Search

Abstract Diagnosing liver lesions is crucial for treatment choices and patient outcomes. This study develops an automatic diagnosis system for liver lesions using multiphase enhanced computed tomography (CT). A total of 4039 patients from six data centers are enrolled to develop Liver Lesion Network (LiLNet). LiLNet identifies focal liver lesions, including hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), metastatic tumors (MET), focal nodular hyperplasia (FNH), hemangioma (HEM), and cysts (CYST). Validated in four external centers and clinically verified in two hospitals, LiLNet achieves an accuracy (ACC) of 94.7% and an area under the curve (AUC) of 97.2% for benign and malignant tumors. For HCC, ICC, and MET, the ACC is 88.7% with an AUC of 95.6%. For FNH, HEM, and CYST, the ACC is 88.6% with an AUC of 95.9%. LiLNet can aid in clinical diagnosis, especially in regions with a shortage of radiologists.

Abstract Background Bone defects, resulting from substantial bone loss that exceeds the natural self-healing capacity, pose significant challenges to current therapeutic approaches due to various limitations. In the quest for alternative therapeutic strategies, bone tissue engineering has emerged as a promising avenue. Notably, excretory proteins from Toxoplasma gondii (TgEP), recognized for their immunogenicity and broad spectrum of biological activities secreted or excreted during the parasite’s lifecycle, have been identified as potential facilitators of osteogenic differentiation in human bone marrow mesenchymal stem cells (hBMSCs). Building on our previous findings that TgEP can enhance osteogenic differentiation, this study investigated the molecular mechanisms underlying this effect and assessed its therapeutic potential in vivo. Methods We determined the optimum concentration of TgEP through cell cytotoxicity and cell proliferation assays. Subsequently, hBMSCs were treated with the appropriate concentration of TgEP. We assessed osteogenic protein markers, including alkaline phosphatase (ALP), Runx2, and Osx, as well as components of the BMP/Smad signaling pathway using quantitative real-time PCR (qRT-PCR), siRNA interference of hBMSCs, Western blot analysis, and other methods. Furthermore, we created a bone defect model in Sprague-Dawley (SD) male rats and filled the defect areas with the GelMa hydrogel, with or without TgEP. Microcomputed tomography (micro-CT) was employed to analyze the bone parameters of defect sites. H&E, Masson and immunohistochemical staining were used to assess the repair conditions of the defect area. Results Our results indicate that TgEP promotes the expression of key osteogenic markers, including ALP, Runx2, and Osx, as well as the activation of Smad1, BMP2, and phosphorylated Smad1/5—crucial elements of the BMP/Smad signaling pathway. Furthermore, in vivo experiments using a bone defect model in rats demonstrated that TgEP markedly promoted bone defect repair. Conclusion Our results provide compelling evidence that TgEP facilitates hBMSC osteogenic differentiation through the BMP/Smad signaling pathway, highlighting its potential as a therapeutic approach for bone tissue engineering for bone defect healing.

To explore the effect of postharvest dehydration on grape berries and wine quality, we determined physicochemical properties, polyphenols, antioxidant activities, volatile compounds and sensory characteristics for wines brewed by ‘Marselan’ (Vitis vinifera L.) grapes with 0%, 10%, 15%, 20%, and 25% of water loss. The result showed that postharvest dehydration improved the alcohol content, residual sugar and titratable acidity of Marselan wine. Phenolic compounds and antioxidant activities in wines with a dehydration of 20% have significantly increased. Postharvest dehydration increased the contents of isobutanol, isoamyl alcohol, phenylethyl alcohol, ethyl acetate, isoamyl acetate and ethyl butyrate in Marselan wines, and enhanced the floral, fruity and sweet taste of wines. Marselan wine had the lowest acceptability score under the condition of severe dehydration (25% dehydration), which was related to the significant increase of tannins content. In summary, postharvest dehydration was beneficial in improving the quality of Marselan wine.

To determine the effect of cofermentation of Saccharomyces cerevisiae and different LABs on prune wine quality, this study compared phenolic compounds, organic acids, soluble sugars, biogenic amines and volatile flavor compounds among different treatments. The results showed that inoculation of LAB increased DPPH and total flavonoid content. Malic acid content was reduced in HS, HB and HF. Histamine content in S, F and B was lower than the limits in French and Australian wines. 15 phenolic compounds were identified. Yangmeilin and chlorogenic acid were detected only in HS, HF and HB. 51 volatile flavor compounds were identified, esters being the most diverse and abundant. 14 volatile flavor compounds with OAV > 1 contributed highly to the aroma of prune wine. 9 chemical markers including resveratrol, rutin, and catechin were screened to explain intergroup differences by OPLS-DA. This study provides new insights into the processing and quality analysis of prunes.

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

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

Chemical and sensory attributes play a vital role in evaluating the quality of grapes and wines. This study compared basic physicochemical parameters, organic acids, phenolic compounds, and aroma profiles of grapes and wines of six cultivars using chemometrics. The results showed that the reducing sugar contents of Beibinghong, Gongniang, and Granoir grapes were significantly higher than those of others cultivars, whereas their juice yields were significantly lower. The phenolic compound contents in Moldova, Beibinghong, and Gongniang grape skins and wines were higher than those in others cultivars. The organic acid contents in Beibinghong grape and Dunkelfelder wine were highest. Beibinghong and Gongniang grapes and wines showed richer aldehyde and ester concentrations. Beibinghong wine obtained the highest sensory scores. Ethyl decanoate, coumaric acid, and methyl dodecanoate were characteristic variables distinguishing wine cultivars, exhibiting important contributions to their sensory characteristics. These findings were useful for viticulturists and winemakers to select grape varieties.

Monodisperse and semi-faceted ultra-small templated mesoporous silica nanoparticles (US-MSNs) of 20–25 nm were synthesized using short-time hydrolysis of tetraethoxysilane (TEOS) at room temperature, followed by a dilution for nucleation quenching. According to dynamic light scattering (DLS), a two-step pH adjustment was necessary for growth termination and colloidal stabilization. The pore size was controlled by cetyltrimethylammonium bromide (CTAB), and a tiny amount of neutral surfactant F127 was added to minimize the coalescence between US-MSNs and to favor the transition towards internal ordering. Flocculation eventually occurred, allowing us to harvest a powder by centrifugation (~60% silica yield after one month). Scanning transmission electron microscopy (STEM) and 3D high-resolution transmission electron microscopy (3D HR-TEM) images revealed that the US-MSNs are partially ordered. The 2D FT transform images provide evidence for the coexistence of four-, five-, and sixfold patterns characterizing an “on-the-edge” crystallization step between amorphous raspberry and hexagonal pore array morphologies, typical of a protocrystalline state. Calcination preserved this state and yielded a powder characterized by packing, developing a hierarchical porosity centered at 3.9 ± 0.2 (internal pores) and 68 ± 7 nm (packing voids) of high potential for support for separation and catalysis.

Irritable Bowel Syndrome (IBS) is a complex functional gastrointestinal disorder primarily characterized by chronic abdominal pain, bloating, and altered bowel habits. Chronic abdominal pain caused by visceral Hypersensitivity (VH) is the main reason why patients with IBS seek medication. Significant research effort has been devoted to the efficacy of acupuncture as a non-drug alternative therapy for visceral-hyperalgesia-induced IBS. Herein, we examined the central and peripheral analgesic mechanisms of acupuncture in IBS treatment. Acupuncture can improve inflammation and relieve pain by reducing 5-hydroxytryptamine and 5-HT3A receptor expression and increasing 5-HT4 receptor expression in peripheral intestinal sensory endings. Moreover, acupuncture can also activate the transient receptor potential vanillin 1 channel, block the activity of intestinal glial cells, and reduce the secretion of local pain-related neurotransmitters, thereby weakening peripheral sensitization. Moreover, by inhibiting the activation of N-methyl-D-aspartate receptor ion channels in the dorsal horn of the spinal cord and anterior cingulate cortex or releasing opioids, acupuncture can block excessive stimulation of abnormal pain signals in the brain and spinal cord. It can also stimulate glial cells (through the P2X7 and prokinetic protein pathways) to block VH pain perception and cognition. Furthermore, acupuncture can regulate the emotional components of IBS by targeting hypothalamic-pituitary-adrenal axis-related hormones and neurotransmitters via relevant brain nuclei, hence improving the IBS-induced VH response. These findings provide a scientific basis for acupuncture as an effective clinical adjuvant therapy for IBS pain.

This study completely investigates the damage detection problem based on strain modal characteristics using simply supported wooden beams as the research object. First, modal analysis was performed, and finite element models of both damaged and undamaged timber beams were created using ABAQUS. Second, a number of strain modal characteristics (strain modal, strain modal difference, and strain modal curvature difference) were used to identify the damage to the wooden beam construction. Lastly, the modal parameters of the wooden beam under various damage scenarios were ascertained using damage identification experiments, and the test results were contrasted with those obtained from a numerical simulation. The findings showed that, while each of the three damage identification indices has a distinct identification effect, they can all locate the damage to wooden beams. Strain mode curvature difference > strain mode difference > strain mode is the order of them. The results of this study can be used as a reference to identify damage to timber beams in the future.

Abstract With the development of heteronuclear fluorine, sodium, phosphorus, and other probes and imaging technologies as well as the optimization of magnetic resonance imaging (MRI) equipment and sequences, multi-nuclear magnetic resonance (multi-NMR) has enabled localize molecular activities in vivo that are central to a variety of diseases, including cardiovascular disease, neurodegenerative pathologies, metabolic diseases, kidney, and tumor, to shift from the traditional morphological imaging to the molecular imaging, precision diagnosis, and treatment mode. However, due to the low natural abundance and low gyromagnetic ratios, the clinical application of multi-NMR has been hampered. Several techniques have been developed to amplify the NMR sensitivity such as the dynamic nuclear polarization, spin-exchange optical pumping, and brute-force polarization. Meanwhile, a wide range of nuclei can be hyperpolarized, such as 2H, 3He, 13C, 15 N, 31P, and 129Xe. The signal can be increased and allows real-time observation of biological perfusion, metabolite transport, and metabolic reactions in vivo, overcoming the disadvantages of conventional magnetic resonance of low sensitivity. HP-NMR imaging of different nuclear substrates provides a unique opportunity and invention to map the metabolic changes in various organs without invasive procedures. This review aims to focus on the recent applications of multi-NMR technology not only in a range of preliminary animal experiments but also in various disease spectrum in human. Furthermore, we will discuss the future challenges and opportunities of this multi-NMR from a clinical perspective, in the hope of truly bridging the gap between cutting-edge molecular biology and clinical applications.

In the paper, a simple-supported wooden beam is used as the research object to identify the damage of the wood beam by finite element analysis and experimental research. First, ANSYS was used to establish the solid finite element model of the wood beam before and after the damage, and then the discrete wavelet transform was performed on the curvature mode of the wood beam before and after the damage, and the wavelet coefficient difference index was obtained after obtaining the high frequency wavelet coefficients. Then, the damage location of the wood beam was judged according to the sudden peak of the wavelet coefficient difference index, and the damage degree of the wood beam was estimated by fitting the relationship between the wavelet coefficient difference index and the degree of damage. Finally, the index was verified by the wooden beam test. The results show that the wavelet coefficient difference index can accurately identify the damaged location of the wood beams. The degree of damage to the wood beams at the damage location can be quantitatively estimated by fitting the relationship between the wavelet coefficient difference index and the degree of damage at the damage location. The research results provide a theoretical basis to identify wooden beam damage.

Particle-dispersed coatings emerged as a promising approach to regulate the apparent radiative properties of underlying substrates in various applications, including but not limited to radiative cooling, thermal management, and infrared stealth. However, most research efforts in this field overlooked the dependent scattering mechanisms between the particles and the substrate, which can impact the optical properties of the particles. In this study, we explored the particle-substrate interactions within the atmospheric radiative window of 8–14 µm. Using the T-matrix method, we calculated the scattering and absorption efficiencies of a dielectric/metallic particle situated above a metallic/dielectric substrate, considering the different gap sizes. Near the small gaps (a with a the sphere radius), we found that the strong local fields induced by the interaction between the induced and image charges largely enhanced the absorption and scattering efficiencies of the particles. With the increasing gap sizes, the absorption and scattering efficiencies presented a significant oscillation with a period of about 4.5a, which was attributed to the interference (standing wave) between the scattered fields from the sphere and the reflected fields from the substrate. Our findings identify a crucial role of the particle–substrate interactions in the infrared properties of particles, which may guide a comprehensive insight on the apparent radiative properties of the particle composite coatings.

ObjectiveEarly detection and diagnosis of hepatocellular carcinoma (HCC) is essential for prognosis; however, the imaging hallmarks for tumor detection and diagnosis has remained the same for years despite the use of many new immerging imaging methods. This study aimed to evaluate the detection performance of hepatic nodules in high risk patients using either hepatobiliary specific contrast (HBSC) agent or extracellular contrast agent (ECA), and further to compare the diagnostic performances for hepatocellular carcinoma (HCC) using different diagnostic criteria with the histopathological results as reference standard.MethodsThis prospective study included 247 nodules in 222 patients (mean age, 53.32 ± 10.84 years; range, 22–79 years). The detection performance and imaging features of each nodule were evaluated in all MR sequences by three experienced abdominal radiologists. The detection performance of each nodule on all MR sequences were compared and further the diagnostic performance of various diagnostic criteria were evaluated.ResultsFor those patients who underwent ECA-MRI, the conventional imaging hallmark of “AP + PVP and/or DP” was recommended, as 60.19% diagnostic sensitivity, 80.95% specificity and 100% lesion detection rate. Additionally, for those patients who underwent HBSC-MRI, the diagnostic criteria of “DWI + HBP” was recommended. This diagnostic criteria demonstrated, both in all tumor size and for nodules ≤2 cm, higher sensitivity (93.07 and 90.16%, all p 0.05, respectively) than that of the European Association for the Study of the Liver (EASL) criteria.ConclusionsDifferent abbreviated MR protocols were recommended for patients using either ECA or HBSC. These provided imaging settings demonstrated high lesion detection rate and diagnostic performance for HCC.

The slow diffusion dynamics hinder aqueous MnO2/Zn batteries’ further development. Here, a Ni/Fe bimetallic co-doped MnO2 (NFMO) cathode material was studied by density functional theory (DFT) calculation and experimental characterization techniques, such as cyclic voltammetry (CV), galvanostatic intermittent titration technique (GITT) and electrochemical impedance spectra (EIS). The results indicated that the energy band structure and electronic state of MnO2 were effectively optimized due to the simultaneous incorporation of strongly electronegative Ni and Fe ions. Consequently, the NFMO cathode material exhibited a faster charge transfer and ion diffusion dynamics than MnO2 (MO), thus, the assembled NFMO/Zn batteries delivered excellent rate performance (181 mA h g−1 at 3 A g−1). The bimetallic ions co-doping strategy provides new directions for the development of oxide cathode materials towards high-performance aqueous zinc-ion batteries.

Energy source and circuit cost are two critical challenges for the future development of the Internet of Things (IoT). Backscatter communications offer a potential solution to conveniently obtain power and reduce cost for sensors in IoT, and researchers are paying close attention to the technology. Backscatter technology originated from the Second World War and has been widely applied in the logistics domain. Recently, both the academic and industrial worlds are proposing a series of new types of backscatter technologies for communications and IoT. In this paper, we review the history of both IoT and backscatter, describe the new types of backscatter, demonstrate their applications, and discuss the open challenges.

Background/Aim: The turbo spin-echo (TSE) sequence is widely used for musculoskeletal (MSK) imaging; however, its acquisition speed is limited and can be easily affected by motion artifacts. We aimed to evaluate whether the use of a simultaneous multi-slice TSE (SMS-TSE) sequence can accelerate MSK imaging while maintaining image quality when compared with the routine TSE sequence.Methods: We prospectively enrolled 71 patients [mean age, 37.43 ± 12.56 (range, 20–67) years], including 37 men and 34 women, to undergo TSE and SMS sequences. The total scanning times for the wrist, ankle and knee joint with routine sequence were 14.92, 13.97, and 13.48 min, respectively. For the SMS-TSE sequence, they were 7.52, 7.20, and 6.87 min. Quantitative parameters, including the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), were measured. Three experienced MSK imaging radiologists qualitatively evaluated the image quality of bone texture, cartilage, tendons, ligament, meniscus, and artifact using a 5-point evaluation system, and the diagnostic performance of the SMS-TSE sequences was evaluated.Results: Compared with the routine TSE sequences, the scanning time was lower by 49.60, 48.46, and 49.04% using SMS-TSE sequences for the wrist, ankle, and knee joints, respectively. For the SNR comparison, the SMS-TSE sequences were significantly higher than the routine TSE sequence for wrist (except for Axial-T2WI-FS), ankle, and knee joint MR imaging (all p < 0.05), but no statistical significance was obtained for the CNR measurement (all p > 0.05, except for Sag-PDWI-FS in ankle joint). For the wrist joint, the diagnostic sensitivity, specificity, and accuracy were 88.24, 100, and 92%. For the ankle joint, they were 100, 75, and 93.33%. For the knee joint, they were 87.50, 85.71, and 87.10%.Conclusion: The use of the SMS-TSE sequence in the wrist, ankle, and knee joints can significantly reduce the scanning time and show similar image quality when compared with the routine TSE sequence.

High Altitude Platform (HAP) systems comprise airborne base stations deployed above 20 km and below 50 km to provide wireless access to devices in large areas. In this paper, two types of applications using HAP systems: one with HAP Station (HAPS) and the other with HAPS as International Mobile Telecommunication (IMT) Base Station (HIBS) are introduced. The HAP system with HAPS has already received wide recognition from the academia and the industry and is considered as an effective solution to provide internet access between fixed points in suburban and rural areas as well as emergencies. HAP systems with HIBS to serve IMT user terminal have just started to draw attention from researchers. The HIBS application is expected to be an anticipate mobile service application complementing the IMT requirement for cell phone or other mobile user terminals in which the service field of HAPS application cannot reach. After describing and characterizing the two types of systems, coexistence studies and simulation results using both the Power Fluxed Density (PFD) mask and separation distance based methods are presented in this paper. This paper also predicts future trends of the evolution paths for the HAP systems along with challenges and possible solutions from the standpoint of system architectures and spectrum regulation.

Nasopharyngeal carcinoma (NPC) is a malignancy that arises from the mucosal epithelium of the nasopharynx, and its prognosis is relatively favorable. The 5-year overall survival rate in patients with locally advanced NPC currently exceeds 80%, but the development of individualized diagnosis and treatment at the molecular level is relatively lacking. Circulating tumor cells (CTCs) is the generic term for tumor cells that are present in the peripheral blood circulation. As a new biomarker with good clinical application prospects, the detection of CTCs has the advantages of being non-invasive, simple, and repeatable. By capturing and detecting CTCs in peripheral blood and monitoring the dynamic variation of its type and quantity, we can assess the biological characteristics of tumor in a timely manner and evaluate the therapeutic effect and prognosis of patients in advance, which will help to develop individualized treatments of tumors. The primary purposes of this review were the clinical application of CTCs in tumor stage determination, treatment efficacy evaluation, and prognosis prediction of NPC. In addition, we estimated the correlation between Epstein-Barr virus infection and CTCs and analyzed the difference in karyotypes and specific markers expressed on CTCs. We believe that our study will provide new insights and biomarkers for the individualized treatment of patients with NPC.

Low-power-consumption optical devices are crucial for large-scale photonic integrated circuits (PICs). In this paper, a three-dimensional (3D) polymer variable optical attenuator (VOA) is proposed. For monolithic integration of silica and polymer-based planar lightwave circuits (PLCs), the vertical VOA is inserted between silica-based waveguides. Optical and thermal analyses are performed through the beam propagation method (BPM) and finite-element method (FEM), respectively. A compact size of 3092 μm × 4 μm × 7 μm is achieved with a vertical multimode interference (MMI) structure. The proposed VOA shows an insertion loss (IL) of 0.58 dB and an extinction ratio (ER) of 21.18 dB. Replacing the graphene heater with an aluminum (Al) electrode, the power consumption is decreased from 29.90 mW to 21.25 mW. The rise and fall time are improved to 353.85 μs and 192.87 μs, respectively. The compact and high-performance VOA shows great potential for a variety of applications, including optical communications, integrated optics, and optical interconnections.

A new three dimensional nonlinear dynamic theoretical model is derived from fluid mechanics system. In this paper, From the quasi-geostrophic barotropic potential vorticity equation, we obtain a three dimensional dissipative Boussinesq equation by the reduced perturbation method, i.e.utt+e1uxx+e2(u2)xx+e3utxy+e4uxxxx+e5uxxyy=0. It is emphasized that the new equation is different from the existing Boussinesq equations, which describe the three dimensional nonlinear Rossby waves in the atmosphere. Moreover, we explore the dispersion relation of the linear wave through the new equation. Using the travelling wave method and simplest equation method, the general solution and soliton solutions of the equation are obtained successfully respectively. Finally, the formation mechanism of Rossby waves is discussed by multiple soliton solutions.

Abstract Background In China, adolescents are frequently left behind by their parents. A great deal of scientific evidence demonstrates considerable psychological and social impacts that negative life events may have on adolescents who are left behind. While a direct relationship between negative life events and psychological and social effects has been observed, indirect effects have yet to be examined. Therefore, the objective of this study was to determine the association between negative life events and positive social adjustment and how resilience and self-esteem mediate this association. Methods A cross-sectional study was carried out in the provinces of Shandong, Henan, and Sichuan in China. A questionnaire was distributed to 4716 left-behind adolescents in ten middle/high schools. We performed Bayesian estimations in structural equation modeling using the Markov Chain Monte Carlo algorithm to test our hypotheses. Results Negative life events were significantly related to resilience (r s = − 0.402), self-esteem (r s = − 0.292), and positive social adjustment (r s = − 0.239). Positive social adjustment was directly affected by resilience (β = 0.639) and self-esteem (β = 0.448). Negative life events were not only directly related to positive social adjustment (β = − 0.187, 95% credible interval: − 0.233 ~ − 0.139), but also showed an indirect effect on positive social adjustment (β = − 0.541, 95% credible interval: − 0.583 ~ − 0.501) through resilience (β = − 0.370) and self-esteem (β = − 0.171). The total effect of negative life events on positive social adjustment was − 0.728, where 74.31% was mediated by resilience and self-esteem. The indirect effect of negative life events on positive social adjustment through resilience and self-esteem was 2.893 times more than the direct effect. Conclusions Resilience and self-esteem mediated most of the effect of negative life events on positive social adjustment. Interventions should be developed to improve the social adjustment of adolescents who are left behind, particularly the enhancement of resilience and self-esteem.

The rapid development of wireless communications brings a tremendous increase in the amount number of data streams and poses significant challenges to the traditional routing protocols. In this paper, we leverage deep reinforcement learning (DRL) for router selection in the network with heavy traffic, aiming at reducing the network congestion and the length of the data transmission path. We first illustrate the challenges of the existing routing protocols when the amount of the data explodes. We then utilize the Markov decision process (RSMDP) to formulate the routing problem. Two novel deep Q network (DQN)-based algorithms are designed to reduce the network congestion probability with a short transmission path: one focusing on reducing the congestion probability; while the other focuses on shortening the transmission path. The simulation results demonstrate that the proposed algorithms can achieve higher network throughput comparing to existing routing algorithms in heavy network traffic scenarios.

In this paper, online deep learning (DL)-based channel estimation algorithm for doubly selective fading channels is proposed by employing the deep neural network (DNN). With properly selected inputs, the DNN can not only exploit the features of channel variation from previous channel estimates but also extract additional features from pilots and received signals. Moreover, the DNN can take the advantages of the least squares estimation to further improve the performance of channel estimation. The DNN is first trained with simulated data in an off-line manner and then it could track the dynamic channel in an online manner. To reduce the performance degradation from random initialization, a pre-training approach is designed to refine the initial parameters of the DNN with several epochs of training. The proposed algorithm benefits from the excellent learning and generalization capability of DL and requires no prior knowledge about the channel statistics. Hence, it is more suitable for communication systems with modeling errors or non-stationary channels, such as high-mobility vehicular systems, underwater acoustic systems, and molecular communication systems. The numerical results show that the proposed DL-based algorithm outperforms the existing estimator in terms of both efficiency and robustness, especially when the channel statistics are time-varying.

The precision of the conventional user identification algorithm is not satisfactory because it ignores the role of user-generated data in identity matching. In this paper, we propose a frequent pattern mining-based cross-social network user identification algorithm that analyzes user-generated data in a personalized manner. We adopt the posterior probability-based information entropy weight allocation method that improves the precision rate and recall rate compared to the empirical weight allocation method. The extensive simulations are provided to demonstrate that the proposed algorithm can enhance the precision rate, recall rate, as well as the F-Measure (F1).

Because of the superiority in distinguishing the target from the background by learning mechanism, discriminative classifier attracts a great deal of attention in target detection and tracking systems. Generally, a discriminative classifier is learned from the initial image patch. However, the other algorithms, using only one image frame inhibit the performance of the classifier. A novel training strategy of cascade iteration, which is based on the multiple image frames, is used to initialize the discriminative classifier for the purpose of weakening the initialization limitation and improving the algorithms' adaptability and robustness. Furthermore, to cope with the changes in natural images, online learning is usually adopted to enhance the performance of classifiers, but it easily leads to tracking failures, especially in the case of full occlusion. In order to attenuate the influence of full occlusion, a multi-classifiers parallel tracking algorithm is proposed by designing the multi-classifiers and inducing extra constraints. The experiments are performed on the visual tracking benchmark, and the proposed algorithm is more robust while the target is fully occluded. The simulation results show that the proposed algorithm exhibits better performance compared to the state-of-the-art trackers, especially with KCF, TLD, and STRUCK.

An ambient backscatter system could utilize the exiting ambient RF signals as both energy source and information carrier to enable the communications among battery-free devices and is deemed as a promising communication primitive for the Internet of Things (IoT). In this paper, we propose a time splitting strategy (TSS) and power splitting strategy (PSS) for the ambient backscatter system, where the tag-reflection coefficient is optimized according to dynamic channel variation. We also derive the analytical expressions of the outage probability and the optimal throughput for both the TSS and the PSS, which provides insights on the impact of system parameters, e.g., channel variance, RF source power, and circuit power consumption. The simulations showed that the proposed strategies can significantly outperform the traditional counterparts that rely on fixed reflection coefficient.

With the popularization of the Internet and the arrival of the big data era, numerous different social networks (SNs) have emerged to satisfy users’ social needs and offer them rich content and convenient services. Under these circumstances, identifying multiple social accounts belonging to the same user across different SNs is of great importance for many applications. Across social networks user identification (ASNUI) can help perfect user information, offer personalized service recommendation, and data mining, as well as provide support for scientific research. This paper first systematically introduces the application of ASNUI in the field of social computing, then states its applications and challenges, and reviews the adopted models, frameworks, and performance comparison state-of-the-art techniques used in ASNUI. Finally, we also identify a few future research directions in ASNUI, such as weight allocation of user attribute information, the fusion of multi-dimensional information, and large-scale user identification.

Biodegradable liquid mulch film (LF), which can be degraded naturally without harming the environment, is a new type of covering material that provides an environmentally friendly alternative to plastic mulch film (PF). In this study, the effects of LF and PF (ploughing (CK) used as a control) on the soil and fruit quality of Hutai-8 were evaluated through an experiment, and several soil physicochemical properties and indicators of fruit quality were measured. In-row mulching significantly increased the content of total potassium, available phosphorus, and available potassium in the topsoil (0–20 cm), the ripeness of the grape berries, and the content of phenolics in the skin. The effects were consistent between the two years. The effect of LF was more pronounced in the same year, indicating that LF is an effective alternative to PF. Therefore, LF can be used as an environmentally friendly substitute for PF to improve soil and fruit quality and incorporated into cultivation management plans. Correlation analysis revealed that the content of reducing sugars, flavonoids, total phenols, flavan-3-ols, and anthocyanins, as well as fruit ripeness, increased as the content of total potassium, available phosphorus, and available potassium in the soil increased.

Drug-induced memory engages complex and dynamic processes and is coordinated at multiple reward-related brain regions. The spatiotemporal molecular mechanisms underlying different addiction phases remain unknown. We investigated the role of β-actin, as well as its potential modulatory protein activity-regulated cytoskeletal-associated protein (Arc/Arg3.1) and extracellular signal-regulated kinase (ERK), in reward-related associative learning and memory using morphine-induced conditioned place preference (CPP) in mice. CPP was established by alternate morphine (10 mg/kg) injections and extinguished after a 10-day extinction training, while the withdrawal group failed to extinguish without training. In the nucleus accumbens (NAc), morphine enhanced the level of β-actin and Arc only during extinction, while p-ERK1/2 was increased during both CPP acquisition and extinction phases. In the dorsal hippocampus, morphine induced an upregulation of p-ERK only during extinction, while p-β-actin was elevated during both CPP establishment and extinction. In the dorsal hippocampus, Arc was elevated during CPP formation and suppressed during extinction. Compared with the NAc and dorsal hippocampus, dynamic changes in the medial prefrontal cortex (mPFC) and caudate putamen (CPu) were not very significant. These results suggested region-specific changes of p-β-actin, Arc/Arg3.1, and p-ERK1/2 protein during establishment and extinction phases of morphine-induced CPP. These findings unveiled a spatiotemporal molecular regulation in opiate-induced plasticity.

Elemental profiles are frequently applied to identify the geographical origin and authenticity of food products, to guarantee quality. The concentrations of fifteen major, minor, and trace elements (Na, Mg, K, Ca, Al, Fe, Mn, Cu, Zn, Rb, Sr, Li, Cd, Cs, and Ba) were determined in soils, “Meili” grapes, and wines from six regions in China by inductively coupled plasma mass spectrometry (ICP-MS). The elemental concentrations in these samples, according to the geographical origins, were analyzed by one-way analysis of variance (ANOVA) with Duncan’s multiple comparisons. The bioconcentration factor (BCF) from soil to grape and the transfer factor (TF) from grape to wine were calculated. Mg, K, Ca, Cu, Zn, Rb, Sr, and Ba presented higher BCF values than the other seven elements. The TF values of six elements (Na, Mg, K, Zn, Li, and Cs) were found to be greater than one. Moreover, the correlation of element content between the pairs of soil–grape, grape–wine, and bioconcentration factor (BCF)–environmental factor were analyzed. Significant correspondences among soil, grape, and wine were observed for K and Li. Two elements (Sr and Li) showed significant correlations between BCF and environmental factor (relative humidity, temperature, and latitude). A linear discriminant analysis (LDA) with three variables (K, Sr, Li) revealed a high accuracy (>90%) to determine the geographical origin for different Chinese regions.

Adolescents are particularly prone to antisocial behavior. The promoting effect of negative life events on antisocial behavior has been well-documented. However, the internal influence mechanisms between negative life events and antisocial behavior tendencies in adolescents are still unknown. The aim of this study was to explore the mediation effect of self-esteem and the moderated mediation effect of family support between negative life events and antisocial behavior tendencies in 8,958 adolescents who were selected from three Chinese provinces. Robust maximum likelihood estimator (MLR) of a structural equation model (SEM) was applied to test the mediation model and the moderated mediation model. The results revealed that negative life events had a positive effect on antisocial behavior tendencies in adolescents, with a direct effect of 0.082 (95% CI: 0.052, 0.111) and an indirect effect via self-esteem of 0.168 (95% CI: 0.146, 0.191). Negative life events had a 67.20% effect on antisocial behavior tendencies, where self-esteem showed mediation. The indirect effect was 2.049-fold greater than the direct effect. Furthermore, the effect of latent interaction of subjective family support and negative life events on self-esteem was negatively significant (β = −0.018, p = 0.032, 95% CI: −0.035, −0.002). The indirect effect of negative life events was greater, where subjective family support was below 1 SD of the mean (conditional indirect effect = 0.227, 95% CI = 0.200, 0.255) than where it was above 1 SD of the mean (conditional indirect effect = 0.203, 95% CI = 0.177, 0.229). The moderated mediation effect index was −0.012, p = 0.033. Moderated mediation showed that the mediated path was less evident in the students who had greater subjective support from family. The results of the current study demonstrated the important role that self-esteem and subjective family support played in minimizing the adverse effect of negative life events on antisocial behavior development of adolescents. These findings have important implications for preventing antisocial behavior in adolescents by developing interventions aimed at enhancing their self-esteem and providing support-skill training to parents aimed at improving subjective family support of adolescents.

Abstract Background The mechanism of the long-lasting effect and the relationship between the long-lasting effect and the deqi sensation, which is the key of achieving the acupuncture effect, has not been well investigated. This trial focuses on investigating the possible central mechanism of the long-lasting effect influenced by the deqi sensation. Methods A randomized controlled functional brain imaging trial is currently being conducted in Sichuan, China. In total 105 functional dyspepsia (FD) patients will be allocated into three groups: an acupuncture with deqi group, an acupuncture without deqi group, and a wait-list group. This trial will include a 2-week baseline period, a 4-week treatment period, and a 4-week follow-up period. During the 4-week treatment, patients in two acupuncture groups will receive 20 sessions of acupuncture treatment with or without deqi. The Nepean Dyspepsia Index (NDI) and the short form Leeds Dyspepsia Questionnaire (SF-LDQ) will be used to evaluate the clinical efficacy of acupuncture treatment at baseline, the end of treatment, and the end of the follow-up. Functional magnetic resonance imaging (fMRI) scans will be performed to detect cerebral functional changes in 25 patients in each group at three time points mentioned above. The clinical data and fMRI data will be analyzed, respectively. Correlation analysis will be conducted to investigate the relationship between cerebral functional changes and symptom improvement. Discussion The results of this trial will allow us to compare the changes of acupuncture therapeutic effect at three time points (the baseline vs. the end of treatment vs. the end of follow-up), and investigate the potential central mechanism of the long-lasting effect influenced by acupuncture with deqi. This trial aims to re-identify the long-lasting effect of acupuncture and investigate its central mechanism, and to further explore the central influence of deqi sensation on the long-lasting effect. Trial registration Chinese Clinical Trial Registry, IDF: ChiCTR-IOR-15006523. Registered on 5 June 2015.

Unmanned aerial vehicle (UAV) communications play an important role in building the space-air-ground network and realizing the seamless wide-area coverage thanks to its long-range connectivity, high maneuverability, flexible deployment, and low latency. Different from the traditional ground-only communications, the control techniques tightly impact UAV communications, which could be jointly designed to enhance the performance of data transmission. In this paper, we explore the opportunities and challenges of combining the communications and control in UAV systems. For single-UAV scenario, we introduce a new frequency-dependent 3D channel model. We then show how to perform channel tracking with a flight control system as well as how to mechanically and electronically formulate the transmission beams. For multi-UAV scenario, we present new techniques as cooperative communications, self-positioning, trajectory design, resource allocation, and seamless coverage. In the end, we provide some interesting discussions over communication protocol, secrecy, 3D dynamic topology heterogeneous networks, and low-cost design for practical UAV applications.

The cooperative communication with simultaneous wireless information and power transfer can provide a potential solution to meet the demands of next-generation green transmission. In this paper, we consider a cooperative system where each user has the capability of energy harvesting (EH) from the radio frequency and relays the data of other users. Our target is to minimize the overall energy consumption while satisfying the quality of service constraints of each user in terms of minimum required data rate. The time division scheme is adopted for data transmission and relaying while power splitting protocol is used at each node to receive information and energy, concurrently. We optimize the transmit power for data and relay transmission at each node and find the optimal time sharing for user cooperation. Unfortunately, under the decode and forward relaying the complex primal problem is not convex. Thus, we first re-formulate the problem into standard optimization and then transform to a convex problem. We solve the problem through duality theory and derive the closed form solution of the primal variables. Further, we consider the cooperative communication without EH and non-cooperative transmission with EH, and then optimal solutions are obtained from similar techniques. Finally, simulation results are provided where the performance of the proposed solutions is compared with the non-optimized cooperation time and without EH models.

With the extreme changes of the global climate, winter freezing injury has become an important limiting factor for the development of the global grape industry. Therefore, there is a significant need for the screening of cold-resistant wine grape germplasms and cold regionalization for cold-resistant breeding and the development of grapevine cultivation in cold regions. In this study, the low-temperature half-lethal temperature (LT50) values were determined for the annual dormant branches of 124 wine grape germplasms (V. vinifera) to evaluate their cold resistance. The LT50 values of the 124 tested germplasms ranged from −22.01 °C to −13.18 °C, with six cold-resistant germplasms below −20 °C. Based on the LT50 values, the 124 germplasms were clustered into four types, with cold resistance from strong to weak in the order of type Ⅱ > type Ⅰ > type Ⅳ > type Ⅲ, corresponding to the four cold hardiness zones. Zones 1, 2, 3, and 4 included 6, 22, 68, and 28 germplasms, respectively, with decreasing cold resistance. The number of germplasms in different hardiness zones followed a normal distribution, with the most in zone 3. In Type Ⅱ, the fruit skin color of germplasms was positively correlated with cold hardiness, while the temperature of origin was negatively correlated with cold hardiness. The average LT50 of germplasms in different origin regions ranged from −17.44 °C to −16.26 °C, with differences among some regions. The cold regionalization analysis resulted in the distribution of 124 germplasms in four temperature regions in China with six germplasms in region A (−22 °C ≤ LT50 ≤ −20 °C), 30 germplasms in region B (−20°C ≤ LT50 ≤ −18°C), 71 germplasms in region C (−18 °C ≤ LT50 ≤ −15 °C), and 17 germplasms in region D (−15 °C ≤ LT50 ≤ −13 °C). Strong cold-resistant wine grape germplasms (V. vinifera) were identified, and these could be used as parental material for cold-resistant breeding. In some areas in China, soil-burial over-wintering strategies are used, but our results suggest that some wine grapes could be cultivated without requiring winter burial during overwintering. The results of this study should provide guidance for the selection of promising strains for cold-resistant breeding for expanded cultivation of improved varieties for wine grape production in China.

Given that the global winegrape planting area is 7.2 × 106 hm2, the potential for winegrape crop-mediated carbon capture and storage as an approach to reducing greenhouse gas emissions warranted further research. Herein, we employed an allometric model of various winegrape organs to assess biomass distributions, and we evaluated the carbon storage distribution characteristics associated with vineyard ecosystems in the Hongsibu District of Ningxia. We found that the total carbon storage of the Vitis vinifera ‘Cabernet Sauvignon’ vineyard ecosystem was 55.35 t·hm−2, of which 43.12 t·hm−2 came from the soil, while the remaining 12.23 t·hm−2 was attributable to various vine components including leaves (1.85 t·hm−2), fruit (2.16 t·hm−2), canes (1.83 t·hm−2), perennial branches (2.62 t·hm−2), and roots (3.78 t·hm−2). Together, these results suggested that vineyards can serve as an effective carbon sink, with the majority of carbon being sequestered at the soil surface. Within the grapevines themselves, most carbon was stored in perennial organs including perennial branches and roots. Allometric equations based on simple and practical biomass and biometric measurements offer a means whereby grape-growers and government entities responsible for ecological management can better understand carbon distribution patterns associated with vineyards.

In this paper, we consider simultaneous wireless information and power transfer in a full-duplex (FD) communication system consisting of one FD access point A (FD-A) and one FD device B (FD-B), each being equipped with a pair of transmitter-receiver antennas for signal transmission and reception respectively. The power splitting (PS) scheme is adopted at FD-B to receive information and energy concurrently. In order to maximize the energy harvested by FD-B while considering the constraints of signal-to-interference-and-noise ratio (SINR) and maximum transmit power at both nodes, we jointly design the optimal transmit power of FD-A and FD-B, as well as the PS ratio of FD-B. Unfortunately, the primal problem is non-convex and is not always feasible with different parameters. Thus, we first present a set of conditions, under which the feasibility of the primal problem is guaranteed. Then, we derive the closed form of the optimal solution with the aid of analyzing the feasible region of the problem. Furthermore, the influences of the parameters on the maximum harvested energy are theoretically analyzed. Finally, simulation results are provided to verify the optimality of the proposed closed-form solution, to validate the analysis of the impact of parameters on the maximum harvested energy and to show the effectiveness of the proposed design, respectively.

The popularity of smart devices and the increase of access rate are switching Internet from link-centric (host-to-host) to content-centric (user-to-content). Since the primary purpose of users is to find their desired contents from the Internet, the traditional host-to-host structure will cause lots of useless traffic and decrease the network efficiency. Content-centric network (CCN) is then introduced to solve this embarrassed situation. As a new-born technology, CCN has not fully explored its potential to utilize the knowledge embedded in the contents. Hence, we propose to enhance the information extraction capability of CCN with data driving methods. Specifically, we add a label vector containing feature descriptions for each content, and then apply neural network (NN) to model users' behavior and predict their responses to new contents. To further increase prediction accuracy and potential benefits, we group users into different cells. The behavior sets of users in a cell at different time intervals are modeled by a series of NNs. Moreover, we design a new caching policy to improve network caching efficiency. Benefits in other aspects and future research directions are also discussed. Quantitative evaluations of the proposed model and caching policy are presented in the end of this paper.

Heterogeneous networks (HetNets) composed of overlapped cells with different sizes are expected to improve the transmission performance of data service significantly. User equipments (UEs) in the overlapped area of multiple cells might be able to access various base stations (BSs) of the cells, resulting in various transmission performances due to cell heterogeneity. Hence, designing optimal cell selection scheme is of particular importance for it may affect user quality of service (QoS) and network performance significantly. In this paper, we jointly consider cell selection and transmit power allocation problem in a HetNet consisting of multiple cells. For a single UE case, we formulate the energy efficiency of the UE, and propose an energy efficient optimization scheme which selects the optimal cell corresponding to the maximum energy efficiency of the UE. The problem is then extended to multiple UEs case. To achieve joint performance optimization of all the UEs, we formulate an optimization problem with the objective of maximizing the sum energy efficiency of UEs subject to QoS and power constraints. The formulated nonlinear fractional optimization problem is equivalently transformed into two subproblems, i.e., power allocation subproblem of each UE-cell pair, and cell selection subproblem of UEs. The two subproblems are solved respectively through applying Lagrange dual method and Kuhn–Munkres (K-M) algorithm. Numerical results demonstrate the efficiency of the proposed algorithm.

In China, adolescents are frequently left behind. To date, few studies have focused on the pro-social tendencies of left-behind adolescents and the relationship of family function, self-esteem, and pro-social tendency is yet to be examined. This study, therefore, aims to understand the status of pro-social tendency of left-behind adolescents and to explore the mediating and moderating roles of self-esteem in the relationship between family function and pro-social tendency. A large, school-based survey was conducted in three Chinese provinces. An analysis of covariance was first used to identify the differences in pro-social tendency between adolescents who were and were not left behind. We then analyzed the variance within left-behind adolescents using demographics, left-behind type, years of being left-behind, and caregiver related characteristics. A structural equation model was used to analyze the relationship of family function, self-esteem, and pro-social tendency, with bootstrapping used to explore the mediating role of self-esteem. Additionally, an ordinary least squares regression was used to examine the moderating effect of self-esteem. The results showed that the pro-social tendency of left-behind adolescents was lower than in non-left-behind adolescents (F = 15.11, p = 0.0001). Family function was positive related to pro-social tendency (r = 0.259), which had not only a direct effect on pro-social tendency (β = 0.254), but also an indirect effect through self-esteem (β = 0.071, bias-corrected 95% CI: 0.051:0.090; percentile 95% CI: 0.053:0.092). Additionally, 21.85% of the total effect of family function on pro-social tendency was mediated by self-esteem. Furthermore, self-esteem negatively moderated the relationship between family function and pro-social tendency (β = -0.208, p < 0.0001), such that the effect of family function on pro-social tendency became weaker as self-esteem increased. The current study verified the negative effect of being left behind on the social development of adolescents and contributed to the understanding of the importance of self-esteem in the relationship between family function and pro-social tendency. Interventions aimed at enhancing self-esteem should be developed and implemented in left-behind adolescents to promote wellness in the entirety of psychological and social outcomes.

This paper considers a full-duplex (FD) point-to-point system consisting of one multi-antenna FD access point (FD-AP) and one two-antenna FD mobile station (FD-MS). We adopt simultaneous wireless information and power transfer scheme and apply the self-energy recycling at FD-MS. In order to minimize the weighted sum transmit power, we jointly design the transmit beamforming vector of FD-AP, the receive power splitting ratio of FD-MS, and the transmit power value of FD-MS. Since the original problem is non-convex, we apply semidefinite relaxation and obtain a new convex problem. We further prove that both problems have exactly the same solutions. Finally, simulations are provided to verify our analysis, and the comparison with a half-duplex system demonstrates the significant performance gain from self-energy recycling.

The dispatch of power at minimum operational cost of thermal energy sources has been a significant part of research since decades. Recently, with increasing interests in renewable energy resources, the optimal economic dispatch has become a challenging issue. This paper presents combined emission economic dispatch model for a solar photo voltaic integrated power system with multiple solar and thermal generating plants. We formulate mixed integer binary programming problem subject to various practical constraints. A decomposition framework is proposed where the original problem is split into two sub-problems. Particle swarm optimization, Newton-Raphson method, and binary integer programming techniques are exploited to find the joint optimization solution. The proposed model is tested on the IEEE 30 bus system. The simulation results demonstrate the effectiveness of the proposed model.

Massive multiple-input multiple-output is a promising physical layer technology for 5G wireless communications due to its capability of high spectrum and energy efficiency, high spatial resolution, and simple transceiver design. To embrace its potential gains, the acquisition of channel state information is crucial, which unfortunately faces a number of challenges, such as the uplink pilot contamination, the overhead of downlink training and feedback, and the computational complexity. In order to reduce the effective channel dimensions, researchers have been investigating the low-rank (sparse) properties of channel environments from different viewpoints. This paper then provides a general overview of the current low-rank channel estimation approaches, including their basic assumptions, key results, as well as pros and cons on addressing the aforementioned tricky challenges. Comparisons among all these methods are provided for better understanding and some future research prospects for these low-rank approaches are also forecasted.

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