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Endoscopic sinus surgery (ESS) has been recognized as an effective treatment modality for paranasal sinus diseases. Over the past decade, continuum robots (CRs) for ESS have been studied, but there are still some challenges. This paper presents a review on the scientific studies of CRs for ESS.Based on the analysis of the anatomical structure of the paranasal sinus, the requirements of CRs for ESS are discussed. Recent studies on rigid robots, handheld flexible robots, and CRs for ESS are presented. Surgical path planning, navigation, and control are also included.Concentric tube CRs and cable-driven CRs have great potential for applications in ESS. The CRs incorporated with multiple replaceable arms with different functions are preferable in ESS.Further study on navigation and control is required to improve the performance of CRs for ESS.

Due to the inherent deformability of continuum robots (CRs), closed-loop control strategies of CRs come with some challenges, including sensor integration within a limited dimension and uncertainties with the CR system. In this paper, to obtain the spatial shape information and tip position of a cable-driven CR, a draw tower grating (DTG) sensor is integrated. A shape sensing algorithm is proposed to reconstruct the shape of the CR based on the relation between the DTG sensor and the CR centerline. Then, with the feedback information of the DTG sensor, a damped least-squares (DLS)-based closed-loop controller is implemented to improve the trajectory tracking performance of the CR. To verify the effectiveness of the proposed scheme, comparative experiments are performed.

Data augmentation, generating new data that are similar but not same with the original data by making a series of transformations to the original data, is one of the mainstream methods to alleviate the problem of insufficient data. Instead of augmenting input data, this paper proposes a method for augmenting features in the middle layers of deep models, called MEML (Mean Extrapolation in Middle Layers). It gets the features outputted by any middle layer of deep models and then generates new features by doing mean extrapolation with some randomly selected features. After that, it replaces these selected features with their corresponding new ones and keeps the labels unchanged, and then lets the new composed output continue to propagate forward. Experiments on two classic deep neural network models and three image datasets show that our MEML method can significantly improve the model classification accuracy and outperform in most experiments the state-of-the-art feature space augmentation methods that factor dropout and K Nearest Neighbors extrapolation. Interestingly, when coupled with some input space augmentation methods, e.g., rotation and horizontal flip, our MEML method further improves the performance of two deep models on three datasets, implying that the input space augmentation methods and MEML could complement each other.

In order to select a reasonable controlling mode of rocky desertification and restrain the development of rocky desertification with local conditions, the soil moisture in Karst area was studied by using full-polarization Synthetic Aperture Radar (SAR) data in this paper. Based on the decisive role of rocky desertification degree, vegetation, slope and characteristic of the soil, different models were employed to invert the soil moisture in different rocky desertification degree areas according to their land use type and vegetation as follows: (1) The advanced integral equation model (AIEM) was employed in the intensive rocky desertification and serious rocky desertification areas. (2) The water-cloud model (WCM) coupled with AIEM was employed in the slight rocky desertification and moderate rocky desertification areas. (3) The Michigan microwave canopy scattering (MIMICS) model coupled with AIEM was employed in the non-rocky desertification and potential rocky desertification areas. As a result, the soil moisture was inverted successfully in the whole study area with the total inversion accuracy of 84.37% and RMSE of 2.10. This result demonstrates that the proposed method can invert the soil moisture accurately and provide a powerful technical support for inverting the soil moisture in the Karst area with large span, fluctuating landform and diverse vegetation.

Due to its effective high-frequency suppression ability, the LCL filter has been widely used between inverters and the grid. However, its resonance causes system instability. The weighted-average current (WAC) strategy has been extensively studied to suppress resonance. By selecting a proper weight factor of the inductor and injected current, the order of the LCL can be reduced to first without resonance in the control loop, which can significantly simplify the controller design. Nevertheless, disturbances and uncertainties in the system will affect the control performance of the inverter. In this article, for a WAC-form LCL grid-tied inverter, a separate-structure uncertainty and disturbance estimator (SUDE) inner-loop control strategy with a zero-phase, low-pass, time-delay FIR filter is designed in the discrete domain to eliminate the influence of disturbances and parameter uncertainties on the system, and a proportional resonant controller is adopted as an outer-loop controller. By using the proposed FIR filter, the performance in the rejection of high-frequency harmonics is improved. Moreover, the stability of the proposed two-degree-of-freedom compound controller is analyzed in detail, and the superiority and effectiveness of its robustness to grid impedance and harmonic rejection are shown. Finally, the proposed strategies are validated on a 2-kW experimental platform.

This paper presents experimental characterizations and device modeling on the nanoscale MOSFETs with 40 nm low-power CMOS technology. Systematic temperature-dependent ${I}_{D}$ - ${V}_{GS}$ results of NMOS/PMOS devices reveal that both the threshold voltage and the effective channel mobility exhibit strong correlations with the device size owning to the depletion region broadening around the gate channel at cryogenic temperatures. By taking the temperature-driven gate geometry effects into consideration, a generic physical model with universal fitting parameters is proposed to depict the transfer characteristics of all CMOS transistors across the device size chart, and further validations of the modified BSIM compact model might pave the way for an accurate design of cryogenic electronics applications.

With the continuous scaling in conventional CMOS technologies, the planar MOSFET device is limited by the severe short-channel-effect (SCE), Multi-gate FETs (MuG-FET) such as FinFETs and Nanowire, Nanosheet devices have emerged as the most promising candidates to extend the CMOS scaling beyond sub-22 nm node. The multi-gate structure has better short channel behaviors due to enhanced control from the multiple gates. Due to the relatively more mature process and rich learning of the device physics, the FinFET is still extended to 5 nm technology node. In this paper, we proposed a 5 nm FINFET device, which is based on typical 5 nm logic design rules. To achieve the challenging device performance target, which is around 15% speed gain or 25% power reduction against the 7 nm device, we have performed an optimization on the process parameters and iterate through device simulation with the consideration of current process capability. Based on our preferred device architecture, we provide our brief process flow, key dimensions, and simulated device DC/AC performance, like Vt, Idsat, SS, DIBL and parasitic parameters. As a part of the final evaluation, RO simulation result has been checked, which demonstrates that the Performance Per Area (PPA) is close to industry reference 5 nm performance.

With the rapid development of smart power terminals equipped with embedded operating systems, business APPs have emerged rapidly along with them. Since various business APPs have excessive access to system resources, this will lead to the waste of system resources, and at the same time, the system security is not guaranteed. Therefore, in this paper, based on the context-aware program access control hardware resource framework, an auxiliary tool is designed to control the access of business APPs with excessive authority. The auxiliary tool trains the model through the steps of training sample collection, sample data processing, feature extraction, parameter selection, and model training. By conducting simulation experiments, the results show that by using the auxiliary tool proposed in this paper, the device can well identify the business APPs with excessive privileges and reduce the abuse of related resources with a small load, which has almost negligible impact on the users’ usage.

Background Existing rigid instruments have difficulties in backward inspection and operation. Moreover, the pathway to the maxillary sinus is curved and narrow, resulting in complex and repetitive manual operations. There is a necessity to develop a retro-flexing robot and achieve path-following motion. Methods A continuum robotic system is developed for maxillary sinus surgery (MSS). And the system adopts an anatomical constraint-based optimization of the follow-the-leader strategy to generate a safe control scheme along a given path. Results The accuracy of the system is evaluated, and the task of reaching deep-seated targets is performed in a constrained anatomical space. The simulations and experiments of the path-following motion have validated the feasibility of the proposed method. Furthermore, a preliminary porcine study is performed to assess the capability of instruments. Conclusions The developed continuum robotic system can meet the requirements of MSS.

BACKGROUND: Microribonucleic acids (miRNAs) have been shown to play important roles in hepatocellular carcinoma (HCC) progression. MiR-448 has frequently been shown to be a tumor suppressor, and is abnormally expressed in HCC tumor tissues. However, little is known about the role of miR-448 in HCC development. In this article, the regulatory role of miR-448 on insulin-like growth factor 1 receptor (IGF-1R) in modulating hepatoma cell viability and glycolysis was investigated. METHODS: The expression of miR-448 profiles in clinical tumor tissues and cell lines was examined using quantitative real-time polymerase chain reaction (qRT-PCR). HepG2 and Huh7 cells were transfected with miR-448 mimics, inhibitors, and scramble sequences. Cell viability and apoptosis were determined by a Cell Counting Kit-8 assay and a flow cytometry analysis. IGF-1R, a potential target of miR-448, was selected following a bioinformatic analysis, and the regulatory effects of miR-448 on IGF-1R expression was confirmed by luciferase reporter assay, qRT-PCR, and western blot. Glucose uptake, lactate production, and adenosine triphosphate (ATP) generation were detected by corresponding kits. RESULTS: Decreased miR-448 expression was observed in both HCC patients’ tumor tissues and hepatoma cells in vitro. The overexpression of miR-448 in HepG2 and Huh7 cells decreased cell viability and increased apoptosis. Additionally, the overexpression of miR-448 or the knockdown of IGF-1R lowered the level of glucose uptake, lactate production, and ATP generation, while the knockdown of miR-448 increased glycolysis. Further, aberrantly expressed miR-448 downregulated IGF-1R levels, while the inhibition of miR-448 resulted in the upregulation of IGF-1R in both HepG2 and Huh7 cells. In addition, miR-448 interacted with the wild-type 3'untranslated regions (3'UTRs) of IGF-1R, but had no effect on the mutant 3'UTRs. The expression of IGF-1R was increased in HCC patients’ tumor tissues and serum, and was inversely correlated with miR-448 expression. CONCLUSIONS: The increased expression of miR-448 appears to downregulate the expression of IGF-1R by interacting with the 3’UTR in HCC progression. These findings highlight its role as a potential target for HCC therapy.

Cross-modal retrieval aims to search the semantically similar instances from the other modalities given a query from one modality. However, the differences of the distributions and representations between different modalities make that the similarity of different modalities can not be measured directly. To address this problem, in this paper, we propose a novel semantic consistent adversarial cross-modal retrieval (SC-ACMR), which learns semantic consistent representation for different modalities under adversarial learning framework by considering the semantic similarity from intra-modality and inter-modality. Specifically, for intra-modality, we minimize the intra-class distances. For the inter-modality, we require class center of different modalities with same semantic label to be as close as possible, and also minimize the distances between the samples and the class center with same semantic label from different modalities. Furthermore, we preserve the semantic similarity of transformed features of different modalities through a semantic similarity matrix. Comprehensive experiments on two benchmark datasets are conducted and the experimental results show that the proposed method have learned more compact semantic representations and achieved better performance than many existing methods in cross-modal retrieval.

Cold-storage containers are widely used in cold-chain logistics transportation due to their energy saving, environmental protection, and low operating cost. The uniformity of temperature distribution is significant in agricultural-product storage and transportation. This paper explored temperature distribution in the container by numerical simulation, which included ventilation velocity and the fan location. Numerical model/numerical simulation showed good agreement with experimental data in terms of temporal and spatial air temperature distribution. Results showed that the cooling rate improved as velocity increased, and temperature at 45 min was the lowest, when velocity was 16 m/s. Temperature-distribution uniformity in the compartment became worse with the increase in ventilation velocity, but its lowest temperature decreased with a velocity increase. With regard to fan energy consumption, the cooling rate of the cooling module, and temperature-field distribution in the product area, velocity of 12 m/s was best. Temperature standard deviation and nonuniformity coefficient in the container were 0.87 and 2.1, respectively, when fans were located in the top four corners of the container. Compared with before, the average temperature in the box was decreased by 0.12 °C, and the inhomogeneity coefficient decreased by more than twofold. The results of this paper provide a better understanding of temperature distribution in cold-storage containers, which helps to optimize their structure and parameters.

Unmanned Aerial Vehicle (UAV) aerial mapping technology is becoming more and more widely used for its specific advantages. But in some areas, where there is fog or haze, the visibility of images degrades severely. To solve this problem, we propose a formation model for UAV remote sensing hazed images by converting the dehazing problem into the computation of two global parameters, including airlight vector and transmission. Specifically, we first get the airlight vector by a statistical law of variation in local image brightness, but only use its precise magnitude; secondly, we estimate the accurate airlight orientation based on the geometric property of pixels (projected in RGB space) of the patches in which the transmission and surface reflectance are approximately constant. Thirdly, we calculate a mean transmission from the top 20% darkest pixels in the dark channel and use it as the global transmission. The dehazing experiments based on synthetic images show that our algorithm can get a more accurate airlight vector and global transmission. The experiments based on actual UAV images show that our algorithm has a good histogram shape preservation, which can effectively enhance the clarity of the hazed images. For UAV hazed remote sensing images of mapping, our algorithm can effectively improve the visual effect and enhance visibility.

In the most tracking approaches, a score function is utilized to determine which candidate is the optimal one by measuring the similarity between the candidate and the template. However, the representative samples selection in the template update is challenging. To address this problem, in this paper, we treat the template as a linear combination of representative samples and propose a novel approach to select representative samples based on the coefficient constrained model. We formulate the objective function into a non-negative least square problem and obtain the solution utilizing standard non-negative least square. The experimental results show that the observation module of our approach outperforms several other observation modules under the same feature and motion module, such as support vector machine, logistic regression, ridge regression and structured outputs support vector machine.

The effect of dissolved oxygen concentration (DO) on simultaneous nitrification and denitrification was studied in a moving bed sequencing batch reactor (MBSBR) by microelectrode measurements and by real-time PCR. In this system, the biofilm grew on polyurethane foam carriers used to treat municipal sewage at five DO concentrations (1.5, 2.5, 3.5, 4.5 and 5.5 mg/L). The results indicated that the MBSBR exhibited good removal of chemical oxygen demand (92.43%) and nitrogen (83.73%) when DO concentration was 2.5 mg/L. Increasing the oxygen concentration in the reactor was inhibitory to denitrification. Microelectrode measurements showed that the thickness of oxygen penetration increased from 1.2 to 2.6 mm when the DO concentration (from 1.5 mg/L to 5.5 mg/L) in the system increased. Oxygen diffusion was not significantly limited by the boundary layer surrounding the carrier and had the largest slope when DO concentration was 2.5 mg/L. The real-time PCR analysis indicated that the amount of the ammonia-oxidizing bacteria and nitrite-oxidizing bacteria increased slowly as DO concentration increased. The proportions of ammonia-oxidizing bacteria and nitrite-oxidizing bacteria, as a percentage of the total bacteria, were low with average values of 0.063% and 0.67%, respectively. When the DO concentration was 2.5 mg/L, oxygen diffusion was optimal and ensured the optimal bacterial community structure and activity; under these conditions, the MBSBR was efficient for total inorganic nitrogen removal. Changing the DO concentration could alter the aerobic zone and the bacterial community structure in the biofilm, directly influencing the simultaneous nitrification and denitrification activity in MBSBRs.

Anaerobic biological phosphorus removal has proposed a new direction for the removal of phosphorus from wastewater, and the discovery of phosphate reduction makes people have a more comprehensive understanding of microbial phosphorus cycling. Here, from the perspective of thermodynamics, the bioreduction reaction of phosphate was analyzed and its mechanism was discussed. The research progress of phosphate reduction and the application prospects of anaerobic biological phosphorus removal from wastewater were introduced, pointing out the situation and guiding the further research in this field.