Search

With the continuous expansion of the scale of the power grid and the gradual maturity of the application of drones, drones with the advantages of flexibility and convenience can overcome terrain constraints while reducing manpower and safety risks and can be well qualified for the power inspection work under the large-scale development of the power grid and improve the inspection efficiency. However, the massive amount of data collected by UAV power line inspection relies on the human judgment through the naked eyes of staff, and the recognition efficiency is very low and the accuracy rate is subjectively influenced. In recent years, the gradual introduction of traditional machine learning and deep learning has led to significant improvements in inspection efficiency and accuracy. The autonomous obstacle avoidance technology based on the inherent electromagnetic field characteristics of power lines makes it possible for UAVs to cruise autonomously. Based on a systematic summary of the achieved results, this paper briefly reviews the overall development of both power component detection and autonomous cruise in UAV power line inspection. At the same time, the current problems and future research trends are described, expecting to provide references for further research in this field.

Background Cervical cancer caused by human papillomavirus (HPV) infections is one of the most common cancers affecting women worldwide. Current preventative HPV vaccines on the market are composed of HPV L1 protein produced either in the yeast such as Gardasil or in the insect cells such as Cervarix. The duration of efficacy and cross-protection remain highly desirable for the improvement of current prophylactic HPV vaccine. Given that HPV carries out infection and replicates in mammalian cells, L2 protein, which is not included in the current licensed vaccines, is included in the third generation of HPV vaccine in pursuing of providing broader prevention. We hypothesize that a virus-like particle (VLP) consisting of HPV L1 plus L2 proteins generated in mammalian cells will present conformations more closely to native HPV, thus it will provide more durable and broader efficacy of prevention. Methods We took advantage of 293TT cells to produce VLP containing L1 and L2 proteins of HPV16 and HPV18, respectively. Results VLP particles of uniformed size and morphology were observed, and potent and broadly neutralizing antibodies were induced in mice and rabbits. In addition, compared to bivalent HPV vaccine of Cervarix, our HPV L1-L2 VLPs elicited higher titer of anti-sera, and the anti-sera also presented comparable neutralization potency against HPV16 and HPV18 infections even a much less potent adjuvant was used in our case. Conclusion Our VLPs were capable of eliciting stronger and more broadly neutralizing activities against various HPV subtypes and were potential candidate HPV vaccines.

MicroRNAs (miRNAs) diagnostics can be useful for diagnosing or confirming miRNA abundance and are used in screening tests and to assess changes in miRNAs in vivo. At present, the use of traditional nucleic acid amplification assays to detect miRNAs has been limited in laboratory environment because of the time, equipment, and technical expertise required to perform these assays. A specialized, rapid affordable miRNA detection system is necessary when there are limited resources or point-of-care testing needs. We designed a portable and affordable fluorescence-based miRNA detection system based on isothermal signal amplification technology, using SYBR Green II as a fluorescent dye. To reduce costs, we chose LED as a light source and designed the corresponding optical path for LED. The portable detection system shows results consistent with those by real-time PCR, and can be used to detect miR-183 with a limit of detection of approximately 2 fmol. We used the system to detect miR-183 in tissues and blood from patients with hepatocellular carcinoma (HCC). The results from the portable detection device were compared with those from clinical trials and indicated that the miR-183 fluorescence signal could successfully identify HCC and provide information related to cancer progression.

Chimeric antigen receptor (CAR) T-cell therapy is the most active field in immuno-oncology and brings substantial benefit to patients with B cell malignancies. However, the complex procedure for CAR T-cell generation hampers its widespread applications. Here, we describe a novel approach in which human CAR T cells can be generated within the host upon injecting an Adeno-associated virus (AAV) vector carrying the CAR gene, which we call AAV delivering CAR gene therapy (ACG). Upon single infusion into a humanized NOD.Cg-Prkdcscid Il2rgem26/Nju tumor mouse model of human T-cell leukemia, AAV generates sufficient numbers of potent in vivo CAR cells, resulting in tumor regression; these in vivo-generated CAR cells produce antitumor immunological characteristics. This instantaneous generation of in vivo CAR T cells may bypass the need for patient lymphodepletion, as well as the β processes of traditional CAR T-cell production, which may make CAR therapy simpler and less expensive. It may allow the development of intricate, individualized treatments in the form of on-demand and diverse therapies.

Rheological property is an important physical index of viscoelastic body. Meat, as a complex viscoelastic body, has certain rheological properties. However, important rheological parameters such as modulus of elasticity and coefficient of viscosity, have never been calculated easily. In this study a meat viscoelasticity detection system was applied to obtain deformation curves for extracting characteristic parameters related to rheological behavior. Then on the basis of the typical characteristics of deformation curves, 6 characteristic parameters were successfully extracted from the deformation curves to characterize rheological property of beef. These characteristic parameters were named maximum impact deformation, recovery deformation, instantaneous impact deformation, instantaneous recovery deformation, impact deformation area and recovery deformation area, respectively. In order to prove the usefulness of these characteristic parameters, the freshness of beef evaluated by TVB-N content was attempted to correlate with them. Common modeling methods including Multiple linear regression (MLR), principal component regression (PCR) and partial least squares regression (PLSR) were attempted to verify that these new parameters may be related to freshness. The PCR method performed the best and obtained the relevance with correlation coefficient in calibration dataset (Rc) of 0.725, root mean squared error in the calibration datasets (RMSEC) of 1.808 mg/100 g. The predicted result was correlation coefficient in verification dataset (Rv) of 0.686 and root mean squared error in the verification dataset (RMSEV) of 1.999 mg/100 g. The results of this study demonstrated that these extracted characteristic parameters could describe rheological properties and could be applied for meat freshness evaluation by modeling analysis.

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a novel tick-borne bunyavirus that recently emerged in East Asian countries. SFTS is characterized by high fever, thrombocytopenia, leukopenia, multiorgan failure, and hemorrhage with case fatality rates of 6.3% to 30%. Neither antivirals nor vaccines are available at present. We previously demonstrated that neutralizing antibodies specific for SFTSV glycoprotein (Gn) played a vital role in the survival of patients with SFTS. Nanobodies from camels present unique properties, such as thermostability, high affinity, and low immunogenicity. In the current study, mammalian expressed SFTSV Gn was used to immunize a camel, and functional nanobodies were isolated from the B cell nanobody library constructed from the immunized animal. Clone SNB02 was selected for in-depth analysis for its inhibition of SFTSV replication both in vitro and in vivo. We showed that SNB02 potently inhibited SFTSV infection and prevented thrombocytopenia in a humanized mouse model and is a potential candidate for therapeutics.

Surface cleaning has always been an important procedure to improve quality and performance of final components in modern industrial manufacturing. Among various surface cleanings, laser cleaning has been identified as the most promising green cleaning technology to replace conventional mechanical and chemical cleaning. Laser cleaning is a green cleaning technology that will not result in environmental pollution. And, laser cleaning is a versatile, precise, and controllable technology. A set of laser cleaning system that consists of line structured light and industrial manipulator, was designed in this paper. The line structured light, combined with camera, was used to scan workpiece surface and reconstruct the 3D model of workpiece surface. The industrial manipulator was utilized to perform scanning and cleaning movements. This new system is called Laser Cleaning Robot (LCR). To improve automation level and cleaning efficiency of the LCR, a path generation method based on line structured light and industrial manipulator was proposed in this paper. Experimental results demonstrate the performance of the proposed method in terms of cleaning efficiency for large-scale workpiece.

Oligonucleotides were screened for strongly silver-stained repetitive sequences. An 'AG'-clustered purine sequence showed strong staining, and the staining density can be compromised by disrupting the continuity of the 'AG'-clustered sequence. The staining-favored sequence was then employed in rolling circle amplification (RCA) for its product detection. A tube-staining method was developed for convenient and visual RCA assay. Moreover, by introducing GalR into RCA, d-galactose was detected by RCA tube-staining with naked eyes without any equipment. About 10 mM d-galactose can be easily identified, and the detection of d-galactose was specific in comparison with that of several other monosaccharides.

Designed with electron-donating and electron-withdrawing moieties as donors and acceptors, respectively, a series of novel organic dyes for dye-sensitized solar cells (DSCs) are simulated using density functional theory (DFT) and time-dependent DFT (TD-DFT) methods The interacting dye/TiO 2 systems are also studied to further explore the interfacial injection process of photo-excited electron. The model dye C275 is featured with donor/acceptor (D/A) molecular architecture, which is primary to achieve the easy charge-transfer excitation and suitable energy levels alignment. To date, considerable efforts are devoted to the design and synthesis of D/A type organic dyes, and the initial configurations are typically comprised of N-annulated perylene donor, porphyrin linker, and carboxylic acid acceptor. Our results show that, the electronic levels and optical absorption properties can be tuned gradually by introducing auxiliary donor units or electron-deficient spacer in acceptor groups. Moreover, the designed dyes also exhibit good performance in terms of photoinduced charge transfer, electron injection, and dye regeneration, etc . Through structural modification of donor moieties, the new tailored dyes provide appropriate energy levels, strong light-harvesting and easy charge separation. Meanwhile, the distinct red-shift of optical absorption and large amount of transferred charges are also obtained by structural tailoring of acceptor groups, whereas the large values of injection time may be harmful for the interfacial photoelectron injection. Therefore, comparing with donor modification, it should be more carefully to choose appropriate acceptor group with the balance of various energetic and kinetic factors for the rational design of high-efficient organic dyes.

A new megastigmane glycoside, named koniside (1), with five known compounds (2–6) was isolated from the pericarp of Euscaphis konishii. The structure of the new compound was determined by the HR-ESI-MS, IR, 1D, and 2D NMR spectra. Compounds 1 and 5 inhibited NO production of RAW264.7 and show moderate activities.

The Coherent Change Detection (CCD) measures the phase difference in repeat passes in SAR images and is a powerful technique for detecting minute changes between two synthetic aperture radar images taken at different times. Nevertheless, the CCD has two problems. These are the high false-alarm rates and threshold selection. To deal with these problems using the likelihood change, this study makes two improvements. First, the model parameters are optimized by the maximum likelihood method and more accurate and robust parameters are obtained by using the sliding window in the neighborhood operations. Second, the automatic change in the threshold method is proposed based on the histogram characteristics of different data. The processing of real data suggests that the proposed method is effective in detecting minute changes.

Chimeric antigen receptor (CAR) therapy has achieved remarkable clinical efficacy against hematological cancers and got FDA approval for B cells tumor. However, the complex manufacturing process and limited success in solids tumors hamper its widespread applications and provoke new strategies to overcome above-mentioned hurdles. In last decade, nanotech provides sustainable strategies to improve cancer immunotherapy for vaccine development, and in delivery of immunomodulatory drugs. Nanotech can boost the CAR-T therapy and may overcome the existing challenges by emerging as a carrier for CAR therapy, or in a joint venture it may defeat the solid tumor more effectively than the conventional approaches. However, the unraveling of cellular mechanisms, barriers, and the potential strategies that could be used to manipulate and/or educate cells would enable unprecedented advances in nanotech for biologics delivery. This review outlines the journey and barriers of nanoparticles (NPs) across the cell. Afterward, the approaches to tackle those barriers and strategies to modulate NPs as a carrier for CAR therapy are discussed. Finally, the role of NPs in CAR-T therapy and the potential challenges are summarized. The main purpose of this review is to provide the readers with a detailed overview of NPs based CAR-T therapy research, and distill this information into an accessible form conducive to design desired CAR therapy by NPs approach.

The gain of the avalanche photodiode (APD) is temperature sensitive, which greatly limits the application of APD for the all-weather operation in field. In this paper, a dual temperature compensation circuit for APD that included temperature control and high voltage compensation was designed. The temperature control part uses MAX1978 for APD proportional-integral-derivative (PID) temperature control through thermistor and thermo electric cooler (TEC), so that APD temperature is kept constant in a certain ambient temperature range. According to general diode‘s temperature characteristics, the high voltage compensation part compensates for the high voltage drift needed to stabilize the gain of the APD when ambient temperature changes, using diode 1N914. This further improves the gain stability of the APD. The dual temperature compensation circuit improves the stability of the APD gain, expands the range of APD's ambient temperature and reduces the thermal noise.

Chromatic confocal point sensors are used to measure the high-precision surface distance, and it’s based on the theory of chromatic dispersion and encodes the distance between the measure surface and chromatic lens. By accurately measuring the wavelength value, it indirectly calculates the distance to object surface. The accuracy of the sensor depends on the chromatic range of the lens and the resolution of the spectrograph. In this paper, the algorithm of spectral peak positioning can effectively filter kinds of noise, such as spectrometer and light source. The spectral data signal peak is extracted by Gaussian fitting method. In practice, the wavelength position can be stably detected effectively.

In order to meet the needs of production, this paper studies the detection data processing algorithm for the angle of the piston shape and position, the groove width and the runout of the groove bottom. An adaptive data fusion method based on Kalman filtering is proposed. This algorithm can use the adaptive method to calculate the different weight coefficients of each data point according to the standardized sampling data and the smoothed data points obtained by the cubic B-spline approximate fitting algorithm. This paper obtain the fusion data; then calculate the groove angle, groove width and groove bottom runout of the piston according to the conversion formula. Finally, experimental data verification is carried out, which shows the effectiveness and good robustness of the data processing of this algorithm. At the same time, a piston shape and position detection system was developed. The system rotates a circle at 90 degrees per second to obtain the measurement data. After the system software and hardware processing, the groove angle detection accuracy can reach ±2 minutes, the groove width and the groove bottom. The detection accuracy of the runout amount is within ±2 microns, and the measurement items in the measurement time and accuracy side meet the customer’s technical document requirements and achieve satisfactory results.