About Smarandache prime additive complement

The main purpose of this paper is using the elementary method to prove a Smarandache prime additive complement

Discussion and design of high vocational education

To set up a vocational technical college within a university is in accordance with the tendency of international high education. It is an important and practical move to develop high vocational education based on China\u27s realities. Although there is much controversy on decision-making and difficulties in operation, in a sense and in a particular period of time, promoting the all-round development of vocational education can not be underestimated. To greatly and timely promote this cause is one of the Key points in the developments of China\u27s 21st century vocational education

2-[7-Chloro-1,1-dioxo-2-(2,4,5-trifluoro­benz­yl)-3,4-dihydro-2H-1,2,4-benzothia­diazin-4-yl]acetic acid

In the mol­ecule of the title compound, C16H12ClF3N2O4S, the thia­diazine ring adopts a half-chair conformation. The dihedral angle between the benzene ring of the benzothia­diazine ring system and trifluoro­phenyl group is 15.02 (7)°. In the crystal, centrosymmetrically related mol­ecules are linked into dimers via pairs of O—H⋯O hydrogen bonds, generating R 2 2(8) ring motifs. The dimers are further connected into a three-dimensional network by C—H⋯O hydrogen bonds

Fillers and methods to improve the effective (out-plane) thermal conductivity of polymeric thermal interface materials – A review

[Abstract]: The internet of things and growing demand for smaller and more advanced devices has created the problem of high heat production in electronic equipment, which greatly reduces the work performance and life of the electronic instruments. Thermal interface material (TIM) is placed in between heat generating micro-chip and the heat dissipater to conduct all the produced heat to the heat sink. The development of suitable TIM with excellent thermal conductivity (TC) in both in-plane and through-plane directions is a very important need at present. For efficient thermal management, polymer composites are potential candidates. But in general, their thermal conductivity is low compared to that of metals. The filler integration into the polymer matrix is one of the two approaches used to increase the thermal conductivity of polymer composites and is also easy to scale up for industrial production. Another way to achieve this is to change the structure of polymer chains, which fall out of the scope of this work. In this review, considering the first approach, the authors have summarized recent developments in many types of fillers with different scenarios by providing multiple cases with successful strategies to improve throughplane thermal conductivity (TPTC) (k⊥). For a better understanding of TC, a comprehensive background is presented. Several methods to improve the effective (out-plane) thermal conductivity of polymer composites and different theoretical models for the calculation of TC are also discussed. In the end, it is given a detailed conclusion that provides drawbacks of some fillers, multiple significant routes recommended by other researchers to build thermally conductive polymer composites, future aspects along with direction so that the researchers can get a guideline to design an effective polymer-based thermal interface material.This research was funded by Ministry of Science and Technology of the People’s Republic of China, “Light Shipbuilding Fire- Resistant Sandwich Panels with Improved Balance of Acoustic Insulation, Mechanical and Environmentally-Friendly Properties”, grant number 2019YFE0124000.China. Ministry of Science and Technolog

Correlation between intercalated magnetic layers and superconductivity in pressurized EuFe2(As0.81P0.19)2

We report comprehensive high pressure studies on correlation between intercalated magnetic layers and superconductivity in EuFe2(As0.81P0.19)2 single crystal through in-situ high pressure resistance, specific heat, X-ray diffraction and X-ray absorption measurements. We find that an unconfirmed magnetic order of the intercalated layers coexists with superconductivity in a narrow pressure range 0-0.5GPa, and then it converts to a ferromagnetic (FM) order at pressure above 0.5 GPa, where its superconductivity is absent. The obtained temperature-pressure phase diagram clearly demonstrates that the unconfirmed magnetic order can emerge from the superconducting state. In stark contrast, the superconductivity cannot develop from the FM state that is evolved from the unconfirmed magnetic state. High pressure X-ray absorption (XAS) measurements reveal that the pressure-induced enhancement of Eu's mean valence plays an important role in suppressing the superconductivity and tuning the transition from the unconfirmed magnetic state to a FM state. The unusual interplay among valence state of Eu ions, magnetism and superconductivity under pressure may shed new light on understanding the role of the intercalated magnetic layers in Fe-based superconductors

Expression analysis of epb41l4a during Xenopus laevis embryogenesis

Epbl41l4a (erythrocyte protein band 4.1-like 4a, also named Nbl4) is a member of the band 4.1/Nbl4 (novel band 4.1-like protein 4) group of the FERM (4.1, ezrin, radixin, moesin) protein superfamily. Proteins encoded by this gene family are involved in many cellular processes such as organization of epithelial cells and signal transduction. On a molecular level, band 4.1/Nbl4 proteins have been shown to link membrane-associated proteins and lipids to the actin cytoskeleton. Epbl41l4a has also recently been identified as a target gene of the Wnt/β-catenin pathway. Here, we describe for the first time the spatiotemporal expression of epbl41l4a using Xenopus laevis as a model system. We observed a strong and specific expression of epb41l4a in the developing somites, in particular during segmentation as well as in the nasal and cranial placodes, pronephros, and neural tube. Thus, epbl41l4a is expressed in tissues undergoing morphogenetic movements, suggesting a functional role of epbl41l4a during these processes

Tumor-Specific Human CD4+ Regulatory T Cells and Their Ligands Implications for Immunotherapy

AbstractRegulatory T cells play an important role in the maintenance of immunological self-tolerance by suppressing immune responses against autoimmune diseases and cancer. Little is known, however, about the nature of the physiological target antigens for CD4+ regulatory T (Treg) cells. Here we report the identification of the LAGE1 protein as a ligand for tumor-specific CD4+ Treg cell clones generated from the tumor-infiltrating lymphocytes (TILs) of cancer patients. Phenotypic and functional analyses demonstrated that they were antigen-specific CD4+ Treg cells expressing CD25 and GITR molecules and possessing suppressive activity on the proliferative response of naive CD4+ T cells to anti-CD3 antibody stimulation. Ligand-specific activation and cell-cell contact were required for TIL102 Treg cells to exert suppressive activity on CD4+ effector cells. These findings suggest that the presence of tumor-specific CD4+ Treg cells at tumor sites may have a profound effect on the inhibition of T cell responses against cancer

Recognize Anything: A Strong Image Tagging Model

We present the Recognize Anything Model (RAM): a strong foundation model for image tagging. RAM can recognize any common category with high accuracy. RAM introduces a new paradigm for image tagging, leveraging large-scale image-text pairs for training instead of manual annotations. The development of RAM comprises four key steps. Firstly, annotation-free image tags are obtained at scale through automatic text semantic parsing. Subsequently, a preliminary model is trained for automatic annotation by unifying the caption and tagging tasks, supervised by the original texts and parsed tags, respectively. Thirdly, a data engine is employed to generate additional annotations and clean incorrect ones. Lastly, the model is retrained with the processed data and fine-tuned using a smaller but higher-quality dataset. We evaluate the tagging capabilities of RAM on numerous benchmarks and observe impressive zero-shot performance, significantly outperforming CLIP and BLIP. Remarkably, RAM even surpasses the fully supervised manners and exhibits competitive performance with the Google API. We are releasing the RAM at \url{https://recognize-anything.github.io/} to foster the advancements of large models in computer vision