Study on the design method of integration of roof and photovoltaic based on aesthetics, technology and energy-saving characteristic

The development and utilization of new energy has been concerned due to the traditional energy is increasingly scarce. In recent years, solar building has developed rapidly in the construction industry which is a major energy consuming component. As an organic part of the building, the combination of roof and solar energy has become the focus of attention because of its large size, less shielding and other characteristics. Based on the works of recent years’ Solar Decathlon, this paper analysed the design and implementation of the integration of solar building’s roof and photovoltaic. Meanwhile, taking an office building in Xinjiang, China as an example, the paper analysed the design points and energy-saving situation of the roof photovoltaic building and prospected the application prospect of integrated design method of building’s solar roof

Role of sea quarks in the nucleon transverse spin

We present a phenomenological extraction of transversity distribution functions and Collins fragmentation functions by simultaneously fitting to semi-inclusive deep inelastic scattering and electron-positron annihilation data. The analysis is performed within the transverse momentum dependent factorization formalism, and sea quark transversity distributions are taken into account for the first time. We find the $\bar u$ quark favors a negative transversity distribution while that of the $\bar d$ quark is consistent with zero according to the current accuracy. In addition, based on a combined analysis of world data and simulated data, we quantitatively demonstrate the impact of the proposed Electron-ion Collider in China on precise determinations of the transversity distributions, especially for sea quarks, and the Collins fragmentation functions

Elixir: Train a Large Language Model on a Small GPU Cluster

In recent years, the number of parameters of one deep learning (DL) model has been growing much faster than the growth of GPU memory space. People who are inaccessible to a large number of GPUs resort to heterogeneous training systems for storing model parameters in CPU memory. Existing heterogeneous systems are based on parallelization plans in the scope of the whole model. They apply a consistent parallel training method for all the operators in the computation. Therefore, engineers need to pay a huge effort to incorporate a new type of model parallelism and patch its compatibility with other parallelisms. For example, Mixture-of-Experts (MoE) is still incompatible with ZeRO-3 in Deepspeed. Also, current systems face efficiency problems on small scale, since they are designed and tuned for large-scale training. In this paper, we propose Elixir, a new parallel heterogeneous training system, which is designed for efficiency and flexibility. Elixir utilizes memory resources and computing resources of both GPU and CPU. For flexibility, Elixir generates parallelization plans in the granularity of operators. Any new type of model parallelism can be incorporated by assigning a parallel pattern to the operator. For efficiency, Elixir implements a hierarchical distributed memory management scheme to accelerate inter-GPU communications and CPU-GPU data transmissions. As a result, Elixir can train a 30B OPT model on an A100 with 40GB CUDA memory, meanwhile reaching 84% efficiency of Pytorch GPU training. With its super-linear scalability, the training efficiency becomes the same as Pytorch GPU training on multiple GPUs. Also, large MoE models can be trained 5.3x faster than dense models of the same size. Now Elixir is integrated into ColossalAI and is available on its main branch

Inverse saturable absorption mechanism and design optimization of mode-locked fiber lasers with a nonlinear amplifying loop mirror

From the point of view of the differential phase delay experienced by the two counterpropagating optical fields, the self-starting of the mode-locked fiber laser with a nonlinear amplifying loop mirror (NALM) is theoretically studied. Although it is generally believed that NALM shows a saturable absorption effect on both continuous wave (CW) light and pulses, we find a counter-intuitive fact that cross-phase modulation (XPM) leads to opposite signs of differential nonlinear phase shifts (NPSs) in these two cases, resulting in inverse saturable absorption (ISA) during pulse formation process. The ISA is not helpful for the self-starting of laser mode-locking and can be alleviated by introducing a non-reciprocal phase shifter into the fiber loop. In addition, we analyze the influences of gain-fiber position, splitting ratio, and optical attenuator in the fiber loop, on the differential NPS and self-starting process. These results are helpful for optimizing the design of NALM and lowering the self-starting threshold of the high-repetition-rate mode-locked fiber laser.Comment: 13 pages, 5 figure

Error reduction method for singularity point detection using Shack–Hartmann wavefront sensor

AbstractA new framework is proposed for realizing high-spatial-resolution detection of singularity points in optical vortex beams using a Shack–Hartmann wavefront sensor (SHWS). The method uses a Shack–Hartmann wavefront sensor (SHWS) to record a Hartmanngram. A map of evaluation values related to phase slope is then calculated from the Hartmanngram. We first determined the singularity's position precisely by calculating the centroid of the circulation of 3×3 crosspoints. After that, we analyzed the error distribution of it, and proposed hybrid centroiding framework for reducing its error. Optical experiments were carried out to verify the method. Good linearity was showed in detecting positions of the singularity points, and it was indicated that the accuracy of detection the position of OV was improved. The average root mean square (RMS) error over various measurements was better than correlation matching method, which we proposed before. The method not only shows higher accuracy, but also consumes much less time than our former work

New Insight into the Anti-liver Fibrosis Effect of Multitargeted Tyrosine Kinase Inhibitors: From Molecular Target to Clinical Trials

Tyrosine kinases (TKs) is a family of tyrosine protein kinases with important functions in the regulation of a broad variety of physiological cell processes. Overactivity of TK disturbs cellular homeostasis and has been linked to the development of certain diseases, including various fibrotic diseases. In regard to liver fibrosis, several TKs, such as vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), fibroblast growth factor receptor (FGFR) and epidermal growth factor receptor (EGFR) kinases, have been identified as central mediators in collagen production and potential targets for anti-liver fibrosis therapies. Given the essential role of TKs during liver fibrogenesis, multitargeted inhibitors of aberrant TK activity, including sorafenib, erlotinib, imatinib, sunitinib, nilotinib, brivanib and vatalanib, have been shown to have potential for treating liver fibrosis. Beneficial effects are observed by researchers of this field using these multitargeted TK inhibitors in preclinical animal models and in patients with liver fibrosis. The present review will briefly summarize the anti-liver fibrosis effects of multitargeted TK inhibitors and molecular mechanisms