CDCL(Crypto) and Machine Learning based SAT Solvers for Cryptanalysis

Over the last two decades, we have seen a dramatic improvement in the efficiency of conflict-driven clause-learning Boolean satisfiability (CDCL SAT) solvers over industrial problems from a variety of applications such as verification, testing, security, and AI. The availability of such powerful general-purpose search tools as the SAT solver has led many researchers to propose SAT-based methods for cryptanalysis, including techniques for finding collisions in hash functions and breaking symmetric encryption schemes. A feature of all of the previously proposed SAT-based cryptanalysis work is that they are \textit{blackbox}, in the sense that the cryptanalysis problem is encoded as a SAT instance and then a CDCL SAT solver is invoked to solve said instance. A weakness of this approach is that the encoding thus generated may be too large for any modern solver to solve it efficiently. Perhaps a more important weakness of this approach is that the solver is in no way specialized or tuned to solve the given instance. Finally, very little work has been done to leverage parallelism in the context of SAT-based cryptanalysis. To address these issues, we developed a set of methods that improve on the state-of-the-art SAT-based cryptanalysis along three fronts. First, we describe an approach called \cdcl (inspired by the CDCL($T$) paradigm) to tailor the internal subroutines of the CDCL SAT solver with domain-specific knowledge about cryptographic primitives. Specifically, we extend the propagation and conflict analysis subroutines of CDCL solvers with specialized codes that have knowledge about the cryptographic primitive being analyzed by the solver. We demonstrate the power of this framework in two cryptanalysis tasks of algebraic fault attack and differential cryptanalysis of SHA-1 and SHA-256 cryptographic hash functions. Second, we propose a machine-learning based parallel SAT solver that performs well on cryptographic problems relative to many state-of-the-art parallel SAT solvers. Finally, we use a formulation of SAT into Bayesian moment matching to address heuristic initialization problem in SAT solvers

Corrigendum to "Repeated stimulation of the dorsolateral-prefrontal cortex improves executive dysfunctions and craving in drug addiction: A randomized, double-blind, parallel-group study" [Brain Stimul 13 (3) (2020) 582-593].

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Original Article Efficacy of Addition of Folic Acid to Sodium Valproate in Treatment of Acute Mania, a Double Blind Clinical Trial Study

Abstract Introduction: Treatment resistance is common in acute mania, so the role of augmented therapies, including nutritional factors and vitamins have always been considered. This study aimed to assess the effect of addition of folic acid to sodium valproate in treatment of acute mania. Methods: This double blind randomized clinical trial study was done in Mashhad Avicenna psychiatric hospital, in 2011 and was registered with IRCT201112188106N1 code in Iranian registry clinical trials site. Twenty nine manic patients, divided into two groups randomly. They received sodium-valproate+folic acid or sodium-valproate+placebo. The severity of mania, by Jung Mania Rating Scale (YMRS), and cognitional improvement, by Mini-Mental State Examination (MMSE), were determined at baseline, after 3 and 6 weeks. Data analyzed by SPSS-16, к 2 and t-student tests. Result: The mean scores of YMRS at baseline, after 3 and 6 weeks, in the folice acid group were 22±2.44, 8.26±4.86 and 3.13±1.64 respectively, and in placebo group were 21.14±1.95, 14.14±4.31 and 13±5.21 respectively. The mean scores of YMRS significantly decreased in the folic acid group compared to the placebo group after 3,6 weeks (p=0.005, p<0.001 respectively). The mean scores of MMSE showed no significant difference in same intervals (p=0.068, p=0.068). Conclusion: Our study showed that adjuvant treatment by folic acid in addition to standard treatment with sodium-valproate during manic phase in patients with BMD-I after 6 weeks of treatment was effective

A variant in CYP2R1 predicts circulating vitamin D levels after supplementation with high-dose of vitamin D in healthy adolescent girls

Aim The determinants of serum vitamin D seems to be the environmental factors (dietary and supplementary intake and exposure to ultraviolet light) and genetic factors. We aimed to study the relationship between a vitamin D‐associated genetic polymorphism and serum 25(OH)D concentrations in healthy adolescent girls in Iran, and its effects on a high‐dose supplement of vitamin D. Material and method A total of 616 healthy adolescent girls with mean age 15 received 50,000 IU of vitamin D3 weekly over 9 weeks. Serum vitamin D levels and other metabolic factors were measured at baseline and after the intervention. The genotyping of the CYP2R1 variant (rs10741657) was performed by TaqMan genotyping assays. Results Regardless of the genetic background, at baseline, 87% of adolescent girls were vitamin D deficient (serum 25(OH)D level < 50 nmol/l). High‐dose supplementation with VitD reduced the proportion of girls who were deficient substantially to about 24%. The genetic analysis revealed that although at baseline there was not a gene‐vitamin D association ( p trend = 0.1), the response to supplementation appeared to be modulated by this variant ( p trend < 0.001). However, other anthropometric and biochemical measures were not affected by this intervention, over this short period. Serum 25(OH)D was increased in all participants although the carriers of the minor A allele seemed to be better responders so that the percentages of the change serum vitamin D in the holder of AA and AG genotypes were 539.4 ± 443.1 and 443.7 ± 384.6, respectively, compared with those with common GG genotype (363.3 ± 354.0). Our regression analysis revealed that the probability of an increase in serum 25(OH)D in a participant with AA genotype was 2.5‐fold greater than those with a GG genotype (OR = 2.5 (1.4–4.4); p value = 0.002). Conclusion Based on our findings, it appears that the rs10741657 variant of the CYP2R1 gene modulates the response to high‐dose of vitamin D supplementation

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

The global burden of cancer attributable to risk factors, 2010–19: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. METHODS: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk–outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. FINDINGS: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01–4·94) deaths and 105 million (95·0–116) DALYs for both sexes combined, representing 44·4% (41·3–48·4) of all cancer deaths and 42·0% (39·1–45·6) of all DALYs. There were 2·88 million (2·60–3·18) risk-attributable cancer deaths in males (50·6% [47·8–54·1] of all male cancer deaths) and 1·58 million (1·36–1·84) risk-attributable cancer deaths in females (36·3% [32·5–41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6–28·4) and DALYs by 16·8% (8·8–25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9–42·8] and 33·3% [25·8–42·0]). INTERPRETATION: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden

An enhanced J-integral for hydraulic fracture mechanics

This article revisits the formulation of the J-integral in the context of hydraulic fracture mechanics. We demonstrate that the use of the classical J-integral in finite element models overestimates the length of hydraulic fractures in the viscosity-dominated regime of propagation. A finite element analysis shows that the inaccurate numerical solution for fluid pressure is responsible for the loss in accuracy of the J-integral. With this understanding, two novel contributions are presented. The first contribution consists of two variations of the J-integral, termed the JHFM$J_{HFM}$ and JHFMA$J_{HFM}A$-integral, that demonstrate an enhanced ability to predict viscosity-dominated propagation. In particular, such JHFM$J_{HFM}$-integrals accurately extract stress intensity factors in both viscosity and toughness-dominated regimes of propagation. The second contribution consists of a methodology to extract the propagation velocity from the energy release rate applicable throughout the toughness-viscous propagation regimes. Both techniques are combined to form an implicit front-tracking JHFM$J_{HFM}$-algorithm capable of quickly converging on the location of the fracture front independently to the toughness-viscous regime of propagation. The JHFM$J_{HFM}$-algorithm represents an energy-based alternative to the aperture-based methods frequently used with the Implicit Level Set Algorithm to simulate hydraulic fracturing. Simulations conducted at various resolutions of the fracture suggest that the new approach is suitable for hydro-mechanical finite element simulations at the reservoir scale.ISSN:0363-9061ISSN:1096-985