Dominant Path Research Articles

Experimental and modeling studies of quadricyclane and 2-ethylnorbornane pyrolysis from atmospheric to high pressure

To improve the understanding of cyclopentadiene-based high-density liquid hydrocarbon fuels combustion chemistry, the pyrolysis experiments of 1,3-cyclopentadiene (c-C5H6), quadricyclane (QC) and ethylnorbornane (EthNB, reported in our recent work: Wang et al.,2020), were performed in a flow reactor at atmospheric and high pressure over 348–1173 K. The mole fraction profiles of products in three fuels pyrolysis were obtained using online GC–MS/FID. Based on theoretical calculations and literature research, a universal kinetic model (397 species and 1522 reactions) of QC and EthNB, incorporating the sub-mechanisms of c-C5H6 and polycyclic aromatics, was constructed in this work. It was validated against the present data and pyrolysis data of c-C5H6 as well as norbornane in literature with reasonable reproducibility. The rate of production analysis shows that the retro-Diels-Alder reaction to c-C5H6 plus C2H2 is always the dominant path to 2,5-norbornadiene (NBD, the only isomer product of QC) consumption at atmospheric and high pressures, whereas the contribution of isomerization to 1,3,5-cycloheptatriene increases with the increasing pressure and is almost equal to that of the former at high pressure and low conversion. The aromatics formation channels in QC pyrolysis are affected by the presence of C2H2 and different from those of c-C5H6 pyrolysis, especially under high pressure. For EthNB decomposition, the open-ring and H-abstraction reactions play a dominant role. The C2-C6 alkene products are formed via the decomposition of ethylnorbornyl radicals and the further reactions of these alkenes are the precursors of aromatics in EthNB pyrolysis. Although QC and EthNB have a similar U-shaped carbon skeleton structure, the difference is that the former has an extra four-membered ring with more strain energy, which leads a lower initial decomposition temperature. Similarly, the extra CC double bonds, in NBD compared to EthNB, result in more c-C5H6 and C2H2 formation and further increase the growing tendency of initial PAH.

Green Restaurant Consumers’ Pride and Social Healthy Narcissism Influencing Self-Actualization and Self-Transcendence That Drive Customer Citizenship Behavior

This study explored green restaurant consumers’ self-actualization and self-transcendence motivations that drive customer citizenship behavior (CCB). A survey of green restaurant consumers was administered, and structural equation modeling (SEM) analysis was performed. The findings indicate the presence of positive associations between pride and self-actualization, and healthy social narcissism and self-transcendence. This study also found a positive relationship between self-actualization and self-transcendence, and they are positively associated with CCB. Interestingly, the findings suggest that green restaurant consumers’ pride, self-actualization and CCB path is more dominant path vis-à-vis the path from healthy social narcissism mediated by self-transcendence to CCB.

Hierarchical value-attainment paths of CBEC consumers: a means-end-chain perspective

PurposeThis study elicits the critical attributes, consequences and values associated with the purchasing process in the context of cross-border e-commerce (CBEC). The purpose is to provide a better understanding of the fundamental factors that determine consumer values in CBEC.Design/methodology/approachThe study applies the means-end-chain theory and soft-laddering techniques to interview 60 CBEC consumers to construct an implication matrix and a hierarchical value map (HVM) of the consumer purchasing process, consisting of attribute-consequence-value (A-C-V) paths.FindingsBy analyzing the significant linkages, elements, ladders and chains in the HVM, four dominant A-C-V paths were identified: economic-driven, efficiency-driven, progress-driven and quality-driven paths.Research limitations/implicationsThis study included only Chinese CBEC buyers. This limitation might affect the generalizability of the conclusions as culture, purchase habits and economic development differ between China and other countries.Practical implicationsThe results of this study provide CBEC practitioners an understanding of the consumer purchasing process and how consumer values are associated with platform characteristics. Thus, the results aid practitioners in allocating resources and developing CBEC platforms in an appropriate manner and direction.Originality/valueThis study sheds lights on the emerging phenomenon of CBEC. By applying the means-end-chain approach, the study provides a comprehensive HVM for interpreting the consumer online purchasing process in this novel context. By illustrating the dominant paths, this research provides deeper theoretical insights into the specific focuses of CBEC consumer purchasing.

The Influences of Livelihood and Land Use on the Variation of Forest Transition in a Typical Mountainous Area of China

As one of the countries which has been experiencing a forest transition, China provides important insights into and theoretical and empirical knowledge of forest transition. In this study, through the framework of Sustainable Livelihood Analysis (SLA) and questionnaire surveys, we examined forest transition, farmers’ land-use activities and livelihood changes in Chicheng county, a typical mountainous area in Northern China, during 1975–2018. Most villages of Chicheng county experienced forest transition during the period of 2003–2005, but some villages experienced forest transition in 2010–2015. Forest transition variation over time was influenced by land use and livelihood changes. Livelihood resources, policy and institutional constraints and livelihood strategies had significant influences on land use and then caused variation in forest transition characteristics. The process of “livelihood–land use–forest transition” was the key to achieving and maintaining forest transition, and the interaction between livelihood and land use was a negative feedback relationship between society and ecology. The dominant path of forest transition in Chicheng county was the “economic development path”. Moreover, the “intensive agriculture path of small-scale farmers” enhanced the “economic development path”, and the “forest scarcity path” promoted both of the above two paths. This implies that the feedback and interactions between society and ecology should be taken into account so as to achieve a sustainable human and environmental system.

A New Methodology for the Multilayer Tight Oil Reservoir Water Injection Efficiency Evaluation and Real-Time Optimization

It is important to determine the reasonable injection and production rates in the development of multilayer tight oil reservoir with water flooding treatment. Based on the INSIM (interconnection-based numeric simulation model), a connected network model, a new method is designed to evaluate the water injection efficiency of different layers in water flooding reservoirs and to optimize the injection-production system to produce more oil. Based on the types of sedimentary facies and corresponding injection-production data, the interwell connections are divided into four major categories (middle channel, channel edge, middle channel bar, and channel bar edge) and twelve subclasses. This classification standard of interwell connections could help to significantly improve the accuracy of judging the dominant flow path without constructing a complicated geological model. The interaction of interwells such as injection-production correlation and water injection efficiency could be revealed by simulating the production performance and computing the layer dividing coefficient and well dividing coefficient. A numerical example is used to validate this method by comparing results from FrontSim and this method, and the computational efficiency of this method is several dozen times faster than that of the traditional numerical simulation. This method is applied to quickly optimize the production schedule of a tight oil reservoir with the water flooding treatment, that is, the water injection rate of multilayer reservoirs could be optimized subtly by the injection efficiency of different layers, and the target of producing more oil with lower water cut could be achieved.

Experimental Study of Acoustic Channel Reciprocity in the Shallow Ocean

The theoretical proof of channel reciprocity assumes static propagation medium and boundary conditions. Since the assumption makes little sense in the case of dynamic shallow-ocean environments, it brings up a question: how well does channel reciprocity hold in the shallow ocean? To answer this important question, a sea-going experiment was recently conducted to study the shallow-water channel reciprocity experimentally. In the experiment, two custom-built software-defined acoustic modems were deployed to probe the shared channel from two opposite directions. The channel reciprocity was evaluated by comparing the two probed channels directly. To minimize the effects of channel dynamics, a novel handshaking protocol was developed to synchronize the two-way channel probing in spite of the time asynchronism between the two modems. A set of handshaking signals was also designed to facilitate real-time channel probing while overcoming the limitations posed by half-duplex acoustic modems. Our experimental results have shown that while the shallow-ocean channels experienced in our study are not fully reciprocal in terms of channel impulse responses, they are partially reciprocal in terms of the arrival time of the dominant paths at a high probability. This article provides the details of this experimental study, including its design, setups, execution, and results.

Origin of leakage current in vertical GaN devices with nonplanar regrown p-GaN

This work demonstrates large-area vertical GaN-on-GaN Schottky barrier diodes (SBDs) with different p-GaN terminations fabricated by the p-GaN regrowth on planar and nonplanar n-GaN structures and studies the leakage current in these regrown p-GaN terminations. The SBDs with planar p-GaN terminations demonstrate a higher breakdown voltage than the non-terminated SBDs. In contrast, the SBDs with nonplanar regrown terminations exhibit a significantly higher leakage current, which agrees with the tunneling behavior. The microscopic current mapping and local current–voltage (I–V) spectra are acquired using conductive atomic force microscopy (C-AFM) in the nonplanar regrown junction region. The local leakage currents and conduction types are derived from the I–V characteristics of the Schottky barrier between the metalized C-AFM tip and GaN. The dominant leakage path is revealed to be the tunneling across the Schottky barrier to the regrowth sidewall assisted by high-concentration interfacial impurities, followed by current flow along the regrowth sidewall. An ∼0.7 μm-wide n-type compensation layer is found next to the non-polar regrowth sidewall, which does not directly induce a major leakage path but moves the p-GaN away from the regrowth interface, thus weakening the p-GaN depletion of the sidewall interfacial impurities as well as facilitating the formation of a crowded electric field and tunneling at the Schottky contact to the regrowth region.

Acoustic design and analyses of a double Skin Façade system

Noise insulation in buildings is an important topic in building acoustics. Existing literature shows a clear lack of simulation tools for the design, analysis, and assessment of the sound insulation performance of building structures, especially when the frequency of interest becomes higher. To tackle this problem, a numerical based Condensed Transfer Function (CTF) method, alongside a piecewise calculation scheme, is adapted to investigate a simplified Double Skin Façade (DSF) system. Embracing a sub-structuring philosophy, the method offers an appealing alternative to existing analyses ones in terms of providing enhanced computational efficiency and enriched physical description of the system. Numerical analyses reveal dominant sound transmission paths into a typical receiving room. Meanwhile, as sound reduction devices, microperforated panels are investigated in two arrangements, triggering different sound absorption behaviors and design principles. The proposed model allows extensions to other building structures.

Millimeter-Wave Hybrid Precoder Design With a Fast Iterative Beam Split and Detection Algorithm

The hybrid analog and digital structure of large-scale antenna array offers a good tradeoff between cost and flexibility, which is a promising solution for millimeter-wave (mm-wave) system. This letter proposes a novel hybrid precoder (HP) design with an iterative beam split and detection algorithm, which works well for sparse mm-wave channels. The proposed strategy can extract the dominant propagation paths by iterative trainings, where the number of dominant paths up to that of radio frequency chains can be detected. The effectiveness and time overhead parameterized by the number of iterations are investigated. The experimental results demonstrated that we can approach optimal HP design with the proposed algorithm with only eight iterations for measured channels, which significantly reduced the complexity compared to the exhaustive search method.

Beamformer Design for Physical Layer Security in Dual-Polarized Millimeter Wave Channels

We develop a beamforming scheme to enhance the physical layer security in dual-polarized millimeter wave (mmWave) systems. We aim to compute a transmit beamformer that maximizes the secrecy rate of the desired user. Assuming the transmitter has a statistical distribution of a dominant radio path, we compute a single-polarization beamforming vector that makes directional transmissions at mmWave frequencies more secure. Moreover, we propose a channel sounding scheme to obtain a weight vector that combines the dual-polarized antennas for improving the secrecy rate. Simulation results are presented to verify the secrecy rate performances of the proposed beamforming algorithm.

Spatial–Temporal evolution of shear banding in bulk metallic glasses

Shear band behaviour plays a critical role in toughening and failure of bulk metallic glasses (BMGs). However, due to instability in time and inhomogeneity in space, spatial–temporal evolutions of shear bands are difficult to be studied in the past decades. Using digital image correlation (DIC) and infrared thermal imaging (ITI) technologies, uniaxial quasi-static compressions for Zr41.2Ti13.8Ni10Cu12.5Be22.5 BMG are carried out. The spatial–temporal evolutions of shear bands, as well as the relationship between shear band and failure in BMGs, are in-situ investigated. A theoretical evaluation of temperature is performed based on the heat conduction theory, in line with the experimental data. Moreover, a free volume theory-based amorphous viscoplasticity model is implemented by finite element method (FEM) to understand the shear band behaviour further. The nucleation, propagation, intersection of shear bands are investigated in detail, and the simulation results are in agreement with the experiments in some respects. Besides, it is found that the primary shear band tends to be activated more easily along a so-called dominant path generated after shear-band competitions. This paper provides insights for the prediction of the primary shear band, prevention of failure, and toughening method in BMGs.

Kinetic study and optimization on SNCR process in pressurized oxy-combustion

Pressurized Oxy-combustion is one of the most promising technologies for carbon capture, utilization, and storage (CCUS) of coal utilization. In pressurized oxy-combustion, the removal of acid gas pollutants and the latent heat of moisture condensation are mainly carried out by an integrated direct-contact wash column (DCC). Recent studies have shown that the inlet concentration of NOx in the column is important for the combined removal of NOx and SOx, therefore, it is essential to control the NOx emissions before the DCC. Selective non-catalytic reduction (SNCR) is a promising and economical technology of NOx reduction; however, no study has been conducted on SNCR at elevated pressure, especially in pressurized oxy-combustion. In this paper, kinetic modeling is carried out to explore and optimize the NOx reduction by SNCR in pressurized oxy-combustion. First, the detailed mechanism used in this study is validated by the experimental results in literature. Based on the validation of the detailed mechanism, the effects of different parameters including temperature, oxygen concentration, moisture content, NH3 concentration, and SO2 concentrations on the SNCR performance are analyzed at higher pressures in oxy-combustion atmosphere. The modeling results show that by increasing the pressure from 1 atm to 15 atm, the SNCR de-NOx efficiency increased by 2–3%. The width of the optimum temperature window for maximum De-NOx is broadened from 1250K to 1450K with increasing the pressure from 1 atm to 10 atm. The increase of pressure has no significant effect on thermal de-NOx efficiency with increasing the NH3/NO ratio. At higher pressure (10 atm) the increase in O2 concentration from 1 to 20% the de-NOx efficiency decreases almost twice as much as at 1 atm. The increase of SO2 and moisture contents at high pressure have no significant effect on the de-NOx efficiency. Rate of production (ROP) and sensitivity analysis are performed to determine the dominant reaction paths of de-NOx in pressurized-oxy SNCR process. This study can provide guidance for the process optimization of de-NOx by SNCR in pressurized oxy-combustion.

From Birth to Overweight and Atopic Disease: Multiple and Common Pathways of the Infant Gut Microbiome

Few studies, even those with cohort designs, test the mediating effects of infant gut microbes and metabolites on the onset of disease. We undertook such a study. Using structural equation modeling path analysis, we tested directional relationships between first pregnancy, birth mode, prolonged labor and breastfeeding; infant gut microbiota, metabolites, and IgA; and childhood body mass index and atopy in 1667 infants. After both cesarean birth and prolonged labor with a first pregnancy, a higher Enterobacteriaceae/Bacteroidaceae ratio at 3 months was the dominant path to overweight; higher Enterobacteriaceae/Bacteroidaceae ratios and Clostridioides difficile colonization at 12 months were the main pathway to atopic sensitization. Depletion of Bifidobacterium after prolonged labor was a secondary pathway to overweight. Influenced by C difficile colonization at 3 months, metabolites propionate and formate were secondary pathways to child outcomes, with a key finding that formate was at the intersection of several paths. Pathways from cesarean section and first pregnancy to child overweight and atopy share many common mediators of the infant gut microbiome, notably C difficile colonization.

SpeedNet: Indoor Speed Estimation With Radio Signals

Indoor human speed estimation is critical to in-home health monitoring of elderly people since it can provide the moving status of the human. Contactless indoor speed estimation with radio signals is challenging due to the complicated relationship between the speed of moving human and radio signals. In this article, we propose an indoor speed estimation framework, SpeedNet, to estimate the speed from the radio signals. Specifically, SpeedNet first extracts the dominant path signal reflected from the human through the beamforming technique. Then, SpeedNet obtains the doppler frequency shift (DFS) corresponding to the moving human by analyzing the short-time Fourier transform (STFT) spectrogram of the dominant path signal. Finally, SpeedNet trains a deep neural network composed of convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) to utilize the spatial and temporal features of DFS to estimate the speed of moving human. The experimental results show that SpeedNet can estimate the human moving speed with an average accuracy of 96.33% in a typical indoor environment, which is better than the state-of-the-art approaches.

EFEKTIVITAS KEBIJAKAN KEPEMIMPINAN TERHADAP PRODUKTIVITAS MASYARAKAT (Riset pada Desa Majegan Kecamatan Tulung Kabupaten Klaten Periode Tahun 2016 – 2017)

This study aims to know, examine and analyze the influence of leadership, communication, commitment and compensation to the productivity of people with motivation and trust as intervening variables in the village Majegan Tulung District Klaten Period Year 2016 – 2017. The data analysis technique used is path analysis, which will be tested by t test, F test and R2 test, Correlations, direct influence and indirect influence and total influence. Data collection techniques using questionaires, researchers took a sample of 50 respondents. T test results show that leadership, commitment and compensation have a significant positive effect on motivation while communication has a negative and insignificant effect on motivation; communication, commitment and compensation have a significant positive effect on trust while leadership has a negative and insignificant effect on trust; leadership, communication, compensation, motivation and trust have a positive and significant effect on productivity while commitment has positive and insignificant effect on productivity. F test results show that leadership, communication, commitment, compensation, motivation and trust together positively and significantly affect the productivity of society. The result of determination coefficient test shows that the value of R square total is 0,987, meaning that productivity variable is explained by leadership, communication, commitment, compensation, motivation and trust equal to 98,7% and the rest equal to 1,3% explained other factor outside research model, variable satisfaction and organizational culture. The result of path analysis shows that the direct path of compensation to Productivity is the most dominant path to productivity directly, hence, to increase productivity directly more effectively the use of compensation variables.

Using weighted directed graphs for identification of flow of emotions in poems

Poem is a spontaneous flow of emotions. There are several emotion detection systems to identify emotions from speech, gestures, and text (blogs, newspapers, stories and medical reports). Since such systems do not exist for poetry, we take the first step in building a system to recognize emotions in poetry by constructing a benchmark corpus, the PERC (Poem Emotion Recognition Corpus), of poems written by Indian poets in English. In this research a novel graphical method, Poem Emotion Trajectory System (PETS), is proposed to depict the flow of emotion in a poem. PETS is based on the construction of a weighted directed graph as a means to represent the emotion flow among the verses of a given poem. The weights represent the transition probability among the emotion states considered. The significant advantage is that a dominant path for each emotion category is identified. Emotion flow along verses is analyzed using a graph-based approach. This method, applied to each emotion category, generalizes the emotion flow in each emotion class. This PETS can be applied in poetry therapy and to enhance creative thinking and writing.

Water Intrusion Characterization in Naturally Fractured Gas Reservoir Based on Spatial DFN Connectivity Analysis

In this study, the non-intrusive embedded discrete fracture model (EDFM) in combination with the Oda method are employed to characterize natural fracture networks fast and accurately, by identifying the dominant water flow paths through spatial connectivity analysis. The purpose of this study is to present a successful field case application in which a novel workflow integrates field data, discrete fracture network (DFN), and production analysis with spatial fracture connectivity analysis to characterize dominant flow paths for water intrusion in a field-scale numerical simulation. Initially, the water intrusion of single-well sector models was history matched. Then, resulting parameters of the single-well models were incorporated into the full field model, and the pressure and water breakthrough of all the producing wells were matched. Finally, forecast results were evaluated. Consequently, one of the findings is that wellbore connectivity to the fracture network has a considerable effect on characterizing the water intrusion in fractured gas reservoirs. Additionally, dominant water flow paths within the fracture network, easily modeled by EDFM as effective fracture zones, aid in understanding and predicting the water intrusion phenomena. Therefore, fracture clustering as shortest paths from the water contacts to the wellbore endorses the results of the numerical simulation. Finally, matching the breakthrough time depends on merging responses from multiple dominant water flow paths within the distributions of the fracture network. The conclusions of this investigation are crucial to field modeling and the decision-making process of well operation by anticipating water intrusion behavior through probable flow paths within the fracture networks.

Vibration transmission and power flow of laminated composite plates with inerter-based suppression configurations

This paper investigates the vibration transmission and power flow behaviour of harmonically excited laminated composite plates attached with different inerter-based suppression configurations. The substructure approach based on analytical and numerical methods is employed to obtain the steady-state dynamic response. Power flow analysis is carried out to determine the time-averaged power flow input and transmission as well as the kinetic energy of the plate. The power flow density vector is used to show explicitly the vibration transmission paths within the composite plate. It is shown that the fibre orientation and stacking sequences can have significant effects on the time-averaged power flow characteristics as well as the dominant vibration transmission paths. It is also shown that passive spring, damper and inerter elements may be attached to the plate to modify its vibration response and transmission according to specific design requirements. The proposed inerter-based suppression device with two different configurations can reduce the vibration level over a wide frequency range for vibration suppression. The findings may provide insights for the enhanced dynamic designs of laminated composite plates, and the suppression of their vibrations using inerter-based devices.

Accurate Angular Inference for 802.11ad Devices Using Beam-Specific Measurements

Due to their sparsity, 60GHz channels are characterized by a few dominant paths. Knowing the angular information of their dominant paths, we can develop various applications, such as the prediction of link performance and the tracking of 802.11ad devices. Although they are equipped with phased arrays, the angular inference for 802.11ad devices is still challenging due to their limited number of RF chains and limited phase control capabilities. Considering the beam sweeping operation and the high communication bandwidth of 802.11ad devices, we propose variation-based angle estimation (VAE), called VAE-CIR, by utilizing beam-specific channel impulse responses (CIRs) measured under different beams and the directional gains of the corresponding beams to infer the angular information of dominant paths. Unlike state-of-the-arts, VAE-CIR exploits the variations between different beam-specific CIRs for angular inference and provides a performance guarantee in the high signal-to-noise-ratio region. To evaluate VAE-CIR, we generate the beam-specific CIRs by simulating the beam sweeping of 802.11ad devices with the beam patterns measured on off-the-shelf 802.11ad devices. The 60GHz channel is generated via a ray-tracing-based simulator and the CIRs are extracted via channel estimation based on Golay sequences. Through extensive experiments, VAE-CIR is shown to achieve more accurate angle estimation than existing schemes.

Machine learning prediction of thermal transport in porous media with physics-based descriptors

Understanding the thermal transport mechanism in porous media is important for various engineering and industrial applications. The effective thermal conductivity of porous media is known to be related to the morphology of porous structures. However, existing effective medium approaches usually miss the morphology effects, and numerical simulations are expensive and not physically intuitive. Machine learning methods have recently been successful in predicting effective thermal conductivity, but the lack of descriptors limits physical insights. In this work, we investigate structural features that have significant effects on thermal transport in porous media and identify five physics-based descriptors to characterize the structural features: shape factor, bottleneck, channel factor, perpendicular nonuniformity, and dominant paths. These descriptors can effectively quantify the anisotropy of pore morphology and strongly correlate with effective thermal conductivities. The proposed descriptors are incorporated into machine learning models to predict the effective thermal conductivity of porous media, and the results are shown to be fairly accurate. They provide new insights into the thermal transport mechanisms in complex heterogeneous media.