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Metal–organic frameworks (Sm-MOFs) were prepared using a microwave-assisted ball milling method with a water solution. The structure was characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and SEM, and the thermal stability of the Sm-MOFs was tested by Thermogravimetry (TGA). The results showed that the Sm-MOF material exhibited a favorable effect on removing the organic dye Congo red (CR). When the concentration of CR was 80 ppm, adding 50 mg of Sm-MOF material achieved an adsorption capacity of 396.8 mg·g−1. The experimental data were analyzed theoretically through dynamics, and the experimental results were consistent with the second dynamics model, with correlation coefficients (R 2) all above 0.99. Comprehensive data analysis revealed that the Sm-MOF materials had great potential for future application in wastewater treatment.

Nucleic acid amplification is crucial for disease diagnosis, especially lethal infectious diseases such as COVID-19. Compared with PCR, isothermal amplification methods are advantageous for point-of-care testing (POCT). However, complicated primer design limits their application in detecting some short targets or sequences with abnormal GC content. Herein, we developed a novel linear displacement isothermal amplification (LDIA) method using two pairs of conventional primers and

Typical transition-metal dichalcogenides (TMDs) and graphdiyne (GDY) often form type-I heterojunctions, which will limit their applications in optoelectronic devices. Here, type-II heterojunctions based on GDY and TMDs are constructed by introducing Janus structures. An intrinsic type-II heterojunction is presented when the GDY is in contact with a Se-terminated layer, but a type-I heterojunction would appear when it is in contact with the S-terminated surface. Such a difference in band alignment can be attributed to the interaction between the dipole moment formed by the Janus structure and the graphdiyne layer. Furthermore, for heterojunctions in contact with the S-terminated layer, they can be converted into type-II heterojunctions by a small external electric field (for WSSe, only 0.05 V A

With the development of Internet of Things (IoT) technologies, Internet-enabled devices have been widely used in our daily lives. As a new service paradigm, cloud computing aims at solving the resource-constrained problem of Internet-enabled devices. It is playing an increasingly important role in resource sharing. Due to the complexity and openness of wireless networks, the authentication protocol is crucial for secure communication and user privacy protection. In this paper, we discuss the limitations of a recently introduced IoT-based authentication scheme for cloud computing. Furthermore, we present an enhanced three-factor authentication scheme using chaotic maps. The session key is established based on Chebyshev chaotic-based Diffie–Hellman key exchange. In addition, the session key involves a long-term secret. It ensures that our scheme is secure against all the possible session key exposure attacks. Besides, our scheme can effectively update user password locally. Burrows–Abadi–Needham logic proof confirms that our scheme provides mutual authentication and session key agreement. The formal analysis under random oracle model proves the semantic security of our scheme. The informal analysis shows that our scheme is immune to diverse attacks and has desired features such as three-factor secrecy. Finally, the performance comparisons demonstrate that our scheme provides optimal security features with an acceptable computation and communication overheads.

Wireless medical sensor networks (WMSNs) are playing an increasingly important role in smart healthcare applications. Since the data transmitted in WMSNs is closely related to patient’s life and health, and considering the resource-constrain feature of the sensor node, constructing an authentication scheme for WMSNs is a formidable task. Recently, Soni et al. presented an elliptic curve cryptosystem based three-factor authentication scheme for WMSNs. However, we discover that their scheme suffers from serious vulnerabilities, such as sensor node capture attack, no forward secrecy, and the violation of three-factor security. To enhance the security and efficiency, we present a novel scheme using Rabin cryptosystem and chaotic maps. We use several widely-accepted security analysis methods to verify the correctness and security of our scheme. The Burrows–Abadi–Needham logic proof confirms the completeness of our scheme. The heuristic analysis indicates that our scheme is resistant to potential attacks and provides various security attributes like forward secrecy and three-factor security. Furthermore, we demonstrate that our scheme is provably secure in the random oracle model. Finally, the performance comparisons indicate that our scheme is superior to the related schemes both in security and efficiency and is more applicable to WMSNs owing to low overhead of the sensor node.

Zero (or near-zero) Poisson's ratio (ZPR) materials have important applications in the field of precision instruments because one of their faces is stable and will not be affected by strain. However, ZPR materials are extremely rare. Here, we report a novel ZPR material, two-dimensional

Given an arbitrary connected $G$, the $n$-polygon graph $\tau_n(G)$ is obtained by adding a path with length $n$ $(n\geq 2)$ to each edge of graph $G$, and the iterated $n$-polygon graphs $\tau_n^g(G)$ ($g\geq 0$), is obtained from the iteration $\tau_n^g(G)=\tau_n(\tau_n^{g-1}(G))$, with initial condition $\tau_n^0(G)=G$. In this paper, a method for calculating the eigenvalues of normalized Laplacian matrix for graph $\tau_n(G)$ is presented if the eigenvalues of normalized Laplacian matrix for graph $G$ is given firstly. Then, the normalized Laplacian spectrums for the graph $\tau_n(G)$ and the graphs $\tau_n^g(G)$ ($g\geq 0$) can also be derived. Finally, as applications, we calculate the multiplicative degree-Kirchhoff index, Kemeny's constant and the number of spanning trees for the graph $\tau_n(G)$ and the graphs $\tau_n^g(G)$ by exploring their connections with the normalized Laplacian spectrum, exact results for these quantities are obtained., Comment: 44pages, 1 figure

In various experimental studies, h-BN/TiO2 heterostructure greatly improves the photocatalytic capacity of TiO2. However, the actual influence of h-BN is unclear. In this work, by performing ab initio nonadiabatic molecular dynamics (NAMD) calculation, we studied the h-BN/TiO2[rutile (110)] heterostructure and found h-BN owns a strong attracting ability of the hole which makes the hole to get out of the atomic oscillation inside TiO2 in a short time (250 fs). By comparing the NAMD result of the intrinsic TiO2 (110) surface, the actual enhancement of the photocatalytic ability is found to be provided by the carrier separation h-BN brings due to the introduction of h-BN will accelerate the hole relaxation. This finding clearly illustrates the role of h-BN in the photocatalysis process in the h-BN/TiO2 heterostructure, thus better control of the TiO2 photocatalytic ability may be conducted.

The Watts–Strogatz networks are important models that interpolate between regular lattices and random graphs, and Barabási–Albert networks are famous models that explain the origin of the scale-free networks. Here, we consider the first encounters between two particles (e.g., prey A and predator B) embedded in the Watts–Strogatz networks and the Barabási–Albert networks. We address numerically the mean first-encounter time (MFET) while the two particles are moving and the mean first-passage time (MFPT) while the prey is fixed, aiming at uncovering the impact of the prey’s motion on the encounter time, and the conditions where the motion of the prey would accelerate (or slow) the encounter between the two particles. Different initial conditions are considered. In the case where the two particles start independently from sites that are selected randomly from the stationary distribution, on the Barabási–Albert networks, the MFET is far less than the MFPT, and the impact of prey’s motion on the encounter time is enormous, whereas, on the Watts–Strogatz networks (including Erdős-Rényi random networks), the MFET is about 0.5–1 times the MFPT, and the impact of prey’s motion on the encounter time is relatively small. We also consider the case where prey A starts from a fixed site and the predator starts from a randomly drawn site and present the conditions where the motion of the prey would accelerate (or slow) the encounter between the two particles. The relation between the MFET (or MFPT) and the average path length is also discussed.

First-passage processes on fractals are of particular importance since fractals are ubiquitous in nature, and first-passage processes are fundamental dynamic processes that have wide applications. The global mean first-passage time (GMFPT), which is the expected time for a walker (or a particle) to first reach the given target site while the probability distribution for the position of target site is uniform, is a useful indicator for the transport efficiency of the whole network. The smaller the GMFPT, the faster the mass is transported on the network. In this work, we consider the first-passage process on a class of fractal scale-free trees (FSTs), aiming at speeding up the first-passage process on the FSTs. Firstly, we analyze the global mean first-passage time (GMFPT) for unbiased random walks on the FSTs. Then we introduce proper weight, dominated by a parameter w (w > 0), to each edge of the FSTs and construct a biased random walks strategy based on these weights. Next, we analytically evaluated the GMFPT for biased random walks on the FSTs. The exact results of the GMFPT for unbiased and biased random walks on the FSTs are both obtained. Finally, we view the GMFPT as a function of parameter w and find the point where the GMFPT achieves its minimum. The exact result is obtained and a way to optimize and speed up the first-passage process on the FSTs is presented.

Similar to most semiconductors, low-dimensional GaN materials also have the problem of asymmetric doping, that is, it is quite difficult to form p-type conductivity compared to n-type conductivity. Here, we have discussed the geometry, structure, and electronic defect properties of a two-dimensional graphene-like gallium nitride (g-GaN) monolayer belonging to the group III–V compounds, doped with different elements (In, Mg, Zn) at the Ga site. Based on first principles calculations, we found that substituting Ga (low concentration impurities) with Mg would be a better choice for fabricating a p-type doping semiconductor under N-rich conditions, which is essential for understanding the properties of impurity defects and intrinsic defects in the g-GaN monolayer (using the “transfer to real state” model). Moreover, the g-GaN monolayer is dynamically stable and can remain stable even in high-temperature conditions. This research provides insight for increasing the hole concentration and preparing potential high-performance optoelectronic devices using low-dimensional GaN materials.

Fractals are ubiquitous in nature and random walks on fractals have attracted lots of scientific attention in the past several years. In this work, we consider discrete random walks on a class of fractal scale-free trees (FST), whose topologies are controlled by two integer parameters (i.e., u≥2 and v≥1) and exhibit a wide range of topological properties by suitably varying the parameters u and v. The mean trapping time (MTT), referred to as T_{y}, which is the mean time it takes the walker to be absorbed by the trap fixed at site y of the FST, is addressed analytically on the FST, and the effects of the trap location y on the MTT for the FST and for the general trees are also analyzed. First, a method, which is based on the connection between the MTT and the effective resistances, to derive analytically T_{y} for an arbitrary site y of the FST is presented, and some examples are provided to show the effectiveness of the method. Then, we compare T_{y} for all the possible site y of the trees, and find the sites where T_{y} achieves the minimum (or maximum) on the FST. Finally, we analyze the effects of trap location on the MTT in general trees and find that the average path length (APL) from an arbitrary site to the trap is the decisive factor which dominates the difference in the MTTs for different trap locations on general trees. We find, for any tree, the MTT obtains the minimum (or maximum) at sites where the APL achieves the minimum (or maximum).

Continuous Implicit Authentication (CIA) provides a imperceptible and passive validation in a whole process of operating the mobile devices. In this paper, we describe users’ behavioral patterns through the build-in sensors of smartphones, and apply them to our authentication system. The current work is mainly implemented in a controlled experimental environment. We prove the effectiveness of the implicit authentication method in the natural environment through the analysis of only the touch screen process and the entire process of the user using the mobile phone. We focus on the multi-class strategy in CIA, in which a classifier has to recognize the “owner” of a series of operations from identity banks. To extract temporal domain and space domain features and enhance the classifier's discriminative power, our system utilizes Resnet with Squeeze-and-Excitation incorporating Attention blocks and Additive Angular Margin Loss. We evaluate our system both in our dataset and BrainRun dataset, and the accuracies of distinguish the correct identity achieves are 96.94% and 87.11% respectively. Specially, with the continuous data in BrainRun, the result is generated from behaviors during 5 s in a more interactive game.

With the improvement of the status of mobile phones and other mobile terminals in life, the privacy protection of mobile phones is still a big problem. Aiming at the Android system, the mobile terminal operating system with the largest share today, this paper proposes a widget intention analysis method to solve the problem of how to judge the user's operation intention in privacy protection. This intention analysis method uses MobilenetV3 to extract image information, BiLSTM to extract text information, then constructs joint features together, and uses deep learning technology to realize intention analysis of widgets. Through comparative experiments, our method improves the detection accuracy and reduces the training time for the existing methods.

The study of boron structure is fascinating because boron has various allotropes containing boron icosahedrons under pressure. Here, we propose a new boron structure (space group F m 3 ¯ m ) that is dynamically stable at 1.4 tera-Pascal (TPa) using density functional theory and an evolutionary algorithm. The unit cell of this structure can be viewed as a structure with a boron atom embedded in the icosahedron. This structure behaves as a metal, and cannot be stable under ambient pressure. Furthermore, we found electrons gather in lattice interstices, which is similar to that of the semiconductor Na or Ca2N-II under high pressure. The discovery of this new structure expands our comprehension of high-pressure condensed matter and contributes to the further development of high-pressure science.

In this work we consider the first encounter problems between a fixed and/or mobile target A and a moving trap B on Bethe Lattices and Cayley trees. The survival probability (SP) of the target A on the both kinds of structures are analyzed analytically and compared. On Bethe Lattices, the results show that the fixed target will still prolong its survival time, whereas, on Cayley trees, there are some initial positions where the target should move to prolong its survival time. The mean first encounter time (MFET) for mobile target A is evaluated numerically and compared with the mean first passage time (MFPT) for the fixed target A. Different initial settings are addressed and clear boundaries are obtained. These findings are helpful for optimizing the strategy to prolong the survival time of the target or to speed up the search process on Cayley trees, in relation to the target's movement and the initial position configuration of the two walkers. We also present a new method, which uses a small amount of memory, for simulating random walks on Cayley trees., 25 pages, 11 figures

We consider two random walkers embedded in a finite, two-dimension comb and we study the mean first-encounter time (MFET) evidencing (mainly numerically) different scalings with the linear size of the underlying network according to the initial position of the walkers. If one of the two players is not allowed to move, then the first-encounter problem can be recast into a first-passage problem (MFPT) for which we also obtain exact results for different initial configurations. By comparing MFET and MFPT, we are able to figure out possible search strategies and, in particular, we show that letting one player be fixed can be convenient to speed up the search as long as we can finely control the initial setting, while, for a random setting, on average, letting one player rest would slow down the search.

Random walks have wide application in real lives, such as target search, reaction kinetics, polymer chains, and so on. In this paper, we consider discrete random walks on general connected networks and focus on the global mean first return time (GMFRT), which is defined as the mean first return time averaged over all the possible starting positions (vertices), aiming at finding the structures which have the maximal (or the minimal) GMFRT. Our results show that, among all trees with a given number of vertices, trees with linear structure are those with the minimal GMFRT and stars are those with the maximal GMFRT. We also find that, among all unweighted and undirected connected simple graphs with a given number of edges and vertices, the graphs maximizing (resp. minimizing) the GMFRT are the ones for which the variance of the nodes degrees is the largest (resp. the smallest).

Monolayer VS2 has two common stable phases, 2H-phase and 1T-phase. Based on first-principles calculations, we studied the optical properties of 2D-VS2, including their dielectric functions, absorption coefficients, refraction indexes and energy loss functions. Also, we fully analyzed the relationship between the electronic structure and the optical characteristics of 2D-VS2. We found that the differences of density of states are the fundamental reasons for the differences of the two phase optical absorption behavior.

Multifunction and high integration has always been a goal worth pursuing when important breakthroughs of multidisciplinary researches in the fields of thermo-luminescent, opto-electronic, photo-magnetic interaction, etc., are emerged. Other significant considerations for a multifunctional strategy proposed in a single-material system are low-cost components and processing, universal applicability, and widespread popularity. Herein, we developed an all-purpose material with a tunable light emission property and controllable optoelectronic and optothermal response process. We showed a disappearance of emission behavior under the excitation of UV light by building a mid-gap host (Bi2O3) along with a rare earth (Sm3+) ion, with multiple energy level configurations, as an emission center. We also demonstrated that this scheme realized the successful imbedding of higher energy level Sm3+ into the conduction band and led to increased current under the excitation of visible light and the depopulated redistribution of the excited state level near the conduction band at higher temperatures. Thus, this phosphor is expected to open up the possibility of potentially free choice of light shielding, temperature sensing, and photodetection in a single-material system.

In this work we consider a class of recursively-grown fractal networks $G_n(t)$, whose topology is controlled by two integer parameters $t$ and $n$. We first analyse the structural properties of $G_n(t)$ (including fractal dimension, modularity and clustering coefficient) and then we move to its transport properties. The latter are studied in terms of first-passage quantities (including the mean trapping time, the global mean first-passage time and the Kemeny's constant) and we highlight that their asymptotic behavior is controlled by network's size and diameter. Remarkably, if we tune $n$ (or, analogously, $t$) while keeping the network size fixed, as $n$ increases ($t$ decreases) the network gets more and more clustered and modular, while its diameter is reduced, implying, ultimately, a better transport performance. The connection between this class of networks and models for polymer architectures is also discussed., Comment: 14 pages, 4 figures

With the rapid development of mobile services, multiserver authentication protocol with its high efficiency has emerged as an indispensable security mechanism for mobile services. Recently, Ali et al. introduced a biometric-based multiserver authentication scheme and claimed the scheme is resistant to various attacks. However, after a careful examination, we find that Ali et al.’s scheme is vulnerable to various security attacks, such as user impersonation attack, server impersonation attack, privileged insider attack, denial of service attack, fails to provide forward secrecy and three-factor secrecy. To overcome these weaknesses, we propose an improved biometric-based multiserver authentication scheme using elliptic curve cryptosystem. Formal security analysis under the random oracle model proves that our scheme is provably secure. Furthermore, BAN (Burrows-Abadi-Needham) logic analysis demonstrates our scheme achieves mutual authentication and session key agreement. In addition, the informal analysis proves that our scheme is secure against all current known attacks and achieves desirable features. Besides, the performance and security comparison shows that our scheme is superior to related schemes.

Layered MnO2 is widely concerned due to its excellent adsorption performance of volatile organic compounds (VOCs). In this work, the first-principles calculations were carried out to thoroughly investigate the adsorption mechanism of typical VOCs (formaldehyde, benzene and methyl chloride) on pristine and Al-modified MnO2 monolayer surfaces. The result shows that there are weak physical interactions between VOCs molecules and MnO2 monolayer, however, the modification by Al atom dramatically enhance these interactions, which can be classified as chemical adsorption. Specifically, the best adsorption performance occurs in the adsorption process of benzene molecule on the Al-modified MnO2 monolayer (with the adsorption energy of −2.416 eV). Besides, the difference of adsorption energy (−2.044 eV, nearly 10 times increase) between pristine MnO2 monolayer and Al-modified MnO2 monolayer demonstrates that the Al atom used for surface modification can dramatically enhance the adsorption performance of MnO2 layer for formaldehyde. Additionally, the projected density of state and charge density difference results confirm that Al atom plays a role of tie to connect these VOCs and MnO2 monolayer. Therefore, the Al-modified MnO2 monolayer is expected to be a promising VOCs adsorbent.

The Tutte polynomial of a graph is a 2-variable polynomial which is quite important in both combinatorics and statistical physics. It contains various numerical invariants and polynomial invariants, such as the number of spanning trees, the number of spanning forests, the number of acyclic orientations, the reliability polynomial, chromatic polynomial and flow polynomial. In this paper, we study and gain recursive formulas for the Tutte polynomial of pseudofractal scale-free web (PSW) which implies logarithmic complexity algorithm is obtained to calculate the Tutte polynomial of PSW although it is NP-hard for general graph. We also obtain the rigorous solution for the the number of spanning trees of PSW by solving the recurrence relations derived from Tutte polynomial, which give an alternative approach for explicitly determining the number of spanning trees of PSW. Further more, we analysis the all-terminal reliability of PSW and compare the results with that of Sierpinski gasket which has the same number of nodes and edges with PSW. In contrast with the well-known conclusion that scale-free networks are more robust against removal of nodes than homogeneous networks (e.g., exponential networks and regular networks). Our results show that Sierpinski gasket (which is a regular network) are more robust against random edge failures than PSW (which is a scale-free network). Whether it is true for any regular networks and scale-free networks, is still a unresolved problem., 19pages,7figures. arXiv admin note: text overlap with arXiv:1006.5333

Fractal (or transfractal) features are common in real-life networks and are known to influence the dynamic processes taking place in the network itself. Here we consider a class of scale-free deterministic networks, called $(u,v)$-flowers, whose topological properties can be controlled by tuning the parameters $u$ and $v$; in particular, for $u>1$, they are fractals endowed with a fractal dimension $d_f$, while for $u=1$, they are transfractal endowed with a transfractal dimension $\tilde{d}_f$. In this work we investigate dynamic processes (i.e., random walks) and topological properties (i.e., the Laplacian spectrum) and we show that, under proper conditions, the same scalings (ruled by the related dimensions), emerge for both fractal and transfractal., 15 pages, 7 figures

We study discrete random walks on the NFSFT and provide new methods to calculate the analytic solutions of the MFPT for any pair of nodes, the MTT for any target node and MDT for any source node. Further more, using the MTT and the MDT as the measures of trapping efficiency and diffusion efficiency respectively, we compare the trapping efficiency and diffusion efficiency for any two nodes of NFSFT and find the best (or worst) trapping sites and the best (or worst) diffusion sites. Our results show that: the two hubs of NFSFT is the best trapping site, but it is also the worst diffusion site, the nodes which are the farthest nodes from the two hubs are the worst trapping sites, but they are also the best diffusion sites. Comparing the maximum and minimum of MTT and MDT, we found that the ratio between the maximum and minimum of MTT grows logarithmically with network order, but the ratio between the maximum and minimum of MTT is almost equal to $1$. These results implie that the trap's position has great effect on the trapping efficiency, but the position of source node almost has no effect on diffusion efficiency. We also conducted numerical simulation to test the results we have derived, the results we derived are consistent with those obtained by numerical simulation., 23 pages, 4 figures

Identifying sources of epidemic spreading or rumor diffusion from minority data is of paramount importance in network science with great applied values to the society. However, a general theoretical frame work dealing with source(s) localization is lacking of perfect understanding. Based on limited observers in the network, we study the problem of estimating the origin of a disease/rumor outbreak: given a contact network and a snapshot of epidemic spread at a certain time, root out the infection source. Assuming that the epidemic spread follows the usual susceptible–infected (SI) model, we introduce an inference algorithm based on sparsely placed observers. We present an algorithm which utilizes the correlated information between the network structure (shortest paths) and the diffusion dynamics (time sequence of infection). The numerical results of artificial and empirical networks show that it leads to significant improvement of performance compared to existing approaches. Our analysis sheds insight into the behavior of the disease/rumor spreading process not only in the local particular regime but also for the whole general network.

Consider the nonparametric regression model Y ni = g(t ni ) + ϵ ni , 1 ≤ i ≤ n, where {t ni } are known design points, and the errors {ϵ ni } have a linear representation with and {e t , − ∞