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Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent times, there has been a sharp increase in the congestion of ground transportation, the scarcity of land resources, and various disasters. Hence, there is an urgent need to find an effective and sustainable approach to transportation. The construction of an underground logistics network, where transportation activities occur beneath the surface of the ground, is anticipated to emerge as a future trend. This study aims to formulate a resilient-maximizing plan for the underground logistics network, ensuring optimal meeting of transportation demands in the aftermath of ground disasters. Accordingly, a two-stage linear programming model is established to determine the layout plan for the most resilient underground logistics network. The first phase of the model is designed to generate viable layouts for the underground logistics network, while the second phase is dedicated to evaluating the resilience of the proposed layout plan. During the evaluation of network resilience, Monte Carlo simulations are used to simulate disaster scenarios. Given the inherent complexity of the model, the traditional solver cannot efficiently solve the problem. Thus, a new hybrid heuristic algorithm is designed to obtain solutions that maximize network resilience. The results show the effectiveness of the designed algorithm and the significant improvement in network resilience achieved by numerical experiments. Moreover, sensitivity analyses are conducted to reveal the relationships between resilience and budget, as well as resilience and the capacity of underground pipelines. It has a significant impact on sustainability when making decisions regarding network planning. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The research on the movement law of surrounding rock under the condition of thick loose layer and thin bedrock mostly adopts theoretical research methods such as establishing a mechanical model and numerical calculation. It lacks research based on field dynamic measurement. The microseismic monitoring technology has been widely used in mine dynamic disaster monitoring and early warning in recent years. However, there are few studies on the failure law of surrounding rock under the condition of thick loose layer and thin bedrock based on microseismic monitoring technology. In view of the above problems, taking the 16001 working face of Zhaogu No. 1 Coal Mine of Coking Coal Energy Co., Ltd. as the engineering background, a high-precision microseismic monitoring system is established. The system is built by selecting the network arrangement mode of the borehole-roadway union. Based on the microseismic monitoring results, the dynamic failure law of surrounding rock in large mining height working face under the condition of thick loose layer and thin bedrock is studied. According to the accumulated released energy of surrounding rock, the energy density of the microseismic event is analyzed by adopting a nuclear density analysis method so as to achieve the purpose of studying the fracture development of the surrounding rock. The analysis results show that the maximum roof damage height is 87.8 m, and the maximum floor damage depth is 21.7 m. The maximum values all appear in the square stage of the working face, at which the roof water inrush risk is the highest. In the square stage, the roof-bearing rock beam is damaged, abnormal pressure occurs, and the damage degree of the roof, floor and advanced support is intensified. The results verify the existence of the stress breakdown effect. The sandy mudstone 48.3 m away from the roof of the working face is the key layer of the roof water barrier. The siltstone 67.7 m away from the roof is the breakdown control layer. The sandy mudstone 26.6 m away from the floor is the key layer of the floor water barrier. The results of microseismic monitoring and analysis are verified by bottom borehole peeping. The results show that the floor damage depth in the square area is more than 18 m, and the floor damage depth in other areas is 12-18 m. These results are consistent with the microseismic monitoring results.

The monitoring capability of microseismic monitoring network depends on many factors, such as network layout, velocity model, seismic phase reading error, regional anomaly of travel time, positioning algorithm, equipment running state and environmental noise. Among these factors, the network layout can be artificially optimized at present stage. In order to effectively evaluate the monitoring capacity of microseismic monitoring network and optimize the network layout, the analysis and optimization method of monitoring capacity of coal mine microseismic monitoring network is proposed. This study analyzes four factors which have the greatest and most direct influence on the monitoring capability of the microseismic monitoring network. The four factors are the number of effective waveforms, the maximum gap angle, the near-station epicenter distance and the height difference between stations. It is pointed out that the number of effective waveforms, the near-station epicenter distance and the height difference between stations play a decisive role in the error of hypocenter depth solution. The number of effective waveforms and the maximum gap angle play a decisive role in the precision of epicenter positioning. According to the situation of the existing network and the working face, the distribution cloud pictures of the four factors are obtained. The monitoring capability of the microseismic network is evaluated item by item through the distribution cloud pictures of the four factors. The new network arrangement scheme is obtained through optimization of the evaluation result. The positioning error and sensitivity of the new scheme are analyzed. The epicenter positioning error, hypocenter positioning error and regional sensitivity of the whole mine are obtained. The second evaluation of the new scheme is carried out. If the secondary evaluation results meet the requirements, the new scheme can be regarded as the best network layout scheme. If the secondary evaluation results do not meet the requirements, the four factors sub item evaluation will be carried out again and the scheme will be optimized until the requirements are met. The field test results show that after the proposed method is used to optimize the microseismic monitoring network of 5307 working face in Tangkou Coal Mine, the average value of blasting hypocenter positioning error is reduced from 59.2 m to 37.2 m. The maximum value of positioning error is reduced to less than 100 m, and the blasting events with error less than 50 m account for 69.0% of the total. The results show that the proposed method can effectively improve the microseismic positioning precision and optimize the monitoring capability of the network.

Green electricity hydrogen production(GEHP) is fundamental support for developing new-type power system (NPS) and achieving the green and low-carbon transformation in the transportation sector. It is key issue to build a hydrogen refueling facility network(HRFN) to link hydrogen production and consumption. Firstly, the framework of HRFN is proposed including hydrogen production points(HPP), hydrogen refueling stations(HRS) and hydrogen demand points(HDP). Secondly, a two-stage model is built. In the first stage, the siting model of HRS cluster is constructed considering the service capacity, service radius, and construction, operation and penalty costs. In the second stage, the bi-objective planning model of HRFN is constructed considering network stability, hydrogen storage and transportation forms and producing total costs. Finally, the Beijing-Tianjin-Hebei region of China(BTH) is taken as case study to verify the effectiveness. Sensitivity analyses are conducted on four factors:HRSs' service radius, service capacity, GEHP's efficiency and HDPs' scope. The key findings are: 1)the service radius and capacity of HRSs and HDPs' scope all affect the layout of HRSs, with HDPs' scope further influencing HPPs' number; 2)the construction and operation costs are more impacted by changes in GEHP's efficiency compared to network stability; 3)the network should be strengthened to cover the whole processes from hydrogen production to consumption. [ABSTRACT FROM AUTHOR]

In the context of rural revitalization, the needs of rural residents' travel and the theoretical construction of rural road network layout are extremely important. In order to improve the efficiency of rural road network, an algorithm based on topology theory was designed. The method is considered through the topology of the radial network and calculated with the characteristics of urban and rural traffic. According to the feature results, the target weight of the importance index of the traffic node was calculated by the gray correlation analysis method. Combined with the dynamic clustering results of traffic nodes, a rural road layout planning model was constructed, and this model was solved with the travel time as the goal to complete the design of this algorithm. The results show that on the basis of improving the efficiency, this algorithm can effectively improve the equilibrium and connectivity of urban and rural road distribution, compared with the traditional spline method and GIS-TransCAD method. [ABSTRACT FROM AUTHOR]

In recent times, there has been a sharp increase in the congestion of ground transportation, the scarcity of land resources, and various disasters. Hence, there is an urgent need to find an effective and sustainable approach to transportation. The construction of an underground logistics network, where transportation activities occur beneath the surface of the ground, is anticipated to emerge as a future trend. This study aims to formulate a resilient-maximizing plan for the underground logistics network, ensuring optimal meeting of transportation demands in the aftermath of ground disasters. Accordingly, a two-stage linear programming model is established to determine the layout plan for the most resilient underground logistics network. The first phase of the model is designed to generate viable layouts for the underground logistics network, while the second phase is dedicated to evaluating the resilience of the proposed layout plan. During the evaluation of network resilience, Monte Carlo simulations are used to simulate disaster scenarios. Given the inherent complexity of the model, the traditional solver cannot efficiently solve the problem. Thus, a new hybrid heuristic algorithm is designed to obtain solutions that maximize network resilience. The results show the effectiveness of the designed algorithm and the significant improvement in network resilience achieved by numerical experiments. Moreover, sensitivity analyses are conducted to reveal the relationships between resilience and budget, as well as resilience and the capacity of underground pipelines. It has a significant impact on sustainability when making decisions regarding network planning.

Copyright of Railway Standard Design is the property of Railway Standard Design Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The layout of microseismic monitoring (MSM) station networks is very important to ensure the effectiveness of source location inversion; however, it is difficult to meet the complexity and mobility requirements of the technology in this new era. This paper proposes a network optimization method based on the geometric parameters of the proposed sensor-point database. First, according to the monitoring requirements and mine-working conditions, the overall proposed point database and model are built. Second, through the developed model, the proposed coverage area, envelope volume, effective coverage radius, and minimum energy level induction value are comprehensively calculated, and the evaluation reference index is constructed. Third, the effective maximum envelope volume is determined by taking the analyzed limit of monitoring induction energy level as the limit. Finally, the optimal design method is identified and applied to provide a sensor station layout network with the maximum energy efficiency. The method, defined as the S-V-E-R-V model, is verified by a comparison with the existing layout scheme and numerical simulation. The results show that the optimization method has strong practicability and efficiency, compared with the mine's layout following the current method. Simulation experiments show that the optimization effect of this method meets the mine's engineering requirements for the variability, intelligence, and high efficiency of the microseismic monitoring station network layout, and satisfies the needs of event identification and location dependent on the station network. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bicycle use is an important measure to promote energy saving in the urban transportation field and reduce the environmental deterioration caused by motorized vehicle development in both warm- and cold-climate cities. However, the severe winter climate makes it harder to set up bicycle lanes in cold-climate cities than in other cities. Considering international and Chinese practice, this article analyzes bicycle travel characteristics in cold-climate cities, summarizes bicycle development patterns and proposes corresponding development strategies. The paper reviews the research status of cycling network planning and design in cold-climate cities in China and worldwide and summarizes the relevant methods that can be used in China. The results showed that compared with other seasons, in winter, the bicycle share rate of Chinese cold-climate cities decreases significantly, and the larger the temperature difference is, the greater the decrease is. In addition, the bicycle traffic flow is volatile and does not strictly maintain a regular straight line. It is necessary to select bicycle traffic development patterns and formulate corresponding strategies according to bicycle travel characteristics. Temperature and wind are two climatic factors that need special attention when planning cycling networks in cold-climate cities. The consideration of solar radiation and electric bicycles is beneficial for optimizing the design of bicycle lane width in cold-climate cities. Isolation forms can be selected according to the bicycle development patterns. The pavement materials, maintenance technology and colored bicycle lanes with anti-freezing function are very important to improve the comfort and safety of bicycle lanes.

A reasonable regional integrated energy system (RIES) structure is the key to achieving its economic and efficient operation. However, in actual engineering construction, only the maximum load is considered as a prerequisite for energy design, which leads to waste of energy allocation. In view of this, this article proposes an electricity-thermal-cooling RIES energy stations and networks planning model that coordinates the operation of multiple-user loads, energy networks, and energy stations based on the idea of load clustering. Firstly, an average peak valley difference rate covering electricity, thermal, and cooling loads was proposed to evaluate the load characteristics of the RIES. Secondly, based on the load cluster characteristics and network costs of RIES, a RIES planning optimization framework is proposed, which includes load cluster division, RIES site selection and network planning, and RIES capacity planning. Thirdly, based on the P-median model and load cluster characteristics, establish an RIES location and network layout model. Fourthly, establish an RIES capacity planning model with the goal of annual total cost and carbon emissions. Finally, Dijkstra, improved particle swarm optimization, and VIKOR were used to solve the model. The results showed that the proposed model reduced the annual total cost by 7.13 % and the annual carbon emissions by 3.72 %. • Establish an average load peak valley difference index. • Establish a RIES planning framework includes network layout and capacity planning. • Establish an IES planning model with the goal of cost and carbon emissions. • Total annual cost decreased by 7.13 % and CO 2 emissions decreased by 2.77 %. [ABSTRACT FROM AUTHOR]

When wireless sensor networks (WSN) are deployed in the vegetable greenhouse with dynamic connectivity and interference environment, it is necessary to increase the node transmit power to ensure the communication quality, which leads to serious network interference. To offset the negative impact, the transmit power of other nodes must also be increased. The result is that the network becomes worse and worse, and node energy is wasted a lot. Taking into account the irregular connection range in the cucumber greenhouse WSN, we measured the transmission characteristics of wireless signals under the 2.4 Ghz operating frequency. For improving network layout in the greenhouse, a semiempirical prediction model of signal loss is then studied based on the measured data. Compared with other models, the average relative error of this semi-empirical signal loss model is only 2.3%. Finally, by combining the improved network topology algorithm and tabu search, this paper studies a greenhouse WSN layout that can reduce path loss, save energy, and ensure communication quality. Given the limitation of node-degree constraint in traditional network layout algorithms, the improved algorithm applies the forwarding constraint to balance network energy consumption and constructs asymmetric network communication links. Experimental results show that this research can realize the energy consumption optimization of WSN layout in the greenhouse. [ABSTRACT FROM AUTHOR]

The understanding of complex biological networks often relies on both a dedicated layout and a topology. Currently, there are three major competing layout-aware systems biology formats, but there are no software tools or software libraries supporting all of them. This complicates the management of molecular network layouts and hinders their reuse and extension. In this paper, we present a high-level overview of the layout formats in systems biology, focusing on their commonalities and differences, review their support in existing software tools, libraries and repositories and finally introduce a new conversion module within the MINERVA platform. The module is available via a REST API and offers, besides the ability to convert between layout-aware systems biology formats, the possibility to export layouts into several graphical formats. The module enables conversion of very large networks with thousands of elements, such as disease maps or metabolic reconstructions, rendering it widely applicable in systems biology. [ABSTRACT FROM AUTHOR]

Identification of genes/proteins involved in pluripotency and their inter-relationships is important for understanding the induction/loss and maintenance of pluripotency. With the availability of large volume of data on interaction/regulation of pluripotency scattered across a large number of biological databases and hundreds of scientific journals, it is required a systematic integration of data which will create a complete view of pluripotency network. Describing and interpreting such a network of interaction and regulation (i.e., stimulation and inhibition) links are essential tasks of computational biology, an important first step in systems-level understanding of the underlying mechanisms of pluripotency. To address this, we have assembled a network of 166 molecular interactions, stimulations and inhibitions, based on a collection of research data from 147 publications, involving 122 human genes/proteins, all in a standard electronic format, enabling analyses by readily available software such as Cytoscape and its Apps (formerly called "Plugins"). The network includes the core circuit of OCT4 (POU5F1), SOX2 and NANOG, its periphery (such as STAT3, KLF4, UTF1, ZIC3, and c-MYC), connections to upstream signaling pathways (such as ACTIVIN, WNT, FGF, and BMP), and epigenetic regulators (such as L1TD1, LSD1 and PRC2). We describe the general properties of the network and compare it with other literature-based networks. Gene Ontology (GO) analysis is being performed to find out the over-represented GO terms in the network. We use several expression datasets to condense the network to a set of network links that identify the key players (genes/proteins) and the pathways involved in transition from one state of pluripotency to other state (i.e., native to primed state, primed to non-pluripotent state and pluripotent to non-pluripotent state).

Copyright of Studia Poliana is the property of Studia Poliana and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We undertake a sturdy body seismogenic model study along the northern margin of the West Qinling fault zone, China, to address some existing problems of neglecting scientific layout based on certain prediction theory and observation facts surrounding underground fluid monitoring networks across faults. A combination of high-density underground fluid measurements and vertical crustal deformation and seismological observations were used to elucidate the interplay between fluid dynamics, crustal deformation, and seismic activity and to comprehensively analyze the fault segment characteristics along the fault zone. We found correspondence between these parameters along the northern margin of the West Qinling fault zone. All parameters showed higher values in the Wu Shan (WS) segment than in the western Xia He–Huang Xiang Gou–Zhang Xian (XH-HXG-ZX) segment and eastern Tian Shui (TS) area. The 222Rn concentration reached 5.0942 at BZC, and the Hg concentration reached 3.4398 at LJG in WS. Similarly, the vertical crustal deformation and seismic activity in this area were both stronger than those in the western XH–HXG–ZX and TS area. Based on the sturdy body seismogenic model, we found that the ZX and TS segments exhibited weaker activity than the surrounding areas and may be in a deep locked state under the corresponding regional stress. Compared with existing monitoring network for background value detection and comprehensive research results, we propose a technical underground flow monitoring network prototype that includes two grade I and five grade II survey sites along the northern margin of the West Qinling fault zone based on the sturdy body seismogenic model. This prototype will provide a more reliable basis for earthquake prediction, tracking and mitigation, and disaster risk reduction. The presented scheme can be used as a guideline for deploying fault soil gas monitoring networks in China. • Seismogenic model validates soil gas monitoring network layout along a fault zone. • Soil gas observations effectively delineate inferred earthquake mechanisms. • Soil gas monitoring network can potentially capture evolution of a fault zone. [ABSTRACT FROM AUTHOR]

In network system design, it becomes more difficult to find the best network layout due to rapidly enhanced complexity. Because edges are costly and the budget is limited, the number of edges to connect target nodes is restricted to a narrow range, with the number of target nodes is given. Considering such a network system design problem that the number of nodes is given and the number of edges is fixed to a certain value, this paper identifies the best network layout based on factoring theory. We firstly enumerate all network layouts based on the concept of neighboring circle, secondly propose three propositions to logically classify these network layouts into different types, and finally compare the reliabilities of all types via factoring to identify the best network layout, which possesses the greatest reliability. Our best network layout identification approach is applicable to the reliability-constrained cost minimization problem and is expected to be very conducive to the efficiency improvement of the optimization problem. [ABSTRACT FROM AUTHOR]

In a looped water distribution network (WDN) alternate paths are available for supply in case a pipe fails and isolated from the network. The provision of minimum size or minimum flow carrying capacity of each pipe in a least-cost design of WDNs, or deciding layout of a looped WDN such that at least two-pipes are connected at each node may assure connectivity but not sufficient capacity of the network to meet demands during failure of any pipe. Reliability of looped network increases with increase in number of pipes at each node, or increase in pipe sizes; however, the cost also increases. Thus, reliability-based design should consider both layout and pipe sizes optimization. Methodologies based on entropy have been suggested for selection of layout and design to consider reliability [1,2] . A new methodology, based on flow uniformity in the network, is attempted for the selection of network layout. The flow-uniformity is assessed through variance of flow-series. It is observed that in a branched network, the variance of pipe-flows is maximum; and the reliability of the network increases as the variance decreases by adding loop-forming links. A heuristic methodology is suggested to obtain a layout with minimum variance. The layout so selected is optimally designed using linear programming. The methodology is applied to a simple problem and cost and reliability values are compared. Further, a network from the literature [3] is considered. The reliability consideration is observed to have a layout with more number of pipes as compared to that obtained for minimum cost design. [ABSTRACT FROM AUTHOR]

Distributed and decentralised energy systems coupled with district heating networks are promising concepts for achieving less carbon-intensive urban energy systems. This paper investigates the optimal design and operation of distributed energy systems as well as optimal heating network layouts for different economic and environmental objectives. A mixed integer linear programming model was used for multi-objective optimisation to minimize total cost and carbon emissions. Improvements include the coupling of equipment and network modelling across many buildings, detailed CHP operational constraints, the inclusion of network heat losses, and improved modelling of thermal storage. The model was used on a case study consisting of eleven residential buildings and one commercial building for various design scenarios (available technologies, network layout limitations, operating constraints). Design results (capacities, network layouts) and operational results (energy supply breakdowns) are presented. The results show that district heating can deliver emissions savings of 23% over a standard solution for the same cost. The optimal number of heating network links increases as more stringent carbon emissions targets are implemented. Limits on possible network routes have significant impacts on the optimal technology capacities and on operational schedules. Also, commonly neglected constraints on CHP operation cause noticeably more reliance on district heating networks. [ABSTRACT FROM AUTHOR]

Connectivity and layout of underlying networks largely determine agent behavior and usage in many environments. For example, transportation networks determine the flow of traffic in a neighborhood, whereas building floorplans determine the flow of people in a workspace. Designing such networks from scratch is challenging as even local network changes can have large global effects. We investigate how to computationally create networks starting from only high-level functional specifications. Such specifications can be in the form of network density, travel time versus network length, traffic type, destination location, etc. We propose an integer programming-based approach that guarantees that the resultant networks are valid by fulfilling all the specified hard constraints and that they score favorably in terms of the objective function. We evaluate our algorithm in two different design settings, street layout and floorplans to demonstrate that diverse networks can emerge purely from high-level functional specifications. [ABSTRACT FROM AUTHOR]

Tanks have always played a crucial role in urban water distribution systems. With well known advantages (as to guarantee reserves for emergencies) they are widely used. But they present, as well, inconveniences such as their contribution to a higher water age and are, as will be seen, energy-hungry. This paper introduces an indicator to assess energy savings of direct water supply (without head tanks) with regard to the traditional indirect one (throughout head tanks). Furthermore a case study is presented showing the reliability of this indicator. The paper concludes with an economic comparison of both strategies. [ABSTRACT FROM AUTHOR]