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In this paper, zirconium-based MOF (Zr-MOFs) materials, namely UIO-66, UIO-66-NH2, GMA-UIO-66 and NB-UIO-66, were selected as fillers to enhance the mechanical properties of polydicyclopentadiene (PDCPD) nanocomposites, and Zr-MOFs/PDCPD nanocomposites were prepared by in situ polymerization. The functional groups and morphology of Zr-MOFs were characterized by Fourier transform infrared (FT-IR), X-ray diffraction (XRD) and field emission scanning electron microscopy (SEM). The mechanical properties of Zr-MOFs/PDCPD composites were studied by tensile toughness, notched impact strength and bending strength test. Furthermore, the optimum Zr-MOFs loading was determined. The results show that when the mass fraction of NB-UIO-66 is 0.4%, the composites' tensile toughness, flexural strength, impact strength and heat distortion temperature (HDT) are simultaneously increased by 47.3%, 37.5%, 119.4%, and 59.2% respectively, compared with the pure PDCPD, which synergistically enhances the mechanical properties. [ABSTRACT FROM AUTHOR]

Drought stress is one of the major abiotic stresses that limit grape growth and yield. Brassinosteroids (BRs) are a class of phytohormones essential for plant growth, development, and adaptation to environmental stress. This study aimed to reveal the physiological and biochemical mechanisms of exogenous BRs in alleviating the drought stress in grapevines. Two-year-old grape seedlings (Vitis vinifera L.) were sprayed with 24-epibrassinolide (EBR), a synthetic analog of BRs, and then subjected to drought treatment. The results showed that exogenous EBR significantly mitigated the reduction of photosynthetic pigment contents and photosystem II efficiency and decreased the damage to chloroplasts when grape seedlings were subjected to drought stress. Drought stress resulted in the accumulation of reactive oxidative species (ROS) and an increase in lipid peroxidation. A reduction in oxidative damage was observed in EBR-pretreated plants, which was probably due to the elevated antioxidant system. Exogenous EBR improved the activities of superoxide dismutase (14%), catalase (18%), peroxidase (17%), and ascorbate peroxidase (9%), and promoted the accumulation of ascorbic acid (10%) and glutathione (7%) under drought stress. EBR pretreatment also promoted autophagic activity, which contributed to the degradation of damaged chloroplasts. Moreover, EBR pretreatment increased the concentrations of abscisic acid, jasmonic acid, auxin, and gibberellic acid. Taken together, exogenous EBR could ameliorate the deleterious effects of drought stress by up-regulating photosynthetic capacity, antioxidant system, autophagic activity, and hormone concentrations. • EBR alleviated drought-induced photosynthesis inhibition in grapevines. • EBR increased AsA and GSH contents by modulating related metabolic genes under drought. • EBR promoted the expression of VvATGs and the formation of autophagosomes under drought. • EBR improved the contents of ABA, JA, IAA, and GA 3 under drought. [ABSTRACT FROM AUTHOR]

Metabolic dysfunction-associated steatotic liver disease (MASLD) has become one of the most prevalent liver diseases worldwide, and its occurrence is strongly associated with obesity, insulin resistance (IR), genetics, and metabolic stress. Ranging from simple fatty liver to metabolic dysfunction-associated steatohepatitis (MASH), even to severe complications such as liver fibrosis and advanced cirrhosis or hepatocellular carcinoma, the underlying mechanisms of MASLD progression are complex and involve multiple cellular mediators and related signaling pathways. Pattern recognition receptors (PRRs) from the innate immune system, including Toll-like receptors (TLRs), C-type lectin receptors (CLRs), NOD-like receptors (NLRs), RIG-like receptors (RLRs), and DNA receptors, have been demonstrated to potentially contribute to the pathogenesis for MASLD. Their signaling pathways can induce inflammation, mediate oxidative stress, and affect the gut microbiota balance, ultimately resulting in hepatic steatosis, inflammatory injury and fibrosis. Here we review the available literature regarding the involvement of PRR-associated signals in the pathogenic and clinical features of MASLD, in vitro and in animal models of MASLD. We also discuss the emerging targets from PRRs for drug developments that involved agent therapies intended to arrest or reverse disease progression, thus enabling the refinement of therapeutic targets that can accelerate drug development. [Display omitted] • PRR signaling is contributed to the pathogenesis for MAFLD. • TLRs、CLRs、NLRs、RLRs and DNA receptors are family members of PRR that involved in the occurrence of liver-related diseases. • The design of drugs targeting the PRR signaling system has show the potential therapeutic effects in the prevention and treatment of MASLD. [ABSTRACT FROM AUTHOR]

• Methyl jasmonate (MeJA) diminished the accumulation of ROS under drought stress. • MeJA improved the photosynthetic capacity and the contents of starch and sucrose. • MeJA promoted nitrogen assimilation and proline accumulation. Drought stress is recognized as one of the foremost abiotic stresses for worldwide agriculture. Methyl jasmonate (MeJA) is a vital phytohormone that is involved in plant growth, development, and stress adaptation. This study aimed to investigate the influence of exogenous MeJA on carbon and nitrogen metabolism in grapevine leaves under drought stress. Two-year-old grape cuttings (Vitis vinifera L.) were foliar sprayed with either 100 μM MeJA solution or distilled water and then exposed to drought stress. The results showed that exogenous MeJA increased the activities of superoxide dismutase (21 %) and catalase (16 %), resulting in decreased accumulation of reactive oxygen species. Drought stress critically disturbed the processes of photosynthesis, sucrose and starch metabolism, nitrogen assimilation, and amino acid metabolism. MeJA pretreatment improved the photosynthetic capacity and decreased the activities of sucrose synthase (31 %), acid invertase (15 %), and neutral invertase (27 %), thereby improving the accumulation of starch (10 %) and sucrose (90 %). In addition, MeJA pretreatment promoted nitrogen assimilation under drought stress. An increase in activities of nitrate reductase (60 %) and glutamine synthetase (13 %), and a decrease in NH 4 + content was observed. Meanwhile, the MeJA application promoted the accumulation of proline and γ-aminobutyric acid, which contributed to the osmotic adjustment and ROS scavenging. In conclusion, exogenous MeJA could promote drought tolerance of grapevines by alleviating oxidative damage and regulating carbon and nitrogen metabolism. [ABSTRACT FROM AUTHOR]

In order to reduce the downlink training overhead of mmWave communications, we propose a novel downlink beamforming strategy using the uplink sub-6GHz channel and downlink mmWave pilots that are sent from a few active antennas. Specifically, we design a novel dual-input neural network architecture, called FusionNet, to merge the sub-6GHz channel and the channel of a few active mmWave antennas. The proposed fusion model could intelligently adjust the attention paid (by the neural network) for sub-6GHz channel and mmWave channel by an attention mechanism. The output of the FusionNet represents the probability for each beam being the optimal one. We also propose an antenna selection model that can choose better active antennas to send the downlink pilots, in which the gradient of antenna selection vector is approximated by that of an antenna probability vector. Simulation results demonstrate the superior performance of the proposed strategy compared to the existing one that purely relies on the sub-6GHz information or compared to the shallow model that directly adds uniform pilots. [ABSTRACT FROM AUTHOR]

Channel covariance matrix (CCM) is one critical parameter for designing the communications systems. In this paper, a novel framework of the deep learning (DL) based CCM estimation is proposed that exploits the perception of the transmission environment without any channel sample or the pilot signals. Specifically, as CCM is affected by the user’s movement, we design a deep neural network (DNN) to predict CCM from user location and user speed, and the corresponding estimation method is named as ULCCME. A location denoising method is further developed to reduce the positioning error and improve the robustness of ULCCME. For cases when user location information is not available, we propose an interesting way that uses the environmental 3D images to predict the CCM, and the corresponding estimation method is named as SICCME. Simulation results show that both the proposed methods are effective and will benefit the subsequent channel estimation. [ABSTRACT FROM AUTHOR]

Purpose: Pleiotrophin (PTN) is a heparin-binding growth-associated molecule and expressed in ameloblasts and odontoblasts throughout tooth maturation. Our previous study has shown that PTN expressed more than 20-fold higher in dental tissue than dental stem cells. However, the role of PTN on proliferation and osteo/dentinogenesis of dental pulp stem cells (DPSCs) is unclear. The purpose of the present study was to investigate the role of PTN on the DPSCs' function. Methods: DPSCs were isolated from human third molars. Short hairpin RNAs (shRNAs) was used to knock down the PTN expression in DPSCs. Real-time RT-PCR, alizarin red staining, quantitative calcium analysis, in vivo transplantation and cell counting kit-8 (CCK8) assay were used to study the function of DPSCs. Possible mechanism was studied by RNA sequencing. Results: After PTN depletion, ALP activity and mineralization ability of DPSCs decreased. Expression of DMP-1 and BSP weakened. Proliferation of DPSCs at 48 h and 72 h was inhibited. Furthermore, 50 pg/mL PTN recombinant protein rescued the impaired osteo/dentinogenic differentiation potential and proliferation ability caused by PTN depletion. In addition, RNA sequencing showed 221 genes were downregulated and 233 genes upregulated in PTN depleted DPSCs. Several genes including BMP2 and IGFBP5 might be associated with PTN function on the DPSCs. P53 and the AMPK signaling pathways were involved. LncRNA analysis displayed 47 significantly upregulated lncRNA and 31 downregulated lncRNA comparing PTN depleted DPSCs with the control. Conclusion: Our research demonstrated that PTN has a positive role in maintaining DPSCs proliferation and osteo/dentinogenic differentiation potential. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRs) are potential therapeutic targets for tumors. The aims of the present study were to investigate the regulatory effects of miR-34a on the proliferation, apoptosis and chemosensitivity of retinoblastoma (RB) cells, and to identify the possible underlying mechanism involving Notch1. It was found that miR-34a was downregulated, and Notch1 was upregulated in HXO-RB44 and Y79 cells. In addition, Notch1 was identified to be a target gene of miR-34a, which could be downregulated by the increased expression of miR-34a. It was demonstrated that miR-34a upregulation and Notch1 downregulation significantly inhibited proliferation, promoted apoptosis and enhanced the carboplatin sensitivity of HXO-RB44 and Y79 cells. The transfection of miR-34a mimics + Notch1 siRNA further enhanced the above anti-tumor responses in HXO-RB44 and Y79 cells. Collectively, the present results suggested that miR-34a may negatively regulate Notch1 expression and may be a potential therapeutic target for RB. [ABSTRACT FROM AUTHOR]

The molecular configuration optimization is crucial for accurately controlling the intermolecular interactions of organic conjugates. Herein, with the purpose to integrate spherical geometry and optoelectronic properties, the first phosphine oxide (PO) bridge‐ring host 5,10‐[1,2]benzenophosphanthrene 5,10‐dioxide (BPAO2) with phosphorus as bridgehead atom is demonstrated. The sphere‐like paddle‐wheel configuration of BPAO2 gives rise to the highly ordered layer‐by‐layer packing mode, owing to its single molecular orientation, which provides the weak π–π interactions in each layer and hydrogen bond networks between layers. These limited but sufficient interactions are preserved in dilute solution and vacuum‐evaporated film, balancing the charge transportation and the quenching suppression. As consequence, its blue thermally activated delayed fluorescence (TADF) diodes achieve the record‐low turn‐on voltage as 2.3 V, which is remarkably below blue photon energy (≈2.6 eV), and the power efficiency up to ≈70 lm W−1. This work demonstrates the great potential of hetero bridge‐ring systems for optoelectronic applications. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) millimeter wave (mmWave) communication is a key technology for next generation wireless networks. One of the consequences of utilizing a large number of antennas with an increased bandwidth is that array steering vectors vary among different subcarriers. Due to this effect, known as beam squint, the conventional channel model is no longer applicable for mmWave massive MIMO systems. In this paper, we study channel estimation under the resulting non-standard model. To that aim, we first analyze the beam squint effect from an array signal processing perspective, resulting in a model which sheds light on the angle-delay sparsity of mmWave transmission. We next design a compressive sensing based channel estimation algorithm which utilizes the shift-invariant block-sparsity of this channel model. The proposed algorithm jointly computes the off-grid angles, the off-grid delays, and the complex gains of the multi-path channel. We show that the newly proposed scheme reflects the mmWave channel more accurately and results in improved performance compared to traditional approaches. We then demonstrate how this approach can be applied to recover both the uplink as well as the downlink channel in frequency division duplex (FDD) systems, by exploiting the angle-delay reciprocity of mmWave channels. [ABSTRACT FROM AUTHOR]

Background. The aim of this study was to assess the retinal and choroidal microvasculature features using optical coherence tomography angiography (OCTA) in patients with retinitis pigmentosa (RP). Methods. This study was a meta-analysis of relevant published studies that were included after a comprehensive search of PubMed, Embase, Cochrane Library, and Web of Science databases. Mean difference (MD) with a 95% confidence interval was used to assess continuous variable outcomes. Heterogeneity was evaluated using the chi-squared test based on the values of P and I2. Results. Seven studies were included in this meta-analysis. The vessel density values measured in the superficial and deep foveal zones of RP patients using OCTA were significantly lower than the recorded values in the control groups (MD = −3.58, P=0.04; MD = −4.93, P=0.02, respectively). The superficial and deep parafoveal vessel density values measured with OCTA were also significantly lower in RP patients than in control groups (MD = −9.09, P<0.00001; MD = −10.74, P<0.00001, respectively); for choriocapillaris vessel density, there was no statistically significant difference between RP patients and controls (MD = −1.33, P=0.09). The deep foveal avascular zone (FAZ) was significantly larger in RP patients than in controls (MD = 0.15, P=0.01), whereas there was no significant difference in the superficial foveal avascular zones in the two groups (MD = 0.08, P=0.11). Conclusions. We showed that retinal and choroidal vessels were attenuated in RP patients. Additionally, we revealed that the FAZ was larger in RP patients, especially the deep FAZ. OCTA may become a useful modality in the diagnosis and monitoring of patients with RP. [ABSTRACT FROM AUTHOR]

In recent years, unmanned aerial vehicle (UAV) communication technology has played an important role in both military and civilian applications. However, with the rapid development of military equipment, the execution efficiency of single UAVs is often limited, for which complex combat missions cannot be completed well. Therefore, UAV swarm has become an important research trend in the field of UAVs. In this paper, we consider the problem of channel estimation and self-positioning for the UAV swarm, where multiple small UAVs are displaced by arbitrarily unknown displacements due to the dynamic moving. To explore the physical characteristics of UAV swarm, the parameters of the channel are decomposed into the direction of arrival (DOA) information, the relative position information, and the channel gain information. Utilizing the rank reduction (RARE) estimator, DOAs of the different target users can be estimated efficiently, regardless of the position of the UAVs. After obtaining the DOA information, we estimate the channel gain information using small amount of training resources, which significantly reduces the training overhead and the feedback cost. Moreover, the unknown displacements among UAVs can be self-recovered from the mixed integer nonlinear programming (MINLP). To reduce the computational complexity, we develop both the sphere decoding (SD) and the least square (LS) based methods. The deterministic Cramér-Rao bound (CRB) of the self-positioning estimation is derived in closed-form. Finally, numerical examples are provided to corroborate the proposed studies. [ABSTRACT FROM AUTHOR]

Native microorganisms on wine grape surface contribute to regional wine characteristics and quality. The Xinjiang Uygur Autonomous Region in northwest China is one of the eight main wine-producing areas in China. To investigate the relationship between the microbial community structure of wine grape epidermises and environmental conditions, 16S rDNA and ITS sequences of 48 wine grape samples from four wine grape cultivars and six wine-growing regions in Xinjiang were sequenced, based on Illumina high-throughput sequencing technology. A total of 691 operational taxonomic units (OTUs) in 16 bacterial phyla and 349 OTUs in three fungal phyla were identified. Among them, Proteobacteria and Ascomycota were the predominant bacteria and fungi, respectively. Canonical correspondence analysis indicated that bacterial community diversity was largely related to altitude, latitude and longitude, while that of the fungi was closely related to altitude, dryness, frost-free period, latitude and longitude. Our results suggest that microbial community structure on the surface of wine grape is controlled primarily by geographical conditions. Unlabelled Image • The microbial community on wine grape surface from different regions of Xinjiang was affected by environment factors. • Proteobacteria and Ascomycota were the predominant bacteria and fungi, respectively. • The complexity of fungal community composition was higher than that of bacterial community composition in all samples. • Bacterial community diversity was largely related to altitude, latitude and longitude. • Fungal community diversity was closely related to altitude, dryness, frost-free period, latitude and longitude. [ABSTRACT FROM AUTHOR]

Integrated sensing and communication (ISAC) is a promising technique for unmanned aerial vehicle‐empowered 6G networks. This letter proposes a novel, adaptable ISAC mechanism. Firstly, both the communication and sensing channel models under the Doppler and beam‐squint effects are investigated. Then, an adaptive sensing method is proposed by the joint design of signal echo sensing and beam‐squint sensing under practical environment. Specifically, when the echo power is larger than the minimum detectable power, the proposed method could realize the effective sensing by utilizing the system model without feedback. Otherwise, the proposed method could exploit the beam‐squint for sensing with the feedback of the sub‐carrier index. Finally, various simulation results are provided to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, we consider a radio-frequency identification (RFID) backscatter system with two scenarios: single input multiple output (SIMO) and multiple input single output (MISO). We investigate the impact of channel correlation between the forward and backscatter links on the symbol error rate (SER), and we compare the performance of SIMO and MISO RFID systems with maximum ratio combining reception over arbitrarily correlated Nakagami- $m$ fading channels. In order to gain an insight for the system design, closed-form expressions for the asymptotic SER and an upper bound are derived for $M$ -ary phase-shift keying and quadrature amplitude modulation. The diversity order in the fully correlated cases, revealed from these expressions, is half of that in the partially correlated and uncorrelated cases. Finally, simulations are performed to validate the theoretical analysis. [ABSTRACT FROM AUTHOR]

Objectives: To prospectively compare the diagnostic performances of three methods of region of interest (ROI) placement for the measurements of intravoxel incoherent motion (IVIM) diffusion-weighted MR imaging in differentiating the histologic grade of hepatocellular carcinoma (HCC).Methods: Eighty-seven patients with 91 newly diagnosed HCCs were studied using IVIM imaging. Two attending radiologists separately identified the selection of tumour tissue for ROI positioning. Three different ROI positioning methods, namely the whole tumour volume (WTV) method, three-ROI method and one-section method, were used for the measurement. Kruskal-Wallis rank test or one-way ANOVA was used to compare the difference in IVIM parameters and ADC across the three different ROI positioning methods. Spearman correlation analysis was used to determine the correlation between each parameter and Edmondson-Steiner (E-S) grade. Receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic performance.Results: For the ADC and ADCslow, the mean value measured by using the WTV method was significant higher than the one-section and three-ROI methods (all p < 0.01). For the ADCslow, the highest area under curve (AUC) with a value of 0.969 was obtained by using the WTV method, followed by the one-section method (AUC = 0.938) and three-ROI method (AUC = 0.873). Additionally, for the ADC, AUC values were 0.861 for WTV method, 0.840 for one-section method and 0.806 for three-ROI method.Conclusions: Different ROI positioning methods used significantly affect the IVIM parameters and ADC measurements. Measurements of ADCslow value derived from WTV method entailed the highest diagnostic performance in grading HCC.Key Points: • Diffusion MRI is useful for non-invasively differentiating the histologic grade of hepatocellular carcinoma. • Different ROI positioning methods used significantly affect the IVIM parameters and ADC measurements. • IVIM model is advantageous over mono-exponential model for assessing the histologic grade of hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

In an indentation test, the effective Young’s modulus of a film/substrate bilayer heterostructure varies with the indentation depth, a phenomenon known as the substrate effect. In previous studies investigating this, only the Young’s modulus of the film was unknown. Once the effective Young’s modulus of a film/substrate structure is determined at a given contact depth, the Young’s modulus of the film can be uniquely determined, i.e., there is a one-to-one relation between the Young’s modulus of the film and the film/substrate effective Young’s modulus. However, at times it is extremely challenging or even impossible to measure the film thickness. Furthermore, the precise definition of the layer/film thickness for a two-dimensional material can be problematic. In the current study, therefore, the thickness of the film and its Young’s modulus are treated as two unknowns that must be determined. Unlike the case with one unknown, there are infinite combinations of film thickness and Young’s modulus which can yield the same effective Young’s modulus for the film/substrate. An inverse problem is formulated and solved to extract the Young’s modulus and thickness of the film from the indentation depth-load curve. The accuracy and robustness of the inverse problem-solving method are also demonstrated. [ABSTRACT FROM AUTHOR]

Massive MIMO, especially in the millimeter- wave frequency bands, has been recognized as a promising technique to enhance spectrum and energy efficiency, as well as network coverage for wireless communications. Most research in massive MIMO just uses the extended conventional MIMO channel model by directly assuming that the channel dimensionality becomes large. With massive numbers of antennas, however, there exists a non-negligible propagation delay across the large array aperture, which then causes a transmitted symbol to reach different antennas with different delays, thereby rendering conventional MIMO channel models inapplicable. Such a phenomenon is known as the spatial-wideband effect in the areas of array signal processing and radar signal processing, and introduces the beam squint effect in beamforming. However, the spatial-wideband effect and the related beam squint issue are seldom studied in massive MIMO communications. To design a practical massive MIMO system, it is important to understand when the spatial-wideband effect appears and how it affects signal transmission, how the spatial-wideband effect interacts with the frequency-wideband effect (frequency selectivity), especially for multi-carrier modulations such as orthogonal frequency- division multiplexing (OFDM), and how we should re-design the transceiver. In this article we suggest a new massive MIMO channel model that embraces both the spatial- and frequency- wideband effects, and discuss these issues. [ABSTRACT FROM AUTHOR]

When there are a large number of antennas in massive MIMO systems, the transmitted wideband signal will be sensitive to the physical propagation delay of electromagnetic waves across the large array aperture, which is called the spatial-wideband effect. In this scenario, the transceiver design is different from most of the existing works, which presume that the bandwidth of the transmitted signals is not that wide, ignore the spatial-wideband effect, and only address the frequency selectivity. In this paper, we investigate spatial- and frequency-wideband effects, called dual-wideband effects in massive MIMO systems from the array signal processing point of view. Taking millimeter-wave-band communications as an example, we describe the transmission process to address the dual-wideband effects. By exploiting the channel sparsity in the angle domain and the delay domain, we develop the efficient uplink and downlink channel estimation strategies that require much less amount of training overhead and cause no pilot contamination. Thanks to the array signal processing techniques, the proposed channel estimation is suitable for both TDD and FDD massive MIMO systems. Numerical examples demonstrate that the proposed transmission design for massive MIMO systems can effectively deal with the dual-wideband effects. [ABSTRACT FROM AUTHOR]

In atomic force microscopy (AFM), the higher modes are highly sensitive to the tip-sample interactions which generate many harmonics. When a higher harmonic is close to the natural frequency of a mode, the harmonic signal is enhanced by a resonance. The step-like cantilever is proposed as an effective design to enhance the higher harmonic signals. The natural frequencies are changed with the variations of the step-like cantilever sizes. By carefully designing the step-like cantilever, the first three modes can be simultaneously excited. A comprehensive map is provided as a guidance of selecting the appropriate geometric parameters. [ABSTRACT FROM AUTHOR]

In this paper, we design robust downlink beamforming against the imperfect channel state information (CSI) for beam division multiple access (BDMA) massive multiple-input multiple output (MIMO) systems. Following a worst-case deterministic model, the proposed design is formulated as minimizing the power consumption of base station (BS) under different signal-to-interference-plus-noise ratio (SINR) constraints. The S-Procedure and semi-definite relaxation (SDR) are used to convert the initial non-convex optimization to a convex semi-definite programming problem. Then the optimality of SDR is strictly proved by showing the rank-one property of the optimal beamforming thanks to the orthogonal channels under BDMA scheme. More importantly, we make one step further by deriving the optimal beamforming directions and optimal beamforming power allocation of the SDR in closed-form, which greatly reduces the optimization complexity and makes the proposed design practical for a real word massive MIMO system. Simulation results are then provided to verify the efficiency of the proposed robust beamforming algorithm. [ABSTRACT FROM AUTHOR]

We study a novel communication technique, ambient backscatter, that utilizes radio frequency signals transmitted from an ambient source as both energy supply and information carrier to enable communications between low-power devices. Different from existing noncoherent schemes, we here design the semi-coherent detection, where channel-related parameters can be obtained from unknown data symbols and a few pilot symbols. In order to obtain a benchmark for overall detection, we first derive a maximum likelihood detector assuming a complex Gaussian ambient source, and the closed-form bit error rate (BER) is computed. To release the dependence on prior knowledge of the ambient source, we next derive a type of robust design, called an energy detector, with the ambient signal being either complex Gaussian or phase shift keying (PSK). The closed-form detection thresholds, analytical BERs, and outage probability are provided correspondingly. Interestingly, the complex Gaussian source would cause an error floor, while the PSK source does not, which brings nontrivial indication of constellation design as opposed to popular Gaussian-embedded literatures. We also propose an effective approach to estimate detection-required parameters rather than channels themselves. Numerical simulations are finally presented to verify theoretical results. [ABSTRACT FROM PUBLISHER]

Large-scale multi-input multi-output (MIMO) technique has drawn considerable research interest recently. However, multiuser transmissions in large-scale MIMO systems would face challenging estimation and compensation for multiple carrier frequency offsets (CFOs) that co-exist at the receiver. In this paper, we design a new frequency synchronization scheme in multiuser orthogonal frequency division multiplexing uplink with the aid of scattered pilot symbols. We specifically consider a base station with a large number of antennas and propose to assign a number of scattered pilot subcarriers to each user. With sufficient spatial dimensions offered by the large number of antennas, the designed scheme could estimate CFO for each user individually and eliminate the necessity of the multidimensional search. Moreover, after the CFO estimation, the receive beamforming matrix is further designed for inter-user interference cancelation, which yields an equivalent single user transmission model. The conventional single user channel estimation and data detection can then be performed. Finally, the numerical results are provided to verify the proposed studies. [ABSTRACT FROM AUTHOR]

This paper proposes a unified transmission strategy for multiuser time division duplex (TDD)/frequency division duplex (FDD) massive multiple-input–multiple-output (MIMO) systems, including uplink (UL)/downlink (DL) channel estimation and user scheduling for data transmission. With the aid of antenna array theory and array signal processing, we build a spatial basis expansion model (SBEM) to represent the UL/DL channels with far fewer parameter dimensions. Hence, both the UL and DL channel estimations of multiusers can be carried out with a small amount of training resource, which significantly reduces the training overhead and feedback cost. Meanwhile, the pilot contamination problem in the UL training is immediately relieved by exploiting the spatial information of users. To enhance the spectral efficiency, we also design a greedy user scheduling scheme during the data transmission period. Compared with existing low-rank models, the newly proposed SBEM offers an alternative for channel acquisition without the need for channel statistics and can be applied to both TDD and FDD systems. Various numerical results are provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

In this paper, we consider spectrum sensing in a new cognitive radio (CR) scenario where the primary user (PU) could possibly transmit with multiple power levels and where the noise power at the secondary user (SU) side is uncertain. The target for the SU is not only to detect the presence of PU, as in the conventional “on–off” CR scenario, but to identify the PU's transmitting power level as well. With the aid of the generalized likelihood ratio test (GLRT), we prove that energy detection (ED) is still the optimal detection technique and then derive the closed-form decision thresholds and the corresponding analytical performance. Interestingly, a unique phenomenon called power ambiguity arises in this new CR scenario that demands careful investigation. Moreover, the signal-to-noise ratio (SNR) wall in the conventional binary CR also exists here and separates all power levels into two groups: One group leads to robust recognition, whereas the other does not. To make the discussion complete, we further design a cooperative spectrum sensing scheme and derive the corresponding analytical performance expression. In the end, we validate our study through various numerical results. [ABSTRACT FROM PUBLISHER]

Ambient backscatter technology that utilizes the ambient radio frequency signals to enable the communications of battery-free devices has attracted much attention recently. In this paper, we study the problem of signal detection for an ambient backscatter communication system that adopts the differential encoding to eliminate the necessity of channel estimation. Specifically, we formulate a new transmission model, design the data detection algorithm, and derive two closed-form detection thresholds. One threshold is used to approximately achieve the minimum sum bit error rate (BER), while the other yields balanced error probabilities for “0” bit and “1” bit. The corresponding BER expressions are derived to fully characterize the detection performance. In addition, the lower and the upper bounds of BER at high signal-to-noise ratio regions are also examined to simplify a performance analysis. Simulation results are then provided to corroborate the theoretical studies. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new blind frequency synchronization scheme for multiuser orthogonal-frequency-division multiplexing (OFDM) uplink transmissions. The spatial multiplexing is supported in the considered model that allows the subcarriers to be simultaneously occupied by multiple users, while the orthogonal frequency division multiple access (OFDMA) can serve as a special case of our discussion. We propose to assign different null subcarriers to different users and design algorithm that can perform blind carrier frequency offset (CFO) estimation for each individual user with the aid of large number of receive antennas, which then removes the necessity of multidimensional searching. After estimating CFO for one user, the orthogonal complement space of the other users can be obtained which could be further utilized for multiuser interference cancelation. Hence, the multiuser OFDM uplink model reduces to an equivalent single user signal model, where the blind channel estimation with scalar ambiguity can be designed and the conventional single-user data detection can be peformed. To make the proposed study complete, the closed-form performance analysis for mean square error (MSE) of the CFO estimation is derived, based on which the discussion about optimal null subcarrier assignment scheme is further provided. Finally, the Cramer–Rao bound (CRB) is derived, and the numerical results are provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

In this correspondence, we propose a cooperative-generalized-sensing-based spectrum sharing approach in centralized cognitive radio networks. Differently from the conventional cooperative approaches, where the secondary base station (SBS) takes a decision on the busy/idle status of the primary user and transmits with constant/binary power, the proposed approach allows the SBS to transmit with power as a continuous function of the detection information vector. We treat the cases of lossless-compression and hard-decision information separately. Optimal sensing time, detection threshold, and power allocation are derived to maximize the achievable rate at the SBS. In this paper, we only consider the case where secondary users (SUs) are merely receivers, and the SBS uses the allocated power to communicate with the SUs; however, the conclusions can also be expanded to the case where SUs use the allocated power under the assumption of a common control channel to exchange the information between the SBS and SUs. Simulation results demonstrate that the proposed approach can improve the performance of the SBS compared with the conventional approaches. [ABSTRACT FROM AUTHOR]

For multiple-input multiple-output (MIMO) transceiver designs, sum power constraint is an elegant and ideal model. When various practical limitations are taken into account e.g., peak power constraints, per-antenna power constraints, etc., covariance shaping constraints will act as an effective and reasonable model. In this paper, we develop a framework for transceiver designs for multi-hop communications under covariance shaping constraints. Particularly, we focus on multi-hop amplify-and-forward (AF) MIMO relaying communications which are recognized as a key enabling technology for device-to-device (D2D) communications for next generation wireless systems such as 5G. The proposed framework includes a broad range of various linear and nonlinear transceiver designs as its special cases. It reveals an interesting fact that the relaying operation in each hop can be understood as a matrix version weighting operation. Furthermore, the nonlinear operations of Tomolision–Harashima Precoding (THP) and Decision Feedback Equalizer (DFE) also belong to the category of this kind of matrix version weighting operation. Furthermore, for both the cases with only pure shaping constraints or joint power constraints, the closed-form optimal solutions have been derived. At the end of this paper, the performance of the various designs is assessed by simulations. [ABSTRACT FROM PUBLISHER]

The very original concept of cognitive radio raised by Mitola targets at all the environment parameters, including those in the physical, MAC, and application layers, as well as the information extracted from reasoning. Hence, the first CR is also referred to as ?full cognitive radio.? However, due to its difficult implementation, the FCC and Simon Haykin separately proposed a very simplified definition, in which CR mainly detects a single parameter, spectrum occupancy, and is also called ?spectrum sensing cognitive radio.? With the rapid development of wireless communications, the infrastructure of a wireless system becomes much more complicated, while the functionality at every node is desired to be as intelligent as possible, say selforganized capability approaching 5G cellular networks. It is then interesting to reconsider Mitola?s definition and think whether one could, besides obtaining the on/off status of the licensed user only, achieve more parameters in a cognitive way. In this article, we propose a new cognitive architecture targeting multiple parameters for future cellular networks, which is one step further toward ?full cognition? compared to most existing CR research. The new architecture is elaborated in detailed stages, and three representative examples are provided based on recent research progress to illustrate the feasibility as well as the validity of the proposed architecture. [ABSTRACT FROM PUBLISHER]

In this paper, a new cognitive radio (CR) scenario called Multiple Primary Transmit Power (MPTP) is investigated where the primary user (PU) could possibly work on more than one discrete transmit power levels. Different from most existing literatures where PU is assumed to operate with a constant transmit power only, this new consideration well matches the practical standards, e.g., IEEE 802.11 Series, GSM, LTE, LTE-A, etc., as well as the adaptive powering concept that a user would vary its transmit power under different situations. The primary target of CR under MPTP may still be detecting the presence of PU. However, there emerges a secondary target as to identify the PU’s transmit power level. Compared to the existing sensing strategy where the secondary user (SU) only detects the “on-off” status of PU, recognizing the transmit power level of PU achieves more “cognition” and makes the CR more intelligent. Meanwhile, SU could utilize the power level information of PU and make the subsequent design. We derive quite many closed-form results for either the threshold expressions or the performance analysis in this new CR scenario, from which many interesting points and discussions are raised. We then study the cooperative sensing schemes under MPTP and demonstrate their significant differences from traditional cooperative algorithms. Lastly, numerical examples are provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

In this paper, we examine the Bayesian Cramér–Rao lower bounds (BCRBs) for the channel estimation in an amplify-and-forward (AF) one-way relay network (OWRN) under the time-selective flat-fading scenario, where the superimposed training is adopted at the relay node in order to achieve the individual channel estimation. We formulate the nonlinear dynamic state space for the individual channels and derive the online/offline BCRBs for the fully data-aided (FDA) channel estimator and the partially data-aided (PDA) estimator. The former estimator has full knowledge about the symbols from both the source and the relay, while the latter one has imperfect statistical information about the data of the source, and possesses full information of the symbols superimposed by the relay. For the FDA scenario, we calculate the closed-form online/offline BCRBs and analyze the effect of the nodes' mobility on the BCRB performance, while for the PDA case, with the assumption of square QAM constellation set at the source, we design one framework to numerically evaluate online/offline BCRBs and analyze the asymptotic BCRBs at high SNRs particularly for the 4-QAM constellation set. Finally, numerical results are provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

In this paper, we design joint information beamforming and jamming beamforming to guarantee both transmit security and receive security for a full-duplex base-station (FD-BS). Specifically, we aim to maximize the secret transmit rate while constrain the secret receive rate to be greater than a predefined bound. When FD-BS is equipped with a single transmit antenna, we derive the optimal solutions in closed-form, and interestingly, the results say that simultaneous information and jamming transmission cannot be optimal. When FD-BS is equipped with multiple transmit antennas, we convert the original nonconvex problem into a sequence of subproblems where the semidefinite programming (SDP) relaxation can be applied to efficiently find the optimal solutions. We strictly prove that such a relaxation does not change the optimality for these subproblems. Then the global optimal solutions of the original nonconvex problem can be obtained via a one-dimensional search. Simulation results are provided to verify the efficiency of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

In this paper, we design a time-multiplexed superimposed training (TMST) scheme to estimate the individual channels in amplify-and-forward one-way relay networks (OWRNs) under a doubly selective channel scenario, where the two-phase zero-prefixed block transmission scheme is adopted. The complex-exponential basis expansion model (CE-BEM) is utilized to approximate the channel of each individual hop and results in a coefficient vector with much smaller size, called in-BEM-CV. The channel estimation of the individual channel is then converted into the estimation of in-BEM-CVs. We develop an estimation algorithm with three steps: the standard least squares (LS) estimator, the time domain or the fast Fourier transform (FFT)-based decoupler, and the iterative LS-based refiner. We also optimize the training parameters, including the number, the position, and the power allocation of the pilot clusters by minimizing the estimation mean square error (MSE), and derive one performance lower bound for the proposed algorithm. Finally, numerical results are provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

[Display omitted] • Element profile of Ecolly grape and wine from six regions was analyzed by ICP-MS. • Ba, Cs, Li, Mg, Na, Rb, and Sr in wine were positively related to those in grape. • Element profile of Ecolly grape and wine was mainly driven by geographical origin. • ICP-MS coupled with ML models was a useful tool to trace grape and wine origins. • Feedforward neural network was the most superior classifier with 100 % accuracy. The authenticity of the geographical origin of grapes and wines is vital for ensuring food safety in the wine market. To authenticate the geographical origin of Ecolly grapes and wines from different Chinese regions, forty-six elements were determined by inductively coupled plasma mass spectrometry (ICP-MS). Moreover, the relationships of element content between grapes and wines and regional differences in element profile were analyzed by multivariate statistics. K, Na, Cs, V, Li, Sc, In, Mn, Mg, Al, and Li, Na, Mg, K, Ca, Mn, Fe, Ni, Cu, Zn were important characteristic variables to distinguish grape and wine origins based on chi-squared tests, respectively. A feed-forward neural network (FNN), random forest (RF), and support vector machine (SVM) exhibited 98.33 %, 96.67 %, and 100 % accuracy for distinguishing the geographical origin of Ecolly grapes using these variables, respectively. All models obtained 100 % accuracy for distinguishing wines. FNN exhibited superior performance compared with RF and SVM according to a comprehensive evaluation based on the overall accuracy, the receiver operating characteristic curve (ROC), an area under the curve (AUC), and tenfold cross-validation. Consequently, this study provides powerful evidence of the potential application of ICP-MS coupled with machine learning models to discriminate the geographical origin of Chinese grapes and wines. [ABSTRACT FROM AUTHOR]

The article focuses on epistemic asset and liability served by the personal experience of patients in debate of assisted dying, and mentions analysis of global data and policy on legislative demand for assisted dying. Topics discussed include conflicts of interests generated by the patients' experience, practices for bioethics in policy settings with the help of paradox of experience, and euthanasia caused due to loss of dignity.

Manifold learning concerns the local manifold structure of high dimensional data, and many related algorithms are developed to improve image classification performance. None of them, however, consider both the relationships among pixels in images and the geometrical properties of various images during learning the reduced space. In this paper, we propose a linear approach, called two-dimensional maximum local variation (2DMLV), for face recognition. In 2DMLV, we encode the relationships among pixels in images using the image Euclidean distance instead of conventional Euclidean distance in estimating the variation of values of images, and then incorporate the local variation, which characterizes the diversity of images and discriminating information, into the objective function of dimensionality reduction. Extensive experiments demonstrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the resource allocation problem in a single-user relay-aided cognitive radio (CR) underlay network. Both the CR network and the primary network operate under the orthogonal frequency-division multiplexing (OFDM) scheme. Different from the conventional resource allocation problem, the relay node here is capable of performing subcarrier permutation over two hops such that the signal received over a particular subcarrier is forwarded via a different subcarrier. The objective is to maximize the throughput of the CR network subject to a limited power budget at the secondary source and the relay node and to interference constraints at the primary receiver. Optimization is performed under a unified framework where power allocation at the source node, power allocation at the relay node, and subcarrier pairing at the two hops are jointly optimized. The joint resource-allocation scheme yields an asymptotically optimal solution. We further design a suboptimal algorithm that sacrifices little on performance but could significantly reduce computational complexity. Finally, numerical examples are provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

A chemical investigation of Lysimachia christinae, a traditional Chinese medicine used as an effective conservative treatment for gall stones, hepatolithiasis, and urinary calculi, resulted in the isolation of two new flavonoids, myricetin 3,3′-di- α- L-rhamnopyranoside ( 1) and quercetin 3,3′-di- α- L-rhamnopyranoside ( 2), along with the five known flavonoids quercetin 3-[ O- α- L-rhamnopyranosyl-(1→2)- β- D-galactopyranoside], amentoflavone, hyperin, quercetin 3- β- D-glucopyranoside, and kaempferol 3- α- L-rhamnopyranoside. Amentoflavone was reported for the first time from the genus Lysimachia, and quercetin 3-[ O- α- L-rhamopyranosyl-(1→2)- β- D-galactopyranoside] was isolated from this plant for the first time. The structures of the new compounds were elucidated on the basis of their chemical reactions and extensive spectroscopic analyses, including UV, mass, and NMR spectra. [ABSTRACT FROM AUTHOR]

In this paper, we propose an Alamouti-code-based relaying scheme for frequency asynchronous amplify-and-forward (AF) relay networks. Both the oscillator frequency offsets and the Doppler shifts among the distributed nodes are considered in our design. We employ orthogonal frequency-division multiplexing (OFDM) modulation at the source node and let the two relay nodes implement only simple operations, such as time reversal, conjugation, and amplification. We show that without Doppler shifts, the multiple carrier frequency offsets (CFOs) can be directly compensated at the destination, and the received signals exhibit an Alamouti-like structure. We further prove that full spatial diversity can be achieved by the fast symbol-wise detection when the oscillator frequency offset between the relay nodes is smaller than a certain threshold, which yields lower decoding complexity compared with the existing schemes. In the case with Doppler shifts, where the direct CFO compensation becomes impossible, we develop a repetition-aided Alamouti coding approach, by which full diversity can be nearly achieved from the fast symbol-wise detection. Numerical results are provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a range-free cooperative localization algorithm for mobile sensor networks by combining hop-distance measurements with particle filtering. In the hop-distance measurement step, we design a differential-error correction scheme to reduce the positioning error accumulated over multiple hops. We also introduce a backoff-based broadcast mechanism in our localization algorithm. It efficiently suppresses redundant broadcasts and reduces message overhead. The proposed localization method has fast convergence with small location estimation error. We verify our algorithm in various scenarios and compare it with conventional localization methods. Simulation results show that our proposed method has similar or superior performance when compared to other state-of-the-art localization algorithms. [ABSTRACT FROM AUTHOR]

This correspondence considers the optimal training design in a classical three-node amplify-and-forward two-way relay network (TWRN) that targets at estimating the individual channel between each source node and the relay node. The transmission environment is assumed to be frequency selective and the orthogonal-frequency-division multiplexing (OFDM) modulation is adopted. We derive the Bayesian Cramér–Rao bound (CRB) for the individual channel estimation, from which the optimal training is obtained. Extensive numerical results are provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

In this paper, we develop two novel blind carrier frequency offset (CFO) estimators for interleaved orthogonal frequency division multiple access (OFDMA) uplink transmission in a multiantenna system. The first estimator is the subspace-based one and could blindly estimate multiple CFOs from a rank reduction approach. The second estimator is based on the maximum likelihood (ML) approach and improves the performance as compared to the first one. The higher computational complexity of the ML estimator is alleviated by the alternating projection (AP) method. Both the proposed estimators support fully loaded data transmissions, i.e., all subcarriers being occupied, which provides higher bandwidth efficiency as compared to the existing schemes. The numerical results are then provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

In this paper, we design a space–frequency (SF) convolutional coding scheme for amplify-and-forward (AF) relay networks that contain multiple distributed relay nodes. The frequency-asynchronous nature of the distributed system is considered in our design. Orthogonal frequency-division multiplexing (OFDM) modulation is adopted, which is robust to certain timing errors. We exploit the signal space diversity technique and employ an extended cyclic prefix (CP) at the source node. The relay nodes need to perform only simple operations, e.g., convolution and amplification, and they need no information about the channels and the frequency offsets. Attributed to the extended CP, the multiple frequency offsets can directly be compensated at the destination. We further prove that both spatial and multipath diversity can be achieved by the proposed scheme. Numerical results are provided to corroborate the proposed studies. [ABSTRACT FROM PUBLISHER]

This paper studies the rate maximization problem and designs the beamforming strategy for relay-aided multiuser multiantenna cognitive radio (CR) network that coexists with a primary radio (PR) system via opportunistic spectrum sharing (OSS). The beamforming is characterized by two layers: 1) Cognitive beamforming (CB) is employed by CR base station (BS), CR relay station (RS), and secondary users (SUs) to mitigate the interference to and from the PR. 2) Joint CR-BS and CR-RS beamforming is used to maximize the weighted sum rate of the SUs. Since the optimization turns out to be nonconvex, we apply the classic Blahut-Arimoto algorithm and solve the original problem through an iterative approach. Interestingly, each iterative step involves only convex optimizations whose closed forms can be found. Moreover, we derive an upper bound for the sum rate to assist system analysis. Numerical results show that the proposed approach achieves higher performance, compared with the widely studied diagonally structured beamformer design. [ABSTRACT FROM PUBLISHER]

This paper studies the transmit strategy for a secondary link or the so-called cognitive radio (CR) link under opportunistic spectrum sharing with an existing primary radio (PR) link. It is assumed that the CR transmitter is equipped with multi-antennas, whereby transmit precoding and power control can be jointly deployed to balance between avoiding interference at the PR terminals and optimizing performance of the CR link. This operation is named as cognitive beamforming (CB).Unlike prior study on CB that assumes perfect knowledge of the channels over which the CR transmitter interferes with the PR terminals, this paper proposes a practical CB scheme utilizing a new idea of effective interference channel (EIC), which can be efficiently estimated at the CR transmitter from its observed PR signals. Somehow surprisingly, this paper shows that the learning-based CB scheme with the EIC improves the CR channel capacity against the conventional scheme even with the exact CRto-PR channel knowledge, when the PR link is equipped with multi-antennas but only communicates over a subspace of the total available spatial dimensions. Moreover, this paper presents algorithms for the CR to estimate the EIC over a finite learning time. Due to channel estimation errors, the proposed CB scheme causes leakage interference at the PR terminals, which leads to an interesting learning-throughput tradeoff phenomenon for the CR, pertinent to its time allocation between channel learning and data transmission. This paper derives the optimal channel learning time to maximize the effective throughput of the CR link, subject to the CR transmit power constraint and the interference power constraints for the PR terminals. [ABSTRACT FROM AUTHOR]

Abstract-In this paper, we study the channel estimation and the optimal training design for relay networks that operate under the decode-and-forward (DF) strategy with the knowledge of the interference covariance. in addition to the total power constraint on all the relays, we introduce individual power constraint for each relay, which reflects the practical scenario here all relays are separated from one another. Considering the individual power constraint for the relay networks is the major difference from that in the traditional point-to-point communication systems where only a total power constraint exists for all colocated antennas. Two types of channel estimation are involved: maximum likelihood (ML) and minimum mean square error (MMSE). For ML channel estimation, the channels are assumed as deterministic and the optimal training results from an efficient multilevel waterfilling type solution that is derived from the majorization theory. For MMSE channel estimation, however, the second-order statistics of the channels are assumed known and the general optimization problem turns out to be nonconvex. We instead consider three special yet reasonable scenarios. The problem in the first scenario is convex and could be efficiently solved by state-of-the-art optimization tools. Closed-form waterfilling type solutions are found in the remaining two scenarios, of which the first one has an interesting physical interpretation as pouring water into caves. [ABSTRACT FROM AUTHOR]

In this paper, we consider the identification problem of multiinput-multioutput (MIMO) finite-impulse-response systems via second-order statistics only. By assigning different block precoders to different transmitters, we develop a new technique that allows blind MILMO channel identification up to a scalar ambiguity for each transmitter. We provide sufficient conditions for removal of the matrix ambiguity for a specific set of precoding matrices and derive a general theorem for other kinds of precoding matrices based on a reasonable conjecture. This theorem is firmly tested via numerical examples. Two potential precoding schemes are proposed, considering different ways of eliminating interblock interference. Finally, numerical results are provided to verify our analysis. [ABSTRACT FROM AUTHOR]

Abstract: Via electrochemical deposition, nanosized zinc oxide (nano-ZnO) is prepared within a template of mesoporous silica (MPS) film fabricated on a conductive substrate. Enhanced dark current from the nano-ZnO in MPS film is obtained because nano-ZnO is located in the nanosized pores of MPS. Most of the nano-ZnO surface is prevented from contacting ambient oxygen, and the combination of oxygen with free electrons of this n-type semiconductor is avoided; thus the free electrons increase the conductivity. Photodetection to ultraviolet (UV) light is examined at the exciting wavelength of 365 nm. The photocurrent with fast growing and decay times is observed due to the photo-generated holes being trapped at the interface between ZnO and pore walls of MPS film, while producing the photocurrent by photo-generated electrons. Photoluminescence (PL) spectrum of nano-ZnO in MPS film at room temperature shows increased amount of oxygen vacancies in these nano-ZnO, which might contribute to the conductivity. [Copyright &y& Elsevier]

Abstract: A three-component reaction of aromatic aldehydes, acetonitrile, and 2-thiohydantoins promoted by TiCl4 was discovered, and a different N–C–N bond-forming reaction took place with FeCl3, AlCl3 or BF3·Et2O as promoter. The thiohydantoin derivatives 1 and 3 were synthesized in moderate to high yields. A plausible mechanism for the formation of 1 and 3 is suggested. [Copyright &y& Elsevier]