Models For Different Phases Research Articles

Development of Phase and Seasonally Dependent Land-Use Regression Models to Predict Atmospheric PAH Levels.

Polycyclic aromatic hydrocarbons (PAHs) are an important class of pollutants in China. The land use regression (LUR) model has been used to predict the selected PAH concentrations and screen the key influencing factors. However, most previous studies have focused on particle-associated PAHs, and research on gaseous PAHs was limited. This study measured representative PAHs in both gaseous phases and particle-associated during the windy, non-heating and heating seasons from 25 sampling sites in different areas of Taiyuan City. We established separate prediction models of 15 PAHs. Acenaphthene (Ace), Fluorene (Flo), and benzo [g,h,i] perylene (BghiP) were selected to analyze the relationship between PAH concentration and influencing factors. The stability and accuracy of the LUR models were quantitatively evaluated using leave-one-out cross-validation. We found that Ace and Flo models show good performance in the gaseous phase (Ace: adj. R2 = 0.14-0.82; Flo: adj. R2 = 0.21-0.85), and the model performance of BghiP is better in the particle phase (adj. R2 = 0.20-0.42). Additionally, better model performance was observed in the heating season (adj R2 = 0.68-0.83) than in the non-heating (adj R2 = 0.23-0.76) and windy seasons (adj R2 = 0.37-0.59). Those gaseous PAHs were highly affected by traffic emissions, elevation, and latitude, whereas BghiP was affected by point sources. This study reveals the strong seasonal and phase dependence of PAH concentrations. Building separate LUR models in different phases and seasons improves the prediction accuracy of PAHs.

Mesoscopic Modeling Approach and Application for Steel Fiber Reinforced Concrete under Dynamic Loading: A Review

Steel fiber reinforced concrete (SFRC) has drawn extensive attention in recent years for its superior mechanical response to dynamic and impact loadings. Based on the existing test results, the high-strength steel fibers embedded in a concrete matrix usually play a strong bridging effect to enhance the bonding force between fiber and the matrix, and directly contribute to the improvement of the post-cracking behavior and residual strength of SFRC. To gain a better understanding of the action behavior of steel fibers in matrix and further capture the failure mechanism of SFRC under dynamic loads, the mesoscopic modeling approach that assumes SFRC to be composed of different mesoscale phases (i.e., steel fibers, coarse aggregates, mortar matrix, and interfacial transition zone (ITZ)) has been widely employed to simulate the dynamic responses of SFRC material and structural members. This paper presents a comprehensive review of the state-of-the-art mesoscopic models and simulations for SFRC under dynamic loading. Generation approaches for the SFRC mesoscale model in the simulation works, including steel fiber, coarse aggregate, and the ITZ between them, are reviewed and compared systematically. The material models for different phases and the interaction relationship between fiber and concrete matrix are summarized comprehensively. Additionally, some example applications for SFRC under dynamic loads (i.e., compression, tension, and contact blast) simulated using the general mesoscale models are given. Finally, some critical analysis on the current shortcomings of the mesoscale modeling of SFRC is highlighted, which is of great significance for the future investigation and development of SFRC.

Deep-Learning-Based Multiple Model Tracking Method for Targets with Complex Maneuvering Motion

The effective detection of unmanned aerial vehicle (UAV) targets is of great significance to guarantee national military security and social stability. In recent years, with the development of communication and control technology, the movement of UAVs has become increasingly flexible and complex, presenting diverse trajectory forms and different motion models in different phases. The Gaussian mixture probability hypothesis density filter incorporating the linear Gaussian jump Markov system approach (LGJMS-GMPHD) provides an efficient method for tracking multiple maneuvering targets, as applied to the switching of motions between a set of models in a Markovian chain. However, in practice, the motion model parameters of targets are generally unknown and the model switching is uncertain. When the preset filtering model parameters are mismatched, the tracking performance is dramatically degraded. In this paper, within the framework of the LGJMS-GMPHD filter, a deep-learning-based multiple model tracking method is proposed. First, an adaptive turn rate estimation network is designed to solve the filtering model mismatch caused by unknown turn rate parameters in coordinate turn models. Second, a filter state modification network is designed to solve the large tracking errors in the maneuvering phase caused by uncertain motion model switching. Finally, based on simulations of multiple maneuvering targets in cluttered environments and experimental field data verification, it can be concluded that the proposed method has strong adaptability to multiple maneuvering forms and can effectively improve the tracking performance of targets with complex maneuvering motion.

A Study on Pedestrian–Vehicle Conflict at Unsignalized Crosswalks Based on Game Theory

A dynamic game model based on multiple decision makers is developed to minimize pedestrian–vehicle conflicts at unsignalized crosswalks. The characteristics of pedestrians and drivers crossing the street are divided into traffic features, behavioral characteristics, and psychological factors, using data collected from a survey of pedestrian crossing behavior. Based on waiting delay and risk assessment, a utility model of pedestrian crossing choice behavior is presented, and a probability model for different phases of the waiting stage is developed by splitting the waiting process into three stages with pedestrian waiting duration. The payment function and the game model of pedestrian–vehicle conflict based on distinct previous decision makers are developed using game theory and “mixed strategy”, and they are resolved in equilibrium.

The circum-Antarctic ice-shelves respond to a more positive Southern Annular Mode with regionally varied melting

The Southern Hemisphere cryosphere has recently shown regionally-contrasted responses to climate change, in particular to the positive phases of the Southern Annular Mode. However, the understanding of the impacts of this mode on ice-shelf basal melt at a circum-Antarctic scale is still limited. Here, we performed idealized experiments with a pan-Antarctic regional ice-shelf cavity-resolving ocean—sea-ice model for different phases of the Southern Annular Mode. We show that positive phases lead to increased upwelling and subsurface ocean temperature and salinity close to ice shelves, while the opposite occurs for negative phases. A one-standard-deviation increase of the Southern Annular Mode leads to a net basal mass loss of 40 Gt yr−1, with strong regional contrasts: increased ice-shelf basal melt in the Bellingshausen and Western Pacific sectors and the opposite response in the Amundsen sector. Estimates of 1000–1200 and 2090–2100 ice-shelf basal melt changes due to the Southern Annular Mode are −86.6 Gt yr−1 and 55.0 to 164.9 Gt yr−1, respectively, compared to the present.

Multi-Phase CT-Based Radiomics Nomogram for Discrimination Between Pancreatic Serous Cystic Neoplasm From Mucinous Cystic Neoplasm.

PurposeThis study aimed to develop and verify a multi-phase (MP) computed tomography (CT)-based radiomics nomogram to differentiate pancreatic serous cystic neoplasms (SCNs) from mucinous cystic neoplasms (MCNs), and to compare the diagnostic efficacy of radiomics models for different phases of CT scans.Materials and MethodsA total of 170 patients who underwent surgical resection between January 2011 and December 2018, with pathologically confirmed pancreatic cystic neoplasms (SCN=115, MCN=55) were included in this single-center retrospective study. Radiomics features were extracted from plain scan (PS), arterial phase (AP), and venous phase (VP) CT scans. Algorithms were performed to identify the optimal features to build a radiomics signature (Radscore) for each phase. All features from these three phases were analyzed to develop the MP-Radscore. A combined model comprised the MP-Radscore and imaging features from which a nomogram was developed. The accuracy of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration tests, and decision curve analysis.ResultsFor each scan phase, 1218 features were extracted, and the optimal ones were selected to construct the PS-Radscore (11 features), AP-Radscore (11 features), and VP-Radscore (12 features). The MP-Radscore (14 features) achieved better performance based on ROC curve analysis than any single phase did [area under the curve (AUC), training cohort: MP-Radscore 0.89, PS-Radscore 0.78, AP-Radscore 0.83, VP-Radscore 0.85; validation cohort: MP-Radscore 0.88, PS-Radscore 0.77, AP-Radscore 0.83, VP-Radscore 0.84]. The combination nomogram performance was excellent, surpassing those of all other nomograms in both the training cohort (AUC, 0.91) and validation cohort (AUC, 0.90). The nomogram also performed well in the calibration and decision curve analyses.ConclusionsRadiomics for arterial and venous single-phase models outperformed the plain scan model. The combination nomogram that incorporated the MP-Radscore, tumor location, and cystic number had the best discriminatory performance and showed excellent accuracy for differentiating SCN from MCN.

Performance of Small-Scale Sawmilling Operations: A Case Study on Time Consumption, Productivity and Main Ergonomics for a Manually Driven Bandsaw

Sawmilling operations represent one of the most important phases of the wood supply chain, because they connect the conversion flow of raw materials into finite products. In order to maintain a high volume of processed wood, sawmills usually adopt different processing strategies in terms of equipment and methods, which can increase the value or volume of the lumber produced from logs. In this study, the performance of small-scale sawmilling operations was monitored, whilst also evaluating the exposure of workers to harmful factors. An assessment of time consumption, productivity, and main ergonomics was conducted during the use of a manually driven bandsaw. In addition, the exposure to noise was investigated to complement the knowledge in this regard. The results indicated a rather high time utilization in productive tasks, which may come at the expense of exposure to noise and to poor working postures. The modelling approach resulted in statistically significant time consumption models for different phases (blade adjustment, effective sawing, returning, unloading lumber, and loading and fixing lumber). The exposure to noise was close to 92 dB (A) (8 h) and, therefore, the level of emitted noise is likely to depend on the condition of the used blades, species sawn and on the dimensional characteristics of the logs. In terms of ergonomic risks, the poorest postures were those related to tasks such as moving the logs, loading the logs, fixing the logs, rotating and removing the logs, as well as unloading the lumber.

Loading history effect on time-dependent deformations after unloading – reversible creep of soft rock (marl)

Practical problem in geotechnical design of support systems for tunnels, slopes, and excavation pits requires numerical modeling of different phases of excavation and support installation. The applied constitutive model should therefore include aspects of the influence of the loading history on the deformation response of the rock material during both loading and unloading. Notwithstanding the practical significance, researches into this subject-matter with a view to soft rocks are rare. Some aspects of deformational behavior of soft rock after unloading given in this paper are based on results of time-cycling loading and stepwise unloading long-term creep experiments conducted by the authors on the marl specimens. The results of the experiment indicate that the time of unloading $t_{\mathrm{c}}$ measured from the beginning of a specific load history is a basic parameter, which can describe the influence of history on the deformation response of marl because it implicitly reflects the process of preconsolidation (hardening) of the material. The deformation response after unloading is described by determining the dependence of the parameters of the modified Wallner rheological model of $t_{\mathrm{c}}$ . This approach requires a larger volume of experimental data, so a semiempirical approach has been applied as an alternative, which can include the influence of magnitude of creep stress, the time of maintaining such stress before unloading, and the duration of the last period in which rock material was completely unloaded during load history.

The Relationship between the Purchasing Managers’ Index (PMI) and Economic Growth: The Case for Poland

Purpose: The article aims to analyze and evaluate the relationship between the Purchasing Managers’ Index PMI (economic sentiment indicator) and GDP dynamics in the Polish economy. The subject of detailed research was the possibility of forecasting Poland’s economic situation using a model built based on the PMI sentiment indicator. Approach/Methodology/Design: The study used data on GDP dynamics, EUR/PLN and USD/PLN exchange rates, as well as two indicators of economic sentiment prepared by independent institutions for Poland: the PMI and ESI indicator. The analysis was based on quarterly data for the period from the third quarter of 1998 to the second quarter of 2019 (84 observations). PMI data came from the bankier.pl website, ESI data from the European Commission database, GDP dynamics data from the World Bank database, and exchange rate information was taken from the stooq.pl website. The analysis contained in the article was performed using the ARDL and ECM models. Findings: The analysis showed that the model based on PMI indicator and the model based on ESI indicator is too inaccurate to be considered a tool for forecasting the economic situation in Poland. It also turned out that extension of the model with other explanatory variables increased its accuracy of fitting to real data. Practical Implications: Even though the estimated models were significantly unreliable, it turned out that in periods of greater economic instability, the PMI model showed better forecasting properties. This indicates the possibility of using the PMI model, e.g., in times of recession or economic crisis. Originality/Value: The article broadened the research perspective for forecasting the Polish economy. The results set the directions for further development of research in this aspect. It turned out that probably the optimal solution would be to create different models for different phases of the business cycle, or a different rate of economic growth.

Experimental and computational analysis of structure-property relationship in carbon fiber reinforced polymer composites fabricated by selective laser sintering

A fundamental understanding of structure-property relationship of carbon fiber reinforced polymer (CFRP) composites fabricated by selective laser sintering (SLS) is essential to provide guidance to improve the mechanical properties in this promising additive manufacturing process. In the present study, we propose a new computational framework to evaluate the mechanical behavior of SLSed CFRP based on the representative volume element (RVE) model. Firstly, a new voxel-based fiber packing algorithm is proposed with the three-dimensional fiber orientation tensor to describe the fiber distribution. The porosity generated in the manufacturing process is also considered by adding spherical voids in the matrix region. In order to remove the artificial stress concentration induced by the voxel-based algorithm, a python script is developed to regenerate the geometries of different phases with conforming mesh. Meanwhile, the constitutive models of different phases in SLSed CFRP, i.e., matrix, fiber and interface, are established according to the material characteristics. Next, the proposed computational framework of SLSed CFRP is validated by the X-ray computed tomography (XCT) measurements and tensile tests of a representative SLSed carbon fiber/polyamide 12 (CF/PA12) composite. The effects of fiber volume fraction and fiber orientation distribution on the mechanical behavior of SLSed CF/PA12 composite are further quantitatively explored and ranked with regards to their influence on stiffness and failure strength.

Insight into the microbiology of nitrogen cycle in the dairy manure composting process revealed by combining high-throughput sequencing and quantitative PCR

Nitrogen cycling during composting process is not yet fully understood. This study explored the key genes involved in nitrogen cycling during dairy manure composting process using high-throughput sequencing and quantitative PCR technologies. Results showed that nitrogen fixation occurred mainly during the thermophilic and cooling phases, and significantly enhanced the nitrogen content of compost. Thermoclostridium stercorarium was the main diazotroph. Ammonia oxidation occurred during the maturation phase and Nitrosomonas sp. was the most abundant ammonia oxidizing bacteria. Denitrification contributed to the greatest nitrogen loss during the composting process. The nirK community was dominated by Luteimonas sp. and Achromobacter sp., while the nirS community was dominated by Alcaligenes faecalis and Pseudomonas stutzeri. The nosZ community varied in a succession of Halomonas ilicicola, Pseudomonas flexibili and Labrenzia alba dominated communities according to different composting phases. Based on these results, nitrogen cycling models for different phases of the dairy manure composting process were established.

Identifying at-risk students based on the phased prediction model

Identifying at-risk students is one of the most important issues in online education. During different stages of a semester, students display various online learning behaviors. Therefore, we propose a phased prediction model to predict at-risk students at different stages of a semester. We analyze students’ individual characteristics and online learning behaviors, extract features that are closely related to their learning performance, and propose combined feature sets based on a time window constraint strategy and a learning time threshold constraint strategy. The results of our experiments show that the precision of the proposed model in different phases is from 90.4 to 93.6%.

Advertising models in the act of eating: How the depiction of different eating phases affects consumption desire and behavior

In print advertising, the use of static pictures depicting models eating food is common practice. However, less is known about how the depiction of models in different phases of consumption (holding food, moving food to mouth, taking a bite, chewing on food) affects consumers. Theories have proposed that not only do individuals mimic actions, but they also adopt the goals and the motivational patterns underlying these actions by observing others. Building on this view, we hypothesized that consumers' desire to eat a food product and their actual consumption of a food product would be greater when the model in the picture was close to engaging in consumption and that desire and actual consumption would be reduced when the model was shown in the process of finishing consumption. In two studies, we found that the participants experienced an increased desire to eat the depicted food (Study 1) and ate more of the advertised food (Study 2) when the model was shown to engage in eating food compared with when the model was shown during completion of a consumption episode. In addition, the results of Study 1 suggest that even subtle differences such as holding food compared with putting food into the mouth might affect consumers' desire to eat. Overall, our results suggest that advertisements may affect consumers’ motivation to engage in food intake differently depending on which consumption state they show with the depiction of a model close to engagement in food consumption being most likely to trigger a desire for consumption and an actual engagement in food intake.

Limited Rolling Time Domain-Based Hybrid Tracking Control for Injection Molding Process

In this paper, a limited rolling time domain-based hybrid tracking control method for injection and packing-holding phase in the injection molding process is proposed. A more flexible controller is designed by adding the adjustable weighting coefficient. First, the input and output models in different phases are established based on the collected input and output data, then, the appropriate state variables are selected to establish a multi-phase state space model. In addition, then, the above model is transformed into an extended state space model containing state variables and output tracking errors, which is transformed into a switched system model. Meanwhile, the performance indicators including the terminal state are selected for different phases, and the optimal hybrid control law is obtained by combining the Riccati equation and the boundary condition. In order to find the minimum run time of each phase for different phases, the dwell time method that depends on the Lyapunov function is designed. The method is simple in design and can improve production efficiency. Finally, the feasibility and effectiveness of the proposed method are verified by modeling and simulating the injection molding process and comparing with the traditional methods.

Agility and resilience as antecedents of supply chain performance under moderating effects of organizational culture within the humanitarian setting: a dynamic capability view

This study examines the effects of supply chain agility (SCAG) and supply chain resilience (SCRES) on performance under the moderating effect of organizational culture. We have used the dynamic capability view (DCV) to conceptualize our theoretical models for different phases of humanitarian supply chain (HSC) (pre and post-disaster phases). We used partial least squares (PLS) to examine the proposed research hypotheses using 335 responses gathered from organizations in India using questionnaires designed for a single respondent. The results suggest that SCAG and SCRES are two important dynamic capabilities of supply chain, have significant effects on pre-disaster performance (PRE-DP). The control orientation does not have significant effect on the path joining SCAG and PRE-DP. However, the control orientation has a significant interaction effect on the path joining SCRES and PRE-DP. Similarly, SCRES has significant effect on post-disaster performance (POST-DP) but SCAG has no significant effect on POST-DP. In contrast, the flexible orientation has significant moderation effects on the paths SCAG/SCRES and POST-DP. These findings contribute to our understanding of the differential effect of SCAG/SCRES on supply chain performance in different contexts. The results provide further understanding to develop appropriate strategies for different phases. Finally, limitations of our study and future research are presented.

A framework for international location decisions for manufacturing firms

The purpose of this paper is to address current shortcomings in international location decisions (ILD), which were identified through an exploratory study, by developing a model that addresses previous limitations in research and encapsulate an adequate theories and frameworks. Based on insights from an exploratory study on 17 Danish manufacturing firms and a literature review of over a 100 publications, the scope model was developed with the MECE principles in mind in order to encompass all aspects as identified, while being supplemented by adequate tools and models in different phases of the ILD process. This paper presents an application-oriented model for facilitating ILDs in manufacturing firms, which is unique in its way of being exhaustive and yet able to decompose the ILD problem in different aspects and abstraction levels to assist firms in balancing and aligning their efforts with strategic goals and organizational values.

Assessment Fargas and BLM Models for Identification of Erosion Degree and Critical Sediment Sources (Case Study: Aghbolagh Drainage Basin, Hashtrood City)

The identification of the different areas in drainage basin (as a natural planning unit) for occurring the sedimentation and its severity in different phases of basic studies has been always one of the most important purposes of the natural resources experts. For achieving to this purpose some experimental models has been presented that Some of them have high efficiency and others have weaknesses. Fargas and BLM models are used in this research and they are run in Aghbolagh drainage basin in Hashtrood town, East Azarbayjan province with 7.8 km 2 area. Fargas model includes only two factors, the rock type erosivity and drainage density in the every rock unit, whereas BLM model includes seven factors; the surface erosion, the litter cover, the rock cover on the surface, the affection of destruction on the surface, the surface rill erosion, the affection of the sedimentation due to the water flow and the amplification of gully erosion. The objective of this research is the handling of these two models for different phases of basic studies in the study area. The results of two models showed, in Fargas model 3.67% area of the basin has high erosion, 14.26% area of the basin has severe erosion and 81.04% has very severe erosion and in BLM model 42.97% area of the basin has moderate erosion and 24.93% has high erosion, therefore 52.85% of the study area in Fargas and BLM models has concurrence in the erosion severity.

Gibbs Free Energy Minimization for Prediction of Solubility of Acid Gases in Water

The disposal of acid gas (CO2/H2S mixtures) is a critical aspect in the production of hydrocarbons from sour gas fields. The increasing emphasis on CO2 sequestration has also renewed interest in the disposal of flue gas mixtures (primarily containing CO2 and H2S). A common strategy for safe disposal, in either case, is to inject the acid gas in aquifers close to production plants. These strategies rely on solubility calculations at different pressures and temperatures, governed by the field operating conditions. We present a comprehensive approach using Gibbs free energy minimization to calculate acid gas solubility in water at high temperatures (298–393 K) and pressures (0.1–80 MPa). The advantage of this approach is the flexibility to use different thermodynamic models for different phases. The proposed model uses the Peng–Robinson (PR) Equation of State (EOS) description for gas components while the liquid components are described using the ideal assumption for the temperature range 298–323 K and the Nonrandom Two-Liquid (NRTL) activity coefficient model at temperatures greater than 323 K. The model predictions compare well with experimental data for binary (CO2–H2O and H2S–H2O) and ternary mixtures (CO2–H2S–H2O). The model can also be easily extended to predict the solubility of any gas in water as well as brine containing ions to incorporate geochemical reactions.

SIGNATURES IN THE CONDUCTANCE FOR PHASE TRANSITIONS IN EXCITONIC SYSTEMS

In this paper, we analyze two phase transitions in exciton bilayer systems: a topological phase transition to a phase which hosts Majorana fermions and a phase transition to a Wigner crystal. Using generic simple models for different phases, we discuss the conductance properties of the latter when contacted to metallic leads and demonstrate the possibility to observe the different phase transitions by simple conductance measurements.

Qualitative discrimination between API GL performance levels of manual transmission fluids by comparing their EP properties determined in a new four-ball scuffing test

To prove that a candidate MTF meets the requirements of a given API performance level, one needs to perform extremely expensive and time-consuming tribological tests on entire lorry units.A new, quick and inexpensive four-ball test method, performed under scuffing conditions was used for testing EP properties of MTFs of GL-1 to GL-5(LS) performance levels. The test makes it possible to discriminate between API performance levels in a “qualitative” way—by the friction torque analysis. For interpretation of the results, scuffing models in different phases were developed on the basis of tribological tests and surface microanalyses.