Edge enhancement in three-dimensional vortex imaging based on FINCH by Bessel-like spiral phase modulation.

Edge enhancement, as an important part of image processing, has played an essential role in amplitude-contrast and phase-contrast object imaging. The edge enhancement of three-dimensional (3D) vortex imaging has been successfully implemented by Fresnel incoherent correlation holography (FINCH), but the background noise and image contrast effects are still not satisfactory. To solve these issues, the edge enhancement of FINCH by employing Bessel-like spiral phase modulation is proposed and demonstrated. Compared with the conventional spiral phase modulated FINCH, the proposed technique can achieve high-quality edge enhancement 3D vortex imaging with lower background noise, higher contrast and resolution. The significantly improved imaging quality is mainly attributed to the effective sidelobes' suppression in the generated optical vortices with the Bessel-like modulation technique. Experimental results of the small circular aperture, resolution target, and the Drosophila melanogaster verify its excellent imaging performance. Moreover, we also proposed a new method for selective edge enhancement of 3D vortex imaging by breaking the symmetry of the spiral phase in the algorithmic model of isotropic edge enhancement. The reconstructed images of the circular aperture show that the proposed method is able to enhance the edges of the given objects selectively in any desired direction.

Three-dimensional ranging system based on Fresnel incoherent correlation holography.

We proposed a three-dimensional (3D) ranging system based on Fresnel incoherent correlation holography (FINCH). Distinct from the displacement measurement based on coherent digital holography (DH), our system simultaneously achieves a 3D range measurement using incoherent illumination. The observation range is obtained by the holographic reconstruction, while the in-plane range is determined using the two-dimensional digital imaging correlation (2D-DIC) technique. Experimental results on the resolution target demonstrate precise 3D ranging determination and improved measurement accuracy.

Progress on CRISPR/Cas9 system in the genetic improvement of livestock and poultry.

CRISPR/Cas9 gene editing technology, as a highly efficient genome editing method, has been extensively employed in the realm of animal husbandry for genetic improvement. With its remarkable efficiency and precision, this technology has revolutionized the field of animal husbandry. Currently, CRISPR/Cas9-based gene knockout, gene knock-in and gene modification techniques are widely employed to achieve precise enhancements in crucial production traits of livestock and poultry species. In this review, we summarize the operational principle and development history of CRISPR/Cas9 technology. Additionally, we highlight the research advancements utilizing this technology in muscle growth and development, fiber growth, milk quality composition, disease resistance breeding, and animal welfare within the livestock and poultry sectors. Our aim is to provide a more comprehensive understanding of the application of CRISPR/Cas9 technology in gene editing for livestock and poultry.

Simultaneously improving the quality factor and outcoupling efficiency of organic light-emitting field-effect transistors with planar microcavity.

Organic light-emitting field-effect transistors (OLEFETs) are regarded as an ideal device platform to achieve electrically pumped organic semiconductor lasers (OSLs). However, the incorporation of a high-quality resonator into OLEFETs is still challenging since the process usually induces irreparable deterioration to the electric-related emission performance of the device. We here propose a dual distributed Bragg reflector (DBR)-based planar microcavity, which is verified to be highly compatible with the OLEFETs. The dual DBR planar microcavity shows the great advantage of simultaneously promoting the quality (Q) factor and outcoupling efficiency of the device due to the reduced optical loss. As a result, a moderately high Q factor of ∼160, corresponding to EL spectrum linewidth as narrow as 3.2 nm, concomitantly with high outcoupling efficiency (∼7.1%) has been successfully obtained. Our results manifest that the dual DBR-based planar microcavity is a promising type of resonator, which might find potential applications in improving the spectra and efficiency performance of OLEFETs as well as in OLEFET-based electrically pumped OSLs.

Design of a Two-Dimensional Conveyor Platform with Cargo Pose Recognition and Adjustment Capabilities.

Linear conveyors, traditional tools for cargo transportation, have faced criticism due to their directional constraints, inability to adjust poses, and single-item conveyance, making them unsuitable for modern flexible logistics demands. This paper introduces a platform designed to convey and adjust cargo boxes according to their spatial positions and orientations. Additionally, a cargo pose recognition algorithm that integrates image and point cloud data are presented. By aligning depth camera data, the axis-aligned bounding box (AABB) point serves as the image's region of interest (ROI). Peaks extracted from the image's Hough transform are refined using RANSAC-based point cloud linear fitting, then integrated with the point cloud's oriented bounding box (OBB). Notably, the algorithm eliminates the need for deep learning and registration, enabling its use in rectangular cargo boxes of various sizes. A comparative experiment using accelerometer sensors for pose acquisition revealed a deviation of <0.7° between the two processes. Throughout the real-time adjustments controlled by the experimental platform, cargo angles consistently remained stable. The proposed two-dimensional conveyance platform, compared to existing methods, exhibits simplicity, accurate recognition, enhanced flexibility, and wide applicability.

A 3D Hand Attitude Estimation Method for Fixed Hand Posture Based on Dual-View RGB Images.

This work provides a 3D hand attitude estimation approach for fixed hand posture based on a CNN and LightGBM for dual-view RGB images to facilitate the application of hand posture teleoperation. First, using dual-view cameras and an IMU sensor, we provide a simple method for building 3D hand posture datasets. This method can quickly acquire dual-view 2D hand image sets and automatically append the appropriate three-axis attitude angle labels. Then, combining ensemble learning, which has strong regression fitting capabilities, with deep learning, which has excellent automatic feature extraction capabilities, we present an integrated hand attitude CNN regression model. This model uses a Bayesian optimization based LightGBM in the ensemble learning algorithm to produce 3D hand attitude regression and two CNNs to extract dual-view hand image features. Finally, a mapping from dual-view 2D images to 3D hand attitude angles is established using a training approach for feature integration, and a comparative experiment is run on the test set. The results of the experiments demonstrate that the suggested method may successfully solve the hand self-occlusion issue and accomplish 3D hand attitude estimation using only two normal RGB cameras.

Calibration of Ultrasonic Transducer Based on Ultrasonic Logging Instrument for Shaft Sinking.

High-precision logging equipment is critical for measuring the borehole diameter and drilling offset in coal mining and petroleum drilling. We propose a module composition and positioning principle for an ultrasonic transducer based on an ultrasonic logging instrument for shaft sinking by drilling (ULISSD) for calculating the reflection distance. The logging distance, which is the primary performance index of a logging system, is determined by using the self-reception sensitivity and error of the ultrasonic transducer in a downhole system. To measure the error between the piezoelectric element of the transducer and the rubber seal of the borehole logging system, we developed an ultrasonic-transducer error-calibration device and a calibration method for a central-air-return-shaft-drilling project. This calibration device can eliminate the inherent error of the transducer and calculate the rate of propagation with high accuracy. The measurement error is reduced by approximately 1.5 mm; thus, the ULISSD measurement accuracy can be effectively improved in central-air-return-shaft drilling.

Investigation of the effective aperture: towards high-resolution Fresnel incoherent correlation holography.

Fresnel incoherent correlation holography (FINCH) shows great advantages of coherent-light-source-free, high lateral resolution, no scanning, and easy integration, and has exhibited great potential in recording three-dimensional information of objects. Despite the rapid advances in the resolution of the FINCH system, little attention has been paid to the influence of the effective aperture of the system. Here, the effective aperture of the point spread function (PSF) has been investigated both theoretically and experimentally. It is found that the effective aperture is mainly restricted by the aperture of the charge-coupled device (CCD), the pixel size of the CCD, and the actual aperture of the PSF at different recording distances. It is also found that the optimal spatial resolution exists only for a small range of recording distance, while this range would become smaller as the imaging wavelength gets longer, leading to the result that the optimal spatial resolution is solely determined by the actual aperture of the PSF. By further combining the FINCH system with a microscopy system and optimizing the recording distance, a spatial resolution as high as 0.78 µm at the wavelength of 633 nm has been obtained, enabling a much higher quality imaging of unstained living biological cells compared to the commercial optical microscope. The results of this work may provide some helpful insights into the design of high-resolution FINCH systems and pave the way for their application in biomedical imaging.

Special Characteristics and Synchronizations of Multi Hybrid-Order Chaotic Systems.

Based on advantages of integer and fractional chaotic systems, hybrid chaotic systems and their definitions and some fundamental concepts are proposed, such as hybrid degree (HD), the lowest order (LO) and the total dimension order (TDO). The preliminary properties of hybrid Lorenz systems and hybrid forms of some classic chaotic systems are studied. Then, the relations between HD, LO and TDO with different parameters is investigated in chaotic systems. To be specific, HD is associated with fractional order. It is a directional method to search LO and TDO in chaotic systems. Finally, based on the incommensurate fractional stability theory, we accomplish combination synchronization for three different hybrid order chaotic systems. The simulation results verify the effectiveness of the synchronization controller.

An Improved Normalized Mutual Information Variable Selection Algorithm for Neural Network-Based Soft Sensors.

In this paper, normalized mutual information feature selection (NMIFS) and tabu search (TS) are integrated to develop a new variable selection algorithm for soft sensors. NMIFS is applied to select influential variables contributing to the output variable and avoids selecting redundant variables by calculating mutual information (MI). A TS based strategy is designed to prevent NMIFS from falling into a local optimal solution. The proposed algorithm performs the variable selection by combining the entropy information and MI and validating error information of artificial neural networks (ANNs); therefore, it has advantages over previous MI-based variable selection algorithms. Several simulation datasets with different scales, correlations and noise parameters are implemented to demonstrate the performance of the proposed algorithm. A set of actual production data from a power plant is also used to check the performance of these algorithms. The experiments showed that the developed variable selection algorithm presents better model accuracy with fewer selected variables, compared with other state-of-the-art methods. The application of this algorithm to soft sensors can achieve reliable results.

A Gas Leakage Localization Method Based on a Virtual Ultrasonic Sensor Array.

In traditional sensory array-based acoustic emission methods that are used for gas leakage localization, the localization resolution depends on the spatial aperture of the array, that is, the number of sensors. Most of the existing methods use small arrays that can only achieve low-resolution localization results because of limitations such as the amplitude and phase consistency, the complexity and cost of the system. This paper reports the first application of a virtual phased array for gas leakage detection to obtain high-resolution localization results. This method uses a virtual linear ultrasonic sensor array composed of only two sensors to acquire leakage signals. Then, we use the virtual beamforming algorithm based on the cross-power spectrum to estimate the location of the leakage source. Several experiments were conducted to evaluate the effectiveness and operability of the proposed method. The impacts of various factors on the performance of the localization technique are compared and discussed, including factors such as the number of sensors and the distance between the leak hole and virtual array. The results demonstrate that the proposed method accurately and reliably localizes gas leakages.

Factors influencing the quality of preconception healthcare in China: applying a preconceptional instrument to assess healthcare needs.

BACKGROUND: Preconception care is defined as the promotion of the health and well-being of a woman and her partner before pregnancy. Improving preconception health can result in improved reproductive health outcomes. China has issued latest version official guideline for preconception care in 2011. The objective of this cross-sectional study is to determine whether there is a variation in the quality of preconception healthcare services in distinct eastern and northern populations of China, and what factors are associated with such variation. METHODS: A cross-sectional survey using our previously developed preconception instrument was conducted. Women at reproductive age planning for pregnancy were surveyed along with their partners at hospitals during their pre-pregnancy health examination. Data collected include general health/life profiles, pregnancy history, alcohol/tobacco/drug exposures, immunizations, micronutrient supplements and the demands in preconception care. After quality assessment, statistical analysis were applied to evaluate the variations in preconception factors between people from Hebei and Jiangsu Provinces. RESULTS: 3202 women of reproductive age in from eastern province, Jiangsu, and in a northern province, Hebei, participated this study. 2806 of them and their partners have completed the questionnaire, at a rate of 87.6%, 1011 were from Jiangsu and 1795 were from Hebei. Statistical significance was obtained for maternal age (P < 0.001), body mass index (u =13.590, P <0.001), education (χ2 = 916.33, P < 0.001), occupation (χ2 = 901.78, P < 0.001), health status/common disease, immunization status, and need for preconception care. CONCLUSIONS: For a country as large as China, the centralized guideline for standardized preconception healthcare does have a very crucial positive role in reproductive healthcare, but it may not be suited for all populations. Regional authorities should consider the demographics and healthcare needs of the local population and modify the centralized guideline accordingly, as well as provide a better education and professional services for the public, to improve the quality of preconception services at both the regional and the national level.

Development and application of a 1K functional liquid chip for lactation performance in Bactrian camels.

Introduction: The advancement of high-throughput, high-quality, flexible, and cost-effective genotyping platforms is crucial for the progress of dairy breeding in Bactrian camels. This study focuses on developing and evaluating a 1K functional liquid single nucleotide polymorphism (SNP) array specifically designed for milk performance in Bactrian camels. Methods: We utilized RNA sequencing data from 125 lactating camels to identify and select 1,002 loci associated with milk production traits for inclusion in the SNP array. The array's performance was then assessed using 24 randomly selected camels. Additionally, the array was employed to genotype 398 individuals, which allowed for population validation to assess the polymorphism of SNP sites. Results: The SNP array demonstrated high overall SNP call rates (> 99%) and a remarkable 100% consistency in genotyping. Population validation results indicate that camels from six breeding areas in Northwest China share a similar genetic background regarding lactation functionality. Discussion: This study highlights the potential of the SNP array to accelerate the breeding process of lactating Bactrian camels and provides a robust technical foundation for improving lactation performance.

Massively Parallel CRISPR-Cas9 Knockout Screening in Sheep Granulosa Cells for FSH Response Genes.

Follicle-stimulating hormone (FSH) regulates ovarian follicle development through specific gene expression programs. Granulosa cells (GCs) are somatic cells surrounding the oocytes, secreting gonadotropins to regulate ovulation and promote follicular development. By analyzing the effects of different doses of FSH on the proliferation of GCs, we found that adding 10 ng/mL of FSH, as the optimal concentration, could promote the growth of GCs. Furthermore, we have successfully constructed the first CRISPR-Cas9 knockout library targeting the genes on chromosomes 2 and 3 and the X chromosomes of the sheep massively parallel coding gene, as well as an ovarian GCs knockout cell library. For the first time, we have exposed the knockout cell library to a concentration of 10 ng/mL FSH to explore the underlying mechanisms. Through this screening, we have identified 836 positive-negative screening genes that are responsive to FSH, thereby revealing the regulatory mechanisms and screening the functionality of candidate genes. Next, RNA-Seq of control (0 ng/mL), low (10 ng/mL), and high (100 ng/mL) doses of FSH revealed 1708 differentially expressed genes, and combined with 836 genes, we obtained 129 FSH dose-dependent genes with extremely significant differences. This enables us to delve deeper into investigating and identifying the mechanisms by which FSH regulates GCs. More generally, we have discovered new regulatory factors and identified reproductivity-associated major effectors. These findings provide novel research directions for further studies on sheep reproduction.

Corrigendum: Improved real-time semantic segmentation network model for crop vision navigation line detection.

[This corrects the article DOI: 10.3389/fpls.2022.898131.].

Non-fragile guaranteed cost control of microbial fuel cells.

A microbial fuel cell (MFC), which is a new type of energy source, utilises electrogenic bacteria in sewage or soil to convert chemical energy into electrical energy. MFCs typically require an external controller to provide a stable output voltage to the external load. This study develops a non-fragile guaranteed cost (NFGC) controller to suppress the interference of the controller of an MFC and ensure that the quadratic cost function of the system satisfies certain performance indexes. First, for the convenience of controller design, a Takagi-Sugeno fuzzy model is established to approximate a single-chamber single-population MFC model. Subsequently, the linear matrix inequality method is used to design the NFGC controller. This control scheme can reduce the influence of controller disturbances on the system and ensure asymptotic stability of the closed-loop system under the specified upper bound of the provided cost function. The simulation results demonstrate that the developed control method has a shorter adjustment time and smaller steady-state error than traditional control methods such as sliding mode control (SMC), backstepping control, and fuzzy SMC.

Candidate Genes and Gene Networks Change with Age in Japanese Black Cattle by Blood Transcriptome Analysis.

Age is an important physiological factor that affects the metabolism and immune function of beef cattle. While there have been many studies using the blood transcriptome to study the effects of age on gene expression, few have been reported on beef cattle. To this end, we used the blood transcriptomes of Japanese black cattle at different ages as the study subjects and screened 1055, 345, and 1058 differential expressed genes (DEGs) in the calf vs. adult, adult vs. old, and calf vs. old comparison groups, respectively. The weighted co-expression network consisted of 1731 genes. Finally, blue, brown, and yellow age-specific modules were obtained, in which genes were enriched in signaling pathways related to growth and development and immune metabolic dysfunction, respectively. Protein-protein interaction (PPI) analysis showed gene interactions in each specific module, and 20 of the highest connectivity genes were chosen as potential hub genes. Finally, we identified 495, 244, and 1007 genes by exon-wide selection signature (EWSS) analysis of different comparison groups. Combining the results of hub genes, we found that VWF, PARVB, PRKCA, and TGFB1I1 could be used as candidate genes for growth and development stages of beef cattle. CORO2B and SDK1 could be used as candidate marker genes associated with aging. In conclusion, by comparing the blood transcriptome of calves, adult cattle, and old cattle, the candidate genes related to immunity and metabolism affected by age were identified, and the gene co-expression network of different age stages was constructed. It provides a data basis for exploring the growth, development, and aging of beef cattle.

Efficient sky-blue cesium lead bromide light-emitting diodes with enhanced stability via synergistic interfacial induction and polymer scaffold inhibition.

All inorganic CsPbX3 perovskite has aroused broad interests in building efficient light-emitting devices with wide color gamut and flexible fabrication process. So far, the realization of high-performance blue perovskite light-emitting devices (PeLEDs) is still a critical challenge. Herein, we propose an interfacial induction strategy to generate low-dimensional CsPbBr3 with sky blue emission by employing γ-aminobutyric acid (GABA) modified poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). The interaction between GABA and Pb2+ inhibited the formation of bulk CsPbBr3 phase. Further assisted by the polymer networks, the sky-blue CsPbBr3 film exhibited much improved stability under both photoluminescence and electrical excitation. This can be ascribed to the scaffold effect and the passivation function of the polymer. Consequently, the obtained sky-blue PeLEDs exhibited an average external quantum efficiency (EQE) of 5.67% (maximum of 7.21%) with a maximum brightness of 3308 cd/m2 and a working lifespan reaching 0.41 h. The strategy in this work provides a new opportunity for exploitation the full potential of blue PeLEDs towards application in lighting and display devices.

[Study on the optical properties of ultra-thin metal films in the THz band].

Thin metal films are good candidates of terahertz detectors, reflectors, waveguides and terahertz quantum-cascade lasers (THz-QCLs). The optical parameter is the basis not only for designing the THz components but also for developing novel optoelectronic materials. In the present paper, the complex refractive indices of the ultra-thin metal (Cr, Ni and Ti) films in the THz band were obtained by the THz differential time-domain spectroscopy. The reflection spectra of the GaAs/metals interface were calculated according to the Fresnel formula. The mean reflectance of 25 nm Cr, Ni and Ti are over 80% from 0.3 to 1.5 THz. The results show that ultra-thin metal films can be used for reflectors as well as the electrodes in the THz band.

Improved Real-Time Semantic Segmentation Network Model for Crop Vision Navigation Line Detection.

Field crops are generally planted in rows to improve planting efficiency and facilitate field management. Therefore, automatic detection of crop planting rows is of great significance for achieving autonomous navigation and precise spraying in intelligent agricultural machinery and is an important part of smart agricultural management. To study the visual navigation line extraction technology of unmanned aerial vehicles (UAVs) in farmland environments and realize real-time precise farmland UAV operations, we propose an improved ENet semantic segmentation network model to perform row segmentation of farmland images. Considering the lightweight and low complexity requirements of the network for crop row detection, the traditional network is compressed and replaced by convolution. Based on the residual network, we designed a network structure of the shunting process, in which low-dimensional boundary information in the feature extraction process is passed backward using the residual stream, allowing efficient extraction of low-dimensional information and significantly improving the accuracy of boundary locations and row-to-row segmentation of farmland crops. According to the characteristics of the segmented image, an improved random sampling consensus algorithm is proposed to extract the navigation line, define a new model-scoring index, find the best point set, and use the least-squares method to fit the navigation line. The experimental results showed that the proposed algorithm allows accurate and efficient extraction of farmland navigation lines, and it has the technical advantages of strong robustness and high applicability. The algorithm can provide technical support for the subsequent quasi-flight of agricultural UAVs in farmland operations.