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Abstract While high-entropy alloy (HEA) catalysts seem to have the potential to break linear scaling relationships (LSRs) due to their structural complexity, the weighted averaging of properties among multiple principal components actually makes it challenging to diverge from the symmetry dependencies imposed by the LSRs. Herein, we develop a ‘surface entropy reduction’ method to induce the exsolution of a component with weak affinity for others, resulting in the formation of few-atom-layer metal (FL-M) on the surface of HEAs. These exsolved FL-M surpass the confines of the original configurational space of conventional HEAs, and collaborate with the HEA substrate, serving as geometrically separated active sites for multiple intermediates in a complex reaction. This FL-M-covered HEA shows an outstanding performance for electrocatalytic reduction of nitrate to ammonia (NH3) with a Faradaic efficiency of 92.7%, an NH3 yield rate of 2.45 mmol h–1 mgcat. –1, and high long-term stability (>200 h). Our work achieves the precise manipulation of atomic arrangement, thereby expanding both the chemical space occupied by known HEA catalysts and their potential application scenarios.

Abstract Fast-charging, non-aqueous lithium-based batteries are desired for practical applications. In this regard, LiMn2O4 is considered an appealing positive electrode active material because of its favourable ionic diffusivity due to the presence of three-dimensional Li-ion diffusion channels. However, LiMn2O4 exhibits inadequate rate capabilities and rapid structural degradation at high currents. To circumvent these issues, here we introduce quintuple low-valence cations to increase the entropy of LiMn2O4. As a result, the entropy-increased LiMn2O4-based material, i.e., LiMn1.9Cu0.02Mg0.02Fe0.02Zn0.02Ni0.02O4, when tested in non-aqueous lithium metal coin cell configuration, enable 1000 cell cycles at 1.48 A g−1 (corresponding to a cell charging time of 4 minutes) and 25°C with a discharge capacity retention of about 80%. We demonstrate that the increased entropy in LiMn2O4 leads to an increase in the disordering of dopant cations and a contracted local structure, where the enlarged LiO4 space and enhanced Mn-O covalency improve the Li-ion transport and stabilize the diffusion channels. We also prove that stress caused by cycling at a high cell state of charge is relieved through elastic deformation via a solid-solution transition, thus avoiding structural degradation upon prolonged cycling.

Video understanding and content boundary detection are vital stages in video recommendation. However, previous content boundary detection methods require collecting information, including location, cast, action, and audio, and if any of these elements are missing, the results may be adversely affected. To address this issue and effectively detect transitions in video content, in this paper, we introduce a video classification and boundary detection method named JudPriNet. The focus of this paper is on objects in videos along with their labels, enabling automatic scene detection in video clips and establishing semantic connections among local objects in the images. As a significant contribution, JudPriNet presents a framework that maps labels to “Continuous Bag of Visual Words Model” to cluster labels and generates new standardized labels as video-type tags. This facilitates automatic classification of video clips. Furthermore, JudPriNet employs Monte Carlo sampling method to classify video clips, the features of video clips as elements within the framework. This proposed method seamlessly integrates video and textual components without compromising training and inference speed. Through experimentation, we have demonstrated that JudPriNet, with its semantic connections, is able to effectively classify videos alongside textual content. Our results indicate that, compared with several other detection approaches, JudPriNet excels in high-level content detection without disrupting the integrity of the video content, outperforming existing methods.

Abstract Local phase transition in transition metal dichalcogenides (TMDCs) by lithium intercalation enables the fabrication of high‐quality contact interfaces in two‐dimensional (2D) electronic devices. However, controlling the intercalation of lithium is hitherto challenging in vertically stacked van der Waals heterostructures (vdWHs) due to the random diffusion of lithium ions in the hetero‐interface, which hinders their application for contact engineering of 2D vdWHs devices. Herein, a strategy to restrict the lithium intercalation pathway in vdWHs is developed by using surface‐permeation assisted intercalation while sealing all edges, based on which a high‐performance edge‐contact MoS2 vdWHs floating‐gate transistor is demonstrated. Our method avoids intercalation from edges that are prone to be random but intentionally promotes lithium intercalation from the top surface. The derived MoS2 floating‐gate transistor exhibits improved interface quality and significantly reduced subthreshold swing (SS) from >600 to 100 mV dec–1. In addition, ultrafast program/erase performance together with well‐distinguished 32 memory states are demonstrated, making it a promising candidate for low‐power artificial synapses. The study on controlling the lithium intercalation pathways in 2D vdWHs offers a viable route toward high‐performance 2D electronics for memory and neuromorphic computing purposes.

Abstract Two-dimensional (2D) AMX2 compounds are a family of mixed ionic and electronic conductors (where A is a monovalent metal ion, M is a trivalent metal, and X is a chalcogen) that offer a fascinating platform to explore intrinsic coupled ionic-electronic properties. However, the synthesis of 2D AMX2 compounds remains challenging due to their multielement characteristics and various by-products. Here, we report a separated-precursor-supply chemical vapor deposition strategy to manipulate the chemical reactions and evaporation of precursors, facilitating the successful fabrication of 20 types of 2D AMX2 flakes. Notably, a 10.4 nm-thick AgCrS2 flake shows superionic behavior at room temperature, with an ionic conductivity of 192.8 mS/cm. Room temperature ferroelectricity and reconfigurable positive/negative photovoltaic currents have been observed in CuScS2 flakes. This study not only provides an effective approach for the synthesis of multielement 2D materials with unique properties, but also lays the foundation for the exploration of 2D AMX2 compounds in electronic, optoelectronic, and neuromorphic devices.

Abstract Improving activity and stability of Ruthenium (Ru)-based catalysts in acidic environments is eager to replace more expensive Iridium (Ir)-based materials as practical anode catalyst for proton-exchange membrane water electrolyzers (PEMWEs). Here, a bicontinuous nanoreactor composed of multiscale defective RuO2 nanomonomers (MD-RuO2-BN) is conceived and confirmed by three-dimensional tomograph reconstruction technology. The unique bicontinuous nanoreactor structure provides abundant active sites and rapid mass transfer capability through a cavity confinement effect. Besides, existing vacancies and grain boundaries endow MD-RuO2-BN with generous low-coordination Ru atoms and weakened Ru-O interaction, inhibiting the oxidation of lattice oxygen and dissolution of high-valence Ru. Consequently, in acidic media, the electron- and micro-structure synchronously optimized MD-RuO2-BN achieves hyper water oxidation activity (196 mV @ 10 mA cm−2) and an ultralow degradation rate of 1.2 mV h−1. A homemade PEMWE using MD-RuO2-BN as anode also conveys high water splitting performance (1.64 V @ 1 A cm−2). Theoretical calculations and in-situ Raman spectra further unveil the electronic structure of MD-RuO2-BN and the mechanism of water oxidation processes, rationalizing the enhanced performance by the synergistic effect of multiscale defects and protected active Ru sites.

Abstract Background Glioma recurrence, subsequent to maximal safe resection, remains a pivotal challenge. This study aimed to identify key clinical predictors influencing recurrence and develop predictive models to enhance neurological diagnostics and therapeutic strategies. Methods This longitudinal cohort study with a substantial sample size (n = 2825) included patients with non-recurrent glioma who were pathologically diagnosed and had undergone initial surgical resection between 2010 and 2018. Logistic regression models and stratified Cox proportional hazards models were established with the top 15 clinical variables significantly influencing outcomes screened by the least absolute shrinkage and selection operator (LASSO) method. Preoperative and postoperative models predicting short-term (within 6 months) postoperative recurrence in glioma patients were developed to explore the risk factors associated with short- and long-term recurrence in glioma patients. Results Preoperative and postoperative logistic models predicting short-term recurrence had accuracies of 0.78 and 0.87, respectively. A range of biological and early symptomatic characteristics linked to short- and long-term recurrence have been pinpointed. Age, headache, muscle weakness, tumor location and Karnofsky score represented significant odd ratios (t > 2.65, p 4.12, p

Green buildings are designed and constructed according to the principles of sustainable development and are an inevitable trend in future architectural development. Nowadays, many works have studied the application of intelligence or intelligent technology in green intelligent buildings, but there is still insufficient discussion on how to integrate intelligent technology into all aspects of buildings. In view of this, this paper summarizes the design concepts of modern green buildings and takes this as the starting point to explore the classification and construction of the core needs for achieving sustainable development throughout the life cycle of buildings from five aspects: building design, building materials, building construction, building renewal and management, and building damage, and analyze the integration of relevant intelligent technologies in buildings under different needs.

[Introduction] Accurate load forecasting underpins the operation optimization of the electricity systems and is an indispensable aspect of energy management within such systems. Given the low accuracy and high computational complexity inherent in traditional methodologies that combine data decomposition and machine learning models, this study proposes a novel Empirical Mode Decomposition and Multi-Layer Perceptron (EMD-MLP) model for predicting day-ahead electrical load. [Method] Initially, the EMD method decomposed the original load time series into multiple Intrinsic Mode Function (IMF). These IMFs were then reconstructed into high-frequency and low-frequency components using extreme point partitioning, simplifying the prediction target. Subsequently, each reconstructed components was modeled separately for prediction, and the results were cumulatively used to provide the forecasted electrical load value. [Result] The proposed model is tested using real-world electrical load data of 2018 and 2019 from the Australian electricity market. [Conclusion] Comparing the extrapolative capabilities of our EMD-MLP model with persistence model, standalone MLP model and traditional EMD ensemble model confirms the effectiveness of our model in enhancing prediction accuracy. Moreover, while ensuring accuracy, the proposed EMD-MLP model simplifies the complexity and improves the efficiency of the forecasting process, thereby providing a practical solution for both day-ahead and real-time electrical load forecasting.

Abstract Background Upper limb dysfunction seriously affects the ability of stroke patients to perform activities of daily living. As a popular exercise therapy, Tai Chi may become an alternative intervention. However, the neurophysiological mechanism by which Tai Chi improves upper limb dysfunction in stroke patients is still unclear, which limits its further promotion and application. Therefore, conducting a strict randomized clinical trial is necessary to observe how Tai Chi affects upper limb dysfunction in stroke patients and to explore its neurophysiological mechanism. Methods/design This report describes a randomized, parallel-controlled trial with distributive concealment and evaluator blinding. A total of 84 eligible participants will be randomly assigned to the Tai Chi group or the control group in a 1:1 ratio. The participants in the Tai Chi group will receive 4 weeks of Tai Chi training: five 60-min sessions a week for a total of 20 sessions. The participants in the control group will not receive Tai Chi training. Both groups will receive medical treatment and routine rehabilitation training. The primary outcome measure is the mean change in the Fugl-Meyer Assessment Upper Extremity (FMA-UE) scale score between baseline and 4 weeks; the secondary outcomes are the mean changes in kinematic characteristics and the Wolf Motor Function Test (WMFT) and Stroke Impact Scale (SIS) scores. In addition, the corticomuscular coupling level and near-infrared brain functional imaging will be monitored to explore the mechanism by which Tai Chi improves upper limb function of stroke patients. Discussion This randomized controlled trial will examine the effectiveness of Tai Chi in stroke patients with upper limb dysfunction and explore the neurophysiological mechanism. Positive results will verify that Tai Chi can improve upper limb function of stroke patients. Trial registration Chinese Clinical Trial Registration Center, ChiCTR2200061376 (retrospectively registered). Registered June 22, 2022. http://www.chictr.org.cn/listbycreater.aspx . Manuscript Version: 3.0 Manuscript Date: October 10, 2023.

Abstract We report a 36-year-old male patient died of V. vulnificus-induced septicaemia and multiple organ failure syndrome after oyster consumption at a restaurant. We isolated and identified V. vulnificus vv16015 from the patient’s blood sample and antibiotic susceptibility tests indicated sensitivity to all 21 antibiotics. Oyster samples were subsequently collected from the restaurant’s supplier and three strains of V. vulnificus were isolated. Whole genome sequencing and analysis revealed vv16015 to be distantly related to these strains and confirmed that V. vulnificus contamination was present in the seafood of the restaurant and supplier. Using a Galleria mellonella larvae infection model, the virulence of vv16015 was determined to be higher than that of comparison strains isolated from a surviving patient (vv15018) and an oyster (vv220015). The human and environment distribution of V. vulnificus in Shenzhen is sporadic and heterogeneous, and vv16015 is highly virulent compared to other strains.

Abstract In tonal languages, which are spoken by nearly one-third of the world’s population, speakers precisely control the tension of vocal folds in the larynx to modulate pitch in order to distinguish words with completely different meanings. The specific pitch trajectories for a given tonal language are called lexical tones. Here, we used high-density direct cortical recordings to determine the neural basis of lexical tone production in native Mandarin-speaking participants. We found that instead of a tone category-selective coding, local populations in the bilateral laryngeal motor cortex (LMC) encode articulatory kinematic information to generate the pitch dynamics of lexical tones. Using a computational model of tone production, we discovered two distinct patterns of population activity in LMC commanding pitch rising and lowering. Finally, we showed that direct electrocortical stimulation of different local populations in LMC evoked pitch rising and lowering during tone production, respectively. Together, these results reveal the neural basis of vocal pitch control of lexical tones in tonal languages.

In this study, the optimal process for the deproteinization of crude polysaccharides from Chinese yam peel was investigated by using the trichloroacetic acid method, Sevag method and Sevag-papain enzyme method. The purified polysaccharide fractions were characterized by infrared spectroscopy, the monosaccharide composition analysis, and the antioxidant activity in vitro was determined. The results indicated that the optimal ethanol final concentration was 90%, the yield of polysaccharide reached 9.55%, and polysaccharide precipitation rate was the highest. The better deproteinization process was papain treatment combined with Sevag method. Under the condition, the polysaccharide retention rate reached 64.7% and the deproteinization rate was 76.8%. Two major polysaccharide fractions named CYPP-1 and CYPP-2 were isolated and purified from crude polysaccharide by DEAE-52 cellulose column chromatography, and their molecular weights were 4.442 kDa and 4.278 kDa respectively. CYPP-1 was consisted of glucosamine hydrochloride, galactose, glucose, mannose and glucuronic acid with the molar ratio of 11.1:14.4:21.8:35:10.8, and CYPP-2 was consisted of glucosamine hydrochloride, mannose and glucuronic acid with the molar ratio of 10.5:47.9:16.8. Infrared spectroscopy showed that both fractions were consistent with the structural characteristics of plant polysaccharides, being α-type polysaccharides. The scavenging effects of different concentrations of CYPP-1 and CYPP-2 on DPPH, hydroxyl radicals, ABTS+ and superoxide anion radicals in vitro were compared, and the scavenging rates of 8.0 mg/mL CYPP-1 were 89.83%, 46.72%, 67.27% and 51.20%, respectively. And its antioxidant activity was higher than that of CYPP-2.

As various software bots are widely used in open source software repositories, some drawbacks are coming to light, such as giving newcomers non-positive feedback and misleading empirical studies of software engineering researchers. Several techniques have been proposed by researchers to perform bot detection, but most of them are limited to identifying bots performing specific activities, let alone distinguishing between GitHub App and OAuth App. In this paper, we propose a bot detection technique for OAuth App, named BDGOA. 24 features are used in BDGOA, which can be divided into three dimensions: account information, account activity, and text similarity. To better explore the behavioral features, we define a fine-grained classification of behavioral events and introduce self-similarity to quantify the repeatability of behavioral sequence. We leverage five machine learning classifiers on the benchmark dataset to conduct bot detection, and finally choose random forest as the classifier, which achieves the highest F1-score of 95.83%. The experimental results comparing with the state-of-the-art approaches also demonstrate the superiority of BDGOA.

Recently, many steganalysis approaches improve their feature extraction ability through adding convolutional layers. However, it often leads to a decrease of resolution in the feature map during downsampling, which makes it challenging to extract weak steganographic signals accurately. To address this issue, this paper proposes a multi-resolution steganalysis net (MRS-Net). MRS-Net adopts a multi-resolution network to extract global image information, fusing the output feature map to ensure high-dimensional semantic information and supplementing low-level detail information. Furthermore, the model incorporates an attention module which can analyze image sensitivity based on different channel and spatial information, thus effectively focusing on areas with rich steganographic signals. Multiple benchmark experiments on the BOSSBase 1.01 dataset demonstrate that the accuracy of MRS-Net significantly improves by 9.9% and 3.3% compared with YeNet and SRNet, respectively, demonstrating its exceptional steganalysis capability.

The deep integration of edge computing and Artificial Intelligence (AI) in IoT (Internet of Things)-enabled smart cities has given rise to new edge AI paradigms that are more vulnerable to attacks such as data and model poisoning and evasion of attacks. This work proposes an online poisoning attack framework based on the edge AI environment of IoT-enabled smart cities, which takes into account the limited storage space and proposes a rehearsal-based buffer mechanism to manipulate the model by incrementally polluting the sample data stream that arrives at the appropriately sized cache. A maximum-gradient-based sample selection strategy is presented, which converts the operation of traversing historical sample gradients into an online iterative computation method to overcome the problem of periodic overwriting of the sample data cache after training. Additionally, a maximum-loss-based sample pollution strategy is proposed to solve the problem of each poisoning sample being updated only once in basic online attacks, transforming the bi-level optimization problem from offline mode to online mode. Finally, the proposed online gray-box poisoning attack algorithms are implemented and evaluated on edge devices of IoT-enabled smart cities using an online data stream simulated with offline open-grid datasets. The results show that the proposed method outperforms the existing baseline methods in both attack effectiveness and overhead.

Abstract The improvement of non-oxide ceramic plasticity while maintaining the high-temperature strength is a great challenge through the classical strategy, which generally includes decreasing grain size to several nanometers or adding ductile binder phase. Here, we report that the plasticity of fully dense boron carbide (B4C) is greatly enhanced due to the boundary non-stoichiometry induced by high-pressure sintering technology. The effect decreases the plastic deformation temperature of B4C by 200 °C compared to that of conventionally-sintered specimens. Promoted grain boundary diffusion is found to enhance grain boundary sliding, which dominate the lower-temperature plasticity. In addition, the as-produced specimen maintains extraordinary strength before the occurrence of plasticity. The study provides an efficient strategy by boundary chemical change to facilitate the plasticity of ceramic materials.

Highlights Density functional theory calculations indicates that interstitial B atoms can tune the atomic spacing of host metal Os and achieve a reversal hydrogen adsorption-distance relationship. The structure–activity relationship between the spacing of active Os atoms and catalytic activity is established. Prepared OsB2 with increasing dOs-Os of 2.96 Å presents the optimal hydrogen evolution reaction activity (8 mV @ 10 mA cm−2) and robust stability in alkaline media.

Fermented Rosa rugosa ‘Dianhong’ petals with brown sugar, a biologically active food popularized in Dali Prefecture, Northwest Yunnan, China, are rich in bioactive compounds, especially polyphenols, exhibiting strong antioxidant activity. This study evaluated their antioxidant activities, total phenolic contents, and concentrations of polyphenols at different fermentation conditions using different assays: DPPH free-radical scavenging activity, Trolox equivalent antioxidant capacity (TEAC), ferric reducing antioxidant power (FRAP), Folin–Ciocalteu assays, and HPLC–MS/MS and HPLC–DAD methods. The results indicated that fermentation significantly increased (p < 0.05) the antioxidant activity and polyphenol concentration of R. rugosa ‘Dianhong’. Furthermore, Saccharomyces rouxii TFR-1 fermentation achieved optimal bioactivity earlier than natural fermentation. Overall, we found that the use of Saccharomyces rouxii (TFR-1) is a more effective strategy for the production of polyphenol-rich fermented R. rugosa ‘Dianhong’ petals with brown sugar compared to natural fermentation.

Toona ciliata, also known as Chinese mahogany, is a high-quality and fast-growing wood species with a high economic value. The wood properties of T. ciliata of different provenances vary significantly. In this study, we conducted comprehensive transcriptome and metabolome analyses of red and non-red T. ciliata wood cores of different provenances to compare their wood properties and explore the differential metabolites and genes that govern the variation in their wood properties. Through combined analyses, three differential genes and two metabolites were identified that are possibly related to lignin synthesis. The lignin content in wood cores from T. ciliata of different provenances shows significant variation following systematic measurement and comparisons. The gene Tci09G002190, one of the three differential genes, was identified as a member of the CAD (Cinnamyl alcohol dehydrogenase) gene family of T. ciliata, which is associated with lignin synthesis. Our data provide insights into the determinants of the wood properties in T. ciliata, providing a solid foundation for research into the subsequent mechanisms of the formation of T. ciliata wood.

Summary: Accurate pathological classification and grading of gliomas is crucial in clinical diagnosis and treatment. The application of deep learning techniques holds promise for automated histological pathology diagnosis. In this study, we collected 733 whole slide images from four medical centers, of which 456 were used for model training, 150 for internal validation, and 127 for multi-center testing. The study includes 5 types of common gliomas.A subtask-guided multi-instance learning image-to-label training pipeline was employed. The pipeline leveraged “patch prompting” for the model to converge with reasonable computational cost. Experiments showed that an overall accuracy of 0.79 in the internal validation dataset. The performance on the multi-center testing dataset showed an overall accuracy to 0.73. The findings suggest a minor yet acceptable performance decrease in multi-center data, demonstrating the model’s strong generalizability and establishing a robust foundation for future clinical applications.

Glioma undergoes adaptive changes, leading to poor prognosis and resistance to treatment. CD99 influences the migration and invasion of glioma cells and plays an oncogene role. However, whether CD99 can affect the adaptiveness of gliomas is still lacking in research, making its clinical value underestimated. Here, we enrolled our in-house and public multiomics datasets for bioinformatic analysis and conducted immunohistochemistry staining to investigate the role of CD99 in glioma adaptive response and its clinical implications.CD99 is expressed in more adaptative glioma subtypes and cell states. Under hypoxic conditions, CD99 is upregulated in glioma cells and is associated with angiogenesis and metabolic adaptations. Gliomas with over-expressed CD99 also increased the immunosuppressive tumor-associated macrophages. The relevance with tumor adaptiveness of CD99 presented clinical significance. We discovered that CD99 overexpression is associated with short-time recurrence and validated its prognostic value. Additionally, Glioma patients with high expression of CD99 were resistant to chemotherapy and radiotherapy. The CD99 expression was also related to anti-angiogenic and immune checkpoint inhibitor therapy response. Inhibitors of the PI3K-AKT pathway have therapeutic potential against CD99-overexpressing gliomas.Our study identified CD99 as a biomarker characterizing the adaptive response in glioma. Gliomas with high CD99 expression are highly tolerant to stress conditions such as hypoxia and antitumor immunity, making treatment responses dimmer and tumor progression. Therefore, for patients with CD99-overexpressing gliomas, tumor adaptiveness should be fully considered during treatment to avoid drug resistance, and closer clinical monitoring should be carried out to improve the prognosis.

Recurrent Neural Networks (RNNs) and their variants have been demonstrated tremendous successes in modeling sequential data such as audio processing, video processing, time series analysis, and text mining. Inspired by these facts, we propose human activity recognition technique to proceed visual data via utilizing convolution neural network (CNN) and Bidirectional-gated recurrent unit (Bi-GRU). Firstly, we extract deep features from frames sequence of human activities videos using CNN and then select most important features from the deep appearances to improve performance and decrease computational complexity of the model. Secondly, to learn temporal motions of frames sequence, we design Bi-GRU and feed those deep-important features extracted from frames sequence of human activities to Bi-GRU which learn temporal dynamics in forward and backward direction at each time step. We conduct extensive experiments on realistic videos of human activity recognition datasets YouTube11, HMDB51 and UCF101. Lastly, we compare the obtained results with existing methods to show the competence of our proposed technique.

Intelligent buildings play a fundamental role in achieving efficient energy management in the building sector in many countries worldwide. Improving energy consumption within a building can represent significant financial savings and reduce carbon emissions. However, intelligent buildings may impose additional burdens and challenges in their energy use. Wireless sensor networks are essential for the control systems of most intelligent building systems. There are still opportunities to reduce the power supplied to their sensor nodes in these networks. These nodes require power levels that range from microwatts to milliwatts. Typically, primary non-rechargeable batteries provide power to the nodes. Replacing or replenishing these batteries could become an impractical activity with detrimental environmental impacts. Energy harvesters (EHs) appear as a potential solution to this problem, as they could complement the use of batteries while extending their lifetimes at the sensor nodes.This paper provides a comprehensive review of the energy harvesting technologies currently under an experimental or development phase. Thus, one of the objectives here is to study if EHs can power by themselves or support current battery-powered sensor nodes at the building level. The environmental sources considered for harvester power extraction were mechanical motion, thermal, light, radio-frequency, and fluid flow. Also, the potential sites and building systems for extracting power through these harvesters are presented and reported. This paper includes the review of the challenges and opportunities for EHs depending on the mounting location and the particular characteristics of each EH technology. The research findings in this paper demonstrate that harvesters at the buildings can generate enough power to partially supply the power requirements for sensor nodes and even completely cover the power demands of specific operation modes.

New Zealand government’s Rural Broadband Initiative (RBI) aims to invest 400 million New Zealand dollar to provide 99% of New Zealanders with access to 50 Mbps peak broadband speed, with the remaining 1% at 10 Mbps by 2025. By 2017, stage 1 of the RBI has been completed, and research is needed to find out the level of usage, proficiency, and productivity achieved by then. Therefore, a survey was carried out to learn whether the rural residents and their communities are making good use of the new fast broadband connection. The survey collected data from 217 rural residents from North Island, and the results indicate that about half of the interview respondents are satisfied with the new broadband speed and the reliability which is offered by RBI stage 1. However, there is about 28% of the respondents disagreed with them. The majority of the Internet uses for rural residents are information searching, reading news, online entertainment, and online banking. Besides that, only a small proportion of respondents know how to utilize the Internet in their work/business and benefit/profit from it, e.g., using cloud technology capabilities and online marketing campaigns, etc. by then. Therefore, we argue that information and communications technologies (ICT) adoption is not only the availability of the infrastructure but also the beneficial outcomes of Internet availability. In other words, Internet skills in-depth training and education need to catch up with the infrastructure deployment, which is useful to fuel the digital productivity and inclusion for booming rural economies. The survey data-driven findings presented in this paper could serve as a reference to inform government policymakers and those who wish to create, invest, and take actions to speed up the economic and social growth of rural communities in Aotearoa New Zealand through the Internet while shifting from the Internet speed and traffic volume-driven to a more effective Internet connectivity and value-added driven rural economy.

Abstract Background Classical pterional appoach for temporal surgeries may cause atrophy and dysfunction of temporalis, injury to the facial nerve, and unnecessary cortical exposure. As an alternative to the classical pterional approach for such surgeries, we hereby describe an mini-temporal approach which reduces these risks and proven to be practical in neurological surgeries. Material and methods In the mini-temporal incision design, the frontal end of the incision never surpassed the hairline at the level of temporal line, and a one-layer skin-galea-muscle flap was detached from the cranium, effectively avoiding the injuries of facial nerve. The surgical bone window was completely located underneath the temporalis muscle, allowing it to be completely repositioned postoperatively. Results We demonstrated the application of mini-temporal approach in a variety of temporal region tumors, which can be applied to complete successful resective surgeries while effectively reducing injuries to extra-temporal cortex, temporalis, and facial nerve. There were no postoperative complications related to extra-temporal cortical damage, atrophy of temporalis, or injury to the facial nerve. Conclusion The mini-temporal approach can effectively shorten the time of craniotomy and closure, decrease the size of bony removal, increase the restoration of temporalis during closure, and lower the chance of facial nerve injury. Therefore, it improves cosmetic outcomes and reduces the risk of unintentional extra-temporal cortical injury, which fully embodies the minimally invasive principle in neurosurgery.

Abstract Primary central nervous system lymphoma (PCNSL) is a type of central nervous system restricted non-Hodgkin lymphoma, whose histopathological diagnosis is majorly large B cell lymphoma. To provide specific, evidence-based recommendations for medical professionals and to promote more standardized, effective and safe treatment for patients with PCNSL, a panel of experts from the Chinese Neurosurgical Society of the Chinese Medical Association and the Society of Hematological Malignancies of the Chinese Anti-Cancer Association jointly developed an evidence-based consensus. After comprehensively searching literature and conducting systematic reviews, two rounds of Delphi were conducted to reach consensus on the recommendations as follows: The histopathological specimens of PCNSL patients should be obtained as safely and comprehensively as possible by multimodal tomography-guided biopsy or minimally invasive surgery. Corticosteroids should be withdrawn from, or not be administered to, patients with suspected PCNSL before biopsy if the patient’s status permits. MRI (enhanced and DWI) should be performed for diagnosing and evaluating PCNSL patients where whole-body PET-CT be used at necessary time points. Mini-mental status examination can be used to assess cognitive function in the clinical management. Newly diagnosed PCNSL patients should be treated with combined high-dose methotrexate-based regimen and can be treated with a rituximab-inclusive regimen at induction therapy. Autologous stem cell transplantation can be used as a consolidation therapy. Refractory or relapsed PCNSL patients can be treated with ibrutinib with or without high-dose chemotherapy as re-induction therapy. Stereotactic radiosurgery can be used for PCNSL patients with a limited recurrent lesion who were refractory to chemotherapy and have previously received whole-brain radiotherapy. Patients with suspected primary vitreoretinal lymphoma (PVRL) should be diagnosed by vitreous biopsy. PVRL or PCNSL patients with concurrent VRL can be treated with combined systemic and local therapy.

Modern linguistic theories and network science propose that language and speech processing are organized into hierarchical, segregated large-scale subnetworks, with a core of dorsal (phonological) stream and ventral (semantic) stream. The two streams are asymmetrically recruited in receptive and expressive language or speech tasks, which showed flexible functional segregation and integration. We hypothesized that the functional segregation of the two streams was supported by the underlying network segregation. A dynamic conditional correlation approach was employed to construct framewise time-varying language networks and k-means clustering was employed to investigate the temporal-reoccurring patterns. We found that the framewise language network dynamics in resting state were robustly clustered into four states, which dynamically reconfigured following a domain-separation manner. Spatially, the hub distributions of the first three states highly resembled the neurobiology of speech perception and lexical-phonological processing, speech production, and semantic processing, respectively. The fourth state was characterized by the weakest functional connectivity and was regarded as a baseline state. Temporally, the first three states appeared exclusively in limited time bins (∼15%), and most of the time (> 55%), state 4 was dominant. Machine learning-based dFC-linguistics prediction analyses showed that dFCs of the four states significantly predicted individual linguistic performance. These findings suggest a domain-separation manner of language network dynamics in resting state, which forms a dynamic “meta-network” framework to support flexible functional segregation and integration during language and speech processing.

Background and ObjectivesPatients with primary malignant brain tumors may experience mental health disturbances that can significantly affect their daily life. This study aims to identify risk factors and generate predictive models for postoperative mental health disturbances (PMHDs) in adult glioma patients in accordance with different clinical periods; additionally, survival analyses will be performed.MethodsThis longitudinal cohort study included 2,243 adult patients (age at diagnosis ≥ 18 years) with nonrecurrent glioma who were pathologically diagnosed and had undergone initial surgical resection. Six indicators of distress, sadness, fear, irritability, mood and enjoyment of life, ranging from 0-10, were selected to assess PMHDs in glioma patients in the third month after surgery, mainly referring to the M.D. Anderson Symptom Inventory Brain Tumor Module (MDASI-BT). Factor analysis (FA) was applied on these indicators to divide participants into PMHD and control groups based on composite factor scores. Survival analyses were performed, and separate logistic regression models were formulated for preoperative and postoperative factors predicting PMHDs.ResultsA total of 2,243 adult glioma patients were included in this study. Based on factor analysis results, 300 glioma patients had PMHDs in the third postoperative month, and the remaining 1,943 were controls. Candidate predictors for PMHDs in the preoperative model were associated with age, clinical symptoms (intracranial space-occupying lesion, muscle weakness and memory deterioration), and tumor location (corpus callosum, basal ganglia and brainstem), whereas age, clinical symptoms (nausea and memory deterioration), tumor location (basal ganglia and brainstem), hospitalization days, WHO grade 4, postoperative chemotherapy or radiotherapy and postoperative Karnofsky Performance Scale (KPS) served as important factors in the postoperative model. In addition, the median overall survival (OS) time for glioma patients with PMHDs was 19 months, compared to 13 months for glioblastoma, IDH-wild type (GBM) patients with PMHDs.ConclusionThe risk factors for PMHDs were identified. These findings may provide new insights into predicting the probability of PMHD occurrence in glioma patients in addition to aiding effective early intervention and improving prognosis based on different clinical stages.

Abstract Although advanced anode materials for the lithium‐ion battery have been investigated for decades, a reliable, high‐capacity, and durable material that can enable a fast charge remains elusive. Herein, we report that a metal phosphorous trichalcogenide of MnPS3 (manganese phosphorus trisulfide), endowed with a unique and layered van der Waals structure, is highly beneficial for the fast insertion/extraction of alkali metal ions and can facilitate changes in the buffer volume during cycles with robust structural stability. The few‐layered MnPS3 anodes displayed the desirable specific capacity and excellent rate chargeability owing to their good electronic and ionic conductivities. When assembled as a half‐cell lithium‐ion battery, a high reversible capacity of 380 mA h g−1 was maintained by the MnPS3 after 3000 cycles at a high current density of 4 A g−1, with a capacity retention of close to or above 100%. In full‐cell testing, a reversible capacity of 450 mA h g−1 after 200 cycles was maintained as well. The results of in‐situ TEM revealed that MnPS3 nanoflakes maintained a high structural integrity without exhibiting any pulverization after undergoing large volumetric expansion for the insertion of a large number of lithium ions. Their kinetics of lithium‐ion diffusion, stable structure, and high pseudocapacitance contributed to their comprehensive performance, for example, a high specific capacity, rapid charge–discharge, and long cyclability. MnPS3 is thus an efficient anode for the next generation of batteries with a fast charge/discharge capability.

Abstract Sodium ion batteries (SIBs) and potassium ion batteries (PIBs) have caught numerous attention due to the low cost and abundant availability of sodium and potassium. However, their power density, cycling stability and safety need further improvement for practical applications. Investigations on the reaction mechanisms and structural degradation when cycling are of great importance. In situ transmission electron microscopy (TEM) is one of the most significant techniques to understand and monitor electrochemical processes at an atomic scale with real‐time imaging. In this review, the current progress in unraveling reaction mechanisms of electrode materials for SIBs and PIBs via in situ TEM is summarized. First, the importance of in situ TEM is highlighted. Then, based on the three types of electrochemical reaction, i.e., intercalation reaction, conversion reaction and alloying reaction, the structural evolution and reaction kinetics at atomic resolution, and their relation to the electrochemical performance of electrode materials are reviewed and described in detail. Finally, future directions of in situ TEM for SIBs and PIBs are proposed. Therefore, the in‐depth understanding revealed by in situ TEM will give an instructive guide in rational design of electrode materials for high performance electrode materials of SIBs and PIBs.

This paper provides a view of green technologies with the relations to sustainability. This paper also discusses the needs of the new international journal, Green Technologies and Sustainability (GTS).

The reaction of a conductive ferroelectric matter to external electric field remains largely unknown. Here, the authors reveal the relationship between the electrically-driven crystalline domain transition along the multiple-polar directions and the resistance change.

NAC-LIKE, ACTIVATED BY AP3/PI (NAP) is a NAC transcription factor regulating leaf senescence in Arabidopsis thaliana. In wild tobacco Nicotiana attenuata, a nuclear localized NAC transcription factor NaNAC29 was identified to be highly elicited after inoculation of Alternaria alternata, a notorious necrotic fungus on tobacco species. The NaNAC29 possesses similar tertiary structure to NAP with 60% amino acid identity. However, it remains unknown the role of NaNAC29 in plant defense responses to A. alternata and leaf senescence in N. attenuata. In this paper, Defensin-like protein 1 (NaDLP1) was highly induced in N. attenuata after A. alternata inoculation and bigger lesions were developed in NaDLP1-silenced plants. Interestingly, A. alternata-induced NaDLP1 was reduced by 76% in VIGS NaNAC29 plants and by 61% in JA deficient irAOC plants at 3 days post inoculation. The regulation of NaDLP1 expression by NaNAC29 was clearly independent on JA pathway, since exogenous methyl jasmonate treatment could not complement the induction levels of NaDLP1 in NaNAC29-silenced plants to the levels in WT plants. Otherwise, the expression of NaNAC29 was low expressed in young leaves but highly in senescent leaves and dark-treated leaves. NaNAC29-silenced plants, which were generated by virus-induced gene silencing (VIGS NaNAC29), showed delayed senescence phenotype. In addition, constitutive over-expression of NaNAC29 in A. thaliana could rescue the delayed-senescence phenotype of nap and caused precocious leaf senescence of wild-type Col-0 plants. All the data above demonstrate that NaNAC29 is a NAP homolog in N. attenuata participating in the defense responses to A. alternata by regulation of a defensin protein NaDLP1 and promoting leaf senescence.

The clinical presentation of primary hyperparathyroidism (PHPT) differs between patients from developed and developing countries. In China, the clinical pattern has changed over the past few decades. Our aim was to elucidate general changes in the clinical characteristics of PHPT from 2010 to 2021. We enrolled 343 patients with PHPT at the Qilu Hospital of Shandong University, Jinan, China, from January 2010 to May 2021, including both surgical and non-surgical patients. Patients were divided into two subgroups, 2010–2016 (group A, n = 152) and 2017–2021 (group B, n = 191), based on the time span. We compared clinical manifestations and laboratory result data between these two groups. The mean patient age was 52.59 ± 13.55 years, and the male-to-f emale ratio was 1:2.54. Of the 343 patients, 183 (53.35%) had symptomatic PHPT; bone pain, urolithiasis, and fatigue were the most common symptoms. Post-operative pathology showed that 96.20% of the patients had parathyroid adenoma, whereas 2.41% had parathyroid carcinoma. Great changes occurred between 2010 and 2021; the percentage of patients with asymptomatic PHPT (aPHPT) increased from 36.18% in group A to 54.97% in grou p B. Moreover, patients in group B showed significantly lower serum calcium, alkaline ph osphatase, parathyroid hormone, and urinary phosphate levels but higher serum 25-hydroxyvitamin D levels than those in group A. Clinical presentations in group B were also m ilder. In conclusion, the clinical characteristics of Chinese PHPT patients changed dramatically from 2010 to 2021, with asymptomatic PHPT (aPHPT becoming the predominant type over the last 3 years.

β-Zn4Sb3 has promising thermoelectric performance, but its ionic migration properties make it prone to degradation. Here the authors exploit the ion migration in an electric field-assisted synthesis method, fast producing β-Zn4Sb3 with improved phase stability and extended temperature range for the thermoelectric operation.

Underwater Wireless Sensor Networks (UWSNs) are widely used in many fields, such as regular marine monitoring and disaster warning. However, UWSNs are still subject to various limitations and challenges: ocean interferences and noises are high, bandwidths are narrow, and propagation delays are high. Sensor batteries have limited energy and are difficult to be replaced or recharged. Accordingly, the design of routing protocols is one of the solutions to these problems. Aiming at reducing and balancing network energy consumption and effectively extending the life cycle of UWSNs, this paper proposes a Hierarchical Adaptive Energy-efficient Clustering Routing (HAECR) strategy. First, this strategy divides hierarchical regions based on the depth of the sensor node in a three-dimensional (3D) space. Second, sensor nodes form different competition radii based on their own relevant attributes and remaining energy. Nodes in the same layer compete freely to form clusters of different sizes. Finally, the transmission path between clusters is determined according to comprehensive factors, such as link quality, and then the optimal route is planned. The simulation experiment is conducted in the monitoring range of the 3D space. The simulation results prove that the HAECR clustering strategy is superior to LEACH and UCUBB in terms of balancing and reducing energy consumption, extending the network lifetime, and increasing the number of data transmissions.

ObjectiveCingulate cortex and cingulum both play crucial roles in limbic system. The aim of study is to observe and analyze surgical outcomes of cingulate gyrus glioma through extents of resection (EORs), overall survival (OS), and postsurgical neurological outcome.MethodThe authors retrospectively studied 95 consecutive adult cases of primary cingulate gliomas that all underwent craniotomies and tumor resection. The patients were classified into unitary sub-region based on the four-division model. The information of clinical symptoms, pathology, EOR, postoperative neurological outcome and survival were analyzed through group comparison.ResultLow-grade gliomas (LGGs) were more prevalent (69.47%) for cingulate gyrus. Diffuse astrocytoma (40.00%) was most common histopathological diagnosis in total. Regarding sub-regions tumor involved in, midcingulate cortex (MCC) glioma was most prevalent (54.74%) followed by anterior cingulate cortex (ACC) glioma. Among all patients, 83 patients (87.37%) received EOR ≥ 90%. In LGG group, 58 patients (87.88%) received EOR ≥ 90%. The achievement of EOR significantly correlated with survival (P = 0.006). MCC cases were significantly associated with short-term morbidity in either language or motor function (P = 0.02). Majority of ACC cases (80.65%) escaped from any short-term deficits and nearly 90% free for permanent morbidity. Tumors in the dominant hemisphere were significantly associated with language dysfunction or cognition dysfunction, either short-term (P=0.0006) or long-term morbidity (P=0.0111). Age was the only postoperative susceptible predictor for all types of transient (P=0.021) and permanent (P=0.02) neurological deficit.ConclusionRegarding cingulate gyrus glioma, the management of surgical plans could be carried out into four sub-region level. In spite of short-term neurological dysfunction caused by surgical procedure, majority of transient dysfunction could be relieved or recovered in long-term. The necessary effort to prolong overall survival is still to achieve advisable EOR.

Fog computing is a new computing paradigm for meeting ubiquitous massive access and latency-critical applications by moving the processing capability closer to end users. The geographical distribution/floating features with potential autonomy requirements introduce new challenges to the traditional methodology of network access control. In this paper, a blockchain-enabled fog resource access and granting solution is proposed to tackle the unique requirements brought by fog computing. The smart contract concept is introduced to enable dynamic, and automatic credential generation and delivery for an independent offer of fog resources. A per-transaction negotiation mechanism supports the fog resource provider to dynamically publish an offer and facilitates the choice of the preferred resource by the end user. Decentralized authentication and authorization relieve the processing pressure brought by massive access and single-point failure. Our solution can be extended and used in multi-access and especially multi-carrier scenarios in which centralized authorities are absent.

Abstract Background This study aimed to identify the most valuable predictors of prognosis in glioblastoma (GBM) patients and develop and validate a nomogram to estimate individualized survival probability. Methods We conducted a real-world retrospective cohort study of 987 GBM patients diagnosed between September 2010 and December 2018. Computer generated random numbers were used to assign patients into a training cohort (694 patients) and internal validation cohort (293 patients). A least absolute shrinkage and selection operator (LASSO)-Cox model was used to select candidate variables for the prediction model. Cox proportional hazards regression was used to estimate overall survival. Models were internally validated using the bootstrap method and generated individualized predicted survival probabilities at 6, 12, and 24 months, which were compared with actual survival. Results The final nomogram was developed using the Cox proportional hazards model, which was the model with best fit and calibration. Gender, age at surgery, extent of tumor resection, radiotherapy, chemotherapy, and IDH1 mutation status were used as variables. The concordance indices for 6-, 12-, 18-, and 24-month survival probabilities were 0.776, 0.677, 0.643, and 0.629 in the training set, and 0.725, 0.695, 0.652, and 0.634 in the validation set, respectively. Conclusions Our nomogram that assesses individualized survival probabilities (6-, 12-, and 24-month) in newly diagnosed GBM patients can assist healthcare providers in optimizing treatment and counseling patients. Trial registration: retrospectively registered.

Context features are mostly used to determine the boundary of a target, which allows one to better locate an object. In this paper, we propose the fusion of the spatial attention mechanism and contextual features to simulate the recognition of objects based on the human eye, thereby improving the detection accuracy of detectors. We chose the PASCAL VOC2007+2012 general dataset to test the generality of our method and examined the improved accuracy of our proposed detector on various targets. Our method showed improved accuracy for small targets and partially overlapping targets. Our proposed model improved the detector’s accuracy by 3.34%.

Different languages rely on different vocal sounds to convey meaning. Here the authors show that language-general coding of pitch occurs in the non-primary auditory cortex for both tonal (Mandarin Chinese) and non-tonal (English) languages, with some language specificity on the population level.

The mechanism for the enhanced piezoelectricity in (K,Na)NbO3 based ceramics has not been fully understood. Here, the authors find that the dopants induced tetragonal phase and the accompanying high-density nanoscale heterostructures are responsible for the high dielectric and piezoelectric properties.

Abstract Background The Coronavirus disease 2019 (COVID-19) pandemic has extraordinarily impacted global healthcare. Neuro-oncological surgery units have peculiar features that make them highly relevant in the strategic reaction to the pandemic. In this Chinese Society of Neuro-Oncology (CSNO) initiated survey, we appraise the changes implemented in neuro-oncological surgery hospitals across different Asian countries and provide expert recommendations for responses at different stages of the pandemic. Methods We performed a 42-question survey of the early experience of neuro-oncological surgery practice in hospitals across different Asian countries on April 1, 2020, with responses closed on April 18, 2020. Results 144 hospitals completed the questionnaire. Most were in WHO post-peak phase of the pandemic and reported a median reduction in neuro-oncological surgery volume of 25–50%. Most (67.4%) resumed elective surgery in only COVID-19 negative patients;11.1% performed only emergency cases irrespective of COVID-19 status;2.1% suspended all surgical activity. Ninety-one (63.2%) relocated personnel from neurosurgery to other departments. Fifty-two (36.1%) hospitals suspended post-operative adjuvant therapy and 94 (65.2%) instituted different measures to administer post-operative adjuvant therapy. Majority (59.0%) of the hospitals suspended research activity. Most (70%) respondents anticipate that current neurosurgery restrictions will continue to remain for > 1 month. Conclusions Majority of the respondents to our survey reported reduced neuro-oncological surgery activity, policy modification, personnel reallocation, and curtailment of educational/research activities in response to the COVID-19 pandemic. The persistent widespread interruption of surgical neuro-oncology in even post-peak phases of the pandemic raises serious concerns about the long-term impact of the pandemic on neuro-oncological patients and highlights the essence of timely measures for pandemic preparedness, patient triage, and workforce protection.

Abstract Designing synergistic heterogeneous catalytic interfaces is the key to developing highly compatible pH‐universal electrocatalysts for complex chemical environments. Our theoretical calculation results demonstrate that the Ru‐Ru2P heterointerface can not only promote the redistribution of charges, but also reduce the d‐band center, and then enhances the adsorption capacity of the key intermediate. However, in situ and facile synthesis of Ru‐Ru2P heterostructures is severely limited by thermodynamic obstacles. Herein, we propose a molten salt‐assisted catalytic synthesis scheme, and successfully build a series of homologous metallic Ru‐Ru2P heterostructure catalysts with different molar ratios of Ru to P under atmospheric pressure and low‐temperature (400°C). The resultant Ru‐Ru2P with rich heterostructures show the Pt‐like HER performance in different pH media. Particularly, it is prominent under alkaline conditions (18 mV @ 10 mA cm−2), which outperforms the Pt catalyst (37 mV @ 10 mA cm−2). Furthermore, Ru‐Ru2P heterostructures also show certain potential in the electrolysis of seawater to produce hydrogen. This work represents a significant supplement of high‐efficiency pH‐universal HER catalysts, and provides a new light on interface engineering in energy technology fields and beyond.

Abstract Amorphous carbon shows great potential as an anode material for high-performance potassium-ion batteries; however, its abundant defects or micropores generally capture K ions, thus resulting in high irreversible capacity with low initial Coulombic efficiency (ICE) and limited practical application. Herein, pore engineering via a facile self-etching strategy is applied to achieve mesoporous carbon (meso-C) nanowires with interconnected framework. Abundant and evenly distributed mesopores could provide short K+ pathways for its rapid diffusion. Compared to microporous carbon with highly disordered structure, the meso-C with Zn-catalyzed short-range ordered structure enables more K+ to reversibly intercalate into the graphitic layers. Consequently, the meso-C shows an increased capacity by ~ 100 mAh g−1 at 0.1 A g−1, and the capacity retention is 70.7% after 1000 cycles at 1 A g−1. Multiple in/ex situ characterizations reveal the reversible structural changes during the charging/discharging process. Particularly, benefiting from the mesoporous structure with reduced specific surface area by 31.5 times and less defects, the meso-C generates less irreversible capacity with high ICE up to 76.7%, one of the best reported values so far. This work provides a new perspective that mesopores engineering can effectively accelerate K+ diffusion and enhance K+ adsorption/intercalation storage.

We investigate the energy-efficient channel estimation in wireless networks, where one pilot is inserted for every several data slots to estimate the channel coefficients. Both the channel state information estimation error and the time-varying model are considered. We first formulate the energy-efficient channel estimation problem into a mixed integer nonlinear programming (MINLP) problem, where the variables include the transmitted power and the number of data slots. Due to the NP-hard nature, we degenerate the MINLP problem into a series of non-concave optimization problems without integer variables. Then we solve these problems using successive convex approximation, geometric programming, and the Dinkelbach algorithm to obtain a point satisfying the Karush-Kuhn-Tucker (KKT) conditions. Furthermore, we develop a low-complexity sub-optimal scheme through binary variable relaxation to obtain a solution, and the convergence point satisfies the KKT conditions of the relaxed non-concave problem. Simulation results demonstrate the convergence and effectiveness of our proposed schemes.

Available charging information exchanges between mobile electric vehicles (EVs) and charging stations are significantly critical in spatio-temporal coordinated charging services introduced by smart girds. In this paper, we propose an efficient information transmission strategy for intelligent charging navigations of enormous moving EVs in large-scale urban environments. Specifically, we firstly design a heterogeneous VANET-based (vehicular ad hoc network) communication framework by means of mobile edge computing concept. In addition, based on the established multi-objective communication optimization problem, we propose an effective charging information dissemination algorithm between mobile edge computing servers and moving EVs. Moreover, in order to further increase charging information delivery efficiency and reduce redundant overheads, an improved local relaying scheme for charging information is designed on the basis of the formulated waiting time model. Finally, a series of simulation experiments are implemented to demonstrate the excellence and feasibility of our charging information transmission strategy.

In this paper, we propose intelligent reflecting surfaces (IRS) assisted secure wireless communications with multi-input and multi-output antennas (IRS-MIMOME). The considered scenario is an access point (AP) equipped with multiple antennas communicates with a multi-antenna enabled legitimate user in the downlink at the present of an eavesdropper configured with multiple antennas. Particularly, the joint optimization of the transmit covariance matrix at the AP and the reflecting coefficients at the IRS to maximize the secrecy rate for the IRS-MIMOME system is investigated, with two different assumptions on the phase shifting capabilities at the IRS, i.e., the IRS has the continuous reflecting coefficients and the IRS has the discrete reflecting coefficients. For the former case, due to the non-convexity of the formulated problem, an alternating optimization (AO)-based algorithm is proposed, i.e., for given the reflecting coefficients at the IRS, the successive convex approximation (SCA)-based algorithm is used to solve the transmit covariance matrix optimization, while given the transmit covariance matrix at the AP, alternative optimization is used again in individually optimizing of each reflecting coefficient at the IRS with other fixed reflecting coefficients. For the individual reflecting coefficient optimization, the closed-form or an interval of the optimal solution is provided. Then, the proposed algorithm is extended to the discrete reflecting coefficient model at the IRS. Finally, some numerical simulations have been done to demonstrate that the proposed algorithm outperforms other benchmark schemes.