Open Path Research Articles

Facile synthesis and efficient electrochemical water splitting of bifunctional nanostructured Ni-based layered double hydroxide/sulfide composite

The development of efficient, stable and low-cost bifunctional electrocatalyst for water splitting is of great practical significance for the industrial application of hydrogen production. In this paper, a well-aligned columnar nickel sulfide and NiAl layered double hydroxides composite (NiAl-LDH/Ni3S2) supported on Ni-foam substrate was successfully designed and prepared by successive hydrothermal processes. Ni3S2 nanorod arrays attached to Ni-foam could provide large open space and short ions diffusion path, and NiAl-LDH provides large contact area with electrolyte, thus enabling fast and reversible redox process, which together could promote electrocatalytic activity. Accordingly, the NiAl-LDH/Ni3S2/NF electrode shows excellent HER and OER performance, in which the low overpotentials of 53.6, 90.2 and 209.2 mV are needed to drive the current density of 10, 20 and 100 mA/cm2 for HER, and similarly for OER, it needs 350.4 mV low overvoltage to reach 100 mA/cm2. In the self-assembled device, the overall water splitting reaction can be driven at a cell voltage of 1.56 V when NiAl-LDH/Ni3S2/NF electrode used as cathode and anode, to achieve the current density of 10 mA/cm2, and the loss voltage is only 16.5 mV within 10 h, showing the excellent stability. The well-constructed NiAl-LDH/Ni3S2/NF is a promising material in the area of electrocatalytic water splitting, which is of practical significance to realize the industrial development of hydrogen production.

Design and Implementation of Semi-Physical Platform for Label Based Frame Switching in Integrated Satellite Terrestrial Networks

With the explosion of traffic demand in recent years, the integration of satellite optical networks and terrestrial networks (ISTN) creates a promising networking solution for future low-latency, high-rate, and high-capacity communications. Owing to the high cost of deploying and maintaining a satellite optical network, it is critical to carefully design and plan the network to ensure the performance of the network. Thus, a semi-physical simulation platform based on software-defined networks (SDNs) is developed to simulate a satellite optical network and evaluate the performance of the proposed label-based advanced orbiting system (AOS) frame switching method that adheres to the Consultative Committee for Space Data Systems’ recommended standard (CCSDS). The semi-physical simulation platform has two major innovations: (1) adapting and integrating network protocols between the CCSDS and open system interconnect (OSI) reference models, particularly at the data link layer, and (2) the foundation for an SDN-based satellite optical network. In the control plane, real-time VxWorks Simulators serve as controllers to establish and manage various network protocols and the link manager protocol (LMP). Here, network protocols include open shortest path first (OSPF) for routing managing and controlling messages, constraint shortest path first–traffic engineering (CSPF-TE), and constraint-label distribution protocol (CR-LDP) for routing data services. LMP is used to assign and reserve satellite optical link resources. The performance of the architecture and protocols is evaluated via a semi-physical simulation platform.

THE SPECTRUM LENGTH METHOD IN QUANTITATIVE INTERPRETATION OF SELECTED OPTICAL SPECTRA

Different algorithms are used for the quantitative interpretation of optical spectra. Regression methods e.g CLS (Classical Least Squares) or PLS (Partial Least Squares) are often used in typical problems of laboratory spectroscopy. The spectra analysis is generally a multi-step process, in which, depending on the spectra type, modification of individual regression methods or special dedicated methods are applied. For example, contour length method or spectra length algorithm are used in this purpose. The basic version of the algorithm is very simple in terms of mathematics. It has been proposed for the analysis of spectra in the OP-FTIR open path spectroscopy, where there are significant fluctuations in the spectrum baseline. The spectrum length is a parameter closely related to the content of the analyzed gas component. Independently of spectral length algorithm, a method has been developed in which difference length of two spectra (measured and reference) is used to compare the spectra. The minimum length of the spectral difference is an indicator of their best fitting. The article presents two ways of using the spectrum length: as a direct and indirect parameter indicating the measured quantity on the basis of the spectrum. There were performed the spectrum length algorithm as a digital differentiating filter with a specific frequency response. There were also analyzed more advanced differentiating filter and the possibility of frequency spectrum filter design used in an analysis of optical spectral signal. There were performed the analysis of the spectrum length method in the case of the synthetic calibration involving the use of model spectra from simulations realized by HITRAN database. There were analyzed numerically the problem of the Instrument Line Shape influence on the synthetic spectra and results of the determining the content of components by the minimizing the difference of spectral length.

Elimination of Scintillation Noise Caused by External Environment Disturbances in Open Space

External environment disturbances in open space cause scintillation noise in tunable diode laser absorption spectroscopy (TDLAS), which is used to detect the concentration of gases in air. However, most gases analyzed by TDLAS are present in trace amounts in air. Thus, useful information is typically submerged in strong noise, thereby reducing the detection accuracy. Herein, a method is proposed to eliminate the scintillation noise caused by external environment disturbances in open space. First, the submerged signal is detected via fast coarse-tuning filtering. Then, scintillation noise is eliminated through the extraction and reconstruction of the main feature information. Thereafter, the background signal is obtained by unequal precision. Furthermore, adaptive iterative fitting is performed. Finally, an experimental setup is established for atmospheric detection in an open optical path. The experimental results show that the COD and RSS fitted using the traditional method are 0.87859 and 1.5772 × 10−5, respectively, and those fitted using the proposed method are 0.91448 and 8.81639 × 10−6, respectively. The field results imply that the proposed method has improved accuracy for detecting trace gases in open space and can be employed for practical engineering applications.

A novel graph theory based two-stage minimum cost routing mechanism in energy internet

Energy internet is a multi-energy system with “source-network-load-storage” coordinated and optimized operation, and the research on the routing mechanism of its core equipment called electric energy router (EER) is a significant aspect of the energy optimization in the energy internet. In this paper, the existing EERs routing mechanisms are improved in terms of optimization objectives, congestion management, and heavy load power supply. Firstly, the structure and function of the EER are described from the perspective of the network, and the topology of the energy internet is designed based on graph theory. Secondly, in combination with the concept of virtual circuit transmission, open shortest path first routing algorithm, policy-based routing, and routing policy in information internet, a two-stage routing mechanism of day-ahead peer-to-peer transaction and intraday power balance is proposed. Furthermore, a minimum cost routing selection algorithm with the cost weight coefficients is also proposed to support the studied mechanism. Besides, an equal-cost incremental principle is proposed to optimize transmission congestion management and heavy load power supply, which can realize the lowest cost transmission through the least path. Finally, the routing mechanism is verified by case analyses which prove the relevance of the proposed method.

Measurement Duration but Not Distance, Angle, and Neighbour-Proximity Affects Precision in Enteric Methane Emissions when Using the Laser Methane Detector Technique in Lactating Dairy Cows.

Simple SummaryMethane that is breathed out and eructed from ruminants is a potent greenhouse gas that contributes to climate change. Although metabolic chambers are the “gold standard” for measuring methane from livestock, their application in production farms is very limited. There is a need to develop proxy methods that can be applied in such production environments. The proprietary Laser Methane Detector (LMD) has been trialed for the previous decade and has demonstrated its usefulness as a non-invasive and portable instrument to determine methane output from ruminants. In validating the reliability and stability of the data generated by the LMD, the current study gives answers to some very practical assumptions used in the use of the LMD and enhances the confidence in its use in ruminants.The laser methane detector (LMD), is a proprietary hand-held open path laser measuring device. Its measurements are based on infrared absorption spectroscopy using a semiconductor laser as a collimated excitation source. In the current study, LMD measurements were carried out in two experiments using 20 and 71 lactating dairy cows in Spain and Scotland, respectively. The study aimed at testing four assumptions that may impact on the reliability and repeatability of the LMD measurements of ruminants. The study has verified that there is no difference in enteric methane measurements taken from a distance of 3 m than from those taken at a distance of 2 m; there was no effect to the measurements when the measurement angle was adjusted from 90° to 45°; that the presence of an adjacent animal had no effect on the methane measurements; and that measurements lasting up to 240 s are more precise than those taken for a shorter duration. The results indicate that angle, proximity to other animals, and distance had no effects and that measurements need to last a minimum of 240 s to maintain precision.

Ppm-level oxygen detection system based on deep-ultraviolet-absorption spectroscopy.

Oxygen is a gas essential to human life and industrial processes. Here, we developed a highly sensitive oxygen gas sensor based on deep ultraviolet absorption spectroscopy between 180 and 200 nm. The implemented method relies on differential absorption spectra extracted from the obtained high-resolution absorption spectra. The detection capability was greatly improved (six-fold) by eliminating air from the open optical path, achieved by purging the entire system with pure nitrogen. A linear relationship was obtained between the optical parameter and the oxygen concentration with a slope of 0.107 and determination coefficient of 0.999. A detection limit of 24 ppm per meter was determined with a response time of 25 s. Good repeatability (standarddeviation=16ppm) and stability were confirmed. We demonstrated that this system can detect ppm oxygen levels with high sensitivity and low uncertainty.

Active knowledge graph completion

Enterprise and public Knowledge Graphs (KGs) are known to be incomplete. Methods for automatic completion, sometimes by rule learning, scale well. While previous rule-based methods learn closed (non-existential) rules, we introduce Open Path (OP) rules that are constrained existential rules. We present a novel algorithm, OPRL, for learning OP rules.Closed rules complete a KG by answering queries of unclear origin, usually derived from a holdback test set in experimental settings. However, OP rules can generate relevant queries for KG completion. OPRL generates queries even when there is no closed rule to answer the query, or when the correct answer is a missing entity that is not present in the KG.For OPRL to scale well, we propose a novel embedding-based fitness function to efficiently estimate rule quality. Additionally, we introduce a novel, efficient vector computation to formally assess rule quality.We evaluate OPRL using adaptations of Freebase, YAGO2, Wikidata, and a synthetic Poker KG. We find that OPRL mines hundreds of accurate rules from massive KGs with up to 8 M facts. The OP rules generate queries with precision as high as 98% and recall of 62% on a complete KG, demonstrating the first solution for active knowledge graph completion.

Comparative Analysis of Dynamic Routing Protocol with Dynamic B/W using Cisco Packet Tracer 8.0

In this digital world, the transmission of data from source to destination is based on some routing protocol that chooses the best path between any two nodes. So, to compare Routing Protocols. We’ve Taken three typical types of routing protocols as the simulation model. RIP (Routing Information Protocol) is the oldest among OSPF & EIGR routing protocols. OSPF (open shortest path first) is the most widely used protocol and is based on Shortest Path First (SPF) Algorithm. EIGRP (Enhanced Interior Gateway Routing Protocol) is a Cisco proprietary routing protocol that runs on the Diffusion Algorithm (DUAL). And to demonstrate this in a Specific Network Environment. Cisco packet Tracer 8.0 is used to study and analyze the effect of Bandwidth, Delay, Communication Mode, and configuration. Index Terms- IGP Routing Protocol, Networking, RIPv2, OSPF, EIGRP, IPv4, Cisco Packet Tracer 8.0

Path optimization of open collaborative innovation of energy industry in urban agglomeration based on particle swarm optimization algorithm

To study the open collaborative innovation path optimization of urban agglomeration energy industry based on particle swarm optimization algorithm. Firstly, this paper brings industrial agglomeration and urban agglomeration into a unified analytical framework, uses location entropy and spatial Gini coefficient to measure the degree of industrial agglomeration, and evaluates the degree of regional industrial agglomeration competitiveness by constructing an evaluation index system of industrial agglomeration competitiveness. Then, the agglomeration index system was established, the development degree analysis method and Carlino model were used to analyze the development degree and agglomeration degree of eco-economic zones, and the agglomeration effect was analyzed by dynamic econometric method and spatial autocorrelation statistical method. Finally, a regional collaborative innovation capability evaluation model based on particle swarm optimization algorithm is constructed. Based on the index system and evaluation model, this paper evaluates and analyzes the collaborative innovation capability, and puts forward countermeasures and suggestions for future collaborative development.

Improved calibration procedures for the EM27/SUN spectrometers of the COllaborative Carbon Column Observing Network (COCCON)

Abstract. In this study, an extension on the previously reported status of the COllaborative Carbon Column Observing Network's (COCCON) calibration procedures incorporating refined methods is presented. COCCON is a global network of portable Bruker EM27/SUN FTIR spectrometers for deriving column-averaged atmospheric abundances of greenhouse gases. The original laboratory open-path lamp measurements for deriving the instrumental line shape (ILS) of the spectrometer from water vapour lines have been refined and extended to the secondary detector channel incorporated in the EM27/SUN spectrometer for detection of carbon monoxide (CO). The refinements encompass improved spectroscopic line lists for the relevant water lines and a revision of the laboratory pressure measurements used for the analysis of the spectra. The new results are found to be in good agreement with those reported by Frey et al. (2019) and discussed in detail. In addition, a new calibration cell for ILS measurements was designed, constructed and put into service. Spectrometers calibrated since January 2020 were tested using both methods for ILS characterization, open-path (OP) and cell measurements. We demonstrate that both methods can detect the small variations in ILS characteristics between different spectrometers, but the results of the cell method indicate a systematic bias of the OP method. Finally, a revision and extension of the COCCON network instrument-to-instrument calibration factors for XCO2, XCO and XCH4 is presented, incorporating 47 new spectrometers (of 83 in total by now). This calibration is based on the reference EM27/SUN spectrometer operated by the Karlsruhe Institute of Technology (KIT) and spectra collected by the collocated TCCON station Karlsruhe. Variations in the instrumental characteristics of the reference EM27/SUN from 2014 to 2017 were detected, probably arising from realignment and the dual-channel upgrade performed in early 2018. These variations are considered in the evaluation of the instrument-specific calibration factors in order to keep all tabulated calibration results consistent.

Sodium Binding Stabilizes the Outward-Open State of SERT by Limiting Bundle Domain Motions.

The human serotonin transporter (hSERT) removes the neurotransmitter serotonin from the synaptic cleft by reuptake into the presynaptic nerve terminal. A number of neurologic diseases are associated with dysfunction of the hSERT, and several medications for their treatment are hSERT blockers, including citalopram, fluoxetine, and paroxetine. The substrate transport is energized by the high concentration of external NaCl. We showed through molecular dynamics simulations that the binding of NaCl stabilized the hSERT in the substrate-binding competent conformation, which was characterized by an open access path to the substrate-binding site through the outer vestibule. Importantly, the binding of NaCl reduced the dynamics of the hSERT by decreasing the internal fluctuations of the bundle domain as well as the movement of the bundle domain relative to the scaffold domain. In contrast, the presence of only the bound chloride ion did not reduce the high domain mobility of the apo state.

A simulation process of tunable open path diode laser spectrometer to detect a carbon monoxide gas in NIR region

By modifying the wavelength of the open path tunable diode laser spectrometer (TDLS) in the near infrared region, theoretical research was implemented to improve the detection limit of carbon monoxide gas. To adjust the correct wavelength in the NIR area, MatLab code was created. Following that, frequency domain measurements were performed in order to extract the second harmonic as an indicator of gas presence. According to the results, the correct wave length in the NIR area is (1584.877 nm), and the lowest limit of CO gas concentration is (0.012 ppb).

Development of a free-form tooth flank optimization method to improve pitting resistance of spur gears

Although steel involute gears are the standard solution for gear transmissions, they tend to suffer from poor pitting resistance. Pitting typically occurs when the gear tooth flanks have high equivalent curvature at the contact point and/or when the equivalent curvature is not constant across the contact path leading to high contact pressures and the development of surface fatigue. In this paper a new optimization method is presented to produce spur gear tooth flanks with improved pitting performance compared to involute ones. The tooth flanks are represented as B-spline curves, the control points of which are the variables for the optimization problem. The constraints were designed to ensure that all the examined profiles satisfy the law of gearing and do not contain any cusps or C1 discontinuities. Deterministic and stochastic algorithms were implemented and both closed and open path of contact gear sets were examined to determine the optimum tooth profile. The optimization results show that the maximum equivalent curvature of the optimum profiles is reduced by 83% compared to the corresponding standard profiles, while the deviation from the mean value is reduced by 98%. Both the standard and the optimized gears where examined comparatively also through finite element analysis. For the case selected the maximum contact pressure developed on the optimized gear set was 77% of the respective maximum contact pressure on the standard gear set whereas the corresponding deviation from the mean value was 5%. At the same time, the bending stresses developed in the optimized gear are slightly lower than those in the standard one.

Robustness of collective scenting in the presence of physical obstacles

Honey bees (Apis mellifera L.) aggregate around the queen by collectively organizing a communication network to propagate volatile pheromone signals. Our previous study shows that individual bees “scent” to emit pheromones and fan their wings to direct the signal flow, creating an efficient search and aggregation process. In this work, we introduce environmental stressors in the form of physical obstacles that partially block pheromone signals and prevent a wide open path to the queen. We employ machine learning methods to extract data from the experimental recordings, and show that in the presence of an obstacle that blocks most of the path to the queen, the bees need more time but can still effectively employ the collective scenting strategy to overcome the obstacle and aggregate around the queen. Further, we increase the complexity of the environment by presenting the bees with a maze to navigate to the queen. The bees require more time and exploration to form a more populated communication network. Overall, we show that given volatile pheromone signals and only local communication, the bees can collectively solve the swarming process in a complex unstructured environment with physical obstacles and hit a limit when the obstacle is a much more complex maze.

OpenET: Filling a Critical Data Gap in Water Management for the Western United States

AbstractThe lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data‐driven irrigation management strategies, and expanding incentive‐driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field‐scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community‐driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well‐established satellite‐based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web‐based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite‐driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT‐JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.

Deep Reinforcement Learning-Based Network Routing Technology for Data Recovery in Exa-Scale Cloud Distributed Clustering Systems

Research has been conducted to efficiently transfer blocks and reduce network costs when decoding and recovering data from an erasure coding-based distributed file system. Technologies using software-defined network (SDN) controllers can collect and more efficiently manage network data. However, the bandwidth depends dynamically on the number of data transmitted on the network, and the data transfer time is inefficient owing to the longer latency of existing routing paths when nodes and switches fail. We propose deep Q-network erasure coding (DQN-EC) to solve routing problems by converging erasure coding with DQN to learn dynamically changing network elements. Using the SDN controller, DQN-EC collects the status, number, and block size of nodes possessing stored blocks during erasure coding. The fat-tree network topology used for experimental evaluation collects elements of typical network packets, the bandwidth of the nodes and switches, and other information. The data collected undergo deep reinforcement learning to avoid node and switch failures and provide optimized routing paths by selecting switches that efficiently conduct block transfers. DQN-EC achieves a 2.5-times-faster block transmission time and 0.4-times-higher network throughput than open shortest path first (OSPF) routing algorithms. The bottleneck bandwidth and transmission link cost can be reduced, improving the recovery time approximately twofold.

Effect of data packet size on the performance of RIP and OSPF routing protocols in hybrid networks

Purpose The purpose of this study is to calculate the effect of different packet sizes 256, 512, 1,024 and 2,048 bytes on a large-scale hybrid network and analysis and identifies which routing protocol is best for application throughput, application delay and network link parameters for different packet sizes. As the routing protocol is used to select the optimal path to transfer data packets from source to destination. It is always important to consider the performance of the routing protocol before the final network configuration. From the literature, it has been observed that RIP (Routing Information Protocol) and OSPF (Open Shortest Path First) are the most popular routing protocols, and it has always been a challenge to select between these routing protocols, especially for hybrid networks. The efficiency of routing protocol mainly depends on resulting throughput and delay. Also, it has been observed that data packet size also plays an essential role in determining the efficiency of routing protocol. Design/methodology/approach To analyse the effect of different packet sizes using two routing protocols, routing information protocol (RIP) and open shortest path first (OSPF) on the hybrid network, require detailed planning. Designing the network for simulate and then finally analysing the results requires proper study. Each stage needs to be understood well for work accomplishment. Thus, the network’s simulation and evaluation require implementing the proposed work step by step, saving time and cost. Here, the proposed work methodology is defined in six steps or stages. Findings The simulation results show that both routing protocols – RIP and OSPF are equally good in terms of network throughput for all different packet sizes. However, OSPF performs better in terms of network delay than RIP routing protocol in different packet size scenarios. Research limitations/implications In this paper, a fixed network of 125 objects and only RIP and OSPF routing protocol have been used for analysis. Therefore, in the future, a comparison of different network sizes can be considered by increasing or decreasing the number of objects in the proposed network. Furthermore, the other routing protocols can be used for performance evaluation on the same proposed network. Originality/value The analysis can be conducted by simulation of the network, enabling us to develop a network environment without restricting the selection of parameters as it minimizes cost, network deployment overhead, human resources, etc. The results are analysed, calculated and compared for each packet size on different routing protocol networks individually and the conclusion is made.

The variability in CO2 fluxes at different time scales in natural and reclaimed wetlands in the Yangtze River estuary and their key influencing factors

With the increasing pace of global warming, studies of the carbon cycle and carbon sink capacity of estuarine wetlands have received increasing attention. Estuarine wetlands are often located in economically developed and densely populated areas, and their reclamation has become an important way to acquire land resources. To explore the effect of reclamation on the carbon sink function of estuarine wetlands, the Chongming Dongtan reclaimed wetland and Jiuduansha natural wetland, which are located in the Yangtze River estuary, were selected to investigate their variabilities in carbon fluxes and the main influencing factors using the open path eddy covariance flux monitoring system. The CO2 uptake capacity of the Dongtan reclaimed wetland was significantly weaker than that of the Jiuduansha natural wetland (P < 0.05). The difference in carbon fluxes between the two wetlands was mainly influenced by plant growth and carbon fixation, which accounted for 70.7% of the variation, with soil respiration being the second most important factor. The soil water content and nitrogen and phosphorus concentrations in the reclaimed wetland significantly decreased due to the barrier to water flow presented by a dam (P < 0.01). Nitrogen limitation was the main reason for the poor plant growth in the reclaimed wetland. Although nitrogen inputs in the natural wetland promoted soil respiration (40.6%), they were overshadowed by the inhibitory effect of soil moisture and salinity (55.8%). It was therefore possible to improve the carbon sink function of reclaimed wetlands if plant growth and carbon fixation efficiency could be enhanced without promoting soil respiration.

Develop an Appropriate Model for the Role of Pressure Groups in the linear Formation of Iran's General Policy

Politics involves decision-making, and decisions are the result of group conflict. Political decisions are nothing but the result of the interaction of pressure groups and the relationship of power between them. Pressure groups try to present their demands to the political system and public policy. To. A pressure group is a group of people who have political goals and want to influence the law, and a stakeholder group is a group of people who have common interests and do not have political goals. Pressure groups can be examined from two perspectives. The classical view that the performance of pressure groups disrupts the political system and public policy; and the modern view that not only does not reject the performance of pressure groups, but also considers the existence of these groups as a dynamic aspect of the organization and a tool to improve public participation. brings. One of the biggest areas of action for pressure groups is the legislature and parliaments. The role of pressure groups in shaping public policy with the foundation data theory approach is through the three stages of open, central and selective coding. The statistical participants are the current and periodic members of parliament in the country. Using purposive sampling method, semi-structured interviews were conducted with 22 members of parliament in an 18-month period until the data saturation stage was reached. Members were validated by matching methods. The present research is a mixed type, so data analysis consists of two phases, qualitative and quantitative. In the qualitative phase, to analyze and interpret (codify) the concepts expressed by members of parliament and experts. Iran is covered, which includes open, axial and selective coding. In addition, Delphi method has been used for localization and screening of indicators. Data analysis has been used using MaxQDA2012, Excel2016 and SPSS software. Open, axial and selective coding was used to analyze the data. During the data comparison process in the open, axial and selective coding path, 132 concepts, 71 subcategories and 24 general categories were obtained and presented in the form of a paradigm model. The integration of categories, based on the existing relationships between them, around the involvement of groups in professional activities, formed a paradigm model that reflected the development of an appropriate model of the role of pressure groups in shaping public policy. Causal conditions (influence of pressure groups on decisions, indirect influence on public opinion, party orientation, incorrect structure of democracy, lack of holistic view, etc.), central category (gaining benefits and advantages, adaptation of pressure groups to policy needs General (intervention) conditions (use of coercive tools of influence, behind-the-scenes issues and interference of officials in each other) strategies (dissemination of information, use of powerful people, transparency and defeat of monopolies) and consequences (promise, policy-making citizen and unity and integrity) emerged and Relationships between different dimensions were shown through the formation of a conceptual model. Finally, legal propositions and strategic hypotheses of the research were developed.