Resource Model Research Articles

High-resolution 3D hydrodynamic modeling and comprehensive assessment of tidal current energy resources

As a clean and renewable resource, tidal current holds significant development potential. However, accurately assessing tidal current energy resources has been a persistent challenge. This study proposes a comprehensive assessment method using a small-scale, high-precision, multi-criteria three-dimensional hydrodynamic model to assess resource reserves applied to the Zhairuoshan Waterway. The hydrodynamic model was employed to simulate critical parameters such as tidal level, flow velocity, and flow direction. Multiple statistical indicators were used to evaluate the model's accuracy, showing consistency. The study analysed the flow speed distribution over a complete cycle, revealing an average flow speed of 1.51 m/s, with a maximum speed reaching 3.83 m/s. The generally high flow speeds within the waterway, coupled with the stability of the tidal current, indicate the significant resource potential of the study area. A quantitative analysis of the spatial distribution of tidal current energy was conducted using energy flux density, and the results showed that high energy density areas are widely distributed. Furthermore, the theoretical tidal energy resources of the waterway were calculated, showing that the maximum resource reserves could reach 9.98 MW at the selected cross-sections. Coupled with the analysis of unit-width energy flux, the high-potential areas within the waterway were further identified.

Revolutionizing the Future of Hydrological Science: Impact of Machine Learning and Deep Learning amidst Emerging Explainable AI and Transfer Learning

Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are revolutionizing hydrology, driving significant advancements in water resource management, modeling, and prediction. This review synthesizes cutting-edge developments, methodologies, and applications of AI-ML-DL across key hydrological processes. By critically evaluating these techniques against traditional models, we highlight their superior ability to capture complex, nonlinear relationships and adapt to diverse environments. We further explore AI applications in precipitation forecasting, evapotranspiration estimation, groundwater dynamics, and extreme event prediction (floods, droughts, and compound events), showcasing their timely potential in addressing critical water-related challenges. A particular emphasis is placed on Explainable AI (XAI) and transfer learning as essential tools for improving model transparency and applicability, enabling broader stakeholder trust and cross-regional adaptability. The review also addresses persistent challenges, including data limitations, computational demands, and model interpretability, proposing solutions that integrate emerging technologies like quantum computing, the Internet of Things (IoT), and interdisciplinary collaboration. This review charts a strategic course for future research and practice by bridging AI advancements with practical hydrological applications. Our findings highlight the importance of embracing AI-driven approaches for next-generation hydrological modeling and provide actionable understandings for researchers, practitioners, and policymakers. As hydrology faces escalating challenges due to human-induced climate change and growing water demands, the continued evolution of AI-integrated models and innovations in data handling and stakeholder engagement will be imperative. In conclusion, the findings emphasize the critical role of AI-driven hydrological modeling in addressing global water challenges, including climate change adaptation, sustainable water resource management, and disaster risk reduction.

Stochastic economic sizing and placement of renewable integrated energy system with combined hydrogen and power technology in the active distribution network.

The current study concentrates on the planning (sitting and sizing) of a renewable integrated energy system that incorporates power-to-hydrogen (P2H) and hydrogen-to-power (H2P) technologies within an active distribution network. This is expressed in the form of an optimization model, in which the objective function is to reduce the annual costs of construction and maintenance of integrated energy systems. The model takes into account the planning and operation model of wind, solar, and bio-waste resources, as well as hydrogen storage (a combination of P2H, H2P, and hydrogen tank), and the optimal power flow constraints of the distribution network. Electrical and hydrogen energy are administered in an integrated energy system. The modeling of the uncertainties regarding the quantity of load and renewable resources is achieved through stochastic optimization using the Unscented Transformation method. The novelties of the scheme include the sizing and placement of a combined hydrogen and power-based renewable integrated energy system, the consideration of the impacts of bio-waste units, P2H, and H2P systems on the planning of the integrated energy system and the operation of the active distribution network, and the modeling of uncertainties using the Unscented Transformation method to reduce the calculation time. The study's results demonstrate the scheme's ability to improve the technical conditions of the distribution network by considering the optimal planning of integrated energy systems. In comparison to the network power flow, the operation status of the network has been improved by approximately 23-45% through the optimal siting, sizing, and energy management of hydrogen storage equipment, as well as renewable resources in the form of integrated energy systems. In other words, optimal energy management and planning of the integrated energy systems in the distribution network has been able to reduce energy losses and voltage drop by 44.5% and 42.4% compared to the load flow studies. In this situation, peak load carrying capability has increased by about 23.7%. In addition, compared to the case of the network with renewable resources, the overvoltage has decreased by about 43.5%. Also, Unscented Transformation method has a lower calculation time than scenario-based stochastic optimization.

The Effect of Red Tape on Employability Competences of Teachers

Red tape forms a major threat to many public organizations around the world. Building on the Job Demands–Resources model, supplemented by arguments from the psychological process theory of red tape, this study explores how and when red tape affects teachers’ employability competences (i.e., balance, anticipation and optimization, and personal flexibility). Analyses ( N = 908 teachers; 92 school leaders) revealed a negative relationship between red tape, on one hand, and balance and personal flexibility, on the other hand, through perceived impact on work outcomes. Interestingly, the analyses also revealed that when organizations provide sufficient developmental rewards to their employees, the negative consequences of red tape on perceived impact are buffered, which indirectly also benefits employees’ balance and personal flexibility.

Research on the Genesis Model of Geothermal Resources in Thermal Storage

Research on the Genesis Model of Geothermal Resources in Thermal Storage

Remembering the blues: negative emotion during encoding improve memory recall in major depressive Disorder

ABSTRACT Substantial research indicates that individuals with Major Depressive Disorder (MDD) remember more negative information compared to neutral and positive information. This phenomenon is commonly attributed to attentional biases toward negative over neutral and positive information. A recent attentional resources model suggests that in MDD, negative cues not only capture attention, but also lead to deeper processing of subsequent information, irrespective of its content. This study aimed to replicate findings supporting this attentional resources model and go beyond it by investigating the effect of negative cues on encoding and retrieval processes. Forty-one participants with MDD and no comorbid diagnoses, and 42 healthy-controls completed the emotional recall task with negative or positive videos presented during encoding and retrieval stages of a neutral word-list memory test. During encoding, only the MDD group exhibited a difference between negative and positive videos, such that for negative videos memory recall was improved and for positive words it was reduced. Emotional videos had no effect when presented during retrieval. These results suggest that in MDD, encountering emotional cues not only biases retrieval processes toward recalling more negative content, but rather fundamentally alters the depth of information processing, while not leading to a broad-spectrum recruitment of cognitive resources.

Work-family interference and life satisfaction: the role of life goals

ABSTRACT The interface between work and family domains has received considerable scholarly attention in recent decades due to its substantial impact on outcomes related to work, family, health, and well-being. However, individuals experience this impact differently, with some demonstrating resilience while others are more vulnerable to negative effects. In this study, we investigate the role of individuals’ life goals and gender in the work-family interface, using the framework of the work-home resources model and selfregulation theory. Using Structural Equation Modeling with data from Waves 8 and 10 of the German Family Panel (pairfam), we found that life goals significantly moderate these effects: individuals prioritizing agentic goals feel the detrimental impact of work-to-family interference (WtFI) on life satisfaction more intensely than those who prioritize communal goals and those whose goals are balanced. In contrast, the effect of family-to-work interference (FtWI) on life satisfaction was significant only for individuals prioritizing communal goals, with no significant moderation effect observed across the other life goal groups. We observed no significant gender difference in the impact of either WtFI or FtWI on life satisfaction. We also discuss potential theoretical and practical implications in light of our findings.

A systematic literature review on public health and healthcare resources for pandemic preparedness planning.

Generating insights into resource demands during outbreaks is an important aspect of pandemic preparedness. The EU PANDEM-2 project used resource modelling to explore the demand profile for key resources during pandemic scenarios. This review aimed to identify public health and healthcare resources needed to respond to pandemic threats and the ranges of parameter values on the use of these resources for pandemic influenza (including the novel influenza A(H1N1)pdm09 pandemic) and the COVID-19 pandemic, to support modelling activities. We conducted a systematic literature review and searched Embase and Medline databases (1995 - June 2023) for articles that included a model, scenario, or simulation of pandemic resources and/or describe resource parameters, for example personal protective equipment (PPE) usage, length of stay (LoS) in intensive care unit (ICU), or vaccine efficacy. Papers with data on resource parameters from all countries were included. We identified 2754 articles of which 147 were included in the final review. Forty-six different resource parameters with values related to non-ICU beds (n = 43 articles), ICU beds (n = 57), mechanical ventilation (n = 39), healthcare workers (n = 12), pharmaceuticals (n = 21), PPE (n = 8), vaccines (n = 26), and testing and tracing (n = 19). Differences between resource types related to pandemic influenza and COVID-19 were observed, for example on mechanical ventilation (mostly for COVID-19) and testing & tracing (all for COVID-19). This review provides an overview of public health and healthcare resources with associated parameters in the context of pandemic influenza and the COVID-19 pandemic. Providing insight into the ranges of plausible parameter values on the use of public health and healthcare resources improves the accuracy of results of modelling different scenarios, and thus decision-making by policy makers and hospital planners. This review also highlights a scarcity of published data on important public health resources.

Parental Burnout—A Model of Risk Factors and Protective Resources Among Mothers of Children with/Without Special Needs

Parents of children With Special Needs and Disabilities (W-SND) who require long-term healthcare are at high risk of Parental Burnout (PB). However, most studies have focused on PB among parents of children Without Special Needs (WO-SN). This study aimed to develop a new model explaining PB of mothers of children W-SND/WO-SN. The main hypothesis was that the nexus of correlations between risk factors of PB (severity of child’s disability/challenge, perceived caregiver burden) and protective resources (social support, learned resourcefulness, deep emotion work) will explain the variance of PB of mothers of children W-SND and WO-SN. A questionnaire assessing PB, its risk factors, and protective resources was completed by 352 Israeli mothers of children W-SND (mean age 36.9) or WO-SN (mean age 32.3). The child’s disabilities were communicative, physical, intellectual and developmental. The main results are that mothers of children W-SND reported higher PB, higher caregiver burden, and a higher severity of disability. About 50% of PB variance was significantly explained by the nexus of correlations between selected risk and protective factors. Among all mothers, the more social support they received, the higher their learned-resourcefulness. However, learned resourcefulness mediates the correlation between caregiver burden and PB among mothers of children W-SND. Accordingly, it is important to increase awareness among healthcare professionals regarding the risk factors and symptoms of PB, and to develop workshops on protective resources in order to prevent PB and promote mothers’ well-being. Further research should be conducted among fathers and parents from diverse cultures.

Adolescent dating violence and leader role occupancy

AbstractWho becomes a leader is of considerable importance to employees, organizations and society. Recently, researchers have considered whether early life events outside of the workplace affect who occupies leadership roles within organizations. Informed by the lifespan approach to leadership, and the work–home resources model, we investigate whether violence in adolescent dating relationships is associated with leader role occupancy in adulthood. We hypothesize that experiencing psychological aggression and physical violence indirectly lowers the likelihood of occupying a leadership role through depressive symptoms. Moreover, we hypothesize that the indirect effects will be weaker when parent–adolescent relationship quality is higher, when adolescents come from higher household incomes, and stronger for women. Drawing on four waves of ADD Health, results showed that experiencing early psychological aggression in dating relationships increased depressive symptoms, hindering leader role occupancy; however, this effect was buffered by income, and stronger for women. Experiencing physical violence exerted indirect negative effects on leader role occupancy via depressive symptoms, regardless of parent–adolescent relationship quality, income or gender. There were no direct effects of aggression or violence on leader role occupancy. Our findings suggest that early personal relationships can impact young adult's mental health, which in turn can influence leadership outcomes into adulthood.

Literature review on optimization of transboundary water for irrigation

ABSTRACT Transboundary water resources are essential for agricultural sustainability and regional development, and they are intrinsically linked to achieving the United Nations' SDGs and the water-food-energy nexus (WFE-NEXUS) concept. Despite challenges such as conflicting allocation and climate change impacts, effective transboundary water management for irrigation is crucial to meeting the SDGs of eradicating hunger, providing clean water and sanitation, offering affordable and sustainable energy, and taking climate action. This work synthesizes approaches to transboundary water for irrigation optimization, highlighting the significance of a holistic plan that considers both technical and social factors. Remote-sensing technologies, data forecasting, hydrology and hydraulic modelling, and water resource modelling all contribute to maximize water allocation and policy creation, particularly when paired with collaborative government features. This integrated approach to transboundary water for irrigation optimization fosters long-term development by improving livelihoods, resilience, and inclusive growth through efficient resource management.

Deducing Aerodynamic Roughness Length From Abundant Anemometer Tower Data to Inform Wind Resource Modeling

AbstractAerodynamic roughness length () fundamentally affects land surface momentum loss and wind resource simulation, but ground truth data of are sparse in space, causing datasets used in atmospheric models are empirically estimated from land cover types through a look‐up table. In this study, we derived values from 101 anemometer towers in China. Taking them as ground truth, we show that existing gridded datasets determined from either a look‐up table or a machine‐learning method contain considerable uncertainty and fail to capture the variability of within each land cover type, although the latter performs better. Even for the widely used ERA5, its is overestimated in wind‐rich regions of China, causing an underestimation of near‐surface wind speed. This highlights the necessity to improve data in atmospheric models. Current rapidly expanding anemometer towers may substantially enrich truth data and thus provide potential to improve wind resource modeling.

Energy in the workplace: job demands, job resources, and employees’ inner resources as pathways to organizational outcomes

In this study, we expanded upon the job demands–resources model to assess the role of employees’ vitality as an inner resource for their work engagement and job commitment. To assess vitality and related job resources, we developed an index of vitality outside of work and adapted measures of manager autonomy support and organizational support. For job demands, we measured work stress and predicted that each of these four variables would contribute independently to work-related outcomes. Then, in a preregistered study, we collected these measures from a sample of 5,280 American workers (primarily ages 18–34, 54% female). Results from multivariate regression analyses largely confirmed our hypotheses, showing that positive work-related outcomes, such as enthusiasm, enjoyment, and job satisfaction, were positively predicted by manager autonomy supports, organizational support, and individuals’ vitality, and negatively predicted by work stress. The reverse pattern was largely observed for the negative outcome of turnover intention. Exploratory analyses also suggested that individual vitality may buffer the negative effects of stress and low manager and organizational support. The results highlight the potential role of employee vitality outside of work and managerial support in bolstering work engagement and reducing turnover intentions, offering a basis for organizational strategies aimed at improving work culture and retaining talent.

Examining the dark side of quality management: analysing work overload, exhaustion and managerial support using a moderated mediation approach

PurposeIn this study, we propose a model for analysing the association between total quality management (TQM) and exhaustion, which considers work overload as a mediation variable and investigates perceptions of managerial support as a moderating condition. Through the job demands–resources model, the study sheds light on the dilemma about the negative implications of TQM for employees.Design/methodology/approachThe proposed model of relationships is analysed using matched employee–organisation survey data from two R&D-intensive sectors in Spain. Structural equation models are employed to examine the proposed relationships.FindingsOnly perceptions of hard TQM trigger a health-impairment process which increases work overload and exhaustion, whereas soft TQM decreases exhaustion and does not have negative consequences for employee well-being. We also find that managerial support can alleviate the consequences of hard TQM on exhaustion due to work overload.Originality/valuePrevious research has mainly assumed that TQM is welcomed by employees. With the aim of warning of the potential negative consequences of TQM on employees, this paper goes beyond previous contributions by analysing how hard and soft TQM may have different consequences on employees’ exhaustion and how managerial support may mitigate the negative repercussions.

Optimal allocation model of port emergency resources based on the improved multi-objective particle swarm algorithm and TOPSIS method

The busy maritime traffic and occurrence of ship accidents have led to a growing recognition of the necessity to maritime emergency resources allocation. The port emergency resource allocation is of significant importance for the maritime safety. This paper presents an optimized allocation model for port emergency resources based on the improved multi-objective particle swarm optimization (IMOPSO). The model introduces the crowding distance and improves the external archive update strategy. The particle inertia weight is adjusted and a dynamic mutation operator is incorporated. The entropy-weighted technique for order preference by similarity to an ideal solution method is also employed to identify the optimal solution. A comprehensive comparison with MOPSO has been presented and discussed. Three metrics of generational distance (GD), spacing (SP) and delta indicator (Δ) were employed for performance evaluation. The results demonstrated that the proposed IMOPSO algorithm exhibited superior performance and robustness, with average values of GD = 0.0386, SP = 0.0023 and Δ = 0.6468 for ZDT test functions. The model efficacy is further validated by a case study of oil spill dispersant configuration at Zhanjiang Port, China. Seven alternative schemes have been obtained, among which the optimal scheme is selected by the entropy-weighted TOPSIS method. The overall cost is potentially to be reduced by approximately 33.03 %. The present study would provide a reference for the water pollutant control and environmental management in port waters.

Cloud Network Collaborative SFC Deployment Under Heterogeneous Resource Of Power White Box Network

The construction of new electric power systems has led to a multiplication in the number of access nodes for electric power IoT information communication, accompanied by a deepening trend in business cloudification. However, due to the insufficient resource linkage and regulation capabilities of the electric power communication network on the cloud side, network side, and edge side, coupled with the lack of a convenient and unified cloud-network resource convergence and control mechanism, the existing electric power communication architecture is gradually finding it difficult to fully meet the demand for deterministic multi-service bearer. Therefore, it is necessary to evolve the original network equipment within the network toward a white box model, opening up interfaces for fine-grained sensing and full-area control, in order to provide more accurate and controllable network transmission services. In this paper, we first propose a cloud-network cooperative resource scheduling architecture for the electric power white box network. This architecture establishes a bearer network to achieve high consistency and cooperativeness of cloud-side end computing power through white box switches, uniformly schedules the global resources of the cloud-network convergence network, and improves the network service quality between cloud-side and side-side. Furthermore, we design a multi-dimensional re-source scheduling method for cloud-network synergy in the electric power white box network. This involves constructing a white box network virtualized heterogeneous resource (VHR) model and a heterogeneous resource control flow (HRCF) model. We transform the problem of merged deployment of service function chains (SFCs) into an SFC merger deployment problem by jointly controlling heterogeneous information, communication, storage, and arithmetic resources, along with the white box switch-specific pipelining resources in the white box network. We then carry out merger optimization of the same kind of function chains. Additionally, we propose a G-GS algorithm based on heuristic methods. Simulation results demonstrate that the method presented in this paper can significantly reduce the cost consumption of white box pipeline resources in the electric power white box network, thereby reducing the processing delay of SFC and improving the quality of electric power service bearing.

An improved framework for mapping and assessment of dynamics in cropping pattern and crop calendar from NDVI time series across a heterogeneous agro-climatic region.

The absence of spatial and temporal cropping information in semi-arid regions poses a significant challenge in assessing the dynamics of agricultural systems at river basin scales. Satellite remote sensing provides qualitative and quantitative information to derive vegetation dynamics over extensive areas of inherent complexities due to limitations in the availability of field data and the diverse nature of agricultural cropping practices. Utilizing phenological information derived from MODIS Normalized Difference Vegetation Index (NDVI) time series data from 2003-2004 to 2021-2022, this study derives major crop types, and cropping calendar (sowing, maturity, and harvest dates) for each season and year at 250-m resolution. This study introduces an integrated function-fitting model based on the Fast Fourier Transform (FFT) and a Lagrangian 3-point derivative-based approach to extract phenological events from the NDVI time series automatically. The derived phenological information is used in a hybrid crop classification algorithm that combines a rule-based decision tree approach (using the phenological events/dates) and a random forest classifier (using the phenological metrics) to generate the classified crop map at a river basin scale for multiple seasons and years. The implemented approach successfully captured sowing and harvesting dates for every crop growing season over 19years, with an RMSE of 9days, as observed with the available field survey data from 2015 to 2021. The classification results from this hybrid approach demonstrate an overall 82% accuracy. The proposed method shows a substantial improvement in cropping area estimation with a 60% reduction in MAE and RMSE compared to the existing algorithm. From the long time series of derived seasonal crop data (19-year analysis period), the influence of monsoonal activities and shifts on the spatial and temporal dynamics of sowing time and cropping patterns are assessed for a large river basin, demonstrating the utility of this continuous crop calendar. Further, an extensive analysis of results highlights farmers' adaptive strategies in response to dry and wet years, providing foundational insights for future studies on assessing the impacts of climate change. Hence, the hybrid framework adopted in this study for deriving a continuous crop calendar holds immense relevance for parameterizing and utilizing such information for developing river basin scale hydrologic and crop growth models for water resources planning and assessment.

THE LINK BETWEEN WORK RESOURCES AND THE FULFILMENT OF FAMILY DEMANDS: MEDIATION ANALYSIS

This study aims to analyze the relationship between work resources and the fulfilment of family demands and to test the mediation effect of work-family enrichment self-efficacy on this relationship. Previous studies focus more on the antecedents and outcomes of work-family enrichment, while the psychological mechanism of work-family enrichment stays under research. The Work-home resources model was used to looked deeper in the mechanism. A convenience sample of 233 Lithuanian employees participated in the study (85.4 per cent of women; average age 39.63 years). The scales of work resources and the scale of fulfilment of family needs have been developed on the basis of the Work-home resources model. In addition, a work-family enrichment self-efficacy scale and demographic questions were used. The results showed positive correlations between all variables tested. Work resources predict a higher level of work-family self-efficacy and the fulfilment of family demands. Meanwhile, the results showed a significant mediation effect. Study revealed that work-family enrichment self-efficacy is an important mediator that helps to better understand the mechanism of work-family enrichment.

Co-creating an appreciative working climate: discussing reasons for appreciation, forms and roles from a communication perspective

PurposeIn recent years, various socio-political developments have led to changes in the labor market that place high demands on both employees and organizations. Research has shown that strong employee–organization relationships depend partly on employees’ perceptions of appreciation at work for which different communicators are attributed with responsibility. This study draws conclusions for the role of internal communication professionals in co-creating an appreciative working climate by exploring employees’ expectations on what they want to be appreciated for, by identifying forms of appreciation and by stressing the contribution of communication professionals in meeting these expectations.Design/methodology/approachThe results base on three focus groups conducted in January 2023 with employees without leadership responsibility working in large Austrian organizations.FindingsThe analysis yields to two areas – “personal characteristics and qualities” and “work-related behaviors” – where employees expect appreciation. In six categories we capture forms of appreciation that reflect employees’ expectations and perceptions. Most of the forms can and should be addressed by managers within an organization—internal communication professionals should follow a communicative professional logic and act as strategic partners and resource providers, enablers and role models.Research limitations/implications(1) What do employees expect to be appreciated for? (2) What forms of appreciation do employees expect? (3) What role do internal communication professionals seize in co-creating an appreciative working climate?Practical implicationsBased on social exchange theory, resource theory and the job-demands resource (JD-R) model, this study conceptualizes appreciation as a prototypical generic socioemotional resource at work that is communicative in nature, and key to both motivation and health.LimitationsThere is a need to capture the perspective of managers and internal communication professionals on employees’ expectations in order to deepen the debate about communication responsibilities, practice and critical aspects of appreciation. Furthermore, a comparison of different work cultures (e.g. Asia) and other institutionalized work forms (e.g. start-ups, small enterprises, public agencies) would advance the debate.Originality/valueThe study provides in-depth knowledge of reasons for and forms of appreciation from an employee’s perspective, which is considered relevant to discuss communication responsibilities in light of dependencies.

Green IT and BYOD: driving sustainability, job performance, and well-being in remote work

Purpose This study aims to explore the impact of bring your own device (BYOD) practices on teleworkers’ job performance, work–life conflict and their implications for environmental sustainability, with a particular focus on Green IT in the post-pandemic remote work context. Drawing on the job demands–resources (JD-R) model, it examines the relationships between private technology adoption, job demands, job resources, job performance and work–life conflict, while also assessing how BYOD impacts environmental outcomes such as electronic waste reduction and carbon emissions. Design/methodology/approach The study used confirmatory factor analysis and structural equation modelling (SEM) using AMOS version 22 to evaluate seven hypotheses among 424 full-time teleworkers from various occupational sectors in Mauritius, a developing country. Findings SEM results confirm that BYOD enhances job performance and work–life conflict through increased job autonomy, workload and work pressure. BYOD and teleworking also contribute to Green IT and environmental sustainability by reducing energy consumption and electronic waste, indirectly supporting broader sustainability goals through reduced corporate device demand and lower commuting-related emissions. Practical implications Organisations should leverage BYOD policies to advance Green IT practices and improve work performance in remote settings, focusing on balancing job demands with resources like work autonomy to enhance productivity and well-being. Originality/value The findings strongly support the JD-R model in the context of remote work and BYOD, particularly in developing economies with limited infrastructure, offering insights for policies that enhance both employee well-being, Green IT and environmental sustainability.