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Previous studies reported that hemoprotein CYP450 catalyzed triclosan coupling is an “uncommon” metabolic pathway that may enhance toxicity, raising concerns about its environmental and health impacts. Hemoglobin, a notable hemoprotein, can catalyze endogenous phenolic amino acid tyrosine coupling reactions. Our study explored the feasibility of these coupling reactions for exogenous phenolic pollutants in plasma. Both hemoglobin and hemin were found to catalyze triclosan coupling in the presence of H₂O₂. This resulted in the formation of five diTCS-2 H, two diTCS-Cl-3 H, and twelve triTCS-4 H in phosphate buffer, with a total of nineteen triclosan coupling products monitored using LC-QTOF. In plasma, five diTCS-2 H, two diTCS-Cl-3 H, and two triTCS-4 H were detected in hemoglobin-catalyzed reactions. Hemin showed a weaker catalytic effect on triclosan transformation compared to hemoglobin, likely due to hemin dimerization and oxidative degradation by H₂O₂, which limits its catalytic efficiency. Triclosan transformation in the human plasma-like medium still occurs with high H₂O₂, despite the presence of antioxidant proteins that typically inhibit such transformations. In plasma, free H₂O₂ was depleted within 40 minutes when 800 µM H₂O₂ was added, suggesting a rapid consumption of H₂O₂ in these reactions. Antioxidative species, or hemoglobin/hemin scavengers such as bovine serum albumin, may inhibit but not completely terminate the triclosan coupling reactions. Previous studies reported that diTCS-2 H showed higher hydrophobicity and greater endocrine-disrupting effects compared to triclosan, which further underscores the potential health risks. This study indicates that hemoglobin and heme in human plasma might significantly contribute to phenolic coupling reactions, potentially increasing health risks.

Deep image coding (DIC) for hybrid application contexts has recently attracted significant research interest because of its potential to support both human and machine visual tasks. Since the regions of interest (ROI) are different for different application contexts, it is important to design an adaptive image coding mechanism in practical DIC. In this paper, we propose the first quantization-based adaptive DIC framework for hybrid contexts of image reconstruction and classification. This framework can be applied to upgrade existing fixed-rate DIC models into adaptive DIC for hybrid contexts. It consists of two key modules: a semantics-based ROI mask generation module and a module for generating ROI gain and inverse gain matrices. These matrices are used to control the quantization accuracy of different latent vector elements, thereby achieving encoding at different rates while prioritizing the reconstruction quality of the ROI. Moreover, we propose a five-stage training method for the quantization-based adaptive DIC model to optimize the rate-distortion-classification-perception (RDCP) tradeoff. Experiments over a wide rate range show that our method achieves superior RDCP tradeoff performance. Compared to the benchmark scheme BM-CHENG, the proposed algorithm improves the classification accuracy by an average of 15%. The average relative improvements on various metrics, such as natural image quality evaluator (NIQE), learned perceptual image patch similarity (LPIPS), and feature similarity index measure (FSIM), are about 22%, 47%, and 1%, respectively. The proposed algorithm is a promising candidate for fast adaptive coding with low-complexity constraints.

Dihydroxylated polybrominated diphenyl ethers (DiOH-PBDEs) could be the metabolites of PBDEs of some organisms or the natural products of certain marine bacteria and algae. OH-PBDEs may demonstrate binding affinity to thyroid hormone receptors (TRs) and can disrupt the functioning of the systems modulated by TRs. However, the thyroid hormone disruption mechanism of diOH-PBDEs remains elusive due to the absence of diOH-PBDEs standards. This investigation explores the potential disruptive effects of OH/diOH-PBDEs on thyroid hormones via competitive binding and coactivator recruitment with TRα and TRβ. At levels of 5000 nM and 25,000 nM, 6-OH-BDE-47 demonstrated significant recruitment of steroid receptor coactivator (SRC), whereas none of the diOH-PBDEs exhibited SRC recruitment within the range of 0.32–25,000 nM. AutoDock CrankPep (ADCP) simulations suggest that the conformation of SRC and TR–ligand complexes, particularly their interaction with Helix 12, rather than binding affinity, plays a pivotal role in ligand agonistic activity. 6,6′-diOH-BDE-47 displayed antagonistic activity towards both TRα and TRβ, while the antagonism of 3,5-diOH-BDE-100 for TRα and TRβ was concentration-dependent. 3,5-diOH-BDE-17 and 3,5-diOH-BDE-51 exhibited no discernible agonistic or antagonistic activities. Molecular docking analysis revealed that the binding energy of 3,3′,5-triiodo-L-thyronine (T3) surpassed that of OH/diOH-PBDEs. 3,5-diOH-BDE-100 exhibited the highest binding energy, whereas 6,6′-diOH-BDE-47 displayed the lowest. These findings suggest that the structural determinants influencing the agonistic and antagonistic activities of halogen phenols may be more intricate than previously proposed, involving factors beyond high-brominated PBDEs or hydroxyl group and bromine substitutions. It is likely that the agonistic or antagonistic propensities of OH/diOH-PBDEs are instigated by protein conformational changes rather than considerations of binding energy.

As the number of wireless applications and devices grows, higher standards for the quality of service and navigation performance of mobile networks are required. Numerous critical applications, including unmanned aerial vehicles, internet of things, digital twin, and military systems, require reliable communication and accurate navigation services. To meet these requirements, the development of the sixth generation (6G) network is necessary. 6G networks provide seamless 3-dimensional coverage in space–air–ground–sea area, as well as deep coupling of communication, sensing, and computation. 6G networks will be combined with low Earth orbit (LEO) satellites to construct a universal and intelligent integrated system of communication, sensing, and computing by utilizing the benefits of LEO satellites, such as miniaturization, modularity, large bandwidth, low latency, and wide area coverage. One of the critical construction tasks in this system is the integration of communication and navigation (ICAN), which can break the limitations of the global navigation satellite system, provide high-precision, robust navigation capability, and enable high-quality communication services. In this article, a comprehensive survey is presented for ICAN technologies toward LEO-enabled 6G networks (LEO-ICAN), including the framework design, system implementation, and key technologies. We also highlight the challenges and opportunities ahead faced by the LEO-ICAN system. Finally, the prospect development and future research trends are discussed, and a few ideas for practical and effective LEO-ICAN solutions are provided. This survey provides a reference for the theoretical design, technological innovation, and system implementation of LEO-ICAN, which is capable of coping with the demand of massive access and global seamless coverage in the upcoming 6G network era.

The traditional vehicular ad hoc network (VANET), which is evolving into the internet of vehicles (IoV), has drawn great attention for its enormous potential in road safety improvement, traffic management, infotainment service support, and even autonomous driving. IEEE 802.11p, as the vital standard for wireless access in vehicular environments, has been released for more than one decade and its evolution, IEEE 802.11bd, has also been released for a few months. Since the analytical models for the IEEE 802.11p/bd medium access control (MAC) play important roles in terms of performance evaluation and MAC protocol optimization, a lot of analytical models have been proposed. However, the existing analytical models are still not accurate as a result of ignoring some important factors of the MAC itself and real communication scenarios. Motivated by this, a novel analytical model is proposed, based on a novel two-dimensional (2-D) Markov chain model. In contrast to the existing studies, all the important factors are considered in this proposed model, such as the backoff freezing mechanism, retry limit, post-backoff states, differentiated packet arrival probabilities for empty buffer queue, and queue model of packets in the buffer. In addition, the influence of the capture effect under a Nakagami-m fading channel has also been considered. Then, the expressions of successful transmission, collided transmission, normalized unsaturated throughput, and average packet delay are all meticulously derived, respectively. At last, the accuracy of the proposed analytical model is verified via the simulation results, which show that it is more accurate than the existing analytical models.

Convolutional neural networks trained on object recognition derive inspiration from the neural architecture of the visual system in mammals, and have been used as models of the feedforward computation performed in the primate ventral stream. In contrast to the deep hierarchical organization of primates, the visual system of the mouse has a shallower arrangement. Since mice and primates are both capable of visually guided behavior, this raises questions about the role of architecture in neural computation. In this work, we introduce a novel framework for building a biologically constrained convolutional neural network model of the mouse visual cortex. The architecture and structural parameters of the network are derived from experimental measurements, specifically the 100-micrometer resolution interareal connectome, the estimates of numbers of neurons in each area and cortical layer, and the statistics of connections between cortical layers. This network is constructed to support detailed task-optimized models of mouse visual cortex, with neural populations that can be compared to specific corresponding populations in the mouse brain. Using a well-studied image classification task as our working example, we demonstrate the computational capability of this mouse-sized network. Given its relatively small size, MouseNet achieves roughly 2/3rds the performance level on ImageNet as VGG16. In combination with the large scale Allen Brain Observatory Visual Coding dataset, we use representational similarity analysis to quantify the extent to which MouseNet recapitulates the neural representation in mouse visual cortex. Importantly, we provide evidence that optimizing for task performance does not improve similarity to the corresponding biological system beyond a certain point. We demonstrate that the distributions of some physiological quantities are closer to the observed distributions in the mouse brain after task training. We encourage the use of the MouseNet architecture by making the code freely available.

Exposure to antibiotics can result in not only ecotoxicity on aquatic organisms but also the development of antibiotic resistance. In the study, the ecotoxicity data and minimum inhibitory concentrations of the antibiotics were screened to derive predicted no-effect concentrations of ecological (PNECeco) and resistance development risks (PNECres) for 36 antibiotics in fresh surface waters of China. The derived PNECeco and PNECres values were ranged from 0.00175 to 2351 μg/L and 0.037–50 μg/L, respectively. Antibiotic ecological and resistance development risks were geographically widespread, especially in the Yongding River, Daqing River, and Ziya River basins of China. Based on the risk quotients, 11 and 14 of 36 target antibiotics were at high ecological risks and high resistance development risks in at least one basin, respectively. The higher tiered assessments provided more detailed risk descriptions by probability values and β-lactams (penicillin and amoxicillin) were present at the highest levels for ecological and resistance development risks. Although there was uncertainty based on the limited data and existing methods, this study can indicate the overall situation of the existing risk levels and provide essential insights and data supporting antibiotic management.

The ecological risks of nonylphenol (NP) and tetrabromobisphenol A (TBBPA) have received continued attention owing to their large consumption, frequently detection, adverse effects on the reproductive fitness, and lack of risk assessment technical systems. The geometric mean of the median concentrations of NP in the 22 surface waters was 0.278 μg/L, and TBBPA in the seven surface waters was 0.014 μg/L in China. The species sensitivity distribution (SSD) models were augmented by extrapolated reproductive toxicity data of native species to reduce uncertainty. The SSD models and the hazardous concentrations for 5% of species exhibited good robustness and reliability using the bootstrap method and minimum sample size determination. The acute and reproductive predicted no-effect concentrations (PNECs) were derived as 9.88 and 0.187 μg/L for NP, and 56.6 and 0.0878 μg/L for TBBPA, respectively. The risk quotients indicated that 11 of 22 locations for NP, and 3 of 7 locations for TBBPA were at high ecological risk levels based on the reproductive PNECs. Furthermore, the higher tier ecological risk assessment (ERA) based on potential affected fraction and joint probability curves indicated that the ecological risks in the four of above locations needed further concern. The ERA based on both the acute and reproductive toxicity is essential for assessing the ecological risks of NP and TBBPA, otherwise using acute PNECs only may result in an underestimation of ecological risk. The developed tiered ERA method and its framework can provide accurate, detailed, quantitative, locally applicable, and economically technical support for ERA of typical endocrine-disrupting chemicals in China.

Vehicular ad hoc networks (VANETs) have recently drawn a large amount of attention because of their enormous potential in road safety improvement and traffic management as well as infotainment service support. As the standard of medium access control (MAC) and physical (PHY) layers for VANETs, IEEE 802.11p has been proposed for more than a decade. Though performance analyses of IEEE 802.11p MAC have been performed, the existing analytical methods still need to be improved. In this paper, to assess the saturated throughput and the average packet delay of IEEE 802.11p MAC in VANETs, a two-dimensional (2-D) Markov model is introduced by considering the capture effect under Nakagami-m fading channel. Moreover, the closed-form expressions of successful transmission, collided transmission, saturated throughput, and average packet delay are carefully derived. Finally, the simulation results are demonstrated to verify the accuracy of the proposed analytical model, which also proves that this analytical model is more precise than the existing ones in terms of saturated throughput and average packet delay.

Phthalates (PAEs), bisphenol A (BPA), and oestrogenic compounds have become major concerns due to their endocrine-disrupting effect. However, few studies related to the occurrence of PAEs, BPA, and oestrogen in food and compost from different growth age livestock have been conducted. In this study, faeces, urine and food samples were collected from a typical livestock (cow) and a special livestock (pigeon) from concentrated animal feeding operations (CAFOs). The daily total oestrogen excretion of a single cow ranged from 192 μg/day to 671 μg/day, which was significantly higher than that of a single pigeon (0–0.01 μg/day). Conjugated oestrogens represented 22.0–46.0% of the total oestrogens excreted from cow faeces and 80.7–91.8% of those from cow urine, indicating that the form of the excreted oestrogens depends on the livestock species and type of excrement. BPA was all detected in all livestock manure and food, and the concentration in pigeon was 9.2–40.2 ng/g and 23.1 ng/g respectively, while that in cattle was 50.5–72.0 ng/g and 41.1 ng/g respectively. The results indicated that the food is significant sources of BPA entering the process of cow and pigeon breeding. Diethyl phthalate (DEP) was detected at high frequency in pigeon faeces samples, suggesting that pigeons were highly exposed to these plasticisers. The total oestradiol equivalent quantity (EEQt) of livestock origin in aquatic environments was estimated to be 2.99 ng/L, which was higher than the baseline hazard value (1 ng/L) (Xu et al., 2018). The study provides data on the emissions and sources of PAEs, BPA, and oestrogenic compounds from different livestock in CAFOs and demonstrates that food is a significant source of BPA entering livestock.

In this paper, we investigate the sum-rate maximization of cellular users (CUs) and device-to-device (D2D) pairs for the D2D communications underlaying cellular networks over the Nakagami-m fading channel. We consider a resource-abundant scenario where the number of CUs is more than that of D2D pairs and discuss the joint optimization of signal-to-interference-plus-noise ratio (SINR) thresholds and CU-D2D pairing. We formulate the problem as mixed-integer non-linear programming, which is NP-hard in general. To solve the problem, we propose a two-step approach. First, we add virtual D2D pairs to make the number of D2D pairs equal to that of CUs and derive the near-optimal SINR threshold for each possible CU-D2D pairing by the simulated annealing algorithm. Second, the optimal CU-D2D pairing can be obtained by the Hungarian (HG) algorithm. The simulation results show that: 1) the proposed SINR policy outperforms the other policies by about 11.3%-63.4% and 2) compared with several state-of-the-art resource allocation policies, HG allocation can achieve an average sum-rate improvement of 10.9%-72.8%.

Since broadcast communication is considered the highly appropriate technique for the dissemination of safety messages in vehicular ad hoc networks (VANETs), it is vital to design a high-efficient medium access control (MAC) protocol for vehicles accessing wireless channel. However, the characteristics of VANETs, such as high-velocity vehicles, highly dynamic topology and very unstable communication link, lower the performance of existing MAC protocols. In this paper, we propose a novel Capture-aware TDMA-based MAC (CT-MAC) protocol, which can better utilize the channel resource than the existing MAC protocols by setting the optimal frame length with taking capture effect into account. To obtain the realistically optimal frame length, the closed form expression of probability of capture effect is derived under Nakagami-m fading channel which is proper to model the small-scale fading channel in VANETs. Besides, a discrete Markov chain is introduced to analyze the impact of capture effect on channel utilization. The theoretical analyses and the simulation results show that the reliability of broadcast and the efficiency of channel utilization are significantly improved.

Antibiotics in aquatic environments at high concentrations and sub-inhibitory concentrations potentially select for the evolution of antibiotic resistant genes (ARGs), posing a potential risk to aquatic ecological safety. Our knowledge of the temporal and successive dynamics of ARGs and bacterial community under the selective pressure of antibiotics in natural water-sediment system was limited. This study used a 120-d operating hydrodynamic mesocosm to explore the temporal dynamics of ARGs in water-sediment systems, and the main selective mechanisms following the attenuation and transport of 14 commonly used antibiotics. Under the selective pressures by antibiotics, ARGs propagated transiently, and persisted after antibiotic removal; the bacterial community structures likewise changed. Mantel test and network analysis indicated that ARGs significantly correlated with the bacterial community in the water and surface sediments. Structural equation model (SEM) further revealed that the evolution of ARGs was mainly due to the direct effect of the change in bacterial community and horizontal gene transfer (HGT) via the class 1 integron-integrase gene (intI1), but antibiotics indirectly influenced ARG profiles. The migration of ARGs in deep layer sediments was not related to the bacterial community and intI1, but may be explained by antibiotic selective effects and ARG transformation. Keywords: ARGs, Horizontal gene transfer, intI1, Selective effect, Migration, Flume study

Per- and polyfluoroalkyl substances (PFASs) are a class of highly fluorinated aliphatic compounds that are persistent and bioaccumulate, posing a potential threat to the aquatic environment. The electroplating industry is considered to be an important source of PFASs. Due to emerging PFASs and many alternatives, the acute toxicity data for PFASs and their alternatives are relatively limited. In this study, a QSAR–ICE–SSD composite model was constructed by combining quantitative structure-activity relationship (QSAR), interspecies correlation estimation (ICE), and species sensitivity distribution (SSD) models in order to obtain the predicted no-effect concentrations (PNECs) of selected PFASs. The PNECs for the selected PFASs ranged from 0.254 to 6.27 mg/L. The ΣPFAS concentrations ranged from 177 to 983 ng/L in a river close to an electroplating industry in Shenzhen. The ecological risks associated with PFASs in the river were below 2.97 × 10−4.

As a key technology of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs) have been promising to provide safety and infotainment for drivers and passengers. To support different applications about traffic safety, traffic efficiency, autonomous driving and entertainment, it is important to investigate how to effectively deliver content in VANETs. Since it takes resources such as bandwidth and power for base stations (BSs) or roadside units (RSUs) to deliver content, the optimal pricing strategy for BSs and the optimal caching incentive scheme for RSUs need to be studied. In this paper, a framework of content delivery is proposed first, where each moving vehicle can obtain small-volume content files from either the nearest BS or the nearest RSU according to the competition among them. Then, the profit models for both BSs and RSUs are established based on stochastic geometry and point processes theory. Next, a caching incentive scheme for RSUs based on Stackelberg game is proposed, where both competition sides (i.e., BSs and RSUs) can maximize their own profits. Besides, a backward introduction method is introduced to solve the Stackelberg equilibrium. Finally, the simulation results demonstrate that BSs can obtain their own optimal pricing strategy for maximizing the profit as well as RSUs can obtain the optimal caching scheme with the maximum profit during the content delivery.

Location-based services for smartphones are becoming more and more popular. The core of location-based services is how to estimate a user’s location. An INS/floor-plan indoor localization system, using the Firefly Particle Filter (FPF), is proposed to estimate a user’s location. INS includes an attitude angle module, a step length module and a step counting module. In the step length module, we propose a hybrid step length model. The proposed step length algorithm reasonably calculates a user’s step length. Because of sensor deviation, non-orthogonality and the user’s jitter, the main bottleneck for INS is that the error grows over time. To reduce the cumulative error, we design cascade filters including the Kalman Filter (KF) and FPF. To a certain extent, KF reduces velocity error and heading drift. On the other hand, the firefly algorithm is used to solve the particle impoverishment problem. Considering that a user may not cross an obstacle, the proposed particle filter is proposed to improve positioning performance. Results show that the average positioning error in walking experiments is 2.14 m.

User-in-the-loop (UiL) content delivery is a recently proposed scheme for personalized content retrieval over mobile communication networks. It is a promising scheme that can better manage the overall user quality-of-experience (QoE) throughout the entire content retrieval process. The performance of the scheme, however, has only been investigated in a simplified system model that assumed synchronized user behavior, inflexible delay constraint, and identical quality-of-service (QoS) requirement among users. This paper studies the performance of UiL content delivery scheme in a generalized and realistic system model with asynchronous user behavior, flexible outage delay constraint, and customized user QoS. Heuristic algorithms and theoretical bounds are investigated for the UiL content delivery problem. The proposed system is shown to be effective in managing the user QoE in generalized practical scenarios.

For smartphone indoor localization, an INS/WiFi hybrid localization system is proposed in this paper. Acceleration and angular velocity are used to estimate step lengths and headings. The problem with INS is that positioning errors grow with time. Using radio signal strength as a fingerprint is a widely used technology. The main problem with fingerprint matching is mismatching due to noise. Taking into account the different shortcomings and advantages, inertial sensors and WiFi from smartphones are integrated into indoor positioning. For a hybrid localization system, pre-processing techniques are used to enhance the WiFi signal quality. An inertial navigation system limits the range of WiFi matching. A Multi-dimensional Dynamic Time Warping (MDTW) is proposed to calculate the distance between the measured signals and the fingerprint in the database. A MDTW-based weighted least squares (WLS) is proposed for fusing multiple fingerprint localization results to improve positioning accuracy and robustness. Using four modes (calling, dangling, handheld and pocket), we carried out walking experiments in a corridor, a study room and a library stack room. Experimental results show that average localization accuracy for the hybrid system is about 2.03 m.

Framed slotted aloha (FSA) is a multiple access protocol widely used in wireless communication for its simplicity and effectivity. The theoretical maximum channel utilization of FSA is approximately equal to 0.37 irrespective of the capture effect. In fact, the capture effect is a common phenomenon in wireless communication, which can increase the channel utilization. In this paper, we derive the closed-form expressions of capture probabilities under Rayleigh, Rician and Nakagami-m fading channels, respectively, and further give the optimal frame length which maximizes the channel utilization in the FSA-based networks. The numerical results are given for indicating the capture probabilities under different fading channels and their impacts on the optimal frame length and the maximum channel utilization.

The deployment density and computational power of small base stations (BSs) are expected to increase significantly in the next generation mobile communication networks. These BSs form the mobile edge network, which is a pervasive and distributed infrastructure that can empower a variety of edge/fog computing applications. This paper proposes a novel edge-computing application called explicit caching, which stores selective contents at BSs and exposes such contents to local users for interactive browsing and download. We formulate the explicit caching problem as a joint content recommendation, caching, and delivery problem, which aims to maximize the expected user quality-of-experience (QoE) with varying degrees of cross-layer sensing capability. Optimal and effective heuristic algorithms are presented to solve the problem. The theoretical performance bounds of the explicit caching system are derived in simplified scenarios. The impacts of cache storage space, BS backhaul capacity, cross-layer information, and user mobility on the system performance are simulated and discussed in realistic scenarios. Results suggest that, compared with conventional implicit caching schemes, explicit caching can better exploit the mobile edge network infrastructure for personalized content dissemination.

Personalized content retrieval service has become a major information service that consumes a large portion of mobile Internet traffic. Joint content recommendation and delivery is a promising design philosophy that could effectively improve the overall user experience with personalized content retrieval services. Existing research mostly focused on a push-type design paradigm called proactive caching, which, however, has multiple inherent drawbacks such as high device cost and low energy efficiency. This paper proposes a novel, interactive joint content recommendation and delivery system as an alternative to overcome the drawbacks of proactive caching systems. We present several optimal and heuristic algorithms for the proposed system and analyze the system performance in terms of user interest and transmission outage probability. Some theoretical performance bounds of the system are also derived. The effectiveness of the proposed system and algorithms is validated by simulation results.

A novel method for solving Doppler ambiguous problem based on compressed sensing (CS) theory is proposed in this paper. A pulse train with the random and sparse transmitting time is transmitted. The received signals after matched filtering can be viewed as randomly sparse sampling from the traditional fixed-pulse repetition frequency (PRF) echo signals. The whole target echo could be reconstructed via CS recovery algorithms. Through refining the sensing matrix, which is equivalent to increase the sampling frequency of target characteristic, the Doppler unambiguous range is enlarged. In particular, Complex Approximate Message Passing (CAMP) algorithm is developed to estimate the unambiguity Doppler frequency. Cramer-Rao lower bound expressions are derived for the frequency. Numerical simulations validate the effectiveness of the proposed method. Finally, compared with traditional methods, the proposed method only requires transmitting a few sparse probing pulses to achieve a larger Doppler frequency unambiguous range and can also reduce the consumption of the radar time resources.

Ti doped Bi2O3 (TDB) and Ag ion modified Ti doped Bi2O3 (Ag@TDB) photocatalysts were prepared by framework replacement synthesis method with different Ag loadings (0.05, 0.3, 0.75, and 1.0 mol/L AgNO3). The structural properties of the prepared catalysts were studied by scanning electron microscope (SEM), X-ray diffraction (XRD), BET surface area, and UV/Vis diffuse reflectance (DRS). The XRD spectra of the Ti doped Bi2O3 calcined at 650°C showed the diffraction peaks of a mixture of Bi12TiO20 and Bi4Ti3O12, with bits of mixed crystallite consisting of TiO2 and B2O3. A high blue shift in the range 650–550 nm was detected in the DRS band. This blue shift increased with the decreasing Ag content. The photocatalytic activities of the catalysts were evaluated for the degradation of crystal violet (CV) under UV light irradiation. The results indicated that the degradation rate of CV by using 1.0 mol/L AgNO3 doped bismuth titanate composite photocatalyst (1.0 Ag@TDB) was 1.9 times higher than that by using the bare Ti doped Bi2O3 photocatalyst. The higher activity of Ag@TDB is due to the enhancement of electron-hole pair separation by the electron trapping of silver particles.

The integration of ad hoc device-to-device (D2D) communications and open-access small cells can result in a networking paradigm called hybrid the ad hoc network, which is particularly promising in delivering delay-tolerant data. The capacity-delay performance of hybrid ad hoc networks has been studied extensively under a popular framework called scaling law analysis. These studies, however, do not take into account aspects of interference accumulation and queueing delay and, therefore, may lead to over-optimistic results. Moreover, focusing on the average measures, existing works fail to give finer-grained insights into the distribution of delays. This paper proposes an alternative analytical framework based on queueing theoretic models and physical interference models. We apply this framework to study the capacity-delay performance of a collaborative cellular D2D network with coverage sensing and two-hop relay. The new framework allows us to fully characterize the delay distribution in the transform domain and pinpoint the impacts of coverage sensing, user and base station densities, transmit power, user mobility and packet size on the capacity-delay trade-off. We show that under the condition of queueing equilibrium, the maximum throughput capacity per device saturates to an upper bound of 0.7239 λ b / λ u bits/s/Hz, where λ b and λ u are the densities of base stations and mobile users, respectively.