Error of disclosure

Was it that there was no law, no land, a land of no one, nothing (terra nullius)? A land, but a land without anyone or anything (a land of nobody\u27s, no one, a land that belonged to the nothing of this other one who by force and contract will have been turned into the subject of this law) or, more precisely, a land with nothing, a land of nothing, a land with a very particular nothing. This land whose non-law, ostensibly, will have become, at once for the future and throughout its indeterminate past (but how could these be separated for a land which was said to have lacked what an officer of the English state could not discover?), a land whose nonsite would be erased in the name of a sovereign law that recognisedjus nullius in the site of law\u27s dominion, demanding in this relation that law enact itself in the very site of its absence (where this nothing would be returned to the identity ofa law that recognised nothing but its law of identity)

Quantitive analysis of electric vehicle flexibility : a data-driven approach

The electric vehicle (EV) flexibility, indicates to what extent the charging load can be coordinated (i.e., to flatten the load curve or to utilize renewable energy resources). However, such flexibility is neither well analyzed nor effectively quantified in literature. In this paper we fill this gap and offer an extensive analysis of the flexibility characteristics of 390k EV charging sessions and propose measures to quantize their flexibility exploitation. Our contributions include: (1) characterization of the EV charging behavior by clustering the arrival and departure time combinations that leads to the identification of type of EV charging behavior, (2) in-depth analysis of the characteristics of the charging sessions in each behavioral cluster and investigation of the influence of weekdays and seasonal changes on those characteristics including arrival, sojourn and idle times, and (3) proposing measures and an algorithm to quantitatively analyze how much flexibility (in terms of duration and amount) is used at various times of a day, for two representative scenarios. Understanding the characteristics of that flexibility (e.g., amount, time and duration of availability) and when it is used (in terms of both duration and amount) helps to develop more realistic price and incentive schemes in DR algorithms to efficiently exploit the offered flexibility or to estimate when to stimulate additional flexibility. (C) 2017 Elsevier Ltd. All rights reserved

Quantifying flexibility in EV charging as DR potential : analysis of two real-world data sets

The increasing adoption of electric vehicles (EVs) presents both challenges and opportunities for the power grid, especially for distribution system operators (DSOs). The demand represented by EVs can be significant, but on the other hand, sojourn times of EVs could be longer than the time required to charge their batteries to the desired level (e.g., to cover the next trip). The latter observation means that the electrical load from EVs is characterized by a certain level of flexibility, which could be exploited for example in demand response (DR) approaches (e.g., to balance generation from renewable energy sources). This paper analyzes two data sets, one from a charging-at-home field trial in Flanders (about 8.5k charging sessions) and another from a large-scale EV public charging pole deployment in The Netherlands (more than 1M sessions). We rigorously analyze the collected data and quantify aforementioned flexibility: (1) we characterize the EV charging behavior by clustering the arrival and departure time combinations, identifying three behaviors (charging near home, charging near work, and park to charge), (2) we fit statistical models for the sojourn time, and flexibility (i.e., non-charging idle time) for each type of observed behavior, and (3) quantify the the potential of DR exploitation as the maximal load that could be achieved by coordinating EV charging for a given time of day t, continuously until t vertical bar Delt

Diffusion tensor imaging mapping of brain white matter pathology in mitochondrial optic neuropathies

BACKGROUND AND PURPOSE: Brain white matter is frequently affected in mitochondrial diseases; optic atrophy gene 1-autosomal dominant optic atrophy and Leber hereditary optic neuropathy are the most frequent mitochondrial monosymptomatic optic neuropathies. In this observational study, brain white matter microstructure was characterized by DTI in patients with optic atrophy gene 1-autosomal dominant optic atrophy and Leber hereditary optic neuropathy, in relation to clinical and genetic features. MATERIALS AND METHODS: Nineteen patients with optic atrophy gene 1-autosomal dominant optic atrophy and 17 with Leber hereditary optic neuropathy older than 18 years of age, all genetically diagnosed, and 19 healthy volunteers underwent DTI by using a 1.5T MR imaging scanner and neurologic and ophthalmologic assessments. Brain white matter DTI metrics were calculated for all participants, and, in patients, their correlations with genetics and clinical findings were calculated. RESULTS: Compared with controls, patients with optic atrophy gene 1-autosomal dominant optic atrophy had an increased mean diffusivity in 29.2% of voxels analyzed within major white matter tracts distributed throughout the brain, while fractional anisotropy was reduced in 30.3% of voxels. For patients with Leber hereditary optic neuropathy, the proportion of altered voxels was only 0.5% and 5.5%, respectively, of which half was found within the optic radiation and 3.5%, in the smaller acoustic radiation. In almost all regions, fractional anisotropy diminished with age in patients with optic atrophy gene 1-autosomal dominant optic atrophy and correlated with average retinal nerve fiber layer thickness in several areas. Mean diffusivity increased in those with a missense mutation. Patients with Leber hereditary optic neuropathy taking idebenone had slightly milder changes. CONCLUSIONS: Patients with Leber hereditary optic neuropathy had preferential involvement of the optic and acoustic radiations, consistent with trans-synaptic degeneration, whereas patients with optic atrophy gene 1-autosomal dominant optic atrophy presented with widespread involvement suggestive of a multisystemic, possibly a congenital/developmental, disorder. White matter changes in Leber hereditary optic neuropathy and optic atrophy gene 1-autosomal dominant optic atrophy may be exploitable as biomarkers. ABBREVIATIONS: DOA autosomal dominant optic atrophy; FA fractional anisotropy; LHON Leber hereditary optic neuropathy; MD mean diffusivity; OPA1 optic atrophy gene 1 ;O R optic radiation; RNFL retinal nerve fiber layer; TBSS tract-based spatial statistic

Measurements of differential and double-differential Drell-Yan cross sections in proton-proton collisions at [Formula: see text][Formula: see text].

Measurements of the differential and double-differential Drell-Yan cross sections in the dielectron and dimuon channels are presented. They are based on proton-proton collision data at [Formula: see text] recorded with the CMS detector at the LHC and corresponding to an integrated luminosity of 19.7[Formula: see text]. The measured inclusive cross section in the [Formula: see text] peak region (60-120[Formula: see text]), obtained from the combination of the dielectron and dimuon channels, is [Formula: see text], where the statistical uncertainty is negligible. The differential cross section [Formula: see text] in the dilepton mass range 15-2000[Formula: see text] is measured and corrected to the full phase space. The double-differential cross section [Formula: see text] is also measured over the mass range 20 to 1500[Formula: see text] and absolute dilepton rapidity from 0 to 2.4. In addition, the ratios of the normalized differential cross sections measured at [Formula: see text] and 8[Formula: see text] are presented. These measurements are compared to the predictions of perturbative QCD at next-to-leading and next-to-next-to-leading (NNLO) orders using various sets of parton distribution functions (PDFs). The results agree with the NNLO theoretical predictions computed with fewz 3.1 using the CT10 NNLO and NNPDF2.1 NNLO PDFs. The measured double-differential cross section and ratio of normalized differential cross sections are sufficiently precise to constrain the proton PDFs

Search for decays of stopped long-lived particles produced in proton-proton collisions at [Formula: see text].

A search has been performed for long-lived particles that could have come to rest within the CMS detector, using the time intervals between LHC beam crossings. The existence of such particles could be deduced from observation of their decays via energy deposits in the CMS calorimeter appearing at times that are well separated from any proton-proton collisions. Using a data set corresponding to an integrated luminosity of 18.6[Formula: see text] of 8[Formula: see text] proton-proton collisions, and a search interval corresponding to 281 h of trigger livetime, 10 events are observed, with a background prediction of [Formula: see text] events. Limits are presented at 95 % confidence level on gluino and top squark production, for over 13 orders of magnitude in the mean proper lifetime of the stopped particle. Assuming a cloud model of R-hadron interactions, a gluino with mass [Formula: see text]1000[Formula: see text] and a top squark with mass [Formula: see text]525[Formula: see text] are excluded, for lifetimes between 1 [Formula: see text]s and 1000[Formula: see text]. These results are the most stringent constraints on stopped particles to date

Distributions of topological observables in inclusive three- and four-jet events in pp collisions at [Formula: see text][Formula: see text].

This paper presents distributions of topological observables in inclusive three- and four-jet events produced in pp collisions at a centre-of-mass energy of 7[Formula: see text] with a data sample collected by the CMS experiment corresponding to a luminosity of 5.1[Formula: see text]. The distributions are corrected for detector effects, and compared with several event generators based on two- and multi-parton matrix elements at leading order. Among the considered calculations, MadGraph interfaced with pythia6 displays the overall best agreement with data