJ,Hage J. Joris,Karim Refaat B,Amant Frederic 대한성형외과학회 2023 Archives of Plastic Surgery Vol.50 No.1

A variety of labiaplasty techniques have been introduced to date, but no single technique will offer the optimal solution for every patient. Rather, the technique should be chosen based on anatomical, configurational, and technical considerations, as well as on patients’ personal preferences regarded maintenance of the labial rim, maintenance of labial sensitivity, and prevention of iatrogenic thickening of the labium. We reviewed, defined, and assessed labial configurational variety, neurovascular supply, reduction techniques, and patient’s preferences as the considerations relevant to the choice of labiaplasty technique. Based on this review, an algorithm was constructed that leads to a choice of reduction technique through five decisions to be made regarding (1) resection or (partial) retention of the labial free rim, (2) the measure of required labial width reduction, (3) labial vascular status, (4) prevention of iatrogenic labial thickening, and (5) preservation of labial sensibility. The choice of techniques includes edge trimming, central spindle form de-epithelialization or full thickness resection, and three modifications of the wedge resection or de-epithelialization technique. These three modifications comprised a modified anterior resection or de-epithelialization combined with posterior flap transposition, a custom flask resection or de-epithelialization, and a modified posterior wedge resection or de-epithelialization combined with anterior flap transposition. Use of the five decisional steps and the inclusion of modifications of all three conventional reduction techniques offer an improved algorithm for the choice of labioplasty technique.

Learning Multiple-Gait Quadrupedal Locomotion via Hierarchical Reinforcement Learning

Lang Wei,Yunxiang Li,Yunfei Ai,Yuze Wu,Hao Xu,Wei Wang,Guoming Hu 한국정밀공학회 2023 International Journal of Precision Engineering and Vol.24 No.9

Over long periods of evolution, legged animals have developed the capability to use a variety of gaits to move efficiently and flexibly at different speeds. To enable quadruped robots to acquire this ability, this study proposes a two-stage training hierarchical framework that can have quadruped robots generate energy-efficient multiple-gait locomotion, consisting of a gait selection policy module and a react controller module. The parameters of both modules are optimized using reinforcement learning. The experimental results in the simulation demonstrate that the proposed method can generate energy-efficient multiple-gait quadrupedal locomotion compared to previous methods. To validate the robustness and effectiveness of the method, we constructed a closed-chain quadruped robot and deployed the controller trained by the method to the robot. The experimental results in the real world suggest that the controller can enable the robot to move stably and efficiently in different gaits. The main contribution of this paper is that the authors propose a novel hierarchical framework, which makes quadruped robots use an optimal gait at a specific speed and smoothly switch to another one after getting a different speed command. These behaviors are automatically produced through simulation training, eliminating the need for the tedious work of designing gaits and modulating controllers. Experimental results showcase that the proposed method has significant advantages compared to previous methods.

Ex vivo Expansion of Bone Marrow Mesenchymal Stem Cells Using Microcarrier Beads in a Stirred Bioreactor

Lang Zhou,Jiantao Kong,Ying-ping Zhuang,Ju Chu,Si-Liang Zhang,Mei-Jin Guo 한국생물공학회 2013 Biotechnology and Bioprocess Engineering Vol.18 No.1

Bone marrow mesenchymal stem cells (bmMSCs)have recently gained attention as a useful resource in the fields of regenerative medicine and tissue engineering. However, the number of bmMSCs obtained from available donors is very low. Here we developed a culture strategy for in vitro expansion of bmMSCs in a 1.5 L stirred bioreactor with microcarrier beads. First, the microcarriers (Cytodex 3) were equilibrated in culture medium containing 3% fetal bovine serum (FBS) for at least 30 min prior to cell addition. After inoculation, the FBS concentration of the medium was maintained at 3% (v/v) in the first 24 h and thereafter maintained at 1% (v/v) and a developed feeding regimen was applied over 5 days. The maximum cell density of 2.6 × 106 cells/mL was achieved at day 5,corresponding to a 10.4 ± 0.8 fold increases in total cell number. Among the harvested cells, 98.95% expressed CD29and 84.48% expressed CD90, suggesting that the majority of expanded bmMSCs still retained their differentiation potential. Therefore, the developed microcarrier-based stirred bioreactor culture system is an effective method to generate significant numbers of bmMSCs for potential applications and research studies.

Encoding-based brain-computer interface controlled by non-motor area of rat brain.

Lang, Yiran,Du, Ping,Shin, Hyung-Cheul Jointly published by Science China Press and Sprin 2011 Science China. Life sciences Vol.54 No.9

<P>As the needs of disabled patients are increasingly recognized in society, researchers have begun to use single neuron activity to construct brain-computer interfaces (BCI), designed to facilitate the daily lives of individuals with physical disabilities. BCI systems typically allow users to control computer programs or external devices via signals produced in the motor or pre-motor areas of the brain, rather than producing actual motor movements. However, impairments in these brain areas can hinder the application of BCI. The current paper demonstrates the feasibility of a one-dimensional (1D) machine controlled by rat prefrontal cortex (PFC) neurons using an encoding method. In this novel system, rats are able to quench thirst by varying neuronal firing rate in the PFC to manipulate a water dish that can rotate in 1D. The results revealed that control commands generated by an appropriate firing frequency in rat PFC exhibited performance improvements with practice, indicated by increasing water-drinking duration and frequency. These results demonstrated that it is possible for rats to understand an encoding-based BCI system and control a 1D machine using PFC activity to obtain reward.</P>

Building blocks of amorphousGe2Sb2Te5

Lang, Christian,Song, Se Ahn,Manh, Duc Nguyen,Cockayne, David J. H. American Physical Society 2007 Physical review. B, Condensed matter and materials Vol.76 No.5

N-Step Sliding Recursion Formula of Variance and Its Implementation

Lang Yu,Gang He,Ahmad Khwaja Mutahir 한국정보처리학회 2020 Journal of information processing systems Vol.16 No.4

The degree of dispersion of a random variable can be described by the variance, which reflects the distance of the random variable from its mean. However, the time complexity of the traditional variance calculation algorithm is O(n), which results from full calculation of all samples. When the number of samples increases oron the occasion of high speed signal processing, algorithms with O(n) time complexity will cost huge amount of time and that may results in performance degradation of the whole system. A novel multistep recursive algorithm for variance calculation of the timevarying data series with O(1) time complexity (constant time) is proposed in this paper. Numerical simulation and experiments of the algorithm is presented and the results demonstrate that the proposed multistep recursive algorithm can effectively decrease computing time and hence significantly improve the variance calculation efficiency for timevarying data, which demonstrates the potential value for timeconsumption data analysis or high speed signal processing.

Characterization of Two-Dimensional Transition Metal Dichalcogenides in the Scanning Electron Microscope Using Energy Dispersive X-ray Spectrometry, Electron Backscatter Diffraction, and Atomic Force Microscopy

Lang, Christian,Hiscock, Matthew,Larsen, Kim,Moffat, Jonathan,Sundaram, Ravi Korean Society of Microscopy 2015 Applied microscopy Vol.20 No.1

Here we show how by processing energy dispersive X-ray spectrometry (EDS) data obtained using highly sensitive, new generation EDS detectors in the AZtec LayerProbe software we can obtain data of sufficiently high quality to non-destructively measure the number of layers in two-dimensional (2D) $MoS_2$ and $MoS_2/WSe_2$ and thereby enable the characterization of working devices based on 2D materials. We compare the thickness measurements with EDS to results from atomic force microscopy measurements. We also show how we can use electron backscatter diffraction (EBSD) to address fabrication challenges of 2D materials. Results from EBSD analysis of individual flakes of exfoliated $MoS_2$ obtained using the Nordlys Nano detector are shown to aid a better understanding of the exfoliation process which is still widely used to produce 2D materials for research purposes.

Diffusion tensor imaging of the C1-C3 dorsal root ganglia and greater occipital nerve for cervicogenic headache

( Lang Wang ),( Jiang Shen ),( Sushant Das ),( Hanfeng Yang ) 대한통증학회 2020 The Korean Journal of Pain Vol.33 No.3

Background: Previous studies showed neurography and tractography of the greater occipital nerve (GON). The purpose of this study was determining diffusion tensor imaging (DTI) parameters of bilateral GONs and dorsal root ganglia (DRG) in unilateral cervicogenic headache as well as the grading value of DTI for severe headache. The correlation between DTI parameters and clinical characteristics was evaluated. Methods: The fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values in bilateral GONs and cervical DRG (C2 and C3) were measured. Grading values for headache severity was calculated using a receiver operating characteristics curve. The correlation was analyzed with Pearson’s coefficient. Results: The FA values of the symptomatic side of GON and cervical DRG (C2 and C3) were significantly lower than that of the asymptomatic side (all the P < 0.001), while the ADC values were significantly higher (P = 0.003, P < 0.001, and P = 0.003, respectively). The FA value of 0.205 in C2 DRG was considered the grading parameter for headache severity with sensitivity of 0.743 and specificity of 0.999 (P < 0.001). A negative correlation and a positive correlation between the FA and ADC value of the GON and headache index (HI; r = -0.420, P = 0.037 and r = 0.531, P = 0.006, respectively) was found. Conclusions: DTI parameters in the symptomatic side of the C2 and C3 DRG and GON were significantly changed. The FA value of the C2 DRG can grade headache severity. DTI parameters of the GON significantly correlated with HI.