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Across plant species and biomes, a conserved set of leaf traits govern the economic strategy used to assimilate and invest carbon. As plants age, they face new challenges that may require shifts in this leaf economic strategy. In this study, we investigate the role of the developmental transition, vegetative phase change (VPC), in altering carbon economics as plants age. We used overexpression of microRNA 156 (miR156), the master regulator of VPC, to modulate the timing of VPC in Populus tremula x alba, Arabidopsis thaliana and Zea mays to understand the impact of this transition on leaf economic traits, including construction cost, payback time and return on investment. Here, we find that VPC causes a shift from a low-cost, quick return juvenile strategy to a high-cost, high-return adult strategy. The juvenile strategy is advantageous in light-limited conditions, whereas the adult strategy provides greater returns in high light. The transition between these strategies is correlated with the developmental decline in the level of miR156, suggesting that is regulated by the miR156/SPL pathway. Our results provide an ecophysiological explanation for the existence of juvenile and adult leaf types and suggest that natural selection for these alternative economic strategies could be an important factor in plant evolution., (© 2022 John Wiley & Sons Ltd.)

The need for 24/7 operation, and the increasing requests of high-quality healthcare services contribute to framing healthcare facilities as a complex topic, also due to the changing and challenging environment and huge impact on the community. Due to its complexity, it is difficult to properly estimate the construction cost in a preliminary phase where easy-to-use parameters are often necessary. Therefore, this paper aims to provide an overview of the issue with reference to the Italian context and proposes an estimation framework for analyzing hospital facilities' construction cost. First, contributions from literature reviews and 14 case studies were analyzed to identify specific cost components. Then, a questionnaire was administered to construction companies and experts in the field to obtain data coming from practical and real cases. The results obtained from all of the contributions are an overview of the construction cost components. Starting from the data collected and analyzed, a preliminary estimation tool is proposed to identify the minimum and maximum variation in the cost when programming the construction of a hospital, starting from the feasibility phase or the early design stage. The framework involves different factors, such as the number of beds, complexity, typology, localization, technology degree and the type of maintenance and management techniques. This study explores the several elements that compose the cost of a hospital facility and highlights future developments including maintenance and management costs during hospital facilities' lifecycle. [ABSTRACT FROM AUTHOR]

Plan shape indices are based on the geometry of the plan shape rather than on empirical data, and are problematic as they embrace implicit assumptions that are not tested empirically nor justified theoretically. Empirical research using data in Hong Kong confirms that these plan shape indices are much poorer predictors of unit construction costs than the variables used to construct the indices. This study also develops a method for constructing a plan shape index that is free from the unjustified assumptions implicit in existing plan shape indices; it involves an empirical cost model. Different functional specifications of the cost models are tested. The result rejects the linear model and other special case models such as semi-log and log-linear models. However, the reciprocal model is not rejected. This result suggests that a linear plan shape index can predict the amount of floor area that can be constructed with a fixed sum of money better than the construction cost per floor area. [ABSTRACT FROM AUTHOR]

A simple neoclassical production function model is used to determine the incremental cost of each floor as building height increases. This analytic method provides an alternative to earlier studies using computer simulation and more cumbersome attempts at measuring the cost variation directly. By modelling construction costs analytically, it is possible to identify and assess the impacts of particular variables more explicitly. There are two main findings. First, cost variation with building height is not only affected by technology; building design, demand and institutional factors also play important roles. Secondly, the model may be used to estimate construction cost variation with building height from readily available data. In this sense it is an improvement over previous methods using simulated or direct cost measurement. [ABSTRACT FROM AUTHOR]

The main purpose of the current study was to design less costly forest roads using cost zoning map. For this purpose, the most important effective factors on cost of forest road construction were weighted using the Analytical Hierarchy Process (AHP). Five factors, terrain slope, hydrology, geology formations, soil texture and road slope, were weighted using the AHP. The cost zoning map was developed after weighting the supposed factors and overlay their corresponding map in ESRI Arc GIS 9.3 environment. In Next step, two variants of forest road were planned to connect the start point to the end point, using a 1) Shortest Path (SP) algorithm and 2) a skill expert. The results showed that the length and the cost of the variant planned by SP algorithm were 55% and 65% lower than the path planned by the expert before designing in the field, respectively. The results of the study after designing both planned variants in the field, demonstrated that the length and the cost of the SP-based feasible path were 19% and 21% lower than the expert-based variants, respectively. This means the SP saved 916000000 Rials. The results showed that using the zoning map cost in combination with a shortest path algorithm can lead to a more favorite layout of the forest roads than traditional methods of planning.

Grain sorghum [Sorghum bicolor (L.) Moench, a C4 crop] and soybean [Glycine max (L.) Merr. cv. Stonewall, a C3 crop] plants were grown in ambient (c. 360 μl l-1) and twice-ambient (c. 720 μl l-1) CO2 levels in open-top chambers in soil without root constriction. Plant dry mass, energy content, composition and construction cost (i. e. amount of carbohydrate required to synthesize a unit plant dry mass) were assessed at the end of the growing season. Elevated CO2 (a) increased phytomass accumulation (kg per plant) in both species, (b) had little affect on energy concentration (MJ kg-1 plant) but caused large increases in the amount of plant energy per ground area (MJ m-2 ground), and (c) did not alter specific growth cost (kg carbohydrate kg-1 plant growth) but greatly increased growth cost per ground area (kg carbohydrate m-2 ground) because growth was enhanced. For soybean, twice-ambient CO2 resulted in a 50% increase in the amount of nitrogen and energy in grain (seed plus pod) per ground area. This response to elevated CO2 has important implications for agricultural productivity during the next century because the rate of human population growth is exceeding the rate of increase of land used for agriculture so that future food demands can only be met by greater production per ground area. [ABSTRACT FROM AUTHOR]

We grew loblolly and ponderosa pine seedlings in a factorial experiment with two CO2 partial pressures (35 and 70 Pa), and two nitrogen treatments (1.0 and 3.5 mol m-3 NH4), for one growing season to examine the effects of carbon and nitrogen availability on leaf construction cost. Growth in elevated CO2 reduced leaf nitrogen concentrations by 17 to 40%, and increased C:N by 22 to 68% Elevated N availability increased leaf N concentrations and decreased C:N. Non-structural carbohydrates increased in high-CO2grown loblolly seedlings, except in fascicles from low N, and in ponderosa primary and fascicle leaves grown in high N. In loblolly, increases in starch were nearly 2-fold greater than the increase in soluble sugars. In ponderosa, only the soluble sugars were affected by CO2 Leaf construction cost (g glucose g -1dm) varied by 9.3% across all treatments. All of the variation in loblolly leaf construction cost could be explained by changes in non-structural carbohydrates. A model of the response of construction cost to changes in the mass of different biochemical fractions suggests that the remainder of the variation in ponderosa, not explained by non-structural carbohydrates, is probably attributable to changes in lignin, phenolic or protein concentrations. [ABSTRACT FROM AUTHOR]

We present a method for estimating the construction costs of plant tissues from measurements of heat of combustion, ash content, and organic nitrogen content. The method predicts glucose equivalents, the amount of glucose required to provide carbon skeletons and reductant to synthesize a quantity of organic product. Glucose equivalents have previously been calculated from the elemental composition of tissue. We define construction cost as the amount of glucose required to provide carbon skeletons, reductant and ATP for synthesizing the organic compounds in a tissue via standard biochemical pathways. The fraction of the total construction cost of a compound or tissue (excluding costs of transporting compounds) that is reflected in its glucose equivalents is the biosynthetic efficiency (EB). This quantity varies between 0.84 and 0.95 for tissues with a wide range of compositions. Using the new method, total construction cost can be estimated to +6% of the value obtained from biochemical pathway analysis. Construction costs of leaves of three chaparral species were estimated using the proposed method and compared to previously published values, derived using different methods. Agreement among methods was generally good. Differences were probably due to a combination of inaccuracy in the estimated biosynthetic efficiency and technical difficulties with biochemical analysis, one of the older methods of determining construction cost. [ABSTRACT FROM AUTHOR]

To determine whether long-term growth in enriched CO2 atmospheres changes the woody tissue respiration component of aboveground carbon budgets, we measured woody tissue respiration of stems of 3-year-old ponderosa pine (Pinus ponderosa Laws.) grown in ambient (350 ppm) or twice ambient (700 ppm) atmospheric CO2 concentrations in open-top field chambers located in Placerville, CA. Total respiration rate was measured by gas exchange, and construction respiration was calculated from the construction cost, percent carbon of stem samples and relative growth rate. Maintenance respiration was determined as the difference between total and construction respiration. The Q10 of respiration was greater in stems grown in elevated CO2 than in stems grown in ambient CO2 (2.20 versus 1.67). As a result, mean daily respiration per unit volume of wood modeled for the month of September was greater in trees growing in elevated CO2 than in ambient CO2 (46.75 versus 40.45 mol m−3 day−1). These effects of atmospheric CO2 concentration were not the result of differences in relative growth rate. Calorimetric analyses of woody tissue construction cost indicated no difference between treatments; however, trees in the elevated CO2 treatment showed a 1% lower carbon concentration than trees in the ambient CO2 treatment. Estimates of construction respiration did not differ between treatments, confirming that the treatment differences in mean daily respiration rate were attributable to the maintenance component. Under future predicted atmospheric conditions, changes in the maintenance respiration of woody tissue may lead to an increase in the respiration component of whole-plant carbon budgets of ponderosa pine. Our results suggest that potential increases in the maintenance component of stem respiration should be considered when modeling the response of forest stand growth to enriched CO2 atmospheres. [ABSTRACT FROM AUTHOR]

We examined the effects of climate and allocation patterns on stem respiration in ponderosa pine ( Pinus ponderosa) growing on identical substrate in the cool, moist Sierra Nevada mountains and the warm, dry, Great Basin Desert. These environments are representative of current climatic conditions and those predicted to accompany a doubling of atmospheric CO2, respectively, throughout the range of many western north American conifers. A previous study found that trees growing in the desert allocate proportionally more biomass to sapwood and less to leaf area than montane trees. We tested the hypothesis that respiration rates of sapwood are lower in desert trees than in montane trees due to reduced stem maintenance respiration (physiological acclimation) or reduced construction cost of stem tissue (structural acclimation). Maintenance respiration per unit sapwood volume at 15°C did not differ between populations (desert: 6.39 ± 1.14 SE μmol m−3 s−1, montane: 6.54 ± 1.13 SE μmol m−3 s−1, P = 0.71) and declined with increasing stem diameter ( P = 0.001). The temperature coefficient of respiration ( Q10) varied seasonally within both environments ( P = 0.05). Construction cost of stem sapwood was the same in both environments (desert: 1.46 ± 0.009 SE g glucose g−1 sapwood, montane: 1.48 ± 0.009 SE glucose g−1 sapwood, P = 0.14). Annual construction respiration calculated from construction cost, percent carbon and relative growth rate was greater in montane populations due to higher growth rates. These data provide no evidence of respiratory acclimation by desert trees. Estimated yearly stem maintenance respiration was greater in large desert trees than in large montane trees because of higher temperatures in the desert and because of increased allocation of biomass to sapwood. By analogy, these data suggest that under predicted increases in temperature and aridity, potential increases in aboveground carbon gain due to enhanced photosynthetic rates may be partially offset by increases in maintenance respiration in large trees growing in CO2-enriched atmospheres. [ABSTRACT FROM AUTHOR]

Seedlings of loblolly pine ( Pinus taeda L.) were grown under varying conditions of soil nitrogen and atmospheric carbon dioxide availability to investigate the interactive effects of these resources on the energetic requirements for leaf growth. Increasing the ambient CO partial pressure from 35 to 65 Pa increased seedling growth only when soil nitrogen was high. Biomass increased by 55% and photosynthesis increased by 13% after 100 days of CO enrichment. Leaves from seedlings grown in high soil nitrogen were 7.0% more expensive on a g glucose g dry mass basis to produce than those grown in low nitrogen, while elevated CO decreased leaf cost by 3.5%. Nitrogen and CO availability had an interactive effect on leaf construction cost expressed on an area basis, reflecting source-sink interactions. When both resources were abundant, leaf construction cost on an area basis was relatively high (81.8±3.0 g glucose m) compared to leaves from high nitrogen, low CO seedlings (56.3±3.0 g glucose m) and low nitrogen, low CO seedlings (67.1±2.7 g glucose m). Leaf construction cost appears to respond to alterations in the utilization of photoassimilates mediated by resource availability. [ABSTRACT FROM AUTHOR]

Photosynthetic capacities and respiration rates of Alocasia macrorrhiza leaves were measured for 4 weeks following reciprocal transfers between high (20% of full sun) and low (1% of full sun) light environments. Photosynthetic capacities and respiration rates of mature, high-light leaves were 1.7 and 4.5 times those of low-light leaves, respectively. Following transfer, respiration rates adjusted within 1 week to those characteristic of plants grown in the new environment. By contrast, photosynthetic capacities either did not adjust or changed only slowly following transfer. Most of the difference in respiration between high- and low-light leaves was related to the carbohydrate status as determined by the daily PFD and little was directly related to the maintenance costs of the photosynthetic apparatus. Leaf construction cost was directly proportional to maximum photosynthetic capacity. Consequently, although daily carbon gain per unit leaf area was the same for low-light and high to low-light transferred plants within a week after transfer, the carbon return per unit of carbon investment in the leaves remained lower in the high to low transfer plants throughout the 4 week measurement period. Conversely, in high-light, the low leaf construction cost of the low to high-light transferred plants resulted in carbon gain per unit investment just as high as that of the high-light plants. [ABSTRACT FROM AUTHOR]

Remodeling underground structures requires careful construction planning, including consideration of costs and scheduling. Therefore, this study aims to analyze and compare the effects of four methods for vertically extending the underground spaces of an existing building under scheduling and cost constraints. The study considers the following extension methods: (1) bottom-up method, (2) normal top-down method after demolition, (3) normal top-down method in parallel with demolition, and (4) top-down method using double beams in parallel with demolition. Twelve illustrative examples are presented to investigate the constructability of these methods in terms of construction scheduling and costs. The construction durations and costs of each example is calculated and compared. We also analyze the structural stability of the examples using MIDAS Gen 2017. We conclude that the top-down method using double beams is the most efficient method in terms of costs and scheduling. The results and analysis process can help practitioners to select appropriate methods to expand underground spaces without demolishing entire existing buildings and efficiently manage costs and schedules. In future studies, these extension methods should be applied to real-world projects in various countries to validate and verify their actual effects on construction costs and scheduling. [ABSTRACT FROM AUTHOR]

This study deals with small investors' demands on thermal insulation systems when choosing the most suitable solution for a family house. By 2050, seventy percent of current buildings, including residential buildings, are still expected to be in operation. To reach carbon neutrality, it is necessary to reduce operational energy consumption and thus reduce the related cost of building operations and the cost of the life cycle of buildings. One solution is to adapt envelopes of buildings by proper insulation solutions. To choose an optimal thermal insulation system that will reduce energy consumption of building, it is necessary to consider the environmental cost of insulation materials in addition to the construction cost of the materials. The environmental cost of a material depends on the carbon footprint from the initial origin of the material. This study presents the results of a multi-criteria decision-making analysis, where five different contractors set the evaluation criteria for selection of the optimal thermal insulation system. In their decision-making, they involved the requirements of small investors. The most common requirements were selected: the construction cost, the construction time (represented by the total man-hours), the thermal conductivity coefficient, the diffusion resistance factor, and the reaction to fire. The confidences of the criteria were then determined with the help of the pairwise comparison method. This was followed by multi-criteria decision-making using the method of index coefficients, also known as the method of basic variant. The multi-criteria decision-making included thermal insulation systems based on polystyrene, mineral wool, thermal insulation plaster, and aerogels' nanotechnology. As a result, it was concluded that, currently, in Slovakia, small investors emphasize the cost of material and the coefficient of thermal conductivity and they do not care as much about the carbon footprint of the material manufacturing, the importance of which is mentioned in this study. [ABSTRACT FROM AUTHOR]

In multi-criteria decision-making (MCDM) problems the decision-maker is often forced to accept a not ideal solution. If the ideal choice exists, it would be certainly chosen. The acceptance of a non- ideal solution leads to some inadequate properties in the chosen solution. MCDM methods help the decision-maker to structure his needs considering different units, in which the properties of the solutions are expressed. Secondly, with MCDM tools the assessment of the available solutions can be calculated with consideration of the decision-maker's needs. The incorporation of the cost criterion into the decision maker's preferences calculation, and the solution assessment calculation, deprives the decision-maker of the ability to calculate the financial result of the decision he must make. A new multi-criteria decision making with cost criterion analysed at the final stage (MCDM-CCAF) method is developed based on principle of Pareto optimal decisions. It is proposed to exclude the cost criterion from the MCDM analysis and consider it at the final phase of the decision-making process. It is illustrated by example solutions with consideration of cost criterion and without it. It is proposed to apply the invented post-processing method to all MCDM analyses where the cost criterion of analysed variants is considered. [ABSTRACT FROM AUTHOR]

Estimating regional costs of green infrastructure (GI) and low-impact development (LID) stormwater management controls is an important issue for many municipalities and water utilities in the United States. The National Stormwater Calculator (NSWC) is a site-scale, planning-level tool. A regional cost estimation methodology was recently added to the NSWC, enabling users to estimate region-specific capital and maintenance costs of commonly used GI controls. This paper discusses the approach used to estimate and regionalize costs in the NSWC.

In this paper, we compared the predictive capabilities of six different machine learning algorithms – linear regression, artificial neural network, random forest, extreme gradient boosting, light gradient boosting, and natural gradient boosting – and demonstrated that a hybrid light gradient boosting and natural gradient boosting model provides the most desirable construction cost estimates in terms of the accuracy metrics, uncertainty estimates, and training speed. We also present a game theory-based model interpretation technique to evaluate the average marginal contribution of each feature value, across all possible combinations of features, on the model predictions. The comparison between the predicted cost and the actual cost confirms good alignment with R 2 ∼ 0.99, R M S E ∼ 0.5, and M B E ∼ -0.009. Besides, the proposed hybrid model can provide uncertainty estimates through probabilistic predictions for real-valued outputs. This probabilistic prediction approach produces a holistic probability distribution over the entire outcome space to quantify the uncertainties related to construction cost predictions. [ABSTRACT FROM AUTHOR]

Yang, Z. and Qiu, H., 2020. Prediction algorithm of bridge construction cost based on regression analysis. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 979–982. Coconut Creek (Florida), ISSN 0749-0208. In the prediction of bridge construction cost, the correlation between the variables that affect the construction cost is an important factor that affects the prediction results. In the previous prediction algorithm, there is the problem of low Pearson correlation coefficient. Therefore, the prediction algorithm of bridge construction cost based on regression analysis is designed. According to the structure of the bridge entity and the various costs in the project, the influencing factors of the construction cost of the bridge project are determined, and the determinable coefficients among the influencing factors are calculated by regression analysis, then the predicted value of the construction cost of the bridge project is calculated, and the average relative error method and the mean square deviation ratio method are set to ensure the reliability of the predicted value. The experimental results show that the Pearson correlation coefficient of the designed prediction algorithm based on regression analysis is higher than that of the traditional prediction algorithm, which shows that the algorithm is suitable for practical bridge engineering projects. [ABSTRACT FROM AUTHOR]

• The paper explores the consequences of sub-optimal cost-safety trade-offs. • An ethnographic approach is used to complement prior quantitative cost-safety studies. • We demonstrate how low-winning tender bids can elevate safety risks. • The construction industry is currently structured for unsafety. • There is a critical need to rethink the industry's competitive bidding practices. Construction accidents can have major social, financial, reputational and legal implications. Hence, it is to be expected that safety is often presented as a key priority for construction organisations. However, existing evidence suggests that within the construction industry, safety often loses the battle when a trade-off is required with project cost. Improved understanding of the manifestations of the cost and safety interaction are needed. A three-year longitudinal study afforded the opportunity to investigate the safety implications of sub-economic bids on a large infrastructure project in the UK. While low-bidding to win tenders is not new, this paper presents empirical evidence of the consequential safety risk implications of such bidding at the project delivery stage. Faced with a perverse form of the tender 'Winner's Curse' where the successful bid is frequently the lowest, cost-saving strategies are often implemented to recoup lost pricing margins. Our investigation revealed several instances of consequentially elevated safety risks, through cheaper and poor-quality equipment, machinery and temporary structures. In addition, lower-paid migrant workers – who already experience a statistically greater safety risk than local workers – were employed on the project without appropriate investment in a safety management approach suitable for a multinational workforce. The study both contributes to the call to critically rethink the construction industry's competitive bidding practices, and highlights an industry structure that creates the conditions for high safety risks and accidents. [ABSTRACT FROM AUTHOR]

• A state-of-the-art pavement structure called advanced reinforced concrete pavement is developed. • ARCP is designed to reduce construction cost and to increase performance of CRCP. • The steel design method of ARCP eliminates unnecessary reinforcements in CRCP. • Crack induction strategies of ARCP provide superior improved performance. • Experimental ARCP sections are constructed to monitor their behavior and to validate ARCP. A state-of-the-art rigid pavement structure called the advanced reinforced concrete pavement (ARCP) was developed to overcome major shortcomings of the continuously reinforced concrete pavement (CRCP), which were the high construction cost because of a huge amount of steel bars and the performance reduction caused by undesirable crack patterns. The steel design method of ARCP was developed to eliminate unnecessary steel bars in CRCP and the crack induction strategies of ARCP were accomplished to provide even better pavement performance. The numerical analyses, laboratory experiments, and field experiments were conducted to confirm the concept of ARCP, to find the most appropriate design of ARCP, and to validate ARCP finally. Details of the efforts to develop ARCP are comprehensively presented. [ABSTRACT FROM AUTHOR]

Leaf venation networks evolved along several functional axes, including resource transport, damage resistance, mechanical strength, and construction cost. Because functions may depend on architectural features at different scales, network architecture may vary across spatial scales to satisfy functional tradeoffs. We develop a framework for quantifying network architecture with multiscale statistics describing elongation ratios, circularity ratios, vein density, and minimum spanning tree ratios. We quantify vein networks for leaves of 260 southeast Asian tree species in samples of up to 2 cm 2 , pairing multiscale statistics with traits representing axes of resource transport, damage resistance, mechanical strength, and cost. We show that these multiscale statistics clearly differentiate species' architecture and delineate a phenotype space that shifts at larger scales; functional linkages vary with scale and are weak, with vein density, minimum spanning tree ratio, and circularity ratio linked to mechanical strength (measured by force to punch) and elongation ratio and circularity ratio linked to damage resistance (measured by tannins); and phylogenetic conservatism of network architecture is low but scale-dependent. This work provides tools to quantify the function and evolution of venation networks. Future studies including primary and secondary veins may uncover additional insights., (©2020 The Authors New Phytologist ©2020 New Phytologist Trust.)