Wrong State Research Articles

Structural prediction of carbon cluster isomers with machine-learning potential

Structural prediction of low-energy isomers of carbon twelve-atom clusters is carried out using the recently developed machine-learning potential GAP-20. The GAP-20 agrees with density-functional theory calculations regarding geometric structures and average C-C bond lengths for most isomers. However, the GAP-20 substantially lowers the energies of cage-like structures, resulting in a wrong ground state. A comparison of the cohesive energies with the density-functional theory points out that the GAP-20 only gives good results for monocyclic rings. Two multicyclic rings appear as new low-energy isomers, which have yet to be discovered in previous research.

A Finite Memory Approach Applied to Verified Pseudo State Estimation of Fractional Models of Lithium-Ion Batteries

Fractional equivalent circuit models have been used in numerous publications to represent long-term memory phenomena of the charging/discharging behavior of Lithium-ion batteries. However, despite the fact that fractional models allow for capturing (infinite horizon) memory properties, the same feature also complicates the numerical evaluation. This is especially critical in cases, in which state estimation procedures are implemented that need to be executed in real time. For this type of applications, it is necessary that the execution time in each time step is bounded a-priori and that it does not grow over time. For that purpose, classical simulation approaches exploit, for example, Grünwald-Letnikov schemes with a finite length of previous state information. However, truncating the memory window without considering the arising errors may lead to wrong state estimates. This is especially critical if interval observers are designed which are meant to include the sets of reachable states with certainty.

Field induced metamagnetic transition and mixed charge transfer Mott-Hubbard character in nanocrystalline FeCo2O4 spinel oxide: A combined study using experimental and first principles techniques

Unusual magnetic behavior of nanocrystalline FeCo2O4 (FCO) has been observed at different annealing temperatures. FCO nanoparticles have been prepared by co-precipitation method and the prepared sample annealed at different temperatures to vary its crystallite size. The powder x-ray diffraction analysis confirms the presence of pure spinel phase in the samples annealed at 900 ℃ and 1000℃. The increase in particle size with annealing temperature has been confirmed by field emission scanning electron microscopy (FESEM) analysis. High resolution x-ray photoelectron spectroscopy (HRXPS) analysis reveals the presence of mixed oxidation states of Fe+2/ Fe+3 and Co+3/Co+2 in the sample annealed at 900℃. The as-synthesized sample at 80 °C shows strong antiferromagnetic behavior due to their smaller particle size, but all the annealed samples have strong ferromagnetic behavior with large coercive field and remanence due to their larger particle size. We have observed a sharp rise in magnetization near small field values in the virgin curve and also the presence of virgin curve completely outside the main hysteresis loop in the M(H) curves measured at 5 K for the samples annealed at and above 1000 ℃ reveal the characteristic of first order nature of field induced metamagnetic transition. Structural parameters obtained after Rietveld refinement of powder x-ray diffraction pattern for sample annealed at 900 ℃ have been used for investigating the magnetic properties using first principles density functional theory. Our calculations using hybrid exchange-correlation functional, HSE06 captures the correct insulating ferromagnetic ground state and band gap for inverse spinel structure in broad agreement with our experimental results while calculations within GGA+U leads to a wrong half metallic ferromagnetic ground state. The partial density of states obtained for inverse spinel structure with HSE06 functional suggests a mixed charge transfer and Mott-Hubbard character in our system. We have explored the interplay among structural, magnetic and transport properties of FCO using experiment as well as first principles density functional theory.

SKDCPM algorithm can improve the single-trial decoding performance of very similar error-related potentials.

Error related potential (ErrP) is an effective control signal for the brain-computer interface (BCI). Current ErrP decoding methods can only distinguish right and wrong mental states. However, in real scenarios, error conditions often contain more detailed information, such as the degree of error, which would induce very similar ErrPs. Distinguishing such ErrPs effectively is of vital importance to provide more detailed information for optimizing BCIs. Hereto, a major challenge is the EEG differences of very similar ErrPs are very small. Thus, it is necessary to develop new efficient method for decoding very similar ErrPs. This study newly proposed an algorithm named shrinkage discriminant canonical pattern matching (SKDCPM), and compared its decoding results with the linear discriminant analysis (LDA), shrinkage LDA (SKLDA), stepwise LDA (SWLDA), Bayesian LDA (BLDA) and the DCPM, which were algorithms commonly used for ErrP decoding. A data set of 18 subjects was built, it had four conditions, i.e., right (0°), errors with varying degrees, i.e., 45°, 90°, 180° deviation from the predicted direction. As a result, the SKDCPM had high balanced accuracy (BACC) in right-wrong classification (0° vs. others). More importantly, it achieved a grand averaged BACC of 69.54% with the highest up to 74.25%, which outperformed all the other algorithms in very similar ErrPs decoding (45° vs. 90° vs. 180°) significantly. This study could provide new decoding methods for developing the ErrP-based BCI system.

Lack of robustness and accuracy of many numerical schemes for phase-field simulations

In this paper, we study the stability, accuracy and convergence behavior of various numerical schemes for phase-field modeling through a simple ODE model. Both theoretical analysis and numerical experiments are carried out on this ODE model to demonstrate the limitation of most numerical schemes that have been used in practice. One main conclusion is that the first-order fully implicit scheme is the only robust algorithm for phase-field simulations while all other schemes (that have been analyzed) may have convergence issue if the time step size is not exceedingly small. More specifically, by rigorous analysis in most cases, we have the following conclusions: (i) The first-order fully implicit scheme converges to the correct steady state solution for all time step sizes. In the case of multiple solutions, one of the solution branches always converges to the correct steady state solution. (ii) The first-order convex splitting scheme, which is equivalent to the first-order fully implicit scheme with a different time scaling, always converges to the correct steady state solution but may seriously lack numerical accuracy for transient solutions. (iii) For the second-order fully implicit and convex splitting schemes, for any time step size [Formula: see text], there exists an initial condition [Formula: see text], with [Formula: see text], such that the numerical solution converges to the wrong steady state solution. (iv) For [Formula: see text], all second-order schemes studied in this paper converge to the correct steady state solution although severe numerical oscillations occur for most of them if the time step size is not sufficiently small. (v) An unconditionally energy-stable scheme (such as the modified Crank–Nicolson scheme) is not necessarily better than a conditionally energy-stable scheme (such as the Crank–Nicolson scheme). Most, if not all, of the above conclusions are expected to be true for more general Allen–Cahn and other phase-field models.

Investigation of the running-in process in photoinduced superlubricity

Photoinduced superlubricity on TiO2 surfaces is a newfound phenomenon which draws researchers’ attention. This study provides a new method to achieve superlubricity (COF<0.01) with an external light field. However, photoinduced superlubricity can only be realized under specific conditions. Improper running-in conditions, such as speed, load, and pH value, will lead to superlubricity failure even after ultraviolet illumination on the TiO2 surface. In this paper, different running-in loads, speeds, or pH values were used in the experiment of photoinduced superlubricity, and the worn surfaces after running-in and testing in 70% v/v glycerol aqueous solution were investigated thoroughly. Results reveal that the morphology of worn scars differs under different running-in conditions. While the running-in speeds and loads are too low (<0.03 m/s and <2 N) or too large (>0.1 m/s and >9 N), the photoinduced superlubricity will fail because of wrong lubrication state. When the pH value of running-in solution is less than 4.5, photoinduced superlubricity is easier to achieve. In discuss, mixed lubrication is believed to be the key to success of photoinduced superlubricity, because the elastohydrodynamic effect, doublelayer effect and adsorption of glycerol molecules works at the same time. In addition, due to the formation of the SiO2 layer on the Si3N4 ball and better attraction to lubricant molecules with hydroxyl radicals on the TiO2 surface, running-in in solutions with low pH values contributes to the success of photoinduced superlubricity. In any event, the ultraviolet illumination can reduce the friction coefficient of the TiO2/Si3N4 tribological system and can realize photoinduced superlubricity under appropriate running-in conditions.

Personality Traits and Voluntary Leaving Organization in Selected Government Establishments in Akwa Ibom State, Nigeria

This study was designed to examine the relationship between personality traits and voluntary leaving organization in selected government establishments in Akwa Ibom State. To achieve the study objective, a survey research design was used. The population of the study consisted 90 senior staff in personnel Department from the Ministries of Agriculture, Finance and Information in Akwa Ibom State. A total sample size of 60 respondents were selected using stratified random sampling technique. Data were collected through questionnaire titled “Personality Traits and Voluntary Leaving Organization Questionnaire (PTVLOQ)” carefully designed and administered to the respondents. A total of 60 copies of questionnaire were distributed to respondents, out of which 58 copies were returned and found to be correctly filled. Data collected were analyzed using tables, simple percentage and Regression. The result of the study showed a positive significant relationship between personality traits and voluntary leaving organization in selected government establishments in ty.ectiveness in organization'toor management of personnel.ibilities , assignment of the right jobs to wrong and unq Akwa Ibom State. The findings also revealed that employees who scored high in openness to experience as well as neuroticism are bound to make a voluntary decision to leave their organizations. It was recommended from the study that, government establishments in Akwa Ibom State should introduce and maintain a fair and effective reward system for outstanding performances so as to motivate employees to always put in their best and remain in their organizations.

Research on the Mechanism of the Stiffness Performance of Rolling Bearings under Wrong Assembly State

In this paper, a quasi-static angular contact ball bearing model, considering assembly accuracy is constructed, while a numerical solution method for bearing stiffness under bad assembly state is established. A 7014C angular contact ball bearing is used as the research object and five groups of different spacer inclinations are designed to imitate the installation error of the spindle bearing. The bearing stiffness performance was comparatively analyzed, according to the five spacers. The effect of preload and rotation speed on bearing stiffness are systematically investigated, considering different parallelism errors, as induced by the spacers. The influence mechanism of the badly assembled bearing on the respective stiffness anisotropy is studied based on the proposed model. The results show that the variations of the inclination between the inner and outer rings of the bearing exhibit a very weak effect on the axial stiffness, while the influence on the radial and angular stiffness is more significant.

Mining Knowledge from Crystal Structures: Oxidation States of Oxygen-Coordinated Metal Atoms in Ionic and Coordination Compounds.

We propose a universal scheme for predicting the oxidation states of metal atoms in ionic and coordination compounds with a small set of structural descriptors, which include the parameters of atomic Voronoi polyhedra. The scheme has been trained and checked with more than 35,000 crystal structures containing more than 90,000 metal atoms in the oxygen environment. The accuracy of the prediction exceeded 95%; we have detected a number of wrong oxidation states and incorrect chemical compositions in the crystallographic databases using this scheme. The scheme is easily extendable to any kind of atomic environment and can be used to search for correlations between geometrical and physical properties of crystal structures.

Measurement-driven blind topology estimation for sparse data injection attack in energy system

Smart grid cyber-security has come to the forefront of national security priorities due to the emergence of new cyber threats such as the False Data Injection (FDI) attack. This specific type of attack modifies smart grid measurements to produce wrong system states during the state estimation which is a critical operational functionality. While most of the existing works assume that power grid topology or the Jacobian matrix (that represents measurement and state relationship) is known to the attacker, this work shows that an intelligent attacker can construct a data-driven sparse FDI attack which does not require prior knowledge of system Jacobian or grid topology. In this paper, we show how the power grid topology, which is an important information for sparse attack construction, can be revealed using only measurement signals. The blind topology estimation is formulated as a constrained optimisation problem. The alternating direction method of multipliers (ADMM) is then employed with a novel initialization process for solving this complex problem. The comparative evaluation using graph-theoretic measures indicates that the power grid topology can be revealed with very high accuracy using such an approach. For example, average eigenvalue centrality measures and degree centrality measures show that the estimated topology is around 95.82% and 94.99% accurate compared to the actual topology for the IEEE-14 bus system and 86.47% and 96.34%, respectively for IEEE-30 bus system. Finally, based on the estimated topology we determine the critical set of measurements, which are then utilised for sparse attack construction. We show that only 7.40% and 3.57% sensors are required to construct the sparsest stealthy attacks for the IEEE 14 bus and the 30 bus system, respectively. The findings of this research conclude that an intelligent attacker can construct a very sparse ‘stealthy’ attack, that can degrade the operational performance significantly, by manipulating a few sensor devices only without any prior system knowledge or information.

Effect of nonideal fluid behavior on the jet mixing process under high-pressure and supersonic flow conditions

The mixing process of extremely underexpanded supercritical jets into a gaseous environment is studied. The focus lies on the influence of the nonideal fluid behavior on the mixing process. Numerical simulations are conducted for eight different injection conditions where experimental sound speed measurements are available. Overall, a very good agreement between simulations and experiments is found. A comparison of the real-gas and the ideal-gas closures shows the necessity to account for nonideal fluid behavior. The application of the ideal-gas law results in an incorrect energetic state which most prominently leads to an overestimation of the post-shock temperature by 70 K. The wrong energetic state yields erroneous thermodynamic properties in the mixing region. Finally, a mixture model is deduced enabling the prediction of mixture properties. As independent measurements of mass/mole fractions are not available, this evaluation procedure is a first attempt to numerically predict the mixture composition in underexpanded jets.

State-of-Charge and State-of-Health Estimation for Lithium-Ion Batteries Based on Dual Fractional-Order Extended Kalman Filter and Online Parameter Identification

Accurate state-of-charge (SOC) and state-of-health (SOH) estimations of batteries are of great significance for electric vehicles. A combined SOC and SOH estimation method for lithium-ion batteries based on a dual extended Kalman filter (EKF) and fractional-order model (FOM) is proposed. A fractional second-order RC model is established and model parameters are identified offline by an adaptive genetic algorithm (AGA). One of the dual filters is used to jointly estimate the SOC and SOH (ohmic internal resistance and capacity), and another is employed to update the model parameters online. Compared with single filter with fixed parameters, the dual filters can obtain more accurate SOC estimation and model voltage prediction. The SOC root-mean square errors (RMSEs) decrease from 6.87%, 8.50% and 7.32% to 0.48%, 0.63% and 0.86% under the Federal Urban Driving Schedule (FUDS), the Dynamic Stress Test (DST) and the US06 Highway Driving Schedule tests, respectively, and the model voltage RMSEs decrease from 88.6 mV, 79.3 mV and 68.4 mV to 4.9 mV, 5.7 mV and 3.8 mV, respectively at room temperature. The accuracy of the SOH estimation is also verified under these three tests. The convergence and robustness of the proposed method are discussed and verified by using the wrong initial state value and noise analysis.

Cyber Attack Detection Based on Wavelet Singular Entropy in AC Smart Islands: False Data Injection Attack

Since Smart-Islands (SIs) with advanced cyber-infrastructure are incredibly vulnerable to cyber-attacks, increasing attention needs to be applied to their cyber-security. False data injection attacks (FDIAs) by manipulating measurements may cause wrong state estimation (SE) solutions or interfere with the central control system performance. There is a possibility that conventional attack detection methods do not detect many cyber-attacks; hence, system operation can interfere. Research works are more focused on detecting cyber-attacks that target DC-SE; however, due to more widely uses of AC SIs, investigation on cyber-attack detection in AC systems is more crucial. In these regards, a new mechanism to detect injection of any false data in AC-SE based on signal processing technique is proposed in this paper. Malicious data injection in the state vectors may cause deviation of their temporal and spatial data correlations from their ordinary operation. The suggested detection method is based on analyzing temporally consecutive system states via wavelet singular entropy (WSE). In this method, to adjust singular value matrices and wavelet transforms' detailed coefficients, switching surface based on sliding mode controller are decomposed; then, by applying the stochastic process, expected entropy values are calculated. Indices are characterized based on the WSE in switching level of current and voltage for cyber-attack detection. The proposed detection method is applied to different case studies to detect cyber-attacks with various types of false data injection, such as amplitude, and vector deviation signals. The simulation results confirm the high-performance capability of the proposed FDIA detection method. This detection method's significant characteristic is its ability in fast detection (10 ms from the attack initiation); besides, this technique can achieve an accuracy rate of over 96.5%.

EEK-SYS: System reliability analysis through estimation error-guided adaptive Kriging approximation of multiple limit state surfaces

In order to approximate the multiple limit state functions for different failure events, the active learning Kriging model proposed for component reliability analysis has been extended to system reliability analysis. Meanwhile, many efficient sampling strategies have been applied to reduce the high computational burden. However, these strategies meet a challenge in wasting some training points and terminating the training process inappropriately, since they do not directly relate to the estimation error of system failure probability. To address the challenge, this work proposes an estimation error-guided adaptive Kriging method. As Kriging prediction may be inaccurate before being well trained, the predicted system failure probability may deviate from the true result. To quantify this estimation error, the true number of failure points is approximated by adding the number of predicted failure points and the number of wrongly classified points. Since it is impossible to learn the exact number of wrongly classified points, its confidence interval is derived based on the probability of making wrong state classification. Subsequently, the refinement of Kriging is achieved by using the probability to identify new points and using the estimation error to determine the termination, which has been demonstrated by three different cases.

A Method to Audit the Assignment of Registered Voters to Districts and Precincts

Electoral boundaries are an integral part of election administration. District boundaries delineate which legislative election voters are eligible to participate in, and precinct boundaries identify, in many localities, where voters cast in-person ballots on Election Day. Election officials are tasked with resolving a tremendously large number of intersections of registered voters with overlapping electoral boundaries. Any large-scale data project is susceptible to errors, and this task is no exception. In two recent close elections, these errors were consequential to the outcome. To address this problem, we describe a method to audit the assignment of registered voters to districts. We apply the methodology to Florida’s voter registration file to identify thousands of registered voters assigned to the wrong state House district, many of which local election officials have verified and rectified. We discuss how election officials can best use this technique to detect registered voters assigned to the wrong electoral boundary.

Research progress of high-performance BEM and investigation on convergence of GMRES in local stress analysis of slender real thin-plate beams

Purpose Based on the error analysis, the authors proposed a new kind of high accuracy boundary element method (BEM) (HABEM), and for the large-scale problems, the fast algorithm, such as adaptive cross approximation (ACA) with generalized minimal residual (GMRES) is introduced to develop the high performance BEM (HPBEM). It is found that for slender beams, the stress analysis using iterative solver GMRES will difficult to converge. For the analysis of slender beams and thin structures, to enhance the efficiency of GMRES solver becomes a key problem in the development of the HPBEM. The purpose of this paper is study on the preconditioning method to solve this convergence problem, and it is started from the 2D BE analysis of slender beams. Design/methodology/approach The conventional sparse approximate inverse (SAI) based on adjacent nodes is modified to that based on adjacent nodes along the boundary line. In addition, the authors proposed a dual node variable merging (DNVM) preprocessing for slender thin-plate beams. As benchmark problems, the pure bending of thin-plate beam and the local stress analysis (LSA) of real thin-plate cantilever beam are applied to verify the effect of these two preconditioning method. Findings For the LSA of real thin-plate cantilever beams, as GMRES (m) without preconditioning applied, it is difficult to converge provided the length to height ratio greater than 50. Even with the preconditioner SAI or DNVM, it is also difficult to obtain the converged results. For the slender real beams, the iteration of GMRES (m) with SAI or DNVM stopped at wrong deformation state, and the computation failed. By changing zero initial solution to the analytical displacement solution of conventional beam theory, GMRES (m) with SAI or DNVM will not be stopped at wrong deformation state, but the stress error is still difficult to converge. However, by GMRES (m) combined with both SAI and DNVM preconditioning, the computation efficiency enhanced significantly. Originality/value This paper presents two preconditioners: DNVM and a modified SAI based on adjacent nodes along the boundary line of slender thin-plate beam. In the LSA, by using GMRES (m) combined with both DNVM and SAI, the computation efficiency enhanced significantly. It provides a reference for the further development of the 3D HPBEM in the LSA of real beam, plate and shell structures.

State Acquiescence or Connivance in the Wrongful Conduct of Third Parties in the Jurisprudence of the European Court of Human Rights

This article examines the jurisprudence of the European Court of Human Rights with regard to the acquiescence or connivance of states parties to the European Convention on Human Rights (ECHR) in the wrongful conduct of third states (which themselves may or may not be parties to the ECHR) or non-state actors. It discusses the origins of the acquiescence or connivance test in the Court’s case law, which is idiosyncratic and does not stem from general international law. The article also discusses the test’s legal nature, arguing that its conceptual basis remains unclear, and that the current state of the case law could support two theories. First, that acquiescence or connivance, as applied in the Court’s most recent cases, is an ECHR-specific rule of attribution of conduct, which deviates from the general rules of attribution in international law, as codified by the International Law Commission in its Articles on State Responsibility. The Articles themselves do allow for the possibility of sector-specific rules of state responsibility; Article 55 ASR, entitled lex specialis, thus provides that the Articles ‘do not apply where and to the extent that the conditions for the existence of an internationally wrongful act or the content or implementation of the international responsibility of a State are governed by special rules of international law.’ One view of the Court’s acquiescence or connivance test is thus that it provides us with an example of a lex specialis rule of attribution of conduct in the sense of Article 55 ASR. The alternative view, however, is that the Court’s acquiescence or connivance jurisprudence would best be conceptually framed as an ECHR-specific theory of state complicity. Under such a framing, the state acquiescing or conniving in the wrongful conduct of a third party is being held responsible for the assistance it provides to that third party, rather than for the third party’s own conduct – in other words, the complicity rule is not necessarily an attributive one. While such a rule would arguably differ from the ILC’s general approach to wrongful state aiding and assisting in Article 16 ASR, it would not be an ECHR-specific rule of attribution, or at least it would not always operate with an attributive effect. I argue that such a conceptual framing would best accommodate human rights-specific needs while maintaining coherence with general international law. Even under such a framing, however, there are many aspects of the acquiescence or connivance test that require further clarification by the Court.

Conflict of Laws for the Age of Cybertorts: A Game-Theoretic Study of Corporate Profiteering from Choice of Law Loopholes and Interstate Torts

This Article identifies a choice of law loophole that corporations can exploit to commit interstate torts against individuals without paying damages—by inducing victims to sue in a state where they are guaranteed to lose. The Second Restatement effectively requires plaintiffs bringing interstate tort claims to allege which state has the most significant relationship to their injury, because most federal courts rely on plaintiffs’ allegations to choose a state law for the purpose of resolving motions to dismiss. However, when torts are committed over state lines (for example, over the internet), plaintiffs can be misinformed or misled as to where the tortious conduct really occurred, even if their knowledge of how they were harmed is otherwise correct. Therefore, if a plaintiff is induced to sue under a wrong state’s law, she would waste years litigating only to lose, even if her claims are meritorious. Her complaint would survive a motion to dismiss because her allegations are plausible, but it would be dismissed at discovery because discovery would reveal that her injury originated in a state other than the one she alleged. This Article has two objectives. First, I show how corporations committing torts remotely can profit from this loophole, using a game-theoretic model and a Third Circuit case in which a corporate defendant apparently misrepresented to the court and plaintiffs the state where the alleged tort originated, resulting in the plaintiffs’ complaint surviving a motion to dismiss but being dismissed after discovery years later. I argue that, if corporations use this loophole often enough, tort victims would be deterred from suing for fear that they would waste years trying cases they are effectively guaranteed to lose. Thus, once a corporation has built a reputation that it will use the loophole, it could commit torts without paying damages or even having to litigate. Second, I use my study as evidence against the prevailing notion that conflict of laws scholarship is unhelpful to the practice of law. I argue that conflicts scholarship has become notorious for irrelevance because too many scholars employ logically fallacious argumentation and are overly concerned with designing theoretically ideal but practically infeasible choice of law rules. I argue that, by focusing more on studying how existing choice of law rules affect actual litigation, conflicts scholarship can lead the effort to fix our territorially tethered, increasingly unsustainable legal system and to design one fit to survive the age of cybertorts.

Back to the Future: Tort’s Capacity to Remedy Historic Human Rights Abuses

A recent cluster of tort actions have challenged historic abuses of power by officials and soldiers engaged in late-colonial counter-insurgency operations. The preliminary judgments in Mutua, relating to the use of torture during the Kenya Emergency, produced a high-profile settlement by the UK Government and became the catalyst for much of the subsequent litigation. These judgments require a re-evaluation of competing claims which have long characterised this juncture of public and private law. They oblige us, however belatedly, to re-evaluate the impact in the context of the British Empire of A.V. Dicey’s assertion that tort is sufficient to provide redress for individual interests affected by wrongful state action, even in circumstances of emergency. They also challenge the orthodoxy, adopted by generations of public lawyers from the 1960s onwards, that a combination of Crown immunities and limited causes of action rendered Dicey’s account illusory. The outcome of the Mutua litigation, moreover, highlights the comparative failure of public law challenges to abuses of power in counter-insurgency contexts, from the Keyu case concerning extra-judicial killings during the Malaya Emergency to the controversy which has attended many of the human rights challenges related to UK military activities in Iraq between 2003 and 2011. Drawing upon archival materials released in the course of the Mutua litigation, this article first evaluates how administrators and soldiers approached legal constraints upon their conduct during the colonial emergencies of the 1950s and 1960s. Second, for all that Mutua showcases tort’s potential as a vehicle for addressing large-scale human rights abuses in the law of England and Wales, this article unpacks the ongoing efforts of the courts to restrict this litigation. This analysis of both the management of the Kenya Emergency and the recent end-of-Empire tort challenges assesses tort’s shortcomings in the 1950s and why it has since proven a rudimentary vehicle for tackling historic abuses of emergency powers.

Capabilities, Freedom and Severe Poverty

Severe poverty is a key challenge for theorists of global justice. Most theorists have approached this issue primarily by developing accounts for understanding which kinds of duties have relevance and how responsibilities for tackling severe poverty might be assigned to agents, whether individuals, nations or states. All such views share a commitment to ending severe poverty as a wrongful deprivation with profoundly negative impact on affected individuals. While much attention has prioritised identifying reasons for others to provide relief, this chapter will examine the nature of the wrongful deprivation that characterises severe poverty. One influential view is championed by Martha Nussbaum in her distinctive capabilities approach. An individual might be considered to experience severe poverty where she is unable to enjoy the use of her capabilities which should be available to her. But this position raises several questions. Take the fact that about 1 billion people are unable to meet their basic needs today. Would the capabilities approach claim the number is much higher given its wider grasp of human flourishing beyond mere material subsistence – and what implications would flow from this? Or would the capabilities approach claim only a portion of those unable to meet their basic needs are in a wrongful state because their circumstances are a result of free choice – and what would this mean? These questions indicate a potential concern about whether the approach is over- or under-inclusive and why. This chapter will proceed by first providing a general overview of Nussbaum’s capabilities approach providing an indication about how her list of ten capabilities might be reformulated differently. The next section applies this approach to severe poverty in a critical discussion of how such poverty is best understood within the capabilities framework. The penultimate section considers the importance of freedom and choice that underpins the approach and its implications for how we apply it to severe poverty. The chapter ends with some concluding remarks about the broad limitations for understanding severe poverty as a kind of capabilities deprivation.