Miracle-dz/UniFAR-FTUs huggingface dataset:
Pak1ip1 Loss-of-Function Leads to Cell Cycle Arrest, Loss of Neural Crest Cells, and Craniofacial Abnormalities

Neural crest cells (NCCs) comprise a transient progenitor cell population of neuroepithelial origin that contributes to a variety of cell types throughout vertebrate embryos including most mesenchymal cells of the cranial and facial structures. Consequently, abnormal NCC development underlies a variety of craniofacial defects including orofacial clefts, which constitute some of the most common birth defects. We previously reported the generation of manta ray (mray) mice that carry a loss-of-function allele of the gene encoding the preribosomal factor Pak1ip1. Here we describe cranioskeletal abnormalities in homozygous mray mutants that arise from a loss of NCCs after their specification. Our results show that the localized loss of cranial NCCs in the developing frontonasal prominences is caused by cell cycle arrest and cell death. In addition, and consistent with deficits in ribosome biosynthesis, homozygous mray mutants display decreased protein biosynthesis, further linking Pak1ip1 to a role in ribosome biogenesis.
CircDENND2A Promotes Non-small Cell Lung Cancer Progression via Regulating MiR-34a/CCNE1 Signaling

The mechanism regulating non-small cell lung cancers (NSCLCs) is unclear. In this study, we aimed to determine the roles of DENN domain containing 2A (circDENND2A) in the progression of NSCLC. Circular RNAs (circRNAs) are composited by “head to tail” splicing of coding or non-coding RNAs (ncRNAs), whose crucial roles in human cancers had been revealed. CircDENND2A, a new circRNA, was revealed to induce cell proliferation and migration. Our data indicated that circDENND2A was a probable oncogene in human cancers. However, the roles of circDENND2A in NSCLC remained unknown. Here, we demonstrated that circDENND2A was down-regulated in NSCLC samples. Loss-of-function assays showed circDENND2A knockdown suppressed cell growth via inducing cell cycle arrest and apoptosis and inhibited cell migration and invasion. Bioinformatics analysis and competing endogenous RNA (ceRNA) network analysis revealed that circDENND2A was involved in regulating cell cycle and tumor protein p53 (TP53) signaling via miR-34a/CCNE1 (cyclin E1). Further validation showed that circDENND2A could directly bind to miR-34a, promoting CCNE1 expression in NSCLC. In addition, rescue assays demonstrated that restoration of CCNE1 significantly impaired the suppressive effects of circDENND2A silencing in terms of NSCLC growth, migration, and invasion. We thought this study indicated that circDENND2A/miR-34a/CCNE1 may be a potential therapeutic target for NSCLC.
Study on the structure and optical imaging characteristics of an all-fiber OCT probe

Abstract. Aiming at small size, compact structure, strong light-collecting ability, and low loss requirements of optical coherence tomography (OCT) probes used for human body detection, we design an all-fiber OCT probe, which is composed of a single-mode fiber and a multimode fiber (MMF) with spherical lens. By measuring the optical performance of these probes, we found that, when the length of the MMF of the composite probe is 372 μm and the diameter of the ball lens is 300 μm, it has the strongest focusing effect and a large reflected light signal receiving angle. Furthermore, the OCT probe studied was applied to a self-made spectral domain OCT system for validation. The results show that our probe can obtain a clear two-dimensional grayscale image of three layers of glass and fish scales, i.e., the probe manufacturing scheme can be used. Furthermore, it meets the needs of miniature OCT probes, which provides more effective options for measuring human blood vessels or other biological tissues.
Toward real-time road detection for autonomous vehicles

Abstract. Road detection is a vital task for autonomous vehicles, as it has a direct link to passengers’ safety. Given its importance, researchers aimed to improve its accuracy and robustness. We look at the task from a holistic point of view, where we aim to balance computation and accuracy. A multimodal road detection pipeline is proposed, which fuses the camera image with the preprocessed LIDAR input. First, the LIDAR input is preprocessed using three-dimensional models inspired from computer graphics to generate image-like representations. Then, the preprocessed LIDAR input is combined with the camera image using a fusion module named inputs cross-fusion module, to reduce the computation amount required by other fusion strategies. To prevent the accuracy loss caused by the computation gain, we introduce the surface normal information to add distinctiveness. Furthermore, we propose a cost/benefit metric to evaluate the trade-off between computation cost and accuracy of road detection approaches. Several tests were conducted using the KITTI road detection benchmark based on deep convolutional neural networks, the obtained results were considered very satisfactory. In particular, the robustness of the proposed approach resulted in accuracies higher than 95% on different road types, comparable to those of the state-of-the-art techniques. In addition to marginally reducing the inference time of the used DCNN on images with a resolution of 1248 × 352 pixels to 130 ms using an NVIDIA GTX-1080TI.
Chromatin Targeting of HIPK2 Leads to Acetylation-Dependent Chromatin Decondensation

The protein kinase homeodomain-interacting protein kinase 2 (HIPK2) plays an important role in development and in the response to external cues. The kinase associates with an exceptionally large number of different transcription factors and chromatin regulatory proteins to direct distinct gene expression programs. In order to investigate the function of HIPK2 for chromatin compaction, HIPK2 was fused to the DNA-binding domains of Gal4 or LacI, thus allowing its specific targeting to binding sites for these transcription factors that were integrated in specific chromosome loci. Tethering of HIPK2 resulted in strong decompaction of euchromatic and heterochromatic areas. HIPK2-mediated heterochromatin decondensation started already 4 h after its chromatin association and required the functionality of its SUMO-interacting motif. This process was paralleled by disappearance of the repressive H3K27me3 chromatin mark, recruitment of the acetyltransferases CBP and p300 and increased histone acetylation at H3K18 and H4K5. HIPK2-mediated chromatin decompaction was strongly inhibited in the presence of a CBP/p300 inhibitor and completely blocked by the BET inhibitor JQ1, consistent with a causative role of acetylations for this process. Chromatin tethering of HIPK2 had only a minor effect on basal transcription, while it strongly boosted estrogen-triggered gene expression by acting as a transcriptional cofactor.
Dual feature extractor generative adversarial network for colorization

Abstract. The coloring efficiency of most colorization algorithms is suboptimal. Therefore, the dual feature extractor generative adversarial network was designed for colorization. The U-Net-like network was used as the trunk network in the generator. The encoder was used to extract the local features of a grayscale image. The branch extractor used the ResNeXt network that was added to the SE module as a high-level feature extractor to extract the global features of the grayscale image. The two features were fused to predict the chrominance. This strategy prevented color leakage and detail loss in colorization. Moreover, the adversarial loss was added to minimize the tendency toward acquiring an unsaturated tone. The effectiveness of the proposed method was evaluated quantitatively and qualitatively.
Determinants of Willingness to Pay for Private Extension Services by Crop Farmers in the Federal Capital Territory (FCT) Abuja, Nigeria

The study analysed determinants of willingness to pay for private extension services among crop farmers in the Federal Capital Territory (FCT) Abuja, Nigeria. Primary data were collected from respondents using a structured questionnaire. Data were analysed using simple descriptive statistics and logit regression model. From the results, the mean age of respondents was 39 years. The mean annual income of respondents was N504,811.1 (SD = N767,997.7). Many (49.4%) of the farmers interviewed had between 6 – 10 persons in their households with an average household size of 8 persons. Majority (79.4%) of the respondents were male while only 20.6% of the respondents were female. Socioeconomic factors influencing crop farmers’ willingness to pay for private extension found in the study were age, income, membership of cooperatives and frequency of extension visits. Age was significant at 10% while Income and membership of cooperatives were both significant at 5% respectively. However, frequency of extension visits was significant at 1%. There should be deliberate policies that will draw younger Nigerian into farming as the study reveals that willingness to pay for private extension increases within the younger generation of farmers. Younger farmers have the innovativeness to incorporate vital innovations and modern technologies in farming.
APPLICATION OF SPOT5 SATELLITE IMAGE AND GIS FOR UPDATING ROAD NETWORK: TOWARDS BUILDING LANDSLIDE SPATIAL DATABASE

Rapid development in urbanization is usually followed by development in transportation network. As the consequence, latest developed road networks are not found on the existing topographic map. As the topographic map-derived road network is not updated in short period, it is important to shorten the map updating cycles. SPOT 5 satellite image offers a cost effective way for updating the map compared to a conventional mapping method. The image, acquired in 2005, is used for updating road network on topographic map scaled at 1:50000, sheet 74, issued by JUPEM which was derived from aerial photograph taken in 1981. The road connecting Simpang Pulai cross and Kampung Raja, Cameron Highlands, is selected due to its considerably rapid development and susceptibility to landslide. Since most landslide occurrences take place along the road, updating road map as part of landslide geo-database becomes necessary. SPOT5 image is registered into Malaysian Coordinate System, RSO, to conform to the existing registered topographic map. Both image classification and on screen digitization methods are used to extract road network feature. The latest method is applied to complement to the first one in case of facing uncertainty in image classification. The quality of extracted road network from image classification is discussed. The extracted road network is stored into landslide spatial database. In regard to landslide aspects, features such as barren land, vegetation coverage, are also extracted. DEM derived from topographic map is used to generate slope risk map. GIS analysis is performed to locate high risk areas that prone to landslide based on two criteria. Those areas having high risk slope (20 0 -35 0 ) and occupy barren/un-vegetated land are considered as high risk area. From this study, only 0.1% of areas occupy high risk locations. Some of which is located at existing slope failure area at Pos Slim.
Learning from dispersed manual annotations with an optimized data weighting policy

Abstract. Purpose: Deep learning methods have become essential tools for quantitative interpretation of medical imaging data, but training these approaches is highly sensitive to biases and class imbalance in the available data. There is an opportunity to increase the available training data by combining across different data sources (e.g., distinct public projects); however, data collected under different scopes tend to have differences in class balance, label availability, and subject demographics. Recent work has shown that importance sampling can be used to guide training selection. To date, these approaches have not considered imbalanced data sources with distinct labeling protocols. Approach: We propose a sampling policy, known as adaptive stochastic policy (ASP), inspired by reinforcement learning to adapt training based on subject, data source, and dynamic use criteria. We apply ASP in the context of multiorgan abdominal computed tomography segmentation. Training was performed with cross validation on 840 subjects from 10 data sources. External validation was performed with 20 subjects from 1 data source. Results: Four alternative strategies were evaluated with the state-of-the-art baseline as upper confident bound (UCB). ASP achieves average Dice of 0.8261 compared to 0.8135 UCB (p < 0.01, paired t-test) across fivefold cross validation. On withheld testing datasets, the proposed ASP achieved 0.8265 mean Dice versus 0.8077 UCB (p < 0.01, paired t-test). Conclusions: ASP provides a flexible reweighting technique for training deep learning models. We conclude that the proposed method adapts the sample importance, which leverages the performance on a challenging multisite, multiorgan, and multisize segmentation task.
Deep learning algorithm for Gaussian noise removal from images

Abstract. A deep learning algorithm for Gaussian noise removal from both grayscale and color images is developed. As opposed to most existing discriminative methods that train a specific model for each noise level, the proposed method can handle a wide range of noise levels using only two trained models, one for low noise levels and the other for high noise levels. In the proposed algorithm, the training process consists of three successive steps. In the first step, a classifier is trained to classify the noisy and clean images. In the second step, a denoiser network aims to remove the noise in the image features that are extracted by the trained classifier. Finally, a decoder is utilized to map back the denoised images features into images pixels. To evaluate the performance of the model, the Berkeley segmentation dataset of 68 images (BSDS68) and 12 widely used images are used, and the denoising performance for additive white Gaussian noise is compared with several state-of-the-art methods in terms of peak signal-to-noise ratio (PSNR) and visual quality. For grayscale image denoising of BSDS68, our method gives the highest PSNR on all noise levels (significant mean improvement of 0.99). For color image denoising of BSDS68, except for one low noise level, the proposed method gives the highest PSNR on all other noise levels (mean improvement of 0.3).
Dimensionality reduction on the symmetric positive definite manifold with application to image set classification

Abstract. In the field of pattern recognition and computer vision, applying the symmetric positive definite (SPD) matrix to represent an image set is widely studied, and the remarkable performance that it yields demonstrates its effectiveness. However, the computational burden of the original SPD matrices is usually high, which may restrict the applicability of existing methods. To address this problem, we proposed an SPD manifold dimensionality reduction (DR) algorithm. Specifically, we map the original SPD manifold into a more discriminative lower-dimensional one via a learned mapping. We first construct a graph model using the mechanism of collaborative representation to characterize the local structure of the original manifold data. Then, we formulate the SPD manifold DR problem into an elaborately designed objective function introduced by the graph-embedding framework, aiming to learn the mapping. Finally, the trace optimization method is chosen to solve this optimization problem. The experimental results on some benchmark datasets demonstrate the superiority of our method over the state-of-the-art image set classification methods.
EOLGD: an edge feature descriptor-based method for long-wave infrared and visible image registration

Abstract. Image registration is an essential prerequisite for multisource image fusion. To further improve the registration accuracy for long-wave infrared and visible images, a feature point descriptor construction method—edge-oriented log-Gabor descriptor is proposed. Initially, grayscale edge images are obtained by a structured random forests edge detector, which is more suitable for extracting features using multiscale and multioriented log-Gabor filters. Then, edge features are used for selecting orientation-stabilized feature points from speeded up robust feature points, and descriptors are constructed with a two-stage Gaussian weighting scheme. Finally, feature point pairs are matched by computing the difference of descriptors. Experimental results show that the proposed approach achieves better performance compared with state-of-the-art methods.
Fiber Bragg grating sensor for measuring rate of dissipation of turbulent kinetic energy of ocean

Abstract. Fiber optic microstructure turbulence sensors (FOMTS) with fiber Bragg gratings can measure the rate of tangential velocity change caused by ocean turbulence. The theoretical principles of the FOMTS and demodulation were verified by a prototype. The demodulation system resolution reached 0.001 pm / Hz, the sensitivity was 4.37 × 10 − 16 m2 s2 / kg, and its natural frequency in air was 595 Hz, similar to the theoretical values. Its resonance frequency in water (534 Hz), exceeded the highest frequency of ocean turbulence (200 Hz). Furthermore, comparative experiments between the FOMTS and a commercially available sensor were performed. Good signal correspondence was observed, proving the effectiveness of the FOMTS and verifying the design principle.
Quantitative Analysis of the Alternative Splicing of Pax5 in Teleost Fish During Spawning

Pax5 is the master regulator of B-cell development. Pax5 is highly conserved between invertebrate and vertebrate species and is known to be alternatively spliced. An isoform missing exon 2 appears to be species independent. This is significant because exon 2 contains the DNA binding domain and thus these isoforms have decreased DNA binding, which change their function as a transcription factor. This project aimed to determine if there are changes in the alternative splicing of Pax5 during a humoral immune response in spawning sockeye salmon (Onchorynchus nerka). Specifically, this project looked at the changes in Onchorynchus Pax5 isoforms that lack exon 2, to determine if these changes correlated with an increase in the amount of secreted IgM in such animals. Real-time PCR was performed using primers that amplified full length Pax5, the Pax5? 2 isoform, and secreted and membrane IgM. The relative expression levels of Pax5? 2/Pax5FL were then compared to the relative expression levels of secreted/membrane IgM. This project concluded that there is a positive correlation between the levels of secreted IgM and Pax5? 2. This positive correlation was observed in vivo in O. mykiss in the laboratory, in vitro in LPS activated B-cells from O. mykiss, and in vivo in spawning O. nerka samples for spleen and blood. This conclusion supports the model that Pax5? 2 is acting as a co-repressor of Pax5FL by binding to the initiation complex on the Xbp1 gene, thus changing the shape of the initiation complex and preventing Pax5FL from binding to the promoter region of the Xbp1 gene.
New Signal Constellation Pairs for the ZTM-OFDM-IM System

In this paper, we investigate new signal constellation pairs for mapping active subcarriers of the zero-padded trimode orthogonal frequency division multiplexing with index modulation (ZTM-OFDM-IM) systems. In the presented system, one of a constellation pair is the same as the one used in the previous work, and the other is a constellation larger than the one used in the previous work. It increases the minimum Euclidean distance between the subblocks of the ZTM-OFDM-IM system with new constellation pairs under the constraint of the same spectral efficiency. Computer simulation in AWGN and frequency-selective fading channels shows that the new ZTM-OFDM-IM system has a much lower bit error rate than OFDM-IM and dual-mode OFDM-IM and slightly outperforms the system with conventional constellation pairs. Since the proposed constellation pairs prove the error performance improvement of the system, it is considered that a further study on generalized design of the constellation pair for the ZTM-OFDM-IM system is necessary in the future.
Inhibition of transient receptor potential melastatin 7 (TRPM7) protects against Schwann cell trans-dedifferentiation and proliferation during Wallerian degeneration

ABSTRACT Irreversible peripheral neurodegenerative diseases such as diabetic peripheral neuropathy are becoming increasingly common due to rising rates of diabetes mellitus; however, no effective therapeutic treatments have been developed. One of main causes of irreversible peripheral neurodegenerative diseases is dysfunction in Schwann cells, which are neuroglia unique to the peripheral nervous system (PNS). Because homeostasis of calcium (Ca2+) and magnesium (Mg2+) is essential for Schwann cell dynamics, the regulation of these cations is important for controlling peripheral nerve degeneration and regeneration. Transient receptor potential melastatin 7 (TRPM7) is a non-selective ion (Ca2+ and Mg2+) channel that is expressed in Schwann cells. In the present study, we demonstrated in an ex vivo culture system that inhibition of TRPM7 during peripheral nerve degeneration (Wallerian degeneration) suppressed dedifferentiable or degenerative features (trans-dedifferentiation and proliferation) and conserved a differentiable feature of Schwann cells. Our results indicate that TRPM7 could be very useful as a molecular target for irreversible peripheral neurodegenerative diseases, facilitating discovery of new therapeutic methods for improving human health.
Generalized monoidal effects and handlers

Abstract Algebraic effects and handlers are a convenient method for structuring monadic effects with primitive effectful operations and separating the syntax from the interpretation of these operations. However, the scope of conventional handlers is limited as not all side effects are monadic in nature. This paper generalizes the notion of algebraic effects and handlers from monads to generalized monoids, which notably covers applicative functors and arrows as well as monads. For this purpose, we switch the category theoretical basis from free algebras to free monoids. In addition, we show how lax monoidal functors enable the reuse of handlers and programs across different computation classes, for example, handling applicative computations with monadic handlers. We motivate and present these handler interfaces in the context of build systems. Tasks in a build system are represented by a free computation and their interpretation as a handler. This use case is based on the work of Mokhov et al. [(2018). PACMPL2(ICFP), 79:1–79:29. ].