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In this paper, a stiffening design imitating the bamboo node is proposed for weight reduction of the long composite pipe beam subjected to bending load. The distribution of bamboo nodes can efficiently suppress the ovalization of the section, thus significantly improving the bending resistance of the bamboo. Based on this principle, ring stiffeners are proposed to be fixed to the pipe beam, making the long beam equivalent to the combination of a series of short pipes that suffered less section ovalization. A database of the optimal laminate orientations for different normalized lengths is obtained through optimizations, where the discreteness of the ply count is considered. Based on this database, weight optimizations are conducted, and the optimal designs of beams with and without stiffeners are obtained and compared. The comparison results show that the proposed bamboo-like stiffened beam not only regains a near-linear load–displacement relationship, but also reduces the weight by up to 16% under the same buckling load. In addition, it is found that for the pipe beams with radius-to-thickness ratios of more than 18, increasing the radius leads to a decrease in elastic buckling resistance when the weight remains a constant, which is opposite to the design for strength and stiffness. The model and database developed in this paper can provide a reference for weight reduction design and weight estimation for composite pipe beams.

In this letter, a radius inversion method of buried elongated metallic cylinders is proposed based on electromagnetic (EM) resonance using broadband dual-polarization radar, which could be used in applications related to EM inverse scattering and nondestructive tests. First, by utilizing the angular complementarity of dual-polarization receiving signals, the influence on resonance properties due to the difference in the cylinder's orientation and polarization direction is removed. Then, the simplified natural resonance frequencies are defined and used to extract the resonance properties from the broadband EM response. Finally, the radius is accurately inverted by establishing a least-squares relationship between the radius and the simplified natural resonance wavelengths. The effectiveness of the proposed method is validated by numerical simulations and laboratory experiments.

The recognition of underground pipelines is an important in urban areas. As an efficient and non-destructive recognition method, ground penetrating radar (GPR) has been increasingly applied in the recognition of underground pipelines. With the growing volume of GPR data, there is an urgent need for automatic recognition. However, due to the complexity of the subsurface environment, existing automatic recognition methods still have drawbacks such as low accuracy, poor robustness, and the requirement for large training datasets. An underground pipeline recognition model for GPR that combines scale-invariant feature transform (SIFT) and support vector machine (SVM) is proposed in this article. The model is based on the fact that there are scale-invariant keypoints at the tops of hyperbolas. First, SIFT is used to identify scale-invariant keypoints in the image. These keypoints undergo symmetry assessment and feature enhancement. Subsequently, SVM is employed to filter out the keypoints located at the tops of the hyperbolas. Finally, keypoints located on the same hyperbola are clustered to obtain the recognition results. The model improves the original SIFT method by modifying the calculation of the blur coefficients in the Gaussian pyramid layers. It also employs manually designed feature enhancement methods when constructing the feature descriptors. Additionally, we have introduced methods such as symmetry judgment to further enhance the model’s accuracy. The results indicate that the proposed method exhibits superior recognition performance for the field data even with very limited training samples.

Multiple-input multiple-output (MIMO) through-the-wall radar (TWR) is utilized for target detection under indoor environments. However, target signals are often overshadowed by wall clutter. Existed clutter suppression methods predominantly work effectively for TWR under synthetic aperture mode, with limited approaches for MIMO TWR. Therefore, this letter introduces amplitude coherence factor (ACF) to suppress the wall clutter. In the proposed method, the ACF is denoted by using the variance across all transmit-receive channels, which directly reflects the correlation of echo amplitudes in each pixel. Then, weights based on the ACF are assigned to the image of raw TWR image. The performance of ACF is validated by simulation and experimental results.

Through-the-wall radar (TWR) can detect and localize hidden targets behind obstacles, which has been widely applied in varieties of civil and military applications. However, wall reflections are usually stronger than those of the targets, making it very challenging to extract the target information. In this article, an adaptive wall clutter mitigation method is proposed. The discrete prolate spheroidal sequence (DPSS) basis is first used to model the wall clutter due to its superiority in modeling the spatially extended property of the walls. Then, by incorporating the compressed sensing (CS) technique, we propose a block adaptive subspace pursuit (SP) algorithm to estimate the support of the wall, which is further sifted by leveraging the correlation of the wall clutter over different antenna positions. Adaptively, the proposed algorithm can realize the mitigation of wall clutter and separate the target echo data without wall parameters or other prior information, which greatly improves the robustness in practice. Extensive simulations and real-world experiments commendably validate the effectiveness and superiority of the proposed method.

Through-the-wall radar (TWR) utilizes range and Doppler information to achieve indoor human activity recognition. However, traditional recognition methods are developed based on range-time maps (RTM) and Doppler-time maps (DTM), resulting in low accuracy and poor robustness. In order to solve these problems, this letter proposes to use micro-Doppler corner feature to achieve activity recognition and gives an adaptive corner feature extraction method based on difference of Gaussian (DoG) filter and deformable convolution. Micro-Doppler corner feature is defined as the points on the radar squared-range and squared-Doppler images where the gray scale changes sharply in different directions, reflecting the inflection, stationing, intersection, and boundaries of the motion trajectory curves of the human limb nodes. The proposed corner feature extraction method utilizes the DoG filter to extract the micro-Doppler corner supervisory labels on simulated data. The labels are then used to train the $\boldsymbol{\mu }$D-CornerDet, which is constructed based on deformable convolution network (DCN), task-adaptive deformable convolution network (TDCN), feature pyramid network (FPN) and learnable regression global attention module (LRGA). For predictions, only $\mu$D-CornerDet is used on measured data to obatin the corner feature maps. Both numerical simulations and experiments are conducted to verify the effectiveness and robustness of the proposed method.

The common middle point (CMP) ground-penetrating radar (GPR) utilizes the time-delay information under different antenna separations to realize layered inversion. However, parameter inversion of multilayered media is mostly subject to heavy computational complexity and worst estimation error in the determination of refraction positions. To address the problems, an effective parameter inversion method is proposed based on off-grid sparse CMP model with refined orthogonal matching pursuit (OMP) for multilayered parameter inversion. In the proposed method, a sparse CMP signal model with accurate reflected wave propagation modeling is developed based on a refraction approximation method. An off-grid sparse CMP model is further constructed based on second-order Taylor expansion to overcome the deviation from the grid node. Then, a refined OMP algorithm based on compressed sensing (CS) is proposed with an off-grid optimization process to achieve accurate off-grid parameter inversion. Finally, the effectiveness of the proposed method is verified by simulations and experiments.

Steering vector (SV) mismatch caused by the DOA uncertainty in the source leads to a remarkable performance degradation for adaptive beamforming particularly in situation where the training data includes an unknown expected signal (ES) component. To mitigate this problem, a robust adaptive beamforming method based on SV phase correction and covariance matrix reconstruction is proposed in this letter. The first step is to correct the SV phase of the ES using the maximum a posteriori (MAP) estimation method. Next, the Gauss-Chebyshev quadrature is introduced to efficiently reconstruct the interference-plus-noise covariance matrix by integrating within the corrected azimuthal sector. The effectiveness and superiority of the proposed method in mitigating SV mismatch errors are confirmed by both numerical simulations and experimental results.

Layered medium parameter inversion is a crucial technique in ground-penetrating radar (GPR) data processing and has wide application in civil engineering and geological exploration. In response to the issues of high computational complexity and low accuracy associated with existing methods, a novel layered medium parameter inversion approach is proposed, comprising the deconvolution autoencoder and the parameter inversion network. First, the deconvolution autoencoder is introduced to solve the pulse response of layered medium systems in an unsupervised manner, which enhances the computational efficiency of deconvolution and decouples the data acquisition system from the supervised model. Subsequently, a parameter inversion network, including a self-attention module and a residual multilayer perceptron (MLP), is proposed to address the challenge posed by the excessively sparse pulse responses. The self-attention module calculates the autocorrelation of the pulse sequence, providing temporal delay information between pulses and reducing the sparsity of the pulse response to facilitate feature extraction. Meanwhile, the residual MLP, known for its low information loss and adaptability to different output dimensions, is employed for model-based and pixel-based inversions in situations with and without prior knowledge of the layer number, respectively. Finally, simulated and measured datasets are constructed to comprehensively train and evaluate the proposed method. The results demonstrate that the proposed method exhibits better performance of inversion accuracy, computational efficiency, robustness, generalization capability, and noise resistance. In addition, it remains applicable even when prior knowledge of the layer number is unknown.

Fuzzy relation system with max-min composition could be applied to describe the three-tier multimedia streaming architecture. In such an architecture, the regional servers supply their local multimedia streaming services to the clients. Random fault has not been considered in the relevant existing researches. However, the random fault of a regional server is possible to occur, or even unavoidable, due to some unpredictable reasons. In this article, we consider a random fault occurring at either one of the regional servers. With such a consideration, the corresponding architecture is characterized by the so-called variable-absent fuzzy relation inequalities system with max-min composition. Some properties of our proposed variable-absent fuzzy relation inequalities system are investigated. Based on such properties, we further propose a 2-D path approach for obtaining the complete solution of the variable-absent system. In addition, we also study a corresponding weighted minimax optimization problem motivated by the practical management objective. An effective algorithm is developed for searching the optimal solution, with an illustrative example.

In recent years, the addition-min fuzzy relation inequalities have been adopted to describe the flow constraint in a P2P network system. Each solution of the inequalities represents a feasible flow control scheme. Motivated by some different managerial objectives, several optimization problems subject to the addition-min inequalities have been recently studied. For example, considering the total efficiency for decreasing the network congestion, the linear objective function was adopted. While considering the fairness among the terminals, the min–max objective function was employed. In this article, combining these two objectives, we establish a corresponding bilevel fuzzy relation programming subject to the addition-min inequalities. For solving the bilevel programming, we first investigate some properties of the first-level programming, using the concept of fixed index set. Based on the properties of the first-level programming, our studied bilevel programming could be equivalently converted into a single-level programming and then solved by the existing linear programming approach. Our resolution approach is carried out by the fixed-index-set based algorithm and illustrated by some numerical examples.

Persistent bacterial infections and excessive oxidative stress prevent the healing of diabetic ulcers, leading to an increased disability rate. Current treatments fail to kill bacteria while simultaneously relieving oxidative stress. Herein, a dynamic microenvironment-adaptable hydrogel (BP@CAu) with photothermal performance and reactive oxygen species scavenging is presented for diabetic ulcer healing. This hydrogel prepared using a dynamic borate-ester could respond to acidity in the infection microenvironment for a controllable drug release. An excellent photothermal conversion effect was integrated in the hydrogel, which exhibited strong antibacterial activity against Staphylococcus aureusand Pseudomonas aeruginosa. The hydrogel attenuated intracellular oxidative stress and inflammation and promoted cell migration. In a full-thickness skin defect model of diabetic rats, the BP@CAu hydrogel contributed to the fastest wound closure, with ideal reepithelialization, granulation tissue formation, and regeneration of blood vessels. Further mechanistic studies revealed that the hydrogel relieved oxidative stress and downregulated the expression of inflammatory cytokines, resulting in dramatic therapeutic effects on diabetic wounds. Therefore, this study provides a synergistic therapeutic strategy for efficient photothermal performance and reactive oxygen species scavenging in diabetic ulcers.

Early control of elevated blood pressure is the most promising treatment for acute intracerebral haemorrhage. We aimed to establish whether implementing a goal-directed care bundle incorporating protocols for early intensive blood pressure lowering and management algorithms for hyperglycaemia, pyrexia, and abnormal anticoagulation, implemented in a hospital setting, could improve outcomes for patients with acute spontaneous intracerebral haemorrhage.

In this work, we introduce the fuzzy relation inequalities with min-plus composition for describing the pricing problem in a product transportation system. Some basic properties of the min-plus inequalities system are investigated. We define the concept of a feasible index chain and further investigate the corresponding quasi-maximal solution. Moreover, it is found that the solution set of a min-plus system could be generated by a unique minimum solution and a finite number of quasi-maximal solutions. As a consequence, one is able to find the complete solution set of a min-plus system. Besides, motivated by the optimal managerial objective, we establish an optimization model with the min-plus inequalities constraints. A so-called feasible index set (FIS)-based algorithm is developed for searching an optimal solution of our studied optimization model. We have provided a simple numerical example for checking the effectiveness of our proposed FIS-based algorithm. The obtained optimal solution would be helpful for the system manager as an optimal pricing scheme.

Through-the-wall radar (TWR) is commonly employed for indoor target imaging and detection. However, the targets’ echoes are often whelmed by the reflected waves of the wall and the rebars inside. Since the shape of clutter caused by rebars is similar to the target echo in B-scan, the performance of many clutter suppression methods in the literature degrades severely. Aiming at the problem of rebar clutter removal, this article proposes a rebar clutter suppression method based on range migration compensation and low-rank and sparse decomposition with total variation regularization. In the proposed method, the Hough transform is used to locate the rebars after removing the reflected waves of the wall. Then, the rebars’ echoes are transformed into a horizontal line by range migration compensation in order to make it in a low-rank subspace. Based on the model of low-rank sparse decomposition and total variation regularization, the target matrix is extracted. Finally, inverse range migration is performed to obtain the target signal. Numerical simulation and experimental results demonstrate the effectiveness and superiority of the proposed method in terms of target-to-clutter ratio (TCR).

Ultrawideband (UWB) through-the-wall radar (TWR) can be used for indoor human behavior recognition via micro-Doppler information. However, faced with weak micro-Doppler features and low accuracy, conventional recognition method does not perform well in shielded environment. To address these problems, this article proposes an indoor human behavior recognition method based on the wavelet scattering network and conditional random field model (TWR-WSN-CRF). In the proposed method, wavelet scattering network (WSN) and speckle reducing anisotropic diffusion (SRAD) with weighted guided image filter (WGIF) are used for feature enhancement and noise suppression, and the signal-to-noise ratio (SNR) is improved. Then, the human behavior recognition network based on the conditional random field (CRF) model is developed to extract global and local features from the wall, target, and noise subspaces obtained by singular value decomposition (SVD). Finally, the multilayer perceptron (MLP) model and weighted majority voting (WMVE) method are used for fusion decision. The effectiveness of the proposed method is verified by experiment. The results show that compared with other methods, the proposed human behavior recognition method achieves highest recognition accuracy with 96.25% on the validation dataset.

Dysregulated skin microbiota and compromised immune responses are the major etiological factors for non‐healing diabetic wounds. Current antibacterial strategies fail to orchestrate immune responses and indiscriminately eradicate bacteria at the wound site, exacerbating the imbalance of microbiota. Drawing inspiration from the beneficial impacts that probiotics possess on microbiota, a living microecological hydrogel containing Lactobacillus plantarumand fructooligosaccharide (LP/FOS@Gel) is formulated to remodel dysregulated skin microbiota and reinstate compromised immune responses, cultivating a conducive environment for optimal wound healing. LP/FOS@Gel acts as an “evocator,” skillfully integrating the skin microecology, promoting the proliferation of Lactobacillus, Ralstonia, Muribaculum, Bacillus, and Allobaculum, while eradicating colonized pathogenic bacteria. Concurrently, LP/FOS@Gel continuously generates lactic acid to elicit a reparative macrophage response and impede the activation of the nuclear factor kappa‐B pathway, effectively alleviating inflammation. As an intelligent microecological system, LP/FOS@Gel reinstates the skin's sovereignty during the healing process and effectively orchestrates the harmonious dialogue between the host immune system and microorganisms, thereby fostering the healing of diabetic infectious wounds. These remarkable attributes render LP/FOS@Gel highly advantageous for pragmatic clinical applications. A living microecological hydrogel, which remodels the skin microbiota and reinstates the host immune responses at the wound site, has been proposed to promote diabetic wound healing. This innovative living hydrogel restores the equilibrium of skin microbiota, elicits a reparative macrophage response, and impedes the activation of the nuclear factor kappa‐B pathway, fostering a conducive environment for healing.

In this paper we consider the wireless Server-to-Client (S2C) network system with server peers and user (client) peers. The server peers provide the data resources to the user peers. In order to describe the wireless S2C network system in which there exists at least one candidate server for each user, we define and investigate the so-called sec-max-product fuzzy relation inequalities. Basic properties and the structure of the solution set have been studied for the sec-max-product fuzzy relation inequalities system. Moreover, the optimal solution under a lexicographic order, namely the lexicographic minimum solution, is further proposed and studied in the sec-max-product system, for minimizing all the variables under some fixed priority grade. An efficient resolution algorithm is developed for computing the lexicographic minimum solution of the sec-max-product system, with several illustrative examples.

•A new biochar-based composite hydrogel (S-B-AA) was synthesized with high water absorption and retention capacity.•S-B-AA can effectively alleviate the adverse effects of drought stress on tobacco seedling.•The utilization of S-B-AA proved to be highly beneficial in mitigating the antioxidant system of tobacco seedlings.•GO and KEGG enrichment analysis showed that S-B-AA hydrogel can regulate multiple signaling pathways.

Transdermal drug delivery against skin cancer may be more effective than oral or injection delivery because patients may be more likely to complete the treatment and it may be less likely to trigger gastrointestinal side effects. Here we developed doxorubicin-loaded nanoparticles based on cationic polyethyleneimine-oleic acid for transdermal delivery, and we applied the nanoparticles to skin pre-treated with metal microneedles to facilitate their passage through the tough epithelial barrier. The cationic nanoparticles were extremely small, which probably also facilitated their transdermal passage. They accumulated in subcutaneous melanoma tumors in mice, slowing tumor growth and inducing apoptosis. These therapeutic effects were weaker but still significant when skin was not pretreated with microneedles. Our results suggest a promising new platform for transdermal treatment of skin cancer and potentially other skin diseases.

Objective: The Kay Pentax nasometer uses a separator plate that touches the philtrum of a patient to separate the nasal and oral sound energies for nasalance measurement. However, the separator plate can restrict the natural movement of the patient’s upper lip and generate unpleasant pressure on the patient’s philtrum. The present study was intended to measure nasalance scores without touching the philtrum for better comfort during speech assessment and therapy.Methods: Nasalance scores of 10 males and 10 females having no speech disorders were measured under 4 levels (0, 5, 10, and 15 mm) of the gap between the plate and the philtrum (denoted as plate-to-philtrum gap) using Nasometer II 6450 for nasal (Nasal Sentences) and oral (Zoo Passage) stimuli. Regression formulas were established to examine the relationships between nasalance score and plate-to-philtrum gap for the stimuli. To provide nasalance scores equivalent to those measured for the contact condition, compensation factors for the 5 mm plate-to-philtrum gap measurement condition were identified for the stimuli.Results: The nasalance scores were significantly different between the 4 different plate-to-philtrum gaps for the stimuli. Compensation factors for the Nasal Sentences and the Zoo Passage were identified as 1.17 and 0.71, respectively.Conclusions: The 5 mm plate-to-philtrum gap condition after multiplying the compensation factors can provide equivalent nasalance scores to the conventional contact measurement condition which may provide better comfort in speech assessment and therapy.

Mercury (Hg) is considered an extremely toxic heavy metal which is extremely harmful to both the human body and environment. In addition, Hg2+-induced oxidative stress also exerts a crucial role to play in pathophysiological mechanisms of mercury toxicity. Thus, efficient and specific fluorescent probes for imaging Hg2+-induced oxidative stress are necessary. In the present study, we rationally design a novel Hg2+-activated and ICT-based NIR emission fluorescent probe NIR-HOfor sequentially monitoring the ONOO–level with a “dual-key-and-lock” strategy. The probe NIR-HOshowed rapid response and excellent specificity and sensitivity for the detection of Hg2+and ONOO–in vitro. Cell imaging demonstrated that Hg2+-induced oxidative stress was involved in ONOO–upregulation. Also, GSH, NAC, and EDTA were employed as excellent detoxifying drugs against Hg2+-induced toxicity. Moreover, the probe NIR-HOwas successfully used for imaging Hg2+and ONOO–in vivo. In brief, NIR-HOprovides a simple and powerful approach which can be used to image Hg2+-induced oxidative stress in the pathological environment.

The effects of xylo-oligosaccharides (XOS) on broiler growth performance, immune function, and intestinal health were investigated. A total of 540 one-day-old Arbor Acres Plus broilers were randomly divided into 5 groups with 6 replicates per group and 18 chickens per replicate. Broilers in the control (CON) group received a corn-soybean meal based basal diet, those in the antibiotics (ANT) group received the basal diet plus 500 mg/kg oxytetracycline, and those in XOS groups received the basal diet plus 150, 300, and 450 mg/kg XOS, respectively. Compared with CON, the body weight at 42 d and average daily gain from 1 to 42 d were significantly increased in the 150, 450 mg/kg XOS-added and ANT groups (P= 0.018), and the relative expression of claudin-1 and ZO-1mRNA in the ileum was significantly higher in the 300 and 450 mg/kg XOS-added groups (P< 0.001). The feed conversion ratios (P< 0.001) and abdominal fat rates (possibly related to short-chain fatty acids [butyric acid] produced by XOS in broilers) (P= 0.012) of broilers from 1 to 42 d of age were significantly lower in all XOS-added groups than in the control group. Splenic index (P= 0.036) and bursa index (P= 0.009) were significantly better in the ANT group and each XOS-added group than in the control group. Compared to CON and ANT, serum IgA (P= 0.007) and IgG (P= 0.002) levels were significantly higher in the 300 mg/kg XOS-added group, and the relative abundance of short-chain fatty acid-producing genera (Alistipes) was also significantly higher (P< 0.001). Meanwhile, ileal villus height (P< 0.001) and V:C (P= 0.001) were significantly increased in XOS-added broilers. In analysis of relationships between cecal microbes and the physical barrier of the gut, [Ruminococcus]_torques_groupwas positively correlated with mRNA expression of ileal claudin-1 (P< 0.05), and Bacteroideswas positively correlated with increased ileal villus height and V:C (P< 0.05). Overall, XOS addition to broiler diets improved growth performance, promoted intestinal health by enhancing intestinal barrier function, and regulating cecal microbiota diversity, and had positive effects on immunity.

The present study estimated instantaneous hand joint centers of rotation (CoR) using 3D reconstructed hand skeleton motions captured from CT scan. We proposed a novel method for estimation of instantaneous joint CoR using the same bone surfaces for different hand postures. Each bone in a template hand posture was registered to the corresponding bone of different hand postures. The registered hand postures (having the same bone surfaces as the template hand posture but different postures) with the template hand posture were then used for estimation of instantaneous joint CoR. The proposed method performed better than the existing methods in estimation of instantaneous joint CoR. Consistency of instantaneous joint CoRs determined in the same rotation angle range was improved by 31.7% to 51.0% in the proposed method. The present study focused on distal interphalangeal (DIP) and proximal interphalangeal (PIP) joints of the index finger of a participant. Joints of the whole hands of more participants will be studied for further generalization of the findings.

NiO/AgNWs/FTO electrode material with three-dimensional structure is prepared by method of electrochemical deposition. The SEM images of NiO/AgNWs/FTO electrode nanocomposite revealed that the NiO is wrapped onto the surface of AgNWs. Furthermore, the effect of annealing time on the electrochemical properties of the electrode was studied, it shows excellent electrochemical performance and good linear relationship during the charge-discharge process. The NiO/AgNWs/FTO electrode with specific capacitance of 408 F g–1has been achieved at a current density of 0.85 A g–1and it has excellent cycling stability with 80% retention over 7,000 cycles at a high current density of 5.5 A g–1when the annealing time is 60 minutes. It can be widely used in the micro-electronic devices, such as micro supercapacitors and chips of computer.

The maintenance of gaze fixation during visual field testing is needed to accurately measure the functionality of the optic nerve. The present study is intended to analyze the performance of gaze fixation and evaluate five gaze fixation induction methods (GFIM) including black dot (BD; conventional method), changing color dot (CCD), alphanumeric characters (AC), flashing black dot (FBD), and bulls-eye with cross hair (BECH). Recruiting 32 participants (16 in 20s and 16 in 30s), the experiment was conducted in four steps: (1) preparation, (2) exercising the visual field testing, (3) main experiment for five GFIMs, and (4) debriefing. The performance of gaze fixation was analyzed in terms of correct fixation rate (CFR), and subjective satisfaction was evaluated in terms of ease of gaze fixation (EGF), eye fatigue (EF), and overall satisfaction (OS) using a 11-point Likert bipolar scale. The CFRs of the four new GFIMs were all higher than that of BD (BD = 86.7%, CCD = 87.9%, AC = 88.8%, FBD = 91.5%, and BECH = 88.0%). However, there was no statistically significant difference among the CFR averages of the five GFIMs, but the variances of CFR of the newly proposed GFIMs were all lower than that of BD. The subjective satisfaction of BECH (EGF = 2.0, EF = -0.4, OS = 1.6) was highest. Therefore, BECH was recommended for an effective GFIM to maintain the examinee’s gaze fixation during a visual field testing in both aspects of the performance and the subjective satisfaction.

Regression equations for estimation of a driver’s hip location (HL) and eye location (EL) using the driver’s anthropometric and posture variables have been developed for US drivers. However, those equations are limited to US drivers and do not include seat adjustment variables (e.g., cushion angle) that may affect a driver’s HL and EL. The present study developed statistical models for prediction of a driver’s HL and EL using seat configurations including (1) fore-aft seat position, (2) seat height, (3) seat back recline angle, and (4) seat cushion angle. Driving postures of 23 Korean drivers (10 females and 13 males) were measured in a seating buck after adjusting seat configurations according to their preferences. The seat configurations, HLs, ELs, and joint angles of the participants were collected by a motion capture system. HL and EL prediction models based on the seat configurations and driving postures were developed by stepwise regression. The proposed models showed high accuracy (adj. R2 = .83 ± .13, RMSE = 19.1 ± 4.2 mm) in prediction of HL and EL. The performance difference between the seat configuration- and posture-based models was not statistically significant. The proposed seat configuration-based models can be used for accurate estimation of a driver’s HL and EL for occupant packaging layout design.

Conventional space-time adaptive processing (STAP) requires large numbers of independent and identically distributed (i.i.d) training samples to ensure the performance of clutter suppression, which is hard to be achieved in practical complex nonhomogeneous environment. In order to improve the performance of clutter suppression with small training sample support, a robust and fast iterative sparse recovery method for STAP is proposed in this paper. In the proposed method, the sparse recovery of clutter spatial-temporal spectrum and the calibration of space-time overcomplete dictionary are achieved iteratively. Firstly, the robust solution of sparse recovery is derived by regularized processing, which can be calculated recursively based on the block Hermitian matrix property, afterwards the mismatch of space-time overcomplete dictionary is calibrated by minimizing the cost function. The proposed method can not only alleviate the effect of noise and dictionary mismatch, but also reduce the computational cost caused by direct matrix inversion. Finally, the proposed method is verified based on the simulated and the actual airborne phased array radar data, which shows that the proposed method is suitable for practical complex nonhomogeneous environment and provides better performance compared with conventional STAP methods.

Objectives The lung cancer is most frequently diagnosed cancer incidence worldwide. A large number of populations are heavily affected to this every year with poor prognosis.Methods Our study investigated the anticancer effect of alternariol, a secondary metabolite, on A549 lung cancer cell line and benzo-α-pyrene induced lung carcinoma model on balb/c mice. The cytotoxicity assay, DAPI staining and the flow cytometry was performed to assess the anticancer efficacy of alternariol in A549 lung cancer cell. For in vivo study the toxicity study was performed. The lung cancer was developed in the animals via intraperitoneal administration of benzo-α-pyrene and subsequently 2 weeks later alternariol treatment was carried out for 24 weeks. The chemotherapeutic effect of alternariol was assessed through histopathological analysis, followed by immunohistochemistry and in vivo antioxidant study.Results The in vitro data suggested a significant percentage of early and late apoptotic events in A549 cells with G0/G1 phase arrest which ultimately caused apoptosis followed by alternariol therapy. The in vivo study showed that alternariol therapy decreased the pulmonary fibrosis and formation of granuloma in lung tissue and restored the normal histopathological characteristics of lung. Furthermore, alternariol treatment downregulated the expression of PI3K, Akt and inflammatory mediators such as IL-6, TNF-α and increased the expression of apoptotic markers, p53.Conclusion In conclusion, the treatment with alternariol effectively decreased the progression of lung cancer through the inhibition of carcinogenic markers by reprogramming the p53/PI3K/Akt pathway and IL-6/TNF-α mediated cytokine signaling in mice.

Copper (I) iodide (CuI) films are grown on glass substrates with a direct vacuum thermal evaporation method, and the effect of substrate temperature on their photoluminescence and transparent conductive properties is discussed. The X‐ray diffraction (XRD) measurement identifies the polycrystalline CuI film has γ‐phase with (111) preferential growth direction. When the substrate temperature is optimised at 120 °C, the average transmittance is about 90% in the wavelength range of 410–1500 nm. The electrical properties measured by Hall effect show the lowest resistivity of 1.0 × 10−2Ωcm with hole concentration of 3.0 × 1019cm−3and mobility of 25 cm2V−1s−1. These results indicate that direct thermal deposition is a simple method to grow high quality p‐type CuI films.

Because of large computational complexity in the inverse space-time covariance matrix computation, the conventional space-time adaptive processing (STAP) is unsuitable for practical implementation. According to the block Hermitian matrix property of covariance matrix, a new element-order recursive method is proposed in this paper to calculate the inverse space-time covariance matrix for STAP weight vector. In the proposed method, the inverse space-time covariance matrix of first element-order is initially calculated recursively based on block Hermitian matrix property, and then the inverse space-time covariance matrix of high element-order is correspondingly deduced recursively based on obtained inverse covariance matrix of previous element-order. Finally, STAP weight vector is calculated based on the final inverse covariance matrix. Afterwards, a modified reduced-dimension STAP method is derived by combining the proposed method with the m-Doppler Transformation (mDT-SAP) STAP approach. Based on the simulated and the actual airborne phased array radar data, the proposed method verified that the computational complexity is much smaller than conventional STAP methods. The proposed element-order recursive method for STAP is applicable for practical airborne phased radar system.

The present study developed a user-centered 3D virtual liver surgery planning system called Dr. Liver™ to assist surgeons in preoperative planning of liver surgeries such as living donor liver transplantation and tumor resection. Use scenarios of Dr. Liver were developed through literature review, benchmarking, and interviews with surgeons. The major functions of Dr. Liver include (1) 3D reconstruction of the liver, vessels, and tumors from abdominal CT images, (2) virtual resection simulation for liver surgery planning, and (3) volumetric measurement of the liver, vessels, tumors, remnant, and/or graft. Novel image processing algorithms were developed and implemented into Dr. Liver for accurate and efficient liver surgery planning. Various user-friendly features such as a hierarchical interface were integrated into Dr. Liver for better usability. The usability of Dr. Liver was systematically evaluated with eight medical doctors from three different medical centers using various performance and preference measures. Dr. Liver received a high score of user satisfaction (6.1 ± 0.2) as measured using a 7-point Likert scale. Dr. Liver will be used in preoperative liver surgery planning for safe and rational liver surgery.

The eigenanalysis canceler (EC) method which is suitable for nonhomogeneous clutter can suppress clutter effectively by discarding the eigenvectors of small eigenvalues, which is a well-known subspace-based space-time adaptive processing (STAP) method. However, the computational complexity of conventional EC STAP method is huge due to the eigenvalue decomposition. Moreover, the corresponding performance would be degraded significantly by the subspace leakage phenomenon, since the clutter subspace is not strictly confined to a low-rank subspace any more. Therefore, an improved EC STAP method based on the data-independent clutter subspace estimation is proposed to reduce the computational complexity, where the clutter subspace is rapidly constructed by sampling the prolate spheroidal wave functions (PSWF) non-uniformly. In order to deal with the subspace leakage phenomenon, the proposed EC-PSWF STAP method is modified based on the covariance matrix taper (CMT) to obtain the covariance matrix by re-establishing the noise floor. The corresponding performance of proposed method is evaluated by using the numerical simulation.

AbstractContext: There are few reports of endothelial progenitor cells (EPCs) in peripheral blood have been found in patients with gastric cancer.Objective: We quantified EPCs in the peripheral blood of patients with gastric cancer, with the expectation that this approach might lead to a new marker for the diagnosis of gastric cancer.Methods: We enumerated CD34/CD133 EPCs in the peripheral blood of 145 subjects by use of flow cytometry.Results and conclusion: The quantity of peripheral blood EPCs in patients with gastric cancer are correlated with patient’s age. In addition, the number of peripheral blood EPCs in patients with gastric cancer increased with tumor node metastasis stage and histological differentiation of the cancers, and with the operative status of the patients.