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1
Chen, Bilin, Weiran Qian, Yiduo Yang, Hong Liu, and Laili Wang. "Carbon Footprint and Water Footprint of Cashmere Fabrics." Fibres and Textiles in Eastern Europe 29, no. 4(148) (August 31, 2021): 94–99. http://dx.doi.org/10.5604/01.3001.0014.8235.
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Given the serious problems of climate change, water shortage and water pollution, researchers have paid increasing attention to the concepts of the carbon footprint and water footprint as useful indices to quantify and evaluate the environmental impacts of the textile industry. In this study, assessment of the carbon footprints and water footprints of ten kinds of cashmere fabrics was conducted based on the PAS 2050 specification, the Water Footprint Network approach and the ISO 14046 standard. The results showed that knitted cashmere fabrics had a greater carbon footprint than woven cashmere fabrics. Contrarily, woven cashmere fabrics had a greater water footprint than knitted cashmere fabrics. The blue water footprint, grey water footprint and water scarcity footprint of combed sliver dyed woven cashmere fabric were the largest among the ten kinds of cashmere fabrics. The main pollutants that caused the grey water footprints of cashmere fabrics were total phosphorus (TP), chlorine dioxide, hexavalent chromium (Cr (VI)) and sulfide. The leading contributors to the water eutrophication footprint were total nitrogen, ammonia nitrogen, chemical oxygen demand and TP. These typical pollutants contributed 39% ~ 48%, 23% ~ 28%, 12% ~ 24% and 12% ~ 14% to each cashmere product’s water eutrophication footprint, respectively. The leading contributors to the water ecotoxicity footprint were aniline, Cr (VI) and absorbable organic halogens discharged in the dyeing and finishing process.
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Samkurashvili, Irakli, and Donal S. Luse. "Structural Changes in the RNA Polymerase II Transcription Complex during Transition from Initiation to Elongation." Molecular and Cellular Biology 18, no. 9 (September 1, 1998): 5343–54. http://dx.doi.org/10.1128/mcb.18.9.5343.
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ABSTRACT We obtained exonuclease III (exoIII) footprints for a series of RNA polymerase II transcription complexes stalled between positions +20 to +51. Downstream advance of the exoIII footprint is normally tightly coordinated with RNA synthesis. However, arrested RNA polymerases slide back along the template, as indicated by exoIII footprints in which the last transcribed base is abnormally close to the downstream edge of the footprint. None of the polymerase II complexes stalled between +20 and +51 were arrested. Nevertheless, the exoIII footprints of complexes with 20-, 23-, or 25-nucleotide RNAs resembled those of arrested complexes, with the last transcribed base very close to the footprint’s front edge. The exoIII footprint of the +27 complex was displaced downstream by 17 bp compared to the footprint of the +25 complex. Many complexes between +27 and +42 also showed evidence of sliding back along the template. We compared the effects of template sequence and transcript length by constructing a new template in which the initial transcribed sequence was duplicated beginning at +98. The exoIII footprints of transcription complexes stalled between +122 to +130 on this DNA did not resemble those of arrested complexes, in contrast to the footprints of analogous complexes stalled over the same DNA sequences early in transcription. Our results indicate that the RNA polymerase II transcription complex passes through a major, sequence-independent structural transition about 25 bases downstream of the starting point of transcription. The fully mature form of the elongation complex may not appear until more than 40 bonds have been made.
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Marsa, Mardhatillah, Yudha Nurhantari, and Santosa Budiharjo. "PENENTUAN RUMUS TINGGI BADAN BERDASARKAN PANJANG JEJAK KAKI PADA ETNIS JAWA." Indonesian Journal of Legal and Forensic Sciences (IJLFS) 8, no. 1 (November 15, 2018): 1. http://dx.doi.org/10.24843/ijlfs.2018.v08.i01.p01.
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Background: Proof of footprints in forensic identification can be used in the determination of personal identification, for example the height. Estimated the height is done by measuring the length of footprints. Based on the literature, height was correlates directly with long bones. Footprints are made by the soles of the feet that are part of the long bones. The calculation of the height is more accurate using the formula derived from the population concerned so that testing needs to be done on each population.
Objective: To find out whether there is a correlation between the length of the footprint of a person's height, especially the Javanese ethnic population and determine the estimation formula of height based on the length of the footprint.
Methods: The study subjects consisted of 100 men and 100 Javanese ethnic women aged 21-30 years who were taken by consecutive sampling technique. Measurements were made by measuring subject height and footprint imprint then calculated each of the length of right and left footprints.
Result: The average height of male Javanese ethnic is 172,36 cm and woman 158,45 cm. The average length of right and left footprints in males is 23,02 cm and female 22 cm. Pearson correlation test on all subjects had r value of 0.968 for right footprint and r 0.967 for left footprint. On the male subject has r value 0.908 for right foot print and r 0.902 for left footprint. In the female subject has r value 0.927 for the right foot print and r 0.931 for the left footprint.
Conclusion: There is a strong relationship between the length of a person's footprint with height and this study has earned a formula of height estimation based on the length of the footprint on the Javanese.
Keywords: height, footprint, identification, Javanese ethnics
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Kan, Daxue, and Weichiao Huang. "An Empirical Study of the Impact of Urbanization on Industry Water Footprint in China." Sustainability 12, no. 6 (March 13, 2020): 2263. http://dx.doi.org/10.3390/su12062263.
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How to advance new urbanization initiatives and reduce the water footprint of industries is one urgent issue about urbanization that needs to be resolved. Based on spatial dynamic panel data, we used the system GMM (Generalized Method of Moments) to study the impact of urbanization on the industrial water footprint. The results show that, overall, urbanization increases the industrial water footprint, industrial virtual water footprint, and industrial gray water footprint in China. There are sectoral and regional differences in the impact of urbanization. Specifically, urbanization reduces the agricultural water footprint and agricultural virtual water footprint but raises the agricultural gray water footprint. Urbanization increases the manufacturing water footprint, manufacturing virtual water footprint, and gray water footprint. Urbanization reduces the virtual water footprint of the service industry but increases the water footprint and gray water footprint in the service industry. At the regional level, urbanization increases the industrial water footprint and gray water footprint across the three major regions. In the eastern region, urbanization has little effect on increasing the industrial water footprint, and reduces the industrial virtual water footprint, whereas in the central and western regions urbanization increases the industrial virtual water footprint. In all three regions, urbanization reduces the agricultural water footprint, increases the manufacturing and service water footprints, reduces the virtual water footprints of agriculture and services, and increases the gray water footprint of agriculture, manufacturing, and services. In the eastern region, the reducing effect of urbanization is the greatest and the increasing effect of urbanization is the smallest. Additionally, in the eastern region, urbanization has reduced the virtual water footprint of manufacturing, whereas in the central and western regions urbanization has increased the virtual water footprint of manufacturing.
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Buchanan, Rachel, Erica Southgate, Shamus P. Smith, Tiana Murray, and Brittany Noble. "Post no photos, leave no trace: Children’s digital footprint management strategies." E-Learning and Digital Media 14, no. 5 (September 2017): 275–90. http://dx.doi.org/10.1177/2042753017751711.
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Given that today’s children are prolific users of the internet, concern has been raised about the future impact of the digital footprints they are currently generating. Here, we report on the Best Footprint Forward project which utilised focus groups to investigate the digital footprint awareness of 33 children (ranging in age from 10 to 12 years old) from three primary schools in regional Australia. The children were very aware of their digital footprints and cyber safety but had little awareness of the positive potential of digital footprints. Instead, they exercised their agency through the use of strategies to minimise their digital footprint. We offer an alternative perspective to the dominant discourse that insists that a digital footprint is primarily a liability and seek to counter the positioning of children as naïve, passive consumers of digital culture. We conclude that 10–12 years old is an appropriate age to begin to educate for positive digital footprint curation as this would build on children’s demonstrated knowledge of cyber safety and supplement their existing digital footprint management strategies with beneficial alternatives.
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Stolen, Eric D., Donna M. Oddy, Mike L. Legare, David R. Breininger, Shanon L. Gann, Stephanie A. Legare, Stephanie K. Weiss, Karen G. Holloway-Adkins, and Ron Schaub. "Preventing Tracking-Tube False Detections in Occupancy Modeling of Southeastern Beach Mouse." Journal of Fish and Wildlife Management 5, no. 2 (August 1, 2014): 270–81. http://dx.doi.org/10.3996/032014-jfwm-025.
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Abstract Quantifying habitat occupancy of the southeastern beach mouse Peromyscus polionotus niveiventris is important for managing this threatened species throughout its limited range. Tracking tubes were used to detect the southeastern beach mouse in coastal areas on the federal lands of the Kennedy Space Center, Cape Canaveral Air Force Station, and Canaveral National Seashore. Because this method relied on observations of footprints, detections of beach mice were confounded by the co-occurrence of cotton mice Peromyscus gossypinus, which have wider but slightly overlapping footprint widths. Mice of both species were captured and footprinted using tracking tubes to collect a database of footprints of known identity. These data were used to develop a Bayesian hierarchical model of the cutoff width at which a print could be assigned as a beach mouse with a known probability of error. Specifically, within the model, observed footprint widths were used to estimate a mean and variance of footprint width for each species, while accounting for variation between individual mice. Then, a distribution of new footprint widths was generated for each species by drawing from their modeled distributions. Finally, the new footprints were compared with a range of potential cutoff widths to evaluate the proportion of times the correct decision to exclude or accept the footprint was made. We graphically evaluated the performance of the cutoff widths and chose one that traded off between reducing false positives and retaining more correct detections for use in occupancy models. We explored the use of the cutoff width using occupancy models that allow for false-positive detections, and found that the use of the cutoff performed as expected. Over 40% of primary dune habitat on the Kennedy Space Center was occupied by beach mice during the period sampled. The proportion of vegetated habitat at a site had a negative influence on detection probability. No ecological covariates had a measurable influence on beach mouse occupancy, probably due to the limited range of environmental variation in the sampled region. The use of a cutoff for footprint width resulted in a reliable method to deal with false-positive detections in tracking tubes with small mammals and allowed the use of occupancy models that rely on certain detection.
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Scott, LuAnn, Daniel LaFoe, and Clifford F. Weil. "Adjacent Sequences Influence DNA Repair Accompanying Transposon Excision in Maize." Genetics 142, no. 1 (January 1, 1996): 237–46. http://dx.doi.org/10.1093/genetics/142.1.237.
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Mobile elements transposing via DNA intermediates often leave small rearrangements, or “transposon footprints,” at sites where they excise. Each excision event leaves its own footprint and, at any given site, these vary in size and sequence. Footprint formation involves DNA repair of sequences flanking the element. We have analyzed the footprints formed by a 2-kb Ds element excising from six different sites in exons of the maize waxy (Wx) gene. We find that groups of footprints left at individual sites are surprisingly nonrandom; different excision products predominate consistently at each site. Less frequent footprints left by each insertion appear related to the predominant type. The data suggest that flanking sequences affect the DNA repair processes associated with element excision. Two models have been proposed to explain footprint formation, one featuring a 5′ exonuclease and the other featuring hairpin loop formation and an endonuclease. Our data have interesting implications for both these models. Evidence is also presented to support the presence of a separate excision mechanism that can remove Ac/Ds elements without leaving any footprint and that operates in parallel with the footprint-forming mechanism.
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Reid, James E., Andreas Pfaffling, and Julian Vrbancich. "Airborne electromagnetic footprints in 1D earths." GEOPHYSICS 71, no. 2 (March 2006): G63—G72. http://dx.doi.org/10.1190/1.2187756.
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Existing estimates of footprint size for airborne electromagnetic (AEM) systems have been based largely on the inductive limit of the response. We present calculations of frequency-domain, AEM-footprint sizes in infinite-horizontal, thin-sheet, and half-space models for the case of finite frequency and conductivity. In a half-space the original definition of the footprint is extended to be the side length of the cube with its top centered below the transmitter that contains the induced currents responsible for 90% of the secondary field measured at the receiver. For a horizontal, coplanar helicopter frequency-domain system, the in-phase footprint for induction numbers less than 0.4 (thin sheet) or less than 0.6 (half-space) increases from around 3.7 times the flight height at the inductive limit to more than 10 times the flight height. For a vertical-coaxial system the half-space footprint exceeds nine times the flight height for induction numbers less than 0.09. For all models, geometries, and frequencies, the quadrature footprint is approximately half to two-thirds that of the in-phase footprint. These footprint estimates are supported by 3D model calculations that suggest resistive targets must be separated by the footprint dimension for their individual anomalies to be resolved completely. Analysis of frequency-domain AEM field data acquired for antarctic sea-ice thickness measurements supports the existence of a smaller footprint for the quadrature component in comparison with the in-phase, but the effect is relatively weak. In-phase and quadrature footprints estimated by comparing AEM to drillhole data are considerably smaller than footprints from 1D and 3D calculations. However, we consider the footprints estimated directly from field data unreliable since they are based on a drillhole data set that did not adequately define the true, 3D, sea-ice thickness distribution around the AEM flight line.
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Gustavsson, D. J. I., and S. Tumlin. "Carbon footprints of Scandinavian wastewater treatment plants." Water Science and Technology 68, no. 4 (August 1, 2013): 887–93. http://dx.doi.org/10.2166/wst.2013.318.
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This study estimates the carbon footprints of 16 municipal wastewater treatment plants (WWTPs), all situated in Scandinavian countries, by using a simple model. The carbon footprint calculations were based on operational data, literature emission factors (efs) and measurements of greenhouse gas emissions at some of the studied WWTPs. No carbon neutral WWTPs were found. The carbon footprints ranged between 7 and 108 kg CO2e P.E.−1 year−1. Generally, the major positive contributors to the carbon footprint were direct emissions of nitrous oxide from wastewater treatment. Whether heat pumps for effluents have high coefficient of performance or not is extremely important for the carbon footprint. The choice of efs largely influenced the carbon footprint. Increased biogas production, efficient biogas usage, and decreased addition of external fossil carbon source for denitrification are important activities to decrease the carbon footprint of a WWTP.
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Zhuo, L., M. M. Mekonnen, and A. Y. Hoekstra. "Sensitivity and uncertainty in crop water footprint accounting: a case study for the Yellow River Basin." Hydrology and Earth System Sciences Discussions 11, no. 1 (January 7, 2014): 135–67. http://dx.doi.org/10.5194/hessd-11-135-2014.
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Abstract. Water Footprint Assessment is a quickly growing field of research, but as yet little attention has been paid to the uncertainties involved. This study investigates the sensitivity of water footprint estimates to changes in important input variables and quantifies the size of uncertainty in water footprint estimates. The study focuses on the green (from rainfall) and blue (from irrigation) water footprint of producing maize, soybean, rice, and wheat in the Yellow River Basin in the period 1996–2005. A grid-based daily water balance model at a 5 by 5 arcmin resolution was applied to compute green and blue water footprints of the four crops in the Yellow River Basin in the period considered. The sensitivity and uncertainty analysis focused on the effects on water footprint estimates at basin level (in m3 t−1) of four key input variables: precipitation (PR), reference evapotranspiration (ET0), crop coefficient (Kc), and crop calendar. The one-at-a-time method was carried out to analyse the sensitivity of the water footprint of crops to fractional changes of individual input variables. Uncertainties in crop water footprint estimates were quantified through Monte Carlo simulations. The results show that the water footprint of crops is most sensitive to ET0 and Kc, followed by crop calendar and PR. Blue water footprints were more sensitive to input variability than green water footprints. The smaller the annual blue water footprint, the higher its sensitivity to changes in PR, ET0, and Kc. The uncertainties in the total water footprint of a crop due to combined uncertainties in climatic inputs (PR and ET0) were about ±20% (at 95% confidence interval). The effect of uncertainties in ET0 was dominant compared to that of precipitation. The uncertainties in the total water footprint of a crop as a result of combined key input uncertainties were on average ±26% (at 95% confidence level). The sensitivities and uncertainties differ across crop types, with highest sensitivities and uncertainties for soybean.
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Lee, Yung-Jaan. "Ecological Footprint and Water Footprint of Taipei." Sustainability 11, no. 20 (October 16, 2019): 5714. http://dx.doi.org/10.3390/su11205714.
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Taiwan suffers from many natural disasters and is vulnerable to climate change. A continuous increase in its ecological footprint (EF) would pose numerous threats to the city. Taipei is Taiwan’s most densely populated city. Whether its citizens are consuming more resources because of their high income and high degree of urbanization, thereby burdening the environment, warrants study. In contrast to most top-down EF analyses, in this study, 445 residents were surveyed to calculate their carbon, built-up land and water footprints. Gender, occupation, age, education level, personal annual income and socio-economic background do not influence water footprint or EF. Moreover, an individual’s water footprint is not correlated with his or her EF. The built-up land footprint that is obtained in this bottom-up study is similar to that in Taiwan’s top-down national footprint account. However, the personal carbon footprint found herein is smaller than that in the national footprint account, because this study asked respondents’ only about consumption related to everyday activities. Since Taipei residents have a high income and high daily consumption, the water footprint herein is larger than the top-down water footprint. This bottom-up EF analysis reflects residents’ daily consumption patterns and can be used in future urban decision-making.
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Johnson, Eric, and Alex Gafford. "USA Carbon Footprints of Grills, by Fuel & Grill Type, 2022–27." Fuels 3, no. 3 (August 3, 2022): 475–85. http://dx.doi.org/10.3390/fuels3030029.
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Grill-specific footprints for common fuel/grill types in the USA have been estimated from public information and data from a major grill manufacturer. In 2022, grill-specific footprints vary by a ratio of 9:1. A typical gas grill has the highest footprint; a wood-pellet grill is lowest; charcoal briquettes, electricity and super-efficient gas grills come in-between those two. Efficiency varies greatly for gas (natural gas or propane) grills: a typical gas grill has twice the footprint of a super-efficient one. In 2027, the footprint rankings could change considerably from 2022. With biofuel substitution, the super-efficient gas grill would move ahead of pellets. Electricity and charcoal could improve but would still place fifth and sixth. The range of grill-specific footprints could fall to 4.5:1, and within a much-lower range. The highest footprint in 2027 is almost 60% lower than 2022′s highest.
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Konar, Megan, and Landon Marston. "The Water Footprint of the United States." Water 12, no. 11 (November 23, 2020): 3286. http://dx.doi.org/10.3390/w12113286.
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This paper commemorates the influence of Arjen Y. Hoekstra on water footprint research of the United States. It is part of the Special Issue “In Memory of Prof. Arjen Y. Hoekstra”. Arjen Y. Hoekstra both inspired and enabled a community of scholars to work on understanding the water footprint of the United States. He did this by comprehensively establishing the terminology and methodology that serves as the foundation for water footprint research. His work on the water footprint of humanity at the global scale highlighted the key role of a few nations in the global water footprint of production, consumption, and virtual water trade. This research inspired water scholars to focus on the United States by highlighting its key role amongst world nations. Importantly, he enabled the research of many others by making water footprint estimates freely available. We review the state of the literature on water footprints of the United States, including its water footprint of production, consumption, and virtual water flows. Additionally, we highlight metrics that have been developed to assess the vulnerability, resiliency, sustainability, and equity of sub-national water footprints and domestic virtual water flows. We highlight opportunities for future research.
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Mekonnen, M. M., and A. Y. Hoekstra. "The green, blue and grey water footprint of crops and derived crop products." Hydrology and Earth System Sciences 15, no. 5 (May 25, 2011): 1577–600. http://dx.doi.org/10.5194/hess-15-1577-2011.
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Abstract. This study quantifies the green, blue and grey water footprint of global crop production in a spatially-explicit way for the period 1996–2005. The assessment improves upon earlier research by taking a high-resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc minute grid. We have used a grid-based dynamic water balance model to calculate crop water use over time, with a time step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid cell. In addition, the water pollution associated with the use of nitrogen fertilizer in crop production is estimated for each grid cell. The crop evapotranspiration of additional 20 minor crops is calculated with the CROPWAT model. In addition, we have calculated the water footprint of more than two hundred derived crop products, including various flours, beverages, fibres and biofuels. We have used the water footprint assessment framework as in the guideline of the Water Footprint Network. Considering the water footprints of primary crops, we see that the global average water footprint per ton of crop increases from sugar crops (roughly 200 m3 ton−1), vegetables (300 m3 ton−1), roots and tubers (400 m3 ton−1), fruits (1000 m3 ton−1), cereals (1600 m3 ton−1), oil crops (2400 m3 ton−1) to pulses (4000 m3 ton−1). The water footprint varies, however, across different crops per crop category and per production region as well. Besides, if one considers the water footprint per kcal, the picture changes as well. When considered per ton of product, commodities with relatively large water footprints are: coffee, tea, cocoa, tobacco, spices, nuts, rubber and fibres. The analysis of water footprints of different biofuels shows that bio-ethanol has a lower water footprint (in m3 GJ−1) than biodiesel, which supports earlier analyses. The crop used matters significantly as well: the global average water footprint of bio-ethanol based on sugar beet amounts to 51 m3 GJ−1, while this is 121 m3 GJ−1 for maize. The global water footprint related to crop production in the period 1996–2005 was 7404 billion cubic meters per year (78 % green, 12 % blue, 10 % grey). A large total water footprint was calculated for wheat (1087 Gm3 yr−1), rice (992 Gm3 yr−1) and maize (770 Gm3 yr−1). Wheat and rice have the largest blue water footprints, together accounting for 45 % of the global blue water footprint. At country level, the total water footprint was largest for India (1047 Gm3 yr−1), China (967 Gm3 yr−1) and the USA (826 Gm3 yr−1). A relatively large total blue water footprint as a result of crop production is observed in the Indus river basin (117 Gm3 yr−1) and the Ganges river basin (108 Gm3 yr−1). The two basins together account for 25 % of the blue water footprint related to global crop production. Globally, rain-fed agriculture has a water footprint of 5173 Gm3 yr−1 (91 % green, 9 % grey); irrigated agriculture has a water footprint of 2230 Gm3 yr−1 (48 % green, 40 % blue, 12 % grey).
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Mekonnen, M. M., and A. Y. Hoekstra. "The green, blue and grey water footprint of crops and derived crop products." Hydrology and Earth System Sciences Discussions 8, no. 1 (January 20, 2011): 763–809. http://dx.doi.org/10.5194/hessd-8-763-2011.
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Abstract. This study quantifies the green, blue and grey water footprint of global crop production in a spatially-explicit way for the period 1996–2005. The assessment is global and improves upon earlier research by taking a high-resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc min grid. We have used a grid-based dynamic water balance model to calculate crop water use over time, with a time step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid cell. In addition, the water pollution associated with the use of nitrogen fertilizer in crop production is estimated for each grid cell. The crop evapotranspiration of additional 20 minor crops is calculated with the CROPWAT model. In addition, we have calculated the water footprint of more than two hundred derived crop products, including various flours, beverages, fibres and biofuels. We have used the water footprint assessment framework as in the guideline of the water footprint network. Considering the water footprints of primary crops, we see that global average water footprint per ton of crop increases from sugar crops (roughly 200 m3 ton−1), vegetables (300 m3 ton−1), roots and tubers (400 m3 ton−1), fruits (1000 m3 ton−1), cereals} (1600 m3 ton−1), oil crops (2400 m3 ton−1) to pulses (4000 m3 ton−1). The water footprint varies, however, across different crops per crop category and per production region as well. Besides, if one considers the water footprint per kcal, the picture changes as well. When considered per ton of product, commodities with relatively large water footprints are: coffee, tea, cocoa, tobacco, spices, nuts, rubber and fibres. The analysis of water footprints of different biofuels shows that bio-ethanol has a lower water footprint (in m3 GJ−1) than biodiesel, which supports earlier analyses. The crop used matters significantly as well: the global average water footprint of bio-ethanol based on sugar beet amounts to 51 m3 GJ−1, while this is 121 m3 GJ−1 for maize. The global water footprint related to crop production in the period 1996–2005 was 7404 billion cubic meters per year (78% green, 12% blue, 10% grey). A large total water footprint was calculated for wheat (1087 Gm3 yr−1), rice (992 Gm3 yr−1) and maize (770 Gm3 yr−1). Wheat and rice have the largest blue water footprints, together accounting for 45% of the global blue water footprint. At country level, the total water footprint was largest for India (1047 Gm3 yr−1), China (967 Gm3 yr−1) and the USA (826 Gm3 yr−1). A relatively large total blue water footprint as a result of crop production is observed in the Indus River Basin (117 Gm3 yr−1) and the Ganges River Basin (108 Gm3 yr−1). The two basins together account for 25% of the blue water footprint related to global crop production. Globally, rain-fed agriculture has a water footprint of 5173 Gm3 yr−1 (91% green, 9% grey); irrigated agriculture has a water footprint of 2230 Gm3 yr−1 (48% green, 40% blue, 12% grey).
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Kim, Ik, and Kyung-shin Kim. "Estimation of Water Footprint for Major Agricultural and Livestock Products in Korea." Sustainability 11, no. 10 (May 25, 2019): 2980. http://dx.doi.org/10.3390/su11102980.
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The Republic of Korea is the only country classified with severe water stress among the 34 Organization for Economic Co-operation and Development (OECD) member countries. Additionally, the self-sufficiency rate of grain in Korea is 27%, which is 1/3 the average of OECD member countries. Because food cannot be produced without water, demand-driven water management of agricultural and livestock products applying water footprints is needed for food security. For this, this study estimates the water footprints of 42 agricultural products and three livestock products. Based on the results, the water footprint of the vegetables grown in facility such as a greenhouse is 7.9 times larger per ton than the footprint of the vegetables cultivated in the open field. Furthermore, the water footprint per ton of beef is about 4.2 times the average water footprint per ton of vegetables grown in facility. Based on the water footprint data of 45 agricultural and livestock products, the footprint of total agricultural and livestock products in 2014 is approximately 27.9% of the total domestic water resources consumed in Korea.
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CAIRD, SALLY, and ROBIN ROY. "HOUSEHOLD ECOLOGICAL FOOTPRINTS — DEMOGRAPHICS AND SUSTAINABILITY." Journal of Environmental Assessment Policy and Management 08, no. 04 (December 2006): 407–29. http://dx.doi.org/10.1142/s1464333206002591.
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How do demographic factors influence the environmental impacts of households? A major two year study used the ecological footprint technique to measure the environmental impacts of over 1000 UK households. Energy and transport were the biggest contributors to the 'footprint' of households. Rural, and adult households and households with few members had significantly larger per capita ecological footprints than urban/suburban households, households with children and households with several members. Although 11% of these UK households could be regarded as environmentally sustainable, the majority would require a reduction of 60% in ecological footprint to achieve a globally sustainable footprint per person. Consideration is given to the policy implications of demographic influences on household ecological footprints, including personal carbon allowances and house planning and design.
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van Noordwijk, Meine, Thuy T. Pham, Beria Leimona, Lalisa A. Duguma, Himlal Baral, Nikhmatul Khasanah, Sonya Dewi, and Peter A. Minang. "Carbon footprints, informed consumer decisions and shifts towards responsible agriculture, forestry, and other land uses?" Carbon Footprints 1, no. 1 (2022): 4. http://dx.doi.org/10.20517/cf.2022.02.
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The urgent global reduction of greenhouse gas emissions depends on political commitments to common but differentiated responsibility. Carbon footprints as a metric of attributable emissions reflect individually determined contributions within, and aggregated national contributions between, countries. Footprints per unit product (e.g., of food, feed, fuel, or fiber) require a lifecycle analysis and support individual decisions on consumption and lifestyles. This perspective presents a framework for analysis that connects the various operationalizations and their use in informing consumer and policy decisions. Footprints show geographical variation and are changing as part of political-economic and social-ecological systems. Articulation of footprints may trigger further change. Carbon footprints partially correlate with water and biodiversity footprints as related ecological footprint concepts. The multifunctionality of land use, as a solution pathway, can be reflected in aggregated footprint metrics. Credible footprint metrics can contribute to change but only if political commitments and social-cultural values and responsibilities align.
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Sandness, Adéla. "“In the footprint of Iḷā” : An EarIy Image of Sacrificial Cosmology in Vedic Tradition." Studies in Religion/Sciences Religieuses 39, no. 4 (October 14, 2010): 509–21. http://dx.doi.org/10.1177/0008429810379970.
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The poets of the Ṛg-Veda speak of the “navel of the earth,” which is the “footprint of Iḷā.” It is among the oldest expressions available which describe a place of ritual offering to the gods. In this case, it is an impression in the ground thought to have been the footprint of a cow, into which was poured milk and butter. The word padá names the footprint in the Indo-Iranian expression “in the footprint of Iḷā.” Yet padá also means “word” and the etymologically related term pāda means a “stanza” of the sacred poetry sung by the ancient visionary poets as they sang their world into being. The footprints are thus also those of the cow Speech whose “supreme place” is parallel to the place of offering which is the footprint of Iḷā. This paper will track the footprints of Iḷā and those of the cow Speech in the Ṛg-Veda.
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Markkanen, T., G. Steinfeld, N. Kljun, S. Raasch, and T. Foken. "Validation of conventional Lagrangian stochastic footprint models against LES driven footprint estimates." Atmospheric Chemistry and Physics Discussions 9, no. 1 (February 9, 2009): 4195–230. http://dx.doi.org/10.5194/acpd-9-4195-2009.
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Abstract. In this study we compare the performance of conventional Lagrangian stochastic (LS) footprint models that use parameterised flow field characteristics with results of a Lagrangian trajectory model embedded in a large eddy simulation (LES) framework. The two conventional models follow the particles backward and forward in time while the trajectories in LES only evolve forward in time. We assess their performance in unstably and neutrally stratified boundary layers at observation levels covering the whole depth of the atmospheric boundary layer. We present a concept for footprint model comparison that can be applied for 2-D footprints and demonstrate that comparison of only cross wind integrated footprints is not sufficient for purposes facilitating two dimensional footprint information. Because the flow field description among the three models is most realistic in LES we use those results as the reference in the comparison. We found that the agreement of the two conventional models against the LES is generally better for intermediate measurement heights and for the convective case, whereas the two conventional flux footprint models agree best under near neutral conditions.
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Barker, S. L., and J. L. Scheuer. "Predictive Value of Human Footprints in a Forensic Context." Medicine, Science and the Law 38, no. 4 (October 1998): 341–46. http://dx.doi.org/10.1177/002580249803800411.
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Previous work from the United States has shown close correlation between an individual's size and weight and predetermined measurements taken from his or her footprints. This study investigated the situation in a group of United Kingdom subjects, for which there is at present little data. Walking and standing footprints, fleshed foot measurements and stature were obtained from 105 adult volunteers from the staff and students of the United Medical and Dental Schools of Guy's and St Thomas' Hospitals, London. The footprints were measured using predetermined landmarks and the results analysed to investigate the significance of the parameters in a forensic context. Inter-observer and intra-observer errors were within acceptable limits. Regression equations were calculated for foot length from various parameters measured on a footprint. Topinard's finding that foot length represents between 14.9%–18.1% of stature in a given individual was confirmed. Footprint length showed a normal distribution in both sexes but male footprint length was greater than female footprint length for any given height. This study provides a quantitative method that could be used both with partial footprints and in the absence of dermatoglyphics to assist in the identification of an individual in a forensic context.
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Markkanen, T., G. Steinfeld, N. Kljun, S. Raasch, and T. Foken. "Comparison of conventional Lagrangian stochastic footprint models against LES driven footprint estimates." Atmospheric Chemistry and Physics 9, no. 15 (August 6, 2009): 5575–86. http://dx.doi.org/10.5194/acp-9-5575-2009.
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Abstract. In this study we introduce a comparison method for footprint model results by evaluating the performance of conventional Lagrangian stochastic (LS) footprint models that use parameterised flow field characteristics with results of a Lagrangian trajectory model embedded in a large eddy simulation (LES) framework. The two conventional models follow the particles backward and forward in time while the trajectories in LES only evolve forward in time. We assess their performance in two unstably stratified boundary layers at observation levels covering the whole depth of the atmospheric boundary layer. We present a concept for footprint model comparison that can be applied for 2-D footprints and demonstrate that comparison of only cross wind integrated footprints is not sufficient for purposes facilitating two dimensional footprint information. Because the flow field description among the three models is most realistic in LES we use those results as the reference in the comparison. We found that the agreement of the two conventional models against the LES is generally better for intermediate measurement heights and for the more unstable case, whereas the two conventional flux footprint models agree best under less unstable conditions. The model comparison in 2-D was found quite sensitive to the grid resolution.
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Zhuo, L., M. M. Mekonnen, and A. Y. Hoekstra. "Sensitivity and uncertainty in crop water footprint accounting: a case study for the Yellow River basin." Hydrology and Earth System Sciences 18, no. 6 (June 17, 2014): 2219–34. http://dx.doi.org/10.5194/hess-18-2219-2014.
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Abstract. Water Footprint Assessment is a fast-growing field of research, but as yet little attention has been paid to the uncertainties involved. This study investigates the sensitivity of and uncertainty in crop water footprint (in m3 t−1) estimates related to uncertainties in important input variables. The study focuses on the green (from rainfall) and blue (from irrigation) water footprint of producing maize, soybean, rice, and wheat at the scale of the Yellow River basin in the period 1996–2005. A grid-based daily water balance model at a 5 by 5 arcmin resolution was applied to compute green and blue water footprints of the four crops in the Yellow River basin in the period considered. The one-at-a-time method was carried out to analyse the sensitivity of the crop water footprint to fractional changes of seven individual input variables and parameters: precipitation (PR), reference evapotranspiration (ET0), crop coefficient (Kc), crop calendar (planting date with constant growing degree days), soil water content at field capacity (Smax), yield response factor (Ky) and maximum yield (Ym). Uncertainties in crop water footprint estimates related to uncertainties in four key input variables: PR, ET0, Kc, and crop calendar were quantified through Monte Carlo simulations. The results show that the sensitivities and uncertainties differ across crop types. In general, the water footprint of crops is most sensitive to ET0 and Kc, followed by the crop calendar. Blue water footprints were more sensitive to input variability than green water footprints. The smaller the annual blue water footprint is, the higher its sensitivity to changes in PR, ET0, and Kc. The uncertainties in the total water footprint of a crop due to combined uncertainties in climatic inputs (PR and ET0) were about ±20% (at 95% confidence interval). The effect of uncertainties in ET0was dominant compared to that of PR. The uncertainties in the total water footprint of a crop as a result of combined key input uncertainties were on average ±30% (at 95% confidence level).
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Li, Ying, Ting Ting Guo, and Pan Pan Li. "Evaluation Analysis of Ecological Footprint Model." Applied Mechanics and Materials 99-100 (September 2011): 487–90. http://dx.doi.org/10.4028/www.scientific.net/amm.99-100.487.
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The conception and calculation of ecological footprint model were concluded. On this basis, the key issue of ecological footprint's calculation was proposed. Advantages and disadvantages of ecological footprint model when it applied in ecological assessment was also proposed. This provides references for application of ecological footprint model's assessment methods.
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Long, Yanling, Runzhi Hu, Tuo Yin, Pengxiang Wang, Jiamin Liu, Tahir Muhammad, Xiuzhi Chen, and Yunkai Li. "Spatial-Temporal Footprints Assessment and Driving Mechanism of China Household Diet Based on CHNS." Foods 10, no. 8 (August 11, 2021): 1858. http://dx.doi.org/10.3390/foods10081858.
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Food consumption is closely associated with resource consumption and environmental sustainability. An unreasonable dietary pattern would cause great pressure or damage to resources and the environment. It is particularly important to reduce the negative impact of household food consumption on resources and the environment while simultaneously ensuring people’s nutrient intake and health. This study applied the China Health and Nutrition Survey (CHNS) database to quantitatively study the spatial-temporal analysis of multiple footprints of household food consumption at multiple scales and explored the driving mechanism of the multiple footprints. The results showed that, except land footprint (LF), the other four types of footprints all decreased at varying degrees; the water footprint (WF), carbon footprint (CF), nitrogen footprint (NF) and energy footprint (EF) decreased by 18.24%, 17.82%, 12.03% and 20.36%, respectively, from 2000 to 2011; multiple footprints of food consumption of household in Guizhou was the highest among the 12 provinces involved in the study; this shows that resource consumption (water, energy and land resource) and environmental influences (CO2 emissions and nitrogen emissions) brought by food consumption of per household in Guizhou are much greater than in other provinces, which has a negative influence on sustainable development; by analyzing the driving factors of multiple footprints, it is shown that nutrient intake, household attributes, educational level and health conditions were significantly correlated to multiple footprints. Among them, nutrient intake has greater impact on the multiple footprints of Chinese household food consumption. By comparing multiple footprints of different dietary patterns, it was found that the current Chinese dietary pattern would cause excessive resource consumption, which would bring more pressure on resources and the environment. Adjusting household living habits would possibly reverse the unsustainable situation, such as reducing the consumption of animal-derived foods and adjusting the dietary pattern of households with a higher educational level and income status. Chinese Dietary Guidelines 2016 has better sustainability; the promotion of this dietary pattern across the country would help China to relieve the pressure on resources and environment from the consumer side, promoting the realization of sustainable development.
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Berhane, Tedros, Charles Lane, Samson Mengistu, Jay Christensen, Heather Golden, Shi Qiu, Zhe Zhu, and Qiusheng Wu. "Land-Cover Changes to Surface-Water Buffers in the Midwestern USA: 25 Years of Landsat Data Analyses (1993–2017)." Remote Sensing 12, no. 5 (February 25, 2020): 754. http://dx.doi.org/10.3390/rs12050754.
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To understand the timing, extent, and magnitude of land use/land cover (LULC) change in buffer areas surrounding Midwestern US waters, we analyzed the full imagery archive (1982–2017) of three Landsat footprints covering ~100,000 km2. The study area included urbanizing Chicago, Illinois and St. Louis, Missouri regions and agriculturally dominated landscapes (i.e., Peoria, Illinois). The Continuous Change Detection and Classification algorithm identified 1993–2017 LULC change across three Landsat footprints and in 90 m buffers for ~110,000 surface waters; waters were also size-binned into five groups for buffer LULC change analyses. Importantly, buffer-area LULC change magnitude was frequently much greater than footprint-level change. Surface-water extent in buffers increased by 14–35x the footprint rate and forest decreased by 2–9x. Development in buffering areas increased by 2–4x the footprint-rate in Chicago and Peoria area footprints but was similar to the change rate in the St. Louis area footprint. The LULC buffer-area change varied in waterbody size, with the greatest change typically occurring in the smallest waters (e.g., <0.1 ha). These novel analyses suggest that surface-water buffer LULC change is occurring more rapidly than footprint-level change, likely modifying the hydrology, water quality, and biotic integrity of existing water resources, as well as potentially affecting down-gradient, watershed-scale storages and flows of water, solutes, and particulate matter.
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Ansorge, Libor, and Lada Stejskalová. "Water Footprint as a Tool for Selection of Alternatives (Comments on “Food Recommendations for Reducing Water Footprint”)." Sustainability 14, no. 10 (May 22, 2022): 6317. http://dx.doi.org/10.3390/su14106317.
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Water footprint is a new tool for assessing sustainability in terms of water use. Researchers are devising new applications that use water footprint, one of which is focused on comparing the water requirements of individual diets. Systems have been proposed to suggest tailor-made recipes that use a lower water quantity in production. This system proposes alternative recipes with lower demands for water resources based on their water footprint. The water footprint consists of three components—blue, green, and grey water footprints. However, focusing only on a reduction in the total water footprint may lead to an increase in some of its parts, such as the blue water footprint, and subsequently to water scarcity in some river basins. Therefore, it is recommended to extend the food recommendations system with sustainability criteria in order to avoid the unsustainable management of water resources. The same criteria can be used in any system for selecting alternatives based on the water footprint.
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Souissi, Asma, Nadhem Mtimet, Laura McCann, Ali Chebil, and Chokri Thabet. "Determinants of Food Consumption Water Footprint in the MENA Region: The Case of Tunisia." Sustainability 14, no. 3 (January 28, 2022): 1539. http://dx.doi.org/10.3390/su14031539.
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Tunisia, like most countries in the Middle East and North Africa (MENA) region, has limited renewable water resources and is classified as a water stress country. The effects of climate change are exacerbating the situation. The agricultural sector is the main consumer (80%) of blue water reserves. In this study, to better understand the factors that influence the food water footprint of Tunisian consumers, we used a multiple linear regression model (MLR) to analyze data from 4853 households. The innovation in this paper consists of integrating effects of socio-economic, demographic, and geographic trends on the food consumption water footprint into the assessment of water and food security. The model results showed that regional variations in food choices meant large differences in water footprints, as hypothesized. Residents of big cities are more likely to have a large water footprint. Significant variability in water footprints, due to different food consumption patterns and socio-demographic characteristics, was also noted. Food waste is also one of the determining factors of households with a high water footprint. This study provides a new perspective on the water footprint of food consumption using “household” level data. These dietary water footprint estimates can be used to assess potential water demand scenarios as food consumption patterns change. Analysis at the geographic and socio-demographic levels helps to inform policy makers by identifying realistic dietary changes.
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Jóhannesson, Sigurður E., Jukka Heinonen, and Brynhildur Davíðsdóttir. "Data accuracy in Ecological Footprint’s carbon footprint." Ecological Indicators 111 (April 2020): 105983. http://dx.doi.org/10.1016/j.ecolind.2019.105983.
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Ho, Zih Ping. "Restaurant Facilities Layout - Reducing Carbon Footprint Aspect." Applied Mechanics and Materials 58-60 (June 2011): 618–23. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.618.
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Reducing carbon footprint is a trend within modern green restaurants. A carbon footprint is the total set of greenhouse gas (GHG) emissions caused by an organization, event or product. Food and beverage restaurants have to deliver food using a minimal carbon footprint. Of previous researches, only a small fraction is focused on reducing carbon footprints in a culinary room. Besides, a carbon footprint cost model was hard to solve in economic computation time. Therefore, the main purpose of this research is through a distributed information system to accelerate computing ability of a carbon footprint cost model. Through the distributed computing, our experimental results showed that the proposed approach outperformed the literature approach efficiently. The algorithm improved rate was 68.6%, and low down 82.1% carbon footprint than manual. The proposed approach could contribute to accelerate calculations in others problems due to using multiple machines in future researches.
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Qafisheh, Nida, Makhtar Sarr, Umm Amara Hussain, and Shikha Awadh. "Carbon Footprint of ADU Students: Reasons and Solutions." Environment and Pollution 6, no. 1 (March 31, 2017): 27. http://dx.doi.org/10.5539/ep.v6n1p27.
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The objective of the study was to calculate the carbon footprint of ADU students, studying environmental sciences and environmental health & safety and compared it with the average carbon footprint of UAE. Students’ activity, which contributed to the highest emissions of carbon dioxide per year, has been determined. The carbon footprints were calculated using the online carbon footprint calculator, which estimated the CO2 emissions of each student. The method resulted from different activities like consumption of gas and electricity, transportation, flights, food as well as other different activities are associated with individual’s life style. The average carbon footprint of Environmental ADU students after decreasing their emissions was 12.22 tons CO2/year, which was 68%, less than the average carbon footprint of UAE (37.8 tons/year). The public transportation, driving friendly cars, eating locally and living in a simply sustainable life style are great solutions to reduce an individual carbon footprint.
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Stevens, Carly J., Allison M. Leach, Sarah Dale, and James N. Galloway. "Personal nitrogen footprint tool for the United Kingdom." Environ. Sci.: Processes Impacts 16, no. 7 (2014): 1563–69. http://dx.doi.org/10.1039/c3em00690e.
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A nitrogen footprint calculator tool for the UK is described together with a historical and international comparison of N footprints. Scenarios show how reductions in individual footprints can be made.
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Su, Weihua, Sibo Chen, Tomas Baležentis, and Ji Chen. "ECONOMY-WATER NEXUS IN AGRICULTURAL SECTOR: DECOMPOSING DYNAMICS IN WATER FOOTPRINT BY THE LMDI." Technological and Economic Development of Economy 26, no. 1 (January 24, 2020): 240–57. http://dx.doi.org/10.3846/tede.2020.11908.
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Traditional economic activities induce environmental pressures. In order to ensure sustainable economic growth, one needs to decouple it from the environmental pressures. Sustainable growth of the agricultural sector is topical in the sense that economic activity supports rural populations, whereas the resulting environmental pressures may affect diverse groups of population. Thus, the analysis of water footprint related to crop farming is important in the sense of efficient resource use and sustainable development of agriculture in general. In this paper, we focus on Lithuanian crop farming and the related green and grey water footprints. Specifically, we decompose the changes in the water footprints during 2000–2016 by exploiting the Logarithmic Mean Divisia Index. Due to the expansion of the areas harvested, the scale effect appeared as an important driver of growth in green and grey water footprints. The shifts in spatial distribution of area harvested virtually had no influence on the dynamics in either of the water footprints. The crop-mix effect was much higher for the grey water footprint (51% over the period of 2000–2015) than it was the case for the green water footprint (21%). The yield growth induced growth in both green and grey water footprints.
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Wu, Yi Ling, Xian Zheng Gong, Yu Liu, Xiao Qing Li, Xiao Fei Tian, Hong Tao Wang, and Chang Xing Ye. "Water Footprint Evaluation of the Production of Float Flat Glass." Materials Science Forum 1035 (June 22, 2021): 1102–8. http://dx.doi.org/10.4028/www.scientific.net/msf.1035.1102.
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The ISO14046 water footprint evaluation method was used in this study to calculate the water shortage footprint and water degradation footprint in plate glass production, in order to improve the water efficiency and management level in the production process of plate glass in China. A certain enterprise in Hebei province was selected for investigation in 2018. The results show that the water shortage footprint generated by the production of flat glass was 0.435 m3H2Oeq/weight box. The proportion at raw material production stage was the largest, being 86%, so the water consumption control in raw material mining and the circulating water system should be strengthened and improved to reduce the fresh water consumption. Water degradation footprint in flat glass industry mainly consisted of eutrophication and acidification footprints. The eutrophication footprint was calculated as 0.027 kgNO3-eq/weight box, and water acidification footprint was 0.271 kgSO2eq/weight box. The largest proportion occurred at flat glass production stage. It should be paid attention at this stage, to update the relatively clean production equipments and add the waste gas processing steps to reduce pollution discharge.
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ZHU, JUXIANG, YIDUO YANG, YI LI, PINGHUA XU, and LAILI WANG. "Water footprint calculation and assessment of viscose textile." Industria Textila 71, no. 01 (February 27, 2020): 33–40. http://dx.doi.org/10.35530/it.071.01.1642.
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Water footprint standards established by the International Standardization Organization (ISO), this paper proposed a newquantitative indicator for water alkalization, and calculated the water footprints involved in viscose textile production. Inaddition, water footprint accounting results were comprehensively evaluated by LCA polygon method which wasdeveloped to interpret LCA results. Results showed that: (1) water scarcity footprint of viscose textile production was60.511 m3H2O eq/ton, of which 85.71% was from the viscose fiber production; (2) water eutrophication footprint ofviscose textile production was 12.439 kg PO43–eq/ton, the major contribution (84.37%) was given by COD and BOD5;(3) water acidification footprint and water alkaline footprint of viscose textile production were 81.453 kg SO2eq/ton and55.675 kg OH–eq/ton, mainly due to H2SO4and NaOH input during the spinning process, respectively; (4) waterecotoxicity footprint of viscose textile production was 3828.169 km3H2O eq/ton, mainly derived from Zn2+in spinningwastewater; (5) LCA polygon analyses showed that environmental load in the spinning was the largest, followed by thepulping and then the dyeing.Keywords:viscose textile, wa
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Thanh Canh, Truong, Thuy-Trang Thi Nguyen, and Anh Hoang Le. "Water footprint assessment for citizens in Ho Chi Minh city." Science and Technology Development Journal - Natural Sciences 4, no. 1 (December 21, 2020): first. http://dx.doi.org/10.32508/stdjns.v4i1.1001.
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The research conducted a survey of the water consumption in Ho Chi Minh City through the consumption of products from agriculture, industry and domestic. The research identified green water, blue water and grey water footprints in consuming products. Then personal water footprints were calculated and evaluated. The results showed that the average personal water footprint in district 3 was 1556 m3/year (77.15% for agriculture, 15.59% for industry and 7.26% for domestic), district 10 was 1587 m3/year (77.58% for agriculture, 15.17% for industry and 7.25% domestic), Nha Be district is 1681 m3/year (80.48% for agriculture, 12.97% for industry and 6.55% for domestic) and Binh Chanh district was 1744 m3/year (81.57% for agriculture, 11.88% for industry and 6.55% for domestic). In the individual components of the water footprint, water footprints in consuming agricultural products accounted for the major percentage and determined the personal water footprint. The results showed that the individual water footprints in countryside areas were higher than those in urban areas. Depending on the amount and forms of each individual's consumption, their eating habit and daily activities, and the sexes, the personal water footprints were different. The perception and behavior of individuals' water consumption also significantly influenced the overall personal water footprints.
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Kong, Vickie, Mark Jason Cassidy, and Christophe Gaudin. "Experimental study of effect of geometry on reinstallation of jack-up next to footprint." Canadian Geotechnical Journal 50, no. 5 (May 2013): 557–73. http://dx.doi.org/10.1139/cgj-2012-0381.
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Mobile jack-up drilling rigs often need to return to a site where a previous installation has left footprints in the seabed. Reinstallation near these depressions is a problematic operation because the jack-up's circular spudcan footings become subjected to eccentric and (or) inclined loading conditions. This can lead to structural failures within the jack-up legs and (or) excessive leg tilt and hull displacement. This paper reports a comprehensive set of geotechnical centrifuge experiments that investigated the effect of footprint geometry on the reinstallation response. Artificial conical shaped footprints were manually cut in the centrifuge sample, ensuring consistent shapes and minimizing any variation of undrained shear strength due to the process of initially installing and retrieving a spudcan. The effect of footprint geometry was thereby isolated. The vertical, horizontal, and moment loads induced on a model footing when penetrated at varying offsets are presented and these provide evidence on the effect of different footprint depths and angles on installation. The footprint geometry governed the horizontal force and moment observed during reinstallation between the level of the touchdown and the footprint toe. Further experimentation has shown that an equivalent skirted footing induced significantly higher horizontal forces (although it can be assumed to be significantly stiffer).
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Fascione, Jeanna M., Ryan T. Crews, and James S. Wrobel. "Dynamic Footprint Measurement Collection Technique and Intrarater Reliability." Journal of the American Podiatric Medical Association 102, no. 2 (March 1, 2012): 130–38. http://dx.doi.org/10.7547/1020130.
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Background: Identifying the variability of footprint measurement collection techniques and the reliability of footprint measurements would assist with appropriate clinical foot posture appraisal. We sought to identify relationships between these measures in a healthy population. Methods: On 30 healthy participants, midgait dynamic footprint measurements were collected using an ink mat, paper pedography, and electronic pedography. The footprints were then digitized, and the following footprint indices were calculated with photo digital planimetry software: footprint index, arch index, truncated arch index, Chippaux-Smirak Index, and Staheli Index. Differences between techniques were identified with repeated-measures analysis of variance with post hoc test of Scheffe. In addition, to assess practical similarities between the different methods, intraclass correlation coefficients (ICCs) were calculated. To assess intrarater reliability, footprint indices were calculated twice on 10 randomly selected ink mat footprint measurements, and the ICC was calculated. Results: Dynamic footprint measurements collected with an ink mat significantly differed from those collected with paper pedography (ICC, 0.85–0.96) and electronic pedography (ICC, 0.29–0.79), regardless of the practical similarities noted with ICC values (P = .00). Intrarater reliability for dynamic ink mat footprint measurements was high for the footprint index, arch index, truncated arch index, Chippaux-Smirak Index, and Staheli Index (ICC, 0.74–0.99). Conclusions: Footprint measurements collected with various techniques demonstrate differences. Interchangeable use of exact values without adjustment is not advised. Intrarater reliability of a single method (ink mat) was found to be high. (J Am Podiatr Med Assoc 102(2): 130–138, 2012)
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Jursova, Simona, Dorota Burchart-Korol, and Pavlina Pustejovska. "Carbon Footprint and Water Footprint of Electric Vehicles and Batteries Charging in View of Various Sources of Power Supply in the Czech Republic." Environments 6, no. 3 (March 26, 2019): 38. http://dx.doi.org/10.3390/environments6030038.
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In the light of recent developments regarding electric vehicle market share, we assess the carbon footprint and water footprint of electric vehicles and provide a comparative analysis of energy use from the grid to charge electric vehicle batteries in the Czech Republic. The analysis builds on the electricity generation forecast for the Czech Republic for 2015–2050. The impact of different sources of electricity supply on carbon and water footprints were analyzed based on electricity generation by source for the period. Within the Life Cycle Assessment (LCA), the carbon footprint was calculated using the Intergovernmental Panel on Climate Change (IPCC) method, while the water footprint was determined by the Water Scarcity method. The computational LCA model was provided by the SimaPro v. 8.5 package with the Ecoinvent v. 3 database. The functional unit of study was running an electric vehicle over 100 km. The system boundary covered an electric vehicle life cycle from cradle to grave. For the analysis, we chose a vehicle powered by a lithium-ion battery with assumed consumption 19.9 kWh/100 km. The results show that electricity generated to charge electric vehicle batteries is the main determinant of carbon and water footprints related to electric vehicles in the Czech Republic. Another important factor is passenger car production. Nuclear power is the main determinant of the water footprint for the current and future electric vehicle charging, while, currently, lignite and hard coal are the main determinants of carbon footprint.
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Xu, Chang Chun, Yao Wu, Hao Jia, and Fu Chen. "Product Water Footprinting: Application with Milk Products at Brand Level." Applied Mechanics and Materials 522-524 (February 2014): 925–29. http://dx.doi.org/10.4028/www.scientific.net/amm.522-524.925.
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The production and consumption of products and services exert much pressure on hydrological cycle. Water footprint is a popular indicator quantifying both direct and indirect water use of a product or service. In this article, water footprints were calculated for three milk products, 180g Yogurt, 250mL Fluid milk and 400g Skim milk powder (SMP) at product brand (YiYi®) level. The process LCA-based water footprint method was applied using primary production data, with both volumetric and stress-weighted results reported. Water footprint values were compared among different life cycle stages and products, and possible mitigation strategies to minimize the burden on freshwater systems from consumptive water use were raised. The results demonstrated the suitability of water footprint as streamlined indicator for product sustainability management and affirmed the importance of farming stage for water footprint reduction.
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Multsch, S., Y. A. Al-Rumaikhani, H. G. Frede, and L. Breuer. "A site-specific agricultural water requirement and footprint estimator (SPARE:WATER 1.0) for irrigation agriculture." Geoscientific Model Development Discussions 6, no. 1 (January 29, 2013): 645–84. http://dx.doi.org/10.5194/gmdd-6-645-2013.
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Abstract. The water footprint accounting method addresses the quantification of water consumption in agriculture, whereby three types of water to grow crops are considered, namely green water (consumed rainfall), blue water (irrigation from surface or groundwater) and grey water (water needed to dilute pollutants). Most of current water footprint assessments focus on global to continental scale. We therefore developed the spatial decision support system SPARE:WATER that allows to quantify green, blue and grey water footprints on regional scale. SPARE:WATER is programmed in VB.NET, with geographic information system functionality implemented by the MapWinGIS library. Water requirement and water footprints are assessed on a grid-basis and can then be aggregated for spatial entities such as political boundaries, catchments or irrigation districts. We assume in-efficient irrigation methods rather than optimal conditions to account for irrigation methods with efficiencies other than 100%. Furthermore, grey water can be defined as the water to leach out salt from the rooting zone in order to maintain soil quality, an important management task in irrigation agriculture. Apart from a thorough representation of the modelling concept we provide a proof of concept where we assess the agricultural water footprint of Saudi Arabia. The entire water footprint is 17.0 km3 yr−1 for 2008 with a blue water dominance of 86%. Using SPARE:WATER we are able to delineate regional hot spots as well as crop types with large water footprints, e.g. sesame or dates. Results differ from previous studies of national-scale resolution, underlining the need for regional water footprint assessments.
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Zhang, Peng, Zihan Xu, Weiguo Fan, Jiahui Ren, Ranran Liu, and Xiaobin Dong. "Structure Dynamics and Risk Assessment of Water-Energy-Food Nexus: A Water Footprint Approach." Sustainability 11, no. 4 (February 23, 2019): 1187. http://dx.doi.org/10.3390/su11041187.
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The “Water-Energy-Food Nexus” is one of the present research hotspots in the field of sustainable development. Water resources are the key factors that limit local human survival and socioeconomic development in arid areas, and the water footprint is an important indicator for measuring sustainable development. In this study, the structural dynamics and complex relationships of the water-energy-food system in arid areas were analyzed from the perspective of the water footprint, and the risk characteristics were evaluated. The results show that: (1) Agriculture products and livestock products account for the largest water footprints (>90%), which is much higher than the water footprints of energy consumption (<5%). From the water footprint type, the blue water footprint (>50%) > the grey water footprint (20%–30%) > the green water footprint (<20%). (2) Since 2000, especially after 2005, while energy consumption drove rapid economic growth, it also led to the rapid expansion of the water footprint in the Manas River Basin. By 2015, the water deficit was relatively serious, with the surface water resource deficit reaching 16.21 × 108 m3. (3) The water-energy risk coupling degree of the water-energy-food system in this basin is comparatively significant, which means that it is facing the dual pressures of internal water shortage and external energy dependence, and it is vulnerable to global warming and fluctuations in the international and domestic energy markets. Thus, it is necessary to adjust the industrial structure through macroeconomic regulation and control, developing new energy sources, reducing the coupling degree of system risks, and achieving sustainable development.
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Bushuyev, Sergey, Denis Bushuiev, Victoria Bushuieva, and Natalia Bushuieva. "CONCEPTUAL MODEL OF DIGITAL TRACE OF PROJECTS IN THE CONDITIONS OF DIGITALIZATION OF SOCIETY." Management of Development of Complex Systems, no. 46 (June 24, 2021): 12–18. http://dx.doi.org/10.32347/2412-9933.2021.46.12-18.
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The problem of creating an effective conceptual model for the formation of digital footprints of projects and development programs in the context of digitalization is considered. The life cycle of projects, knowledge, and management technologies is significantly shortened and digitization processes create requirements for the creation of their digital footprints and shadows. The technical and technological complexity of development projects increases due to innovation. These trends create significant challenges in the development of project and program management systems in the context of digitalization of society. It is proposed to use genomic representations as a basic model and methodology for the formation of digital footprints of projects. The proposed conceptual model of digital footprint formation of projects allows to take into account the external and internal environment of the project within a certain activity. The formalized model of the carrier of methodology of formation of a digital footprint of the project on the basis of system of knowledge of P2M is resulted. The classes of a hypothetically complete model of project management methodology for genome formation within the digital footprint creation are determined. The algebra of methodology which allows to form complex digital footprints of projects and programs is defined.
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Maré, Frikkie Alberts, Henry Jordaan, and Mesfin Mergia Mekonnen. "The Water Footprint of Primary Cow–Calf Production: A Revised Bottom-Up Approach Applied on Different Breeds of Beef Cattle." Water 12, no. 9 (August 19, 2020): 2325. http://dx.doi.org/10.3390/w12092325.
Full textAbstract:
Beef has been identified as the farm animal product with the largest total water footprint in previous research, although various concerns have been raised regarding the top-down analyses approach followed in these studies. The objective of this study was to estimate the water footprint of weaned calves and culled cows from seven different beef breeds by applying a revised water footprint analyses approach. A bottom-up approach was followed to provide a true representation of the production system, and the water footprint of the production system, with the estimated water footprint for the system being allocated to weaned calves and culled cows according to the value factor of each. The results show that there are prominent differences between the seven breeds in terms of their respective water footprints per kilogram weaned calf, even though the total water footprint per herd for each breed revealed little variation between the breeds. There is a 45% difference between the breed with the lowest and the breed with the highest water footprint per kg calf. This knowledge can be applied by both water users (primary producers) and policy formulators to assist in the optimal use of fresh water for beef production.
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Fan, Xiaomei, Hongguang Liu, and Mengmeng Wang. "Study on the Agricultural Land Transfer Embodied in Inter-Provincial Trade in China." Land 11, no. 5 (April 29, 2022): 656. http://dx.doi.org/10.3390/land11050656.
Full textAbstract:
The research on the land resources embodied in the inter-regional economic linkages is of great significance for the ecological compensation and sustainable use of the cultivated land. We constructed a model to estimate the agricultural land transfer embodied in inter-regional trade by using the agricultural land footprint model and the multi-regional input–output model. Taking China as an example, using a 2017 multi-regional input–output table and agricultural land and production data, we evaluated the agricultural land footprints embodied in the inter-provincial demand–supply chain in China and explored their characteristics, revealing the balance of income and expenditure that makes up the agricultural land footprint in each region. The results show that: (1) In 2017, China’s total agricultural land footprint was 557.63 million ha2. Developed areas such as Shandong, Guangdong, and Jiangsu in the East generally had a greater footprint than the underdeveloped areas in the west. Provinces with more agricultural land do not necessarily have larger agricultural footprints. (2) The Agriculture, Hunting, Forestry, and Fishing industry and the Food, Beverages, and Tobacco industry were the main two sectors that contributed to the agricultural land footprint for each province, accounting for more than 60% of the total agricultural land footprint in China. (3) The embodied agricultural land transfer between regions showed two main directions on the whole: one was from north to south and the other from west to east, reflecting the transfer law of movement from the less developed regions to those that were more developed.
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Yin, Changchun, Xin Huang, Yunhe Liu, and Jing Cai. "Footprint for frequency-domain airborne electromagnetic systems." GEOPHYSICS 79, no. 6 (November 1, 2014): E243—E254. http://dx.doi.org/10.1190/geo2014-0007.1.
Full textAbstract:
An airborne electromagnetic (AEM) survey often covers hundreds of square kilometers. Huge amounts of survey data make 2D/3D data inversion very difficult. However, due to the compact configurations of AEM systems, the sensitive area for each single survey station is much smaller than the whole survey area, which makes it possible to only invert partial survey data. The sensitive area is called the footprint. Based on “moving-footprint” technology, the entire survey can be divided into subareas and the data are first inverted individually and then combined to form the inversions of the entire survey area, so that the cost for forward and inverse modeling can be vastly reduced. Contrary to previous electromagnetic (EM) footprints defined only for an EM transmitter or for a perfectly conductive earth, we defined the frequency-domain AEM footprint by considering a complete AEM transmitter-receiver system over an earth with limited conductivity. We used the tensor Green’s function to calculate the secondary magnetic field from the induced underground current and evaluate the EM footprint as the volume in which the induced current contributes 90% to the total secondary magnetic field at the EM receiver. Numerical experiments for horizontal coplanar and vertical coaxial coil configurations revealed that among all influence factors on the AEM footprint, the flight altitude was dominant, with a high flight altitude corresponding to a large EM footprint, whereas the transmitting frequency and earth resistivity played a secondary role and in a combined way of induction number, with the low frequency or high earth resistivity (small induction number) corresponding to large EM footprints.
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Jackson, S. M., C. A. Keech, D. J. Williamson, and A. Gutierrez-Hartmann. "Interaction of basal positive and negative transcription elements controls repression of the proximal rat prolactin promoter in nonpituitary cells." Molecular and Cellular Biology 12, no. 6 (June 1992): 2708–19. http://dx.doi.org/10.1128/mcb.12.6.2708-2719.1992.
Full textAbstract:
The proximal rat prolactin (rPRL) promoter contains three cell-specific elements, designated footprints I, III, and IV, which restrict rPRL gene expression to anterior pituitary lactotroph cells. Footprint II (-130 to -120) binds a factor, which we have termed F2F, present in pituitary and nonpituitary cell types. Here we demonstrate that a key role of the footprint II site is to inhibit rPRL promoter activity in nonpituitary cells, specifically, by interfering with the basal activating function of a vicinal element. Gene transfer analysis revealed 20-fold activation of the rPRL promoter in nonpituitary cell types when footprint II was either deleted or specifically mutated. Similar activation of the intact rPRL promoter was obtained by in vivo F2F titration studies. In GH4 rat pituitary cells, the footprint II inhibitory activity was masked by the redundant, positively acting cell-specific elements and was inhibitory only if the two upstream sites, footprints III and IV, were deleted. Deletion of the -112 to -80 region in the footprint II site-specific mutant background resulted in complete loss of rPRL promoter activity in both pituitary and nonpituitary cell types, mapping a basal activating element that is operative irrespective of cell type to this region. While the basal activating element imparted an activating function in a heterologous promoter assay, the footprint II sequence did not display any inherent repressor function and actually induced several minimal heterologous promoters. However, the inhibitory activity of the footprint II site was detected only if it was in context with the basal activating element. These data underscore the importance of ubiquitous activating and inhibitory factors in establishing cell-specific gene expression and further emphasize the complexity of the molecular mechanisms which restrict gene expression to specific cell types. We provide a novel paradigm to study rPRL promoter function and hormone responsiveness independently of lactotroph cell-specific requirements.
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Jackson, S. M., C. A. Keech, D. J. Williamson, and A. Gutierrez-Hartmann. "Interaction of basal positive and negative transcription elements controls repression of the proximal rat prolactin promoter in nonpituitary cells." Molecular and Cellular Biology 12, no. 6 (June 1992): 2708–19. http://dx.doi.org/10.1128/mcb.12.6.2708.
Full textAbstract:
The proximal rat prolactin (rPRL) promoter contains three cell-specific elements, designated footprints I, III, and IV, which restrict rPRL gene expression to anterior pituitary lactotroph cells. Footprint II (-130 to -120) binds a factor, which we have termed F2F, present in pituitary and nonpituitary cell types. Here we demonstrate that a key role of the footprint II site is to inhibit rPRL promoter activity in nonpituitary cells, specifically, by interfering with the basal activating function of a vicinal element. Gene transfer analysis revealed 20-fold activation of the rPRL promoter in nonpituitary cell types when footprint II was either deleted or specifically mutated. Similar activation of the intact rPRL promoter was obtained by in vivo F2F titration studies. In GH4 rat pituitary cells, the footprint II inhibitory activity was masked by the redundant, positively acting cell-specific elements and was inhibitory only if the two upstream sites, footprints III and IV, were deleted. Deletion of the -112 to -80 region in the footprint II site-specific mutant background resulted in complete loss of rPRL promoter activity in both pituitary and nonpituitary cell types, mapping a basal activating element that is operative irrespective of cell type to this region. While the basal activating element imparted an activating function in a heterologous promoter assay, the footprint II sequence did not display any inherent repressor function and actually induced several minimal heterologous promoters. However, the inhibitory activity of the footprint II site was detected only if it was in context with the basal activating element. These data underscore the importance of ubiquitous activating and inhibitory factors in establishing cell-specific gene expression and further emphasize the complexity of the molecular mechanisms which restrict gene expression to specific cell types. We provide a novel paradigm to study rPRL promoter function and hormone responsiveness independently of lactotroph cell-specific requirements.
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Bates, K. T., R. Savage, T. C. Pataky, S. A. Morse, E. Webster, P. L. Falkingham, L. Ren, et al. "Does footprint depth correlate with foot motion and pressure?" Journal of The Royal Society Interface 10, no. 83 (June 6, 2013): 20130009. http://dx.doi.org/10.1098/rsif.2013.0009.
Full textAbstract:
Footprints are the most direct source of evidence about locomotor biomechanics in extinct vertebrates. One of the principal suppositions underpinning biomechanical inferences is that footprint geometry correlates with dynamic foot pressure, which, in turn, is linked with overall limb motion of the trackmaker. In this study, we perform the first quantitative test of this long-standing assumption, using topological statistical analysis of plantar pressures and experimental and computer-simulated footprints. In computer-simulated footprints, the relative distribution of depth differed from the distribution of both peak and pressure impulse in all simulations. Analysis of footprint samples with common loading inputs and similar depths reveals that only shallow footprints lack significant topological differences between depth and pressure distributions. Topological comparison of plantar pressures and experimental beach footprints demonstrates that geometry is highly dependent on overall print depth; deeper footprints are characterized by greater relative forefoot, and particularly toe, depth than shallow footprints. The highlighted difference between ‘shallow’ and ‘deep’ footprints clearly emphasizes the need to understand variation in foot mechanics across different degrees of substrate compliance. Overall, our results indicate that extreme caution is required when applying the ‘depth equals pressure’ paradigm to hominin footprints, and by extension, those of other extant and extinct tetrapods.
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Hu, Yaohui, Chun Liu, Zheng Li, Junkui Xu, Zhigang Han, and Jianzhong Guo. "Few-Shot Building Footprint Shape Classification with Relation Network." ISPRS International Journal of Geo-Information 11, no. 5 (May 14, 2022): 311. http://dx.doi.org/10.3390/ijgi11050311.
Full textAbstract:
Buildings are important entity objects of cities, and the classification of building shapes plays an indispensable role in the cognition and planning of the urban structure. In recent years, some deep learning methods have been proposed for recognizing the shapes of building footprints in modern electronic maps. Furthermore, their performance depends on enough labeled samples for each class of building footprints. However, it is impractical to label enough samples for each type of building footprint shapes. Therefore, the deep learning methods using few labeled samples are more preferable to recognize and classify the building footprint shapes. In this paper, we propose a relation network based method for the recognization of building footprint shapes with few labeled samples. Relation network, composed of embedding module and relation module, is a metric based few-shot method which aims to learn a generalized metric function and predict the types of the new samples according to their relation with the prototypes of these few labeled samples. To better extract the shape features of the building footprints in the form of vector polygons, we have taken the TriangleConv embedding module to act as the embedding module of the relation network. We validate the effectiveness of our method based on a building footprint dataset with 10 typical shapes and compare it with three classical few-shot learning methods in accuracy. The results show that our method performs better for the classification of building footprint shapes with few labeled samples. For example, the accuracy reached 89.40% for the 2-way 5-shot classification task where there are only two classes of samples in the task and five labeled samples for each class.