Palatini formulation of f(R,T)f(R,T) gravity theory, and its cosmological implications

We consider the Palatini formulation of $f(R,T)$ gravity theory, in which a nonminimal coupling between the Ricci scalar and the trace of the energy-momentum tensor is introduced, by considering the metric and the affine connection as independent field variables. The field equations and the equations of motion for massive test particles are derived, and we show that the independent connection can be expressed as the Levi-Civita connection of an auxiliary, energy-momentum trace dependent metric, related to the physical metric by a conformal transformation. Similarly to the metric case, the field equations impose the non-conservation of the energy-momentum tensor. We obtain the explicit form of the equations of motion for massive test particles in the case of a perfect fluid, and the expression of the extra-force, which is identical to the one obtained in the metric case. The thermodynamic interpretation of the theory is also briefly discussed. We investigate in detail the cosmological implications of the theory, and we obtain the generalized Friedmann equations of the $f(R,T)$ gravity in the Palatini formulation. Cosmological models with Lagrangians of the type $f=R-\alpha ^2/R+g(T)$ and $f=R+\alpha ^2R^2+g(T)$ are investigated. These models lead to evolution equations whose solutions describe accelerating Universes at late times.Comment: 22 pages, no figures, accepted for publication in EPJC; references adde

Coupling vibration model for hot rolling mills and its application

In this paper, we propose an effective mechanical-electrical-hydraulic-interfacial coupling vibration model for hot rolling mills and obtain a practical measure to relieve mill vibration. First, an experiment related to mill modulus control gain in automatic gauge control (AGC) is carried out during manufacturing. Rolling mill vibration is observed to gradually be enhanced with increasing mill modulus control gain. Then, to explain this phenomenon, the mechanical-electrical-hydraulic-interface coupling dynamic model is modeled based on Sims’ rolling force method. Finally, we analyze the influence of mill modulus control gain on the vibration numerically on the basis of the coupling dynamic model. Moreover, the agreement between the experiment result and the simulation result is confirmed and the measure reducing the mill modulus control gain is obtained to relieve mill vibration

Molecular and Paleontological Evidence for a Post-Cretaceous Origin of Rodents

The timing of the origin and diversification of rodents remains controversial, due to conflicting results from molecular clocks and paleontological data. The fossil record tends to support an early Cenozoic origin of crown-group rodents. In contrast, most molecular studies place the origin and initial diversification of crown-Rodentia deep in the Cretaceous, although some molecular analyses have recovered estimated divergence times that are more compatible with the fossil record. Here we attempt to resolve this conflict by carrying out a molecular clock investigation based on a nine-gene sequence dataset and a novel set of seven fossil constraints, including two new rodent records (the earliest known representatives of Cardiocraniinae and Dipodinae). Our results indicate that rodents originated around 61.7–62.4 Ma, shortly after the Cretaceous/Paleogene (K/Pg) boundary, and diversified at the intraordinal level around 57.7–58.9 Ma. These estimates are broadly consistent with the paleontological record, but challenge previous molecular studies that place the origin and early diversification of rodents in the Cretaceous. This study demonstrates that, with reliable fossil constraints, the incompatibility between paleontological and molecular estimates of rodent divergence times can be eliminated using currently available tools and genetic markers. Similar conflicts between molecular and paleontological evidence bedevil attempts to establish the origination times of other placental groups. The example of the present study suggests that more reliable fossil calibration points may represent the key to resolving these controversies.Organismic and Evolutionary Biolog

Measurements of Natural Carbonate Rare Earth Elements in Femtogram Quantities by Inductive Coupled Plasma Sector Field Mass Spectrometry

A rapid and precise standard-bracketing method has been developed for measuring femtogram quantity rare earth element (REE) levels in natural carbonate samples by inductively coupled plasma sector field mass spectrometry that does not require chemical separation steps. A desolvation nebulization system was used to effectively reduce polyatomic interference and enhance sensitivity. REE/Ca ratios are calculated directly from the intensities of the ion beams of 46Ca, 139La, 140Ce, 141Pr, 146Nd, 147Sm, 153Eu, 160Gd, 159Tb, 163Dy, 165Ho, 166Er, 169Tm, 172Yb, and 175Lu using external matrix-matched synthetic standards to correct for instrumental ratio drifting and mass discrimination. A routine measurement time of 3 min is typical for one sample containing 20-40 ppm Ca. Replicate measurements made on natural coral and foraminiferal samples with REE/Ca ratios of 2-242 nmol/mol show that external precisions of 1.9-6.5% (2 RSD) can be achieved with only 10-1000 fg of REEs in 10-20 μg of carbonate. We show that different sources for monthly resolved coral ultratrace REE variability can be distinguished using this method. For natural slow growth-rate carbonate materials, such as sclerosponges, tufa, and speleothems, the high sample throughput, high precision, and high temporal resolution REE records that can be produced with this procedure have the potential to provide valuable time-series records to advance our understanding of paleoclimatic and paleoenvironmental dynamics on different time scales

Strong Pseudospin-Lattice Coupling in Sr3Ir2O7: Coherent Phonon Anomaly and Negative Thermal Expansion

The similarities to cuprates make iridates an interesting potential platform for investigating superconductivity. Equally attractive are their puzzling complex intrinsic interactions. Here, we report an ultrafast optical spectroscopy investigation of a coherent phonon mode in Sr3Ir2O7, a bilayer Ruddlesden-Popper perovskite iridate. An anomaly in the A1g optical phonon ({\nu} = 4.4 THz) is unambiguously observed below the N\'eel temperature (TN), which we attribute to pseudospin-lattice coupling (PLC). Significantly, we find that PLC is the dominant interaction at low temperature, and we directly measure the PLC coefficient to be {\lambda} = 150 +/- 20 cm-1, which is two orders of magnitude higher than that in manganites (< 2.4 cm-1) and comparable to that in CuO (50 cm-1, the strongest PLC or spin-lattice coupling (SLC) previously known). Moreover, we find that the strong PLC induces an anisotropic negative thermal expansion. Our findings highlight the key role of PLC in iridates and uncovers another intriguing similarity to cuprates

Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.

PURPOSE This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism. METHODS This study involved 1017 subjects who underwent DAT PET imaging ([11C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism. A full-gradient saliency map approach was employed to investigate the functional basis related to the decision mechanism of the network. Furthermore, deep-learning-guided radiomics features and quantitative analysis were compared with their conventional counterparts to further interpret the performance of deep learning. RESULTS The proposed network achieved area under the curve of 0.953 (sensitivity 87.7%, specificity 93.2%), 0.948 (sensitivity 93.7%, specificity 97.5%), and 0.900 (sensitivity 81.5%, specificity 93.7%) in the cross-validation, together with sensitivity of 90.7%, 84.1%, 78.6% and specificity of 88.4%, 97.5% 93.3% in the blind test for the differential diagnosis of IPD, MSA and PSP, respectively. The saliency map demonstrated the most contributed areas determining the diagnosis located at parkinsonism-related regions, e.g., putamen, caudate and midbrain. The deep-learning-guided binding ratios showed significant differences among IPD, MSA and PSP groups (P < 0.001), while the conventional putamen and caudate binding ratios had no significant difference between IPD and MSA (P = 0.24 and P = 0.30). Furthermore, compared to conventional radiomics features, there existed average above 78.1% more deep-learning-guided radiomics features that had significant differences among IPD, MSA and PSP. CONCLUSION This study suggested the developed deep neural network can decode in-depth information from DAT and showed potential to assist the differential diagnosis of parkinsonism. The functional regions supporting the diagnosis decision were generally consistent with known parkinsonian pathology but provided more specific guidance for feature selection and quantitative analysis