3-Factor-criticality in double domination edge critical graphs

A vertex subset $S$ of a graph $G$ is a double dominating set of $G$ if $|N[v]\cap S|\geq 2$ for each vertex $v$ of $G$, where $N[v]$ is the set of the vertex $v$ and vertices adjacent to $v$. The double domination number of $G$, denoted by $\gamma_{\times 2}(G)$, is the cardinality of a smallest double dominating set of $G$. A graph $G$ is said to be double domination edge critical if $\gamma_{\times 2}(G+e)<\gamma_{\times 2}(G)$ for any edge $e \notin E$. A double domination edge critical graph $G$ with $\gamma_{\times 2}(G)=k$ is called $k$-$\gamma_{\times 2}(G)$-critical. A graph $G$ is $r$-factor-critical if $G-S$ has a perfect matching for each set $S$ of $r$ vertices in $G$. In this paper we show that $G$ is 3-factor-critical if $G$ is a 3-connected claw-free $4$-$\gamma_{\times 2}(G)$-critical graph of odd order with minimum degree at least 4 except a family of graphs.Comment: 14 page

Unified Predefined-time Stability Conditions of Nonlinear Systems with Lyapunov Analysis

This brief gives a set of unified Lyapunov stability conditions to guarantee the predefined-time/finite-time stability of a dynamical systems. The derived Lyapunov theorem for autonomous systems establishes equivalence with existing theorems on predefined-time/finite-time stability. The findings proposed herein develop a nonsingular sliding mode control framework for an Euler-Lagrange system to analyze its stability, and its upper bound for the settling time can be arbitrarily determined a priori through predefined time constant

Analysis of temperature field for a surface-mounted and interior permanent magnet synchronous motor adopting magnetic-thermal coupling method

Aiming at obtaining high power density of surface-mounted and interior permanent magnet synchronous motor (SIPMSM), it is important to accurately calculate the temperature field distribution of SIPMSM, and a magnetic-thermal coupling method is proposed. The magnetic-thermal coupling mechanism is analyzed. The thermal network model and finite element model are built by this method, respectively. The effects of power frequency on iron losses and temperature fields are analyzed by the magnetic-thermal coupling finite element model under the condition of rated load, and the relationship between the load and temperature field is researched under the condition of the synchronous speed. In addition, the equivalent thermal network model is used to verify the magnetic-thermal coupling method. Then the temperatures of various nodes are obtained. The results show that there are advantages in both computational efficiency and accuracy for the proposed coupling method, which can be applied to other permanent magnet motors with complex structures

Global Cross-Entropy Loss for Deep Face Recognition

Abstract Contemporary deep face recognition techniques predominantly utilize the Softmax loss function, designed based on the similarities between sample features and class prototypes. These similarities can be categorized into four types: in-sample target similarity, in-sample non-target similarity, out-sample target similarity, and out-sample non-target similarity. When a sample feature from a specific class is designated as the anchor, the similarity between this sample and any class prototype is referred to as in-sample similarity. In contrast, the similarity between samples from other classes and any class prototype is known as out-sample similarity. The terms target and non-target indicate whether the sample and the class prototype used for similarity calculation belong to the same identity or not. The conventional Softmax loss function promotes higher in-sample target similarity than in-sample non-target similarity. However, it overlooks the relation between in-sample and out-sample similarity. In this paper, we propose Global Cross-Entropy loss (GCE), which promotes 1) greater in-sample target similarity over both the in-sample and out-sample non-target similarity, and 2) smaller in-sample non-target similarity to both in-sample and out-sample target similarity. In addition, we propose to establish a bilateral margin penalty for both in-sample target and non-target similarity, so that the discrimination and generalization of the deep face model are improved. To bridge the gap between training and testing of face recognition, we adapt the GCE loss into a pairwise framework by randomly replacing some class prototypes with sample features. We designate the model trained with the proposed Global Cross-Entropy loss as GFace. Extensive experiments on several public face benchmarks, including LFW, CALFW, CPLFW, CFP-FP, AgeDB, IJB-C, IJB-B, MFR-Ongoing, and MegaFace, demonstrate the superiority of GFace over other methods. Additionally, GFace exhibits robust performance in general visual recognition task.Abstract Contemporary deep face recognition techniques predominantly utilize the Softmax loss function, designed based on the similarities between sample features and class prototypes. These similarities can be categorized into four types: in-sample target similarity, in-sample non-target similarity, out-sample target similarity, and out-sample non-target similarity. When a sample feature from a specific class is designated as the anchor, the similarity between this sample and any class prototype is referred to as in-sample similarity. In contrast, the similarity between samples from other classes and any class prototype is known as out-sample similarity. The terms target and non-target indicate whether the sample and the class prototype used for similarity calculation belong to the same identity or not. The conventional Softmax loss function promotes higher in-sample target similarity than in-sample non-target similarity. However, it overlooks the relation between in-sample and out-sample similarity. In this paper, we propose Global Cross-Entropy loss (GCE), which promotes 1) greater in-sample target similarity over both the in-sample and out-sample non-target similarity, and 2) smaller in-sample non-target similarity to both in-sample and out-sample target similarity. In addition, we propose to establish a bilateral margin penalty for both in-sample target and non-target similarity, so that the discrimination and generalization of the deep face model are improved. To bridge the gap between training and testing of face recognition, we adapt the GCE loss into a pairwise framework by randomly replacing some class prototypes with sample features. We designate the model trained with the proposed Global Cross-Entropy loss as GFace. Extensive experiments on several public face benchmarks, including LFW, CALFW, CPLFW, CFP-FP, AgeDB, IJB-C, IJB-B, MFR-Ongoing, and MegaFace, demonstrate the superiority of GFace over other methods. Additionally, GFace exhibits robust performance in general visual recognition task

Distinct regulation of ATM signaling by DNA single-strand breaks and APE1

In response to DNA double-strand breaks or oxidative stress, ATM-dependent DNA damage response (DDR) is activated to maintain genome integrity. However, it remains elusive whether and how DNA single-strand breaks (SSBs) activate ATM. Here, we provide direct evidence in Xenopus egg extracts that ATM-mediated DDR is activated by a defined SSB structure. Our mechanistic studies reveal that APE1 promotes the SSB-induced ATM DDR through APE1 exonuclease activity and ATM recruitment to SSB sites. APE1 protein can form oligomers to activate the ATM DDR in Xenopus egg extracts in the absence of DNA and can directly stimulate ATM kinase activity in vitro. Our findings reveal distinct mechanisms of the ATM-dependent DDR activation by SSBs in eukaryotic systems and identify APE1 as a direct activator of ATM kinase

Distinct regulation of ATM signaling by DNA single-strand breaks and APE1

In response to DNA double-strand breaks or oxidative stress, ATM-dependent DNA damage response (DDR) is activated to maintain genome integrity. However, it remains elusive whether and how DNA single-strand breaks (SSBs) activate ATM. Here, we provide direct evidence in Xenopus egg extracts that ATM-mediated DDR is activated by a defined SSB structure. Our mechanistic studies reveal that APE1 promotes the SSB-induced ATM DDR through APE1 exonuclease activity and ATM recruitment to SSB sites. APE1 protein can form oligomers to activate the ATM DDR in Xenopus egg extracts in the absence of DNA and can directly stimulate ATM kinase activity in vitro. Our findings reveal distinct mechanisms of the ATM-dependent DDR activation by SSBs in eukaryotic systems and identify APE1 as a direct activator of ATM kinase

Ground-state shape evolution in Er and Yb isotopes

The ground-state shape (phase) evolution in Er and Yb isotopes is manifested in the axially deformed Nilsson mean-field plus extended pairing model. The energy ratio R 0 2 + /2 1 + , the odd-even mass differences, the ground-state occupation probabilities of valence nucleon pairs with different angular momenta and the information entropy are calculated. It is shown from these quantities as functions of the quadrupole deformation parameter and the overall pairing interaction strength that the ground-state shape (phase) evolution is mainly driven by the pairing interaction and less affected by the quadrupole deformation, which thus provides a possible origin of the ground-state shape (phase) evolution of these isotopes

Delivery of coenzyme Q10 loaded micelle targets mitochondrial ROS and enhances efficiency of mesenchymal stem cell therapy in intervertebral disc degeneration

Stem cell transplantation has been proved a promising therapeutic instrument in intervertebral disc degeneration (IVDD). However, the elevation of oxidative stress in the degenerated region impairs the efficiency of mesenchymal stem cells (BMSCs) transplantation treatment via exaggeration of mitochondrial ROS and promotion of BMSCs apoptosis. Herein, we applied an emulsion-confined assembly method to encapsulate Coenzyme Q10 (Co-Q10), a promising hydrophobic antioxidant which targets mitochondria ROS, into the lecithin micelles, which renders the insoluble Co-Q10 dispersible in water as stable colloids. These micelles are injectable, which displayed efficient ability to facilitate Co-Q10 to get into BMSCs in vitro, and exhibited prolonged release of Co-Q10 in intervertebral disc tissue of animal models. Compared to mere use of Co-Q10, the Co-Q10 loaded micelle possessed better bioactivities, which elevated the viability, restored mitochondrial structure as well as function, and enhanced production of ECM components in rat BMSCs. Moreover, it is demonstrated that the injection of this micelle with BMSCs retained disc height and alleviated IVDD in a rat needle puncture model. Therefore, these Co-Q10 loaded micelles play a protective role in cell survival and differentiation through antagonizing mitochondrial ROS, and might be a potential therapeutic agent for IVDD

Influence of coal structure and macrolithotype of coal on coal adsorption and desorption of gas

In order to study the influence of coal body structure and macrolithotype of coal in high rank coal on coal body adsorption and desorption, The data of coal petrography, coal quality, isothermal adsorption and desorption of 79 coal rock samples from 55 coal-bed methane wells in No.3 Coal Seam in the south of Qinshui Basin were collected, and the change laws in the Langmuir volume (VL), Langmuir pressure (PL), desorption rate of coal samples with the same macrolithotype of coal, different coal body structures and the same coal body structure, different macrolithotype of coal of coal samples, were discussed in the influential mechanisms of coal body structure and macrolithotype of coal on coal body adsorption and desorption. The results show that the average VL of coal samples in the study area is 37.00 m3/t, of which 86.61% is distributed in 33.00—41.00 m3/t, and the average PL is 2.82 MPa, of which 82.28% is distributed in 2.30~3.30 MPa. The adsorption and desorption capacities of fractured coal are better than those of primary structure coal and the difference of pore connectivity caused by structural destruction is the fundamental reason for the difference of desorption and adsorption characteristics between primary structural coal and fractured coal; The development degree of pores and fissures of primary structure coal is different from that of fractured coal. The methane emission effect of fractured coal is better than that of primary structure coal because of more developed pores. The decreasing rule of surface free energy of coal for methane adsorption is the mylonitic coal > granulitic coal > fractured coal > primary structure coal, which reflects the difference of methane adsorption capacity of coal with different coal structure; the adsorption and desorption capabilities of the three types of macro coals are bright coal > semibright coal > semidull coal. On the one hand, the specific surface area of coal decreases roughly in the order of bright coal, semibright coal, and semidull coal, which reflects the difference in adsorption sites on the surface of the coal matrix. On the other hand, it is caused by the difference of vitrinite and inertinite content between vitrain and durain. The purpose of this study is to further reveal the occurrence and production mechanism of CBM in high-rank coal reservoirs, and to provide a basis for the optimization of CBM favorable areas and target horizons