IEEE 802.20 Based Broadband Railroad Digital Network – The Infrastructure for M-Commerce on the Train

The broadband wireless access is emerging as a promising technology to meet the ever-increasing demand of M-commerce on the train. The traditional railroad communication system (RCS) is not only in charge of the traditional train scheduling, but also offers broadband WLAN services to passengers and provides the network platform to the intelligent railroad information system. This imposes a major challenge on the capability of the RCS in response to the increasing application requirements, particularly, the one for ubiquitous Internet access. To take the advantage of the rapid evolving mobile communication technology, this paper proposes an IEEE 802.20 based broadband railroad digital network, namely BRDN, for the next generation RCS. The paper further presents the scenario how BRDN operates and identifies the IP mobility as the major technical issue to be solved for BRDN. The predictability of mobile IP for the train-based applications will ease the difficulties in implementing BRDN. With the availability of IP standard for the next generation Internet - IPv6, BRDN will eventually become a reality

Eagle-YOLO : An Eagle-Inspired YOLO for Object Detection in Unmanned Aerial Vehicles Scenarios

Funding Information: This research was funded by National Natural Science Foundation of China OF FUNDER grant number 41471333, 61304199. This research was funded by Fujian Provincial Department of Science and Technology OF FUNDER grant number 2021Y4019, 2020D002, 2020L3014, 2019I0019. This research was funded by Fujian University of Technology OF FUNDER grant number KF-J21012. This research was funded by Shenzhen Science and Technology Innovation Program OF FUNDER grant number JCYJ20220530160408019. This research was funded by Basic and Applied Basic Research Foundation of Guangdong Province OF FUNDER grant number 2023A1515011915. This research was funded by the Key Research and Development Project of Hunan Province of China OF FUNDER grant number 2022GK2020. This research was funded by Hunan Natural Science Foundation of China OF FUNDER grant number 2022JJ30171. Publisher Copyright: © 2023 by the authors.Peer reviewedPublisher PD

A Multi-Sensory Stimulating Attention Model for Cities’ Taxi Service Demand Prediction

Taxi demand forecasting is crucial to building an efficient transportation system in a smart city. Accurate taxi demand forecasting could help the taxi management platform to allocate taxi resources in advance, alleviate traffic congestion, and reduce passenger waiting time. Thus, more efforts in industrial and academic circles have been directed towards the cities’ taxi service demand prediction (CTSDP). However, the complex nonlinear spatio-temporal relationship in demand data makes it challenging to construct an accurate forecasting model. There remain challenges in perceiving the micro spatial characteristics and the macro periodicity characteristics from cities’ taxi service demand data. What’s more, the existing methods are significantly insufficient for exploring the potential multi-time patterns from these demand data. To meet the above challenges, and also stimulated by the human perception mechanism, we propose a Multi-Sensory Stimulus Attention (MSSA) model for CTSDP. Specifically, the MSSA model integrates a detail perception attention and a stimulus variety attention for capturing the micro and macro characteristics from massive historical demand data, respectively. The multiple time resolution modules are employed to capture multiple potential spatio-temporal periodic features from massive historical demand data. Extensive experiments on the yellow taxi trip records data in Manhattan show that the MSSA model outperforms the state-of-the-art baselines

Lineage diversification and historical demography of a montane bird Garrulax elliotii - implications for the Pleistocene evolutionary history of the eastern Himalayas

<p>Abstract</p> <p>Background</p> <p>Pleistocene climate fluctuations have shaped the patterns of genetic diversity observed in many extant species. In montane habitats, species' ranges may have expanded and contracted along an altitudinal gradient in response to environmental fluctuations leading to alternating periods of genetic isolation and connectivity. Because species' responses to climate change are influenced by interactions between species-specific characteristics and local topography, diversification pattern differs between species and locations. The eastern Himalayas is one of the world's most prominent mountain ranges. Its complex topography and environmental heterogeneity present an ideal system in which to study how climatic changes during Pleistocene have influenced species distributions, genetic diversification, and demography. The Elliot's laughing thrush (<it>Garrulax elliotii</it>) is largely restricted to high-elevation shrublands in eastern Himalayas. We used mitochondrial DNA and microsatellites to investigate how genetic diversity in this species was affected by Pleistocene glaciations.</p> <p>Results</p> <p>Mitochondrial data detected two partially sympatric north-eastern and southern lineages. Microsatellite data, however, identified three distinct lineages congruent with the geographically separated southern, northern and eastern eco-subregions of the eastern Himalayas. Geographic breaks occur in steep mountains and deep valleys of the Kangding-Muli-Baoxin Divide. Divergence time estimates and coalescent simulations indicate that lineage diversification occurred on two different geographic and temporal scales; recent divergence, associated with geographic isolation into individual subregions, and historical divergence, associated with displacement into multiple refugia. Despite long-term isolation, genetic admixture among these subregional populations was observed, indicating historic periods of connectivity. The demographic history of <it>Garrulax elliotii </it>shows continuous population growth since late Pleistocene (about 0.125 mya).</p> <p>Conclusion</p> <p>While altitude-associated isolation is typical of many species in other montane regions, our results suggest that eco-subregions in the eastern Himalayas exhibiting island-like characteristics appear to have determined the diversification of <it>Garrulax elliotii</it>. During the Pleistocene, these populations became isolated on subregions during interglacial periods but were connected when these expanded to low altitude during cooler periods. The resultant genetic admixture of lineages might obscure pattern of genetic variation. Our results provide new insights into sky island diversification in a previously unstudied region, and further demonstrate that Pleistocene climatic changes can have profound effects on lineage diversification and demography in montane species.</p

Expressway Speed Prediction Based on Electronic Toll Collection Data

Expressway section speed can visually reflect the section operation condition, and accurate short time section speed prediction has a wide range of applications in path planning and traffic guidance. However, existing expressway speed prediction data have defects, such as sparse density and incomplete object challenges. Thus, this paper proposes a framework for a combined expressway traffic speed prediction model based on wavelet transform and spatial-temporal graph convolutional network (WSTGCN) of the Electronic Toll Collection (ETC) gantry transaction data. First, the framework pre-processes the ETC gantry transaction data to construct the section speeds. Then wavelet decomposition and single-branch reconstruction are performed on the section speed sequences, and the spatial features are captured by graph convolutional network (GCN) for each reconstructed single-branch sequence, and the temporal features are extracted by connecting the gated recurrent unit (GRU). The experiments use the ETC gantry transaction data of the expressway from Quanzhou to Xiamen. The results indicate that the WSTGCN model makes notable improvements compared to the model of the baseline for different prediction ranges

Vectorial Acylation in \u3ci\u3eSaccharomyces cerevisiae\u3c/i\u3e

In Saccharomyces cerevisiae Fat1p and fatty acyl-CoA synthetase (FACS) are hypothesized to couple import and activation of exogenous fatty acids by a process called vectorial acylation. Molecular genetic and biochemical studies were used to define further the functional and physical interactions between these proteins. Multicopy extragenic suppressors were selected in strains carrying deletions in FAA1 and FAA4 or FAA1 and FAT1. Each strain is unable to grow under synthetic lethal conditions when exogenous long-chain fatty acids are required, and neither strain accumulates the fluorescent long-chain fatty acid C1-BODIPY-C12 indicating a fatty acid transport defect. By using these phenotypes as selective screens, plasmids were identified encoding FAA1, FAT1, and FAA4 in the faa1Δ faa4Δ strain and encoding FAA1 and FAT1 in the faa1Δ fat1Δ strain. Multicopy FAA4 could not suppress the growth defect in the faa1Δ fat1Δ strain indicating some essential functions of Fat1p cannot be performed by Faa4p. Chromosomally encoded FAA1 and FAT1 are not able to suppress the growth deficiencies of the fat1Δ faa1Δ and faa1Δ faa4Δ strains, respectively, indicating Faa1p and Fat1p play distinct roles in the fatty acid import process. When expressed from a 2μ plasmid, Fat1p contributes significant oleoyl-CoA synthetase activity, which indicates vectorial esterification and metabolic trapping are the driving forces behind import. Evidence of a physical interaction between Fat1p and FACS was provided using three independent biochemical approaches. First, a C-terminal peptide of Fat1p deficient in fatty acid transport exerted a dominant negative effect against long-chain acyl-CoA synthetase activity. Second, protein fusions employing Faa1p as bait and portions of Fat1p as trap were active when tested using the yeast two-hybrid system. Third, co-expressed, differentially tagged Fat1p and Faa1p or Faa4p were co-immunoprecipitated. Collectively, these data support the hypothesis that fatty acid import by vectorial acylation in yeast requires a multiprotein complex, which consists of Fat1p and Faa1p or Faa4p

A Framework for Travel Speed Prediction Inclusive of Service Area Dwell Times

Accurate modeling of travel speeds is crucial for optimizing roadway management, yet traditional methods overlook a key factor the influence of vehicle dwell times in service areas. This oversight introduces bias into speed measurements, impairing their utility for fine-grained traffic monitoring. To address this problem, we propose an innovative framework that integrates machine learning prediction of service area dwell times into travel speed calculation. We focus on a 9.3 km segment of a major highway in Fujian Province, China that includes the Qingyunshan service area. A Gradient Boosting Decision Tree model identifies vehicles entering the service area, while a Bayesian Backpropagation Neural Network predicts their dwell time. By adjusting the overall travel times using these predicted dwell times, our approach recovers normal driving behavior outside service areas. Experiments on electronic toll collection data from over 17 million transactions validate the framework&#x2019;s effectiveness. The corrected travel speeds better reflect typical highway conditions and enable more precise assessment of traffic state across multiple time horizons. This study highlights the vital role of service area dwell time in travel speed modeling. Our solution provides a promising direction to enhance the fidelity of current prediction practices

The application of mineral casting in high-precision printed circuit board drilling machine

Purpose – The purpose of this paper is to verify the feasibility and reliability of mineral casting applied in high-precision printed circuit board (PCB) drilling machine. The mechanical properties of machine frame are quantified to provide a solution for machine tool industry to seek a perfect substance competing with classic materials such as cast iron and granite. Design/methodology/approach – The optimal design of machine frame is performed via the CAD system combined with finite element analysis (FEA). The mechanical properties of the frame elements are evaluated by a series of mechanical experiments: static performance is quantified by flatness tests, dynamic behavior is estimated by experimental and numerical models, respectively. Meanwhile, the performance of the frame element with traditional materials is examined experimentally. Findings – Mineral casting parts can be successfully applied to PCB drilling machine to meet high accuracy requirements. The characteristic of mineral casing gives the most possibilities in structural design. The frame parts show good static/dynamic behaviors by structural optimization processes. Especially, the machine frame with mineral casting gains a great weight reduction compared with traditional materials. Originality/value – The application of mineral casting in PCB drilling machine offers greater design flexibility and innovative system solutions. The combination of FEA is convincing to achieve optimal structure and ideal weight to maximize the economic and technical benefits. Moreover, lightweight design of machine structural components achieves not only higher kinematic/dynamic precision but also considerable cost reduction