Some remarks on the dynamical systems approach to fourth order gravity

Building on earlier work, we discuss a general framework for exploring the cosmological dynamics of Higher Order Theories of Gravity. We show that once the theory of gravity has been specified, the cosmological equations can be written as a first-order autonomous system and we give several examples which illustrate the utility of our method. We also discuss a number of results which have appeared recently in the literature.Comment: 19 pages, LaTe

Spinocerebellar ataxia type 14: refining clinicogenetic diagnosis in a rare adult-onset disorder

OBJECTIVES: Genetic variant classification is a challenge in rare adult-onset disorders as in SCA-PRKCG (prior spinocerebellar ataxia type 14) with mostly private conventional mutations and nonspecific phenotype. We here propose a refined approach for clinicogenetic diagnosis by including protein modeling and provide for confirmed SCA-PRKCG a comprehensive phenotype description from a German multi-center cohort, including standardized 3D MR imaging. METHODS: This cross-sectional study prospectively obtained neurological, neuropsychological, and brain imaging data in 33 PRKCG variant carriers. Protein modeling was added as a classification criterion in variants of uncertain significance (VUS). RESULTS: Our sample included 25 cases confirmed as SCA-PRKCG (14 variants, thereof seven novel variants) and eight carriers of variants assigned as VUS (four variants) or benign/likely benign (two variants). Phenotype in SCA-PRKCG included slowly progressive ataxia (onset at 4-50 years), preceded in some by early-onset nonprogressive symptoms. Ataxia was often combined with action myoclonus, dystonia, or mild cognitive-affective disturbance. Inspection of brain MRI revealed nonprogressive cerebellar atrophy. As a novel finding, a previously not described T2 hyperintense dentate nucleus was seen in all SCA-PRKCG cases but in none of the controls. INTERPRETATION: In this largest cohort to date, SCA-PRKCG was characterized as a slowly progressive cerebellar syndrome with some clinical and imaging features suggestive of a developmental disorder. The observed non-ataxia movement disorders and cognitive-affective disturbance may well be attributed to cerebellar pathology. Protein modeling emerged as a valuable diagnostic tool for variant classification and the newly described T2 hyperintense dentate sign could serve as a supportive diagnostic marker of SCA-PRKCG

Fatigue behavior of PBO FRCM composite applied to concrete substrate

Several reinforced-concrete (RC) structural elements are subjected to cyclic load, such those employed in highway and railroad bridges and viaducts. The durability of these elements may be reduced as a consequence of fatigue, which mainly affects the steel reinforcement. The use of externally bonded (EB) fiber-reinforced cementitious matrix (FRCM) composites allows the moment capacity to be shared by the internal reinforcement and the EB composite, thus increasing the fatigue life of the strengthened RC member. The effectiveness of EB FRCM composites is related to the composite bond properties. However, limited research is currently available on the effect of fatigue on the bond behavior of FRCM-substrate joints. This study provides first the state of the art on the fatigue behavior of different FRCM composites bonded to a concrete substrate. Then, the fatigue bond behavior of a polyparaphenylene benzo-bisoxazole (PBO) FRCM is experimentally investigated using a modified beam test set-up. The use of this set-up provided information on the effect of fiber-matrix interface shear and normal stresses on the specimen fatigue bond behavior. The results showed that fatigue loading may induce premature debonding at the matrix-fiber interface and that stresses normal to the interface reduce the specimen fatigue life

Spinocerebellar ataxia type 14: refining clinico-genetic diagnosis in a rare adult-onset disorder

OBJECTIVES: Genetic variant classification is a challenge in rare adult-onset disorders as in SCA-PRKCG (prior spinocerebellar ataxia type 14) with mostly private conventional mutations and nonspecific phenotype. We here propose a refined approach for clinicogenetic diagnosis by including protein modeling and provide for confirmed SCA-PRKCG a comprehensive phenotype description from a German multi-center cohort, including standardized 3D MR imaging. METHODS: This cross-sectional study prospectively obtained neurological, neuropsychological, and brain imaging data in 33 PRKCG variant carriers. Protein modeling was added as a classification criterion in variants of uncertain significance (VUS). RESULTS: Our sample included 25 cases confirmed as SCA-PRKCG (14 variants, thereof seven novel variants) and eight carriers of variants assigned as VUS (four variants) or benign/likely benign (two variants). Phenotype in SCA-PRKCG included slowly progressive ataxia (onset at 4-50 years), preceded in some by early-onset nonprogressive symptoms. Ataxia was often combined with action myoclonus, dystonia, or mild cognitive-affective disturbance. Inspection of brain MRI revealed nonprogressive cerebellar atrophy. As a novel finding, a previously not described T2 hyperintense dentate nucleus was seen in all SCA-PRKCG cases but in none of the controls. INTERPRETATION: In this largest cohort to date, SCA-PRKCG was characterized as a slowly progressive cerebellar syndrome with some clinical and imaging features suggestive of a developmental disorder. The observed non-ataxia movement disorders and cognitive-affective disturbance may well be attributed to cerebellar pathology. Protein modeling emerged as a valuable diagnostic tool for variant classification and the newly described T2 hyperintense dentate sign could serve as a supportive diagnostic marker of SCA-PRKCG

Prospects for precise predictions of aμa_\mu in the Standard Model

We discuss the prospects for improving the precision on the hadronic corrections to the anomalous magnetic moment of the muon, and the plans of the Muon $g-2$ Theory Initiative to update the Standard Model prediction