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Forests have experienced unprecedented decline and mortality beyond their historical range in past decades, which is attributed to disturbances like drought, fire, insects and disease. Traditional disturbance detection methods that typically employ a time series perspective to identify discrete disturbance events within continuous tree growth signals and were mainly designed for gap-scale often fail to identify disturbances across populations. To more accurately identify growth suppression and release clusters based on the perspective of forest population dynamics, here we applied a novel method of detecting forest disturbances using a Gaussian mixture model with an expectation maximisation algorithm (DGE), to fit annual distributions of growth indicators, i.e., tree-ring index. We further compared our novel approach of DGE with five traditional methods based on two sets of real tree-ring data and simulated tree-ring data. The results show an improvement of accuracy (35.5 %–48.1 %), sensitivity (36.6 %–58.1 %), precision (21.2 %–51.5 %) and specificity (11.1 %–20.6 %) for the average of two real radial growth datasets and an improvement of accuracy (7.6 %–13.9 %), sensitivity (70 %), precision (100 %) and specificity (9.1 %–9.7 %) for the simulation radial growth dataset, indicating that our DGE approach performs much better than the traditional methods. This study contributes to an improved strategy and understanding for sustainable forest management in the context of climate warming, demonstrating that our DGE approach can be better applied to global forest disturbance detection under global change.

Regional budget assessments of methane (CH4) are critical for future climate and environmental management. CH4 emissions from rice cultivation (CH4-rice) constitute one of the most significant sources. However, previous studies mainly focus on historical emission estimates and lack consideration of future changes in CH4-rice under climate change or anthropogenic policy intervention, which hampers our understanding of long-term trends and the implementation of targeted emission reduction efforts. This study investigates the spatiotemporal variations of CH4-rice over the past two decades, using an integrated method to identify the major drivers and predict future emissions under climate change scenarios and policy perspectives. Results indicate that the CH4-rice emissions in China ranged between 6.21 and 6.57 Tg yr−1 over the past two decades, with a spatial distribution characterized by decreases in the south and increases in the north, associated with economic development, dietary shifts, technological advancements, and climate change. Factors such as the rate of straw added (RSA), fertilization, soil texture, temperature, and precipitation significantly influence CH4 emissions per unit rice production (CH4-urp), with RSA identified as the most significant tillage management factor, explaining 32 % of the variance. Lowering RSA to 8 % is beneficial for reducing CH4-urp. Scenario analysis indicates that under policies focusing on production or demand, CH4-rice is expected to increase by 0.3 % to 5.6 %, while adjusting RSA can reduce CH4-rice by 9.4 % to 10.0 %. Structural adjustments and regional cooperation serve as beneficial starting points for controlling and reducing CH4-rice in China, while optimizing industrial layouts contributes to regional development and CH4-rice control. Implementing policies related to maintaining field and crop yields can achieve a balance between rice supply and demand ahead of schedule. Dynamic adjustment of rice cultivation based on supply–demand balance can effectively reduce CH4-rice from excess rice production. By 2060, the reduction effect could reach 8.95 %–12.01 %. Introducing policy-driven tillage management measures as reference indicators facilitates the reduction of CH4-rice.

Abstract Background Head and neck squamous carcinoma (HNSCC) is known for its high aggressiveness and susceptibility to cervical lymph node metastasis, which greatly contributes to its poor prognosis. During tumorigenesis, many types of cancer cells acquire oncogenic super-enhancers (SEs) that drive the overexpression of oncogenes, thereby maintaining malignant progression. This study aimed to identify and validate the role of oncogenic SE-associated genes in the malignant progression of HNSCC. Methods We identified HNSCC cell-specific SE-associated genes through H3K27Ac ChIP-seq and overlapped them with HNSCC-associated genes obtained from The Cancer Genome Atlas (TCGA) dataset and Gene Expression Omnibus (GEO) datasets using weighted gene coexpression network analysis (WGCNA) to identify hub genes. The expression of IGF2BP2 and KLF7 in HNSCC was detected using clinical samples. To determine the biological role of IGF2BP2, we performed CCK-8, colony formation assay, Transwell migration assay, invasion assay, and orthotopic xenograft model experiments. Furthermore, we utilized a CRISPR/Cas9 gene-editing system, small-molecule inhibitors, ChIP-qPCR, and dual-luciferase reporter assays to investigate the molecular mechanisms of IGF2BP2 and its upstream transcription factors. Results Our study identified IGF2BP2 as a hub SE-associated gene that exhibited aberrant expression in HNSCC tissues. Increased expression of IGF2BP2 was observed to be linked with malignant progression and unfavorable prognosis in HNSCC patients. Both in vitro and in vivo experiments confirmed that IGF2BP2 promotes the tumorigenicity and metastasis of HNSCC by promoting cell proliferation, migration, and invasion. Mechanistically, the IGF2BP2-SE region displayed enrichment for H3K27Ac, BRD4, and MED1, which led to the inhibition of IGF2BP2 transcription and expression through deactivation of the SE-associated transcriptional program. Additionally, KLF7 was found to induce the transcription of IGF2BP2 and directly bind to its promoter and SE regions. Moreover, the abundance of KLF7 exhibited a positive correlation with the abundance of IGF2BP2 in HNSCC. Patients with high expression of both KLF7 and IGF2BP2 showed poorer prognosis. Lastly, we demonstrated that the small molecule inhibitor JQ1, targeting BRD4, attenuated the proliferation and metastatic abilities of HNSCC cells. Conclusions Our study reveals the critical role of IGF2BP2 overexpression mediated by SE and KLF7 in promoting HNSCC progression. Targeting SE-associated transcriptional programs may represent a potential therapeutic strategy in managing HNSCC.

Abstract Ameloblastoma is a benign tumor characterized by locally invasive phenotypes, leading to facial bone destruction and a high recurrence rate. However, the mechanisms governing tumor initiation and recurrence are poorly understood. Here, we uncovered cellular landscapes and mechanisms that underlie tumor recurrence in ameloblastoma at single-cell resolution. Our results revealed that ameloblastoma exhibits five tumor subpopulations varying with respect to immune response (IR), bone remodeling (BR), tooth development (TD), epithelial development (ED), and cell cycle (CC) signatures. Of note, we found that CC ameloblastoma cells were endowed with stemness and contributed to tumor recurrence, which was dominated by the EZH2-mediated program. Targeting EZH2 effectively eliminated CC ameloblastoma cells and inhibited tumor growth in ameloblastoma patient-derived organoids. These data described the tumor subpopulation and clarified the identity, function, and regulatory mechanism of CC ameloblastoma cells, providing a potential therapeutic target for ameloblastoma.

Abstract The monitoring of physiological parameters is a crucial topic in promoting human health and an indispensable approach for assessing physiological status and diagnosing diseases. Particularly, it holds significant value for patients who require long-term monitoring or with underlying cardiovascular disease. To this end, Visual Contactless Physiological Monitoring (VCPM) is capable of using videos recorded by a consumer camera to monitor blood volume pulse (BVP) signal, heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2) and blood pressure (BP). Recently, deep learning-based pipelines have attracted numerous scholars and achieved unprecedented development. Although VCPM is still an emerging digital medical technology and presents many challenges and opportunities, it has the potential to revolutionize clinical medicine, digital health, telemedicine as well as other areas. The VCPM technology presents a viable solution that can be integrated into these systems for measuring vital parameters during video consultation, owing to its merits of contactless measurement, cost-effectiveness, user-friendly passive monitoring and the sole requirement of an off-the-shelf camera. In fact, the studies of VCPM technologies have been rocketing recently, particularly AI-based approaches, but few are employed in clinical settings. Here we provide a comprehensive overview of the applications, challenges, and prospects of VCPM from the perspective of clinical settings and AI technologies for the first time. The thorough exploration and analysis of clinical scenarios will provide profound guidance for the research and development of VCPM technologies in clinical settings.

Abstract Pleomorphic adenoma (PA) is the most common benign tumour in the salivary gland and has high morphological complexity. However, the origin and intratumoral heterogeneity of PA are largely unknown. Here, we constructed a comprehensive atlas of PA at single-cell resolution and showed that PA exhibited five tumour subpopulations, three recapitulating the epithelial states of the normal parotid gland, and two PA-specific epithelial cell (PASE) populations unique to tumours. Then, six subgroups of PASE cells were identified, which varied in epithelium, bone, immune, metabolism, stemness and cell cycle signatures. Moreover, we revealed that CD36+ myoepithelial cells were the tumour-initiating cells (TICs) in PA, and were dominated by the PI3K-AKT pathway. Targeting the PI3K-AKT pathway significantly inhibited CD36+ myoepithelial cell-derived tumour spheres and the growth of PA organoids. Our results provide new insights into the diversity and origin of PA, offering an important clinical implication for targeting the PI3K-AKT signalling pathway in PA treatment.

Abstract With the increasing number of user terminals (UTs), the interference among UTs might significantly decrease the throughput of the low earth orbit satellite communication system. In this paper, the user scheduling method is investigated to suppress user interference. Specifically, leveraging the strong spatial directivity of satellite channels, a low‐complexity angle‐based orthogonal user selection (AOUS) algorithm is proposed, which selects UTs with nearly orthogonal channels via angle information of UTs. A rate‐based proportionally fair (PF)‐AOUS algorithm is further proposed to ensure fairness among UTs, which combines the AOUS with the PF criterion. To reduce complexity, an improved angle‐based PF‐AOUS algorithm that schedules UTs according to their pitch angles rather than their rates is proposed. In addition, efficient precoding schemes for orthogonal UTs are designed by combining the steering vector and power allocation matrix, and it is shown that precoding can be converted into power allocation problems that further balance fairness and throughput. The numerical results indicate that the AOUS achieves a near‐optimal sum rate performance, and the angle‐based PF‐AOUS has the similar performance to the rate‐based PF‐AOUS, which achieves a high fairness index with the proposed precoding scheme.

Abstract Tumor budding (TB) is a small tumor cell cluster with highly aggressive behavior located ahead of the invasive tumor front. However, the molecular and biological characteristics of TB and the regulatory mechanisms governing TB phenotypes remain unclear. This study reveals that TB exhibits a particular dynamic gene signature with stemness and partial epithelial‐mesenchymal transition (p‐EMT). Importantly, nuclear expression of CYTOR is identified to be the key regulator governing stemness and the p‐EMT phenotype of TB cells, and targeting CYTOR significantly inhibits TB formation, tumor growth and lymph node metastasis in head and neck squamous cell carcinoma (HNSCC). Mechanistically, CYTOR promotes tumorigenicity and metastasis of TB cells by facilitating the formation of FOSL1 phase‐separated condensates to establish FOSL1‐dependent super enhancers (SEs). Depletion of CYTOR leads to the disruption of FOSL1‐dependent SEs, which results in the inactivation of cancer stemness and pro‐metastatic genes. In turn, activation of FOSL1 promotes the transcription of CYTOR. These findings indicate that CYTOR is a super‐lncRNA that controls the stemness and metastasis of TB cells through facilitating the formation of FOSL1 phase separation and SEs, which may be an attractive target for therapeutic interventions in HNSCC.

Electrocardiogram (ECG) reconstruction from contact photoplethysmogram (PPG) would be transformative for cardiac monitoring. We investigated the fundamental and practical feasibility of such reconstruction by first replicating pioneering work in the field, with the aim of assessing the methods and evaluation metrics used. We then expanded existing research by investigating different cycle segmentation methods and different evaluation scenarios to robustly verify both fundamental feasibility, as well as practical potential. We found that reconstruction using the discrete cosine transform (DCT) and a linear ridge regression model shows good results when PPG and ECG cycles are semantically aligned—the ECG R peak and PPG systolic peak are aligned—before training the model. Such reconstruction can be useful from a morphological perspective, but loses important physiological information (precise R peak location) due to cycle alignment. We also found better performance when personalization was used in training, while a general model in a leave-one-subject-out evaluation performed poorly, showing that a general mapping between PPG and ECG is difficult to derive. While such reconstruction is valuable, as the ECG contains more fine-grained information about the cardiac activity as well as offers a different modality (electrical signal) compared to the PPG (optical signal), our findings show that the usefulness of such reconstruction depends on the application, with a trade-off between morphological quality of QRS complexes and precise temporal placement of the R peak. Finally, we highlight future directions that may resolve existing problems and allow for reliable and robust cross-modal physiological monitoring using just PPG.

BackgroundThe increasing number of older adults with mental, behavioral, and memory challenges presents significant public health concerns. Reminiscence is one type of nonpharmacological intervention that can effectively evoke memories, stimulate mental activities, and improve psychological well-being in older adults through a series of discussions on previous experiences. Fully immersive virtual reality (FIVR) may be a useful tool for reminiscence interventions because it uses realistic virtual environments connected to a person’s significant past stories. ObjectiveThis review aims to examine empirical evidence regarding the application of FIVR in reminiscence interventions, its usability and acceptability, and its effectiveness in assisting the intervention to achieve optimal outcomes. MethodsWe followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach for scoping reviews. The PubMed, PsycINFO, Embase, CINAHL, Web of Science, ACM, and IEEE Xplore electronic databases were used for the search. We included peer-reviewed studies that used FIVR as an assistive tool for reminiscence interventions; were published between January 1, 2000, and August 1, 2022; reported empirical research; involved older adults as participants; and addressed health- and behavior-related outcomes or the feasibility and usability of FIVR. We used Endnote X9 to organize the search results and Microsoft Excel for data extraction and synthesis. ResultsOf the 806 articles collected from the databases and other resources, 11 were identified. Most of the studies involved participants aged between 70 and 90 years. Only 1 study did not involve those with cognitive impairments, whereas 3 specifically targeted people living with dementia. The results indicated that FIVR reminiscence interventions enhanced engagement and reduced fatigue. Although some studies have observed positive effects on anxiety, apathy, depression, cognitive functions, and caregiver burden reduction, these findings were inconsistent across other research. In addition, FIVR showed overall usability and acceptability with manageable side effects among older adults across various health conditions during reminiscence sessions. However, 1 study reported adverse feelings among participants, triggered by unpleasant memories evoked by the virtual reality content. ConclusionsThe role of FIVR in reminiscence interventions remains nascent, with limited studies evaluating its impacts on older adults. Many of the reviewed studies had notable limitations: small sample sizes, absence of rigorous research design, limited assessment of long-term effects, lack of measures for health and behavior outcomes, and quality of life. Beyond these limitations, this review identified a list of future research directions in 6 categories. On the basis of the review findings, we provide practical recommendations to enhance FIVR reminiscence interventions, covering topics such as virtual reality content, device choice, intervention types, and the role and responsibility of facilitators.

Abstract Organic electrochemical transistors (OECTs) have emerged as versatile platforms for broad applications spanning from flexible and wearable integrated circuits to biomedical monitoring to neuromorphic computing. A variety of materials and tailored micro/nanostructures have recently been developed to realized stretchable OECTs, however, a solid-state OECT with high elasticity has not been demonstrated to date. Herein, we present a general platform developed for the facile generation of highly elastic all-polymer OECTs with high transconductance (up to 12.7 mS), long-term mechanical and environmental durability, and sustainability. Rapid prototyping of these devices was achieved simply by transfer printing lithium bis(trifluoromethane)sulfonimide doped poly(3,4-ethylenedioxythiophene): poly(styrene sulfonate) (PEDOT:PSS/LiTFSI) microstructures onto a resilient gelatin-based gel electrolyte, in which both depletion-mode and enhancement-mode OECTs were produced using various active channels. Remarkably, the elaborate 3D architectures of the PEDOT:PSS were engineered, and an imprinted 3D-microstructured channel/electrolyte interface combined with wrinkled electrodes provided performance that was retained (> 70%) through biaxial stretching of 100% strain and after 1000 repeated cycles of 80% strain. Furthermore, the anti-drying and degradable gelatin and the self-crosslinked PEDOT:PSS/LiTFSI jointly enabled stability during > 4 months of storage and on-demand disposal and recycling. This work thus represents a straightforward approach towards high-performance stretchable organic electronics for wearable/implantable/neuromorphic/sustainable applications.

Abstract Background Trimalleolar fracture is a common ankle fracture with serious complications and costly healthcare problem. Most studies used clinical assessments to evaluate the functional status of the patients. Although clinical assessments are valid, they are static and subjective. Dynamic, objective and precise evaluations such as gait analysis are needed. Ankle biomechanics studies on gait in patients with trimalleolar fractures are still rare. This study aimed to investigate the clinical outcomes and gait biomechanics in patients with trimalleolar fractures in the early postoperative period and compared to healthy controls. Methods This was a cross-sectional study. 12 patients with trimalleolar fractures were recruited, and 12 healthy people served as controls. All patients underwent clinical assessments: Olerud and Molander ankle score (OMAS), ankle swelling and passive range of motion (ROM) of ankle, and completed gait biomechanical analysis when weight-bearing was allowed: temporal-spatial parameters, plantar pressure distributions, and surface electromyography (sEMG). The control group only performed gait test. Results Patients had poor outcomes of clinical assessments in the short-term. During gait analysis, patients presented compromised gait patterns: shorter step length, larger step width, slower walking speed and shorter single support compared to healthy controls (P

To achieve fast and secure information steganography in underwater acoustic channel scenarios, this paper proposes a PSO (Particle Swarm Optimization) and IWT (integer wavelet transform) based image steganography algorithm for underwater acoustic communication. Firstly, the underwater image to be embedded is interleaved and packed to generate the secret information code-stream to improve the detection and recovery performance of transmission errors. Secondly, the cover image is divided into non-overlapping blocks and IWT is applied to each block, which can save PSO search space and improve the optimal solution performance. Thirdly, the embedding position matrix of the high frequency sub-band coefficients is chaotic scrambled, and PSO is used to select the optimal key to obtain the optimal matching position for the secret information to produce the best stego-image quality. Finally, transmission error detection and recovery measures are applied to the extracted secret information to improve the reconstruction quality in underwater acoustic channel scenarios. Experimental results show that the proposed algorithm outperforms existing approaches in terms of information embedding capacity and steganographic visual quality, meeting the requirements of safety and real-time performance of underwater communication. Moreover, it also has the ability of error detection and recovery for harsh underwater acoustic channel.

Abstract In this paper, massive multiple‐input‐multiple‐output (MIMO) wireless communication systems are considered to investigate joint transceiver beamforming. A base station (BS) equipped with a uniform planar array (UPA) serves several multi‐antennas users in a single cell. Based on the channel state information (CSI), the low complexity design of transceiver beamforming to minimize the transmit power subject to some quality of service (QoS) constraints is investigated. As the upper bound of the transmit power performance, the existing iteration‐based algorithms are leveraged as a reference. A general deep learning (DL)‐based framework and deep neural network (DNN) structure are proposed to reduce the complexity of the existing algorithms, where the properly trained DNN structure can learn directly from CSI. Consider the complexity of the DNN structure itself, a heuristic algorithm is proposed to replace the DNN structure, which takes the max‐eigenvalue‐eigenvector of the CSI as the direction of receive beamforming directly. The DNN structure is trained in the offline stage, therefore, only the complexity in the online stage is taken into consideration. Based on the numerical simulation, the complexity of the proposed DL‐based framework and the transceiver beamforming algorithms is reduced significantly while maintaining nearly the optimal performance compared with the existing iterative algorithms.

Satellite communication is an indispensable part of future wireless communications given its global coverage and long-distance propagation. In satellite communication systems, channel acquisition and energy consumption are two critical issues. To this end, we investigate the tradeoff between the total energy efficiency (TEE) and minimum EE (MEE) for robust multigroup multicast satellite communication systems in this paper. Specifically, under the total power constraint, we investigate the robust beamforming aimed at balancing the TEE-MEE, so as to achieve the balance between the fairness and total performance on the system EE. For this optimization problem, we first model the balancing problem as a nonconvex problem while deriving its approximate closed-form average user rate. Then, the nonconvex problem is handled by solving convex programs sequentially with the help of the semidefinite relaxation and the concave-convex procedure. In addition, depending on the solution rank value, Gaussian randomization and eigenvalue decomposition method are applied to generate the feasible solutions. Finally, simulation results illustrate that the proposed approach can effectively achieve the balance between the TEE and MEE, thus realizing a tradeoff between fairness and system EE performance. It is also indicated that the proposed robust approach outperforms the conventional baselines in terms of EE performance.

Abstract To validate the accuracy of Cone beam computed tomography (CBCT) cervical spine modeling with three dimensional (3D)-3D registration for in vivo measurements of cervical spine kinematics. CBCT model accuracy was validated by superimposition with computed tomography (CT) models in 10 healthy young adults, and then cervical vertebrae were registered in six end positions of functional movements, versus a neutral position, in 5 healthy young adults. Registration errors and six degrees of freedom (6-DOF) kinematics were calculated and reported. Relative to CT models, mean deviations of the CBCT models were

BackgroundSeveral studies have revealed a positive correlation between a Helicobacter pylori (HP) infection and the risk of non-alcoholic fatty liver disease (NAFLD). This meta-analysis was conducted to explore further the relationship between HP infection and NAFLD in the Asian and non-Asian populations.MethodsRelevant studies published from inception to July 22, 2021, in the following databases: PubMed, EMBASE, the Cochrane library, and Web of Science were comprehensively searched. The odds ratio (OR) and hazard ratio (HR) with a 95% confidence interval (95%CI) were pooled by the random-effects model or fixed-effects model. Additionally, subgroup and sensitivity analyses were performed. The funnel plot and the Egger test were used to estimate publication bias.ResultsThis meta-analysis included 25 studies involving 107,306 participants. Positive associations between HP infection and NAFLD were found both for the Asian (OR = 1.30, 95% CI: 1.13–1.49, P < 0.01; I2 = 94.30%, P < 0.01) and non-Asian populations (OR = 1.42, 95% CI: 1.04–1.94, P = 0.03; I2 = 44.90%, P = 0.09). Moreover, similar results were observed in the Asian female group (OR = 1.31, 95% CI: 1.17–1.46, P < 0.01; I2 = 46.30%, P = 0.07) but not for the Asian male group. Subgroup analyses for the Asian population showed that there were differences in the association among NAFLD diagnosis methods (P < 0.01) and the study design (P < 0.01). However, subgroup and sensitivity analyses results showed that the association for the non-Asian population was not stable enough.ConclusionsThe data obtained in this systematic review and meta-analysis suggested that an HP infection was associated with an increased risk of NAFLD for Asian and non-Asian populations. However, the association was not found for Asian males. Further studies are required to establish the causal association, especially for the non-Asian population.Systematic review registrationIdentifier: CRD42021266871.

Objectives: The subjectivity of the Physician Global Assessment (PGA) is a limitation of the Mayo score in assessing severity of ulcerative colitis (UC). We compared treatment efficacy using endpoint definitions based on modified Mayo (mMayo) score, versus those based on Mayo score, using data from the tofacitinib OCTAVE program. Design: This post hoc analysis included data from two 8-week induction studies (OCTAVE Induction 1 and 2) and a 52-week maintenance study (OCTAVE Sustain). Methods: Remission and clinical response [with nonresponder imputation (NRI)] were assessed using mMayo (without PGA) and Mayo scores, and further stratified by prior tumor necrosis factor inhibitor (TNFi) failure status. Results: At week 8 of OCTAVE Induction 1 and 2, remission rates with placebo and tofacitinib 10 mg twice daily (BID), respectively, were 7.7% and 24.8% (mMayo) and 6.0% and 17.6% (Mayo). At week 52 of OCTAVE Sustain, remission rates with placebo, tofacitinib 5 and 10 mg BID, respectively, were 12.1%, 35.9%, and 42.1% (mMayo) and 11.1%, 34.3%, and 40.6% (Mayo). A statistically significant ( p

BackgroundFOSL1, a key component of the Activating protein-1 (AP-1) transcriptional complex, plays an important role in cancer cell migration, invasion, and proliferation. However, the impact of FOSL1 in ameloblastoma (AM) has not been clarified. Herein, we aimed to assess the expression of FOSL1 and investigate its functional role in AM.MethodsThe expression of FOSL1 was examined based on an immunohistochemistry analysis of 96 AM samples. Cell proliferation, migration, invasion, and tumorigenesis were assessed using Cell Counting Kit-8 (CCK-8), colony formation, Transwell, and sphere formation assays. RNA sequencing (RNA-seq) was employed to investigate the molecular alterations of AM cells upon FOSL depletion. Microarrays of AMs were downloaded from the Gene Expression Omnibus (GEO) database for bioinformatics analysis. In addition, patient-derived AM organoids were used to evaluate the therapeutic value of the AP-1 inhibitor.ResultsFOSL1 was detected in the nuclei of AMs and upregulated in conventional AMs compared to unicystic AMs and normal oral epithelium. Compared with primary AM, FOSL1 expression was significantly increased in recurrent AM. Genetic knockdown of FOSL1 suppressed the proliferation, migration, invasion, and sphere formation of AMs. Similar results were also observed by pharmacological inhibition of AP-1 activity. Moreover, the AP-1 inhibitor T5224 impeded the growth of organoids derived from AM patients. Mechanistically, our Ingenuity Pathway Analysis (IPA) and gene set enrichment analysis (GSEA) results revealed that depletion of FOSL1 inactivated kinetochore metaphase signaling and the epithelial–mesenchymal transition pathway and then impaired the aggressiveness of AM cells accordingly.ConclusionFOSL1 promotes tumor recurrence and invasive growth in AM by modulating kinetochore metaphase signaling and the epithelial–mesenchymal transition pathway; thus, it represents a promising therapeutic target for AM treatment.

Background Little is known about the sensate recovery of skin grafts over free non-neurotized muscle flaps. The aim of this study was to evaluate the sensitivity of free gracilis muscle flaps and meshed skin grafts without nerve coaptation. Methods Thirteen consecutive patients with a median age of 55 years (range, 21–70 years) who underwent lower extremity reconstruction between September 2014 and October 2016 were included. Complications, flap contour, skin perception, and sensate recovery were assessed. Results All flaps survived completely. In one patient, wound dehiscence and infection occurred 1 month after surgery. After a median follow-up of 14 months (range, 10–51 months), a satisfactory contour and skin perception were achieved. The Semmes-Weinstein (SW) monofilament test (154.8±22 g) and static two-point discrimination (2-PD) (12.6±0.7 mm) showed intermediate recovery compared to the surrounding site (41% and 76%, respectively). There was an intermediate correlation between flap size and sensate recovery (2-PD: r=0.27, P=0.36; SW test: r=0.45, P=0.12). Vibration sensation recovered to 60%, whereas thermal sensation remained poor (19% at 5°C and 25% at 25°C). Conclusions Finer sensation could be partially restored. However, thermal sensation remained poor.

Network slicing is a promising technology that can tailor the network to support diverse types of services over a common physical network infrastructure, and tenants can lease the customized slices from network providers to provide customized services for their users. This paper focuses on tenant profit optimization in 5G Radio Access Network (RAN) slicing and analyzes slice resource reservation and reconfiguration operation. A slice cost model is proposed, in which a base cost is included to compensate reconfiguration management overhead for the network providers. Increasing the accuracy of tenant resource requirement prediction can decrease tenant cost while guaranteeing QoS of its users. Further, we analyze the price strategy based on user traffic, and propose several alternative price scheme. In slicing across multiple Base Stations (BSs) scenario, we study two slice management operations, called slice mergence/split, similar but not identical to the breathing behavior of conventional cellular BS management. The tenant profit optimization problem across adjacent BSs is formulated, which can be used in slice mergence/splilt decision making. Taking VR (Virtual Reality) application as an example, simulation in allusion to the typical user arrival process is performed. The simulation indicates how these two operations can increase tenant profits.

In this article, we propose a novel deep domain adaptation method based on graph neural network (GNN) for multitemporal hyperspectral remote sensing images. In GNN, graphs are constructed for source and target data, respectively. Then the graphs are utilized in each hidden layer to obtain features. GNN operates on graph structure and the relations between data samples can be exploited. It aggregates features and propagate information through graph nodes. Thus, the extracted features have an improved smoothness in each spectral neighborhood which is beneficial to classification. Furthermore, the domain-wise correlation alignment (CORAL) and class-wise CORAL are jointly embedded in GNN network to achieve a joint distribution adaptation performance. By introducing the joint CORAL strategy in GNN, the extracted features can not only be aligned between domains but also have a superior discriminability in each domain. This domain adaptation network is named as joint CORAL-based graph neural network. Experiments using multitemporal Hyperion and NSF-funded center for airborne laser mapping datasets demonstrate the effectiveness of the proposed method.

For acquisition of accurate aerodynamic parameters of the pipeline suspension bridge, the numerical wind tunnel model for the typical girder section of the oil and gas pipeline suspension bridge was built, and SST k-ε model was used as the numerical wind tunnel turbulence model. The bypass flow pressure field distribution acquired from the numerical wind tunnel shows that the negative pressure area on the upper and lower surfaces of the pipeline is obvious, the largest positive pressure area appears on the windward side of the pipeline, and the pressure difference between the windward side and the leeward side of the truss girder in the inflow direction is particularly obvious. The bypass flow velocity field distribution shows that the pipeline and truss girder exert significant blocking effect on the wind speed, and the flow separation and vortex shedding phenomena occur apparently on the pipeline, windward railings and truss girder. According to the root mean square pressure of the flow field, vortex vibration is most likely to occur in the inflow side truss. Through the analysis of the three component coefficients of different pipeline diameters and different girder widths at the wind attack angles of －3°, 0° and 3°, it is concluded that the girder width has little influence on resistance coefficient and lift coefficient, and the torsion coefficient decreases with the increase of the girder width at －3° wind attack angle. The pipeline diameter definitively influences the three component coefficients, that is, with the increase of pipeline diameter, the resistance coefficient increases gradually, while the lift coefficient and torsion coefficient decrease gradually. The research results are expected to provide wind-resistant data support for the design of suspension bridge deck structure and the piping layout.

This paper studies the optimal three-dimensional (3-D) antenna array for direction finding when the antenna array is subject to geometric constraint. Two-dimensional (2-D) planar array has been widely used in existing direction finding systems, and the optimal geometry for planar array has also been investigated in existing works. However, the optimal antenna array in the 3-D space, especially when the positions of the antennas are subject to geometric constraint, has not been studied yet. In this paper, a novel approach based on coordinate transformation is proposed for optimal antenna array design in the 3-D space with geometric constraint. Due to geometric constraint, the position of each antenna has only two degrees-of-freedom even thought it has three coordinate values, so that coordinate transformation can be used to convert 3-D coordinates of the array elements to 2-D ones. Then, existing optimization approach for 2-D planar array can be applied to address the issue of optimal 3-D antenna array. Simulation results show that the proposed antenna array in this paper can outperform the defacto uniform circular array (UCA) even in the presence of geometric constraint. As a potential application, the result in this paper can be applied to design the high-frequency (HF) direction finding antenna arrays that are placed in mountain area.

Associative learning-based domain adaptation approach is investigated for the classification of hyperspectral remote sensing images in this article. It employs the criterion of cycle consistency to achieve features that are both domain-invariant and discriminative. Two cross-domain similarity matrices based on network-generated features and probability predictions are introduced in the two-step transition procedure. The associative learning with feature and prediction-based similarity metrics is referred to as augmented associative learning (AAL). The AAL-based domain adaptation network does not require target labeled information and can achieve unsupervised classification of the target image. The experimental results using Hyperion and AVIRIS hyperspectral data demonstrated the efficiency of the proposed approach.

N6-methyladenosine (m6A) is the most abundant internal mRNA modification in eukaryotes and is related to stability, localization, or translation efficiency in tumorigenesis. Autophagy plays an important role in the occurrence and development of tumours. However, the relationship between m6A and autophagy remains unclear. In this study, we used a rapamycin-induced autophagy model of oral squamous cell carcinoma (OSCC) cells, and observed increased m6A RNA methylation. When autophagy was activated, the methyltransferase-like 14 (METTL14) expression was upregulated and influenced the proliferation, migration, and invasiveness of OSCC cells. Through meRIP-seq and RNA-seq analysis, we found that METTL14 directly combined with eukaryotic translation initiation factor gamma 1 (eIF4G1) mRNA and decreased its RNA stability. According to the dual-luciferase reporter and mutagenesis assay, the mutated site 1 of exon 11 of eIF4G1 is the key target of METTL14. Knockdown of the main m6A binding protein YTHDF2 may rescue the shortened half-life of eIF4G1 mRNA induced by METTL14 overexpression. Furthermore, an in vivo tumour xenograft model confirmed that a high METTL14 expression can effectively reduce OSCC growth. Additionally, using clinical samples, we found that patients with advanced or moderately/poorly differentiated tumours exhibited lower METTL14 levels. Taken together, our results revealed that METTL14 mediated eIF4G1 expression via m6A modification and regulated autophagy levels and biological functions in OSCC. Our findings not only expand our understanding of the correlation between autophagy and RNA methylation in tumorigenesis but also present an opportunity to develop new therapeutic options.

The reduced graphene oxide (rGO)-promoted α-MnO2 nanorods-supported Pt (xPt-yrGO/α-MnO2, x = 0.93 wt%, y = 0.5, 1.0, and 2.0 wt%) nanocatalysts were prepared using a polyvinyl alcohol (PVA)-protected reduction method. After an appropriate loading of Pt on α-MnO2, the strong metal–support interaction between Pt and α-MnO2 was beneficial for an increase in catalytic activity. The simultaneous addition of rGO to α-MnO2 not only provided a more amount of benzene adsorption sites, but also acted as an electron transfer channel to accelerate charge migration, thus further improving catalytic activity of α-MnO2. Among all of the catalyst samples, 0.94Pt-1.0rGO/α-MnO2 showed the best catalytic performance with 90% benzene conversion at 160 °C and a gas hourly space velocity (GHSV) of 60,000 mL/(g h), which was better than that over the other Pt-based catalysts. The results of in situ DRIFTS characterization revealed that phenol, benzoquinone, and carboxylate species were the intermediates and eventually oxidized to CO2 and H2O. When sulfur dioxide was present, catalytic activity of α-MnO2 decreased due to the formation of manganese sulfate that blocked the active sites, while the loading of Pt and rGO hindered the chemisorption of SO2 and prevented the active sites of the catalyst from being poisoned by SO2, thus enhancing sulfur resistance of the catalyst. The 0.94Pt-1.0rGO/α-MnO2 catalyst presented in this work can be considered as a cost-effective and promising catalyst for the oxidative removal of volatile organic compounds.

Direction-of-arrival (DOA) estimation in the presence of mutual coupling among the antennas is an important problem in direction finding systems. To address the mutual coupling issue, a polynomial manifold interpolation approach is proposed in this paper. In this approach, a set of sample manifold vectors corresponding to pre-determined DOA grids are acquired and stored in advance in the direction finding receiver. The manifold vector corresponding to the DOA of interest can be obtained via polynomial interpolation over the sample manifold vectors. Then, MUtiple SIgnal Classification (MUSIC) algorithm can be used over the interpolated manifold vector to obtain the desired DOA estimation. Compared to the linear manifold interpolation, the density of the pre-determined DOA grids can be greatly reduced for polynomial manifold interpolation, and thus the burden for acquisition and storage of the sample manifold vectors can be also reduced substantially. Simulation results are also presented in this paper to demonstrate the effectiveness of the proposed approach.

The integration of satellite and terrestrial 5G networks aims to provide ubiquitous coverage, improve service reliability, and enable the network scalability. However, the inherent characteristics of satellite channels bring challenges on the air interface design of integrated terrestrial-satellite networks. For example, for low earth orbits (LEO) mobile satellite communication (SatCom) system, it is unclear so far whether the 5G new radio (5G-NR) synchronization signals could meet the requirement of timing and frequency offset estimation in the presence of large Doppler shifts. In this paper, we investigate time and frequency synchronization for the downlink transmission of 5G-NR signals over LEO satellite channels. Starting from the maximum log-likelihood criterion for timing offset estimation given the observation of the received primary synchronization signals (PSS), we derive an upper bound of the objective function for simplicity. With a priori information that the maximum Doppler shift of LEO satellite-ground link is within a specific range, we construct the local synchronization sequence via using the modulated discrete prolate spheroidal sequences (DPSS) vectors. Then the timing offset estimation can be recast into a one-dimensional peak search problem. Moreover, the cyclic prefix (CP) structure of orthogonal frequency division multiplexing (OFDM) can be utilized to improve the estimation performance further. Once the timing and frequency offset are captured in the above initial synchronization phase, the tracking synchronization can be much simplified as the variation of both the timing and frequency offset is very small between two adjacent synchronization blocks. Simulation results show that by using the proposed algorithms, the 5G-NR signals can achieve near optimal downlink time and frequency synchronization in typical LEO SatCom systems.

When observing the Earth from space, the synthetic aperture radiometer antenna array is sometimes set as a non-uniform array. In non-uniform synthetic aperture radiometer image reconstruction, the existing brightness temperature image reconstruction methods include the grid method and array factor forming (AFF) method. However, when using traditional methods for imaging, errors are usually introduced or some prior information is required. In this article, we propose a new IASR imaging method with deep convolution neural network (CNN). The frequency domain information is extracted through multiple convolutional layers, global pooling layers, and fully connected layers to achieve non-uniform synthetic aperture radiometer imaging. Through extensive numerical experiments, we demonstrate the performance of the proposed imaging method. Compared to traditional imaging methods such as the grid method and AFF method, the proposed method has advantages in image quality, computational efficiency, and noise suppression.

MiR-21-5p is one of the most common oncogenic miRNAs that is upregulated in many solid cancers by inhibiting its target genes at the posttranscriptional level. However, the upstream regulatory mechanisms of miR-21-5p are still not well documented in cancers. Here, we identify a super-enhancer associated with the MIR21 gene (MIR21-SE) by analyzing the MIR21 genomic regulatory landscape in head and neck squamous cell carcinoma (HNSCC). We show that the MIR21-SE regulates miR-21-5p expression in different HNSCC cell lines and disruption of MIR21-SE inhibits miR-21-5p expression. We also identified that a key transcription factor, FOSL1 directly controls miR-21-5p expression by interacting with the MIR21-SE in HNSCC. Moreover, functional studies indicate that restoration of miR-21-5p partially abrogates FOSL1 depletion-mediated inhibition of cell proliferation and invasion. Clinical studies confirmed that miR-21-5p expression is positively correlated with FOSL1 expression. These findings suggest that FOSL1-SE drives miR-21-5p expression to promote malignant progression of HNSCC

Urinary bladder carcinoma refers to the commonest carcinoma with weak prognostic result for the patient as impacted by the limited treatment possibilities and challenging diagnosing process. Nevertheless, the molecular underpinning of bladder carcinoma malignant progression is still not clear. As a novel core part of pluripotency circuitry, testicular expression 10 (TEX10) plays an actively noticeable effect on reprogramming, early embryo development, and embryonic stem cell self-renewal. Nevertheless, TEX10 expressions and functions within bladder carcinoma are still not known. The present work is aimed at revealing TEX10 expression and biological function within urinary bladder carcinoma and elucidating the potential mechanisms. Results showed that TEX10 is abundant in urinary bladder carcinoma, and its protein level was related to poor disease-free survival in a positive manner. Reduced TEX10 level inhibited urinary bladder carcinoma cell proliferating process and metastasis in vitro and xenograft tumorigenicity in vivo. Notably, TEX10 might regulate carcinoma cell proliferating process and metastasis via XRCC6, thereby controlling the signaling of Wnt/β-catenin and DNA repair channel. Moreover, TEX10 gene knockout reduced the radiotherapy resistance of urinary bladder carcinoma. In brief, this work revealed that TEX10 could exert a significant carcinogenic effect on urinary bladder carcinoma tumorigenesis and radiotherapy resistance through the activation of XRCC6-related channels. Accordingly, targeting TEX10 is likely to offer a novel and feasible therapeutically related strategy for inhibiting urinary bladder carcinoma tumorigenicity.

We investigate non-orthogonal unicast and multicast (NOUM) transmission for massive multiple-input multiple-output systems, where only statistical channel state information of all user terminals is available at the base station. We adopt a weighted sum of the achievable ergodic unicast rate and multicast rate as the design objective. We first show the closed-form eigenvectors of the optimal unicast and multicast transmit covariance matrices, respectively, which reveals the optimality of beam domain transmission and simplifies the large-dimensional matrix-valued NOUM transmission design into a beam domain power allocation problem. Via invoking the concave-convex procedure, we, then, propose an efficient iterative beam domain power allocation algorithm with guaranteed convergence to a stationary point. In addition, we derive the deterministic equivalent of the objective in each iteration to further reduce the optimization complexity. Simulation results show that the proposed NOUM transmission can provide a significant performance gain in terms of the achievable ergodic unicast-multicast rate region over the conventional orthogonal approach.

We investigate robust multigroup multicast transmission for frame-based multi-beam satellite communication systems with full frequency reuse. To mitigate the effect of outdated channel state information (CSI), we first investigate robust multigroup multicast precoding that maximizes the minimum average signal to interference plus noise ratio (SINR) under the per-beam power constraints. We show the relationship between the robust max-min fair problem and the robust power minimization problem with partial CSI and propose a low complexity precoder for the robust power minimization problem. We then investigate user clustering which only requires partial CSI. We show that the approximated average SINR can be maximized provided that the estimated channel vectors of the users in the same cluster are linearly dependent while those in different clusters are mutually orthogonal. Motivated by this user clustering condition, we further propose a low-complexity user clustering algorithm. Simulation results demonstrate that the proposed robust approach can provide substantial performance gains over the conventional approach in multi-beam satellite communication systems.

To control the spread of coronavirus disease 2019 (COVID-19), it is effective to perform a fast screening of the respiratory rate of the subject at the gate before entering a space to assess the potential risks. In this paper, we examine the potential of a novel yet cost-effective solution, called thermopile-based respiratory gating, to contactlessly screen a subject by measuring their respiratory rate in the scenario with an entrance gate. Based on a customized thermopile array system, we investigate different image and signal processing methods that measure respiratory rate from low-resolution thermal videos, where an automatic region-of-interest selection-based approach obtains a mean absolute error (MAE) of 0.8 breaths per minute. We show the feasibility of thermopile-based respiratory gating and quantify its limitations and boundary conditions in a benchmark (e.g., appearance of face mask, measurement distance and screening time). The technical validation provided by this study is helpful for designing and implementing a respiratory gating solution toward the prevention of the spread of COVID-19 during the pandemic.

Schwann cells (SCs) de-differentiate in Wallerian degeneration (WD) following nerve injury and, by doing so, can actively promote nerve repair and functional recovery. An innate-immune response is an important component of the complex of events referred to as WD. Damaged peripheral nervous system SCs produce IL-1β and other inflammatory cytokines. We hypothesized that, in addition to a role in immune responses, IL-1β participates in de-differentiation and proliferation of SCs. qPCR and ELISA demonstrated that expression of IL-1β mRNAs and protein increased after nerve injury. Immunofluorescent staining and western blotting demonstrated that expression of the p75 neurotrophin receptor (p75NTR) was significantly increased and levels of myelin protein zero (MPZ) were significantly decreased after IL-1β exposure compared with control groups in vitro WD. Additionally, qPCR demonstrated that IL-1β elevated expression of the de-differentiation gene p75NTR and decreased expression of myelination locus MPZ and promoted SCs de-differentiation. Furthermore, immunofluorescent staining, western blotting, qPCR and ELISA revealed that IL-1β promoted c-JUN expression and activation of AP-1 activity of SCs in an in vitro WD model. Finally, Immunofluorescent staining illustrated that IL-1β elevated expression of Ki67 in SCs nuclei, the apoptosis of SCs were detected by TUNEL. SCs of WD produce IL-1β which promotes SCs de-differentiation and proliferation.

Contact-free sensors offer important advantages compared to traditional wearables. Radio-frequency sensors (e.g., radars) offer the means to monitor cardiorespiratory activity of people without compromising their privacy, however, only limited information can be obtained via movement, traditionally related to heart or breathing rate. We investigated whether five complex hemodynamics scenarios (resting, apnea simulation, Valsalva maneuver, tilt up and tilt down on a tilt table) can be classified directly from publicly available contact and radar input signals in an end-to-end deep learning approach. A series of robust k-fold cross-validation evaluation experiments were conducted in which neural network architectures and hyperparameters were optimized, and different data input modalities (contact, radar and fusion) and data types (time and frequency domain) were investigated. We achieved reasonably high accuracies of 88% for contact, 83% for radar and 88% for fusion of modalities. These results are valuable in showing large potential of radar sensing even for more complex scenarios going beyond just heart and breathing rate. Such contact-free sensing can be valuable for fast privacy-preserving hospital screenings and for cases where traditional werables are impossible to use.

Herein, we focus on energy efficiency optimization for massive multiple-input multiple-output (MIMO) downlink secure multicast transmission exploiting statistical channel state information (CSI). Privacy engineering in the field of communication is a hot issue under study. The common signal transmitted by the base station is multicast transmitted to multiple legitimate user terminals in our system, but an eavesdropper might eavesdrop this signal. To achieve the energy efficiency utility–privacy trade-off of multicast transmission, we set up the problem of maximizing the energy efficiency which is defined as the ratio of the secure transmit rate to the power consumption. To simplify the formulated nonconvex problem, we use a lower bound of the secure multicast rate as the molecule of the design objective. We then obtain the eigenvector of the optimal transmit covariance matrix into a closed-form, simplifying the matrix-valued multicast transmission strategy problem into a power allocation problem in the beam domain. By utilizing the Minorize-Maximize method, an iterative algorithm is proposed to decompose the secure energy efficiency optimization problem into a sequence of iterative fractional programming subproblems. By using Dinkelbach’s transform, each subproblem becomes an iterative problem with the concave objective function, and it can be solved by classical convex optimization. We guarantee the convergence of the two-level iterative algorithm that we propose. Besides, we reduce the computational complexity of the algorithm by substituting the design objective with its deterministic equivalent. The numerical results show that the approach we propose performs well compared with the conventional methods.

As the core technology of 5G mobile communication systems, massive multi-input multi-output (MIMO) can dramatically enhance the energy efficiency (EE), as well as the spectral efficiency (SE), which meets the requirements of new applications. Meanwhile, physical layer multicast technology has gradually become the focus of next-generation communication technology research due to its capacity to efficiently provide wireless transmission from point to multipoint. The availability of channel state information (CSI), to a large extent, determines the performance of massive MIMO. However, because obtaining the perfect instantaneous CSI in massive MIMO is quite challenging, it is reasonable and practical to design a massive MIMO multicast transmission strategy using statistical CSI. In this paper, in order to optimize the system resource efficiency (RE) to achieve EE-SE balance, the EE-SE trade-offs in the massive MIMO multicast transmission are investigated with statistical CSI. Firstly, we formulate the eigenvectors of the RE optimization multicast covariance matrices of different user terminals in closed form, which illustrates that in the massive MIMO downlink, optimal RE multicast precoding is supposed to be done in the beam domain. On the basis of this viewpoint, the optimal RE precoding design is simplified into a resource efficient power allocation problem. Via invoking the quadratic transform, we propose an iterative power allocation algorithm, which obtains an adjustable and reasonable EE-SE tradeoff. Numerical simulation results reveal the near-optimal performance and the effectiveness of our proposed statistical CSI-assisted RE maximization in massive MIMO.

Many camera-based remote photoplethysmography (PPG) applications require sensing in near infrared (NIR). The performance of PPG systems benefits from multi-wavelength processing. The illumination source in such system is explored in this paper. We demonstrate that multiple narrow-band LEDs have inferior color homogeneity compared to broadband light sources. Therefore, we consider the broadband option based on phosphor material excited by LEDs. A first prototype was realized and its details are discussed. It was tested within a remote-PPG monitoring scenario in darkness and the full system demonstrates robust pulse-rate measurement. Given its accuracy in pulse rate extraction, the proposed illumination principle is considered a valuable asset for large-scale NIR-PPG applications as it enables multi-wavelength processing, lightweight set-ups with relatively low-power infrared light sources.

The X-rudder concept has been applied to more and more autonomous underwater vehicles (AUVs) in recent years, since it shows better maneuverability and robustness against rudder failure compared to the traditional cruciform rudder. Aiming at the fault-tolerant control of the X-rudder AUV (hereinafter abbreviated as xAUV), a fault-tolerant steering prototype system which can realize dynamics control, autonomous rudder fault detection and fault-tolerant control is presented in this paper. The steering prototype system is deployed on a verification platform, an xAUV, in which the monitor software is developed based on the factory method and the onboard software is developed based on the finite state machine (FSM). Dual-loop increment feedback control (DIFC) is first introduced to obtain smooth virtual rudder commands considering actuator’s limitations. Then the virtual rudder commands are transformed into X-rudder commands based on the mapping theory. In rudder fault diagnosis, an optimized particle filter is proposed for estimating rudder effect deduction, with proposal distribution derived from unscented Kalman filter (UKF). Then the fault type can be determined by analyzing indicators related to the deduction. Fault-tolerant control is addressed by dealing with nonlinear programming (NLP) problem, where minimization of allocation errors and control efforts are set as the optimization objectives, and rudder failure, saturation and actuators limitations are considered as constraints. The fixed-point iteration method is utilized to solve this optimization problem. Many field tests have been conducted in towing tank. The experimental results demonstrate that the proposed steering prototype system is able to detect rudder faults and is robust against rudder failure.

This article proposed a novel method for submarine hovering control implement by ballast tanks based on L1 adaptive theory. The ballast tanks are able to provide submerge/emerge force by let in/out ballast tank water, and therefore adjust submarine position and altitude when low-speed maneuver largely limits rudder effect. After formulate and analysis models of ballast tanks as well as submarine dynamic, control scheme is determined as cascaded controller system. L1 adaptive theory is adopted for outer loop control, to deal with the nonlinearity and uncertainties of model, as well as environmental disturbance in hovering condition for the first time. Robustness of control system is tested through simulations based on Simscape. Large impact force is exerted on submarine to simulate missile launching and test restoring ability of ballast tanks control. Simulation results demonstrated that the submarine is able to maneuver and response precisely, despite of sudden impact.

In this paper, we investigate energy-efficient multicast precoding for massive multiple-input multiple-output (MIMO) transmission. In contrast with most previous work, where instantaneous channel state information (CSI) is exploited to facilitate energy-efficient wireless transmission design, we assume that the base station can only exploit statistical CSI of the user terminals for downlink multicast precoding. First, in terms of maximizing the system energy efficiency, the eigenvectors of the optimal energy-efficient multicast transmit covariance matrix are identified in closed form, which indicates that optimal energy-efficient multicast precoding should be performed in the beam domain in massive MIMO. Then, the large-dimensional matrix-valued precoding design is simplified into an energy-efficient power allocation problem in the beam domain with significantly reduced optimization variables. Using Dinkelbach’s transform, we further propose a sequential beam domain power allocation algorithm which is guaranteed to converge to the global optimum. In addition, we use the large-dimensional random matrix theory to derive the deterministic equivalent of the objective to reduce the computational complexity involved in sample averaging. We present numerical results to illustrate the near-optimal performance of our proposed energy-efficient multicast precoding for massive MIMO.

In order to reduce the effect of numerical weather prediction (NWP) error on short term load forecasting (STLF) and improve the forecasting accuracy, a new hybrid model based on support vector regression (SVR) optimized by an artificial bee colony (ABC) algorithm (ABC-SVR) and seasonal autoregressive integrated moving average (SARIMA) model is proposed. According to the different day types and effect of the NWP error on forecasting prediction, working days and weekends load forecasting models are selected and constructed, respectively. The ABC-SVR method is used to forecast weekends load with large fluctuation, in which the best parameters of SVR are determined by the ABC algorithm. The working days load forecasting model is constructed based on SARIMA modified by ABC-SVR (AS-SARIMA). In the AS-SARIMA model, the ability of SARIMA to respond to exogenous variables is improved and the effect of NWP error on prediction accuracy is reduced more than with ABC-SVR. Contrast experiments are constructed based on International Organization for Standardization (ISO) New England load data. The experimental results show that prediction accuracy of the proposed method is less affected by NWP error and has higher forecasting accuracy than contrasting approaches.