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Zhu et al. introduced the |$h$| -edge tolerable diagnosability to measure the fault diagnosis capability of a multiprocessor system with faulty links. This kind of diagnosability is a generalization of the concept of traditional diagnosability. A graph is called a maximally connected graph if its minimum degree equals its vertex connectivity. It is well-known that many irregular networks are maximally connected graphs and the |$h$| -edge tolerable diagnosabilities of these networks are unknown, which is our motivation for research. In this paper, we obtain the lower bound of the |$h$| -edge tolerable diagnosability of a class of |$t$| -connected graphs and establish the |$h$| -edge tolerable diagnosability of a class of maximally connected graphs under the PMC model and the MM |$^*$| model, which extend some results in (Hakimi, S.L. and Amin, A.T. (1974) Characterization of connection assignment of diagnosable systems. IEEE Trans. Comput. 23, 86–88) , (Chang, C.P. Lai, P.L. Tan, J.J.M. and Hsu, L.H. (2004) Diagnosability of t-connected networks and product networks under the comparison diagnosis model. IEEE Trans. Comput. , 53, 1582–1590) and (Lian, G. Zhou, S. Hsieh, S.Y. Liu, J. Chen, G. and Wang, Y. (2019) Performance evaluation on hybrid fault diagnosability of regular networks. Theoret. Comput. Sci. , 796, 147–153). [ABSTRACT FROM AUTHOR]

Conventional reinforced concrete shear walls are widely used as primary lateral-force-resisting members owing to their high in-plane stiffness. However, some of these walls have been severely damaged in past earthquakes because of their limited energy dissipation capacity and ductility, thus requiring laborious repairs or even demolition. Self-centering rocking walls have recently been developed and proven effective for reducing the damage and residual displacement of structures after earthquakes. Because self-centering rocking walls are usually constructed by releasing constraints at the foundation, their contribution to structural stiffness may be limited, and they are very vulnerable to vibration. To overcome these limitations, a shear wall with variable phases of deformation was proposed; this wall consists of a rocking bearing, low-strength concrete zones, and buckling-restrained rebars. With increasing seismic intensity, the proposed wall first exhibits the shear–bending deformation mode of conventional reinforced concrete shear walls, which transitions into the rocking deformation mode of self-centering rocking walls. Cyclic loading tests were conducted to investigate the seismic performance of the proposed wall. The results demonstrated that the presented concept of the mechanism transformation is feasible in practice, and compared with conventional shear walls, the proposed wall displays improved seismic performance in terms of the damage mechanism, lateral resistance degradation, and deformation capacity. Moreover, a spring–truss model and a performance prediction model were also developed to predict the seismic performance of the proposed wall. Validating the predictions of the analytical models against the test results confirmed the accuracy of the developed models. [ABSTRACT FROM AUTHOR]

Periodicity is a frequently happening phenomenon for social interactions in temporal networks. Mining periodic communities are essential to understanding periodic group behaviors in temporal networks. Unfortunately, most previous studies for community mining in temporal networks ignore the periodic patterns of communities. In this paper, we study the problem of seeking periodic communities in a temporal network, where each edge is associated with a set of timestamps. We propose novel models, including $\sigma$ σ -periodic $k$ k -core and $\sigma$ σ -periodic $k$ k -clique, that represent periodic communities in temporal networks. Specifically, a $\sigma$ σ -periodic $k$ k -core (or $\sigma$ σ -periodic $k$ k -clique) is a $k$ k -core (or clique with size larger than $k$ k ) that appears at least $\sigma$ σ times periodically in the temporal graph. The problem of searching periodic core is efficient but the resulting communities may be not enough cohesive; the problem of enumerating all periodic cliques is not efficient (NP-hard) but the resulting communities are very cohesive. To compute all of them efficiently, we first develop two effective graph reduction techniques to significantly prune the temporal graph. Then, we transform the temporal graph into a static graph and prove that mining the periodic communities in the temporal graph equals mining communities in the transformed graph. Subsequently, we propose a decomposition algorithm to search maximal $\sigma$ σ -periodic $k$ k -core, a Bron-Kerbosch style algorithm to enumerate all maximal $\sigma$ σ -periodic $k$ k -cliques, and a branch-and-bound style algorithm to find the maximum $\sigma$ σ -periodic clique. The results of extensive experiments on five real-life datasets demonstrate the efficiency, scalability, and effectiveness of our algorithms. [ABSTRACT FROM AUTHOR]

Degeneracy is an important concept to measure the sparsity of a graph which has been widely used in many network analysis applications. Many network analysis algorithms, such as clique enumeration and truss decomposition, perform very well in graphs having small degeneracies. In this paper, we propose an I/O-efficient algorithm to compute the degeneracy of the massive graph that cannot be fully kept in the main memory. The proposed algorithm only uses $O(n)$ O (n) memory, where $n$ n denotes the number of nodes of the graph. We also develop an I/O-efficient algorithm to incrementally maintain the degeneracy on dynamic graphs. Extensive experiments show that our algorithms significantly outperform the state-of-the-art degeneracy computation algorithms in terms of both running time and I/O costs. The results also demonstrate high scalability of the proposed algorithms. For example, in a real-world web graph with 930 million nodes and 13.3 billion edges, the proposed algorithm takes only 633 seconds and uses less than 4.5GB memory to compute the degeneracy. [ABSTRACT FROM AUTHOR]

The g -extra edge-connectivity is an important measure for the reliability of interconnection networks. Recently, Yang et al. [Appl. Math. Comput. 320 (2018) 464–473] determined the 3 -extra edge-connectivity of balanced hypercubes B H n and conjectured that the g -extra edge-connectivity of B H n is λ g ( B H n) = 2 (g + 1) n − 4 g + 4 for 2 ≤ g ≤ 2 n − 1. In this paper, we confirm their conjecture for n ≥ 6 − 1 2 g + 1 and 2 ≤ g ≤ 8 , and disprove their conjecture for n ≥ 3 e g ( B H n) g + 1 and 9 ≤ g ≤ 2 n − 1 , where e g ( B H n) = max { | E ( B H n [ U ]) | | U ⊆ V (B H n) , | U | = g + 1 }. [ABSTRACT FROM AUTHOR]

Mining cohesive subgraphs from a network is a fundamental problem in network analysis. Most existing cohesive subgraph models are mainly tailored to unsigned networks. In this paper, we study the problem of seeking cohesive subgraphs in a signed network, in which each edge can be positive or negative, denoting friendship or conflict, respectively. We propose a novel model, called maximal (α,k)-clique, that represents a cohesive subgraph in signed networks. Specifically, a maximal (α,k)-clique is a clique in which every node has at most k negative neighbors and at least ⌈αk⌉ positive neighbors (α ≥ 1). We show that the problem of enumerating all maximal (α,k)-cliques in a signed network is NP-hard. To enumerate all maximal (α,k)-cliques efficiently, we first develop an elegant signed network reduction technique to significantly prune the signed network. Then, we present an efficient branch and bound enumeration algorithm with several carefully-designed pruning rules to enumerate all maximal (α,k)--cliques in the reduced signed network. In addition, we also propose an efficient algorithm with three novel upper-bounding techniques to find the maximum (α,k)-clique in a signed network. The results of extensive experiments on five large real-life datasets demonstrate the efficiency, scalability, and effectiveness of our algorithms. [ABSTRACT FROM AUTHOR]

Structural clustering is a fundamental graph mining operator which is not only able to find densely-connected clusters, but it can also identify hub vertices and outliers in the graph. Previous structural clustering algorithms are tailored to deterministic graphs. Many real-world graphs, however, are not deterministic, but are probabilistic in nature because the existence of the edge is often inferred using a variety of statistical approaches. In this paper, we formulate the problem of structural clustering on probabilistic graphs, with the aim of finding reliable clusters in a given probabilistic graph. Unlike the traditional structural clustering problem, our problem relies mainly on a novel concept called reliable structural similarity which measures the probability of the similarity between two vertices in the probabilistic graph. We develop a dynamic programming algorithm with several powerful pruning strategies to efficiently compute the reliable structural similarities. With the reliable structural similarities, we adapt an existing solution framework to calculate the structural clustering on probabilistic graphs. Comprehensive experiments on five real-life datasets demonstrate the effectiveness and efficiency of the proposed approaches. [ABSTRACT FROM AUTHOR]

As a global biodiversity hotspot, the subtropical evergreen broadleaved forest (SEBF) in southern China is strongly influenced by the humid monsoon climate, with distinct hot-wet and cool-dry seasons. However, the hydraulic strategies of this forest are not well understood. Branch and leaf hydraulic safety margins (HSMbranch and HSMleaf, respectively), as well as seasonal changes in predawn and midday leaf water potential (Ψpd and Ψmd), stomatal conductance (G s), leaf to sapwood area ratio (A L/ A S) and turgor loss point (Ψtlp), were examined for woody species in a mature SEBF. For comparison, we compiled these traits of tropical dry forests (TDFs) and Mediterranean-type woodlands (MWs) from the literature because they experience a hot-dry season. We found that on average, SEBF showed larger HSMbranch and HSMleaf than TDF and MW. During the dry season, TDF and MW species displayed a significant decrease in Ψpd and Ψmd. However, SEBF species showed a slight decrease in Ψpd but an increase in Ψmd. Similar to TDF and MW species, G s was substantially lower in the dry season for SEBF species, but this might be primarily because of the low atmospheric temperature (low vapor pressure deficit). On the other hand, A L/ A S and Ψtlp were not significant different between seasons for any SEBF species. Most SEBF species had leaves that were more resistant to cavitation than branches. Additionally, species with stronger leaf-to-branch vulnerability segmentation tended to have smaller HSMleaf but larger HSMbranch. Our results suggest that SEBF is at low hydraulic risk under the current climate. [ABSTRACT FROM AUTHOR]

Real-time ride-sharing applications (e.g., Uber and Lyft) are very popular in recent years. Motivated by the ride-sharing application, we propose a new type of query in road networks, called the optimal multi-meeting-point route (\mathsf OMMPR ) query. Given a road network $G$ , a source node $s$ , a target node $t$ , and a set of query nodes $U$ , the \mathsf OMMPR query aims at finding the best route starting from $s$ and ending at $t$ such that the weighted average cost between the cost of the route and the total cost of the shortest paths from every query node to the route is minimized. We show that the problem of computing the \mathsf OMMPR query is NP-hard. To answer the \mathsf OMMPR query efficiently, we propose two novel parameterized solutions based on dynamic programming (DP), with the number of query nodes $l$ (i.e., $l=|U|$ ) as a parameter, which is typically very small in practice. The two proposed parameterized algorithms run in $O(3^l\cdot m+ 2^l \cdot n\cdot (l+\log (n)))$ and $O(2^l \cdot (m + n\cdot (l+\log (n))))$ time, respectively, where $n$ and $m$ denote the number of nodes and edges in graph $G$ , thus they are tractable in practice. To reduce the search space of the DP-based algorithms, we propose two novel optimized algorithms based on bidirectional DP and a carefully-designed lower bounding technique. We conduct extensive experimental studies on four large real-world road networks, and the results demonstrate the efficiency of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

Uncertain graph management has been recognized as an important research topic in recent years. In this paper, we first introduce two types of query evaluation problems on uncertain graphs, named expectation query evaluation and threshold query evaluation. Most previous solutions for these problems are based on naive Monte-Carlo (NMC ) sampling, which typically result in large variances. To reduce the variance of NMC, we propose two efficient estimators, called RSS-I and RSS-II estimators, based on the idea of recursive stratified sampling (RSS). To further reduce the variances of RSS-I and RSS-II, we propose a recursive cut-set based stratified sampling estimator for a particular kind of query evaluation problem. We show that all the proposed estimators are unbiased and their variances are significantly smaller than that of NMC. Moreover, the time complexity of all the proposed estimators are the same as that of NMC under a mild assumption. In addition, we develop an elegant graph simplification technique to further improve the accuracy and running time of our estimators. We also apply the proposed estimators to three different uncertain graph query evaluation problems. Finally, we conduct extensive experiments to evaluate the proposed estimators, and the results show the accuracy, efficiency, and scalability of our estimators. [ABSTRACT FROM AUTHOR]

Background: Malignant melanoma is the most aggressive and deadly form of skin cancer. Dacarbazine (DTIC) has been the approved first-line treatment for metastatic melanoma in routine clinical practice. However, response rates with single-agent DTIC are low. The objective of this study was to compare the efficacy and safety of DTIC with or without placebo and DTIC-based combination therapies in patients with advanced metastatic melanoma. Methods: We searched from electronic databases such as The Cochrane Library, MEDLINE, EBSCO, EMBASE, Ovid, CNKI, and CBMDisc from 2003 to 2013. The primary outcome measures were overall response and 1-year survival, and the secondary outcome measurements were adverse events. Results: Nine randomized controlled trials (RCTs) involving 2,481 patients were included in the meta-analysis. DTIC-based combination therapies was superior to DTIC alone in overall response (combined risk ratio [RR]  = 1.60, 95% confidence interval [CI]: 1.27–2.01) and 1-year survival (combined RR = 1.26, 95% CI: 1.14–1.39). Patients with DTIC-based combination therapies had higher incidence of adverse events including nausea (combined RR = 1.23, 95% CI: 1.10–1.36), vomiting (combined RR = 1.73, 95% CI: 1.41–2.12) and neutropenia (combined RR = 1.75, 95% CI: 1.42–2.16) compared to the group for DTIC alone. Conclusion: These data suggested that DTIC-based combination therapies could moderately improve the overall response and the 1-year survival but increased the incidence of adverse events. Further large-scale, high-quality, placebo-controlled, double-blind trials are needed to confirm this conclusion. [ABSTRACT FROM AUTHOR]

The \(k\) -core decomposition in a graph is a fundamental problem for social network analysis. The problem of \(k\) -core decomposition is to calculate the core number for every node in a graph. Previous studies mainly focus on \(k\) -core decomposition in a static graph. There exists a linear time algorithm for \(k\) -core decomposition in a static graph. However, in many real-world applications such as online social networks and the Internet, the graph typically evolves over time. In such applications, a key issue is to maintain the core numbers of nodes when the graph changes over time. A simple implementation is to perform the linear time algorithm to recompute the core number for every node after the graph is updated. Such simple implementation is expensive when the graph is very large. In this paper, we propose a new efficient algorithm to maintain the core number for every node in a dynamic graph. Our main result is that only certain nodes need to update their core numbers when the graph is changed by inserting/deleting an edge. We devise an efficient algorithm to identify and recompute the core numbers of such nodes. The complexity of our algorithm is independent of the graph size. In addition, to further accelerate the algorithm, we develop two pruning strategies by exploiting the lower and upper bounds of the core number. Finally, we conduct extensive experiments over both real-world and synthetic datasets, and the results demonstrate the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Background: The effect of neuroinflammatory cytokines on cognitive deficits in patients with major depressive disorder (MDD) can be altered by selective serotonin reuptake inhibitors (SSRIs). This study aimed to examine serum interleukin-8 (IL-8) levels, cognitive function, and their associations in MDD patients with SSRIs. Methods: Thirty SSRI-treated MDD patients and 101 healthy controls were recruited for this study. We examined cognitive performance using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and serum IL-8 levels using the Human Inflammatory Cytokine Cytometric Bead Array in both cases and controls. Results: The RBANS test scores were significantly lower in MDD patients with SSRIs than in healthy controls after controlling for covariates (all p < 0.001). Serum levels of IL-8 were higher in MDD patients with SSRIs than in healthy controls after adjusting for covariates (F = 3.82, p = 0.05). Serum IL-8 levels were positively correlated with sub-scores of delayed memory (r = 0.37, p = 0.04) and visuospatial/constructional (r = 0.43, p = 0.02) in MDD patients with SSRIs but not in in healthy controls (delayed memory score: r = -0.12, p = 0.24; visuospatial/constructional score: r = 0.02, p = 0.81). Conclusions: Our findings suggested that increased serum IL-8 level might not only be involved in the MDD psychopathology or the use of SSRIs but also correspond to improving MDD delayed memory and visuospatial/constructional function. [ABSTRACT FROM AUTHOR]

Abstract: The emission spectrum from the optically excited single electron tunneling devices, electrostatically coupled to a p-type side quantum dot, has been investigated. The 12 exciton-complexes transition processes have been found and can be classified into six electron-like and six hole-like transition processes. The self-consistent numerical analysis shows that the gate and bias voltages can be tuned to change the weight functions associated with the particular exciton-complexes transition processes, thereby influencing the intensity and frequency-dependence of the spontaneous emission signals. The energy discrepancies up to the quadratic terms with respect to bias voltages are taken into account to interpret different degrees of the Stark shifts experienced by the electron and the hole. There exist several competition mechanisms, where the increase of the gate voltage can neutralize the shift to lower-energy transition channels produced by the increase of the hole occupancy in the side dot, and the interdot repulsive and attractive Coulombic blockades compete with each other to determine the superiority or inferiority of the different resonance channels. The electron-like resonance channels can be switched to the hole-like ones or vice versa in the optical spectra by tuning the gate voltages. [Copyright &y& Elsevier]

Enhancing diversity in ranking on graphs has been identified as an important retrieval and mining task. Nevertheless, many existing diversified ranking algorithms either cannot be scalable to large graphs due to the time or memory requirements, or lack an intuitive and reasonable diversified ranking measure. In this paper, we propose a new diversified ranking measure on large graphs, which captures both relevance and diversity, and formulate the diversified ranking problem as a submodular set function maximization problem. Based on the submodularity of the proposed measure, we develop an efficient greedy algorithm with linear time and space complexity w.r.t. the size of the graph to achieve near-optimal diversified ranking. In addition, we present a generalized diversified ranking measure and give a near-optimal randomized greedy algorithm with linear time and space complexity for optimizing it. We evaluate the proposed methods through extensive experiments on five real data sets. The experimental results demonstrate the effectiveness and efficiency of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Traveler's dilemma (TD) is one of social dilemmas which has been well studied in the economics community, but it is attracted little attention in the physics community. The TD game is a two-person game. Each player can select an integer value between and () as a pure strategy. If both of them select the same value, the payoff to them will be that value. If the players select different values, say and (), then the payoff to the player who chooses the small value will be and the payoff to the other player will be . We term the player who selects a large value as the cooperator, and the one who chooses a small value as the defector. The reason is that if both of them select large values, it will result in a large total payoff. The Nash equilibrium of the TD game is to choose the smallest value . However, in previous behavioral studies, players in TD game typically select values that are much larger than , and the average selected value exhibits an inverse relationship with . To explain such anomalous behavior, in this paper, we study the evolution of cooperation in spatial traveler's dilemma game where the players are located on a square lattice and each player plays TD games with his neighbors. Players in our model can adopt their neighbors' strategies following two standard models of spatial game dynamics. Monte-Carlo simulation is applied to our model, and the results show that the cooperation level of the system, which is proportional to the average value of the strategies, decreases with increasing until is greater than the critical value where cooperation vanishes. Our findings indicate that spatial reciprocity promotes the evolution of cooperation in TD game and the spatial TD game model can interpret the anomalous behavior observed in previous behavioral experiments. [ABSTRACT FROM AUTHOR]

Abstract: In this Letter, the bosonic projected variational method is used to study the strongly correlated 87Rb atoms in optical lattice. A global phase diagram is obtained by this method. There exist two characteristic lattice depths V for 87Rb atoms in optical lattice: one is to label the maximum height of the ‘zero-momentum’ peak of condensation, the other is the quantum critical point for the superfluid–insulator (SI) transition at . As a result of strongly correlated effect for lattice bosons, the suppressed superfluid state is predicted near the SI transition with the suppressed superfluid density and the very slowly velocity of the sound-like excitons. [Copyright &y& Elsevier]

Community search that finds query-dependent communities has been studied on various kinds of graphs. As one instance of community search, intimate-core group (community) search over a weighted graph is to find a connected $k$ k -core containing all query nodes with the smallest group weight. However, existing state-of-the-art methods start from the maximal $k$ k -core to refine an answer, which is practically inefficient for large networks. In this paper, we develop an efficient framework, called local exploration k-core search (LEKS), to find intimate-core groups in graphs. We propose a small-weighted spanning tree to connect query nodes, and then expand the tree level by level to a connected $k$ k -core, which is finally refined as an intimate-core group. In addition, to support the intimate group search over large weighted graphs, we develop a weighted-core index (WC-index) and two new WC-index-based algorithms for expansion and refinement phases in LEKS. Specifically, we propose a WC-index-based expansion to efficiently find a candidate graph of intimate-core group, leveraging on a two-level expansion of $k$ k -breadth and 1-depth. We propose two graph removal strategies: coarse-grained refinement is designed for large graphs to delete a batch of nodes in a few iterations; fine-grained refinement is designed for small graphs to remove nodes carefully and achieve high-quality answers. Extensive experiments on real-life networks with ground-truth communities validate the effectiveness and efficiency of our proposed methods. [ABSTRACT FROM AUTHOR]

Silibinin, one of the flavonoids isolated from milk thistle seeds of Silybum marianum , has hepatoprotective properties against toxins in clinical. However, the detailed mechanisms have remained unclear. This study investigates the underlying mechanism of silibinin in the protection against ethanol- or acetaldehyde-induced damage of neonatal mouse primary hepatocytes in vitro. The results show that ethanol inhibited proliferation of hepatocytes in a time (12, 24, 36 h) and dose-dependent (0–800 mM) manner. However, silibinin did not show protective effect on ethanol (500 mM)-induced suppression of hepatocyte proliferation. Acetaldehyde, the toxic metabolite of ethanol, appearing immediately in individuals after drink also inhibited the proliferation of hepatocytes in a dose-dependent (0–12 mM) manner. Surprisingly, silibinin significantly increased the cell viability and reduced the leakage of alanine amino transferase (ALT) and aspartate amino transferase (AST) in acetaldehyde-treated hepatocytes, suggesting that silibinin protected cell injury caused by acetaldehyde treatment. The apoptosis-inducing effect of acetaldehyde was demonstrated by the increased number of cells in sub-G1 phase as well as caspase-3 activation. Further study shows that acetaldehyde induced autophagy in the hepatocytes. The autophagy inhibitors, 3-Methyladenine (3-MA) and chloroquine (CQ), further decreased the viability of cells treated with acetaldehyde, suggesting that autophagy plays a protective role against apoptosis. Consistently, silibinin (20 μM) significantly reduced the activation of caspase 3 or apoptosis and increased the conversion of LC3-I to LC3-II or autophagy. Taken together, it is concluded that silibinin does not repress the ethanol- induced hepatocyte injury, whereas silibinin reduces acetaldehyde-caused hepatocyte injury through down-regulation of apoptosis and up-regulation of autophagy. • Acetaldehyde (ACH) induced apoptosis in liver cells; • AcH induced autophagy in liver cells; • Silibinin protects AcH-induced death, but not ethanol-induced death of hepatocytes. [ABSTRACT FROM AUTHOR]

Real-world networks, such as phone-call networks and social networks, are often not static but temporal. Mining cohesive subgraphs from static graphs is a fundamental task in network analysis and has been widely investigated in the past decades. However, the concepts of cohesive subgraphs shift from static to temporal graphs raise many important problems. For instance, how to detect stable cohesive subgraphs on temporal networks such that the nodes in the subgraph are densely and stably connected over time. To address this problem, we resort to the conventional quasi-clique and propose a new model, called maximal $\rho $ -stable ($\delta, \gamma $)-quasi-clique, to capture both the cohesiveness and the stability of a subgraph. We show that the problem of enumerating all maximal $\rho $ -stable ($\delta, \gamma $)-quasi-cliques is NP-hard. To efficiently tackle our problem, we first devise a novel temporal graph reduction algorithm to significantly reduce the temporal graph without losing any maximal $\rho $ -stable ($\delta, \gamma $)-quasi-clique. Then, on the reduced temporal graph, we propose an effective branch and bound enumeration algorithm, named BB&SCM, with four carefully designed pruning techniques to accomplish the enumeration process. Finally, we conduct extensive experiments on seven real-world temporal graphs, and the results demonstrate that the temporal graph reduction algorithm can safely reduce 98% nodes of the temporal graph (with millions of nodes and edges) and BB&SCM is at least two orders of magnitude faster than the baseline algorithms. Moreover, we also evaluate the effectiveness of our model against other baseline models. [ABSTRACT FROM AUTHOR]

Let G be a graph and H be a certain connected subgraph of G. The H -structure connectivity κ (G ; H) (resp. H -substructure connectivity κ s (G ; H)) of G is the minimum number of a set of subgraphs F = { H 1 , H 2 , ⋯ , H m } (resp. F = { H 1 ′ , H 2 ′ , ⋯ , H m ′ }) such that H i is isomorphic to H (resp. H i ′ is a connected subgraph of H) for every 1 ≤ i ≤ m , and F 's removal will disconnect G. For the k -ary n -cube Q n k , the κ (Q n k ; H) and κ s (Q n k ; H) were determined for H ∈ { K 1 , K 1 , 1 , K 1 , 2 , K 1 , 3 }. In this paper, we show κ (Q n k ; H) and κ s (Q n k ; H) for H ∈ { P l , C l } where 3 ≤ l ≤ 2 n. [ABSTRACT FROM AUTHOR]

In this paper, we propose the direction heat maps to visualize the spreads of points w.r.t. different observers in the Euclidean space. It is a new way to look points. Traditionally, the spread of points is unique because it depends on the absolute coordinates of points w.r.t. the zero point. However, considering the relative directions of the points, the spread varies if the observers are different. To visualize the multiple views on the same set of points, we design a pie-shaped heat map. On a direction range the more points are, on the heat map the darker the corresponding sector is. Supporting by the heat map, we can visually know whether the points spread over evenly around or the points scatter only in small direction ranges. The heat map can be widely used in many decision-making applications where the tasks are direction sensitive. Typically, in bicycle sharing applications, the heat map can tell a user the general spread of the available bikes around, and the user may choose to walk on the deep coloured direction to meet more bikes. To generate the heat map, we propose the direction profile to store the direction intervals associated with the number of points in the intervals. We design an algorithm to build the direction profile incrementally. To measure a spread, we define the direction-based centrality which is a statistic value to reflect the uniform degree of the spread. The lower the centrality is, the more evenly the points spread. The observer with the minimum centrality is a direction-based center, while the observer with the maximum centrality is a direction-based edge. We design an algorithm to calculate the centralities. To find the center faster, we also design an algorithm to approximate the centralities. The experimental results show that the heat map can visualize different spreads effectively and the direction-based centralities can be calculated efficiently. [ABSTRACT FROM AUTHOR]

Representative skyline computation is a fundamental issue in database area, which has attracted much attention in recent years. A notable definition of representative skyline is the distance-based representative skyline (DBRS). Given an integer k, a DBRS includes k representative skyline points that aims at minimizing the maximal distance between a non-representative skyline point and its nearest representative. In the 2D space, the state-of-the-art algorithm to compute the DBRS is based on dynamic programming (DP) which takes O( k m ) time complexity, where m is the number of skyline points. Clearly, such a DP-based algorithm cannot be used for handling large scale datasets due to the quadratic time cost. To overcome this problem, in this paper, we propose a new approximate algorithm called ARS, and a new exact algorithm named PSRS, based on a carefully-designed parametric search technique. We show that the ARS algorithm can guarantee a solution that is at most 휖 larger than the optimal solution. The proposed ARS and PSRS algorithms run in O( klog2 mlog( T/ 휖)) and O( k log3 m) time respectively, where T is no more than the maximal distance between any two skyline points. We also propose an improved exact algorithm, called PSRS+, based on an effective lower and upper bounding technique. We conduct extensive experimental studies over both synthetic and real-world datasets, and the results demonstrate the efficiency and effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Social hierarchy (i.e., pyramid structure of societies) is a fundamental concept in sociology and social network analysis. The importance of social hierarchy in a social network is that the topological structure of the social hierarchy is essential in both shaping the nature of social interactions between individuals and unfolding the structure of the social networks. The social hierarchy found in a social network can be utilized to improve the accuracy of link prediction, provide better query results, rank web pages, and study information flow and spread in complex networks. In this paper, we model a social network as a directed graph G, and consider the social hierarchy as DAG (directed acyclic graph) of G, denoted as GD. By DAG, all the vertices in G can be partitioned into different levels, the vertices at the same level represent a disjoint group in the social hierarchy, and all the edges in DAG follow one direction. The main issue we study in this paper is how to find DAG GD in G. The approach we take is to find GD by removing all possible cycles from G such that G=U(G)∪GD, where U(G) is a maximum Eulerian subgraph which contains all possible cycles. We give the reasons for doing so, investigate the properties of GD found, and discuss the applications. In addition, we develop a novel two-phase algorithm, called Greedy-&-Refine, which greedily computes an Eulerian subgraph and then refines this greedy solution to find the maximum Eulerian subgraph. We give a bound between the greedy solution and the optimal. The quality of our greedy approach is high. We conduct comprehensive experimental studies over 14 real-world datasets. The results show that our algorithms are at least two orders of magnitude faster than the baseline algorithm. [ABSTRACT FROM AUTHOR]

Uncertain graph management and analysis have attracted many research attentions. Among them, computing $k$ k -cores in uncertain graphs (aka, $(k,\eta)$ (k , η) -cores) is an important problem and has emerged in many applications such as community detection, protein-protein interaction network analysis and influence maximization. Given an uncertain graph, the $(k,\eta)$ (k , η) -cores can be derived by iteratively removing the vertex with an $\eta$ η -degree of less than $k$ k . However, the results heavily depend on the two input parameters $k$ k and $\eta$ η . The settings for these parameters are unique to the specific graph structure and the user's subjective requirements. In addition, computing and updating the $\eta$ η -degree for each vertex is the most costly component in the algorithm, and the cost is high. To overcome these drawbacks, we propose an index-based solution for computing $(k,\eta)$ (k , η) -cores. The size of the index is well bounded by $O(m)$ O (m) , where $m$ m is the number of edges in the graph. Based on the index, queries for any $k$ k and $\eta$ η can be answered in optimal time. We propose an algorithm for index construction with several different optimizations. We also propose a new algorithm for index construction in external memory. We conduct extensive experiments on eight real-world datasets to practically evaluate the performance of all proposed algorithms. [ABSTRACT FROM AUTHOR]

Influence maximization has recently received significant attention for scheduling online campaigns or advertisements on social network platforms. However, most studies only focus on user influence via cyber interactions while ignoring their physical interactions which are also essential to gauge influence propagation. Additionally, targeted campaigns or advertisements have not received sufficient attention. To address these issues, we first devise a novel holistic influence diffusion model that takes into account both cyber and physical user interactions in an effective and practical way. Based on the new diffusion model, we formulate a new problem of holistic influence maximization, denoted as HIM query, for targeted advertisements in a spatial social network. The HIM query problem aims to find a minimum set of users whose holistic influence can cover all target users in the network, which belongs to a set covering problem. Since the HIM query problem is NP-hard, we develop a greedy baseline algorithm and then improve on this algorithm to reduce the computational cost. To deal with large networks, we also design a spatial-social index to maintain the social, spatial and textual information of users, as well as developing an index-based efficient solution. Finally, we conduct extensive experiments using one synthetic and three real-world datasets to validate the efficiency and effectiveness of the proposed holistic influence diffusion model and our developed algorithms. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to investigate the effect of Ki67-ZD55-IL-24 with temozolomide (TMZ) against melanoma in mice. Methods: Seventy-eight mice with subcutaneous injection of A375 cells (2 × 10) into the right flank were randomized to receive phosphate buffered saline (PBS), Ki67-ZD55, Ki67-ZD55-IL-24, TMZ, TMZ + Ki67-ZD55, and TMZ + Ki67-ZD55-IL-24. Six mice were killed in each group 10 days after intervention for detecting IL-24 mRNA and protein expression. The remaining mice were monitored to draw the body weight change curve and tumor growth curve, and killed 30 days after intervention. Tumors were excised and weighted. The morphology of tumor tissues was determined by hematoxylin and eosin (HE) staining, and the apoptosis index and rate of apoptotic cells were determined by TUNEL assay and AnnexinV-FITC/PI double staining, respectively. Results: The Ki67-ZD55-IL-24-treated group generated much more reactive oxygen species than the untreated group. There was no significant difference in IL-24 expression between Ki67-ZD55-IL-24 and TMZ + Ki67-ZD55-IL-24 groups. Immunohistochemical analysis and Western blot revealed that both the Ki67-ZD55 and Ki67-ZD55-IL-24 could significantly reduce the expression of MGMT. Toxicity assessments demonstrated that mice in the three groups that received TMZ exhibited significant body weight loss following treatment. HE staining showed that TMZ + Ki67-ZD55-IL-24 group had much fewer karyokinesis in the tumors, compared with other groups. The apoptosis index of tumor tissues and the rate of apoptotic cells were significantly higher in TMZ + Ki67-ZD55-IL-24 group than in other groups (all P < 0.05). Conclusions: These findings indicate this novel strategy holds promising potentials for treatment of malignant melanoma. [ABSTRACT FROM AUTHOR]

Community evolution remains a heavily researched and challenging area in the analysis of dynamic complex network structures. Currently, the primary limitation of traditional event-based approaches for community evolution analysis is the lack of strict constraint conditions for distinguishing evolutionary events, which entails that as the cardinality of discovered events increases, so does the number of redundant events. Another limitation of existing approaches is the lack of consideration for weak events. Weak events can be generated by small changes in communities, which are empirically prevalent, and are typically not captured by traditional events. To manage these two aforementioned limitations, this research aims to formalize a weak and strong events-based framework, which includes the following newly discovered events: “weak shrink,” “weak expand,” “weak merge,” and “weak splity” predicated on the community overlapping degree and community degree membership, this article refines these traditional strong events, as well as new constraints for weak events. In addition, a community evolution mining framework, which is based on both strong and weak events, is proposed and denoted by a weak-event-based community evolution method (WECEM). The framework can be summarized by the following: 1) communities in complex networks with adjacent time-stamps are compared to determine the community overlapping degree and community membership degree; 2) the values of the community overlapping degree and membership degree meet the definition of events; and 3) weak events are effectively identified. Extensive experimental results, on real and synthetic data sets consisting of dynamic complex networks and online social networks, demonstrate that WECEM is able to identify weak events more effectively than traditional frameworks. Specifically, WECEM outperforms traditional frameworks by 22.9% in the number of discovered strong events. The detection accuracy of evolutionary events is approximately 12.2% higher than that of traditional event-based frameworks. It is also worth noting that, as the cardinality of the data grows, the proposed framework, when compared with traditional frameworks, can more effectively, and efficiently, mine large-scale complex networks. [ABSTRACT FROM AUTHOR]

ABSTRACT It is important to understand the ecophysiological characters of plants when exploring mechanisms underlying species substitution in the process of plant succession. In the present study, we selected 34 woody species from different stages of secondary succession in subtropical forests of southern China, and measured their hydraulic conductivity, gas exchange rates, leaf nutrients and drought-tolerance traits such as xylem resistance to cavitation, turgor loss point and carbon isotope ratio. Principal component analysis revealed that early-, mid- and late-successional species were significantly separated along axis 1, which was strongly associated with hydraulic-photosynthetic coordination. In contrast to species distributed in late-successional forest, early-successional species had the highest hydraulic conductivity, net photosynthetic rates, photosynthetic nitrogen and phosphorus use efficiencies, but had the lowest photosynthetic water-use efficiency. However, changes of the measured drought-tolerance traits of the 34 species along the succession did not demonstrate a clear trend - no significant correlations between these traits and plant successional stages were found. Moreover, the trade-off between hydraulic efficiency and safety was not identified. Taken together, our results suggested that hydraulic efficiency and photosynthetic function, rather than drought tolerance, play an important role in species distributions along plant succession in subtropical forests. [ABSTRACT FROM AUTHOR]

Abstract: A wear resistant (Cr, Fe)7C3/γ-Fe ceramal composite coating was fabricated on substrate of a 0.45%C carbon steel by plasma transferred arc (PTA) cladding process using the Fe–Cr–C elemental powder blends. The microstructure, microhardness and dry-sliding wear resistance of the coating were evaluated. Results shown that the plasma transferred arc clad ceramal composite coating has a rapidly solidified microstructure consisting of blocky primary (Cr, Fe)7C3 and the inter-blocky (Cr, Fe)7C3/γ-Fe eutectics and is metallurgically bonded to the 0.45%C carbon steel substrate. The ceramal composite coating has high hardness and excellent wear resistance under dry sliding wear test condition. [Copyright &y& Elsevier]

Most, if not all, orogenic gold deposits form during the late stages of deformation. In some cases, there is barren pre-mineralization hydrothermal alteration which may be part of a single progressive hydrothermal event or a temporally distinct event relative to deposition of gold. At the Huangjindong orogenic gold deposit in the Jiangnan Orogen of southern China, there are two phases of vein generation, the earlier of which is largely barren. Structural analysis, petrography, mineralogy, and in situ laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) gold mapping of different generations of gold-bearing sulfides reveal the relationship between different phases of hydrothermal alteration and quartz veins. Pre-existing barren and brittle quartz veins, which are controlled by tight folds and thrust faults, provide favorable competent hosts for later overprinting by gold-bearing ore-bearing fluids that infiltrated during ongoing reverse-sinistral fault movement. These overpressured fluids caused hydrofracturing to complete brecciation of segments of the earlier quartz veins and associated pre-existing breccias, with deposition of auriferous quartz-sulfide veins and breccia cements or matrices within them. Although fluid inclusion data are non-definitive, fluid pressure fluctuations are interpreted to have resulted in phase separation within the ore fluid which was primarily responsible for destabilization of gold complexes and deposition of native gold with other invisible gold-bearing ore-related sulfides formed by sulfidation reactions, in hydrofractures and breccia matrices. Thus, competent barren quartz veins in fold/thrust belts may locally host superimposed gold mineralization and provide favorable targets for gold resources. [ABSTRACT FROM AUTHOR]

Point-of-Interest (POI) recommendation is one of the most essential tasks in LBSNs to help users discover new interesting locations, especially when users travel out of town or to unfamiliar areas. Current studies on POI recommendation in LBSNs mainly focus on modeling multiple factors extracted from users' profiles and checking-in records. Data sparsity and incompleteness of user-POI interaction matrix are very common problems in POI recommendation, especially for the out-of-town scenario. Another challenge is that most information in the LBSNs is unreliable due to users' different backgrounds or preferences. Because of the close relationship between users, information from trustable friends on Communication-Based Social Networks (CBSNs) is more valuable than that in LBSNs, which can give a preferable suggestion instead of trustless reviews in LBSNs. In this study, we propose a latent probabilistic generative model called HI-LDA (Heterogeneous Information based LDA), which can accurately capture users' words on CBSNs by taking into full consideration the information on LBSNs including geographical effect as well as the abundant information including social relationship, users' interactive behaviors and comment content. In particular, the parameters of the HI-LDA model can be inferred by the Gibbs sampling method in an effective fashion. Beyond these proposed techniques, we introduce an POI recommendation framework integrating geographical clustering approach considering the locations and popularity of POIs simultaneously. Extensive experiments were conducted to evaluate the performance of the proposed framework on two real heterogeneous LBSN-CBSN networks. The experimental results demonstrate the superiority of HI-LDA on effective and efficient POI recommendation in both home-town and out-of-town scenarios, when compared with the state-of-the-art baseline approaches. [ABSTRACT FROM AUTHOR]

Nowadays, Online shopping has been tremendous lifestyle choices due to the lower management cost for product/service providers and the cheaper prices for buyers/customers. Meanwhile, it raises a big challenge for both buyers and sellers to identify the right product items from the numerous choices and the right customers from a large number of different buyers. This motivates the study of recommendation system which computes recommendation scores for product items and filters out those with low scores. Recently, a promising direction involves the consideration of the social network influence in recommendation system. While significant performance improvement has been observed, it is still unclear to which extension the social network influence can help differentiate product items in terms of recommendation scores. This is an interesting problem in particular in the situation that the recommended product items have the highly similar (or identical) scores. As the first effort to this problem, this paper probes the boundary of social network influence to recommendation outputs by solving an optimization problem called evidence-driven dubious decision making. Two solutions have been proposed and the evaluation on two real world datasets has verified the effectiveness of the proposed solutions. [ABSTRACT FROM AUTHOR]

It is well known that the labeling problems of graphs arise in many (but not limited to) networking and telecommunication contexts. In this paper we introduce the anti- k -labeling problem of graphs which we seek to minimize the similarity (or distance) of neighboring nodes. For example, in the fundamental frequency assignment problem in wireless networks where each node is assigned a frequency, it is usually desirable to limit or minimize the frequency gap between neighboring nodes so as to limit interference. Let k ≥ 1 be an integer and ψ is a labeling function (anti- k -labeling) from V (G) to { 1 , 2 , ... , k } for a graph G. A no-hole anti-k-labeling is an anti- k -labeling using all labels between 1 and k. We define w ψ (e) = | ψ (u) − ψ (v) | for an edge e = u v and w ψ (G) = min { w ψ (e) : e ∈ E (G) } for an anti- k -labeling ψ of the graph G. The anti-k-labeling number of a graph G, λ k (G), is max { w ψ (G): ψ }. In this paper, we first show that λ k (G) = ⌊ k − 1 χ − 1 ⌋ , and the problem that determines the anti- k -labeling number of graphs is NP-hard. We mainly obtain the lower bounds on no-hole anti- n -labeling number for trees, grids and n -cubes. [ABSTRACT FROM AUTHOR]

The existing approaches for attribute discrimination are applied to clinical data with unambiguous boundaries, and rarely take into careful consideration on how to utilize psychometric data with fuzziness. In addition, it is difficult for conventional attribute reduction methods to reduce attributes of psychometric data which are composed of a lot of attributes and contain a relatively small-scale samples. Importantly, these methods cannot be used to reduce options which are relevant to each other. In this paper, we first introduce new concepts, that is, option entropy and option influence degree, which are employed to describe the relation and distribution of options. Then, we propose a hybrid attribute discrimination method for psychometric data with fuzziness, called a hybrid attribute discrimination for psychometric data with fuzziness (ADPDF). ADPDF contains three essential techniques: 1) a fuzzy option reduction method, which aims to combine a fuzzy option to adjacent options, and is used to reduce the fuzziness of options in a psychometry and 2) ${k}$ -fold attribute reduction method, which partitions all samples into several subsets and negotiates the reduction results of different subsets, and reduces the noise for the purpose of accurately discovering key attributes. In order to show the advantages of the proposed approach, we conducted experiments on two real datasets collected from clinical diagnoses. The experimental results show that the proposed method can decrease the correlation between options effectively. Interestingly, we find three reserved options and one hundred samples in each subset show the best classification performance. Finally, we compare the proposed method with typical attribute discrimination algorithms. The results reveal that our method can improve the classification accuracy with the guarantee of time performance. [ABSTRACT FROM AUTHOR]

Community discovery plays an essential role in the analysis of the structural features of complex networks. Since online networks grow increasingly large and complex over time, the methods traditionally used for community discovery cannot efficiently handle large-scale network data. This introduces the important problem of how to effectively and efficiently discover large communities from complex networks. In this study, we propose a fast parallel community discovery model called picaso (a parallel community discovery a lgorithm based on approximate optimization), which integrates two new techniques: (1) Mountain model, which works by utilizing graph theory to approximate the selection of nodes needed for merging, and (2) Landslide algorithm, which is used to update the modularity increment based on the approximated optimization. In addition, the GraphX distribution computing framework is employed in order to achieve parallel community detection over complex networks. In the proposed model, clustering on modularity is used to initialize the Mountain model as well as to compute the weight of each edge in the networks. The relationships among the communities are then simplified by applying the Landslide algorithm, which allows us to obtain the community structures of the complex networks. Extensive experiments were conducted on real and synthetic complex network datasets, and the results demonstrate that the proposed algorithm can outperform the state of the art methods, in effectiveness and efficiency, when working to solve the problem of community detection. Moreover, we demonstratively prove that overall time performance approximates to four times faster than similar approaches. Effectively our results suggest a new paradigm for large-scale community discovery of complex networks. [ABSTRACT FROM AUTHOR]

The Zhengchong gold deposit, with a proven gold reserve of 19 t, is located in the central part of Jiangnan Orogenic Belt (JOB), South China. The orebodies are dominated by NNE- and NW- trending auriferous pyrite-arsenopyrite-quartz veins and disseminated pyrite-arsenopyrite-sericite-quartz alteration zone, structurally hosted in the Neoproterozoic epimetamorphic terranes. Three stages of hydrothermal alteration and mineralization have been defined at the Zhengchong deposit: (i) Quartz–auriferous arsenopyrite and pyrite; (ii) Quartz–polymetallic sulfides–native gold–minor chlorite; (iii) Barren quartz–calcite vein. Both invisible and native gold occurred at the deposit. Disseminated arsenopyrite and pyrite with invisible gold in them formed at an early stage in the alteration zones have generally undergone syn-mineralization plastic-brittle deformation. This resulted in the generation of hydrothermal quartz, chlorite and sulfides in pressure shadows around the arsenopyrite and the formation of fractures of the arsenopyrite. Meanwhile, the infiltration of the ore-forming fluid carrying Sb, Cu, Zn, As and Au resulted in the precipitation of polymetallic sulfides and free gold. The X-ray elements mapping of arsenopyrite and spot composition analysis of arsenopyrite and chlorite were carried out to constrain the ore-forming physicochemical conditions. The results show that the early arsenopyrite and invisible gold formed at 322–397 °C with lgf(S2) ranging from −10.5 to −6.7. The crack-seal structure of the ores indicates cyclic pressure fluctuations controlled by fault-valve behavior. The dramatic drop of pressure resulted in the phase separation of ore-forming fluids. During the phase separation, the escape of H2S gas caused the decomposition of the gold-hydrosulfide complex, which further resulted in the deposition of the native gold. With the weakening of the gold mineralization, the chlorite formed at 258–274 °C with lgf(O2) of −50.9 to −40.1, as constrained by the results from mineral thermometer. [ABSTRACT FROM AUTHOR]

The molecular mechanisms of osteogenic differentiation of bone marrow‑derived mesenchymal stem cells (BMSCs) remain to be fully elucidated. MicroRNAs (miRs) serve vital roles in the process of regulating osteogenic differentiation of BMSCs. The present study aimed to investigate the role of miR‑23a‑5p in osteogenic differentiation of human (h)BMSCs, and the underlying molecular mechanism. The results of reverse transcription‑quantitative polymerase chain reaction demonstrated that miR‑23a‑5p was significantly downregulated in the process of osteogenic differentiation. Upregulation of miR‑23a‑5p inhibited osteogenic differentiation of hBMSCs, and down‑regulated expression of miR‑23a‑5p enhanced this process, which was confirmed by alkaline phosphatase (ALP) and Alizarin Red S staining. A dual‑luciferase reporter assay confirmed that mitogen‑activated protein kinase 13 (MAPK13) was a direct target of miR‑23a‑5p. In addition, knockdown of MAPK13 inhibited osteogenic differentiation of hBMSCs, similar to the effect of upregulation of miR‑23a‑5p. Finally, the knockdown of MAPK13 also blocked the effect of miR‑23a‑5p in osteogenic differentiation of hBMSCs, which was also confirmed by ALP and Alizarin Red S staining. These results indicated that by targeting MAPK13, miR‑23a‑5p serves a vital role in osteogenic differentiation of hBMSCs, which may provide novel clinical treatments for bone injury however, further studies are required. [ABSTRACT FROM AUTHOR]

Traditionally, location suggestion systems have employed collaborative filtering model to make recommendations for users based on data gathered from users with similar interests, demographics, and check-in records. However, these techniques fail to take into account on very important element present in online social networks, the online relationships that these users maintain. Arguably, this is the most important aspect of their online profiles, often more revealing than their self reported personal interests and check-in records. Aiming to improve the accuracy and novelty of recommendations, this research proposes a hybrid location suggestion algorithm, called SocialMix, of which, takes into full consideration a user’s familiarity and preference (interest) similarity, along with relationships. In the first part of this study, we compute the degrees of familiarity between users using three feature variables: the number of mutual friends, the Jaccard index and cosine similarity. In order to determine the weights of the these feature variables, maximum likelihood estimation used, and then the features are fit to a Logistic Regression model in order to calculate the degrees of familiarity. The second part of this research we present a new method for calculating similarity between individuals by integrating users familiarity and preference similarity. This allows us to introduce a new location interest degree calculation method on the hybrid similarity. Extensive experiments were conducted on several real datasets. The performance of SocialMix was analyzed for both accuracy and time complexity using the following metrics: MAE (mean absolute error), RMSE (root mean square error), Precision, Recall, F-measure, Coverage rate, Popularity and Response time. Results were compared against classical recommendation approaches as a baseline. The results show that the accuracy and time performance of SocialMix, when compared with other algorithms which do not consider social relationships, are demonstratively improved. In addition, a positive by product worth noting is that SocialMix has a tendency to recommend more obscure but still interesting locations. [ABSTRACT FROM AUTHOR]

D-galactose injection has been shown to induce many changes in mice that represent accelerated aging. This mouse model has been widely used for pharmacological studies of anti-aging agents. The underlying mechanism of D-galactose induced aging remains unclear, however, it appears to relate to glucose and 1ipid metabolic disorders. Currently, there has yet to be a study that focuses on investigating gene expression changes in D-galactose aging mice. In this study, integrated analysis of gas chromatography/mass spectrometry-based metabonomics and gene expression profiles was used to investigate the changes in transcriptional and metabolic profiles in mimetic aging mice injected with D-galactose. Our findings demonstrated that 48 mRNAs were differentially expressed between control and D-galactose mice, and 51 potential biomarkers were identified at the metabolic level. The effects of D-galactose on aging could be attributed to glucose and 1ipid metabolic disorders, oxidative damage, accumulation of advanced glycation end products (AGEs), reduction in abnormal substance elimination, cell apoptosis, and insulin resistance. [ABSTRACT FROM AUTHOR]

[Display omitted] • Postmortem ATP catabolism changed in a tissue-dependent pattern in the mud crab. • Muscle K value could be an optimal freshness indicator for mud crab. • ATP catabolism was closely associated with microbiota in the muscle, but not in the hepatopancreas. • Various bacterial community characteristics contributed to muscle K value. • The mud crab of 4 h postmortem at room temperature remains edible. The seafood microbiome is highly diverse and plays an essential role in the spoilage of seafood. Nevertheless, how such a diverse microbiome influences freshness of mud crab (Scylla paramamosain) remains unclear. Here we investigated the postmortem ATP catabolism and succession of the bacterial community in the hepatopancreas and muscle of S. paramamosain using a high-performance liquid chromatography method and 16S rRNA gene amplicon sequencing. Our results showed a tissue-dependent change in ATP catabolism determinized the differences in the changes of nucleotide freshness indices of hepatopancreas and muscle over postmortem time of mud crab. The muscle K value could be used as an optimal nucleotide freshness indicator for the freshness of mud crab, with a proposed threshold of 20%. From a microbiota perspective, a more significant bacterial community change was observed in the muscle than in the hepatopancreas. These changes could result in a close relationship between ATP and its catabolites and microbial taxa in the muscle. Moreover, Photobacterium , Peptostreptococcaceae , average path distance, OTU richness, and Shannon index of muscle bacterial community markedly contributed to K value. These findings suggest that the mud crab of 4 h postmortem at room temperature is still edible. Notably, the importance of microbial community composition and interaction for the spoilage of mud crab should be carefully considered. [ABSTRACT FROM AUTHOR]

Highlights: [•] Ti5Si3 reinforced composite coatings were in-situ prepared on PTA cladding process. [•] The coatings consist of Ti5Si3 primary phases and NiTi2/α-Ti/Ti5Si3 eutectics. [•] Ti/Si/Ni ratios have a noticeable effect on microstructure of the coatings. [•] Content and morphologies of primary Ti5Si3influence wear properties of the coatings. [ABSTRACT FROM AUTHOR]

Abstract: A self-consistent theory for calculation of built-in voltage (U bi) of metal–organic semiconductor–metal (MOSM) structures is developed based on Gaussian energy distribution of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO). It is shown that the built-in voltage depends not only on the work function difference of the two electrodes, but also on the mean energy level of HOMO and LUMO, as well as the Gaussian width of the energy distribution. The theory predicts that the spreading of HOMO and LUMO levels will results in an increase of U bi, and that U bi decreases with increasing temperature. [Copyright &y& Elsevier]

A novel organic ligand, 6-parachloroaniline carbonyl 2-pyridine carboxylic acid, and the corresponding europium complex, tris(6-parachloroaniline carbonyl-2-pyridine carboxylate) europium (III) have been designed and synthesized. The results showed that the synthesized product was a conjugated complex, emitting remarkable strong red luminescence, and was a good red luminescence material with good thermal stability. The 5D0 lifetime of Eu3+ in the complex was examined using time-resolved spectroscopic analysis. The lifetime values for 1.0×10−5 mol/l ethanol solution of the complex and for the complex solid were 0.49±0.01 and 1.94±0.01 ms, respectively. [Copyright &y& Elsevier]

• Multiple Au, Au-Sb and Sb events related to complex tectonic evolution of Orogen. • Early Devonian intracontinental orogeny and related Au-Sb mineralization. • Triassic distal effect of collisional orogeny and related Au-Sb event. • Early Cretaceous Sb and Au events linked to rollback of paleo-Pacific Plate. • Definition of structural geometries is critical for future exploration targeting. The Jiangnan Orogen, located between the Yangtze and Cathaysia Blocks in southern China, hosts significant gold and antimony resources. Long-standing controversies over the number and precise timing of gold, gold-antimony and antimony mineralization event(s), and the genesis of these deposits, limit the understanding and exploration of this giant gold and antimony system. Together with geological evidence, a critical review of the published geochronological data of these deposits suggest that there were two gold events in the Triassic (~235 Ma) and Early Cretaceous (~142–130 Ma), two gold-antimony events in the Early Devonian (~402 Ma) and Late Triassic-Middle Jurassic (~224–163 Ma: possibly equivalent to the two gold events), and one antimony event in the Early Cretaceous (~130 Ma). There are other possible gold events in the Neoproterozoic or at an even older age, and Ordovician to Early Devonian, which are constrained only by limited geological evidence and a few non-robust isotopic ages. The regional distribution of the gold, gold-antimony and antimony districts, and deposits therein, reveal a first-order control on the mineralization by crustal scale faults which acted as ore-forming fluid pathways connected to deep fluid and metal source areas. Second- and third-order faults that are situated along the jogs of the first-order faults, especially fault corridors defined by NNE-NE-trending second-order faults and third-order NW to E-W-trending discontinuous oblique faults, provided favorable locations for Pre-Cretaceous gold-(antimony) mineralization. In addition, NE-trending open anticlines, linked to deep crustal levels by first-order faults, host significant antimony and minor gold mineralization, and the curvilinear Fanjingshan detachment Fault hosts some gold and antimony deposits. Locally, at deposit to orebody-scales, pre-ore barren quartz veins and magmatic dikes were the loci for mineralization in some gold-antimony deposits. The structural geometry of the pre-Cretaceous gold and gold-antimony deposits suggests an Early Devonian orogenic gold-antimony mineralization event during a transpressional tectonic regime related to coeval intracontinental orogeny between the Yangtze and Cathaysian Blocks. In contrast, Triassic orogenic gold and Triassic-Middle Jurassic orogenic gold-antimony events are interpreted to relate to distal effects of the collision between the North and South China blocks. The structurally-contrasting major Early Cretaceous epizonal antimony mineralization event, together with contemporaneous hydrothermal gold mineralization, is interpreted to have been controlled by normal faults and pre-ore open folds in an extensional tectonic regime related to the distal effects of rollback of the paleo-Pacific Plate after ~135 Ma. For future geoscience-based exploration in the Orogen, documentation and interpretation of critical structural geometries of gold, gold-antimony and antimony deposits is a vital step towards successful target generation. [ABSTRACT FROM AUTHOR]

A chart is presented regarding the synthesis of unnatural nitrogen (N)-glycosyl αamino acids through petasis reaction.