Post-processing Procedures for Passive GPS based Travel Survey

AbstractA challenge in posteriori data processing for passive GPS based travel survey, which constitute the heart of this paper, is to develop a series of methods to automatically restore the sequences of data points, both in space and time. It means the trips and activities occurred in the survey time should be identifiable chronologically and those identified by the program should respect this definition convention. Reference to the research results of our colleagues, and by combining the experiences of other French travel survey and personal mobility survey at Lille, a series of methods has been developed and put into application. The data outcome is ready for further applications

Self-supervised arbitrary scale super-resolution framework for anisotropic MRI

In this paper, we propose an efficient self-supervised arbitrary-scale super-resolution (SR) framework to reconstruct isotropic magnetic resonance (MR) images from anisotropic MRI inputs without involving external training data. The proposed framework builds a training dataset using in-the-wild anisotropic MR volumes with arbitrary image resolution. We then formulate the 3D volume SR task as a SR problem for 2D image slices. The anisotropic volume's high-resolution (HR) plane is used to build the HR-LR image pairs for model training. We further adapt the implicit neural representation (INR) network to implement the 2D arbitrary-scale image SR model. Finally, we leverage the well-trained proposed model to up-sample the 2D LR plane extracted from the anisotropic MR volumes to their HR views. The isotropic MR volumes thus can be reconstructed by stacking and averaging the generated HR slices. Our proposed framework has two major advantages: (1) It only involves the arbitrary-resolution anisotropic MR volumes, which greatly improves the model practicality in real MR imaging scenarios (e.g., clinical brain image acquisition); (2) The INR-based SR model enables arbitrary-scale image SR from the arbitrary-resolution input image, which significantly improves model training efficiency. We perform experiments on a simulated public adult brain dataset and a real collected 7T brain dataset. The results indicate that our current framework greatly outperforms two well-known self-supervised models for anisotropic MR image SR tasks.Comment: 10 pages, 5 figure

New material of alagomyids

29 p. : ill. ; 26 cm.Includes bibliographical references (p. 26-29).Newly discovered specimens of alagomyids, mostly isolated teeth collected by screenwashing at the Gashatan (late Paleocene) Subeng locality in Inner Mongolia, document considerable intraspecific variation in Tribosphenomys minutus that has not been appreciated previously because of limited sample sizes. P4s of Tribosphenomys are described for the first time, which helps to clarify the posterior premolar identification of alagomyids. Some of the alagomyid specimens are referred to Tribosphenomys cf. T. secundus and Neimengomys qii gen. and sp. nov. Based on the new data, Tribosphenomys borealis from the Bumban Member of the Naran Bulak Formation, Mongolia, is considered to be a junior synonym of Alagomys inopinatus, and T. tertius from the Zhigden Member of the Naran Bulak Formation is regarded as a junior synonymof T. minutus. Alagomyidae, consisting of Tribosphenomys, Alagomys and Neimengomys, is maintained as a valid family. The presence of a diversity of alagomyids and other recently obtained fossils and stratigraphic evidence from the Erlian Basin suggest that the Gashatan and Bumbanian of Asia are probably correlative to the late Tiffanian-early Wasachian of North America. The faunal turnover during the Gashatan and Bumbanian in Asia is probably related to the late Paleocene-early Eocene global warming, but current evidence is insufficient to link any specific event with the Paleocene-Eocene Thermal Maximum

A dexamethasone prodrug reduces the renal macrophage response and provides enhanced resolution of established murine lupus nephritis

We evaluated the ability of a macromolecular prodrug of dexamethasone (P-Dex) to treat lupus nephritis in (NZB × NZW)F1 mice. We also explored the mechanism underlying the anti-inflammatory effects of this prodrug. P-Dex eliminated albuminuria in most (NZB × NZW)F1 mice. Furthermore, P-Dex reduced the incidence of severe nephritis and extended lifespan in these mice. P-Dex treatment also prevented the development of lupus-associated hypertension and vasculitis. Although P-Dex did not reduce serum levels of anti-dsDNA antibodies or glomerular immune complexes, P-Dex reduced macrophage recruitment to the kidney and attenuated tubulointerstitial injury. In contrast to what was observed with free dexamethasone, P-Dex did not induce any deterioration of bone quality. However, P-Dex did lead to reduced peripheral white blood cell counts and adrenal gland atrophy. These results suggest that P-Dex is more effective and less toxic than free dexamethasone for the treatment of lupus nephritis in (NZB × NZW)F1 mice. Furthermore, the data suggest that P-Dex may treat nephritis by attenuating the renal inflammatory response to immune complexes, leading to decreased immune cell infiltration and diminished renal inflammation and injury

An Optimized Implementation of Activation Instruction Based on RISC-V

Activation is an important component of the neural network, and the standard instructions of RISC-V are difficult to use to effectively handle the activation of the array. In this paper, we propose an optimized implementation of activation instruction based on RISC-V. Based on the opensource RISC-V processor Hummingbird E203, we designed a special instruction for the implementation of activation functions. A single instruction is chosen to implement the entire activation operation, including data loading, data arithmetic and data write-back. At the hardware level, we designed a method of alternate reading and writing that only needs a small hardware storage unit to meet the requirements of the activation operation for long arrays without affecting the activation efficiency. In addition, we added the length of the array as a new parameter to instruct our designed hardware to adapt to any length of arrays. Finally, the scheduling method of some instructions in the activation process was optimized in accordance with the law of instructions, which improves the execution efficiency of instructions. Considering an activation process with an array length of 15, our design demonstrates a 4.89-fold increase in speed compared to RISC-V standard instructions while consuming only 7.78% of the energy

Correction: He et al. A 3.95 ppm/°C 7.5 μW Second-Order Curvature Compensated Bandgap Reference in 0.11 μm CMOS. <i>Electronics</i> 2022, <i>11</i>, 2869

In the published publication [...

An Optimized Method for Nonlinear Function Approximation Based on Multiplierless Piecewise Linear Approximation

In this paper, we propose an optimized method for nonlinear function approximation based on multiplierless piecewise linear approximation computation (ML-PLAC), which we call OML-PLAC. OML-PLAC finds the minimum number of segments with the predefined fractional bit width of input/output, maximum number of shift-and-add operations, user-defined widths of intermediate data, and maximum absolute error (MAE). In addition, OML-PLAC minimizes the actual MAE as much as possible by iterating. As a result, under the condition of satisfying the maximum number of segments, the MAE can be minimized. Tree-cascaded 2-input and 3-input multiplexers are used to replace multi-input multiplexers in hardware architecture as well, reducing the depth of the critical path. The optimized method is applied to logarithmic, antilogarithmic, hyperbolic tangent, sigmoid and softsign functions. The results of the implementation prove that OML-PLAC has better performance than the current state-of-the-art method

A 3.95 ppm/°C 7.5 μW Second-Order Curvature Compensated Bandgap Reference in 0.11 μm CMOS

In order to meet the requirements of modern portable electronics for high accuracy and low power consumption of bandgap reference circuits, a new low-voltage bandgap reference with a second-order compensated circuit at 1.8 V is proposed. It features a new self-biased fully symmetric differential operational amplifier circuit with the help of split transistors for achieving low power consumption and high accuracy; by adding a new sub-threshold compensated circuit. The results of simulation show that the temperature coefficient of the second-order circuit is 3.95 ppm/°C in the temperature range of −40 to 125 °C, and the power consumption is only 7.5 μW; this meets both the requirements of high precision and low power consumption. At the same time, the output noise voltage of the design is less than 30 μV/sqrt (Hz) at a frequency of 100 Hz, and the low-frequency supply voltage rejection ratio is −103 dB@100 Hz; these are acceptable for bandgap reference circuits

An Optimized Method for Nonlinear Function Approximation Based on Multiplierless Piecewise Linear Approximation

In this paper, we propose an optimized method for nonlinear function approximation based on multiplierless piecewise linear approximation computation (ML-PLAC), which we call OML-PLAC. OML-PLAC finds the minimum number of segments with the predefined fractional bit width of input/output, maximum number of shift-and-add operations, user-defined widths of intermediate data, and maximum absolute error (MAE). In addition, OML-PLAC minimizes the actual MAE as much as possible by iterating. As a result, under the condition of satisfying the maximum number of segments, the MAE can be minimized. Tree-cascaded 2-input and 3-input multiplexers are used to replace multi-input multiplexers in hardware architecture as well, reducing the depth of the critical path. The optimized method is applied to logarithmic, antilogarithmic, hyperbolic tangent, sigmoid and softsign functions. The results of the implementation prove that OML-PLAC has better performance than the current state-of-the-art method