In recent years, design high catalytic graphitic carbon nitride (g–C3N4)–based catalysts has drawn broad attention in environmental remediation. In this work, a series of iron-doped g-C3N4 compounds ...were synthesized through a simple bottom-up strategy. By controlled pyrolysis, iron-doped g-C3N4 materials split from bulk structure into multi-layer structure with uniformly dispersed mesopores. The catalytic activities of layered iron-doped g-C3N4 in Fenton-like and photo-Fenton-like processes were investigated. Due to the doped iron, unique layered structure, and mesopore feature, the catalysts present greatly enhanced performance in heterogeneous Fenton-like reactions. Moreover, the degradation parameters calculated by the pseudo-first-order kinetic model fitted well with the specific surface area of the catalyst, indicating that the catalytic activities rely heavily on the specific surface area of layered and porous g-C3N4. This study presents a facile and generic method to regulate C3N4 morphology and structure for enhanced catalytic activity in Fenton-like reactions.
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•A rigid–flexible coupling error model is established for robot non-kinematic calibration.•A simplified physical model (i.e. three lines) is formulated for interference detection.•A dual-index (i.e. ...an observability index and an identification accuracy index) is used as the evaluation target.•The full pose measurement optimization method employs the SAPSO algorithm used to obtain a set of optimal measurement poses with the optimum minimum number intelligently.•The modified identification algorithm takes into account the geometric and compliance error parameters.
This study addresses the non-negligible flexibility problem of industrial robots and describes a rigid–flexible coupling error model for robot non-kinematic calibration. Simulation confirms that compliance errors are major sources of inaccuracies and affect robot accuracy with geometric errors. To reduce the impact of measurement noise and improve calibration performance, an enhanced approach is proposed for full pose measurement and identification optimisation. This approach is based on the self-adaption particle swarm optimisation (SAPSO) algorithm with a dual-index (i.e. observability index O1 and identification accuracy index Omin) and a modified Levenberg–Marquardt algorithm, which considers external constraints (i.e. structural interference and angular limitation). Simulation results illustrate that the 36 error parameters of the proposed error model can be identified with improved accuracy and stability using the proposed approach. Finally, experimental results obtained with a Staubli TX60L robot with a FARO laser tracker are introduced to demonstrate the practical effectiveness of our approach in robot accuracy improvement.
The main object of this paper is to construct a new generalization of the Bernstein operator, depending on a non-negative real parameter. We investigate some elementary properties of this operator, ...such as end point interpolation, linearity and positivity, etc. By using these generating operators, we provide another proof of the Weierstrass Approximation Theorem. We give the detailed proofs to the rate of convergence and Voronovskaja type asymptotic estimate formula for the operators. Moreover, an upper bound for the error is obtained in terms of the usual modulus of continuity. Shape preserving properties of the generalized Bernstein operators are also studied. It is proved that monotonic or convex functions produce monotonic or convex generalized Bernstein polynomials.
Article Highlights
Recent advances of two-dimensional (2D) transition-metal dichalcogenide (TMDC)-based field-effect transistor (FET) sensors for environmental analysis are summarized.
Representative ...TMDC FET sensors in gaseous and aqueous media analysis are introduced.
Challenges and future research directions of 2D TMDC FET sensors are discussed.
Field-effect transistors (FETs) present highly sensitive, rapid, and in situ detection capability in chemical and biological analysis. Recently, two-dimensional (2D) transition-metal dichalcogenides (TMDCs) attract significant attention as FET channel due to their unique structures and outstanding properties. With the booming of studies on TMDC FETs, we aim to give a timely review on TMDC-based FET sensors for environmental analysis in different media. First, theoretical basics on TMDC and FET sensor are introduced. Then, recent advances of TMDC FET sensor for pollutant detection in gaseous and aqueous media are, respectively, discussed. At last, future perspectives and challenges in practical application and commercialization are given for TMDC FET sensors. This article provides an overview on TMDC sensors for a wide variety of analytes with an emphasize on the increasing demand of advanced sensing technologies in environmental analysis.
Sleep deprivation (SD) correlates with exacerbated systemic inflammation after sepsis. However, the underlying mechanisms remain unclear. This study aimed to evaluate the roles and mechanisms of SD ...in inflammatory organ injury after lipopolysaccharide (LPS) administration.
Mice were intraperitoneally injected with LPS followed by 3 consecutive days of SD. The pseudo germ-free (PGF) mice received fecal microbiota transplant by being gavaged with supernatant from fecal suspension of septic mice with or without SD. The subdiaphragmatic vagotomy (SDV) or splenectomy was performed 14 days prior to LPS injection or antibiotics administration.
Post-septic SD increased the plasma levels of interleukin (IL)-6 and tumor necrosis factor-α (TNF-α), reduced IL-10 plasma level, increased spleen weight, and promoted inflammatory injury of the lung, liver and kidney. The relative abundance of Proteobacteria and its subgroups were increased after post-septic SD. PGF mice transplanted with fecal bacteria from septic mice subjected to SD developed splenomegaly, systemic inflammation, organ inflammation and damage as their donors did. Intriguingly, SDV abolished the aggravated effects of SD on splenomegaly and inflammatory organ injury in septic mice received SD or in PGF mice transplanted with fecal bacteria from septic mice subjected to SD. Furthermore, splenectomy also abrogated the increase in IL-6 and TNF-α plasma levels and the decrease in IL-10 plasma level in PGF mice transplanted with fecal bacteria from septic mice subjected to SD.
Gut microbiota-vagus nerve axis and gut microbiota-spleen axis play key roles in modulating systemic inflammation induced by SD after LPS administration.
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Monolayer MoS2 (ML-MoS2) with various polymorphic phases attracts growing interests for device applications in recent years. Herein, a field-effect transistor (FET) gas sensor is developed on the ...basis of monolayer MoS2 with a heterophase of a 1T metallic phase and a 2H semiconducting phase. Lithium-exfoliated MoS2 nanosheets own a monolayer structure with rich active sites for gas adsorption. With thermal annealing from 50 to 300 °C, the initial lithium-exfoliated 1T-phase MoS2 gradually transforms into the 2H phase, during which the 1T and 2H heterophases can be modulated. The 1T/2H heterophase MoS2 shows p-type semiconducting properties and prominent adsorption capability for NO2 molecules. The highest response is observed for 100 °C annealed MoS2 of a 40% 1T phase and a 60% 2H phase, which shows a sensitivity up to 25% toward 2 ppm NO2 at room temperature in a very short time (10 s) and a lower limit of detection down to 25 ppb. This study demonstrates that the gas detection capability of ML-MoS2 could be boosted with the heterophase construction, which brings new insights into transition-metal dichalcogenide gas sensors.
BACKGROUND In this study, we aimed to investigate the association between UCA1 and miR-27b in gastric cancer and further study their involvement in multi-drug resistance (MDR) of gastric cancer. ...MATERIAL AND METHODS The microarray data of dysregulated lncRNAs in gastric cancer tissues was retrieved in the GEO dataset. QRT-PCR analysis was performed to assess UCA1 expression based on 28 paired cancerous and peritumoral normal tissues. The human gastric cancer cell line SGC-7901, and SGC-7901 derived Adriamycin (doxorubicin) resistant SGC-7901/ADR, cisplatin resistant SGC-7901/DDP, and 5-FU resistant SGC-7901/FU cells were used as in vitro cell models to assess the effect of UCA1 and miR-27b on MDR. RESULTS UCA1 was significantly upregulated in the cancerous tissues and its expression was negatively correlated with miR-27b expression level. Inhibition of UCA1 significantly restored miR-27b expression in MDR gastric cancer cells. UCA1 knockdown and miR-27b overexpression reduced IC50 of ADR, DDP, and 5-FU in SGC-7901/ADR cells and increased ADR induced cell apoptosis. UCA1 overexpression and miR-27b inhibition increased the IC50 of ADR, DDP, and 5-FU in SGC-7901 cells and reduced ADR induced cell apoptosis. Western blot analysis showed that UCA1 knockdown and miR-27b overexpression also decreased anti-apoptotic protein BCL-2 and increased apoptotic protein cleaved caspase-3. CONCLUSIONS UCA1 is negatively correlated with miR-27b expression in gastric cancer tissue. Knockdown of UCA1 restored miR-27b expression in gastric cancer cells. The UCA1-miR-27b axis was involved in regulation of chemosensitivity of gastric cancer cells.
Coronavirus 2019 (COVID-19) is a new acute respiratory disease that has spread rapidly throughout the world. This paper proposes a novel deep learning network based on ResNet-50 merged transformer ...named RMT-Net. On the backbone of ResNet-50, it uses Transformer to capture long-distance feature information, adopts convolutional neural networks and depth-wise convolution to obtain local features, reduce the computational cost and acceleration the detection process. The RMT-Net includes four stage blocks to realize the feature extraction of different receptive fields. In the first three stages, the global self-attention method is adopted to capture the important feature information and construct the relationship between tokens. In the fourth stage, the residual blocks are used to extract the details of feature. Finally, a global average pooling layer and a fully connected layer perform classification tasks. Training, verification and testing are carried out on self-built datasets. The RMT-Net model is compared with ResNet-50, VGGNet-16, i-CapsNet and MGMADS-3. The experimental results show that the RMT-Net model has a Test_ acc of 97.65% on the X-ray image dataset, 99.12% on the CT image dataset, which both higher than the other four models. The size of RMT-Net model is only 38.5 M, and the detection speed of X-ray image and CT image is 5.46 ms and 4.12 ms per image, respectively. It is proved that the model can detect and classify COVID-19 with higher accuracy and efficiency.
•1D Zn2SnO4–2D ZnO hybrid hierarchical structures were successfully synthesized.•ZTO–ZnO hybrid structures displayed superior gas-sensing performance toward TEA.•The sensing mechanism of the ZTO–ZnO ...hybrid structures has been proposed.
In this work, unique Zn2SnO4–ZnO hierarchical structures composed of one-dimensional Zn2SnO4 nanowires and two-dimensional ZnO nanosheets were successfully synthesized via a facile hydrothermal method combined with calcination. The Zn2SnO4 nanowires bridged across the ZnO nanosheets, which played an important role in electron transmission. Compared with pure Zn2SnO4 nanowires and pure ZnO nanosheets, the obtained Zn2SnO4–ZnO hierarchical structures exhibited improved gas-sensing performance toward triethylamine (TEA) in terms of a low operating temperature, high sensor response, and good selectivity. Gas-sensing test results revealed that the sensor response of Zn2SnO4–ZnO sensor reached 175.5 toward 100 ppm TEA at an optimum operating temperature of 200 °C, which is approximately 47.4 and 30.8 times higher than that of pure Zn2SnO4 and pure ZnO, respectively. In addition, the Zn2SnO4–ZnO hierarchical structures exhibited good selectivity and long-term stability to TEA, suggesting their potential application in advanced TEA gas sensors. The improved sensing properties of the Zn2SnO4–ZnO hierarchical structure could mainly be attributed to their large specific surface areas, unique bridged hierarchical microstructure, and appropriate energy band structure.
Antibiotic residue, as emerging pollution resulting from antibiotic abuse, poses a serious threat on ecosystem and human health. Conventional methods for antibiotic detection, e.g., liquid/gas ...chromatography, are based on complicated instruments and time-consuming; therefore, efforts have been made to realize in situ and real-time monitoring of antibiotics. Here, a miniaturized and integratable electronic antibiotic sensor based on field-effect transistor (FET) is reported. The reduced graphene oxide (rGO) nanosheet is used as the channel material and the aptamer RNA for tobramycin is modified onto rGO as the probe. A novel sensor design with 6-mercapto-1-hexanol (MCH)/1-pyrenebutanol (PBA) blocking layer (BL) for structure optimization is applied to enhance the sensor reliability and specificity. This rGO/aptamer/BL sensor shows an ultra-sensitivity to tobramycin with a lower detection limit of 0.3 nM and a quick response within 5 s, as well as a high specificity over other antibiotics such as kanamycin, streptomycin, ciprofloxacin, and tetracycline. The sensing mechanism based on the deformation of the charged aptamer probe is proposed via an in-depth analysis of the interactions between aptamer, tobramycin and rGO. In addition, sensing test performed under controlled microfluidic flow conditions demonstrates a great potential of the sensors in practical applications.
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•Real-time detection of tobramycin under controlled microfluidic flow conditions is achieved.•Aptamer RNA is modified on graphene as the sensing probe.•Highly sensitive and selective sensing of tobramycin is realized.•Blocking layers are applied for sensor structure optimization.
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