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Background As the number of diabetics worldwide continues to increase, diabetic cardiomyopathy has become one of the main causes of cardiovascular disease risk in diabetic patients. Currently, the pathophysiological mechanism of DCM has not been fully elucidated. In the present study, relevant pathological changes of cardiomyocytes in the high glucose environment were simulated by in vitro culture of rat H9C2 cardiomyocytes, to explore the mechanism by which MCU induces apoptosis in cardiomyocytes. Method: Cultured rat myocardium H9C2 cells in vitro and divided into high glucose group (glucose concentration 33 mmol/L), normal group (glucose concentration 5.5 mmol/L), experimental group (5.5 mmol/L glucose and transfected with MCU siRNA) and control group (5.5 mmol/L glucose and transfected negative control siRNA). Comparative analysis of MCU expression, Ca2+ uptake, mitochondrial function, oxidative stress and apoptosis of two groups of cells. Results (1) Compared with normal group, in the high glucose group the MCU expression of myocardial cells in H9C2 rats decreased, The Ca2+ levels, membrane potential and mitochondrial ATP levels decreased, mitochondrial ROS levels increased, NADH+/NADPH ratio in cardiomyocytes increased, GSH/GSSG ratio decreased, the expression levels of cleaved caspase-3 and cleaved caspase-9 increased, bcl-2 expression decreased, the number of cardiomyocytes apoptotic cells increases. (2) Compared with the normal group and the control group, the experimental group MCU expression of myocardial cells in H9C2 rats decreased, The Ca2+ levels, membrane potential and mitochondrial ATP levels decreased, mitochondrial ROS levels increased, NADH+/NADPH ratio in cardiomyocytes increased, GSH/GSSG ratio decreased, the expression levels of cleaved caspase-3 and cleaved caspase-9 increased, bcl-2 expression decreased, the number of cardiomyocytes apoptotic cells increases. Discussion This study suggested that MCU expression in rat H9C2 cardiomyocytes was decreased in the high glucose environment, causing abnormal mitochondrial calcium uptake and imbalanced calcium homeostasis, which may further contribute to mitochondrial dysfunction and enhanced oxidative stress in cardiomyocytes. Mitochondrial dysfunction and enhanced oxidative stress ultimately led to apoptosis in cardiomyocytes.

The application of compressed sensing and machine learning in power quality disturbance (PQD) classification has drawn more and more attention. This paper presents an adaptive compressed sensing and machine learning (ACSML) method to classify both single PQD and combined PQDs with the consideration of the correlation and the sparsity properties in the PQD signals. This method first uses random projection to reduce the dimensionality of the PQD signals. Meanwhile, a simplified near neighbor algorithm is proposed to reduce the size of the required PQD signal training dataset. The PQD classification problem is finally solved using an adaptive compressed sensing classification algorithm. Experiment results show that the proposed ACSML method achieves higher classification accuracy and faster classification speed in classifying PQDs than the other existing compressed sensing based PQD classification methods.

Indoor positioning system plays an important role in smart grid. Although GPS is the predominant outdoor positioning technology, it is unsuitable to be used in many fields of smart grid for three main reasons: first, signals sent from GPS could easily get blocked by solid materials such as metal or brick; second, the complex electromagnetic interference induced by electrical circuits greatly affects GPS signals; third, GPS can only achieve meter-level real time positioning accuracy, which is far from sufficient for many requirements of smart grid applications. Some other indoor positioning technologies, such as Bluetooth, Wi-Fi, ultrasound, infrared and RFID, fail in either the positioning accuracy, the positioning range, or the positioning speed required in many smart grid applications. Therefore, this paper proposes a real time indoor positioning system for smart gird based on a more promising technology, ultra-wideband (UWB). UWB is suitable for real-time localization in smart grid because UWB has short radio frequency pulse duration and wide bandwidth, which can minimize the effects of multipath interference and allow for high-resolution ranging and easier material penetration. In addition, since high-accuracy position information is required in many smart grid fields, a comprehensive framework integrating several artificial intelligence techniques, including outlier detection, line-of-sight/non-line-of-sight classification, filter design, range measurement correction and maximum likelihood localization estimation, is also proposed to further improve the positioning accuracy. At last, the performance of this system is verified through a series of experiments.

Compressive sensing related methods have achieved success in power system fault classification. However, those methods, either only focus on sparsity without considering the correlation within power system fault signals, or emphasize too much on the correlation but neglect the sparsity property of power system fault signals, resulting in the decrease of classification precision and the increase of the number of training samples needed. In addition, those methods do not explore other machine learning techniques at the same time to further improve the classification accuracy and speed. To overcome the drawbacks and limitations of those methods, this paper proposes an adaptive compressive sensing and machine learning classification framework to quickly and accurately classify power system faults considering both the correlation and the sparsity properties inherited in power system fault signals. First, random projection is applied to reduce the dimensionality of the fault signal. Second, a k-nearest neighbor based algorithm is designed to reduce the number of fault signals needed in the training dataset. Finally, the classification of power system faults is formulated as solving an adaptive L1-norm and L2-norm combined objective function using an alternating direction optimization method. Simulation results and analyses show that the proposed framework has better performance than the existing compressive sensing based power system faulty classification methods in both accuracy and speed.

We introduce modified generalized Wigner-Yanase-Dyson (MGWYD) skew information and modified weighted generalized Wigner-Yanase-Dyson (MWGWYD) skew information. By revisiting state-channel interaction based on MGWYD skew information, a family of coherence measures with respect to quantum channels is proposed. Furthermore, explicit analytical expressions of these coherence measures of qubit states are derived with respect to different quantum channels. Moreover, complementarity relations based on MGWYD skew information and MWGWYD skew information are also presented. Specifically, the conservation relations are investigated, while two interpretations of them including symmetry-asymmetry complementarity and wave-particle duality have been proposed., 20pages

Canonical correlation analysis (CCA) is a popular and powerful technique for two-view dimension reduction and feature extraction. But, CCA is not able to directly handle more than two view data and has a rigorous assumption that all the samples from two different views are paired. However, practical multiple view data are often semi-paired. To address this problem, we in this paper propose a novel semi-paired multiview dimension reduction approach, which takes cross-view neighborhood relationship among semi-paired data and within-view global structure information into consideration. The proposed approach can not only deal with multiview (more than two) data, but also take sufficient advantage of unpaired multiview data and then mitigate overfitting effectively caused by the limited paired data. Experimental results on two benchmark data sets demonstrate the effectiveness of our proposed method.

Information transfer in generalized probabilistic theories (GPT) is an important problem. We have dealt with the problem based on repeatability postulate, which generalizes Zurek's result to the GPT framework [Phys. Lett. A \textbf{379} (2015) 2694]. A natural question arises: can we deduce the information transfer result under weaker assumptions? In this paper, we generalize Zurek's result to the framework of GPT using weak repeatability postulate. We show that if distinguishable information can be transferred from a physical system to a series of apparatuses under the weak repeatability postulate in GPT, then the initial states of the physical system must be completely distinguishable. Moreover, after each step of invertible transformation, the composite states of the composite system composed of the physical systems and the apparatuses must also be completely distinguishable., 11 pages

Depression has been a major concern for the employers due to its high prevalence and cost. In United States, 6.8% of the work population had depression and it is accountable for over $100 billion workplace loss every year. Early detection and timely intervention is the key to address this challenge. In this paper, we proposed to leverage a large claim dataset to build depression risk prediction model. This approach is easy to implement and scale because the claim data is accessible for employers at no additional cost. We derived a subset of over 7.2 million patients in a 3-year period, with 2,099 variables including the diagnosis, procedure, medication, and health service provider information. We trained two models (Least Absolute Shrinkage and Selection Operator (LASSO) and random forest *RF)) with first two years data to predict the onset of depression in the third year. Both models achieved the best comparable performance so far according to our knowledge. The important variables identified by our algorithms are mental health related medications and diagnoses (other than depression), gender (female), and other chronic conditions such as back pain. We further validated these variables by confirming in clinical literature. We concluded that the claim data based depression prediction is a viable and low cost approach, especially for self-insured employers.

In this paper, we introduce the concepts of cyclic $$\varphi $$ -contractions in Menger PM-spaces and cyclic weak $$\phi $$ -contractions in generalized Menger PM-spaces. Based on these concepts, some fixed point results for cyclic $$\varphi $$ -contractions in Menger PM-spaces are obtained. Furthermore, some fixed point theorems for cyclic weak $$\phi $$ -contractions and cyclic $$\varphi $$ -contractions in generalized Menger PM-spaces are obtained by assuming that the number of cyclic sets is odd. An example is also given to show the validity of our main results.

In this paper, we obtain some new fixed point theorems for (?,?,?,?) -contractive multi-valued mappings in ?-?-T-complete Menger PM-spaces, which turn out to generalize many results in existing literatures. Some examples are also given to illustrate the definition and support our new results. Moreover, some interesting fixed point results endowed with binary relations or graphs are derived as applications of our main results.

A key aspect of the mimetic defense system is the scheduling of heterogeneous executions to ensure that the system is dynamic. The existing scheduling strategy only performs random scheduling to satisfy heterogeneity and service quality. Combined with the historical information of the arbiter in the mimicry defense system, this paper proposed a random seed scheduling algorithm based on historical confidence for maximum heterogeneity and quality of service. First, the seed performer is randomly selected in the historical confidence executor that satisfies the threshold, and then the scheduling scheme is determined according to the maximum heterogeneity type and the quality of service indicator. The simulation results showed that the scheduling period of the algorithm is lower than the random scheduling algorithm. However, the scheduling effect is higher than the random scheduling algorithm, which achieved a good dynamic balance between dynamics, security, and quality of service.

In this paper, we propose some new coupled coincidence point and fixed point theorems for the mappings F and g. Our results are obtained by exploring the corresponding initial value problems for the mapping F and weakening the involved contractive conditions. As an application, we study the existence and uniqueness of solution to integro-differential equations.

Anti-washout underwater concrete (AWC) is widely used in nondrainage strengthening, however, there still exist some problems with it, such as high strength loss and poor interfacial bond in practical engineering application. Based on the study of self-stressed concrete (SSC), a research on the mix ratio for the C30 self-stressed anti-washout underwater concrete (SSAWC) was carried out in this paper in hope of solving the above problems, specifically, by adding an expansive agent to the AWC. The parameters, such as strength, fluidity, anti-dispersity, and expansibility, were picked as target indices in determination of the mix ratio. The orthogonal test design and range analysis were used to determine the reasonable mix ratio and study the influence of various parameters on the performance of SSAWC. The experimental program conducted includes a series of strength, fluidity, anti-dispersity, and expansibility tests on 18 groups of specimens. The results show that C30 SSAWC has an excellent performance using the optimal mix ratio. Compared with AWC, the expansibility and self-stress of the SSAWC can be easily observed, and the compressive strength ratio of the SSAWC casted in water to that casted in air is much bigger. This implies that SSAWC is applicable to the nondrainage strengthening.

We investigate facial expression recognition using state-of-the-art classification models. Recently, CNNs have been extensively used for face recognition. However, CNNs have not been thoroughly evaluated for facial expression recognition. In this paper, we train and test a CNN model for facial expression recognition. The performance of the CNN model is used as benchmark for evaluating other pre-trained deep CNN models. We evaluate the performance of Inception and VGG which are pre-trained for object recognition, and compare these with VGG-Face which is pre-trained for face recognition. All experiments are performed on publicly available face databases, namely, CK+, JAFFE and FACES.

The initial rotational stiffness of connections is important for the design of semirigid frames. However, most current studies on steel beam to concrete-filled steel tube column connections...

The conflict between the dynamics postulate (unitary evolution) and the measurement postulate (wave-packet collapse) of quantum mechanics has been reconciled by Zurek from an information transfer perspective [Phys. Rev. A 76 (2007) 052110], and has further been extended to a more general scenario [Phys. Rev. A 87 (2013) 052111]. In this paper, we reconsider Zurek's new derivation by using weak repeatability postulate or covariant condition instead of repeatability postulate.

In this paper, the new concepts of \(\alpha \)-admissible mappings with respect to \(\eta \) in single-valued case and \(\alpha _{*}\)-admissible mappings with respect to \(\eta _{*}\) in set-valued case in Menger PM-spaces are introduced, and some new fixed point results for both single-valued and set-valued mappings under certain contractive conditions are studied, which extend and generalize some results in corresponding literatures. Some examples are provided to illustrate the validity of our main results, and an application is also given to discuss the existence of solution for Volterra type integral equations.

The tension between unitarity and wave-packet collapse is an annoying problem in quantum mechanics, while a breakthrough was made by Zurek recently from the point of view of information transfer. In this paper, we reconsider Zurek's derivation in the setting of generalized probabilistic theories (GPT), and establish that actionable information about a system can be repeatedly passed on to other systems only when the chosen states of the system have mutual zero fidelity. This may be interpreted as an extension of Zurek's result to GPT.

The bolted T-stub connection joining beam with column is being widely applied. To enhance the energy dissipation capacity of conventional T-stub connections, two rectangular plates are proposed to be inserted between the T-stub and column, so that the T-stub flange can yield both under tensile and compressive loads. This study put forward a mechanical model of a new T-stub connection with inserted plates and investigated important factors that could affect its mechanical behavior through experimental tests. Thirty specimens were designed with different configurations that differed according to the existence or absence of inserted plates, the fabrication method and the width of inserted plates. These configurations were tested under axial and cyclic loading conditions, and results showed that the proposal aiming to improve the energy dissipation capacity was feasible. The mechanical model presented coincided with the test observation and data. The advent of two inserted plates elevated the load bearing capacity, stiffness and ductility of connections under compression, whereas in tension the properties were not substantially enhanced. The welded T-stub connections outperformed those cut from standard section steel. The energy dissipated by connections with inserted plates was about 150% of that by traditional connections without inserted plates. Only within a reasonable range can the increment of plate width promote the energy dissipation capacity of T-stub connections. The optimum width of plates in terms of energy consumption accounted for around 31% of the overall width of connections.

Circular steel tube members with the absence of anticorrosive protection or coating failure are prone to uniform corrosion, which threatens the reliability and safety of members in the atmospheric environment. To fully study the mechanical behavior of uniformly corroded circular steel tubes, compression test and theoretical analysis were conducted, and two methods considering section reduction and material degradation, respectively, were adopted for the calculation of ultimate load carrying capacities of specimens. The results indicate that uniform corrosion did not change the failure modes of specimens, and all of them belonged to global buckling failure. The load carrying capacities and stiffness of specimens decreased with the increase of corrosion ratio, and the degree of reduction was greater than that of material degradation, showing a linear relationship with the corrosion rate. Under the same corrosion ratio, the specimens with larger eccentricity represented more obvious load carrying capacity and stiffness degradation. The load carrying capacities predicted by both methods were in good agreement with the test results and had a certain safety margin. The conservative degree of calculation results from three specifications followed a descending order of ANSI/AISC 360-16, GB 50017-2017, and EN 1993-1-1. Under the same corrosion ratio, the load carrying capacity variation of specimens between one-sided corrosion and two-sided corrosion was less than 3%.

Five square reinforced concrete (RC) stub columns were fabricated and experimental tested under an axial compression load in order to study the effectiveness of strengthening by using prestressed carbon fiber reinforced polymer (CFRP) strips. The specimens tested included one un-strengthened and four strengthened. Three specimens were strengthened by using prestressed strips, and the other one strengthened by using non-prestressed was used to compare. The prestress of the strip was achieved by tensed using a special device before it was pasted to the column. The experimental data such as the failure modes, load-displacement curves and strain distribution of CFRP strips were obtained. The effects of prestress magnitude of CFRP strips on the ultimate bearing capacity and deformation capacity of the specimens were analyzed. The results show that the prestress of CFRP strips can effectively increase the ultimate capacity and delay the crack occurrence of the specimens. And ultimate strain, plastic deformation of the specimens were also improved with increase of prestress magnitude of strip.

Local specialties or souvenirs are called ‘shouxin’ in the Lingnan area. Through market research on a number of shouxin enterprises in Zhuhai, this thesis contrasts different products of the same type investigated with multi-dimensional analysis, and summarizes the features and benefits of the various products. Referring to theories and experience of cultural innovation in Taiwan especially the design context “building a brand on the basis of culture and using it in daily life in the form of a specific product”, it proposes that souvenir enterprises in Zhuhai could take humanity as the core of its creative design and culture as the basis. It constructs a development strategy and framework of creative design for local shouxin enterprises in Zhuhai.

Based on the aesthetic conclusions from works on Ding white porcelain of Song dynasty, this paper is intended to illustrate the relationship between design and culture symbols by studying a case on the design of a culturally creative product combining cultural icons derived from both the aesthetic perfection of white porcelain and modern products. Ding white porcelain of Song dynasty is one of the most prominent products in the history of Chinese porcelain craft. The purpose of this study is to expound that the design styles of modern culturally creative products in China should be based on the heritage of China porcelain aesthetics, and uniquely integrate both fascination of ancient culture and the charisma of modern times, and that the design of porcelain products should be stemmed from culture. Therefore, the purpose of this paper is to build up a theoretical frame for designers to follow in their design of culturally creative porcelain products, and to explicitly discuss on cross-cultural communication and propagation and the Chinese porcelain culture as the foundation of modern porcelain products design.

We investigate facial expression recognition based on geometric features, and image appearance, using a range of classifier models. First, we evaluate expression recognition of face images based on geometric features, namely, facial landmarks based on the Active Appearance Model, and Action Units based on the Facial Action Coding System. A generalized linear model and a neural network are used to classify face images based on these geometric features. Second, the classification achieved by facial landmarks and Action Units is compared with the classification achieved by convolutional neural network (CNN) which extracts image features from raw pixels. Finally, we use transfer learning technique to evaluate classification using a pre-trained model. All experiments are performed on the state-of-the-art CK+ face database.

This paper investigated on the performance of slender concrete-filled carbon fiber-reinforced polymer (CFRP)–PVC tubular columns under axial compression. Four specimens with different slenderness ratios were firstly carried out to explore their performance and failure modes under axial compressive loads in laboratory. Secondly, a nonlinear finite element model (NFEM) was developed to analyze the relation between loads and deformation, and the analytical values were compared with the experimental results. After the efficiency of NFEM was verified, the parametric analyses varying the number of CFRP layer, concrete compressive strength and the slenderness ratio were conducted by the NFEM, and the ultimate bearing capacity formula as well as the relation model of the stability coefficient (φ) versus slenderness ratios (λ) were proposed. To validate the efficiency, ultimate bearing capacity was compared among the experimental results, NFEM analytical values and the prediction by the proposed formula. The results indicate that not only the developed NFEM can effectively depict the varying process of the loads and deformation in details, but also the proposed ultimate bearing capacity formula is reasonable and reliable in the fast prediction of the bearing capacity for slender concrete-filled CFRP–PVC tubular columns. It is beneficial to widely apply such new type composite columns in pile foundation or corrosion environments.

The incompatibility of dynamics postulate (unitary evolution) and the measurement postulate (wave-packet collapse) of quantum mechanics has recently been solved by Zurek from an information transfer perspective. Luo gave his derivation by relaxing the repeatability postulate. In this paper, we reconsider Luo’s derivation in the setting of general probabilistic theory (GPT). We also introduce the concept of sub- and super-fidelity in GPT and discuss their properties.

This paper proposes a new structural novelty detection method in the case of vast measurement data having uncertainties. Considering the effects of measurement accuracy and environmental variations on measurement variance, precise analytical methods of adaptive confidence distance and measurement variance are presented on the basis of statistical theory, and thus an adaptive consensus data fusion algorithm has been firstly developed to deal with the large volume of data involving considerable uncertainties. The proposed adaptive fusion algorithm can adaptively choose sensors whose data will be subsequently fused. The algorithm is then incorporated with wavelet analysis for the purpose of structural novelty detection. Two numerical examples are carried out to validate the efficiency and adaptability of the proposed method. The obtained results have been compared with those from other existing methods, which demonstrate the high efficiency of the proposed method in data processing considering uncertainties and unsatisfied performance of some sensors, as well as its accuracy in structural novelty detection. The proposed method also shows some robustness to noise.

This paper presents an innovative bolt model suitable for the three dimensional finite element analysis (FEA) of the semirigid beam-to-column bolted connections. The model is particularly useful for the moment-rotation relationship of beam-tocolumn connections, especially in cases where the connectors such as endplates, angles, T-stubs, are not particularly thin. In this paper, the bolt tensile behavior is firstly discussed by using a refined finite element model, in which the complex geometries of both external and internal threads were modeled. Then, the bolt behavior predicted by the commonly used models was compared with that of the refined FEA to appraise the accuracy of these models. The comparison shows most of the models commonly used can not predict accurately the axial stiffness, carrying capacity and ductility of bolt simultaneously. Afterwards, an innovative bolt model was proposed and the model accorded with the refined FEA for single bolts. Finally, the proposed model was applied to analyze the moment-rotation behavior of several experimented and well documented connections with different configurations. The results indicate that the proposed model is feasible and efficient.

When A ∈ B ( H ) and B ∈ B ( K ) are given, we denote by M C the operator acting on the infinite dimensional separable Hilbert space H ⊕ K of the form M C = ( A C 0 B ) . In this paper, we first give some necessary and sufficient conditions for M C to be a left invertible operator (an upper semi-Weyl, upper semi-Fredholm) operator for some C ∈ B ( K , H ) , which extend the corresponding results in Cao et al. (2006) [4] , Cao and Meng (2005) [5] , Hwang and Lee (2001) [12] and Li and Du (2006) [15] . Then we present some counter-examples.

In this work, we introduce a new φ-contractive mapping; following that, we obtain some multipled common fixed point theorems for a pair of mappings $T: \underbrace{X \times X \times\cdots\times X}_{m\text{-times}}\rightarrow X$ and $A: X\rightarrow X$ . The main results of this paper are generalization of the main results of Kutbi et al. (Fixed Point Theory Appl. 2015(1):32, 2015). As an illustration, we give an example to demonstrate the validity of the obtained results.

In this paper, we generalize the algebraic sum ⊕ of Fang. Based on this concept, we prove some common fixed point theorems for three pairs of self-mappings satisfying the common $(E.A)$ property in Menger $PGM$ -spaces. Finally, an example is given to exemplify our main results.

In this paper, some new fixed point theorems for semi-closed 1-set-contractive operators of functional type are obtained, which generalize the famous Petryshyn's theorem and Altman's theorem by replacing the norm with some classes of functionals.

In this paper, we introduce a new concept of generalized cyclic (κh, ϕL)S-weak contraction mappings and establish some coincidence point results for such mappings in complete partially ordered Menger PM-spaces. Our results generalize the main results of Nashine (Nonlinear Anal. 75:6160-6169, 2012) and Gopal et al. (Appl. Math. Comput. 233:955-967, 2014). We also obtain the corresponding coincidence point theorems for generalized cyclic (κh, ϕL)S-weak contractions in partially ordered metric spaces. MSC: 47H10; 54H25