Homozygous mutation in DNALI1 leads to asthenoteratozoospermia by affecting the inner dynein arms

Asthenozoospermia is the most common cause of male infertility. Dynein protein arms play a crucial role in the motility of sperm flagella and defects in these proteins generally impair the axoneme structure and affect sperm flagella function. In this study, we performed whole exome sequencing for a cohort of 126 infertile patients with asthenozoospermia and identified homozygous DNALI1 mutation in one patient from a consanguineous family. This identified homozygous mutation was verified by Sanger sequencing. In silico analysis showed that this homozygous mutation is very rare, highly pathogenic, and very conserved. Sperm routine analysis confirmed that the motility of the spermatozoa from the patient significantly decreased. Further sperm morphology analysis showed that the spermatozoa from the patient exhibited multiple flagella morphological defects and a specific loss in the inner dynein arms. Fortunately, the patient was able to have his child via intracytoplasmic sperm injection treatment. Our study is the first to demonstrate that homozygous DNALI1 mutation may impair the integration of axoneme structure, affect sperm motility and cause asthenoteratozoospermia in human beings

Do teashirt family genes specify trunk identity? Insights from the single tiptop/teashirt homolog of Tribolium castaneum

The Drosophila teashirt gene acts in concert with the homeotic selector (Hox) genes to specify trunk (thorax and abdomen) identity. There has been speculation that this trunk-specifying function might be very ancient, dating back to the common ancestor of insects and vertebrates. However, other evidence suggests that the role of teashirt in trunk identity is not well conserved even within the Insecta. To address this issue, we have analyzed the function of Tc-tiotsh, the lone teashirt family member in the red flour beetle, Tribolium castaneum. Although Tc-tiotsh is important for aspects of both embryonic and imaginal development including some trunk features, we find no evidence that it acts as a trunk identity gene. We discuss this finding in the context of recent insights into the evolution and function of the Drosophila teashirt family genes

Measuring the Conditional Luminosity and Stellar Mass Functions of Galaxies by Combining the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 Data

In this investigation, we leverage the combination of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 data sets to estimate the conditional luminosity functions and conditional stellar mass functions (CLFs and CSMFs) of galaxies across various halo mass bins and redshift ranges. To support our analysis, we utilize a realistic DESI mock galaxy redshift survey (MGRS) generated from a high-resolution Jiutian simulation. An extended halo-based group finder is applied to both MGRS catalogs and DESI observation. By comparing the r- and z-band luminosity functions (LFs) and stellar mass functions (SMFs) derived using both photometric and spectroscopic data, we quantified the impact of photometric redshift (photo-z) errors on the galaxy LFs and SMFs, especially in the low-redshift bin at the low-luminosity/mass end. By conducting prior evaluations of the group finder using MGRS, we successfully obtain a set of CLF and CSMF measurements from observational data. We find that at low redshift, the faint-end slopes of CLFs and CSMFs below ∼109 h −2 L ⊙ (or h −2 M ⊙) evince a compelling concordance with the subhalo mass functions. After correcting the cosmic variance effect of our local Universe following Chen et al., the faint-end slopes of the LFs/SMFs turn out to also be in good agreement with the slope of the halo mass function

A Novel Method of Aircraft Detection Based on High-Resolution Panchromatic Optical Remote Sensing Images

In target detection of optical remote sensing images, two main obstacles for aircraft target detection are how to extract the candidates in complex gray-scale-multi background and how to confirm the targets in case the target shapes are deformed, irregular or asymmetric, such as that caused by natural conditions (low signal-to-noise ratio, illumination condition or swaying photographing) and occlusion by surrounding objects (boarding bridge, equipment). To solve these issues, an improved active contours algorithm, namely region-scalable fitting energy based threshold (TRSF), and a corner-convex hull based segmentation algorithm (CCHS) are proposed in this paper. Firstly, the maximal variance between-cluster algorithm (Otsu’s algorithm) and region-scalable fitting energy (RSF) algorithm are combined to solve the difficulty of targets extraction in complex and gray-scale-multi backgrounds. Secondly, based on inherent shapes and prominent corners, aircrafts are divided into five fragments by utilizing convex hulls and Harris corner points. Furthermore, a series of new structure features, which describe the proportion of targets part in the fragment to the whole fragment and the proportion of fragment to the whole hull, are identified to judge whether the targets are true or not. Experimental results show that TRSF algorithm could improve extraction accuracy in complex background, and that it is faster than some traditional active contours algorithms. The CCHS is effective to suppress the detection difficulties caused by the irregular shape

Dynamic and static performance optimization of dual active bridge DC-DC converters

Abstract High efficiency and fast dynamic response are two main control objectives for dual active bridge (DAB) DC-DC converters. Traditional extended phase shift (EPS) control can significantly enhance the conversion efficiency of DAB DC-DC converters by reducing current stress; however, it cannot fulfill fast dynamic response requirements. In this paper, a novel hybrid control scheme consisting of EPS control and direct power control (DPC), named as EPS-DPC, is proposed. EPS-DPC control has salient features in both efficiency and dynamic performance. In order to verify the outstanding performance of the proposed EPS-DPC scheme, an experimental comparison was carried out on a scale-down DAB DC-DC converter among several control strategies, including single phase shift control with traditional voltage-loop (SPS-TVL), EPS control with traditional voltage-loop (EPS-VTL), and EPS-DPC. Experimental results have been high consistent with theoretical analysis, and verified these advantages of the proposed EPS-DPC scheme

A Method of Ship Detection under Complex Background

The detection of ships in optical remote sensing images with clouds, waves, and other complex interferences is a challenging task with broad applications. Two main obstacles for ship target detection are how to extract candidates in a complex background, and how to confirm targets in the event that targets are similar to false alarms. In this paper, we propose an algorithm based on extended wavelet transform and phase saliency map (PSMEWT) to solve these issues. First, multi-spectral data fusion was utilized to separate the sea and land areas, and the morphological method was used to remove isolated holes. Second, extended wavelet transform (EWT) and phase saliency map were combined to solve the problem of extracting regions of interest (ROIs) from a complex background. The sea area was passed through the low-pass and high-pass filter to obtain three transformed coefficients, and the adjacent high frequency sub-bands were multiplied for the final result of the EWT. The visual phase saliency map of the product was built, and locations of ROIs were obtained by dynamic threshold segmentation. Contours of the ROIs were extracted by texture segmentation. Morphological, geometric, and 10-dimensional texture features of ROIs were extracted for target confirmation. Support vector machine (SVM) was used to judge whether targets were true. Experiments showed that our algorithm was insensitive to complex sea interferences and very robust compared with other state-of-the-art methods, and the recall rate of our algorithm was better than 90%

Research and design of image style transfer technology based on multi‐scale convolutional neural network feature fusion

Abstract To reduce the occurrence of information loss and distortion in image style transfer, a method is proposed for researching and designing image style transfer technology based on multi‐scale convolutional neural networks (CNNs) feature fusion. Initially, the VGG19 model is designed for coarse and fine‐scale networks to achieve multi‐scale CNN feature extraction of target image information. Subsequently, while setting the corresponding feature loss function, an additional least‐squares penalty parameter is introduced to balance the optimal total loss function. Finally, leveraging the characteristics of stochastic gradient descent iteration, image features are fused and reconstructed to obtain better style transfer images. Experimental evaluations utilize peak signal‐to‐noise ratio (PSNR), structural similarity index (SSIM), information entropy (IE), and mean squared error (MSE) as metrics for assessing the transferred images, comparing them with three typical image style transfer methods. Results demonstrate that the proposed method achieves optimal performance across all metrics, realizing superior image style transfer effects