Three-way Model Research Articles

A new three-dimensional modeling of fluorescence excitation-emission measurements to explore the interaction of hydroxychloroquine and DNA, and to quantify their binding constant

A new three-dimensional chemometric approach was introduced to explore the interaction of hydroxychloroquine (HCQ)-calf thymus deoxyribonucleic acid (DNA) and quantify binding constant using fluorescence excitation and emission measurements. The fluorescence excitation-emission spectra were recorded after gradual titration of HCQ with DNA. Then, the excitation and emission curves and relative concentrations of the drug and drug-DNA complex were quantitatively estimated using a three-dimensional model called Parallel Factor Analysis (PARAFAC) to a cubic fluorescence data array. The interaction of HCQ and DNA was predicted by applying newly modified Stern-Volmer equations to the relationship between the actual DNA concentration, and the HCQ concentration in the relative concentration profile of the PARAFAC model. In the PARAFAC application, the binding constants of the HCQ-DNA complex at 288, 298, and 310 K were found as 6.78 × 103, 5.07 × 103, and 3.74 × 103 L mol−1, respectively. From the temperature studies, the thermodynamic parameters (ΔS0= 3.528 J mol−1 K−1, ΔH0= −20.099 kJ mol−1 and ΔG0=-21.11, −21.12, and −21.19 kJ mol−1 at 288, 298, and 310 K, respectively) were calculated. The drug-DNA interaction is spontaneous due to negative ΔG0 values. The positive ΔS0 and negative ΔH0 values revealed the major role of the electrostatic force on the binding of HCQ to DNA. Assay results obtained from the proposed three-way modeling were compared to those provided by the traditional spectrofluorimetric method.

Imbalance between Employees and the Organisational Context: A Catalyst for Workplace Bullying Behaviours in Both Targets and Perpetrators.

Research on workplace bullying from the perpetrators' perspective is limited, leading to few interventions tailored to them. This gap stems from insufficient understanding of how organisational conditions and individual dispositions trigger or amplify perpetrator behaviour. To develop effective interventions in preventing bullying, perceived organisational factors were examined. This study, guided by the Job Demands-Resources (JD-R) model and the three-way model of workplace bullying (WB), aims to explore the effects of perceived (im)balances in the task or employee focus, social atmosphere (positive or negative), and hierarchical structure (high or low) in organisations on the incidence of WB, both in terms of perpetrator and target experiences. The research involved 1044 employees from multiple Spanish organisations and sectors: 51.7% in services, 24.6% in education, 14.5% in wholesale and retail trade, and 9.2% in manufacturing. The average age of participants was 35.43 years (SD = 10.9), with a female majority of 61.3%. Using a cross-sectional study design, the experiences of being a target and perpetrator were quantitatively assessed through validated WB target and perpetrator scales. Additionally, the study qualitatively examined employees' perceptions of their organisational context through free descriptions, using adjectives to depict their views. Correspondence analysis was employed to test the hypotheses, and the results affirmed them. The study found that perceived imbalances in organisational focus, social atmosphere, and hierarchy correlate with higher WB target and perpetrator reports, whereas balanced atmospheres correlate with no WB. This research underscores the significance of balanced organisational contexts in mitigating WB. It highlights a gap in the current literature regarding the broader organisational factors that influence bullying and advocates for a more in-depth understanding of these dynamics. Furthermore, it contributes to the existing body of knowledge by offering a comprehensive and harmonised approach to preventing WB, transcending isolated interventions.

Toward Automating Diagnosis of Middle- and Inner-ear Mechanical Pathologies With a Wideband Absorbance Regression Model.

During an initial diagnostic assessment of an ear with normal otoscopic exam, it can be difficult to determine the specific pathology if there is a mechanical lesion. The audiogram can inform of a conductive hearing loss but not the underlying cause. For example, audiograms can be similar between the inner-ear condition superior canal dehiscence (SCD) and the middle-ear lesion stapes fixation (SF), despite differences in pathologies and sites of lesion. To gain mechanical information, wideband tympanometry (WBT) can be easily performed noninvasively. Absorbance, the most common WBT metric, is related to the absorbed sound energy and can provide information about specific mechanical pathologies. However, absorbance measurements are challenging to analyze and interpret. This study develops a prototype classification method to automate diagnostic estimates. Three predictive models are considered: one to identify ears with SCD versus SF, another to identify SCD versus normal, and finally, a three-way classification model to differentiate among SCD, SF, and normal ears. Absorbance was measured in ears with SCD and SF as well as normal ears at both tympanometric peak pressure (TPP) and 0 daPa. Characteristic impedance was estimated by two methods: the conventional method (based on a constant ear-canal area) and the surge method, which estimates ear-canal area acoustically.Classification models using multivariate logistic regression predicted the probability of each condition. To quantify expected performance, the condition with the highest probability was selected as the likely diagnosis. Model features included: absorbance-only, air-bone gap (ABG)-only, and absorbance+ABG. Absorbance was transformed into principal components of absorbance to reduce the dimensionality of the data and avoid collinearity. To minimize overfitting, regularization, controlled by a parameter lambda, was introduced into the regression. Average ABG across multiple frequencies was a single feature.Model performance was optimized by adjusting the number of principal components, the magnitude of lambda, and the frequencies included in the ABG average. Finally, model performances using absorbance at TPP versus 0 daPa, and using the surge method versus constant ear-canal area were compared. To estimate model performance on a population unknown by the model, the regression model was repeatedly trained on 70% of the data and validated on the remaining 30%. Cross-validation with randomized training/validation splits was repeated 1000 times. The model differentiating between SCD and SF based on absorbance-only feature resulted in sensitivities of 77% for SCD and 82% for SF. Combining absorbance+ABG improved sensitivities to 96% and 97%. Differentiating between SCD and normal using absorbance-only provided SCD sensitivity of 40%, which improved to 89% by absorbance+ABG. A three-way model using absorbance-only correctly classified 31% of SCD, 20% of SF and 81% of normal ears. Absorbance+ABG improved sensitivities to 82% for SCD, 97% for SF and 98% for normal. In general, classification performance was better using absorbance at TPP than at 0 daPa. The combination of wideband absorbance and ABG as features for a multivariate logistic regression model can provide good diagnostic estimates for mechanical ear pathologies at initial assessment. Such diagnostic automation can enable faster workup and increase efficiency of resources.

Unmasking the influence of employees’ coping strategies on workplace bullying

ABSTRACT Bullying is known to impair employees’ emotional state; however, the employees’ coping strategies used to manage stress may contribute to employees’ emotional state and their exposure to workplace bullying. Hence, drawing from the Cognitive Theory of Stress and Coping and the Three-Way Model of Workplace Bullying, our study hypothesized a link between coping strategies and exposure to workplace bullying. We proposed that active coping (problem-oriented and seeking support) is negatively related to workplace bullying exposure, while passive coping (avoidance-oriented) is positively associated with bullying exposure. Emotional exhaustion was posited to mediate this association by decreasing the effect of the active and increasing the passive strategy. Results from employing PLS-SEM on data from 440 participants indicated that avoidance-oriented coping influences bullying exposure and emotional exhaustion positively. Problem-oriented coping mitigates emotional exhaustion with no impact on bullying exposure. While problem-oriented coping negatively affects emotional exhaustion, it demonstrates no effect on bullying exposure. The discussion delves into theoretical insights, practical implications, and paths for future research.

Research on the tripartite evolutionary game promoting the transformation of traditional buildings to prefabricated buildings.

The practices of prefabricated buildings illustrate the incentives in prefabricated markets as well as the decision-making behavior of stakeholders, which can influence the transformation, upgrading, and sustainability of the buildings sector. The game between the stakeholders in the prefabricated buildings market becomes complicated by the fact that they dynamically adjust their strategies in response to changing market conditions. With the aim of quantitatively studying the implications of the dynamic decision behavior of prefabricated construction stakeholders on the prefabricated construction market, this study introduces component suppliers as participating agents and government subsidies and penalties as the main measures. And a three-way model of the evolutionary game involving government subsidies and punitive schemes is constructed by this study. The essay examines the evolutionary equilibrium strategies of each game subject as well as the effect of original strategies and different parameter choices on the decision-making of each subject using MATLAB. The findings reveal that (1) decision-making behaviors among the government, component suppliers, and developers are both interrelated and constrained, but governments are the dominant agents in the evolution of prefabricated buildings. (2) Parameters such as subsidies, penalties, costs, and benefits affect the stability of the tripartite evolutionary model, which remains consistent with the previous research. (3) Component suppliers have an equally important position in the development of prefabricated buildings as recognized entities such as developers and contractors. (4) When subsidies are kept at 40% of the incremental cost and penalties at 80% of the incremental cost, the model combines a fast evolutionary rate with stable model evolution. In conclusion, the article's research findings not only validate the rationality and feasibility of component suppliers as research subjects and confirm the importance of component suppliers but also propose a more reasonable boundary value for penalties and subsidies, which provides a reference for the government to improve the incentive and punishment measures as well as the dynamic adjustment strategy of stakeholders and also provides a new perspective to achieve the goal of sustainable development of construction.

An Innovative Decision Model Utilizing Intuitionistic Hesitant Fuzzy Aczel-Alsina Aggregation Operators and Its Application

The intuitionistic hesitant fuzzy set is a significant extension of the intuitionistic fuzzy set, specifically designed to address uncertain information in decision-making challenges. Aggregation operators play a fundamental role in combining intuitionistic hesitant fuzzy numbers into a unified component. This study aims to introduce two novel approaches. Firstly, we propose a three-way model for investors in the business domain, which utilizes interval-valued equivalence classes under the framework of intuitionistic hesitant fuzzy information. Secondly, we present a multiple-attribute decision-making (MADM) method using various aggregation operators for intuitionistic hesitant fuzzy sets (IHFSs). These operators include the IHF Aczel–Alsina average (IHFAAA) operator, the IHF Aczel–Alsina weighted average (IHFAAWAϣ) operator, and the IHF Aczel–Alsina ordered weighted average (IHFAAOWAϣ) operator and the IHF Aczel–Alsina hybrid average (IHFAAHAϣ) operators. We demonstrate the properties of idempotency, boundedness, and monotonicity for these newly established aggregation operators. Additionally, we provide a detailed technique for three-way decision-making using intuitionistic hesitant fuzzy Aczel–Alsina aggregation operators. Furthermore, we present a numerical case analysis to illustrate the pertinency and authority of the esteblished model for investment in business. In conclusion, we highlight that the developed approach is highly suitable for investment selection policies, and we anticipate its extension to other fuzzy information domains.

Modeling maize evapotranspiration using three types of canopy resistance models coupled with single-source and dual-source hypotheses—A comparative study in a semi-humid and drought-prone region

The reliability and accuracy of canopy resistance (rc) are crucial for the evapotranspiration (ET) estimation in sparsely vegetated ecosystems, but most studies are still limited to the single-source Penman-Monteith (PM) model. In this study, we coupled three types of rc models (three-way model: Jarvis, JA; two-way model: Kelliher-Leuning, KL; Farias, FA; one-way model: Katerji-Perrier, KP; Massman, MA) to the PM and Shuttleworth-Wallace (SW) models to assess their applicability and stability under single-source and dual-source hypotheses in a maize field in northwest China. The models were calibrated and validated against the observed data from a three-year (2011–2013) field experiment based on genetic algorithms (GA). The results indicated that the rc coupled models optimized by GA greatly alleviated the overestimation of the original PM and SW models with mean absolute error (MAE) decreased by 13.85%-40.77% and determination coefficient (R2) increased by 0.40%-7.37%. The SW-type models achieved overall high performance to simulate ET at a diurnal timescale over the entire crop season compared to the equivalent PM-type models. The three-way JA model including crop, soil and meteorological factors tended to perform more accurately than the other rc models, and the coupled SW-JA model was optimal for predicting maize ET over the entire growing season. The two-way KL model produced lower errors than the FA model, whereas the FA model had the potential to be improved due to the highest R2 with the field-based ET for both PM- and SW- hypotheses. In addition, the sensitivity analysis to environmental variables showed the effect of leaf area index (LAI) and vapor pressure deficit (VPD) was less on ET compared with net radiation (Rn) and soil moisture (θ). This study contributes to the knowledge in the area of actual ET modeling over sparse vegetation, which provides a reference for agricultural and environmental applications.

Nonnegative Estimation of Variance Components for a Nested Three-Way Random Model

A nonnegative variance estimation procedure is suggested for an unbalanced data where two factors are nested in another. Since the involved factors are all random, the approach is based on a nested three-way random model. The proposed method for the estimation of variance components is compared with Henderson’s Method I and III in view of the same estimation procedure based on the method of moments. Although both the Henderson’s Method I and III are known to be useful for the estimation of variance components for balanced or unbalanced data, they often yield negative values as variance estimates whereas the estimates by the suggested method are never be negative. Hence, it points out what makes this happen and discusses how to fix the problem. The proposed method shows how to define sums of squares and the orthogonal coefficient matrices that are necessary for the evaluation of expectations. All the matrices of the quadratic forms for computing sums of squares are symmetric and idempotent. It also reveals the individual coefficient of each variance component does not change from equation to equation.

A multiple attribute decision-making three-way model at four-branch fuzzy environment

Three-way decisions (TWDs) theory is one of the core ideas of decision-theoretic rough sets (DTRSs). Reviewing the existing research results, we find that TWDs provides us with more flexible decision choices. And the traditional fuzzy number does not take into account the absence of information (indifference) in the evaluation process. In order to construct a new model which can get flexible decision results in complex decision environment, we introduce four-branch fuzzy numbers (FBFNs) to describe the evaluation information, so that the decision-makers can express the evaluation information more comprehensively. In this paper, a novel TWDs model in four-branch fuzzy environment is proposed to solve multiple-attribute decision-making (MADM) problem. The first challenge is to construct a TWDs model based on FBFNs and to develop a new linguistic interpretation of the loss functions. Then, we extend a method for aggregating the loss functions obtained from the attribute evaluation values. Finally, we use the nonlinear solution to solve the threshold, and apply TOPSIS method to solve the conditional probability of FBFNs. The effectiveness of this method is illustrated by an example, and the decision results are compared with a MADM method based on OWGA operator.

Novel insight into pancreatic adenocarcinoma pathogenesis using liquid association analysis

BackgroundPancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy associated with a poor prognosis. High-throughput disease-related-gene expression data provide valuable information on gene interaction, which consequently lead to deeper insight about pathogenesis. The co-expression analysis is a common approach that is used to investigate gene interaction. However, such an approach solely is inadequate to reveal the complexity of the gene interaction. The three-way interaction model is known as a novel approach applied to decode the complex relationship between genes.MethodsIn the current study, the liquid association method was used to capture the statistically significant triplets involved in the PDAC pathogenesis. Subsequently, gene set enrichment and gene regulatory network analyses were performed to trace the biological relevance of the statistically significant triplets.ResultsThe results of the current study suggest that “response to estradiol” and “Regulation of T-cell proliferation” are two critical biological processes that may be associated with the PDAC pathogenesis. Additionally, we introduced six switch genes, namely Lamc2, Klk1, Nqo1, Aox1, Tspan1, and Cxcl12, which might be involved in PDAC triggering.ConclusionIn the current study, for the first time, the critical genes and pathways involved in the PDAC pathogenesis were investigated using the three-way interaction approach. As a result, two critical biological processes, as well as six potential biomarkers, were suggested that might be involved in the PDAC triggering. Surprisingly, strong evidence for the biological relevance of our results can be found in the literature.

Abstract 73: Blood-based Biological Aging Measures Are Easy-to-access Biomarkers For Detection Of Incident Stroke

Introduction: The relationship between biological age and stroke remains unclear. We assessed the role of six DNA methylation and physiology-based biological aging measures as biomarkers of stroke risk. Methods: Participants (N=3520, mean age=69±9 years) in the US Health and Retirement Study’s 2016 Venous Blood and DNA methylation studies. Biological aging measures included: Horvath, Hannum, GrimAge, Levine, Pace of Aging (POA) and Phenotypic Age. The clocks and POA were based on DNA methylation and Phenotypic age was based on serum physiology biomarkers (albumin, creatinine, glucose, C reactive protein, lymphocyte percent, mean cell volume, red blood cell distribution width, alkaline phosphatase, and white blood cell count). All measures were regressed on chronological age and residual values were computed. Multivariable logistic regression and three-way decomposition models were conducted. Total, direct and indirect effect of modifiable risk factors (smoking, BMI, blood pressure, diabetes mellitus, and education) on stroke through biological aging was assessed. Results: A total of 291 incident strokes were included. Individuals who were biologically older had higher odds of stroke with statistically significant estimates for GrimAge (DNA methylation-based) OR (95%CI): 1.32(1.07, 1.62), P=0.009 and PhenoAge (physiology-based) OR: 1.39(1.15, 1.69), P=0.001. In tertiles analysis (lowest tertile as reference), the odds of a new stroke were two to three times higher in biologically older individuals: GrimAge OR 3rd tertile: 2.42(1.08, 5.42), P=0.03; PhenoAge OR: 3.49(1.60, 7.65), P=0.002. Modifiable factors that showed highly significant indirect effect on incident stroke through biological aging are smoking, high blood pressure, diabetes mellitus and education (college or above). Conclusions: Biologically older individuals have 2 to 3 folds higher odds of new stroke occurrence compared to biologically younger individuals. The time lag between biological aging acceleration and manifestation of clinical disease is an opportunity for interventions targeted towards primary stroke prevention.

The Judge as a Negotiator: Claims Negotiating and Inequalities in China’s Judicial Mediation

I propose a three-way model of negotiation on judicial mediation: the judge as a negotiator. Primarily drawing on ethnographic observations of a civil judge in a basic-level court in hinterland China, I document Chinese judges’ tactics at the micro level. I find that the Chinese judge not only “expands” and “narrows” claims. In addition, included in her repertoire are “repression,” “conversion,” and “facilitation.” Following this, I explore the inequitable consequences of the judge’s apparent success in disposing cases. In negotiating the claims, the judge convinces or cajoles litigants who are economically vulnerable, inexperienced in the courtroom, legally bewildered, or timid in confronting the judges’ authority, into the settlement. But she often facilitates the claims of litigants who can mount credible political resistance. The interests of those who are vulnerable in one way or another, but not in a position to initiate political threats, are often dispensed. Inequalities are thus generated, reproduced, and reinforced. This three-way negotiation model provides a new perspective to study judicial mediation comparatively.

Three-hierarchical three-way decision models for conflict analysis: A qualitative improvement and a quantitative extension

Conflict analysis facilitates cause revelation and action treatments for widespread conflicts. Relevant three-way decisions on agreement, disagreement, and neutrality attitude subsets are valuable, but the initial model has a complex definition and ambiguous semantics. This paper conducts in-depth three-way decision modeling on attitude subsets by using rough sets and three-way decisions, and it establishes both an improved qualitative model and an extended quantitative model. The two novel models are formed by an intuitionistic attitude function and a complete three-way structure, so they acquire effective connotations, optimal calculations, and thorough mechanisms. Aiming at the attitude subsets of conflict analysis, first, a qualitative three-way decision model is proposed by remedying the limitations of the existing model, and the qualitative model obtains the perfect semantics, computational algorithm, qualitative monotonicity, and equivalent characterization. Then, a quantitative three-way decision model is constructed by considering probability measures and tolerance thresholds, and the quantitative model achieves the statistical measurement, computational algorithm, and quantitative nonmonotonicity. Finally, all results are effectively verified by conflict examples and data experiments. For conflict analysis, the initial, qualitative, and quantitative three-way models constitute the three levels of attitude subsets, and the latter two offer improvements and extensions. The obtained results uncover rough set interpretations and enrich three-way decision making, mainly in terms of certainty and uncertainty.

A four-way model (FEST) for source apportionment: Development, verification, and application

In studying the spatial, temporal, and particle size variations heavy metal sources, a source apportionment model for a four-way array of data is required. In this study, referencing two-way and three-way models, a four-way (particle fractions, elements, sites, and time) source apportionment model (FEST) was developed. Errors in the three-way models solving four-way problems verified the necessity of developing the FEST model. The results showed that the FEST model had a higher accuracy than the existing models, which was probably because of more constraints and input data in the FEST model. Based on the sampled data in Beijing, sources were apportioned for the four-way array of data using the FEST model, and the spatial, temporal, and particle size variations of sources were evaluated. The main sources of heavy metals were similar to those in our prior studies, whereas the contributions of sources to specific heavy metals differed. Traffic exhaust and fuel combustion contributed more to fine particles than coarse particles, indicating that the two should be controlled preferentially among all sources. The management of traffic exhaust should be focused on the central and northern areas in each season, and the control of fuel combustion should be strengthened in the southern area in winter.

Heterogeneity in outcome assessment for inflammatory bowel disease in routine clinical practice: a mixed-methods study in a sample of English hospitals

ObjectivesKnowledge of the extent of variation in outcome assessment for inflammatory bowel disease (IBD) in routine practice is limited. We aimed to describe and quantify variation in outcome coverage and...

Children’s Health Capital Investment: Effects of U.S. Infant Breastfeeding on Teenage Obesity

Obesity, as a health and social problem with rising prevalence and soaring economic cost, is increasingly drawing scholarly and public policy attention. While many studies have suggested that infant breastfeeding protects against childhood obesity, empirical evidence on this causal relationship is fragile. Using the health capital development theory, this study exploited multiple data sources from the U.S. and a three-way error components model (ECM) with a jackknife resampling plan to estimate the effect of in-hospital breastfeeding initiation and breastfeeding for durations of 3, 6, and 12 months on the prevalence of obesity during teenage years. The main finding was that a 1% rise in the in-hospital breastfeeding initiation rate reduces the teenage obesity prevalence rate by 1.7% (9.6% of a standard deviation). The magnitude of this effect declines as the infant breastfeeding duration lengthens—e.g., the 12-month infant breastfeeding duration rate is associated with a 0.53% (3.7% of a standard deviation) reduction in obesity prevalence in the teenage years (9th to 12th grades). The study findings agree with both the behavioral and physiological theories on the long-term effects of breastfeeding, and have timely implications for public policies promoting infant breastfeeding to reduce the economic burden of teenage and later adult-stage obesity prevalence rates.

Nkx3-1 and Fech genes might be switch genes involved in pituitary non-functioning adenoma invasiveness

Non-functioning pituitary adenomas (NFPAs) are typical pituitary macroadenomas in adults associated with increased mortality and morbidity. Although pituitary adenomas are commonly considered slow-growing benign brain tumors, numerous of them possess an invasive nature. Such tumors destroy sella turcica and invade the adjacent tissues such as the cavernous sinus and sphenoid sinus. In these cases, the most critical obstacle for complete surgical removal is the high risk of damaging adjacent vital structures. Therefore, the development of novel therapeutic strategies for either early diagnosis through biomarkers or medical therapies to reduce the recurrence rate of NFPAs is imperative. Identification of gene interactions has paved the way for decoding complex molecular mechanisms, including disease-related pathways, and identifying the most momentous genes involved in a specific disease. Currently, our knowledge of the invasion of the pituitary adenoma at the molecular level is not sufficient. The current study aimed to identify critical biomarkers and biological pathways associated with invasiveness in the NFPAs using a three-way interaction model for the first time. In the current study, the Liquid association method was applied to capture the statistically significant triplets involved in NFPAs invasiveness. Subsequently, Random Forest analysis was applied to select the most important switch genes. Finally, gene set enrichment (GSE) and gene regulatory network (GRN) analyses were applied to trace the biological relevance of the statistically significant triplets. The results of this study suggest that “mRNA processing” and “spindle organization” biological processes are important in NFAPs invasiveness. Specifically, our results suggest Nkx3-1 and Fech as two switch genes in NFAPs invasiveness that may be potential biomarkers or target genes in this pathology.

The Impact of Citizenship Pressure on Organizational Citizenship Performance: A Three-Way Interactive Model.

Citizenship pressure has recently been a hot topic in organizational citizenship behavior research since it aids in understanding the driving mechanism of organizational citizenship behavior. However, previous research has revealed discrepancies in the connection. This article develops a theoretical model of the impact of citizenship pressure on organizational citizenship performance based on expectancy theory. A leader–employee paired questionnaire was used to evaluate the hypotheses. The results indicate that organizational citizenship performance is positively influenced by citizenship pressure. The connection between organizational citizenship performance and citizenship pressure is positively moderated by transformational leadership. The better the transformational leadership, the greater the influence of citizenship pressure on organizational citizenship performance. Furthermore, the impact of transformational leadership on the link between citizenship pressure and organizational citizenship performance is dependent on the political skill of employees. When individuals with strong political skill encounter transformational leadership, the relationship between citizenship pressure and organizational citizenship performance is minimal. On the contrary, this relationship is enhanced when personnel with limited political skill are confronted with transformational leadership.

Size−resolved source apportionment of particulate matter from a megacity in northern China based on one-year measurement of inorganic and organic components

This research apportioned size-resolved particulate matter (PM) contributions in a megacity in northern China based on a full year of measurements of both inorganic and organic markers. Ions, elements, carbon fractions, n-alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes and steranes in 9 p.m. size fractions were analyzed. High molecular weight PAHs concentrated in fine PM, while most other organic compounds showed two peaks. Both two-way and three-way receptor models were used for source apportionment of PM in different size ranges. The three-way receptor model gave a clearer separation of factors than the two-way model, because it uses a combination of chemical composition and size distributions, so that factors with similar composition but distinct size distributions (like more mature and less mature coal combustion) can be resolved. The three-way model resolved six primary and three secondary factors. Gasoline vehicles and coal and biomass combustion, nitrate and high relative humidity related secondary aerosol, and resuspended dust and diesel vehicles (exhaust and non-exhaust) are the top two contributors to pseudo-ultrafine (<0.43 μm), fine (0.43–2.1 μm) and coarse mode (>2.1 μm) PM, respectively. Mass concentration of PM from coal and biomass combustion, industrial emissions, and diesel vehicle sources showed a bimodal size distribution, but gasoline vehicles and resuspended dust exhibited a peak in the fine and coarse mode, separately. Mass concentration of sulphate, nitrate and secondary organic aerosol exhibited a bimodal distribution and were correlated with temperature, indicating strong photochemical processing and repartitioning. High relative humidity related secondary aerosol was strongly associated with size shifts of PM, NO3− and SO42− from the usual 0.43–0.65 μm to 1.1–2.1 μm. Our results demonstrated the dominance of primary combustion sources in the <0.43 μm particle mass, in contrast to that of secondary aerosol in fine particle mass, and dust in coarse particle mass in the Northern China megacity.

Remote sensing and GIS forest landscape assessment for sustainable forest management

This study set out to assess the dynamic characteristics of the Ikere forest reserve landscape between 1985 and 2017 using remote sensing data and spatial metrics. Landscape of the study area maintained complex patterns of spatial heterogeneity over the years. Forest cover loss to other land cover types results in new large non-forest area at increasing rate. As at the year 2017, the changes in land cover types were not yet at equilibrium, thus the need to determine the future forest cover extent using a three-way markov Chain model. The decrease in number of patches of forest land (NumP) with increase in its mean patch size (MPS) shows that the forest is becoming a single unit probably due to clearing of existing patches of forest trees. The decrease in class diversity and evenness (SDI and SEI) of the general landscape over the years strengthens this assertion. The findings of this study would be very helpful to government and other stakeholders responsible for ensuring sustainable forest and general environment.&#x0D; Keyword: Landscape, Spatial metrics, sustainable forest and Environment