Future Scenarios Research Articles

Simulation of Responsive Envelopes in Current and Future Climate Scenarios: A New Interactive Computational Platform for Energy Analyses

Despite the strong interest concerning the responsive façades, today there are still few built examples and few tools to assess their benefits due to the complex description of the phenomenon. Energy simulations should consider the interactions between a time-varying environment and an environment-dependent envelope, increasing the intricacy of the problem; moreover, these strong environment–envelope interlinkages increase the importance of the location and climate scenarios considered. The aim of this study is to provide a tool to easily model these phenomena in different geographical and climate contexts. For this purpose, an innovative interactive computational platform (ICP) was developed based on EnergyPlus as a simulation engine, Python as a simulation manager, and Grasshopper as a user interface. Thanks to a single user-friendly environment, the users can simply select the climate scenario, the location, the responsive technology, and its main properties to set and run the dynamic energy simulation. After an overview of the current state of the art, this study provides a description of the structure and workflow adopted for developing this platform and details regarding its functioning and input management. Finally, the platform was tested to run an evolutionary optimization of an electrochromic window control strategy in different climate scenarios.

Prediction of number of generations of serpentine leaf miner, <i>Liriomyza trifolii</i> (Burgess) (Agromyzidae: Diptera) in India assessed by CLIMEX under climate change scenario

The serpentine leaf miner, Liriomyza trifolii, is an invasive pest that affects plants, causing damage to the leaves and reducing crop yield. Number of generations of serpentine leaf miner was assessed under current and expected future climate change scenarios. The assessment was done for Representative Concentration Pathway (RCP 8.5) future climate change scenario in India. L. trifolii would have had 16-19 generations, in base line and 17-24 in 2050-time frame under future climate change in Andhra Pradesh conditions. Under Arunachal Pradesh conditions, it would have had 6-14 generations in base line and is expected to complete the same number of generations in 2050, scenario. Under Sikkim conditions 3 - 4 and 5 number of generations were assessed for present and future climate change scenario. Suitability of the localities was expressed in terms of Ecoclimatic index (EI) ranging from 0 to > 20 by combining the interaction effect of various stress indices and growth indices for the development of L. trifolii. It was observed that in temperate areas the pest incidence may increase in future, in contrast to the decreasing trend in areas where already the prevailing temperatures are near upper thresholds. It is therefore expected that number of generations of L. trifolii would increase with the rising temperatures under climate change situations.

Natural and anthropogenically driven change of organic carbon burial rate in two alpine lakes from the southeastern margin of the Tibetan Plateau

The rate of organic carbon (OC) burial in lakes depends considerably on natural and anthropogenic factors. Delineating how and to what extent potential drivers shape a lake’s OC burial rate is crucial for anticipating OC sequestration under future environmental change scenarios. Alpine lakes provide valuable opportunities for studying the influence of climate warming and atmospheric nitrogen (N) deposition on OC burial in lakes, owing to the lack of human activities in their catchments; however, this aspect has not been sufficiently documented. Here, the OC burial rate was reconstructed in two alpine lakes (Heihai and Jiren) from the southeastern margin of the Tibetan Plateau over the past ∼ 160 years, and the associated drivers were identified by resolving the temporal trends in organic matter (OM) input from specific sources to lake sediments via paleolimnological methods. The results demonstrated a consistently low OC burial rate (6.21–10.86 g m−2 yr−1) in Lake Heihai. The low hydrogen index (HI), moderate Paq, and high long-chain n-alkane flux revealed that submerged macrophytes and terrestrial plants are major contributors to the sequestrated OC. The notable decrease in the OC burial rate after 1980 was hypothesized to be caused by regional climate warming during this period because a greater export of terrestrial materials under such a climate can inhibit light penetration, diminishing submerged macrophyte productivity and OM input. In contrast, the synchronous input of higher amounts of terrestrial plant OM was largely degraded owing to the increased water temperature and the intensification of water column stratification. In Lake Jiren, a notably high OC burial rate (13.82–46.75g m−2 yr−1) was observed. The high HI, Paq, and short-chain n-alkane flux showed that phytoplankton and submerged macrophytes were the major contributors to the sequestrated OC. The two-phase increase in the OC burial rate in this lake, including a slow increase after 1947 and a rapid increase after 1983, might have resulted from strengthening aquatic primary productivity and OM input, driven by anthropogenic intensification of nutrient emissions, especially reactive N, from highly urbanized areas and the subsequent long-term atmospheric transport and deposition of these materials over the lake basin. A comparative analysis of the results between the two lakes suggested that atmospheric N deposition has a stronger influence on the OC burial than climate warming. These drivers affect the OC burial rate by altering aquatic productivity rather than the terrestrial OM input. This study provides a basic for predicting future OC burial scenarios in warmer climates with more intense anthropogenic N emissions.

A Global Analysis of Historical and Future Changes in Mediterranean Climate‐Type Regions

ABSTRACTMediterranean climate‐type regions (MCRs) are characterised by warm‐to‐hot dry summers and mild‐wet winters. These regions are typically found on the western or southern edges of continents, for example, in the Mediterranean Basin, the west coast of North and South America, southern Africa and southwest Australia. The MCRs are vulnerable to climate variability and change related to their unique characteristics, such as pronounced rainfall seasonality and prolonged hot and dry summers. Based on historical observations and CMIP6 climate projections, we apply an empirical bio‐climatic assessment of how the geographic distribution of MCRs has changed during the last century and how these zones will be further impacted under continued warming. Results indicate a poleward and eastward expansion of MCRs in the Mediterranean Basin, North America‐California and South America‐Central Chile regions. For parts of Southern Africa and Southern Australia, a retreat of the MCR margins and an expansion of more arid climate zones are projected. These shifts are particularly profound according to high emission and radiative forcing pathways and future scenarios. The warming in MCRs is projected to accelerate (e.g., mean regional warming of up to 5.5°C under a 4°C global warming scenario), and precipitation will decrease by about 5%–10% for every additional degree of global warming. One exception is the California MCR, where rainfall will likely increase. Such changes can challenge water resources, food security and other aspects of human livelihood and ecosystems in these unique geographical zones.

Prediction of Potential Suitable Distribution Areas for Northeastern China Salamander (Hynobius leechii) in Northeastern China

The Northeastern China Salamander (Hynobius leechii) is classified as a rare, nationally protected Class II wild animal in China. Its population is declining, and its habitat is deteriorating. This study aimed to predict the distribution of suitable habitats for the Northeastern China Salamander under both current and future climate scenarios, utilizing the MaxEnt model optimized through ENMeval parameters. Species distribution data were collected from field surveys, existing literature, amphibian records in China, and the Global Biodiversity Information Network. A total of 97 records were compiled, with duplicate records within the ENMTools grid unit removed, ensuring that only one record existed within every 5 km. Ultimately, 58 distinct distribution points for the Northeastern China Salamander were identified. The R software package ‘ENMeval 2.0’ was employed to optimize the feature complexity (FC) and regularization multiplier (RM), and the optimized model was applied to assess the suitable distribution regions for the Northeastern China Salamander under present and future climate conditions. The findings indicated that rainfall and temperature are the primary environmental factors influencing Hynobius. Currently, the suitable habitat for the Northeastern China Salamander constitutes 6.6% of the total area of Northeastern China. Projections for the periods of 2050 and 2070 suggest that suitable habitats for the Northeastern China Salamander will continue to expand towards higher latitudes across three climate scenarios. While this study focuses solely on climate change factors and acknowledges certain limitations, it serves as a reliable reference and provides essential information for the distribution and conservation of the Northeastern China Salamander.

Best Practices in Supporting Inpatient Communication With Technology During Visitor Restrictions: An Integrative Review.

Since the onset of the COVID-19 pandemic, healthcare workers around the world have experimented with technologies to facilitate communication and care for patients and their care partners. Our team reviewed the literature to examine best practices in utilizing technology to support communication between nurses, patients, and care partners while visitation is limited. We searched four major databases for recent articles on this topic, conducted a systematic screening and review of 1902 articles, and used the Johns Hopkins Nursing Evidence-Based Practice for Nurses and Healthcare Professionals Model & Guidelines to appraise and translate the results of 23 relevant articles. Our evaluation yielded three main findings from the current literature: (1) Virtual contact by any technological means, especially video visitation, improves satisfaction, reduces anxiety, and is well-received by the target populations. (2) Structured video rounding provides effective communication among healthcare workers, patients, and offsite care partners. (3) Institutional preparation, such as a standardized checklist and dedicating staff to roles focused on facilitating communication, can help healthcare workers create environments conducive to therapeutic virtual communication. In situations that require healthcare facilities to limit visitation between patients and their care partners, the benefits of virtual visitation are evident. There is variance in the types of technologies used to facilitate virtual visits, but across all of them, there are consistent themes demonstrating the benefits of virtual visits and virtual rounding. Healthcare institutions can prepare for future limited-visitation scenarios by reviewing the current evidence and integrating virtual visitation into modern healthcare delivery.

Boron to salinity ratios in the Fram Strait entering the Central Arctic: The role of sea ice formation and future predictions

The Arctic Ocean's sea ice loss dynamically impacts carbon uptake potential, as assessed through measured carbonate parameters, such as total alkalinity. In the open ocean, boron (B) is the third largest contributor to alkalinity via borate and is usually accounted for through the conservative boron to salinity ratio (B/S), and not directly measured. Here, we present findings on non-conservative boron dynamics, that results in significant B/S deviations, observed in ice melt zone waters, snow, slush, brine, and annual sea ice (n = 169) in the Fram Strait entering the Central Arctic. These samples were collected during the onset of the melt season on the 2023 ARTofMELT expedition, covering a wide practical salinity range (2–59). Barring snow, the average B/S ratio across the study was 0.1321 ± 0.0032 mg kg−1 ‰−1, similar to the mean B/S ratio measured amongst several polar water masses near Iceland, as well as the accepted B/S for other ocean regions. Results indicate minor deviations from accepted B/S ratios (indicating conservative behavior) across the sample practical salinity range and reflect an uncertainty in the borate contribution to total alkalinity of less than 2.9 μmol kg−1 at in-situ temperatures. B fractionation appears to occur during sea ice formation, causing greater B in the sea ice reservoir whereas brine, slush, lead, and under-ice water reservoirs are depleted in B. As such, under-ice and lead, brine, and slush samples all had measured B/S ratios (0.1305 ± 0.0011, 0.1305 ± 0.0018, and 0.1304 ± 0.0017 mg kg−1 ‰−1, respectively) lower than the established ratio whereas the average sea ice B/S ratio (0.1331 ± 0.0035 mg kg−1 ‰−1) was closest to accepted values (0.1336 ± 0.0005 mg kg−1 ‰−1). Arctic open ocean samples also had a lower B/S ratio (0.1304 ± 0.0014 mg kg−1 ‰−1). Our findings, together with a previous Arctic B ice study, suggest that B (probably in the form of B(OH)4−) is incorporated into authigenic CaCO3 minerals, replacing CO32− within the mineral lattice during sea ice formation. This process consequentially lowers the B/S ratio in the open Arctic Ocean, compared to the established global ocean ratio. Nevertheless, the incorporation of B into the sea ice reservoir does not fully account for the deficit of B in the Arctic Ocean samples, suggesting further accounting of B Arctic pathways is necessary. In future climate scenarios involving increased sea ice melt, the transition from multiyear to annual sea ice, permafrost thaw, and increased riverine discharge, the behavior of B in the Arctic Ocean is expected to become more dynamic.

How to Achieve the Ecological Sustainability Goal of Ecologically Fragile Areas on the Qinghai-Tibet Plateau: A Multi-Scenario Simulation of Lanzhou-Xining Urban Agglomerations

The future of the ecologically fragile areas on the Qinghai-Tibet Plateau (QTP) is a matter of concern. With the implementation of the Western Development Strategy, the Lanzhou-Xining Urban Agglomeration (LXUA) has encountered conflicts and compromises between urban expansion, ecological protection, and farmland protection policies in the rapid development of the past 2 decades. These deeply affect the land use layout, making the ecological sustainable development of the ecologically fragile areas of the QTP a complex and urgent issue. Exploring the impact of different policy-led land use patterns on regional ecosystem services is of great significance for the sustainable development of ecologically fragile areas and the formulation of relevant policies. Following the logical main line of “history-present-future”, the Patch-level Land Use Simulation (PLUS) model, which explores potential factors of historical land use, and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model were used to construct three future scenarios for the modernization stage in 2031 dominated by different land use policies in this study. These scenarios include the Business-as-Usual Scenario (BS), the Cropland Protection Scenario (CP), and the Ecological Protection Scenario (EP). The study analyzed and predicted land use changes in the LXUA from 2001 to 2031 and assessed carbon storage, habitat quality at different time points, and water yield in 2021. The results indicated that land use changes from 2001 to 2021 reflect the impacts and conflicts among the Western Development Strategy, ecological protection policies, and cropland preservation policies. In 2031, construction land continues to increase under all three scenarios, expanding northwards around Lanzhou, consistent with the actual “northward expansion” trend of Lanzhou City. Changes in other land uses are in line with the directions guided by land use policy. By 2031, carbon storage and habitat quality decline under all scenarios, with the highest values observed in the EP scenario, the lowest carbon storage in the BS scenario, and the lowest habitat quality in the CP scenario. Regarding water yield, the LXUA primarily relies on alpine snowmelt, with construction land overlapping high evapotranspiration areas. Based on the assessment of ecosystem services, urban expansion, delineation of ecological red lines, and improvement of cropland quality in the LXUA were proposed. These findings and recommendations can provide a scientific basis for policy makers and planning managers in the future.

A Machine Learning Approach to Adapt Local Land Use Planning to Climate Change

The impacts on living conditions and natural habitats deriving from planning decisions require complex analysis of cross-acting factors, which in turn require interdisciplinary data. At the municipal level, both data collection and the knowledge needed to interpret it are often lacking. Additionally, climate change and species extinction demand rapid and effective policies in order to preserve soil resources for future generations. Ex-ante evaluation of planning measures is insufficient owing to a lack of data and linear models capable of simulating the impacts of complex systemic relationships. Integrating machine learning (ML) into systemic planning increases awareness of impacts by providing decision-makers with predictive analysis and risk mitigation tools. ML can predict future scenarios beyond rigid linear models, identifying patterns, trends, and correlations within complex systems and depicting hidden relationships. This article focuses on a case study of single-family houses in Upper Austria, chosen for its transferability to other regions. It critically reflects on an ML approach, linking data on past and current planning regulations and decisions to the physical environment. We create an inventory of categories of areas with different features to inform nature-based solutions and backcasting planning decisions and build a training dataset for ML models. Our model predicts the effects of planning decisions on soil sealing. We discuss how ML can support local planning by providing area assessments in soil sealing within the case study. The article presents a working approach to planning and demonstrates that more data is needed to achieve well-founded planning statements.

MARKETING DIGITAL PARA STARTUPS: MARKETING DIGITAL PARA MICROEMPRESÁRIOS, UMA IDEIA REVOLUCIONÁRIA PARA ALCANÇAR O SUCESSO

Who never faced lines to make a payment or even to buy a certain product. Some time ago we did this, wasting hours in market lines, banks, bookstores and airports. Nowadays we can do all of this, without having to queue, without leaving home or watching a movie; reducing waiting time, being able to receive at home. All of this is in the consumer's possession, through his Smartphone device. As a result, the importance of developing and working on an action plan with digital marketing grows; because every person who has a device your company will be there too. It is possible to ask scientifically how Digital Marketing is a factor influencing consumer behavior in the Brazilian economic sector, how often consumers buy over the internet. What companies face today is not a lack of inputs (raw materials and components), or service companies. And, yes, the lack of loyal customers (followers). Contemporary companies can manufacture products beyond what customers can consume. This increases the level of competition in the competitive market, and consumers are the winners. The success of an electronic business depends on many factors. It is not enough for the company to have a welltructured website, with an attractive design and the best technologies. Companies and startups must go beyond the perception of customers, they must engender a profitable reciprocal familiarity. The company needs to define its position in the market, and envision possible future scenarios. Digital Marketing is an undeniable reality that has been joining forces with traditional commerce, a versatile means of communication that integrates sales opportunities, customer relations and positive word of mouth advertising.

A IMPORTÂNCIA DA GOVERNANÇA CORPORATIVA PARA A GESTÃO FINANCEIRA DAS ORGANIZAÇÕES EMPRESARIAIS: UMA IDEIA REVOLUCIONÁRIA PARA ALCANÇAR O SUCESSO

This study analyzed the relationship between Financial Management and Corporate Governance of Micro and Small Companies and their financial performance. To know the reasons that lead a micro and small company to close. By not carrying out an investment plan, spending more than what is actually invoiced and the difficulty of controlling accounts is something that many entrepreneurs suffer. With the world economy and international trade increasingly integrated and diffuse. Micro and small companies are in a competitive rivalry between competitors, and having good quantitative and qualitative methods for analyzing decisions are some performance indicators (KPIs). From small organizations to large multinationals in the world, they continually seek a predictable and profitable future scenario. So that they can control or anticipate any eventualities through financial governance. In the financial market, there is a growing search by organizations for more information and data to assist in their decision-making arrangements. Financial Management has been increasing its area of expertise in terms of needs: cash; planning; capital expenditure research and decisions. Financial management as a refined tool becomes a privilege in the organization's decision making, envisioning future scenarios, which if used correctly leverages profits.

Markov Chain Analysis of Land-use Changes in India and Maharashtra

Dynamics of Agriculture resembles the history of agriculture in India which examines the emphasizing significance to the nation's legacy, culture and civilization. India's agriculture changed after independence from a food-scarce nation to one that exports food this comes true primarily due to the result of scientific advancements. The present study is based on secondary data with the use of Markov Chain analysis to ascertain land-use changes in India and Maharashtra state. Changes in land use brought on by agriculture, urbanization and environmental factors significantly impact resource management and sustainability. We build a Markov Chain model with secondary land utilization data from government reports to measure the transition probabilities between various land use categories over time. The Markov chain model is easy to understand and communicate. It effectively captures transitions between land-use changes over time. The model works with limited data as compared to other complex models, making it accessible for studies. The results of the study emphasize dynamic interactions between various land-use patterns in India and Maharashtra. There we have concluded a stable land-use changing pattern. A trend towards intensive cropping has been observed during this study. This study reveals important trends in land conversion, most notably the growth of urban areas at the expense of forested and agricultural areas. The predictive abilities of model highlight the significance of well-informed policy-making for sustainable land management by offering insights into potential future land use scenarios.

Quantum-Like Approaches Unveil the Intrinsic Limits of Predictability in Compartmental Models.

Obtaining accurate forecasts for the evolution of epidemic outbreaks from deterministic compartmental models represents a major theoretical challenge. Recently, it has been shown that these models typically exhibit trajectory degeneracy, as different sets of epidemiological parameters yield comparable predictions at early stages of the outbreak but disparate future epidemic scenarios. In this study, we use the Doi-Peliti approach and extend the classical deterministic compartmental models to a quantum-like formalism to explore whether the uncertainty of epidemic forecasts is also shaped by the stochastic nature of epidemic processes. This approach allows us to obtain a probabilistic ensemble of trajectories, revealing that epidemic uncertainty is not uniform across time, being maximal around the epidemic peak and vanishing at both early and very late stages of the outbreak. Therefore, our results show that, independently of the models' complexity, the stochasticity of contagion and recovery processes poses a natural constraint for the uncertainty of epidemic forecasts.

Assessment of Urban Resilience to Floods: A Spatial Planning Framework for Cities

Urbanization-led economic growth drives infrastructure investments and population accumulation in cities, hence exploiting natural resources at an extreme rate. In this context, coastal cities have become vulnerable to climate change-induced extreme weather events and human-made disasters in recent history, where effective measures to improve the resilience of cities are pivotal for developing sustainable living environments. This study proposes a framework for assessing urban resilience to natural disasters (floods) using bottom-up spatial interactions among natural, physical, and social systems within cities and regions. It is noted that seminal studies focus on either the mitigation or adaptation strategies within urban environments to assess disaster resilience, where limited multidisciplinary and operational models hinder evaluations at the city scale. Therefore, urban system interactions and quantifiable parameters proposed in this framework are essential for policymakers and disaster management agencies in the timely allocation of resources to optimize the recovery process. Moreover, spatial planning agencies can adopt resilience mapping to identify the potential risk zones and orient sustainable land use management. Urban resilience can be embodied in spatial strategies with the operational framework proposed here, and future urban growth scenarios can be tested in multiple disaster conditions.

Measuring rising heat and flood risk along the belt-and-road initiative

China’s global infrastructure financing flagship, the Belt and Road Initiative (BRI) encompasses countries hosting over 60% of the global population and one-third of worldwide GDP. It is based mainly on long-term loans that will mature decades into the future, and timely repayments are only possible if they remain commercially viable. But despite its vast global scope, little is known about the climate risks that could imperil the operations of BRI projects over the next few decades, and, consequently, threaten their long-term sustainability. We narrow this gap by estimating the impacts of future climate change on 217 BRI projects across 70 countries and 9 sectors in two dimensions. First, the effects of increased heat stress on human physical work capacity are calculated using the wet bulb globe temperature and an assessment of the workload for each selected BRI project. Second, the potential structural damages from more frequent flooding incidents are measured by return period (RP), where a shorter RP signals heightened risk. Both have direct impacts on human productivity and infrastructural integrity, which are essential to maintaining the operational viability and financial stability of BRI projects. We compared projected changes on both measures for the mid- and late-twentieth centuries (2041–2060 and 2081–2100) to the historical baseline (1981–2010). We found that BRI projects face escalating vulnerability to climatic risks on both counts. The results underscore a broad variance across different future carbon emission scenarios measured under the Shared Socioeconomic Pathways (including SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). BRI’s aggregated climatic risks are substantially elevated under a high carbon emission scenario compared to a low emission scenario. By the end of the twentieth century, labor workability under SSP3-7.0 (31%) could potentially decrease three times more compared to SSP1-2.6 (10%). Under an intermediate-emission scenario (SSP2-4.5), floods with a historical return period of 10 years could have a return period of 5 years in the future. Significantly hampering the utilization and economic return generation potential of infrastructure projects. In addition, regional geography contributes to risk heterogeneity, with 100-year floods occurring every 15 years in South Asia and every 24 years in Sub-Saharan Africa. Such climate risk implications, potentially overlooked by development financiers, represent significant risks to the sustenance of the BRI, estimated to be worth $1 trillion.

A Coupled CA Urban Development Model (UDM) and Urban Fabric Generator (UFG) for the Assessment of Climate Hazards on Future Urban Development

Abstract. Cellular Automata (CA) spatial models have become a de facto means by which to simulate future scenarios of land use activity, particularly urban development. Increasingly, such models are being employed within large scale climate impact, adaption and resilience studies to provide future scenarios of land use change and urban development, facilitating the calculation of the economic impact of future climate hazards and development land use adaption options. However, many spatial CA models only provide information on whether land has undergone a transition from one use/activity to a new one. In the case of urban development, they are unable to provide information on the spatial pattern of new development at an intra-cell level of spatial fidelity. However, in many cases such information is important as the spatial impacts of hazards and the adaption and resilience of new urban development will be dependent on the precise spatial configuration of buildings, roads and urban green space. In this paper an Urban Fabric Generator (UFG) is presented that takes the outputs of an Urban Development Model (UDM) and simulates plausible spatial configurations of buildings, roads and urban green space. The utility of the UFG is demonstrated via two flooding case studies, where generated spatial patterns of urban form are used to parameterise a hydrodynamic pluvial flood model that evaluates the impact of future climate driven rainfall on property damage and the utility of infrastructure investment with regards to improving surface water flood resilience.

Microbial carbon utilization in a boreal lake under the combined pressures of brownification and eutrophication: insights from a field experiment

AbstractClimate and land use changes can increase terrestrial runoff to aquatic systems, leading to brownification and eutrophication in northern boreal lakes. Brownification may boost bacterial respiration and production, while eutrophication can enhance primary production and algal blooms. However, their combined effects on basal producers and bacterial carbon utilization are less understood. This study explores the combined impacts of the two stressors: brownification and eutrophication on microbial dynamics in Lake Bolmen. Utilizing a field mesocosm experimental design, treatments received different combinations of organic matter (OM) and inorganic nutrients to simulate predicted future scenarios. Results showed that OM additions significantly increased bacterial production and respiration, regardless of nutrient additions. Nutrient additions enhanced bacterial production but did not affect respiration. Both nutrients and OM stimulated bacterial growth efficiency. Labile carbon from DOM was the main driver of higher bacterial respiration and short-term production increases. Fluorescence data indicated that the combination of brownification and eutrophication led to higher terrestrial DOM utilization than each stressor alone. The study suggests that future boreal lakes may become more heterotrophic, thus increasing CO2 release. These findings highlight the complex interactions between DOM and nutrients and underscore the importance of considering multiple stressors in lake management and mitigation strategies.

BUSINESS INTELLIGENCE: TOMADA DE DECISÃO PARA MICROEMPRESÁRIOS, UMA IDEIA REVOLUCIONÁRIA PARA ALCANÇAR O SUCESSO

With the world economy and international trade increasingly integrated and diffuse. Companies find a competitive rivalry between competitors, and having good quantitative and qualitative methods for making decisions are some performance indicators. From small organizations to large multinationals in the world, they continually seek a predictable and profitable future scenario. So that they can control or anticipate any eventualities. In the commercial market there is a growing search by organizations for more information and data to assist in decision making. On the other hand, there is an increase in Information Technology (IT) tools, capable of managing, analyzing, generating reports and decisive graphics for decision making (whether for investments; purchases; contracting services; projects and events). Business Intelligence (BI) decision making is accurate, and its information (dice + evidence = strategic decision), based on dynamic statistical data and its environment meets business demands. Implementation project managers, both in BI and ERP, need to be aware of the impact of these systems, otherwise the implementation will fail, as in the Hershey’s case study. The benefits that ERP

BUSINESS INTELLIGENCE: TOMADA DE DECISÃO PARA MICROEMPRESÁRIOS, UMA IDEIA REVOLUCIONÁRIA PARA ALCANÇAR O SUCESSO

With the world economy and international trade increasingly integrated and diffuse. Companies find a competitive rivalry between competitors, and having good quantitative and qualitative methods for making decisions are some performance indicators. From small organizations to large multinationals in the world, they continually seek a predictable and profitable future scenario. So that they can control or anticipate any eventualities. In the commercial market there is a growing search by organizations for more information and data to assist in decision making. On the other hand, there is an increase in Information Technology (IT) tools, capable of managing, analyzing, generating reports and decisive graphics for decision making (whether for investments; purchases; contracting services; projects and events). Business Intelligence (BI) decision making is accurate, and its information (dice + evidence = strategic decision), based on dynamic statistical data and its environment meets business demands. Implementation project managers, both in BI and ERP, need to be aware of the impact of these systems, otherwise the implementation will fail, as in the Hershey’s case study. The benefits that ERP and BI systems bring are numerous and the results are reflected positively within the

Future Consumption Scenarios of Power Sector in Bangladesh

Future electricity demand is an essential prerequisite for planning the expansion of a power system. The purpose of this paper is to provide a forecast of electricity consumption in Bangladesh. Forecast is done here total as well as sector-wise consumption up to 2040 considering the base year 2009. The time series analysis to find the trend line by the method of Least Squares (LS) is applied in this study. We accumulated data from the annual reports of the Bangladesh Power Development Board for the years 2009 to 2023 and used that for forecasting purposes. For the convenient and policy purposes, the forecast is presented for every five years interval. The findings have significant implications with respect to energy conservation and economic development. As the study differentiated sector-wise projected growth of electricity consumption in Bangladesh, it has implications for the planners related to electricity distribution system. The findings can create awareness among the planners of power system expansion in Bangladesh to meet the continuous future development demand.