23 research outputs found
ConsenSys/gnark: v0.6.0
No full text[v0.6.0] - 2022-01-03
Important: next release (v0.7.0) will be compatible with Go1.18+ only
Breaking changes
circuit.Define(curveID, api) -> circuit.Define(api); added api.Curve() to retrieve curve info
api.Constant(...) was removed. Can now directy assign values with = operator in the circuit definition and the witness assignment.
frontend.Variable is now an alias for interface{}
assert helper is now under gnark/test. Instead of taking a CompiledConstraintSystem it takes a Circuit as input, enabling easier tests accross curves and proving schemes through the use of test/TestingOption (WithBackends(backend.GROTH16), WithCurves(ecc.BN254), ...)
api.NewHint handles multiple outputs and custom solver Hint definition has changed
Feat
added explicit warning when parser encounters unadressable struct field #169
FromInterface supports uintXX and intXX types closes #197
lighter stack trace by default for circuits, more verbose when -tags=debug provided
added api.Tag and api.AddCounter to measure number of constraints in portion of circuit
api.DivUnchecked does not handle zero divisor. api.Div does.
added frontend.IsConstant and ConstantValue apis
add support for bw6-633 curve
added api.Lookup2 method (2-bit lookup)
frontend: plonk frontend directly implements the frontend.API interface instead of building on top of the R1CS builder
std: fields and pairing over BLS24-315 in BW6-633 circuit
test: add Run for running circuit test configurations as subtests
test: add Log method for logging in subtests
test: assert helper cross check constraint system solver results with big.Int test execution engine
Perf
std: verifying a Pairing (bls12-377, Groth16) inside a circuit went from ~40k constraints to less than <12k constraints
Fix
fixes #169 ensure frontend.Circuit methods are defined on pointer receiver
fixes #178 by adding cbor.MaxMapPairs options when reading R1CS
fixed AssertIsBoolean in plonk (mul by constant failed)
fixes #168 adds context to a non-deterministic compilation error in the Assert object
frontend: reduce constant by modulus
frontend: plonk compiler now outputs a reasonable number of constraints #186
Build
updated to gnark-crypto v0.6.0
Pull Requests
Merge pull request #192 from ConsenSys/multi-hint
Merge pull request #220 from ConsenSys/feat-from-interface
Merge pull request #217 from ConsenSys/fix-internal-compiled
Merge pull request #191 from ConsenSys/assert-subtests
Merge pull request #200 from ConsenSys/refactor/frontend
Merge pull request #205 from ConsenSys/fix/constant-mod-reduction
Merge pull request #186 from ConsenSys/fix/plonk_constraints
Merge pull request #185 from ConsenSys/feat/bw6-633
Merge pull request #189 from ConsenSys/lookup2
Merge pull request #183 from ivokub/hint-registry
Merge pull request #182 from ConsenSys/std/pairing
Merge pull request #176 from ConsenSys/feat-constraint-counter
Merge pull request #180 from ConsenSys/refactor-variable-interface
Merge pull request #173 from ConsenSys/feat-debug-ta
ConsenSys/gnark-crypto: v0.6.0
No full text[v0.6.0] - 2021-12-22
Feat
plookup: added plookup lookup proof
field: generate optimized addition chains for Sqrt & Legendre exp functions
field: added field.SetInt64, support for intX and uintX #109
field: added UnmarshalJSON and MarshalJSON on fields
field: added field.Text(base) to return field element string in a given base, like big.Int
field: field.SetString now supports 0b 0o 0x prefixes (base 2, 8 and 16)
kzg: test tampered proofs whith quotient set to zero
bls24: Fp-Fp2-Fp4-Fp12-Fp24 tower
Fix
fixes #104 code generation for saturated modulus like secp256k1 incorrect. added secp256k1 test
Perf
field inverse is ~30-70% faster (implements Pornin's optimizations)
bls12-381: faster Miller loop (sparse-sparse mul)
bls12-381: faster final exp (faster expt)
bn254: better short addition chain for Expt()
bn254: addchain with max squares (weighting mul x2.6 cyclosq)
Pull Requests
Merge pull request #111 from ConsenSys/field-intX-support
Merge pull request #114 from ConsenSys/fix-dynamic-link
Merge pull request #108 from ConsenSys/perf/bls12381-pairing
Merge pull request #106 from ConsenSys/improvement/field-inv-pornin20
Merge pull request #105 from ConsenSys/field-from-json
Merge pull request #83 from ConsenSys/experiment/BLS24
Merge pull request #102 from ConsenSys/feat/plookup
Merge pull request #97 from ConsenSys/feat-addchain
Merge pull request #99 from ConsenSys/feat-addchain-exp
Dictionnaire de droit foncier et de géomatique
No full textNational audienceLe droit foncier regroupe les concepts et les règles régissant les immeubles, bâtis ou non, pour définir les droits et les obligations de chacun vis-à-vis d’un fonds déterminé.La géomatique consiste à collecter, traiter et diffuser des données géographiques numériques afin de les représenter et de les analyser, à l’aide d’outils et de méthodes dédiés. Elle est étroitement liée à l’information géographique, à la représentation d’un objet ou d’un phénomène localisé dans l’espace.Associer ces deux disciplines en un seul ouvrage permet ainsi d’appréhender l’ensemble des règles, physiques ou juridiques, définissant chaque espace.Composé de plus de 350 entrées, le Dictionnaire de droit foncier et de géomatique est à la fois théorique et pratique, à visée scientifique et juridique. Les mots sélectionnés exposent les concepts indispensables aux deux domaines et les procédures applicables. Richement illustrée – schémas, graphiques, jurisprudence, etc. –, chaque entrée présente une définition ainsi que le cadre législatif et réglementaire ou l’évolution technique, le fonctionnement, les domaines d’application mais également les intérêts pratiques de la notion
Dictionnaire de droit foncier et de géomatique
No full textNational audienceLe droit foncier regroupe les concepts et les règles régissant les immeubles, bâtis ou non, pour définir les droits et les obligations de chacun vis-à-vis d’un fonds déterminé.La géomatique consiste à collecter, traiter et diffuser des données géographiques numériques afin de les représenter et de les analyser, à l’aide d’outils et de méthodes dédiés. Elle est étroitement liée à l’information géographique, à la représentation d’un objet ou d’un phénomène localisé dans l’espace.Associer ces deux disciplines en un seul ouvrage permet ainsi d’appréhender l’ensemble des règles, physiques ou juridiques, définissant chaque espace.Composé de plus de 350 entrées, le Dictionnaire de droit foncier et de géomatique est à la fois théorique et pratique, à visée scientifique et juridique. Les mots sélectionnés exposent les concepts indispensables aux deux domaines et les procédures applicables. Richement illustrée – schémas, graphiques, jurisprudence, etc. –, chaque entrée présente une définition ainsi que le cadre législatif et réglementaire ou l’évolution technique, le fonctionnement, les domaines d’application mais également les intérêts pratiques de la notion
Dictionnaire de droit foncier et de géomatique
No full textNational audienceLe droit foncier regroupe les concepts et les règles régissant les immeubles, bâtis ou non, pour définir les droits et les obligations de chacun vis-à-vis d’un fonds déterminé.La géomatique consiste à collecter, traiter et diffuser des données géographiques numériques afin de les représenter et de les analyser, à l’aide d’outils et de méthodes dédiés. Elle est étroitement liée à l’information géographique, à la représentation d’un objet ou d’un phénomène localisé dans l’espace.Associer ces deux disciplines en un seul ouvrage permet ainsi d’appréhender l’ensemble des règles, physiques ou juridiques, définissant chaque espace.Composé de plus de 350 entrées, le Dictionnaire de droit foncier et de géomatique est à la fois théorique et pratique, à visée scientifique et juridique. Les mots sélectionnés exposent les concepts indispensables aux deux domaines et les procédures applicables. Richement illustrée – schémas, graphiques, jurisprudence, etc. –, chaque entrée présente une définition ainsi que le cadre législatif et réglementaire ou l’évolution technique, le fonctionnement, les domaines d’application mais également les intérêts pratiques de la notion
Extracranial anticoagulant related bleedings admitted to intensive care units: a French multicenter retrospective study
No full textAbstract Background Anticoagulants are widely used but can lead to iatrogenic events such as bleeding. Limited data exists regarding the characteristics and management of patients admitted to intensive care units (ICU) for severe anticoagulant-related extracranial bleeding. Methods A retrospective observational study was conducted in five French ICUs. From January 2007 to December 2018, all patients aged over 18 years admitted to ICU for extracranial bleeding while receiving therapeutic anticoagulation were included. Results 486 patients were included, mainly male (61%) with an average age of 73 ± 13 years. Most patients had comorbidities, including hypertension (68%), heart disease (49%) and diabetes (33%). Patients were treated by vitamin K antagonists (VKA, 54%), heparins (25%) and direct oral anticoagulants (DOAC, 7%). The incidence of patients admitted to ICU for anticoagulant-related bleeding increased from 3.2/1000 admissions in 2007 to 5.8/1000 in 2018. This increase was particularly high for DOAC class. Upon admission, patients exhibited severe organ failure, as evidenced by a high SOFA score (7 ± 4) and requirement for organ support therapies such as vasopressors (31.5%) and invasive mechanical ventilation (34%). Adherence to guidelines for the specific treatment of anticoagulant-related bleeding was generally low. ICU mortality was 27%. In multivariate analysis, five factors were independently associated with mortality: chronic hypertension, need for vasopressors, impaired consciousness, hyperlactatemia and prolonged aPTT > 1.2. Conclusion Anticoagulant-related extracranial bleeding requiring ICU admission is a serious complication responsible for organ failure and significant mortality. Its incidence is rising. The therapeutic management is suboptimal and could be improved by educational programs
Machine learning-enhanced prediction of operating room occupation time and length of stay: a retrospective cohort study on emergency surgery care pathways
No full textInternational audienceEmergency surgeries are resource-intensive procedures with high variability in operating room occupation time (OT) and hospital length of stay (LOS), complicating scheduling and capacity planning. Manual estimates by surgeons are frequently inaccurate, especially in emergency settings. Machine learning models (MLMs) have shown good predictive performance in elective surgery, but their applicability to emergency contexts remains underexplored. We conducted a retrospective, single-center study on 3,117 emergency procedures performed at the Pitié-Salpêtrière hospital, a major trauma center, between 2015 and 2018. Preoperative data available at the time of surgical scheduling were used to train four regression models for OT and LOS prediction: Ridge Regression, Random Forest, XGBoost, and a Multi-Layer Perceptron. Model performance was evaluated using Mean Absolute Error, Root Mean Square Error, Mean Absolute Percentage Error, and operational metrics: proportion of OT predictions within 20% of actual value (Within20) and LOS within fixedday thresholds. RF and XGB outperformed manual estimates for OT, with RF achieving a MAE of 32 min and Within20 of 60%, improving surgeon estimates by 13%. For LOS, XGB was the best performing model with a MAE of 5 days and RMSE of 12 days. As measured through MAPE, prediction performance varied across specialties, with better accuracy in digestive and maxillofacial procedures. As for elective cases, MLMs can improve OT and LOS predictions in emergency surgery, though predictive performance remains moderate. Future work should refine models through enriched data, clinically relevant thresholds, and integration into decision-support tools to enhance emergency surgical care coordination
Additional file 1 of Extracranial anticoagulant related bleedings admitted to intensive care units: a French multicenter retrospective study
No full textAdditional file 1. Table S1: Personal list for the screening of patients admitted in ICU for anticoagulant-related bleeding, based on ICD-10 nomenclature
PEPS: a platform for supporting studies in pharmaco-epidemiology using medico-administrative databases
No full textInternational audienceBackground:New approaches of pharmaco-epidemiology consist in using large EHR databases to investigate the effects and uses (or misuses) of drugs in real conditions. The objective is to benefit from nationwide available data to answer accurately and in a short time pharmaco-epidemiological queries for national public health institutions. Despite the potential availability of the data, their size and complexity make their analysis long and tremendous. The challenge we tackle is the conception of a generic digital toolbox to support the efficient design of a broad range of pharmaco-epidemiology studies from EHR databases.Methods:To be able to answer the broad range of pharmaco-epidemiological queries from national public health institutions, the PEPS platform exploits, in secondary use, the French health cross-schemes insurance system, called SNIIRAM. The SNIIRAM covers most of the French population with a sliding period of 3 past years. To tackle the volume and the diversity of the SNIIRAM data warehouse, a research program has been established to design an innovative toolbox. This research program is focused first on the modeling of care pathways from the SNIIRAM database and, second, on the design of tools supporting meaningful insights extraction about massive and complex care pathways by clinicians.Results:A data infrastructure has been set up to collect and to access the data securely. We proposed and developed a high level abstraction model to access and to visualize care pathways. We designed the principle of a toolbox to carry out generic pharmaco-epidemiological studies from the SNIIRAM data warehouse (see figure). This toolbox is oriented toward data analytics with data visualisation, domain specific query language, knowledge discovery and statistics modules.Conclusions:The preliminary results on the development of the PEPS platform show that our care pathways model is very expressive and that it allows to have a highly abstracted representation of the warehouse's complex data. Our modular architecture supports clinicians and epidemiologists all along their analysis process
PEPS: a platform for supporting studies in pharmaco-epidemiology using medico-administrative databases
No full textInternational audienceBackground:New approaches of pharmaco-epidemiology consist in using large EHR databases to investigate the effects and uses (or misuses) of drugs in real conditions. The objective is to benefit from nationwide available data to answer accurately and in a short time pharmaco-epidemiological queries for national public health institutions. Despite the potential availability of the data, their size and complexity make their analysis long and tremendous. The challenge we tackle is the conception of a generic digital toolbox to support the efficient design of a broad range of pharmaco-epidemiology studies from EHR databases.Methods:To be able to answer the broad range of pharmaco-epidemiological queries from national public health institutions, the PEPS platform exploits, in secondary use, the French health cross-schemes insurance system, called SNIIRAM. The SNIIRAM covers most of the French population with a sliding period of 3 past years. To tackle the volume and the diversity of the SNIIRAM data warehouse, a research program has been established to design an innovative toolbox. This research program is focused first on the modeling of care pathways from the SNIIRAM database and, second, on the design of tools supporting meaningful insights extraction about massive and complex care pathways by clinicians.Results:A data infrastructure has been set up to collect and to access the data securely. We proposed and developed a high level abstraction model to access and to visualize care pathways. We designed the principle of a toolbox to carry out generic pharmaco-epidemiological studies from the SNIIRAM data warehouse (see figure). This toolbox is oriented toward data analytics with data visualisation, domain specific query language, knowledge discovery and statistics modules.Conclusions:The preliminary results on the development of the PEPS platform show that our care pathways model is very expressive and that it allows to have a highly abstracted representation of the warehouse's complex data. Our modular architecture supports clinicians and epidemiologists all along their analysis process
