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Van der Waals (vdW) heterostructures provide an effective strategy for exploring and expanding the potential applications of two-dimensional materials. In this study, we employ first-principles density functional theory (DFT) to investigate the geometric, electronic, and optical properties of MoGe2N4/AlN and MoSiGeN4/AlN vdW heterostructures. The stable MoGe2N4/AlN heterostructure exhibits an indirect band gap semiconductor with a type-I band gap arrangement, making it suitable for optoelectronic devices. Conversely, the stable MoSiGeN4/AlN heterostructure demonstrates various band gap arrangements depending on stacking modes, rendering it suitable for photocatalysis applications. Additionally, we analyze the effects of mechanical strain and vertical electric field on the electronic properties of these heterostructures. Our results indicate that both mechanical strain and vertical electric field can adjust the band gap. Notably, application of an electric field or mechanical strain leads to the transformation of the MoGe2N4/AlN heterostructure from a type-I to a type-II band alignment and from an indirect to a direct band transfer, while MoSiGeN4/AlN can transition from a type-II to a type-I band alignment. Type-II band alignment is considered a feasible scheme for photocatalysis, photocells, and photovoltaics. The discovery of these characteristics suggests that MoGe2N4/AlN and MoSiGeN4/AlN vdW heterostructures, despite their high lattice mismatch, hold promise as tunable optoelectronic materials with excellent performance in optoelectronic devices and photocatalysis. [ABSTRACT FROM AUTHOR]

With the increasing demand for tooth bleaching in esthetic dentistry, its safety has been the focus of a comprehensive body of literature. In this context, the aim of the present study was to evaluate the application effects of pentalysine β-carbonylphthalocyanine zinc (ZnPc(Lys)5)-mediated photodynamic therapy in dentin bleaching and its effects on dentin collagen. We first established a new and reproducible tooth staining model using dentin blocks stained by Orange II and then bleached with ZnPc(Lys)5 (25 μM) and hydrogen peroxide (10% or 30%). Data were analyzed with one- and two-way ANOVA and a significance level of p < 0.05. ZnPc(Lys)5 effectively bleached the dentin samples to an extent comparable to hydrogen peroxide at either 10% or 30% concentrations. Further studies on the dentin morphology, chemical element distribution, and protein constituents, using an electron microscope, energy dispersive spectroscopy, X-ray photoelectron spectroscopy, and SDS-PAGE, demonstrated that treatment with the photosensitizer preserved the dentin structure and, at the same time, the major organic component, collagen type I. For comparison, hydrogen peroxide (10% or 30%) treatment significantly degraded the collagen protein. This work indicated that the photosensitizer exerts potent bleaching effects on dentin staining; importantly, does not damage dentin and its collagen content; and opens up a new strategy to further explore various photosensitizers for the bleaching of both tooth enamel and dentin. [ABSTRACT FROM AUTHOR]

In vehicular edge computing (VEC), some tasks can be processed either locally or on the mobile edge computing (MEC) server at a base station (BS) or a nearby vehicle. In fact, tasks are offloaded or not, based on the status of vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication. In this paper, device-to-device (D2D)-based V2V communication and multiple-input multiple-output and nonorthogonal multiple access (MIMO-NOMA)-based V2I communication are considered. In actual communication scenarios, the channel conditions for MIMO-NOMA-based V2I communication are uncertain, and the task arrival is random, leading to a highly complex environment for VEC systems. To solve this problem, we propose a power allocation scheme based on decentralized deep reinforcement learning (DRL). Since the action space is continuous, we employ the deep deterministic policy gradient (DDPG) algorithm to obtain the optimal policy. Extensive experiments demonstrate that our proposed approach with DRL and DDPG outperforms existing greedy strategies in terms of power consumption and reward. [ABSTRACT FROM AUTHOR]

As naturally derived material, cellulose aerogels have excellent thermal insulation properties due to their unique high porosity and three-dimensional mesoporous structure. However, its hydrophilic properties limit its application in the field of building insulation. Here, we propose a method to prepare high hydrophobicity by adopting the sol-gel method and chemical vapor reaction strategy using cellulose acetate type II as raw material and 2,4-toluene diisocyanate as the cross-linking agent. Thermal properties of cellulose acetate aerogels (CAAs) were measured, where pyridine was the catalyst, acetone was the solvent, and perfluorodecyltriethoxysilane (PFDS), hexamethyldisilazane (HMDS), and methyltriethoxysilane (MTES) were used as hydrophobic agents (by process hydrophobic test). Compared with MTES-modified cellulose acetate aerogels (M-CAAs) and HMDS (H-CAAs)-modified cellulose acetate aerogels, PFDS-modified (P-CAAs) cellulose acetate aerogels are the most hydrophobic. By implementing hydrophobic modification of PFDS both inside and outside the structure of cellulose acetate aerogels, the water contact angle can reach up to 136°, strongly demonstrating the potential of PFDS as a hydrophobic agent. The results show that the thermal conductivity and compressive strength of cellulose acetate aerogel with the best hydrophobic properties are 0.035 W m−1 K−1 at normal pressure and 0.39 MPa at 3% strain, respectively. This work shows that the highly hydrophobic cellulose acetate aerogel has potential as a waterproof material in the field of building thermal-insulation materials. [ABSTRACT FROM AUTHOR]

Understanding the response of tropospheric ozone (O3) to nitrogen dioxide (NO2) change is important for local O3 control. The relationship between O3 and NO2 at county scale in China has been extensively studied using models, but there is a lack of results from direct measurements. In this study, we used measurements of O3, NO2 and meteorological conditions from a dense network in the Yangtze River Delta (YRD), and satellite observed formaldehyde (HCHO) and NO2 column densities for the analysis of O3 variabilities and its relationship to NO2. As a result, severe O3 pollution occurred mainly in Shanghai city, southern Jiangsu and northern Zhejiang provinces in YRD during April–September. In addition, meteorological conditions could explain 54% the diurnal O3 variation over YRD. During April–September 2015–2021, O3 showed a significant positive relationship (r = 0.61 ± 0.10) with NO2 after removing the impact from meteorological conditions. However, the relationship could be reversed with NO2 concentration change. Our result suggested that the controllable O3 related to NO2 change is up to 100 μg·m−3 in megacities over Shanghai and northern Zhejiang province. The O3 is much more sensitive to the NO2 reduction in megacities than surrounding areas. Our results evaluate the different impacts of NO2 changes on O3 formation, which provides explanation for the simultaneously alleviated O3 pollution and reduced NO2 in 2020 in Shanghai and northern Zhejiang, as well as the increased O3 in most counties before 2019 with reduced NO2 during October–March. The driving mechanism as revealed from this study for O3 and NO2 will be valuable for the O3 abatement through NO2 reduction at sub-county scale over YRD in China. [ABSTRACT FROM AUTHOR]

In the context of global warming, how to measure summer climate suitability at a local scale is important for meteorological services. Considering meteorological and ecological conditions, body comfort, and the atmospheric environment, an assessment method for summer climate suitability for Zhejiang Province is proposed. In this paper, a summer suitable index (SSI) for Zhejiang is calculated, including four secondary indices: a summer cool index (SCI), a comfort days index (CDI), a good air days index (GADI) and a vegetation cover index (VCI). Using a local evaluation criterion, summer climate suitable areas are distinguished objectively according to the SSI. The results show that especially suitable regions account for 4.97% of Zhejiang Province, very suitable regions account for 22.2%, suitable regions account for 39.58%, and general regions account for 33.25%. The summer climate suitable areas are located mainly in high mountains and hills and coastal island areas while plain areas cannot be considered a suitable destination for summer tourism. By comparison and discussion, the SSI is demonstrated to capture summer climate suitability well. In contrast to a fixed evaluation index, benchmark values obtained for the SSI depend on the local climate and the index is straightforward to apply. [ABSTRACT FROM AUTHOR]

In multiuser visible light communication (VLC) systems, many transmit precoding (TPC) techniques have been investigated to suppress multiuser interference. However, these conventional works restrict their modulation to the special case of zero mean, which inherently limits their application to some popular modulations associated with the non-zero mean in VLC, such as pulse position modulation (PPM). Since the modulation with non-zero mean leads to more intricate optical power constraints and design objective functions than the case of zero mean, the TPC design that can support a general modulation is still an open problem. In the paper, we conceive of a general solution of the TPC scheme combined with dimming control for multiuser VLC systems, which is capable of mitigating multiuser interference, while at the same time, achieving the desired dimming level. The proposed scheme is applicable to a wide range of modulations in VLC, such as pulse amplitude modulation (PAM), PPM, and so on. Simulation results demonstrate that the proposed scheme outperforms the traditional pseudo-inverse-based zero-forcing TPC in terms of bit error rate (BER). [ABSTRACT FROM AUTHOR]

Wind energy, as a vital renewable energy source, also plays a significant role in reducing carbon emissions and mitigating climate change. It is therefore of utmost necessity to evaluate ocean wind energy resources for electricity generation and environmental management. Ocean wind distribution around the globe can be obtained from satellite observations to compensate for limited in situ measurements. However, previous studies have largely ignored uncertainties in ocean wind energy resources assessment with multiple satellite data. It is against this background that the current study compares mean wind speeds (MWS) and wind power densities (WPD) retrieved from scatterometers (QuikSCAT, ASCAT) and radiometers (WindSAT) and their different combinations with National Data Buoy Center (NDBC) buoy measurements at heights of 10 m and 100 m (wind turbine hub height) above sea level. Our results show an improvement in the accuracy of wind resources estimation with the use of multiple satellite observations. This has implications for the acquisition of reliable data on ocean wind energy in support of management policies. [ABSTRACT FROM AUTHOR]

Conventional optical orthogonal frequency division multiplexing (OFDM) schemes, such as adaptively biased optical OFDM (ABO-OFDM) and hybrid asymmetrically clipped optical OFDM (HACO-OFDM), are unable to tap all the resources of the subcarriers and only achieve relatively high power efficiency. In this paper, a hybrid adaptive bias optical OFDM (HABO-OFDM) scheme for visible light communication (VLC) is proposed to improve spectral efficiency and power efficiency. In the proposed HABO-OFDM scheme, different optical OFDM components are combined for transmission at the same time, and the adaptive bias is designed to ensure the non-negativity, as well as obtaining significantly high power efficiency. Meanwhile, the implementation complexity of the HABO-OFDM receiver is notably lower than the conventional superimposed optical OFDM schemes. Simulation results show that the proposed HABO-OFDM scheme outperforms ABO-OFDM and HACO-OFDM in terms of both peak-to-average-power ratio (PAPR) and power efficiency. The PAPR performance of HABO-OFDM is about 3.2 dB lower than that of HACO-OFDM and 1.7 dB lower than that of ABO-OFDM. Moreover, we can see that the E b (e l e c) / N 0 required for HABO-OFDM to reach the BER target is lower than the other two schemes at the Bit rate/Normalized bandwidth range of 3.5 to 8.75, which means that the power efficiency of HABO-OFDM is higher in this range. [ABSTRACT FROM AUTHOR]

Due to the weak absorption of (CH3NH3)PbI3 in the communication regime, which restricts its optoelectronic applications, we design a adjustable dual-band perfect absorber based on the (CH3NH3)PbI3 to significantly enhance its absorption capability. Since the localized plasmon (LP) mode and surface plasmon (SP) mode are excited in the structure, which can both greatly enhance light absorption of the (CH3NH3)PbI3 layer, dual-band perfect absorption peaks are formed in the communication regime, and the absorption of (CH3NH3)PbI3 layer is increased to 43.1% and 64.2% at the dual-band absorption peaks by using finite-difference time-domain (FDTD) methods, respectively. By varying some key structural parameters, the dual-band absorption peaks of (CH3NH3)PbI3 can be separately shifted in a wide wavelength region. Moreover, the designed absorber can keep good performance under wide angles of incidence and manifested polarization correlation. Furthermore, not just for (CH3NH3)PbI3, the physical mechanism in this absorber can also be utilized to strengthen the absorption of other halide perovskites. [ABSTRACT FROM AUTHOR]

In order to maximize energy efficiency in heterogeneous networks (HetNets), a turbo Q-Learning (TQL) combined with multistage decision process and tabular Q-Learning is proposed to optimize the resource configuration. For the large dimensions of action space, the problem of energy efficiency optimization is designed as a multistage decision process in this paper, according to the resource allocation of optimization objectives, the initial problem is divided into several subproblems which are solved by tabular Q-Learning, and the traditional exponential increasing size of action space is decomposed into linear increase. By iterating the solutions of subproblems, the initial problem is solved. The simple stability analysis of the algorithm is given in this paper. As to the large dimension of state space, we use a deep neural network (DNN) to classify states where the optimization policy of novel Q-Learning is set to label samples. Thus far, the dimensions of action and state space have been solved. The simulation results show that our approach is convergent, improves the convergence speed by 60% while maintaining almost the same energy efficiency and having the characteristics of system adjustment. [ABSTRACT FROM AUTHOR]

With the rapid development of cloud computing and big data, traditional Vehicular Ad hoc Networks (VANETs) are evolving into the Internet of Vehicles (IoV). As an important communication technology in IoV, IEEE 802.11p protocols have been studied by many experts and scholars. In IEEE 802.11p, a node's backoff counter will be frozen when the channel is detected as busy. However, most studies did not consider the possibility of continuous backoff freezing when calculating delay. Thus, in this paper, we focus on the performance analysis of IEEE 802.11p for continuous backoff freezing. Specifically, we establish an analytical model to analyze the broadcast performance in the highway scene where vehicles can obtain traffic density from roadside units through Vehicle to Infrastructure (V2I) communications. We first calculate the relationship between vehicle density and the number of vehicles. Then, we derive the relationship between the number of vehicles and packet delay according to Markov chains. Next, we utilize the probability generating function (PGF) to transform traditional Markov chains into z domain under the situation of non-saturation. Finally, we employ the Mason formula to derive packet delay. As compared with the performance without considering the continuous backoff freezing, the simulation results have demonstrated that our analytical model is more reasonable. [ABSTRACT FROM AUTHOR]

In this paper, a novel iterative discrete estimation (IDE) algorithm, which is called the modified IDE (MIDE), is proposed to reduce the computational complexity in MIMO detection in uplink massive MIMO systems. MIDE is a revision of the alternating direction method of multipliers (ADMM)-based algorithm, in which a self-updating method is designed with the damping factor estimated and updated at each iteration based on the Euclidean distance between the iterative solutions of the IDE-based algorithm in order to accelerate the algorithm's convergence. Compared to the existing ADMM-based detection algorithm, the overall computational complexity of the proposed MIDE algorithm is reduced from O N t 3 + O N r N t 2 to O N t 2 + O N r N t in terms of the number of complex-valued multiplications, where Ntand Nr are the number of users and the number of receiving antennas at the base station (BS), respectively. Simulation results show that the proposed MIDE algorithm performs better in terms of the bit error rate (BER) than some recently-proposed approximation algorithms in MIMO detection of uplink massive MIMO systems. [ABSTRACT FROM AUTHOR]

Massive multiple-input-multiple-output (MIMO) is one of the key technologies in the fifth generation (5G) cellular communication systems. For uplink massive MIMO systems, the typical linear detection such as minimum mean square error (MMSE) presents a near-optimal performance. Due to the required direct matrix inverse, however, the MMSE detection algorithm becomes computationally very expensive, especially when the number of users is large. For achieving the high detection accuracy as well as reducing the computational complexity in massive MIMO systems, we propose an improved Jacobi iterative algorithm by accelerating the convergence rate in the signal detection process.Specifically, the steepest descent (SD) method is utilized to achieve an efficient searching direction. Then, the whole-correction method is applied to update the iterative process. As the result, the fast convergence and the low computationally complexity of the proposed Jacobi-based algorithm are obtained and proved. Simulation results also demonstrate that the proposed algorithm performs better than the conventional algorithms in terms of the bit error rate (BER) and achieves a near-optimal detection accuracy as the typical MMSE detector, but utilizing a small number of iterations. [ABSTRACT FROM AUTHOR]

Relay technology application becomes prevalent nowadays, as it can effectively extend the communication distance, especially for vehicular networks with a limited communication range. Combined with vehicular cloud (VC), transmission efficiency can be improved by offloading partial data. Hence, designing a vehicle relay algorithm and implementation embedded vehicle device is critical. In this paper, VC is considered to deal with the complexity computation in our proposed system model. Without a loss of generality, an end-to-end vehicle communication with one assisted vehicle is analyzed firstly on a transmission link based on VC. Here, the signal-to-noise ratio (SNR) on the receiving end and link outage probability is obtained to enhance the link reliability. The VC computing helps us further simplify computational complexity. Subsequently, an embedded vehicle-enabled device is designed to achieve the optimal path relay selection in realistic vehicular environments. In the functional device framework, we display an optimal path relay selection algorithm according to the link quality. Finally, the performance of the transmission link on the outage probability related with SNR is verified in the simulation results. Meanwhile, the effect of the relay gain is also analyzed. The application of a vehicle-enabled embedded device could improve the performance of vehicular networks. [ABSTRACT FROM AUTHOR]

In order to reduce the computational complexity of the inverse matrix in the regularized zero-forcing (RZF) precoding algorithm, this paper expands and approximates the inverse matrix based on the truncated Kapteyn series expansion and the corresponding low-complexity RZF precoding algorithm is obtained. In addition, the expansion coefficients of the truncated Kapteyn series in our proposed algorithm are optimized, leading to further improvement of the convergence speed of the precoding algorithm under the premise of the same computational complexity as the traditional RZF precoding. Moreover, the computational complexity and the downlink channel performance in terms of the average achievable rate of the proposed RZF precoding algorithm and other RZF precoding algorithms with typical truncated series expansion approaches are analyzed, and further evaluated by numerical simulations in a large-scale single-cell multiple-input-multiple-output (MIMO) system. Simulation results show that the proposed improved RZF precoding algorithm based on the truncated Kapteyn series expansion performs better than other compared algorithms while keeping low computational complexity. [ABSTRACT FROM AUTHOR]

With the proliferation of the Internet-of-Things (IoT), the users' trajectory data containing privacy information in the IoT systems are easily exposed to the adversaries in continuous location-based services (LBSs) and trajectory publication. Existing trajectory protection schemes generate dummy trajectories without considering the user mobility pattern accurately. This would cause that the adversaries can easily exclude the dummy trajectories according to the obtained geographic feature information. In this paper, the continuous location entropy and the trajectory entropy are defined based on the gravity mobility model to measure the level of trajectory protection. Then, two trajectory protection schemes are proposed based on the defined entropy metrics to protect the trajectory data in continuous LBSs and trajectory publication, respectively. Experimental results demonstrate that the proposed schemes have a higher level than the enhanced dummy-location selection (enhance-DLS) scheme and the random scheme. [ABSTRACT FROM AUTHOR]

Platooning strategy is an important component of autonomous driving technology. Autonomous vehicles in platoons are often equipped with a variety of on-board sensors to detect the surrounding environment. The abundant data collected by autonomous vehicles in platoons can be transmitted to the infrastructure through vehicle-to-infrastructure (V2I) communications using the IEEE 802.11 distributed coordination function (DCF) mechanism and then uploaded to the cloud platform through the Internet. The cloud platform extracts useful information and then sends it back to the autonomous vehicles respectively. In this way, autonomous vehicles in platoons can detect emergency conditions and make a decision in time. The characteristics of platoons would cause a fair-access problem in the V2I communications, i.e., vehicles in the platoons moving on different lanes with different velocities would have different resident time within the infrastructure's coverage and thus successfully send different amounts of data to the infrastructure. In this case, the vehicles with different velocities will receive different amounts of useful information from the cloud. As a result, vehicles with a higher velocity are more likely to suffer from a traffic accident as compared to the vehicles with a lower velocity. Hence, this paper considers the fair-access problem and proposes a fair-access scheme to ensure that vehicles with different velocities successfully transmit the same amount of data by adaptively adjusting the minimum contention window of each vehicle according to its velocity. Moreover, the normalized throughput of the proposed scheme is derived. The validity of the fair-access scheme is demonstrated by simulation. [ABSTRACT FROM AUTHOR]

Multi-platooning is an important management strategy for autonomous driving technology. The backbone vehicles in a multi-platoon adopt the IEEE 802.11 distributed coordination function (DCF) mechanism to transmit vehicles' kinematics information through inter-platoon communications, and then forward the information to the member vehicles through intra-platoon communications. In this case, each vehicle in a multi-platoon can acquire the kinematics information of other vehicles. The parameters of DCF, the hidden terminal problem and the number of neighbors may incur a long and unbalanced one-hop delay of inter-platoon communications, which would further prolong end-to-end delay of inter-platoon communications. In this case, some vehicles within a multi-platoon cannot acquire the emergency changes of other vehicles' kinematics within a limited time duration and take prompt action accordingly to keep a multi-platoon formation. Unlike other related works, this paper proposes a swarming approach to optimize the one-hop delay of inter-platoon communications in a multi-platoon scenario. Specifically, the minimum contention window size of each backbone vehicle is adjusted to enable the one-hop delay of each backbone vehicle to get close to the minimum average one-hop delay. The simulation results indicate that, the one-hop delay of the proposed approach is reduced by 12% as compared to the DCF mechanism with the IEEE standard contention window size. Moreover, the end-to-end delay, one-hop throughput, end-to-end throughput and transmission probability have been significantly improved. [ABSTRACT FROM AUTHOR]

This study investigates the superiority of cooperative broadcast transmission over traditional orthogonal schemes when applied in a downlink relaying broadcast channel (RBC). Two proposed cooperative broadcast transmission protocols, one with an amplify-and-forward (AF) relay, and the other with a repetition-based decode-and-forward (DF) relay, are investigated. By utilizing superposition coding (SupC), the source and the relay transmit the private user messages simultaneously instead of sequentially as in traditional orthogonal schemes, which means the channel resources are reused and an increased channel degree of freedom is available to each user, hence the half-duplex penalty of relaying is alleviated. To facilitate a performance evaluation, theoretical outage probability expressions of the two broadcast transmission schemes are developed, based on which, we investigate the minimum total power consumption of each scheme for a given traffic requirement by numerical simulation. The results provide details on the overall system performance and fruitful insights on the essential characteristics of cooperative broadcast transmission in RBCs. It is observed that better overall outage performances and considerable power gains can be obtained by utilizing cooperative broadcast transmissions compared to traditional orthogonal schemes. [ABSTRACT FROM AUTHOR]