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AbstractThis special issue was written to reflect on the current role of human rights in the United Kingdom, seventy years after the United Nations General Assembly voted in favour of the Universal Declaration of Human Rights. Human rights are explored by the authors in this issue from a wide variety of perspectives. Some authors are critical of the failure of the state to implement human rights principles in practice; others lament how human rights often appear of little relevance to most people's lives in the UK. The overall message, however, remains consistent: a human rights framework brings many positive elements to our country, ensuring it is a society where individuals, no matter their actions or characteristics, are treated with dignity.

This report documents the program of the Dagstuhl Seminar 12381 "Privacy-Oriented Cryptography", which took place at Schloss Dagstuhl in September 16-21, 2012. Being the first Dagstuhl seminar that explicitly aimed to combine cryptography and privacy research communities, it attracted a high number of participants, many of whom were new to Dagstuhl. In total, the seminar was attended by 39 international researchers, working in different areas of cryptography and privacy, from academia, industry, and governmental organizations. The seminar included many interactive talks on novel, so-far unpublished results, aiming at the design, analysis, and practical deployment of cryptographic mechanisms for protecting privacy of users and data. The seminar featured two panel discussions to address various approaches towards provable privacy and different challenges but also success stories for practical deployment of existing cryptographic privacy-oriented techniques.

We consider privacy-preserving learning in the context of online learning. Insettings where data instances arrive sequentially in streaming fashion, incremental trainingalgorithms such as stochastic gradient descent (SGD) can be used to learn and updateprediction models. When labels are costly to acquire, active learning methods can beused to select samples to be labeled from a stream of unlabeled data. These labeled datasamples are then used to update the machine learning models. Privacy-preserving onlinelearning can be used to update predictors on data streams containing sensitive information.The differential privacy framework quantifies the privacy risk in such settings. This workproposes a differentially private online active learning algorithm using stochastic gradientdescent (SGD) to retrain the classifiers. We propose two methods for selecting informativesamples. We incorporated this into a general-purpose web application that allows a non-expert user to evaluate the privacy-aware classifier and visualize key privacy-utility tradeoffs.Our application supports linear support vector machines and logistic regression and enablesan analyst to configure and visualize the effect of using differentially private online activelearning versus a non-private counterpart. The application is useful for comparing theprivacy/utility tradeoff of different algorithms, which can be useful to decision makers inchoosing which algorithms and parameters to use. Additionally, we use the application toevaluate our SGD-based solution and to show that it generates predictions with a superiorprivacy-utility tradeoff than earlier methods.

Accurate assessment of anthropogenic carbon dioxide ( CO2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere - the "global carbon budget" - is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions ( E FF ) are based on energy statistics and cement production data, while emissions from land use and land-use change ( E LUC ), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate ( G ATM ) is computed from the annual changes in concentration. The ocean CO2 sink ( S OCEAN ) and terrestrial CO2 sink ( S LAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance ( B IM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1 σ . For the last decade available (2008-2017), E FF was 9.4±0.5 GtC yr ĝ'1 , E LUC 1.5±0.7 GtC yr ĝ'1 , G ATM 4.7±0.02 GtC yr ĝ'1 , S OCEAN 2.4±0.5 GtC yr ĝ'1 , and S LAND 3.2±0.8 GtC yr ĝ'1 , with a budget imbalance B IM of 0.5 GtC yr ĝ'1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in E FF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr ĝ'1 . Also for 2017, E LUC was 1.4±0.7 GtC yr ĝ'1 , G ATM was 4.6±0.2 GtC yr ĝ'1 , S OCEAN was 2.5±0.5 GtC yr ĝ'1 , and S LAND was 3.8±0.8 GtC yr ĝ'1 , with a B IM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6-9 months indicate a renewed growth in E FF of + 2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959-2017, but discrepancies of up to 1 GtC yr ĝ'1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013).

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1, SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of 0.5 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017, ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013)

Accurate assessment of anthropogenic carbon dioxide (CO₂) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO₂ emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO₂ concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO₂ sink (SOCEAN) and terrestrial CO₂ sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was 9.4 ± 0.5 GtC yr⁻¹, ELUC 1.5 ± 0.7 GtC yr⁻¹ , GATM 4.7 ± 0.02 GtC yr⁻¹, SOCEAN 2.4 ± 0.5 GtC yr⁻¹, and SLAND 3.2 ± 0.8 GtC yr⁻¹ , with a budget imbalance BIM of 0.5 GtC yr⁻¹ indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9 ± 0.5 GtC yr⁻¹. Also for 2017, ELUC was 1.4 ± 0.7 GtC yr⁻¹ , GATM was 4.6 ± 0.2 GtC yr⁻¹, SOCEAN was 2.5 ± 0.5 GtC yr⁻¹, and SLAND was 3.8 ± 0.8 GtC yr⁻¹, with a BIM of 0.3 GtC. The global atmospheric CO₂ concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr⁻¹ persist for the representation of semi-decadal variability in CO₂ fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO₂ flux in the northern extra-tropics, and (3) an apparent underestimation of the CO₂ variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013)

Accurate assessment of anthropogenic carbon dioxide ( CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO 2 emissions ( E FF ) are based on energy statistics and cement production data, while emissions from land use and land-use change ( E LUC ), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO 2 concentration is measured directly and its growth rate ( G ATM ) is computed from the annual changes in concentration. The ocean CO 2 sink ( S OCEAN ) and terrestrial CO 2 sink ( S LAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance ( B IM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1 σ . For the last decade available (2008–2017), E FF was 9.4±0.5 GtC yr −1 , E LUC 1.5±0.7 GtC yr −1 , G ATM 4.7±0.02 GtC yr −1 , S OCEAN 2.4±0.5 GtC yr −1 , and S LAND 3.2±0.8 GtC yr −1 , with a budget imbalance B IM of 0.5 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in E FF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr −1 . Also for 2017, E LUC was 1.4±0.7 GtC yr −1 , G ATM was 4.6±0.2 GtC yr −1 , S OCEAN was 2.5±0.5 GtC yr −1 , and S LAND was 3.8±0.8 GtC yr −1 , with a B IM of 0.3 GtC. The global atmospheric CO 2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in E FF of + 2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr −1 persist for the representation of semi-decadal variability in CO 2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO 2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO 2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018 .